scholarly journals Polygenic risk for ADHD and ASD and their relation with cognitive measures in school children

2020 ◽  
pp. 1-9
Author(s):  
Sofía Aguilar-Lacasaña ◽  
Natàlia Vilor-Tejedor ◽  
Philip R. Jansen ◽  
Mònica López-Vicente ◽  
Mariona Bustamante ◽  
...  
Keyword(s):  
Multiple Testing ◽  
Autism Spectrum ◽  
Developmental Trajectory ◽  
Risk Scores ◽  
Cognitive Measures ◽  
Multiple Testing Correction ◽  
Polygenic Risk ◽  
Common Genetic Variants ◽  
Attention Performance ◽  
Over Time

Abstract Background Attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are child-onset neurodevelopmental disorders frequently accompanied by cognitive difficulties. In the current study, we aim to examine the genetic overlap between ADHD and ASD and cognitive measures of working memory (WM) and attention performance among schoolchildren using a polygenic risk approach. Methods A total of 1667 children from a population-based cohort aged 7–11 years with data available on genetics and cognition were included in the analyses. Polygenic risk scores (PRS) were calculated for ADHD and ASD using results from the largest GWAS to date (N = 55 374 and N = 46 351, respectively). The cognitive outcomes included verbal and numerical WM and the standard error of hit reaction time (HRTSE) as a measure of attention performance. These outcomes were repeatedly assessed over 1-year period using computerized version of the Attention Network Test and n-back task. Associations were estimated using linear mixed-effects models. Results Higher polygenic risk for ADHD was associated with lower WM performance at baseline time but not over time. These findings remained significant after adjusting by multiple testing and excluding individuals with an ADHD diagnosis but were limited to boys. PRS for ASD was only nominally associated with an increased improvement on verbal WM over time, although this association did not survive multiple testing correction. No associations were observed for HRTSE. Conclusions Common genetic variants related to ADHD may contribute to worse WM performance among schoolchildren from the general population but not to the subsequent cognitive-developmental trajectory assessed over 1-year period.

scholarly journals Pathway-based polygene risk for severe depression implicates drug metabolism in CONVERGE

2019 ◽  
Vol 50 (5) ◽  
pp. 793-798
Author(s):  
Anna R. Docherty ◽  
Arden Moscati ◽  
Tim B. Bigdeli ◽  
Alexis C. Edwards ◽  
Roseann E. Peterson ◽  
...  
Keyword(s):  
Drug Metabolism ◽  
Drug Targets ◽  
Multiple Testing ◽  
Age At Onset ◽  
Severe Depression ◽  
Risk Scores ◽  
Future Research ◽  
Recurrent Depression ◽  
Multiple Testing Correction ◽  
Polygenic Risk

AbstractBackgroundThe Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic. Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways (MPs) proved successful in treating MDD. It is possible that examining polygenicity within specific MPs implicated in MDD can further refine molecular drug targets.MethodsUsing a large case–control GWAS based on low-coverage whole genome sequencing (N = 10 640) in Han Chinese women, we derived polygenic risk scores (PRS) for MDD and for MDD specific to each of over 300 MPs previously shown to be relevant to psychiatric diagnoses. We then identified sets of PRSs, accounting for critical covariates, significantly predictive of case status.ResultsOver and above global MDD polygenic risk, polygenic risk within the GO: 0017144 drug metabolism pathway significantly predicted recurrent depression after multiple testing correction. Secondary transcriptomic analysis suggests that among genes in this pathway, CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1) might be most relevant to MDD. Within the cases, pathway-based risk was additionally associated with age at onset of MDD.ConclusionsResults indicate that pathway-based risk might inform etiology of recurrent major depression. Future research should examine whether polygenicity of the drug metabolism gene pathway has any association with clinical presentation or treatment response. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.

