Branched-chain amino acids and type 2 diabetes: a bidirectional Mendelian randomization analysis
Corresponding Author
Jonathan D. Mosley
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Correspondence
Jonathan D. Mosley, Medicine and Biomedical Informatics, Vanderbilt University Medical Center, 1285 Medical Research Building IV, Nashville, TN, 37232, USA.
Email: [email protected]
Search for more papers by this authorMingjian Shi
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorDavid Agamasu
Meharry Medical College, Nashville, Tennessee, USA
Search for more papers by this authorNataraja Sarma Vaitinadin
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorVenkatesh L. Murthy
Division of Cardiovascular Medicine, Department of Medicine, University of Michigan, Ann Arbor, Michigan, USA
Search for more papers by this authorRavi V. Shah
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorMinoo Bagheri
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorJane F. Ferguson
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorCorresponding Author
Jonathan D. Mosley
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Correspondence
Jonathan D. Mosley, Medicine and Biomedical Informatics, Vanderbilt University Medical Center, 1285 Medical Research Building IV, Nashville, TN, 37232, USA.
Email: [email protected]
Search for more papers by this authorMingjian Shi
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorDavid Agamasu
Meharry Medical College, Nashville, Tennessee, USA
Search for more papers by this authorNataraja Sarma Vaitinadin
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorVenkatesh L. Murthy
Division of Cardiovascular Medicine, Department of Medicine, University of Michigan, Ann Arbor, Michigan, USA
Search for more papers by this authorRavi V. Shah
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorMinoo Bagheri
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorJane F. Ferguson
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
Search for more papers by this authorJonathan D. Mosley and Mingjian Shi contributed equally to this work.
Abstract
Objective
Genetic studies have suggested that the branched-chain amino acids (BCAAs) valine, leucine, and isoleucine have a causal association with type 2 diabetes (T2D). However, inferences are based on a limited number of genetic loci associated with BCAAs.
Methods
Instrumental variables (IVs) for each BCAA were constructed and validated using large well-powered data sets and their association with T2D was tested using a two-sample inverse-variance weighted Mendelian randomization approach. Sensitivity analyses were performed to ensure the accuracy of the findings. A reverse association was assessed using instrumental variables for T2D.
Results
Estimated effect sizes between BCAA IVs and T2D, excluding outliers, were as follows: valine (β = 0.14 change in log-odds per SD change in valine, 95% CI: −0.06 to 0.33, p = 0.17), leucine (β = 0.15, 95% CI: −0.02 to 0.32, p = 0.09), and isoleucine (β = 0.13, 95% CI: −0.08 to 0.34, p = 0.24). In contrast, T2D IVs were positively associated with each BCAA, i.e., valine (β = 0.08 per SD change in levels per log-odds change in T2D, 95% CI: 0.05 to 0.10, p = 1.8 × 10−9), leucine (β = 0.06, 95% CI: 0.04 to 0.09, p = 4.5 × 10−8), and isoleucine (β = 0.06, 95% CI: 0.04 to 0.08, p = 2.8 × 10−8).
Conclusions
These data suggest that the BCAAs are not mediators of T2D risk but are biomarkers of diabetes.
CONFLICT OF INTEREST STATEMENT
Ravi V. Shah receives consulting fees from Cytokinetics, Inc. Venkatesh L. Murthy receives consulting fees from INVIA Medical Imaging Solutions; Massachusetts General Hospital (MGH); and Siemens Medical Imaging; and has stock options from Johnson & Johnson, Merck, Eli Lilly and Company, and Cardinal Health, Inc. The other authors declared no conflict of interest.
Supporting Information
| Filename | Description |
|---|---|
| oby23951-sup-0001-Figures.pdfPDF document, 823.3 KB | Figure S1. Summary of a leave-one-out analysis for the associations between genetic instruments for (A) valine, (B) leucine and (C) isoleucine and type 2 diabetes. Each figures shows the IVW estimate (95% CI) after exclusion of the indicated SNP. Note that the name of the closest gene was substituted for the SNP name, when available. Figure S2. MR-Clust analysis for the associations between SNP instruments for leucine and isoleucine (exposure) and type 2 diabetes (outcome). The scatterplot shows the associations between the BCAA SNP genetic instruments and with type 2 diabetes. Each cluster is differentially colored. The “junk” cluster comprises SNPs not associated with any cluster. The inclusion probability is the probability that the SNPs belongs to the assigned cluster. BCAA measurement units are standardized values of inverse-normalized transformed levels and units for type 2 diabetes are log(association odds-ratio). Figure S3. Associations between SNP instruments for type 2 diabetes and BCAAs measured in the KORA population. (A-C) Scatterplots showing of the associations between genetic instruments for type 2 diabetes (n = 90 SNPs) and valine, leucine and isoleucine. The lines represent the association based on the IVW method. (D) Forest plot summarizing the associations by the inverse variance weighted (IVW) method between genetic instruments for type 2 diabetes and valine, leucine and isoleucine. |
| oby23951-sup-0002-Tables.xlsxExcel 2007 spreadsheet , 40.4 KB | Table S1. Description of the study population. Table S2. SNPs significantly associated with valine, leucine and isoleucine in the UK Biobank set. Table S3. Associations with BCAAs from the UK Biobank and METSIM cohort, and for type 2 diabetes, for lead SNPs identified by Lotta et al. (PLoS Med. 2016 Nov 29;13 [11]:e1002179). Table S4. SNPs used as instrumental variables for valine, leucine and isoleucine. Association statistics from GWAS are shown for the amino acid in UKB and METSIM data sets, and with type 2 diabetes. A1 represents the affect allele. Table S5. Summary of association analyses between the BCAA (UKB) and their corresponding AA in METSIM. Results are shown for MR analyses and MR-PRESSO. Table S6. Summary of association analyses between the BCAA (UKB) and type 2 diabetes by MR methods and MR-PRESSO. Table S7. Summary of association analyses between genetic instruments for type 2 diabetes (T2D) and BCAAs measured in the UK Biobank cohort for MR methods and MR-PRESSO. Table S8. Summary of association analyses between genetic instruments for type 2 diabetes (T2D) and BCAAs measured in the KORA cohort for MR methods and MR-PRESSO. Table S9. Multivariable IVW analyses using genetic instruments for type 2 diabetes (T2D), fasting insulin and body mass index (BMI) with each BCAA. These analyses exclude a pleiotropic SNP near the GCKR gene. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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