Gene-environment Interactions Research Articles

Childhood trauma in bipolar affective disorder: A case control study

ABSTRACT Background: The etiology of Bipolar Affective Disorder (BPAD) is influenced by a variety of factors, possibly related to gene-environment interactions. Childhood trauma (CT) has been associated with an increased risk of developing BPAD. It also impacts the course of illness. The association of subcomponents of CT with BPAD and its various characteristics has not been studied in detail. Aim: This study was conducted to evaluate the association of CT with BPAD and compare it with age and sex-matched healthy controls. Materials and Methods: Fifty cases of BPAD diagnosed as per International Classification Diseases 10 (Diagnostic Criteria for Research) and 50 years age and sex-matched healthy control were studied. The required sample size was 38. Assessment of CT was done using the Childhood Trauma Questionnaire and statistical methods were applied. Results: Among all cases of BPAD, 38 (76%) cases had experienced moderate to severe CT as compared to 10 (20%) of controls. This was statistically significant. All subtypes of CT were significantly associated with BPAD as compared to healthy controls. Among subtypes, emotional abuse had the highest association with BPAD (odds ratio 7.37, confidence interval 1.98-27.31). Conclusion: CT is significantly associated with BPAD. All subtypes of CT are associated with BPAD and among them, emotional abuse appeared to exert the biggest impact. A multicentric study with larger sample sizes will further substantiate this finding regarding subtypes.

Deciphering genotype-by-environment interaction in new soybean lines based on multiple traits using different adaptability and stability methods.

The multi-environmental trials aid breeders in selecting the best genotypes for specific or general adaptability to different environments before commercial release. This study aimed to assess the stability of 13 new soybean pure lines, along with two controls, in terms of seed yield and important agronomic traits. The assessment was based on a completely randomized block design with three replications across four areas during 2020-2022. Various adaptability methods, including parametric, AMMI, GGE biplot, PCA, and SIIG were employed. The mixed analysis showed that the effects of environment, genotype, and genotype-environment (GE) interaction were significant for most studied traits. The AMMI showed the highest portion of environment (65.89%) in soybean seed yield. Based on all stability parameters, lines 2 and 5 were selected for their average seed yields of 3349 and 3142 kg ha-1, respectively. Additionally, lines 6 and 5 showed the most stability, yielding higher than the average, which were 2992 and 3142 kg ha-1, respectively, according to GGE biplot results. Furthermore, lines 2, 5, and 8 were identified as the ideal genotypes concerning seed yield and other agronomic traits, with high SIIG parameters and yields exceeding the average. Finally, the soybean line 5 was deemed the most suitable due to its higher yield, stability, and early maturity (128-day growth period). Therefore, line 5 is considered appropriate for its high stability and earliness in various regions of Iran.

A retrospective analysis of historical data of multi‐environment trials for dry bean (Phaseolus vulgaris L.) in Michigan

AbstractPlant breeding programs use multi‐environment trials (METs) to test multiple genotypes with the aim of selecting superior lines and increasing genetic gain. However, METs can be affected by the genotype × environment interactions (GEI) which hinders the ability to identify stable and high‐yielding dry bean varieties. This study investigates the impact of GEI on grain yield (GY) in three dry bean market classes across multiple environments in Michigan. The goal is to identify genotypes with superior performance under GEI effects and describe the genetic correlation between locations and other agronomic traits. Furthermore, we evaluate genetic yield trends on three major dry bean market classes in Michigan. Using linear mixed models, stability analysis, and a multi‐trait index, this study accounted for the effects of the environment on genotype performance to improve the prediction of GY. Our results highlight the importance of considering GEI in dry bean breeding programs to enhance the selection accuracy of GY. The genotype by environment interaction biplot analysis and the GEI model aided in identifying and classifying mega‐environments, leading to specific strategies for testing commercial bean classes across target production environments. Multiple‐trait performance selection showed positive results, although limited gains were observed for early maturing genotypes. Finally, the analysis of genetic trends reveals a positive trend in yield for black beans, while navy beans and small red beans show a slight decrease which can be attributed to unfavorable growing conditions and lack of genetic diversity in these market classes.

