Background & aims: A quarter of the world population is estimated to have metabolic dysfunction-associated steatotic liver disease. Here, we aim to understand the impact of liver trait-associated genetic variants on fat content and tissue volume across organs and body compartments and on a large set of biomarkers.

Methods: Genome-wide association analyses were performed on liver fat and liver volume estimated with magnetic resonance imaging in up to 27,243 unrelated European participants from the UK Biobank. Identified variants were assessed for associations with fat fraction and tissue volume in >2 million 'Imiomics' image elements in 22,261 individuals and with circulating biomarkers in 310,224 individuals.

Results: We confirmed four liver fat and nine liver volume previously reported genetic variants (p values <5 × 10-8). We further found evidence suggestive of a novel liver volume locus, ADH4, where each additional T allele increased liver volume by 0.05 SD (SE = 0.01, p value = 3.3 × 10-8). The Imiomics analyses showed that liver fat-increasing variants were specifically associated with fat fraction of the liver tissue (p values <2.8 × 10-3) and with higher inflammation, liver and renal injury biomarkers, and lower lipid levels. Associations of liver volume variants with fat content, tissue volume, and biomarkers were more heterogeneous, for example the liver volume-increasing alleles at CENPW and PPP1R3B were associated with higher skeletal muscle volumes and were more pronounced in men, whereas the GCKR variant was negatively associated with lower skeletal muscle volumes in women (p values <2.8 × 10-3).

Conclusions: Liver fat-increasing variants were mostly linked to fat fraction of the liver and were positively associated with some adverse metabolic biomarkers and negatively with lipids. In contrast, liver volume-associated variants showed a less consistent pattern across organs and biomarkers.

Impact and implications: Liver fat and liver volume are common metabolic traits with a strong genetic component, yet the extent to which they exert organ-specific vs. systemic effects remains poorly defined. By integrating genome-wide association analyses and high-resolution neck-to-knee magnetic resonance imaging data through the Imiomics framework, this study reveals distinct genetic architectures for liver fat and liver volume, including sex-specific effects. These findings provide new insights into the biological, organ-level, tissue-specific, and systemic characteristics of steatotic liver disease and its genetic determinants. The results may inform the development of precision imaging genetic approaches, biomarker discovery, and stratified risk assessment strategies, while reinforcing the importance of incorporating sex-specific analyses in future research and clinical applications.

Aims Diet is a determinant of cardiovascular diseases (CVD) with coronary disease as predominant cause of pre-mature death. To analyse how diet was associated with coronary atherosclerosis, including plaque features.Methods and results The cross-sectional population-based study using data from the Swedish CArdioPulmonary BioImage Study (SCAPIS) included 24 079 adults aged 50-64 years, recruited in 2013 to 2018 who were free of clinical cardiovascular disease. The recruitment and comprehensive examinations were conducted at six locations in Sweden. A dietary index (DI) based on a previously published anti-inflammatory DI including high proportion of plant-based foods, and low in red or processed meat and sugar-sweetened beverages was constructed. The reference group was within lowest DI tertile. Coronary atherosclerosis assessed by coronary computed tomography angiography, including any-, significant-, and adverse or high-risk coronary plaque, which is non-calcified with a significant stenosis >= 50%. Lowest, compared to highest DI tertile was associated with younger age, more often men (62.2% vs. 32.9%), higher high-sensitive C-reactive protein, more cardiometabolic risk and smokers, higher alcohol-, and higher energy-intake. In the highest and lowest tertile, coronary plaques were present in 36.3% and 44.3%, respectively, stenosis >= 50% in 3.7% and 6.0%. Non-calcified coronary plaques with stenosis >= 50% were present in 0.9% and 1.5% in highest and lowest tertiles. In multivariable analyses, the lowest tertile of DI was associated with high-risk plaque features after adjusting for age, sex, smoking, with waist circumference, triglycerides (TGs), and hypertension as possible mediators.Conclusion A low-fibre diet with high red meat content was associated with high-risk plaques features, increased coronary calcification and significant stenosis. Waist circumference, TGs, and hypertension emerged as potential mediators of these associations, underscoring the role of metabolic and hemodynamic factors in the dietary impact on coronary atherosclerosis. Our findings strengthen the importance of cardioprotective dietary recommendations.

Objective: Meat intake is suggested to affect gut microbiome composition and the risk of chronic diseases. We aimed to identify meat-associated gut microbiome features and their association with host factors.

Design: Gut microbiota species were profiled by deep shotgun metagenomics sequencing in 9669 individuals. Intake of white meat, unprocessed red meat, and processed red meat was assessed using a food frequency questionnaire. The associations of meat intake with alpha-diversity and relative abundance of gut microbiota species were tested using linear regression models with adjustment for dietary fiber intake, body mass index, and other potential confounders. Meat-associated species were further assessed for association with enrichment of microbial gene function, meat-associated plasma metabolites, and clinical biomarkers.

Results: Higher intake of processed red meat was associated with reduced alpha microbial diversity. White meat, unprocessed, and processed red meat intakes were associated with 36, 14, and 322 microbiota species, respectively. Species associated with processed red meat were enriched for bacterial pathways like amino acid degradation, while those negatively linked were enriched for pathways like homoacetogenesis. Furthermore, species positively associated with processed red meat were to a large extent associated with reduced trimethylamine N-oxide and glutamine levels but increased creatine and carnitine metabolites, fasting insulin and glucose, C-reactive protein, apolipoprotein A1, and triglyceride levels and higher blood pressure.

Conclusion: This largest to date population-based study on meat and gut microbiota suggests that meat intake, particularly processed red meat, may modify the gut microbiota composition, functional capacity, and health-related biomarkers.

Background: Higher meat intake has been associated with adverse health outcomes, including cardiovascular disease (CVD). This study investigated plasma metabolites associated with meat intake and their relation with cardiometabolic biomarkers, subclinical CVD markers, and incident CVD.

Methods: Associations between self-reported meat intake and 1272 plasma metabolites were investigated in the SCAPIS cohort (n = 8819; ages 50-64). Meat-associated metabolites were further examined for relation with subclinical CVD markers in the POEM cohort (n = 502; age 50) and incident CVD in the EpiHealth cohort (n = 2278; ages 45-75; 107 incident cases over 9.6 years follow-up). Meat intake was categorized into white, unprocessed red, and processed red meat. Linear regression analyzed associations between meat intake, metabolites and cardiometabolic biomarkers, and subclinical CVD markers, while Cox models evaluated association between meat-associated metabolites and incident CVD.

Results: After correction for multiple testing, 458, 368, and 403 metabolites were associated with white, unprocessed red, and processed red meat, respectively. Processed red meat-associated metabolites were associated with higher levels of fasting insulin, hemoglobin A1c, and lipoprotein(a), and were inversely associated with maximal oxygen consumption. Two metabolites, 1-palmitoyl-2-linoleoyl-GPE (16:0/18:2) (hazard ratios (HR: 1.32; 95 % CI: 1.08, 1.62)) and glutamine degradant (HR: 1.35; 95 % CI: 1.07, 1.72), that were inversely associated with intake of all meat types, were also associated with a higher risk of incident CVD.

Conclusions: This study provides comprehensive analysis of self-reported meat intake and plasma metabolites. The findings may enhance our understanding of the relationship between meat intake and CVD, and provide insights into underlying mechanisms.

Background: The urinary microbiome, or urobiome, is a novel area of research that has been gaining attention recently, as urine was thought to be sterile for years. There is limited information about the composition of the urobiome in health and disease. The urobiome may be affectedby several factors and diseases such as diabetes, a disease that often leads to kidney damage. Thus, we need to understand the role of the urobiome to assess and monitor kidney disease related to diabetes over time.

Methods: We conducted a systematic review to summarize knowledge about the urobiome in association with diabetes mellitus and diabetic kidney disease. The search was conducted in severalelectronic databases until November 2024.

Results: Eighteen studies were selected including cross-sectional case-control studies, cross-sectionalsurveys and one prospective longitudinal study. In total, the urobiome of 1,571 people was sequenced, of which 662 people had diabetes, and of these 36 had confirmed diabetickidney disease; 609 were healthy individuals, 179 had prediabetes or were at risk of type 2 diabetes mellitus and 121 did not have diabetes but had other comorbidities. Eight studies analysed data from females, one was focused on male data, and the other nine had mixed female-male data. Most of the studies had a small sample size, used voided midstream urine, and used 16S rRNA sequencing.

Conclusion: This systematic review summarizes trends seen throughout published data available tohave a first baseline knowledge of the urinary microbiome, and its microbiota, in association with diabetes including the decreased richness and α-diversity in urinary microbiota in individuals with diabetes compared to healthy controls and the decreased α-diversity with theevolution of kidney disease independently of the cause.

Background: Previous population -based studies investigating the relationship between physical activity and the gut microbiota have relied on self -reported activity, prone to reporting bias. Here, we investigated the associations of accelerometer -based sedentary (SED), moderate -intensity (MPA), and vigorous -intensity (VPA) physical activity with the gut microbiota using cross-sectional data from the Swedish CArdioPulmonary bioImage Study.

Methods: In 8416 participants aged 50-65, time in SED, MPA, and VPA were estimated with hip -worn accelerometer. Gut microbiota was profiled using shotgun metagenomics of faecal samples. We applied multivariable regression models, adjusting for sociodemographic, lifestyle, and technical covariates, and accounted for multiple testing.

