Sarah Elizabeth Medland

Sarah Elizabeth Medland

Top Cited Scholar 2026
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Sarah Elizabeth Medland

QIMR Berghofer Medical Research Institute, Brisbane, Australia

Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 February 2015 in Nature
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ALAdam E Locke
Adam E Locke
BKBratati Kahali
Bratati Kahali
SBSonja I Berndt
Sonja I Berndt
AJAnne E Justice
Anne E Justice
TPTune H Pers
Tune H Pers
ESElizabeth K. Speliotes
Elizabeth K. Speliotes

26 November 2018 in Nature Genetics
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Journal Article
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DDDitte Demontis
Ditte Demontis
RWRaymond K. Walters
Raymond K. Walters
JMJoanna Martin
Joanna Martin
MMManuel Mattheisen
Manuel Mattheisen
TAThomas D. Als
Thomas D. Als
BNBenjamin M. Neale
Benjamin M. Neale
Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

18 March 2012 in Nature Genetics
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GCGenetic Investigation of ANthropometric Traits (GIANT) Consortium
Genetic Investigation of ANthropometric Traits (GIANT) Consortium
JYJian Yang
Jian Yang
DCDIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
TFTeresa Ferreira
Teresa Ferreira
AMAndrew P Morris
Andrew P Morris
PVPeter M Visscher
Peter M Visscher

3 May 2016 in Molecular Psychiatry
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LSLianne Schmaal
Lianne Schmaal
DHD P Hibar
D P Hibar
PSP G Sämann
P G Sämann
GHG B Hall
G B Hall
BBB T Baune
B T Baune
DVD J Veltman
D J Veltman
The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen’s d effect sizes: −0.10 to −0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: −0.26 to −0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

25 June 2018 in Nature Genetics
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JSJeanne E. Savage
Jeanne E. Savage
PJPhilip R. Jansen
Philip R. Jansen
SSSven Stringer
Sven Stringer
KWKyoko Watanabe
Kyoko Watanabe
JBJulien Bryois
Julien Bryois
DPDanielle Posthuma
Danielle Posthuma
Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3,4,5,6,7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer’s disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

11 May 2016 in Nature
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AOAysu Okbay
Aysu Okbay
JBJonathan P. Beauchamp
Jonathan P. Beauchamp
MFMark Alan Fontana
Mark Alan Fontana
JLJames J. Lee
James J. Lee
TPTune H. Pers
Tune H. Pers
DBDaniel J. Benjamin
Daniel J. Benjamin
Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.