Dietary Polyphenols in Brain Aging: Molecular Mechanisms and Implications for Neurodegeneration
Abstract
1. Introduction
2. Methods
3. Geroscience Framework: Biological Hallmarks of Brain Aging
3.1. Oxidative Stress and Redox Imbalance
3.2. Chronic Inflammation and Inflammaging
3.3. Mitochondrial Dysfunction
3.4. Cellular Senescence
3.5. Impaired Proteostasis
3.6. Dysregulation of Nutrient-Sensing Signaling Pathways
4. Dietary Polyphenols as Food-Derived Bioactive Compounds
4.1. Classification of Polyphenols
4.1.1. Flavonoids
4.1.2. Phenolic Acids
4.1.3. Stilbenes
4.1.4. Lignans
4.2. Major Dietary Sources of Polyphenols
4.3. Polyphenol-Rich Dietary Patterns
5. Bioavailability and Metabolism of Polyphenols
5.1. Gastrointestinal Absorption
5.2. Phase II Metabolism
5.2.1. Glucuronidation
5.2.2. Sulfation
5.2.3. Methylation
5.3. Role of the Gut Microbiota
5.4. Transport Across the Blood–Brain Barrier
5.5. Determinants of Bioavailability
5.5.1. Food Matrix
5.5.2. Genetic Factors
5.5.3. Microbiome Composition
6. Molecular Mechanisms of Polyphenol-Mediated Neuroprotection
6.1. Antioxidant Signaling Pathways
6.2. Anti-Inflammatory Mechanisms
6.3. Mitochondrial Protection and Energy Metabolism
6.4. Regulation of Autophagy and Proteostasis
6.5. Synaptic Plasticity and Neurotrophic Signaling
6.6. Epigenetic Regulation
7. Polyphenols and Neurodegenerative Diseases
7.1. Alzheimer’s Disease
7.1.1. Amyloid-β Aggregation
7.1.2. Tau Hyperphosphorylation
7.1.3. Neuroinflammation
7.2. Parkinson’s Disease
7.2.1. α-Synuclein Aggregation
7.2.2. Degeneration of Dopaminergic Neurons
7.3. Cognitive Aging and Mild Cognitive Impairment
8. Evidence from Epidemiological and Clinical Studies
8.1. Prospective Cohort Studies
8.2. Dietary Pattern Studies
8.3. Clinical Intervention Trials
8.4. Cognitive Outcomes
9. Gut–Brain Axis and Microbiome Interactions
9.1. Polyphenol–Microbiota Interactions
9.2. Microbial Metabolites
9.3. Modulation of Neuroinflammation
9.4. Microbiome-Mediated Neuroprotective Effects
10. Challenges and Research Gaps
10.1. Bioavailability and Dose–Response Considerations
- Habitual dietary intake, reflecting polyphenol consumption from whole foods within typical dietary patterns;
- Enhanced dietary intake, achievable through targeted dietary modification;
- Pharmacological or supplemental exposure, often involving concentrated extracts or purified compounds.
