{ "abstract": "Although genome-wide association studies (GWAS) now routinely reveal genetic associations and biological insights in millions of individuals, underrepresentation of global populations, such as those from Polynesia, continue to persist. These exclusions, often driven by logistical challenges and lack of data, prevent systematic identification of population-enriched associations, such as the association of the missense variant at the CREBRF locus to BMI and type 2 diabetes discovered commonly occurring in Polynesian populations due to its rarity in global populations. Armed with the recently updated TOPMed imputation panel that could benefit studies in diverse populations that previously had poorer imputation performance, we performed the first GWAS of Native Hawaiians and Samoans, the largest to date of Polynesian-ancestry populations (combined N up to 8,461) to identify population-enriched associations for 13 adiposity and cardiometabolic traits available across both cohorts: BMI, fasting glucose, fasting insulin, HDL, height, hip circumference, HOMA-IR, LDL, T2D, total cholesterol, triglycerides, waist circumference, and waist-hip ratio. We found 25 trait-loci associations that met genome-wide significance: 20 previously reported or known associations and 5 putatively new associations via meta-analysis. In particular, with improved statistical power, we were able to confirm the previously suggestive association between the missense CREBRF variant with fasting glucose levels. The remaining 4 potentially novel loci-trait associations for BMI, LDL, and waist-hip ratio, however, were not replicated in All-of-Us. The lack of Polynesian-enriched findings outside of the CREBRF locus informs the bounds of the effect sizes or frequencies of any enriched variants and suggests that further expansion of cohort sizes from this region of the world and improved imputation references specific to these populations are needed to identify more population-enriched associations. Author summary: Understudied populations, like those from the Pacific Islands, are often excluded from large-scale human genetic studies due to small cohort sizes and unique study considerations, resulting in a growing disparity of benefits compared to well-studied groups. Although Polynesian-ancestry individuals remain underrepresented, recent updates to publicly available genomic resources such as one provided by the TOPMed initiative provide a renewed potential to map Polynesian-enriched variants for association with complex traits. We leveraged these resources to conduct the largest GWAS in Polynesian-ancestry individuals to date in up to 8,461 individuals, combining Native Hawaiian and Samoan cohorts for the first time. Across 13 adiposity and cardiometabolic traits, we identified 775 significant variant-trait associations at 25 loci, including five putative and 20 previously established loci-trait associations. Notably, we illustrated the effects of the Polynesian-enriched CREBRF missense variant on multiple traits but failed to replicate four other potentially novel associations for BMI, LDL, and waist-hip ratio. Our results help define the realistic bounds of associations disproportionately impacting these populations and underscore the need for further increased representation to identify more population-enriched genetic risk factors.", "abstract_shown": true, "affiliations": [ "Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, United States of America", "Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America", "Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America", "Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America", "Ministry of Health, Apia, Samoa", "Department of Epidemiology, Brown University, Providence, Rhode Island, United States of America", "Oceania University of Medicine, Apia, Samoa", "Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, United States of America", "Population Sciences in the Pacific Program, Cancer Center, University of Hawaiʻi, Honolulu, Hawai‘i, United States of America" ], "article_type": "Research Article", "arxiv": null, "author_total": 14, "authors": [ { "affs": [ 0, 1 ], "name": "Bryan L. Dinh", "orcid": "0000-0002-5351-6145" }, { "affs": [ 0 ], "name": "Xinran Wang" }, { "affs": [ 0 ], "name": "Xin Sheng" }, { "affs": [ 0 ], "name": "Peggy Wan" }, { "affs": [ 2, 3 ], "name": "Amit Kumar Srivastava", "orcid": "0000-0002-7162-1678" }, { "affs": [ 4, 5 ], "name": "Take Naseri" }, { "affs": [ 6, 7 ], "name": "Satupa‘itea Viali" }, { "name": "The Samoan Obesity, Lifestyle and Genetic Adaptations (OLaGA) Study Group" }, { "affs": [ 8 ], "name": "Lynne R. Wilkens" }, { "affs": [ 8 ], "name": "Loïc Le Marchand" }, { "affs": [ 0 ], "name": "Christopher A. Haiman" }, { "affs": [ 2, 3 ], "name": "Daniel E. Weeks" }, { "affs": [ 0, 1 ], "name": "Charleston