**3. CLU in Alzheimer's disease: clinical findings**

#### **3.1. CLU polymorphisms in LOAD**

mCLU, nCLU, and to a lesser extent icCLU isoforms indicating that neurons are also capable of generating de novo CLU. Though the exact physiological functions of CLU remain a mystery, the nearly ubiquitous nature of CLU indicates the significance of this protein in

Though the gene promoter of CLU is highly conserved across species, the transcriptional regulation of CLU is complex as the predominant CLU transcriptional regulators appear to differ between tissue and cell type. However, despite the controversy in the literature, it is generally agreed that CLU is primarily upregulated by cellular injury, cytotoxic insult, and various stress stimuli [52–54]. For instance, Loisen and colleagues demonstrated that the CLU gene promoter contains an MG132 responsive region and a heat-shock element (HSE) indi‐ cating that proteasomal stress directly influences CLU transcription [52]. Another study demonstrated that the CLU gene promoter contains both HSEs and an activator protein-1 (AP-1) response element indicating direct transcriptional regulation by stimuli derived from cellular proliferation and differentiation [54]. In addition to these data, alternative stressrelated transcription factor response elements have been identified in the CLU gene promoter including a cAMP response element (CRE), an AP-2 response element, a specificity protein-1 (SP1) response element, and a glucocorticoid response element (GRE) [33, 53]. It has also been demonstrated that apoptotic stimuli modulates CLU transcription, specifically in cancer. An early study from Cervellera et al. identified a MYB binding site in the 5' flanking region of CLU and that B-MYB, a MYB family member that regulates cellular proliferation and apop‐ tosis, directly bound to and transactivated the CLU gene [55]. CLU transcription is also regulated by several different growth factors including nerve growth factor (NGF) and transforming growth factor beta (TGFβ) [56–58]. For instance, it has been demonstrated that TGFβ induces the upregulation of CLU gene expression by stimulating the interaction between the CLU gene promoter and AP-1 [57]. An extension of these studies demonstrated that TGFβ deficiency resulted in the repression of CLU gene expression via interaction between c-Fos and the CLU gene promoter; an interaction that was abrogated upon cellular stimulation

CLU is regulated by several types of posttranslational modification (PTM), the most predom‐ inant type being N-linked glycosylation. As previously indicated, mCLU is N-glycosylated at six different asparagine residues (N86, N103, N145, N291, N354, and N374) during ER-Golgi processing: a modification that comprises approximately 20–25% of the total mass of mCLU [59]. While glycosylation status was originally thought to have little to no impact on CLU function [40, 60], a recent study demonstrated that the chaperone activity of mCLU is depend‐ ent upon mCLU glycosylation [61]. This study also demonstrated that the glycosylation of nCLU did not result in chaperone activity indicating that glycosylation-mediated effects are specific to the mCLU isoform. It has also been established that complete deglycosylation of mCLU results in a 70–90% decrease in mCLU chaperone activity and a significant decrease in

cellular homeostasis.

316 Update on Dementia

with TGFβ [58].

