Author
Merete Nordentoft
Other affiliations: Martin Luther University of Halle-Wittenberg, SUNY Downstate Medical Center, University of California, Davis ...read more
Bio: Merete Nordentoft is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 89, co-authored 723 publications receiving 36487 citations. Previous affiliations of Merete Nordentoft include Martin Luther University of Halle-Wittenberg & SUNY Downstate Medical Center.
Papers published on a yearly basis
Papers
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TL;DR: A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent and significant loci and finds important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia.
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
1,898 citations
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Stephan Ripke1, Alan R. Sanders2, Kenneth S. Kendler3, Douglas F. Levinson4 +207 more•Institutions (71)
TL;DR: The authors examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects.
Abstract: We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 x 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 x 10(-9)), ANK3 (rs10994359, P = 2.5 x 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 x 10(-9)).
1,671 citations
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deCODE genetics1, Maastricht University Medical Centre2, University of California, Los Angeles3, Utrecht University4, University of Oslo5, University of Bonn6, Ludwig Maximilian University of Munich7, Copenhagen University Hospital8, Wellcome Trust Sanger Institute9, Aarhus University Hospital10, Aarhus University11, University of Iceland12, University of Helsinki13, Bispebjerg Hospital14, Glostrup Hospital15, Heidelberg University16, Semmelweis University17, University of Verona18, Radboud University Nijmegen Medical Centre19, Russian Academy20, University of Valencia21, King's College London22, Royal Cornhill Hospital23, Duke University24, University of Santiago de Compostela25, Hospital General Universitario Gregorio Marañón26, