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Results for “gene-environment correlations”

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PubMed2026

Methods for modeling gene-environment interplay using polygenic risk scores.

Polygenic risk scores (PRS) are increasingly recognized as pivotal tools for quantifying disease risk through the aggregation of multiple genetic variants. As sample sizes in genome-wide association studies (GWAS) continue to expand and PRS become more powerful, they are set to play a key role in translational research and personalized medicine. Understanding the interplay of PRS with environmental factors is critical for interpreting and applying PRS in diverse contexts. This interplay manifests in two forms: PRS-by-environment interaction (PRS × E) and gene-environment correlation (rGE). However, despite the growing application and importance of PRS, there are limited guidelines for performing PRS × E interaction analyses while controlling for rGE, which can lead to inconsistencies across studies and misinterpretation of results. Here we provide a review of different methods for performing PRSxE interaction in various epidemiological study designs, propose recommendations for best-practice, and discuss future challenges.

Gene-Environment Interaction↗
PubMed2026

Genetic risk scores, perceived neighborhood disorder, and sleep duration.

STUDY OBJECTIVES: Most studies of neighborhood context and sleep health emphasize direct effects and fail to account for the role of genetics. In this paper, we draw on the socioecological model to examine the interplay of genetics, neighborhood context, and sleep health. We specifically examine the independent and joint effects of genetic risk scores (GRS) and perceived neighborhood disorder on sleep duration. METHODS: We combine genomic and cross-sectional survey data from the All of Us Research Program, a non-probability sample of 22 575 adults of European ancestry living in the United States. We use the sleep duration-increasing risk allele count for 78 genome-wide single nucleotide polymorphisms (SNPs) to construct weighted genetic risk scores. Our analyses include an index of perceived neighborhood disorder and an objective measure of sleep duration based on wrist actigraphy. RESULTS: Genetic risk scores are inversely associated with neighborhood disorder, positively associated with continuous sleep duration, and inversely associated with the odds of short sleep. Neighborhood disorder is inversely associated with continuous sleep duration and positively associated with the odds of short and long sleep. The association between genetic risk scores and sleep duration (continuous and categorical) is invariant across levels of neighborhood disorder. CONCLUSIONS: Our analyses confirm the independent direct effects of genetic risk scores and neighborhood disorder on sleep duration. Our findings extend the socioecological model by assessing the role of genetics in the study of neighborhood context and sleep health. Although we observed a gene-environment correlation between genetic risk scores and perceived neighborhood disorder, there was little indication of genetic confounding and no evidence of gene-environment interaction.

Humans↗
PubMed2026

Variance Polygenic Scores (vPGS) as a Tool for Studying Gene-Environment Interactions Associated With Refractive Error.

PURPOSE: Conventional polygenic scores predict an individual's phenotype based on their genetics. By contrast, variance polygenic scores (vPGS) quantify genetic predisposition to phenotypic variance. We tested the hypothesis that a vPGS for refractive error can identify individuals with increased susceptibility to environmental risk factors for myopia. METHODS: Six vPGS construction strategies were evaluated in UK Biobank participants: three variance heterogeneity genome-wide association study (vGWAS) methods and two reweighting schemes. vPGS performance was assessed using two metrics: (i) "Diff"-difference in phenotypic variance in vPGS decile ten versus one; (ii) Spearman correlation of phenotypic variance versus vPGS decile. The optimal vPGS was used to test for vPGS × time spent reading or vPGS × time spent outdoors interactions in children aged 15 years (ALSPAC cohort; n = 3471). RESULTS: Of the vGWAS methods, conditional quantile regression outperformed SCAMPI and Levene's Test. Of the re-weighting schemes, LDpred2 outperformed pruning and thresholding. In an independent sample of UK Biobank participants (n = 19,470), the top-performing vPGS successfully stratified individuals into groups with increasing variance in refractive error, even after adjusting for a conventional PGS (Diff: 2.55, 95% confidence interval [CI], 1.64-3.47; Spearman correlation = 0.87; 95% CI, 0.43-0.93). However, in ALSPAC participants, there was minimal support for vPGS interactions with time reading (P = 0.80) or time outdoors (P = 0.89). CONCLUSIONS: A novel vPGS successfully stratified individuals into groups with relatively high or low genetic susceptibility to refractive error variance. However, the vPGS could not identify individuals at enhanced risk from lifestyle risk factors for myopia.