Findings: Overall, associations between time in SED and microbiota species abundance were in opposite direction to those for MPA or VPA. For example, MPA was associated with lower, while SED with higher abundance of Escherichia coli. MPA and VPA were associated with higher abundance of the butyrate -producers Faecalibacterium prausnitzii and Roseburia spp. We observed discrepancies between specific VPA and MPA associations, such as a positive association between MPA and Prevotella copri, while no association was detected for VPA. Additionally, SED, MPA and VPA were associated with the functional potential of the microbiome. For instance, MPA was associated with higher capacity for acetate synthesis and SED with lower carbohydrate degradation capacity.

Interpretation: Our findings suggest that sedentary and physical activity are associated with a similar set of gut microbiota species but in opposite directions. Furthermore, the intensity of physical activity may have specific effects on certain gut microbiota species.

Importance  Higher adherence to the Mediterranean diet has been associated with reduced risk of all-cause mortality, but data on underlying molecular mechanisms over long follow-up are limited.

Objectives  To investigate Mediterranean diet adherence and risk of all-cause mortality and to examine the relative contribution of cardiometabolic factors to this risk reduction.

Design, Setting, and Participants  This cohort study included initially healthy women from the Women’s Health Study, who had provided blood samples, biomarker measurements, and dietary information. Baseline data included self-reported demographics and a validated food-frequency questionnaire. The data collection period was from April 1993 to January 1996, and data analysis took place from June 2018 to November 2023.

Exposures  Mediterranean diet score (range, 0-9) was computed based on 9 dietary components.

Main Outcome and Measures  Thirty-three blood biomarkers, including traditional and novel lipid, lipoprotein, apolipoprotein, inflammation, insulin resistance, and metabolism measurements, were evaluated at baseline using standard assays and nuclear magnetic resonance spectroscopy. Mortality and cause of death were determined from medical and death records. Cox proportional hazards regression was used to calculate hazard ratios (HRs) for Mediterranean diet adherence and mortality risk, and mediation analyses were used to calculate the mediated effect of different biomarkers in understanding this association.

Results  Among 25 315 participants, the mean (SD) baseline age was 54.6 (7.1) years, with 329 (1.3%) Asian women, 406 (1.6%) Black women, 240 (0.9%) Hispanic women, 24 036 (94.9%) White women, and 95 (0.4%) women with other race and ethnicity; the median (IQR) Mediterranean diet adherence score was 4.0 (3.0-5.0). Over a mean (SD) of 24.7 (4.8) years of follow-up, 3879 deaths occurred. Compared with low Mediterranean diet adherence (score 0-3), adjusted risk reductions were observed for middle (score 4-5) and upper (score 6-9) groups, with HRs of 0.84 (95% CI, 0.78-0.90) and 0.77 (95% CI, 0.70-0.84), respectively (P for trend < .001). Further adjusting for lifestyle factors attenuated the risk reductions, but they remained statistically significant (middle adherence group: HR, 0.92 [95% CI, 0.85-0.99]; upper adherence group: HR, 0.89 [95% CI, 0.82-0.98]; P for trend = .001). Of the biomarkers examined, small molecule metabolites and inflammatory biomarkers contributed most to the lower mortality risk (explaining 14.8% and 13.0%, respectively, of the association), followed by triglyceride-rich lipoproteins (10.2%), body mass index (10.2%), and insulin resistance (7.4%). Other pathways, including branched-chain amino acids, high-density lipoproteins, low-density lipoproteins, glycemic measures, and hypertension, had smaller contributions (<3%).

Conclusions and Relevance  In this cohort study, higher adherence to the Mediterranean diet was associated with 23% lower risk of all-cause mortality. This inverse association was partially explained by multiple cardiometabolic factors.

Genetic variants associated with increased liver fat and volume have been reported, but whether physical activity (PA) can attenuate the impact of genetic susceptibility to these traits is poorly understood. We aimed to investigate whether higher PA modify genetic impact on liver-related traits in the UK Biobank cohort. PA was self-reported, while magnetic resonance images were used to estimate liver fat (n = 27,243) and liver volume (n = 24,752). Metabolic dysfunction-associated liver disease (MASLD) and chronic liver disease (CLD) were diagnosed using ICD-9 and ICD-10 codes. Ten liver fat and eleven liver volume-associated genetic variants were selected and unweighted genetic-risk scores for liver fat (GRSLF) and liver volume (GRSLV) were computed. Linear regression analyses were performed to explore interactions between GRSLF/ GRSLV and PA in relation to liver-related traits. Association between GRSLF and liver fat was not different among lower (β = 0.063, 95% CI 0.041–0.084) versus higher PA individuals (β = 0.065, 95% CI 0.054–0.077, pinteraction = 0.62). The association between the GRSLV and liver volume was not different across different PA groups (pinteraction = 0.71). Similarly, PA did not modify the effect of GRSLF and GRSLV on MASLD or CLD. Our findings show that physical activity and genetic susceptibility to liver-related phenotypes seem to act independently, benefiting all individuals regardless of genetic risk.