ABSTRACT The human skin microbiome is attracting increasing attention due to its association with health. However, comprehensive knowledge about the impact of various factors on skin microbiome variation and their comparative magnitudes remains to be investigated. Here, we profiled the human skin microbiome through an integrated analysis of public datasets. Skin microbiomes exhibit high diversity and possess distinct co‐occurrence patterns, based on which they have been classified into several modules. Key host and environmental factors were assessed for microbiome associations, and lifestyle habits (such as alcohol intake and physical activity) were notably found to be highly impactful. We thus conducted a local cohort for validation, and the results are highly consistent. Through machine learning‐based analysis, we further identified potential microbial biomarkers and demonstrated accurate bidirectional prediction based on either the skin microbiome or alcohol intake. Our study reveals that alcohol intake is a primary driver of skin microbial community structure, exhibiting an effect size comparable to traditional host factors. This work advances the skin microbiome field by revealing skin‐specific ecology and establishing it as a promising lifestyle mirror and physiological predictor. Clinical Trial Registration Clinical trial registration number: NCT05804851.

The gut microbiota plays an important role in host physiology and is highly influenced by dietary factors. This study aimed to investigate the effects of cricket powder (CP) supplementation on gut microbiota composition in high-fat diet-fed C57BL/6J mice. Male C57BL/6J mice were fed a normal diet or a high-fat diet. Mice fed the high-fat diet were administered low, medium, or high doses of CP by gavage. Serum lipid levels and liver-related biochemical indicators were measured, and gut microbiota composition was analyzed using 16S rRNA gene sequencing. We found that CP supplementation significantly (p < 0.05) altered gut microbiota diversity and community structure, with differences observed among CP doses. Alpha diversity indices were significantly reduced after the intervention (p < 0.05). Beta diversity analysis showed no significant separation among groups before the intervention, whereas a clear separation in gut microbiota structure was observed after the intervention. Correlation analysis further revealed that beneficial bacterial genera, including Lactobacillus, Bifidobacterium, and Akkermansia, were negatively associated with lipid-related parameters. Overall, these findings suggest that CP supplementation can modulate gut microbiota composition under high-fat dietary conditions, indicating its potential role in metabolic regulation.

The protein-level functionalities of the human gut microbiota in large populations, and their associations with host factors, remain unexplored. This study reports a metaproteomic study of 1,967 fecal samples from 1,399 middle-aged and elderly Chinese individuals, identifying microbial functions linked to 44 phenotypes. We uncover aging-associated functional shifts in carbon metabolism and energy production driven by species within the Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota. Across metabolic diseases, we observe the consistent depletion of Bacillota species and their proteins involved in carbohydrate, energy, amino acid metabolism, and short-chain fatty acid production. We also identify medication-associated features across diabetes, hypertension, and dyslipidemia. Validated in an independent cohort, Megasphaera elsdenii emerged as a hub species in type 2 diabetes. Experimental validation indicates that M. elsdenii is promoted by antidiabetic drugs and may regulate glucose homeostasis through butyrate production. This study provides protein-level evidence of microbial functions in health and disease, highlighting potential therapeutic targets.

BACKGROUND:To examine serum purine metabolites as biomarkers of maternal dietary purine intake and their associations with glycaemic control and preterm birth during pregnancy. METHODS:We included 1480 pregnant Chinese women with gestational diabetes mellitus (GDM) from the Westlake Precision Birth Cohort (WeBirth) at mid-pregnancy, divided into discovery (n = 1230) and internal validation (n = 250) subcohorts. Linear regression was used to assess associations between serum metabolites, dietary purine intake, and continuous glucose monitoring (CGM) metrics. A purine score was developed and evaluated for associations with glycaemic control and preterm birth, with replication in 936 pregnant women from the Tongji-Huaxi-Shuangliu Birth Cohort (THSBC). FINDINGS:Serum purine level was associated with dietary purine intake and with the mean of daily difference (β = 0.096 [95% CI, 0.038, 0.15]). The association between higher serum purine and preterm birth risk in the WeBirth cohort (OR = 1.29 [95% CI, 1.06, 1.52]) was replicated in the THSBC cohort. Early-pregnancy serum purine also predicted GDM risk (OR = 1.38 [95% CI, 1.13, 1.63]) in the THSBC. A purine score comprising purine, adenine, 6-O-methylguanine, and uric acid showed consistent associations with glycaemic variability and preterm birth across both cohorts. INTERPRETATION:Reflecting dietary purine intake, serum purine level and purine score are associated with greater glycaemic variability and higher preterm birth risk. Monitoring dietary purine intake may improve glycaemic control in GDM and prevent pregnancy complications. FUNDING:National Key R&D Program of China; National Natural Science Foundation of China; Zhejiang Provincial Key Laboratory Construction Project; Sichuan Provincial Natural Science Foundation.

