METHODS: A multiplex analytic microarray system was used to analyze the occurrence of antibodies to 10 different citrullinated peptides (filaggrin [fil307-324], vimentin [Vim2-17, Vim60-75], fibrinogen [Fibα563-583, Fibα580-600, Fibβ36-52, Fibβ62-81a, Fibβ62-81b], enolase [Eno5-21], and type II collagen [CitCII355-378]) in serum samples from 4,089 RA patients (1,231 Malaysian and 2,858 Swedish) and 827 healthy control subjects (249 Malaysian and 578 Swedish). The positive reaction threshold for each peptide was set separately for each population based on a specificity of 98%.
RESULTS: Distinct differences in the frequencies of 5 ACPA fine specificities (Vim60-75, Vim2-17, Fibβ62-81b, Eno5-21, and CitCII355-378) were found between the Malaysian and Swedish RA populations, despite a nearly identical percentage of patients in each population who were positive for anti-cyclic citrullinated peptide 2 antibodies. In Malaysian RA patients compared with Swedish RA patients, the frequencies of antibodies to Vim60-75 (54% versus 44%, corrected P [Pcorr ] = 1.06 × 10-8 ) and CitCII355-378 (17% versus 13%, Pcorr = 0.02) were significantly higher, while the frequencies of antibodies to Vim2-17 (25% versus 32%, Pcorr = 1.91 × 10-4 ), Fibβ62-81b (15% versus 30%, Pcorr = 2.47 × 10-22 ), and Eno5-21 (23% versus 50%, Pcorr = 3.64 × 10-57 ) were significantly lower.
CONCLUSION: Serum ACPA fine specificities differ between RA patients in different populations, although the total proportions of individuals positive for ACPAs are similar. Differing patterns of ACPA fine specificity could be attributed to variations in genetic and/or environmental factors.
METHODS: We imputed the classical HLA alleles, amino acids, and haplotypes using the Immunochip genotyping data of 1260 RA cases (i.e., 530 Malays, 259 Chinese, 412 Indians, and 59 mixed ethnicities) and 1571 controls (i.e., 981 Malays, 205 Chinese, 297 Indians, and 87 mixed ethnicities) from the Malaysian Epidemiological Investigation of Rheumatoid Arthritis (MyEIRA) population-based case-control study. Stepwise logistic regression was performed to identify the independent genetic risk factors for RA within the HLA region.
RESULTS: We confirmed that the HLA-DRB1 amino acid at position 11 with valine residue conferred the strongest risk effect for ACPA-positive RA (OR = 4.26, 95% CI = 3.30-5.49, PGWAS = 7.22 × 10-29) in the Malays. Our study also revealed that HLA-DRB1 amino acid at position 96 with histidine residue was negatively associated with the risk of developing ACPA-positive RA in the Indians (OR = 0.48, 95% CI = 0.37-0.62, PGWAS = 2.58 × 10-08). Interestingly, we observed that HLA-DQB1*03:02 allele was inversely related to the risk of developing ACPA-positive RA in the Malays (OR = 0.17, 95% CI = 0.09-0.30, PGWAS = 1.60 × 10-09). No association was observed between the HLA variants and risk of developing ACPA-negative RA in any of the three major ethnic groups in Malaysia.
CONCLUSIONS: Our results demonstrate that the RA-associated genetic factors in the multi-ethnic Malaysian population are similar to those in the Caucasian population, despite significant differences in the genetic architecture of HLA region across populations. A novel and distinct independent association between the HLA-DQB1*03:02 allele and ACPA-positive RA was observed in the Malays. In common with the Caucasian population, there is little risk from HLA region for ACPA-negative RA.
METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.
RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.
CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.