Ludwig-Słomczyńska Agnieszka H, Seweryn Michał T, Kapusta Przemysław, Pitera Ewelina, Mantaj Urszula, Cyganek Katarzyna, Gutaj Paweł, Dobrucka Łucja, Wender-Ożegowska Ewa, Małecki Maciej T, Wołkow Paweł P
Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kraków, Poland.
Department of Cancer Biology and Genetics, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Mol Med. 2021 Jan 20;27(1):6. doi: 10.1186/s10020-020-00266-z.
Clinical 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.
We 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 (1 Mb around identified loci) with the mentioned phenotypes.
In Analysis 1 we have found 175 BMI associated genes and 19 variants (p < 10) 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) 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.
Here, 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.
临床数据表明,体重指数(BMI)和孕期体重增加(GWG)是紧密相关的表型;然而,后者的遗传基础尚不清楚。在此,我们旨在寻找影响BMI和/或GWG的基因及遗传变异。
我们使用Illumina Infinium Omni Express Exome-8 v1.4芯片对316例1型糖尿病患者进行了基因分型。GIANT、ARIC和T2D-GENES汇总统计数据用于在脂肪组织中进行全转录组关联研究(TWAS,使用PrediXcan进行)。接下来,在普通人群和糖尿病队列中进行了推断表达与BMI的关联分析(分析1和2)或与GWG的关联分析(分析3和4),随后对上述表型进行了变异关联分析(在已识别位点周围1 Mb范围内)。
在分析1中,我们发现了175个与BMI相关的基因和19个影响GWG的变异(p < 10),其中CCL24基因中的rs11465293关联最强(p = 3.18E-06)。分析2将糖尿病纳入模型后,发现了1812个与BMI相关的位点和207个影响GWG的变异(p < 10),其中PODXL基因中的rs9690213关联最强(p = 9.86E-07)。在分析3中,在648个与GWG相关的位点中,有2091个变异与BMI相关(错误发现率< 0.05)。在分析4中,GWG相关位点中的7个变异在ARIC队列中影响BMI。
在此,我们表明,在普通人群和1型糖尿病队列中,影响BMI的位点可能对GWG有影响,而与GWG相关的位点可能影响BMI。结果表明,这两种表型均与胰岛素信号传导、葡萄糖稳态、线粒体代谢、泛素化和炎症反应有关。