Older individuals often live with diverse combinations of chronic diseases. However, whether multimorbidity contributes to glycaemic dysregulation remains unclear. Here we show that cumulative disease trajectories shape interindividual glycaemic variability throughout the ageing process. Tracking 1,398 participants in the Guangzhou Nutrition and Health Study cohort over 12 years, we develop a systemic multimorbidity index (MMI-system) that reflects the cumulative burden of chronic disorders. We also measure individual glycaemic dynamics and responses to dietary challenges using continuous glucose monitoring at the latest follow-up visit (mean age, 69.2 years). MMI-system exhibits dose-dependent associations with glycaemic variability and sensitivity to dietary challenges, independent of diabetes status. Longitudinal proteome mapping reveals that lipid homeostasis proteins explain 12.9% of the association between MMI-system and personalized dietary responses. These findings are independently validated in the China Health and Nutrition Survey cohort. Overall, our study suggests that integrating longitudinal multimorbidity profiling with circulating proteomics may enhance precision glycaemic management, offering actionable insights for dietary interventions in the older population.

INTRODUCTION:Chronic kidney disease (CKD) is a major health burden, yet its underlying mechanisms and early predictors remain poorly understood. OBJECTIVES:This prospective study identified serum proteins associated with incident CKD and examined their upstream determinants related to inflammation and diet. METHODS:A total of 2,182 participants with baseline serum proteomic data and repeated measurements of estimated glomerular filtration rate (eGFR) over four 3-year intervals were included. Proteins associated with incident CKD were identified using multivariable-adjusted models, with internal validation from repeated measurements and external replication in the UK Biobank (UKB). Associations of CKD-related proteins with serum inflammatory markers, inflammation-related dietary indices, and serum carotenoids were also examined. RESULTS:Twenty-two proteins were associated with 9-year CKD risk (11 positively and 11 inversely; adjusted p < 0.05). A combined protein score predicted CKD with an area under the curve (AUC) of 0.75 in the discovery cohort, 0.76 in the internal validation using averaged protein data, and 0.70 in the UKB replication using 15 overlapping proteins. Standardized hazard ratios of CKD risk ranged from 1.31 to 1.66 for the top 4 risk proteins (PEDF, CFAD, RET4, APOH) and from 0.77 to 0.80 for the top 4 protective proteins (A1BG, A2AP, ENAM, GPX3) (all adjusted p < 0.01). Inflammatory markers (e.g., C-reactive protein) were positively associated with deleterious proteins and inversely associated with protective ones. Higher serum carotenoid concentrations and DASH diet scores were associated with lower inflammatory markers and more favorable CKD-related protein profiles. CONCLUSIONS:We identified 22 serum proteins associated with CKD incidence, supporting their potential for early prediction and mechanistic insight. Systemic inflammation was adversely associated with, whereas circulating carotenoids were beneficially associated with, CKD-related protein profiles.

