Importance:Weight gain is common during menopause, and healthy dietary patterns are key to its management. However, effectiveness of different diets for weight management during this period remains unclear. Objective:To examine and compare associations of multiple dietary patterns with weight gain and obesity risk in the years surrounding menopause. Design, Setting, and Participants:This prospective, population-based cohort study included women observed over a 12-year period surrounding menopause in the Nurses' Health Study II (1989-2019). Data analysis was performed between November 2024 and May 2025. Exposures:Diet was assessed every 4 years using validated food frequency questionnaires. Dietary scores included the plant-based diet index (PDI), healthy PDI, unhealthy PDI, Mediterranean diet, Dietary Approaches to Stop Hypertension, Planetary Health Diet Index (PHDI), low-carbohydrate diet (LCD), healthy LCD, unhealthy LCD, empirical dietary inflammatory pattern, empirical dietary index for hyperinsulinemia (EDIH), and ultraprocessed food intake. Main Outcomes and Measures:The outcomes were annual changes in self-reported body weight (kilograms per year) and incident obesity. Generalized estimating equations were used to estimate annual weight change across dietary patterns. Cox proportional hazards models were used to estimate risk of obesity across dietary patterns. Results:Among 38 283 women (mean [SD] age, 45.6 [3.0] years), the mean (SD) weight gain was 0.80 (1.00) kg per year. During 340 122 person-years of follow-up, 5214 women developed obesity. After adjusting for age, race and ethnicity, marital status, income, postmenopausal hormone therapy use, parity, smoking, alcohol, energy intake, physical activity, and baseline body mass index, the reverse EDIH (quintile 5 vs 1) was associated with the largest reduction in weight gain (mean, -0.28 kg/y; 95% CI, -0.30 to -0.26 kg/y). For incident obesity, the lowest risk was observed for the PHDI (hazard ratio, 0.46; 95% CI, 0.42 to 0.51) and reverse EDIH (hazard ratio, 0.51; 95% CI, 0.46 to 0.56). EDIH showed the largest positive correlations with red or processed meats, sodium, and French fries. PHDI showed the largest positive correlations with nuts, unsaturated fats, whole grain carbohydrates, and vegetable protein. Conclusions and Relevance:In this prospective cohort study of women during menopause, adopting low-insulinemic and planetary health diets, low in red and processed meats, sodium, potatoes, and French fries and rich in nuts, legumes, fruits, vegetables, and whole grains, was associated with optimized weight management.

To identify metabolites as potential biomarkers of fructose vs glucose consumption and related metabolic changes, we conducted exploratory metabolomic profiling of fasting blood samples from participants in a double-blind, parallel-arm trial involving 31 male and female adults with overweight or obesity, both before and after supplementation with glucose- or fructose-sweetened beverages. Orthogonal Partial Least Square Discriminatory Analysis (OPLS-DA) was used to identify metabolites that could discriminate between the 2 intervention groups. Changes in 16 metabolites (5 of which are branched-chain amino acid catabolic pathway metabolites) and the branched chain keto acid (BCKA) composite score showed nominal (FDR adjusted P-value < .2, unadjusted P-value ≤ .08) differences in response to the 2 interventions. We observed a 2.19 µM (or 13%) and a 10.17 µM (or 25%) increase in ketomethylvaleric acid (P FDR = 0.04, P = .001) and 2-hydroxybutyrate (P FDR = 0.11, P = .008), respectively, after glucose supplementation compared to a null change after fructose supplementation. Notable trends after fructose supplementation included increased long- and median-chain acylcarnitines (ACs); decreased short-chain ACs; and increased homocysteine compared to the glucose supplementation. These data suggest that in people with overweight/obesity, consumption of beverages high in glucose vs fructose may differentially affect the metabolism of branched-chain amino acids and acylcarnitine species reflective of changes in fatty acid oxidation and de novo lipogenesis.

