Diaz, R. | bioRxiv Science

bioRxiv2018

The Portal Project: a long-term study of a Chihuahuan desert ecosystem

This is a data paper for the Portal Project, a long-term ecological study of rodents, plants, and ants located in southeastern Arizona, U.S.A. This paper contains an overview of methods and information about the structure of the data files and the relational structure among the files. This is a living data paper and will be updated with new information as major changes or additions are made to the data. All data - along with more detailed data collection protocols and site information - is archived at: https://doi.org/10.5281/zenodo.1215988.

ecology↗

bioRxiv2017

Penetrance of polygenic obesity susceptibility loci across the body mass index distribution: an update on scaling effects.

A growing number of single nucleotide polymorphisms (SNPs) have been associated with body mass index (BMI) and obesity, but whether the effect of these obesity susceptibility loci is uniform across the BMI distribution remains unclear. We studied the effects of 37 BMI/obesity-associated SNPs in 75,230 adults of European ancestry along BMI percentiles using conditional quantile regression (CQR) and meta-regression (MR) models. The effects of 9 SNPs (24%) increased significantly across the sample BMI distribution including, FTO (rs1421085, p=8.69x10-15), PCSK1 (rs6235, p=7.11x10-06), TCF7L2 (rs7903146, p=9.60x10-06), MC4R (rs11873305, p=5.08x10-05), FANCL (rs12617233, p=5.30x10-05), GIPR (rs11672660, p=1.64x-04), MAP2K5 (rs997295, p=3.25x10-04), FTO (rs6499653, p=6.23x10-04) and NT5C2 (rs3824755, p=7.90x10-04). We showed that such increases stem from unadjusted gene interactions that enhanced the effects of SNPs in persons with high BMI. When 125 height-associated were analyzed for comparison, only one (<1%), IGF1 (rs6219, p=1.80x10-04), showed effects that varied significantly across height percentiles. Cumulative gene scores of these SNPs (GS-BMI and GS-Height, respectively) showed that only GS-BMI had effects that increased significantly across the sample distribution (BMI: p=7.03x10-37, Height: p=0.499). Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method to detect such interactions using only the sample outcome distribution.

genetics↗