Monitoring Drought Tolerance Mechanisms of Sorghum and Maize Under Unevenly Distributed Precipitation

The study examines the morpho-physiological differences in leaf characteristics between two species of C4 plants: sorghum and maize. The research was conducted in field conditions where plants were rainfed. Both species different varieties were cultivated at two distinct sites that exhibited variations in soil texture and drought stress incidence according to the vegetation condition index (VCI). Samples were collected during various growth stages to analyze the relative water content (RWC), proline levels, and stomatal density. Sorghum plants displayed higher RWC, proline levels, and stomatal density than maize plants. In sorghum, the biochemical traits, such as the proline content, may play a more critical role in withstanding water-limited conditions than in maize in our experiment. Under the same water restriction period, sorghum showed higher RWC levels. Sorghum plants reduced stomatal density under more water-limited conditions, which proves its plasticity. Additionally, early maturation played a crucial role in both species. The early sorghum variety KWS Kallisto and maize variety Walterinio KWS had a more stable yield at both sites. Nevertheless, the highest yields were found in the later varieties, KWS Hannibal and KWS Inteligens. The higher proline levels and the relative water content are drought-tolerant mechanisms and may be used to indicate drought intensity in field conditions. Our findings spotlight the influence of genetic diversity and genotype-environment interactions in determining crop responses to drought stress, providing valuable information for future breeding programs to enhance drought tolerance in crops.

Gene–environment interactions: Epstein–Barr virus infection and risk of pediatric-onset multiple sclerosis

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 mother’s 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 < 0.001). There was evidence for additive interaction between childhood EBV infection and the presence of the HLA-DRB1*15 allele (RERI = 10.25, 95% confidence interval (CI) = 3.78 to 16.72; AP = 0.61, 95% CI = 0.47 to 0.75). There was evidence for multiplicative interaction (p < 0.05) between childhood EBV infection and the presence of DRB1*15 alleles (odds ratio (OR) = 3.43, 95% CI = 1.06 to 11.07). Among the pediatric MS variants also associated with EBV infection, we detected evidence for additive interaction (p = 0.02) between prior EBV infection and the presence of the GG genotype in risk variant (rs2255214) within CD86 (AP = 0.30, 95% CI = 0.03 to 0.58). Conclusion: We report evidence for interactions between childhood EBV infection and DRB1*15 and the GG genotype of CD86 POMS risk variant. Our results suggest an important role of antigen-presenting cells (APCs) in EBV-associated POMS risk.

Characterization of caffeine response regulatory variants in vascular endothelial cells.

Genetic variants in gene regulatory sequences can modify gene expression and mediate the molecular response to environmental stimuli. In addition, genotype-environment interactions (GxE) contribute to complex traits such as cardiovascular disease. Caffeine is the most widely consumed stimulant and is known to produce a vascular response. To investigate GxE for caffeine, we treated vascular endothelial cells with caffeine and used a massively parallel reporter assay to measure allelic effects on gene regulation for over 43,000 genetic variants. We identified 665 variants with allelic effects on gene regulation and 6 variants that regulate the gene expression response to caffeine (GxE, false discovery rate [FDR] < 5%). When overlapping our GxE results with expression quantitative trait loci colocalized with coronary artery disease and hypertension, we dissected their regulatory mechanisms and showed a modulatory role for caffeine. Our results demonstrate that massively parallel reporter assay is a powerful approach to identify and molecularly characterize GxE in the specific context of caffeine consumption.

A Kpna1-deficient psychotropic drug-induced schizophrenia model mouse for studying gene–environment interactions

KPNA1 is a mediator of nucleocytoplasmic transport that is abundantly expressed in the mammalian brain and regulates neuronal differentiation and synaptic function. De novo mutations in Kpna1 have been identified using genome-wide association studies in humans with schizophrenia; however, it remains unclear how KPNA1 contributes to schizophrenia pathogenesis. Recent studies have suggested a complex combination of genetic and environmental factors that are closely related to psychiatric disorders. Here, we found that subchronic administration of phencyclidine, a psychotropic drug, induced vulnerability and behavioral abnormalities consistent with the symptoms of schizophrenia in Kpna1-deficient mice. Microarray assessment revealed that the expression levels of dopamine d1/d2 receptors, an RNA editing enzyme, and a cytoplasmic dynein component were significantly altered in the nucleus accumbens brain region in a gene-environment (G × E) interaction-dependent manner. Our findings demonstrate that Kpna1-deficient mice may be useful as a G × E interaction mouse model for psychiatric disorders and for further investigation into the pathogenesis of such diseases and disorders.