Purpose:Exfoliation glaucoma (XFG) is the most common secondary glaucoma. Prior studies suggest a higher incidence in women and links to reproductive history, implying estrogen-related pathways. Metabolomic data also indicated inverse associations with steroid-related plasma metabolites, suggesting steroid involvement in XFG pathogenesis. Methods:We conducted a nested case-control study within the Nurses' Health Study (NHS) (1980-2018), NHSII (1989-2019), and Health Professionals Follow-up Study (1986-2018), with 217 XFG suspect (XFGS)/XFG cases and 217 matched controls (62 men and 372 women). We evaluated 18 endogenous steroids and five steroid classes using conditional logistic regression. Secondary analyses examined effect modifications by age and residential latitude, and heterogeneity by disease severity (XFGS vs. XFG). Metabolite set enrichment analysis (MSEA) was used for class-level associations. Multiple comparisons were addressed using the number of effective tests (NEF) for individual steroids and false discovery rate (FDR) for steroid classes. Results:No individual steroid or steroid class met NEF- or FDR-adjusted significance thresholds, overall or by sex. Nonetheless, across both sexes, MSEA demonstrated a non-significant inverse trend between androgen levels and XFG/XFGS risk (FDR=0.22), with 11-ketotestosterone showing a nominal inverse association (OR=0.54; 95%CI=0.31-0.93; P=0.03). Progestogens showed enrichment scores in the positive trend (FDR=0.31), with a borderline positive association between progesterone and XFG/XFGS (OR=2.21; 95%CI=1.00-4.87; P=0.05). Conclusions:Although we observed no statistically significant associations with steroids after correction for multiple testing, the suggestive patterns for androgens and progestogens support the possibility of steroid-related pathways in XFG etiology and support further evaluation in larger studies.

Table S8 Shows Hazard Ratios and 95% Confidence Intervals for Total Mortality in Women Diagnosed with Breast Cancer with or without Excluding People Reporting Post-Diagnosis Diet Less than 12 Month after Diagnosis

Aging and age-related diseases share convergent pathways at the proteome level. Here, using plasma proteomics and machine learning, we developed organismal and ten organ-specific aging clocks in the UK Biobank (n = 43,616) and validated their high accuracy in cohorts from China (n = 3,977) and the USA (n = 800; cross-cohort r = 0.98 and 0.93). Accelerated organ aging predicted disease onset, progression and mortality beyond clinical and genetic risk factors, with brain aging being most strongly linked to mortality. Organ aging reflected both genetic and environmental determinants: brain aging was associated with lifestyle, the GABBR1 and ECM1 genes, and brain structure. Distinct organ-specific pathogenic pathways were identified, with the brain and artery clocks linking synaptic loss, vascular dysfunction and glial activation to cognitive decline and dementia. The brain aging clock further stratified Alzheimer's disease risk across APOE haplotypes, and a super-youthful brain appears to confer resilience to APOE4. Together, proteomic organ aging clocks provide a biologically interpretable framework for tracking aging and disease risk across diverse populations.

Table S2 Shows Pearson's Correlation Coefficients (r) for Diet Quality Index Scores

Background: Exfoliation glaucoma (XFG) represents a form of deleterious ocular aging of unclear etiology. We evaluated prediagnostic nuclear magnetic resonance (NMR)-based metabolites in relation to XFG risk, expanding on our prior findings of XFG-related metabotypes using liquid chromatography-mass spectrometry (LC-MS). Methods: We identified 217 XFG cases and 217 matched controls nested within three prospective health professional cohorts with plasma collected a mean 11.8 years before case identification. Plasma metabolites were analyzed using the targeted NMR Nightingale platform. Conditional logistic models and Metabolite Set Enrichment Analysis were performed. Multiple comparison issues were addressed using the number of effective tests (NEF) and false discovery rate (FDR). Results: Among 235 profiled metabolites, higher glucose was significantly associated with a lower risk of XFG (odds ratio (95%CI) = 0.42 (0.26, 0.7); NEF = 0.03). Among metabolite classes, lipoprotein subclasses and branched-chain amino acids were inversely associated, while relative lipoprotein lipid concentrations were adversely associated (FDR < 0.05). Conclusion: NMR profiling revealed that glucose, branched-chain amino acids, lipoprotein subclasses, and relative lipoprotein lipid concentrations may play important roles in XFG etiology.

