Submitted:
07 December 2025
Posted:
09 December 2025
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Methods
3. Liver Fibrosis: Pathophysiology and Clinical Relevance
3.1. Stages
3.2. Prevalence and Risk Factors
3.3. Pathomechanisms of Liver Fibrosis
3.4. Liver Fibrosis and Extrahepatic Outcomes
4. Dementia: Overview
4.1. Definitions and Spectrum
4.2. Pathophysiology and Risk Factors
5. Evidence Linking Liver Fibrosis and Dementia
5.1. Epidemiological Evidence
5.2. Mechanistic Insights
5.2.1. Liver-Brain Axis: Neuroinflammation, Insulin Resistance, and Vascular Dysfunction
5.2.2. Metabolic Dysregulation and Oxidative Stress
5.2.3. Gut-Liver-Brain Axis: Intestinal Microbiota, Endotoxins, and Ammonia
5.3. Sex and Age Differences
6. Diagnostic Considerations
6.1. Fibrosis Assessment
6.1.1. Blood-Based Non-Invasive Tests
6.1.2. Elastometry
6.1.3. Sequential Non-Invasive Assessment of Liver Fibrosis
7. Cognitive Assessment and Biomarkers
7.1. Mini-Mental State Examination and Montreal Cognitive Assessment
7.2. Additional Diagnostic Techniques
7.3. Risk Prediction Models
8. Therapeutic and Preventive Implications
8.1. Liver-Directed Interventions: Lifestyle, Pharmacological, and Bariatric Approaches
8.2. Neuroprotective Potential of Liver-Focused Therapies
8.3. Multidisciplinary Care: Integrating Hepatology and Cognitive Medicine
9. Gaps in Knowledge and Future Directions
10. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| β | Regression coefficient |
| AD | Alzheimer’s disease |
| AF | Atrial fibrillation |
| ALD | Alcohol-related liver disease |
| ALT | Alanine aminotransferase |
| APOE | Apolipoprotein E |
| APRI | aminotransferase–platelet ratio index |
| AST | Aspartate aminotransferase |
| AST/ALT | Aspartate aminotransferase / alanine aminotransferase ratio |
| BBB | Blood–brain barrier |
| CI | Confidence interval |
| CLD | Chronic liver disease |
| DBil | Direct bilirubin |
| ECM | Extracellular matrix |
| FHS | Framingham Heart Study |
| ELF | enhanced liver fibrosis score |
| FA | Fractional anisotropy |
| FIB-4 | Fibrosis-4 index |
| GGT | Gamma-glutamyl transpeptidase |
| GLP-1 RAs | glucagon-like peptide-1 receptor agonists |
| HOMA | Homeostatic model assessment |
| HR | Hazard ratio |
| HSC | Hepatic stellate cell |
| MASH | Metabolic dysfunction-associated steatohepatitis |
| MASLD | Metabolic dysfunction-associated steatotic liver disease |
| MD | Mean diffusivity |
| MetALD | Metabolic dysfunction and ALD |
| MMSE | Mini-Mental State Examination |
| MoCA | Montreal Cognitive Assessment |
| MRE | Magnetic Resonance Elastography |
| MRI | Magnetic resonance imaging |
| MRI-PDFF | Magnetic resonance imaging–proton density fat fraction |
| NFS | NAFLD fibrosis score |
| PDD | Parkinson’s Disease Dementia |
| PET | Positron emission tomography |
| PFDR | False discovery rate–adjusted p-value |
| PNPLA3 | Patatin-like phospholipase domain-containing protein 3 |
| RS | Rotterdam Study |
| SHIP | Study of Health in Pomerania |
| TBil | Total bilirubin |
| T2D | Type 2 diabetes |
| TMAO | trimethylamine-N-oxide |
| UK | United Kingdom |
| VaD | Vascular dementia |
| VCTE | Vibration-controlled transient elastography |
| WMH | White matter hyperintensity |
Appendix A
| Database | Syntax |
