IRA ORATION - Dr V S Negi

Dr. Vir Singh NEGI JIPMER, Puducherry

JIPMER….Breaking barriers….. Finding Frontiers….. Jawaharlal Institute of Medical Education and Research

Immunogenetics of Rheumatoid Arthritis

in South India

25.11.2016

Dr. Dominique Charron

Director, Hematology (BMT) Hopital Saint Louis

& Dean, International Collaborations, University of

Paris-7, France

Dr. Helene Moins

IUH, Hopital Saint Louis, Paris, France

Dr. Ryad TamouzaINSERM U1160,

Hopital Saint Louis Paris, France

Dr. Srini V. KaveriDirector , INSERM U 419, Paris,

France

Dr. Rajagopal Krishnamoorthy

Ex-Director of Research, Inserm U763, Hôpital Robert

Debré, Paris, France

Chronic, progressive, inflammatory autoimmune disease

0.5 -1% of the adult population affected (developed countries)

Female Predominance

Heterogeneous phenotype with articular, extra-articular and systemic manifestations

Differential response to treatment

Rheumatoid Arthritis

Shapira, Y. et al. (2010), Nat. Rev. Rheumatol.

Worldwide Prevalence

0.5% - 0.75%

Prevalence in India

Pathogenesis of RA

― Sibling & twin pair studies - estimated genetic contribution to RA

as 50% - 60%

― The prevalence of RA in general population <1% - among siblings

increases to 2–4%

― Strongest risk : HLA-DRB1 followed by PTPN22

― In Asians PADI4 instead of PTPN22

Genetic Contribution

— Prevalence similar to that reported from the developed countries but higher than China, Indonesia, Philippines and rural Africa

— HLA-DRB1*04 to be the major susceptibility allele for RA in north Indian population

— Study from Malaysia reported in a mixed ethnic population of Indian origin

— HLA DRB1*10 - associated with ACPA positive RA — HLA DRB1*13 - with ACPA negative disease

— Paucity of data on the role of HLA & non HLA genes conferring susceptibility to RA in south India population of Dravidian descent

RA in India

Genetic susceptibility to rheumatoid arthritis, clinical phenotype, response to therapy and prognosis in South Indians may be different from other populations

Background

Genetic polymorphisms in HLA and non HLA genes

Influence cytokine gene expression and cellular activation

Influence disease phenotype and treatment response in RA

Hypothesis

To characterize the immuno-inflammatory genetic variants

and their influence on disease phenotype and response to

treatment in South Indian Tamil patients with Rheumatoid

arthritis

Aim

1. To characterize the polymorphism of • Classical HLA Class II genes DRB1 & DQB1• Non-classical HLA Class I genes HLA-G, HLA-E & MICA• Non-HLA genes TNF-α & NK cell receptors (NKG2D)

2. To determine the association of these gene variants with RA

susceptibility, disease phenotypes and response to treatment 3. To construct population specific haplotypes of HLA and non

HLA genes 4. To assess and characterize cytokine gene expression profile &

cytokine levels in patients with RA

Objectives

Collection of 10 ml of venous blood

Extraction of RNA Extraction of DNA Separation of Plasma

Cytokine/Transcript analysis by real time

relative quantitation assay

HLA/non-HLA genotyping by PCR/Real time PCR,

Sequencing & Next generation sequencing

Autoantibody, inflammatory marker

measurements by ELISA/Nephelometry

Measurement of sMICA, Cytokines by ELISA /

Multiplex Assay

Classification based on various clinical phenotypes. Correlation of phenotype/genotype

Establishment of population specific haplotype, clinical / genetic profile for South Indian Tamils

First visit to Clinical Immunology clinic

Informed consent - from the study subjects

Enrolled based on ACR criteria for RA

Separation of Serum

Sample Size a) Genotyping 271 cases 233 controls b) Gene expression 48 cases 48 controls

Methods

Classical HLA Class II

• HLA-DRB1• HLA-DQB1

Non-Classical HLA Class I

• MICA• HLA-E• HLA-G

Non-HLA

• TNF-α• NK cell receptor

Genes analyzed

Viatte, S. et al. (2013) Genetics and epigenetics of rheumatoid arthritisNat. Rev. Rheumatol.

