Abstract
Background
Dyslipidaemia is highly prevalent in individuals with type 2 diabetes mellitus (T2DM). Numerous studies have sought to disentangle the causal relationship between dyslipidaemia and T2DM liability. However, conventional observational studies are vulnerable to confounding. Mendelian Randomization (MR) studies (which address this bias) on lipids and T2DM liability have focused on European ancestry individuals, with none to date having been performed in individuals of African ancestry. We therefore sought to use MR to investigate the causal effect of various lipid traits on T2DM liability in African ancestry individuals.
Methods
Using univariable and multivariable two-sample MR, we leveraged summary-level data for lipid traits and T2DM liability from the African Partnership for Chronic Disease Research (APCDR) (N = 13,612, 36.9% men) and from African ancestry individuals in the Million Veteran Program (Ncases = 23,305 and Ncontrols = 30,140, 87.2% men), respectively. Genetic instruments were thus selected from the APCDR after which they were clumped to obtain independent instruments. We used a random-effects inverse variance weighted method in our primary analysis, complementing this with additional sensitivity analyses robust to the presence of pleiotropy.
Findings
Increased genetically proxied low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) levels were associated with increased T2DM liability in African ancestry individuals (odds ratio (OR) [95% confidence interval, P-value] per standard deviation (SD) increase in LDL-C = 1.052 [1.000 to 1.106, P = 0.046] and per SD increase in TC = 1.089 [1.014 to 1.170, P = 0.019]). Conversely, increased genetically proxied high-density lipoprotein cholesterol (HDL-C) was associated with reduced T2DM liability (OR per SD increase in HDL-C = 0.915 [0.843 to 0.993, P = 0.033]). The OR on T2DM per SD increase in genetically proxied triglyceride (TG) levels was 0.884 [0.773 to 1.011, P = 0.072] . With respect to lipid-lowering drug targets, we found that genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with increased T2DM liability (OR per SD decrease in genetically proxied LDL-C = 1.68 [1.03-2.72, P = 0.04]) but we did not find evidence of a relationship between genetically proxied proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition and T2DM liability.
Interpretation
Consistent with MR findings in Europeans, HDL-C exerts a protective effect on T2DM liability and HMGCR inhibition increases T2DM liability in African ancestry individuals. However, in contrast to European ancestry individuals, LDL-C may increase T2DM liability in African ancestry individuals. This raises the possibility of ethnic differences in the metabolic effects of dyslipidaemia in T2DM.
Dyslipidaemia is highly prevalent in individuals with type 2 diabetes mellitus (T2DM). Numerous studies have sought to disentangle the causal relationship between dyslipidaemia and T2DM liability. However, conventional observational studies are vulnerable to confounding. Mendelian Randomization (MR) studies (which address this bias) on lipids and T2DM liability have focused on European ancestry individuals, with none to date having been performed in individuals of African ancestry. We therefore sought to use MR to investigate the causal effect of various lipid traits on T2DM liability in African ancestry individuals.
Methods
Using univariable and multivariable two-sample MR, we leveraged summary-level data for lipid traits and T2DM liability from the African Partnership for Chronic Disease Research (APCDR) (N = 13,612, 36.9% men) and from African ancestry individuals in the Million Veteran Program (Ncases = 23,305 and Ncontrols = 30,140, 87.2% men), respectively. Genetic instruments were thus selected from the APCDR after which they were clumped to obtain independent instruments. We used a random-effects inverse variance weighted method in our primary analysis, complementing this with additional sensitivity analyses robust to the presence of pleiotropy.
Findings
Increased genetically proxied low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) levels were associated with increased T2DM liability in African ancestry individuals (odds ratio (OR) [95% confidence interval, P-value] per standard deviation (SD) increase in LDL-C = 1.052 [1.000 to 1.106, P = 0.046] and per SD increase in TC = 1.089 [1.014 to 1.170, P = 0.019]). Conversely, increased genetically proxied high-density lipoprotein cholesterol (HDL-C) was associated with reduced T2DM liability (OR per SD increase in HDL-C = 0.915 [0.843 to 0.993, P = 0.033]). The OR on T2DM per SD increase in genetically proxied triglyceride (TG) levels was 0.884 [0.773 to 1.011, P = 0.072] . With respect to lipid-lowering drug targets, we found that genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with increased T2DM liability (OR per SD decrease in genetically proxied LDL-C = 1.68 [1.03-2.72, P = 0.04]) but we did not find evidence of a relationship between genetically proxied proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition and T2DM liability.
