scholarly journals Childhood urbanization affects prefrontal cortical responses to trait anxiety and interacts with polygenic risk for depression

2018 ◽  
Author(s):  
Xiao Zhang ◽  
Hao Yan ◽  
Hao Yu ◽  
Xin Zhao ◽  
Shefali Shah ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Social Status ◽  
Trait Anxiety ◽  
Genetic Risk ◽  
Social Inequalities ◽  
Disease Risk ◽  
Critical Role ◽  
Polygenic Risk ◽  
Anxiety Depression ◽  
Risk For Depression

AbstractGlobal increases in urbanization have brought dramatic economic, environmental and social changes. However, less is understood about how these may influence disease-related brain mechanisms underlying epidemiological observations that urban birth and childhoods may increase the risk for neuropsychiatric disorders, including increased social stress and depression. In a genetically homogeneous Han Chinese adult population with divergent urban and rural birth and childhoods, we examined the structural and functional MRI neural correlates of childhood urbanicity, focusing on behavioral traits responding to social status threats, and polygenic risk for depression. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhoods, however, were associated with higher trait anxiety-depression. On structural MRI, urban childhoods were associated with relatively reduced medial prefrontal gray matter volumes. Functional medial prefrontal engagement under social status threat during working memory correlated with trait anxiety-depression in subjects with urban childhoods, to a significantly greater extent than in their rural counterparts, implicating an exaggerated physiological response to the threat context. Stress-associated medial prefrontal engagement also interacted with polygenic risk for depression, significantly predicting a differential response in individuals with urban but not rural childhoods. Developmental urbanicity thus differentially influenced medial prefrontal structure and function, at least in part through mechanisms associated with the neural processing of social status threat, trait anxiety, and genetic risk for depression, which may be factors in the association of urbanicity with adult psychopathology.Significance StatementUrban living has been associated with social inequalities and stress. However, less is understood about the neural underpinnings by which these stressors affect disease risk, and in particular, genetic risk for depression. Leveraging urbanization in China, we studied adults with diverse urban and rural upbringings, who were genetically homogeneous and with similar current socioeconomic status, to isolate the effects of childhood urbanicity. At medial prefrontal cortex, a region critical for processing emotional stressors and social status, genetic risk for depression resulted in more deleterious function under stress in individuals with urban, but not rural childhoods. This implicates medial prefrontal cortex’s critical role in brain development, integrating genetic mechanisms of stress and depression with the childhood environment.

scholarly journals Childhood urbanicity interacts with polygenic risk for depression to affect stress-related medial prefrontal function

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao Zhang ◽  
Hao Yan ◽  
Hao Yu ◽  
Xin Zhao ◽  
Shefali Shah ◽  
...  
Keyword(s):  
Trait Anxiety ◽  
Social Stress ◽  
Depressive Illness ◽  
Behavioral Risk ◽  
Polygenic Risk ◽  
Prefrontal Function ◽  
Rural And Urban ◽  
Functional Relevance ◽  
Anxiety Depression ◽  
Risk For Depression

AbstractUrbanization is increasing globally, and is associated with stress and increased mental health risks, including for depression. However, it remains unclear, especially at the level of brain function, how urbanicity, social threat stressors, and psychiatric risk may be linked. Here, we aim to define the structural and functional MRI neural correlates of social stress, childhood urbanicity, and their putative mechanistic relevance to depressive illness risk, in terms of behavioral traits and genetics. We studied a sample of healthy adults with divergent urban and rural childhoods. We examined childhood urbanicity effects on brain structure as suggested by MRI, and its functional relevance to depression risk, through interactions between urbanicity and trait anxiety-depression, as well as between urbanicity and polygenic risk for depression, during stress-related medial prefrontal cortex (mPFC) engagement. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhood was associated with relatively reduced mPFC gray matter volumes as suggested by MRI. MPFC engagement under social status threat correlated with the higher trait anxiety-depression in subjects with urban childhoods, but not in their rural counterparts, implicating an exaggerated physiological response to the threat context with urbanicity, in association with behavioral risk for depression. Stress-associated mPFC engagement also interacted with polygenic risk for depression, significantly predicting a differential mPFC response in individuals with urban but not rural childhoods. Developmental urbanicity, therefore, appears to interact with genetic and behavioral risk for depression on the mPFC neural response to a threat context.

scholarly journals Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

2021 ◽  
pp. 1-12
Author(s):  
Simon Schmitt ◽  
Tina Meller ◽  
Frederike Stein ◽  
Katharina Brosch ◽  
Kai Ringwald ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mental Disorders ◽  
Cortical Thickness ◽  
Genetic Risk ◽  
Right Hemisphere ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Grey Matter Volume ◽  
Polygenic Risk ◽  
Risk For Depression

