Signer Rebecca, Seah Carina, Young Hannah, Retallick-Townsley Kayla, De Pins Agathe, Cote Alanna, Lee Seoyeon, Jia Meng, Johnson Jessica, Johnston Keira J A, Xu Jiayi, Brennand Kristen J, Huckins Laura M
Department of Psychiatry, Yale University School of Medicine, 34 Park Street, New Haven, CT 06520, USA.
Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029.
medRxiv. 2024 Nov 28:2024.11.26.24317923. doi: 10.1101/2024.11.26.24317923.
Genome-wide association studies identify common genomic variants associated with disease across a population. Individual environmental effects are often not included, despite evidence that environment mediates genomic regulation of higher order biology. Body mass index (BMI) is associated with complex disorders across clinical specialties, yet has not been modeled as a genomic environment. Here, we tested for expression quantitative trait (eQTL) loci that contextually regulate gene expression across the BMI spectrum using an interaction approach. We parsed the impact of cell type, enhancer interactions, and created novel BMI-dynamic gene expression predictor models. We found that BMI main effects associated with endocrine gene expression, while interactive variant-by-BMI effects impacted gene expression in the brain and gut. Cortical BMI-dynamic loci were experimentally dysregulated by inflammatory cytokines in an system. Using BMI-dynamic models, we identify novel genes in nitric oxide signaling pathways in the nucleus accumbens significantly associated with depression and smoking. While neither genetics nor BMI are sufficient as standalone measures to capture the complexity of downstream cellular consequences, including environment powers disease gene discovery.
全基因组关联研究可识别出与人群中疾病相关的常见基因组变异。尽管有证据表明环境介导了高阶生物学的基因组调控,但个体环境效应通常未被纳入考虑。体重指数(BMI)与各个临床专科的复杂疾病相关,但尚未被建模为一种基因组环境。在此,我们使用一种交互作用方法,对在整个BMI范围内上下文调控基因表达的表达数量性状(eQTL)位点进行了检测。我们剖析了细胞类型、增强子相互作用的影响,并创建了新的BMI动态基因表达预测模型。我们发现BMI的主效应与内分泌基因表达相关,而BMI与变异的交互效应则影响大脑和肠道中的基因表达。在一个系统中,皮质BMI动态位点在实验上被炎性细胞因子失调。利用BMI动态模型,我们在伏隔核中一氧化氮信号通路中识别出与抑郁症和吸烟显著相关的新基因。虽然遗传学和BMI作为单独的测量方法都不足以捕捉下游细胞后果的复杂性,但纳入环境因素有助于疾病基因的发现。