An integrated approach to identify environmental modulators of genetic risk factors for complex traits.

Complex traits and diseases can be influenced by both genetics and environment. However, given the large number of environmental stimuli and power challenges for gene-by-environment testing, it remains a critical challenge to identify and prioritize specific disease-relevant environmental exposures. We propose a framework for leveraging signals from transcriptional responses to environmental perturbations to identify disease-relevant perturbations that can modulate genetic risk for complex traits and inform the functions of genetic variants associated with complex traits. We perturbed human skeletal-muscle-, fat-, and liver-relevant cell lines with 21 perturbations affecting insulin resistance, glucose homeostasis, and metabolic regulation in humans and identified thousands of environmentally responsive genes. By combining these data with GWASs from 31 distinct polygenic traits, we show that the heritability of multiple traits is enriched in regions surrounding genes responsive to specific perturbations and, further, that environmentally responsive genes are enriched for associations with specific diseases and phenotypes from the GWAS Catalog. Overall, we demonstrate the advantages of large-scale characterization of transcriptional changes in diversely stimulated and pathologically relevant cells to identify disease-relevant perturbations.

The Role of the Environment in Horizontal Gene Transfer.

Gene-by-environment interactions play a crucial role in horizontal gene transfer by affecting how the transferred genes alter host fitness. However, how the environment modulates the fitness effect of transferred genes has not been tested systematically in an experimental study. We adapted a high-throughput technique for obtaining very precise estimates of bacterial fitness, in order to measure the fitness effects of 44 orthologs transferred from Salmonella Typhimurium to Escherichia coli in six physiologically relevant environments. We found that the fitness effects of individual genes were highly dependent on the environment, while the distributions of fitness effects across genes were not, with all tested environments resulting in distributions of same shape and spread. Furthermore, the extent to which the fitness effects of a gene varied between environments depended on the average fitness effect of that gene across all environments, with nearly neutral and nearly lethal genes having more consistent fitness effects across all environments compared to deleterious genes. Put together, our results reveal the unpredictable nature of how environmental conditions impact the fitness effects of each individual gene. At the same time, distributions of fitness effects across environments exhibit consistent features, pointing to the generalizability of factors that shape horizontal gene transfer of orthologous genes.

Using Transcriptomic Hidden Variables to Infer Context-Specific Genotype Effects in the Brain.

Deciphering the environmental contexts at which genetic effects are most prominent is central for making full use of GWAS results in follow-up experiment design and treatment development. However, measuring a large number of environmental factors at high granularity might not always be feasible. Instead, here we propose extracting cellular embedding of environmental factors from gene expression data by using latent variable (LV) analysis and taking these LVs as environmental proxies in detecting gene-by-environment (GxE) interaction effects on gene expression, i.e., GxE expression quantitative trait loci (eQTLs). Applying this approach to two largest brain eQTL datasets (n = 1,100), we show that LVs and GxE eQTLs in one dataset replicate well in the other dataset. Combining the two samples via meta-analysis, 895 GxE eQTLs are identified. On average, GxE effect explains an additional ∼4% variation in expression of each gene that displays a GxE effect. Ten of these 52 genes are associated with cell-type-specific eQTLs, and the remaining genes are multi-functional. Furthermore, after substituting LVs with expression of transcription factors (TF), we found 91 TF-specific eQTLs, which demonstrates an important use of our brain GxE eQTLs.

Neuroinflammation represents a common theme amongst genetic and environmental risk factors for Alzheimer and Parkinson diseases.