Risk loci for RA

― Highest (37% ) risk from HLA class II alleles

― In Caucasian RA : DRB1*04:01 & DRB1*04:04

― Others : DRB1*01 or DRB1*10:01

― North & Western regions of India DRB1*04

― Malaysian South Indian Tamil migrants : DR*10:01

Plasma Cells

Autoantibody Synthesis (RF, ACPA)

Immune Complex formation

DC HLA

CD40

B7

CD40L

CD28

Self antigen presentation

TCR

B

T

HLA DRB1 & DQB1

Polymorphism in DRB1/DQB1Breakdown of tolerance Auto reactive T cell Susceptibility to RA

Physiological role Immune regulation at maternal – fetal interfaceHLA-G & HLA-E are co-expressedNaturally occurring tolerance inducing molecules

HLA-G

Polymorphism in HLA GModulates the expression of the geneLow sHLA G levels – incomplete immune suppression Initiates autoimmune process

HLA-G

HLA-E

— On surface, HLA-E interacts with CD94/NKG2 receptors : inhibitory signal protecting cells from NK mediated lysis

— Virally infected / tumor cells by reducing the supply of leader peptides – reduces HLA-E on surface

— This causes loss of the inhibitory signal rendering them vulnerable to NK cell mediated lysis

Physiological role HLA-E : expressed by T, B, NK cells & macrophagesModulates NK cell activity APC for αβT cells & Implicated in adaptive immunity

Polymorphism in HLA EModulates gene expression Affects immunosuppressive function

— HLA E has two known alleles HLA-E*01:01 and HLA-E*01:03

— They have variable binding affinity to NK cell receptors and act as ligands for both Innate and adaptive immune responses

— HLA Ers2844724 is a C>T single nucleotide substitution at the 3’ UTR, affects the serum/plasma levels of soluble HLA-E

HLA-E

CD4+

CD28-

T

NK CD8+ T

GI epitheliu

mEnothelial cells

Fibroblasts

MICA

Physiological roleInnate & Adaptive immunity

Immune surveillance

NKG2D

MICA

— Molecule of cellular stress, binds to NKG2D

— MICA alleles associated with susceptibility or resistance to autoimmunity

— MICA-129 val allele is weak binders of NKG2D while met allele is strong binder of NKG2D

NK CD8+ T

Synovial

Fibroblasts

MICA

Polymorphism in MICA & NKG2DAffect MICA-NKG2D binding affinity Modulate activation of NK, CD8+ & CD4+CD28- T cells

CD4+

CD28-

T

NKG2D

Plasma Cells

Autoantibody Synthesis (RF ( IgG & IgM)

Immune Complex formation

B

Complement receptor

Fc receptor

Macrophages

Recruitment of immune cells Secretion of proinflammatory cytokinesActivation of Synoviocytes and OsteoclastsDysregulation of MICA & NKG2D expression in synovium perpetuating chronic auto-inflammation Tissue & bone damage

MICA

NK cell receptor

Activated CD4+

NK CD8+ T

GI epitheliu

mEnothelial cells

Fibroblasts

MICA

NKG2D

• NKG2D (KLRK1) is a C-type lectin, activatory receptor encoded by chromosome 12

• Expressed on NK cells, CD8+ αβ+ T cells, NKT cells, γδ+ T cells, and on a small subset of CD4+ αβ+ T cells

• NKG2D binds to MICA, MICB & ULBP family

• Ligand binding of NKG2D delivers activatory signals to NK cells but co-stimulatory signals to activated CD4+ T cells

Activatory signal

Co-stimulatory signal

• IL-2, IL-15– NKG2D & DAP10 on CD8+ T Cells

• IL-15, TNF-α - NKG2D on CD4+ NKG2D+ T cells

• IL-15, IL-17 - NKG2D on activated CD8+ T cells with NKG2D co-stimulation

• IL-21, IL-12, TGF-β1, IFN-γ - NKG2D

— TNF-α: potent pleiotropic pro-inflammatory cytokine produced mainly by macrophages

— Important role in inflammation & contributes to the regulation of normal immune homeostasis

— The dual but opposing biological function of TNF-α is pro-inflammatory in the initial infectious phase, which progressively transitions towards anti-inflammatory/immuno regulatory activity in the later phases

— Polymorphisms in the TNF-α gene can either behave as biomarkers or may have direct impact on its expression and function

TNF-α

TNF-α

— Available data on association of TNF-α promoter polymorphism with RA is controversial

— A number of SNPs in this region are reported to be associated with susceptibility to RA & its clinical phenotypes in different populations

— The reported relationship between TNF-α polymorphism & response to anti-TNF therapy is also inconsistent

— From India, the only study that addressed the potential influence of the TNF-α -308 G>A and -863 C>A polymorphisms observed that-308A allele conferred protection against RA -863A had weak association with early onset disease in females (Gambhir et al, 2010)

