Table 1 Identification of potential biomarkers for rheumatoid arthritis with omic-approaches
From: Potential clinical biomarkers in rheumatoid arthritis with an omic approach
Biomarker | Kind | Description | References | |
|---|---|---|---|---|
PHASE 1 | HLA-DRB1*04 and *03 allelic groups | Genomics | Association with genetic susceptibility to RA in a female population in Bosnia and Herzegovina | |
PHASE 1 | DRB1*01/DRB1*15 and DRB1*07/DRB1*16 genotypes | Genomics | Protective factor for RA in a female population in Bosnia and Herzegovina | [23] |
PHASE 1 | HLA-DRB5 gene variants | Genomics | Protective factor for RA in a female population in Bosnia and Herzegovina | [23] |
PHASE 1 | TNFSF10 gen | Genomics | Protective role in eRA, however, it has the effect to promote the disease | [38] |
PHASE 1 | IL-12A rs2243115 GG genotype | Genomics | Significant association with increased risk of RA (RF negative patients) | [100] |
PHASE 1 | IL-12B rs3212227 AC and AC + CC genotypes | Genomics | Associated with RA risk in older patients, RF positive patients and ACPA negative patients | [100] |
PHASE 1 | IL-10 rs1800872 A/C polymorphisms | Genomics | Association with risk of RA in East Chinese Han patients | [118] |
PHASE 1 | Members of the S100 protein family of calcium-binding proteins, S100A8 (Calgranulin A), S100A9 (Calgranulin B) and S100A12 (Calgranulin C) | Proteomics | Discrimination between RA and other inflammatory arthritides. The calgranulin C is the unique protein of this family that discriminate significatively RA and PsA | [24] |
PHASE 1 | Collagen type II (CII), collagen type IX (CIX) and collagen type XI (CXI) | Proteomics | Serum levels of CII, CIX and CXI antibodies can serve as clinical diagnostic indicators. Patients with antibodies Cll are correlated with a phenotype of increased inflammation and early joint destruction | |
PHASE 1 | Interleukin 1 (IL-1) | Proteomics | Clinic risk factor predisposing to RA | |
PHASE 1 | 30 metabolites | Metabolomics | Discrimination between RA patients and healthy subjects | [31] |
PHASE 1 | COL14A1 and CXCL12 genes | Transcriptomics | Overexpression in RA patients | [38] |
PHASE 1 | C-reactive protein (CRP) | Non-omics | Biomarker of elevated systemic inflammation in patients with RA. High serum value is a prognosis that indicates progressive bone erosion | |
PHASE 1 | Rheumatoid factor (RF) | Non-omics | Present (IgM isotype) in approximately 70–80% of patients with confirmed RA, with a sensitivity of 65–80% and 85% specificity for diagnosis. Considered useful in early stages of the disease to predict the development of erosions and the presence of the IgA isotype is associated with extra-articular manifestations. Aggressive development of the disease and decreased response to anti-TNF therapy have been reported at high levels | |
PHASE 1 | Anti-citrullinated protein antibodies (ACPA) | Non-omics | Biomarker more sensitive (60–80%) and specific (95–98%) for the diagnosis of RA than RF. ACPA + patients develop a more aggressive and erosive progressive disease clinical phase compared to ACPA- patients; Positivity has been associated with a better response to treatment in early stages but medication-free remission is less frequent. Baseline levels can be predictive for the response to methotrexate and ACPA + subjects are associated with a better response to abatacept independent of disease activity. It has been detected in healthy patients therefore increases the risk of developing RA by 5% in the next 5 years | [42, 51, 53,54,55,56,57, 65, 68, 74, 75, 99, 109, 110, 112, 121] |
PHASE 1 | Anticarbamylated protein (anti-CarP) antibodies | Non-omics | Association with rapid radiological damage and severe course of the disease independent of the ACPA value. In patients ACPA—it is associated with the development of arthralgias | |
PHASE 1 | Regulatory B lymphocytes (Breg) | Non-omics | Protective role in RF + patients (Lower T2/Breg levels) | [62] |
