Introduction: The increasing incidence of endometrial cancer (EC) requires an extensive search for novel preventive tools and early intervention approaches. However, the development of reliable predictive models is impossible without knowledge of genetic alterations prior to diagnosis. In this work, we aimed to establish whether known EC risk factors are associated with peripheral blood gene expression changes in a prospective design and whether such associations differ between women who later developed EC and matched controls. Methods: First, we selected variables (parity status, lifetime number of years of menstruation, coffee consumption, body mass index (BMI), age at menopause, use of oral contraceptives) that were shown to have an impact on EC risk in a large prospective cohort (165,000 women). Next, using BeadChip microarray technology, we tested the association between these variables and gene expression profiles in RNA extracted from mixed circulating immune cells in a nested case-control study (79 case-control pairs) of women from the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis (GSEA). Results: At overall gene expression level, we found no difference between the EC cases and controls. The introduction of parity status into the statistical model revealed changes in the expression of 1,379 genes in the controls, while we did not observe any expression changes in the cases. Twenty-seven genes were associated with BMI increase in the controls, whereas there was no association observed between changes in BMI and gene expression in women with EC. In GSEA, 2,407 significantly enriched gene sets were attributed to a parity increase among cancer-free women. Conclusion: In this study, we found that an increased number of parities has a life-long effect on the gene expression profile in the peripheral blood of women who never developed cancer. In contrast, in women who were diagnosed with EC later in life, neither multiparity nor elevated BMI showed a significant association with gene expression patterns. However, given the modest sample size and exploratory nature of the study, these findings should be verified in larger cohorts.

Creatine is a central regulator of cellular energy homeostasis and one of the most extensively studied dietary supplements in human nutrition. Although creatine supplementation consistently increases tissue creatine availability and supports performance and health across diverse populations, substantial interindividual variability in responsiveness persists. Approximately one-quarter of individuals demonstrate minimal increases in tissue creatine or functional benefit following supplementation. While non-genetic factors such as baseline creatine status, diet, age, sex, and training load contribute to this heterogeneity, the role of common genetic variation remains insufficiently explored. Importantly, creatine bioavailability and functional responsiveness are related but distinct outcomes, and both may be modified by genetic background. This paper aims to reframe creatine responsiveness as a quantitative, polygenic trait shaped by common low-impact genetic variants rather than a binary responder-non-responder phenomenon driven by rare pathogenic mutations. The review synthesizes evidence on genetic variation affecting creatine transport, endogenous synthesis, and downstream energy metabolism, with an emphasis on population-relevant mechanisms. A narrative, mechanism-oriented review was conducted integrating data from human genetics databases, biochemical pathways, and physiological studies. The analysis focused on (i) common low-impact variants in genes directly regulating creatine transport (SLC6A8) and biosynthesis (GATM, GAMT), and (ii) modifier genes involved in mitochondrial function, phosphagen buffering, and muscle or neural energetic phenotype. Variant classification frameworks from expert curation initiatives were used to distinguish pathogenic from low-impact population variants. Low-impact variants in the creatine transporter gene SLC6A8 are highly prevalent and likely contribute to a continuum of creatine transport efficiency, with sex-dependent effects due to X-linked inheritance. Similarly, common polymorphisms in creatine biosynthetic enzymes (GATM and GAMT) may subtly alter synthetic efficiency or methyl-group demand, increasing dietary creatine dependence while not causing overt deficiency. Beyond creatine-specific pathways, genetic variation in mitochondrial regulators, electron transport chain components, creatine kinase isoforms, and muscle fiber-type determinants can act as effect modifiers, amplifying or dampening the functional benefits of creatine despite comparable tissue uptake. Collectively, small additive effects across transport, synthesis, and utilization pathways may prevent supplementation from exceeding the threshold required for measurable benefit in certain individuals. Creatine non-responsiveness in the general population is more plausibly explained by the cumulative influence of common low-impact genetic variants than by rare monogenic defects. Viewing creatine responsiveness as a graded, polygenic trait provides a coherent framework to interpret heterogeneous findings in supplementation trials. Incorporating genetic context into study design, through stratified analyses or pathway-based approaches, may improve sensitivity to detect true effects and support the development of precision-guided creatine supplementation strategies in both clinical and public health settings.