| PubMed | (("liver"[Mesh] AND ("Elasticity Imaging Techniques"[Mesh] OR "biopsy"[Mesh] OR "fibrosis"[Mesh])) OR “Liver Cirrhosis”[Mesh] OR (("liver"[tiab] OR "hepatic"[tiab]) AND ("biops*"[tiab] OR "fibros*"[tiab] OR "cirrhos*"[tiab] OR "stiffness*"[tiab] OR "puncture"[tiab] OR "elastogra*"[tiab] OR "elasticit*"[tiab] OR "acoustography"[tiab] OR "vibroacoustography"[tiab] OR "vibro-acoustography"[tiab] OR "sonoelastograph*"[tiab] OR "fibroscan"[tiab] OR "acoustic radiation force impulse imaging"[tiab] OR "arfi imaging*"[tiab]))) AND ("Dementia"[Mesh] OR "Dementia*"[tiab] OR "Alzheimer*"[tiab] OR "Binswanger encephalopathy"[tiab] OR "CADASIL"[tiab] OR "Lewy body disease"[tiab] OR "Neurofibrillary tangles with calcification"[tiab] OR "Primary progressive aphasia"[tiab] OR "Progressive nonfluent aphasia"[tiab] OR "Hereditary diffuse leukoencephalopathy with spheroids"[tiab] OR "Huntington chorea"[tiab] OR "Kluver-Bucy syndrome"[tiab] OR "Mental deterioration"[tiab] OR "Nasu-Hakola disease"[tiab] OR "Neuronal ceroid lipofuscinosis"[tiab] OR "Prion disease"[tiab] OR "Bovine spongiform encephalopathy"[tiab] OR "Chronic wasting disease"[tiab] OR "Creutzfeldt-Jakob disease"[tiab] OR "Feline spongiform encephalopathy"[tiab] OR "Fatal familial insomnia"[tiab] OR "Gerstmann-Straussler-Scheinker syndrome"[tiab] OR "Kuru"[tiab] OR "Scrapie"[tiab] OR "Transmissible mink encephalopathy"[tiab] OR "Variably protease-sensitive prionopathy"[tiab] OR "Pseudodementia"[tiab] OR "Rett syndrome"[tiab] OR "Senility"[tiab] OR "Tauopathy"[tiab] OR "Creutzfeldt-Jakob syndrome"[tiab] OR "Diffuse neurofibrillary tangles with calcification"[tiab] OR "Frontotemporal lobar degeneration"[tiab] OR "Huntington disease"[tiab] OR "Amentia*"[tiab]) AND ("1900/01/01"[Date - Publication] : "2025/11/30"[Date - Publication]) AND (humans[Filter]) AND(english[Filter]) AND (alladult[Filter]) |
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|
Global Prevalence of Advanced Fibrosis |
Global Prevalence of Cirrhosis |
|
| Overall | 3.3% (95% CI, 2.4–4.2) | 1.3% (95% CI, 0.9–1.7) |
| In men | 3.5% (95% CI, 2.6–4.5) | 2.5% (95% CI, 1.0–4.0) |
| In women | 2.2% (95% CI, 1.3–3.1) | 0.9% (95% CI, 0.0–1.8) |
| Author, [Ref] | Method | Findings | Comment |
| Gao et al. [59] | Prospective cohort study of 431,699 UK Biobank participants with a mean follow-up of 8.65 ± 2.61 years. Cox proportional hazards analysis was used to assess associations of liver markers (ALT, AST, AST/ALT ratio, GGT), alcoholic liver disease, fibrosis, and cirrhosis with incident dementia. Additionally, linear regression was used to evaluate cognition and brain structure. | Each SD decrease in ALT is associated with a lower risk of all-cause dementia (HR 0.917, PFDR<0.001). Conversely, each SD increase in AST (HR 1.048, PFDR=0.010), AST/ALT ratio (HR 1.195, PFDR<0.001), GGT (HR 1.066, PFDR<0.001), alcoholic liver disease (HR 2.872, PFDR<0.001), and fibrosis/cirrhosis (HR 2.285, PFDR=0.002) increases the risk of dementia. Cognition shows a positive correlation with AST, AST/ALT, DBil, and GGT, and a negative correlation with ALT, albumin, and TBil. ALT, GGT, AST/ALT, and ALD are linked to cortical/subcortical changes in regions such as the hippocampus, amygdala, thalamus, pallidum, and fusiform (PFDR<0.05). | Large-scale evidence indicates that liver dysfunction predicts dementia and cognitive impairment, and is associated with cortical/subcortical changes |