Multifactorial diseases are characterized by inter-individual variation in etiology, age of onset, and penetrance. These diseases tend to be relatively common and arise from the combined action of genetic and environmental factors; however, parsing the convoluted mechanisms underlying these gene-by-environment interactions presents a significant challenge to their study and management. For neurodegenerative disorders, resolving this challenge is imperative, given the enormous health and societal burdens they impose. The mechanisms by which genetic and environmental effects may act in concert to destabilize homeostasis and elevate risk has become a major research focus in the study of common disease. Emphasis is further being placed on determining the extent to which a unifying biological principle may account for the progressively diminishing capacity of a system to buffer disease phenotypes, as risk for disease increases. Data emerging from studies of common, neurodegenerative diseases are providing insights to pragmatically connect mechanisms of genetic and environmental risk that previously seemed disparate. In this review, we discuss evidence positing inflammation as a unifying biological principle of homeostatic destabilization affecting the risk, onset, and progression of neurodegenerative diseases. Specifically, we discuss how genetic variation associated with Alzheimer disease and Parkinson disease may contribute to pro-inflammatory responses, how such underlying predisposition may be exacerbated by environmental insults, and how this common theme is being leveraged in the ongoing search for effective therapeutic interventions.

The Relationship Between Chemokine and Chemokine Receptor Genes Polymorphisms and Chronic Obstructive Pulmonary Disease Susceptibility in Tatar Population from Russia: A Case Control Study.

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease affecting primarily distal respiratory pathways and lung parenchyma. This study aimed to determine possible genetic association of chemokine and chemokine receptor genes polymorphisms with COPD in a Tatar population from Russia. SNPs of CCL20, CCR6, CXCL8, CXCR1, CXCR2, CCL8, CCL23, CCR2, and CX3CL1 genes and their gene-gene interactions were analyzed for association with COPD in cohort of 601 patients and 617 controls. As a result statistically significant associations with COPD in the study group under the biologically plausible assumption of additive genetic model were identified in CCL20 (rs6749704) (P = 0.00001, OR 1.55), CCR6 (rs3093024) (P = 0.0003, OR 0.74), CCL8 (rs3138035) (P = 0.0001, OR 0.67), CX3CL1 (rs170364) (P = 0.023, OR 1.21), CXCL8 (rs4073) (P = 0.007, OR 1.23), CXCR2 (rs2230054) (P = 0.0002, OR 1.32). Following SNPs CCL20 (rs6749704), CX3CL1 (rs170364), CCL8 (rs3138035), CXCL8 (rs4073), CXCR2 (rs2230054) showed statistically significant association with COPD only in smokers. The association of CCR6 (rs3093024) with COPD was confirmed both in smokers and in non-smokers. A relationship between smoking index and CCL20 (rs6749704) (P = 0.04), CCR6 (rs3093024) (P = 0.007), CCL8 (rs3138035) (P = 0.0043), and CX3CL1 (rs170364) (P = 0.04) was revealed. A significant genotype-dependent variation of Forced Vital Capacity was observed for CCL23 (rs854655) (P = 0.04). Forced Expiratory Volume in 1 s / Forced Vital Capacity ratio was affected by CCL23 (rs854655) (P = 0.05) and CXCR2 (rs1126579) (P = 0.02). Using the APSampler algorithm, we obtained nine gene-gene combinations that remained significantly associated with COPD; loci CCR2 (rs1799864) and CCL8 (rs3138035) were involved in the largest number of the combinations. Our results indicate that CCL20 (rs6749704), CCR6 (rs3093024), CCR2 (rs1799864), CCL8 (rs3138035), CXCL8 (rs4073), CXCR1 (rs2234671), CXCR2 (rs2230054), and CX3CL1 (rs170364) polymorphisms are strongly associated with COPD in Tatar population from Russia, alone and in combinations. For the first time combination of the corresponding SNPs were considered and as a result 8 SNP patterns were associated with increased risk of COPD.

Associations of air pollution with obesity and body fat percentage, and modification by polygenic risk score for BMI in the UK Biobank.

