Genome‐Wide Association Study of NAFLD Using Electronic Health Records
Bibliographic record
Abstract
Abstract Background & Aims Genome-wide association studies (GWAS) have identified several risk loci for non-alcoholic fatty liver disease (NAFLD). Previous studies have largely relied on small sample sizes and have assessed quantitative traits. We performed a case-control GWAS in the UK Biobank using recorded diagnosis of NAFLD based on diagnostic codes recommended in recent consensus guidelines. Approach & Results We performed a GWAS of 4,761 cases of NAFLD and 373,227 healthy controls without evidence of NAFLD. Sensitivity analyses were performed excluding other co-existing hepatic pathology, adjusting for BMI and adjusting for alcohol intake. 9,723,654 variants were assessed by logistic regression adjusted for age, sex, genetic principal components and genotyping batch. We performed a GWA meta-analysis using available summary association statistics from two previously published case-control GWAS of NAFLD. Six risk loci were identified (P<5*10^(−8)) of which one is novel in GWAS (rs429358 in APOE) and five are known (PNPLA3, TM6SF2, GCKR, MARC1 and TRIB1). Rs429358 (P=2.17*10^(−11)) is a missense variant within the APOE gene determining ⍰4 vs ⍰2/⍰3 alleles. All loci retained significance in sensitivity analyses without co-existent hepatic pathology and after adjustment for BMI. PNPLA3 and TM6SF2 remained significant after adjustment for alcohol (alcohol intake was known in only 158,388 individuals) with others demonstrating consistent direction and magnitude of effect. All 6 loci were significant on meta-analysis including APOE P=3.42*10^(−13) with consistent direction and magnitude of effect in all 6 loci in all three studies. The ⍰4 allele of APOE offered protection against NAFLD (odds ratio for heterozygotes 0.84 [95%CI 0.78-0.90] and homozygotes 0.64 [0.50-0.79]). Conclusions This GWAS demonstrates that the ∈ 4 allele of APOE is strongly associated with protection against NAFLD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".