BackgroundType 2 diabetes (T2D) is a global metabolic disorder characterized by chronic hyperglycemia and disruption of the gut microbiome. Nutritional and microbiota-targeted interventions have emerged as promising strategies for glycemic management, yet longitudinal clinical evidence integrating microbial and metabolic mechanisms remains limited. This study investigated microbiota-metabolites alterations during a standardized dietary herbal intervention (QingYun7, QY7) and explored their relationship with glycemic regulation across both animal study and clinical settings.MethodsThe metabolic and microbial effects of QY7 were first evaluated in diabetic rats through measurements of blood glucose, and gut microbiota composition. Subsequently, a prospective cohort of 385 patients with T2D received QY7, with longitudinal monitoring of fasting, random, and 2-h postprandial glucose, gut microbiota, and serum metabolites across multiple time points. Fecal microbiota transplantation (FMT) from patients before and after intervention into antibiotic-treated mice was performed to evaluate the causal contribution of the gut microbiome to glycemic improvement. Mediation analyses were conducted to delineate potential pathways linking gut microbes, serum metabolites, and glucose outcomes.ResultsIn diabetic rats, QY7 administration significantly reduced blood glucose, and restored gut microbial composition. In the clinical cohort, the intervention was associated with rapid and sustained reductions in fasting, random, and postprandial glucose levels, accompanied by consistent remodeling of the gut microbiome and serum metabolite profile. FMT experiments demonstrated that microbiota derived from post-intervention patients conferred improved glycemic responses in recipient mice, supporting a causal role of gut microbiota in metabolic regulation. Serum metabolomic profiling revealed significant alterations, including enrichment of branched-chain amino acid related pathways. Mediation analyses identified key metabolites, phenyllactic acid, 3-methyl-2-oxobutanoic acid, and anandamide, as mediators linking specific bacterial taxa (Alistipes shahii and Limosilactobacillus mucosae) to fasting and postprandial glucose levels.ConclusionThis study provides translational evidence that a dietary herbal intervention associated with glycemic improvement in T2D through microbiota-mediated metabolic reprogramming. Gut microbiome alterations induced by the intervention exerted causal effects on blood glucose regulation, with serum metabolites acting as potential key intermediaries. These findings highlight the mechanistic insight in nutrition-based microbiome modulation strategy in T2D.

Background and Objectives: Recent large-scale studies have consistently linked healthy dietary patterns to improved cardiometabolic health; however, the underlying biological pathways remain largely unclear, especially in non-European populations. In this study, we leverage data from four population-based cohorts (UK Biobank, NEO study, GNHS, and 10K) to investigate both common and cohort-specific biological pathways linking healthy dietary patterns to cardiometabolic disease through multi-omics profiling. Material and methods: In each cohort, we first assessed the associations between each of the five major dietary pattern scores (i.e., AMED, hPDI, DII, AHEI, and EDIH) and cardiometabolic disease risk using Cox or logistic regression models. To explore the potential mediating role, metabolomics and proteomics measurements were incorporated into the models. All models were adjusted for relevant confounders, and false discovery rate correction was applied to account for multiple testing. Results: With a total of 71,679 individuals without pre-existing cardiometabolic disease across four participating cohorts (UKB: 54,024, NEO: 4,838, GNHS: 3,201, and 10K: 9,616), we confirmed that adherence to healthy dietary patterns was associated with a 5-10% reduced risk of cardiometabolic disease. Three common biological pathways were identified: (1) mediation via large HDL particles and apolipoprotein F; (2) mediation via DNAJ/Hsp40 and triglyceride-rich lipoproteins; and (3) mediation via CRHBP-regulated HPA axis activity affecting triglyceride-rich lipoproteins. Conclusions: Our integrative multi‐omics analysis across diverse populations identifies novel biomarkers that connect healthy dietary patterns with cardiometabolic risk. These findings deepen our understanding of the biological mechanisms underlying diet‐related disease and hold promise for enhancing the development of precision nutrition interventions. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The NEO study is supported by the participating departments, the Division and the Board of Directors of the Leiden University Medical Centre, and by the Leiden University, Research Profile Area "Vascular and Regenerative Medicine". R.L-G is supported by JPI HDHL NUTRIMMUNE DIYUFOOD project. K.D is supported by China Scholarship Council (No. 202206210140). All the funders did not participant in the process of the whole study. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All studies obtained ethical approval from their respective institutional ethics committees, and all participants provided written informed consent. All the four datasets that we used in the manuscript are de-identified. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Original data are subject to access restrictions according to each cohort's data sharing policies.

