Mengyang Wang

Metabolic dysfunction-associated steatotic liver disease (MASLD) links hepatic lipid accumulation with insulin resistance, disturbed sleep, and impaired muscle health. This critical narrative review integrates clinical, metabolomics, and mechanistic evidence identified through a structured multi-database search and citation-tracing workflow covering PubMed, Web of Science, Scopus, and Google Scholar to 30 September 2026, focusing on circadian regulation, exercise, and muscle-preserving care. Hepatic clocks coordinate nutrient handling, bile-acid signaling, mitochondrial metabolism, and redox balance. Sleep and meal-timing disruption are associated with adverse metabolic phenotypes, although MASLD-specific causal evidence remains limited. Exercise improves liver and metabolic outcomes, but no universal optimal session time has been established. Time-restricted eating should be evaluated alongside energy intake, diet quality, protein distribution, sleep, and adherence. Complex lipids, acylcarnitines, bile acids, ketone bodies, and amino acids offer complementary research signals; their interpretation requires standardized sampling, analytical quality control, and external validation. Circulating concentrations should not be equated with tissue flux or treatment benefit. Clinical care should integrate fibrosis and cardiometabolic risk assessment with sustainable weight management, progressive resistance and aerobic exercise, adequate protein, and sleep assessment. Future trials should pair repeated, timed metabolite measurements with liver, body-composition, strength, and physical-function outcomes to establish whether these signatures improve clinical decisions.

Acute kidney injury (AKI) is characterized by tubular epithelial stress, inflammation, and metabolic dysfunction, yet the transcriptional programs associated with effective metabolic recovery remain poorly defined. Ergothioneine (EGT) has demonstrated renal and mitochondrial protective effects, but its potential involvement in conserved tubular injury programs is unclear. Here, we integrated human and mouse transcriptomic datasets to identify injury-associated programs that were conserved across proximal tubules and oppositely associated with EGT treatment. Pathway-level analyses revealed coordinated inflammatory and redox responses in human AKI, while the mouse intervention model showed broad reversal of disease-associated transcription following EGT treatment. Cross-species analysis of 9700 common orthologs identified seven pathways that consistently exhibited human injury-associated, mouse disease-associated, and EGT-opposed enrichment after removal of cytosolic ribosomal genes. These pathways converged on a mitochondrial bioenergetic–translation program involving oxidative phosphorylation, respiratory electron transport, complex I biogenesis, and mitochondrial translation, together with mTORC1 and MYC signaling. Within this conserved program, OXA1L, NDUFAB1, and TUFM repeatedly contributed to multiple pathway leading edges, highlighting them as potential candidates for functional investigation. Collectively, our findings identify a conserved mitochondrial transcriptional program associated with EGT in injured proximal tubules and provide a mechanistic framework for testing whether modulation of mitochondrial bioenergetics and translation contributes to the renal protective effects of EGT.

