Measuring Kidney Function

Chapter 1

Abstract

Medicine

Barbara Katharina Geist

nuclear medicine, Cr-EDTA, Tc-DTPA

1. Introduction

3

Calculation of GFR via the

Slope-Intercept Method in Nuclear

A determination of the glomerular filtration rate (GFR) with high accuracy is of great relevance especially in cases of insufficient kidney function. In nuclear medicine, the standard method is based on blood sample measurements with Cr-51 ethylenediaminetetraacetic acid (Cr-51-EDTA) or Tc-99m diethylene-triamine-pentaacetate (Tc-99m-DTPA), providing very high accuracy and reliability. In particular, the slope-intercept method turned out to be the most appropriate and is therefore routinely used in many hospitals worldwide. For this purpose, blood samples are drawn at certain time points starting 120 minutes after injection, which are then measured together with a standard probe in a gamma counter; based on the results, the GFR calculation is then usually performed automatically with an appropriate software. In this chapter, the mathematical background as well as a step-by-step description of the slope-intercept method is given. In our study, we found that at least three blood samples should be drawn in order to achieve highest quality and reliability. Furthermore, a sample size of at least three blood samples allows an error calculation which

provides an estimation of the reliability of the preceding measurement.

Keywords: glomerular filtration rate, slope-intercept method, error calculation,

The glomerular filtration rate (GFR) is an important clinical measure for estimating not only the health of the kidneys but also the overall health of a patient, since it is directly proportional to the number of working nephrons. However, an exact determination of the GFR is not simple, and very often, an estimated GFR (eGFR) is calculated from the serum creatinine in the blood [1, 2]. For this, various formulas are available for different purposes [2–4]. Although these methods are convenient, they are not very sensitive, in particular in the case of insufficient kidney function [5]. An approved method for an accurate determination of the GFR was the inulin clearance, because inulin serves as a marker which is filtered by the glomeruli without tubular secretion or reabsorption [6]. Considered as gold standard, this method is time-consuming and needs urine as well as blood sample collection. In nuclear medicine, several invasive and noninvasive methods are available to calculate the GFR. In principle, radiotracers, i.e., biological markers labeled with a radioactive isotope, are injected into the patient. The behavior of the tracer gives

#### Chapter 1

## Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine

Barbara Katharina Geist

#### Abstract

A determination of the glomerular filtration rate (GFR) with high accuracy is of great relevance especially in cases of insufficient kidney function. In nuclear medicine, the standard method is based on blood sample measurements with Cr-51 ethylenediaminetetraacetic acid (Cr-51-EDTA) or Tc-99m diethylene-triamine-pentaacetate (Tc-99m-DTPA), providing very high accuracy and reliability. In particular, the slope-intercept method turned out to be the most appropriate and is therefore routinely used in many hospitals worldwide. For this purpose, blood samples are drawn at certain time points starting 120 minutes after injection, which are then measured together with a standard probe in a gamma counter; based on the results, the GFR calculation is then usually performed automatically with an appropriate software. In this chapter, the mathematical background as well as a step-by-step description of the slope-intercept method is given. In our study, we found that at least three blood samples should be drawn in order to achieve highest quality and reliability. Furthermore, a sample size of at least three blood samples allows an error calculation which provides an estimation of the reliability of the preceding measurement.

Keywords: glomerular filtration rate, slope-intercept method, error calculation, nuclear medicine, Cr-EDTA, Tc-DTPA

#### 1. Introduction

The glomerular filtration rate (GFR) is an important clinical measure for estimating not only the health of the kidneys but also the overall health of a patient, since it is directly proportional to the number of working nephrons. However, an exact determination of the GFR is not simple, and very often, an estimated GFR (eGFR) is calculated from the serum creatinine in the blood [1, 2]. For this, various formulas are available for different purposes [2–4]. Although these methods are convenient, they are not very sensitive, in particular in the case of insufficient kidney function [5].

An approved method for an accurate determination of the GFR was the inulin clearance, because inulin serves as a marker which is filtered by the glomeruli without tubular secretion or reabsorption [6]. Considered as gold standard, this method is time-consuming and needs urine as well as blood sample collection.

In nuclear medicine, several invasive and noninvasive methods are available to calculate the GFR. In principle, radiotracers, i.e., biological markers labeled with a radioactive isotope, are injected into the patient. The behavior of the tracer gives

information about the health condition of the organ and can be tracked by the emitted radiation from the labeled isotope. After injection, the radiation and therefore the concentration of the tracer can be measured either from drawn blood samples or with imaging techniques (so-called renal scintigraphy). The latter thus additionally allow a visualization of the anatomical properties of the organ.

To give an example, the very common radio tracer MAG3 (mercaptoacetyltriglycine, labeled to the gamma emitting isotope Tc-99m), providing excellent image quality, is not filtered in the glomeruli and therefore used with imaging techniques to determine the split renal function and the renal transit [7]. In contrary, the tracers Tc-99m diethylene-triamine-pentaacetate (Tc-99m-DTPA) and Cr-51 ethylenediaminetetraacetic acid (Cr-51-EDTA) are similar to inulin and therefore used to determine the GFR [8].

Cr-51-EDTA is only suitable for blood sample measurements since the physical properties of its labeled isotope Cr-51 do not allow the usage of imaging techniques. Tc-99m-DTPA on the other hand might be used for both blood sample and imaging methods.

For the sake of completeness, it is mentioned that methods are available to estimate the GFR from renal scintigraphy images, based on the accumulation of Tc-99m-DTPA in the kidneys within the first minutes after injection [9]. However, these methods only provide an estimation of the GFR and will therefore not be discussed in this chapter.

P tðÞ¼ P<sup>0</sup> � e

Measured tracer concentrations of three plasma samples are plotted as dots; an exponential curve (see Eq. (1)) was fitted through the data points (line). The abscissa gives the time in minutes after injection of the tracer.

<sup>A</sup> <sup>¼</sup> <sup>P</sup><sup>0</sup>

The curve P(t) is obtained by fitting the measured blood plasma samples with the exponential function from Eq. (1) (see Figure 1), e.g., with a least squares algorithm. The fit parameters are the values P<sup>0</sup> (the "intercept") and L (the

Another information needed for the GFR calculation is the applied dose to the

patient. While the syringe with the tracer is measured in an activimeter (or a comparable detector) before injection, the blood samples, showing considerably less radioactivity, are measured in a very different device (gamma counter). In order to connect the measurements of both devices, a so-called standard (a small amount of the tracer) must be prepared, which is then measured in both devices. The ratio of these two measurements is used to convert the injected dose measured in the activimeter to the units of the gamma counter. The converted applied dose D

D ¼ ActSyringe �

with ActSyringe as measured syringe activity before application and ActStd as standard activity in the activimeter and GCStd as measured standard activity in the

The GFR can then be expressed as the converted total dose applied to the patient, D, divided by the area under the plasma concentration curve [11]

GFR <sup>¼</sup> <sup>D</sup> � <sup>V</sup>

ActStd GCStd � <sup>V</sup> � <sup>L</sup> P0

with V as the dilution of the standard (usually around 500, see Section 3).

Therefore, using Eqs. (2) and (3), the GFR can be written as

GFR ¼ ActSyringe �

ActStd GCStd

The area A under this curve obviously is

Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine

DOI: http://dx.doi.org/10.5772/intechopen.85739

"slope"), which are then used to calculate A.

therefore can be written as

gamma counter.

5

Figure 1.

�L�<sup>t</sup> (1)

<sup>L</sup> (2)

<sup>A</sup> (4)

(3)

(5)

The main purpose of this chapter is to introduce the idea and the measurement procedure of the so-called slope-intercept method. In short, an appropriate tracer such as Tc-99m-DTPA or Cr-51-EDTA is injected, and at least two blood samples are taken at certain time points after the injections. The blood samples are then measured in a detector, a so-called gamma counter, in order to determine the emitted radiation, from which the GFR can be calculated. Methods using only one or two blood samples exist, but these are less accurate and error-prone [10]. The most accurate method involves the measurement of at least three blood samples because in this case a determination of the systematic error can be provided which in turn gives information about the reliability of the measurement.

#### 2. Mathematical background

#### 2.1 GFR calculation

For the determination of the GFR from an appropriate tracer, e.g., Tc-99m-DTPA or Cr-51-EDTA, the area under the so-called plasma concentration curve is needed, which is obtained from the drawn blood samples as described in the following.

After injection, the tracer travels through the blood vessels into the kidneys, where it is freely filtered and finally excreted. Assuming that other renal processes of the tracer are negligible, the decrease of the tracer concentration in the blood plasma after certain time points is then a measure for the glomerular filtration. Ideally, starting at 1 hour after injection, every 30 or 60 minutes a blood sample is drawn, in particular in the case of three blood samples at 120, 180, and 240 minutes after injection (see Figure 1) [11]. Due to its radioactivity, i.e., its emission of radiation, the tracer concentration in the blood plasma samples can be measured, usually with a gamma counter which allows the measurement of small samples.

The decrease of the tracer concentration in the blood plasma, expressed with a function P(t), follows an exponential decay. This means due to glomerular filtration, the initial tracer concentration in the body (P0) is decreasing exponentially (time, t) with a certain biological decrease constant L.

Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine DOI: http://dx.doi.org/10.5772/intechopen.85739

Figure 1.

information about the health condition of the organ and can be tracked by the emitted radiation from the labeled isotope. After injection, the radiation and therefore the concentration of the tracer can be measured either from drawn blood samples or with imaging techniques (so-called renal scintigraphy). The latter thus additionally allow a visualization of the anatomical properties of the organ. To give an example, the very common radio tracer MAG3 (mercaptoacetyltriglycine, labeled to the gamma emitting isotope Tc-99m), providing excellent image quality, is not filtered in the glomeruli and therefore used with imaging techniques to determine the split renal function and the renal transit [7]. In contrary, the tracers Tc-99m diethylene-triamine-pentaacetate (Tc-99m-DTPA) and Cr-51 ethylenediaminetetraacetic acid (Cr-51-EDTA) are similar to inulin and

Cr-51-EDTA is only suitable for blood sample measurements since the physical properties of its labeled isotope Cr-51 do not allow the usage of imaging techniques. Tc-99m-DTPA on the other hand might be used for both blood sample and imaging

For the sake of completeness, it is mentioned that methods are available to estimate the GFR from renal scintigraphy images, based on the accumulation of Tc-99m-DTPA in the kidneys within the first minutes after injection [9]. However, these methods only provide an estimation of the GFR and will therefore not be

The main purpose of this chapter is to introduce the idea and the measurement procedure of the so-called slope-intercept method. In short, an appropriate tracer such as Tc-99m-DTPA or Cr-51-EDTA is injected, and at least two blood samples are taken at certain time points after the injections. The blood samples are then measured in a detector, a so-called gamma counter, in order to determine the emitted radiation, from which the GFR can be calculated. Methods using only one or two blood samples exist, but these are less accurate and error-prone [10]. The most accurate method involves the measurement of at least three blood samples because in this case a determination of the systematic error can be provided which

For the determination of the GFR from an appropriate tracer, e.g., Tc-99m-DTPA or Cr-51-EDTA, the area under the so-called plasma concentration curve is needed, which is obtained from the drawn blood samples as described in the following. After injection, the tracer travels through the blood vessels into the kidneys, where it is freely filtered and finally excreted. Assuming that other renal processes of the tracer are negligible, the decrease of the tracer concentration in the blood plasma after certain time points is then a measure for the glomerular filtration. Ideally, starting at 1 hour after injection, every 30 or 60 minutes a blood sample is drawn, in particular in the case of three blood samples at 120, 180, and 240 minutes after injection (see Figure 1) [11]. Due to its radioactivity, i.e., its emission of radiation, the tracer concentration in the blood plasma samples can be measured, usually with a gamma counter which allows the measurement of small samples. The decrease of the tracer concentration in the blood plasma, expressed with a function P(t), follows an exponential decay. This means due to glomerular filtration, the initial tracer concentration in the body (P0) is decreasing exponentially

in turn gives information about the reliability of the measurement.

(time, t) with a certain biological decrease constant L.

therefore used to determine the GFR [8].

Glomerulonephritis and Nephrotic Syndrome

methods.

discussed in this chapter.

2. Mathematical background

2.1 GFR calculation

4

Measured tracer concentrations of three plasma samples are plotted as dots; an exponential curve (see Eq. (1)) was fitted through the data points (line). The abscissa gives the time in minutes after injection of the tracer.

$$P(t) = P\_0 \cdot e^{-L \cdot t} \tag{1}$$

The area A under this curve obviously is

$$A = \frac{P\_0}{L} \tag{2}$$

The curve P(t) is obtained by fitting the measured blood plasma samples with the exponential function from Eq. (1) (see Figure 1), e.g., with a least squares algorithm. The fit parameters are the values P<sup>0</sup> (the "intercept") and L (the "slope"), which are then used to calculate A.

Another information needed for the GFR calculation is the applied dose to the patient. While the syringe with the tracer is measured in an activimeter (or a comparable detector) before injection, the blood samples, showing considerably less radioactivity, are measured in a very different device (gamma counter). In order to connect the measurements of both devices, a so-called standard (a small amount of the tracer) must be prepared, which is then measured in both devices. The ratio of these two measurements is used to convert the injected dose measured in the activimeter to the units of the gamma counter. The converted applied dose D therefore can be written as

$$D = Act\_{\text{Spring}} \cdot \frac{Act\_{\text{Sdd}}}{GC\_{\text{Sdd}}} \tag{3}$$

with ActSyringe as measured syringe activity before application and ActStd as standard activity in the activimeter and GCStd as measured standard activity in the gamma counter.

The GFR can then be expressed as the converted total dose applied to the patient, D, divided by the area under the plasma concentration curve [11]

$$\text{GFR} = \frac{D \cdot V}{A} \tag{4}$$

with V as the dilution of the standard (usually around 500, see Section 3). Therefore, using Eqs. (2) and (3), the GFR can be written as

$$\text{GFR} = \text{Act}\_{\text{Spring}} \cdot \frac{\text{Act}\_{\text{Sdd}}}{\text{GC}\_{\text{Sdd}}} \cdot V \cdot \frac{L}{P\_0} \tag{5}$$

#### 2.2 Corrections

#### 2.2.1 AUC correction

Due to underlying biological processes, the plasma concentration curve P(t) appears not as a perfect exponential decay in particular in the beginning, leading to a wrong area under the curve (AUC). This can be solved by fitting the curve with multiple exponential curves, which would need much more blood samples. Another option is to start blood sample withdrawal after 120 minutes, i.e., after initial renal processes, using a simple AUC correction formula. Several formulas for adults and children are provided [11–14]. The Brochner-Mortensen correction is recommended [11, 15]:

For adults

$$GFR\_{corr} = 0.9908 \cdotGFR - 0.001218 \cdotGFR^2$$

For children

GFRcorr <sup>¼</sup> <sup>1</sup>:<sup>01</sup> � GFR � <sup>0</sup>:<sup>0017</sup> � GFR<sup>2</sup>

gamma counter continuously measure background radiation which must be

Exponential decrease due to glomerular filtration with a typical half-life of 90 minutes (gray dots). Due to radioactive decay, real obtained curves are shown as black line in the case of Cr-51 and as gray line in the case

estimate the body surface area for adults and children [16–20].

Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine

DOI: http://dx.doi.org/10.5772/intechopen.85739

counter measurements are assumed to be negligible [10].

sA ¼

<sup>n</sup> � <sup>1</sup> <sup>n</sup> � <sup>2</sup> �

<sup>X</sup>ti

<sup>2</sup> � <sup>1</sup> <sup>n</sup> � <sup>2</sup> �

L. This problem can be solved analytically, leading to

s

s

sL ¼

sP<sup>0</sup> ¼ P<sup>0</sup> �

with ti as time interval after injection.

Since the GFR varies with the body surface area (BSA), it usually is presented as pure value but also corrected for the body surface area (BSA-GFR), normalized to

In clinical routine, irregularities during the measurement process, inadvertence,

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

sL � P<sup>0</sup> L2 � �<sup>2</sup>

<sup>P</sup>ð Þ ln <sup>P</sup><sup>0</sup> � Lti � lnP tð Þ<sup>i</sup>

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

n Pt 2 <sup>i</sup> � <sup>P</sup>ð Þti

2

2

2

2

<sup>P</sup>ð Þ ln <sup>P</sup><sup>0</sup> � Lti � lnP tð Þ<sup>i</sup>

þ

with sA as error of the area under the curve A, sP<sup>0</sup> as error of P0, and sL as error of

n Pt 2 <sup>i</sup> � <sup>P</sup>ð Þti

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

radioactive contamination, and other so-called systematic errors might lead to inaccurate results. Statistical (random) errors from the activimeter and gamma

To estimate these systematic errors, the error of the area under the tracer concentration curve A (Eq. (2)) can be calculated after the fitting procedure [10], provided at least three blood samples have been taken. According to the Gaussian error propagation law, the errors of L and P<sup>0</sup> need to be calculated in order to obtain

> sP<sup>0</sup> L � �<sup>2</sup>

s

). Several formalisms are available to

(6)

(7)

(8)

subtracted from all measured values.

the "standard man" (body surface 1.73 m<sup>2</sup>

2.2.4 BSA correction

Figure 2.

of Tc-99m.

2.3 Error calculation

the error of A:

7

#### 2.2.2 Radioactive decay correction

Furthermore, both tracers not only have a biological half-life due to their glomerular clearance but also a physical half-life due to the radioactivity of their labeled isotopes. Consequently, the tracer concentration in the blood samples not only decreases due to the biological clearance but virtually also due to the physical loss of decayed isotopes which are labeled to the tracer.

Keeping in mind that the blood samples for the GFR determination with the slope-intercept method must be drawn 3 or even more hours after injection and the half-life of the isotope is not infinite, the physical half-life of the isotope might lead to a significant loss of tracer concentration due to its radioactivity (and not due to glomerular filtration). Ideally, the physical half-life of the corresponding isotope therefore should be very high in order to minimize the concentration loss due to radioactivity. This issue is illustrated in Figure 2.

In case of Cr-51-EDTA, the physical half-life of Cr-51 is 27.7 days. Assuming that, starting with injection, the blood sample withdrawing takes 4 hours, one can easily calculate that the virtual loss of tracer concentration due to its radioactivity during this time interval is about 1%. The radioactivity of Cr-51 therefore can be considered as negligible and the tracer can be treated as physically stable (see Figure 2).

On the other hand, the isotope Tc-99m from the tracer Tc-99m-DTPA has a physical half-life of about 6 hours; the concentration loss during a time period of 4 hours is not negligible anymore. As illustrated in Figure 2, measured values of drawn sample appear with a significantly lower measured concentration value due to the radioactive decay of Tc-99m; in this example, the calculated GFR would be falsely overstated by 20%. Thus, measurements with Tc-99m-DTPA must be corrected for the physical half-life of Tc-99m.

#### 2.2.3 Background correction

Another important issue is the unavoidable measurement of unintended radioactivity. First, the remaining radioactivity in the syringe after injection must be measured and subtracted from the applied dose. Furthermore, both activimeter and Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine DOI: http://dx.doi.org/10.5772/intechopen.85739

Figure 2.

2.2 Corrections

2.2.1 AUC correction

Glomerulonephritis and Nephrotic Syndrome

recommended [11, 15]: For adults

For children

Figure 2).

6

2.2.2 Radioactive decay correction

loss of decayed isotopes which are labeled to the tracer.

radioactivity. This issue is illustrated in Figure 2.

corrected for the physical half-life of Tc-99m.

2.2.3 Background correction

Due to underlying biological processes, the plasma concentration curve P(t) appears not as a perfect exponential decay in particular in the beginning, leading to a wrong area under the curve (AUC). This can be solved by fitting the curve with multiple exponential curves, which would need much more blood samples. Another option is to start blood sample withdrawal after 120 minutes, i.e., after initial renal processes, using a simple AUC correction formula. Several formulas for adults and

GFRcorr <sup>¼</sup> <sup>0</sup>:<sup>9908</sup> � GFR � <sup>0</sup>:<sup>001218</sup> � GFR<sup>2</sup>

GFRcorr <sup>¼</sup> <sup>1</sup>:<sup>01</sup> � GFR � <sup>0</sup>:<sup>0017</sup> � GFR<sup>2</sup>

Furthermore, both tracers not only have a biological half-life due to their glomerular clearance but also a physical half-life due to the radioactivity of their labeled isotopes. Consequently, the tracer concentration in the blood samples not only decreases due to the biological clearance but virtually also due to the physical

Keeping in mind that the blood samples for the GFR determination with the slope-intercept method must be drawn 3 or even more hours after injection and the half-life of the isotope is not infinite, the physical half-life of the isotope might lead to a significant loss of tracer concentration due to its radioactivity (and not due to glomerular filtration). Ideally, the physical half-life of the corresponding isotope therefore should be very high in order to minimize the concentration loss due to

In case of Cr-51-EDTA, the physical half-life of Cr-51 is 27.7 days. Assuming that, starting with injection, the blood sample withdrawing takes 4 hours, one can easily calculate that the virtual loss of tracer concentration due to its radioactivity during this time interval is about 1%. The radioactivity of Cr-51 therefore can be considered as negligible and the tracer can be treated as physically stable (see

On the other hand, the isotope Tc-99m from the tracer Tc-99m-DTPA has a physical half-life of about 6 hours; the concentration loss during a time period of 4 hours is not negligible anymore. As illustrated in Figure 2, measured values of drawn sample appear with a significantly lower measured concentration value due to the radioactive decay of Tc-99m; in this example, the calculated GFR would be falsely overstated by 20%. Thus, measurements with Tc-99m-DTPA must be

Another important issue is the unavoidable measurement of unintended radioactivity. First, the remaining radioactivity in the syringe after injection must be measured and subtracted from the applied dose. Furthermore, both activimeter and

children are provided [11–14]. The Brochner-Mortensen correction is

Exponential decrease due to glomerular filtration with a typical half-life of 90 minutes (gray dots). Due to radioactive decay, real obtained curves are shown as black line in the case of Cr-51 and as gray line in the case of Tc-99m.

gamma counter continuously measure background radiation which must be subtracted from all measured values.

#### 2.2.4 BSA correction

Since the GFR varies with the body surface area (BSA), it usually is presented as pure value but also corrected for the body surface area (BSA-GFR), normalized to the "standard man" (body surface 1.73 m<sup>2</sup> ). Several formalisms are available to estimate the body surface area for adults and children [16–20].

#### 2.3 Error calculation

In clinical routine, irregularities during the measurement process, inadvertence, radioactive contamination, and other so-called systematic errors might lead to inaccurate results. Statistical (random) errors from the activimeter and gamma counter measurements are assumed to be negligible [10].

To estimate these systematic errors, the error of the area under the tracer concentration curve A (Eq. (2)) can be calculated after the fitting procedure [10], provided at least three blood samples have been taken. According to the Gaussian error propagation law, the errors of L and P<sup>0</sup> need to be calculated in order to obtain the error of A:

$$s\_A = \sqrt{\left(\frac{s\_{P0}}{L}\right)^2 + \left(\frac{s\_L \cdot P\_0}{L^2}\right)^2} \tag{6}$$

with sA as error of the area under the curve A, sP<sup>0</sup> as error of P0, and sL as error of L. This problem can be solved analytically, leading to

$$s\_L = \sqrt{n \cdot \frac{1}{n-2} \cdot \frac{\sum \left(\ln P\_0 - Lt\_i - \ln P(t\_i)\right)^2}{n\sum t\_i^2 - \left(\sum t\_i\right)^2}}\tag{7}$$

$$s\_{P0} = P\_0 \cdot \sqrt{\sum t\_i^2 \cdot \frac{\mathbf{1}}{n-2} \cdot \frac{\sum \left(\ln P\_0 - Lt\_i - \ln P(t\_i)\right)^2}{n\sum t\_i^2 - \left(\sum t\_i\right)^2}}\tag{8}$$

with ti as time interval after injection.

Under the assumption that random errors are negligible, sA represents the error of the calculated GFR. Although errors of <10% are considered insignificant, high errors allow to identify irregularities and re-evaluate the results.

5. Conclusions

Abbreviations

Nomenclature

Author details

9

Barbara Katharina Geist

Nuclear Medicine, Vienna, Austria

provided the original work is properly cited.

clinical routine, patients comfort, and accuracy.

DOI: http://dx.doi.org/10.5772/intechopen.85739

Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine

Tc-99m-DTPA Tc-99m diethylene-triamine-pentaacetate Cr-51-EDTA Cr-51ethylenediaminetetraacetic acid

Department of Biomedical Imaging and Image-Guided Therapy, Division of

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: barbara.geist@meduniwien.ac.at

Appendices and nomenclature

AUC area under the curve BSA body surface area GFR glomerular filtration rate

The slope-intercept method is based on several blood samples and an accurate calculation procedure including corrections and error estimation. In particular in case of low GFRs, this method is the best compromise between the effort for the

#### 3. Measurement

#### 3.1 Preparation

A standard is prepared, i.e., 1 ml of the used tracer is filled in an appropriate holder. Both the standard and the full syringe are measured in the activimeter. The empty syringe must also be measured after application in order to subtract the remaining activity from the measured value before application. In Eq. (3), this delivers the values ActSyringe and ActStd.

#### 3.2 Blood sample measurement

At least three blood samples are taken, starting at 120 minutes after injection, with an interval of 1 hour. The exact time period between injection and blood sample withdrawal needs to be recorded in order to minimize errors.

The standard usually needs to be diluted, e.g., by a factor of around 500. Around 1 ml is transferred into holders appropriate for the gamma counter. After separating blood plasma from hematocrit, 1 ml of each plasma sample is also transferred into holders for the gamma counter; all probes are measured. This gives the value GCStd as well as all necessary data points to obtain the plasma concentration curve P(t) (Eq. (1)).

#### 3.3 GFR calculation procedure

Before starting any calculations, all measured values need to be corrected for background. Note that in case of Tc-99m-DTPA, values need to be corrected for radioactive decay. The measured data points are fitted with an exponential function (Eq. (1)) to obtain the plasma concentration curve function P(t) and from this P<sup>0</sup> and L, which are needed to calculate the GFR (Eq. (5)).

If possible, i.e., if more than two blood samples have been drawn, the error is calculated according to Eq. (6). Furthermore, AUC correction and BSA correction are applied to the final GFR result.

#### 4. Comparison of different blood sample methods

There are several methods allowing an estimation of the GFR from only one blood sample [21–24]. Although these methods are from high convenience for the routine and the patients, they are not recommended for low GFRs [11] and show significant deviations to the slope-intercept method [10].

The slope-intercept method with blood samples drawn after 120 minutes after injection is suggested to be the best compromise between accuracy and simplicity; it furthermore is a repeatable and reliable method [10, 11, 25, 26]. Since an error calculation helps in identifying errors in the measurement process such as radioactive contamination or irregularities in the routine, the slope-intercept method with three blood samples appears ideal.

Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine DOI: http://dx.doi.org/10.5772/intechopen.85739

### 5. Conclusions

Under the assumption that random errors are negligible, sA represents the error of the calculated GFR. Although errors of <10% are considered insignificant, high

A standard is prepared, i.e., 1 ml of the used tracer is filled in an appropriate holder. Both the standard and the full syringe are measured in the activimeter. The empty syringe must also be measured after application in order to subtract the remaining activity from the measured value before application. In Eq. (3), this

At least three blood samples are taken, starting at 120 minutes after injection, with an interval of 1 hour. The exact time period between injection and blood

The standard usually needs to be diluted, e.g., by a factor of around 500. Around 1 ml is transferred into holders appropriate for the gamma counter. After separating blood plasma from hematocrit, 1 ml of each plasma sample is also transferred into holders for the gamma counter; all probes are measured. This gives the value GCStd as well as all necessary data points to obtain the plasma concentration curve P(t)

Before starting any calculations, all measured values need to be corrected for background. Note that in case of Tc-99m-DTPA, values need to be corrected for radioactive decay. The measured data points are fitted with an exponential function (Eq. (1)) to obtain the plasma concentration curve function P(t) and from this P<sup>0</sup>

If possible, i.e., if more than two blood samples have been drawn, the error is calculated according to Eq. (6). Furthermore, AUC correction and BSA correction

There are several methods allowing an estimation of the GFR from only one blood sample [21–24]. Although these methods are from high convenience for the routine and the patients, they are not recommended for low GFRs [11] and show

The slope-intercept method with blood samples drawn after 120 minutes after injection is suggested to be the best compromise between accuracy and simplicity; it furthermore is a repeatable and reliable method [10, 11, 25, 26]. Since an error calculation helps in identifying errors in the measurement process such as radioactive contamination or irregularities in the routine, the slope-intercept method with

sample withdrawal needs to be recorded in order to minimize errors.

and L, which are needed to calculate the GFR (Eq. (5)).

4. Comparison of different blood sample methods

significant deviations to the slope-intercept method [10].

errors allow to identify irregularities and re-evaluate the results.

3. Measurement

delivers the values ActSyringe and ActStd.

Glomerulonephritis and Nephrotic Syndrome

3.2 Blood sample measurement

3.3 GFR calculation procedure

are applied to the final GFR result.

three blood samples appears ideal.

8

3.1 Preparation

(Eq. (1)).

The slope-intercept method is based on several blood samples and an accurate calculation procedure including corrections and error estimation. In particular in case of low GFRs, this method is the best compromise between the effort for the clinical routine, patients comfort, and accuracy.

### Appendices and nomenclature

#### Abbreviations


#### Nomenclature


### Author details

Barbara Katharina Geist Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Vienna, Austria

\*Address all correspondence to: barbara.geist@meduniwien.ac.at

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### References

[1] National Kidney Foundation. K/ DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. American Journal of Kidney Diseases. 2002;39:S1-S266

[2] Levey AS, Stevens LA, Schmid CH, Zhang Y, Castro AF, Feldman HI, et al. New equation to estimate glomerular filtration rate. Annals of Internal Medicine. 2009;150:604-612

[3] Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of diet in renal disease study group. Annals of Internal Medicine. 1999;130:461-470

[4] Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16: 31-41

[5] Chew DJ, DiBartola S. Diagnosis and pathophysiology of renal disease. In: Ettinger SJ, editor. Textbook of Veterinary Internal Medicine. Philadelphia: WB Saunders; 1989. pp. 1893-1962

[6] Walser M, Davidson DG, Orloff J. The renal clearance of alkali-stable inulin. The Journal of Clinical Investigation;34:1520-1523

[7] Al-NahhasRafaqat AA, Jafri RA, Britton KE, Solanki K, Bomanji J, Mather S, et al. Clinical experience with 99mTc-MAG3, mercaptoacetyltriglycine, and a comparison with 99mTc-DTPA. European Journal of Nuclear Medicine. 1988;14:453

[8] Daniel GB, Mitchell SK, Mawby D, Sackman JE, Schmidt D. Renal nuclear medicine: A review. Veterinary

Radiology & Ultrasound. 1999;40(6): 572-587

glomerular filtration rate measurement with plasma sampling: A technical review. Journal of Nuclear Medicine Technology. 2013;41(2):67-75

DOI: http://dx.doi.org/10.5772/intechopen.85739

Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine

Nuclear Medicine Communications.

[25] Chantler C, Baratt TM. Estimation of glomerular filtration Raten from plasma clearance of 51-chromium Edetic acid. Archives of Disease in Childhood.

[26] Bird NJ, Peters C, Robert Michell A, Michael Peters A. Comparison of GFR measurements assessed from single versus multiple samples. American Journal of Kidney Diseases. 2009;54:

1999;20:273-278

1972;47:613-617

278-288

[16] Mosteller RD. Simplified calculation of body-surface area. The New England Journal of Medicine. 1987;317:1098-1098

[17] DuBois D, EF DB. A formula to estimate the approximate surface area if height and weight be known. Archives of Internal Medicine. 1916;17:863-871

[18] Haycock GB, Schwartz GJ, Wisotsky DH. Geometric method for measuring body surface area: A heightweight formula validated in infants, children and adults. The Journal of

[19] Gehan EA, George SL. Estimation of human body surface area from height and weight. Cancer Chemotherapy

[20] Boyd E. The Growth of the Surface Area of the Human Body. Minneapolis: University of Minnesota Press; 1935

[21] Russell CD, Bischoff PG, Kontzen FN, Rowell KL, Yester MV, Lloyd KL, et al. Measurement of glomerular filtration rate: Single injection plasma clearance method without urine

collection. Journal of Nuclear Medicine.

[22] Watson WS. A simple method of estimating glomerular filtration rate. European Journal of Nuclear Medicine.

[23] Ham HR, Piepsz A. Estimation of glomerular filtration rate in infants and in children using a single-plasma method. Journal of Nuclear Medicine.

[24] Hamilton D, Miola UJ. Body surface correction in single-sample methods of glomerular filtration rate estimation.

Pediatrics. 1978;93:62-66

Reports. 1970;54:225-235

1985;26:1243-1247

1992;19:827-827

1991;32:1294-1297

11

[9] Gates GF. Glomerular filtration rate: Estimation from fractional renal accumulation of 99mTc-DTPA. American Journal of Roentgenology. 1982;138:565-570

[10] Geist BK, Diemling M, Staudenherz A. Glomerular filtration rate and error calculation based on the slope-intercept method with Chromium-51 ethylenediaminetetraacetic acid via a new clinical software: GFRcalc. Medical Principles and Practice. 2016;25(4): 368-373

[11] Fleming JS, Zivanovic MA, Blake GM, Burniston M, Cosgriff PS. Guidelines for the measurement of glomerular filtration rate using plasma sampling. Nuclear Medicine Communications. 2004;25:759-769

[12] Brochner-Mortensen J. A simple method for the determination of glomerular filtration rate. Scandinavian Journal of Clinical and Laboratory Investigation. 1972;30:271-274

[13] Brochner-Mortensen J, Haahr J, Christoffersen J. A simple method for accurate assessment of the glomerular filtration rate in children. Scandinavian Journal of Clinical and Laboratory Investigation. 1974;33:140-143

[14] Jodal L, Brochner-Mortensen J. Reassessment of a classical single injection 51Cr-EDTA clearance method for determination of renal function in children and adults. Part I: Analytically correct relationship between total and one-pool clearance. Scandinavian Journal of Clinical and Laboratory Investigation. 2009;69:305-313

[15] Murray AW, Barnfield MC, Waller ML, Telford T, Peter AM. Assessment of Calculation of GFR via the Slope-Intercept Method in Nuclear Medicine DOI: http://dx.doi.org/10.5772/intechopen.85739

glomerular filtration rate measurement with plasma sampling: A technical review. Journal of Nuclear Medicine Technology. 2013;41(2):67-75

References

2002;39:S1-S266

[1] National Kidney Foundation. K/ DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. American Journal of Kidney Diseases.

Glomerulonephritis and Nephrotic Syndrome

Radiology & Ultrasound. 1999;40(6):

[9] Gates GF. Glomerular filtration rate: Estimation from fractional renal accumulation of 99mTc-DTPA. American Journal of Roentgenology.

[10] Geist BK, Diemling M, Staudenherz A. Glomerular filtration rate and error calculation based on the slope-intercept

ethylenediaminetetraacetic acid via a new clinical software: GFRcalc. Medical Principles and Practice. 2016;25(4):

[11] Fleming JS, Zivanovic MA, Blake GM, Burniston M, Cosgriff PS. Guidelines for the measurement of glomerular filtration rate using plasma

[12] Brochner-Mortensen J. A simple method for the determination of glomerular filtration rate. Scandinavian Journal of Clinical and Laboratory Investigation. 1972;30:271-274

[13] Brochner-Mortensen J, Haahr J, Christoffersen J. A simple method for accurate assessment of the glomerular filtration rate in children. Scandinavian Journal of Clinical and Laboratory Investigation. 1974;33:140-143

[14] Jodal L, Brochner-Mortensen J. Reassessment of a classical single injection 51Cr-EDTA clearance method for determination of renal function in children and adults. Part I: Analytically correct relationship between total and one-pool clearance. Scandinavian Journal of Clinical and Laboratory Investigation. 2009;69:305-313

[15] Murray AW, Barnfield MC, Waller ML, Telford T, Peter AM. Assessment of

method with Chromium-51

sampling. Nuclear Medicine Communications. 2004;25:759-769

572-587

368-373

1982;138:565-570

[2] Levey AS, Stevens LA, Schmid CH, Zhang Y, Castro AF, Feldman HI, et al. New equation to estimate glomerular filtration rate. Annals of Internal Medicine. 2009;150:604-612

[3] Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of diet in renal disease study group. Annals of Internal Medicine. 1999;130:461-470

[4] Cockcroft DW, Gault MH.

31-41

10

pp. 1893-1962

Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16:

[5] Chew DJ, DiBartola S. Diagnosis and pathophysiology of renal disease. In: Ettinger SJ, editor. Textbook of Veterinary Internal Medicine. Philadelphia: WB Saunders; 1989.

[6] Walser M, Davidson DG, Orloff J. The renal clearance of alkali-stable inulin. The Journal of Clinical Investigation;34:1520-1523

[7] Al-NahhasRafaqat AA, Jafri RA, Britton KE, Solanki K, Bomanji J, Mather S, et al. Clinical experience with

99mTc-MAG3, mercaptoacetyltriglycine, and a comparison with 99mTc-DTPA. European Journal of Nuclear Medicine. 1988;14:453

[8] Daniel GB, Mitchell SK, Mawby D, Sackman JE, Schmidt D. Renal nuclear medicine: A review. Veterinary

[16] Mosteller RD. Simplified calculation of body-surface area. The New England Journal of Medicine. 1987;317:1098-1098

[17] DuBois D, EF DB. A formula to estimate the approximate surface area if height and weight be known. Archives of Internal Medicine. 1916;17:863-871

[18] Haycock GB, Schwartz GJ, Wisotsky DH. Geometric method for measuring body surface area: A heightweight formula validated in infants, children and adults. The Journal of Pediatrics. 1978;93:62-66

[19] Gehan EA, George SL. Estimation of human body surface area from height and weight. Cancer Chemotherapy Reports. 1970;54:225-235

[20] Boyd E. The Growth of the Surface Area of the Human Body. Minneapolis: University of Minnesota Press; 1935

[21] Russell CD, Bischoff PG, Kontzen FN, Rowell KL, Yester MV, Lloyd KL, et al. Measurement of glomerular filtration rate: Single injection plasma clearance method without urine collection. Journal of Nuclear Medicine. 1985;26:1243-1247

[22] Watson WS. A simple method of estimating glomerular filtration rate. European Journal of Nuclear Medicine. 1992;19:827-827

[23] Ham HR, Piepsz A. Estimation of glomerular filtration rate in infants and in children using a single-plasma method. Journal of Nuclear Medicine. 1991;32:1294-1297

[24] Hamilton D, Miola UJ. Body surface correction in single-sample methods of glomerular filtration rate estimation.

Nuclear Medicine Communications. 1999;20:273-278

[25] Chantler C, Baratt TM. Estimation of glomerular filtration Raten from plasma clearance of 51-chromium Edetic acid. Archives of Disease in Childhood. 1972;47:613-617

[26] Bird NJ, Peters C, Robert Michell A, Michael Peters A. Comparison of GFR measurements assessed from single versus multiple samples. American Journal of Kidney Diseases. 2009;54: 278-288

**13**

**Table 1**.

**Chapter 2**

**Abstract**

of the disease.

**1. Introduction**

cal and standard method in diagnosing GN.

Biomarkers in Renal Vasculitis

*Polyvios Arseniou, Stamatia Stai and Maria Stangou*

**Keywords:** vasculitis, biomarkers, cytokines, growth factors, outcome

The use of biomarkers in glomerular diseases has been subject of investigation during the last decades, as it can provide worthwhile evidence in diagnosis, but also, it can guide treatment and give information about prognosis and response. Renal biopsy is still the compulsory technique to establish diagnosis, and also to offer information about the severity of renal damage. However, as an invasive method, it cannot be regularly performed during follow up, so the need to find and establish measurement of molecules, easily collected, which are associated with disease pathogenesis and predict renal function outcome seems very attractive to nephrologists. The renal complications of systemic vasculitis are very important for the outcome of the disease, and several substances and molecules, such as inflammatory cells, autoantibodies, cytokines, chemokines and growth factors are produced and may serve as biomarkers to provide useful information for diagnosis, follow up

The classical presentation of a primary or secondary glomerular disease (GD) is

A patient who presents with microhematuria, 2 g of proteinuria and a GRF of around 35 ml/min is possible to have IgAN, focal segmental sclerosis (FSGS) or membranous nephropathy (MN) or focal necrotising glomerulonephritis, due to vasculitis, and the diagnosis will be established with renal biopsy, which is the typi-

However, renal biopsy is an invasive method, which is usually mandatory for diagnosis, but, carrying the probability of complications, it cannot be repeated regularly during follow up. This is the reason, why the need to find and apply biomarkers that could help in diagnosis and follow up of the GNs is imperative.

**2. Biomarkers: which are the characteristics of an ideal biomarker?**

The precise characteristics of an ideal biomarker depend upon the disease of investigation, but certain features are considered as important, and are depicted in

Primary and secondary GDs have some unique advantages; first of all kidneys produce urine, and urine are easy to collect in order to repeat measurements during follow up, but also excreted molecules in the urine represent histological changes in the kidneys. Nevertheless, kidneys are highly perfused organs, meaning that any

the triad of microscopic hematuria, proteinuria and impaired renal function.

#### **Chapter 2**

## Biomarkers in Renal Vasculitis

*Polyvios Arseniou, Stamatia Stai and Maria Stangou*

#### **Abstract**

The use of biomarkers in glomerular diseases has been subject of investigation during the last decades, as it can provide worthwhile evidence in diagnosis, but also, it can guide treatment and give information about prognosis and response. Renal biopsy is still the compulsory technique to establish diagnosis, and also to offer information about the severity of renal damage. However, as an invasive method, it cannot be regularly performed during follow up, so the need to find and establish measurement of molecules, easily collected, which are associated with disease pathogenesis and predict renal function outcome seems very attractive to nephrologists. The renal complications of systemic vasculitis are very important for the outcome of the disease, and several substances and molecules, such as inflammatory cells, autoantibodies, cytokines, chemokines and growth factors are produced and may serve as biomarkers to provide useful information for diagnosis, follow up of the disease.

**Keywords:** vasculitis, biomarkers, cytokines, growth factors, outcome

#### **1. Introduction**

The classical presentation of a primary or secondary glomerular disease (GD) is the triad of microscopic hematuria, proteinuria and impaired renal function.

A patient who presents with microhematuria, 2 g of proteinuria and a GRF of around 35 ml/min is possible to have IgAN, focal segmental sclerosis (FSGS) or membranous nephropathy (MN) or focal necrotising glomerulonephritis, due to vasculitis, and the diagnosis will be established with renal biopsy, which is the typical and standard method in diagnosing GN.

However, renal biopsy is an invasive method, which is usually mandatory for diagnosis, but, carrying the probability of complications, it cannot be repeated regularly during follow up. This is the reason, why the need to find and apply biomarkers that could help in diagnosis and follow up of the GNs is imperative.

#### **2. Biomarkers: which are the characteristics of an ideal biomarker?**

The precise characteristics of an ideal biomarker depend upon the disease of investigation, but certain features are considered as important, and are depicted in **Table 1**.

Primary and secondary GDs have some unique advantages; first of all kidneys produce urine, and urine are easy to collect in order to repeat measurements during follow up, but also excreted molecules in the urine represent histological changes in the kidneys. Nevertheless, kidneys are highly perfused organs, meaning that any


**Table 1.**

*Specific characteristics, an ideal biomarker should carry.*

substances in the serum may have a direct effect on them. On the other hand, there are major disadvantages. Pathogenesis of GDs, especially of vasculitis affecting kidneys, is not a simple issue, it is complicated and in most cases not completely identified. Histological lesions are the result of different synergistic or counteracting pathways, which lead to proliferation, inflammation and fibrosis. In addition, the same molecule will not have the same effect in all glomerular diseases [1–5].

All the above mean that all the information provided by kidney biopsy cannot be easily substituted by one biomarker, and the question that comes up is: do the biomarkers have something to offer which is beyond the renal biopsy results and beyond the classical approach of glomerular diseases, including estimation of renal function impairment, degree of proteinuria, microhematuria and active urine sediment, or do they just correlate with these parameters and reflect renal damage?

In the present chapter, we are going to describe biomarkers involved in pathogenesis and outcome of systemic vasculitis affecting the kidneys, and we shall investigate possible advantage instead of using classical parameters.

#### **3. ANCA-associated vasculitides**

ANCA-associated vasculitides (AAV) are a group of systemic pauci-immune diseases, characterized by inflammatory necrosis of the small vessels (arterioles, capillaries and venules) and the presence of antineutrophil cytoplasmic antibodies (ANCA) [6–11]. There are four clinical and pathological phenotypes of AAV: granulomatosis with polyangiitis (GPA, formerly known as Wegener's granulomatosis), eosinophilic granulomatosis with polyangiitis (EGPA, also known as Churg-Strauss syndrome), microscopic polyangiitis (MPA) and, finally, renal limited vasculitis (RLV), also known as idiopathic rapidly progressive glomerulonephritis (RPGN) [9, 11]. Contrary to other small-vessel vasculitides, which are immune-complexmediated, in AAV there is no significant immunoglobulin deposition [6, 9–11].

