Effective Sample Size: Quick Estimation of the Effect of Related Samples in Genetic Case-Control Association Analyses

Correlated samples have been frequently avoided in case-control
genetic association
 studies in part because the methods for handling them are either not
easily implemented or not widely known. We
advocate one method for case-control association analysis of correlated
samples -- the effective sample size method -- as a simple and
accessible approach that does not require specialized computer programs.
The effective sample size method captures the variance inflation
of allele frequency estimation exactly, and can be used to modify the
chi-square test statistic, p-value, and 95% confidence interval of
odds-ratio simply by replacing the apparent number of allele counts with the
effective ones. For genotype frequency estimation, although a single
effective sample size is unable to completely characterize the variance inflation,
an averaged one can satisfactorily approximate the simulated result.
The effective sample size method is applied to the rheumatoid arthritis
siblings data collected from the North American Rheumatoid Arthritis Consortium (NARAC)
to establish a significant association with the interferon-induced
helicasel gene (IFIH1) previously being identified as a type 1 diabetes
susceptibility locus. Connections between the effective sample size
method and other methods, such as generalized estimation equation,
variance of eigenvalues for correlation matrices, and genomic controls,
are also discussed.
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Data for Genetic Analysis Workshop 16 Problem 1, Association Analysis of Rheumatoid Arthritis Data

For Genetic Analysis Workshop 16 Problem 1, we provided data for genome-wide association analysis of rheumatoid arthritis. Single-nucleotide polymorphism (SNP) genotype data were provided for 868 cases and 1194 controls that had been assayed using an Illumina 550 k platform. In addition, phenotypic data were provided from genotyping DRB1 alleles, which were classified according to the rheumatoid arthritis shared epitope, levels of anti-cyclic citrullinated peptide, and levels of rheumatoid factor IgM. Several questions could be addressed using the data, including analysis of genetic associations using single SNPs or haplotypes, as well as gene-gene and genetic analysis of SNPs for qualitative and quantitative factors

Clinical and serological features of systemic sclerosis in a multicenter African American cohort: Analysis of the genome research in African American scleroderma patients clinical database.

Racial differences exist in the severity of systemic sclerosis (SSc). To enhance our knowledge about SSc in African Americans, we established a comprehensive clinical database from the largest multicenter cohort of African American SSc patients assembled to date (the Genome Research in African American Scleroderma Patients (GRASP) cohort).African American SSc patients were enrolled retrospectively and prospectively over a 30-year period (1987-2016), from 18 academic centers throughout the United States. The cross-sectional prevalence of sociodemographic, clinical, and serological features was evaluated. Factors associated with clinically significant manifestations of SSc were assessed using multivariate logistic regression analyses.The study population included a total of 1009 African American SSc patients, comprised of 84% women. In total, 945 (94%) patients met the 2013 American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) classification criteria for SSc, with the remaining 64 (6%) meeting the 1980 ACR or CREST (calcinosis, Raynaud's phenomenon, esophageal dysmotility, sclerodactyly, telangiectasia) criteria. While 43% were actively employed, 33% required disability support. The majority (57%) had the more severe diffuse subtype and a young age at symptom onset (39.1 ± 13.7 years), in marked contrast to that reported in cohorts of predominantly European ancestry. Also, 1 in 10 patients had a severe Medsger cardiac score of 4. Pulmonary fibrosis evident on computed tomography (CT) chest was present in 43% of patients and was significantly associated with anti-topoisomerase I positivity. 38% of patients with CT evidence of pulmonary fibrosis had a severe restrictive ventilator defect, forced vital capacity (FVC) ≤50% predicted. A significant association was noted between longer disease duration and higher odds of pulmonary hypertension, telangiectasia, and calcinosis. The prevalence of potentially fatal scleroderma renal crisis was 7%, 3.5 times higher than the 2% prevalence reported in the European League Against Rheumatism Scleroderma Trials and Research (EUSTAR) cohort.Our study emphasizes the unique and severe disease burden of SSc in African Americans compared to those of European ancestry

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, Genetic Causes of Rheumatoid Arthritis and Associated Traits

