Cognitive Capacity Genome-wide Polygenic Scores Identify Individuals Resilient to Cognitive Decline in Aging

Abstract The genetic underpinnings of cognitive resilience in aging remains unknown. Predicting an individual’s rate of cognitive decline—or cognitive resilience—using genetics will allow personalized intervention for cognitive enhancement and optimal selection of target samples in clinical trials. Here, using genome-wide polygenic scores(GPS) of cognitive capacity as the genomic indicators for variations of human intelligence, we examined the genetic liability of cognitive abilities in the behavioral/cognitive phenome to understand individual phenotypic differences over time. We analyzed the 18-year records of the cross-sectional and longitudinal sociogenomic data of 8,511 European-ancestry adults from the Wisconsin Longitudinal Study (WLS), especially focusing on the cognitive assessments that were repeatedly administered to the participants at their average ages of 64.5 and 71.5. Our linear mixed-effects model identified a significant interaction effect between age and cognitive capacity GPS, which indicates that a higher cognitive capacity GPS significantly correlates with a slower cognitive decline in the domain of immediate memory recall (p-value = 1.79E-03, β = 1.86E-01). Also, the phenome-wide analysis identified several significant associations of cognitive capacity GPSs on the cognitive and behavioral phenome, such as Similarities task (p-value = 3.59E-74, β = 1.36, 95% CI=(1.22, 1.51)), Number Series task(p-value = 2.55E-78, β = 0.94, 95% CI=(0.85, 1.04)), IQ scores(p-value = 7.74E-179, β = 1.42, 95% CI=(1.32, 1.51)), high school class rank (p-value = 3.07E-101, β = 1.86, 95% CI=(1.69, 2.02), Openness from the BIG 5 personality factor(p-value = 2.19E-14, β = 0.57, 95% CI=(0.42, 0.71)), and social participation of reading books (p-value = 2.03E-21, β = 0.50, 95% CI=(0.40, 0.60)), attending cultural events, such as concerts, plays or museums (p-value = 2.06E-23, β = 0.60, 95% CI=(0.49, 0.72)), and watching TV (p-value = 4.16E-18, β=-0.48, 95% CI=(-0.59, -0.37)). As the first phenome-wide analysis of cognitive and behavioral phenotypes, this study presents the novel genetic protective effects of cognitive ability on the decline of memory recall in an aging population.

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Cognitive Capacity Genomewide Polygenic Scores Identify Individuals Resilient to Cognitive Decline in Aging

10.21203/rs.3.rs-139515/v1 ◽

2021 ◽

Author(s):

Yoonjung Yoonie Joo ◽

Jiook Cha ◽

Jeremy Freese ◽

M Geoffrey Hayes

Keyword(s):

Cognitive Decline ◽

Cognitive Abilities ◽

Cognitive Capacity ◽

European Ancestry ◽

Memory Recall ◽

Protective Effects ◽

The Novel ◽

Cognitive Domains ◽

Genome Wide ◽

Polygenic Scores

Abstract The genetic underpinnings of cognitive resilience in aging remains unknown. Predicting an individual’s rate of cognitive decline—or cognitive resilience—using genetics will allow personalized intervention for cognitive enhancement and optimal selection of target samples in clinical trials. Here, using genome-wide polygenic scores(GPS) as the genomic indicators for variations of human intelligence, we examined the genetic liability of cognitive abilities in the behavioral/cognitive phenome to understand individual differences in cognitive capacity over time. Using the longitudinal sociogenomic data of 8,509 European-ancestry adults between the ages of mid-60s to 70s, we found that a higher cognitive GPS significantly correlated with a slower cognitive decline specifically in memory recall, but not in other cognitive domains. Linear mixed models with cognitive GPSs explained proportions of the variances in cognitive tests up to 60.4%. This study presents the novel genetic protective effects of cognitive ability on the decline of memory recall in aging population.

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

10.21203/rs.3.rs-136949/v2 ◽

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.

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Abstract 16160: Common Autosomal Variants are Associated With Bicuspid Aortic Valve in Turner Syndrome

Circulation ◽

10.1161/circ.130.suppl_2.16160 ◽

2014 ◽

Vol 130 (suppl_2) ◽

Author(s):

Siddharth Prakash ◽

Michael Silberbach ◽

Federico Asch ◽

Giuseppe Limongelli ◽

Hector Michelena ◽

...