#### **4. ANCA**

ANCA are IgG autoantibodies directed against proteinase 3 (PR3-ANCA), expressed in neutrophil granules, and myeloperoxidase (MPO-ANCA), expressed in monocyte lysosomes. PR3 and MPO are also expressed in the neutrophil extracellular traps (NET), localized to inflammatory lesions within the affected organs [6–11]. Because of their immunofluorescence pattern, PR3-ANCA are also described as cytoplasmic ANCA (c-ANCA), whereas MPO-ANCA are referred to as perinuclear ANCA (p-ANCA) [5, 9–11]. Indirect immunofluorescence and enzymelinked immunosorbent assay (ELISA) methods are used to detect ANCA in the

**15**

possible therapeutic target [6–11].

*Biomarkers in Renal Vasculitis*

the serotype of the AAV [8, 11].

the formation of antibodies [6–10].

**5. Pathogenesis**

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

serum of patients [9, 11]. The type of ANCA (PR3-ANCA or MPO-ANCA) defines

There is a correlation between the serotype and the phenotype of AAV. PR3- ANCA are most common (75%) in patients with GPA and least common (5%) in patients with EGPA. MPO-ANCA occur more frequently in patients with RLV (70%), while they appear in 60% of patients with EGPA and 50% of patients with MPA. The occurrence of seronegativity is 5 and 30% in GPA and EGPA, respectively, and 10% in MPO and RLV [9]. ANCA-positive patients present either PR3-ANCA or MPO-ANCA, whereas the occurrence of both ANCA in the same individual is extremely

rare and related to infection-induced or drug-mediated vasculitis [5, 9–11].

However, autoantibodies against different antigenic targets, such as lysosomeassociated membrane protein-2 (LAMP-2), plasminogen, moesin, have been demonstrated recently, and they were related to different precipitating causes, as well as different disease presentation and severity. Specifically, anti-LAMP-2 antibodies have been found in most patients with RLV linked to *E. coli* urinary tract infection (UTI), suggesting that molecular mimicking mechanisms may be responsible for

PR3 and MPO antigens are presented by autoreactive antigen-presenting B cells to autoreactive T cells, thus stimulating their activation and polarization, with the formation of pro-inflammatory Th1, Th2 and Th17 cells. In that environment, T cells activate B cells, promoting the formation of ANCA. Autoreactivity of B and T cells is presented in patients with genetic susceptibility, as shown by correlation of the disease with specific HLA gene loci, while both SNP in certain genes and epigenetic factors are associated with increased antigenic expression in neutrophils and monocytes. That increased expression of PR3 on the monocyte cell surface causes macrophage activation, while binding of MPO-ANCA promotes the release of pro-inflammatory cytokines, such as IL-1β, IL-6 and IL-8. On the other side, increased PR3 expression on the neutrophil surface, in patients with GPA, promotes diminished macrophage phagocytosis of neutrophils that have undergone apoptosis, leading to uncontrolled necrosis and release of more antigens and pro-inflammatory cytokines, including IL-6, IL-8 and TNF-α, which

further amplify the previous pathological immune mechanism [6–11].

The involvement of immune cells in pathogenesis of AAV, through impaired immune tolerance and balance between immune response and immune regulation is crucial. As mentioned, B cells are responsible for antigen presentation and antibody production, but also for cytokine production and activation of T cells. That is why rituximab, a chimeric monoclonal anti-CD20 antibody, is successfully administered as therapy for AAV. Besides that, regulating B cells, which act suppressing immune response, are found numerically normal, but with impaired function. This also applies for regulating T cells, while, on the contrary, effector T cells are found infiltrating affected tissues, alongside with macrophages, neutrophils and monocytes. These cells are responsible for direct tissue damage, releasing reacting oxygen species. Neutrophils, specifically, appear to be the main participating cell in vessel damage, via

the respiratory burst and the release of proteolytic enzymes and NET [6–11]. There are recent data from animal and patient studies suggesting that the complement is also involved in AAV. Altered levels of C3, C4, and CH50 are found in some patients during presentation and are associated with adverse outcome. Moreover, C5a and its receptor are implicated in neutrophil activation, thus establishing the alternative compliment pathway as a promoting disease factor and a

#### *Biomarkers in Renal Vasculitis DOI: http://dx.doi.org/10.5772/intechopen.86489*

*Glomerulonephritis and Nephrotic Syndrome*

4. Associated with pathogenic mechanisms 5. Prognosis and response to treatment 6. Biomarker sources should be easily available

*Specific characteristics, an ideal biomarker should carry.*

1. High sensitivity 2. High specificity 3. Biological plausibility

**Table 1.**

substances in the serum may have a direct effect on them. On the other hand, there are major disadvantages. Pathogenesis of GDs, especially of vasculitis affecting kidneys, is not a simple issue, it is complicated and in most cases not completely identified. Histological lesions are the result of different synergistic or counteracting pathways, which lead to proliferation, inflammation and fibrosis. In addition, the same molecule will not have the same effect in all glomerular diseases [1–5]. All the above mean that all the information provided by kidney biopsy cannot be easily substituted by one biomarker, and the question that comes up is: do the biomarkers have something to offer which is beyond the renal biopsy results and beyond the classical approach of glomerular diseases, including estimation of renal function impairment, degree of proteinuria, microhematuria and active urine sediment, or do they just correlate with these parameters and reflect renal damage? In the present chapter, we are going to describe biomarkers involved in pathogenesis and outcome of systemic vasculitis affecting the kidneys, and we shall

investigate possible advantage instead of using classical parameters.

ANCA-associated vasculitides (AAV) are a group of systemic pauci-immune diseases, characterized by inflammatory necrosis of the small vessels (arterioles, capillaries and venules) and the presence of antineutrophil cytoplasmic antibodies (ANCA) [6–11]. There are four clinical and pathological phenotypes of AAV: granulomatosis with polyangiitis (GPA, formerly known as Wegener's granulomatosis), eosinophilic granulomatosis with polyangiitis (EGPA, also known as Churg-Strauss syndrome), microscopic polyangiitis (MPA) and, finally, renal limited vasculitis (RLV), also known as idiopathic rapidly progressive glomerulonephritis (RPGN) [9, 11]. Contrary to other small-vessel vasculitides, which are immune-complexmediated, in AAV there is no significant immunoglobulin deposition [6, 9–11].

ANCA are IgG autoantibodies directed against proteinase 3 (PR3-ANCA), expressed in neutrophil granules, and myeloperoxidase (MPO-ANCA), expressed in monocyte lysosomes. PR3 and MPO are also expressed in the neutrophil extracellular traps (NET), localized to inflammatory lesions within the affected organs [6–11]. Because of their immunofluorescence pattern, PR3-ANCA are also described as cytoplasmic ANCA (c-ANCA), whereas MPO-ANCA are referred to as perinuclear ANCA (p-ANCA) [5, 9–11]. Indirect immunofluorescence and enzymelinked immunosorbent assay (ELISA) methods are used to detect ANCA in the

**3. ANCA-associated vasculitides**

**14**

**4. ANCA**

serum of patients [9, 11]. The type of ANCA (PR3-ANCA or MPO-ANCA) defines the serotype of the AAV [8, 11].

There is a correlation between the serotype and the phenotype of AAV. PR3- ANCA are most common (75%) in patients with GPA and least common (5%) in patients with EGPA. MPO-ANCA occur more frequently in patients with RLV (70%), while they appear in 60% of patients with EGPA and 50% of patients with MPA. The occurrence of seronegativity is 5 and 30% in GPA and EGPA, respectively, and 10% in MPO and RLV [9]. ANCA-positive patients present either PR3-ANCA or MPO-ANCA, whereas the occurrence of both ANCA in the same individual is extremely rare and related to infection-induced or drug-mediated vasculitis [5, 9–11].

However, autoantibodies against different antigenic targets, such as lysosomeassociated membrane protein-2 (LAMP-2), plasminogen, moesin, have been demonstrated recently, and they were related to different precipitating causes, as well as different disease presentation and severity. Specifically, anti-LAMP-2 antibodies have been found in most patients with RLV linked to *E. coli* urinary tract infection (UTI), suggesting that molecular mimicking mechanisms may be responsible for the formation of antibodies [6–10].

#### **5. Pathogenesis**

PR3 and MPO antigens are presented by autoreactive antigen-presenting B cells to autoreactive T cells, thus stimulating their activation and polarization, with the formation of pro-inflammatory Th1, Th2 and Th17 cells. In that environment, T cells activate B cells, promoting the formation of ANCA. Autoreactivity of B and T cells is presented in patients with genetic susceptibility, as shown by correlation of the disease with specific HLA gene loci, while both SNP in certain genes and epigenetic factors are associated with increased antigenic expression in neutrophils and monocytes. That increased expression of PR3 on the monocyte cell surface causes macrophage activation, while binding of MPO-ANCA promotes the release of pro-inflammatory cytokines, such as IL-1β, IL-6 and IL-8. On the other side, increased PR3 expression on the neutrophil surface, in patients with GPA, promotes diminished macrophage phagocytosis of neutrophils that have undergone apoptosis, leading to uncontrolled necrosis and release of more antigens and pro-inflammatory cytokines, including IL-6, IL-8 and TNF-α, which further amplify the previous pathological immune mechanism [6–11].

The involvement of immune cells in pathogenesis of AAV, through impaired immune tolerance and balance between immune response and immune regulation is crucial. As mentioned, B cells are responsible for antigen presentation and antibody production, but also for cytokine production and activation of T cells. That is why rituximab, a chimeric monoclonal anti-CD20 antibody, is successfully administered as therapy for AAV. Besides that, regulating B cells, which act suppressing immune response, are found numerically normal, but with impaired function. This also applies for regulating T cells, while, on the contrary, effector T cells are found infiltrating affected tissues, alongside with macrophages, neutrophils and monocytes. These cells are responsible for direct tissue damage, releasing reacting oxygen species. Neutrophils, specifically, appear to be the main participating cell in vessel damage, via the respiratory burst and the release of proteolytic enzymes and NET [6–11].

There are recent data from animal and patient studies suggesting that the complement is also involved in AAV. Altered levels of C3, C4, and CH50 are found in some patients during presentation and are associated with adverse outcome. Moreover, C5a and its receptor are implicated in neutrophil activation, thus establishing the alternative compliment pathway as a promoting disease factor and a possible therapeutic target [6–11].

As far as genetic susceptibility is concerned, genome-wide association studies (GWAS) have documented a close relation between the phenotype and serotype of AAV and specific HLA gene loci. In detail, studies on Northern European and American populations have shown that GPA and PR3-ANCA are strongly associated with HLA-DP loci (with HLA-DP 0401 being associated with PR3-ANCA vasculitis and recurrence of disease, regardless of phenotype or serotype), while MPO-ANCA are related to HLA-DQ loci. HLA-DR B1501 is associated with AAV presentation in African American patients and HLA-DR B4 with EGPA. Besides HLA genes, SNP in genes PRTN3, coding for PR3, and SERPINA1, coding for a1-antitrypsin (A1AT), a protein regulating PR3, are associated with the formation of PR3-ANCA, while SNP in gene PTPN22, coding for a protein tyrosine phosphatase, regulating B and T cell receptor-mediated cell activation, is implicated in the dysregulation of immune response [6–11].

#### **6. Clinical presentation**

AAV is, as mentioned before, a necrotizing inflammation of the small vessels. Therefore, it is considered a systemic disorder, affecting all tissues and organs. The clinical presentation depends on the activity and the chronicity of the disease and the specific system involvement and determines, together with the pathology, the phenotype of the disease [9].

The onset of the disease may be accompanied by non-specific systemic symptoms, such as fever, fatigue, malaise, anorexia, weight loss, arthralgia and myalgia. These symptoms, reminiscent of flu-like illness, may precede weeks or even months before the occurrence of specific systemic manifestations [9, 12].

Renal involvement is the most significant and severe of AAV clinical presentation. It affects almost every patient with MPA (90%) and GPA (80%), but less than half of the patients with EGPA (45%). The most common presentation is with RPGN, thus featuring typically microscopic or gross hematuria, subnephrotic proteinuria, hypertension, edema and, finally, renal failure, while examination of the urine reveals active urinary sediment, with dysmorphic red blood cells and red blood cell casts. Another presentation, common to patients with MPO-ANCA, is indolent glomerulonephritis, featuring a more chronic presence of microscopic hematuria and a slower decline of renal function. Interestingly, 5% of the patients with ANCA vasculitis (mostly MPO-ANCA) are also positive for anti-glomerular base membrane (anti-GBM) antibodies, suggesting concomitant glomerular lesions of AAV and anti-GBM disease. Renal involvement is the only manifestation of RLV [9, 11, 12].

Lower respiratory system involvement is more frequent in GPA (90%) and EGPA (70%) and less frequent in MPA (50%). Pulmonary manifestations vary from transient infiltration of the alveoli to severe pulmonary hemorrhage. Clinical, laboratory and imaging findings include dyspnea, cough, hemoptysis, acid-base balance and blood gases disorder, lung functional tests disorder, as well as radiological ground-glass pattern, with nodules and diffuse infiltrates [9, 11, 12].

Upper respiratory system is also involved in the clinical presentation, concerning mostly patients with GPA (90%), but also half of the patients with EGPA and 35% of the patients with MPA. Patients present sinusitis, rhinitis, ocular inflammatory disorders, such as episcleritis, necrosis and perforation of the nasal septum and subglottic stenosis. Interestingly, EGPA, is less associated with RPGN and pulmonary hemorrhage and is characterized by a prodromal phase of atopic manifestations, asthma and allergic rhinitis, followed by an eosinophilic phase of increased eosinophil counts in the blood and eosinophilic perfusion of affected tissues, before evolving to active vasculitis [9, 11, 12].

**17**

**Figure 1.**

*Biomarkers in Renal Vasculitis*

ges is less frequent [9, 11, 12].

**7. Renal pathology**

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

Involvement of the central and peripheral nervous system accompanies 70% of patients with EGPA, 50% of patients with GPA and 30% of patients with MPA and manifests usually as mononeuritis multiplex, while the inflammation of the menin-

Cardiovascular involvement, mainly in ANCA-negative EGPA patients, presents as endocarditis, pericarditis or myocarditis, hypokinesis of the ventricles arrhythmias, such

Gastrointestinal involvement, affecting half of the patients with AAV, presents as an acute abdomen, with abdominal pain, hematochezia and sometimes even

Finally, AAV present with a plethora of cutaneous lesion, such as purpura,

Renal biopsy is the gold standard for the diagnosis of renal disease, and this also applies for AAV. The classical histopathological feature in renal biopsy of AAV patients

as atrioventricular blocks, and, lastly, as acute myocardial infarction [9, 11, 12].

perforation, due to mesenterial ischemia and ulceration [9, 12].

*Histology of renal involvement in ANCA associated vasculitis (A) and IgAV-N (B).*

petechiae, ecchymoses, ulcers, nodules and more [9].

*Biomarkers in Renal Vasculitis DOI: http://dx.doi.org/10.5772/intechopen.86489*

Involvement of the central and peripheral nervous system accompanies 70% of patients with EGPA, 50% of patients with GPA and 30% of patients with MPA and manifests usually as mononeuritis multiplex, while the inflammation of the meninges is less frequent [9, 11, 12].

Cardiovascular involvement, mainly in ANCA-negative EGPA patients, presents as endocarditis, pericarditis or myocarditis, hypokinesis of the ventricles arrhythmias, such as atrioventricular blocks, and, lastly, as acute myocardial infarction [9, 11, 12].

