Non-alcoholic fatty liver disease (NAFLD) as a neglected metabolic companion of psychiatric disorders: common pathways and future approaches
Bibliographic record
Abstract
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis in over 5% of the parenchyma in the absence of excessive alcohol consumption. It is more prevalent in patients with diverse mental disorders, being part of the comorbidity driving loss of life expectancy and quality of life, yet remains a neglected entity. NAFLD can progress to non-alcoholic steatohepatitis (NASH) and increases the risk for cirrhosis and hepatic carcinoma. Both NAFLD and mental disorders share pathophysiological pathways, and also present a complex, bidirectional relationship with the metabolic syndrome (MetS) and related cardiometabolic diseases. MAIN TEXT: This review compares the demographic data on NAFLD and NASH among the global population and the psychiatric population, finding differences that suggest a higher incidence of this disease among the latter. It also analyzes the link between NAFLD and psychiatric disorders, looking into common pathophysiological pathways, such as metabolic, genetic, and lifestyle factors. Finally, possible treatments, tailored approaches, and future research directions are suggested. CONCLUSION: NAFLD is part of a complex system of mental and non-communicable somatic disorders with a common pathogenesis, based on shared lifestyle and environmental risks, mediated by dysregulation of inflammation, oxidative stress pathways, and mitochondrial function. The recognition of the prevalent comorbidity between NAFLD and mental disorders is required to inform clinical practice and develop novel interventions to prevent and treat these complex and interacting disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".