Gene expression & cytokine profiling

Type Cytokine /Transcript

Th1 T-betIFN-γIL-12p40

Th2 GATA3IL-4

Anti inflammatory IL-10TGF-β

Pro inflammatory IL-1bTNF-α

Th17 IL-6IL-17aIL-1b

Tregs Foxp3

Cytokine/Transcription factors analyzed

Cytokine gene polymorphism and mRNA expression Affect the threshold cytokine levels in synovium

The Cytokine Network

Laboratory Methods

Results

Part I : Patients Characteristics

Characteristic RA (n=271) HC (n=233)Female :Male (ratio) 247:24 (10:1) 201:32 (6:1)Age, Mean (SD) years 41.2 (10.9) 39.6 (13.6)Average Age at onset (years) 37.7 NilAverage Duration of disease (years) 8.4 Nil

Results : Patient Characteristics (1)

YORA: Young onset RA (<55 yrs)

LORA: Late onset RA (≥55 yrs)

DF: Deforming disease

NDF: Non-Deforming disease

EAM: Extra-articular Manifestations

NEAM: Non-Extra articular manifestations

Results : Patient Characteristics (2)

Results : Patient Characteristics (3)

RF: Rheumatoid Factor ACPA: Anti-citrullinated protein antibody

Results: Patient Characteristics (4)

Part I : Summary

— Study groups: 271 active RA (247 females, 24 males) 233 healthy controls (201 females, 32 males)

— Majority (94%) of the patients were young onset RA while Late onset RA contributed 6%.

— The clinical phenotype suggested erosive, deforming disease in majority (59%) of patients with moderate (13%) to high (87%) disease activity at enrolment

— None of the patients had low disease activity or emission

— Majority of the patients were seropositive (RF+-75%, ACPA+ - 60%, RF+ACPA+ - 53%).

— Only 19% of the patients were both RF & ACPA negative

— None of the patients were smokers

— Treatment with DMARDs resulted in good response in 21%, moderate response in 72%

— Poor response to therapy in 7%

Part I : Summary

Results

Part II : Characterization of HLA & Non-HLA genes

HLA-DQB1 RA, n=271AC = 542 (%)

HC, n=233AC = 466 (%) P

*02 48(9) 53(11) NS

*03 167(31) 141(30) NS

*04 11(2) 12(3) NS

*05 164(30) 125(27) NS

*06 152(28) 135(29) NS

HLA Class II : DQB1, Cases vs. Controls

RA: Rheumatoid Arthritis, HC: Healthy Controls, AC: Allele count, NS: Not Significant

HLA-DRB1

RA, n=271AC = 542 (%)

HC, n=233AC = 466 (%) P value P *14 OR (95% CI)

*01 20(3.69) 9 (1.93) NS*03 26 (4.8) 23 (4.94) NS*04 91 (16.79) 66 (14.16) NS

*05 2 (0.37) 2 (0.43) NS

*07 66 (12.18) 73 (15.66) NS*08 13 (2.40) 20 (4.29) NS*09 4 (0.74) 3 (0.64) NS

*10:01 100 (18.0) 43 (9.23) 0.00 0.0004* 2.31 (1.558-3.460)*11 18 (3.32) 18 (3.86) NS*12 15 (2.77) 13 (2.79) NS*13 25 (4.61) 47 (10.09) 0.00 0.01* 0.43 (0.250-0.729)*14 30 (5.54) 56 (12.02) 0.00 0.003* 0.43 (0.261-0.695)*15 131 (24.17) 91 (19.53) NS*16 1 (0.18) 2 (0.43) NS

*- Susceptible allele * - Protective Allele

HLA Class II : DRB1, Cases vs. Controls

RA: Rheumatoid Arthritis, HC: Healthy Controls, AC: Allele count, NS: Not Significant, OR: Odds ratio, 95% CI: 95% confidence interval. P*14 (Bonferroni’s correction) : <0.05 is considered significant.

HLA Class I: HLA-G, Cases vs. Controls

rs66554220 (14bp Ins/Del) RA, n=221 (%) HC, n=200 (%) P+14 307 (49) 210 (53) NS-14 224 (51) 190 (47) NS

+14/+14 43 (19) 47 (23) NS+14/-14 132 (60) 116 (58) NS-14/-14 46 (21) 37 (19) NS

rs1063320 (+3142 C>G)G 315 (71) 282 (71) NSC 127 (29) 118 (29) NS

GG 112 (51) 106 (53) NSGC 91 (41) 70 (35) NSCC 18 (8) 24 (12) NS

rs9380142 (+3187 A>G)A 361 (82) 327 (82) NSG 81 (18.3) 73 (18) NS

AA 149 (67) 138 (69) NSAG 63 (29) 51 (26) NSGG 9 (4) 11 (5) NS

RA: Rheumatoid Arthritis, HC: Healthy Controls, NS: Not Significant

HLA-E (rs1264457) RA, n=221 (%) HC, n=200 (%) P

*01:01 220 (50) 195 (49) NS*01:03 222 (50) 205 (51) NS

*01:01/*01:01 51 (23) 46 (23) NS*01:01/*01:03 118 (53) 103 (52) NS*01:03/*01:03 52 (24) 51 (25) NS

HLA-E (rs2844724) C 94 (21) 93 (23) NST 348 (79) 307 (77) NS

CC 9 (4) 14 (7) NSCT 76 (34) 65 (32) NSTT 136 (62) 121 (61) NS

RA: Rheumatoid Arthritis, HC: Healthy Controls, NS: Not Significant.

