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Am J Hum Genet ; 100(6): 865-884, 2017 Jun 01.
Artículo en Inglés | MEDLINE | ID: mdl-28552196

RESUMEN

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.


Asunto(s)
Antropometría , Genoma Humano , Estudio de Asociación del Genoma Completo , Sitios de Carácter Cuantitativo/genética , Análisis de Secuencia de ADN/métodos , Estatura/genética , Estudios de Cohortes , Metilación de ADN/genética , Bases de Datos Genéticas , Femenino , Variación Genética , Humanos , Lipodistrofia/genética , Masculino , Metaanálisis como Asunto , Obesidad/genética , Mapeo Físico de Cromosoma , Caracteres Sexuales , Síndrome , Reino Unido
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