Authors

Samira Asgari, Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Yang Luo, Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Ali Akbari, Broad Institute of MIT and Harvard
Gillian M. Belbin, The Institute for Genomic Health
Xinyi Li, Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Daniel N. Harris, University of Maryland School of Medicine
Martin Selig, Pathology Service, Massachusetts General Hospital, Harvard Medical School, Boston, USA
Eric Bartell, Broad Institute of MIT and Harvard
Roger Calderon, Socios En Salud, Lima, Peru
Kamil Slowikowski, Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Carmen Contreras, Socios En Salud, Lima, Peru
Rosa Yataco, Socios En Salud, Lima, Peru
Jerome T. Galea, University of South FloridaFollow
Judith Jimenez, Socios En Salud, Lima, Peru
Julia M. Coit, Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Chandel Farroñay, Socios En Salud, Lima, Peru
Rosalynn M. Nazarian, Pathology Service, Massachusetts General Hospital, Harvard Medical School, Boston, USA
Timothy D. O’Connor, University of Maryland School of Medicine
Harry C. Dietz, Johns Hopkins University School of Medicine
Joel N. Hirschhorn, Broad Institute of MIT and Harvard
Heinner Guio, Instituto Nacional de Salud, Lima, Peru
Leonid Lecca, Socios En Salud, Lima, Peru
Eimear E. Kenny, The Institute for Genomic Health
Esther E. Freeman, Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
Megan B. Murray, Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
Soumya Raychaudhuri, Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA

Document Type

Article

Publication Date

2020

Keywords

Evolutionary biology, Genetic variation, Genome-wide association studies

Digital Object Identifier (DOI)

https://doi.org/10.1038/s41586-020-2302-0

Abstract

On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru. In an ethnically diverse group of Peruvian individuals, the population-specific, missense variant in FBN1 (E1297G) is associated with lower height and shows evidence of positive selection within the Peruvian population.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

Nature, v. 582, p. 234-239

This is an accepted manuscript of an article published by Nature Research in Nature. The final authenticated version is available online at:

Included in

Social Work Commons

Share

COinS