HLA Class I: HLA-E, Cases vs. Controls

MICA-129 (rs1051792)

RAn=270 (%)

HCn=232, (%) P Pc OR (95% CI)

met 145 (27) 163 (35) 0.005 0.006* 0.68(0.51-0.89)

val 395 (73) 301 (65) 0.005 0.006* 1.48(1.12-1.95)

met/met 16 (5.9) 33 (14.2) 0.002 0.003* 0.38 (0.19-0.74)

met/val 113 (41.9) 97 (41.8) NS

val/val 141 (52.2) 102 (44) 0.01 0.03 1.42 (1.04-2.01)

RA: Rheumatoid Arthritis, HC: Healthy Controls, Pc: Yates corrected P value, OR: Odds ratio, 95% CI: 95% confidence interval. Pc<0.05 is considered significant.

HLA Class I Typing : MICA-129, Cases vs. Controls

MICA-129 val allele and val/val genotype associated with susceptibility MICA-129 met allele and met/met genotype associated with protection

TNFa-857 (rs1799724) RAn= 269 (%)

HC n=233 (%) Pc OR (95% CI)

C 475 (88) 403 (87) NST 63 (12) 61 (13) NS

CC 210 (78) 175 (75) NS CT+TT 59 (22) 57 (25) NS

TNFa-308 (rs800629) G 529 (98) 450 (97) NS A 9 (2) 14 (3) NS

GG 260 (97) 218 (94) NS AG+AA 9 (3) 14 (6) NS

TNFa-238 (rs361525) G 499 (93) 404 (87) 0.004* 1.90 (1.22-2.99)A 39 (7) 60 (13) 0.004* 0.53 (0.34-0.82)

GG 234 (87) 177 (76) 0.003* 2.08 (1.27-3.42)GA+AA 35 (13) 55 (24) 0.003* 0.48 (0.29-0.79)

Non-HLA genotyping : TNF-α, Cases vs. Controls

TNFa- 238 G allele and GG genotype associated with susceptibilityTNFa- 238 A allele and GA+ AA genotype associated with protection

Non-HLA genotyping : NK cell receptor: Cases vs. ControlsRA, n=236 (%) HC, n=187 (%) P RA, n=236 (%) HC, n=187 (%) P

NKG2D3 (rs1049174)

NKG2D10 (rs2617169)

CC 86(36) 75(40) NS AA 202(85.5) 158(84.5) NSCG 97(41) 83(44) NS TA 33(14) 28(15) NSGG 53(23) 29(16) NS TT 1(0.5) 1(0.5) NS

NKG2D4 (rs2255336)

NKG2D11 (rs2617170)

GG 197(84) 157(84) NS CC 85(36) 75(40) NSGA 36(15) 30(16) NS CT 100(42) 84(45) NSAA 3(1) 0(0) NS TT 51(22) 28(15) NS

NKG2D7 (rs2617160)

NKG2D12 (rs2617171)

AA 49(21) 26(14) NS CC 53(22) 28(15) NSAT 105(44) 86(46) NS CG 101(43) 86(46) NSTT 82(35) 75(40) NS GG 82(35) 73(39) NS

NKG2D9 (rs2246809)

NKG2A17 (rs1983526)

AA 2(1) 0(0) NS CC 90(38) 54(29) NSAG 35(15) 30(16) NS CG 102(43) 98(52) NSGG 199(84) 157(84) NS GG 44(19) 35(19) NS

RA: Rheumatoid Arthritis, HC: Healthy Controls, NS: Not Significant

Part II : Summary

1. Susceptibility genotypes/alleles for RA

―HLA-DRB1*10:01 and MICA-129 val alleles belonging to HLA genes on chromosome 6 are associated with increased risk of developing RA

―GG genotype of TNF-α -238, member of non-HLA genes on chromosome 6 is associated with risk of developing RA

2. Protective genotypes/alleles for RA ―HLA-DRB1*13, *14 and MICA-129 met alleles, members of HLA genes on chromosome 6 are associated with protection

