Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2600 disease traits

  1. Joshua K Park
  2. Shantanu Bafna
  3. Iain S Forrest
  4. Áine Duffy
  5. Carla Marquez-Luna
  6. Ben O Petrazzini
  7. Ha My Vy
  8. Daniel M Jordan
  9. Marie Verbanck
  10. Jagat Narula
  11. Robert S Rosenson
  12. Ghislain Rocheleau
  13. Ron Do  Is a corresponding author
  1. Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, United States
  2. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, United States
  3. Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, United States
  4. Université Paris Cité, France
  5. Department of Medicine, Icahn School of Medicine at Mount Sinai, United States
  6. Cardiovascular Imaging Program, Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, United States
  7. Metabolism and Lipids Unit, Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, United States
4 figures and 8 additional files

Figures

Study overview.

A schematic summarizing the study design. GLGC, Global Lipids Genetics Consortium; HDL, high-density lipoprotein; IVW, inverse-variance weighted; LDL, low-density lipoprotein; MR, Mendelian randomization; MR-PRESSO, Mendelian Randomization Pleiotropy RESidual Sum and Outlier; SNP, single-nucleotide polymorphism; TG, triglyceride; UKB, UK Biobank. Tier 1 (BB): At least Bonferroni-significant in both the discovery and replication analyses. Tier 2 (BN): At least Bonferroni-significant in the discovery analysis and at least nominally significant in the replication analysis. Tier 3 (NB): At least nominally significant in the discovery analysis and at least Bonferroni-significant in the replication analysis.

Causal estimates of genetically proxied plasma triglyceride (TG) levels on disease risk using inverse-variance weighted (IVW) regression in UKB and FinnGen.

Causal estimates from IVW regression are shown as odds ratios (OR) per 1 SD increase in plasma TG levels (mmol/L). Asterisks indicate novel associations. Black indicates discovery analysis results using UKB. Red indicates replication analysis results using FinnGen. Horizontal error bars represent 95% CIs. Tier 1 (BB): At least Bonferroni-significant in both the discovery (p<1.92 × 10–5) and replication (p<2.26 × 10–4) analyses. Tier 2 (BN): At least Bonferroni-significant in the discovery analysis (p<1.92 × 10–5) and at least nominally significant in the replication analysis (p<0.05). Tier 3 (NB): At least nominally significant in the discovery analysis (p<0.05) and at least Bonferroni significant in the replication analysis (p<2.26 × 10–4). Full results and sample sizes (n) of each GWAS for each trait are provided in Supplementary file 1 and Supplementary file 2.

Causal estimates of genetically proxied plasma triglyceride (TG) levels on disease risk using MR-Egger, Weighted Median, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) methods in UKB.

Shown are sensitivity analysis results from the discovery stage using instruments from Global Lipids Genetics Consortium (GLGC) and outcomes from UKB. Associations with insignificant global MR-PRESSO test results (p>0.05) were not rerun and do not have data points for inverse-variance weighted (IVW) after MR-PRESSO. Tier 1 (BB): At least Bonferroni-significant in both the discovery (p<1.92 × 10–5) and replication (p<2.26 × 10–4) analyses. Tier 2 (BN): At least Bonferroni-significant in the discovery analysis (p<1.92 × 10–5) and at least nominally significant in the replication analysis (p<0.05). Tier 3 (NB): At least nominally significant in the discovery analysis (p<0.05) and at least Bonferroni significant in the replication analysis (p<2.26 × 10–4). Horizontal error bars represent 95% CIs. Full results and sample sizes (n) of each GWAS for each trait are found in Supplementary file 1 and Supplementary file 3.

Causal estimates of genetically proxied plasma triglyceride (TG) levels on disease risk using multivariable inverse-variance weighted (IVW) regression controlling for plasma low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and apolipoprotein B (ApoB) levels in UKB.