Introduction: Breast cancer (BC) is the most frequent cancer in women, driven by a combination of genetic, environmental, and lifestyle factors. Whether modifiable sleep behaviors causally affect BC risk remains unclear. Aims of the study were to systematically assess the causal impact of sleep-related phenotypes on overall BC and its major subtypes using two-sample mendelian randomization (MR) and to determine whether inflammatory proteins mediate these relationships. Methods: Inverse variance weighted served as the main analysis, with sensitivity and reverse-MR analyses as supporting checks. Mediation was quantified with a two-step MR design. Results: Morning chronotype significantly reduced the risk of overall BC (OR = 0.936, 95% CI: 0.893–0.980) and luminal A subtype (OR = 0.944, 95% CI: 0.894–0.996). Short sleep duration was associated with decreased risk of overall BC (OR = 0.482, 95% CI: 0.284–0.818) and luminal A subtype (OR = 0.385, 95% CI: 0.194–0.766), whereas long sleep duration increased the risk of triple-negative BC (OR = 9.433, 95% CI: 2.419–36.775) and luminal A subtype (OR = 2.186, 95% CI: 1.111–4.302). Mediation analysis indicated that CXCL11 accounted for 22.4% of the total causal effect of short sleep duration on luminal A BC. Conclusion: Morning chronotype confers protection against BC, whereas prolonged sleep duration elevates the risk of triple-negative and luminal A BC. CXCL11 mediates part of the protective effect of short sleep on luminal A BC. These findings provide evidence-based support for BC prevention strategies focusing on sleep optimization.

Introduction: Type 2 diabetes (T2D) risk factors are associated with gut microbiota dysregulation that can alter circulating metabolite levels such as bile acids (BAs) and short-chain fatty acids (SCFAs). The objective was to investigate how the high dairy (HD) (≥4 servings/day) product intake compared to adequate dairy (AD) (≤2 servings/day) intake influences the correlations between Roseburia, Faecalibacterium, Flavonifractor, as well as Verrucomicrobia and circulating BAs and SCFAs in subjects at risk of T2D. Methods: In a randomized crossover trial, 10 hyperinsulinemic adults were randomized to HD or AD for 6 weeks separated by a 6-week washout period. Gut microbiota were measured with 16S rRNA-based high-throughput sequencing. BA profiling in plasma was performed by high-performance liquid chromatography-tandem mass spectrometry. Serum SCFAs were determined using headspace gas chromatography. Results: No significant differences were observed in mean circulating BA or SCFA levels between AD and HD consumption. Verrucomicrobia and Flavonifractor showed positive correlations with secondary BAs following HD and AD intake, respectively. Additionally, Flavonifractor correlated positively with acetic and propionic acids after HD intake. Roseburia correlated positively with primary BAs, propionate, and butyrate after HD intake. Faecalibacterium was positively correlated with cholic acid after AD intake and with hexanoic acid after HD intake. Conclusion: These findings suggest that HD intake may modulate microbiota-metabolite interactions without altering circulating metabolite concentrations, highlighting a potential role for dietary patterns in shaping gut-derived metabolic signals in individuals at risk of T2D.

The Body Mass Index (BMI) is a limited tool for assessing metabolic risk, as it fails to capture the metabolic heterogeneity seen in phenotypes like metabolically healthy obesity (MHO) and metabolically unhealthy normal weight (MUNW). This commentary evaluates a recent study by Sierra-Ruelas et al. that investigated the context-dependent effects of uncoupling protein (UCP) gene variants on cardiometabolic health. The study stratified a cohort of 228 women into four distinct metabolic phenotypes to test the hypothesis that the pathogenic effect of a UCP variant is conditional on an individual's metabolic state. Sierra-Ruelas et al. found that a UCP1 variant was associated with a five-fold increased risk of hypercholesterolemia, but only in the normal weight-metabolically unhealthy group, while a UCP2 variant was linked to a three-fold increased risk of abdominal obesity exclusively in the excess weight-metabolically unhealthy group. The primary strength of the study is its innovative stratification framework, which represents a robust model for future research in precision nutrition. Methodological considerations, including small sample sizes resulting from stratification and a cross-sectional design, are discussed, highlighting the need for future validation in larger longitudinal cohorts and mechanistic studies to explore gene-environment interactions. Ultimately, this work supports a paradigm shift toward a more integrated and personalized approach to assessing genetic risk, emphasizing that the clinical impact of a gene variant can be conditional on an individual's broader metabolic environment.

