scholarly journals Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization

2021 ◽  
Author(s):  
Zhiqiang Sha ◽  
Dick Schijven ◽  
Clyde Francks
Keyword(s):  
Sex Differences ◽  
Executive Functions ◽  
Autism Spectrum ◽  
Brain Asymmetry ◽  
Risk Scores ◽  
Imaging Data ◽  
Polygenic Risk ◽  
Left Right Asymmetry ◽  
The Uk ◽  
The Brain

AbstractAutism spectrum disorder (ASD) and schizophrenia have been conceived as partly opposing disorders in terms of systemizing versus empathizing cognitive styles, with resemblances to male versus female average sex differences. Left-right asymmetry of the brain is an important aspect of its organization that shows average differences between the sexes, and can be altered in both ASD and schizophrenia. Here we mapped multivariate associations of polygenic risk scores (PRS) for ASD and schizophrenia with asymmetries of regional cerebral cortical surface area, thickness and subcortical volume measures in 32,256 participants from the UK Biobank. PRS for the two disorders were positively correlated (r=0.08, p=7.13×10−50), and both were higher in females compared to males, consistent with biased participation against higher-risk males. Each PRS was associated with multivariate brain asymmetry after adjusting for sex, ASD PRS r=0.03, p=2.17×10−9, schizophrenia PRS r=0.04, p=2.61×10−11, but the multivariate patterns were mostly distinct for the two PRS, and neither resembled average sex differences. Annotation based on meta-analyzed functional imaging data showed that both PRS were associated with asymmetries of regions important for language and executive functions, consistent with behavioural associations that arose in phenome-wide association analysis. Overall, the results indicate that distinct patterns of subtly altered brain asymmetry may be functionally relevant manifestations of polygenic risk for ASD and schizophrenia, but do not support brain masculinization or feminization in their etiologies.

scholarly journals Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization

2021 ◽  
Author(s):  
Zhiqiang Sha ◽  
Dick Schijven ◽  
Clyde Francks
Keyword(s):  
Sex Differences ◽  
Executive Functions ◽  
Autism Spectrum ◽  
Brain Asymmetry ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Imaging Data ◽  
Polygenic Risk ◽  
Left Right Asymmetry ◽  
The Uk

AbstractAutism spectrum disorder (ASD) and schizophrenia have been conceived as partly opposing disorders in terms of systemizing vs. empathizing cognitive styles, with resemblances to male vs. female average sex differences. Left–right asymmetry of the brain is an important aspect of its organization that shows average differences between the sexes and can be altered in both ASD and schizophrenia. Here we mapped multivariate associations of polygenic risk scores for ASD and schizophrenia with asymmetries of regional cerebral cortical surface area, thickness, and subcortical volume measures in 32,256 participants from the UK Biobank. Polygenic risks for the two disorders were positively correlated (r = 0.08, p = 7.13 × 10−50) and both were higher in females compared to males, consistent with biased participation against higher-risk males. Each polygenic risk score was associated with multivariate brain asymmetry after adjusting for sex, ASD r = 0.03, p = 2.17 × 10−9, and schizophrenia r = 0.04, p = 2.61 × 10−11, but the multivariate patterns were mostly distinct for the two polygenic risks and neither resembled average sex differences. Annotation based on meta-analyzed functional imaging data showed that both polygenic risks were associated with asymmetries of regions important for language and executive functions, consistent with behavioral associations that arose in phenome-wide association analysis. Overall, the results indicate that distinct patterns of subtly altered brain asymmetry may be functionally relevant manifestations of polygenic risks for ASD and schizophrenia, but do not support brain masculinization or feminization in their etiologies.

scholarly journals The genetic architecture of structural left–right asymmetry of the human brain

2021 ◽  
Author(s):  
Zhiqiang Sha ◽  
Dick Schijven ◽  
Amaia Carrion-Castillo ◽  
Marc Joliot ◽  
Bernard Mazoyer ◽  
...  
Keyword(s):  
Brain Asymmetry ◽  
Functional Enrichment ◽  
Brain Organization ◽  
Genome Wide ◽  
Brain Expression ◽  
Using Data ◽  
Left Right Asymmetry ◽  
The Uk ◽  
Subcortical Volume

AbstractLeft–right hemispheric asymmetry is an important aspect of healthy brain organization for many functions including language, and it can be altered in cognitive and psychiatric disorders. No mechanism has yet been identified for establishing the human brain’s left–right axis. We performed multivariate genome-wide association scanning of cortical regional surface area and thickness asymmetries, and subcortical volume asymmetries, using data from 32,256 participants from the UK Biobank. There were 21 significant loci associated with different aspects of brain asymmetry, with functional enrichment involving microtubule-related genes and embryonic brain expression. These findings are consistent with a known role of the cytoskeleton in left–right axis determination in other organs of invertebrates and frogs. Genetic variants associated with brain asymmetry overlapped with those associated with autism, educational attainment and schizophrenia. Comparably large datasets will likely be required in future studies, to replicate and further clarify the associations of microtubule-related genes with variation in brain asymmetry, behavioural and psychiatric traits.