Shown are the multivariable MR (MVMR) results from the discovery analysis, using genetic instruments for plasma TG levels from Global Lipids Genetics Consortium (GLGC) and disease traits from UKB. Levels of statistical significance are categorized into three tiers: Tier 1 (BB): At least Bonferroni-significant in both the discovery (p<1.92 × 10–5) and replication (p<2.26 × 10–4) analyses. Tier 2 (BN): At least Bonferroni-significant in the discovery analysis (p<1.92 × 10–5) and at least nominally significant in the replication analysis (p<0.05). Tier 3 (NB): At least nominally significant in the discovery analysis (p<0.05) and at least Bonferroni significant in the replication analysis (p<2.26 × 10–4). Horizontal error bars represent 95% CIs. Full results are provided in Supplementary file 4. Sample sizes (n) of each GWAS for each trait are found in Supplementary file 1.

Additional files

Supplementary file 1

Causal estimates of plasma TG levels on 2600 traits in UKB using multiple MR methods.

Shown are the estimates, standard deviations, and p-values of MR results using IVW, MR-Egger, and weighted median methods. 141 SNPs were used as instrumental variables to proxy plasma TG levels. A Bonferroni threshold for statistical significance was set to p<0.05/2600=1.92 × 10–5 for this discovery analysis.

https://cdn.elifesciences.org/articles/80560/elife-80560-supp1-v2.xlsx
Supplementary file 2

Causal estimates of plasma TG levels on 221 traits in FinnGen using multiple MR methods.

Shown are the estimates, standard deviations, and p-values of MR results using IVW, MR-Egger, and weighted median methods. 1248 SNPs were used as instrumental variables to proxy plasma TG levels. A Bonferroni threshold for statistical significance was set to p<0.05/221=2.26 × 10–4 for this replication analysis.

https://cdn.elifesciences.org/articles/80560/elife-80560-supp2-v2.xlsx
Supplementary file 3

IVW-MR estimates of significant and replicated associations (tier 1–3) after MR-PRESSO outlier tests using UKB data.

Shown are the estimates, standard deviations, and p-values of IVW-MR results in the discovery analysis, before and after outlier IV removal, for significant and replicated traits (tier 1–3) that had significant MR-PRESSO global test results (p<0.05) in the primary IVW analysis of the discovery UKB cohort.

https://cdn.elifesciences.org/articles/80560/elife-80560-supp3-v2.xlsx
Supplementary file 4

Multivariable IVW-MR estimates of plasma TG levels on significant and replicated associations (tier 1–3) using UKB data.

Shown are the estimates, standard deviations, and p-values of multivariable IVW-MR results controlling for HDL-C, LDL-C, ApoB levels, or all three, in the discovery stage. Only tier 1–3 results significant and replicated as predefined in the methods were examined in this analysis.

https://cdn.elifesciences.org/articles/80560/elife-80560-supp4-v2.xlsx
Supplementary file 5

IVW-MR estimates of significant associations (tier 1–3) using GLGC data for exposure instruments and FinnGen data for outcome instruments.

Shown are the estimates, standard deviations, and p-values of IVW-MR results when using GLGC data to select instruments for plasma TG levels, as was done in the discovery analysis.

https://cdn.elifesciences.org/articles/80560/elife-80560-supp5-v2.xlsx
Supplementary file 6

Bidirectional MR estimates of significant associations (tier 1–3) using multiple MR methods.

Shown are the estimates, standard deviations, p-values, MR-PRESSO outlier test results, and the number of instruments used in bidirectional MR analyses estimating the causal effects of nine disease traits on plasma TG levels using IVW, MR-Egger, and Weighted Median methods. Exposure instruments were selected from UKB, and outcome instruments were selected from GLGC.

https://cdn.elifesciences.org/articles/80560/elife-80560-supp6-v2.xlsx
MDAR checklist
https://cdn.elifesciences.org/articles/80560/elife-80560-mdarchecklist1-v2.pdf
Reporting standard 1

STROBE checklist.

https://cdn.elifesciences.org/articles/80560/elife-80560-repstand1-v2.pdf

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  1. Joshua K Park
  2. Shantanu Bafna
  3. Iain S Forrest
  4. Áine Duffy
  5. Carla Marquez-Luna
  6. Ben O Petrazzini
  7. Ha My Vy
  8. Daniel M Jordan
  9. Marie Verbanck
  10. Jagat Narula
  11. Robert S Rosenson
  12. Ghislain Rocheleau
  13. Ron Do
(2023)
Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2600 disease traits
eLife 12:e80560.
https://doi.org/10.7554/eLife.80560