Dementia is a growing global health challenge with limited pharmacological treatments. Emerging evidence from randomized controlled trials and prospective cohort studies suggests that healthy dietary patterns may contribute to the prevention or delay of cognitive decline. This review summarizes current evidence on the relations of overall dietary patterns and specific foods and nutrients to cognitive aging, with a particular focus on the potential role of gut microbiota, which is largely shaped by diet. Certain healthy dietary patterns, such as the Mediterranean and the Mediterranean–DASH Intervention for Neurodegenerative Delay (MIND) diets, characterized by specific foods (e.g., vegetables and fruits) and dietary nutrients (e.g., n-3 fatty acids, B vitamins, and carotenoids) have shown potential benefits on cognitive health. However, inconsistencies across study findings necessitate further investigation. We review how the gut microbiota may mediate or moderate the diet-cognition association, or serve as a marker for cognitive health, particularly through mechanisms involving metabolic, immune, and neuroinflammatory pathways. Finally, we highlight key methodological challenges, including variability in exposure assessment, study design, and population heterogeneity, and propose a roadmap for future research, advocating for large-scale, multi-omics studies across diverse populations. These efforts are expected to facilitate the development of precision nutrition strategies for the prevention of cognitive decline and dementia.

The gut microbiome undergoes significant alterations during pregnancy. Perturbations in these microbial communities are increasingly associated with a range of pregnancy complications, including miscarriage, gestational diabetes mellitus, preeclampsia, preterm birth, and fetal growth restriction, among others. This review synthesizes current evidence on the dynamic changes in the maternal gut microecosystem including bacterial, fungal, and viral communities throughout gestation and examines its relationships with various pregnancy complications. We also summarize the underlying mechanisms driving these interactions, focusing on metabolic regulations involving short-chain fatty acids, bile acids, indoles, sex hormones, intestinal barrier integrity, and the modulation of maternal immune responses essential for fetal tolerance. Additionally, we discuss the lasting impact of the maternal microbiome on offspring health via vertical transmission and developmental programming. This review provides a conceptual framework that integrates mechanistic insights with clinical findings, with the goal of informing future research and supporting the development of microbiome-based interventions to improve maternal and neonatal health outcomes.

Temporal alterations in the host lipidome and gut microbiome, and their dynamic interactions, in the progression of antenatal depression remain poorly understood. Here, we characterized the maternal lipidome and gut microbiome in 1086 Chinese pregnant women from the Tongji-Huaxi-Shuangliu Birth Cohort using 2954 serum and 2812 fecal samples collected longitudinally across early, mid, and late pregnancy. Our analyses identified 95 host lipids, and seven gut microbial genera associated with antenatal depression. Period-specific and longitudinal analyses indicated that lysophosphatidylethanolamines (LPEs) exhibited concordant associations with antenatal depression. In addition, temporal analyses suggested that decreases in the abundances of gut microbial genera [Ruminococcus]_gnavus_group and Enterococcus preceded the onset of antenatal depression and demonstrated extensive associations with LPEs and acylcarnitines (CARs). Integrative analyses revealed bidirectional concurrent and temporal crosstalk between microbiota-lipid axis and antenatal depression, with LPEs and medium- and long-chain CARs constituting key molecules of this axis. Collectively, this study offers valuable insights into the interplay between host lipidome and gut microbiome in the development of antenatal depression, laying a foundation for future investigations into the microbiota-lipid axis during pregnancy.

Interindividual variability in metabolic responses to diets complicates the relationship between nutrition and metabolic health, which highlights the existence of metabolic heterogeneity across populations. This variability challenges the conventional "one-size-fits-all" approach to dietary recommendations and underscores the need for precision nutrition. In the current era, characterized by breakthroughs in sophisticated data collection technologies, the explosion of big data, and progress in artificial intelligence, the implementation of precision nutrition is becoming increasingly feasible. This review aims to summarize potential sources of metabolic heterogeneity from the angle of the host genome, gut microbiome, and brain connectome to explore the implications of their interactions with diet. Furthermore, we discuss the application of artificial intelligence in leveraging multimodal data for predicting individualized dietary responses. Aggregating data on host genetics, gut microbes, and brain activity profiling offers profound insights into the personalized response to diets. We also highlight the development of individual-specific predictive models that combine n-of-1 study designs with advanced wearable technologies and machine learning algorithms, thereby placing the individual at the center of nutritional decision-making. Finally, this review summarizes current challenges in the field and outlines potential directions for advancing precision nutrition.