W. K. Chiang", "orcid": "0000-0002-0668-7865" }, { "affs": [ 2, 3 ], "name": "Jenna C. Carlson", "orcid": "0000-0001-5483-0833" } ], "bibtex": "https://research.draconitic.com/paper/7apq4mkh04s8m.bib", "cited_by": 0, "doi": "10.1371/journal.pgen.1012342", "fulltext_url": "https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1012342", "id": "7apq4mkh04s8m", "issns": [ "1553-7404", "1553-7390" ], "landing_url": "https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1012342", "language": "en", "licence": "CC-BY-4.0", "licence_label": "CC BY 4.0", "licence_source": "article", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "heading", "Austronesian People" ], [ "heading", "Biochemistry" ], [ "heading", "Biology and Life Sciences" ], [ "heading", "Carbohydrates" ], [ "heading", "Chemical Compounds" ], [ "heading", "Chemistry" ], [ "heading", "Cholesterol" ], [ "heading", "Computational Biology" ], [ "heading", "Diabetes Mellitus" ], [ "heading", "Endocrine Disorders" ], [ "heading", "Endocrinology" ], [ "heading", "Ethnicities" ], [ "heading", "Genetic Loci" ], [ "heading", "Genetics" ], [ "heading", "Genome Analysis" ], [ "heading", "Genome-Wide Association Studies" ], [ "heading", "Genomics" ], [ "heading", "Glucose" ], [ "heading", "Human Genetics" ], [ "heading", "Lipids" ], [ "heading", "Mathematical and Statistical Techniques" ], [ "heading", "Mathematics" ], [ "heading", "Medical Conditions" ], [ "heading", "Medicine and Health Sciences" ], [ "heading", "Metaanalysis" ], [ "heading", "Metabolic Disorders" ], [ "heading", "Monosaccharides" ], [ "heading", "Organic Chemistry" ], [ "heading", "Organic Compounds" ], [ "heading", "People and Places" ], [ "heading", "Physical Sciences" ], [ "heading", "Polynesian People" ], [ "heading", "Population Groupings" ], [ "heading", "Quantitative Trait Loci" ], [ "heading", "Research Article" ], [ "heading", "Research and Analysis Methods" ], [ "heading", "Statistical Methods" ], [ "heading", "Statistics" ], [ "heading", "Type 2 Diabetes" ], [ "openalex", "1311|Genetic Associations and Epidemiology" ], [ "plos", "/Biology and life sciences/Biochemistry/Lipids/Cholesterol" ], [ "plos", "/Biology and life sciences/Computational biology/Genome analysis/Genome-wide association studies" ], [ "plos", "/Biology and life sciences/Genetics/Genetic loci" ], [ "plos", "/Biology and life sciences/Genetics/Genetic loci/Quantitative trait loci" ], [ "plos", "/Biology and life sciences/Genetics/Genomics/Genome analysis/Genome-wide association studies" ], [ "plos", "/Biology and life sciences/Genetics/Human genetics/Genome-wide association studies" ], [ "plos", "/Medicine and health sciences/Endocrinology/Endocrine disorders/Diabetes mellitus/Type 2 diabetes" ], [ "plos", "/Medicine and health sciences/Medical conditions/Metabolic disorders/Diabetes mellitus/Type 2 diabetes" ], [ "plos", "/People and places/Population groupings/Ethnicities/Austronesian people/Polynesian people" ], [ "plos", "/Physical sciences/Chemistry/Chemical compounds/Organic compounds/Carbohydrates/Monosaccharides/Glucose" ], [ "plos", "/Physical sciences/Chemistry/Organic chemistry/Organic compounds/Carbohydrates/Monosaccharides/Glucose" ], [ "plos", "/Physical sciences/Mathematics/Statistics/Statistical methods/Metaanalysis" ], [ "plos", "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Metaanalysis" ] ], "openalex": "W7223109587", "pdf_url": "https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1012342&type=printable", "pmcid": "PMC13712763", "pmid": "42905873", "published": "2026-10-21", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/7apq4mkh04s8m.ris", "sources": [ { "first_seen": "2026-10-30T12:17:23Z", "native_id": "10.1371/journal.pgen.1012342", "source": "plos", "url": "https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1012342" }, { "first_seen": "2026-10-31T12:23:16Z", "native_id": "PMC13712763", "source": "pmc", "url": "https://doi.org/10.1371/journal.pgen.1012342" } ], "subjects": [ { "field": "biochemistry", "origin": "heading:Biochemistry", "subfield": "general" }, { "field": "biology", "origin": "heading:Computational Biology", "subfield": "bioinformatics" }, { "field": "biology", "origin": "plos:genetics", "subfield": "genetics-genomics" }, { "field": "mathematics", "origin": "plos:statistical methods", "subfield": "statistics" }, { "field": "medicine", "origin": "plos:endocrinology", "subfield": "endocrinology-metabolism" } ], "title": "Meta-analysis of over 8,000 individuals from Hawai‘i and Samoa for genetic associations to cardiometabolic phenotypes", "title_text": "Meta-analysis of over 8,000 individuals from Hawai‘i and Samoa for genetic associations to cardiometabolic phenotypes", "type": "peer-reviewed", "updated_at": "2026-10-31T12:23:16Z", "url": "https://research.draconitic.com/paper/7apq4mkh04s8m", "venue": "PLOS Genetics", "versions": [] }