Background:Replacing added sugars with nonnutritive sweeteners, such as sucralose, may help reduce weight gain in adults over time. Because sucralose is primarily excreted in the stool, its consumption could lead to changes in the gut microbiome. Objectives:We aimed to explore whether replacing sucrose used in beverages with small quantities of sucralose led to gut microbiome changes among Asian Indian adults with type 2 diabetes (T2D) or overweight/obesity (BMI ≥23 kg/m2) without T2D. Methods:In 2 analogous substudies nested within two 12-wk, open-label parallel-arm randomized controlled trials, adults with T2D (n = 49) or overweight/obesity and no T2D (n = 48) were instructed to replace sucrose in their daily coffee and tea with sucralose or to continue their use of sucrose. We examined changes in gut microbiome community structure and taxonomic composition profiled using 16S rRNA sequencing in stool samples collected before and after the 12-wk interventions. The false discovery rate was controlled using the Benjamini-Hochberg method (q < 0.20). Results:Compared with the control group, the sucralose intervention decreased α diversity (Shannon index: P = 0.02; Simpson index: P = 0.03) and increased β diversity (P = 0.001) in gut microbiome communities of adults with T2D, but not among adults with overweight/obesity (all between-group P > 0.05). Among 185 genera tested in the T2D trial, compared with the control, relative abundances of 14 primarily sugar-fermenting or short-chain fatty-acid-producing Firmicutes bacteria in the Lachnospiracae family were reduced, whereas Enterococcus and Pediococcus increased during the intervention (q < 0.20). In contrast, adults with overweight/obesity and no T2D showed no similar changes. Conclusions:Replacing daily sucrose added to coffee and tea with sucralose resulted in changes in gut microbiome community structure and taxonomic composition among Asian Indian adults with T2D, but not those with overweight/obesity and no T2D. Further studies are needed to understand potential health implications and the underlying drivers of these gut microbiome changes.Clinical Trial Register No. (India Trial Register): CTRI/2021/04/032686, CTRI/2021/04/032809.

Table S3 Shows Hazard Ratios and 95% Confidence Intervals for All-Cause Mortality in Women Diagnosed with Breast Cancer (unrelated women)

Evidence is limited on the associations between the consumption of sweetened beverages, their proteomic signatures and liver health. We used data from the UK Biobank with 173,840 participants aged 40–69 years and applied Cox proportional hazards regression to examine associations of sugar- and artificially sweetened beverages, along with their proteomic signatures (derived from elastic net regressions), with adverse liver outcomes. After a median follow-up of 8.9 years, 1 serving increment of both sugar- and artificially sweetened beverages per day was positively associated with risk of metabolic dysfunction-associated steatotic liver disease, severe liver disease and chronic liver disease mortality. The proteomic signatures of sugar- and artificially sweetened beverages showed positive associations with risk of metabolic dysfunction-associated steatotic liver disease, liver cirrhosis and severe liver disease. Our results suggest the potential importance of reducing sweetened beverage intake to improve liver health. This study examines associations between sugar- and artificially sweetened beverages or proteomic signatures and adverse liver outcomes using UK Biobank data. The findings highlight the potential benefits of reducing sweetened beverage intake for liver health.

Table S6 Shows Hazard Ratios and 95% Confidence Intervals for All-Cause Mortality in Women Diagnosed with Breast Cancer According to AHEI and aMED, Stratified by Patient and Treatment Characteristics

Table S1 Shows Criteria for Maximum Scoring for 4 Diet Quality Indices Using Standardized Cup and Ounce Equivalents from the MyPyramid Equivalents Database