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

Air pollution interacts with genetic risk to influence cortical networks implicated in depression

2021 ◽  
Vol 118 (46) ◽  
pp. e2109310118
Author(s):  
Zhi Li ◽  
Hao Yan ◽  
Xiao Zhang ◽  
Shefali Shah ◽  
Guang Yang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Genetic Risk ◽  
Information Transfer ◽  
Depressive Disorders ◽  
Effective Connectivity ◽  
Brain Network ◽  
Brain Atlas ◽  
Polygenic Risk ◽  
Increased Risk ◽  
Risk For Depression

Air pollution is a reversible cause of significant global mortality and morbidity. Epidemiological evidence suggests associations between air pollution exposure and impaired cognition and increased risk for major depressive disorders. However, the neural bases of these associations have been unclear. Here, in healthy human subjects exposed to relatively high air pollution and controlling for socioeconomic, genomic, and other confounders, we examine across multiple levels of brain network function the extent to which particulate matter (PM2.5) exposure influences putative genetic risk mechanisms associated with depression. Increased ambient PM2.5 exposure was associated with poorer reasoning and problem solving and higher-trait anxiety/depression. Working memory and stress-related information transfer (effective connectivity) across cortical and subcortical brain networks were influenced by PM2.5 exposure to differing extents depending on the polygenic risk for depression in gene-by-environment interactions. Effective connectivity patterns from individuals with higher polygenic risk for depression and higher exposures with PM2.5, but not from those with lower genetic risk or lower exposures, correlated spatially with the coexpression of depression-associated genes across corresponding brain regions in the Allen Brain Atlas. These converging data suggest that PM2.5 exposure affects brain network functions implicated in the genetic mechanisms of depression.

scholarly journals Genetic assessments of breast cancer risk that do not account for polygenic background are incomplete and lead to incorrect preventative strategies

2021 ◽  
Author(s):  
George B Busby ◽  
Paul Craig ◽  
Nesrine Yousfi ◽  
Saurabh Hebbalker ◽  
Paolo Di Domenico ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Genetic Risk ◽  
Disease Risk ◽  
Population Level ◽  
Polygenic Risk ◽  
Cancer Susceptibility Genes ◽  
Pathogenic Mutations ◽  
Genome Wide

Breast cancer is the most common cancer among women and is a leading cause of cancer mortality worldwide. There is a significant genetic component to breast cancer risk which is the result of both rare pathogenic mutations and common genome-wide variation. However, the penetrance of pathogenic mutations varies widely and their frequency is low, both at a population level and amongst breast cancer cases. Polygenic risk scores, which aggregate the effect of hundreds to millions of common genome-wide variants offer a way to further understand the contribution of genetics to disease risk. Here we analyse genome-wide data from 221,479 women and 90,307 high coverage exomes to understand how rare and common variation affect lifetime breast cancer risk. We show that PRS strongly modulates the penetrance of mutations in 8 breast cancer susceptibility genes. For example, lifetime risk in BRCA1 carriers with low polygenic risk is almost one third that of carriers with high PRS (26% v 69% in the bottom and top PRS deciles, respectively). Adding family history of breast cancer provides additional stratification on the potential outcome of disease in carriers of rare mutations. PRS also identifies a significant fraction of the population at equivalent risk to carriers of moderate impact pathogenic variants and who are an order of magnitude more common at a population level. These results have important implications for breast cancer risk mitigation strategies, indicating that the genetic risk of breast cancer is determined by both monogenic mutation and polygenic background, and that assessments of genetic risk for breast cancer risk that do not consider the polygenic background are imprecise and unreliable.

scholarly journals A critical role of brain network architecture in a continuum model of autism spectrum disorders spanning from healthy individuals with genetic liability to individuals with ASD

2021 ◽  
Author(s):  
Budhachandra Khundrakpam ◽  
Neha Bhutani ◽  
Uku Vainik ◽  
Noor B Al-Sharif ◽  
Alain Dagher ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Network Architecture ◽  
Continuum Model ◽  
Critical Role ◽  
Autism Spectrum ◽  
Brain Network ◽  
Healthy Individuals ◽  
Polygenic Risk ◽  
Spectrum Disorders

