Comparing Effects of FOXO3A and Residing in Urban Areas on Longevity: A Gene-Environment Interaction Study

Forkhead box O3 (FOXO3A) is a candidate longevity gene. Urban residents are also positively associated with longer life expectancy. We conducted a gene-environment interaction to assess the synergistic effect of FOXO3A and urban/rural environments on mortality. We included 3085 older adults from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We used single nucleotide polymorphisms (SNPs) rs2253310, rs2802292, and rs4946936 to identify the FOXO3A gene and classified residential locations as "urban" and "rural." Given the open cohort design, we used the Cox-proportional hazard regression models to assess the mortality risk. We found the minor allele homozygotes of FOXO3A to have a protective effect on mortality [HR (95% CI) for rs4946936 TT vs. CC: 0.807 (0.653, 0.996); rs2802292 GG vs TT: 0.812 (0.67, 0.985); rs2253310 CC vs. GG: 0.808 (0.667, 0.978)]. Participants living in urban areas had a lower risk of mortality [HR of the urban vs. the rural: 0.854 (0.759, 0.962)]. The interaction between FOXO3A and urban and rural regions was statistically significant (pinteraction<0.01). Higher air pollution (fine particulate matter: PM2.5) and lower residential greenness (Normalized Difference Vegetation Index: NDVI) both contributed to higher mortality. After adjusting for NDVI and PM2.5, the protective effect size of FOXO3A SNPs was slightly attenuated while the protective effect size of living in an urban environment increased. The effect size of the beneficial effect of FOXO3 on mortality is roughly equivalent to that of living in urban areas. Our research findings indicate the effect of places of residence and genetic predisposition of longevity are intertwined.

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results.Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the user’s unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications.Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.

The Effect of Prenatal Valproate Exposure in Serotonin Transporter Knockout Rats On Anxiety and Cognition: A Gene*Environment Interaction Model of Autism Spectrum Disorder

<p>Autism Spectrum Disorder is a complex neurodevelopmental disorder which is often associated with increased anxiety and deficits in cognitive ability. The present research investigated a potential gene*environment interaction between two factors previously implicated in ASD in a rat model; prenatal exposure to valproate (VPA) and genetic reduction of the serotonin transporter (SERT). Wildtype and heterozygous SERT knockout rats prenatally exposed to VPA or saline on gestational day12.5 (G12.5) were assessed on measures of anxiety: elevated plus-maze and novelty suppressed-feeding and cognitive ability: prepulse inhibition and latent inhibition. A significant main effect was found for VPA exposure in all paradigms, showing increased anxiety-typical behaviour and abnormal cognitive ability. However, no significant effect of genotype or interaction was observed. Results from the present study do not confirm gene*environment interaction between prenatal VPA and heterozygous SERT knockout but this may be due to several factors that are discussed within the thesis. In any case, this study represents a starting point for further studies investigating other combinations of genetic and environmental factors as models of ASD pathogenesis.</p>

The Effect of Prenatal Valproate Exposure in Serotonin Transporter Knockout Rats On Anxiety and Cognition: A Gene*Environment Interaction Model of Autism Spectrum Disorder

<p>Autism Spectrum Disorder is a complex neurodevelopmental disorder which is often associated with increased anxiety and deficits in cognitive ability. The present research investigated a potential gene*environment interaction between two factors previously implicated in ASD in a rat model; prenatal exposure to valproate (VPA) and genetic reduction of the serotonin transporter (SERT). Wildtype and heterozygous SERT knockout rats prenatally exposed to VPA or saline on gestational day12.5 (G12.5) were assessed on measures of anxiety: elevated plus-maze and novelty suppressed-feeding and cognitive ability: prepulse inhibition and latent inhibition. A significant main effect was found for VPA exposure in all paradigms, showing increased anxiety-typical behaviour and abnormal cognitive ability. However, no significant effect of genotype or interaction was observed. Results from the present study do not confirm gene*environment interaction between prenatal VPA and heterozygous SERT knockout but this may be due to several factors that are discussed within the thesis. In any case, this study represents a starting point for further studies investigating other combinations of genetic and environmental factors as models of ASD pathogenesis.</p>

Characterisation of insomnia as an environmental risk factor for asthma via Mendelian randomization and gene environment interaction

Asthma is a complex disease that is reportedly associated with insomnia. However, the causal directionality of this association is still unclear. We used asthma and insomnia-associated single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) summary statistics to test the causal directionality between insomnia and asthma via Mendelian randomization (MR) analysis. We also performed a cross-trait meta-analysis using UK Biobank GWAS summary statistics and a gene–environment interaction study using data from UK Biobank. The interaction of genetic risk score for asthma (GRSasthma) with insomnia on asthma was tested by logistic regression. Insomnia was a risk factor for the incidence of asthma, as revealed by three different methods of MR analysis. However, asthma did not act as a risk factor for insomnia. The cross-trait meta-analysis identified 28 genetic loci shared between asthma and insomnia. In the gene–environment interaction study, GRSasthma interacted with insomnia to significantly affect the risk of asthma. The results of this study highlight the importance of insomnia as a risk factor of asthma, and warrant further analysis of the mechanism through which insomnia affects the risk of asthma.