Introduction: Puerto Ricans on the US mainland have poor diet quality linked to adverse cardiometabolic risk, but underlying mechanisms are unclear. Hypothesis: Plasma metabolomic signatures reflect Puerto Rican diet patterns and are associated with cardiometabolic risk independent of diet. Methods: We used LC/MS to measure 714 plasma metabolites in 722 participants (45-75 y) [n=372 with type 2 diabetes (T2D); n=346 without T2D; n=4 with T2D missing] in the Boston Puerto Rican Health Study. Diet was assessed using an ethnic-specific validated food frequency questionnaire (FFQ). We identified diet patterns using principle component analysis (PCA) and diet-related metabolomic signatures via elastic net regression. We assessed cross-sectional and prospective associations of baseline metabolomic signatures with baseline and 5-year changes in cardiometabolic risk using linear regression, adjusting for confounders and FFQ/PCA derived diet scores. Baseline risk factors were log-transformed and back-transformed for reporting. We applied a false discovery rate (FDR<0.05) for multiple testing correction. We tested for interaction by T2D status (p<0.05). Results: We identified three distinct diet patterns: oils, rice, and beans (traditional); meat, processed meat, and French fries (meat/fries); and sweetened beverages, candy, and soft drinks (sweets). Metabolomic signatures for meat/fries (47 metabolites, r=0.39-0.43) and sweets (51 metabolites, r=0.15-0.34), but not traditional (45 metabolites, r=0.08-0.13) pattern, were significantly correlated (p<0.05) with their respective FFQ/PCA derived diet scores. Cross-sectionally, the meat/fries metabolomic signature (per SD) was associated with a 1.2% (95% CI: 0.5% to 2.0%) higher waist circumference (WC, cm) among overall participants, a 6% (3%-10%) higher homocysteine (umol/L) only among those without T2D, and a 10% (5%-16%) higher glucose (mg/dl) among those with T2D. The sweets signature (per SD) was linked to a 9% (4%-13%) higher low-density lipoprotein cholesterol (mg/dl) and a 4% (2%-6%) lower glycated hemoglobin (%) only in those with T2D. Prospectively, the meat/fries metabolomic signature (per SD) was positively associated with a mean increase in WC over time [β=0.87, 95%CI (0.37-1.38)] in those without T2D. All FDRs were <0.05. Conclusions: Metabolomic signatures for meat/fries and sweets diet patterns identified among Puerto Ricans were associated with distinct cardiometabolic risk profiles, varying by T2D status.

Background: Plant-based diets are recommended to lower the risk of type 2 diabetes (T2D) and coronary heart disease (CHD). Proteomic responses to plant-based diets may reveal biological pathways underlying the associations between plant-based diets and cardiometabolic disease risk. Hypothesis: Proteomic profiles reflecting adherence and biological response to an overall plant-based diet index (PDI) and a healthy PDI (hPDI) will associate with lower risks of T2D and CHD, but to an unhealthy PDI (uPDI) will associate with higher risks. Methods: We analyzed baseline plasma Olink antibody-based proteomic profiling and food frequency questionnaire (FFQ) data from 1,660 participants in the Nurses’ Health Study (NHS), NHSII, and Health Professional Follow-up Study. First, proteome-wide association analyses were conducted among 532 proteins for each PDI, adjusting for demographics, lifestyle, and BMI. For proteins with p <0.05, we applied elastic net regression with 10-fold cross-validation to develop plasma proteomic profiles related to baseline self-reported PDIs in a training set (n=1,162). We validated these profiles in a testing set (n=498). Multivariable Cox regression models examined associations between proteomic profiles of PDIs and incident T2D and CHD, adjusting for respective FFQ-derived PDI scores and many potential confounders. Results: We documented 173 T2D cases and 85 CHD cases during median follow-up periods of 23 and 24 years. We identified proteomic profiles comprised of 35, 54, and 40 proteins that correlated with (Spearman r) the FFQ-derived PDI (0.23), hPDI (0.29), and uPDI (0.23) scores, respectively. Each SD increment in the proteomic profiles of the PDI and hPDI was associated with a lower incident T2D risk (PDI: HR=0.59 [0.50, 0.69]; hPDI: HR=0.75 [0.64, 0.88]), whereas the proteomic profile of the uPDI was associated with a higher incident T2D risk (HR=1.37 [1.17, 1.60]). Each SD increment in the PDI proteomic profile, but not the hPDI proteomic profile, was associated with a lower incident CHD risk (HR=0.76 [0.60, 0.96]), whereas the uPDI proteomic profile was associated with a higher incident CHD risk (HR=1.28 [1.02, 1.60]). All the associations remained statistically significant after further adjustment for BMI, except for the association between the hPDI proteomic profile and T2D risk (HR=0.87 [0.73, 1.03]). Conclusions: Proteomic profiles of PDIs were associated with risks of T2D and CHD, independent of self-reported diet measures.

Table S7 Shows Hazard Ratios and 95% Confidence Intervals for Total Mortality in Women Diagnosed with Breast Cancer According to Diet Quality Index Stratified by Race and Ethnicity