**2.4. CLU: posttranslational modification**

**2.3. CLU: transcriptional regulation**

Since the initial determination of CLU SNP-associated AD risk by Harold et al. and Lambert et al. [26, 27], there have been approximately 40 independent follow-up meta-analyses and case-control studies that have examined the association between CLU SNPs and AD risk (**Table 1**). These reports were located through a PubMed search focused on topics pertaining to CLU SNPs in AD. Resulting articles were reviewed and those studies which provided a listing of the CLU SNP(s) studied, population demographics, and a thorough description of cognitive assessment and statistical analysis were included in **Table 1**. Though conflicting evidence exists, the majority of the studies indicate that genetic variation in CLU increases the risk of developing AD and that this association is independent of APOE ε4 status. There are approximately 355 identified SNPs in the CLU gene [67]; however, it appears that the primary risk-conferring CLU SNP is rs11136000. Of the 33 studies summarized in **Table 1**, 25 studies either include or exclusively focus on the impact of the rs11136000 SNP on AD risk; however, the results are inconsistent. Thirteen studies conclude that possession of rs11136000 does confer increased AD risk [26, 27, 68–77], while ten studies conclude no significant association between rs11136000 and AD [78–85]. Moreover, two studies conclude that possession of the rs11136000 SNP reduces risk of AD development [86, 87]. A possible explanation for these discrepancies may be found by examining the population ethnicities. Of the 13 studies that conclude rs11136000 confers AD risk, 11 studies are performed in a predominantly or exclu‐ sively western European or American Caucasian population. Alternatively, nine of the 10 studies that conclude no significant association (NSA) between rs11136000 and AD were performed in Asian, eastern European and Russian, Middle Eastern, or Hispanic populations indicating that the risk associated with the rs11136000 SNP may vary based on population ethnicity. Contrary to these data, two separate studies performed in exclusively German and American Caucasian populations found NSA between rs11136000 and AD risk. Moreover, the notion that rs11136000 does not confer AD risk in Asian populations is contradicted by two independent studies that indicate rs11136000-mediated AD risk in exclusively Chinese populations. As all the presented studies performed in Asian populations are adjusted for age, gender, and APOE status, and are comprised of numerically similar sample sizes, it is difficult to identify the exact reason underlying these discrepancies. One observation is that some studies have divided study populations into much smaller groups based upon the specific nucleotide substitution located at the rs11136000 SNP site (i.e. C,T,A substitution), while others have examined only rs11136000 carriers vs. non-carriers. The failure to stratify study popula‐ tions based on the rs11136000 allele/genotype would have a significant impact on study outcome as the C allele of rs11136000 is considered the risk-conferring allele, while the A allele and T allele are considered normal and neuroprotective, respectively (i.e. C = risk allele, A = normal, and T = protective). Specifically, studies have indicated that the C allele confers a 1.16 fold increased chance of developing LOAD and that 36% of Caucasians carry two copies of this AD-risk variant [26, 27]. Moreover, the C allele is associated with faster cognitive decline in preclinical AD [66] and lower memory scores in healthy elderly controls and elderly AD patients [67]. Young healthy carriers of the C allele exhibit neural hyperactivation in memoryassociated brain regions during working memory tasks [73], neural inefficiency in memoryrelated prefrontal and limbic areas during working memory [88], and reduced coupling between hippocampus and prefrontal cortex during memory processing [89]. Structurally, possession of the C allele is associated with diminished white matter integrity in several brain regions [90] and increased longitudinal ventricular expansion in elderly patients independent of APOE ε4 and dementia status [91]. Taken together, these data indicate that the rs11136000 SNP is significantly associated with the development of AD in predominantly Caucasian populations and that the rs11136000 AD-associated risk may be initiated several decades prior to the onset of AD.