How socio-political change is associated with the number of individually reported negative life events: a population-based study using the German reunification 1989/1990 as an example

BackgroundSocio-political change often leads to disruptions in employment and social networks, which can exacerbate health issues and increase mortality rates. These consequences are likely observed as an increase in negative...

Genotype × environment interactions of organic winter naked barley for agronomic, disease, and grain quality traits

AbstractThe modeling of genotype × environment interactions (GEI) is important to understand how new crops perform in different environments and management systems. Naked barley (Hordeum vulgare L.) is a type of barley where the hull threshes freely from the grain and can be used for multiple end uses, including food, malt, and animal feed. We examined the performance of a winter naked barley trial grown in organic conditions across three regions and 3 years in northern latitude regions of the United States. We recorded yield, test weight, heading date, plant height, threshability, winter survival, barley stripe rust (Puccinia striiformis f. sp. hordei Westend), barley scald (Rhynchosporium commune Zaffarano, McDonald and Linde sp. nov), and spot blotch (Cochliobolus sativus, anamorph Bipolaris sorokiniana (S. Ito &amp; Kurib.). Barley stripe rust, plant height, heading date, preharvest sprouting, and threshability had high heritability and low GEI. Grain yield, test weight, scald, and winter survival had high GEI and were analyzed using the additive main effect and multiplicative interaction (AMMI) model, genotype plus GEI biplot (GGE), and Finlay–Wilkinson (FW) stability analysis. The environmental patterns explained by the AMMI and GGE models indicated that selection for high GEI traits should occur within target environments and across multiple years within the target environments. Environmental groups were separated by Oregon as the first group and Wisconsin and New York as the second group.

Gut Microbiome and Cancer: From Cancer Development to Therapeutics with a Special Focus on Hepatocellular Carcinoma.

The body of a human has a vast array of microorganisms termed the microbiome that impacts almost every function of the body. Gene-environment interactions play a major role in making us susceptible to cancer and the microbiome is such an environmental factor that we are exposed to from the very beginning of our lives to the very end. Increasing pieces of evidence are pointing towards an association of cancer and the microbiome. The bacteria inside our body might help us prevent some cancers as well as may increase the risk of carcinogenesis and treatment responses. Many studies are suggesting that tinkering with the microbiome might be a new way to treat and prevent many kinds of cancer. Although information on the roles of the microbiome in carcinogenesis is scant and almost no direct links have been found between these two yet. This review offers some of the recent evidences of the association between cancer and the microbiome, discuss the impact of gut bacteria on cancer and provide a detailed discussion on gut microbiota mediated therapeutic approaches with a special focus on Hepatocellular Carcinoma. The implementation of the new knowledge discovered in this subject calls for a great deal of research.

AMMI and GGE biplot analysis of genotype by environment interaction for yield and yield contributing traits in confectionery groundnut

The global market has a high demand for premium edible grade groundnut, particularly for table use. India, in particular, exhibits significant potential for exporting confectionary grade large seeded groundnut. The environment plays a significant impact in influencing the expression of seed traits, which subsequently affects the confectionary quality of groundnut genotypes. The states of Gujarat and Rajasthan in India are prominent producers of high-quality groundnuts specifically used for confectionary purposes. The current study was conducted with 43 confectionery groundnut genotypes at Junagadh, Gujarat, and Bikaner, Rajasthan, with the goals of understanding genotype-by-environment interaction (GEI) effects and identifying stable, high yielding confectionery quality groundnut genotypes using AMMI and GGE biplot models. Pod yield per plant (PYP), number of pods per plant (NPP), hundred kernel weight (HKW), and shelling percent (SP) were estimated. The interplay between the environment and genotype has had a notable impact on the manifestation of confectionary grade characteristics in peanuts. The results from the Interaction Principal Component Analysis (IPCA) indicate that HKW contributed 76.68% and 18.95% towards the Global Environmental Index (GEI) through IPCA1 and IPCA2, respectively. Similarly, NPP contributed 87.52% and 8.65%, PYP contributed 95.87% and 2.1%, and SP contributed 77.4% and 16.22% towards GEI through IPCA1 and IPCA2, respectively. Based on the ranking of genotypes, the ideal genotypes were PBS 29079B for HKW, PBS 29230 for NPP. The genotypes PBS 29233 and PBS 29230 exhibited superior performance and stability in terms of pod yield, hundred kernel weight, number of pods per plant, and shelling percentage across various sites. These breeding lines have the potential to be developed for the purpose of producing confectionary grade groundnut with larger seeds, in order to fulfil the growing demand for export.

