91 research outputs found
Majority of human traits do not show evidence for sex-specific genetic and environmental effects
No full textSex differences in the etiology of human trait variation are a major topic of interest in the social and medical sciences given its far-reaching implications. For example, in genetic research, the presence of sex-specific effects would require sex-stratified analysis, and in clinical practice sex-specific treatments would be warranted. Here, we present a study of 2,335,920 twin pairs, in which we tested sex differences in genetic and environmental contributions to variation in 2,608 reported human traits, clustered in 50 trait categories. Monozygotic and dizygotic male and female twin correlations were used to test whether the amount of genetic and environmental influences was equal between the sexes. By comparing dizygotic opposite sex twin correlations with dizygotic same sex twin correlations we could also test whether sex-specific genetic or environmental factors were involved. We observed for only 3% of all trait categories sex differences in the amount of etiological influences. Sex-specific genetic factors were observed for 25% of trait categories, often involving obviously sex-dependent trait categories such as puberty-related disorders. Our findings show that for most traits the number of sex-specific genetic variants will be small. For those traits where we do report sexual dimorphism, sex-specific approaches may aid in future gene-finding efforts
Behavioural genetics methods
Get PDFThe question of why people show individual differences in their behaviours and capacities has intrigued researchers for centuries. Behaviour genetics offers us various methods to address this question. The answers are interesting for a range of research fields, varying from medicine to psychology, economics and neuroscience. Starting with twin and family studies in the late 1970s, the field of behaviour genetics has rapidly developed by applying molecular genetic techniques next to, and sometimes combined with, family data. The overarching conclusion at this point in time is that all measured human traits are to some extent heritable, and that many genetic variants, with each exerting a small effect, explain this heritability. Against this backdrop, we offer readers who might be less familiar with behaviour genetics a brief Primer on the topic. Sitting atop our list of goals is to be a resource for scholars interested in applying the widely useful techniques of the field to their particular specialty, regardless of what that might be
Erratum to: Majority of human traits do not show evidence for sex-specific genetic and environmental effects (Scientific Reports, (2017), 7, 1, (8688), 10.1038/s41598-017-09249-3)
No full textA correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper
Systematic Review: How the Attention-Deficit/Hyperactivity Disorder Polygenic Risk Score Adds to Our Understanding of ADHD and Associated Traits
No full textObjective: To investigate, by systematically reviewing the literature, whether the attention-deficit/hyperactivity disorder (ADHD) polygenic risk score (PRS) associates with ADHD and related traits in independent clinical and population samples. Method: PubMed, Embase and PsychoInfo were systematically searched, alongside study bibliographies. Quality assessments were conducted, and a best-evidence synthesis was applied. Studies were excluded when the predictor was not based on the latest ADHD genome-wide association study, when PRS was not based on genome-wide results, or when the study was a review. Initially, 197 studies were retrieved (February 22, 2020), and a second search (June 3, 2020) yielded a further 49 studies. From both searches, 57 studies were eligible, and 44 studies met inclusion criteria. Results: Included studies were published in the last 3 years. Over 80% of the studies were rated excellent, based on a standardized quality assessment. Evidence of associations between ADHD PRS and the following categories was strong: ADHD, ADHD traits, brain structure, education, externalizing behaviors, neuropsychological constructs, physical health, and socioeconomic status. Evidence for associations with addiction, autism, and mental health were mixed and were, so far, inconclusive. Odds ratios for PRS associating with ADHD ranged from 1.22% to 1.76%; variance explained in dimensional assessments of ADHD traits was 0.7% to 3.3%. Conclusion: A new wave of high-quality research using the ADHD PRS has emerged. Eventually, symptoms may be partly identified based on PRS, but the current ADHD PRS is useful for research purposes only. This review shows that the ADHD PRS is robust and reliable, associating not only with ADHD but many outcomes and challenges known to be linked to ADHD.</p
COVID-19 and child and adolescent psychiatry: an unexpected blessing for part of our population?
