Gene-environment Interactions Research Articles

GENOTYPE-ENVIRONMENT INTERACTION ON THE SEED QUALITY OF MAIZE HYBRID PROGENITORS (Zea mays L.)

The environmental conditions at the multiplication site have an impact on seed quality. Parents capable of counteracting changes in production environments are required to maintain and conserve the excellent attributes of maize (Zea mays L.) seed. This study sought to determine the effects of genotype and environment on the physical and physiological traits of single crosses and inbred lines, which are the progenitors of trilineal maize hybrids adapted to the High Valleys of Mexico. During the spring-summer 2014 and 2015 cycles, nine inbred lines, three single crosses, and three hybrids were evaluated in Coatlinchán, Celaya, and San Luis de la Paz, Mexico, in a randomized complete block design with three replications. The hectoliter and thousand-seeds weight, commercial seed percentage, standard germination, and after-cold test were evaluated. A pooled analysis of variance and multiple comparison of means with Tukey (p ≤ 0.05) were performed. The site regression model (SREG) was used to account for the genotype-environment interaction. The best environments for physical quality were San Luis de la Paz 2014; for a thousand-seeds weight (295.3 g), Coatlinchán 2015; for hectoliter weight (74.7 kg hL-1), Coatlinchán 2014; and for commercial seed percentage (76 and 73.3 %), San Luis de la Paz 2014. With the exception of Celaya 2014, the environments were statistically equal for physiological quality in standard germination, and San Luis de la Paz 2015 (82 %) was the best environment for germination after cold exposure. Regarding the genotype-environment interaction, parents M-47xM-46 and M-55xM-54 performed best for physical quality and M-43xM-44 for physiological quality at San Luis de la Paz; thus, seed production from these parents is possible in this location.

Effects on family functioning and the home environment of a family-based preventive intervention for children of parents with severe mental illness: A randomized controlled trial.

Children of parents with severe mental illness are at increased risk of mental illness throughout their lifespan due to complex gene-environment interactions. Preventive interventions supporting parents and children are warranted. Compared with usual treatment, we tested the effectiveness of a multidisciplinary family-based preventive intervention, VIA Family. We did a parallel randomized controlled superiority trial in Copenhagen, Denmark. A total of 95 families, of 95 parents with either schizophrenia spectrum disorder (n = 12 [12.6%]), bipolar disorder (n = 25 [26.3%]), or recurrent major depressive disorder (n = 58 [61.1%]), participated. A total of 179 coparents and 113 children (6-12 years) participated. Assessments took place at baseline and after 18 months of intervention. We estimated the effects on family functioning with the McMaster Family Assessment Device and on levels of stimulation and support in the home environment with the Home Observation Measurement of the Environment. Effects on family functioning did not differ between the two groups: parents with severe mental illness (0.11; 95% CI [-0.10, 0.31]), p = .296, and coparents (-0.07; 95% CI [-0.27, 0.13]), p = .482. Assessor-rated levels of stimulation and support in the home environment improved in VIA Family, but not significantly compared with usual treatment (Mdiff: 1.79; 95% CI [-0.37, 3.95], p = .104). Sensitivity analyses confirmed our main findings. Effects on family functioning and the home environment did not differ between VIA Family and usual treatment. We cannot rule out a clinically relevant effect of VIA Family on levels of stimulation and support in the home environment. Long-term follow-up will investigate potential preventive effects. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Association of long non-coding RNA genes (<i>H19</i>, <i>MEG3</i>, <i>MALAT1</i>, <i>Linc00305</i>, <i>Linc00261</i>, <i>Linc02227</i>, and <i>CDKN2B-AS1</i>) polymorphic loci with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a chronic lung disease resulting from dynamic, cumulative gene-environment interactions that cause lung tissue injury, alteration of its normal function and acceleration of cellular senescence. Long non-coding RNAs (lncRNAs) function as critical epigenetic regulators of various aspects of cellular senescence. The objective of the present study is to identify the association between polymorphic variants of H19 (rs3741219), MEG3 (rs7158663), MALAT1 (rs619586), LINC00305 (rs2850711), LINC00261 (rs6048205), CDKN2B-AS1 (rs4977574), and LINC02227 (rs2149954) lncRNAs genes with COPD. DNA samples from COPD patients (N = 703) and healthy individuals (N = 655) were studied in this study and polymorphic loci were analyzed by real–time PCR. Association with COPD was established with H19 (rs3741219), MEG3 (rs7158663), LINC02227 (rs2149954), MALAT1 (rs619586) and CDKN2B-AS1 (rs4977574). Polygenic analysis has allowed to identify informative gene-gene combinations that include polymorphic variants of the studied lncRNAs genes and genes encoding molecules of signaling cascades associated with cellular senescence and apoptosis. Multiple regression and ROC-analysis revealed a COPD risk predictive model, which included gene–gene combinations of lncRNAs genes and smoking index (P = 4.01 x 10-48, AUC = 0.87).