Keyword(s):

Turner Syndrome ◽

Meta Analysis ◽

Copy Number Variants ◽

European Ancestry ◽

P Value ◽

Scaling Analysis ◽

Aortic Valves ◽

Genome Wide ◽

Independent Review ◽

Tests Of Association

Introduction: The prevalence of bicuspid aortic valves (BAV) is enriched thirty-fold in women with Turner Syndrome (TS) in comparison with the general population. Hypothesis: Common autosomal variants influence the development of BAV in TS women, who may be uniquely sensitized to these variants by the loss of one X chromosome. We sought to identify autosomal BAV susceptibility genes in a cohort of TS women (average age 30 years, 38% BAV, 18% coarctation). Methods: A total of 106 TS women of European ancestry with BAV and 173 TS women with tricuspid aortic valves were genotyped on Illumina Omni-Express arrays. Valve phenotypes were determined by independent review of echocardiograms from the enrolling sites. Tests of association were performed using logistic regression without adjustment for covariates and were summarized in a meta-analysis. Results: Xp dosage was inversely and quantitatively associated with BAV status (P=0.02). Large, recurrent copy number variants in 1p36.13, 3q29, 8p23.1 and 9p24.3 were significantly enriched in BAV cases. After exclusion of 26 outlier samples in multidimensional scaling analysis, there was no significant genomic inflation (lambda= 1.02). The strongest genome-wide association signals were observed in 1p36.23, 3q23, 12q21.2, 18q21 and 22q13.31, and did not overlap with previously reported loci for BAV. A total of 13 SNPs in 18q21 were positively associated with BAV (OR=2.5-4.3) with a minimum P value of 1x10-7. Replication of these regions in independent groups of cases is ongoing. Conclusion: Our results demonstrate that autosomal variants with large magnitudes of effect contribute to BAV in TS women, confirming our hypothesis, and provide evidence for gene-gene interactions in BAV formation.

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Genome-Wide Association Study Identifies Loci Associated with Sensitive Skin

Cosmetics ◽

10.3390/cosmetics7020049 ◽

2020 ◽

Vol 7 (2) ◽

pp. 49

Author(s):

Miranda A. Farage ◽

Yunxuan Jiang ◽

Jay P. Tiesman ◽

Pierre Fontanillas ◽

Rosemarie Osborne

Keyword(s):

Genome Wide Association Study ◽

Association Studies ◽

Genome Wide Association ◽

European Ancestry ◽

P Value ◽

Genome Wide Association Studies ◽

Online Questionnaire ◽

Sensitive Skin ◽

Genome Wide ◽

Skin Conditions

Individuals suffering from sensitive skin often have other skin conditions and/or diseases, such as fair skin, freckles, rosacea, or atopic dermatitis. Genome-wide association studies (GWAS) have been performed for some of these conditions, but not for sensitive skin. In this study, a total of 23,426 unrelated participants of European ancestry from the 23andMe database were evaluated for self-declared sensitive skin, other skin conditions, and diseases using an online questionnaire format. Responders were separated into two groups: those who declared they had sensitive skin (n = 8971) and those who declared their skin was not sensitive (controls, n = 14,455). A GWAS of sensitive skin individuals identified three genome-wide significance loci (p-value < 5 × 10−8) and seven suggestive loci (p-value < 1 × 10−6). Of the three most significant loci, all have been associated with pigmentation and two have been associated with acne.

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Genetic Effects on Longitudinal Cognitive Decline During the Early Stages of Alzheimer's Disease

10.21203/rs.3.rs-149163/v1 ◽

2021 ◽

Author(s):

