Dataset Information

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations.

ABSTRACT: The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single nucleotide polymorphism (SNP) and locus-wide comparisons. SNPs in FTO and near MC4R, obesity-susceptibility loci first identified in Europeans, replicate widely across other ancestries. SNP-to-SNP comparisons suggest that more than half of the 36 body mass index-associated loci are shared across European and East Asian ancestry populations, whereas locus-wide analyses suggest that the transferability might be even more extensive. Furthermore, by taking advantage of differences in haplotype structure, populations of different ancestries can help to narrow down loci, thereby pinpointing causal genes for functional follow-up. Larger-scale genetic association studies in ancestrally diverse populations will be needed for in-depth and locus-wide analyses aimed at determining, with greater confidence, the transferability of loci and allowing fine-mapping. Understanding similarities and differences in genetic susceptibility across populations of diverse ancestries might eventually contribute to a more targeted prevention and customized treatment of obesity.

SUBMITTER: Lu Y

PROVIDER: S-EPMC3706771 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations.

Lu Yingchang Y Loos Ruth Jf RJ

Genome medicine 20130628 6

The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single n ...[more]

PMID: 23806069

Similar Datasets

Project description:Purpose of reviewThe prevalence of obesity continues to rise, fueling a global public health crisis characterized by dramatic increases in type 2 diabetes, cardiovascular disease, and many cancers. In the USA, several minority populations, who bear much of the obesity burden (47% in African Americans and Hispanic/Latinos, compared to 38% in European descent groups), are particularly at risk of downstream chronic disease. Compounding these disparities, most genome-wide association studies (GWAS)-including those of obesity-have largely been conducted in populations of European or East Asian ancestry. In fact, analysis of the GWAS Catalog found that while the proportion of participants of non-European or non-Asian descent had risen from 4% in 2009 to 19% in 2016, African-ancestry participants are still just 3% of GWAS, Hispanic/Latinos are < 0.5%, and other ancestries are < 0.3% or not represented at all. This review summarizes recent developments in obesity genomics in US minority populations, with the goal of reducing obesity health disparities and improving public health programs and access to precision medicine.Recent findingsGWAS of populations with the highest burden of obesity are essential to narrow candidate variants for functional follow-up, to identify additional ancestry-specific variants that contribute to individual genetic susceptibility, and to advance both public health and precision medicine approaches to obesity. Given the global public health burden posed by obesity and downstream chronic conditions which disproportionately affect non-European populations, GWAS of obesity-related traits in diverse populations is essential to (1) locate causal variants in GWAS-identified regions through fine mapping, (2) identify variants which influence obesity across ancestries through generalization, and (3) discover novel ancestry-specific variants which may be low frequency in European populations but common in other groups. Recent efforts to expand obesity genomic studies to understudied and underserved populations, including AAAGC, PAGE, and HISLA, are working to reduce obesity health disparities, improve public health, and bring the promise of precision medicine to all.

Project description:BackgroundSystematic reviews of research evidence have become an expected basis for decisions about practice guidelines and policy decisions in the health and welfare sectors. Review authors define inclusion criteria to help them determine which studies to search for and include in their reviews. However, these studies may still vary in the extent to which they reflect the context of interest in the review question. While most review authors would agree that systematic reviews should be relevant and useful for decision makers, there appears to be few well known, if any, established methods for supporting review authors to assess the transferability of review findings to the context of interest in the review. With this systematic mapping and content analysis, we aim to identify whether there exists checklists to support review authors in considering transferability early in the systematic review process. The secondary aim was to develop a comprehensive list of factors that influence transferability as discussed in existing checklists.MethodsWe conducted a systematic mapping of checklists and performed a content analysis of the checklist criteria included in the identified checklists. In June 2016, we conducted a systematic search of eight databases to identify checklists to assess transferability of findings from primary or secondary research, without limitations related to publication type, status, language, or date. We also conducted a gray literature search and searched the EQUATOR repository of checklists for any relevant document. We used search terms such as modified versions of the terms "transferability," "applicability," "generalizability," etc. and "checklist," "guideline," "tool," "criteria," etc. We did not include papers that discussed transferability at a theoretical level or checklists to assess the transferability of guidelines to local contexts.ResultsOur search resulted in 11,752 titles which were screened independently by two review authors. The 101 articles which were considered potentially relevant were subsequently read by two authors, independently in full text and assessed for inclusion. We identified 31 relevant checklists. Six of these examined transferability of economic evaluations, and 25 examined transferability of primary or secondary research findings in health (n?=?23) or social welfare (n?=?2). The content analysis is based on the 25 health and social welfare checklists. We identified seven themes under which we grouped categories of checklist criteria: population, intervention, implementation context (immediate), comparison intervention, outcomes, environmental context, and researcher conduct.ConclusionsWe identified a variety of checklists intended to support end users (researchers, review authors, practitioners, etc.) to assess transferability or related concepts. While four of these checklists are intended for use in systematic reviews of effectiveness, we found no checklists for qualitative evidence syntheses or for the field of social welfare practice or policy. Furthermore, none of the identified checklists for review authors included guidance to on how to assess transferability, or present assessments in a systematic review. The results of the content analysis can serve as the basis for developing a comprehensive list of factors to be used in an approach to support review authors in systematically and transparently considering transferability from the beginning of the review process.

Project description:Genetic studies of bone mineral density (BMD) largely have been conducted in European populations. We therefore conducted a meta-analysis of six independent African ancestry cohorts to determine whether previously reported BMD loci identified in European populations were transferable to African ancestry populations. We included nearly 5000 individuals with both genetic data and assessments of BMD. Genotype imputation was conducted using the 1000G reference panel. We assessed single-nucleotide polymorphism (SNP) associations with femoral neck and lumbar spine BMD in each cohort separately, then combined results in fixed effects (or random effects if study heterogeneity was high, I2 index >60) inverse variance weighted meta-analyses. In secondary analyses, we conducted locus-based analyses of rare variants using SKAT-O. Mean age ranged from 12 to 68 years. One cohort included only men and another cohort included only women; the proportion of women in the other four cohorts ranged from 52% to 63%. Of 56 BMD loci tested, one locus, 6q25 (C6orf97, p = 8.87 × 10-4 ), was associated with lumbar spine BMD and two loci, 7q21 (SLC25A13, p = 2.84 × 10-4 ) and 7q31 (WNT16, p = 2.96 × 10-5 ), were associated with femoral neck BMD. Effects were in the same direction as previously reported in European ancestry studies and met a Bonferroni-adjusted p value threshold, the criteria for transferability to African ancestry populations. We also found associations that met locus-specific Bonferroni-adjusted p value thresholds in 11q13 (LRP5, p < 2.23 × 10-4 ), 11q14 (DCDC5, p < 5.35 × 10-5 ), and 17p13 (SMG6, p < 6.78 × 10-5 ) that were not tagged by European ancestry index SNPs. Rare single-nucleotide variants in AKAP11 (p = 2.32 × 10-2 ), MBL2 (p = 4.09 × 10-2 ), MEPE (p = 3.15 × 10-2 ), SLC25A13 (p = 3.03 × 10-2 ), STARD3NL (p = 3.35 × 10-2 ), and TNFRSF11A (p = 3.18 × 10-3 ) were also associated with BMD. The majority of known BMD loci were not transferable. Larger genetic studies of BMD in African ancestry populations will be needed to overcome limitations in statistical power and to identify both other loci that are transferable across populations and novel population-specific variants. © 2020 American Society for Bone and Mineral Research (ASBMR).

Dataset Information

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations.

Publications

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets