scholarly journals Polygenic profiles define aspects of clinical heterogeneity in ADHD

2021 ◽  
Author(s):  
Andrew Schork ◽  
Sonja LaBianca ◽  
Isabell Brickell ◽  
Dorte Helenius ◽  
Robert Loughnan ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Clinical Heterogeneity ◽  
Behavioral Traits ◽  
Complex Disorder ◽  
Novel Approach ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Significant Locus ◽  
Unique Approach ◽  
Genetic Contributions

Abstract Attention deficit hyperactivity disorder (ADHD) is a complex disorder with heterogeneous clinical presentations that manifest variability in long-term outcomes. The genetic contributions to this clinical heterogeneity, however, are not well understood. Here, we study 14 084 individuals diagnosed with ADHD to identify several genetic factors underlying clinical heterogeneity. One genome-wide significant locus was specifically associated with an autism spectrum disorder (ASD) diagnosis among individuals diagnosed with ADHD and it was not previously associated with ASD nor ADHD, individually. We used a novel approach to compare profiles of polygenic scores for groups of individuals diagnosed with ADHD and uncovered robust evidence that biology is an important factor in on-going clinical debates. Specifically, individuals diagnosed with ASD and ADHD, substance use disorder (SUD) and ADHD, or first diagnosed with ADHD in adulthood had different profiles of polygenic scores for ADHD and multiple other psychiatric, cognitive, and socio-behavioral traits. A polygene overlap between an ASD diagnosis in ADHD and cognitive performance was replicated in an independent, typically developing cohort. Our unique approach uncovered evidence of genetic heterogeneity in a widely studied complex disorder, allowing for timely contributions to the understanding of ADHD etiology and providing a model for similar studies of other disorders.

scholarly journals Polygenic profiles define aspects of clinical heterogeneity in ADHD

2021 ◽  
Author(s):  
Sonja LaBianca ◽  
Isabell Brikell ◽  
Dorte Helenius ◽  
Robert John Loughnan ◽  
Joel Mefford ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Clinical Heterogeneity ◽  
Behavioral Traits ◽  
Complex Disorder ◽  
Novel Approach ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Significant Locus ◽  
Unique Approach ◽  
Genetic Contributions

Attention deficit hyperactivity disorder (ADHD) is a complex disorder with heterogeneous clinical presentations that manifest variability in long-term outcomes. The genetic contributions to this clinical heterogeneity, however, are not well understood. Here, we study 14 084 individuals diagnosed with ADHD to identify several genetic factors underlying clinical heterogeneity. One genome-wide significant locus was specifically associated with an autism spectrum disorder (ASD) diagnosis among individuals diagnosed with ADHD and it was not previously associated with ASD nor ADHD, individually. We used a novel approach to compare profiles of polygenic scores for groups of individuals diagnosed with ADHD and uncovered robust evidence that biology is an important factor in on-going clinical debates. Specifically, individuals diagnosed with ASD and ADHD, substance use disorder (SUD) and ADHD, or first diagnosed with ADHD in adulthood had different profiles of polygenic scores for ADHD and multiple other psychiatric, cognitive, and socio-behavioral traits. A polygene overlap between an ASD diagnosis in ADHD and cognitive performance was replicated in an independent, typically developing cohort. Our unique approach uncovered evidence of genetic heterogeneity in a widely studied complex disorder, allowing for timely contributions to the understanding of ADHD etiology and providing a model for similar studies of other disorders.

scholarly journals Genome-wide Polygenic Scores for Multiple Psychiatric and Common Traits Identify Preadolescent Youth with Risk for Suicide

2021 ◽  
Author(s):  
Yoonjung Yoonie Joo ◽  
Seo-Yoon Moon ◽  
Hee-Hwan Wang ◽  
Hyeonjin Kim ◽  
Eun-Ji Lee ◽  
...  
Keyword(s):  
Machine Learning ◽  
Suicidal Ideation ◽  
Family Environment ◽  
Autism Spectrum ◽  
Cognitive Capacity ◽  
European Ancestry ◽  
Environment Interaction ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Preadolescent Youth

Abstract Importance. Suicide is the second leading cause of death in children worldwide but no available means exist to identify the risk in youth. Objective. To predict the risk of suicide in children and to investigate whether and to what extents genetic factors and a major environmental risk factor, early life stress(ELS), influence youth suicide. Design, Setting and Participants. We analyzed the genotype-phenotype data of 11,869 preadolescent children ages 9- to 10-year-old from the Adolescent Brain and Cognitive Development (ABCD) study. We estimated genome-wide polygenic scores (GPSs) of 25 complex traits to investigate their phenome-wide associations and predictive utility with suicidality (suicidal ideation and attempt) with machine learning approaches. Predictors. GPSs of 25 traits including psychiatric disorders, personality, cognitive capacity, and psychological traits. Parent Child Behavior Checklist to measure ELS in youth and Youth Family Environment Scale to assess family environment. Main outcomes and Measures. Records of suicidal ideation and attempt of the participants were derived from the computerized version of Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS). Results. We identified three GPSs associated with youth suicidality in multiethnic (n = 7,206) and European-ancestry (n = 5,749) participants: ADHD (P = 3.48x10− 4; odds ratio = 1.13 in multiethnic participants, P = 5.60x10− 5, OR = 1.25 in European-ancestry participants), general happiness (P = 1.43x10− 3; OR = 0.89 in multiethnic, P = 8.61x10− 4, OR = 0.89 in European) and autism spectrum disorder(ASD) (P = 1.81x10− 3; OR = 1.15 in multiethnic, P = 1.26x10− 3, OR = 1.18 in European). We also found a significant GPS-by-environment interaction between the effects of genetic risk factors for ASD and the level of ELS in increasing the risk for suicidal ideation (P = 1.36x10− 2, OR = 1.12 in multiethnic, P = 1.39x10− 3, OR = 1.19 in European). A machine learning model trained on the same data showed moderately accurate prediction of children with overall suicidal ideation with a test ROC-AUC of 0.727 (0.746 in European), and with suicidal attempts with a test ROC-AUC of 0.641 (0.975 in European) in held-out samples. Conclusions and Relevance. This study provides the first quantitative account of polygenic and environmental factors of suicidality in a large, representative population of preadolescent youth. It thus shows the potential utility of the GPSs in identifying a child with high risk for suicidality for early screening, intervention, and prevention.

Identification of a Novel Locus for Gait Speed Decline with Aging: The Long Life Family Study

2021 ◽  
Author(s):  
Adam J Santanasto ◽  
Mary K Wojczynski ◽  
Ryan K Cvejkus ◽  
Shiow Lin ◽  
Lihua Wang ◽  
...  
Keyword(s):  
Gait Speed ◽  
Family Study ◽  
Linkage Peak ◽  
Chromosome 16 ◽  
Association Analyses ◽  
Genome Wide ◽  
Maximum Likelihood Methods ◽  
Significant Locus ◽  
Long Life ◽  
Genetic Contributions

Abstract Background Gait speed is a powerful indicator of health with aging. Potential genetic contributions to gait speed and its decline with aging are not well defined. We determined the heritability of and potential genetic regions underlying change in gait speed using longitudinal data from 2379 individuals belonging to 509 families in the Long Life Family Study (mean age 64±12, range 30–110 years; 45% men). Methods Gait-speed was measured over 4 meters at baseline and follow up (7±1 years). Quantitative trait linkage analyses were completed using pedigree-based maximum-likelihood methods with logarithm of the odds (LOD) scores >3.0 indicating genome-wide significance. We also performed linkage analysis in the top 10% of families contributing to LOD scores to allow for heterogeneity among families (HLOD). Data were adjusted for age, sex, height, and field center. Results At baseline, 26.9% of individuals had “slow” gait-speed <1.0 m/s (mean: 1.1±0.2 m/s) and gait speed declined at a rate of -0.02±0.03 m/s per year (p<0.0001). Baseline and change in gait-speed were significantly heritable (h  2 = 0.24-0.32, p<0.05). We did not find significant evidence for linkage for baseline gait speed; however, we identified a significant locus for change in gait speed on chromosome 16p (LOD=4.2). A subset of 21 families contributed to this linkage peak (HLOD = 6.83). Association analyses on chromosome 16 showed that the strongest variant resides within the ADCY9 gene. Conclusion Further analysis of the chromosome 16 region, and ADCY9 gene, may yield new insight on the biology of mobility decline with aging.

scholarly journals Genetic Contributions to Health Literacy

2019 ◽  
Vol 22 (03) ◽  
pp. 131-139
Author(s):  
Chloe Fawns-Ritchie ◽  
Gail Davies ◽  
Saskia P. Hagenaars ◽  
Ian J. Deary
Keyword(s):  
Health Literacy ◽  
Cognitive Function ◽  
Genome Wide Association Study ◽  
Nucleotide Polymorphisms ◽  
Limited Health Literacy ◽  
Adequate Health Literacy ◽  
Genome Wide ◽  
A Genome ◽  
Polygenic Scores ◽  
Genetic Contributions

AbstractHigher health literacy is associated with higher cognitive function and better health. Despite its wide use in medical research, no study has investigated the genetic contributions to health literacy. Using 5783 English Longitudinal Study of Ageing (ELSA) participants (mean age = 65.49, SD = 9.55) who had genotyping data and had completed a health literacy test at wave 2 (2004–2005), we carried out a genome-wide association study (GWAS) of health literacy. We estimated the proportion of variance in health literacy explained by all common single nucleotide polymorphisms (SNPs). Polygenic profile scores were calculated using summary statistics from GWAS of 21 cognitive and health measures. Logistic regression was used to test whether polygenic scores for cognitive and health-related traits were associated with having adequate, compared to limited, health literacy. No SNPs achieved genome-wide significance for association with health literacy. The proportion of variance in health literacy accounted for by common SNPs was 8.5% (SE = 7.2%). Greater odds of having adequate health literacy were associated with a 1 standard deviation higher polygenic score for general cognitive ability [OR = 1.34, 95% CI (1.26, 1.42)], verbal-numerical reasoning [OR = 1.30, 95% CI (1.23, 1.39)], and years of schooling [OR = 1.29, 95% CI (1.21, 1.36)]. Reduced odds of having adequate health literacy were associated with higher polygenic profiles for poorer self-rated health [OR = 0.92, 95% CI (0.87, 0.98)] and schizophrenia [OR = 0.91, 95% CI (0.85, 0.96)). The well-documented associations between health literacy, cognitive function and health may partly be due to shared genetic etiology. Larger studies are required to obtain accurate estimates of SNP-based heritability and to discover specific health literacy-associated genetic variants.

scholarly journals Genome-wide association study of suicide death and polygenic prediction of clinical antecedents

2017 ◽  
Author(s):  
Anna R. Docherty ◽  
Andrey A. Shabalin ◽  
Emily DiBlasi ◽  
Eric Monson ◽  
Niamh Mullins ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Case Control ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Behavioral Disinhibition ◽  
Suicide Death ◽  
Polygenic Score ◽  
Death Case ◽  
Genome Wide ◽  
Polygenic Scores

ABSTRACTObjectiveSuicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort.MethodsThe analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression.ResultsGWAS identified two genome-wide significant loci (6 SNPs, p<5×10−8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder.ConclusionsIn this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.

scholarly journals Genome-wide Polygenic Scores for Multiple Psychiatric and Common Traits Identify Preadolescent Youth with Risk for Suicide

2020 ◽  
Author(s):  
Yoonjung Yoonie Joo ◽  
Seo-Yoon Moon ◽  
Hee-Hwan Wang ◽  
Hyeonjin Kim ◽  
Eun-Ji Lee ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Life Stress ◽  
Odds Ratio ◽  
Area Under The Curve ◽  
Autism Spectrum ◽  
Environment Interaction ◽  
Early Screening ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Preadolescent Youth

Abstract Suicide is a leading cause of death in youth worldwide, but identifying which youth are at high risk for suicide remains challenging. We constructed genome-wide polygenic scores (GPSs) from 24 psychiatric disorders and common traits from 8,212 US preadolescent children ages 9 to 10 and investigated their associations and predictive utility with suicidality (suicidal ideation and attempt). We identified three GPSs significantly associated with youth suicidality: ADHD (P=2.83x10-4; odds ratio=1.12), general happiness with a belief that life is meaningful (P=1.30x10-3; odds ratio=0.89) and autism spectrum disorder (ASD) (P=1.81x10-3; odds ratio=1.14). We also found a significant gene-by-environment interaction such that the GPS of ASD in the context of early life stress substantially increased suicidal ideation (P=1.39x10-2, odds ratio=1.11). Machine learning models showed, in predicting suicidal ideation, a receiver operators characteristics-area under the curve (ROC-AUC) of 0.72, and, in suicidal attempts, a ROC-AUC of 0.765. By providing the first quantitative account of the polygenic and environmental factors of suicidality in a large, representative population of preadolescent youth, this study shows the potential utility of the GPSs in investigating youth suicidality for early screening, intervention, and prevention.

scholarly journals Genetic Contributions To Health Literacy

2019 ◽  
Author(s):  
Chloe Fawns-Ritchie ◽  
Gail Davies ◽  
Saskia P Hagenaars ◽  
Ian J Deary
Keyword(s):  
Health Literacy ◽  
Cognitive Function ◽  
Genome Wide Association Study ◽  
Nucleotide Polymorphisms ◽  
Limited Health Literacy ◽  
Adequate Health Literacy ◽  
Genome Wide ◽  
A Genome ◽  
Polygenic Scores ◽  
Genetic Contributions

AbstractHigher health literacy is associated with higher cognitive function and better health. Despite its wide use in medical research, no study has investigated the genetic contributions to health literacy. Using 5,783 English Longitudinal Study of Ageing (ELSA) participants (mean age=65.49, SD=9.55) who had genotyping data and had completed a health literacy test at wave 2 (2004-2005), we carried out a genome-wide association study (GWAS) of health literacy. We estimated the proportion of variance in health literacy explained by all common single nucleotide polymorphisms (SNPs). Polygenic profile scores were calculated using summary statistics from GWAS of 21 cognitive and health measures. Logistic regression was used to test whether polygenic scores for cognitive and health-related traits were associated with having adequate, compared to limited, health literacy. No SNPs achieved genome-wide significance for association with health literacy. The proportion of variance in health literacy accounted for by common SNPs was 8.5% (SE=7.2%). Greater odds of having adequate health literacy were associated with a 1SD higher polygenic score for general cognitive ability (OR=1.34, 95% CI 1.26-1.42), verbal-numerical reasoning (OR=1.30, 1.23-1.39), and years of schooling (OR=1.29, 1.21-1.36). Reduced odds of having adequate health literacy were associated with higher polygenic profiles for poorer self-rated health (OR=0.92, 0.87-0.98) and schizophrenia (OR=0.91, 0.85-0.96). The well-documented associations between health literacy, cognitive function and health may partly be due to shared genetic aetiology. Larger studies are required to obtain accurate estimates of SNP-based heritability, and to discover specific health literacy-associated genetic variants.

scholarly journals Investigating genetic links between grapheme–colour synaesthesia and neuropsychiatric traits

2019 ◽  
Vol 374 (1787) ◽  
pp. 20190026 ◽  
Author(s):  
Amanda K. Tilot ◽  
Arianna Vino ◽  
Katerina S. Kucera ◽  
Duncan A. Carmichael ◽  
Loes van den Heuvel ◽  
...  
Keyword(s):  
Genetic Factors ◽  
Autism Spectrum ◽  
Negative Control ◽  
Genomic Variation ◽  
Sensory Sensitivity ◽  
Sensory Experiences ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Prior Literature ◽  
Family Based

Synaesthesia is a neurological phenomenon affecting perception, where triggering stimuli (e.g. letters and numbers) elicit unusual secondary sensory experiences (e.g. colours). Family-based studies point to a role for genetic factors in the development of this trait. However, the contributions of common genomic variation to synaesthesia have not yet been investigated. Here, we present the SynGenes cohort, the largest genotyped collection of unrelated people with grapheme–colour synaesthesia ( n = 723). Synaesthesia has been associated with a range of other neuropsychological traits, including enhanced memory and mental imagery, as well as greater sensory sensitivity. Motivated by the prior literature on putative trait overlaps, we investigated polygenic scores derived from published genome-wide scans of schizophrenia and autism spectrum disorder (ASD), comparing our SynGenes cohort to 2181 non-synaesthetic controls. We found a very slight association between schizophrenia polygenic scores and synaesthesia (Nagelkerke's R 2 = 0.0047, empirical p = 0.0027) and no significant association for scores related to ASD (Nagelkerke's R 2 = 0.00092, empirical p = 0.54) or body mass index ( R 2 = 0.00058, empirical p = 0.60), included as a negative control. As sample sizes for studying common genomic variation continue to increase, genetic investigations of the kind reported here may yield novel insights into the shared biology between synaesthesia and other traits, to complement findings from neuropsychology and brain imaging. This article is part of a discussion meeting issue ‘Bridging senses: novel insights from synaesthesia'.

scholarly journals Association between polygenic propensity for psychiatric disorders and nutrient intake

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Avina K. Hunjan ◽  
Christopher Hübel ◽  
Yuhao Lin ◽  
Thalia C. Eley ◽  
Gerome Breen
Keyword(s):  
Psychiatric Disorders ◽  
Nutrient Intake ◽  
Autism Spectrum ◽  
Dietary Behaviour ◽  
Obsessive Compulsive ◽  
Higher Alcohol ◽  
Polygenic Score ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
Polygenic Scores

AbstractDespite the observed associations between psychiatric disorders and nutrient intake, genetic studies are limited. We examined whether polygenic scores for psychiatric disorders are associated with nutrient intake in UK Biobank (N = 163,619) using linear mixed models. We found polygenic scores for attention-deficit/hyperactivity disorder, bipolar disorder, and schizophrenia showed the highest number of associations, while a polygenic score for autism spectrum disorder showed no association. The relatively weaker obsessive-compulsive disorder polygenic score showed the greatest effect sizes suggesting its association with diet traits may become more apparent with larger genome-wide analyses. A higher alcohol dependence polygenic score was associated with higher alcohol intake and individuals with higher persistent thinness polygenic scores reported their food to weigh less, both independent of socioeconomic status. Our findings suggest that polygenic propensity for a psychiatric disorder is associated with dietary behaviour. Note, nutrient intake was self-reported and findings must therefore be interpreted mindfully.

scholarly journals Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores

2019 ◽  
Author(s):  
Sam Trejo ◽  
Benjamin W. Domingue
Keyword(s):  
Fixed Effects ◽  
Regression Models ◽  
Genome Wide Association Study ◽  
Causal Effect ◽  
Genetic Effects ◽  
Summary Statistics ◽  
Behavioral Traits ◽  
Genome Wide ◽  
A Genome ◽  
Polygenic Scores

AbstractSummary statistics from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS). For complex, behavioral traits, the correlation between an individual’s PGS and their phenotype may contain bias alongside the causal effect of the individual’s genes (due to geographic, ancestral, and/or socioeconomic confounding). We formalize the recent introduction of a different source of bias in regression models using PGSs: the effects of parental genes on offspring outcomes, also known as genetic nurture. GWAS do not discriminate between the various pathways through which genes influence outcomes, meaning existing PGSs capture both direct genetic effects and genetic nurture effects. We construct a theoretical model for genetic effects and show that, unlike other sources of bias in PGSs, the presence of genetic nurture biases PGS coefficients from both naïve OLS (between-family) and family fixed effects (within-family) regressions. This bias is in opposite directions; while naïve OLS estimates are biased upwards, family fixed effects estimates are biased downwards. We quantify this bias for a given trait using two novel parameters that we identify and discuss: (1) the genetic correlation between the direct and nurture effects and (2) the ratio of the SNP heritabilities for the direct and nurture effects.

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