Introduction: Cardiometabolic multimorbidity (CMM) is increasingly common and carries substantial clinical and public-health burden. The cholesterol-high-density lipoprotein-glucose (CHG) index has been linked to adverse cardiometabolic outcomes, but prospective evidence comparing baseline and cumulative exposure and testing external reproducibility under design-appropriate survey methods remains limited. Methods: We analyzed a baseline CHG cohort ( n = 7,077) and a cumulative-CHG subcohort ( n = 4,881) from the China Health and Retirement Longitudinal Study (CHARLS), and conducted a supportive external replication analysis in the National Health and Nutrition Examination Survey (NHANES; 1999–2018; n = 23,797). Cox models were used in CHARLS and fasting-subsample survey-weighted logistic models in NHANES. CHG and cumulative CHG were modeled per 1-standard deviation (SD) increment and by tertiles. Restricted cubic spline and threshold analyses characterized dose–response patterns. Sensitivity analyses included a stricter disease-free cumulative CHARLS cohort and additional hypertension adjustment in NHANES. Results: Higher baseline CHG in CHARLS was associated with greater incident CMM risk (adjusted hazard ratio [HR] per 1-SD increase, 1.55; 95% CI, 1.39–1.73); participants in the highest tertile had higher risk than those in the lowest tertile (adjusted HR, 2.93; 95% CI, 2.15–4.00). Associations were stronger for cumulative CHG (adjusted HR per 1-SD increase, 1.75; 95% CI, 1.61–1.89; adjusted HR for T3 vs. T1, 5.46; 95% CI, 3.91–7.63). In weighted NHANES analyses, CHG remained positively associated with prevalent CMM (adjusted odds ratio per 1-SD increase, 1.91; 95% CI, 1.75–2.08; adjusted OR for T3 vs. T1, 3.58; 95% CI, 2.73–4.69). Baseline CHG in CHARLS showed a significant overall association without clear nonlinearity, whereas cumulative CHG in CHARLS and CHG in NHANES showed significant nonlinear patterns. Sensitivity analyses were directionally consistent with the main findings. Conclusions: Higher baseline and cumulative CHG were associated with greater incident CMM risk in the longitudinal CHARLS analyses, with larger effect estimates observed for cumulative CHG. A positive association was also observed between CHG and prevalent CMM in the cross-sectional NHANES analysis. These findings suggest that CHG, particularly its cumulative exposure, may serve as a potential marker of CMM risk and burden. However, further prospective validation is needed before CHG can be used for clinical risk prediction or to define decision thresholds.

Functional decline is a major clinical feature of Alzheimer's disease (AD), yet the blood metabolic pathways associated with lifestyle factors and multidimensional functional performance across cognitive stages remain incompletely characterized. We applied a pathway-level blood metabolomics framework to harmonized, de-identified data from aging and dementia-related cohort resources spanning cognitively normal aging (CN), mild cognitive impairment (MCI), and AD. Metabolites were mapped to curated pathways and summarized into pathway activity scores across five domains: energy metabolism, amino acid metabolism, lipid metabolism, inflammation/oxidative stress, and microbiome-linked metabolism. We evaluated associations among physical activity, diet quality, pathway activity scores, and functional outcomes, including activities of daily living, gait speed, grip strength, global cognition, composite function, and frailty. To summarize pathway patterns jointly associated with physical activity and diet quality, we derived a lifestyle-modulated metabolic pathway score (LMPS) using elastic net regression with cross-validation, out-of-fold score estimation, and bootstrap stability assessment. Lifestyle-associated pathway activity showed coordinated patterns across metabolic domains and was associated with functional performance across cognitive groups. Higher LMPS values were associated with better physical and cognitive function and lower frailty, with graded differences observed across CN, MCI, and AD. Internal robustness analyses indicated greater stability at the pathway-domain level than at the individual-pathway coefficient level. Sensitivity analyses adjusting for cognitive group attenuated but did not eliminate the directionally consistent associations between LMPS and major functional outcomes. Convergent pathway patterns involved mitochondrial energy metabolism, lipid remodeling, inflammatory regulation, and microbiome-related metabolism. Pathway-level blood metabolomics identified lifestyle-associated metabolic patterns related to multidimensional functional outcomes across the cognitive aging spectrum. LMPS provides a data-driven summary of lifestyle-associated pathway variation in this cohort and may help generate hypotheses about metabolic correlates of functional performance. Independent and longitudinal validation will be required to determine its reproducibility, temporal relevance, and translational utility.

