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.

Parietal–prefrontal feedforward connectivity in association with schizophrenia genetic risk and delusions

2019 ◽  
Author(s):  
Danielle Borrajo ◽  
Michelle La ◽  
Shefali Shah ◽  
Qiang Chen ◽  
Karen F Berman ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Regression Models ◽  
Information Transfer ◽  
Effective Connectivity ◽  
Support Vector ◽  
Prior Beliefs ◽  
Feed Forward ◽  
Polygenic Risk ◽  
New Information ◽  
Information Processing Deficits

AbstractBackgroundConceptualizations of delusion formation implicate, in part, deficits at feed-forward information transfer across posterior to prefrontal cortices, resulting in dysfunctional integration of new information in favor of over-familiar prior beliefs. Here, we used functional MRI and machine learning models to examine feedforward parietal-prefrontal information transfer in schizophrenia patients in relation to delusional thinking, and polygenic risk for schizophrenia.MethodsWe studied 66 schizophrenia patients and 143 healthy controls as they performed context updating during working memory (WM). Dynamic causal models of effective connectivity were focused on prefrontal and parietal cortex, where we examined parietal-prefrontal connectivity in relation to delusions in patients. We further tested for an effect of polygenic risk for schizophrenia on connectivity in healthy individuals. We then leveraged support vector regression models to define optimal normalized target connectivity tailored for each patient, and tested the extent to which deviation from this target predicted individual variation in delusion severity.ResultsIn schizophrenia patients, updating and manipulating context information was disproportionately less accurate than was WM maintenance, with a task accuracy-by-diagnosis interaction. Also, patients with delusions tended to have relatively reduced feedforward effective connectivity during context updating in WM manipulation. The same parietal-prefrontal feedforward prefrontal effective connectivity was adversely influenced by polygenic risk for schizophrenia in healthy subjects. Individual patients’ deviation from predicted ‘normal’ feedforward connectivity based on the support vector models correlated with delusional severity.ConclusionsThese computationally-derived observations support a role for feed-forward parietal-prefrontal information processing deficits in delusional psychopathology, and in genetic risk for schizophrenia.

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.

scholarly journals Schizophrenia liability shares common molecular genetic risk factors with sleep duration and nightmares in childhood

2019 ◽  
Vol 4 ◽  
pp. 15
Author(s):  
Zoe E. Reed ◽  
Hannah J. Jones ◽  
Gibran Hemani ◽  
Stanley Zammit ◽  
Oliver S. P. Davis
Keyword(s):  
Sleep Duration ◽  
Genetic Risk ◽  
Sleep Disturbances ◽  
Molecular Genetic ◽  
Polygenic Risk Score ◽  
Genetic Covariance ◽  
Polygenic Risk ◽  
Parents And Children ◽  
Increased Risk ◽  
Sleep Abnormalities

Background: Sleep abnormalities are common in schizophrenia, often appearing before psychosis onset; however, the mechanisms behind this are uncertain. We investigated whether genetic risk for schizophrenia is associated with sleep phenotypes. Methods: We used data from 6,058 children and 2,302 mothers from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined associations between a polygenic risk score for schizophrenia and sleep duration in both children and mothers, and nightmares in children, along with genetic covariances between these traits. Results: Polygenic risk for schizophrenia was associated with increased risk of nightmares (OR=1.07, 95% CI: 1.01, 1.14, p=0.02) in children, and also with less sleep (β=-44.52, 95% CI: −88.98, −0.07; p=0.05). We observed a similar relationship with sleep duration in mothers, although evidence was much weaker (p=0.38). Finally, we found evidence of genetic covariance between schizophrenia risk and reduced sleep duration in children and mothers, and between schizophrenia risk and nightmares in children. Conclusions: These molecular genetic results support recent findings from twin analysis that show genetic overlap between sleep disturbances and psychotic-like experiences. They also show, to our knowledge for the first time, a genetic correlation between schizophrenia liability and risk of nightmares in childhood.

Abstract P460: Genetic Risk for Obesity Across the Transition From Young to Older Adulthood: A Pathway Based Analysis

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Ruixue Hou ◽  
Annie Green Howard ◽  
Hsiao-Chuan Tien ◽  
Mariaelisa Graff ◽  
Wei Huang ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Young Adulthood ◽  
Genetic Risk ◽  
Linear Mixed Model ◽  
European Ancestry ◽  
Polygenic Risk Score ◽  
Middle Adulthood ◽  
Polygenic Risk ◽  
Increased Risk ◽  
Indirect Association