Air pollution has consistently been associated with cardiometabolic outcomes, although associations with obesity have only been recently reported. Studies of air pollution and adiposity have mostly relied on body mass index (BMI) rather than body fat percentage (BF%), and most have not accounted for noise as a possible confounder. Additionally, it is unknown whether genetic predisposition for obesity increases susceptibility to the obesogenic effects of air pollution. To help fill these gaps, we used the UK Biobank, a large, prospective cohort study in the United Kingdom, to explore the relationship between air pollution and adiposity, and modification by a polygenic risk score for BMI. We used 2010 annual averages of air pollution estimates from land use regression (NO2, NOX, PM2.5, PM2.5absorbance, PM2.5-10, PM10), traffic intensity (TI), inverse distance to road (IDTR), along with examiner-measured BMI, waist-hip-ratio (WHR), and impedance measures of BF%, which were collected at enrollment (2006-2010, n = 473,026) and at follow-up (2012-2013, n = 19,518). We estimated associations of air pollution with BMI, WHR, and BF% at enrollment and follow-up, and with obesity, abdominal obesity, and BF%-obesity at enrollment and follow-up. We used linear and logistic regression and controlled for noise and other covariates. We also assessed interactions of air pollution with a polygenic risk score for BMI. On average, participants at enrollment were 56 years of age, 54% were female, and 32% had completed college or a higher degree. Almost all participants (~95%) were white. All air pollution measures except IDTR were positively associated with at least one continuous measure of adiposity at enrollment. However, NO2 was negatively associated with BMI but positively associated with WHR at enrollment, and IDTR was also negatively associated with BMI. At follow-up (controlling for enrollment adiposity), we observed positive associations for PM2.5-10 with BMI, PM10 with BF%, and TI with BF% and BMI. Associations were similar for binary measures of adiposity, with minor differences for some pollutants. Associations of NOX, NO2, PM2.5absorbance, PM2.5 and PM10, with BMI at enrollment, but not at follow-up, were stronger among individuals with higher BMI polygenic risk scores (interaction p <0.05). In this large, prospective cohort, air pollution was associated with several measures of adiposity at enrollment and follow-up, and associations with adiposity at enrollment were modified by a polygenic risk score for obesity.

Effects of mutation and selection on plasticity of a promoter activity in Saccharomyces cerevisiae.

Phenotypic plasticity is an evolvable property of biological systems that can arise from environment-specific regulation of gene expression. To better understand the evolutionary and molecular mechanisms that give rise to plasticity in gene expression, we quantified the effects of 235 single-nucleotide mutations in the Saccharomyces cerevisiae TDH3 promoter (PTDH3 ) on the activity of this promoter in media containing glucose, galactose, or glycerol as a carbon source. We found that the distributions of mutational effects differed among environments because many mutations altered the plastic response exhibited by the wild-type allele. Comparing the effects of these mutations with the effects of 30 PTDH3 polymorphisms on expression plasticity in the same environments provided evidence of natural selection acting to prevent the plastic response in PTDH3 activity between glucose and galactose from becoming larger. The largest changes in expression plasticity were observed between fermentable (glucose or galactose) and nonfermentable (glycerol) carbon sources and were caused by mutations located in the RAP1 and GCR1 transcription factor binding sites. Mutations altered expression plasticity most frequently between the two fermentable environments, with mutations causing significant changes in plasticity between glucose and galactose distributed throughout the promoter, suggesting they might affect chromatin structure. Taken together, these results provide insight into the molecular mechanisms underlying gene-by-environment interactions affecting gene expression as well as the evolutionary dynamics affecting natural variation in plasticity of gene expression.

Evolutionary perspectives on ageing.

From an evolutionary perspective, ageing is a decrease in fitness with chronological age - expressed by an increase in mortality risk and/or decline in reproductive success and mediated by deterioration of functional performance. While this makes ageing intuitively paradoxical - detrimental to individual fitness - evolutionary theory offers answers as to why ageing has evolved. In this review, I first briefly examine the classic evolutionary theories of ageing and their empirical tests, and highlight recent findings that have advanced our understanding of the evolution of ageing (condition-dependent survival, positive pleiotropy). I then provide an overview of recent theoretical extensions and modifications that accommodate those new discoveries. I discuss the role of indeterminate (asymptotic) growth for lifetime increases in fecundity and ageing trajectories. I outline alternative views that challenge a universal existence of senescence - namely the lack of a germ-soma distinction and the ability of tissue replacement and retrogression to younger developmental stages in modular organisms. I argue that rejuvenation at the organismal level is plausible, but includes a return to a simple developmental stage. This may exempt a particular genotype from somatic defects but, correspondingly, removes any information acquired during development. A resolution of the question of whether a rejuvenated individual is the same entity is central to the recognition of whether current evolutionary theories of ageing, with their extensions and modifications, can explain the patterns of ageing across the Tree of Life.

