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BACKGROUND: The pathogenesis of multiple sclerosis (MS) requires both genetic factors and environmental events. The question remains, however, whether these factors and events completely describe the MS disease process. This question was addressed using the Canadian MS data, which includes 29 478 individuals, estimated to represent 65-83% of all Canadian patients with MS. METHOD: The genetically-susceptible subset of the population, (G), includes everyone who has any non-zero life-time chance of developing MS, under some environmental conditions. A sufficient environmental exposure, for any genetically-susceptible individual, includes every set of environmental conditions, each of which is sufficient, by itself, to cause MS in that person. This analysis incorporates many epidemiological parameters, involved in MS pathogenesis, only some of which are directly observable, and establishes plausible value ranges for each parameter. Those parameter value combinations (ie, solutions) that fall within these plausible ranges are then determined. RESULTS: Only a small proportion of the population (≤52%) has any possibility of developing MS, regardless of any environmental conditions that they could experience. Moreover, some of these genetically-susceptible individuals, despite their experiencing a sufficient environmental exposure, will still not develop disease. CONCLUSIONS: This analysis explicitly includes all of those genetic factors and environmental events (including their interactions), which are necessary for MS pathogenesis, regardless of whether these factors, events and interactions are known, suspected or as yet unrecognised. Nevertheless, in addition, a truly random mechanism also seems to play a critical role in disease pathogenesis. This observation provides empirical evidence, which undermines the widely-held deterministic view of nature. Moreover, both sexes seem to share a similar genetic and environmental disease basis. If so, then it is this random mechanism, which is primarily responsible for the currently-observed differences in MS disease expression between susceptible women and susceptible men.

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p

BACKGROUND AND OBJECTIVE: Prior Epstein-Barr virus (EBV) infection is associated with an increased risk of pediatric-onset multiple sclerosis (POMS) and adult-onset multiple sclerosis (MS). It has been challenging to elucidate the biological mechanisms underlying this association. We examined the interactions between candidate human leukocyte antigen (HLA) and non-HLA variants and childhood EBV infection as it may provide mechanistic insights into EBV-associated MS. METHODS: Cases and controls were enrolled in the Environmental and Genetic Risk Factors for Pediatric MS study of the US Network of Pediatric MS Centers. Participants were categorized as seropositive and seronegative for EBV-viral capsid antigen (VCA). The association between prior EBV infection and having POMS was estimated with logistic regression. Interactions between EBV serostatus, major HLA MS risk factors, and non-HLA POMS risk variants associated with response to EBV infection were also evaluated with logistic regression. Models were adjusted for sex, age, genetic ancestry, and the mothers education. Additive interactions were calculated using relative risk due to interaction (RERI) and attributable proportions (APs). RESULTS: A total of 473 POMS cases and 702 controls contributed to the analyses. Anti-VCA seropositivity was significantly higher in POMS cases compared to controls (94.6% vs 60.7%, p

Gene-environmental interactions create risk profiles for sporadic cancer development in patients with colorectal cancer (CRC). For instance, a persons socioeconomic status over their lifetime can affect their level of physical activity and type of diet, and their exposure to tobacco and alcohol may affect their gut microbiome and ultimate risk for developing CRC. Metabolic disease can independently or further change the gut microbiome and alter the typical timing of CRC development, such as is observed and linked with early-onset disease. Patients with microsatellite unstable tumors where DNA mismatch repair is defective have altered immune environments as a result of tumor hypermutability and neoantigen generation, allowing for immune checkpoint inhibitor susceptibility; in such cases, the genetics of the tumor changed the environment. The environment can also change the genetics, where interleukin-6-generated inflammation can inactivate MSH3 protein function that is associated with CRCs which are more metastatic, and patients show poor outcomes. Some specific aspects of the local microbial environment that may be influenced by diet and metabolism are associated with CRC risk, such as Fusobacterium nucleatum infection, and may affect the initiation, perpetuation, and spread of CRC. Overall, both the macro- and microenvironments associated with a person play a major role in CRC formation, progression, and metastases.

An increasing number of studies have shown that lead is an important cardiovascular risk factor, but the impact of cardiovascular related gene polymorphisms on lead induced cardiovascular diseases is still unclear. To assess the interaction of lead exposure and related key cardiovascular regulating gene polymorphisms on blood pressure traits, three single-nucleotide polymorphisms including NOTCH1 rs3124591, Cerebral cavernous malformations 3 (CCM3) rs3804610 and Vascular endothelial growth factor receptor type 2 (VEGFR2) rs2305948 were selected and genotyped using improved multiplex ligase detection reaction method in 568 lead exposure workers in South China. General characteristics, blood lead and biochemical parameters including glucose, lipid profile and creatinine were also collected according to standard protocols. Regression analysis was used to evaluate the association of blood pressure with lead exposure, polymorphisms and their interaction. This study displayed that CCM3 rs3804610 had a positive interaction with lead and VEGFR2 rs2305948 had a negative interaction with lead. Specifcally, compared with the wild-type population, the blood lead of the genotype population carrying the risk allele increased by 1 µg/dL, systolic blood pressure increased by 0.53 mmHg (p < 0.01) and diastolic blood pressure increased by 0.34 mmHg (p < 0.05) for CCM3 rs3804610, and systolic blood pressure decreased by 0.28 mmHg (p < 0.05) and diastolic blood pressure decreased by 0.22 mmHg (p < 0.05) for VEGFR2 rs2305948. Thus our findings showed that the interaction between CCM3 rs3804610 and VEGFR2 rs2305948 and lead exposure were associated with blood pressure and may provide guidance for future research on hypertension prevention and personalized clinical treatment in lead exposed populations. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Methods Results Conclusion Metabolic dysfunction‐associated steatotic liver disease (MASLD) affects up to 30% of Western populations. While obesity is a recognized risk factor, MASLD does not develop in all obese individuals, highlighting the need to understand genetic and environmental interactions. The PNPLA3 I148M variant has been identified as a key genetic risk factor, significantly increasing the likelihood of MASLD development and progression.We reviewed current literature on the role of PNPLA3 I148M in MASLD, focusing on gene‐environment interactions involving diet, physical activity, obesity, and insulin resistance. We included studies analysing ethnic differences in PNPLA3 I148M prevalence and its association with MASLD. Additionally, we reviewed data on how PNPLA3 I148M influences the response to therapies, including lipid‐lowering medications and GLP‐1 agonists.The PNPLA3 I148M variant markedly heightens MASLD risk, particularly in Hispanic populations, where a higher prevalence of MASLD is observed. Lifestyle factors such as high sugar intake, alcohol consumption, and physical inactivity exacerbate MASLD risk among I148M carriers. Evidence shows that insulin resistance amplifies MASLD risk associated with the I148M variant, especially in non‐diabetic individuals. Moreover, the PNPLA3 I148M variant interacts with other genetic loci, further modifying MASLD risk and disease course. The variant also influences treatment response, with variability observed in effectiveness of lipid‐lowering therapies and GLP‐1 agonists among carriers.The interplay between PNPLA3 I148M and environmental factors underscores the need for personalized MASLD prevention and treatment strategies. Targeting both genetic and lifestyle contributors may enhance MASLD management, offering a tailored approach to reducing disease burden. [ABSTRACT FROM AUTHOR]