Interpretation
Consistent with MR findings in Europeans, HDL-C exerts a protective effect on T2DM liability and HMGCR inhibition increases T2DM liability in African ancestry individuals. However, in contrast to European ancestry individuals, LDL-C may increase T2DM liability in African ancestry individuals. This raises the possibility of ethnic differences in the metabolic effects of dyslipidaemia in T2DM.
| Original language | English |
|---|---|
| Article number | 103953 |
| Number of pages | 9 |
| Journal | EBioMedicine |
| Volume | 78 |
| Early online date | 21 Mar 2022 |
| DOIs | |
| Publication status | E-pub ahead of print - 21 Mar 2022 |
Bibliographical note
Funding Information:SF is an international Intermediate Fellow funded by the Wellcome Trust grant (220740/Z/20/Z) at the MRC/UVRI and LSHTM. TC is an international training fellow supported by the Wellcome Trust grant (214205/Z/18/Z). DG was supported by the British Heart Foundation Centre of Research Excellence (RE/18/4/34215) at Imperial College, and a National Institute for Health Research Clinical Lectureship (CL-2020-16-001) at St. George's, University of London. VK is supported by the Academy of Finland Project 312123, and European Union's Horizon 2020 research and innovation programme under Grant Agreement No 848158 (EarlyCause). M. Nakabuye acknowledges the support of Makerere University Non-Communicable Diseases (MacNCD). This research is made possible by the MakNCD Research Training Program: National Institutes of Health (NIH) 1D43TW011401-01 through the Fogarty International Center (FIC). C Soremekun, B. Udosen, and S Fatumo acknowledge H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), and the Center for Genomics Research and Innovation (CGRI) Abuja, Nigeria. Dr Mason is funded by the EC-Innovative Medicines Initiative (BigData@Heart). Dr Burgess is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z). This research was funded by UK Research and Innovation (UKRI) Medical Research Council (MC_UU_00002/7) and supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The funding sources did not have any role in designing the study, performing analysis, or communicating findings.
Funding Information:
The authors thank Million Veteran Program (MVP) staff, researchers, and volunteers, who have contributed to MVP, and especially participants who previously served their country in the military and now generously agreed to enroll in the study. (See https://www.research.va.gov/mvp/ for more details). The citation for MVP is Gaziano, J.M. et al. Million Veteran Program: A mega-biobank to study genetic influences on health and disease. J Clin Epidemiol 70, 214-23 (2016). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by the Veterans Administration (VA) Cooperative Studies Program (CSP) award #G002, SF is an international Intermediate Fellow funded by the Wellcome Trust grant (220740/Z/20/Z) at the MRC/UVRI and LSHTM. TC is an international training fellow supported by the Wellcome Trust grant (214205/Z/18/Z). DG was supported by the British Heart Foundation Centre of Research Excellence (RE/18/4/34215) at Imperial College, and a National Institute for Health Research Clinical Lectureship (CL-2020-16-001) at St. George's, University of London. VK is supported by the Academy of Finland Project 312123, and European Union's Horizon 2020 research and innovation programme under Grant Agreement No 848158 (EarlyCause). M. Nakabuye acknowledges the support of Makerere University Non-Communicable Diseases (MacNCD). This research is made possible by the MakNCD Research Training Program: National Institutes of Health (NIH) 1D43TW011401-01 through the Fogarty International Center (FIC). C Soremekun, B. Udosen, and S Fatumo acknowledge H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), and the Center for Genomics Research and Innovation (CGRI) Abuja, Nigeria. Dr Mason is funded by the EC-Innovative Medicines Initiative (BigData@Heart). Dr Burgess is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z). This research was funded by UK Research and Innovation (UKRI) Medical Research Council (MC_UU_00002/7) and supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The funding sources did not have any role in designing the study, performing analysis, or communicating findings. Dr. Segun Fatumo is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Funding Information:
The authors thank Million Veteran Program (MVP) staff, researchers, and volunteers, who have contributed to MVP, and especially participants who previously served their country in the military and now generously agreed to enroll in the study. (See https://www.research.va.gov/mvp/ for more details). The citation for MVP is Gaziano, J.M. et al. Million Veteran Program: A mega-biobank to study genetic influences on health and disease. J Clin Epidemiol 70, 214-23 (2016). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by the Veterans Administration (VA) Cooperative Studies Program (CSP) award #G002
Publisher Copyright:
© 2022 The Author(s)
Keywords
- Type 2 diabetes mellitus
- Lipid traits
- Mendelian Randomization
- PCSK9
- HMGCR
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