Background: Genetics and lifestyle behaviors are key contributors to obesity. However, few studies explicitly examine the differential genetic association with BMI across critical lifecycle periods between young adulthood and later adulthood. Hypothesis: We anticipate that genetic risk will be directly associated with BMI in young adulthood and there will be a strong indirect association with BMI later in life, as a result the increased risk of BMI associated with young adulthood. Methods: For 7,397 Chinese adult participants (age 18 to 65y) of the China Health and Nutrition Survey (CHNS; 1991-2015), we calculated an obesity polygenic risk score (PRS) based on BMI-related SNPs selected from the largest BMI GWAS in 700,000 individuals of European ancestry from UK biobank and GIANT consortium, weighted by effect size estimated from the GWAS study. We used linear mixed models to estimate BMI across all periods of adulthood, adjusting for calendar time and sex. In a subsample of participants with three measurements across 24 years (n=1220), we used pathway based analysis to estimate the direct effects of genetic risk in association with BMI during young (18-35y), middle (35-45y), and later (45-65y) adulthood as well as the indirect genetic effects of at later adulthood through BMI at each of these earlier periods in life. Results: In the full sample, the linear mixed model-adjusted mean BMI (Standard Error (SE)) was 22.4 (0.04) kg/m 2 at young adulthood, 23.1 (0.04) kg/m 2 at middle adulthood and 23.2 (0.04) kg/m 2 at later adulthood, adjusting for sex and calendar year. In the subsample, a one standard deviation higher obesity PRS was directly associated with a 0.38 (0.07 SE) and 0.21 (0.06 SE) kg/m 2 higher BMI in young and middle adulthood, respectively. We found no evidence of a direct estimated effect of PRS in later adulthood (age 45-64y), but evidence of an indirect association between obesity PRS and BMI in later adulthood (age 45-64y). For example, we found a one standard deviation higher PRS was indirectly associated with 0.31 (0.06 SE) kg/m 2 higher BMI at age 35-45y through BMI at age 18-35y, and a 0.25 (0.05 SE) kg/m 2 higher BMI at age 45-65y through BMI at age 18-35y and subsequently BMI at age 35-45y. Conclusion: We observed a strong direct association between polygenic risk for obesity in young adulthood (age 18-35y), with persistence through age 35-45y and into age 45-65y.

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 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.

scholarly journals Genetic risk, incident stroke, and the benefits of adhering to a healthy lifestyle: cohort study of 306 473 UK Biobank participants

BMJ ◽  
2018 ◽  
pp. k4168 ◽  
Author(s):  
Loes CA Rutten-Jacobs ◽  
Susanna C Larsson ◽  
Rainer Malik ◽  
Kristiina Rannikmäe ◽  
Cathie L Sudlow ◽  
...  
Keyword(s):  
Cohort Study ◽  
Risk Score ◽  
Genetic Risk ◽  
Cox Regression ◽  
Healthy Lifestyle ◽  
Lifestyle Factors ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Increased Risk

AbstractObjectiveTo evaluate the associations of a polygenic risk score and healthy lifestyle with incident stroke.DesignProspective population based cohort study.SettingUK Biobank Study, UK.Participants306 473 men and women, aged 40-73 years, recruited between 2006 and 2010.Main outcome measureHazard ratios for a first stroke, estimated using Cox regression. A polygenic risk score of 90 single nucleotide polymorphisms previously associated with stroke was constructed at P<1×10−5to test for an association with incident stroke. Adherence to a healthy lifestyle was determined on the basis of four factors: non-smoker, healthy diet, body mass index <30 kg/m2, and regular physical exercise.ResultsDuring a median follow-up of 7.1 years (2 138 443 person years), 2077 incident strokes (1541 ischaemic stroke, 287 intracerebral haemorrhage, and 249 subarachnoid haemorrhage) were ascertained. The risk of incident stroke was 35% higher among those at high genetic risk (top third of polygenic score) compared with those at low genetic risk (bottom third): hazard ratio 1.35 (95% confidence interval 1.21 to 1.50), P=3.9×10−8. Unfavourable lifestyle (0 or 1 healthy lifestyle factors) was associated with a 66% increased risk of stroke compared with a favourable lifestyle (3 or 4 healthy lifestyle factors): 1.66 (1.45 to 1.89), P=1.19×10−13. The association with lifestyle was independent of genetic risk stratums.ConclusionIn this cohort study, genetic and lifestyle factors were independently associated with incident stroke. These results emphasise the benefit of entire populations adhering to a healthy lifestyle, independent of genetic risk.

Puberty and depression: the roles of age, pubertal status and pubertal timing

1998 ◽  
Vol 28 (1) ◽  
pp. 51-61 ◽  
Author(s):  
A. ANGOLD ◽  
E. J. COSTELLO ◽  
C. M. WORTHMAN
Keyword(s):  
Sex Ratio ◽  
Depressive Disorders ◽  
Tanner Stage ◽  
Stage Iii ◽  
Pubertal Stage ◽  
Female Ratio ◽  
Pubertal Status ◽  
Increased Risk ◽  
Prevalence Of Depression ◽  
Risk For Depression

Background. Previous work has indicated that the 2[ratio ]1 female[ratio ]male sex ratio in unipolar depressive disorders does not emerge until some time between ages 10 and 15.Methods. Data from four annual waves of data collection from the Great Smoky Mountains Study (GSMS) involving children aged nine to 16 were employed.Results. Pubertal status better predicted the emergence of the expected sex ratio than did age. Only after the transition to mid-puberty (Tanner Stage III and above) were girls more likely than boys to be depressed. The timing of this transition had no effect on depression rates. Before Tanner Stage III, boys had higher rates of depression than girls, and the prevalence of depression appeared to fall in boys at an earlier pubertal stage than that at which it began to rise in girls. In addition, recent transition to Tanner Stage III or higher had a transient effect in reducing the prevalence of depression in boys.Conclusions. The period of emergence of increased risk for depression in adolescent girls appears to be a relatively sharply demarcated developmental transition occurring in mid-puberty. Previously reported effects of the timing of puberty (which have tended to be transient) appeared less important in increase of risk for depression than pubertal status.

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