Abstract Gestational diabetes mellitus (GDM) reflects metabolic dysregulation that becomes clinically apparent during pregnancy and shares key pathophysiological features with broader forms of diabetes. Gut microbiome‐host metabolic interactions may contribute to this process, yet their role in early pregnancy remains incompletely understood. In this prospective nested case‐control study within the Tongji‐Huaxi‐Shuangliu Birth Cohort, 784 pregnant women, including 222 who developed GDM, underwent first‐trimester gut metagenomic and plasma lipidomic profiling. Cross‐omics analyses were performed to identify microbiome‐lipid associations and potential mediation patterns. Women who later developed GDM showed reduced gut microbial diversity and altered microbial profiles in early pregnancy. We identified 26 microbial species associated with GDM risk, with seven species, including Ruminococcus bicirculans ( R. bicirculans ), showing concordant associations in external type 2 diabetes populations. Microbial pathways related to fatty acid and lipid biosynthesis were enriched in women at higher risk. Plasma lipidomics revealed widespread alterations, particularly among glycosphingolipid‐related metabolites. Integrated analyses suggested that lipidomic variation statistically accounted for part of the microbiome‐GDM association. A class‐level dihexosylceramide feature, DHC 24:1, consistent with lactosylceramide‐related metabolites, emerged as a potential mediator and was prioritized for exploratory follow‐up. Experimental analyses provided functional support for a microbiome‐lipid‐host interaction axis. R. bicirculans promoted lactosylceramide 24:1 production in vitro , bacterial colonization and metabolite administration improved insulin tolerance in vivo , and lactosylceramide 24:1 modulated insulin‐stimulated AKT signaling dynamics in hepatocytes. These findings identify a gut microbiome‐lipid axis associated with metabolic dysregulation in pregnancy and suggest a potential mechanism linking microbial metabolism to host insulin signaling.

Tea consumption may be associated with skeletal muscle health, but longitudinal evidence based on repeated assessments remains limited. We examined the associations of tea intake and serum biomarkers with repeated skeletal muscle measures and explored whether these associations might be partly explained by multi-omics features. In this prospective cohort, 3408 adults were followed for approximately 12 years. Skeletal muscle mass was measured by dual-energy X-ray absorptiometry, handgrip strength by digital dynamometry, gut microbial taxonomic and functional profiles by shotgun metagenomic sequencing, serum proteins by data-independent acquisition mass spectrometry, and fecal metabolites by targeted UPLC-MS/MS metabolomics. Linear mixed-effects models examined longitudinal associations, and mediation analyses estimated indirect effects. In longitudinal analyses, higher tea consumption frequency was associated with greater appendicular skeletal muscle mass, appendicular skeletal muscle index, and handgrip strength (β: 0.037–0.140; 95% CI: 0.002–0.205). Higher circulating flavan-3-ols showed similar associations with these muscle-related outcomes (β: 0.085–0.174; 95% CI: 0.007–0.254), whereas no significant associations were observed with walking speed. Exploratory multi-omics analyses identified tea-related differences in gut microbial species and functional pathways, fecal metabolites, and circulating proteins, including Gemmiger formicilis, amino acid biosynthesis pathways, fructose 1,6-bisphosphate, VTN, CFI, CNDP1, and ITIH4. Exploratory mediation analyses identified statistical indirect associations involving multi-omics features, with estimated proportions mediated ranging from 4.5% to 19.0%. Overall, higher tea consumption and circulating biomarkers were associated with greater skeletal muscle mass and strength, accompanied by distinct multi-omics features that may provide potential biological links between tea exposure and muscle-related outcomes.

