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PubMed2026

Comparing genome-wide significant and chemosensory variants as instruments for dietary patterns in Mendelian randomization.

BACKGROUND: Diet is a modifiable risk factor for cardiometabolic disease, yet establishing causality remains challenging. Mendelian randomization (MR) leverages genetic variants as instrumental variables (IVs) to enable causal inference. METHOD: Using two-sample MR, we assessed the causal effects of four principal component-derived dietary patterns (DPs)-Unhealthy, Healthy, Meat-based, Pescatarian-on cardiometabolic outcomes including body mass index, coronary artery disease, blood lipids, blood pressures, type 2 diabetes, fasting glucose and insulin, and glycated haemoglobin. Two sets of IVs were employed: conventional genome-wide significant variants associated with each DP, filtered for pleiotropy and directionality; and biologically informed variants in chemosensory receptor genes, given the role of taste and smell perception in food choice. RESULTS: Using conventional IVs, the Pescatarian DP was associated with reduced fasting insulin (βIVW = -0.10 pmol/L per SD increase in the Pescatarian DP score, 95% confidence interval -0.15, -0.04; P = 1.19 × 10-3), surviving multiple sensitivity analyses. Associations between the Unhealthy DP and elevated blood pressure and glycated haemoglobin should be interpreted cautiously; one of the two filtered IVs was strongly associated with caffeine intake, limiting the attribution of these findings to the DP itself. Chemosensory Receptor IVs yielded null findings, reflecting insufficient power. CONCLUSION: Evidence for causal effects of DPs on cardiometabolic traits was limited, with the strongest support for a protective effect of the Pescatarian DP on fasting insulin. Chemosensory IVs demonstrated limited utility for DPs, likely reflecting the heterogeneous and complex sensory profiles of overall diets. Future efforts should consider guideline-based dietary indices to facilitate interpretability and translation.

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PubMed2025

The Association of Prenatal Dietary Factors with Child Autism Diagnosis and Autism-Related Traits Using a Mixtures Approach: Results from the Environmental Influences on Child Health Outcomes Cohort.

BACKGROUND: Previous research on the role of maternal diet in relation to autism has focused on examining individual nutrient associations. Few studies have examined associations with multiple nutrients using mixtures approaches, which may better reflect true exposure scenarios. OBJECTIVES: This study aims to examine associations of nutrient mixtures with children's autism diagnosis and trait scores within a large, diverse population. METHODS: Participants were drawn from the United States Environmental influences on Child Health Outcomes (ECHO) consortium. Maternal prenatal diet was reported via validated food frequency questionnaires. Children's autism-related traits were measured using the Social Responsiveness Scale (SRS) and autism diagnoses were from parent reports of physician diagnosis. Bayesian kernel machine regression was used to examine the overall mixture effect and interactions between a set of 5 primary nutrients (folate, vitamin D, omega 3 and omega 6 fatty acids, and iron), adjusted for potential confounders, in relationship to child outcomes. Secondary analyses were conducted in a subset of cohorts with an expanded set of 14 nutrients. Traditional linear and logistic regression models were also analyzed for comparison of results to mixture models. RESULTS: A total of 2614 participants drawn from 7 ECHO cohorts were included in primary analysis. Mixture analyses suggested that increasing the overall 5-nutrient mixture was associated with lower SRS scores. Individual U-shaped associations and bivariate interactions between folate and omega 3 fatty acids were suggested. In the subset included in the secondary analyses of the 14-nutrient mixture, a modest inverse trend remained, but individual nutrient associations were altered, with vitamin D demonstrating higher relative importance than other nutrients. Strong associations with autism diagnosis were not observed. CONCLUSIONS: In this large sample, we found evidence for combined nutrient effects with broader autism-related traits. Because results for individual nutrients were sensitive to mixture components, replication of combined associations between nutrients and autism-related outcomes is needed.

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PubMed2026

Waist-to-height ratio as a practical indicator for screening pediatric metabolic dysfunction-associated steatotic liver disease in diverse populations and genetic backgrounds.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading chronic liver disease in children and adolescents; this parallels the global obesity epidemic. The contribution of genetic susceptibility to pediatric MASLD, and its interaction with anthropometric and biochemical indices used for non-invasive screening remains poorly understood. We aimed to evaluate waist-to-height ratio (WHtR) as a simple, equitable, and scalable tool for early identification of pediatric MASLD and relate this to genetic risk. METHODS: We combined school-based data from 1010 Chinese children with analyses of the Global Burden of Disease, the 1000 Genomes Project, and the US National Health and Nutrition Examination Survey (NHANES). Thirteen MASLD-related single-nucleotide polymorphisms (SNPs) were genotyped to construct a genetic risk score (GRS). We examined global epidemiological patterns, quantified inter-population allele divergence, and assessed how GRS modifies cutoffs and performance of nine anthropometric and biochemical indices. RESULTS: Genetic analysis revealed minimal frequency divergence across most ancestries (mean Fixation index < 0.05), except for the African ancestry where there was moderate divergence. Higher GRS were associated with lower cutoffs across indices. When GRS Z-score increased from -3 to 3, visceral adiposity index showed the sharpest changes (Z-score decreased from 1.5 to -1.8), while BFP (1.2 to 0.1) and WHtR (1.5 to 0.1) showed gradual change. Furthermore, incorporating GRS into the base anthropometric models yielded only marginal improvements in overall screening performance [area under the receiver operating characteristic curve (AUC) and Youden Index]. Validation in NHANES showed WHtR ≥ 0.48 retained high discrimination (AUC > 0.87) across most genetic variants. CONCLUSIONS: This study suggests that WHtR is a consistent and practical tool for screening pediatric patients with MASLD across diverse populations. While genetic variation may influence optimal thresholds, WHtR ≥ 0.48 appears broadly applicable, supporting its potential use as a frontline screening metric in diverse settings.