Gastrointestinal involvement, affecting half of the patients with AAV, presents as an acute abdomen, with abdominal pain, hematochezia and sometimes even perforation, due to mesenterial ischemia and ulceration [9, 12].

Finally, AAV present with a plethora of cutaneous lesion, such as purpura, petechiae, ecchymoses, ulcers, nodules and more [9].

#### **7. Renal pathology**

*Glomerulonephritis and Nephrotic Syndrome*

response [6–11].

**6. Clinical presentation**

phenotype of the disease [9].

As far as genetic susceptibility is concerned, genome-wide association studies (GWAS) have documented a close relation between the phenotype and serotype of AAV and specific HLA gene loci. In detail, studies on Northern European and American populations have shown that GPA and PR3-ANCA are strongly associated with HLA-DP loci (with HLA-DP 0401 being associated with PR3-ANCA vasculitis and recurrence of disease, regardless of phenotype or serotype), while MPO-ANCA are related to HLA-DQ loci. HLA-DR B1501 is associated with AAV presentation in African American patients and HLA-DR B4 with EGPA. Besides HLA genes, SNP in genes PRTN3, coding for PR3, and SERPINA1, coding for a1-antitrypsin (A1AT), a protein regulating PR3, are associated with the formation of PR3-ANCA, while SNP in gene PTPN22, coding for a protein tyrosine phosphatase, regulating B and T cell receptor-mediated cell activation, is implicated in the dysregulation of immune

AAV is, as mentioned before, a necrotizing inflammation of the small vessels. Therefore, it is considered a systemic disorder, affecting all tissues and organs. The clinical presentation depends on the activity and the chronicity of the disease and the specific system involvement and determines, together with the pathology, the

The onset of the disease may be accompanied by non-specific systemic symptoms, such as fever, fatigue, malaise, anorexia, weight loss, arthralgia and myalgia. These symptoms, reminiscent of flu-like illness, may precede weeks or even months

Renal involvement is the most significant and severe of AAV clinical presentation. It affects almost every patient with MPA (90%) and GPA (80%), but less than half of the patients with EGPA (45%). The most common presentation is with RPGN, thus featuring typically microscopic or gross hematuria, subnephrotic proteinuria, hypertension, edema and, finally, renal failure, while examination of the urine reveals active urinary sediment, with dysmorphic red blood cells and red blood cell casts. Another presentation, common to patients with MPO-ANCA, is indolent glomerulonephritis, featuring a more chronic presence of microscopic hematuria and a slower decline of renal function. Interestingly, 5% of the patients with ANCA vasculitis (mostly MPO-ANCA) are also positive for anti-glomerular base membrane (anti-GBM) antibodies, suggesting concomitant glomerular lesions of AAV and anti-GBM disease. Renal involvement is the only manifestation of RLV

Lower respiratory system involvement is more frequent in GPA (90%) and EGPA (70%) and less frequent in MPA (50%). Pulmonary manifestations vary from transient infiltration of the alveoli to severe pulmonary hemorrhage. Clinical, laboratory and imaging findings include dyspnea, cough, hemoptysis, acid-base balance and blood gases disorder, lung functional tests disorder, as well as radiologi-

Upper respiratory system is also involved in the clinical presentation, concerning mostly patients with GPA (90%), but also half of the patients with EGPA and 35% of the patients with MPA. Patients present sinusitis, rhinitis, ocular inflammatory disorders, such as episcleritis, necrosis and perforation of the nasal septum and subglottic stenosis. Interestingly, EGPA, is less associated with RPGN and pulmonary hemorrhage and is characterized by a prodromal phase of atopic manifestations, asthma and allergic rhinitis, followed by an eosinophilic phase of increased eosinophil counts in the blood and eosinophilic perfusion of affected tissues, before

cal ground-glass pattern, with nodules and diffuse infiltrates [9, 11, 12].

before the occurrence of specific systemic manifestations [9, 12].

**16**

evolving to active vasculitis [9, 11, 12].

[9, 11, 12].

Renal biopsy is the gold standard for the diagnosis of renal disease, and this also applies for AAV. The classical histopathological feature in renal biopsy of AAV patients

**Figure 1.** *Histology of renal involvement in ANCA associated vasculitis (A) and IgAV-N (B).*

is segmental necrotizing glomerulonephritis. Characteristic findings include inflammatory perfusion of both glomeruli and interstitial tissue, fibrinoid necrosis of glomeruli, glomerular capillary obstruction and crescents. Granulomas are also found in GPA and EGPA. It is worth mentioning again that, because AAV are pauci-immune vasculitides, immunofluorescence is negative, that meaning there is a paucity or absence of glomerular immune deposits. Nevertheless, there are patients who demonstrate atypical histopathological features, such as interstitial nephritis with vasa recta vasculitis. These patients eventually develop the classical lesions of AAV [9, 11, 12] (**Figure 1**).

#### **8. Biomarkers in AAV**

Any substance that can be objectively measured and evaluated as an indicator of normal and pathogenic processes or response to an intervention can be used as a biomarker [13].

Inflammatory markers, such as erythrocyte sedimentation rate (ESR) and c-reactive protein (CRP), are non-specific and, although they can be used in the diagnosis of AAV, when evaluated together with clinical and pathological presentation, they are of no value in the differential diagnosis and assessment of disease activity and relapse in diagnosed patients [14].

On the contrary, research on platelet (PLT) counts, which are an acknowledged inflammatory marker, found elevated PLT counts in patients with active disease, compared to patients in remission, and also elevated PLT counts in AAV patients with active disease, compared to AAV patients with infection, thus highlighting their role as an AAV specific marker of disease activity [15].

#### **9. ANCA as biomarkers**

Although ANCA are important in the diagnosis of AAV, there are seronegative patients with clinically and pathologically established disease. Furthermore, because diagnosed patients tend to remain ANCA-positive during clinical remission, the use of ANCA as a marker of disease activity and relapse is also limited. Nevertheless, increased values of ANCA in seropositive patients or emergence in seronegative patients, can be evaluated as a marker of disease relapse [14]. Studies have suggested that increase of ANCA titer should not be taken into consideration in terms of changing treatment decisions, but could be used to select patients requiring closer monitoring [14, 16].

#### **10. LAMP-2**

Unlike PR3 and MPO, LAMP-2 is also expressed in glomerular endothelial cells, an important site of inflammatory injury [17]. As mentioned before, anti-LAMP-2 antibodies are believed to be formatted through molecular mimicking of bacterial proteins, proposing the implication of this mechanism in the pathogenesis of disease.

One study indicated that anti-LAMP-2 antibodies are present in 80–90% of untreated patients, including PR3-ANCA negative and MPO-ANCA negative patients, while being undetected in healthy controls. Interestingly, anti-LAMP-2antibodies become rapidly undetectable after immunosuppressive therapy, thus suggesting a possible role in the diagnosis and monitoring of AAV patients. However, these findings were not replicated by other investigators, meaning that the use of these antibodies as a biomarker of disease activity is rather inappropriate [10, 14, 17].

**19**

*Biomarkers in Renal Vasculitis*

**11. Plasminogen**

**12. Moesin**

**13. NET**

**14. Leucocytes**

**15. Monocytes**

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

nitrogen, serum creatinine and proteinuria [14, 18].

of customized therapeutic regimens [14, 17, 20].

The presence of anti-plasminogen antibodies, in about 18–26% of AAV patients, depending on the study, is strongly correlated with glomerular lesion severity, but only weakly correlated with ESR, renal function and renal histopathology [14].

Moesin, a heparin-binding protein linking actin to the plasma membrane of the cellular cortex, is identified as a possible molecule responsible for the formation of MPO-ANCA, using molecular-mimicking mechanisms, similarly to LAMP-2. Anti-moesin antibodies are found increased in both active AAV disease and remission, but are associated with renal damage, as assessed by correlation to blood urea

The contribution of NET in the pathogenesis of AAV is already mentioned. Excessive NET formation is observed in both PR3-ANCA and MPO-ANCA positive patients with active AAV compared to healthy individuals, which is interestingly independent of ANCA titers. Moreover, excessive NET formation is presented in hospitalized AAV patients for disease relapse, but not for infection, suggesting a specificity of NET as a marker of autoimmunity, rather than infection [19].

Regulatory B cells (Bregs) have been investigated as a potential biomarker of AAV. A research group found CD25+ B cells to be increased during disease remission, compared to active disease and healthy controls. Another study revealed CD5+ B cells numerical deficiency in AAV patients, compared to healthy controls. These data, however, are insufficient for the establishment of Bregs as biomarkers in AAV [14, 17]. A study attempted to clarify the role of CD8+ T cells as a biomarker of AAV. The presence of particular gene expression profiles of CD8+ T cells were associated with disease relapse, among patients with the same disease activity, inflammatory markers and treatment. If validated, these data could be used to identify patients in need

Regulatory T cells (Tregs) have also been studied by researchers. Decreased number and impaired functionality of Tregs was found in patients with active AAV. Furthermore, the proportion of Tregs was found inversely correlated with relapse and positively associated with time of remission. Based on these data, Tregs could be used as a biomarker of therapeutic and prognostic importance [14, 17].

The role of monocytes in the pathogenesis and tissue damage in AAV has already been discussed. Soluble and cell surface markers of monocyte activation are increased in AAV patients, even during disease remission. Furthermore, monocyte-derived macrophages and giant cells within affected tissues and

granulomas may be responsible for maintaining autoimmunity. These data suggest

#### **11. Plasminogen**

*Glomerulonephritis and Nephrotic Syndrome*

**8. Biomarkers in AAV**

**9. ANCA as biomarkers**

requiring closer monitoring [14, 16].

**10. LAMP-2**

activity and relapse in diagnosed patients [14].

their role as an AAV specific marker of disease activity [15].

biomarker [13].

is segmental necrotizing glomerulonephritis. Characteristic findings include inflammatory perfusion of both glomeruli and interstitial tissue, fibrinoid necrosis of glomeruli, glomerular capillary obstruction and crescents. Granulomas are also found in GPA and EGPA. It is worth mentioning again that, because AAV are pauci-immune vasculitides, immunofluorescence is negative, that meaning there is a paucity or absence of glomerular immune deposits. Nevertheless, there are patients who demonstrate atypical histopathological features, such as interstitial nephritis with vasa recta vasculitis. These

Any substance that can be objectively measured and evaluated as an indicator of normal and pathogenic processes or response to an intervention can be used as a

On the contrary, research on platelet (PLT) counts, which are an acknowledged inflammatory marker, found elevated PLT counts in patients with active disease, compared to patients in remission, and also elevated PLT counts in AAV patients with active disease, compared to AAV patients with infection, thus highlighting

Although ANCA are important in the diagnosis of AAV, there are seronegative patients with clinically and pathologically established disease. Furthermore, because diagnosed patients tend to remain ANCA-positive during clinical remission, the use of ANCA as a marker of disease activity and relapse is also limited. Nevertheless, increased values of ANCA in seropositive patients or emergence in seronegative patients, can be evaluated as a marker of disease relapse [14]. Studies have suggested that increase of ANCA titer should not be taken into consideration in terms of changing treatment decisions, but could be used to select patients

Unlike PR3 and MPO, LAMP-2 is also expressed in glomerular endothelial cells, an important site of inflammatory injury [17]. As mentioned before, anti-LAMP-2 antibodies are believed to be formatted through molecular mimicking of bacterial proteins, proposing the implication of this mechanism in the pathogenesis of disease. One study indicated that anti-LAMP-2 antibodies are present in 80–90% of untreated patients, including PR3-ANCA negative and MPO-ANCA negative patients, while being undetected in healthy controls. Interestingly, anti-LAMP-2antibodies become rapidly undetectable after immunosuppressive therapy, thus suggesting a possible role in the diagnosis and monitoring of AAV patients. However, these findings were not replicated by other investigators, meaning that the use of these antibodies as a biomarker of disease activity is rather inappropriate [10, 14, 17].

Inflammatory markers, such as erythrocyte sedimentation rate (ESR) and c-reactive protein (CRP), are non-specific and, although they can be used in the diagnosis of AAV, when evaluated together with clinical and pathological presentation, they are of no value in the differential diagnosis and assessment of disease

patients eventually develop the classical lesions of AAV [9, 11, 12] (**Figure 1**).

**18**

The presence of anti-plasminogen antibodies, in about 18–26% of AAV patients, depending on the study, is strongly correlated with glomerular lesion severity, but only weakly correlated with ESR, renal function and renal histopathology [14].

#### **12. Moesin**

Moesin, a heparin-binding protein linking actin to the plasma membrane of the cellular cortex, is identified as a possible molecule responsible for the formation of MPO-ANCA, using molecular-mimicking mechanisms, similarly to LAMP-2. Anti-moesin antibodies are found increased in both active AAV disease and remission, but are associated with renal damage, as assessed by correlation to blood urea nitrogen, serum creatinine and proteinuria [14, 18].

#### **13. NET**

The contribution of NET in the pathogenesis of AAV is already mentioned. Excessive NET formation is observed in both PR3-ANCA and MPO-ANCA positive patients with active AAV compared to healthy individuals, which is interestingly independent of ANCA titers. Moreover, excessive NET formation is presented in hospitalized AAV patients for disease relapse, but not for infection, suggesting a specificity of NET as a marker of autoimmunity, rather than infection [19].

#### **14. Leucocytes**

Regulatory B cells (Bregs) have been investigated as a potential biomarker of AAV. A research group found CD25+ B cells to be increased during disease remission, compared to active disease and healthy controls. Another study revealed CD5+ B cells numerical deficiency in AAV patients, compared to healthy controls. These data, however, are insufficient for the establishment of Bregs as biomarkers in AAV [14, 17].

A study attempted to clarify the role of CD8+ T cells as a biomarker of AAV. The presence of particular gene expression profiles of CD8+ T cells were associated with disease relapse, among patients with the same disease activity, inflammatory markers and treatment. If validated, these data could be used to identify patients in need of customized therapeutic regimens [14, 17, 20].

Regulatory T cells (Tregs) have also been studied by researchers. Decreased number and impaired functionality of Tregs was found in patients with active AAV. Furthermore, the proportion of Tregs was found inversely correlated with relapse and positively associated with time of remission. Based on these data, Tregs could be used as a biomarker of therapeutic and prognostic importance [14, 17].

#### **15. Monocytes**

The role of monocytes in the pathogenesis and tissue damage in AAV has already been discussed. Soluble and cell surface markers of monocyte activation are increased in AAV patients, even during disease remission. Furthermore, monocyte-derived macrophages and giant cells within affected tissues and granulomas may be responsible for maintaining autoimmunity. These data suggest that monocytes may account for disease relapse, thus be used as a prognostic biomarker of negative outcome [21].

#### **16. Inflammatory response**


**21**

**Table 2.**

*vasculitis and controls.*

*Biomarkers in Renal Vasculitis*

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

successful therapy of AAV [14, 27].

outcome and disease relapse [14, 17, 28].

**Cytokine (pg/mg Ucr) RPGN**

**18. Urinary biomarkers**

controls [29].