| Weinstein et al. [60] | A cross-sectional meta-analysis was conducted on 5660 individuals with NAFLD and 3022 individuals with fibrosis, who were free of dementia and stroke, from the FHS, RS, and SHIP cohorts. NAFLD was assessed using abdominal imaging, while fibrosis was assessed using FibroScan. Linear regression was used to analyze total brain volume, gray matter volume, hippocampal volumes, and WMH. | NAFLD is associated with smaller total brain volume (β=-3.5, 95% CI -5.4 to -1.7), gray matter volume (β=-1.9, 95% CI -3.4 to -0.3), and cortical gray matter volume (β=-1.9, 95% CI -3.7 to -0.01). Fibrosis (liver stiffness ≥8.2 kPa) is linked to smaller total brain volume (β=-7.3, 95% CI -11.1 to -3.5). There is low heterogeneity. | This suggests that NAFLD and fibrosis may play a role in brain aging. |
| Weinstein et al. [61] | Participants from the Framingham Offspring and Third Generation cohorts underwent amyloid (11C-PiB) and tau (18F-Flortaucipir) PET scans, as well as abdominal CT scans or had FIB-4 data. Linear regression was used to assess associations of NAFLD and FIB-4 with regional tau and amyloid-β levels, adjusting for confounders. | FIB-4 is associated with increased rhinal tau levels (β=1.03±0.33, p=0.002). In NAFLD participants, higher FIB-4 levels are correlated with increased tau in regions such as the inferior temporal (β=2.01±0.47, p<0.001), parahippocampal (β=1.60±0.53, p=0.007), entorhinal (β=1.59±0.47, p=0.003), and rhinal cortex (β=1.60±0.42, p=0.001), as well as increased overall amyloid-β (β=1.93±0.47, p<0.001) and in regions like inferior temporal/parahippocampal. | Liver fibrosis, as opposed to NAFLD alone, could drive early Alzheimer’s pathology, including tau accumulation in certain brain regions. |
| Fan et al. [62] | A cross-sectional study was conducted on 29,195 UK Biobank participants aged 45–82 who underwent T1, T2 FLAIR, and DTI MRI scans. MASLD was defined as MRI-PDFF ≥5% plus ≥1 cardiometabolic criterion. Multiple linear regression was used to assess total and subcortical gray matter, AD-signature cortical thickness, WMH, FA, and MD. | MASLD is associated with smaller total/subcortical gray matter (p<0.05) and reduced cortical thickness in AD signature/regions (β=-0.04, 95% CI -0.07, -0.01). Higher total WMH volume (β=0.12, 95% CI 0.10, 0.15), increased global FA (β=0.05, 95% CI 0.03, 0.08), and reduced global MD (β=-0.04, 95% CI -0.07, -0.01). | MASLD affects gray and white matter integrity, further supporting a connection between liver metabolic dysfunction and brain structure. |
|
Test (calculation) |
Condition | Cutoff | Sensitivity (%) | Specificity/NPV% | Reference |
| APRI (AST level ÷ ULN ÷ platelet count) |
Significant fibrosis due to HBV Cirrhosis due to HCV |
> 0.35 >1.0 |
78 76 |
63 71 |
Yue et al. [105] Shaheen et al. [106] |
| FIB-4 (age × AST level) ÷ (platelet count × √ALT level) |
Significant fibrosis due to HCV | <1.45 >3.25 |
60-92 11-54 |
52-95 91-98 |
Xu et al. [107] |
| NFS (−1.675 + (0.037 × age) + (0.094 × BMI) + (1.13 × IR or diabetes [yes = 1, no = 0]) + (0.99 × AST:ALT ratio) − (0.013 × platelet count) − (0.66 × albumin) |
Identification of individuals with MASLD at risk of developing fibrosis | -0.835 | 100 | 70 | Torres et al. [108] |
| Author, year [Ref] | Method | Findings | Conclusion |
| Gaur, 2023[119] | Meta-analysis of 10 studies | In CSF, concentrations of NfL (SMD=0.69 [0.56, 0.83]), GFAP (SMD=0.41 [0.07, 0.75]), and HFABP (SMD=0.57 [0.26, 0.89]) were elevated in individuals with MCI. In blood, increased concentrations of T-tau (SMD=0.19 [0.09, 0.29]), NfL (SMD=0.41 [0.32, 0.49]), and GFAP (SMD=0.39 [0.23, 0.55]) were found in MCI. |
