Genetic Associations Among Appendicular Lean Mass, Alanine Aminotransferase, and Type 2 Diabetes: Multi-Dataset Mendelian Randomization and Colocalization at the SERPINA1 Candidate Locus.

Background/

Objectives

Appendicular lean mass (ALM), alanine aminotransferase (ALT), and type 2 diabetes (T2D) may be genetically linked. However, the ALT-related pathway and shared signals at the SERPINA1 candidate locus remain uncertain. We used Mendelian randomization (MR) to evaluate associations among ALM, ALT, and T2D and compared candidate-locus signals across datasets. ALM represented muscle mass, not clinical sarcopenia.

Methods

Using European-ancestry GWAS summary statistics, we performed six bidirectional two-sample MR analyses, multivariable MR (MVMR) with finite-sample t-based inference, and exploratory path-specific two-step MR. FinnGen R12 provided the T2D outcome data for MR and pathway analyses. Pathway analyses used 5000 shared-sampling bootstrap replicates to assess uncertainty in path estimates. We combined locus-level coloc/ABF with signal-specific SuSiE-coloc in the GRCh37 SERPINA1 region. T2DGGI was used only for colocalization. Molecular-QTL and external-omics analyses were treated as supportive or limiting evidence.

Results

Higher genetically predicted ALM was associated with lower ALT and lower T2D risk, whereas higher genetically predicted ALT was associated with greater T2D risk. T2D→ALT was method-dependent. In MVMR, the ALT conditional effect remained positive, whereas the ALM direct effect was model-dependent. Path decomposition was compatible with an ALT-related statistical pathway, but product- and difference-based estimates disagreed, and residual heterogeneity remained. ALM-T2DGGI supported an rs28929474-related shared component, although component-cohort overlap was possible. FinnGen supported other ALT-related signals but did not independently corroborate rs28929474. Tissue eQTL and external omics did not provide consistent mechanistic support.

Conclusions

The data support directionally connected MR-based associations and dataset-dependent shared candidate signals. These findings do not establish biological mediation, a unique causal variant, gene-level causal assignment, or a molecular mechanism.