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 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 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 Autism spectrum disorder diagnosis in adults: phenotype and genotype findings from a clinically derived cohort

2019 ◽  
Vol 215 (5) ◽  
pp. 647-653 ◽  
Author(s):  
Jack F. G. Underwood ◽  
Kimberley M. Kendall ◽  
Jennifer Berrett ◽  
Catrin Lewis ◽  
Richard Anney ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Social History ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Self Report ◽  
Risk Scores ◽  
Rare Cnvs ◽  
Patient Counselling ◽  
Genetic Characteristics ◽  
Common Genetic Variants

BackgroundThe past decade has seen the development of services for adults presenting with symptoms of autism spectrum disorder (ASD) in the UK. Compared with children, little is known about the phenotypic and genetic characteristics of these patients.AimsThis e-cohort study aimed to examine the phenotypic and genetic characteristics of a clinically presenting sample of adults diagnosed with ASD by specialist services.MethodIndividuals diagnosed with ASD as adults were recruited by the National Centre for Mental Health and completed self-report questionnaires, interviews and provided DNA; 105 eligible individuals were matched to 76 healthy controls. We investigated demographics, social history and comorbid psychiatric and physical disorders. Samples were genotyped, copy number variants (CNVs) were called and polygenic risk scores were calculated.ResultsOf individuals with ASD, 89.5% had at least one comorbid psychiatric diagnosis, with depression (62.9%) and anxiety (55.2%) being the most common. The ASD group experienced more neurological comorbidities than controls, particularly migraine headache. They were less likely to have married or be in work, and had more alcohol-related problems. There was a significantly higher load of autism common genetic variants in the adult ASD group compared with controls, but there was no difference in the rate of rare CNVs.ConclusionsThis study provides important information about psychiatric comorbidity in adult ASD, which may inform clinical practice and patient counselling. It also suggests that the polygenic load of common ASD-associated variants may be important in conferring risk within the non-intellectually disabled population of adults with ASD.Declaration of interestNone.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals ASD Diagnosis in Adults: Phenotype and Genotype Findings from a Clinically-derived Cohort

2018 ◽  
Author(s):  
Underwood Jack F G ◽  
Kendall Kimberley M ◽  
Berrett Jennifer ◽  
Anney Richard ◽  
Van den Bree Marianne B.M. ◽  
...  
Keyword(s):  
Social History ◽  
Copy Number Variants ◽  
Autism Spectrum ◽  
Self Report ◽  
Risk Scores ◽  
Healthy Controls ◽  
Rare Cnvs ◽  
Patient Counselling ◽  
Genetic Characteristics ◽  
Common Genetic Variants

AbstractBackgroundThe last decade has seen the development of services for adults presenting with symptoms of autism spectrum disorder (ASD) in the UK. Compared to children, little is known about the phenotypic and genetic characteristics of these patients.AimsThis e-cohort study aimed to examine the phenotypic and genetic characteristics of a clinically-presenting sample of adults diagnosed with ASD by specialist services.MethodsIndividuals diagnosed with ASD as adults were recruited by the National Centre for Mental Health and completed self-report questionnaires, interviews and provided DNA. 105 eligible individuals were matched to 76 healthy controls. We investigated the demographics, social history, comorbid psychiatric and physical disorders. Samples were genotyped, copy number variants (CNVs) were called and polygenic risk scores calculated.Results89.5% of individuals with ASD had at least one comorbid psychiatric diagnosis with comorbid depression (62.9%) and anxiety (55.2%) the most common. The ASD group experienced more neurological comorbidities than healthy controls, particularly migraine headache. They were less likely to have married or be in work and had more alcohol-related problems. There was a significantly higher load of autism common genetic variants in the adult ASD group compared to controls, but there was no difference in the rate of rare CNVs.ConclusionsThis study provides important information about psychiatric comorbidity in adult ASD which may be used to inform clinical practice and patient counselling. It also suggests that the polygenic load of common ASD-associated variants may be important in conferring risk within non-intellectually disabled population of adults with ASD.

scholarly journals Gamete simulation improves polygenic transmission disequilibrium analysis

2020 ◽  
Author(s):  
Jiawen Chen ◽  
Jing You ◽  
Zijie Zhao ◽  
Zheng Ni ◽  
Kunling Huang ◽  
...  
Keyword(s):  
Complex Traits ◽  
Statistical Power ◽  
Association Studies ◽  
Autism Spectrum ◽  
Genetic Maps ◽  
Risk Scores ◽  
Parental Genotype ◽  
Genome Wide Association Studies ◽  
Transmission Disequilibrium ◽  
Polygenic Risk

AbstractPolygenic risk scores (PRS) derived from summary statistics of genome-wide association studies (GWAS) have enjoyed great popularity in human genetics research. Applied to population cohorts, PRS can effectively stratify individuals by risk group and has promising applications in early diagnosis and clinical intervention. However, our understanding of within-family polygenic risk is incomplete, in part because the small samples per family significantly limits power. Here, to address this challenge, we introduce ORIGAMI, a computational framework that uses parental genotype data to simulate offspring genomes. ORIGAMI uses state-of-the-art genetic maps to simulate realistic recombination events on phased parental genomes and allows quantifying the prospective PRS variability within each family. We quantify and showcase the substantially reduced yet highly heterogeneous PRS variation within families for numerous complex traits. Further, we incorporate within-family PRS variability to improve polygenic transmission disequilibrium test (pTDT). Through simulations, we demonstrate that modeling within-family risk substantially improves the statistical power of pTDT. Applied to 7,805 trios of autism spectrum disorder (ASD) probands and healthy parents, we successfully replicated previously reported over-transmission of ASD, educational attainment, and schizophrenia risk, and identified multiple novel traits with significant transmission disequilibrium. These results provided novel etiologic insights into the shared genetic basis of various complex traits and ASD.

scholarly journals Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases

Stroke ◽  
2021 ◽  
Author(s):  
Gad Abraham ◽  
Loes Rutten-Jacobs ◽  
Michael Inouye
Keyword(s):  
Risk Prediction ◽  
Risk Scores ◽  
Future Research ◽  
Cvd Risk ◽  
Polygenic Risk ◽  
Monogenic Disorders ◽  
Current State ◽  
Common Genetic Variants ◽  
Artery Disease

Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of disease prevention. Clinical risk scores have been widely used for predicting CVD risk from known risk factors. Most CVDs have a substantial genetic component, which also has been confirmed for stroke in recent gene discovery efforts. However, the role of genetics in prediction of risk of CVD, including stroke, has been limited to testing for highly penetrant monogenic disorders. In contrast, the importance of polygenic variation, the aggregated effect of many common genetic variants across the genome with individually small effects, has become more apparent in the last 5 to 10 years, and powerful polygenic risk scores for CVD have been developed. Here we review the current state of the field of polygenic risk scores for CVD including stroke, and their potential to improve CVD risk prediction. We present findings and lessons from diseases such as coronary artery disease as these will likely be useful to inform future research in stroke polygenic risk prediction.

scholarly journals Integration of rare large-effect expression variants improves polygenic risk prediction

2020 ◽  
Author(s):  
Craig Smail ◽  
Nicole M. Ferraro ◽  
Matthew G. Durrant ◽  
Abhiram S. Rao ◽  
Matthew Aguirre ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Rare Variants ◽  
Complex Trait ◽  
Risk Scores ◽  
Multiple Traits ◽  
Polygenic Risk ◽  
Common Genetic Variants ◽  
Using Data ◽  
The Uk ◽  
The Impact

SummaryPolygenic risk scores (PRS) aim to quantify the contribution of multiple genetic loci to an individual’s likelihood of a complex trait or disease. However, existing PRS estimate genetic liability using common genetic variants, excluding the impact of rare variants. We identified rare, large-effect variants in individuals with outlier gene expression from the GTEx project and then assessed their impact on PRS predictions in the UK Biobank (UKB). We observed large deviations from the PRS-predicted phenotypes for carriers of multiple outlier rare variants; for example, individuals classified as “low-risk” but in the top 1% of outlier rare variant burden had a 6-fold higher rate of severe obesity. We replicated these findings using data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) biobank and the Million Veteran Program, and demonstrated that PRS across multiple traits will significantly benefit from the inclusion of rare genetic variants.

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