Post-Traumatic Stress Symptoms in Head and Neck Cancer Patients: The Impact of the COVID-19 Pandemic and Gene-Environment Interaction.

This study aimed to assess the occurrence of post-traumatic stress symptoms (PTSS) in head and neck cancer (HNC) patients. The goal also was to explore potential associations between PTSS, demographic factors, psychological variables, and specific genetic variants. This study included a total of 155 HNC patients, divided into pre-pandemic (n = 76) and COVID-19 pandemic (n = 79) groups. PTSS assessments were conducted using a standardized questionnaire. The assessment of adverse childhood experiences (ACEs) involved specific questionnaire items. Genetic variants were identified via RT-PCR. Statistical analysis employed linear multivariate regression, while mediation analysis examined gene-environment interactions. In the pre-pandemic, higher PTSS scores were found to be associated with younger age (p = 0.02) and a history of cumulative ACEs (p = 0.001). Mediation analysis revealed that ACEs had a direct impact on PTSS scores, with the FKBP5 CC genotype (rs1360780, C>T) mediating this association by 29%. In the pandemic, elevated PTSS scores were correlated with a history of depression (p = 0.001), the negative impact of the pandemic (p = 0.007), and undergoing palliative treatment (p = 0.02). Our findings provide insights into the psychosocial and genetic factors contributing to PTSS in HNC patients, considering the additional stressors introduced by the COVID-19 pandemic.

Integration of GWAS models and GS reveals the genetic architecture of ear shank in maize.

Maize is one of the most important crops for human food, animal feed, and industrial raw materials. Ear shank length (ESL) and ear shank node number (ESNN) are crucial selection criteria in maize breeding, impacting grain yield and dehydration rate during mechanical harvesting. To unravel the genetic basis of ESL and ESNN in maize, an association panel consisting of 379 multi-parent doubled-haploid (DH) lines was developed for genome-wide association studies (GWAS) and genomic selection (GS). The heritabilities of ESL and ESNN were 0.68 and 0.55, respectively, which were controlled by genetic factors and genotype-environment interaction factors. Using five different models for GWAS, 11 significant single nucleotide polymorphisms (SNPs) located on chromosomes 1, 2, and 4 were identified for ESL, with the phenotypic variation explained (PVE) value of each single SNP ranging from 4.91% to 21.35%, and 11 significant SNPs located on chromosomes 1, 2, 4, and 5 were identified for ESNN, with the PVE value of each SNP ranging from 1.22% to 18.42%. Genetic regions in bins 1.06, 2.06, and 2.08 were significantly enriched in SNPs associated with ear shank-related traits. The GS prediction accuracy using all markers by the five-fold cross-validation method for ESL and ESNN was 0.39 and 0.37, respectively, which was significantly improved by using only 500-1000 significant SNPs with the lowest P-values. The optimal training population size (TPS) and marker density (MD) for ear shank-related traits were 50%-60% and 3000, respectively. Our results provide new insights into the GS of ear shank-related traits.

Trends and the Role of Gene-Environment Interactions in Idiopathic Membranous Nephropathy in Northern China.