PHASE 1 | Erythrocyte Sedimentation Rate (ESR) | Non-omics | Nonspecific indicator of the amount of inflammation in the elevated body in patients with RA. It correlates with CRP with radiographic progression and these indices have been incorporated into the composite scores that are generally used to predict damage | |
PHASE 2 | MicroRNAs (miRNAs): miR 361-5p | Epigenomics | Elevated levels in the serum of patients with early stage of the disease | [20] |
PHASE 2 | Human Ficolin-2 protein | Proteomics | Increased levels in RA patients | [125] |
PHASE 2 | Matrix metalloproteinase-1 (MMP-1) | Proteomics | Elevated baseline MMP-1 levels are significantly correlated with radiographic progression | |
PHASE 2 | Interleukin-7 receptor subunit alpha (IL7R) | Proteomics | Possible applications in the diagnosis and therapy of RA | [28] |
PHASE 2 | C–C motif chemokine 5 (CCL5) | Proteomics | Prediction of a negative impact in the development of RA | [28] |
PHASE 2 | Resistin | Proteomics | High level in RA patients | [98] |
PHASE 2 | Malondialdehyde (MDA) | Metabolomics | Increased in patients with RA | |
PHASE 2 | 3-hydroxyisobutyrate, acetate, NAC, acetoacetate, and acetone levels | Metabolomics | Discrimination between RA and healthy subjects | [87] |
PHASE 2 | Valine, isoleucine, lactate, alanine, creatinine, GPC APC and histidine levels | Metabolomics | Decreased in RA patients | [88] |
PHASE 2 | Arginine, aspartic acid, glutamic acid, serine, phenylalanine, threonine, lysine | Metabolomics | Higher plasma concentration of arginine, aspartic acid, glutamic acid, serine, phenylalanine, threonine in RA patients than control was demonstrated while concentration of lysine was lower in RA patients | [95] |
PHASE 2 | Malondialdehyde-Acetaldehyde (MAA) | Metabolomics | Increased in RA patients. Furthermore, is associated to cardiovascular risk | [112] |
PHASE 2 | Glycan GP1 | Glycomics | Putative diagnostic biomarker for RA in the Han Chinese population | [78] |
PHASE 2 | 21 N-glycans | Glycomics | Discrimination between RA patients and HS | [51] |
PHASE 2 | Sulfated IgG N-glycans (SGm1 y SGm2) | Glycomics | Discrimination between RA and HS (sensitivity of 84% and specificity of 86%). Biomarkers for the classification of both RF negative and ACPA negative. (precision 93% y 95% in RA patients) | [52] |
PHASE 2 | Anti-mutated citrullinated vimentin (anti-MCV) | Non-omics | Significant correlation with ACPA (r = 0.73). comparable value to ACPA for RA early diagnosis, with lower sensitivity and specificity | |
PHASE 3 | MicroRNAs (miRNAs): miR 223‐3p and miR 16‐5p | Epigenomics | Prediction of disease outcome in eAR | [43] |
PHASE 3 | miR-642b-5p, miR-483-3p, miR-371b-5p (up-regulated) and miR-25-3p, miR-378d (down-regulated) | Epigenomics | Association with devolopment RA in undifferentiated arthritis patients after 4 years | [46] |
PHASE 3 | Hypo-methylation in 4 genes (FCRLA, CCDC88C, BCL11B and APOL6) | Epigenomics | Association with RA progression | [50] |
PHASE 3 | M1V variant SNP (rs3764880, A>G) | Genomics | Association with good activity of disease and classifies patients that require less therapeutic interventions | [58] |
PHASE 3 | Genetic variant (rs7607479) of the SPAG16 gene | Genomics | Protective role for radiological progression | [91] |
PHASE 3 | BF*S07 allotype of complement factor B | Genomics | Significantly associated with extra-articular manifestations (EAM) in brazilian RA patients | [99] |
PHASE 3 | B cell antigen receptor complexassociated protein alpha chain (CD79A) | Proteomics | Correlation with joint destruction | [28] |
PHASE 3 PHASE 6 | Interleukin 6 (IL-6) | Proteomics | Association with joint erosive progression. Patients with high levels might need an intensive treatment | |
PHASE 3 | Casein kinase 2 interacting protein 1 (CKIP-1) and a micro RNAs 214 | Proteomics and transcriptomics | Biomarkers that Predict the progression of bone erosion | [37] |
PHASE 3 | C-telopeptide of type I collagen (CTX-I) | Proteomics | High values reflect association with RA active and rapid joint destruction | |
