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.

Gene-environmental interactions create risk profiles for sporadic cancer development in patients with colorectal cancer (CRC). For instance, a person\'s 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.

The increased prevalence of metabolic diseases in the Arab countries is mainly associated with genetic susceptibility, lifestyle behaviours, such as physical inactivity, and an unhealthy diet. The objective of this review was to investigate and summarise the findings of the gene-lifestyle interaction studies on metabolic diseases such as obesity and type 2 diabetes in Arab populations. Relevant articles were retrieved from a literature search on PubMed, Web of Science, and Google Scholar starting at the earliest indexing date through to January 2024. Articles that reported an interaction between gene variants and diet or physical activity were included and excluded if no interaction was investigated or if they were conducted among a non-Arab population. In total, five articles were included in this review. To date, among three out of twenty-two Arab populations, fourteen interactions have been found between the FTO rs9939609, TCF7L2 rs7903146, MC4R rs17782313, and MTHFR rs1801133 polymorphisms and diet or physical activity on obesity and type 2 diabetes outcomes. The majority of the reported gene-diet/ gene-physical activity interactions (twelve) appeared only once in the review. Consequently, replication, comparisons, and generalisation of the findings are limited due to the sample size, study designs, dietary assessment tools, statistical analysis, and genetic heterogeneity of the studied sample.

This study aims to estimate the familial risks of pterygium and assess its relative contributions to environmental and genetic factors using the 2000-2017 Taiwan National Health Insurance Research Database. The marginal Cox\'s model and the polygenic liability model were made. In Taiwan, the prevalence rate of pterygium in 2017 was 1.64% for individuals with affected first-degree relatives, higher than the general population (1.34%). The adjusted relative risk (RR) for pterygium was highest for twins of the same sex (15.54), followed by siblings of the same sex (4.69), offsprings (3.39), siblings of the different sex (2.88), spouse (2.12), parents (1.86), twins of the different sex (1.57), respectively. The phenotypic variance of pterygium was 21.6% from additive genetic variance, 24.3% from common environmental factors shared by family members, and 54.1% from non-shared environmental factors, respectively. Sensitivity analysis by restricting those with surgical pterygium reveals that aRRs and the three components were similar to those of the overall pterygium. In summary, the prevalence rate of pterygium was higher for individuals with affected first-degree relatives than for the general population. The non-shared environmental factors account for half of the phenotypic variance of pterygium; genetic and shared environmental factors explain the rest.

Understanding the genotype-by-environment interaction (GEI) and considering it in the selection process is a sine qua non condition for the expansion of Brazilian eucalyptus silviculture. This study\'s objective is to select high-performance and stable eucalyptus clones based on a novel selection index that considers the Factor Analytic Selection Tools (FAST) and the clone\'s reliability. The investigation explores the nuances interplay of GEI and extends its insights by scrutinizing the relationship between latent factors and real environmental features. The analysis, conducted across seven trials in five Brazilian states involving 78 clones, employs FAST. The clonal selection was performed using an extended FAST index weighted by the clone\'s reliability. Further insights about GEI emerge from the integration of factor loadings with 25 environmental features through a principal component analysis. Ten clones, distinguished by high performance, stability, and reliability, have been selected across the target population of environments. The environmental features most closely associated with factor loadings, encompassing air temperature, radiation, and soil characteristics, emerge as pivotal drivers of GEI within this dataset. This study contributes insights to eucalyptus breeders, equipping them to enhance decision-making by harnessing a holistic understanding-from the genotypes under evaluation to the diverse environments anticipated in commercial plantations.

CONCLUSIONS: The simulation of genotype-by-environment interaction using multiplicative models provides a general and scalable framework to generate realistic multi-environment datasets and model plant breeding programmes. Plant breeding has been historically shaped by genotype-by-environment interaction (GEI). Despite its importance, however, many current simulations do not adequately capture the complexity of GEI inherent to plant breeding. The framework developed in this paper simulates GEI with desirable structure using multiplicative models. The framework can be used to simulate a hypothetical target population of environments (TPE), from which many different multi-environment trial (MET) datasets can be sampled. Measures of variance explained and expected accuracy are developed to tune the simulation of non-crossover and crossover GEI and quantify the MET-TPE alignment. The framework has been implemented within the R package FieldSimR, and is demonstrated here using two working examples supported by R code. The first example embeds the framework into a linear mixed model to generate MET datasets with low, moderate and high GEI, which are used to compare several popular statistical models applied to plant breeding. The prediction accuracy generally increases as the level of GEI decreases or the number of environments sampled in the MET increases. The second example integrates the framework into a breeding programme simulation to compare genomic and phenotypic selection strategies over time. Genomic selection outperforms phenotypic selection by ∼ 50-70% in the TPE, depending on the level of GEI. These examples demonstrate how the new framework can be used to generate realistic MET datasets and model plant breeding programmes that better reflect the complexity of real-world settings, making it a valuable tool for optimising a wide range of breeding methodologies.