The lifetime production of dairy cows is a complex trait influenced not only by genetics but also by the environment in which a cow lives and the management practices of the farmer. Moreover, these influential factors show complex interactions with each other, making it difficult to reliably predict the lifetime production of individual animals at birth. However, because well-managed dairy farms often have a surplus of youngstock, reliable lifetime production predictions would offer the opportunity to make more substantiated decisions when selecting calves or heifers to sell. Therefore, using data from Dutch herds, we constructed a dataset capturing information on genetics, environment, and management practices to develop multiple machine learning models capable of predicting the lifetime production of dairy cattle soon after birth. We found that a coupling of trends observed at the country level with farm-specific models largely outperforms off-the-shelf approaches. At birth, our best model could explain up to 47% of the variance in lifetime production, a considerable improvement compared with linear regression on the breeding values supplemented with the average lifetime production at farm level, which could explain only 21.7% of the variance in lifetime production. Moreover, we demonstrated that surplus youngstock selection according to our model could more than double the surplus animal selection effect compared with the benchmark methodology, offering opportunities to significantly increase the average (future) potential lifetime production of the retained heifers. Assuming a static 20% surplus liveborn heifer scenario and random surplus animal selection as the default, our best model for surplus animal selection resulted in a 9.4% greater lifetime production in the retained animals compared with the current Dutch average lifetime production. The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. [ABSTRACT FROM AUTHOR]

Benzene, toluene, and xylene (BTX) co-exist in human environments, yet their individual and combined effects on genetic damage at low exposure levels are not fully understood. Additionally, single nucleotide polymorphisms in microRNAs (mirSNPs) might be involved in cancer etiology by affecting the related early health damage. To investigate the influence of BTX exposure, mirSNPs, and their interactions on genetic damage, we conducted a cross-sectional study in 1083 Chinese petrochemical workers, quantifying the BTX cumulative exposure levels and multiple genetic damage biomarkers. Additionally, we genotyped multiple common mirSNPs. Benzene and a BTX mixture were positive associated with the olive tail moment (OTM) and tail DNA% (p < 0.05). Higher levels of toluene and xylene enhanced the association of benzene with genetic damage levels. Genotypes and/or mutant allele counts of miR-4482-related rs11191980, miR-4433-related rs136547, miR-27a-related rs2594716, miR-3130-related rs725980, and miR-3928-related rs878718 might significantly influence genetic damage levels. Stronger effect estimates of benzene/BTX exposure were found in carriers of miR-196a-2-related rs11614913 heterozygotes and of wild homozygotes of miR-1269b-related rs12451747, miR-612-related rs12803915, and miR-4804-related rs266437. Our findings provide further support of the involvement of BTX co-exposure, mirSNPs, and their gene–environment interactions in determining the severity of DNA strand break in a complex manner. [ABSTRACT FROM AUTHOR]

This study aimed to understand the potassium voltage-gated channel KQT-like subfamily, member 1 gene polymorphism in a rural elderly population in a county in Guangxi and to explore the possible relationship between its gene polymorphism and blood sugar. The 6 SNP loci of blood DNA samples from 4355 individuals were typed using the imLDRTM Multiple SNP Typing Kit from Shanghai Tianhao Biotechnology Co. The data combining epidemiological information (baseline questionnaire and physical examination results) and genotyping results were statistically analyzed using GMDR0.9 software and SPSS22.0 software. A total of 4355 elderly people aged 60 years and above were surveyed in this survey, and the total abnormal rate of glucose metabolism was 16·11 % (699/4355). Among them, male:female ratio was 1:1·48; the age group of 60–69 years old accounted for the highest proportion, with 2337 people, accounting for 53·66 % (2337/4355). The results of multivariate analysis showed that usually not doing farm work (OR 1·26; 95 % CI 1·06, 1·50), TAG ≥ 1·70 mmol/l (OR 1·19; 95 % CI 1·11, 1·27), hyperuricaemia (OR 1·034; 95 % CI 1·01, 1·66) and BMI ≥ 24 kg/m2 (OR 1·06; 95 % CI 1·03, 1·09) may be risk factors for abnormal glucose metabolism. Among all participants, rs151290 locus AA genotype, A allele carriers (AA+AC) were 0.70 times more likely (0.54 to 0.91) and 0.82 times more likely (0.70 to 0.97) to develop abnormal glucose metabolism than CC genotype carriers, respectively. Carriers of the T allele at the rs2237892 locus (CT+TT) were 0.85 times more likely to have abnormal glucose metabolism than carriers of the CC genotype (0.72 to 0.99); rs2237897 locus CT gene. The possibility of abnormal glucose metabolism in the carriers of CC genotype, TT genotype and T allele (CT + TT) is 0·79 times (0·67–0·94), 0·74 times (0·55–0·99) and 0·78 times (0·66, 0·92). The results of multifactor dimensionality reduction showed that the optimal interaction model was a three-factor model consisting of farm work, TAG and rs2237897. The best model dendrogram found that the interaction between TAG and rs2237897 had the strongest effect on fasting blood glucose in the elderly in rural areas, and they were mutually antagonistic. Environment–gene interaction is an important factor affecting abnormal glucose metabolism in the elderly of a county in Hechi City, Guangxi. [ABSTRACT FROM AUTHOR]

Mathematical ability is influenced by genes and environment. This study focused on the effect of DRD2, a candidate gene for working memory, on mathematical ability. The results in child participants revealed associations between the DRD2 gene and mathematical ability. It was found that individual's mathematical ability was influenced by Single Nucleotide Polymorphisms (SNPs) in DRD2, both in the form of haplotypes and in the way of interaction with parental education. These findings suggest that dopaminergic genes are linked to mathematical ability. This study provides evidence for the genetic basis of mathematical ability and offers guidance for personalized intervention in mathematical education. [ABSTRACT FROM AUTHOR]

Abstract An increasing number of studies have shown that lead is an important cardiovascular risk factor, but the impact of cardiovascular related gene polymorphisms on lead induced cardiovascular diseases is still unclear. To assess the interaction of lead exposure and related key cardiovascular regulating gene polymorphisms on blood pressure traits, three single-nucleotide polymorphisms including NOTCH1 rs3124591, Cerebral cavernous malformations 3 (CCM3) rs3804610 and Vascular endothelial growth factor receptor type 2 (VEGFR2) rs2305948 were selected and genotyped using improved multiplex ligase detection reaction method in 568 lead exposure workers in South China. General characteristics, blood lead and biochemical parameters including glucose, lipid profile and creatinine were also collected according to standard protocols. Regression analysis was used to evaluate the association of blood pressure with lead exposure, polymorphisms and their interaction. This study displayed that CCM3 rs3804610 had a positive interaction with lead and VEGFR2 rs2305948 had a negative interaction with lead. Specifcally, compared with the wild-type population, the blood lead of the genotype population carrying the risk allele increased by 1 µg/dL, systolic blood pressure increased by 0.53 mmHg (p

Abstract Mathematical ability is influenced by genes and environment. This study focused on the effect of DRD2, a candidate gene for working memory, on mathematical ability. The results in child participants revealed associations between the DRD2 gene and mathematical ability. It was found that individual’s mathematical ability was influenced by Single Nucleotide Polymorphisms (SNPs) in DRD2, both in the form of haplotypes and in the way of interaction with parental education. These findings suggest that dopaminergic genes are linked to mathematical ability. This study provides evidence for the genetic basis of mathematical ability and offers guidance for personalized intervention in mathematical education.

