Breathing New Life into Interstitial Lung Disease in Rheumatoid Arthritis

Clinical heterogeneity is a hallmark of many autoimmune disorders, and clinical or subclinical pulmonary involvement is a common extraarticular feature of the rheumatoid arthritis (RA) phenotype. High-resolution computed tomography reveals evidence of pulmonary abnormalities in more than half of patients with RA, and clinically significant interstitial lung disease (ILD) will develop in approximately 10% of patients.It is currently difficult to identify these patients and to intervene early in the clinical course of their lung disease

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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Identification of the NF-κB activating protein-like locus as a risk locus for rheumatoid arthritis

Objective: To fine-map the NF-κB activating protein-like (NKAPL) locus identified in a prior genome-wide study as a possible rheumatoid arthritis (RA) risk locus and thereby delineate additional variants with stronger and/or independent disease association. Methods: Genotypes for 101 SNPs across the NKAPL locus on chromosome 6p22.1 were obtained on 1368 Canadian RA cases and 1471 controls. Single marker associations were examined using logistic regression and the most strongly associated NKAPL locus SNPs then typed in another Canadian and a US-based RA case/control cohort. Results: Fine-mapping analyses identified six NKAPL locus variants in a single haplotype block showing association with p≤5.6×10−8 in the combined Canadian cohort. Among these SNPs, rs35656932 in the zinc finger 193 gene and rs13208096 in the NKAPL gene remained significant after conditional logistic regression, contributed independently to risk for disease, and were replicated in the US cohort (Pcomb=4.24×10−10 and 2.44×10−9, respectively). These associations remained significant after conditioning on SNPs tagging the HLA-shared epitope (SE) DRB1*0401 allele and were significantly stronger in the HLA-SE negative versus positive subgroup, with a significant negative interaction apparent between HLA-DRB1 SE and NKAPL risk alleles. Conclusions: By illuminating additional NKAPL variants with highly significant effects on risk that are distinct from, but interactive with those arising from the HLA-DRB1 locus, our data conclusively identify NKAPL as an RA susceptibility locus

European Population Substructure: Clustering of Northern and Southern Populations

Using a genome-wide single nucleotide polymorphism (SNP) panel, we observed population structure in a diverse group of Europeans and European Americans. Under a variety of conditions and tests, there is a consistent and reproducible distinction between “northern” and “southern” European population groups: most individual participants with southern European ancestry (Italian, Spanish, Portuguese, and Greek) have >85% membership in the “southern” population; and most northern, western, eastern, and central Europeans have >90% in the “northern” population group. Ashkenazi Jewish as well as Sephardic Jewish origin also showed >85% membership in the “southern” population, consistent with a later Mediterranean origin of these ethnic groups. Based on this work, we have developed a core set of informative SNP markers that can control for this partition in European population structure in a variety of clinical and genetic studies