scholarly journals Do Low Polygenic Scores Buffer the Effects of Maltreatment? A Polygene-Environment Interaction Study of ADHD

2021 ◽  
Author(s):  
Quanfa He ◽  
James Janford Li
Keyword(s):  
Genome Wide Association Study ◽  
Alternative Methods ◽  
Future Research ◽  
Environment Interaction ◽  
Adult Health ◽  
Adhd Symptoms ◽  
Social Emotional ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Psychiatric Outcomes

Objective: This study explored whether maltreatment moderates the association of polygenic risk for ADHD. Because individuals with low polygenic scores (PGS) for ADHD were previously shown to have better than expected functional outcomes (i.e., cognitive, mental health, social-emotional) than individuals with middle or high ADHD PGS, we hypothesized that low ADHD PGS may possible confer a protective effect against maltreatment in the development of ADHD. Method: Data were from participants with phenotypic and genotypic data in the National Longitudinal Study of Adolescent to Adult Health (Add Health; n=4,722), which was used to examine the effects of ADHD PGS, maltreatment, and their interaction on childhood ADHD symptoms. ADHD PGS were generated from the most recent genome-wide association study on ADHD and categorized into three groups (i.e., low, medium, high) using empirically determined cut-points. A maltreatment factor score was derived from five forms of self-reported maltreatment experiences prior to age 18. Results: ADHD PGS and maltreatment were positively associated with ADHD symptoms, as expected. However, we did not detect an interaction between ADHD PGS and maltreatment on ADHD symptoms. Conclusion: Despite the increase in predictive power afforded by PGS, the lack of an interaction between ADHD PGS and maltreatment on ADHD symptoms converges with an emerging body of psychiatric PGS studies that have also failed to detect polygenic-environment interplay on psychiatric outcomes. We discuss possible reasons for this pattern of results and offer alternative methods for future research in revealing important polygenic-environment interactions for ADHD.

scholarly journals How interactions between ADHD and schools affect educational achievement: a family-based genetically sensitive study

2021 ◽  
Author(s):  
Rosa Cheesman ◽  
Espen Moen Eilertsen ◽  
Ziada Ayorech ◽  
Nicolai T. Borgen ◽  
Ole A. Andreassen ◽  
...  
Keyword(s):  
Multilevel Models ◽  
Educational Achievement ◽  
Future Research ◽  
Environment Interaction ◽  
Test Results ◽  
Adhd Symptoms ◽  
School Factors ◽  
Polygenic Scores ◽  
Family Based ◽  
Inattention And Hyperactivity

Background: Children with ADHD tend to achieve less than their peers in school. It is unknown whether schools moderate this ADHD deficit. Selection into schools poses a methodological problem.Methods: We linked data on ADHD symptoms of inattention and hyperactivity and parent-child ADHD polygenic scores (PGS) from the Norwegian Mother, Father, and Child Cohort Study (MoBa) to standardised test results and school identifiers. Using multilevel models, we estimated interactions of school effects with individual differences between students in inattention, hyperactivity, and ADHD-PGS. In our PGS analyses, we ruled out selection by adjusting for parental ADHD-PGS (a within-family PGS design). We then tested whether five measures of the social backgrounds of students at the schools explained any interactions. Results: Analysis of up to 23,598 students attending 2,579 schools revealed interactions between school and ADHD effects on standardised test results. The variability between schools in the effects of inattention, hyperactivity, and within-family ADHD-PGS on achievement was 0.08, 0.07, and 0.05 SDs, respectively. For example, a one SD increase in inattention changed achievement by -0.23 SDs (SE=0.009) on average, but in 2.5% of schools with the weakest effects, the value was -0.07 or less. Schools contributed more to achievement differences for students with higher levels of ADHD, explaining more than four times as much variance in achievement for children with high versus average inattention symptoms. School sociodemographic measures could not explain the ADHD-by-school interactions.Conclusion: Associations between ADHD and achievement are context dependent. Children with elevated ADHD symptoms and genetic risk perform better in some schools than others. Future research should identify specific school factors that support these students, potentially using the within-family gene-environment interaction approach introduced here.

scholarly journals Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data

2018 ◽  
Vol 115 (22) ◽  
pp. E4970-E4979 ◽  
Author(s):  
Thomas A. DiPrete ◽  
Casper A. P. Burik ◽  
Philipp D. Koellinger
Keyword(s):  
Instrumental Variable ◽  
Fixed Effects ◽  
Genome Wide Association Study ◽  
Body Height ◽  
Outcome Variable ◽  
Endogeneity Bias ◽  
Multiple Indicators ◽  
Instrumental Variable Regression ◽  
Genome Wide ◽  
Polygenic Scores

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA.

scholarly journals European landrace diversity for common bean biofortification: a genome-wide association study

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Leonardo Caproni ◽  
Lorenzo Raggi ◽  
Elise F. Talsma ◽  
Peter Wenzl ◽  
Valeria Negri
Keyword(s):  
Common Bean ◽  
Genome Wide Association Study ◽  
Preliminary Evidence ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Future Research ◽  
Balanced Diet ◽  
Genome Wide ◽  
Seed Content ◽  
A Genome