Alcohol use is influenced by genetic and environmental factors. We examined the interactive effects between genome-wide polygenic risk scores for alcohol use (alc-PRS) and social support in relation to alcohol use among European American (EA) and African American (AA) adults across sex and developmental stages (emerging adulthood, young adulthood, and middle adulthood). Data were drawn from 4,011 EA and 1,274 AA adults from the Collaborative Study on the Genetics of Alcoholism who were between ages 18-65 and had ever used alcohol. Participants completed the Semi-Structured Assessment for the Genetics of Alcoholism and provided saliva or blood samples for genotyping. Results indicated that social support from friends, but not family, moderated the association between alc-PRS and alcohol use among EAs and AAs (only in middle adulthood for AAs); alc-PRS was associated with higher levels of alcohol use when friend support was low, but not when friend support was high. Associations were similar across sex but differed across developmental stages. Findings support the important role of social support from friends in buffering genetic risk for alcohol use among EA and AA adults and highlight the need to consider developmental changes in the role of social support in relation to alcohol use.

Bipolar disorder is a complex and severe mental illness characterised by manic and depressive episodes that can be triggered and exacerbated by psychosocial, environmental, and biological stressors. Genetic variations are a risk factor for bipolar disorder. However, the identification of the exact gene variants and genotypes remains complex. This study, therefore, aims to identify the potential association between genotypes of analysed single nucleotide polymorphisms and the presence of a stressor in bipolar disorder patients. We analysed 114 single nucleotide polymorphisms (SNPs) from bipolar and stress-related candidate genes in 550 patients with bipolar disorders (60.36 % females and 39.64 % male). We compared SNPs of patients reporting the presence (40.73 %) or absence of stressors (59.27 %) before the first episode using the Persons Chi-square test and Bayes Factor t -test. The genotyping of 114 SNPs was done using TaqMan assays. Statistical analysis was done using Statistica 13.3 software (StatSoft Poland, Krakow, Poland), R programming, and G*Power statistics. We found significant differences in genotype distribution (p < 0.05) in 6 polymorphisms (AVPRIB /rs28536160, FKBP4 /rs2968909, ADRA2A /rs3750625, 5HTR2A /rs6311, 5HTR2A /rs6313, and GLCCI1 /rs37972) when comparing BD patient with and without stressor with a small effect of d = 0.2. Of these, two gene variants (ADRA2A /rs3750625/AC and AVPRIB /rs28536160/CT) with minor alleles formed an association with the presence of a stressor prior to the disease onset and favoured the alternative hypothesis using Bayes Factor Analysis t -test for hypothesis testing. This study presents a novel association of ADRA2A /rs3750625/AC and AVPR1B /rs28536160/CT gene variants in stress-related bipolar disorder with the AC genotype of ADRA2A /rs3750625 constituting a risk genotype and CT of AVPR1B /rs28536160 constituting a protective genotype. However, further functional analysis is required to fully understand their clinical and biological significance and interaction. [Display omitted] • This study identified novel associations between specific gene variants (ADRA2A /rs3750625/AC and AVPRIB /rs28536160/CT) with stress-related bipolar disorder. • These less commonly observed gene variants, contribute to the understanding of gene-environment interactions in bipolar disorder. • The findings underscore the need for further functional studies to understand the clinical and biological significance of these gene variants and their interaction with stress in bipolar disorder. [ABSTRACT FROM AUTHOR]

Abstract Background Air pollution, a reversible environmental factor, was significantly associated with the cognitive domains that are impaired in major depressive disorder (MDD), notably processing speed. Limited evidence explores the interactive effect of air pollution and the genetic risk of depression on cognition. This cross-sectional study aims to extend the research by specifically examining how this interaction influences depression-related cognitive impairment and resting-state brain function. Methods Eligible participants were 497 healthy adult volunteers (48.7% males, mean age 24.5) living in Beijing for at least 1 year and exposed to relatively high air pollution from the local community controlling for socioeconomic and genomic. Six months’ ambient air pollution exposures were assessed based on residential addresses using monthly averages of fine particulate matter with a diameter of less than or equal to 2.5 μm (PM2.5). A cross-sectional analysis was conducted using functional magnetic resonance imaging (fMRI) and cognitive performance assessments. The polygenic risk score (PRS) of MDD was used to estimate genetic susceptibility. Results Using a general linear model and partial least square regression, we observed a negative association between resting-state local connectivity in precuneus and PRS-by-PM2.5 interactive effect (P FWE = 0.028), indicating that PM2.5 exposure reduced the spontaneous activity in precuneus in individuals at high genetic risk for MDD. DNA methylation and gene expression of the SLC30A3 gene, responsible for maintaining zinc-glutamate homeostasis, was suggestively associated with this local connectivity. For the global functional connectivity, the polygenic risk for MDD augmented the neural impact of PM2.5 exposure, especially in the frontal-parietal and frontal-limbic regions of the default mode network (P FDR

Abstract Background Current research on the epigenetic repercussions of exposure to a combination of pollutants is limited. This study aims to discern DNA methylation probes associated with exposure to multiple pollutants, serving as early effect markers, and single-nucleotide polymorphisms (SNPs) as surrogate indicators for population susceptibility. The investigation involved the analysis of urine exposure biomarkers for 11 heavy metals (vanadium, arsenic, mercury, cadmium, chromium, nickel, lead, manganese, copper, strontium, thallium), polycyclic aromatic hydrocarbon (PAHs) (1-hydroxypyrene), genome-wide DNA methylation sequencing, and SNPs array on all study participants. The data were integrated with metabolomics information and analyzed both at a community level based on proximity to home addresses relative to the complex and at an individual level based on exposure biomarker concentrations. Results On a community level, 67 exposure-related CpG probes were identified, while 70 CpG probes were associated with urine arsenic concentration, 2 with mercury, and 46 with vanadium on an individual level. These probes were annotated to genes implicated in cancers and chronic kidney disease. Weighted quantile sum regression analysis revealed that vanadium, mercury, and 1-hydroxypyrene contributed the most to cg08238319 hypomethylation. cg08238319 is annotated to the aryl hydrocarbon receptor repressor (AHRR) gene, and AHRR hypomethylation was correlated with an elevated risk of lung cancer. AHRR was further linked to deregulations in phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, along with heightened oxidative stress. Additionally, three SNPs (rs11085020, rs199442, and rs10947050) corresponding to exposure-related CpG probes exhibited significant interaction effects with multiple heavy metals and PAHs exposure, and have been implicated in cancer progression and respiratory diseases. Conclusion Our findings underscore the pivotal role of AHRR methylation in gene-environment interactions and highlight SNPs that could potentially serve as indicators of population susceptibility in regions exposed to multiple heavy metals and PAHs.

Heading date determines rice seasonal and regional adaptation, while plant height is an important trait related to rice lodging resistance. In this study, a recombinant inbred line population was used to detect quantitative trait loci (QTLs) for both traits in long-day (LD) and short-day (SD) environments. Three and two QTLs for heading date were detected in LD and SD environments, respectively. Notably, qHD8 and qHD10 were commonly detected in both environments. Five and four QTLs for plant height were identified in LD and SD environments, respectively. Among them, qPH3, qPH5 and qPH6 showed no pleiotropic effects on heading date and were detected in both environments. These three QTLs are considered to be the primary targets for improving rice plant height. Additionally, two genomic regions exhibited pleiotropic effects on both heading date and plant height. The alleles delayed the heading date while simultaneously increasing plant height. This study indicated that most QTLs for heading date are sensitive to photoperiod and have pleiotropic effects on plant height, thereby complicating their application in breeding programs. These findings provide useful information for the breeding of rice varieties with desired heading dates and plant heights.

