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Dive into the research topics where Margaret J. Wright is active.

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Featured researches published by Margaret J. Wright.


Nature Communications | 2015

Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis (vol 5, 4926, 2014)

Beben Benyamin; Tonu Esko; Janina S. Ried; Aparna Radhakrishnan; Sita H. Vermeulen; Michela Traglia; Martin Goegele; Denise Anderson; Linda Broer; Clara Podmore; Jian'an Luan; Zoltán Kutalik; Serena Sanna; Peter van der Meer; Toshiko Tanaka; Fudi Wang; Harm-Jan Westra; Lude Franke; Evelin Mihailov; Lili Milani; Jonas Haelldin; Juliane Winkelmann; Thomas Meitinger; Joachim Thiery; Annette Peters; Melanie Waldenberger; Augusto Rendon; Jennifer Jolley; Jennifer Sambrook; Lambertus A. Kiemeney

Corrigendum: Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis


Molecular Psychiatry | 2010

The heritability of general cognitive ability increases linearly from childhood to young adulthood

Claire M. A. Haworth; Margaret J. Wright; Michelle Luciano; Nicholas G. Martin; E.J.C. de Geus; C.E.M. van Beijsterveldt; M. Bartels; Danielle Posthuma; Dorret I. Boomsma; Oliver S. P. Davis; Yulia Kovas; Robin P. Corley; John C. DeFries; John K. Hewitt; Richard K. Olson; Sa Rhea; Sally J. Wadsworth; William G. Iacono; Matt McGue; Lee A. Thompson; Sara A. Hart; Stephen A. Petrill; David Lubinski; Robert Plomin

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 lifes ‘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.


The Journal of Neuroscience | 2009

Genetics of Brain Fiber Architecture and Intellectual Performance

Ming-Chang Chiang; Marina Barysheva; David W. Shattuck; Agatha D. Lee; Sarah K. Madsen; Christina Avedissian; Andrea D. Klunder; Arthur W. Toga; Katie L. McMahon; Greig I. de Zubicaray; Margaret J. Wright; Anuj Srivastava; N. Balov; Paul M. Thompson

The study is the first to analyze genetic and environmental factors that affect brain fiber architecture and its genetic linkage with cognitive function. We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4 Tesla), in 92 identical and fraternal twins. White matter integrity, quantified using fractional anisotropy (FA), was used to fit structural equation models (SEM) at each point in the brain, generating three-dimensional maps of heritability. We visualized the anatomical profile of correlations between white matter integrity and full-scale, verbal, and performance intelligence quotients (FIQ, VIQ, and PIQ). White matter integrity (FA) was under strong genetic control and was highly heritable in bilateral frontal (a2 = 0.55, p = 0.04, left; a2 = 0.74, p = 0.006, right), bilateral parietal (a2 = 0.85, p < 0.001, left; a2 = 0.84, p < 0.001, right), and left occipital (a2 = 0.76, p = 0.003) lobes, and was correlated with FIQ and PIQ in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, callosal isthmus, and the corona radiata (p = 0.04 for FIQ and p = 0.01 for PIQ, corrected for multiple comparisons). In a cross-trait mapping approach, common genetic factors mediated the correlation between IQ and white matter integrity, suggesting a common physiological mechanism for both, and common genetic determination. These genetic brain maps reveal heritable aspects of white matter integrity and should expedite the discovery of single-nucleotide polymorphisms affecting fiber connectivity and cognition.


Molecular Psychiatry | 2016

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.

Lianne Schmaal; Dick J. Veltman; T G M van Erp; Philipp G. Sämann; Thomas Frodl; Neda Jahanshad; Elizabeth Loehrer; Henning Tiemeier; A. Hofman; Wiro J. Niessen; Meike W. Vernooij; M. A. Ikram; K. Wittfeld; H. J. Grabe; A Block; K. Hegenscheid; Henry Völzke; D. Hoehn; Michael Czisch; Jim Lagopoulos; Sean N. Hatton; Ian B. Hickie; Roberto Goya-Maldonado; Bernd Krämer; Oliver Gruber; Baptiste Couvy-Duchesne; Miguel E. Rentería; Lachlan T. Strike; N T Mills; G. I. de Zubicaray

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.


Behavior Genetics | 2001

Genetic structure of spatial and verbal working memory

Juko Ando; Yutaka Ono; Margaret J. Wright

Working memory (WM) encompasses both short-term memory (storage) and executive functions that play an essential role in all forms of cognition. In this study, the genetic structure of storage and executive functions engaged in both a spatial and verbal WM span task is investigated using a twin sample. The sample consists of 143 monozygotic (MZ) and 93 dizygotic (DZ) Japanese twin pairs, ages 16 to 29 years. In 155 (87 MZ, 62 DZ) of these pairs, cognitive ability scores from the Kyodai Japanese IQ test are also obtained. The phenotypic relationship between WM and cognitive ability is confirmed (r = 0.26−0.44). Individual differences in WM storage and executive functions are found to be significantly influenced by genes, with heritability estimates all moderately high (43%–49%), and estimates for cognitive ability comparable to previous studies (65%). A large part of the genetic variance in storage and executive functions in both spatial and verbal modalities is due to a common genetic factor that accounts for 11% to 43% of the variance. In the reduced sample, this common genetic factor accounts for 64% and 26% of the variance in spatial and verbal cognitive ability, respectively. Additional genetic variance in WM (7%–30%) is due to modality specific factors (spatial and verbal) and a storage specific factor that may be particularly important for the verbal modality. None of the variance in cognitive ability is accounted for by the modality and storage genetic factors, suggesting these may be specific to WM.