Mitigating type 1 error inflation and power loss in GxE PRS: Genotype-environment interaction in polygenic risk score models.

The use of polygenic risk score (PRS) models has transformed the field of genetics by enabling the prediction of complex traits and diseases based on an individual's genetic profile. However, the impact of genotype-environment interaction (GxE) on the performance and applicability of PRS models remains a crucial aspect to be explored. Currently, existing genotype-environment interaction polygenic risk score (GxE PRS) models are often inappropriately used, which can result in inflated type 1 error rates and compromised results. In this study, we propose novel GxE PRS models that jointly incorporate additive and interaction genetic effects although also including an additional quadratic term for nongenetic covariates, enhancing their robustness against model misspecification. Through extensive simulations, we demonstrate that our proposed models outperform existing models in terms of controlling type 1 error rates and enhancing statistical power. Furthermore, we apply the proposed models to real data, and report significant GxE effects. Specifically, we highlight the impact of our models on both quantitative and binary traits. For quantitative traits, we uncover the GxE modulation of genetic effects on body mass index by alcohol intake frequency. In the case of binary traits, we identify the GxE modulation of genetic effects on hypertension by waist-to-hip ratio. These findings underscore the importance of employing a robust model that effectively controls type 1 error rates, thus preventing the occurrence of spurious GxE signals. To facilitate the implementation of our approach, we have developed an innovative R software package called GxEprs, specifically designed to detect and estimate GxE effects. Overall, our study highlights the importance of accurate GxE modeling and its implications for genetic risk prediction, although providing a practical tool to support further research in this area.

Lack of Association between TP73 G4C14-A4T14 Polymorphism and Cervical Cancer Risk in Overall and Asian Women: A Meta-Analysis.

Growing studies revealed the association between polymorphisms in Tumor Protein TP73 (TP73) and susceptibility to cancer, especially with gynecological cancers. but, the results remained inconsistent. This meta-analysis was carried out to examine the relationship of the TP73 G4C14-to-A4T14 polymorphism (hereafter, G4C14-to-A4T14) with susceptibility to cervical cancer globally and by ethnicity. Eligible studies were collected by retrieving PubMed, Scopus, Web of Science, Embase, Wan Fang, and CNKI published before 25 October, 2023. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of such association. A total of 10 case-control studies with 1804 cervical cancer cases and 2433 healthy controls were included to this study. The pooled results showed that TP73 G4C14-to-A4T14 polymorphism was not associated with cervical cancer risk in overall. in terms of stratified analyses by ethnicity, this polymorphism was not associated with risk of cervical cancer among East-Asian women. however, there was a significant association based source of control among hospital-based studies. Inconsistent with previous meta-analyses, our pooled results revealed that TP73 G4C14-to-A4T14 polymorphism might not be a risk factor for development of cervical cancer globally and among East-Asian women. Moreover, further studies examining the effect of gene-gene and gene-environment interactions may eventually provide a better knowledge.

SLC6A4 gene variants moderate associations between childhood food insecurity and adolescent mental health.

Food insecurity is a persistent concern in the United States and has been shown to affect child mental health and behavior. The SLC6A4 gene has been indicated as a moderator of the effects of chronic stress on anxiety in adolescents aged 14-21. However, it is unclear if SLC6A4 may also play a role in the effects of childhood food insecurity, a form of chronic stress, on adolescent mental health. This study aimed to identify effects of food insecurity on adolescents' mental health and delinquent behavior when both mom and child go hungry in the child's early years, and the potential interaction with SLC6A4 variants (SS/LL). The data and sample for this research are from the Future of Families and Child Wellbeing Study. The cohort consists of 4898 children (age 1-15 years, male=47%, African American=50%) and their respective caregivers sampled from large cities in the United States from 1998 to 2000. The SLC6A4 serotonin transporter short/short allele emerged statistically significant as a moderator of childhood food insecurity and adolescent mental health. Specifically, the presence of the short/short allele increased anxiety symptoms in adolescents with exposure to food insecurity in childhood. The SLC6A4 short/short allele amplifies risk of anxiety-related mental illness when children experience food insecurity. The gene-environment interaction provides insight into the mechanistic pathway of the effects of poverty-related adversity, such as food insecurity, on developmental trajectories of mental health.