The complex association between obesity and prostate cancer necessitates exploring how obesity impacts the incidence, progression, treatment response, and prognosis of prostate cancer. An analysis was conducted to determine the potential adverse effects of obesity on prostate cancer treatment, including changes in drug metabolism and surgical complications. It also discusses how obesity increases the risk of disease progression and recurrence. Further emphasis was provided to the importance of comprehensive interventions to reduce the risk of prostate cancer through lifestyle modifications (including healthy diet, moderate exercise, and maintaining normal weight), pharmacological treatments (such as potential drugs targeting obesity and prostate cancer-related mechanisms), and regular check-ups and screenings. Lastly, the work envisions future research directions, including exploring the specific mechanisms linking obesity and prostate cancer, designing more scientific clinical trials, and enhancing interdisciplinary cooperation. These opportunities and challenges aim to provide references and insights for future research and development

In addition to considering the main effects, understanding gene‐environment (G × E) interactions is imperative for determining the etiology of diseases and the factors that affect their prognosis. In the existing statistical framework for censored survival outcomes, there are several challenges in detecting G × E interactions, such as handling high‐dimensional omics data, diverse environmental factors, and algorithmic complications in survival analysis. The effect heredity principle has widely been used in studies involving interaction identification because it incorporates the dependence of the main and interaction effects. However, Bayesian survival models that incorporate the assumption of this principle have not been developed. Therefore, we propose Bayesian heredity‐constrained accelerated failure time (BHAFT) models for identifying main and interaction (M‐I) effects with novel spike‐and‐slab or regularized horseshoe priors to incorporate the assumption of effect heredity principle. The R package rstan was used to fit the proposed models. Extensive simulations demonstrated that BHAFT models had outperformed other existing models in terms of signal identification, coefficient estimation, and prognosis prediction. Biologically plausible G × E interactions associated with the prognosis of lung adenocarcinoma were identified using our proposed model. Notably, BHAFT models incorporating the effect heredity principle could identify both main and interaction effects, which are highly useful in exploring G × E interactions in high‐dimensional survival analysis. The code and data used in our paper are available at https://github.com/SunNa‐bayesian/BHAFT. [ABSTRACT FROM AUTHOR]

Background : Air pollution, a reversible environmental factor, was significantly associated with the cognitive domains that are impaired in major depressive disorder (MDD), notably processing speed. Limited evidence explores the interactive effect of air pollution and the genetic risk of depression on cognition. This cross-sectional study aims to extend the research by specifically examining how this interaction influences depression-related cognitive impairment and resting-state brain function. Methods: Eligible participants were 497 healthy adult volunteers (48.7% males, mean age 24.5) living in Beijing for at least 1 year and exposed to relatively high air pollution from the local community controlling for socioeconomic and genomic. Six months' ambient air pollution exposures were assessed based on residential addresses using monthly averages of fine particulate matter with a diameter of less than or equal to 2.5 μm (PM2.5). A cross-sectional analysis was conducted using functional magnetic resonance imaging (fMRI) and cognitive performance assessments. The polygenic risk score (PRS) of MDD was used to estimate genetic susceptibility. Results: Using a general linear model and partial least square regression, we observed a negative association between resting-state local connectivity in precuneus and PRS-by-PM2.5 interactive effect (PFWE = 0.028), indicating that PM2.5 exposure reduced the spontaneous activity in precuneus in individuals at high genetic risk for MDD. DNA methylation and gene expression of the SLC30A3 gene, responsible for maintaining zinc-glutamate homeostasis, was suggestively associated with this local connectivity. For the global functional connectivity, the polygenic risk for MDD augmented the neural impact of PM2.5 exposure, especially in the frontal-parietal and frontal-limbic regions of the default mode network (PFDR < 0.05). In those genetically predisposed to MDD, increased PM2.5 exposure positively correlated with resting-state functional connectivity between the left angular gyrus and left cuneus gyrus. This connectivity was negatively associated with processing speed. Conclusions: Our cross-sectional study suggests that air pollution may be associated with an increased likelihood of cognitive impairment in individuals genetically predisposed to depression, potentially through alterations in the resting-state function of the occipitoparietal and default mode network. [ABSTRACT FROM AUTHOR]

Parental genes can influence the phenotype of their offspring through genomic-epigenomic interactions even without the direct inheritance of specific parental genotypes. Maternal genetic variations can affect the ovarian and intrauterine environments and potentially alter lactation behaviors, impacting offspring nutrition and health outcomes independently of the fetal genome. Similarly, paternal genetic changes can affect the endocrine system and vascular functions in the testes, influencing sperm quality and seminal fluid composition. These changes can initiate early epigenetic modifications in sperm, including alterations in microRNAs, tRNA-derived small RNAs (tsRNAs), and DNA methylation patterns. These epigenetic modifications might induce further changes in target organs of the offspring, leading to modified gene expression and phenotypic outcomes without transmitting the original parental genetic alterations. This review presents clinical evidence supporting this hypothesis and discusses the potential underlying molecular mechanisms. Parental gene-offspring epigenome-offspring phenotype interactions have been observed in neurocognitive disorders and cardio-renal diseases. [ABSTRACT FROM AUTHOR]

Steatotic liver disease (SLD), characterized by elevated liver fat content (LFC), is influenced by genetics and diet. However, whether diet has a differential effect based on genetic risk is not well-characterized. We aimed to determine how genetic factors interact with diet to affect SLD in a large national biobank. We included UK Biobank participants with dietary intake measured by 24-hour recall and genotyping. The primary predictors were dietary pattern, PNPLA3 -rs738409-G, TM6SF2 -rs58542926-T, a 16-variant hepatic steatosis polygenic risk score (PRS), and gene-environment interactions. The primary outcome was LFC, and secondary outcomes were iron-controlled T1 time (cT1, a measure of liver inflammation and fibrosis) and liver-related events/mortality. A total of 21,619 participants met inclusion criteria. In non-interaction models, Mediterranean diet and intake of fruit/vegetables/legumes and fish associated with lower LFC, while higher red/processed meat intake and all genetic predictors associated with higher LFC. In interaction models, all genetic predictors interacted with Mediterranean diet and fruit/vegetable/legume intake, while the steatosis PRS interacted with fish intake and the TM6SF2 genotype interacted with red/processed meat intake, to affect LFC. Dietary effects on LFC were up to 3.8-fold higher in PNPLA3 -rs738409-GG vs. –CC individuals, and 1.4-3.0-fold higher in the top vs. bottom quartile of the steatosis PRS. Gene-diet interactions were stronger in participants with vs. without overweight. The steatosis PRS interacted with Mediterranean diet and fruit/vegetable/legume intake to affect cT1 and most dietary and genetic predictors associated with risk of liver-related events or mortality by age 70. Effects of diet on LFC and cT1 were markedly accentuated in patients at increased genetic risk for SLD, implying dietary interventions may be more impactful in these populations. Genetic variants and diet both influence risk of hepatic steatosis, inflammation/fibrosis, and hepatic decompensation; however, how gene-diet interactions influence these outcomes has previously not been comprehensively characterized. We investigated this topic in the community-based UK Biobank and found that genetic risk and dietary quality interacted to influence hepatic steatosis and inflammation/fibrosis on liver MRI, so that the effects of diet were greater in people at elevated genetic risk. These results are relevant for patients and medical providers because they show that genetic risk is not fixed (i.e. modifiable factors can mitigate or exacerbate this risk) and realistic dietary changes may result in meaningful improvement in liver steatosis and inflammation/fibrosis. As genotyping becomes more routinely used in clinical practice, patients identified to be at high baseline genetic risk may benefit even more from intensive dietary counseling than those at lower risk, though future prospective studies are required. [Display omitted] • Poor diet quality and specific genetic alleles are associated with steatotic liver disease. • Diet has a much greater impact on hepatic steatosis in those at higher genetic risk. • These effects were seen for both liver fat content and iron-controlled T1 time (a measure of fibrosis and inflammation). • Hence, dietary interventions may have a greater impact in populations at higher genetic risk. [ABSTRACT FROM AUTHOR]