Idiopathic membranous nephropathy (iMN) has become one of the most prevalent primary glomerular diseases, with a marked increase in prevalence over the past two decades in northern China. Fine particulate matter (PM2.5) is considered to be associated with this rising prevalence. In this study, we aim to evaluate the trends of iMN in relation to improved air quality and conduct a cross-sectional study in Hebei province (northern China, near Beijing) to investigate the role of gene-environment interactions in its development. This study established two cohorts. Cohort 1 included 22,937 pathology reports from Peking University First Hospital (2002-2021) to assess iMN prevalence. Cohort 2 comprised 5,635 iMN patients from 11 cities in Hebei Province (2009-2013). DNA samples from 374 iMN patients and 1,259 controls were genotyped for SNPs rs4664608 (PLA2R1) and rs2187668 (HLA-DQA1). Patients were stratified by air pollution risk levels. The annual percentage change (APC) and average annual percentage change (AAPC) were estimated using a join-point regression model. Gene-environment interactions were analyzed using logistic regression and epinet-calculation. In Cohort 1, 5,586 patients with iMN were identified, representing 24.3% of the 22,937 patients from 2002 to 2021. The general population showed a significant increase in iMN proportion with an APC of +12.7% per year from 2002 to 2014 (95% CI: 10.3 to 17.5, p < 0.001), followed by a decline with an APC of -5.6% per year from 2014 to 2021 (95% CI: -9.6 to -2.6, p < 0.001).In Hebei Province, the iMN frequency rose significantly with an APC of +17.6% per year from 2002 to 2016 (95% CI: 14.5 to 28.6, p < 0.001), peaking at 60%, and then declined with an APC of -5.5% per year from 2016 to 2021 (95% CI: -13.1 to -1.2, p = 0.02). Cohort 2 highlighted significant regional variation in iMN incidence across Hebei Province. Geographic exposure to pollution was identified as an independent risk factor for iMN (RR 1.49, 95% CI 1.38-1.56, p<0.001). Gene-environment interaction analysis revealed that patients with risk alleles in the PLA2R1 gene and exposure to risk environments had a markedly increased risk of developing iMN (OR=38.72, 95% CI 11.95-125.46, p<0.01). The annual growth rate of iMN in northern China appears to be slowing down. Gene-environment interactions may have contributed to the previously observed increase in iMN prevalence.

Maize yields could benefit from increased vapor pressure deficit in hot managed environments

Abstract Recent studies highlight the adverse effects of increasing vapor pressure deficit (VPD) due to climate change on maize yields. Maize breeders are utilizing available genetic diversity to address these challenges. However, contrasting ecophysiological properties and genotype by environment interactions (GEI) often hinder these efforts. This study by the Agricultural Institute Osijek, in collaboration with Turkish company Tarım Kredi Tohumculuk, explores the adaptation of maize germplasm to hot, managed environments in Türkiye, originally bred for Southeast and Central European rainfed conditions. Over an 11-year period (2009–2019), multi-environment trials (MET) were conducted in two stages. In cycle 0 (C0), 22 hybrids were evaluated across 17 environments in Croatia and Türkiye. In cycle 1 (C1), MET was conducted in 18 Turkish environments. Complete linkage hierarchical clustering based on hybrid performance and climatic variables revealed two distinct clusters with positive or negative responses to increasing VPD in C0. In C1, genetic variances increased with rising VPD, maintaining distinct responses. Our findings align with reports on the limited transpiration trait in maize and sorghum, suggesting that while such traits can reduce water loss, they may also limit yield potential in high-VPD environments.

Adequate sleep duration accentuates the effect of glucagon-like peptide-1 receptor variant on HbA1c: A gene-environment interaction study

BackgroundBoth glucagon-like peptide-1 receptor (GLP1R) agonists and lifestyle modifications are widely adopted in managing glycemia. However, the joint effects of GLP1R agonists with lifestyle on glycemic traits have not been evaluated. MethodsThis gene-environment study tested the interaction between GLP1R-rs10305492 variant, consistent with the effect of GLP1R agonist therapies, and four lifestyle factors (diet, physical activity, sleep duration, and chronotype) for glucose and glycated hemoglobin (HbA1c) levels among 263,846 UK Biobank participants. Linear regression models were conducted to evaluate the effects of the rs10305492 and lifestyle factors on glucose and HbA1c levels. ResultsGLP1R-rs10305492-AA/AG genotype combined a healthy diet, regular physical activity, adequate sleep duration, or morning chronotype were associated with lower glucose and HbA1c levels (all P for trend < 0.001). A synergistic effect was found between rs10305492 and sleep duration on HbA1c, suggesting a recommended adequate sleep duration (7–8 h/day) may amplify the HbA1c lowering effect of GLP1R agonists. Joint effects of the rs10305492 and adequate sleep were associated with a 26 % reduced risk of hyperglycemia (>7.8 mmol/L) risk and a 22 % lower of high HbA1c (>39 mmol/mol or 5.7 %). ConclusionsCombining GLP1R agonists with adequate sleep may provide additional benefits for glycemic control in clinical practice.