BACKGROUND:The alternative pathway (AP) plays a crucial role in triggering complement activation and promoting chronic inflammation. This study aims to investigate the longitudinal association between AP and atherosclerosis, and explore the potential role of gut microbiota and inflammatory factors in their association. METHOD:This study was based on a 9-year prospective cohort of 3382 participants from Guangzhou, China (mean age±SD, 57.75±5.85 years; 68.8% female), with data on serum APACPs (AP-associated complement proteins) and carotid plaque (measured by ultrasound) repeatedly measured up to 3×. Baseline inflammatory markers were evaluated in 923 participants, and gut shotgun metagenome data were obtained from 1567 participants. Mendelian randomization analysis was performed using genome-wide significant genetic variants as instrumental variables to suggest potential causal associations. RESULTS:Both longitudinal and prospective analyses consistently demonstrated positive associations between carotid plaque and 3 complement components: C3 (complement C3; odds ratios [95% Cl] for the highest versus lowest quartiles, 1.36 [1.07-1.74] in longitudinal analysis and 1.29 [1.06-1.56] in prospective analysis), CFB (complement factor B; 1.36 [1.07-1.72] in longitudinal analysis and 1.39 [1.15-1.69] in prospective analysis), and CFH (complement factor H; 1.39 [1.10-1.76] in longitudinal analysis and 1.31 [1.07-1.61] in prospective analysis). Mendelian randomization analysis suggested a potential causal association between CFB and carotid plaque. Inflammatory factors (CRP [C-reactive protein] and IL-6 [interleukin-6]) and microbial species (Ruminococcus bromii, Roseburia hominis, Rothia mucilaginosa, Collinsella stercoris, Olsenella scatoligenes, and Bacteroides massiliensis) were significantly associated with both APACPs and carotid plaque (P<0.05). For example, butyrate-producing bacterium R bromii was inversely associated with CFB and carotid plaque (odds ratios [95% CI], 0.83 [0.79-0.88]) and may mediate the CFB-carotid plaque association (proportion mediated, 13.5%; P=0.005). Microbial risk score (weighted sum of selected microbial species; proportion mediated, 42.6%; P<0.001) and total immune factors (the sum of all inflammatory factors; proportion mediated, 19.0%; P=0.002) mediated the association between Total-APACPs (sum of standardized carotid plaque-related APACPs [C3, CFB, and CFH]) and carotid plaque. CONCLUSIONS:Our study showed a negative association between the AP and carotid plaque in a longitudinal cohort. Gut microbiota and inflammatory biomarkers may provide mechanistic insights into the association between the AP and atherosclerosis. Our findings pave the way for the development of new therapeutic targets for atherosclerosis.

Circulating proteomics acts as an intermediate phenotype linking genetic susceptibility to MASLD. However, current evidence rarely establishes a direct concordance between serum protein levels and hepatic gene expression. We aimed to perform a multi-cohort joint analysis of serum proteomics and transcriptomics to characterize essential molecular features for MASLD. For the serum proteomic analysis of simple steatosis (MASL), we conducted a cross-sectional investigation in an MRI-based cohort (N/cases: 1048/428) and further examined the prospective association between protein features and MASL incidence (N/cases: 2945/1947) ascertained by ultrasonography over a median 9.8-year follow-up in the Guangzhou Nutrition and Health Study (GNHS) cohort. In parallel, we characterized fibrosis and MASH-related transcriptional features using liver transcriptomics from the MASH cohort (N = 94) and validated these gene signatures for MASH in liver transcriptomes from the independent Japanese and German populations (N = 98 and 59). The serum proteomic analysis identified the C3, C9, F9, VTN, AFM, APOD, APOF, and SHBG proteins were significantly associated with MASL risk (P < 0.05). Liver transcriptomic analysis revealed a coordinated downregulation of C9, C4BPB, C1RL, APOF, and ITIH4 in the high NAS group, implicating dysregulated complement activation as a critical mechanism driving disease progression. Furthermore, SHBG, A2M, GSN, C7, LUM, IGHG3, and IGFALS were associated with liver fibrosis stages, and pathways related to extracellular exosomes and vesicles were implicated in fibrotic development. Consistently, in the Japanese and Germany cohorts, APOF, GSN, and LUM exhibited aberrant expression in both MASH patients and those with high NAS scores. The multi-cohort study identified specific serum protein signatures associated with MASL risk, which correspond to dysregulated gene expression patterns in hepatocytes. These findings bridge the gap between systemic circulatory changes and intrahepatic pathological progression, providing not only robust non-invasive biomarkers for early stratification but also potential mechanistically-driven therapeutic targets for halting the progression of MASLD.