The AZFc partial deletions of Y chromosome and lifestyle/epidemiological factors such as the use of smokeless chewing tobacco (SCT) exhibit intriguing variations in their association with male infertility across the population, ethnicity, and genetic background. Here, a pioneering attempt has been made to elucidate the interactions of such deletions with the habits of SCT consumption among the participating individuals, using their large epidemiological data. This screening program was conducted among Bengali-speaking men in West Bengal, India. We screened the prevalence and association of distinct partial deletions (gr/gr, b1/b3, and b2/b3) of the AZFc region using locus-specific sequence-tagged site (STS) markers among 728 case subjects and compared them with 264 ethnicity- and age-matched proven-fertile control men. The recorded epidemiological data of the study group and the outcome of partial deletion analysis were compiled to frame the plausible Gene × Epidemiological factor (G × E) interactions. The gr/gr deletion was reported to be significantly associated with azoospermic (p =.0015, odds ratio [OR] = 3.413) and oligozoospermic (p =.0382, OR = 3.012) case subgroups, and b1/b3 deletions were also detected among the infertile persons only. The G × E model revealed that men who carried microdeletions as well as were SCT users had an elevated risk of infertility (p =.002, OR = 6.38). The study highlights the fact that AZFc partial deletions and SCT, when co-occurred, synergistically increase the risk of infertility among men. This work helps to get more insight into the etiology of male infertility in the light of gene–environmental interaction. [ABSTRACT FROM AUTHOR]

Variation in political preferences is increasingly understood to stem from both environmental influences and genetics. Research in political psychology has argued that a pathway for genetic effects on ideology is via cognitive performance, showing a sizable genetic overlap between the traits. Yet the link between actual trait cognitive performance and economic conservatism is itself highly ambiguous, with both positive, null, and negative estimates prevalent in the literature. In this study, I argue that this puzzle can only be understood from a gene–environment interaction (GxE) perspective. Drawing on traditional theories of political preference formation, I argue that genetics associated with cognitive performance should cause more left‐wing economic preferences if you grow up in relative poverty, but more right‐wing economic preferences if you grow up affluent. Utilizing variation in a polygenic index (PGI) of cognitive performance within dizygotic twin pairs, coupled with unique register data on economic conditions for the twins, their parents, and their childhood neighborhood, I show that the causal effect of the PGI on economic conservatism is zero on average, but indeed sizable and sign‐discordant by class background. The GxE perspective thus has wide‐ranging implications for future research attempting to integrate genetic methods into political psychology. [ABSTRACT FROM AUTHOR]

Background: Current research on the epigenetic repercussions of exposure to a combination of pollutants is limited. This study aims to discern DNA methylation probes associated with exposure to multiple pollutants, serving as early effect markers, and single-nucleotide polymorphisms (SNPs) as surrogate indicators for population susceptibility. The investigation involved the analysis of urine exposure biomarkers for 11 heavy metals (vanadium, arsenic, mercury, cadmium, chromium, nickel, lead, manganese, copper, strontium, thallium), polycyclic aromatic hydrocarbon (PAHs) (1-hydroxypyrene), genome-wide DNA methylation sequencing, and SNPs array on all study participants. The data were integrated with metabolomics information and analyzed both at a community level based on proximity to home addresses relative to the complex and at an individual level based on exposure biomarker concentrations. Results: On a community level, 67 exposure-related CpG probes were identified, while 70 CpG probes were associated with urine arsenic concentration, 2 with mercury, and 46 with vanadium on an individual level. These probes were annotated to genes implicated in cancers and chronic kidney disease. Weighted quantile sum regression analysis revealed that vanadium, mercury, and 1-hydroxypyrene contributed the most to cg08238319 hypomethylation. cg08238319 is annotated to the aryl hydrocarbon receptor repressor (AHRR) gene, and AHRR hypomethylation was correlated with an elevated risk of lung cancer. AHRR was further linked to deregulations in phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, along with heightened oxidative stress. Additionally, three SNPs (rs11085020, rs199442, and rs10947050) corresponding to exposure-related CpG probes exhibited significant interaction effects with multiple heavy metals and PAHs exposure, and have been implicated in cancer progression and respiratory diseases. Conclusion: Our findings underscore the pivotal role of AHRR methylation in gene-environment interactions and highlight SNPs that could potentially serve as indicators of population susceptibility in regions exposed to multiple heavy metals and PAHs. [ABSTRACT FROM AUTHOR]

Introduction: Vitamin C is an essential nutrient. Sex differences in serum vitamin C concentrations have been observed but are not fully known. Investigation of levels of metabolites may help shed light on how dietary and other environmental exposures interact with molecular processes. O-methylascorbate and ascorbic acid 2-sulfate are two metabolites in the vitamin C metabolic pathway. Past research has found genetic factors that influence the levels of these two metabolites. Therefore, we investigated possible effect modification by sex of genetic variant-metabolite associations and characterized the biological function of these interactions. Methods: We included individuals of European descent from the Canadian Longitudinal Study on Aging with available genetic and metabolic data (n = 9004). We used linear mixed models to tests for genome-wide associations with O-methylascorbate and ascorbic acid 2-sulfate, with and without a sex interaction. We also investigated the biological function of the important genetic variant-sex interactions found for each metabolite. Results: Two genome-wide statistically significant (p value < 5 × 10-8) interaction effects and several suggestive (p value < 10-5) interaction effects were found. These suggestive interaction effects were mapped to several genes including HSD11B2, associated with sex hormones, and AGRP, associated with hunger drive. The genes mapped to O-methylascorbate were differently expressed in the testis tissues, and the genes mapped to ascorbic acid 2-sulfate were differently expressed in stomach tissues. Discussion: By understanding the genetic factors that impact metabolites associated with vitamin C, we can better understand its function in disease risk and the mechanisms behind sex differences in vitamin C concentrations. [ABSTRACT FROM AUTHOR]

Environment and genes both contribute to schizophrenia. However, the impact of different natural environments surrounding residential addresses on schizophrenia in urban settings remains unknown. This study aimed to investigate the association of urbanisation, measured by residential environments, with late-onset schizophrenia and explore whether genetic risk for schizophrenia modified the associations. We examined the associations between residential environments and late-onset schizophrenia and its interaction with genetic risk factors in UK Biobank, followed from 2006 to 2010 (baseline) to Dec 2021. Residential environments, including greenspace, domestic garden, blue space, and total natural environment, were evaluated using land use coverage percentage. The polygenic risk score (PRS) of schizophrenia was derived using a Bayesian approach and adjusted it against ancestry. Cox proportional hazard regression model was used to assess the associations between per interquartile (IQR) increase of each type of residential environments and late-onset schizophrenia. Interactive effects of PRS and residential environments on late-onset schizophrenia were assessed on both additive and multiplicative scales. A total of 393,680 participants were included in the analysis, with 844 cases of late-onset schizophrenia being observed after 12.8 years of follow-up. Within 300 m buffer surrounding the residential addresses, per interquartile increase in greenspace (31.5 %) and total natural environment (34.4 %) were both associated with an 11 % (HR = 0.89, 95 % CI 0.80, 0.99) lower risk of late-onset schizophrenia. Domestic garden and blue space did not show significant protective effects on late-onset schizophrenia. A strong dose-response relationship between schizophrenia PRS and schizophrenia was found, while no additive or multiplicative interaction effects were present between residential environments and PRS on late-onset schizophrenia. Residential greenspace and total natural environment may protect against late-onset schizophrenia in older people regardless of genetic risk. These findings shed light on the prevention of schizophrenia and urban planning to optimise ecosystem benefits linked to schizophrenia. [Display omitted] • Residential green and natural space were related to lower late-onset schizophrenia. • Such protective associations were not found for domestic garden or blue space. • Gene did not modify the associations of residential environments with late-onset schizophrenia. • Our results show important implications for urban planning to prevent schizophrenia. [ABSTRACT FROM AUTHOR]

