Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes

• Objective: This MR study partitioned BMI-associated genetic variants into two distinct groups based on their association with gene expression in subcutaneous adipose tissue (metabolic) or brain tissue (appetite) to assess their differential effects on cardiometabolic risk.
• Key Finding: The brain-mediated genetic pathway (appetite regulation) for higher BMI was found to be significantly more strongly associated with increased risk of Type 2 Diabetes Mellitus (T2DM) compared to the adipose-mediated pathway.
• Shared Effects: Both tissue-specific pathways showed similar detrimental effects on blood lipids (LDL-C, triglycerides) and blood pressure, suggesting these are shared downstream consequences of increased BMI regardless of the initiating genetic mechanism.

PubMed: 35090585 DOI: 10.1016/j.ajhg.2021.12.013 Overview generated by: Gemini 2.5 Flash, 28/11/2025

Key Findings: Tissue-Specific Genetic Effects of BMI

This two-sample Mendelian randomization (MR) study aimed to distinguish the effects of BMI-associated genetic variants that act via metabolic pathways (proxied by subcutaneous adipose tissue expression) from those that act via appetite regulation (proxied by brain tissue expression) on various cardiometabolic phenotypes.

• Distinct Gene Sets Identified: The study successfully identified two distinct sets of BMI-associated genetic instruments:
  1. Adipose-Mediated Set (Metabolic): 8 variants (e.g., near IRS1, IGF2BP2) associated with gene expression in subcutaneous adipose tissue.
  2. Brain-Mediated Set (Appetite): 11 variants (e.g., near BDNF, FTO) associated with gene expression in the brain.
• Brain-Mediated Pathway and T2DM: The brain-mediated genetic variants were found to be more strongly associated with Type 2 Diabetes Mellitus (T2DM) risk compared to the adipose-mediated variants. This suggests that the genetic propensity for higher BMI driven by appetite regulation in the brain is a major driver of T2DM risk.
  • The brain-mediated set resulted in an Odds Ratio (OR) of 1.43 (95% CI 1.30; 1.57) per standard deviation (SD) increase in BMI, whereas the adipose-mediated set OR was 1.15 (95% CI 1.05; 1.25).
• Similar Effects on Lipids and Blood Pressure: Both the adipose-mediated and brain-mediated genetic sets were similarly associated with detrimental effects on blood lipids (LDL-cholesterol, triglycerides) and blood pressure, suggesting these consequences of BMI are likely shared downstream effects regardless of the initial genetic pathway (appetite vs. metabolism).

Study Design and Methods

Study Design

This was a two-sample Mendelian randomization (MR) study. The analysis partitioned the overall genetic liability for BMI into two hypothesized causal pathways (adipose-mediated and brain-mediated) to examine their downstream effects on specific cardiometabolic outcomes.

Data and Genetic Instrument Selection

1. Exposure GWAS (BMI): Summary statistics for BMI were taken from a large-scale GWAS meta-analysis (Locke et al., 2015).
2. Tissue-Specific eQTL Data (Mediators): Genetic variants were prioritized based on their association with gene expression (eQTLs) in two relevant tissues:
   • Subcutaneous Adipose Tissue (Metabolic): Expression data from a meta-analysis (n=1257).
   • Brain Tissue (Appetite/Central): Expression data from the GTEx consortium (n=1194).
3. Instrument Selection: Instruments were selected as cis-eQTLs associated with both BMI and gene expression in a specific tissue. Strict quality control and linkage disequilibrium (LD) clumping were applied. This procedure resulted in the final, mostly non-overlapping 8 adipose-mediated and 11 brain-mediated genetic instruments.

Outcome GWAS Data

Outcome data were sourced from large-scale consortia GWAS for:

• Type 2 Diabetes Mellitus (T2DM)
• Coronary Artery Disease (CAD)
• Lipid traits (LDL-C, HDL-C, Triglycerides)
• Blood pressure (systolic and diastolic)

Statistical Analysis

• Primary MR Method: The Inverse-Variance Weighted (IVW) method was used to combine the effects of the variants within each tissue-specific set (adipose vs. brain).
• Sensitivity Analyses: MR-Egger and Weighted Median methods were used to test for horizontal pleiotropy. MR-PRESSO was used to detect and correct for outliers. The results were robust across these sensitivity methods.
• Testing for Difference in Effects: A formal statistical test was applied to compare the strength of the causal effect estimates between the adipose-mediated and brain-mediated gene sets on each outcome.

Conclusions and Implications

The study provides compelling evidence that the genetic pathways influencing BMI have differential downstream causal effects on cardiometabolic outcomes, particularly T2DM.

• Targeted Interventions: The strong link between brain-mediated genetic risk (appetite regulation) and T2DM suggests that therapeutic or preventative interventions targeting central regulation of appetite may be particularly effective in reducing T2DM risk among genetically predisposed individuals.
• Biological Dissection: The methodology effectively dissects the genetic architecture of a complex trait (BMI), linking tissue-specific molecular effects to disease risk. This approach offers a powerful strategy for prioritizing therapeutic targets based on biological mechanism.
• Future Work: The authors recommend expanding the tissue types analyzed to include visceral adipose tissue and other relevant metabolic organs (e.g., liver) to provide a more complete picture of the causal pathways.