The gut microbiome undergoes profound changes during aging, including shifts in the microbial antibiotic resistome: the collective repertoire of antibiotic resistance genes (ARGs). We developed a language model-based ARG explorer (LARGE), which used frozen ESM-2 and FGeneBERT encoders to embed protein sequences and three independent multilayer perceptron classifiers to predict resistance type, mechanism, and gene name. LARGE was trained on 34,008 ARG and 30,309 non-ARG sequences from the NCRD95 and UniProt databases and benchmarked against DeepARG, RGI, PLM-ARG, and ARGNet using F1-scores on multiple independent test sets. We applied LARGE to a longitudinal cohort (GNHS, n = 1078, mean baseline age 64.6 years), and validated key findings in independent cohorts (CHNS, n = 356; ZMSC, n = 1361). Linear mixed-effects models were used to assess age-related ARG trajectories, and logistic regression examined associations with 13 chronic diseases. In benchmark test, LARGE substantially outperformed all four tools, achieving superior F1-scores. In longitudinal cohorts, LARGE revealed declining ARG burdens in dominant resistance drug classes and identified 31 species with significant ARG changes. The ARGs of these 31 species are closely associated with multiple age-related chronic diseases, such as chronic kidney disease and coronary heart disease; a specific chronic kidney disease ARG score was consistently associated with disease risk in both discovery and validation cohorts. The findings highlight the pivotal role of aging in resistome evolution and potentially provide microbiome-targeted interventions to mitigate antibiotic resistance and promote healthy aging.

Cardiovascular diseases (CVDs) are leading causes of mortality and morbidity globally, including conditions such as coronary heart disease, stroke, and heart failure. Dietary interventions play an essential role in the prevention and management of CVDs, and vegetarian diets have gained increasing attention for their potential cardioprotective effects. The vegetarian diet, characterized by excluding meat, seafood, and any products derived from these foods, has shown substantial health benefits in mitigating CVD risks. This chapter reviews the relationship between vegetarian dietary patterns and CVD risk, by integrating current scientific evidence from epidemiological studies, clinical trials, and mechanistic research. Most prospective cohort studies and randomized controlled trials have demonstrated the protective role of vegetarian diets in the development of CVDs and subtypes as well as cardiometabolic risk factors such as dyslipidemia, inflammation, hypertension, diabetes, and obesity. Additionally, key metabolic pathways are regulated by vegetarian diets. Taken together, this chapter aims to provide a comprehensive overview of how vegetarian diets impact cardiovascular health, inform dietary guidelines and healthcare policies, and guide future research directions in preventive cardiology.

The genetic architecture of glycemic dynamic metrics derived from continuous-glucose monitoring (CGM) across different populations remains poorly understood. Here, we conducted a trans-ethnic genome-wide association study (GWAS) meta-analysis of 20 CGM-derived glycemic traits, building upon a previously established European-ancestry CGM dataset and extending it through the inclusion of additional cohorts, in up to 9677 individuals originating from 2051 Chinese, 901 Dutch, and 6725 Israelis. Across 20 glycemic traits, we identified 18 genome-wide significant associations, of which 9 met study-wide significance, and three variants were novel. These variants indicated a shared genetic basis for continuous glycemic regulation and exhibited consistent patterns with those of sequential fingerstick glucose tests. Our findings further demonstrated that the identified genetic variants were enriched in pathways related to the nervous system. These findings were further supported by observed associations with brain magnetic resonance imaging (MRI) metrics, high CGM-related gene expression and co-regulation of quantitative trait loci in brain tissues. Additionally, we observed a positive relationship between genetic liability for the coefficient of variation (CV) and total cholesterol and a bi-directional putative causal relationship between hyperglycemia and type 1 diabetes across trans-ethnic populations. Moreover, we established a polygenic risk score (PRS) for additional participants and reported that certain glycemic traits were significantly associated with the risk of diabetes or pre-diabetes. These variants constituting the PRS demonstrated high transferability across general populations and pregnant women. Overall, our study yields unique insights into the high trans-ethnic and generalizable genetic architecture of CGM-derived glycemic profiles, supporting improved characterization of interindividual differences in glycemic dynamics and underscoring the potential for more personalized glucose management.