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John K. Hewitt

Bio: John K. Hewitt is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Twin study & Population. The author has an hindex of 79, co-authored 373 publications receiving 22354 citations. Previous affiliations of John K. Hewitt include University of British Columbia & VCU Medical Center.


Papers
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Journal ArticleDOI
TL;DR: A multivariate twin study of 3 executive functions (inhibiting dominant responses, updating working memory representations, and shifting between task sets), measured as latent variables, examined why people vary in these executive control abilities and why they are correlated but separable from a behavioral genetic perspective.
Abstract: Recent psychological and neuropsychological research suggests that executive functions--the cognitive control processes that regulate thought and action--are multifaceted and that different types of executive functions are correlated but separable. The present multivariate twin study of 3 executive functions (inhibiting dominant responses, updating working memory representations, and shifting between task sets), measured as latent variables, examined why people vary in these executive control abilities and why these abilities are correlated but separable from a behavioral genetic perspective. Results indicated that executive functions are correlated because they are influenced by a highly heritable (99%) common factor that goes beyond general intelligence or perceptual speed, and they are separable because of additional genetic influences unique to particular executive functions. This combination of general and specific genetic influences places executive functions among the most heritable psychological traits. These results highlight the potential of genetic approaches for uncovering the biological underpinnings of executive functions and suggest a need for examining multiple types of executive functions to distinguish different levels of genetic influences.

1,320 citations

Journal ArticleDOI
TL;DR: Examination of the relations of fluid and crystallized intelligence and Wechsler Adult Intelligence Scale IQ to three separable EFs in young adults indicates that intelligence measures differentially relate to these three EFs, suggesting that current intelligence measures do not equally assess a wide range of executive control abilities likely required for many “intelligent” behaviors.
Abstract: Accumulating evidence suggests that executive functions (EFs) are related to intelligence, despite neuro- psychological results initially considered evidence of no such relation. However, findings that EFs are not unitary raise the issue of how intelligence relates to different EFs. This study examined the relations of fluid and crystallized intelligence and Wechsler Adult Intelligence Scale IQ to three separable EFs--inhibiting prepotent responses (in- hibiting), shifting mental sets (shifting), and updating working memory (updating)—in young adults. Updating was highly correlated with the intelligence measures, but inhibiting and shifting were not. Furthermore, in struc- tural equation models controlling for the inter-EF corre- lations, updatingremained strongly relatedtointelligence, but the relations of inhibiting and shifting to intelligence were small and not significant. The results indicate that intelligence measures differentially relate to these three EFs, suggesting that current intelligence measures do not equally assess a wide range of executive control abilities likely required for many ''intelligent'' behaviors.

1,141 citations

Journal ArticleDOI
TL;DR: It is shown for general cognitive ability that, to the contrary, genetic influence increases with age, and this finding suggests new ways of thinking about the interface between nature and nurture during the school years.
Abstract: Although common sense suggests that environmental influences increasingly account for individual differences in behavior as experiences accumulate during the course of life, this hypothesis has not previously been tested, in part because of the large sample sizes needed for an adequately powered analysis. Here we show for general cognitive ability that, to the contrary, genetic influence increases with age. The heritability of general cognitive ability increases significantly and linearly from 41% in childhood (9 years) to 55% in adolescence (12 years) and to 66% in young adulthood (17 years) in a sample of 11 000 pairs of twins from four countries, a larger sample than all previous studies combined. In addition to its far-reaching implications for neuroscience and molecular genetics, this finding suggests new ways of thinking about the interface between nature and nurture during the school years. Why, despite life's ‘slings and arrows of outrageous fortune’, do genetically driven differences increasingly account for differences in general cognitive ability? We suggest that the answer lies with genotype–environment correlation: as children grow up, they increasingly select, modify and even create their own experiences in part based on their genetic propensities.

