Molecular MedicineGenetic & Genomic MedicinePeer-reviewed journal article
The transcriptome-wide association search for genes and genetic variants which associate with BMI and gestational weight gain in women with type 1 diabetes
Agnieszka H. Ludwig‐SłomczyńskaiD, Michał T. SeweryniD, Przemysław KapustaiD, Ewelina PiteraiD, Urszula MantajiD, Katarzyna CyganekiD, Paweł GutajiD, Łucja DobruckaiD, Ewa Wender-OżegowskaiD, Maciej Tadeusz MaleckiiD, Paweł P. WołkowiD
Abstract
BackgroundClinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes, however the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG. MethodsWe have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1Mb around identified loci) with the mentioned phenotypes. ResultsIn Analysis 1 we have found 175 BMI associated genes and 19 variants (p<10-4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p=3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p<10-4) influencing GWG, with the strongest association for rs9690213 in PODXL (p=9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR<0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort. ConclusionsHere, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.
- organism: human
- assay: GWAS summary statistics
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 8
- FWCI
- 0.42
- Field percentile
- top 45%
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