Results

Part III : Association of HLA & Non-HLA polymorphisms with RA disease phenotypes & treatment response

Disease Phenotypes

Autoantibody Phenotype

―RF+ vs. RF-

―RF high vs. low―ACPA+ vs. ACPA-

―ACPA high vs. low―RF+ACPA+ vs. RF-ACPA-

Clinical Phenotype

―Female vs. Male RA―YORA vs. LORA―Deforming vs. Non Deforming Ds.―Extra-articular manifestations vs. without EAM

Treatment Response

―Responders vs. Non

responders

  Total RA Pc OR (95% CI) Female RA Pc OR(95% CI) YORA Pc OR (95% CI)Deformities + - + - + -

n (%) 140(%) 96(%)     132(%) 84(%)     131(%) 91(%)    

NK9A 11 5 0.03 2.44(1.09-5.98) 11 5 0.05 2.26(1.01-5.57) 10 4 0.04 2.50(1.07-6.51)

G 89 95 0.03 0.41(0.17-0.91) 89 95 0.05 0.44(0.18- 0.99) 90 96 0.04 0.40(0.15-0.94)

AA 1 0 NS 1 0 NS 1 0 NS

AG 19 9 NS 20 11 NS 18 9 NS 2.21(0.89- 5.99) 

GG 80 91 0.04 0.41(0.16-0.96)  79 89 NS 81 91 0.05 0.41(0.15-0.99) 

NK10A 90 96 0.04 0.41(0.16-0.95) 90 95 0.06 0.44(0.17-1.03) 90 96 0.04 0.38(0.14-0.93)

T 10 4 0.04 2.45(1.05-6.39) 10 5 0.04 2.28(0.97-5.95) 10 4 0.04 2.64(1.08-7.38)

AA 81 92 0.04  0.40(0.15-0.97)  80 90 NS  82 92 0.04  0.37(0.13-0.95)

TA 18 8 NS  19 10 NS  18 8 NS

TT 1 0  NS   1 0 NS   1 0 NS  

NKG2D polymorphism : deformities

‘A’ allele of NK9 and ‘T ‘allele of NK10 associated with deformities

HLA-DRB1 Patients HC P Pc OR (95% CI)RF+, AC=406 (%) AC=466 (%)

*10:01 81 (19.9) 43 (9.23) 6.1x10-6 9x10-6 2.45 (1.62-3.74)*13 20 (4.9) 47 (10.1) 0.003 0.04 0.44 (0.24-0.78)*14 18 (4.4) 56 (12.0) 6.1x10-5 0.0009 0.34 (0.19-0.60)

ACPA+, AC=324 (%)*10:01 57 (17.6) 43 (9.23) 5.1x10-4 0.007 2.10 (1.35-3.29)

*13 12 (3.7) 47 (10.1) 7.9x10-4 0.01 0.34 (0.16-0.67)*14 13 (4.0) 56 (12.0) 8.9x10-5 0.001 0.31 (0.15-0.58)

SP, AC=288 (%)

*10:01 53 (18.4) 43 (9.23) 0.0002 0.003 2.22 (1.41-3.51)

*13 12 (4.2) 47 (10.1) 0.003 0.04 0.39 (0.18-0.76) *14 11 (3.8) 56 (12.0) 0.0001 0.001 0.29 (0.14-0.57)

HLA-DRB1 alleles : autoantibody status

AC: Allele count, HC: Healthy controls, RF: Rheumatoid Factor, ACPA: Anti-citrullinated peptide antibody, SP: RF +ACPA+, Pc: Bonferroni correction for multiple alleles, OR: odds ratio, 95% CI: 95% confidence interval. Pc values <0.05 were considered significant. Higher frequency of HLA-DRB1*10:01 in RF+ and ACPA+ patients

Total RA Pc OR (95% CI) Female RA Pc OR(95% CI) YORA Pc OR (95% CI)

RF + - + - + - n 173 48 161 42 161 45 % % % % % %

A 84 74 0.04 1.82(1.02-3.21) 83 71 0.02 1.99(1.08-3.56) 84 73 0.03 1.89(1.03-3.38)

G 16 26 0.04 0.55(0.31-0.99) 17 29 0.02 0.50(0.28-0.92) 16 26 0.03 0.53(0.3-0.97)

AA 70 56 NS 70 52 NS 71 55 NS AG 27 36 NS 27 38 NS 26 36 NS GG 3 8 NS 3 10 NS 3 9 NS

HLA-G (rs9380142) : RF status

RA: Rheumatoid Arthritis, YORA : young onset RA, RF : Rheumatoid Factor, Pc: Yates corrected P value, OR: odds ratio, 95% CI: 95% confidence interval. Pc values <0.05 were considered significant.