545 citations

Journal ArticleDOI
TL;DR: A widespread influence of genetic factors on risk to adolescent psychopathology is supported and suggests that the contribution of different types of social influence may vary consistently across domains of measurement.
Abstract: Little is known about the contribution of genetic and environmental factors to risk for juvenile psychopathology. The Virginia Twin Study of Adolescent Behavioral Development allows these contributions to be estimated. A population-based, unselected sample of 1412 Caucasian twin pairs aged 8-16 years was ascertained through Virginia schools. Assessment of the children involved semi-structured face-to-face interviews with both twins and both parents using the Child and Adolescent Psychiatric Assessment (CAPA). Self-report questionnaires were also completed by parents, children, and teachers. Measures assessed DSM-III-R symptoms of Attention Deficit Hyperactivity Disorder (ADHD). Conduct Disorder, Oppositional Defiant Disorder, Overanxious Disorder, Separation Anxiety, and Depressive Disorder. Factorially derived questionnaire scales were also extracted. Scores were normalized and standardized by age and sex. Maximum likelihood methods were used to estimate contributions of additive and nonadditive genetic effects, the shared and unique environment, and sibling imitation or contrast effects. Estimates were tested for heterogeneity over sexes. Generally, monozygotic (MZ) twins correlated more highly than dizygotic (DZ) twins, parental ratings more than child ratings, and questionnaire scales more highly than interviews. DZ correlations were very low for measures of ADHD and DZ variances were greater than MZ variances for these variables. Correlations sometimes differed between sexes but those for boy-girl pairs were usually similar to those for like-sex pairs. Most of the measures showed small to moderate additive genetic effects and moderate to large effects of the unique individual environment. Measures of ADHD and related constructs showed marked sibling contrast effects. Some measures of oppositional behavior and conduct disorder showed shared environmental effects. There were marked sex differences in the genetic contribution to separation anxiety, otherwise similar genetic effects appear to be expressed in boys and girls. Effects of rater biases on the genetic analysis are considered. The study supports a widespread influence of genetic factors on risk to adolescent psychopathology and suggests that the contribution of different types of social influence may vary consistently across domains of measurement.

495 citations

Journal ArticleDOI
TL;DR: An extension to current maximum-likelihood variance-components procedures for mapping quantitative-trait loci in sib pairs that allows a simultaneous test of allelic association is proposed, which partitions the mean effect of a locus into between- and within-sibship components.
Abstract: An extension to current maximum-likelihood variance-components procedures for mapping quantitative-trait loci in sib pairs that allows a simultaneous test of allelic association is proposed. The method involves modeling of the allelic means for a test of association, with simultaneous modeling of the sib-pair covariance structure for a test of linkage. By partitioning of the mean effect of a locus into between- and within-sibship components, the method controls for spurious associations due to population stratification and admixture. The power and efficacy of the method are illustrated through simulation of various models of both real and spurious association.

452 citations


Cited by
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Journal ArticleDOI
TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
Abstract: Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

26,280 citations

Journal ArticleDOI
TL;DR: Although mental disorders are widespread, serious cases are concentrated among a relatively small proportion of cases with high comorbidity, as shown in the recently completed US National Comorbidities Survey Replication.
Abstract: Background Little is known about the general population prevalence or severity of DSM-IV mental disorders. Objective To estimate 12-month prevalence, severity, and comorbidity of DSM-IV anxiety, mood, impulse control, and substance disorders in the recently completed US National Comorbidity Survey Replication. Design and Setting Nationally representative face-to-face household survey conducted between February 2001 and April 2003 using a fully structured diagnostic interview, the World Health Organization World Mental Health Survey Initiative version of the Composite International Diagnostic Interview. Participants Nine thousand two hundred eighty-two English-speaking respondents 18 years and older. Main Outcome Measures Twelve-month DSM-IV disorders. Results Twelve-month prevalence estimates were anxiety, 18.1%; mood, 9.5%; impulse control, 8.9%; substance, 3.8%; and any disorder, 26.2%. Of 12-month cases, 22.3% were classified as serious; 37.3%, moderate; and 40.4%, mild. Fifty-five percent carried only a single diagnosis; 22%, 2 diagnoses; and 23%, 3 or more diagnoses. Latent class analysis detected 7 multivariate disorder classes, including 3 highly comorbid classes representing 7% of the population. Conclusion Although mental disorders are widespread, serious cases are concentrated among a relatively small proportion of cases with high comorbidity.

10,951 citations

Journal Article
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

9,847 citations

BookDOI
01 Nov 2000
TL;DR: From Neurons to Neighborhoods as discussed by the authors presents the evidence about "brain wiring" and how children learn to learn to speak, think, and regulate their behavior, and examines the effect of the climate-family, child care, community-within which the child grows.
Abstract: How we raise young children is one of today's most highly personalized and sharply politicized issues, in part because each of us can claim some level of "expertise." The debate has intensified as discoveries about our development-in the womb and in the first months and years-have reached the popular media. How can we use our burgeoning knowledge to assure the well-being of all young children, for their own sake as well as for the sake of our nation? Drawing from new findings, this book presents important conclusions about nature-versus-nurture, the impact of being born into a working family, the effect of politics on programs for children, the costs and benefits of intervention, and other issues. The committee issues a series of challenges to decision makers regarding the quality of child care, issues of racial and ethnic diversity, the integration of children's cognitive and emotional development, and more. Authoritative yet accessible, From Neurons to Neighborhoods presents the evidence about "brain wiring" and how kids learn to speak, think, and regulate their behavior. It examines the effect of the climate-family, child care, community-within which the child grows.

5,295 citations

01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

4,409 citations