10.2. Heterogeneity of Polyphenol Intake
10.3. Lack of Large-Scale Clinical Trials
10.4. Interindividual Variability
10.5. Limitations in Measuring Dietary Intake
10.6. Timing and Duration of Polyphenol Intake
10.7. Safety and Toxicity Considerations
11. Future Perspectives
11.1. Precision Nutrition
11.2. Nutrigenomics
11.3. Metabolomics-Based Approaches
11.4. Microbiome-Targeted Strategies
11.5. Integrative Multi-Omics Approaches
12. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
| AD | Alzheimer’s disease |
| PD | Parkinson’s disease |
| ROS | Reactive oxygen species |
| RNS | Reactive nitrogen species |
| Nrf2 | Nuclear factor erythroid 2–related factor 2 |
| NF-κB | Nuclear factor kappa B |
| AMPK | AMP-activated protein kinase |
| mTOR | Mechanistic target of rapamycin |
| SIRT1 | Sirtuin 1 |
| BDNF | Brain-derived neurotrophic factor |
| CREB | cAMP response element-binding protein |
| BBB | Blood–brain barrier |
| CNS | Central nervous system |
| IL-6 | Interleukin-6 |
| TNF-α | Tumor necrosis factor alpha |
| CRP | C-reactive protein |
| ATP | Adenosine triphosphate |
| mtDNA | Mitochondrial DNA |
| SASP | Senescence-associated secretory phenotype |
| EGCG | Epigallocatechin gallate |
| MCI | Mild cognitive impairment |
| APP | Amyloid precursor protein |
| Aβ | Amyloid-beta |
| GSK-3β | Glycogen synthase kinase 3 beta |
| LPS | Lipopolysaccharide |
| PGC-1α | Peroxisome proliferator-activated receptor gamma coactivator 1-alpha |
| UGT | UDP-glucuronosyltransferase |
| SULT | Sulfotransferase |
| COMT | Catechol-O-methyltransferase |
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| Polyphenol Class | Representative Compounds | Major Dietary Sources | Bioavailability | Evidence Level | Biological Relevance to Brain Aging |
|---|---|---|---|---|---|
| Flavonoids | Quercetin, catechin, epicatechin, anthocyanins | Berries, apples, onions, tea, cocoa | Low–moderate (structure-dependent) | Human and preclinical | Antioxidant and anti-inflammatory effects; modulation of neuronal signaling and synaptic plasticity |
| Phenolic acids | Caffeic acid, ferulic acid, chlorogenic acid | Coffee, fruits, vegetables, cereals | Moderate | Human and preclinical | Regulation of redox homeostasis; attenuation of oxidative stress and inflammation |
| Stilbenes | Resveratrol | Grapes, red wine, berries | Low (rapid metabolism) | Human and preclinical | Activation of SIRT1; mitochondrial function and metabolic regulation |
| Lignans | Secoisolariciresinol, matairesinol | Flaxseed, sesame seeds, whole grains | Low–moderate (microbiota-dependent) | Preclinical and limited human | Gut microbiota-derived metabolites; antioxidant and hormone-like effects |
| Polyphenol | Major Dietary Sources | Molecular Target | Signaling Pathway | BBB Permeability | Evidence Level | Reported Neuroprotective Effects |
|---|---|---|---|---|---|---|
| Resveratrol | Grapes, red wine, berries | SIRT1 activation | SIRT1–AMPK axis | Yes (limited bioavailability) | Human + animal | Mitochondrial biogenesis, reduced oxidative stress, improved cognitive performance (small RCTs) |
| Epigallocatechin gallate (EGCG) | Green tea | Nrf2 activation | Nrf2–ARE pathway | Limited | Mostly preclinical | Enhanced antioxidant defense, reduced neuronal oxidative damage |
| Quercetin | Apples, onions, tea | NF-κB inhibition | NF-κB signaling | Low–moderate | Preclinical + limited human | Anti-inflammatory effects, attenuation of neuroinflammation |
| Curcumin | Turmeric | mTOR inhibition | mTOR–autophagy pathway | Low (poor bioavailability) | Human + animal (heterogeneous) | Enhanced autophagy, reduced protein aggregation, mixed cognitive outcomes |
| Anthocyanins | Berries | BDNF modulation | CREB–BDNF pathway | Moderate (metabolite-dependent) | Human + animal | Improved synaptic plasticity, memory, and cognitive function |
| Microbial Metabolite | Polyphenol Precursors | Major Microbial Transformation | Reported Biological Effects |
|---|---|---|---|
| Phenolic acids (e.g., phenylpropionic and phenylacetic acids) | Flavonoids, phenolic acids | Ring cleavage and reduction | Antioxidant activity, modulation of redox homeostasis |
| Phenyl-γ-valerolactones | Flavan-3-ols (catechins, epicatechins) | Microbial degradation in the colon | Anti-inflammatory effects, vascular and neuronal protection |