PHASE 3 | C-telopeptide of type II collagen (CTX-II) | Proteomics | High level of CTX II are associated with greater progression of joint damage in patients with RA | |
PHASE 3 | Receptor Activator for Nuclear Factor κ B Ligand (RANKL) | Proteomics | Prediction of radiological progression in eRA patients | |
PHASE 3 | Interleukin-13 (IL-13) | Proteomics | Along with IL-17, it could be of better use than RF and ACPA for predicting the state of eAR activity | [56] |
PHASE 3 | CD4 + T-cell-derived CD161 + CD39 + and CD39 + CD73 + microparticles | Proteomics | Association with disease progression (high levels) | [64] |
PHASE 3 | Osteoprotegerin (OPG) | Proteomics | Prediction (RANKL/OPG ratio) of joint damage in 5 and 11 years in patients without early treatment | [69] |
PHASE 3 | C-X-C motif chemokine 13 (CXCL13) | Proteomics | High baseline CXCL13 levels are associated with a higher probability of remission after 2 years. Further, high concentrations in plasma indicate that patient can respond better to an early more aggressive treatment | [73] |
PHASE 3 | Cartilage oligomeric matrix protein (COMP) | Proteomics | Association with degradation of articular cartilage | [74] |
PHASE 3 | Heme oxygenase-1 (HO-1) | Proteomics | Biomarker for bone metabolism in patients with RA and ankylosing spondylitis | [77] |
PHASE 3 | Bone morphogenetic protein (BMP) | Proteomics | Biomarkers for bone metabolism in patients with RA and ankylosing spondylitis | [77] |
PHASE 3 | Orosomucoid (ORM)1, ORM2 and soluble CD14 (sCD14) | Proteomics | Association with disease activity, furthermore ORM2 predicts the radiological progression | [93] |
PHASE 3 | Adiponectin, Visfactin | Proteomics | Correlation with increased radiological progression | |
PHASE 3 | Vascular endothelial growth factor (VEGF) | Proteomics | High levels are significantly correlated with radiological progression after 1 year | [109] |
PHASE 3 | Angiopoietin-1 | Proteomics | Prediction of joint damage after 1 year | [109] |
PHASE 3 | Cartilage oligomeric matrix protein (COMP) | Proteomics | Predictions of joint damage at 1,2 and 5 years | [109] |
PHASE 3 | Human serum amyloid A (SAA) | Proteomics | Correlation with radiological progression. This protein reflects systemic and local inflammation | [109] |
PHASE 3 | Leptin | Proteomics | Association with decreased radiological progression | [109] |
PHASE 3 | C–C motif chemokine 11 (CCL11) | Proteomics | Association with decreased radiological progression | [109] |
PHASE 3 | Anti-peptidyl-arginine deaminase 3 (PAD3) | Proteomics | Association with severe radiological damage | [112] |
PHASE 3 | Coronary artery calcium | Metabolomics | Association with cardiovascular risk assessment in RA patients | [21] |
PHASE 3 | Vitamin K homologs: MK-4, MK-7 y PK | Metabolomics | Correlation with disease activity (lower levels in RA patients) | [68] |
PHASE 3 | Cholesterol, lactate, acetylated glycoprotein, and lipid signatures | Metabolomics | Prediction of disease severity | [85] |
PHASE 3 | Pigment epithelium-derived factor (PEDF) | Transcriptomics | Association with obesity in RA patients that influences the goal of remission | [41] |
PHASE 3 | 313 differentially expressed genes (232 up-regulated genes and 81 down-regulated genes) | Transcriptomics | Association between inflammatory and immune with RA progression | [50] |
PHASE 3 | Model of FKBP1A, FGF12, ANO1, LRRC31, and AKR1D1 | Transcritomics | The model is useful for efficiently predict the response to infliximab therapy in RA | [59] |
PHASE 3 | Signal transducer and activator of transcription 3 (STAT3) | Transcriptomics | Prediction of RA progression in ACPA negatives patients | [83] |
PHASE 3 | Platelet/lymphocyte ratio (PLR) | Non-omics | Discrimination between RA patients and rheumatoid arthritis-associated interstitial lung disease (RA-ILD) patients and for distinguishing healthy subjects | [22] |
PHASE 4 | Circular RNAs hsa_circ_0044235 | Epigenomics | Discrimination between RA and systemic lupus erythematosus (SLE) | [39] |
