作者
So–Youn Shin,Eric B. Fauman,Ann-Kristin Petersen,Jan Krumsiek,Rita Santos,Jie Huang,Matthias Arnold,Idil Erte,Vincenzo Forgetta,Tsun-Po Yang,Klaudia Walter,Cristina Menni,Lu Chen,Louella Vasquez,Ana M. Valdes,Craig Hyde,Vicky Wang,Daniel Ziemek,Phoebe M. Roberts,Xi Li,Elin Grundberg,Melanie Waldenberger,J. Brent Richards,Robert P. Mohney,Michael V. Milburn,Sally John,Jeff K. Trimmer,Fabian J. Theis,John P. Overington,Karsten Suhre,M. Julia Brosnan,Christian Gieger,Gabi Kastenmüller,Tim D. Spector,Nicole Soranzo
摘要
Nicole Soranzo, Tim Spector, Gabi Kastenmüller and colleagues report a large-scale analysis of genetic variants influencing human blood metabolite levels. They identify genome-wide significant associations at 145 loci, providing a framework for exploring relationships between genetic variation, metabolism and complex disease. Genome-wide association scans with high-throughput metabolic profiling provide unprecedented insights into how genetic variation influences metabolism and complex disease. Here we report the most comprehensive exploration of genetic loci influencing human metabolism thus far, comprising 7,824 adult individuals from 2 European population studies. We report genome-wide significant associations at 145 metabolic loci and their biochemical connectivity with more than 400 metabolites in human blood. We extensively characterize the resulting in vivo blueprint of metabolism in human blood by integrating it with information on gene expression, heritability and overlap with known loci for complex disorders, inborn errors of metabolism and pharmacological targets. We further developed a database and web-based resources for data mining and results visualization. Our findings provide new insights into the role of inherited variation in blood metabolic diversity and identify potential new opportunities for drug development and for understanding disease.