**17. Other serum inflammatory proteins**

Among many serum inflammatory proteins, such as cytokine, chemokines, soluble receptors, etc., CXCL13 (BCA-1), matrix metalloproteinase-3 (MMP-3) and tissue inhibitor of metalloproteinases-1 (TIMP-1) report the strongest correlation with AAV. Specifically, higher levels of these proteins are found in patients with active disease, compared to healthy individuals, and are also able to distinguish active disease from disease remission. Additionally, lower levels are measured after

A study investigated the role of four urinary proteins [alpha-1 acid glycoprotein (AGP), kidney injury molecule-1 (KIM-1), MCP-1 and NGAL (with the last two being already mentioned above as serum biomarkers)] as biomarkers of active disease. All four proteins were found increased in the urine of patients during active renal disease, compared to remission, with MCP-1 being the most accurate discriminator between the two [23]. MCP-1 levels were also strongly indicative of poor

Another research studied the possible use of urinary soluble CD163 (sCD163), secreted by monocytes and macrophages, as a biomarker in small vessel vasculitis (SVV). Glomeruli of patients with SVV contained remarkably higher levels of CD163 RNA, thus presented increased expression of CD163, than those of patients from disease controls (lupus nephritis, diabetic nephropathy, nephrotic syndrome) [29]. In addition, patients with active SSV had higher levels of urinary sCD163, compared to patients in disease remission [14, 29], disease controls and healthy

Urinary excretion of angiogenic factors (VEGF, EGF), cytokines with known pro-inflammatory (IL-6, MCP-1, MIP-1b), anti-inflammatory (IL-2, IL-4, IL-15), and pro-fibrotic activity (TGF-β, IL-6) have been evaluated as biomarkers in renal

IL-2 0.003 ± 0.01 0 0.04 IL-4 0.003 ± 0.006 0.008 ± 0.001 0.04 IL-6 1.2 ± 0.03 0.001 ± 0.001 0.05 IL-8 0.94 ± 2.8 0.04 ± 0.09 0.05 IL-9 0.9 ± 0.0001 0.04 ± 0.09 0.02 IL-15 0.2 ± 0.5 0 0.03 TGF-β1 27.5 ± 79 0.02 ± 0.05 0.04 VEGF 4.3 ± 3.6 0.001 ± 0.0007 <0.0001 MCP-1 2.5 ± 0.001 0.1 ± 0.04 0.01 MIP-1β 1.6 ± 0.001 0.06 ± 0.05 0.02 EGF 0.15 ± 0.3 0.14 ± 0.07 NS

*Differences in the urinary excretion between patients with rapidly progressive glomerulonephritis due to* 

**Controls n = 10**

**p**

**n = 38**

*Glomerulonephritis and Nephrotic Syndrome*

biomarker of negative outcome [21].

**16. Inflammatory response**

biopsy [14, 17].

levels and proteinuria severity [23].

with AAV, compared to healthy individuals [24].

CPR and ANCA titers [25].

of relapse onset [26].

that monocytes may account for disease relapse, thus be used as a prognostic

• **Complement**: Plasma levels of C3a, C5a, soluble C5b-9 and Bbare found increased in patients with active disease, compared to patients with disease remission and healthy controls [14, 17]. C5a receptor (C5aR) expression is found lower in renal tissue of patients with active disease [17, 22]. Furthermore, plasma levels of Bb, which is indicative of alternative pathway activation, is associated with serum inflammatory markers and the presence of crescents in renal biopsy. Similarly, urinary levels of Bb are positively correlated with serum creatinine levels, indicative of renal function, and negatively correlated with the percentage of normal glomeruli in renal

• **Monocyte chemotactic protein-1**: Monocyte chemotactic protein-1 (MCP-1), as declared by its name, affects the monocyte/macrophage migration to the tissues. It is also related to the number of circulating monocytes and T cells. Serum MCP-1 is measured significantly higher in patients with AAV, compared to healthy controls. Interestingly, in AAV patients, MCP-1 is found elevated in those with renal involvement, compared to patients without renal involvement. Moreover, serum MCP-1 levels are correlated with serum creatinine

• **Calprotectin**: Calprotectin is a heterodimer complex of two calcium-binding proteins, expressed on neutrophils, monocytes and early differentiated macrophages [14, 24]. Serum calprotectin is found increased in patients with active AAV and decreased, but not normalized, during remission, thus implicating subclinical disease [24]. Calprotectin levels are, additionally, elevated in patients who discontinued treatment [24] and in patients who relapsed [9, 19], with the elevation predictive of relapse happening during remission [14]. Correlation between calprotectin expression and renal biopsy indicates higher expression of calprotectin in patients with focal lesions and crescents and lower expression in patients with sclerotic findings. Furthermore, neutrophil and monocyte cell surface calprotectin expression is, also, higher in patients

• **Neutrophil gelatinase-associated lipocalin**: Neutrophil gelatinase-associated lipocalin (NGAL) is a protein contained in neutrophil granules and, because of its primary secretion, is considered a marker of neutrophil degranulation. Serum levels of NGAL are higher at initial onset and disease relapse of AAV, compared to disease remission, thus suggesting a role in AAV diagnosis and evaluation of activity. Moreover, they are associated with disease severity, ESR,

• **Angiopoietin-2**: Angiopoietin-2 (Ang-2), an important regulator of endothelial activation, is also positively associated with AAV severity. However, levels of Ang-2 do not decline after successful therapy, thus are not predictive of response to therapy, and, moreover, levels during remission are not predictive

**20**

#### **17. Other serum inflammatory proteins**

Among many serum inflammatory proteins, such as cytokine, chemokines, soluble receptors, etc., CXCL13 (BCA-1), matrix metalloproteinase-3 (MMP-3) and tissue inhibitor of metalloproteinases-1 (TIMP-1) report the strongest correlation with AAV. Specifically, higher levels of these proteins are found in patients with active disease, compared to healthy individuals, and are also able to distinguish active disease from disease remission. Additionally, lower levels are measured after successful therapy of AAV [14, 27].

#### **18. Urinary biomarkers**

A study investigated the role of four urinary proteins [alpha-1 acid glycoprotein (AGP), kidney injury molecule-1 (KIM-1), MCP-1 and NGAL (with the last two being already mentioned above as serum biomarkers)] as biomarkers of active disease. All four proteins were found increased in the urine of patients during active renal disease, compared to remission, with MCP-1 being the most accurate discriminator between the two [23]. MCP-1 levels were also strongly indicative of poor outcome and disease relapse [14, 17, 28].

Another research studied the possible use of urinary soluble CD163 (sCD163), secreted by monocytes and macrophages, as a biomarker in small vessel vasculitis (SVV). Glomeruli of patients with SVV contained remarkably higher levels of CD163 RNA, thus presented increased expression of CD163, than those of patients from disease controls (lupus nephritis, diabetic nephropathy, nephrotic syndrome) [29]. In addition, patients with active SSV had higher levels of urinary sCD163, compared to patients in disease remission [14, 29], disease controls and healthy controls [29].

Urinary excretion of angiogenic factors (VEGF, EGF), cytokines with known pro-inflammatory (IL-6, MCP-1, MIP-1b), anti-inflammatory (IL-2, IL-4, IL-15), and pro-fibrotic activity (TGF-β, IL-6) have been evaluated as biomarkers in renal


#### **Table 2.**

*Differences in the urinary excretion between patients with rapidly progressive glomerulonephritis due to vasculitis and controls.*

**Figure 2.** *Impact of cytokines during the acute and chronic phase of vasculitis.*

**23**

*Biomarkers in Renal Vasculitis*

the disease [30, 31].

[32–34].

**20. Renal pathology**

classification [35].

**19. IgA vasculitis-nephritis**

(PRES) (EULAR/PRI NTO/PRES) [35, 36].

tion may vary between cases (**Figure 1**) [35, 36].

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

vasculitis. Most of them were significantly increased compared to controls (**Table 2**). Cytokines with possible impact to histologic findings were TGF-β1, IL-15, MCP-1, MIP-1b and EGF. Several factors, such as IL-6, VEGF, MIP-1b and IL-15 could predict worse outcome of renal function, while others, including EGF, IL-2 and IL-9 were correlated with a favorable outcome (**Figures 2** and **3**). The above findings suggested that these factors may act synergistically or competitively during the progression of

Immunoglobulin A vasculitis-nephritis (IgAV-N), formerly known as Henoch-Schonlein purpura nephritis (HSPN) is the most common vasculitis in childhood, with an annual incidence of 13–20/100,000 children under 17 years of age, but also affects adults and elderly patients with increasing incidence. IgAV is a small vessel vasculitis, usually presents by palpable purpura on the lower legs, arthritis, abdominal pain, and nephritis, while less frequent are manifestations from pulmonary involvement, such as alveolar hemorrhage and neurologic involvement

Diagnosis of the IgAV-N is mainly based on the criteria defined by The European

Among children with IgAV a proportion of 20–60% will show renal complications, most of them occur at disease onset. Manifestations of renal involvement cover a wide spectrum of symptoms ranging from urinary abnormalities, such as hematuria or/and proteinuria, to rapidly progressive glomerulonephritis and acute kidney disease. Although disease is considered as mild and self-limited, a considerable proportion reaching to 15% will develop chronic kidney disease. The presence of nephritic syndrome, impaired renal function at presentation, increased levels of proteinuria, severe histology and no response to treatment are considered as

Histology of IgAV-N is characterized by mesangial hypercellularity and mesangial deposition of IgA and C3, with or without IgG. Fibrinoid necrosis and crescents are a common finding, while the presence of segmental or global sclerosis, endocapillary hyperplasia, severity of tubulointerstital fibrosis and inflammatory infiltra-

Several classification systems have attempted to organize histological findings and evaluate their significance. The classification proposed by the International Study of Kidney Disease in Children (ISKDC), mainly based on the presence and extent of crescents, is widely used, although lately there have been attempts to apply Oxford classification system in IgAV-N, in the same way as this is used for IgAN

According to ISKDC classification, optical microscopy findings are categorized into six histological grades. Grades I-V are based on the extension of crescents, grade VI describes a membranoproliferative type glomerulonephritis. The system was designed to estimate vasculitic lesions and inflammation, therefore it took into account the state of glomeruli only and not tubulointerstitial lesions. This seems to be the main disadvantage of the system, as presence and percentage of crescent

League Against Rheumatism (EULAR), Paediatric Rheumatology International Trials Organization (PRINTO) and Paediatric Rheumatology European Society

parameters predicting adverse outcome of renal function [32, 34].

**Figure 3.** *Favorable influence of cytokines in renal function outcome.*

*Glomerulonephritis and Nephrotic Syndrome*

**22**

**Figure 3.**

**Figure 2.**

*Impact of cytokines during the acute and chronic phase of vasculitis.*

*Favorable influence of cytokines in renal function outcome.*

vasculitis. Most of them were significantly increased compared to controls (**Table 2**). Cytokines with possible impact to histologic findings were TGF-β1, IL-15, MCP-1, MIP-1b and EGF. Several factors, such as IL-6, VEGF, MIP-1b and IL-15 could predict worse outcome of renal function, while others, including EGF, IL-2 and IL-9 were correlated with a favorable outcome (**Figures 2** and **3**). The above findings suggested that these factors may act synergistically or competitively during the progression of the disease [30, 31].

#### **19. IgA vasculitis-nephritis**

Immunoglobulin A vasculitis-nephritis (IgAV-N), formerly known as Henoch-Schonlein purpura nephritis (HSPN) is the most common vasculitis in childhood, with an annual incidence of 13–20/100,000 children under 17 years of age, but also affects adults and elderly patients with increasing incidence. IgAV is a small vessel vasculitis, usually presents by palpable purpura on the lower legs, arthritis, abdominal pain, and nephritis, while less frequent are manifestations from pulmonary involvement, such as alveolar hemorrhage and neurologic involvement [32–34].

Diagnosis of the IgAV-N is mainly based on the criteria defined by The European League Against Rheumatism (EULAR), Paediatric Rheumatology International Trials Organization (PRINTO) and Paediatric Rheumatology European Society (PRES) (EULAR/PRI NTO/PRES) [35, 36].

Among children with IgAV a proportion of 20–60% will show renal complications, most of them occur at disease onset. Manifestations of renal involvement cover a wide spectrum of symptoms ranging from urinary abnormalities, such as hematuria or/and proteinuria, to rapidly progressive glomerulonephritis and acute kidney disease. Although disease is considered as mild and self-limited, a considerable proportion reaching to 15% will develop chronic kidney disease. The presence of nephritic syndrome, impaired renal function at presentation, increased levels of proteinuria, severe histology and no response to treatment are considered as parameters predicting adverse outcome of renal function [32, 34].

#### **20. Renal pathology**

Histology of IgAV-N is characterized by mesangial hypercellularity and mesangial deposition of IgA and C3, with or without IgG. Fibrinoid necrosis and crescents are a common finding, while the presence of segmental or global sclerosis, endocapillary hyperplasia, severity of tubulointerstital fibrosis and inflammatory infiltration may vary between cases (**Figure 1**) [35, 36].

Several classification systems have attempted to organize histological findings and evaluate their significance. The classification proposed by the International Study of Kidney Disease in Children (ISKDC), mainly based on the presence and extent of crescents, is widely used, although lately there have been attempts to apply Oxford classification system in IgAV-N, in the same way as this is used for IgAN classification [35].

According to ISKDC classification, optical microscopy findings are categorized into six histological grades. Grades I-V are based on the extension of crescents, grade VI describes a membranoproliferative type glomerulonephritis. The system was designed to estimate vasculitic lesions and inflammation, therefore it took into account the state of glomeruli only and not tubulointerstitial lesions. This seems to be the main disadvantage of the system, as presence and percentage of crescent

formation merely reflect active inflammation, and their predictive value has been doubted in recent studies, which showed that patients on higher grades may experience spontaneous remission, while those with low grade histologic lesions may develop chronic renal failure [37–40].

The Oxford classification system, available since 2009, has been designed to estimate histology in IgAN, and it was based initially on four morphologic features: mesangial hypercellularity (M), endocapillary proliferation (E), segmental glomerulosclerosis (S) and tubular atrophy/interstitial fibrosis (T), which formed the MEST score [41–43]. More recently, the system was revised to MEST-C score, including the present of crescents, as crescent score (C) [44]. Although patients with IgAV-N were not included in the validation cohort, and therefore, the classification system cannot officially be recommend for patients with this condition, there have been few recent attempts to apply Oxford classification in IgAV-N. The presence of endocapillary proliferation and tubulointerstitial fibrosis were the main histologic findings associated with worse outcome of renal function [44–46].

Renal biopsy is essential for diagnosing IgAV-N, probably guide treatment and predict outcome, but, the procedure cannot be used repeatedly during follow up of the patients. The use of biomarkers is again mandatory to estimate disease outcome. IgAV-N share the same pathogenic pathway with IgAN, mediated by aberrant O-linked glycosylation of IgA1 hinge region, they are considered similar diseases that share common pathophysiologic mechanisms. Based on this fact, researchers tried to evaluate the utility of IgAN biomarkers in the assessment of the clinical course of IgAV-N. It was thus found that several of them could be used in IgAV-N patients as well [47, 48].