Introduction: The AMY1 gene, which encodes salivary amylase, exhibits copy number variation (CNV) that affects starch metabolism and may influence obesity risk. This study aimed to assess AMY1 CNV among selected participants of the 2018–2019 Expanded National Nutrition Survey (ENNS), using a validated digital PCR method. Method: The method validation was initially performed using certified reference material. Whole blood DNA was isolated from selected nutrition survey respondents who had available daily rice intake data. The daily rice intake of participants was divided into tertiles. Chi-square tests were used to compare AMY1 CNV, age, BMI, smoking and alcohol status, and other variables across daily rice intake tertiles. Results: Data from selected ENNS participants revealed AMY1 CNV ranging from 6 to 18 copies. Higher rice intake was significantly associated with increased AMY1 CNV (p = 0.035). Lower AMY1 CNV was more prevalent among overweight and obese individuals. Conclusion: Findings highlight gene-diet interactions and support the relevance of personalized nutrition approaches in the Philippines.

Background: Omega-3 long-chain polyunsaturated fatty acids (n3-LCPUFAs) have strong triglyceride-lowering and anti-inflammatory properties, and high levels of these fatty acids have been associated with reduced risk of cardiovascular disease. The synthesis of n3-LCPUFA, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), and n6-LCPUFA, arachidonic acid, share a common pathway mediated by fatty acid desaturase genes, FADS1 and FADS2. LCPUFA synthesis is regulated by both modifiable and non-modifiable factors. Of particular interest is the role of genetic variants in the FADS gene cluster, which are associated with altered FADS1 and FADS2 expression, as well as LCPUFA levels. However, the specific functional variants and the precise molecular mechanisms by which these variants regulate FADS gene expression remain to be elucidated. Variation in the FADS gene cluster is thought to have arisen through natural selection and changing dietary patterns. Available evidence suggests these variants, either individually or as a haplotype, may alter FADS gene expression by modifying DNA methylation in regulatory regions, as well as microRNA and transcription factor binding sites. Summary: This review explores the current state of knowledge regarding the functional roles of these variants on LCPUFA synthesis and how these new insights will help support precision nutrition strategies aimed at improving an individual’s n3-LCPUFA status and health. Key Messages: Identifying specific functional variants in or near the FADS gene cluster and elucidating the mechanisms by which these variants impact LCPUFA synthesis requires further investigation. However, hypothesis generating in vitro studies have revealed roles for epigenetics, non-coding RNAs, and modification of transcription factor binding sites. This knowledge will generate new insights that will help improve our understanding of the genetic basis underlying LCPUFA synthesis and how this may differ across populations.

Introduction: Previous studies have reported the impact of the hypoxia inducible factor-1α (HIF1α) gene on risk of renal cell carcinoma (RCC). However, the results of these previous studies were inconsistent. Hence, this study aimed to verify the influence of single-nucleotide polymorphisms (SNPs) in the HIF1α gene and their interaction with environmental factors on RCC risk. Methods: PCR-based restriction fragment length polymorphism was used to genotype four SNPs. Logistic regression was utilized to test the association between HIF1α SNPs and RCC risk. A generalized multifactor dimensionality reduction model was employed to evaluate the potential interaction of the four SNPs in the HIF1α gene with environmental factors. Results: The rs11549465-CT, rs11549465-TT, and rs11549465-CT+TT genotypes were all associated with increased risk of RCC; the adjusted ORs (95% CI) were 1.74 (1.38–2.12) (CT vs. CC), 1.93 (1.47–2.43) (TT vs. CC), and 1.78 (1.41–2.18) (CT+TT vs. CC), respectively. We also found that the rs11549467-GA and rs11549467-GA+AA genotypes were associated with increased RCC risk, and adjusted ORs (95% CI) were 1.81 (1.49–2.16) (GA vs. GG), 1.79 (1.47–2.13) (GA+AA vs. GG), respectively. We found a statistically significant combination (including rs11549465 and smoking). Compared to non-smokers with the rs11549465-CC genotype, current or ever smokers with rs11549465-CT+TT genotype had the highest RCC risk; the OR (95% CI) was 3.68 (1.97–5.41). Conclusion: This study demonstrated a significant impact of HIF1α polymorphisms on RCC risk. Additionally, this impact could be influenced by environmental factors, such as smoking status.