| Urolithins | Ellagitannins (pomegranate, berries, nuts) | Microbial conversion of ellagic acid | Activation of mitophagy, improved mitochondrial function |
| Dihydroresveratrol | Resveratrol | Microbial reduction | Anti-inflammatory activity and metabolic regulation |
| Enterolignans (enterolactone, enterodiol) | Dietary lignans (flaxseed, sesame) | Microbial dehydroxylation and demethylation | Hormone-like activity and antioxidant effects |
| Exposure Level | Typical Dose Range | Source | Bioavailability Characteristics | Relevance for Dose–Response Interpretation |
|---|---|---|---|---|
| Habitual dietary intake | ~100–1000 mg/day (total polyphenols) | Fruits, vegetables, tea, coffee, wine | Low, variable; strong matrix and microbiome influence | Reflects real-life exposure; effects modest but physiologically relevant |
| Enhanced dietary intake | ~500–2000 mg/day | Polyphenol-rich diets (e.g., Mediterranean diet, berries, cocoa) | Still food-matrix dependent; moderate increase in metabolites | Allows evaluation of diet-based interventions |
| Supplemental intake | ~100–1000 mg/day (single compounds, e.g., resveratrol, EGCG) | Dietary supplements, extracts | Higher systemic exposure; altered metabolism | May exceed physiological range; relevance to diet unclear |
| Pharmacological/experimental doses | Often >> 1000 mg/day (or high µM in vitro) | Preclinical models | Not representative of human exposure | Limits translational relevance |
| Research Domain | Key Limitation | Priority for Future Research | Translational Relevance |
|---|---|---|---|
| Bioavailability | Low and variable systemic exposure | Development of novel delivery systems (e.g., encapsulation, nanoformulations) | Improve clinical efficacy |
| Dose–response relationships | Poorly defined, non-linear effects | Standardized dose–response studies across dietary and supplemental ranges | Establish evidence-based recommendations |
| Clinical trials | Small sample sizes, short duration, heterogeneity | Large-scale, long-term randomized controlled trials with standardized endpoints | Strengthen causal inference |
| Interindividual variability | Microbiome, genetics, metabolism differences | Precision nutrition and stratified intervention approaches | Identify responders vs. non-responders |
| Polyphenol interactions | Limited data on synergistic or additive effects | Investigation of combinations with other bioactive compounds | Optimize therapeutic potential |
| Safety and toxicity | Limited long-term human data, especially for supplements | Dose-dependent safety assessment and toxicological profiling | Ensure safe clinical application |
| Biomarkers | Lack of validated exposure and response markers | Integration of metabolomics-based biomarkers | Improve exposure assessment |
| Gut–brain axis | Mechanistic pathways not fully validated in humans | Human studies on microbiota-derived metabolites | Enhance mechanistic understanding |
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Mózes, N.; Varga, J.T.; Szwajgier, D.; Kryczyk-Poprawa, A.; Zábó, V.; Lehoczki, A.; Lipécz, Á.; Csípő, T.; Fazekas-Pongor, V.; Major, D.; et al. Dietary Polyphenols in Brain Aging: Molecular Mechanisms and Implications for Neurodegeneration. Nutrients 2026, 18, 1470. https://doi.org/10.3390/nu18091470
Mózes N, Varga JT, Szwajgier D, Kryczyk-Poprawa A, Zábó V, Lehoczki A, Lipécz Á, Csípő T, Fazekas-Pongor V, Major D, et al. Dietary Polyphenols in Brain Aging: Molecular Mechanisms and Implications for Neurodegeneration. Nutrients. 2026; 18(9):1470. https://doi.org/10.3390/nu18091470
Chicago/Turabian StyleMózes, Noémi, János Tamás Varga, Dominik Szwajgier, Agata Kryczyk-Poprawa, Virág Zábó, Andrea Lehoczki, Ágnes Lipécz, Tamás Csípő, Vince Fazekas-Pongor, Dávid Major, and et al. 2026. "Dietary Polyphenols in Brain Aging: Molecular Mechanisms and Implications for Neurodegeneration" Nutrients 18, no. 9: 1470. https://doi.org/10.3390/nu18091470
APA StyleMózes, N., Varga, J. T., Szwajgier, D., Kryczyk-Poprawa, A., Zábó, V., Lehoczki, A., Lipécz, Á., Csípő, T., Fazekas-Pongor, V., Major, D., Varga, P., Matiscsák, A., & Fekete, M. (2026). Dietary Polyphenols in Brain Aging: Molecular Mechanisms and Implications for Neurodegeneration. Nutrients, 18(9), 1470. https://doi.org/10.3390/nu18091470