An adaptive dynamical system model for development of schizophrenia: Epigenetics and false memories

This paper introduces a fifth-order adaptive dynamical system model represented as a self-modelling network model to understand the role of epigenetic factors in developing schizophrenia, particularly about the occurrence of false memories. Schizophrenia, affecting a significant portion of the global population, presents complex challenges due to its symptoms across cognitive, emotional, and social domains. Central to this paper is the exploration of epigenetic influences on the development of schizophrenia, with a focus on how these epigenetic factors contribute to the generation of false memories, a notable symptom of the disorder. The model assumes that early adverse experiences significantly affect hippocampal development, which is crucial for memory processes. By employing a fifth-order adaptive dynamical system model represented as a self-modelling network, this paper examines the intricate dynamics between genetic predispositions, environmental factors, and epigenetic modifications in schizophrenia. The model’s sophistication allows for a nuanced understanding of the gene-environment interactions, particularly highlighting the role of early-life trauma in shaping lifelong cognitive outcomes. This approach offers a comprehensive framework for analyzing the multifaceted nature of schizophrenia, contributing to a deeper understanding of its etiology and progression.

Adaptive capacity and ecological stability of some bean varieties in the conditions of the western forest-steppe of the Priobie region

Relevance. Crop productivity is determined by genotype, environmental effects and their interactions. Comprehensive evaluation of crop varieties based on their adaptability, plasticity and stability makes it possible to select the most promising varieties, high-yielding and adapted to many environmental conditions to improve productivity.Materials and Methods. Fourteen common bean varieties were tested in a randomized complete block design with three replications during two years (2022 and 2023) in the experimental field “Michurintsev Garden” of Novosibirsk State Agrarian University. Productivity traits were taken into account: number and weight of beans per plant, weight of 1000 seeds, yield. The purpose of the work was to evaluate bean samples for adaptive capacity and ecological stability in the conditions of the forest-steppe Priobie.Results. The article provides an assessment of the adaptability and stability of bean varieties in order to identify varieties with high productivity and adapted to climatic and farming conditions in the Siberian region. The results of the tests showed that the highest average net yields of Rubin, Krasnopestraya, Zolotistaya and Muhranula varieties were in the range of 0.41-0.64 kg/m2. Analysis of genotype-environment interaction (GxE) according to the mathematical model of Eberhart and Russel shows that varieties Rubin, Krasnopestraya, Zolotistaya and Muhranula have high indices of general adaptability and breeding value of genotype, Among them, varieties Rubin and Zolotistaya have stable productivity and high adaptability to environmental conditions.

Influence of Genetic Ancestry on Gene-Environment Interactions of Polygenic Risk and Sociocultural Factors: Results from the Hispanic Community Health Study/Study of Latinos.

Many present analyses of Hispanic/Latino populations in epidemiologic research aggregate all members of this ethnic group, despite immense diversity in genetic backgrounds, environment, and culture between and across Hispanic/Latino background groups. Using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we examined the role of self-identified background group and genetic ancestry proportions in gene-environment interactions influencing the relationship between body mass index (BMI) and a polygenic score for BMI (PGS BMI ). Weighted univariate and multivariable generalized linear models were executed to compare the effects of environmental variables identified a priori by McArdle et al. 2021. Both Amerindigenous (AME) ancestry proportion and background group identity were statistically modeled as confounders both through stratified and joint analyses to understand their influence on the relationship between BMI and PGS BMI , while incorporating gene-environment interactions of PGS x diet and PGS x age-at-immigration. After complex survey weighting, 7,075 participants remained in the analytic sample, representing individuals of six background groups: Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American. The distributions of key environmental and sociocultural variables were heterogeneous between Hispanic/Latino background groups. Associations of these variables with AME ancestry were similarly heterogeneous upon stratification, indicating confounding by background group. In a predictive model for BMI incorporating health, immigration, and environmental variables, PGS BMI performance decreased with increasing AME ancestry proportion. In this model, most statistically significant GxE interactions lost significance after ancestry and background stratification, except for PGS x age-at-immigration interactions in some strata: Mexican background individuals born in the US compared to those >=21 years old at migration (β=1.33, p<0.01), Dominican background individuals 6-12 years old at migration compared to those >=21 years old at migration (β=4.38, p<0.001), and Cuban background individuals 0-5 years old at migration compared to those >=21 years old at migration (β=2.20, p=0.015), where US-born includes individuals born in the US 50 states/DC. Controlling for self-identified background group identity and genetic ancestry did not eliminate statistically significant differences in interactions between AME ancestry and environmental variables in certain strata of AME ancestry among some Hispanic/Latino background groups in HCHS/SOL.