Frequency of HLA-G ‘A’ allele significantly higher in RF+ patients

Deforming RA (n=159)P Pc OR (95% CI)

RF+, (%) RF-, (%)

met 62(23) 19(35) NS

val 202(77) 35(65) NS

met/met 7(6) 1(4) NS

met/val 48(36) 17(63) 0.01 0.02 0.34 (0.13-0.86)

val/val 77(58) 9(33) 0.02 0.03 2.80 (1.09-7.59)

RF-Rheumatoid Factor, Pc-Yates corrected P value, OR-Odds ratio, 95% CI-95% confidence interval. Pc<0.05 is considered significant.

MICA-129 : RF status in deforming RA

MICA-129 val/val genotype associated with RF+ status in deforming RA

Soluble MICA levels, Cases vs. Controls  

RA: Rheumatoid Arthritis, HC: Healthy Control. Each symbol represents individual samples and horizontal lines show the mean values, Mann-Whitney test (two tailed) was used, p value <0.05 considered significant

sMICA levels significantly higher in RA patients vs. controls

MICA-129 : sMICA levels

MM: met/met, MV: met/val, VV: val/val. Each symbol represents individual samples and horizontal lines show the mean values, Mann-Whitney test (two tailed) was used, p value <0.05 considered significant

MICA-129 , val/val genotype associated with higher sMICA levels

TNFα -857 High titres (%) Low titres (%) P Pc OR (95% CI)Total RA n=28 n=230

C 79 89 0.02 0.03 0.44(0.21-0.97)

T 21 11 0.02 0.03 2.29(1.03-4.78)CC 64 80 0.07 NS

CT+TT 36 20 0.07 NSFemale RA n=26 n=207

C 79 90 0.02 0.03 0.41(0.19-0.95)

T 21 10 0.02 0.03 2.44(1.05-5.30)CC 65 81 0.07 NS

CT+TT 35 19 0.07 NSYORA n=28 n=216

C 79 90 0.01 0.02 0.41(0.19-0.91)

T 21 10 0.01 0.02 2.47(1.10-5.20)

CC 64 81 0.05 NS

CT+TT 36 19 0.05 NS

TNFα -857, : TNFa levels

. ‘T’ allele associated with high and ‘C’ allele with low serum levels of TNF-α

HLA-DQB1 : Treatment response

DQB1*03 allele more frequent in responders (good responders + remission)

DQB1*03 All RA, n=253 YORA, n=237 Female RA, n=247 DF RA, n=160

Good-Responders (%) 32 32 32 34

Non-Responders (%) 11 11 11 11

P 0.008 0.01 0.01 0.006

Pc 0.03 0.04 0.04 0.03

OR (95% CI) 3.8 (1.3-15.0) 3.7 (1.3-14.7) 3.7 (1.3-14.7) 4.1 (1.4-16.3)

Responders: >1.2 improvement in DAS28 score (good responders) and a DAS28 of ≤2.6 (remission), Non-responders: ≤0.6 change in DAS28 score or a change between 0.6 and 1.2 with DAS28 score >3.7 on follow up, RA: Rheumatoid Arthritis, YORA: young onset RA, DF: Deforming. Pc: Bonferroni correction for multiple alleles, OR: odds ratio, 95% CI: 95% confidence interval, Pc values <0.05 were considered significant.

HLA-E (rs1264457) GR, n=47 NR, n=13 P Pc OR (95% CI)$YORA (n=206) % %

*01:01 44 69 0.02 0.04 0.34(0.12-0.94)

*01:03 56 31 0.02 0.04 2.91(1.07-8.47)

*01:01/*01:01 15 46 0.02 0.04 0.20(0.04-0.99)

*01:01/*01:03 57 46 NS

*01:03/*01:03 28 8 NS

GR: good responders [>1.2 improvement in DAS28 score and a DAS of ≤2.6 (remission)], NR: non-responders [≤0.6 change in DAS score or a change between 0.6 and 1.2 with DAS score >3.7 on follow up], YORA: young onset RA, Pc: Yates corrected P value, OR: Odds ratio, 95% CI: 95% confidence interval. Pc<0.05 is considered significant.$ Response in YORA (n=206) group: GR-47, NR-13 and Moderate responders-146