The complexity of cancer development involves intricate interactions among multiple biomarkers, such as gene-environment interactions. Utilizing microarray gene expression profile data for cancer classification is anticipated to be effective, thus drawing considerable interest in the fields of bioinformatics and computational biology. Due to the characteristics of genomic data, problems of high-dimensional interactions and noise interference do exist during the analysis process. When building cancer diagnosis models, we often face the dilemma of model adaptation errors due to an imbalance of data types. To mitigate the issues, we apply the SMOTE-Tomek procedure to rectify the imbalance problem. Following this, we utilize the overlapping group screening method alongside a binary logistic regression model to integrate gene pathway information, facilitating the identification of significant biomarkers associated with clinically imbalanced cancer or normal outcomes. Simulation studies across different imbalanced rates and gene structures validate our proposed method's effectiveness, surpassing common machine learning techniques in terms of classification prediction accuracy. We also demonstrate that prediction performance improves with SMOTE-Tomek treatment compared to no imbalance treatment and SMOTE treatment across various imbalance rates. In the real-world application, we integrate clinical and gene expression data with prior pathway information. We employ SMOTE-Tomek and our proposed methods to identify critical biomarkers and gene-environment interactions linked to the imbalanced binary outcomes (cancer or normal) in patients from the Cancer Genome Atlas datasets of lung adenocarcinoma and breast invasive carcinoma. Our proposed method consistently achieves satisfactory classification accuracy. Additionally, we have identified biomarkers indicative of gene-environment interactions relevant to cancer and have provided corresponding estimates of odds ratios. Moreover, in high-dimensional imbalanced data, for achieving good prediction results, we recommend considering the order of balancing processing and feature screening. [ABSTRACT FROM AUTHOR]

Gene–environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene–Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits. [ABSTRACT FROM AUTHOR]

Tobacco carcinogens metabolism-related genes (TCMGs) could generate reactive metabolites of tobacco carcinogens, which subsequently contributed to multiple diseases. However, the association between genetic variants in TCMGs and bladder cancer susceptibility remains unclear. In this study, we derived TCMGs from metabolic pathways of polycyclic aromatic hydrocarbons and tobacco-specific nitrosamines, and then explored genetic associations between TCMGs and bladder cancer risk in two populations: a Chinese population of 580 cases and 1101 controls, and a European population of 5930 cases and 5468 controls, along with interaction and joint analyses. Expression patterns of TCMGs were sourced from Nanjing Bladder Cancer (NJBC) study and publicly available datasets. Among 43 TCMGs, we observed that rs7087341 T > A in AKR1C2 was associated with a reduced risk of bladder cancer in the Chinese population [odds ratio (OR) = 0.84, 95% confidence interval (CI) = 0.72–0.97, P = 1.86 × 10–2]. Notably, AKR1C2 rs7087341 showed an interaction effect with cigarette smoking on bladder cancer risk (Pinteraction = 5.04 × 10–3), with smokers carrying the T allele increasing the risk up to an OR of 3.96 (Ptrend < 0.001). Genetically, rs7087341 showed an allele-specific transcriptional regulation as located at DNA-sensitive regions of AKR1C2 highlighted by histone markers. Mechanistically, rs7087341 A allele decreased AKR1C2 expression, which was highly expressed in bladder tumors that enhanced metabolism of tobacco carcinogens, and thereby increased DNA adducts and reactive oxygen species formation during bladder tumorigenesis. These findings provided new insights into the genetic mechanisms underlying bladder cancer. [ABSTRACT FROM AUTHOR]

A high level of homocysteine (Hcy) is associated with oxidative/ER stress, apoptosis, and impairment of angiogenesis, whereas hydrogen sulfide (H2S) has been found to reverse this condition. Recent studies have shown that cancer cells need to produce a high level of endogenous H2S to maintain cell proliferation, growth, viability, and migration. However, any novel mechanism that targets this balance of Hcy and H2S production has yet to be discovered or exploited. Cells require homocysteine metabolism via the methionine cycle for nucleotide synthesis, methylation, and reductive metabolism, and this pathway supports the high proliferative rate of cancer cells. Although the methionine cycle favors cancer cells for their survival and growth, this metabolism produces a massive amount of toxic Hcy that somehow cancer cells handle very well. Recently, research showed specific pathways important for balancing the antioxidative defense through H2S production in cancer cells. This review discusses the relationship between Hcy metabolism and the antiapoptotic, antioxidative, anti-inflammatory, and angiogenic effects of H2S in different cancer types. It also summarizes the historical understanding of targeting antioxidative defense systems, angiogenesis, and other protective mechanisms of cancer cells and the role of H2S production in the genesis, progression, and metastasis of cancer. This review defines a nexus of diet and precision medicine in targeting the delicate antioxidative system of cancer and explores possible future therapeutics that could exploit the Hcy and H2S balance.

BackgroundWe previously reported an association between household chemical exposures and an increased risk of paediatric-onset multiple sclerosis.MethodsUsing a case-control paediatric multiple sclerosis study, gene-environment interaction between exposure to household chemicals and genotypes for risk of paediatric-onset multiple sclerosis was estimated.Genetic risk factors of interest included the two major HLA multiple sclerosis risk factors, the presence of DRB1*15 and the absence of A*02, and multiple sclerosis risk variants within the metabolic pathways of common household toxic chemicals, including IL-6 (rs2069852), BCL-2 (rs2187163) and NFKB1 (rs7665090).Results490 paediatric-onset multiple sclerosis cases and 716 controls were included in the analyses. Exposures to insect repellent for ticks or mosquitos (OR 1.47, 95% CI 1.06 to 2.04, p=0.019), weed control products (OR 2.15, 95% CI 1.51 to 3.07, p

Background Whether genetic susceptibility to cardiovascular diseases (CVDs) enhances the vulnerability to adverse cardiovascular outcomes by air pollution is unknown. We assessed the combined effect of air pollution and genetic predispositions on CVD risk. Methods and Results From the UK Biobank cohort, we selected genetically unrelated White British participants without CVD. Levels of ambient particulate matter with a diameter of

Background: The present genome-wide association study (GWAS) aimed to reveal the genetic loci associated with folate metabolites, as well as to detect related gene–environment interactions in Japanese. Methods: We conducted the GWAS of plasma homocysteine (Hcy), folic acid (FA), and vitamin B12 (VB12) levels in the Japan Multi-Institutional Collaborative Cohort (J-MICC) Study participants who joined from 2005 to 2012, and also estimated gene–environment interactions. In the replication phase, we used data from the Yakumo Study conducted in 2009. In the discovery phase, data of 2,263 participants from four independent study sites of the J-MICC Study were analyzed. In the replication phase, data of 573 participants from the Yakumo Study were analyzed. Results: For Hcy, MTHFR locus on chr 1, NOX4 on chr 11, CHMP1A on chr 16, and DPEP1 on chr 16 reached genome-wide significance (P < 5 × 10−8). MTHFR also associated with FA, and FUT2 on chr 19 associated with VB12. We investigated gene-environment interactions in both studies and found significant interactions between MTHFR C677T and ever drinking, current drinking, and physical activity >33% on Hcy (β = 0.039, 0.038 and −0.054, P = 0.018, 0.021 and

