Metabolomic Profiling of Type 2 Diabetes Pathway-Partitioned Polygenic Risk Scores Offers Insights into Disease Etiology

DIABETES(2023)

引用 0|浏览1
暂无评分
摘要
Previous studies have identified type 2 diabetes (T2D) subtypes using clinical phenotypes and/or genetic information. This study aimed to identify molecular signatures associated with genetically based T2D subtypes. We analyzed data from ~100,000 unrelated European UK Biobank participants without T2D and not taking lipid-lowering medications. T2D subtypes were characterized using five polygenic scores denoting three forms of insulin resistance (lipodystrophy, obesity, and impaired lipid/hepatic metabolism) and two subtypes of insulin secretion (beta-cell dysfunction and impaired proinsulin synthesis). Nuclear magnetic resonance profiles of 249 plasma metabolites on the Nightingale platform were tested for association with T2D subtypes using linear regression adjusted for age, sex, batch, and ancestry-derived principal components; P<0.0002 was considered significant. Independent validation was conducted in two independent cohorts, including 720 from the ANTORCHA cohort. In general, the T2D subtypes driven by insulin resistance were characterized by alterations in lipid and lipoproteins, while the impaired insulin secretion subtypes showed aberrant plasma amino acid levels. The lipodystrophy cluster showed the most distinct molecular signature, with higher concentrations of extremely large, very large, and large VLDL particles which were enriched by triglycerides and phospholipids, and lower concentrations of HDL. The beta-cell dysfunction cluster was characterized by higher concentrations of amino acids (alanine, valine, leucine, and tyrosine). These associations were broadly consistent after adjusting for BMI, and the pattern of alterations in lipid metabolites was partially replicated in the ANTORCHA cohort. We identified specific metabolic signatures related to T2D genetic clusters before T2D onset, offering further characterization of the putative underlying pathways. Disclosure M.Sevilla: None. I.Lamiquiz-moneo: None. K.Smith: None. M.Canyelles: None. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck & Co., Inc. A.Manning: None. F.Civeira: None. J.Merino: None. M.Udler: None. Funding American Diabetes Association (9-22-PDFPM-04 to M.S.)
更多
查看译文
关键词
polygenic risk scores,metabolomic profiling,diabetes,disease etiology,pathway-partitioned
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要