listing of the CLU SNP(s) studied, population demographics, and a thorough description of cognitive assessment and statistical analysis were included in **Table 1**. Though conflicting evidence exists, the majority of the studies indicate that genetic variation in CLU increases the risk of developing AD and that this association is independent of APOE ε4 status. There are approximately 355 identified SNPs in the CLU gene [67]; however, it appears that the primary risk-conferring CLU SNP is rs11136000. Of the 33 studies summarized in **Table 1**, 25 studies either include or exclusively focus on the impact of the rs11136000 SNP on AD risk; however, the results are inconsistent. Thirteen studies conclude that possession of rs11136000 does confer increased AD risk [26, 27, 68–77], while ten studies conclude no significant association between rs11136000 and AD [78–85]. Moreover, two studies conclude that possession of the rs11136000 SNP reduces risk of AD development [86, 87]. A possible explanation for these discrepancies may be found by examining the population ethnicities. Of the 13 studies that conclude rs11136000 confers AD risk, 11 studies are performed in a predominantly or exclu‐ sively western European or American Caucasian population. Alternatively, nine of the 10 studies that conclude no significant association (NSA) between rs11136000 and AD were performed in Asian, eastern European and Russian, Middle Eastern, or Hispanic populations indicating that the risk associated with the rs11136000 SNP may vary based on population ethnicity. Contrary to these data, two separate studies performed in exclusively German and American Caucasian populations found NSA between rs11136000 and AD risk. Moreover, the notion that rs11136000 does not confer AD risk in Asian populations is contradicted by two independent studies that indicate rs11136000-mediated AD risk in exclusively Chinese populations. As all the presented studies performed in Asian populations are adjusted for age, gender, and APOE status, and are comprised of numerically similar sample sizes, it is difficult to identify the exact reason underlying these discrepancies. One observation is that some studies have divided study populations into much smaller groups based upon the specific nucleotide substitution located at the rs11136000 SNP site (i.e. C,T,A substitution), while others have examined only rs11136000 carriers vs. non-carriers. The failure to stratify study popula‐ tions based on the rs11136000 allele/genotype would have a significant impact on study outcome as the C allele of rs11136000 is considered the risk-conferring allele, while the A allele and T allele are considered normal and neuroprotective, respectively (i.e. C = risk allele, A = normal, and T = protective). Specifically, studies have indicated that the C allele confers a 1.16 fold increased chance of developing LOAD and that 36% of Caucasians carry two copies of this AD-risk variant [26, 27]. Moreover, the C allele is associated with faster cognitive decline in preclinical AD [66] and lower memory scores in healthy elderly controls and elderly AD patients [67]. Young healthy carriers of the C allele exhibit neural hyperactivation in memoryassociated brain regions during working memory tasks [73], neural inefficiency in memoryrelated prefrontal and limbic areas during working memory [88], and reduced coupling between hippocampus and prefrontal cortex during memory processing [89]. Structurally, possession of the C allele is associated with diminished white matter integrity in several brain regions [90] and increased longitudinal ventricular expansion in elderly patients independent of APOE ε4 and dementia status [91]. Taken together, these data indicate that the rs11136000 SNP is significantly associated with the development of AD in predominantly Caucasian

318 Update on Dementia

In addition to rs11136000, another CLU SNP, rs9331888, which was also identified by Lambert and colleagues in the original GWA studies, has also been repeatedly investigated as an AD risk SNP. Of the 33 studies presented in **Table 1**, seven clinical studies and two meta-analyses examined the association of rs9331888 with AD risk [27, 69, 81, 83, 84, 92–95]. However, similar to that of rs11136000, the results vary and appear to be dependent upon population ethnicity. For instance, two separate meta-analyses conclude that rs9331888 confers AD risk in Caucasian but not Asian populations [92, 95]. However, two separate case-control studies performed in exclusively Chinese populations both indicate that rs9331888 is significantly associated with AD risk [84, 94]. In addition to differing and/or small sample sizes, one possible confounding factor could be sex of the study population. As sex modulates an individual's risk for LOAD, it is likely that stratification of study populations by sex will have a significant impact on the study results.



#### Clusterin (APOJ) in Alzheimer's Disease: An Old Molecule with a New Role http://dx.doi.org/10.5772/64233 321


**CLU gene variant Study and**

320 Update on Dementia

*rs11136000* Seshadri et al.

*rs7982 rs7012010 rs11136000* **year of publication** 

(2010)

Jun et al. (2010)

al. (2010)

*rs11136000* Corneveaux et

**Study design and subjects** 

Three-stage GWA study in a white population: *Stage 1 population:* Dementia -free subjects at start: *n* = 8935, AD cases: *n* = 2033, dementia-free control cases: *n* = 14,642

*Stage 2 population:* AD cases: *n* = 2032, control cases:

*Stage 3 population:* AD cases: *n* = 3333, control cases:

*Independent case-control replication population:* Ethnicity—Spanish, AD

*n* = 1140, age = 78.8 ± 7.9, 69.9% female; control cases: *n* = 1209, age = 49.9 ± 9.2, 58.2% female

Meta-analysis in nine European white cohorts and five non-European cohorts (African American, Israeli-Arab, and Caribbean

GWA study of a European

*n* = 1019, 652 females,

Hispanic): *AD cases: n* = 7070 *Control cases: n* = 8169

population *AD cases:*

367 males *Control cases:*

*n* = 5328

*n* = 6995

cases:

**Diagnoses criteria Major findings** 

Han Chinese population.


polymorphisms examined demonstrated a significant association with AD in only white

cohorts.


and examination and MMSE score > 28 Subjects with CHF, MI, T2DM, and AS were excluded from study

*Dementia diagnoses:* DSM-IV

Not provided - All CLU

*AD diagnoses:* Clinically diagnosable dementia at time of death and neuropathological confirmation of AD (Braak stage V or VI) upon autopsy

*AD diagnoses*: NINCDS-ADRDA criteria for definite, probable, or possible AD; AD pathology confirmed at

criteria

autopsy



**CLU gene variant Study and**

*rs11136000* Golenkina

*Rs7982 Rs572844 rs1532277 rs2279590 Rs9331888 rs10503814*

322 Update on Dementia

*rs881146 rs11136000 rs17057441 rs70120100*

*rs11136000* Ma et al.

**year of publication** 

Komatsu et al. (2011)

et al. (2010)

Lee et al. (2011)

(2011)

**Study design and subjects** 

Japanese population:

*n* = 180, 101 females, 79 males, age = 67.4±6.7

Cohort study in a Russian

*AD cases:* Early-onset *n* = 214, AOO = 56.9 ± 5.38

*n* = 320, AOO 72.2 ± 5.04

*n* = 343, age range = 35–85, age = 60.96 ± 7.94 Ural

*n* = 160, age range = 69–89, age = 73.87 ± 3.87 Siberian

*n* = 199, age range = 41–96, age = 61 ± 15.34

Nested case-control GWAS in a cohort of Caribbean Hispanic

Case-control study in Chinese Han population:

*n* = 127, 73 females, 54

age = 73.12 ± 8.58 *Control cases: n* = 143, 79 females, 64 males, age = 73.80 ± 6.30

Case-control study in

*AD cases:*

*Control cases: n* = 130, 67 females, 63 males, age = 64.4±6.7

population:

Late-onset—

*Control cases:* Moscow region:

region:

region:

subjects: *AD cases*: *n* = 549, age of onset = 79.98 ± 8.0 *Control cases*: *n* = 544

*AD cases:*

males,

**Diagnoses criteria Major findings** 




with LOAD rs11136000 and other SNPs were not significantly associated with LOAD in a Caribbean Hispanic population.


*AD diagnoses:* NINCDS-ADRDA criteria; subjects had no family history of AD *Control criteria:*

No history of dementia or other neuropsychiatric

*AD diagnoses:* NINCDS-ADRDA criteria, ICD-10 criteria, and DSM-IV criteria *Control criteria:* Cognitively intact individuals

*Dementia diagnoses:* Diagnoses established on

of all available information gathered from initial and follow-up studies *AD diagnoses:*

NINDS-ADRDA criteria

*AD diagnoses:* 2007 revised AD diagnoses criteria *Control criteria:*

No history of neurological disease and MMSE score >

the basis

29

disorders



**CLU gene variant Study and**

324 Update on Dementia

*rs9331888* Xing et al.

*rs11136000* Klimkowicz-

*18 CLU SNPS* Yu et al.

*rs11136000* Thambisetty et

**year of publication** 

(2012)

Mrowiec et al. (2012)

(2013)

al. (2013)

*rs11136000 AD cases:*

**Study design and subjects** 

Case-control study:

*n* = 104, AOO = ≥65, age = 80.20 ± 5.57, 63 females, 41

*n* = 104, age = 79.32 ± 5.37, 58 females, 46 males

*n* = 253, age = 73.9 ± 5.8, 173

*n* = 240, age = 73.8 ± 6.9, 138

Case-control study in Han Chinese population:

*n* = 796, AOO = ≥65, age = 74.3 ± 7.0, 396 females

*n* = 796, age = 73.9 ± 6.5, 388

Two-part longitudinal study from Baltimore Longitudinal Aging Study: *Study 1 population: n* = 88, age = 69, age range

Case-control study in a Polish population: *AD cases:*

*n* = 462 *Control cases: n* = 350

*AD cases:*

males *Control cases:*

females *Control cases:*

females

*AD cases:*

*Control cases:*

females

= 56–86

= 60–93

*Study 2 population: n* = 599, age = 67.5, age range

**Diagnoses criteria Major findings** 

southern Chinese population.


levels.