#### **21. Biomarkers in IgAV-N**

#### **21.1 Serum and urine immunoglobins and immune complexes**

Since IgA deposition in various tissues is an important parameter of the disease pathophysiology, several studies have tried to examine immunoglobin production in IgAV patients. It has been found that IgA and IgE serum concentrations are higher in individuals with IgAV compared to normal controls, although it has not been proven that they can be useful in distinguishing patients with and without nephritis [47]. Moreover, serum Gd-IgA1 and IgA-IgG complexes, as well as urine IgA and IgA-IgG complexes are potential biomarkers for IgAV-N. More specifically, elevated levels of Gd-IgA1 in the blood of IgAV patients have been correlated with the presence of nephritis [47]. It has been proposed that recognition of the under galactosylated IgA1 hinge region by IgA or IgG antibodies induces the production of circulating immune complexes [47, 48]. Indeed, high concentrations of IgA-IgG complexes have been found in the serum of all IgAV-N patients, while in urine, the levels of these complexes are increased only in patients who have developed nephritis [47, 48]. It seems though that deterioration of renal function is not associated with the serum levels of Gd-IgA1 and IgA-IgG complexes. Recently, a French multicenter prospective study showed that urinary IgA concentration can be used as an additional index in order to improve patient risk stratification for poor outcome at disease onset. This is an important finding, since only a small percentage of IgAV patients finally develop severe deterioration of renal function and can benefit from intensive care, monitoring and follow-up and for the time IgAV outcome assessment is based on conventional clinical factors [48].

**25**

*Biomarkers in Renal Vasculitis*

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

**22. Cluster of differentiation (CD) antigens**

earlier in the urine of patients with IgAV-N [51].

Concerning CD antigens that could be used as biomarkers, CD89 has been found

to be useful in the assessment of IgAV. CD89 is the human myeloid specific IgA Fc receptor. It is expressed on neutrophils, eosinophils, monocytes/macrophages, dendritic cells and Kupffer cells [49, 50]. In IgAN patients, cleavage of the CD89 extracellular domain and release of IgA-soluble CD89 (IgA-sCD89) complexes is caused by the binding of IgA to CD89. Therefore, high levels of circulating IgAsCD89 complexes are observed in these patients. The complexes are trapped in the mesangium by the transferin receptor. Their deposition, as well as mesangial activation, is facilitated by transglutaminase 2 (TG2) [48, 51]. IgAV patients demonstrate decreased expression of CD89 at their monocyte and granulocyte cell surface. This finding is combined with increased blood concentration of IgA-sCD89 complexes. Urinary levels of these complexes are more elevated in individuals who develop nephritis [47, 48]. Furthermore, according to the findings of a 2016 multicenter study, urinary CD89 and TG2 concentrations are significantly lower in patients with active IgA vasculitis with nephritis (IgAV-N) compared to individuals whose disease has gone into complete or partial remission. More specifically, urinary CD89 and TG2 levels were found to be positively correlated with each other and negatively correlated with the level of proteinuria. It has been proposed that this decrease is consistent with the reduction in CD89 and TG2 urinary excretion as a result of the mononuclear-cell mediated inflammatory reaction that is induced by IgA-sCD89 deposition in the kidney. During this active phase, large multimolecular complexes containing CD89, TG2, CD71 and IgA1 are stabilized on the mesangial cell surface, thus causing CD89 and TG2 molecules to remain in the renal tissue. Interestingly, there seems to be a stronger negative correlation between proteinuria and urinary CD89 levels in comparison to TG2 levels, thus suggesting that CD89 might decrease

CD62L (L-selectin) and CD11b are also found to be upregulated in IgAN patients and are considered to be involved in IgAV pathogenesis. CD62L, is an adhesion molecule observed on the neutrophil surface that mediates the initial adhesion of neutrophils to the endothelium and could consequently be important in the early development of IgAV. CD11b is a predominant β2 integrin, also expressed on neutrophils. High CD11b and IgA levels possibly promote vascular damage through

Regarding pro-inflammatory cytokines, IgAV patients with or without nephritis present high serum concentrations of IL-1b, IL-6 and IL-8 compared with normal controls, with the increase in IL-6 and IL-8 levels being very significant in individuals with renal involvement. Urine IL-6, IL-8 and IL-10 concentrations appear to be more elevated in IgAV-N patients, in the same way as in patients with IgAN [53, 54]. These cytokines possibly play a role in mesangial cell activation, proliferation, crescent formation and glomerulosclerosis. Additionally, increase in IL-6 blood concentration seems to be an index of the acute phase of IgAV [47, 48]. Tumor necrosis factor (TNF) blood levels, that have also been associated with the development of interstitial fibrosis and tubular atrophy regardless of renal function, are higher in IgAV patients who present with nephritis [47]. Furthermore, several other inflammatory parameters, including C-reactive protein (CRP), Serum Amyloid A (SAA) and Neutrophil-Lymphocyte ratio (NLR), also seem to be upregulated in IgAV patients in comparison

induction of antibody-dependent cellular toxicity (ADCC) [52].

**23. Cytokines and other inflammatory factors**

*Glomerulonephritis and Nephrotic Syndrome*

develop chronic renal failure [37–40].

renal function [44–46].

patients as well [47, 48].

**21. Biomarkers in IgAV-N**

is based on conventional clinical factors [48].

formation merely reflect active inflammation, and their predictive value has been doubted in recent studies, which showed that patients on higher grades may experience spontaneous remission, while those with low grade histologic lesions may

The Oxford classification system, available since 2009, has been designed to estimate histology in IgAN, and it was based initially on four morphologic features: mesangial hypercellularity (M), endocapillary proliferation (E), segmental glomerulosclerosis (S) and tubular atrophy/interstitial fibrosis (T), which formed the MEST score [41–43]. More recently, the system was revised to MEST-C score, including the present of crescents, as crescent score (C) [44]. Although patients with IgAV-N were not included in the validation cohort, and therefore, the classification system cannot officially be recommend for patients with this condition, there have been few recent attempts to apply Oxford classification in IgAV-N. The presence of endocapillary proliferation and tubulointerstitial fibrosis were the main histologic findings associated with worse outcome of

Renal biopsy is essential for diagnosing IgAV-N, probably guide treatment and predict outcome, but, the procedure cannot be used repeatedly during follow up of the patients. The use of biomarkers is again mandatory to estimate disease outcome. IgAV-N share the same pathogenic pathway with IgAN, mediated by aberrant O-linked glycosylation of IgA1 hinge region, they are considered similar diseases that share common pathophysiologic mechanisms. Based on this fact, researchers tried to evaluate the utility of IgAN biomarkers in the assessment of the clinical course of IgAV-N. It was thus found that several of them could be used in IgAV-N

Since IgA deposition in various tissues is an important parameter of the disease pathophysiology, several studies have tried to examine immunoglobin production in IgAV patients. It has been found that IgA and IgE serum concentrations are higher in individuals with IgAV compared to normal controls, although it has not been proven that they can be useful in distinguishing patients with and without nephritis [47]. Moreover, serum Gd-IgA1 and IgA-IgG complexes, as well as urine IgA and IgA-IgG complexes are potential biomarkers for IgAV-N. More specifically, elevated levels of Gd-IgA1 in the blood of IgAV patients have been correlated with the presence of nephritis [47]. It has been proposed that recognition of the under galactosylated IgA1 hinge region by IgA or IgG antibodies induces the production of circulating immune complexes [47, 48]. Indeed, high concentrations of IgA-IgG complexes have been found in the serum of all IgAV-N patients, while in urine, the levels of these complexes are increased only in patients who have developed nephritis [47, 48]. It seems though that deterioration of renal function is not associated with the serum levels of Gd-IgA1 and IgA-IgG complexes. Recently, a French multicenter prospective study showed that urinary IgA concentration can be used as an additional index in order to improve patient risk stratification for poor outcome at disease onset. This is an important finding, since only a small percentage of IgAV patients finally develop severe deterioration of renal function and can benefit from intensive care, monitoring and follow-up and for the time IgAV outcome assessment

**21.1 Serum and urine immunoglobins and immune complexes**

**24**

#### **22. Cluster of differentiation (CD) antigens**

Concerning CD antigens that could be used as biomarkers, CD89 has been found to be useful in the assessment of IgAV. CD89 is the human myeloid specific IgA Fc receptor. It is expressed on neutrophils, eosinophils, monocytes/macrophages, dendritic cells and Kupffer cells [49, 50]. In IgAN patients, cleavage of the CD89 extracellular domain and release of IgA-soluble CD89 (IgA-sCD89) complexes is caused by the binding of IgA to CD89. Therefore, high levels of circulating IgAsCD89 complexes are observed in these patients. The complexes are trapped in the mesangium by the transferin receptor. Their deposition, as well as mesangial activation, is facilitated by transglutaminase 2 (TG2) [48, 51]. IgAV patients demonstrate decreased expression of CD89 at their monocyte and granulocyte cell surface. This finding is combined with increased blood concentration of IgA-sCD89 complexes. Urinary levels of these complexes are more elevated in individuals who develop nephritis [47, 48]. Furthermore, according to the findings of a 2016 multicenter study, urinary CD89 and TG2 concentrations are significantly lower in patients with active IgA vasculitis with nephritis (IgAV-N) compared to individuals whose disease has gone into complete or partial remission. More specifically, urinary CD89 and TG2 levels were found to be positively correlated with each other and negatively correlated with the level of proteinuria. It has been proposed that this decrease is consistent with the reduction in CD89 and TG2 urinary excretion as a result of the mononuclear-cell mediated inflammatory reaction that is induced by IgA-sCD89 deposition in the kidney. During this active phase, large multimolecular complexes containing CD89, TG2, CD71 and IgA1 are stabilized on the mesangial cell surface, thus causing CD89 and TG2 molecules to remain in the renal tissue. Interestingly, there seems to be a stronger negative correlation between proteinuria and urinary CD89 levels in comparison to TG2 levels, thus suggesting that CD89 might decrease earlier in the urine of patients with IgAV-N [51].

CD62L (L-selectin) and CD11b are also found to be upregulated in IgAN patients and are considered to be involved in IgAV pathogenesis. CD62L, is an adhesion molecule observed on the neutrophil surface that mediates the initial adhesion of neutrophils to the endothelium and could consequently be important in the early development of IgAV. CD11b is a predominant β2 integrin, also expressed on neutrophils. High CD11b and IgA levels possibly promote vascular damage through induction of antibody-dependent cellular toxicity (ADCC) [52].

### **23. Cytokines and other inflammatory factors**

Regarding pro-inflammatory cytokines, IgAV patients with or without nephritis present high serum concentrations of IL-1b, IL-6 and IL-8 compared with normal controls, with the increase in IL-6 and IL-8 levels being very significant in individuals with renal involvement. Urine IL-6, IL-8 and IL-10 concentrations appear to be more elevated in IgAV-N patients, in the same way as in patients with IgAN [53, 54]. These cytokines possibly play a role in mesangial cell activation, proliferation, crescent formation and glomerulosclerosis. Additionally, increase in IL-6 blood concentration seems to be an index of the acute phase of IgAV [47, 48]. Tumor necrosis factor (TNF) blood levels, that have also been associated with the development of interstitial fibrosis and tubular atrophy regardless of renal function, are higher in IgAV patients who present with nephritis [47]. Furthermore, several other inflammatory parameters, including C-reactive protein (CRP), Serum Amyloid A (SAA) and Neutrophil-Lymphocyte ratio (NLR), also seem to be upregulated in IgAV patients in comparison

to healthy individuals [55]. Of all these inflammatory indexes, NLR seems to present the strongest diagnostic value concerning the development of extracutaneal manifestations in adult IgAV (gastrointestinal and/or renal). The severity of the systemic involvement has been found to be associated with high NLR before treatment [56]. There is also a possible connection between high SAA levels also has a possible connection with the presence of gastrointestinal manifestations [52].

#### **24. Neutrophil gelatinase-associated lipocalin (NGAL)**

NGAL protein, a member of the lipocalin superfamily initially found in activated neutrophils, is produced in various cell types including renal tubules. It is a factor promoting kidney cellular proliferation and differentiation that is significantly upregulated in response to epithelial injury, thus serving as an index of kidney damage [47, 57]. It can possibly predict the appearance of acute renal impairment and the acute deterioration of unstable nephropathies. Furthermore, it may also be implicated in the pathophysiology of some chronic kidney disease (CKD) conditions, such as polycystic kidney disease and glomerulonephritis, while its levels are directly associated with the degree of renal damage [25]. In IgAV, NGAL concentrations seem to be high in both patients with and without nephritis, while its levels in urine, found more elevated in patients with nephritis, are useful in distinguishing them from individuals without kidney impairment [47, 48].

#### **25. Soluble transferin receptor (sTfR)**

sTfR consists of a single polypeptide chain and has been found to be upregulated in IgAV-N and IgAN patients, perhaps as a result of IgA1 polymer-mediated induction. Its overexpression is thought to be associated with the disease severity. Normally, it cannot cross the glomerular membrane because of its molecular size. However, when non-selective glomerular proteinuria is present, it is possible that the molecule can passively cross the membrane and then be detected in the urine. Interestingly, it has been found that in IgAV-N and IgAN patients the sTfR/creatinine ratio is higher than the ratio measured in healthy individuals or patients with other glomerulopathies. Therefore, it can possibly be used as a non-invasive tool to distinguish those two diseases from other pathologies that cause proteinuria. It has also been proposed that sTfR can additionally be further evaluated as a potential prognostic and activity marker for IgAV-N and IgAN [58].

**27**

**Author details**

Polyvios Arseniou1

Thessaloniki, Greece

, Stamatia Stai1

\*Address all correspondence to: mstangou@auth.gr

provided the original work is properly cited.

1 School of Medicine, Aristotle University of Thessaloniki, Greece

2 Department of Nephrology, Hippokration Hospital, Aristotle University of

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and Maria Stangou1,2\*

*Biomarkers in Renal Vasculitis*

*DOI: http://dx.doi.org/10.5772/intechopen.86489*

*Biomarkers in Renal Vasculitis DOI: http://dx.doi.org/10.5772/intechopen.86489*

*Glomerulonephritis and Nephrotic Syndrome*

to healthy individuals [55]. Of all these inflammatory indexes, NLR seems to present the strongest diagnostic value concerning the development of extracutaneal manifestations in adult IgAV (gastrointestinal and/or renal). The severity of the systemic involvement has been found to be associated with high NLR before treatment [56]. There is also a possible connection between high SAA levels also has a possible con-

NGAL protein, a member of the lipocalin superfamily initially found in activated neutrophils, is produced in various cell types including renal tubules. It is a factor promoting kidney cellular proliferation and differentiation that is significantly upregulated in response to epithelial injury, thus serving as an index of kidney damage [47, 57]. It can possibly predict the appearance of acute renal impairment and the acute deterioration of unstable nephropathies. Furthermore, it may also be implicated in the pathophysiology of some chronic kidney disease (CKD) conditions, such as polycystic kidney disease and glomerulonephritis, while its levels are directly associated with the degree of renal damage [25]. In IgAV, NGAL concentrations seem to be high in both patients with and without nephritis, while its levels in urine, found more elevated in patients with nephritis, are useful in

distinguishing them from individuals without kidney impairment [47, 48].

sTfR consists of a single polypeptide chain and has been found to be upregulated in IgAV-N and IgAN patients, perhaps as a result of IgA1 polymer-mediated induction. Its overexpression is thought to be associated with the disease severity. Normally, it cannot cross the glomerular membrane because of its molecular size. However, when non-selective glomerular proteinuria is present, it is possible that the molecule can passively cross the membrane and then be detected in the urine. Interestingly, it has been found that in IgAV-N and IgAN patients the sTfR/creatinine ratio is higher than the ratio measured in healthy individuals or patients with other glomerulopathies. Therefore, it can possibly be used as a non-invasive tool to distinguish those two diseases from other pathologies that cause proteinuria. It has also been proposed that sTfR can additionally be further evaluated as a potential

**25. Soluble transferin receptor (sTfR)**

prognostic and activity marker for IgAV-N and IgAN [58].

nection with the presence of gastrointestinal manifestations [52].

