Genetic and epigenetic determinants of non-alcoholic fatty liver disease (NAFLD) in lean individuals: a systematic review
Bibliographic record
Abstract
Background: Non-alcoholic fatty liver disease (NAFLD) is common in obese individuals, but its occurrence in lean individuals and the underlying mechanisms are not well understood. This study aimed to systematically review the literature on the genetic and epigenetic factors influencing NAFLD in lean individuals. Methods: A comprehensive search was conducted on April 2nd, 2023, in seven databases using specific criteria. Only peer-reviewed studies in English, focusing on genetic or epigenetic effects on NAFLD in lean individuals, were included for qualitative synthesis. The Newcastle Ottawa Scale (NOS) was used for quality assessment. This study is registered with PROSPERO (CRD42023413809). Results: Following PRISMA guidelines, 18 studies were included in this review. The studies were conducted globally, with varying sample sizes and study designs. The NOS quality assessment revealed a moderate overall quality with variations in risk of bias and limitations in comparability and ascertainments of exposure among contributing studies. Genetic determinants related to lipid metabolism, inflammation, and oxidative stress pathways were identified, including PNPLA3 and TM6SF2 gene variants associated with increased NAFLD risk in lean individuals. Epigenetic modifications, particularly depletion of histone variants, were also implicated. However, some studies found no significant associations between genetic or clinical characteristics and lean NAFLD. Less frequent genetic risk factors, such as CETP and APOC3 gene variants, were reported. Conclusions: This systematic review underscores the importance of investigating genetic and epigenetic factors in lean NAFLD. The findings highlight the role of PNPLA3 and TM6SF2 gene variants and suggest potential epigenetic contributions. Further research is needed to fully understand the genetic and epigenetic mechanisms underlying NAFLD in lean individuals.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".