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Biomarkers, Genetic Association, and Genomic Studies

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Understanding Evidence-Based Rheumatology

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Abstract

Rheumatoid arthritis (RA) is a common autoimmune disorder which shows clinical heterogeneity. It has multiple treatment options, and there is individual variation in response to treatment. These features make RA an ideal condition to develop biomarkers for its preclinical detection, diagnosis, subtyping, prognostic stratification, and selection of most optimal treatment. While a number of markers have been assessed for their biomarker quality, currently no marker has the statistical properties of a biomarker to be considered as a good classifier. In this chapter, a general review of biomarkers is followed by a detailed discussion of biomarker candidates for various aspects of RA. It is unlikely that a single marker will ever be sufficiently powerful as a biomarker, but combinations of clinical, biochemical, genetic, epigenetic, proteomic, and metabolomic markers have the strongest potential to fulfill the requirements of biomarkers. Given the high heritability of RA and the progress in methodology of genome-wide association studies, genetic markers are the most promising group to be developed as biomarkers, in particular when epigenetic markers become more widely used. It is possible that in the near future, biomarkers with documented clinical utility will be available for use in clinical decision making and will most probably use multiple omics platforms.

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Abbreviations

ABCC3:

ATP-binding cassette, subfamily C member 3

ACPA:

Antibodies to citrullinated protein antigen

ACR:

American College of Rheumatology

ACYP1:

Acylphosphatase 1, erythrocyte

AFP:

Alpha-fetoprotein

AIF1:

Allograft inflammatory factor 1

ANA:

Antinuclear antibody

anti-CarP:

Anti-carbamylated protein

anti-CCP:

Anti-cyclic citrullinated protein

anti-TNF:

Anti-tumor necrosis factor

ARHGEF16:

Rho guanine exchange factor 16

AUC:

Area under “ROC” curve

BF:

Factor B

BMI:

Body mass index

BRAF:

v-raf murine sarcoma viral oncogene homologue B1

CACNB2:

Calcium channel, voltage-dependent, beta 2 subunit

CDAI:

Clinical disease activity index

CEA:

Carcinoembryonic antigen

cfNRI:

Category-free NRI

COL4A1:

Collagen, type IV, alpha 1

COMP:

Cartilage oligomeric matrix protein

CRP:

C-reactive protein

CTX-I:

Collagen cross-linked C-telopeptide

CXCL13:

C-X-C motif chemokine 13

DAS:

Disease activity score

DMARDs:

Disease-modifying antirheumatic drugs

EGF:

Epidermal growth factor

EHD1:

EH domain-containing 1

EIF3S9:

Eukaryotic translation initiation factor 3, subunit 9 eta

ESR:

Erythrocyte sedimentation rate

EULAR:

European League Against Rheumatism

F2RL1:

Coagulation factor II receptor-like 1

FHL3:

Four and a half LIM domains 3

FLS:

Fibroblast-like synoviocytes

FVT1:

Follicular lymphoma variant translocation 1

GADD45A:

Growth arrest and DNA-damage-inducible, alpha

GAS:

Global arthritis score

GWAS:

Genome-wide association studies

HSPA1A:

Heat shock 70 kDa protein 1A

IDI:

Integrated discrimination improvement

IL-15:

Interleukin-15

IL-6:

Interleukin-6

LTBR:

Lymphotoxin-beta receptor

MALDI-TOF-MS:

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

MBDA:

Multi-biomarker disease activity

MDHAQ:

Multidimensional health assessment questionnaire

mHAQ:

Modified health assessment questionnaire

MIF:

Migration inhibitory factor

MLL:

Myeloid/lymphoid or mixed-lineage leukemia

MMP-1:

Matrix metalloproteinase-1

MMP-3:

Matrix metalloproteinase-3

NPV:

Negative predictive value

NRI:

Net reclassification improvement

OMERACT:

Outcome Measures in Rheumatology

OPG:

Osteoprotegerin

OR:

Odds ratio

PAD4:

Peptidyl arginine deiminase type 4

pain VAS:

Pain visual analogue scale

PGA:

Patient global assessment

PhGA:

Physician global assessment

PPP1R12B:

Protein phosphatase 1, regulatory subunit 12B

PPV:

Positive predictive value

PRMT2:

Protein arginine methyltransferase 2

PSA:

Prostate-specific antigen

PSMB8:

Proteasome subunit, beta type, 8

PTPN22:

Protein tyrosine phosphatase non-receptor 22 gene

RA:

Rheumatoid arthritis

RANKL:

Nuclear factor kappa-B ligand

RAPID-3:

Routine assessment of patient index data-3

RF:

Rheumatoid factor

ROC:

Receiver operating characteristics

RPIA:

Ribose 5-phosphate isomerase A

SAA:

Serum amyloid A protein

SDAI:

Simplified disease activity index

sICAM-1:

Soluble intercellular adhesion molecule-1

sIL-2Ralpha:

Soluble interleukin-2 receptor alpha

SJC:

Swollen joint count index

SKIL:

SKI-like oncogene

SLE:

Systemic lupus erythematosus

SPRY2:

Sprouty homologue 2 (Drosophila)

STNFRII:

Soluble tumor necrosis factor receptor II

STNFRs:

Soluble tumor necrosis factor receptors

sVCAM-1:

Soluble vascular cell adhesion molecule-1

TCR:

T-cell receptor

TFCP2:

Transcription factor CP2

TJC:

Tender joint count

TLR:

Toll-like receptor

TNFAIP3:

Tumor necrosis factor-alpha-induced protein 3

U-CTX-I/II:

Urine C-telopeptide of types I and II

VEGF-A:

Vascular endothelial growth factor-A

YKL-40:

Cartilage glycoprotein-39

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Authors and Affiliations

  1. School of Health Sciences, Liverpool Hope University, Hope Park, HCA-EW 208, Liverpool, L16 9JD, UK

    Mehmet Tevfik Dorak MD, PhD

  2. Division of Rheumatology, Department of Medicine, Seligman Center for Advanced Therapeutics and Behcet’s Syndrome Center, NYU Hospital for Joint Diseases, New York University School of Medicine, New York University, 333 East 38th Street, New York, NY, 10016, USA

    Yusuf Yazici MD

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Correspondence to Yusuf Yazici MD .

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  1. Istanbul University, Beyazit, Istanbul, Turkey

    Hasan Yazici

  2. New York University School of Medicine, NYU Hospital for Joint Diseases, New York, New York, USA

    Yusuf Yazici

  3. Department of Biostatistics, L-Biostat, KU Leuven, Leuven, Belgium, and Erasmus MC, Rotterdam, The Netherlands

    Emmanuel Lesaffre

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Dorak, M.T., Yazici, Y. (2014). Biomarkers, Genetic Association, and Genomic Studies. In: Yazici, H., Yazici, Y., Lesaffre, E. (eds) Understanding Evidence-Based Rheumatology. Springer, Cham. https://doi.org/10.1007/978-3-319-08374-2_4

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