Cardiometabolic diseases are increasingly understood as disorders involving compartment-specific redox disruption rather than a uniform excess of reactive oxygen species. This narrative review synthesizes evidence for a proposed gut microbiota–mitochondria ferroptosis framework in which dysbiosis-derived lipopolysaccharide, trimethylamine N-oxide, short-chain fatty acids, bile acids, and tryptophan metabolites may modulate mitochondrial reactive species production, antioxidant defenses, iron handling, lipid peroxide detoxification, and inflammatory signaling. The reference set was assembled through searches of PubMed and Web of Science Core Collection, supplemented by targeted Google Scholar searches and citation chaining during manuscript preparation and revision through June 2026 and was organized around microbial metabolites, mitochondrial redox biology, ferroptosis pathways, disease-specific evidence, and redox-targeted interventions. Because this is a narrative synthesis rather than a systematic review, the framework should be interpreted as hypothesis-generating rather than as a systematically validated pathological model. Across atherosclerosis, diabetic cardiomyopathy, metabolic dysfunction-associated steatotic liver disease, obesity-associated insulin resistance, chronic kidney disease, and cardiorenal metabolic injury, the most consistent mechanistic links involve mtROS, impaired mitophagy, glutathione/GPX4 and SLC7A11 dysfunction, ACSL4-dependent lipid peroxidation, Nrf2 signaling, NLRP3 activation, and cGAS-STING-associated inflammation, although human causal evidence remains uneven. Importantly, much of the current literature supports local links within this sequence rather than a fully verified dysbiosis–metabolite–mitochondria ferroptosis–organ dysfunction chain in the same study. We therefore emphasize evidence tiers, terminology discipline, and biomarker requirements when interpreting ferroptosis-sensitive injury. Polyphenols, flavonoids, probiotics, postbiotics, melatonin, CoQ10-related strategies, mitochondria-targeted antioxidants, and ferroptosis-sensitive approaches may be most translatable when paired with microbiome, metabolomic, lipidomic, pharmacokinetic, and redox biomarkers.

Type 2 diabetes mellitus and sarcopenia are increasingly recognized as interrelated syndromes sharing pathophysiological pathways, yet empirical evidence for their reciprocal, time-dependent relationship in aging populations remains limited. Conventional analytical approaches fail to capture the dynamic, trajectory-based nature of their coprogression because of restrictive assumptions regarding state transitions and sojourn time. We conducted a prospective cohort study using harmonized data from 2 nationally representative Chinese longitudinal surveys: the China Health and Retirement Longitudinal Study and the Chinese Longitudinal Healthy Longevity Survey, with follow-up spanning 2008–2018. A semi-Markov multi-state model was employed to estimate sojourn-time-dependent transition hazards across 5 clinically defined states: diabetes-free/sarcopenia-free, diabetes-only, sarcopenia-only, comorbid diabetes-sarcopenia, and death (absorbing state). All models adjusted for time-varying sociodemographic, lifestyle, and functional covariates and accounted for competing risks. Population attributable fractions were derived via counterfactual simulation. The semi-Markov model demonstrated superior fit over the Markov specification (global ΔAkaike information criterion = 316.4), confirming strong sojourn-time dependence in transition risks. Incident diabetes was associated with an 82% higher hazard of progressing to comorbid diabetes-sarcopenia (hazard ratio = 1.82, 95% confidence interval [CI] = 1.47–2.25), while incident sarcopenia conferred a 65% elevated risk of subsequent diabetes onset (hazard ratio = 1.65, 95% CI = 1.35–2.02). These bidirectional associations remained robust across multiple sensitivity analyses. Counterfactual modeling revealed that 38.2% (95% CI = 31.5%–44.1%) of new comorbid cases could be prevented by blocking diabetes→sarcopenia progression, and 32.6% (26.8%–38.0%) by interrupting sarcopenia→diabetes progression. Strikingly, 58.9% (53.4%–64.1%) of all 5-year mortality was attributable to entry into any chronic disease state. These findings suggest that diabetes and sarcopenia are dynamically and bidirectionally associated in aging Chinese adults. Integrated assessment of glycemic status and muscle health may help identify older adults at elevated risk of comorbidity and mortality. Further interventional studies are needed to determine whether dual-domain prevention strategies can modify these trajectories.