UNASSIGNED: Genetic and environmental factors contribute to psoriasis, but the impact of residential environments on this condition remains uncertain. We aimed to investigate the association of residential environments with psoriasis risk and explore its interaction with genes.
UNASSIGNED: We retrieved data on the spatial distribution of residential environments at 300 and 1000 m buffer zones from the UK Biobank, including the proportions of natural environments, domestic gardens, green spaces, and blue spaces within these zones. We then used Cox hazard models to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between residential environments and psoriasis risk. Lastly, we constructed polygenic risk scores to determine genetic susceptibility and further analyse the interaction with residential environments.
UNASSIGNED: Overall, 3755 incident cases of psoriasis were documented during a median follow-up of 12.45 years. Compared with the lowest exposure quantile (Q1), Q4 exposure to natural environments (1000 m buffer: HR = 1.16, 95% CI = 1.05-1.29; 300 m buffer: HR = 1.12, 95% CI = 1.02-1.24) and green spaces (1000 m buffer: HR = 1.16, 95% CI = 1.04-1.28; 300m buffer: HR = 1.10, 95% CI = 1.00-1.21) increased the risk of psoriasis, while Q4 exposure to domestic gardens (1000 m buffer: HR = 0.85, 95% CI = 0.77-0.93; 300m buffer: HR = 0.91, 95% CI = 0.83-1.00) and Q3 exposure to blue spaces (1000 m buffer: HR = 0.89, 95% CI = 0.81-0.98) were negatively associated with psoriasis risk. Among participants with a high genetic risk, those exposed to high levels of natural environments (1000 m buffer: HR = 1.49, 95% CI = 1.15-1.93; 300 m buffer: HR = 1.39, 95% CI = 1.10-1.77) and green spaces (300 m buffer: HR = 1.30, 95% CI = 1.04-1.64) had a higher risk of psoriasis, while those exposed to blue spaces (1000 m buffer: HR = 0.78, 95% CI = 0.63-0.98) had a lower risk of psoriasis. We also observed joint effects of genetic risk and residential environments and an antagonistic additive interaction between blue spaces and genetic risk (P = 0.011).
UNASSIGNED: We observed that residing in natural environments and green areas increased the risk of psoriasis in our sample, while proximity to blue spaces and domestic gardens was associated to reduced risks. The association of residential environments with psoriasis risk was modified by genetic susceptibility.

BACKGROUND: Spina bifida is a type of neural tube defect (NTD); NTDs are developmental malformations of the spinal cord that result from failure of neural tube closure during embryogenesis and are likely caused by interactions between genetic and environmental factors. Arsenic induces NTDs in animal models, and studies demonstrate that mice with genetic defects related to folate metabolism are more susceptible to arsenic\'s effects. We sought to determine whether 25 single-nucleotide polymorphisms (SNPs) in genes involved in folate and arsenic metabolism modified the associations between maternal arsenic exposure and risk of spina bifida (a common NTD) among a hospital-based case-control study population in Bangladesh.
METHODS: We used data from 262 mothers and 220 infants who participated in a case‒control study at the National Institutes of Neurosciences & Hospital and Dhaka Shishu Hospital in Dhaka, Bangladesh. Neurosurgeons assessed infants using physical examinations, review of imaging, and we collected histories using questionnaires. We assessed arsenic from mothers\' toenails using inductively coupled plasma mass spectrometry (ICP-MS), and we genotyped participants using the Illumina Global Screening Array v1.0. We chose candidate genes and SNPs through a review of the literature. We assessed SNP-environment interactions using interaction terms and stratified models, and we assessed gene-environment interactions using interaction sequence/SNP-set kernel association tests (iSKAT).
RESULTS: The median toenail arsenic concentration was 0.42 μg/g (interquartile range [IQR]: 0.27-0.86) among mothers of cases and 0.47 μg/g (IQR: 0.30-0.97) among mothers of controls. We found an two SNPs in the infants\' AS3MT gene (rs11191454 and rs7085104) and one SNP in mothers\' DNMT1 gene (rs2228611) were associated with increased odds of spina bifida in the setting of high arsenic exposure (rs11191454, OR 3.01, 95% CI: 1.28-7.09; rs7085104, OR 2.33, 95% CI: 1.20-4.and rs2228611, OR 2.11, 95% CI: 1.11-4.01), along with significant SNP-arsenic interactions. iSKAT analyses revealed significant interactions between mothers\' toenail concentrations and infants\' AS3MT and MTR genes (p = 0.02), and mothers\' CBS gene (p = 0.05).
CONCLUSIONS: Our results support the hypothesis that arsenic increases spina bifida risk via interactions with folate and arsenic metabolic pathways and suggests that individuals in the population who have certain genetic polymorphisms in genes involved with arsenic and folate metabolism may be more susceptible than others to the arsenic teratogenicity.

BACKGROUND: In 2015, the World Health Organization (WHO) introduced the concept of intrinsic capacity (IC) to define healthy aging based on functional capacity. In this scoping review, we summarized available evidence on the development and validation of IC index scores, the association of IC with health-related factors, and its biological basis. The review specifically focused on identifying current research gaps, proposed strategies to leverage biobank datasets, and opportunities to study the genetic mechanisms and gene-environment interactions underlying IC.
METHODS: The literature search was conducted across six databases, including PubMed, CINAHL, Web of Science, Scopus, AgeLine, and PsycINFO, using keywords related to IC.
RESULTS: This review included 84 articles, and most of them (n=38) adopted the 5-domains approach to operationalize IC, utilizing correlated five factors or bifactor structures. Intrinsic capacity has consistently shown significant associations with socio-demographic and health-related outcomes, including age, sex, wealth index, nutrition, exercise, smoking, alcohol use, ADL, IADL, frailty, multimorbidity, and mortality. While studies on the biological basis of the composite IC are limited, with only one study finding a significant association with the ApoE gene variants, studies on specific IC domains - locomotor, vitality, cognitive, psychological, and sensory suggest a heritability of 20-85% of IC and several genetic variants associated with these subdomains have been identified. However, evidence on how genetic and environmental factors influence IC is still lacking, with no available study to date.
CONCLUSIONS: Our review found that there was inconsistency in the use of standardized IC measurement tools and indicators, but the IC indices had shown good construct and predictive validity. Research into the genetic and gene-to-environment interactions underlying IC is still lacking, which calls for the use of resources from large biobank datasets in the future.

OBJECTIVE: 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.