**6. Glossary- the language of biomarker and proteomic research**

*Bias*- In statistics, bias is systematic favoritism present in data collection, analysis or reporting of quantitative research

*Biomarker*- or *biological marker*, is a molecular characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.

*Classifier*- in statistics is the formula or criteria for identifying a sub-population based on quantitative information on one or more measurements, traits or characteristics.

*Development pipeline*- represents the process from candidate discovery, through verification, validation and final pre-market approval.

*Diagnostic*- in the context of medicine is any test performed or criteria applied to aid to determine and/or identity a possible disease or disorder.

*Discovery*- in the context of biomarkers, describes the initial process of observation, identification and quantification of one or more biological molecules which may act as a classifier.

*Isoform*- describes the biological phenomenon of several different structural forms of the same protein which may arise by alternate gene splicing and single-nucleotide polymorphisms before messenger RNA translation and chemical modifications e.g. phosphorylation or glycosylation which occur post-translation of proteins.

*Multiplex*- in the context of protein assay is a method or platform which permits the simultaneously measururement of multiple analytes (dozens or more) in a single test.

Validation of Protein Biomarkers to Advance the Management of Autoimmune Disorders 155

Addona T.A. Abbatiello S.E., Schilling B., Skates S.J., Mani D.R., Bunk D.M., Spiegelman

Anderson N.L. The clinical plasma proteome: a survey of clinical assays for proteins in

Batstra M.R., Aanstoot H.J. & Herbrink P. Prediction and diagnosis of type 1 diabetes using

Bloemen K., Van Den Heuvel R., Govarts E., Hooyberghs J., Nelen V., Witters E., Desager K.

Bongartz T., Sutton A.J., Sweeting M.J., Buchan I., Matteson E.L. & Montori V. Anti-TNF

Borges C.R., Jarvis J.W., Oran P.E. & Nelson R.W. Population studies of Vitamin D Binding

Borges C.R., Jarvis J.W., Oran P.E., Rogers S.P. & Nelson R.W. Population studies of intact

Borges C.R., Rehder D.S., Jarvis J.W., Schaab M.R., Oran P.E. & Nelson R.W. Full-length

Bowes J.D., Potter C., Gibbons L.J., Hyrich K., Plant D., Morgan A.W., Wilson A.G., Isaacs

Brauer H.A., Lampe P.D., Yasui Y.Y., Hamajima N. & Stolowitz M.L. Biochips that

& Schoeters G. A new approach to study exhaled proteins as potential biomarkers

antibody therapy in rheumatoid arthritis and the risk of serious infections and malignancies: systematic review and meta-analysis of rare harmful effects in

Protein microheterogeneity by mass spectrometry lead to characterization of its genotype-dependent O-glycosylation patterns. *J. Proteome Res.*, 7(9), (2008), pp 4143-

vitamin D binding protein by affinity capture ESI-TOF-MS. *J. Biomol. Tech*., 19(3),

characterization of proteins in human populations. *Clin. Chem*., 56(2), (2010), pp

J.D.,Worthington J. & Barton A. Investigation of genetic variants within candidate genes of the TNFRSF1B signalling pathway on the response to anti-TNF agents in a UK cohort of rheumatoid arthritis patients. *Pharmacogenet. Genomics*, 19(4), (2009),

sequentially capture and focus antigens for immunoaffinity MALDI-TOF MS: a new tool for biomarker verification. *Proteomics*, 10(21), (2010), pp 3922-7. Cairns D.A., Barrett J.H., Billingham L.J., Stanley A.J., Xinarianos G., Field J.K., Johnson P.J., Selby P.J. & Banks R.E. Sample size determination in clinical proteomic profiling experiments using mass spectrometry for class comparison. *Proteomics*,

plasma and serum. *Clin. Chem.*, 56(2), (2010), pp 177-85.

for asthma. *Clin. Exp. Allergy*, 41(3), (2011), pp 346-56.

beta-cell autoantibodies. *Clin. Lab.*, 47(9-10), (2001), pp 497-507.

randomized controlled trials. *JAMA*, 295(19), (2006), pp 2275-85.

207.

53.

202-11.

pp 319-23.

9(1), (2009), pp 74-86.

(2008), pp 167-76.

C.H., Zimmerman L.J., Ham A.J., Keshishian H., Hall S.C., Allen S., Blackman R.K., Borchers C.H., Buck C., Cardasis H.L., Cusack M.P., Dodder N.G., Gibson B.W., Held J.M., Hiltke T., Jackson A., Johansen E.B., Kinsinger C.R., Li J., Mesri M., Neubert T.A., Niles R.K., Pulsipher T.C., Ransohoff D., Rodriguez H., Rudnick P.A., Smith D., Tabb D.L., Tegeler T.J., Variyath A.M., Vega-Montoto L.J., Wahlander A., Waldemarson S., Wang M., Whiteaker J.R., Zhao L., Anderson N.L., Fisher S.J., Liebler D.C., Paulovich A.G., Regnier F.E., Tempst P. & Carr S.A.. Multi-site assessment of the precision and reproducibility of multiple reaction monitoringbased measurements of proteins in plasma. *Nat. Biotechnol.*, 27, (2009), pp 633-641. Aebersold R. & Mann M. Mass spectrometry-based proteomics. *Nature*, 422, (2003), pp 198-

*Omics*- this suffix, often used in modern biological research, refers to the lofty aim of observing, identifying and quantifying the totality of a particular class of molecules i.e. genomics, proteomics.

*Orthogonal method*- describes the ideal of using alternate types of analyses to corroborate the original findings by independent means.

*Peptide-centric*- or *bottom-up,* proteomics is a common method used to identify proteins by proteolytic digestion of proteins prior to analysis by mass spectrometry.

*Protein-centric***-** or *top-down,* proteomics is a method of intact protein identification e.g. an ion trapping mass spectrometer used to store an isolated protein ion for mass measurement and tandem mass spectrometry analysis.

*Power analysis*- to calculate the number of samples required for a study to reach statistically sound conclusions.

*Predictive model*- in the context of medicine, is created or chosen to try to predict the probability of a clinical outcome by use of one or more *classifiers*.

*Prognostic*- is a clinical test which can forecast the likely course or outcome of an illness.

*Sensitivity*- measures the proportion of true positives which are correctly identified as such (e.g. the percentage of sick people who are correctly identified as having the condition).

*Specificity*- measures the proportion of true negatives which are correctly identified (e.g. the percentage of healthy people who are correctly identified as not having the condition).

*Throughput*- refers to the rate of analysis of samples by a particular method e.g. analysis of a single protein by Western blotting is relatively low throughput compared to ELISA.

*Validation*- later stage in the biomarker pipeline is defined as the documented act of demonstrating that putative biomarker classifiers will consistently lead to the expected results i.e establish *sensitivity* and *specificity* performance in large populations and begin to optimize the assay for commercial use.

*Verification*- intermediate phase in biomarker pipeline bridging *discovery* and *validation*, which typically reduces the number of candidates, confirms specific protein isoforms within a *classifier* and begins to assess the sensitivity in expanded populations.