Atul Kumar ◽

Maryam Shoai ◽

Sebastian Palmqvist ◽

Erik Stomrud ◽

John Hardy ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Decline ◽

Genome Wide Association Study ◽

Early Stage ◽

Cognitive Change ◽

Preclinical Ad ◽

Genome Wide ◽

A Genome ◽

Polygenic Scores

Abstract Background Cognitive decline in early-stage Alzheimer’s disease (AD) may depend on genetic variability. Methods In the Swedish BioFINDER study, we used polygenic scores (PGS) (for AD, intelligence and educational attainment), and genetic variants (in a genome-wide association study [GWAS]) to predict longitudinal cognitive change (measured by MMSE) over a mean of 4.2 years. We included 555 β-amyloid (Aβ) negative cognitively unimpaired (CU) individuals, 206 Aβ-positive CU (preclinical AD), 110 Aβ-negative mild cognitive impairment (MCI) patients, and 146 Aβ-positive MCI patients (prodromal AD). Results Polygenic scores for AD (in Aβ-positive individuals) and intelligence (independent of Aβ-status) were associated with cognitive decline. Eight genes were associated with cognitive decline in GWAS (3 independent of Aβ-status). Conclusions AD risk genes may influence cognitive decline in early AD, while genes related to intelligence may modulate cognitive decline irrespective of disease. Therapies targeting the implicated biological pathways may modulate the clinical course of AD.

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Genetic contribution to ‘theory of mind’ in adolescence

10.1101/254524 ◽

2018 ◽

Author(s):

Varun Warrier ◽

Simon Baron-Cohen

Keyword(s):

Theory Of Mind ◽

Mental States ◽

Cognitive Empathy ◽

P Value ◽

Association Analyses ◽

Cognitive Aptitude ◽

Genome Wide ◽

Polygenic Scores ◽

Psychiatric Conditions ◽

The Mind

AbstractDifficulties in ‘theory of mind’ (the ability to attribute mental states to oneself or others, and to make predictions about another’s behaviour based on these attributions) have been observed in several psychiatric conditions. We investigate the genetic architecture of theory of mind in 4,577 13-year-olds who completed the Emotional Triangles Task (Triangles Task), a first-order test of theory of mind. We observe a small but significant female-advantage on the Triangles Task (Cohen’s d = 0.19, P < 0.01), in keeping with previous work using other tests of theory of mind. Genome-wide association analyses did not identify any significant loci, and SNP heritability was small and non-significant. Polygenic scores for six psychiatric conditions (ADHD, anorexia, autism, bipolar disorder, depression, and schizophrenia), and empathy were not associated with scores on the Triangles Task. However, polygenic scores of cognitive aptitude, and cognitive empathy, a term synonymous with theory of mind and measured using the “Reading the Mind in the Eyes” Test, were significantly associated with scores on the Triangles Task at multiple P-value thresholds, suggesting shared genetics between different measures of theory of mind and cognition.

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GENECHOC study: genetic markers of arrhythmic risk in heart failure

European Heart Journal ◽

10.1093/ehjci/ehaa946.0335 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

S Anys ◽

S Rigade ◽

E Baron ◽

...

Keyword(s):

Heart Failure ◽

Genetic Markers ◽

Left Ventricular ◽

European Ancestry ◽

Left Ventricular Ejection ◽

P Value ◽

Funding Source ◽

Ventricular Ejection Fraction ◽

Cardioverter Defibrillator ◽

Genome Wide

Abstract Background Ventricular arrhythmic events are responsible for 50% of death in heart failure but no reliable predictive marker is known to discriminate patients at risk of fatal arrhythmia. Interestingly, familial predisposition has been reported suggesting a role of genetic factors. Purpose Identify genetic markers increasing the arrhythmic risk in heart failure population. Method We prospectively included heart failure patients with left ventricular ejection fraction (LVEF) under 35% and a cardioverter defibrillator in primary prevention in 22 French centres between 2009 and 2017. Patients were followed for 72 months and divided into two groups: cases with an arrhythmic event during follow-up and controls. A Genome Wide Association Study (GWAS) was done. Single Nucleotide Polymorphisms (SNPs) genotyping was performed on Affymetrix Axiom Precision Medicine Research Array plates. To complement the directly genotyped SNPs we performed large-scale imputation based on the Haplotype Reference Consortium European ancestry panel leading to a dataset of 7,5 million of SNPs. Results 332 cases and 567 controls were included (86% men, mean age at implantation 52±11 years). 78% of patients had ischaemic cardiopathy, 20% had dilated cardiomyopathy. Mean LVEF was 27±5%. No statistical difference was found between cases and controls on clinical parameters, biological results, electrocardiographic measures. No locus shows genome-wide significant association (p<5.10–8) on the GWAS analysis. However, 16 signals with a p-value between 5.10–8 and 5.10–5 were investigated. eQTL and chromatin conformation point to 35 genes with cardiac expression previously associated with heart failure, cardiomyopathies, cardiogenesis, arrhythmias and inflammation. Variants identified point to regulatory regions of the genome and may then propose a molecular mechanism predisposing patients to arrhythmias. Conclusion No locus raises genome-wide significance, but several signals with a nominal p-value point to relevant genes and pathways. Replication of the GWAS is ongoing on a cohort of 156 new patients with a less severe cardiopathy implanted with a cardioverter defibrillator in secondary prevention. Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Nantes University Hospital