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted

Specificity of the STAT4 Genetic Association for Severe Disease Manifestations of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. A polymorphism in the STAT4 gene has recently been established as a risk factor for SLE, but the relationship with specific SLE subphenotypes has not been studied. We studied 137 SNPs in the STAT4 region genotyped in 4 independent SLE case series (total n = 1398) and 2560 healthy controls, along with clinical data for the cases. Using conditional testing, we confirmed the most significant STAT4 haplotype for SLE risk. We then studied a SNP marking this haplotype for association with specific SLE subphenotypes, including autoantibody production, nephritis, arthritis, mucocutaneous manifestations, and age at diagnosis. To prevent possible type-I errors from population stratification, we reanalyzed the data using a subset of subjects determined to be most homogeneous based on principal components analysis of genome-wide data. We confirmed that four SNPs in very high LD (r2 = 0.94 to 0.99) were most strongly associated with SLE, and there was no compelling evidence for additional SLE risk loci in the STAT4 region. SNP rs7574865 marking this haplotype had a minor allele frequency (MAF) = 31.1% in SLE cases compared with 22.5% in controls (OR = 1.56, p = 10−16). This SNP was more strongly associated with SLE characterized by double-stranded DNA autoantibodies (MAF = 35.1%, OR = 1.86, p<10−19), nephritis (MAF = 34.3%, OR = 1.80, p<10−11), and age at diagnosis<30 years (MAF = 33.8%, OR = 1.77, p<10−13). An association with severe nephritis was even more striking (MAF = 39.2%, OR = 2.35, p<10−4 in the homogeneous subset of subjects). In contrast, STAT4 was less strongly associated with oral ulcers, a manifestation associated with milder disease. We conclude that this common polymorphism of STAT4 contributes to the phenotypic heterogeneity of SLE, predisposing specifically to more severe disease

Brief Report: Deficiency of Complement 1r Subcomponent in Early-Onset Systemic Lupus Erythematosus: The Role of Disease-Modifying Alleles in a Monogenic Disease

Objective: To identify a genetic cause of early-onset systemic lupus erythematosus (SLE) in a large consanguineous family from Turkey and to study the mechanisms of the disease. Methods: We performed whole-exome sequencing and single-nucleotide polymorphism array genotyping in family members with and without SLE. Protein and gene expression, cytokine profile, neutrophil extracellular trap (NET) formation, and presence of low-density granulocytes were evaluated in patient primary cells and serum samples. Results: We identified a novel, homozygous, loss-of-function mutation (p.Pro445Leufs*11) in the C1R gene. Using the Sanger method of DNA sequencing in 14 family members, we confirmed the presence of the mutation in 4 patients with SLE and in an asymptomatic 9-year-old girl. Complement levels were low in sera from patients with truncated C1r protein. Two siblings with SLE who were available for detailed evaluation exhibited strong type I interferon (IFN) inflammatory signatures despite their disease being clinically inactive at the time of sampling. The type I IFN transcriptional signature in the patients’ blood correlated with disease expressivity, whereas the neutrophil signature in peripheral blood mononuclear cells was likely associated with disease severity. The female patient with SLE with the most severe phenotype presented with a stronger neutrophil signature, defined by enhanced NET formation and the presence of low-density granulocytes. Analysis of exome data for modifying alleles suggested enrichment of common SLE-associated variants in the more severely affected patients. Lupus-associated HLA alleles or HLA haplotypes were not shared among the 4 affected subjects. Conclusion: Our findings revealed a novel high-penetrance mutation in C1R as the cause of monogenic SLE. Disease expressivity in this family appears to be influenced by additional common and rare genetic variants

Genetic architecture distinguishes systemic juvenile idiopathic arthritis from other forms of juvenile idiopathic arthritis: Clinical and therapeutic implications

Objectives Juvenile idiopathic arthritis (JIA) is a heterogeneous group of conditions unified by the presence of chronic childhood arthritis without an identifiable cause. Systemic JIA (sJIA) is a rare form of JIA characterised by systemic inflammation. sJIA is distinguished from other forms of JIA by unique clinical features and treatment responses that are similar to autoinflammatory diseases. However, approximately half of children with sJIA develop destructive, long-standing arthritis that appears similar to other forms of JIA. Using genomic approaches, we sought to gain novel insights into the pathophysiology of sJIA and its relationship with other forms of JIA. Methods We performed a genome-wide association study of 770 children with sJIA collected in nine countries by the International Childhood Arthritis Genetics Consortium. Single nucleotide polymorphisms were tested for association with sJIA. Weighted genetic risk scores were used to compare the genetic architecture of sJIA with other JIA subtypes. Results The major histocompatibility complex locus and a locus on chromosome 1 each showed association with sJIA exceeding the threshold for genome-wide significance, while 23 other novel loci were suggestive of association with sJIA. Using a combination of genetic and statistical approaches, we found no evidence of shared genetic architecture between sJIA and other common JIA subtypes. Conclusions The lack of shared genetic risk factors between sJIA and other JIA subtypes supports the hypothesis that sJIA is a unique disease process and argues for a different classification framework. Research to improve sJIA therapy should target its unique genetics and specific pathophysiological pathways