AbstractMineral deficiencies represent a global challenge that needs to be urgently addressed. An adequate intake of iron and zinc results in a balanced diet that reduces chances of impairment of many metabolic processes that can lead to clinical consequences. In plants, bioavailability of such nutrients is reduced by presence of compounds such as phytic acid, that can chelate minerals and reduce their absorption. Biofortification of common bean (Phaseolus vulgaris L.) represents an important strategy to reduce mineral deficiencies, especially in areas of the world where this crop plays a key role in the diet. In this study, a panel of diversity encompassing 192 homozygous genotypes, was screened for iron, zinc and phytate seed content. Results indicate a broad variation of these traits and allowed the identification of accessions reasonably carrying favourable trait combinations. A significant association between zinc seed content and some molecular SNP markers co-located on the common bean Pv01 chromosome was detected by means of genome-wide association analysis. The gene Phvul001G233500, encoding for an E3 ubiquitin-protein ligase, is proposed to explain detected associations. This result represents a preliminary evidence that can foster future research aiming at understanding the genetic mechanisms behind zinc accumulation in beans.

scholarly journals A genome-wide association study unravels cytokinin as a major component in the root defense responses against Ralstonia solanacearum

2021 ◽  
Author(s):  
Alejandro Alonso-Díaz ◽  
Santosh B Satbhai ◽  
Roger de Pedro-Jové ◽  
Hannah M Berry ◽  
Christian Göschl ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Allelic Variation ◽  
Defense Responses ◽  
Genome Wide Association ◽  
Root Growth Inhibition ◽  
Future Research ◽  
Cytokinin Signaling ◽  
Genome Wide ◽  
A Genome

Abstract Bacterial wilt caused by the soil-borne pathogen Ralstonia solancearum is economically devastating, with no effective methods to fight the disease. This pathogen invades plants through their roots and colonizes their xylem, clogging the vasculature and causing rapid wilting. Key to preventing colonization are the early defense responses triggered in the host’s root upon infection, which remain mostly unknown. Here, we have taken advantage of a high-throughput in vitro infection system to screen natural variability associated to the root growth inhibition phenotype caused by R. solanacearum in Arabidopsis during the first hours of infection. To analyze the genetic determinants of this trait, we have performed a Genome-Wide Association Study, identifying allelic variation at several loci related to cytokinin metabolism, including genes responsible for biosynthesis and degradation of cytokinin. Further, our data clearly demonstrate that cytokinin signaling is induced early during the infection process and cytokinin contributes to immunity against R. solanacearum. This study highlights a new role of cytokinin in root immunity, paving the way for future research that will help understanding the mechanisms underpinning root defenses.

scholarly journals Father Absence and Accelerated Reproductive Development

2017 ◽  
Author(s):  
Lauren Gaydosh ◽  
Daniel W. Belsky ◽  
Benjamin W. Domingue ◽  
Jason D. Boardman ◽  
Kathleen Mullan Harris
Keyword(s):  
Genome Wide Association Study ◽  
Reproductive Development ◽  
Father Absence ◽  
Age At Menarche ◽  
Adult Health ◽  
Reproductive Timing ◽  
First Birth ◽  
Gene Environment ◽  
Polygenic Scores ◽  
Study Results

AbstractEvidence shows that girls who experience father absence in childhood experience accelerated reproductive development in comparison to peers with present fathers. One hypothesis advanced to explain this empirical pattern is genetic confounding, wherein gene-environment correlation (rGE) causes a spurious relationship between father absence and reproductive timing. We test this hypothesis by constructing polygenic scores for age at menarche and first birth using recently available genome wide association study results and molecular genetic data on a sample of non-Hispanic white females from the National Longitudinal Study of Adolescent to Adult Health. Young women’s accelerated menarche polygenic scores were unrelated to their exposure to father absence. In contrast, earlier first-birth polygenic scores tended to be higher in young women raised in homes with absent fathers. Nevertheless, father absence and the polygenic scores independently and additively predict reproductive timing. We find limited evidence in support of the gene-environment correlation hypothesis.

scholarly journals Genetic Instrumental Variable (GIV) regression: Explaining socioeconomic and health outcomes in non-experimental data

2017 ◽  
Author(s):  
Thomas A. DiPrete ◽  
Casper A.P. Burik ◽  
Philipp D. Koellinger
Keyword(s):  
Experimental Data ◽  
Fixed Effects ◽  
Genome Wide Association Study ◽  
Body Height ◽  
Outcome Variable ◽  
Endogeneity Bias ◽  
Multiple Indicators ◽  
Genome Wide ◽  
Alternative Approach ◽  
Polygenic Scores

Identifying causal effects in non-experimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables (i.e. Mendelian Randomization - MR). However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in non-experimental data that would also undermine the ability of MR to correct for endogeneity bias from non-genetic sources. Here, we propose an alternative approach, GIV regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGS) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into non-overlapping subsamples, we obtain multiple indicators of the outcome PGS that can be used as instruments for each other, and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA.

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

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.

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.

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