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Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores

Genome Medicine ◽

10.1186/s13073-019-0682-2 ◽

2019 ◽

Vol 11 (1) ◽

Cited By ~ 7

Author(s):

Julian R. Homburger ◽

Cynthia L. Neben ◽

Gilad Mishne ◽

Alicia Y. Zhou ◽

Sekar Kathiresan ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Imputation Accuracy ◽

European Ancestry ◽

Whole Genome ◽

Common Variants ◽

Genotyping Array ◽

Genome Wide ◽

Polygenic Scores ◽

Low Coverage

Abstract Background Inherited susceptibility to common, complex diseases may be caused by rare, pathogenic variants (“monogenic”) or by the cumulative effect of numerous common variants (“polygenic”). Comprehensive genome interpretation should enable assessment for both monogenic and polygenic components of inherited risk. The traditional approach requires two distinct genetic testing technologies—high coverage sequencing of known genes to detect monogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). We assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs. Methods First, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for 3 common diseases—coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF)—calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in a cohort of 11,502 individuals of European ancestry. Results We found imputation accuracy r2 values of greater than 0.90 for all ten samples—including those of African and Ashkenazi Jewish ancestry—with lcWGS data at 0.5×. GPSs calculated using lcWGS and genotyping array followed by imputation in 184 individuals were highly correlated for each of the 3 common diseases (r2 = 0.93–0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse ancestral backgrounds, we found similar results with respect to imputation accuracy and GPS correlations. Finally, we calculated GPSs for CAD, BC, and AF using lcWGS in 11,502 individuals of European ancestry, confirming odds ratios per standard deviation increment ranging 1.28 to 1.59, consistent with previous studies. Conclusions lcWGS is an alternative technology to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.

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Interaction between Genetic Risk Scores for reduced pulmonary function and smoking, asthma and endotoxin

Thorax ◽

10.1136/thoraxjnl-2020-215624 ◽

2021 ◽

pp. thoraxjnl-2020-215624

Author(s):

Sinjini Sikdar ◽

Annah B Wyss ◽

Mi Kyeong Lee ◽

Thanh T Hoang ◽

Marie Richards ◽

...

Keyword(s):

Pulmonary Function ◽

Genetic Risk ◽

Association Studies ◽

European Ancestry ◽

Risk Scores ◽

P Value ◽

Genome Wide Association Studies ◽

Inverse Association ◽

Genetic Risk Scores ◽

Genome Wide

RationaleGenome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene–environment interactions, but studies are few.MethodsWe analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case–control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV1, FVC and FEV1/FVC. Using data from a recent large meta-analysis of GWAS, we constructed a weighted GRS for each trait by combining the top (p value<5×10−9) genetic variants, after clumping based on distance (±250 kb) and linkage disequilibrium (r2=0.5). We used linear regression, adjusting for relevant covariates, to estimate associations of each trait with its GRS and to assess interactions.ResultsEach trait was highly significantly associated with its GRS (all three p values<8.9×10−8). The inverse association of the GRS with FEV1/FVC was stronger for current smokers (pinteraction=0.017) or former smokers (pinteraction=0.064) when compared with never smokers and among asthmatics compared with non-asthmatics (pinteraction=0.053). No significant interactions were observed between any GRS and house dust endotoxin.ConclusionsEvaluation of interactions using GRSs supports a greater impact of increased genetic susceptibility on reduced pulmonary function in the presence of smoking or asthma.

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