Unravelling Yield and Yield-Related Traits in Soybean Using GGE Biplot and Path Analysis

Soybean (Glycine max) is a vital crop for food, animal feed, and industrial products. However, its yield performance is significantly affected by genotype-by-environment interaction (GEI), which complicates the selection of high-yielding, stable varieties. This study aimed to evaluate the yield performance and stability of 12 elite soybean varieties across five major production areas in Uganda using GGE biplot and path analysis. The varieties were planted in a randomized complete block design with three replications over two consecutive seasons. Results revealed significant differences in grain yield among the varieties, locations, and their interactions (p &lt; 0.001). The highest-yielding varieties were Maksoy 5N (979 kg ha−1), Maksoy 4N (978 kg ha−1), Maksoy 3N (930 kg ha−1), and Signal (930 kg ha−1). GGE biplot analysis grouped the locations into two mega-environments, with the Maksoy varieties exhibiting greater yield stability compared to Seed Co. varieties. Path analysis showed that traits such as the number of lower internodes, central internode length, and filled pods had the highest positive direct effects on grain yield. This study provides insights into soybean breeding in tropical environments, highlighting traits that can be targeted to improve yield and stability. The findings offer a framework for breeding programs in Uganda and similar agro-ecological regions, promoting more resilient and productive soybean varieties. This study also illustrated the potential advantages of employing more complex mathematical techniques like path analysis to uncover yield and yield-related traits in soybean breeding programs.

Stability of anthocyanin, carotenoid and root yield of 10 sweet potato genotypes

ABSTRACT Sweet potato roots are rich in phytochemicals. The objective of this study was to evaluate the stability of number of storage roots, storage root dry weight, harvest index and anthocyanin and carotenoid contents of 10 sweet potato genotypes. Ten sweet potato genotypes were evaluated in a randomised complete block design with three replications at three locations in Surin province, including Rajamangala University of Technology Isan (RMUTI), Chomphra district and Sanom district during November 2022 to March 2023. Results indicated that the environment significantly influenced most traits, except for carotenoid content. Genotypes and genotype–environment interactions were significant for all traits. Number of storage roots was highest in genotypes found in RMUTI. Storage root yield and anthocyanin content was highest in genotypes found in Chomphra district, while harvest index and carotenoid content were highest in genotypes found in Sanom district. SR 2022/03 had the highest storage root yield across locations and in Chomphra district. KS 2022/07 had the highest harvest index and anthocyanin content across locations. SR 2022/10 had the highest anthocyanin content at RMUTI and also had the highest carotenoid content across locations. KS 2022/07 had the most stable storage root yield. SR 2022/01 had the most stable anthocyanin and carotenoid contents. Information on the levels and variability of phytochemicals in sweet potato enables breeders to select sweet potato genotypes with high and stable phytochemicals for sweet potato breeding.

КОМПЛЕКСНАЯ ОЦЕНКА ГЕНОТИПОВ LINUM USITATISSIMUM L. ПО ФЕНОТИПИЧЕСКИМ ПРИЗНАКАМ И СТАБИЛЬНОСТИ В УСЛОВИЯХ ПОДТАЕЖНОЙ АГРОЭКОЛОГИЧЕСКОЙ ЗОНЫ ТЮМЕНСКОЙ ОБЛАСТИ