HLA-E : Treatment response

HLA E*01:03 associated with good response to treatment with DMARDs

HLA-E : Treatment Response

HLA-E (rs1264457) GR, n=47 NR, n=13 P Pc OR (95% CI)*Total RA (n=213) n=46, % n=12, %*01:01 45 71 0.02 0.03 0.33(0.11-0.95)*01:03 55 29 0.02 0.03 3.02(1.06-9.39)*01:01/*01:01 15 50 0.01 0.03 0.18(0.04-0.91)*01:01/*01:03 59 42 NS*01:03/*01:03 26 8 NS#YORA (n=198) n=44, % n=12, %*01:01 43 71 0.02 0.03 0.31(0.10-0.90)*01:03 57 29 0.02 0.03 3.02(1.11-9.98)*01:01/*01:01 14 50 0.007 0.03 0.16(0.03-0.83)*01:01/*01:03 59 42 NS*01:03/*01:03 27 8 NS§Female RA (n=195) n=45, % n=12, %*01:01 44 71 0.02 0.04 0.33(0.11-0.95)*01:03 56 29 0.02 0.04 3.04(1.06-9.46)*01:01/*01:01 15 50 0.01 0.03 0.18(0.04-0.94)*01:01/*01:03 58 42 NS*01:03/*01:03 27 8 NS

HLA-E*01:01 allele & HLA-E*01:01/01:01 genotype associated with poor response

Part III : Summary

3. Genes influencing autoantibody production —HLA-DRB1*10:01, HLA-G ‘A’ allele & MICA-129 val/val genotype are associated with RF positivity

—Presence of HLA-G (rs9380142) AA genotype associated with RF positivity

—MICA-129 val/val genotype associated with RF positivity and high sMICA levels especially in patients with deforming disease

—Presence of the TNFα -857 ‘T’ allele associated with high circulating TNF-α levels

Part III : Summary

Results

Part IV : Construction of population specific haplotypes for HLA & non HLA

genes

DQB1-DRB1 RA, n=542 (%) HC, n=466 (%) P OR(95% CI)

05-10:01 95(18) 37(8) 6.8X10-6 2.46 (1.63-3.79)

05-14 26(5) 48(10) 8.4X10-4 0.44 (0.26-0.74)

06-13 19(4) 39(8) 9.5X10-4 0.40(0.21-0.72)

06-15 121(22) 79(17) 0.03 1.41(1.02-1.96)RA: Rheumatoid Arthritis, HC: Healthy control, OR: odds ratio, 95% CI: 95% confidence interval, P values <0.05 are considered significant

Haplotypes : HLA-DQB1-DRB1

— 47 haplotype combinations in 504 individuals (patients +controls)— 6 haplotypes were identified as major haplotypes (frequency >5)

Haplotypes DQB1*05-DRB1*10:01 & DQB1*06-DRB1*15 – RA susceptibilityHaplotypes DQB1*05-DRB1*14 & DQB1*06-DRB1*13 – Protective

― Haplotype constructed for 232 controls & 269 RA patients ― Seven haplotypes identified

Haplotype C-G-G more frequent in patients - susceptibility to RAHaplotype C-G-A & T-G-A was higher in controls - protective

Haplotype (1-2-3) RA, n=538 (%) HC, n=464 (%) P OR (95% CI)

C-G-G 429(80) 343(74) 0.03 1.39(1.02-1.89)T-G-G 61(11) 49(10.6) NSC-G-A 37(7) 50(10.6) 0.03 0.61(0.38-0.98)C-A-G 9(1.6) 8(1.7) NST-G-A 2(0.4) 8(1.7) 0.03 0.21(0.02-1.08)

T-A-G 0(0) 4(0.9) 0.03 0.00(0.00-1.30)C-A-A 0(0) 2(0.4) NS

Haplotypes : TNF-α

1-rs1799724, 2-rs1806629, 3- rs361525, RA: Rheumatoid Arthritis, HC: Healthy control, OR: odds ratio, 95% CI: 95% confidence interval, NS: Not significant. P values <0.05 are considered significant

― Haplotype constructed for 152 controls & 252 RA patients. ― Four haplotype combinations identified

Haplotypes frequency similar between patients and controls

Haplotype (1-2) RA, n=504 (%) HC, n=304 (%) P

01:01-T 191(38) 117(38) NS

01:01-C 59(12) 33(11) NS

01:03-T 208(41) 118(39) NS

01:03-C 46(9) 36(12) NS

1-rs1264457, 2-rs2844724, RA: Rheumatoid Arthritis, HC: Healthy control, NS: Not significant.