Studies have shown cortical alterations in individuals with autism spectrum disorders (ASD) as well as in individuals with high polygenic risk for ASD. An important addition to the study of altered cortical anatomy is the investigation of the underlying brain network architecture that may reveal brain-wide mechanisms in ASD and in polygenic risk for ASD. Such an approach has been proven useful in other psychiatric disorders by revealing that brain network architecture shapes (to an extent) the disorder-related cortical alterations. This study uses data from a clinical dataset: 560 male subjects (266 individuals with ASD and 294 healthy individuals, CTL, mean age at 17.2 years) from the Autism Brain Imaging Data Exchange database, and data of 391 healthy individuals (207 males, mean age at 12.1 years) from the Pediatric Imaging, Neurocognition and Genetics database. ASD-related cortical alterations (group difference, ASD-CTL, in cortical thickness) and cortical correlates of polygenic risk for ASD were assessed, and then statistically compared with structural connectome-based network measures (such as hubs) using spin permutation tests. Next, we investigated whether polygenic risk for ASD could be predicted by network architecture by building machine-learning based prediction models, and whether the top predictors of the model were identified as disease epicenters of ASD. We observed that ASD-related cortical alterations as well as cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. We also observed that age progression of ASD-related cortical alterations and cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. Further investigation revealed that structural connectomes predicted polygenic risk for ASD (r=0.30, p<0.0001), and two brain regions (the left inferior parietal and left suparmarginal) with top predictive connections were identified as disease epicenters of ASD. Our study highlights a critical role of network architecture in a continuum model of ASD spanning from healthy individuals with genetic risk to individuals with ASD. Our study also highlights the strength of investigating polygenic risk scores in addition to multi-modal neuroimaging measures to better understand the interplay between genetic risk and brain alterations associated with ASD.

Abstract 26: Polygenic Risk Score for Obesity Modifies Associations of Proinflammatory Diets With Obesity, Long-term Weight Gain, and Cardiovascular Disease Risk: The Utilization of Polygenic Prediction in 3 US Prospective Cohorts

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Jun Li ◽  
Jie Hu ◽  
Dong Hoon Lee ◽  
Wonil Chung ◽  
Baoshan Ma ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Weight Gain ◽  
Genetic Risk ◽  
Central Obesity ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Polygenic Risk Score ◽  
Dietary Interventions ◽  
Polygenic Risk

Background: Individuals predisposed to higher genetic risk of obesity may need early dietary interventions to prevent obesity and its comorbidities. Hypothesis: Proinflammatory diets may interact with genetic background to modify risks of obesity, long-term weight gain, and cardiovascular disease (CVD). Methods: We prospectively followed 16 281 and 11 832 women in the Nurses’ Health Study I and II, and 10 172 men in Health Professionals Follow-up Study, with available genetic data, for up to 28 years. Diet and weight were assessed every 4 years. Dietary inflammatory potential was assessed by an empirical dietary inflammatory pattern (EDIP) score pre-defined based on associations of foods with inflammatory markers. Polygenic risk scores (PRS) of body mass index (BMI), waist-hip ratio, and body fat mass, developed based on genome-wide association data of 9 million variants in 389 972 UK Biobank participants using LDpred, were applied to characterize genetic predispositions to obesity, central obesity, and adiposity. Results: All 3 PRS were highly predictive for BMI ( Fig. A ). In pooled multivariable analyses, higher EDIP scores were associated with a higher BMI, with the association 2-3 folds stronger comparing participants in the highest 10% to the lowest 10% of genetic risk of obesity/adiposity ( P interaction ≤0.001; Fig. B ). The positive association between EDIP and CVD incidence was 1.6-fold stronger in participants at a higher genetic risk of central obesity ( P interaction =0.04; Fig. C ). In addition, an increase in EDIP scores was associated with a greater long-term weight gain, while a reduction in EDIP was associated with a greater weight loss, comparing participants in the highest 10% of genetic risk to those at lower risks, among participants aged <65 years but not above ( P interaction <0.005; Fig. D ). Conclusions: Polygenic background modifies associations of proinflammatory diets with obesity, long-term weight change, and CVD risk. PRS may be useful tools to identify individuals in need for early dietary interventions.

scholarly journals Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring

2021 ◽  
Author(s):  
Sophia Gunn ◽  
Michael Wainberg ◽  
Zeyuan Song ◽  
Stacy Andersen ◽  
Robert Boudreau ◽  
...  
Keyword(s):  
General Population ◽  
Genetic Risk ◽  
Disease Risk ◽  
Association Studies ◽  
Risk Scores ◽  
Human Longevity ◽  
Genome Wide Association Studies ◽  
Predictive Values ◽  
Polygenic Risk ◽  
Polygenic Scores

Background: A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict risk of disease than individual significant variants alone. Methods: We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring and controls and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting ancestral background of the individuals (PCs). In our analyses we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits. Results: We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer's disease (AD), coronary artery disease (CAD) and systemic lupus than controls, suggesting genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function. In addition, the PRS for AD was associated with higher risk of dementia among controls but not ELLIs (p = 0.0004, 0.3 in NECS, p = 0.03, 0.93 in LLFS respectively). Interestingly, ELLIs did not have a larger number of homozygous risk genotypes for AD (TNECS = -1.72, TLLFs = 0.83) and CAD (TNECS = -5.08, TLLFs = -0.31) in both cohorts, but did have significantly larger number of homozygous protective genotypes than controls for the two traits (AD: TNECS =3.10, TLLFs = 2.2, CAD: TNECS = 6.57, TLLFs =2.36, respectively). Conclusions: ELLIs have a similar burden of genetic disease risk as the general population for most traits, but have significantly lower genetic risk of AD, CAD, and lupus. The lack of association between AD PRS and dementia among ELLIs suggests that their genetic risk for AD is somehow buffered by protective genetic or environmental factors.

