The present study is the first largest GWAS cohort conducted among Thai SLE patients. We found the association in the HLA class II region (HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DRB5, HLA-DRB9, and HLA-DRA) as the highest significant association in both independent groups and meta-analysis. These results were consistent with previous reports in SLE patients from other ethnic groups [27]. Since there are vast differences of HLA-class II allele frequency among populations and sophisticated genetic structure of the HLA-class II allele, the study of the specific haplotype is needed. There were two publications reported about specific HLA-class II alleles in Thai SLE patients. First, the fine genetic mapping of the HLA allele from SLE patients in the northern part of Thailand has identified the association of HLA-DRB5*01:01 and HLA-DRB1*16:02 [30]. In the following, HLA haplotype analysis found HLA-DRB1*15:02 and HLA-DRB1*05:01 associated with Thai SLE patients [31]. None of the studies has been fully characterized specific HLA haplotypes in the Thai population. Further study on the HLA class II allele using whole genome sequencing or exome sequencing might be useful to specify the impact of the HLA-class II allele on SLE pathogenesis.
Apart from the HLA-class II alleles, our study found variants in STAT4, GTF2I, and BLK regions. For BLK locus, this gene encoded for Src-tyrosine kinase, which is an important signalling molecule under B-cell development [32]. This gene showed protein-protein interaction with BANK1 (B-cell specific cytoplasmic protein involved in B-cell receptor signalling) and might plausibly involve in dysregulation of the B-cell receptor, which is a common feature found in SLE patients [33]. For STAT4 and GTF2I alleles, these genes are encoded for the transcription factors that mediate many immune-related genes and inflammatory cytokines transcription machinery. Both BLK and STAT4 loci have been reported as SLE susceptible alleles in Thai SLE patients recently [7], whereas GTF2I locus has firstly identified in our study. Interestingly, the variants on STAT4 and GTF2I loci were correlated with lupus nephritis (LN) in the various SLE ancestries [29]. The GTF2I allele was likely to specific in Asian background, especially Han Chinese [34]. Our analysis found several LN-susceptible loci such as IRF5 [35, 36], ITGAM [9, 37], IKZF1 [38], and TNFSF4 [39]. While IKZF1 is a co-transcription factor with STAT-4 mediated Th1 lymphocyte differentiation and interferon pathways [40], the TNFSF4 locus, also called OX40L, encoded for the TNF superfamily ligand, which actively stimulates CD4 + T-cells activation [39]. Study in the Finnish and Swedish SLE patients found the correlation of ITGAM with cutaneous discoid lupus erythematosus (DLE) and LN as well as Ro/SSA auto-antibody positive [41]. Not only LN, but we also found several loci that have been verified in the specific sub-phenotype of SLE patients. For example, our result found a variant on ETS1, which previously showed association with juvenile SLE, as well as a variant on RasGRP3, which was involved in malar rash or discoid rash [38]. The recent SLE susceptible loci identified in the cardiac manifestation of neonatal lupus, NOTCH4, was found in our results [42].
Note that we found some of the known SNPs which are nonsynonymous variants such as NCF2 [43], IFIH1 [44], TNFAIP3 [45], UHRF1BP1[46], ATG16L2 [47], and PLD4 [48]. A few pieces of evidence have revealed the impact of those variants on various pathways including, neutrophil extracellular traps (NETs) formation [49], sensor molecule to detect viral genome inside cells [50], a negative regulator for NF-kB transcription factors [51], a negative regulator of cell growth [52]. These pathways resembled with our functional enrichment pathways analysis. Interestingly, our results found extracellular matrix organization (ECM) pathways associated with Thai SLE patients. Previously, single-cell transcriptome analysis in non-responder LN patients highlighted the upregulated genes in the ECM pathway correlated with treatment failure [53]. The ECM reflected the active fibrotic process, and tubulointerstitial fibrosis is a marker of poor prognosis for LN [54]. Remarkably, the prevalence of severe LN was high in the South East Asian ethnic included Thai [55]. Thus, our results supported that genetic background was a pivotal factor driving a severe LN among Thai SLE patients. Taken together, these pieces of evidence could justify the link between genetic variants and clinical involvement in Thai SLE patients. As our study used a mixed population model analysis (Fast-LMM platform), we did not characterize the heterogeneity of our sample. We, therefore, aimed for further investigation using subpopulation stratification to determine populations heterogeneity and identified the genetic association with specific clinical manifestations.