Gene × Environment Interactions: From Molecular Mechanisms to Behavior.

Gene-by-environment interactions (G×Es) can provide important biological insights into psychiatric disorders and may consequently have direct clinical implications. In this review, we begin with an overview of the major challenges G×E studies have faced (e.g., difficulties replicating findings and high false discovery rates). In light of these challenges, this review focuses on describing examples in which we might begin to understand G×Es on the molecular, cellular, circuit, and behavioral level and link this interaction to altered risk for the development of psychiatric disorders. We also describe recent studies that utilize a polygenic approach to examine G×Es. Finally, we discuss how gaining a deeper understanding of G×Es may translate into a therapeutic practice with more targeted treatments.

Genome-wide interaction study of dust mite allergen on lung function in children with asthma.

BACKGROUND: Childhood asthma is likely the result of gene-by-environment (G × E) interactions. Dust mite is a known risk factor for asthma morbidity. Yet, there have been no genome-wide G × E studies of dust mite allergen on asthma-related phenotypes. OBJECTIVE: We sought to identify genetic variants whose effects on lung function in children with asthma are modified by the level of dust mite allergen exposure. METHODS: A genome-wide interaction analysis of dust mite allergen level and lung function was performed in a cohort of Puerto Rican children with asthma (Puerto Rico Genetics of Asthma and Lifestyle [PRGOAL]). Replication was attempted in 2 independent cohorts, the Childhood Asthma Management Program (CAMP) and the Genetics of Asthma in Costa Rica Study. RESULTS: Single nucleotide polymorphism (SNP) rs117902240 showed a significant interaction effect on FEV1 with dust mite allergen level in PRGOAL (interaction P = 3.1 × 10-8), and replicated in the same direction in CAMP white children and CAMP Hispanic children (combined interaction P = .0065 for replication cohorts and 7.4 × 10-9 for all cohorts). Rs117902240 was positively associated with FEV1 in children exposed to low dust mite allergen levels, but negatively associated with FEV1 in children exposed to high levels. This SNP is on chromosome 8q24, adjacent to a binding site for CCAAT/enhancer-binding protein beta, a transcription factor that forms part of the IL-17 signaling pathway. None of the SNPs identified for FEV1/forced vital capacity replicated in the independent cohorts. CONCLUSIONS: Dust mite allergen exposure modifies the estimated effect of rs117902240 on FEV1 in children with asthma. Analysis of existing data suggests that this SNP may have transcription factor regulatory functions.

Dissection of genetic architecture of nine hazardous component traits of mainstream smoke in tobacco (Nicotiana tabacum L.).

Tobacco (Nicotiana tabacum L.) use is the leading cause of preventable death, due to deleterious chemical components and smoke from tobacco products, and therefore reducing harmful chemical components in tobacco is one of the crucial tobacco breeding targets. However, due to complexity of tobacco smoke and unavailability of high-density genetic maps, the genetic architecture of representative hazardous smoke has not been fully dissected. The present study aimed to explore the genetic architecture of nine hazardous component traits of mainstream smoke through QTL mapping using 271 recombinant inbred lines (RILs) derived from K326 and Y3 in multiple environments. The analysis of genotype and genotype by environment interaction (GE) revealed substantially greater heritability over 95% contributed mostly by GE interaction effects. We also observed strong genetic correlations among most studied hazardous smoke traits, with the highest correlation coefficient of 0.84 between carbon monoxide and crotonaldehyde. Based on a published high-density genetic map, a total of 19 novel QTLs were detected for eight traits using a full QTL model, of which 17 QTLs showed significant additive effects, six showed significant additive-by-environment interaction effects, and one pair showed significant epistasis-by-environment interaction effect. Bioinformatics analysis of sequence in QTL region predicted six genes as candidates for four traits, of which Nt21g04598.1, Nt21g04600.1, and Nt21g04601.1 had pleiotropic effects on PHE and TAR.

Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy.

Chemical genetic screens are a powerful tool for exploring how cancer cells' response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or nuclear factor κB (NF-κB) inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs across hundreds of fluconazole-resistant yeast strains.

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into 6 classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, and some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings empower multidrug strategies that leverage tradeoffs to combat resistance. Finally, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

Long-term effects of adolescent sport experience, DRD2 and COMT genes, and their interaction on sport participation in adulthood.

BACKGROUND: The present study investigated the joint impact of adolescent sport experience and dopamine-related genes (i.e., DRD2 and COMT genes) on sport participation in adulthood. METHODS: Using the National Longitudinal Study of Adolescent Health (Add Health) data, the hierarchical multivariable logistic regression models for predicting sport participation in wave 3 (around 20 years of age) and wave 4 (around 30 years of age) were conducted separately by gender (male and female) and gene (DRD2 and COMT genes). RESULTS: Adolescent sport experience significantly interacted with the number of DRD2 A1 alleles and COMT Met alleles in affecting wave 3 sport participation among male adults. The interaction between adolescent sport experience and DRD2 gene significantly affected wave 4 sport participation in opposite direction to that affected wave 3 sport participation among male participants. Among female participants, there were no significant interaction effects between dopamine-related genes and adolescent sport experience on sport participation in both wave 3 and 4. CONCLUSIONS: Since adult sport participation is most likely to be influenced by the joint impact of environmental and genetic factors, it is important to consider gene-by-environment interactions when designing policies or programs to promote adult sport participation.

Developmental Plasticity in Butterfly Eyespot Mutants: Variation in Thermal Reaction Norms Across Genotypes and Pigmentation Traits.

Developmental plasticity refers to the property by which a genotype corresponds to distinct phenotypes depending on the environmental conditions experienced during development. This dependence of phenotype expression on environment is graphically represented by reaction norms, which can differ between traits and between genotypes. Even though genetic variation for reaction norms provides the basis for the evolution of plasticity, we know little about the genes that contribute to that variation. This includes understanding to what extent those are the same genes that contribute to inter-individual variation in a fixed environment. Here, we quantified thermal plasticity in butterfly lines that differ in pigmentation phenotype to test the hypothesis that alleles affecting pigmentation also affect plasticity therein. We characterized thermal reaction norms for eyespot color rings of distinct Bicyclus anynana genetic backgrounds, corresponding to allelic variants affecting eyespot size and color composition. Our results reveal genetic variation for the slope and curvature of reaction norms, with differences between eyespots and between eyespot color rings, as well as between sexes. Our report of prevalent temperature-dependent and compartment-specific allelic effects underscores the complexity of genotype-by-environment interactions and their consequence for the evolution of developmental plasticity.

Prenatal Maternal Stress From a Natural Disaster and Hippocampal Volumes: Gene-by-Environment Interactions in Young Adolescents From Project Ice Storm.

