In Nature this week, researchers at the Stanford University School of Medicine along with their colleagues at the Albert Einstein College of Medicine report that "chromatin regulation by Brg1 underlies heart muscle development and disease." Specifically, the team shows that the chromatin-remodeling protein Brg1 "has a critical role in regulating cardiac growth, differentiation, and gene expression," and that it maintains cardiomyocytes in an embryonic state. The authors suggest that Brg1 cooperates with HDAC and PARP to control both developmental and pathological gene expression.
An international research team presents the results of their genome-wide association study of alopecia areata, a prevalent human autoimmune disease, which implicate both innate and acquired immunity. By interrogating 1,054 cases and 3,278 controls, the team initially identified 139 SNPs associated with AA. They also "show an association with genomic regions containing several genes controlling the activation and proliferation of regulatory T cells," and suggest that their work defines the "genetic underpinnings of AA placing it within the context of shared pathways among autoimmune diseases, and implicating a novel disease mechanism ... in triggering autoimmunity."
In another GWAS analysis, appearing in the most recent issue of Nature Genetics, Benjamin Voight at the Broad Institute and an extensive set of co-authors report 12 type II diabetes susceptibility loci, which they've identified by combining data from 8,130 cases and close to 40,000 controls. Among the 12 loci is a second independent signal at the KCNQ1 locus, "the first report, to our knowledge of an X-chromosomal association," near DUSP9, and an overlap between loci "implicated in monogenic and multifactorial forms of diabetes," at HNF1A, the authors write.
And in the most recent publication of Nature Reviews Genetics, Alkes Price of the Broad and Harvard and his colleagues suggest "new approaches to population stratification in genome-wide association studies," in an effort to reduce errors that confound study results. They review "recent progress on methods that correct for stratification while accounting for these additional complexities."