The study of known SNPs showed most of the polymorphisms resembled with previous reports in Thais, such as ARID5B, TNFSF4, BANK1, TNFAIP3, CXCR5 SLC15A, ITGAM, WDFY4, ETS1, and BLK [7–11]. It confirmed that our analysis processes were reliable. Noticeably, The allele frequency of ITGAM was higher among Thai SLE when compared to Chinese Hong Kong [9], but has no association with Japanese and Korean background [56]. Thus, this implies the specificity of these variants to the Thai SLE patients. Although we did not recognize polymorphisms on chromosome 11q23.3 (rs11603023 on PHLDB1 and rs638893 on DDX6), which has been identified in the Thais' SLE, our meta-analysis enhanced signal from rs10845606 on GPR19 allele which does not correlate with Thai SLE patients previously [8].
It is noteworthy that meta-analysis in the Thai population discovered novel SLE susceptible variants on FBN2. The FBN2 allele is located on a chromosome 5 encoded protein called fibrillin-2 [57]. Fibrillins are a primary extracellular backbone structure of connective tissue microfibrils [58]. Fibrillins are composed of two subtypes, including fibrillin-1 and fibrillin-2. Mutation of both genes leads to Musculo-skeleton tissue disorders, which are typical features in the SLE [58]. Recently, studies in Chinese and Turkish SLE patients found the mutation of FBN2 was a marker for congenital contractural arachnoldactyly (CCA) or Beals syndrome, a rare autosomal dominant congenital connective tissue disorder [57, 59, 60]. Although none of the evidence has been identified FBN2 as SLE susceptible allele, pristane induced spontaneous LN developed mouse model (SWR X NZB1 F1) demonstrated the upregulation of FBN2 correlated with fibrosis prevalence [61]. Besides, the fibrillin-2 protein showed modulation effects on the concentration, presentation, and activation (bioavailability) of transforming growth factor β (TGF-β) and bone morphogenic protein (BMP) complexes, which is crucial for the fibrosis formation [62]. Moreover, this variant was predicted to disturb methylation capping and enhancer marker, incorporating with the evidence from genetic inheritance model analysis, we hypothesized that this variant might lead to overexpression of fibrillin-2 proteins involving in the musculoskeletal system disorder in the SLE patients. As discussed above, variants found in the FBN2 allele showed the possible risk associated with the Thai SLE patients; however, a further experiment in the larger cohort is necessary.
Furthermore, there were few low significant value variants (p-value < 10E-05) on loci, including ATP6V1B1, MYO5C, MIR4472-2, ADCY5, and DGKG. For ATP6V1B1 locus, a case report from primary distal renal tubular acidosis (dRTA) patients showed mutation of this gene affected the H (+) ion secretion in the collecting duct [63]. It is therefore suspected that variants on ATP6V1B1 might involve with kidney function in the Thai SLE patients. For MYO5C, the gene encodes myosin protein, which plays a vital role in muscle contraction. A piece of evidence in dermatomyositis, a rare autoimmune disease with muscle inflammation, showed that MYO5C was interferon-signature genes and might be associated with muscle inflammation [64]. The ADCY5 genes are encoded enzymes called adenylate cyclase, which changes ATP to cAMP [65]; meanwhile, DGKG is responsible for lipid metabolisms and cell cycle regulation [66]. Both genes were upregulated in Genome-wide DNA methylation in CD4 + T cells case-control study of SLE patients [67]. The mutation of ADCY5 has been associated with movement disorder in paediatric patients [65], while DGKG was reported as a phospholipid-binding protein associated with neuronal function [66]. Regards to accumulating data suggested that polymorphisms found in these loci might have downstream clinical implication in Thai SLE patients; however, the experimental confirmations are needed.
Note that some of the variants were previously characterized in other autoimmune diseases, including rheumatoid arthritis and primary Sjögren Syndrome (pSS). It, therefore, indicates the sharing of underlying genetic factors between autoimmune disease. However, predisposing factors which could affect clinical manifestation driving different autoimmune disease outcome has not been elucidated yet. Recently, the GRS (genetic risk score) has been widely adopted to predict disease outcomes from genetic variants [68]. The previous studies in SLE showed that overall mortality was higher in the striking GRS SLE patients; also, the high cumulative genetic risk could predict the specific organ damages such as proliferative nephritis and cardiovascular disease [69]. Our study showed a high sensitivity for using polygenic risk scored as a marker for SLE disease development in the Thai population. It is exciting for further study to calculate the genetics risk score and specific clinical manifestation among Thai SLE patients.