Wonder symphony: epigenetics and the enchantment of the arts.

Epigenetics, the study of heritable changes in gene expression without altering the DNA sequence, has gained significant attention due to its implications for gene regulation and chromatin stability. Epigenetic mechanisms play a fundamental role in gene-environment interactions, shaping individual development and adaptation. DNA methylation, histone modifications, and non-coding RNAs are key epigenetic regulators. Epigenetic changes can be triggered by environmental factors, including stress, toxins, and social interactions, influencing health and well-being. Positive experiences, such as engagement with the arts, have been linked to emotional responses and neurotransmitter release. While the impacts of detrimental factors on epigenetics have been widely studied, the effects of positive influences are less explored. Specifically, visual art and music have profound effects on emotions, cognition, and mood regulation. Exposure to arts enhances memory, reduces stress, and fosters social inclusion. Recent research has begun to explore the links between positive experiences and epigenetic modifications, suggesting that aesthetic experiences, including visual art and music fruition, might induce dynamic and/or stable changes in gene expression profiles. However, this field is in its infancy, and more research is needed to establish clear connections. Collaborative efforts among genetics, epigenetics, neuroscience, psychology, and the arts are essential for a comprehensive understanding. Longitudinal studies tracking sustained exposure to positive experiences and examining the influence of childhood artistic education on the biological bases of therapeutic effects of art and music are promising avenues for future research. Ultimately, understanding how positive experiences influence epigenetics could provide insights into the long-term enhancement of human well-being.

Stability analysis and genotype X environment interaction of cotton seed and fiber yield of some cotton (Gossypium hirsutum L.) genotypes in multi-environment in Mali

Cotton is a strategically important crop for Mali. Mainly used for export, it represents 50–60 % of the value of the country's exports. Genotype by environment interaction study was carried out to identify the most stable cotton genotype(s) and the most desirable for seed cotton yield and lint yield in 35 villages across six different environments(High Valley of the Niger, New Cotton Growing Zone, North Sudan-Sahel, Old Basin, Southern Extension Zone and Zone Sikasso-Bougouni) in a dispersed block design. Where each village represented a block, giving a total of 35 blocks or replications. A combined analysis of variance showed that yields of seed cotton and fiber were significantly affected by environments (p&lt;0.05), but did not reveal any significant difference between genotypes or genotype-environment interactions. The result of GGE biplot analysis method showed that the polygonal view identified three mega-environments (ME1, ME2 and ME3) with three winning genotypes: BRS 293, NTA B149 and NTA L66, respectively, for seed cotton yield. For fiber yield, the winning genotypes were CG1, NTA L65 and BRS 293, respectively. Given that all the varieties tested have a mean fiber yield within the recommended norms, the two promising varieties NTA B149 and NTA L66 with good seed cotton yields and the standard check BRS 293 can be recommended for extension in the environments to which they have been assigned.

Bisphenol F affects neurodevelopmental gene expression, mushroom body development, and behavior in Drosophila melanogaster

Bisphenol F (BPF) is a potential neurotoxicant used as a replacement for bisphenol A (BPA) in polycarbonate plastics and epoxy resins. We investigated the neurodevelopmental impacts of BPF exposure using Drosophila melanogaster as a model. Our transcriptomic analysis indicated that developmental exposure to BPF caused the downregulation of neurodevelopmentally relevant genes, including those associated with synapse formation and neuronal projection. To investigate the functional outcome of BPF exposure, we evaluated neurodevelopmental impacts across two genetic strains of Drosophila— w1118 (control) and the Fragile X Syndrome (FXS) model—by examining both behavioral and neuronal phenotypes. We found that BPF exposure in w1118 Drosophila caused hypoactive larval locomotor activity, decreased time spent grooming by adults, reduced courtship activity, and increased the severity but not frequency of β-lobe midline crossing defects by axons in the mushroom body. In contrast, although BPF reduced peristaltic contractions in FXS larvae, it had no impact on other larval locomotor phenotypes, grooming activity, or courtship activity. Strikingly, BPF exposure reduced both the severity and frequency of β-lobe midline crossing defects in the mushroom body of FXS flies, a phenotype previously observed in FXS flies exposed to BPA. This data indicates that BPF can affect neurodevelopment and its impacts vary depending on genetic background. Further, BPF may elicit a gene-environment interaction with Drosophila fragile X messenger ribonucleoprotein 1 (dFmr1)—the ortholog of human FMR1, which causes fragile X syndrome and is the most common monogenetic cause of intellectual disability and autism spectrum disorder.