Haplotypes : HLA-E

― Haplotype constructed for 172 controls & 243 RA patients― Six different haplotypes identified

Haplotype Del-C-G higher in patients – Susceptibility to RAHaplotype Ins-C-G higher in controls – Protective

Haplotype(1-2-3) RA, n=486(%) HC, n=344(%) P OR (95% CI)

Ins-G-A 203(41.8) 129(37.5) NSDel-G-A 147(30.2) 116(33.7) NS

Ins-C-A 35(7.2) 20(5.8) NSDel-C-A 16(3.3) 18(5.2) NSIns-C-G 3(0.6) 30(8.7) 4x10-9 0.07(0.01-0.21)Del-C-G 82(16.9) 31(9.0) 0.001 2.05(1.30-3.29)

Haplotypes : HLA-G

1-rs66554220, 2-rs1063320, 3-9380142, RA: Rheumatoid Arthritis, HC: Healthy control, OR: odds ratio, 95% CI: 95% confidence interval, NS: Not significant, P values <0.05 are considered significant.

— Haplotypes constructed for 236 patients & 187 controls— Six different haplotypes identified

— Haplotype G-C-A-G-A-T-C-C higher in patients – Susceptibility to RA

Haplotypes : NK G2D

1-2-3-4-5-6-7-8-9 RA, n=472 (%) HC, n=296 (%) P OR (95% CI)C-G-G-Val-01:01-C-Ins-G-A 46(9.8) 18(6.1) 0.07 1.67(0.93-3.12)C-G-G-Val-01:03-T-Ins-G-A 21(4.5) 5(1.7) 0.04 2.71(0.98-9.29)C-G-G-Met-01:01-C-Ins-G-A 3(0.6) 7(2.4) 0.04 0.26(0.04-1.17)C-G-A-Met-01:03-T-Ins-G-A 2(0.4) 6(2) 0.03 0.21(0.02-1.16)C-G-A-Met-01:03-T-Del-G-A 4(0.85) 8(2.7) 0.04 0.31(0.07-1.16)T-G-G-Val-01:03-T-Del-G-A 11(2.3) 1(0.3) 0.03 7.04(1.0-304)

Haplotype (TNF-α-MICA-HLA-E-HLA-G)

Haplotypes C-G-G-Val-01:03-T-Ins-G-A and T-G-G-Val-01:03-T-Del-G-A associated with susceptibility to RA

Results

Part V : Assessment & characterization of cytokine gene expression profile & cytokine

levels

Cytokine Gene expression

— Higher expression of the pro-inflammatory IL-12p40 (Th1) (p=0.02) & TNF-α (p = 0.01) gene transcripts in patients

— Higher expression of IFNγ (p=0.03) gene transcripts in controls

RA: Rheumatoid Arthritis, HC: Healthy Controls, Each symbol represents individual samples and horizontal lines show the median values, Mann-Whitney test (two tailed) was used, p value <0.05 considered significant.

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RA: Rheumatoid Arthritis, HC: Healthy Controls, A) T-bet, B) GATA-3, and C) Foxp3, Each symbol represents individual samples and horizontal lines show the median values, Mann-Whitney test (two tailed) was used, p value <0.05 considered significant

Transcription factor Gene expression

Expression of transcription factors T-bet, GATA3 & FoxP3 higher in controls

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Circulating cytokine levels

— Circulating levels of measured cytokines (IFN-γ, IL-12p40, IL-4, TNF-α, IL-6, IL-17A and IL-10) higher in patients

Part V : Summary

1. Cytokine gene expression —Expression of transcription factors T-bet, GATA3 and FoxP3 higher in controls

—Higher expression of pro-inflammatory IL-12p40 (Th1) and TNF-α genes transcripts in patients

—Lower expression of anti-inflammatory IFN-γ and IL-10 gene in patients

2. Circulating cytokine levels —Plasma levels of all the measured cytokines (IFN-γ, IL-12p40, IL-4, IL-1β, TNF-α, IL-6, IL-17A and IL-10) were significantly higher in patients as compared to controls

TNF-α ---susceptibility & TNF-α titres

HLA-DR *13,*14 ---Protection HLA-DR *10:01 --- SusceptibilityHLA-DQ *03 --- Treatment response

MICA-129 val --- RA susceptibility, RF positivity, sMICA levels

HLA-E ---Treatment response

HLA-G --- autoantibody status

Chromosome 6 : Major findings

Chromosome 12 : Major findings

Deformities

― Our work identified genetic factors contributing to disease susceptibility & those capable of modulating/influencing the disease phenotype & treatment response

― Identified unique RISK haplotypes for RA suggesting that the genetic pool of South Indian Tamils may be different from other parts of the country and other populations of the world

― Confirmed the dysregulation of T cell subsets that may contribute to a chronic inflammatory state characteristic of RA

Conclusion

In the absence of comprehensive information on the genetics of RA, our data will serve as reference for future studies

Conclusion

Thank you

Thank You

Merci

Jawaharlal Institute of Postgraduate Medical Education & Research