Despite the established importance of the human microbiome in health, the integrated microbial exposures occurring within the sleep environment remain poorly understood. Sleep represents a critical period of prolonged exposure to indoor microbial reservoirs, yet no study has simultaneously examined the connectivity between environmental sources and the human oral microbiome. We present a novel, tri-source microbiome dataset characterizing microbial communities from co-located saliva, pillow dust, and bedroom air collected from healthy participants in real-world sleep environments. Samples were collected under standardized protocols and analyzed using 16S rRNA gene amplicon sequencing (V3-V4 region). Rigorous quality control and bioinformatic processing were applied to generate high-resolution amplicon sequence variants. Alpha diversity analysis revealed that pillow dust serves as the most diverse and stable microbial reservoir, exhibiting significantly higher species richness and phylogenetic diversity than saliva or air (p < 0.05). Beta diversity analysis showed distinct clustering by sample type, with indoor air and pillow dust exhibiting closer microbial similarity to each other than to saliva. Notably, significant genus-level correlations were identified between air and pillow dust (e.g., Brevitalea, Gardnerella) and between pillow dust and saliva (e.g., Actinomyces, Bifidobacterium), suggesting potential microbial exchange through gravitational settling and physical contact. This tri-source dataset provides a unique resource for investigating host-environment microbial interactions during rest. Our findings highlight the sleep environment as a significant exposome factor that may influence oral microbiome dynamics, offering new avenues for research into respiratory health, built environment science, and human exposome studies.
Background: Celiac disease (CeD) is a chronic, immune-mediated condition driven by dietary gluten in genetically predisposed individuals, primarily those carrying HLA-DQ2 and HLA-DQ8. Unlike other autoimmune diseases, CeD offers an exceptional degree of mechanistic clarity, stemming from the identification of the main environmental driver, gluten, and its link with genetic susceptibility. Summary: While gluten and HLA genotype are necessary for developing CeD, they are not sufficient. Emerging research highlights that environmental and lifestyle factors, including early-life ecosystem, infections, and gut microbiota, critically modulate CeD risk and severity. This review synthesizes emerging insights and focuses on the role of the intestinal epithelium not just as target of immune-mediated injury but as an active interface integrating genetic susceptibility with environmental cues. Recent data reveal that intestinal epithelial cells can release tissue transglutaminase 2 that modifies gluten peptide antigenicity, participate in antigen presentation and immune signaling, and respond to microbial and dietary factors, positioning them as contributors to CeD initiation and progression. The review also highlights knowledge gaps and areas of active debate in CeD. Key Messages: CeD has a main environmental driver (gluten) and a defined genetic susceptibility, linked to major histocompatibility complex class II DQ2 and DQ8. Activation of the CD4+ T-cell response by gluten and cytotoxic transformation of intraepithelial lymphocytes culminate in villus atrophy of the proximal small intestine. In this opinion-based perspective, we integrate and review recent evidence suggesting the intestinal epithelium plays an active role in CeD initiation and/or progression, which could lead to strategies to prevent or better treat this condition.
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.
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.
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.
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.
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.
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.
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. 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. Non-invasive imaging, blood-based metabolic profiling, and genomic risk prediction may soon offer safer, more effective screening tools for anesthesia planning. Ultimately, a shift from reactive crisis management to proactive risk identification could redefine how we approach MH-potentially improving patient outcomes and saving lives.
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.
INTRODUCTION:The prevalence of gout, a chronic metabolic disease, has recently increased. Polygenic risk scores (PRSs) represent a useful tool for predicting patient outcomes of this condition. However, the clinical utility of PRS in disease prediction remains controversial. METHODS:Using data from the Korean Genome and Epidemiology Study, machine learning (ML) models were developed to predict gout based on PRS and clinical variables such as uric acid, lifestyle habits, and metabolic syndrome (MetS) profiles. Five supervised learning algorithms were applied: logistic regression (a traditional statistical model often used in ML contexts), random forest (RF), decision tree, extreme gradient boosting, and light gradient boosting. RESULTS:Among the models, the RF model incorporating PRS, age, sex, MetS, and uric acid levels achieved the highest area under the curve (0.7204, 95% CI = 0.7124-0.7284). Feature importance analysis highlighted uric acid levels as the most important predictor of gout, followed by PRS and age. Although PRS enhanced the predictive power of the ML models, its effect was modest, suggesting that traditional risk factors remain important for gout prediction. CONCLUSION:This study demonstrated that integrating genetic data with clinical variables improves gout prediction. Further research is necessary to optimize the utility of PRS in diverse populations.