*Control criteria:* Cognitively normal individuals as indicated by CDR scale

*AD diagnoses:* NINCDS-ADRDA criteria for probable AD

*Control criteria:* Confirmed healthy by medical history, medical examination, and MMSE score > 28

*AD diagnoses:* NINCDS-ADRDA criteria for probable AD—no family

*Control criteria:* MMSE > 26, no family history of

no apparent neurological,

cerebrovascular disease

*AD diagnoses:* NINCDS-ADRDA criteria for probable AD. No family

history of AD

dementia,

history of neurodegenerative disorders or dementia *Control criteria:* Free of cognitive impairment as

indicated by

neurophysiological and medical exams

*Inclusion criteria:* No history of clinical stroke, head trauma, or CNS inflammation; Subject without cognitive impairment as indicated by NINCDS-ADRDA criteria

psychiatric, or



**Abbreviations**: Age of onset (AOO), behavioural pathology in Alzheimer's disease (BEHAVE-AD), the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), Clinical Dementia Rating (CDR), congestive heart failure (CHF), Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised (DSM-III-R), Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), functional magnetic resonance imaging (fMRI), genome-wide association (GWA), mini-mental state examination (MMSE), National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA), odds ratio (OR), type 2 diabetes mellitus (T2DM).

**Table 1.** CLU polymorphisms in AD (2009–2016).

#### **3.2. CLU as an AD biomarker**

**CLU gene variant Study and**

326 Update on Dementia

*rs11136000* Sohrabifar

*rs9331888* Toral-Rios

*rs9331888* Shuai et al.

*rs2279590* Zhang et al.

*rs9331888* Zhang et al.

**year of publication** 

et al. (2015)

et al. (2015)

(2015)

(2015)

(2015)

**Study design and subjects** 

Case-control study in an Iranian population:

Case-control study in a Mexican population:

Meta-analysis of 11 case-control studies: *Ethnicities:* Caucasian and Asian populations *AD cases: n* = 8766 *Control cases: n* = 11,366

Meta-analysis of 11 case-control studies: *Ethnicities:* Caucasian and Asian populations *AD cases: n* = 8605 *Control cases: n* = 12,050

Meta-analysis of 12 case-control studies: *Ethnicities:* Caucasian and Asian populations *AD cases: n* = 16,876 *Control cases: n* = 19,295

*AD cases: n* = 160 *Control cases: n* = 163

*AD cases: n* = 94, age > 60 *Control cases: n* = 100, age > 60 **Diagnoses criteria Major findings** 

Not provided - No significant

*AD diagnoses:* NINCDS-ADRDA criteria *Control criteria:* MMSE ≥ 24, no memory complaints,

no acute or severe chronic

*Study inclusion criteria:* (1) Study evaluated rs9331888 SNP and AD risk (2) Case-control design (3) Sufficient study population was provided

*Study inclusion criteria:* (1) Study evaluated rs2279590 SNP and AD risk (2) Case-control design (3) Study provided the number of rs2279590

(4) Study provided OR with

*Study inclusion criteria:* (1) Study evaluated rs9331888 SNP and AD risk (2) Case-control design (3) Study provided the number of SNP genotypes (4) Study provided OR with a 95% CI

genotypes

a 95% CI

illness

suggesting a possible association between the TT genotype and female Turkish subjects.

association between rs11136000 and AD in an Iranian population.





models.

