<scp>PNPLA3 I148M</scp> and response to treatment for hepatic steatosis: A systematic review
Bibliographic record
Abstract
BACKGROUND: It is unclear whether the patatin-like phospholipase domain-containing protein 3 (PNPLA3) rs738409 C-to-G single nucleotide polymorphism, resulting in the substitution of isoleucine to methionine at position 148 (I148M), impedes regression of hepatic steatosis when treating non-alcoholic fatty liver disease (NAFLD). OBJECTIVES: Investigate if carriage of the PNPLA3 148M allele affects the anti-steatotic efficacy of all possible anti-NAFLD interventions, identify gaps in current knowledge and provide guidance for individual treatment. METHODS: Research available in public databases was searched up to 13 November 2022. Studies were included if a treatment in NAFLD patients decreased hepatic steatosis in the pooled patient group or a PNPLA3 I148M polymorphism subgroup (II/IM/MM). The risk of bias was assessed using the Cochrane Risk-Of-Bias 2 Tool and the Newcastle-Ottawa Scale. RESULTS: Moderate evidence indicates that NAFLD patients homozygous for the PNPLA3 148M allele benefit less or not at all from omega-3 carboxylic acids to decrease liver fat, while the PNPLA3 148I allele shows moderate benefit. Low evidence suggests that interventions employing lifestyle changes are more effective to reduce liver fat in NAFLD patients homozygous for the PNPLA3 148M allele compared to patients with wild-type PNPLA3. CONCLUSIONS: NAFLD patients homozygous for the PNPLA3 148M allele might not benefit from omega-3 carboxylic acids to reduce hepatic steatosis in contrast to patients with wild-type PNPLA3. Instead, patients with two PNPLA3 148M alleles should be especially advised to adopt lifestyle changes. Genotyping for PNPLA3 I148M should be encouraged in therapeutic studies for NAFLD. REGISTRATION NUMBER (PROSPERO): CRD42022375028.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".