Obesity is a major risk factor for a myriad of diseases, affecting >600 million people worldwide. Genome-wide association studies (GWASs) have identified hundreds of genetic variants that influence body mass index (BMI), a commonly used metric to assess obesity risk. Most variants are non-coding and likely act through regulating genes nearby. Here, we apply multiple computational methods to prioritize the likely causal gene(s) within each of the 536 previously reported GWAS-identified BMI-associated loci. We performed summary-data-based Mendelian randomization (SMR), FINEMAP, DEPICT, MAGMA, transcriptome-wide association studies (TWASs), mutation significance cutoff (MSC), polygenic priority score (PoPS), and the nearest gene strategy. Results of each method were weighted based on their success in identifying genes known to be implicated in obesity, ranking all prioritized genes according to a confidence score (minimum: 0; max: 28). We identified 292 high-scoring genes (≥11) in 264 loci, including genes known to play a role in body weight regulation (e.g., , , , , , , , , ) and genes related to comorbidities (e.g., , , , , , ). For most of the high-scoring genes, however, we found limited or no evidence for a role in obesity, including the top-scoring gene . Many of the top-scoring genes seem to act through a neuronal regulation of body weight, whereas others affect peripheral pathways, including circadian rhythm, insulin secretion, and glucose and carbohydrate homeostasis. The characterization of these likely causal genes can increase our understanding of the underlying biology and offer avenues to develop therapeutics for weight loss.

中文翻译：

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一个综合框架，可对 500 多个与体重指数相关的基因座中的基因进行优先排序


肥胖是多种疾病的主要危险因素，影响着全球超过 6 亿人。全基因组关联研究 (GWAS) 已经确定了数百种影响体重指数 (BMI) 的遗传变异，BMI 是评估肥胖风险的常用指标。大多数变体都是非编码的，可能通过调节附近的基因发挥作用。在这里，我们应用多种计算方法来优先考虑 536 个先前报告的 GWAS 识别的 BMI 相关位点中每个可能的因果基因。我们进行了基于汇总数据的孟德尔随机化 (SMR)、FINEMAP、DEPICT、MAGMA、全转录组关联研究 (TWAS)、突变显着性截断 (MSC)、多基因优先评分 (PoPS) 和最近基因策略。每种方法的结果根据其在识别已知与肥胖有关的基因方面的成功程度进行加权，并根据置信度得分（最小值：0；最大值：28）对所有优先基因进行排序。我们在264个位点中鉴定了292个高分基因（≥11），包括已知在体重调节中发挥作用的基因（例如，，，，，，，，，，，，，）和与合并症相关的基因（例如，，，，，， , )。然而，对于大多数高分基因，包括最高分基因，我们发现有限或没有证据表明它们在肥胖中起作用。许多得分最高的基因似乎通过体重的神经元调节发挥作用，而其他基因则影响外周通路，包括昼夜节律、胰岛素分泌以及葡萄糖和碳水化合物稳态。这些可能的因果基因的表征可以增加我们对潜在生物学的理解，并为开发减肥疗法提供途径。