In 1992, it was suggested that peripheral CLU (then referred to as SGP-2) expression may serve as a potential biomarker for predicting the onset and/or severity of neurodegenerative disorders such as LOAD [96]. Though this concept was proposed over 20 years ago, the possibility of CLU as an AD biomarker is only recently being examined. Since 2010, 10 different studies have been performed with the aim of determining the validity of CLU as an AD biomarker (**Table 2**). However, the conclusions of these studies are contradictory at best. Of the 10 studies presented in **Table 2**, six studies conclude that increased plasma CLU levels are associated with increased rate of cognitive decline [97], increased white matter atrophy [98], increased risk for AD [99], and were indicative of greater fibrillar Aβ burden [100]. However, contrary to these findings, four studies conclude that CLU levels are not significantly different between control subjects and subjects with MCI, AD, or dementia, suggesting that peripheral CLU is unreliable as an AD biomarker [101–105]. One primary difference between these studies is the fluid that was analyzed for CLU concentration. The six studies concluding that CLU would be a reliable biomarker utilize plasma samples for analysis, whereas the three of the four studies indicating no difference between control and AD subjects measure serum or platelets. Another key difference between these conflicting reports is the sample size. In three of the four studies concluding that CLU would not be a reliable AD biomarker, the sample size per group is less than 70 subjects, whereas most of the studies indicating the possibility of CLU as a peripheral biomarker contain several hundred subjects per group. Therefore, it is also possible that these differences are the result of inadequate sample size. Despite these discrep‐ ancies, these studies collectively suggest that at least plasma CLU could provide a predictive biomarker for determining the risk for AD.




**Study and year of publication** 

328 Update on Dementia

Schrijvers et al. (2011)

Thambisetty et al.

(2012)

Mukaetova-Ladinska et al. (2012)

**Fluid analyzed**  **Study design and subjects** 

Plasma Case-cohort study from

time

*AD cases:*

females *Control cases: n* = 43, age = 78 ± 6.8,

32 females

subjects, age = 70.5

Plasma Longitudinal cohort study:

Platelets Case-control study: *AD cases:*

Silajdzic et al. (2012)Plasma Quantitative ELISA

females *Control cases: n* = 26, age = 70.81 ± 1.98, 18 females

derived from the Rotterdam Scan Study:

*n* = 43, age = 78 ± 6.5, 32

139 cognitively intact

*n* =25, age = 78.08 ± 1.0, 10

assessment of plasma

Ijsselstijn et al. (2011)Serum Case-control study

*Ethnicity:* White European (UK, France, Italy, Finland, Poland, Greece) derived from the KLC-ART and AddNeuroMed cohort studies and the Baltimore Longitudinal Study of Aging

the Rotterdam Study in the Netherlands: *Subjects:* 60 individuals with prevalent AD at baseline, a sub-cohort of 926 subjects, and an additional 156 subjects diagnosed with AD throughout follow-up

**Diagnoses criteria Major findings** 

predictive of greater fibrillar Aβ burden.



severe AD. - The likelihood of prevalent AD increased with increasing plasma

CLU levels.

0.54).




patients.

*MCI diagnoses:* Subjective memory complaints, CDR scores of less than 1, and evidence of objective memory impairment using the CERAD criteria *Control criteria:* Subjects with no MCI and MMSE ≥

28

*Study outcome:* Prevalent AD

*AD diagnoses:* Severity of AD measured by the MMSE score, and the risk of developing AD during follow-up examinations

*AD diagnoses:* DSM-III R

*Control criteria:* MMSE

*Baseline criteria:* Free of clinical diagnosis of dementia at evaluation *MCI diagnoses:* Petersen

*Dementia diagnoses:* DSM III criteria

NINCDS-ADRDA criteria for probable AD *Control criteria:* Subjects with no cognitive and/or neurological problems

*AD diagnoses:* DSM-IIIR criteria and NINCDS-

*AD diagnoses:*

criteria

criteria

≥ 28


**Table 2.** CLU as an AD biomarker (2010–2016).