PHASE 4 | Serum amyloid A4 and vitamin D binding protein | Proteomics | Selection of patients with rheumatoid arthritis from healthy controls | [19] |
PHASE 4 | 14–3-3η proteins | Proteomics | Increased levels in RA patients. Further it is associated with joint damage. Determination of this protein with RF y ACPA increases the diagnostic rate (72%) | |
PHASE 4 | Binding immunoglobulin protein (BiP) | Proteomics | Discrimination between RA patients and healthy subjects | [57] |
PHASE 4 | Presepsin and procalcitonin | Proteomics | Identification of infections in patients with RA (presepsin has better infectious reflective status than procalcitonin) | [79] |
PHASE 4 | MMP7, PARC y SP-D biomarker signature | Proteomics | Association with Interstitial lung disease in RA | [114] |
PHASE 4 | γ-inducible protein 10 (IP-10)/CXCL10 | Proteomics | Association with Interstitial lung disease in RA | [122] |
PHASE 4 | Matrix metalloproteinase-7 (MMP-7) | Proteomics | Discrimination between RA patients and rheumatoid arthritis-associated interstitial lung disease (RA-ILD) | [122] |
PHASE 4 | Histidine, methionine, asparagine and threonine | Metabolomics | Discrimination between RA and psoriatic arthritis | [86] |
PHASE 4 | Signal transducer and activator of transcription 1 (STAT1) signature | Transcriptomics | High levels in RA patients. Useful for Discrimination between RA patients and Osteoarthritis patients | [34] |
PHASE 4 | Mitogen-activated protein kinase kinase kinase 3 (MAP3K3) gene | Transcriptomics | Discrimination between RA and PsA | [82] |
PHASE 4 | CD117 + and CD138 + cells | Non-omics | Discrimination between psoriatic arthritis (PsA) patients and RA patients in the context of ACPA negativity | [27] |
PHASE 4 | Natural Killer (NK) cell (CD3 + CD56 +) | Non-omics | Discrimination between RA patients and chronic chikungunya arthritis patients | [60] |
PHASE 4 | Perforin + NK cells | Non-omics | Discrimination between RA patients and chronic chikungunya arthritis patients | [60] |
PHASE 4 | Diagnostic algorithm combining plasma/serum ACPA and hydroxyproline | Non-omics | Discrimination specific and sensivity between early stage osteoarthritis, early rheumatoid arthritis, other non-RA inflammatory joint diseases and good skeletal health and detection | [115] |
PHASE 5 | MicroRNAs (miRNAs): miR-132, miR-146a y miR-155 | Epigenomics | Low baseline levels can be used to predict the positive response to MTX after 4 months of therapy | [33] |
PHASE 5 | MicroRNAs (miRNAs): miR-23 y miR-223 | Epigenomics | Association with negative response to combined anti-TNFα/ DMARDs therapy and as biomarkers of response to combined anti-TNFα/DMARDs therapy (so that their levels are indicative of the efficacy of the treatment and also of the degree of response) | [113] |
PHASE 5 | SNP NUBPL (rs2378945) | Genomics | Significant association with a poor response to etanercept in patients with Spanish and Greek ancestry | [29] |
PHASE 5 | SNP CD84 (rs6427528) | Genomics | Possibly associated with the response to etanercept in patients with Spanish and Greek ancestry | [29] |
PHASE 5 | C3435T (rs1045642) SNP in ABCB1 | Genomics | Association with the risk of poor response to methotrexate | [66] |
PHASE 5 | Two SNP (rs6028945) and (rs7305646) | Genomics | Prediction of response to anti-TNF therapy | [73] |
PHASE 5 | SNP (rs6427528) of the CD84 gene | Genomics | Association with good response to etanercept | [92] |
PHASE 5 | HLA-DRB1* haplotypes 04–04, 04–01 and 04–11 | Genomics | Significantly associated with usage of T Cell Receptor Beta Variable 25–1 (TRBV25), higher disease activity at the onset of disease and poor response to DMARD | [94] |
PHASE 5 | SNP (rs6427528) in CD84 gene | Genomics | Association with positive response to etanercept, but not adalimumab and infliximab in patients of European descent | [103] |
PHASE 5 | SNP (rs3794271) in PDE3A-SLCO1C1 locus | Genomics | Association with positive response to infliximab and etanercept, but not adalimumab in Spanish and Danish patients | [104] |