Levels of NfL and GFAP can be measured in both CSF and blood. Monitoring these biomarkers may provide valuable information about neurodegeneration in individuals with MCI. |
| Ma, 2024[120] | Meta-analysis of 63 studies | The following biomarkers were significantly higher in patients with PSCI compared to the non-PSCI group: Hcy (p<0.00001), CRP (p=0.0008), UA (p=0.02), IL-6 (p=0.005), Cys-C (p=0.0001), creatinine (p<0.00001) and TNF-α (p=0.02). | Integrating of neuroimaging and neuropsychological assessments with blood biomarker levels is crucial for evaluating the risk of PSCI. |
| Chen, 2024[121] | Meta-analysis of 13 studies | A notable elevation in MI concentration was found, along with reductions in Glu, Glx, and NAA/Cr ratios in DCI. | These biomarkers are highly sensitive metabolic indicators for assessing the progression of DCI. |
| Huang, 2025[122] | Meta-analysis of 30 studies | Peripheral Aβ42 levels, the Aβ42/Aβ40 ratio, NfL, and S100B show significant differences between VCI and non-VCI groups. | Peripheral Aβ42, the Aβ42/Aβ40 ratio, NfL, and S100B are potential blood biomarkers for VCI. |
| Risk Prediction Model | Parameters Included | Comment | References |
| CAIDE Dementia Risk Score | Age, sex, Education Level, Physical Inactivity, SBP, TChol, BMI. | Originally developed to predict the 20-year dementia risk among middle-aged Finnish individuals, this is the most established and frequently used mid-life risk score for predicting future dementia risk. | Kivipelto et al. [123] Farkas et al. [124] |
| ANU-ADRI | Age, sex, education level, BMI, diabetes, depression, TChol, traumatic brain injury, smoking, alcohol intake, social engagement, physical activity, cognitive activity, fish intake, and pesticide exposure. | In contrast to constructing risk indices using individual cohort studies, this methodology enables the inclusion of a broader range of risk factors, enhances the generalizability of outcomes, and facilitates the integration of interactions informed by research conducted across various stages of the life course. | Anstey et al. [125] |
| UKBDRS | Age, education, parental history of dementia, material deprivation, a history of diabetes, stroke, depression, hypertension, high cholesterol, household occupancy, and sex | This is an easy-to-use tool to identify individuals at risk of dementia in the UK. Further research is required to determine the validity of this score in other populations. | Anaturk et al. [126] |
| CogDrisk tool | Age, sex, education, HTN, midlife obesity, midlife high cholesterol, diabetes, insufficient physical activity, depression, TBI, AF, smoking, social engagement, cognitive engagement, fish consumption, stroke, and insomnia. | A comprehensive risk assessment tool for AD, VaD, and any other type of dementia, which will be applicable in high and low-resource settings. | Anstey et al. [127,128] |
| LIBRA and LIBRA2 | LIBRA focuses on 12 modifiable lifestyle and vascular risk factors, while the updated LIBRA2 version adds three more: hearing impairment, social contact, and sleep. | LIBRA2 demonstrates improved capability in identifying individuals at elevated risk for dementia and serves as an effective tool for public health initiatives focused on reducing dementia risk. | Rosenau et al. [129] |
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