scholarly journals Genetic risk of major depressive disorder: the moderating and mediating effects of neuroticism and psychological resilience on clinical and self-reported depression

2017 ◽  
Vol 48 (11) ◽  
pp. 1890-1899 ◽  
Author(s):  
L. B. Navrady ◽  
M. J. Adams ◽  
S. W. Y. Chan ◽  
S. J. Ritchie ◽  
A. M. McIntosh ◽  
...  
Keyword(s):  
Structural Equation Modelling ◽  
Genetic Risk ◽  
Structural Equation ◽  
Short Form ◽  
Large Population ◽  
Clinical Depression ◽  
Psychological Resilience ◽  
Polygenic Risk ◽  
Equation Modelling ◽  
Risk For Depression

AbstractBackgroundPolygenic risk scores (PRS) for depression correlate with depression status and chronicity, and provide causal anchors to identify depressive mechanisms. Neuroticism is phenotypically and genetically positively associated with depression, whereas psychological resilience demonstrates negative phenotypic associations. Whether increased neuroticism and reduced resilience are downstream mediators of genetic risk for depression, and whether they contribute independently to risk remains unknown.MethodsModerating and mediating relationships between depression PRS, neuroticism, resilience and both clinical and self-reported depression were examined in a large, population-based cohort, Generation Scotland: Scottish Family Health Study (N = 4166), using linear regression and structural equation modelling. Neuroticism and resilience were measured by the Eysenck Personality Scale Short Form Revised and the Brief Resilience Scale, respectively.ResultsPRS for depression was associated with increased likelihood of self-reported and clinical depression. No interaction was found between PRS and neuroticism, or between PRS and resilience. Neuroticism was associated with increased likelihood of self-reported and clinical depression, whereas resilience was associated with reduced risk. Structural equation modelling suggested the association between PRS and self-reported and clinical depression was mediated by neuroticism (43–57%), while resilience mediated the association in the opposite direction (37–40%). For both self-reported and clinical diagnoses, the genetic risk for depression was independently mediated by neuroticism and resilience.ConclusionsFindings suggest polygenic risk for depression increases vulnerability for self-reported and clinical depression through independent effects on increased neuroticism and reduced psychological resilience. In addition, two partially independent mechanisms – neuroticism and resilience – may form part of the pathway of vulnerability to depression.

scholarly journals Pathway specific polygenic risk scores identify pathways and patient clusters associated with inflammatory bowel disease risk, severity and treatment response

2021 ◽  
Author(s):  
Corneliu A Bodea ◽  
Michael Macoritto ◽  
Yingchun Liu ◽  
Wenliang Zhang ◽  
Jozsef Karman ◽  
...  
Keyword(s):  
Treatment Response ◽  
Genetic Risk ◽  
Disease Risk ◽  
Clinical Care ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Stratification Method ◽  
Inflammatory Bowel

Crohn's disease (CD) and ulcerative colitis (UC) are inflammatory bowel diseases (IBD) with a strong genetic component. Genome-wide association studies (GWAS) have successfully identified over 240 genetic loci that are statistically associated with risk of developing IBD, and these associations provide valuable insights into disease pathobiology. Building on GWAS findings, conventional polygenic risk scores (cPRS) aim to quantify the aggregated disease risk based on DNA variation, and these scores can identify individuals at high risk. While stratifying individuals based on cPRS has the potential to inform clinical care, the development of novel therapeutics requires deep insight into how aggregated genetic risk leads to disruption of specific biological pathways. Here, we developed a pathway-specific PRS (pPRS) methodology to assess IBD common variant genetic risk burden across 31 manually curated pathways. We first prioritized 206 genes based on comprehensive fine-mapping and eQTL colocalization analyses of genome-wide significant IBD GWAS loci and 58 highly penetrant genes based on their involvement in early onset IBD or autoimmunity-related colitis. These 264 genes were assigned to at least one of the 31 pathways based on Gene Ontology annotations and manual curation. Finally, we integrated these inputs into a novel pPRS model and performed an extensive investigation of IBD disease risk, severity, complications, and anti-TNF treatment response by applying our pPRS approach to three complementary datasets encompassing IBD cases and controls. Our analysis identified multiple promising pathways that can inform drug target discovery and provides a patient stratification method that offers insights into the biology of treatment response.

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