The article presents the results of testing 12 hybrid combinations of fiber flax F3-F5 obtained based on interparietal crossings of four initial parental forms (Yarok, Grant, Alizee, Betertelsdorf 6884/60) for a set of morpho-biological parameters considering their ecological stability. Field research was carried out at the Biological Station of Tyumen State University "Lake Kuchak" (Nizhnetavdinsky District, Tyumen Region, 57°21' N, 66°04' E). Reliable differences (p&lt;0.05; p&lt;0.01) between them for all the studied traits were revealed. In the total phenotypic variability of the studied traits, the maximum influence of genotype-environment interactions (48.5%) was determined. A group of stable (bi=1.0, S2di=0, G1, G2, G3, G4, G5, G6, G8, G9), highly (bi&lt;1.0, S2di=0) and weakly responsive (bi&gt;1.0, S2di=0) hybrids was determined. Using the index (SI), the most stable of them in two groups were determined (SI=61.0-80.0% and 81.0-100.0%). According to the stability index (I), valuable flax genotypes were identified by plant height (G1, G2), number of capsules (G1, G2, G10), number of seeds in 1 capsule (G1, G8), and vegetation period (G1, G2, G8). Using the Kang rank criterion (RS), two groups by stability were identified, of which the first has the highest value for plant height (G1, G3, G5), inflorescence length (G1), number of capsules (G1, G6, G10, G11), number of seeds in 1 capsule (G8), fiber content (G1, G3, G5, G12), and vegetation period (G4). Hybrid combinations (G1, G2, G3, G5, G6, G7, G11) were selected, which are of the greatest practical interest for the selection process.

A dual-recognition precise nucleic acid probe based on tetrahedron and Cas12a reveals gene-environment interactions

Precise detection of gene expression is crucial for understanding the interactions between organisms and their environment. In this study, we developed a highly sensitive dual-recognition gene detection method based on the CRISPR-Cas12a system and DNA tetrahedron and validated its application in biological samples. By optimizing the Cas12a signal readout system, the method demonstrated excellent sensitivity and stability. Further experiments showed that the method could accurately detect the expression of the LKB1 gene, with good linearity observed in the concentration range of 10 pM to 10 nM, and a detection limit as low as 1 pM. Using an arsenic-induced mouse liver injury model, we validated the applicability in complex biological samples and found that this detection system outperformed traditional RT-qPCR in recognizing gene expression differences, offering higher sensitivity and specificity.

Cultivating sustainable futures: multi-environment evaluation and seed yield stability of faba bean (Vicia faba L.) genotypes by using different stability parameters in Ethiopia

Faba bean is an important legume crop with significant potential to contribute to sustainable agricultural systems and food security in Ethiopia. Despite its importance, the crop is prone to various biotic and abiotic constraints that can reduce seed yield and affect its stability and adaptability. To identify stable and adaptable genotypes, 10 faba bean genotypes were evaluated at three locations over two growing seasons using different stability parameters. Genotype-by-environment interaction (GGE biplot) and additive main effect and multiplicative interaction (AMMI) analyses are the statistical methods used to evaluate crop genotype performance across different environments to identify high-performing, stable, and adaptable genotypes and to highlight preferable environments for genotype differentiation. This study utilized cultivar superiority, regression coefficients, and deviations from regression parameters that provide valuable insights into genotype performance under varying environmental conditions. This approach helps to identify robust cultivars that can thrive across different agricultural settings and challenges, ultimately contributing to improved crop production and food security. The results revealed that G9, G8, and G7 are the three most stable and adaptable genotypes. These faba bean genotypes showed greater resilience to environmental changes and improved suitability for sustainable production, making them better options for local farmers. They also bolster resilience against climate variability and ultimately ensure agricultural sustainability. The AMMI model indicated that the genotype-environment interaction (GEI) significantly influences seed yield. These findings provide crucial insights into the genetic potential of faba bean genotypes that can help breeding programs to develop high-yielding, adaptable, and stable varieties for the region and other areas with similar agro-ecological conditions.