Humans↗
PubMed2026

Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.

BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.

Humans↗
PubMed2026

Using high-dimensional environmental covariates to study genotype by environment interaction for reproductive traits in Duroc boars.

We investigated the potential of incorporating grid-cell-based environmental covariates (ECs) in the genetic evaluation of total sperm count (TSC), sperm motility (MOT), and sperm morphology (MOR) for Duroc boars. A total of 188,665 records derived from 3,684 genotyped boars, born between December 2018 and October 2024 and raised in three stud farms located in different U.S. states, were analyzed using multi-trait linear-threshold repeatability models. To account for genotype by environment interactions (GE), we constructed an interaction matrix as the Hadamard product of the genomic relationship matrix and an environmental (co)variance matrix. The environmental groups were defined in three ways: farm, farm-season, and farm-year-season. The (co)variance matrix was constructed based on daily ECs obtained from the NASA POWER database for each environmental group. Of all available ECs, those significantly associated with TSC, MOT, and MOR (temperature, relative humidity, atmospheric pressure, and wind speed and direction) were retained. We evaluated five models with different GE structures: M1 represented the baseline without accounting for GE, in M2 the GE included farm as environmental groups, in M3 the GE included farm-season as environmental groups, in M4 the GE included farm-year-season as environmental groups, and M5 involved M3 with an additional random effect of the farm-season. Estimates of heritability for TSC, MOT, and MOR ranged from 0.03 to 0.04, 0.05 to 0.08, and 0.04 to 0.08, respectively. Corresponding repeatability ranged from 0.15 to 0.23, 0.28 to 0.49, and 0.28 to 0.49. The proportion of phenotypic variance attributed to GE variance ranged from 0.00 to 0.32, 0.00 to 0.44, and 0.00 to 0.44. Lastly, estimates of genetic correlation, TSC-MOT, TSC-MOR, and MOT-MOR ranged from 0.27 to 0.31, 0.24 to 0.31, and 0.98 to 0.99, respectively, with minor differences across models. We assessed the predictive ability of models using the linear regression validation. Across traits and models, bias ranged from -0.05 to 0.02 standard deviations, slope varied from 0.88 to 0.99, the correlation ranged from 0.75 to 0.84, and accuracy from 0.41 to 0.53. Overall, building the GE matrix considering grid-cell-based ECs helped to account for GE, thereby reducing the proportion of phenotypic variance attributed to genetic components; however, it did not improve the validation metrics. Additional on-farm records for ECs may improve the model performance.

Animals↗
PubMed2026

Humanizing acidic mammalian chitinase variants establish lung immune conditioning and control environmentally driven inflammation and fibrosis.

Chitin, a widespread environmental particle constituent, triggers lung inflammation but is degraded by chitinases. In humans, single-nucleotide polymorphisms (SNPs) in CHIA (acidic mammalian chitinase; AMCase) are associated with lung disease, suggesting that chitinase variants influence responses to airborne particles. Here, we edit the mouse Chia1 locus to generate humanized (hChia) mice harboring common human SNPs. Compared with controls expressing disease-protective SNPs, hChia mice lack robust chitinase activity and fail to degrade natural chitin substrates. Lung-resident lymphocytes and macrophages are spontaneously primed and sensitive to inflammatory triggering by environmental chitin. Immune cell infiltration correlates with airway chitin following challenge, and hChia mice exhibit exacerbated inflammatory and fibrotic lung disease. In humans with acute respiratory failure, alveolar hemorrhage coincides with environmentally derived chitin particles that are susceptible to chitinase degradation, attenuating inflammatory cell responses. Thus, environmental chitin and chitinase activity are crucial determinants of lung immune conditioning with potential therapeutic applications.

