Dietary intake is a major contributor to the global obesity epidemic and represents a complex behavioural phenotype that is partially affected by innate biological differences. Here, we present a multivariate genome-wide association analysis of overall variation in dietary intake to account for the correlation between dietary carbohydrate, fat and protein in 282,271 participants of European ancestry from the UK Biobank (n = 191,157) and Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 91,114), and identify 26 distinct genome-wide significant loci. Dietary intake signals map exclusively to specific brain regions and are enriched for genes expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons. We identified two main clusters of genetic variants for overall variation in dietary intake that were differently associated with obesity and coronary artery disease. These results enhance the biological understanding of interindividual differences in dietary intake by highlighting neural mechanisms, supporting functional follow-up experiments and possibly providing new avenues for the prevention and treatment of prevalent complex metabolic diseases.

膳食摄入是全球肥胖流行的主要原因，代表了一种复杂的行为表型，部分受先天生物学差异的影响。在这里，我们对来自英国生物库 ( n  = 191,157) 和心脏与衰老队列的 282,271 名欧洲血统参与者的膳食摄入总体变化进行了多变量全基因组关联分析，以解释膳食碳水化合物、脂肪和蛋白质之间的相关性基因组流行病学联盟研究（n = 91,114)，并识别出 26 个不同的全基因组重要位点。饮食摄入信号专门映射到特定的大脑区域，并丰富了在 GABA 能、多巴胺能和谷氨酸能神经元的特殊亚型中表达的基因。我们确定了饮食摄入总体变异的两个主要遗传变异群，它们与肥胖和冠状动脉疾病的相关性不同。这些结果通过突出神经机制、支持功能性后续实验并可能为预防和治疗流行的复杂代谢疾病提供新途径，增强了对膳食摄入个体差异的生物学理解。