Abstract Background Both genetic and environmental factors play crucial roles in the development of major depressive disorder (MDD) and suicide attempts (SA). However, the interaction between both items remains unknown. This study aims to explore the interactions between the genetic variants of the serotonin 2 A receptor (HTR2A) and the nitric oxide synthase 1 (NOS1) and environmental factors in patients who experience MDD and SA. Methods A total of 334 patients with MDD and a history of SA (MDD-SA) were recruited alongside 518 patients with MDD with no history of SA (MDD-NSA), and 716 healthy controls (HC). The demographic data and clinical characteristics were collected. Sequenom mass spectrometry was used to detect eight tag-single nucleotide polymorphisms (tagSNPs) in HTR2A (rs1328683, rs17068986, and rs3125) and NOS1 (rs1123425, rs2682826, rs3741476, rs527590, and rs7959232). Generalized multifactor dimensionality reduction (GMDR) was used to analyze the gene-environment interactions. Results Four tagSNPs (rs17068986, rs3125, rs527590, and rs7959232) exhibited significant differences between the three groups. However, these differences were not significant between the MDD-SA and MDD-NSA groups after Bonferroni correction. A logistic regression analysis revealed that negative life events (OR = 1.495, 95%CI: 1.071–2.087, P = 0.018), self-guilt (OR = 2.263, 95%CI: 1.515–3.379, P

BackgroundGenome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.MethodsAnalyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.ResultsAssuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Exposure to inorganic arsenic (As) is recognized as a risk factor for non-melanoma skin cancer (NMSC). We followed up with 7000 adults for 6 years who were exposed to As. During follow-up, 2.2% of the males and 1.3% of the females developed basal cell carcinoma (BCC), while 0.4% of the male and 0.2% of the female participants developed squamous cell carcinoma (SCC). Using a panel of more than 400 cancer-related genes, we detected somatic mutations (SMs) in the first 32 NMSC samples (BCC = 26 and SCC = 6) by comparing paired (tissue–blood) samples from the same individual and then comparing them to the SM in healthy skin tissue from 16 participants. We identified (a) a list of NMSC-associated SMs, (b) SMs present in both NMSC and healthy skin, and (c) SMs found only in healthy skin. We also demonstrate that the presence of non-synonymous SMs in the top mutated genes (like PTCH1, NOTCH1, SYNE1, PKHD1 in BCC and TP53 in SCC) significantly affects the magnitude of differential expressions of major genes and gene pathways (basal cell carcinoma pathways, NOTCH signaling, IL-17 signaling, p53 signaling, Wnt signaling pathway). These findings may help select groups of patients for targeted therapy, like hedgehog signaling inhibitors, IL17 inhibitors, etc., in the future. [ABSTRACT FROM AUTHOR]

Background: The way in which socioeconomic status (SES) moderates the etiology of reading attainment has been explored many times, with past work often finding that genetic influences are suppressed under conditions of socioeconomic deprivation and more fully realized under conditions of socioeconomic advantage: a gene–SES interaction. Additionally, past work has pointed toward the presence of gene–location interactions, with the relative influence of genes and environment varying across geographic regions of the same country/state. Method: This study investigates the extent to which SES and geographical location interact to moderate the genetic and environmental components of reading attainment. Utilizing data from 2,135 twin pairs in Florida (mean age 13.82 years, range 10.71–17.77), the study operationalized reading attainment as reading comprehension scores from a statewide test and SES as household income. We applied a spatial twin analysis procedure to investigate how twin genetic and environmental estimates vary by geographic location. We then expanded this analysis to explore how the moderating role of SES on said genetic and environmental influences also varied by geographic location. Results: A gene–SES interaction was found, with heritability of reading being suppressed in lower‐ (23%) versus higher‐SES homes (78%). The magnitude of the moderating parameters were not consistent by location, however, and ranged from −0.10 to 0.10 for the moderating effect on genetic influences, and from −0.30 to 0.05 for the moderating effect on environmental influences. For smaller areas and those with less socioeconomic variability, the magnitude of the genetic moderating parameter was high, giving rise to more fully realized genetic influences on reading there. Conclusions: SES significantly influences reading variability. However, a child's home location matters in both the overall etiology and how strongly SES moderates said etiologies. These results point toward the presence of multiple significant environmental factors that simultaneously, and inseparably, influence the underlying etiology of reading attainment. [ABSTRACT FROM AUTHOR]

While genetic and environmental factors have been shown as predictors of children's reading ability, the interaction effects of identified genetic risk susceptibility and the specified environment for reading ability have rarely been investigated. The current study assessed potential gene–environment (G×E) interactions on reading ability in 1477 school-aged children. The gene–environment interactions on character recognition were investigated by an exploratory analysis between the risk single-nucleotide polymorphisms (SNPs), which were discovered by previous genome-wide association studies of developmental dyslexia (DD), and parental education (PE). The re-parameterized regression analysis suggested that this G×E interaction conformed to the strong differential susceptibility model. The results showed that rs281238 exhibits a significant interaction with PE on character recognition. Children with the "T" genotype profited from high PE, whereas they performed worse in low PE environments, but "CC" genotype children were not malleable in different PE environments. This study provided initial evidence for how the significant SNPs in developmental dyslexia GWA studies affect children's reading performance by interacting with the environmental factor of parental education. [ABSTRACT FROM AUTHOR]

Objectives: Few studies have been conducted on gene–environment interactions in the Chinese population with Crohn's disease (CD). We aimed to investigate the association between single nucleotide polymorphisms (SNPs) on the T helper 17 (Th17) cell and CD susceptibility/performance in Chinese individuals. Methods: We conducted a case–control and case‐only study at the Peking Union Medical College Hospital. Four SNPs related to the Th17 cell pathway genes were prioritized, including rs2284553 (interferon gamma receptor 2), rs7517847 (interleukin 23 receptor), rs7773324 (interferon regulatory factor 4), and rs4263839 (tumor necrosis factor superfamily 15). SNP frequency was calculated, and gene–environment interaction was assessed by multifactor dimensionality reduction analysis. Results: Altogether 159 CD patients and 316 healthy controls were included. All analyzed SNPs were found in Hardy–Weinberg equilibrium (P > 0.05). The frequency of rs2284553‐A allele and rs4263839‐A allele were lower in CD patients compared with controls (P < 0.05). While the rs4263839‐A allele was more prevalent in ileocolonic CD patients than in those with isolated small intestinal or colonic disease (P = 0.035). Gene–environment interactions revealed associations between rs2284553 and breastfeeding, sunshine exposure, and fridge‐stored food, affecting age at diagnosis, intestinal involvement, and intestinal stricture. Interaction of rs4263839 and breastfeeding influenced small intestinal lesions and intestinal stricture in CD. Conclusions: This study provided information on the genetic background in Chinese CD patients. Incorporating these SNPs into predictive models may improve risk assessment and outcome prediction. Gene–environment interaction contributes to the understanding of CD pathogenesis. [ABSTRACT FROM AUTHOR]