Gene-by-environment interactions influence brain development from conception to adulthood. In particular, the prenatal period is a window of vulnerability for the interplay between environmental and genetic factors to influence brain development. Rodent and human research demonstrates that prenatal maternal stress (PNMS) alters hippocampal volumes. Although PNMS affects hippocampal size on average, similar degrees of PNMS lead to different effects in different individuals. This differential susceptibility to the effects of PNMS may be due to genetic variants. Hence, we investigated the role of genetic variants of two SNPs that are candidates to moderate the effects of PNMS on hippocampal volume: COMT (rs4680) and BDNF (rs6265). To investigate this, we assessed 53 children who were in utero during the January 1998 Quebec ice storm. In June 1998 their mothers responded to questionnaires about their objective, cognitive, and subjective levels of stress from the ice storm. When children were 11 1/2 years old, T1-weighted structural magnetic resonance imaging (MRI) scans were obtained using a 3T scanner and analyzed to determine hippocampal volumes. We collected and genotyped the children's saliva DNA. Moderation analyses were conducted to determine whether either or both of the SNPs moderate the effect of PNMS on hippocampal volumes. We found that objective hardship was associated with right hippocampal volume in girls, and that the BDNF and COMT genotypes were associated with left hippocampal volume in boys and girls. In addition, SNPs located on COMT moderated the effect of maternal objective distress in boys, and subjective distress in girls, on both right hippocampal volume. Thus, we conclude that an individual's genotype alters their susceptibility to the effects of PNMS.

High-Order Association Mapping for Expression Quantitative Trait Loci.

Mapping expression quantitative trait loci (eQTLs) is an important avenue to identify putative genetic variants in regulatory regions. Famed eQTL mapping methods exploit the mean effects of locus-wise genetic variants on expression quantitative traits. Despite their successes, such methods are suboptimal because they neglect high-order heterogeneity inherent in genetic variants and covariates. High-order effects of observed loci are common due to their connections to various latent factors, i.e., latent interactions among genes and environmental factors. In this chapter, we introduce a new scheme to harmoniously integrate mean and high-order effects of genetic variants on expression quantitative trait. We rigorously evaluate its validity and utility of signal augmentation.

Multitissue Multiomics Systems Biology to Dissect Complex Diseases.

Most complex diseases involve genetic and environmental risk factors, engage multiple cells and tissues, and follow a polygenic or omnigenic model depicting numerous genes contributing to pathophysiology. These multidimensional complexities pose challenges to traditional approaches that examine individual factors. In turn, multitissue multiomics systems biology has emerged to comprehensively elucidate within- and cross-tissue molecular networks underlying gene-by-environment interactions and contributing to complex diseases. The power of systems biology in retrieving novel insights and formulating new hypotheses has been well documented. However, the field faces various challenges that call for debate and action. In this opinion article, I discuss the concepts, benefits, current state, and challenges of the field and point to the next steps toward network-based systems medicine.

Genetic predictors of hippocampal subfield volume in PTSD cases and trauma-exposed controls.

Behavioural, structural, and functional neuroimaging have implicated the hippocampus as a critical brain region in posttraumatic stress disorder (PTSD) pathogenesis. Recent work in a normative, primarily European, sample identified 15 unique genetic loci contributing to structural variability in six hippocampal subfield volumes. We explored the relevance of these loci in two samples (Mental Illness Research Education and Clinical Centre [MIRECC] and Grady; n = 290) of trauma-exposed individuals enriched for PTSD and of diverse ancestry. Four of the previous loci demonstrated nominal evidence of replication in the MIRECC dataset, primarily within non-Hispanic whites (NHW). One locus replicated in the Grady cohort, which was composed exclusively of non-Hispanic blacks (NHB). Our data supported genetic interactions with diagnosis of lifetime PTSD and genetic interactions with childhood trauma in the MIRECC sample, but not the Grady sample. Given the racial, diagnostic, and trauma-exposure differences with the original genome-wide association study (GWAS) report, we conducted a full GWAS in the MIRECC and Grady datasets. Interactions between genetic variants and lifetime PTSD or childhood trauma were interrogated for single nucleotide polymorphisms (SNPs) with evidence of main effects. Genetic associations surpassed false discovery rate (FDR)-correction within hippocampal subfields in fimbria, subiculum, cornu ammonis-1 (CA1), and hippocampal amygdala transition area (HATA). One association was replicated in the Grady cohort (rs12880795 in TUNAR with left (L)-HATA volume). The most significant association in the MIRECC dataset was between rs6906714 in LINC02571 and right (R)-fimbria volume (p = 5.99×10-8, q = 0.0056). Interestingly, the effect of rs6906714 on R-fimbria volume increased with exposure to childhood trauma (gene*environment [G*E] interaction p = 0.022). These preliminary results argue for G*E interactions between genetic loci with PTSD and childhood trauma on hippocampal phenotypes. Our results underscore the need for larger neuroimaging-genetic studies in PTSD, trauma, and ancestrally diverse populations.