PHASE 5 | SNP (rs113878252) in MED15 gene | Genomics | Association with negative response to etanercept in European Caucasian patients with grandparents born in Spain | [105] |
PHASE 5 | SNP (rs6941263) in the ARMC2 locus | Genomics | Association with global negative response to anti-TNF therapy in European Caucasian patients with grandparents born in Spain | [105] |
PHASE 5 | SNP (rs6065221) in the MAFB locus | Genomics | Association with negative response to etanercept and infliximab in European Caucasian patients with grandparents born in Spain | [105] |
PHASE 5 | SNP (rs10919563) in the PTPRC locus | Genomics | Association with positive response to etanercept, adalimumab and infliximab in patients with European ancestry especially among those seropositive for ACPA or RF | [106] |
PHASE 5 | SNP (rs1800896) in the IL10 | Genomics | Association with response to etanercept, adalimumab and infliximab at 3 months | [107] |
PHASE 5 | SNP (rs 6,683,595) in the PTPRC | Genomics | Association with positive response to etanercept, adalimumab and infliximab at 6 months in patients of Spanish Caucasian or Greek Caucasian descent | [107] |
PHASE 5 | SNP (rs11591741) in the CHUK | Genomics | Association with positive response to adalimumab and infliximab at 3 months in patients of Spanish Caucasian or Greek Caucasian descent | [107] |
PHASE 5 | Single-nucleotide polymorphism (SNP) TNF-α − 308 G > A (rs1800629) | Genomic | Association with a poor response to infliximab, etanercept and adalimumab. However, patients who carry the G allele respond positively to biological therapy | |
PHASE 5 | 9-protein signature | Proteomics | Association with a decreased chance (6/9) achieving sustained drug-free remission after initiation of tocilizumab plus methotrexate therapy in DMARD-naive patients with early RA | [44] |
PHASE 5 | 14-protein signature | Proteomics | Association with a decreased chance (6/14) achieving sustained drug-free remission after initiation of tocilizumab plus methotrexate therapy in DMARD-naive patients with early RA | [44] |
PHASE 5 | 13-protein signature | Proteomics | Association with a decreased chance (5/13) achieving sustained drug-free remission after initiation of tocilizumab plus methotrexate therapy in DMARD-naive patients with early RA | [44] |
PHASE 5 | Osteopontin | Proteomics | Serum levels before treatment predict the clinical remission for tocilizumab therapy but not for clinical remission induced for infliximab therapy | [51] |
PHASE 5 | TTTT B lymphocyte stimulator promoter haplotype (TTTT BLyS) | Proteomics | Significant association with good response to rituximab for seropositive RA patients after anti-TNF agents have failed | [53] |
PHASE 5 | Favorable Fcγ receptor III (FcγRIII) genotype | Proteomics | Prediction of positive response to treatment with Rituximab | [53] |
PHASE 5 | Cluster of differentiation 20 (CD20) | Proteomics | Prediction of response to rituximab therapy (significantly high values predict a negative response) | |
PHASE 5 | 15-protein signature | Proteomics | Association with response to IFX | [81] |
PHASE 5 | 8-protein signature | Proteomics | Association with response to ADA | [81] |
PHASE 5 | 8-protein signature | Proteomics | Association with response to IFX + ADA | [81] |
PHASE 5 | C-X-C motif chemokine 10 (CXCL10) and C-X-C motif chemokine 13 (CXCL13) | Proteomics | Baseline CXCL10 and CXCL13 levels are associated with favorable response to anti-TNF therapy (adalimumab or etanercept) at 14 weeks | [120] |
PHASE 5 | Erythrocyte folate levels | Metabolomics | Association with a poor response to MTX (Lower baseline levels) | [66] |
PHASE 5 | Histamine, glutamine, xanthurenic acid, and ethanolamine | Metabolomics | Association with anti-TNF therapy as responders and non-responders with infliximab and etanercept | [89] |
PHASE 5 | Increased levels of isoleucine, leucine, valine alanine, glutamine, tyrosine, and glucose, and decreased levels of 3-hydroxybutyrate | Metabolomics | Expressed in patients with good response before treatment with etanercept | [90] |