Australian Journal of Psychology | 2004

Brisbane adolescent twin study: Outline of study methods and research projects

Margaret J. Wright; Nicholas G. Martin

An ongoing program at the Queensland Institute of Medical Research (QIMR) uses a resource of adolescent twins (2720 individuals) and their singleton siblings (1179), constituting 1324 families. A large number (> 500 families) have participated in two main studies (the mole and the cognition studies) with the aim of identifying genetic polymorphisms associated with moliness and cognitive function respectively, as well as several other projects that run in parallel with these studies. Most recently 950 families were invited to participate in a mail and phone study assessing reading ability, taste and smell sensitivity, and health and wellbeing. Although the program measures a broad range of phenotypes, the common focus of all studies is to reveal the genetic architecture underlying the trait, and thereby facilitate the search for quantitative trait loci. The present paper provides an overview of the studies, and highlights the significance of the resource, as well as some of the unique aspects of twin research.


Molecular Psychiatry | 2012

Meta-analysis of genome-wide association studies for personality

M.H.M. de Moor; Paul T. Costa; Antonio Terracciano; Robert F. Krueger; E.J.C. de Geus; T Toshiko; Brenda W. J. H. Penninx; Tonu Esko; P. A. F. Madden; Jaime Derringer; Najaf Amin; Gonneke Willemsen; J.J. Hottenga; Marijn A. Distel; Manuela Uda; Serena Sanna; Philip Spinhoven; C. A. Hartman; Patrick F. Sullivan; Anu Realo; Jüri Allik; A. C. Heath; Michele L. Pergadia; Arpana Agrawal; Peng Lin; Richard A. Grucza; Teresa Nutile; Marina Ciullo; Dan Rujescu; Ina Giegling

Personality can be thought of as a set of characteristics that influence peoples thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17 375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ∼2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P=2.8 × 10−8 and 3.1 × 10−8) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P=4.9 × 10−8). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.


American Journal of Human Genetics | 2009

Common Variants in the Trichohyalin Gene Are Associated with Straight Hair in Europeans

Sarah E. Medland; Dale R. Nyholt; Jodie N. Painter; Brian P. McEvoy; Allan F. McRae; Gu Zhu; Scott D. Gordon; Manuel A. Ferreira; Margaret J. Wright; Anjali K. Henders; Megan J. Campbell; David L. Duffy; Narelle K. Hansell; Stuart Macgregor; Wendy S. Slutske; Andrew C. Heath; Grant W. Montgomery; Nicholas G. Martin

Hair morphology is highly differentiated between populations and among people of European ancestry. Whereas hair morphology in East Asian populations has been studied extensively, relatively little is known about the genetics of this trait in Europeans. We performed a genome-wide association scan for hair morphology (straight, wavy, curly) in three Australian samples of European descent. All three samples showed evidence of association implicating the Trichohyalin gene (TCHH), which is expressed in the developing inner root sheath of the hair follicle, and explaining approximately 6% of variance (p=1.5x10(-31)). These variants are at their highest frequency in Northern Europeans, paralleling the distribution of the straight-hair EDAR variant in Asian populations.


PLOS Genetics | 2012

A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans

Fan Liu; Fedde van der Lijn; Gu Zhu; M. Mallar Chakravarty; Pirro G. Hysi; Andreas Wollstein; Oscar Lao; Marleen de Bruijne; M. Arfan Ikram; Aad van der Lugt; Fernando Rivadeneira; André G. Uitterlinden; Albert Hofman; Wiro J. Niessen; Georg Homuth; Greig I. de Zubicaray; Katie L. McMahon; Paul M. Thompson; Amro Daboul; Ralf Puls; Katrin Hegenscheid; Liisa Bevan; Zdenka Pausova; Sarah E. Medland; Grant W. Montgomery; Margaret J. Wright; Carol Wicking; Stefan Boehringer; Tim D. Spector; Tomáš Paus

Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes—PRDM16, PAX3, TP63, C5orf50, and COL17A1—in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.


NeuroImage | 2013

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.

Neda Jahanshad; Peter Kochunov; Emma Sprooten; René C.W. Mandl; Thomas E. Nichols; Laura Almasy; John Blangero; Rachel M. Brouwer; Joanne E. Curran; Greig I. de Zubicaray; Ravi Duggirala; Peter T. Fox; L. Elliot Hong; Bennett A. Landman; Nicholas G. Martin; Katie L. McMahon; Sarah E. Medland; Braxton D. Mitchell; Rene L. Olvera; Charles P. Peterson; Jessika E. Sussmann; Arthur W. Toga; Joanna M. Wardlaw; Margaret J. Wright; Hilleke E. Hulshoff Pol; Mark E. Bastin; Andrew M. McIntosh; Ian J. Deary; Paul M. Thompson; David C. Glahn

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

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Nicholas G. Martin

QIMR Berghofer Medical Research Institute

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Paul M. Thompson

University of Southern California

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Greig I. de Zubicaray

Queensland University of Technology

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Arthur W. Toga

University of Southern California

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Neda Jahanshad

University of Southern California

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Sarah E. Medland

QIMR Berghofer Medical Research Institute

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