Las neuroimagenologia, conductual, estructural y funcional ha implicado que el hipocampo se constituye como una región cerebral critica en la patogénesis del trastorno de estrés postraumático (TEPT). Un trabajo reciente, realizado en una muestra normativa, principalmente europea, identifico 15 loci genéticos únicos que contribuyen a la variabilidad estructural de seis volúmenes de subcampos hipocampales. Exploramos la relevancia de estos loci en dos muestras enriquecidas para TEPT (del Centro de Educación y Clínica Investigación sobre Enfermedades Mentales, MIRECC por sus siglas en inglés y Grady; n=290) de individuos expuestos a trauma y de ascendencia diversa. Cuatro de los loci previos demostraron evidencia nominal de replicación en la base de datos MIRECC, principalmente en personas de raza blanca no hispánicos (NHW). Se replicó un locus en la cohorte Grady, que estaba compuesta exclusivamente por personas de raza negra no hispánicos (NHB). Nuestros datos respaldaron las interacciones genéticas con el diagnostico de TEPT a lo largo de la vida e interacciones genéticas con trauma infantil en la muestra MIRECC, pero no en la de Grady. Debido a las diferencias raciales, diagnósticas y de exposición a trauma con el reporte original del estudio de asociación del genoma completo (GWAS por sus siglas en ingles), realizamos un GWAS completo con la base de datos MIRECC y Grady. Se exploraron polimorfismos de nucleótido único (SNPs por sus siglas en ingles) en las interacciones de variantes genéticas del TEPT a lo largo de la vida y del trauma infantil, con evidencia de un efecto genético principal. Las asociaciones genéticas sobrepasaron a la corrección de tasa de falso descubrimiento (FDR) dentro de los subcampos hipocampales de la fimbria, subículo, asta de Amon-1 (CA1), y el área de transición hipocampo-amigdaliana (HATA). Una asociación se replicó en la cohorte de Grady (rs 12880795 en TUNAR con volumen izquierdo del HATA). La asociación más significativa en la base de datos de MIRECC estuvo entre rs6906714 en LINC02571 y el volumen de la fimbria derecha (p=5.99×10-8, q=0.0056). Interesantemente, el efecto rs6906714 sobre el volumen de la fimbria derecha se incrementaba con la exposición al trauma infantil (interacción gen* ambiente [G*A] p=0.022). Estos resultados preliminares orientarían a la presencia de interacciones G*A de loci genéticos con el TEPT y trauma infantil en fenotipos del hipocampo. Nuestro resultados destacan la necesidad de estudios más grandes que vinculen neuroimagenes y genética en poblaciones con TEPT, trauma, y genealogía diversa.

Genetics of Resilience: Gene-by-Environment Interaction Studies as a Tool to Dissect Mechanisms of Resilience.

The identification and understanding of resilience mechanisms holds potential for the development of mechanistically informed prevention and interventions in psychiatry. However, investigating resilience mechanisms is conceptually and methodologically challenging because resilience does not merely constitute the absence of disease-specific risk but rather reflects active processes that aid in the maintenance of physiological and psychological homeostasis across a broad range of environmental circumstances. In this conceptual review, we argue that the principle used in gene-by-environment interaction studies may help to unravel resilience mechanisms on different investigation levels. We present how this could be achieved by top-down designs that start with gene-by-environment interaction effects on disease phenotypes as well as by bottom-up approaches that start at the molecular level. We also discuss how recent technological advances may improve both top-down and bottom-up strategies.