Genetic variation in &lt;i&gt;GSTP1&lt;/i&gt; and &lt;i&gt;TBXA2R&lt;/i&gt; genes: influence of Badoush cement factory pollutant

Industrial advancements, while driving economic growth, have simultaneously intensified environmental pollution levels, posing significant health risks to populations residing near industrial hubs. The release of a complex mixture of pollutants, including heavy metals, particulate matter, and volatile organic compounds, has been linked to a range of adverse health outcomes, including respiratory diseases, cardiovascular complications, and cancer. The Badoush Cement Factor in Mosul city, Nineveh, Iraq, a major industrial facility, exemplifies this challenge, emitting substantial quantities of air pollutants capable of long-range transport. This study, therefore, investigated the potential gene-environment interactions focusing on TBXA2R and GSTP1 genes and contributing to respiratory health disparities among 64 employees of the Badoush Cement Factory compared to 10 control subjects. Specifically, the study employed the tetra-primer amplification refractory mutation system-polymerase chain (ARMS-PCR) reaction technique to analyze the role of the TBXA2R gene, known for its involvement in bronchoconstriction and susceptibility to asthma, and the GSTP1 gene, encoding a crucial antioxidant enzyme protecting lung tissue from oxidative stress. By examining these genetic markers within the context of occupational exposure at the Badoush Cement Factory, this research aimed to elucidate the intricate interplay between genetic predisposition and environmental factors in determining respiratory health outcomes. The results indicated that there was no direct correlation between exposure to pollutants and genetic variation in the TBXA2R gene. However, prolonged exposure to pollutants may increase the risk of developing respiratory diseases. No significant association was found between pollutants emitted from the cement plant and genetic variation in the GSTP1 gene.

Cyclic and pseudo-cyclic electron pathways play antagonistic roles during nitrogen deficiency in Chlamydomonas reinhardtii.

Nitrogen (N) scarcity frequently constrains global biomass productivity. N deficiency halts cell division, downregulates photosynthetic electron transfer, and enhances carbon storage. However, the molecular mechanism downregulating photosynthesis during N deficiency and its relationship with carbon storage are not fully understood. Proton Gradient Regulator-like 1 (PGRL1) controlling cyclic electron flow (CEF) and Flavodiiron proteins (FLV) involved in pseudo-CEF (PCEF) are major players in the acclimation of photosynthesis. To determine the role of PGRL1 or FLV in photosynthesis under N deficiency, we measured photosynthetic electron transfer, oxygen gas exchange, and carbon storage in Chlamydomonas reinhardtii pgrl1 and flvB knockout mutants. Under N deficiency, pgrl1 maintained higher net photosynthesis and O2 photoreduction rates and higher levels of Cytochrome b6f and PSI compared to the control and flvB. The photosynthetic activity of flvB and pgrl1 flvB double mutants decreased in response to N deficiency, similar to the control strains. Furthermore, the preservation of photosynthetic activity in pgrl1 was accompanied by an increased accumulation of triacylglycerol in certain genetic backgrounds but not others, highlighting the importance of gene-environment interaction in determining traits such as oil content. Our results suggest that in the absence of PGRL1-controlled CEF, FLV-mediated PCEF maintains net photosynthesis at a high level and that CEF and PCEF play antagonistic roles during N deficiency. They further illustrate how a strain's nutrient status and genetic makeup can affect regulation of photosynthetic energy conversion in relation to carbon storage and provide additional strategies for improving lipid productivity in algae.

PNPLA3 I148M Interacts With Environmental Triggers to Cause Human Disease.

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.

Cross-ancestral GWAS identifies 29 novel variants across Head and Neck Cancer subsites.

In this multi-ancestry genome-wide association study (GWAS) and fine mapping study of head and neck squamous cell carcinoma (HNSCC) subsites, we analysed 19,073 cases and 38,857 controls and identified 29 independent novel loci. We provide robust evidence that a 3' UTR variant in TP53 (rs78378222, T>G) confers a 40% reduction in odds of developing overall HNSCC. We further examine the gene-environment relationship of BRCA2 and ADH1B variants demonstrating their effects act through both smoking and alcohol use. Through analyses focused on the human leukocyte antigen (HLA) region, we highlight that although human papilloma virus (HPV)(+) oropharyngeal cancer (OPC), HPV(-) OPC and oral cavity cancer (OC) all show GWAS signal at 6p21, each subsite has distinct associations at the variant, amino acid, and 4-digit allele level. We also defined the specific amino acid changes underlying the well-known DRB1*13:01-DQA1*01:03-DQB1*06:03 protective haplotype for HPV(+) OPC. We show greater heritability of HPV(+) OPC compared to other subsites, likely to be explained by HLA effects. These findings advance our understanding of the genetic architecture of head and neck squamous cell carcinoma, providing important insights into the role of genetic variation across ancestries, tumor subsites, and gene-environment interactions.