Introduction. It has been reported that even with the same body mass index (BMI), there are subjects with metabolically healthy or unhealthy phenotype. The main determinants of the unhealthy phenotype are the type and distribution of fat, ectopic fat accumulation, genetics, and lifestyle factors. Uncoupling proteins (UCPs) disengage mitochondrial respiration from ATP synthesis and result in heat production, which in turn is related to energy expenditure and, thus, to fat mass accumulation. The association of the UCP1 -3826A/G (rs1800592), UCP2 Ala55Val (rs660339), and UCP3 -55C/T (rs1800849) variants with metabolic variables was evaluated according to metabolic phenotype in Mexican women. Methods. Women aged 18 to 65 years classified as normal weight (NW) or excessive weight (EW) according to their BMI (from 18.5 to <25 kg/m2 for NW, and from 25 to <40 kg/m2 for EW), were included. Participants were classified into two metabolic phenotypes: metabolically healthy or metabolically unhealthy (MH or MUH, respectively) based on ATP-III criteria and the homeostasis model assessment of insulin resistance (HOMA-IR). The genetic variants were determined by allelic discrimination using TaqMan® probes. Results. In participants with the UCP1 -3826A/G variant, an increased risk of hypercholesterolemia was observed in those with the NW-MUH phenotype (OR=5.09, CI=1.03-25.12, p=0.017). The UCP2 Ala55Val variant in EW-MUH subjects was associated with higher abdominal obesity risk (OR=3.23, CI=1.21-8.60, p=0.019), while no associations were found with the UCP3 -55C/T variant. Conclusion. UCP1 and UCP2 variants are related with hypercholesterolemia and visceral fat accumulation in women with MUH phenotype.
INTRODUCTION:This study aimed to determine the frequency of genetic testing awareness, the number of individuals who have undergone genetic testing, and the subsequent behavior changes following testing. METHODS:The analysis utilized recent data from the Health Information National Trends Survey (HINTS) 6, collected between March and September 2022, from a diverse sample of adults aged 18 and older. Logistic regressions were applied to assess predictors of outcome variables. A p value of < 0.05 was considered statistically significant. RESULTS:Among the 4,631 respondents, 81.6% reported being aware of genetic testing, 28.7% (n = 1,327) had undergone some form of testing, and 16.3% of those tested reported making behavioral changes based on their results. Ancestry-related genetic testing was the most widely recognized and frequently utilized. However, behavioral changes were most commonly reported among individuals who underwent disease-specific genetic testing, especially those who perceived themselves to be at high risk, were motivated to take preventive measures, and received assistance in understanding their results. Within this subgroup, lifestyle modification was the most frequently cited change, followed by adjustments in dietary supplement use, increased health screenings, and changes to medications. Additionally, individuals from racial and ethnic minority groups were more likely than non-Hispanic white respondents to undergo specific types of genetic testing and to report behavior changes in response to the findings. CONCLUSION:The study highlights an increasing awareness and involvement in genetic testing, though a smaller percentage of individuals have altered their behavior based on the test results. Additionally, the study identifies genetic literacy as a key factor in predicting behavior changes.
Introduction: Creatine is a conditionally essential nutrient integral to cellular energy homeostasis, with emerging evidence suggesting its potential role in modulating biological aging. However, associations between dietary creatine intake and epigenetic biomarkers of mortality remain unexplored. This study investigates the relationship between dietary creatine intake and DNA methylation-derived mortality indices in US adults aged 50 years and older. Methods: Data from the NHANES 1999–2002 cycles were analyzed, including dietary creatine intake estimated from 24-h recall interviews and DNA methylation profiles measured using the Illumina EPIC array. Epigenetic mortality predictors GrimAgeMort and GrimAge2Mort were examined in relation to creatine intake. Results: Among 4,983 participants (mean age 67.6 ± 10.7 years), a significant inverse correlation was observed between dietary creatine and both GrimAgeMort (r = −0.041, p = 0.045) and GrimAge2Mort (r = −0.047, p = 0.019), indicating that higher creatine consumption was associated with lower epigenetic mortality risk scores. These associations persisted as statistically significant after adjustment for demographic variables and pertinent dietary factors. Conclusions: Higher dietary creatine intake is linked to reduced biological age acceleration and mortality risk as estimated by epigenetic biomarkers. These findings highlight creatine’s potential as a modifiable dietary factor promoting healthy aging and longevity. Further research is warranted to elucidate underlying mechanisms.
BACKGROUND:Diet-induced obesity (DIO) leads to insulin resistance (IR) and alters gene expression through epigenetic mechanisms, including DNA methylation. Here, we aimed to investigate whether experimental environment is an important variable in determining DNA methylation and one-carbon metabolism in DIO mice fed a multi-vitamin-mineral mixture (MVM). METHODS:Three experiments with identical design were conducted in three independent animal facilities (i.e., experimental environments or locations). In each location, 12-week-old male C57BL/6J mice were randomly assigned to two dietary groups: high-fat (HF) and HF-MVM for an average of 10 weeks. Global and gene-specific methylation of adipose function related genes in epididymal white adipose tissue (eWAT), and insulin signaling genes in the liver were analyzed using bisulfite pyrosequencing. Hepatic 1-C metabolites were measured and the ratio of S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) was used as an indicator of methylation potential. RESULTS:Experimental location affected global methylation patterns in the eWAT, but not in the liver. At the gene-specific level, experimental location, MVM, and their interaction altered the methylation of genes related to adipose function (Srebf1, Acaca, Fasn, Pparg, and Rbp4) in the eWAT and insulin signaling (Pi3kr1 and Akt1) in the liver (p < 0.05). The SAM/SAH ratio was correlated with gene-specific methylation at some CpG sites of Srebf1, Pi3kr1, Acaca, Fasn, Pparg, Rbp4, and Akt1) genes (p < 0.05). CONCLUSION:The experimental environment is a significant determinant of the effects of micronutrient supplement on 1-C metabolism and the methylation of genes associated with IR in tissues of DIO adult male mice.