No full textThe relation between ADHD symptoms and fine motor control: a genetic study
Get PDFPrevious research has shown that fine motor control (MC) performance, measured with a computerized task, was less accurate in children with ADHD and in their unaffected siblings, compared to healthy children. This might indicate a shared genetic etiology between MC and ADHD; it was therefore suggested that MC could serve as endophenotype for ADHD. We examined the association between ADHD symptoms (AS) and MC in a genetically informative design that can distinguish between a genetic and a nongenetic familial etiology for the association. Participants were 12-year-old twins and their siblings (N = 409). AS were rated on a continuous scale with the Strengths and Weaknesses of ADHD and Normal behavior scale (SWAN). MC accuracy and stability was measured with the computerized pursuit task of the Amsterdam Neuropsychological Tasks (ANT). Analyses were performed with Structural Equation Modelling. AS were weakly associated with MC accuracy of the left and right hand (r =-.10/-.10). No association with MC stability was found (r =-.01/-.03). AS were highly heritable (75%), while MC accuracy of the right hand and MC stability showed no genetic influences. For MC accuracy of the left hand, variance was explained by genetic (10%), common environmental (23%), and unique environmental variances. The association between MC accuracy of the left hand and AS was explained by a shared genetic influence but the genetic correlation was low (r =-.14). The phenotypic and genetic associations between AS and computerized MC were weak, suggesting that fine MC is not a proper endophenotype for ADHD. © 2010 Psychology Press
Masculinization in Parents of Offspring With Autism Spectrum Disorders Could Be Involved in Comorbid ADHD Symptoms
Get PDFOBJECTIVE: People with autism spectrum disorders (ASD) often have comorbid ADHD symptoms. ASD and ADHD are both associated with high intrauterine testosterone (T) levels. This study aims to investigate whether masculinization predicts inattention symptoms in parents, and in their ASD-affected offspring. METHOD: The sample consisted of 32 parents with ASD-affected children (13 male, 19 female) and 32 offspring individuals (28 male, 4 female). Masculinization of parents was measured by 2D:4D finger ratio, and current T levels. Inattention in both parents and in their offspring was measured with behavior questionnaires. RESULTS: The results indicated that masculinized 2D:4D explains inattentive ADHD symptoms in ASD parents and in their offspring. These predictions are mediated by T and inattention symptoms of ASD parents, respectively. CONCLUSION: These findings suggest the existence of a masculinized endophenotype in ASD parents, which may be characterized by high attentional sensitivity to T effects
Twin studies of complex traits and diseases
No full textThis chapter will first present an overview of the genetic and environmental mechanisms that cause differences in human complex traits and diseases. We focus on findings that demonstrate that all traits are heritable, whether and how heritability of traits and diseases differ between men and women, and the same genetic factors account for why two traits or two diseases correlate. We then present findings on how environmental factors, both measured and unmeasured, augment, moderate, and correlate with genotype to maximize (and minimize) genetic expression of traits and diseases. Here, we give the three most common examples in the behavior genetics literature: cognitive ability, personality, and psychopathology. Finally, we cover the ways in which behavior genetics will be important in future research for clarifying the role of genotype and environment in understanding the etiology of traits and diseases
Across the continuum of attention skills: A twin study of the SWAN ADHD rating scale.
Get PDFIntroduction: Most behavior checklists for attention problems or attention deficit/hyperactivity disorder (ADHD) such as the Child Behavior Checklist (CBCL) have a narrow range of scores, focusing on the extent to which problems are present. It has been proposed that measuring attention on a continuum, from positive attention skills to attention problems, will add value to our understanding of ADHD and related problems. The Strengths and Weaknesses of ADHD symptoms and Normal behavior scale (SWAN) is such a scale. Items of the SWAN are scored on a seven-point scale, with in the middle 'average behavior' and on the extremes 'far below average' and 'far above average'. Method: The SWAN and the CBCL were completed by mothers of respectively 560 and 469 12-year-old twin pairs. The SWAN consists of nine DSM-IV items for Attention Deficit (AD) and nine DSM-IV items for Hyperactivity/Impulsivity (HI). The CBCL Attention Problem (AP) scale consists of 11 items, which are rated on a three-point scale. Results: Children who had a score of zero on the CBCL AP scale can be further differentiated using the SWAN, with variation seen between the average behavior and far above average range. In addition, SWAN scores were normally distributed, rather than kurtotic or skewed as is often seen with other behavioral checklists. The CBCL AP scale and the SWAN-HI and AD scale were strongly influenced by genetic factors (73%, 90% and 82%, respectively). However, there were striking differences in genetic architecture: variation in CBCL AP scores is in large part explained by non-additive genetic influences. Variation in SWAN scores is explained by additive genetic influences only. Conclusion: Ratings on the SWAN cover the continuum from positive attention skills to attention and hyperactivity problems that define ADHD. Instruments such as the SWAN offer clinicians and researchers the opportunity to examine variation in both strengths and weaknesses in attention skills. © 2007 The Authors
Data Related to Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use
No full textFiles include summary statistics for associations with each phenotype: Drinks per week, Cigarettes per day, Smoking initiation, Smoking cessation, and Age of initiation. Details for each file can be found in the readme file or in the article's Supplementary Text.We conducted a meta-analysis of over 30 genome wide association studies (GWAS) in over 1.2 million participants with European ancestry on nicotine and substance use. Specifically, we targeted different stages and kinds of substance use from initiation (smoking initiation and age of regular smoking initiation) to regular use (drinks per week and cigarettes per day) to cessation (smoking cessation). The GWAS included have all been imputed to Haplotype Reference Consortium, 1000 Genomes or a combination including more specific reference panels. The studies are then meta-analyzed using sample size, allele frequencies and the imputation quality score as weight. Here we present the final set of filtered meta-analysis summary statistics as presented in the paper (https://doi.org/10.1038/s41588-018-0307-5) excluding 23andMe. As per requirement and to ease dissemination of our results for other scientific endeavors, we are sharing our results here to facilitate downloading.R01DA037904R01HG008983R21DA040177Liu, Mengzhen; Jiang, Yu; Wedow, Robbee; Li, Yue; Brazel, David M; Chen, Fang; Datta, Gargi; Davila-Velderrain, Jose; McGuire, Daniel; Tian, Chao; Zhan, Xiaowei; 23andMe Research Team; HUNT All-In Psychiatry; Choquet, Hélène; Docherty, Anna R; Faul, Jessica D; Foerster, Johanna R; Fritsche, Lars G; Gabrielsen, Maiken Elvestad; Gordon, Scott D; Haessler, Jeffrey; Hottenga, Jouke-Jan; Huang, Hongyan; Jang, Seon-Kyeong; Jansen, Philip R; Ling, Yueh; Mägi, Reedik; Matoba, Nana; McMahon, George; Mulas, Antonella; Orrù, Valeria; Palviainen, Teemu; Pandit, Anita; Reginsson, Gunnar W, Skogholt, Anne Heidi; Smith, Jennifer A; Taylor, Amy E; Turman, Constance; Willemsen, Gonneke; Young, Hannah; Young, Kendra A; Zajac, Gregory J M; Zhao, Wei; Zhou, Wei; Bjornsdottir, Gyda; Boardman, Jason D; Boehnke, Michael; Boomsma, Dorret I; Chen, Chu; Cucca, Francesco; Davies, Gareth E; Eaton, Charles B; Ehringer, Marissa A; Esko, Tõnu; Fiorillo, Edoardo; Gillespie, Nathan A; Gudbjartsson, Daniel F; Haller, Toomas; Harris, Kathleen Mullan; Heath, Andrew C; Hewitt, John K; Hickie, Ian B; Hokanson, John E; Hopfer, Christian J; Hunter, David J; Iacono, William G; Johnson, Eric O; Kamatani, Yoichiro; Kardia, Sharon L. R; Keller, Matthew C; Kellis, Manolis; Kooperberg, Charles; Kraft, Peter; Krauter, Kenneth S; Laakso, Markku; Lind, Penelope A; Loukola, Anu; Lutz, Sharon M; Madden, Pamela A F; Martin, Nicholas G; McGue, Matt; McQueen, Matthew B; Medland, Sarah E; Metspalu, Andres; Mohlke, Karen L; Nielsen, Jonas B; Okada, Yukinori; Peters, Ulrike; Polderman, Tinca J C; Posthuma, Danielle; Reiner, Alexander P; Rice, John P; Rimm, Eric; Rose, Richard J; Runarsdottir, Valgerdur; Stallings, Michael C; Stančáková, Alena; Stefansson, Hreinn; Thai, Khanh K; Tindle, Hilary A; Tyrfingsson, Thorarinn; Wall, Tamara L; Weir, David R; Weisner, Constance; Whitfield, John B; Winsvold, Bendik Slagsvold; Yin, Jie; Zuccolo, Luisa; Bierut, Laura J; Hveem, Kristian; Lee, James J; Munafò, Marcus R; Saccone, Nancy L; Willer, Cristen J; Cornelis, Marilyn C; David, Sean P; Hinds, David A; Jorgenson, Eric; Kaprio, Jaakko; Stitzel, Jerry A; Stefansson, Kari; Thorgeirsson, Thorgeir E; Abecasis, Gonçalo; Liu Dajiang J; Vrieze Scott. (2019). Data Related to Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/3b1n-ff32
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