A method for inferring genotype-by-environment interactions (GEIs) from genetic variants associated with phenotypic variability in large samples, without the need for measuring environmental factors, is presented in Science Advances this week. A University of Brisbane-led team conducted a genome-wide variance quantitative trait locus analysis for 13 quantitative traits in 348,501 unrelated individuals using the UK Biobank database, finding 75 significant vQTLs for 9 traits, particularly ones related to obesity. "Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects," they write. "Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data."
A genome-wide association study published in Science Translational Medicine this week identifies two genetic mutations tied to Alzheimer's disease risk. The study's authors analyzed concentrations of soluble triggering receptor expressed on myeloid cells 2 (sTREM2) — a glycoprotein member of the immunoglobulin superfamily that has been associated with AD — in cerebrospinal fluid samples from 813 people in a large AD clinical database. They find one variant in the MS4A gene region associated with higher concentrations of CSF sTREM2 and a lower risk of AD, as well as another associated with lower CSF sTREM2 concentrations, a higher risk of AD, and an earlier onset of disease. The investigators replicated the findings in additional samples from AD patients and healthy controls, and find that silencing a specific gene within the MS4A subfamily in human macrophages led to lower levels of sTREM2 released by the cells.