The postnatal brain undergoes chromatin and transcriptional changes that underlie functional maturation (e.g., electrophysiological properties, morphology, connectivity, network activity) across the lifespan. While these changes are observed across the animal kingdom, changes associated with maturation, including timing, are often neuron-type, brain-region, and species specific. Sensory stimulus coordination of neuronal activity and cross-modal neurotransmission is one mechanism by which the external environment regulates neuronal maturation. Neuronal activity controls the molecular changes underlying neuronal maturation by regulating transcriptional and chromatin factors. Aspects of postnatal neuronal maturation are regulated by cell-intrinsic sensory stimulus-independent genetic timer cascades. These mechanisms are intertwined with cell-extrinsic mechanisms to control maturation. Embryonic neurodevelopment, particularly neural progenitor differentiation into post-mitotic neurons, has been extensively studied. While the number and composition of post-mitotic neurons remain relatively constant from birth to adulthood, the brain undergoes significant postnatal maturation marked by major property changes frequently disrupted in neural diseases. This review first summarizes recent characterizations of the functional and molecular maturation of the postnatal nervous system. We then review regulatory mechanisms controlling the precise gene expression changes crucial for the intricate sequence of maturation events, highlighting experience-dependent versus cell-intrinsic genetic timer mechanisms. Despite significant advances in understanding of the gene-environmental regulation of postnatal neuronal maturation, many aspects remain unknown. The review concludes with our perspective on exciting future research directions in the next decade. [ABSTRACT FROM AUTHOR]

Copy number variations (CNVs) critically influence individual genetic diversity and phenotypic traits. In this study, we employed whole-genome resequencing technology to conduct an in-depth analysis of 50 pigs from five local swine populations [Rongchang pig (RC), Wuzhishan pig (WZS), Tibetan pig (T), Yorkshire (YL) and Landrace (LR)], aiming to assess their genetic potential and explore their prospects in the field of animal model applications. We identified a total of 96,466 CNVs, which were subsequently integrated into 7112 non-redundant CNVRs, encompassing 1.3% of the swine genome. Functional enrichment analysis of the genes within these CNVRs revealed significant associations with sensory perception, energy metabolism, and neural-related pathways. Further selective scan analyses of the local pig breeds RC, T, WZS, along with YL and LR, uncovered that for the RC variety, the genes PLA2G10 and ABCA8 were found to be closely related to fat metabolism and cardiovascular health. In the T breed, the genes NCF2 and CSGALNACT1 were associated with immune response and connective tissue characteristics. As for the WZS breed, the genes PLIN4 and CPB2 were primarily linked to fat storage and anti-inflammatory responses. In summary, this research underscores the pivotal role of CNVs in fostering the diversity and adaptive evolution of pig breeds while also offering valuable insights for further exploration of the advantageous genetic traits inherent to China's local pig breeds. This facilitates the creation of experimental animal models tailored to the specific characteristics of these breeds, contributing to the advancement of livestock and biomedical research. [ABSTRACT FROM AUTHOR]

A recent report by G. Clark points to a sustained persistence of social status in England that extends vertically across several generations and horizontally across many levels of kinship. We seek to put his findings in historical perspective. We do so by relating them to two lines of thinking related to biological inheritance. One predated the rediscovery of Mendel’s work and led to the field of quantitative genetics, which dealt on the whole with quasi-continuously varying traits. The other is based on the rediscovery itself and led to a reconciliation between quantitative genetics and discrete Mendelian elements of heredity. Both were enmeshed with the supposed need for, and societal consequences of, eugenics and assortative mating. Also on both issues, the significant ideas can be traced to R. A. Fisher, inspired in one case by F. Galton and in the other by J. A. Cobb, with strong support for Galton and Cobb coming from Karl Pearson. Clark’s findings point to societal stratification, and assortative mating for wealth is a straightforward hypothesis to account for it. However, it should be noted that the findings support, but do not prove, the hypothesis. [ABSTRACT FROM AUTHOR]

The current knowledge on pancreatic ductal adenocarcinoma (PDAC) risk factors is limited and no study has comprehensively tested the exposome in combination with the genetic variability in relation to the disease susceptibility. The aim of this study was to analyze the exposome and its interaction with known genetic susceptibility loci, in relation to PDAC risk. A case-control study nested in UK Biobank cohort was conducted on 816 PDAC cases and 302,645 controls. A total of 347 exposure variables, and a polygenic risk score (PRS) were analyzed through logistic regression. Gene-environment interaction analyses were conducted. A total of 52 associations under the Bonferroni corrected threshold of p < 1.46 × 10−4 were observed. Known risk factors such as smoking, pancreatitis, diabetes, PRS, heavy alcohol drinking and overweight were replicated in this study. As for novel associations, a clear indication for length and intensity of mobile phone use and the stress-related factors and stressful events with increase of PDAC risk was observed. Although the PRS was associated with PDAC risk (P = 2.09 × 10−9), statistically significant gene-exposome interactions were not identified. In conclusion, our results suggest that a stressful lifestyle and sedentary behaviors may play a major role in PDAC susceptibility independently from the genetic background. [ABSTRACT FROM AUTHOR]

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The development of modern science and technology has facilitated the collection of a large amount of matrix data in fields such as biomedicine. Matrix data modeling has been extensively studied, which advances from the naive approach of flattening the matrix into a vector. However, existing matrix modeling methods mainly focus on homogeneous data, failing to handle the data heterogeneity frequently encountered in the biomedical field, where samples from the same study belong to several underlying subgroups, and different subgroups follow different models. In this paper, we focus on regression-based heterogeneity analysis. We propose a matrix data heterogeneity analysis framework, by combining matrix bilinear sparse decomposition and penalized fusion techniques, which enables data-driven subgroup detection, including determining the number of subgroups and subgrouping membership. A rigorous theoretical analysis is conducted, including asymptotic consistency in terms of subgroup detection, the number of subgroups, and regression coefficients. Numerous numerical studies based on simulated and real data have been constructed, showcasing the superior performance of the proposed method in analyzing matrix heterogeneous data. [ABSTRACT FROM AUTHOR]

Previous research concerning the interplay between genetics and parenting in the development of the parent-child relationship during adolescence has been extremely scarce, predominantly adopting single-gene designs. This limited body of work has largely overlooked the distinct effects of maternal and paternal roles, as well as potential gender differences. Additionally, existing gene-by-environment (G × E) studies have mainly concentrated on adverse environmental factors and associated negative outcomes, somewhat neglecting positive environments and outcomes. The present study examined the interactions of cumulative genetic scores (CGS, dopamine receptor D2 TaqIA and oxytocin receptor gene rs53576 polymorphisms) with both positive and negative parenting on parent-adolescent cohesion and conflict. Furthermore, this study aimed to ascertain with which gene-environment model the potential G × E interactions would align. A total of 745 Chinese Han adolescents (Mage = 13.36 ± 0.96 years; 46.8% girls) from grades 7 to 9 participated in this study. Results revealed a significant effect of CGS and negative maternal parenting on mother-adolescent conflict among males, consistent with the weak differential susceptibility model. As CGS increased, the effects of negative maternal parenting on mother-son conflict were magnified. These findings have implications for the timing and focus of interventions aimed at improving parent-adolescent relationships. [ABSTRACT FROM AUTHOR]

There is a negative association between intelligence and psychopathology. We analyzed data on intelligence and psychopathology to assess this association in seven-year-old Dutch twin pairs (ranging from 616 to 14,150 depending on the phenotype) and estimated the degree to which genetic and environmental factors common to intelligence and psychopathology explain the association. Secondly, we examined whether genetic and environmental effects on psychopathology are moderated by intelligence. We found that intelligence, as assessed by psychometric IQ tests, correlated negatively with childhood psychopathology, as assessed by the DSM-oriented scales of the Child Behavior Check List (CBCL). The correlations ranged between −.09 and −.15 and were mainly explained by common genetic factors. Intelligence moderated genetic and environmental effects on anxiety and negative affect, but not those on ADHD, ODD, and autism. The heritability of anxiety and negative affect was greatest in individuals with below-average intelligence. We discuss mechanisms through which this effect could arise, and we end with some recommendations for future research. [ABSTRACT FROM AUTHOR]