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.

Abstract P256: Genetic Determinants Of Blood Pressure Associate With Apparent Treatment Resistant Hypertension

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Joseph H Breeyear ◽  
Megan M Shuey ◽  
Todd L Edwards ◽  
Jacklyn Hellwege
Keyword(s):  
Blood Pressure ◽  
Risk Scores ◽  
Uncontrolled Hypertension ◽  
Polygenic Risk Score ◽  
Genetic Determinants ◽  
Treatment Resistant ◽  
Polygenic Risk ◽  
Blood Pressures ◽  
The Uk ◽  
Hispanic White

Hypertension is estimated to affect more than 49.6% of US adults 20 years and older. Of those individuals with hypertension, more than ten million are classified as apparent treatment resistant hypertensive (aTRH). The attributable risk of uncontrolled hypertension was estimated to be 49% for cardiovascular disease and 62% for stroke. We developed a polygenic risk score (PRS) for systolic (SBP) and diastolic (DBP) blood pressure to examine the association between the genetic determinants of blood pressure and aTRH with the goal of identifying high risk individuals. The meta-analyzed transethnic results of Giri et al., Biobank Japan, and Liang et al. were used to generate a PRS with PRS-CS followed by p -value thresholding, and validation in the UK Biobank (n max =341,930). Associations were modeled with logistic regression adjusted for age, age-squared, BMI, sex, and ten principal components of ancestry in BioVU’s transethnic population (n max =37,978), as well as non-Hispanic Black (n max =5,026) and non-Hispanic White (n max =28,545) subsets. The SBP PRS was significantly associated with an increased aTRH risk in the non-Hispanic White subset (1.08 (1.04 - 1.12), p = 0.00037) and transethnic (1.08 (1.04 - 1.13), p = 0.00020) populations, but not the non-Hispanic Black subset. The DBP PRS was not associated with aTRH in any population. Our findings present evidence that individuals with a higher genetic predisposition towards hypertension are at higher risk of aTRH. By integrating polygenic risk scores and clinical covariates in prediction of aTRH, individuals’ therapeutic regimens may be tailored to help maintain stable blood pressures, therefore reducing their risk of comorbidities.

scholarly journals Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003782
Author(s):  
Michael Wainberg ◽  
Samuel E. Jones ◽  
Lindsay Melhuish Beaupre ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Risk Scores ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Major Depressive ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

scholarly journals An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

2018 ◽  
Author(s):  
Tom G. Richardson ◽  
Sean Harrison ◽  
Gibran Hemani ◽  
George Davey Smith
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Polygenic Risk ◽  
The Uk

AbstractThe age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5×l0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

scholarly journals Using Connectivity to Explain Autism

2019 ◽  
Author(s):  
Jack Adamek ◽  
Yu Luo ◽  
Joshua Ewen
Keyword(s):  
Scientific Explanation ◽  
Causal Explanation ◽  
Autism Spectrum ◽  
Imaging Method ◽  
Imaging Data ◽  
Reverse Engineer ◽  
Physiological Processes ◽  
The Mind ◽  
The Brain

The chapters in this Handbook reveal the breadth of brilliant imaging and analysis techniques designed to fulfill the mandate of cognitive neuroscience: to understand how anatomical structures and physiological processes in the brain cause typical and atypical behavior. Yet merely producing data from the latest imaging method is insufficient to truly achieve this goal. We also need a mental toolbox that contains methods of inference that allow us to derive true scientific explanation from these data. Causal inference is not easy in the human brain, where we are limited primarily to observational data and our methods of experimental perturbation in the service of causal explanation are limited. As a case study, we reverse engineer one of the most influential accounts of a neuropsychiatric disorder that is derived from observational imaging data: the connectivity theories of autism spectrum disorder (ASD). We take readers through an approach of first considering all possible causal paths that are allowed by preliminary imaging-behavioral correlations. By progressively sharpening the specificity of the measures and brain/behavioral constructs, we iteratively chip away at this space of allowable causal paths, like the sculptor chipping away the excess marble to reveal the statue. To assist in this process, we consider how current imaging methods that are lumped together under the rubric of “connectivity” may actually offer a differentiated set of connectivity constructs that can more specifically relate notions of information transmission in the mind to the physiology of the brain.

