Type 2 diabetes is a major public health concern. Diabetes currently affects 25.8 million people in the US alone and 90-95% of all cases are type 2. There are many complications related to diabetes, including a significantly increased risk of heart disease and stroke, blindness, kidney failure and kidney disease, nonalcoholic fatty liver disease, neuropathy, hearing loss and lower-limb amputations. There are several risk factors predisposing individuals to the development of this disease including demographic characteristics like sex, age and ethnicity; and behavioral and lifestyle-related modifications. In addition, metabolic determinants such as impaired glucose tolerance and insulin resistance increase the risk of an individual progressing to type 2 diabetes. Significant diabetes health disparities exist in minority populations, including Hispanics and African Americans, where prevalence of diabetes is increased. Evidence from both epidemiological and lipidomic studies have shown that specific lipoproteins and their constituent lipids are important factors in the development of type 2 diabetes, where, like many other metabolic diseases, lipid metabolism is disrupted. The classical lipid parameters most commonly examined in relation to disease risk are themselves complex entities composed of multiple lipid species. We hypothesize that these basic lipid species represent intermediate phenotypes that lie closer to the genomic level in the interplay between phenotype and disease, and therefore may be better predictors of disease risk and increase the pace of discovery of genes causally involved in lipid variation and type 2 diabetes. In this project, we will exploit whole genome sequence (WGS) information in powerful extended pedigrees of Mexican American individuals in combination with comprehensive measures of the human lipidome, to identify novel genes and functional variants influencing lipid variation and type 2 diabetes, in an effort to reduce the diabetes health disparities evident in Hispanic populations. The combination of these precise biological lipid phenotypes and WGS gives us an unprecedented opportunity to identify novel genes and functional variants influencing human lipid variation and risk of diabetes. To achieve these objectives, we will (I) measure T2D risk phenotypes including targeted lipid profiling of more than 800 lipid species; and multiple measures of metabolic function, and perform quantitative genetic analyses; (II) identify sequence variation influencing lipid variation and diabetes in all individuals using WGS; (Ill) perform hypothesis based replication in an independent Mexican American population; and (IV) perform functional assessments of variants of interest in relevant iPSC-derived cells and analyze free and total fatty acid content in a subset of the cohort. The estimated economic burden of diabetes in the United States alone is approximately $245 billion per year, making this disease of major public health importance. The ability to identify genes that are causally involved in disease risk provides an unparalleled opportunity to quickly determine biological pathways that are involved in disease pathology. A better understanding of the genetic contribution to lipid variation and diabetes development will provide novel approaches for the characterization, treatment and potential prevention of this costly disease.

Public Health Relevance

Type 2 diabetes (T2D) is a global public health problem, with staggering rates of disease evidenced in the US and throughout both developed and developing nations. T2D disparately affects minority populations, with Hispanics being one of the highest at-risk populations. Evidence from both epidemiological and lipidomic studies have shown that specific lipids and their constituent components are important factors in the development of T2D. The human lipidome is made up of thousands of different lipid species, the simpler constituent components of classical lipid measures like HDL. By focusing on biologically simple lipid species, we hope to more rapidly identify genes influencing lipid variation and T2D. We will use whole genome sequencing to identify novel genes underlying the relationship between human lipid variation and T2D in extended pedigrees of Mexican American individuals, and functionally assess identified targets. This approach may lead us to the identification of potential drug targets relevant for lipid modifying therapy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
1R01DK127636-01
Application #
10142857
Study Section
Kidney, Nutrition, Obesity and Diabetes Study Section (KNOD)
Program Officer
Zaghloul, Norann
Project Start
2021-01-01
Project End
2024-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
University of Texas Rio Grande Valley
Department
Type
Schools of Medicine
DUNS #
069444511
City
Edinburg
State
TX
Country
United States
Zip Code
78539