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Obesity, type 2 diabetes, hyperlipidaemia, hypertension and liver disease are common metabolic disorders in Mexican Americans, the largest minority population in the US. Mexican Americans are an admixed population with European, Amerindian and African ancestries. Association of ancestral components and these common metabolic disorders is a compelling issue because it may provide significant insight into personalised medicine based on quantitative ethnic information.
It has not been possible to get precise ancestral information for Mexican Americans using questionnaires. Indeed, siblings in the same family may give different ethnic information. Thanks to the impressive progress of human genomics research, genetic ancestral analysis using DNA polymorphism markers offers the opportunity to acquire accurate ancestry/ethnicity data in admixed human populations.1 ,2 Quantitative ancestral information can be readily acquired by genotyping a set of ancestry informative markers (AIMs) across the human genome. The AIMs are comprised of a number of autosomal single nucleotide polymorphisms (SNPs) with substantially different allele frequencies in different ancestral populations. We used this approach to investigate the ancestral components of our community-based Cameron County Hispanic Cohort (CCHC) consisting of Mexican Americans with high rates of obesity, type 2 diabetes, …
Funding This work was supported by MD000170 P20 funded from the National Center on Minority Health and Health Disparities, and the Centers for Translational Science Award 1U54RR023417-01 from the National Center for Research Resources. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. H-QQ is supported by intramural funding from the University of Texas School of Public Health.
Competing interests None.
Ethics approval The ethics approval was provided by the Committee for the Protection of Human Subjects of the University of Texas Health Science Center at Houston.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement The corresponding authors agree to comply with the NIH Data Sharing Policy guidelines. Access to the CCHC biobank containing de-identified data with demographic information and other data and to archived specimens will be available to academic researchers, provided formal requests are submitted and approved by the data sharing committee of the CCHC biobank. Human subject data will be shared within the limits of Health Insurance Portability and Accountability Act and other patient confidentiality requirements.