AMCase↗
PubMed2025

Identification of a novel heterozygous GPD1 missense variant in a Chinese adult patient with recurrent HTG-AP consuming a high-fat diet and heavy smoking.

BACKGROUND: Glycerol-3-phosphate dehydrogenase 1 (GPD1) gene defect can cause hypertriglyceridemia (HTG), which usually occurs in infants. The gene defect has rarely been reported in adult HTG patients. In the present study, we described the clinical and functional analyses of a novel GPD1 missense variant in a Chinese adult patient with recurrent hypertriglyceridemia‑related acute pancreatitis (HTG-AP), consuming a high-fat diet and smoking heavily. METHODS: Exome sequencing was used to analyze the DNA of the adult patient's blood sample. It was found that there was a new variant of GPD1 gene-p.K327N, which was verified by gold standard-sanger sequencing method. In vitro, the corresponding plasmid was constructed and transfected into human renal HEK-293T cells, and GPD1 protein levels were detected. A biogenic analysis was performed to study the population frequency, conservation, and electric potential diagram of the new variant p.K327N. Finally, the previously reported GPD1 variants were sorted and their phenotypic relationships were compared. RESULTS: A novel heterozygous variant of GPD1, p.K327N (c.981G > C), was found in the proband. Furthermore, the patient's daughter carried this variant, whereas his wife did not carry the variant. The proband with obesity suffered eight episodes of HTG-AP from the age of 36 years, and each onset of AP was correlated to high-fat diet consumption and heavy smoking. In vitro, this variant exerted a relatively mild effect on GPD1 functions, which were associated with its effect upon secretion (~ 25% of secretion decreased compared with that of the wild-type); thus, eventually impairing protein synthesis. Additionally, 36 patients with GPD1 variants found in previous studies showed significant transient HTG in infancy. The proband carrying the GDP1 variant was the first reported adult with recurrent HTG-AP. CONCLUSION: We identified a novel GPD1 variant, p.K327N, in a Chinese adult male patient with recurrent HTG-AP. The variant probably exerted a mild effect on GPD1 functions. The heterozygosity of this GPD1 variant, in addition to high-fat diet consumption and heavy smoking, probably triggered HTG-AP in the patient.

Adult↗
PubMed2025

Haplotype stacking to improve stability of stripe rust resistance in wheat.

Genotype-by-environment interaction analysis and haplotype-level characterisation provide novel insights into the stability of stripe rust resistance. Breeding selection strategies are proposed to achieve rapid and stable genetic gains across environments. This study investigated stripe/yellow rust (YR) responses in the Vavilov wheat diversity panel evaluated across 11 field experiments conducted in Australia and Ethiopia during 2014-2021. Genotype-by-environment interaction (GEI) was analysed using a factor analytic (FA) model. Genotype-level selection was performed with overall performance (OP) and root-mean-square deviation (RMSD), which reflected average performance and stability of YR resistance across environments, respectively. Genomic estimated breeding values (GEBV) for these traits were calculated and compared with those from a multi-trait GBLUP model with average performance represented by the mean GEBV across environments and stability by the standard deviation of GEBV across environments. The FA-based and multi-trait GBLUP GEBV had high correlations. Haplotypes with large effects on OP and RMSD were identified using the local GEBV method. Favourable haplotypes were then used for stacking in breeding simulations, using the Vavilov collection as a base. Compared to truncation selection, optimal haplotype selection (OHS) using an artificial intelligence (AI)-based algorithm achieved longer-term genetic gains for both OP and RMSD (after many generations) by initially selecting founder parents that maximised favourable haplotypes. Simulations using YR responses from diverse environments that mimicked fluctuating environmental conditions across seasons were conducted to evaluate strategies for selection of YR resistance that is stable across years. Strategies which gave most weight to OP, but some weight to RMSD were optimal in these conditions, and substantially reduced variation of performance across years. This study provides useful information for breeding cultivars with both high YR resistance and high stability of resistance across environments.

Triticum↗