Importance: Treatment to lower high levels of low-density lipoprotein cholesterol (LDL-C) reduces incident coronary artery disease (CAD) risk but modestly increases the risk for incident type 2 diabetes (T2D). The extent to which genetic factors across the cholesterol spectrum are associated with incident T2D is not well understood.
Objective: To investigate the association of genetic predisposition to increased LDL-C levels with incident T2D risk.
Design, Setting, And Participants: In this large prospective, population-based cohort study, UK Biobank participants who underwent whole-exome sequencing and genome-wide genotyping were included. Participants were separated into 7 groups with familial hypercholesterolemia (FH), predicted loss of function (pLOF) in APOB or PCSK9 variants, and LDL-C polygenic risk score (PRS) quintiles. Data were collected between 2006 and 2010, with a median follow-up of 13.7 (IQR, 12.9-14.5) years. Data were analyzed from March 1 to November 1, 2024.
Exposures: LDL-C level, LDL-C PRS, FH, or pLOF variant status.
Main Outcomes And Measures: Cox proportional hazards regression models adjusted for age, sex, genotyping array, lipid-lowering medication use, and the first 10 genetic principal components were fitted to assess the association between LDL-C genetic factors and incident T2D and CAD risks.
Results: Among the 361 082 participants, mean (SD) age was 56.8 (8.0) years, 194 751 (53.9%) were female, and mean (SD) baseline LDL-C level was 138.0 (33.6) mg/dL. During the follow-up period, 22 619 (6.3%) participants developed incident T2D and 17 966 (5.0%) developed incident CAD. The hazard ratio for incident T2D was lowest in the FH group (0.65; 95% CI, 0.54-0.77), while the highest risk was in the pLOF group (1.48; 95% CI, 1.18-1.86). The association between LDL-C PRS and incident T2D was 0.72 (95% CI, 0.66-0.79) for very high LDL-C PRS, 0.87 (95% CI, 0.84-0.90) for high LDL-C PRS, 1.13 (95% CI, 1.09-1.17) for low LDL-C PRS, and 1.26 (95% CI, 1.15-1.38) for very low LDL-C PRS. CAD risk increased directly with the LDL-C PRS.
Conclusions And Relevance: In this cohort study, LDL-C and T2D risks were inversely associated across genetic mechanisms for LDL-C variation. Further elucidation of the mechanisms associating low LDL-C risk with increased risk of T2D is warranted.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1001/jamacardio.2024.5072 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Genetic Predisposition to Low-Density Lipoprotein Cholesterol and Incident Type 2 Diabetes.
JAMA Cardiol
January 2025
Program of Medical and Population Genetics, Broad Institute of MIT (Massachusetts Institute of Technology) and Harvard, Cambridge, Massachusetts.
Importance: Treatment to lower high levels of low-density lipoprotein cholesterol (LDL-C) reduces incident coronary artery disease (CAD) risk but modestly increases the risk for incident type 2 diabetes (T2D). The extent to which genetic factors across the cholesterol spectrum are associated with incident T2D is not well understood.
Objective: To investigate the association of genetic predisposition to increased LDL-C levels with incident T2D risk.
[Not Available].
Tunis Med
January 2025
Department of Endocrinology and Internal Medicine, Fattouma Bourguiba Hospital, Monastir. Tunisia.
Unlabelled: Introduction-Aim: Type 2 diabetes (T2D) is a major public health problem. To succeed its management and prevent its complications, good therapeutic adherence must be ensured. The objectives of our work were to estimate the prevalence of poor therapeutic adherence in our patients and to identify its associated factors.
View Article and Find Full Text PDFEarly Postpartum Metabolic Heterogeneity Among Women Who Progressed to Type 2 Diabetes After Gestational Diabetes: A Prospective Cohort.
Diabetes Metab Res Rev
January 2025
Division of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.
Aims: Gestational diabetes mellitus (GDM) poses a significant risk for developing type 2 diabetes mellitus (T2D) and exhibits heterogeneity. However, understanding the link between different types of post-GDM individuals without diabetes and their progression to T2D is crucial to advance personalised medicine approaches.
Materials And Methods: We employed a discovery-based unsupervised machine learning clustering method to generate clustering models for analysing metabolomics, clinical, and biochemical datasets.
Trends and analysis of risk factor differences in the global burden of chronic kidney disease due to type 2 diabetes from 1990 to 2021: A population-based study.
Diabetes Obes Metab
January 2025
Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Background: Chronic kidney disease (CKD) is a significant contributor to the global burden of disease. Among its causes, chronic kidney disease due to type 2 diabetes (CKD-T2D) is the primary subtype. This study aims to provide an updated assessment of the global disease burden of CKD-T2D from 1990 to 2021.
View Article and Find Full Text PDFInvestigating misclassification of type 1 diabetes in a population-based cohort of British Pakistanis and Bangladeshis using polygenic risk scores.
Sci Rep
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
Correct classification of type 1 (T1D) and type 2 diabetes (T2D) is challenging due to overlapping clinical features and the increasingly early onset of T2D, particularly in South Asians. Polygenic risk scores (PRSs) for T1D and T2D have been shown to work relatively well in South Asians, despite being derived from largely European-ancestry samples. Here we used PRSs to investigate the rate of potential misclassification of diabetes amongst British Bangladeshis and Pakistanis.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!