Myhre, R. | Search bioRxiv

bioRxiv2024

Associations between common genetic variants and income provide insights about the socioeconomic health gradient

We conducted a genome-wide association study (GWAS) on income among individuals of European descent and leveraged the results to investigate the socio-economic health gradient (N=668,288). We found 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes. Our GWAS-derived polygenic index captures 1 - 4% of income variance, with only one-fourth attributed to direct genetic effects. A phenome-wide association study using this polygenic index showed reduced risks for a broad spectrum of diseases, including hypertension, obesity, type 2 diabetes, coronary atherosclerosis, depression, asthma, and back pain. The income factor showed a substantial genetic correlation (0.92, s.e. = .006) with educational attainment (EA). Accounting for EAs genetic overlap with income revealed that the remaining genetic signal for higher income related to better mental health but reduced physical health benefits and increased participation in risky behaviours such as drinking and smoking.

genetics↗

bioRxiv2017

Maternal and fetal genetic contribution to gestational weight gain

BackgroundClinical recommendations to limit gestational weight gain (GWG) imply high GWG is causally related to adverse outcomes in mother or offspring, but GWG is the sum of several inter-related complex phenotypes (maternal fat deposition and vascular expansion, placenta, amniotic fluid and fetal growth). Understanding the genetic contribution to GWG could help clarify the potential effect of its different components on maternal and offspring health. Here we explore the genetic contribution to total, early and late GWG.\n\nParticipants and MethodsA genome-wide association study was used to identify maternal and fetal variants contributing to GWG in up to 10,543 mothers and up to 16,317 offspring of European origin, with replication in 10,660 mothers and 7,561 offspring. Additional analyses determined the proportion of variability in GWG from maternal and fetal common genetic variants and the overlap of established genome-wide significant variants for phenotypes relevant to GWG (e.g. maternal BMI and glucose, birthweight).\n\nResultsWe found that approximately 20% of the variability in GWG was tagged by common maternal genetic variants, and that the fetal genome made a surprisingly minor contribution to explaining variation in GWG. We were unable to identify any genetic variants that reached genome-wide levels of significance (P<5x10-8) and replicated. Some established maternal variants associated with increased BMI, fasting glucose and type 2 diabetes were associated with lower early, and higher later GWG. Maternal variants related to higher systolic blood pressure were related to lower late GWG. Established maternal and fetal birthweight variants were largely unrelated to GWG.\n\nConclusionWe found a modest contribution of maternal common variants to GWG and some overlap of maternal BMI, glucose and type 2 diabetes variants with GWG. These findings suggest that associations between GWG and later offspring/maternal outcomes may be due to the relationship of maternal BMI and diabetes with GWG.

genetics↗