scholarly journals Neural correlates of polygenic risk score for autism spectrum disorders in general population

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Budhachandra Khundrakpam ◽  
Uku Vainik ◽  
Jinnan Gong ◽  
Noor Al-Sharif ◽  
Neha Bhutani ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
White Matter ◽  
General Population ◽  
Cortical Thickness ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Cortical Regions ◽  
White Matter Connectivity

Abstract Autism spectrum disorder is a highly prevalent and highly heritable neurodevelopmental condition, but studies have mostly taken traditional categorical diagnosis approach (yes/no for autism spectrum disorder). In contrast, an emerging notion suggests a continuum model of autism spectrum disorder with a normal distribution of autistic tendencies in the general population, where a full diagnosis is at the severe tail of the distribution. We set out to investigate such a viewpoint by investigating the interaction of polygenic risk scores for autism spectrum disorder and Age2 on neuroimaging measures (cortical thickness and white matter connectivity) in a general population (n = 391, with age ranging from 3 to 21 years from the Pediatric Imaging, Neurocognition and Genetics study). We observed that children with higher polygenic risk for autism spectrum disorder exhibited greater cortical thickness for a large age span starting from 3 years up to ∼14 years in several cortical regions localized in bilateral precentral gyri and the left hemispheric postcentral gyrus and precuneus. In an independent case–control dataset from the Autism Brain Imaging Data Exchange (n = 560), we observed a similar pattern: children with autism spectrum disorder exhibited greater cortical thickness starting from 6 years onwards till ∼14 years in wide-spread cortical regions including (the ones identified using the general population). We also observed statistically significant regional overlap between the two maps, suggesting that some of the cortical abnormalities associated with autism spectrum disorder overlapped with brain changes associated with genetic vulnerability for autism spectrum disorder in healthy individuals. Lastly, we observed that white matter connectivity between the frontal and parietal regions showed significant association with polygenic risk for autism spectrum disorder, indicating that not only the brain structure, but the white matter connectivity might also show a predisposition for the risk of autism spectrum disorder. Our findings showed that the fronto-parietal thickness and connectivity are dimensionally related to genetic risk for autism spectrum disorder in general population and are also part of the cortical abnormalities associated with autism spectrum disorder. This highlights the necessity of considering continuum models in studying the aetiology of autism spectrum disorder using polygenic risk scores and multimodal neuroimaging.

scholarly journals Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb

PLoS Genetics ◽  
2019 ◽  
Vol 15 (6) ◽  
pp. e1008202 ◽  
Author(s):  
Lars G. Fritsche ◽  
Lauren J. Beesley ◽  
Peter VandeHaar ◽  
Robert B. Peng ◽  
Maxwell Salvatore ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Risk Scores ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
The Uk

Sex Differences Shape Brain Development and Function, in Health and Disease: Policy Implications

2017 ◽  
Vol 5 (1) ◽  
pp. 104-109 ◽  
Author(s):  
Staci D. Bilbo
Keyword(s):  
Sex Differences ◽  
Autism Spectrum ◽  
Policy Implications ◽  
Female Ratio ◽  
Brain Sciences ◽  
Health And Disease ◽  
Fundamental Research ◽  
And Function ◽  
Sex Disparity ◽  
The Brain

Sex differences profoundly impact health and disease. Despite this, the inclusion of females in clinical and fundamental research lags far behind advances in other aspects of medicine, especially in the brain sciences. Regardless of whether neuroscientists are intrinsically interested in sex differences per se, observing a sex disparity in the incidence or presentation of a given neurological disorder provides a significant clue into the neurobiology of that disorder. Autism spectrum disorder (ASD) is one of the most sex-biased disorders, with a 4:1 male-to-female ratio, an important aspect of its etiology and biology that has largely been ignored in the preclinical literature. This article briefly overviews what is known about the sexual differentiation of the developing healthy brain, with a focus on the preclinical literature. This places observed sex differences in neurological disorders such as ASD into the context of known sex differences in neurobiology—along with insight from known sex-specific mechanisms in other systems that impact the brain (e.g., immune system, microbiome). Finally, the article provides recommendations for progress forward.

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