Background: Klotho, a transmembrane protein with pleiotropic antiaging properties, is increasingly recognized as a central regulator of longevity and metabolic resilience. Primarily expressed in the kidneys and brain, Klotho governs phosphate and calcium homeostasis, modulates redox signaling, and influences key metabolic pathways, including PI3K/AKT and IGF-1. Declining Klotho expression is associated with both biological and chronological aging and has been mechanistically implicated in the pathogenesis of chronic kidney disease, cardiovascular disease, neurodegeneration, and metabolic dysfunction. Summary: Klotho expression is modifiable through diet, in preclinical and observational studies, offering a promising avenue for delaying cellular aging and preserving physiological function. Micronutrients such as magnesium, vitamin D, folate, and vitamin B12, as well as phytochemicals including sulforaphane and curcumin, have been shown to modulate Klotho expression through redox-sensitive and transcriptional mechanisms. Macronutrient balance, particularly carbohydrate quality and saturated fat intake, also plays a critical role in maintaining Klotho activity via insulin sensitivity, mitochondrial integrity, and inflammatory signaling. Inflammatory dietary profiles, quantified through tools such as the Dietary Inflammatory Index (DII), have been inversely associated with serum α-Klotho concentrations and biological age acceleration. This review critically synthesizes current knowledge on nutrient-specific and dietary pattern-level influences on Klotho, with emphasis on antioxidant, anti-inflammatory, and epigenetically active compounds. In parallel, the Klotho-FGF23 axis is examined regarding dietary calcium and phosphate regulation, highlighting the distinct effects of whole food-derived versus supplemental calcium on mineral metabolism and vascular health. Key Messages: Klotho emerges as a potential modifiable determinant with current limitations as a potential biomarker within precision nutrition strategies aimed at extending health span and attenuating age-related disease risk. Key concepts discussed include dietary factors in Klotho modulation and chronic disease prevention. Opportunities and limitations of soluble Klotho as a multifaceted biomarker of human health and longevity are highlighted.

Background: Malignant hyperthermia (MH) is a rare but serious pharmacogenetic disorder triggered by specific anesthetic agents, leading to a rapid and often fatal hypermetabolic response. While its genetic roots – primarily involving RYR1 and CACNA1S mutations – are well documented, many susceptible individuals remain undiagnosed until they are exposed to the triggering anesthetic. Despite dantrolene being an instrumental drug in combatting MH mortality, global access remains inconsistent, and morbidity rates remains high. Current diagnostic tools are invasive and limited to specialized centers, and routine screening is rarely feasible. Summary: This review explores how recent advances in multi-omics – genomics, proteomics, metabolomics, transcriptomics, and radiomics – are reshaping our understanding of MH pathophysiology. From chronic calcium dysregulation and mitochondrial dysfunction to shifts in energy metabolism and subtle muscle changes, a complex picture is emerging. Integrative analyses reveal promising biomarkers for early detection, while CRISPR-based gene editing and machine learning offer potential pathways for future targeted interventions. Noninvasive imaging, blood-based metabolic profiling, and genomic risk prediction may soon offer safer, more effective screening tools for anesthesia planning. Key Messages: Ultimately, a shift from reactive crisis management to proactive risk identification could redefine how we approach MH – potentially improving patient outcomes and saving lives.