Exploring the genotype-environment interaction of bread wheat in ambient and high-temperature planting conditions: a rigorous investigation

The current study is carried out to find out the stable wheat genotype in ambient and high temperature planting conditions. The objective was to estimate the genotype x environment interactions through various univariates and multivariate techniques. Twenty wheat genotypes were evaluated at Jabalpur, Narmadapuram, and Sagar districts of Madhya Pradesh, India, across cropping years 2019–20 and 2021–21, considering both timely and late planting conditions. The univariate and multivariate stability analysis were performed based on per-plant grain yield and grain filling rate. Our result revealed that environment, genotype, and GEI effects were significant (P < 0.001) across all the environments. The wheat genotypes JW3288, L8, and L13 have been discerned as top performers, exhibiting remarkable stability in grain yield per plant. Similarly, for grain filling rate, genotypes L11 and L13 have emerged as superior and consistently stable performers. Notably, the AMMI and GGE models demonstrated superior effectiveness and accuracy compared to the linear regression model. In conclusion, based on thorough univariate and multivariate stability analyses, L13 emerges as the most stable genotype across all environments under both planting conditions. Consequently, L13 holds promise for inclusion in future breeding programs. It's noteworthy that Jabalpur stands out as the most discriminating and representative environment among all the conditions assessed.

Evaluating breeding for broad versus narrow adaptation for cassava in Nigeria using stochastic simulation

AbstractThe cassava (Manihot esculenta Crantz) breeding program at the International Institute of Tropical Agriculture (IITA) has adopted genomic selection to accelerate genetic gain. The program continues to develop varieties broadly adapted across Nigeria's diverse agroclimatic zones. However, for this purpose, genotype‐by‐environment interaction (GEI) presents a challenge. To decide whether broad adaptation breeding is a good strategy, we evaluated broad versus narrow adaptation strategies using stochastic simulation, assessing genetic gain, genetic variance, heritability, and selection accuracy at 0 versus realistic levels of GEI variance. To parameterize the models, we analyzed historical data from four phenotypic evaluation stages of the IITA breeding program to estimate genetic and error variances, and genetic correlations across environments. Based on these observed parameters, the genomic‐enabled breeding programs exhibited higher genetic gain than the conventional program for both GEI variances. At realistic GEI variance, the narrow adaptation program showed higher genetic gain than the broad adaptation program. Across all programs, the genetic variance declined over time, though the genomic‐enabled programs showed higher initial variance due to the selection of parents at earlier stages. At realistic GEI variance, an increase in genetic variance was observed in the narrow adaptation program due to its conversion of GEI between mega‐environments into main genetic variance within mega‐environments. This higher genetic variance led to higher heritabilities and selection accuracies. This study highlights the potential of genomic selection in accelerating genetic gain and suggests that dividing the IITA cassava breeding program to target more than one mega‐environment should be considered.

Gene-environment interaction in the pathophysiology of type 1 diabetes.

Type 1 diabetes (T1D) is a complex metabolic autoimmune disorder that affects millions of individuals worldwide and often leads to significant comorbidities. However, the precise trigger of autoimmunity and disease onset remain incompletely elucidated. This integrative perspective article synthesizes the cumulative role of gene-environment interaction in the pathophysiology of T1D. Genetics plays a significant role in T1D susceptibility, particularly at the major histocompatibility complex (MHC) locus and cathepsin H (CTSH) locus. In addition to genetics, environmental factors such as viral infections, pesticide exposure, and changes in the gut microbiome have been associated with the development of T1D. Alterations in the gut microbiome impact mucosal integrity and immune tolerance, increasing gut permeability through molecular mimicry and modulation of the gut immune system, thereby increasing the risk of T1D potentially through the induction of autoimmunity. HLA class II haplotypes with known effects on T1D incidence may directly correlate to changes in the gut microbiome, but precisely how the genes influence changes in the gut microbiome, and how these changes provoke T1D, requires further investigations. These gene-environment interactions are hypothesized to increase susceptibility to T1D through epigenetic changes such as DNA methylation and histone modification, which in turn modify gene expression. There is a need to determine the efficacy of new interventions that target these epigenetic modifications such as "epidrugs", which will provide novel avenues for the effective management of T1D leading to improved quality of life of affected individuals and their families/caregivers.