PHASE 5 | Type I interferons (IFNs) signature | Transcriptomics | Discrimination between responders and non-responders patients to MTX treatment for the first time after 6 months. High titles are also associated with a poor response of Infliximab at 12 y 22 weeks. Similarly, classifies non-responders patients to treatment of rituximab. In preclinic phases represents an independent risk clinical factor for predicter RA | |
PHASE 5 | 9 (8 up-regulated, 1 down-regulated) signature genes | Transcriptomics | Prediction of sustained drug-free remission after initiation of tocilizumab plus methotrexate therapy in DMARD-naive patients with early RA | [45] |
PHASE 5 | 7 (6 up-regulated, 1 down-regulated) siganture genes | Transcriptomics | Prediction of sustained drug-free remission after initiation of tocilizumab in DMARD-naive patients with early RA | [45] |
PHASE 5 | 14 (11 upregulated, 3 downregulated) signature genes | Transcriptomics | Prediction of sustained drug-free remission after initiation of methotrexate in DMARD-naive patients with early RA | [45] |
PHASE 5 | A combination of 3 genes [cytidine monophosphate kinase 2 (CMPK2), IFN-induced protein with tetratricopeptide repeats 1B (IFIT1B), and RNASE3] | Transcriptomics | Prediction of responders and non-responders patients to anti-TNF therapy (ADA, ETP and Golimumab) | [67] |
PHASE 5 | 13- gene expression signature | Transcriptomics | Association with anti-TNF responders (ADA, ETP and Golimumab) | [67] |
PHASE 5 | 10- IFN-regulated genes expression signature | Transcriptomics | Association with anti-TNF nonresponders (ADA, ETP and Golimumab) | [67] |
PHASE 5 | 8-gene expression signature | Transcriptomics | Association with response to anti-TNF therapy | [73] |
PHASE 5 | Total lymphocyte counts and plasmablast | Non-omics | Association with negative response from Rituximab therapy | [72] |
PHASE 5 | B cells | Non-omics | Association with positive response to Rituximab | [97] |
PHASE 6 | MicroRNAs (miRNAs): miR 26b ‐ 5p, miR 487b ‐ 3p y miR 495‐3p | Epigenomics | Association with good response to Allogeneic Adipose‐Derived Mesenchymal Stem Cells therapy | [61] |
PHASE 6 | MicroRNAs (miRNAs): miR-16-5p, miR-23-3p, miR125b-5p, miR-126-3p, miRN-146a-5p, miR -223-3p | Epigenomics | Significantly associated with positive response to anti-TNFα/DMARDs therapy y parallel to the reduction de TNFα, IL-6, IL-17, RF, CRP | [113] |
PHASE 6 | GALNT18 C allele SNP (rs4910008) | Genomics | Association with a low disease activity at 6 months in patients previously treated with tocilizumab | [76] |
PHASE 6 | CD69 A allele SNP (rs11052877) | Genomics | Association with a low disease activity at 6 months in patients previously treated with tocilizumab | [76] |
PHASE 6 | Matrix metalloproteinase-3 (MMP-3) | Proteomics | Association with radiological progression particularly in early RA. High decrease of this biomarker may indicate better scope of remission; high baseline amounts is associated with clinic response of infliximab | |
PHASE 6 | C–C motif chemokine 22 (CCL22) and C–C motif chemokine 17 (CCL17) | Proteomics | Specific Pharmacodynamics Biomarkers for therapies targeting to Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF) | [36] |
PHASE 6 | Chemerin | Proteomics | Association with metainflammation and as a clinic modifiable risk factor associated to treatment response | [41] |
PHASE 6 | Matrix metalloproteinase-8 (MMP-8) | Proteomics | High concentrations in RA chronic patients. MMP-8 levels in saliva was high in eRA patients | [47] |
PHASE 6 | Matrix metalloproteinase-derived types I, II, and III collagen neoepitopes [C1M, C2M, and C3M] | Proteomics | C1M is associated with radiological progression and both C1M as C3M are associated with treatment efficacy | |
PHASE 6 | Fibulin-3 | Proteomics | Decreased levels during anti-TNF clinic therapy in patients with RA | [49] |
PHASE 6 | Interleukin 6 receptor (IL6R) | Proteomics | High levels in RA patients are associated with clinical response to tocilizumab | |