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PubMed2024

Prediction of metabolic syndrome using machine learning approaches based on genetic and nutritional factors: a 14-year prospective-based cohort study.

INTRODUCTION: Metabolic syndrome is a chronic disease associated with multiple comorbidities. Over the last few years, machine learning techniques have been used to predict metabolic syndrome. However, studies incorporating demographic, clinical, laboratory, dietary, and genetic factors to predict the incidence of metabolic syndrome in Koreans are limited. In the present study, we propose a genome-wide polygenic risk score for the prediction of metabolic syndrome, along with other factors, to improve the prediction accuracy of metabolic syndrome. METHODS: We developed 7 machine learning-based models and used Cox multivariable regression, deep neural network (DNN), support vector machine (SVM), stochastic gradient descent (SGD), random forest (RAF), Naïve Bayes (NBA) classifier, and AdaBoost (ADB) to predict the incidence of metabolic syndrome at year 14 using the dataset from the Korean Genome and Epidemiology Study (KoGES) Ansan and Ansung. RESULTS: Of the 5440 patients, 2,120 were considered to have new-onset metabolic syndrome. The AUC values of model, which included sex, age, alcohol intake, energy intake, marital status, education status, income status, smoking status, dried laver intake, and genome-wide polygenic risk score (gPRS) Z-score based on 344,447 SNPs (p-value < 1.0), were the highest for RAF (0.994 [95% CI 0.985, 1.000]) and ADB (0.994 [95% CI 0.986, 1.000]). CONCLUSIONS: Incorporating both gPRS and demographic, clinical, laboratory, and seaweed data led to enhanced metabolic syndrome risk prediction by capturing the distinct etiologies of metabolic syndrome development. The RAF- and ADB-based models predicted metabolic syndrome more accurately than the NBA-based model for the Korean population.

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PubMed2026

Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.

Fatty acids (FAs) are bioactive dietary and metabolic molecules that participate in membrane architecture, energy homeostasis, inflammatory signaling, gene regulation and immune function, all of which intersect with breast cancer (BC) risk, progression and treatment response. In this narrative review we integrate epidemiological, clinical, translational and mechanistic evidence on the role of FAs in BC. Saturated, monounsaturated, trans- and polyunsaturated FAs (PUFAs) are treated as distinct biological exposures rather than interchangeable measures of total fat intake. Similarly, evidence from dietary assessment, circulating biomarkers, erythrocyte membrane composition, adipose tissue stores and tumor lipid signatures is interpreted separately, because each captures exposure and biology at a different level. BC subtypes differ in FA synthesis, uptake, oxidation, storage and remodeling: luminal tumors are frequently linked to hormone-regulated lipogenesis, human epidermal growth factor receptor 2 (HER2)-positive tumors to growth-factor-driven lipid metabolism, and triple-negative tumors to exogenous FA uptake, inflammatory lipid mediators and ferroptosis-related vulnerabilities. FA-derived mediators also shape immune-cell polarization, cytokine signaling and the tumor microenvironment, and dietary FAs may reshape the gut microbiota; the fiber-derived short-chain FAs it produces, distinct from dietary FAs, likewise help regulate immune and inflammatory tone. Clinical data suggest possible roles for fat-quality modification and selected n-3 PUFA interventions, but findings are heterogeneous and not yet sufficient to support routine biomarker-guided precision onco-nutrition. Candidate biomarkers, such as erythrocyte n-6:n-3 composition, require prospective validation before clinical implementation. FA biology thus represents a modifiable but complex axis in BC prevention, tumor biology and supportive care.

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PubMed2026

Identification of genes promoting fitness of a plant-associated Salmonella Choleraesuis strain on alfalfa sprouts during cold storage.

