Electronic Health Record-Based Genome-Wide Meta-Analysis Identifies New Susceptibility Loci for Non-Alcoholic Fatty Liver Disease
Bibliographic record
Abstract
Abstract Background: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent form of liver disease. Observational studies documented associations of NAFLD with several chronic and infectious diseases but whether these associations underlie causal effects is unknown. The molecular mechanisms and genetic architecture of NAFLD are poorly understood. Our objectives were to identify genetic loci associated with NAFLD and determine whether the presence of NAFLD was causally associated with human diseases. Methods: We created a NAFLD genetic instrument through the identification of independent single-nucleotide polymorphisms (SNPs) associated with NAFLD in a meta-analysis of genome-wide association study (GWAS) (6715 cases and 682,748 controls). Using inverse-variance weighted Mendelian Randomization (MR), we investigated the impact of NAFLD on human disease-related phenotypes in the UK Biobank and FinnGen cohorts as well as in the COVID-19 host genetics initiative. Results: We first performed a GWAS meta-analysis of four cohorts and found variants significantly associated with NAFLD (p<5.0E-8) at six genetic loci (MTARC1, GCKR, TRIB1, LMO3, SUGP1 [TM6SF2] and PNPLA3). Using a risk factor informed Bayesian approach (bGWAS), we identify variants at three additional loci (LPL, FTO, and APOE). To determine if the association between NAFLD and human diseases shows evidence of causality, we performed MR across the human disease-related phenome (>800 diseases) using a genetic instrument for NAFLD. Results of these analyses suggest that NAFLD was not causally associated with diseases outside the spectrum of liver diseases. We also found no causal association between genetically predicted NAFLD and COVID-19-related outcomes. Conclusions: This study identified several new genetic loci associated with NAFLD. NAFLD was not causally associated with diseases outside those of the spectrum of liver diseases. This finding suggests that the resolution of NAFLD might not prevent other diseases previously associated with NAFLD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.009 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".