PHASE 6 | Tumor necrosis factor α (TNF-α) | Proteomics | Increased levels in patients with RA. The baseline level is associated with the clinical response to anti-TNF therapy | |
PHASE 6 | Calprotectin | Proteomics | Association with good or moderate response to RTX and high levels predicts more severe radiological damage after 10 years | |
PHASE 6 | Intra-Cellular Adhesion Molecule-1 (ICAM-1) | Proteomics | Association with response to anti-TNF therapy | [73] |
PHASE 6 | Prothrombin fragment F1 + 2and fibrin fragment D-dimer | Proteomics | The reduction of prothrombotic biomarkers parallels the reduction of inflammatory parameters and clinical symptoms in RA patients treated with tocilizumab | [80] |
PHASE 6 | Interleukin-17 (IL-17) | Proteomics | Significantly higher levels in serum of RA patients. Further, Il-17 is associated to a more active state of disease | [101] |
PHASE 6 | Soluble gp130 (Spg130), granulocyte macrophage colony-stimulating factor (GM-CSF), interferon gamma-induced protein 10 (IP10) | Proteomics | Prediction of DAS28-CRP score in RA patients not treated with tocilizumab | [102] |
PHASE 6 | Spg130, Il-6,IP10 and soluble tumor necrosis factor receptor two (sTNFRII) | Proteomics | Prediction of remission in ingenious patients after treatment with tocilizumab | [102] |
PHASE 6 | Spg130 | Proteomics | Prediction of remission in Ra patients treated with tocilizumab at 16 weeks (high levels: > 0,2 μg/ml) | [102] |
PHASE 6 | Interleukina IL-9 (IL-9), TNF-α, vascular endothelial growth factor (VEGF) | Proteomics | Prediction of DAS28-CRP score at 16 weeks in RA patients treated with etanercept (low fiability) | [102] |
PHASE 6 | 11 metabolites | Metabolomics | Significantly correlated positively or negatively with DAS28-ESR and significantly differed between active and inactive patients | [25] |
PHASE 6 | Methotrexate polyglutamate | Metabolomics | Measure the response to MTX therapy | [66] |
PHASE 6 | Concentration parameter calculated as [aspartic acid] + [threonine] + [tryptophan]—[histidine]—[phenylalanine] | Metabolomics | Correlation between painful joints count, inflamed joints count and DAS28 value | [95] |
PHASE 6 | Dihydrofolate reductase (DHFR), T cell receptor alpha variable 8–3 (TRAV8-3), ephrin receptor A4 (EPHA4) and coiled-coil domain containing 32 (CCDC32) | Transcriptomics | Association with response to tocilizumab therapy (there are expressed after treatment) | [84] |
PHASE 6 | 28 sets of genes (each set contained 22–325 gene probes) | Transcriptomics | Determine the presence of reduced disease activity in response to therapy with anti‐TNF | [111] |
PHASE 6 | Multi-biomarker disease activity (MBDA) | Non-omics | Calculated based on the 12 different biomarkers (VCAM-1, EGF, VEGF-A, IL-6, TNF-RI, YKL-40, MMP-1, MMP-3, leptin, resistin, SAA, CRP). The score reflects the current clinical activity of the disease | |
PHASE 6 | Regulatory T cells (Treg) | Non-omics | Monitoring patients but not for predicting their personal response | [62] |
PHASE 6 | T helper 17 (Th17) cells | Non-omics | Prediction for response to anti-cytokine treatments (Low levels of Th17 cells) | [62] |
PHASE 6 | Volume transfer constant for Gadolinium-based contrast agent between blood plasma and extravascular (Ktrans/min-1) | Non-omics | Measure the response to biological therapy at 6 weeks | [63] |
PHASE 6 | Sonography | Non-omics | Measure disease state and predict the relapse and refractary nature of RA | [71] |
PHASE 6 | Reactive oxygen species and reactive nitrogen species | Non-omics | Effectively serve as biomarkers for monitoring disease progression | [75] |
PHASE 6 | Residual memory B cells | Non-omics | High levels (Especially memory B cells increased) increase the response risk inadequate or recaid to rituximab therapy | [108] |
PHASE 6 | Circulating monocytes: CD14+ high CD16− and CD14+ high CD16+ subset cells | Non-omics | Prediction of clinic response reduced to MTX in Ra patients with no treatment previously | [119] |