Consumption of sprouted seeds, such as alfalfa sprouts, has increased in recent years due to their nutritional value and antioxidant content. However, these products have repeatedly been implicated in outbreaks of foodborne pathogens, including Salmonella enterica. Although host-adapted Salmonella serovars are less frequently associated with foodborne illness, infections caused by these serovars often result in invasive and severe outcomes, highlighting the importance of understanding their persistence in food production systems. Moreover, the variability among Salmonella serovars requires characterization beyond the most prevalent types to support the development of precision food safety strategies effective across the diversity of serovars capable of contaminating fresh produce. Here, a plant-internalized Salmonella Choleraesuis strain was used as a model to investigate persistence mechanisms on alfalfa sprouts. A bar-coded transposon mutant library comprising approximately 33,000 unique insertions was generated, along with a collection of individual insertion mutants. These resources were used to identify genetic determinants contributing to strain fitness on sprouts under abusive cold storage (8°C) simulating commercial shelf-life environments. Genome-wide analyses identified negative selection for mutants with insertions in eda, fabF, lpp1_2, pnp, stpA, SCHChr_03621, and two intergenic regions. Competition assays confirmed fitness defects associated with eda, encoding a key enzyme of the Entner-Doudoroff pathway; mnmG, encoding a tRNA modification enzyme involved in translational fidelity; and fabF, involved in fatty acid biogenesis. These findings provide a genome-wide perspective on mechanisms enabling persistence on sprouts of a plant-associated, host-adapted Salmonella strain during cold storage and inform risk assessment and intervention design within precision food safety frameworks.IMPORTANCEFood safety strategies are frequently based on knowledge derived from well-studied, epidemiologically relevant Salmonella serovars, yet many less frequent types still pose a risk to consumers and may contaminate fresh produce. Different Salmonella serovars may vary in the relative contribution of persistence mechanisms. Recognizing these differences is essential for improving precision food safety efforts, particularly for foods such as sprouts that are repeatedly linked to outbreaks. This study highlights that less-studied serovars can rely on both shared survival strategies and unique traits that might otherwise not be captured by current control approaches. By demonstrating that strain diversity influences persistence on fresh produce, this work supports the development of precision food safety strategies that address a broader spectrum of Salmonella, thereby improving risk assessment and helping to better protect public health.

food safety↗

PubMed2025

DNA methylation age deviation and cognitive status among older adults in the US, NHANES 1999-2002.

Biological aging, measured using DNA methylation, is a potential biomarker for cognitive health outcomes. We evaluated associations between DNA methylation measures of aging and cognition in a nationally representative sample of adults aged 60+ in the National Health and Nutrition Examination Survey (NHANES), 1999-2002. Genome-wide DNA methylation data were used to create 13 measures of biological aging trained on different aging phenotypes. Cognition was assessed with the Digit Symbol Substitution Test (DSST). To evaluate associations between each DNA methylation measure and DSST score, survey-weighted linear regression models adjusted for age, sex, race/ethnicity, education, smoking, serum cotinine, and BMI were run. We assessed effect modification by sex, education, and race and ethnicity. Included participants (N=1,463) were an average of 70.5 years old and 82.7% non-Hispanic White. The average DSST score was 46.9 (SD 17.6). Ten of 13 DNA methylation measures were associated with DSST (adjusted p<0.05). One year of GrimAge2 accelerated aging was associated with -0.41 points lower DSST score (95% CI: -0.61, -0.21; adjusted p=5×10-4). In stratified analyses, higher magnitudes of association were observed among male and non-Hispanic White participants across multiple aging measures. DNA methylation may be a useful biomarker of cognitive status among older adults.

DNA methylation↗

PubMed2026

Lifestyle Combination Patterns as Key Modifiable Factors for Type 2 Diabetes Mellitus Risk among Middle-Aged Korean Men.

BACKGRUOUND: The increasing prevalence of type 2 diabetes mellitus (T2DM) worldwide highlights the need to understand risk factors and effective prevention strategies. Although individual lifestyle factors associated with diabetes risk have been identified, research on their collective interactions is limited. This study aimed to identify lifestyle combination patterns in middle-aged Korean men and evaluate their impact on T2DM risk. METHODS: A total of 2,332 middle-aged men without T2DM at baseline (2001-2002) from the Korean Genome and Epidemiology Study (KoGES) cohort were included. T2DM incidence was tracked through the 8th follow-up survey (2017-2018). Lifestyle combination patterns were identified using factor analysis based on sociodemographic, lifestyle, and dietary data. Cox regression was used to assess T2DM incidence across patterns. RESULTS: Four lifestyle combination patterns were identified: 'Healthy Lifestyle,' 'Low Carb & High Protein,' 'High SES & Irregular Lifestyle,' and 'Bad Eating Habits.' The risk of developing T2DM varied across patterns. The 'Healthy Lifestyle' and 'Low Carb & High Protein' patterns showed a slight decrease in risk in T3, but the differences were not significant. The 'High SES & Irregular Lifestyle' pattern was associated with a higher T2DM risk in T3 than in T1 (hazard ratio [HR], 1.25; 95% confidence interval [CI], 1.05 to 1.55), but the association was attenuated after adjustment for family history. The 'Bad Eating Habits' pattern showed a 1.21-fold higher risk in T3 (HR, 1.21; 95% CI, 1.01 to 1.47). CONCLUSION: This study underscores the existence of distinct lifestyle combination patterns and their differential implications for T2DM risk. These findings support the need for tailored preventive strategies based on lifestyle patterns.

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