**24. Neutrophil gelatinase-associated lipocalin (NGAL)**

**26**

### **Author details**

Polyvios Arseniou1 , Stamatia Stai1 and Maria Stangou1,2\*

1 School of Medicine, Aristotle University of Thessaloniki, Greece

2 Department of Nephrology, Hippokration Hospital, Aristotle University of Thessaloniki, Greece

\*Address all correspondence to: mstangou@auth.gr

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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[20] Chen A, Lee K, Guan T, He J, Schlondorff D. Role of CD8<sup>+</sup>

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[21] Brunini F, Page T, Gallieni M, Pusey C. The role of monocytes in ANCAassociated vasculitides. Autoimmunity Reviews. 2016;**15**(11):1046-1053. DOI:

T cells

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[31] Stangou M, Bantis C, Skoularopoulou M, Korelidou L, Kouloukouriotou D, Scina M, et al. Th1, Th2 and Treg/T17 cytokines in two types of proliferative glomerulonephritis. Indian Journal Nephrology. 2016;**26**(3):159-166

[29] O'Reilly V, Wong L, Kennedy C, Elliot L, O'Meachair S, Coughlan A, et al. Urinary soluble CD163 in active renal vasculitis. Journal of the American Society of Nephrology.

[30] Stangou M, Papagianni A, Bantis C, Liakou H, Pliakos K, Giamalis P, et al. Detection of multiple cytokines in the urine of patients with focal necrotising glomerulonephritis may predict short and long term outcome of renal function. Cytokine.

M. Circulating neutrophil gelatinaseassociated lipocalin: A useful biomarker for assessing disease activity of ANCAassociated vasculitis. Rheumatology.

[26] Monach P, Kümpers P, Lukasz A, Tomasson G, Specks U, Stone J, et al. Circulating angiopoietin-2 as a biomarker in ANCA-associated vasculitis. PLoS ONE. 2012;**7**(1):e30197. DOI: 10.1371/journal.pone.0030197

[27] Monach P, Warner R, Tomasson G, Specks U, Stone J, Ding L, et al. Serum proteins reflecting inflammation, injury and repair as biomarkers of disease activity in ANCA-associated vasculitis. Annals of the Rheumatic Diseases.

[28] Lieberthal J, Cuthbertson D, Carette S, Hoffman G, Khalidi N, Koening C, et al. Urinary biomarkers in relapsing antineutrophil cytoplasmic antibodyassociated vasculitis. The Journal of Rheumatology. 2013;**40**(5):674-683.

10.1007/s10157-013-0861-1

10.1016/j.kint.2018.01.013

ndt/gfz043

*Biomarkers in Renal Vasculitis DOI: http://dx.doi.org/10.5772/intechopen.86489*

Rheumatology Reports. 2013;**15**(10):363. DOI: 10.1007/s11926-013-0363-x

[18] Suzuki K, Suzuki K, Nagao T, Nakayama T. Proposal of anti-moesin as a novel biomarker for ANCA-associated vasculitis. Clinical and Experimental Nephrology. 2013;**17**(5):638-641. DOI: 10.1007/s10157-013-0861-1

[19] Kraaij T, Kamerling S, van Dam L, Bakker J, Bajema I, Page T, et al. Excessive neutrophil extracellular trap formation in ANCA-associated vasculitis is independent of ANCA. Kidney International. 2018;**94**(1):139-149. DOI: 10.1016/j.kint.2018.01.013

[20] Chen A, Lee K, Guan T, He J, Schlondorff D. Role of CD8<sup>+</sup> T cells in crescentic glomerulonephritis. Nephrology, Dialysis, Transplantation. 16 Mar 2019. pii: gfz043. DOI: 10.1093/ ndt/gfz043

[21] Brunini F, Page T, Gallieni M, Pusey C. The role of monocytes in ANCAassociated vasculitides. Autoimmunity Reviews. 2016;**15**(11):1046-1053. DOI: 10.1016/j.autrev.2016.07.031

[22] Dick J, Gan P, Ford S, Odobasic D, Alikhan M, Loosen S, et al. C5a receptor 1 promotes autoimmunity, neutrophil dysfunction and injury in experimental anti-myeloperoxidase glomerulonephritis. Kidney International. 2018;**93**(3):615-625

[23] Liu S, Li N, Zhu Q, Zhu B, Wu T, Wang G, et al. Increased serum MCP-1 levels in systemic vasculitis patients with renal involvement. Journal of Interferon and Cytokine Research. 2018;**38**(9):406-412

[24] Pepper R, Hamour S, Chavele K, Todd S, Rasmussen N, Flint S, et al. Leukocyte and serum S100A8/ S100A9 expression reflects disease activity in ANCA-associated vasculitis and glomerulonephritis. Kidney International. 2013, 2013;**83**(6):1150-1158

[25] Chen M, Wang F, Zhao M. Circulating neutrophil gelatinaseassociated lipocalin: A useful biomarker for assessing disease activity of ANCAassociated vasculitis. Rheumatology. 2009;**48**(4):355-358

[26] Monach P, Kümpers P, Lukasz A, Tomasson G, Specks U, Stone J, et al. Circulating angiopoietin-2 as a biomarker in ANCA-associated vasculitis. PLoS ONE. 2012;**7**(1):e30197. DOI: 10.1371/journal.pone.0030197

[27] Monach P, Warner R, Tomasson G, Specks U, Stone J, Ding L, et al. Serum proteins reflecting inflammation, injury and repair as biomarkers of disease activity in ANCA-associated vasculitis. Annals of the Rheumatic Diseases. 2013;**72**(8):1342-1350

[28] Lieberthal J, Cuthbertson D, Carette S, Hoffman G, Khalidi N, Koening C, et al. Urinary biomarkers in relapsing antineutrophil cytoplasmic antibodyassociated vasculitis. The Journal of Rheumatology. 2013;**40**(5):674-683. DOI: 10.3899/jrheum.120879

[29] O'Reilly V, Wong L, Kennedy C, Elliot L, O'Meachair S, Coughlan A, et al. Urinary soluble CD163 in active renal vasculitis. Journal of the American Society of Nephrology. 2016;**27**(9):2906-2916

[30] Stangou M, Papagianni A, Bantis C, Liakou H, Pliakos K, Giamalis P, et al. Detection of multiple cytokines in the urine of patients with focal necrotising glomerulonephritis may predict short and long term outcome of renal function. Cytokine. 2012;**57**(1):120-126

[31] Stangou M, Bantis C, Skoularopoulou M, Korelidou L, Kouloukouriotou D, Scina M, et al. Th1, Th2 and Treg/T17 cytokines in two types of proliferative glomerulonephritis. Indian Journal Nephrology. 2016;**26**(3):159-166

**28**

*Glomerulonephritis and Nephrotic Syndrome*

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[57] Bolignano D, Donato V, Coppolino G, Campo S, Buemi A, Lacquaniti A, et al. Neutrophil gelatinase-associated lipocalin (NGAL) as a marker of kidneydamage. American Journal of Kidney Diseases. 2008;**52**(3):595-605

[58] Delanghe SE, Speeckaert MM, Segers H, Desmet K, VandeWalle J, Laecke SV, et al. Soluble transferrin receptor in urine, a new biomarker for IgA nephropathy and Henoch-Schönleinpurpura nephritis. Clinical Biochemistry. 2013;**46**(7-8):591-597

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[52] Kuret T, Lakota K, Žigon P, Ogrič M, Sodin-Šemrl S, Čučnik S, et al. Insight into inflammatory cell and cytokine profiles in adult IgA vasculitis. Clin Rheumatology. 2019;**38**(2):331-338

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*Glomerulonephritis and Nephrotic Syndrome*

K. Immunoglobulin A nephropathy and immunoglobulin A vasculitis. Pediatric Clinics of North America. Predictors of outcome in Henoch-Schönlein nephritis in children and adults. American Journal of Kidney

[40] Soylemezoglu O, Ozkaya O, Ozen S, Bakkaloglu A, Dusunsel R, Peru H, et al. Henoch-Schönlein nephritis: A nationwide study. Nephron. Clinical

[41] Roberts ISD, Cook HT, Troyanov S, Alpers CE, Amore A, Barratt J, et al. The Oxford classification of IgA nephropathy: Pathology definitions, correlations, and reproducibility. Kidney International. 2009;**76**:546-556

[42] Cattran DC, Coppo R, Cook HT, Feehally J, Roberts ISD, Troyanov S, et al. The Oxford classification of IgA nephropathy: Rationale, clinicopathological correlations, and classification. Kidney International.

[43] Trimarchi H, Barratt J, Cattran DC, Cook HT, Coppo R, Haas M, et al. Oxford classification of IgA nephropathy 2016: An update from the IgA. Kidney International.

[44] Inagaki K, Kaihan AB, Hachiya A, Ozeki T, Ando M, Kato S, et al. Clinical impact of endocapillary proliferation according to the Oxford classification among adults with Henoch-Schönleinpurpura nephritis: A multicenter retrospective cohort study. BMC Nephrology. 2018;**19**(1):208. DOI:

2009;**76**:534-545

2017;**91**(5):1014-1021

10.1186/s12882-018-1009-z

2014;**27**(7):972-982

[45] Kim CH, Lim BJ, Bae YS, Kwon YE, Kim YL, Nam KH, et al. Using the Oxford classification of IgA nephropathy to predict long-term outcomes of Henoch-Schönlein purpura nephritis in adults. Modern Pathology.

[46] Nasri H. Oxford classification of IgA nephropathy is applicable

Diseases. 2006;**47**:993-1003

Practice. 2009;**112**:199-204

[33] Heineke MH, Ballering AV, Jamin A, Ben Mkaddem S, Monteiro RC, Van Egmond M. New insights in the pathogenesis of immunoglobulin A vasculitis (Henoch-Schönleinpurpura).

[32] Nicoara O, Twombley

2019;**66**(1):101-110

Autoimmunity Reviews. 2017;**16**(12):1246-1253

2017;**97**(10):1160-1166

[34] Hetland LE, Susrud KS, Lindahl KH, Bygum A. Henoch-SchönleinPurpura: A literature review. Acta Dermato-Venereologica.

[35] Ozen S, Pistorio A, Lusan SM, Bakkaloglu A, Herlin T, Brik R, et al. EULAR/PRINTO/PRES criteria for Henoch-Schonleinpurpura, childhood polyarteritisnodosa, childhood

Wegener granulomatosis and childhood Takayasu arteritis: Ankara 2008. Part I: Overall methodology and clinical characterisation. Annals of the Rheumatic Diseases. 2010;**69**:790-797

[36] Jelusic M, Sestan M, Cimaz R, Ozen S. Different histological classifications

for Henoch-Schönleinpurpura nephritis: Which one should be used? Pediatric Rheumatology Online Journal.

[37] Mao S, Xuan X, Sha Y, Zhao S, Zhu C, Zhang A, et al. Clinicopathological association of Henoch-Schoenleinpurpuranephritis and IgA nephropathy in children. International Journal of Clinical and Experimental Pathology. 2015;**8**(3):2334-2342

[38] Ronkainen J, Nuutinen M, Koskimies O. The adult kidney 24 years after childhood Henoch-Schonleinpurpura: A retrospective cohort study. Lancet. 2002;**360**:666-670

[39] Coppo R, Andrulli S, Amore A, Gianoglio B, Conti G, Peruzzi L, et al.

2019;**17**(1):10

**30**

to predict long-term outcomes of Henoch-Schönlein purpura nephritis. Iranian Journal of Allergy, Asthma, and Immunology. 2014;**13**(6):456-458

[47] Pillebout E, Jamin A, Ayari H, Housset P, Pierre M, Sauvaget V, et al. Biomarkers of IgA vasculitis nephritis in children. PLoS ONE. 2017;**12**(11):e0188718. DOI: 10.1371/ journal.pone.0188718. eCollection 2017

[48] Berthelot L, Jamin A, Viglietti D, Chemouny JM, Ayari H, Pierre M, et al. Value of biomarkers for predicting immunoglobulin A vasculitis nephritis outcome in an adult prospective cohort. Nephrology, Dialysis, Transplantation. 2018;**33**(9):1579-1590

[49] van de Winkel JG. Fc receptors: Role in biology and antibody therapy. Immunology Letters. 2010;**128**(1):4-5

[50] Monteiro RC, Van De Winkel JG. IgA Fc receptors. Annual Review of Immunology. 2003;**21**:177-204

[51] Moresco RN, Speeckaert MM, Zmonarski SC, Krajewska M, Komuda-Leszek E, Perkowska-Ptasinska A, et al. Urinary myeloid IgA Fc alpha receptor (CD89) and transglutaminase-2 as new biomarkers for active IgA nephropathy and Henoch-Schönleinpurpura nephritis. BBA Clinical. 2016;**5**:79-84

[52] Kuret T, Lakota K, Žigon P, Ogrič M, Sodin-Šemrl S, Čučnik S, et al. Insight into inflammatory cell and cytokine profiles in adult IgA vasculitis. Clin Rheumatology. 2019;**38**(2):331-338

[53] Stangou M, Papagianni A, Bantis C, Moisiadis D, Kasimatis S, Spartalis M, et al. Up-regulation of urinary markers predict outcome in IgA nephropathy but their predictive value is influenced by treatment with steroids and azathioprine. Clinical Nephrology. 2013;**80**(3):203-210

[54] Stangou M, Alexopoulos E, Papagianni A, Pantzaki A, Bantis C, Dovas S, et al. Urinary levels of epidermal growth factor, interleukin-6 and monocyte chemoattractant protein-1 may act as predictor markers of renal function outcome in immunoglobulin A nephropathy. Nephrology (Carlton). 2009;**14**(6):613-620

[55] Purevdorj N, Mu Y, Gu Y, Zheng F, Wang R, Yu J, et al. Clinical significance of the serum biomarker index detection in children with Henoch-Schonleinpurpura. Clinical Biochemistry. 2018;**52**:167-170

[56] Nagy GR, Kemény L, Bata-Csörgő Z. Neutrophil-to-lymphocyte ratio: A biomarker for predicting systemic involvement in adult IgA vasculitis patients. Journal of the European Academy of Dermatology and Venereology. 2017;**31**(6):1033-1037

[57] Bolignano D, Donato V, Coppolino G, Campo S, Buemi A, Lacquaniti A, et al. Neutrophil gelatinase-associated lipocalin (NGAL) as a marker of kidneydamage. American Journal of Kidney Diseases. 2008;**52**(3):595-605

[58] Delanghe SE, Speeckaert MM, Segers H, Desmet K, VandeWalle J, Laecke SV, et al. Soluble transferrin receptor in urine, a new biomarker for IgA nephropathy and Henoch-Schönleinpurpura nephritis. Clinical Biochemistry. 2013;**46**(7-8):591-597

**33**

Section 2

Glomerulonephritis in

Childhood

### Section 2
