My NCBI Sign In
Jump to: Authorized Access | Attribution | Authorized Requests

Study Description

This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, one called Freeze 4 (GRCh37) and another called Freeze 5b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, "TOPMed Whole Genome Sequencing Project - Freeze 4, Phase 1" and "TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession.

The individuals sequenced here represent a small subset of the parent study (described below) and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing.

The research goal of the parent study (dbGaP ID phs000914) is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.

  • Study Types: Cross-Sectional, Population
  • dbGaP estimated ancestry components using GRAF-pop
  • Number of study subjects that have individual level data available through Authorized Access: 1332

Authorized Access
Publicly Available Data (Public ftp)

Connect to the public download site. The site contains release notes and manifests. If available, the site also contains data dictionaries, variable summaries, documents, and truncated analyses.

Study Inclusion/Exclusion Criteria

Participants were eligible for inclusion in the parent study (from which these sequenced individuals were selected) if they self-reported having four Samoan grandparents, if they were 23-70 years of age, not pregnant, able to complete questionnaires and anthropometric measures, and able and willing to complete the interview portions of the study in Samoan. For more detail, please see the following publication, which describes the origin of the parent dataset: Hawley NL, Minster RL, Weeks DE, Viali S, Reupena MS, Sun G, Cheng H, Deka R, McGarvey ST. Prevalence of Adiposity and Associated Cardiometabolic Risk Factors in the Samoan Genome-Wide Association Study. Am J Human Biol 2014. 26: 491-501. DOI: 10.1002/jhb.22553. PMID: 24799123. PMCID: PMC4292846. The individuals sequenced here represent a subset of the parent study and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing.

Molecular Data
TypeSourcePlatformNumber of Oligos/SNPsSNP Batch IdComment
Whole Genome Sequencing Illumina HiSeq X Ten N/A N/A Sequencing was performed at the Northwest Genomics Center at the University of Washington and at the New York Genome Center
Study History

Samoans have been studied for >40 years with a focus on the increase in, and levels of, BMI, obesity, and associated cardiometabolic conditions due to economic modernization. Earlier studies focused on these broad environmental influences but the current team of investigators began genetic epidemiology studies of Samoan cardiometabolic conditions ~20 years ago. The parent study combined the best approach for detecting genetic variants across the genome with a study population experiencing the risk exposures of the nutrition transition. The main aim of the sequencing of this selected subset of individuals was to enable the construction of a Samoan-specific reference panel for imputation back into the parent study. As such, the sequenced individuals were carefully selected to be optimal for constructing such a reference panel using the INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348). Samoans have been studied for >40 years with a focus on the increase in, and levels of, BMI, obesity, and associated cardiometabolic conditions due to economic modernization. Earlier studies focused on these broad environmental influences but the current team of investigators began genetic epidemiology studies of Samoan cardiometabolic conditions ~20 years ago. The current GWAS combined the best approach for detecting genetic variants across the genome with a study population experiencing the risk exposures of the nutrition transition.

Selected publications
Diseases/Traits Related to Study (MESH terms)
Authorized Data Access Requests
Study Attribution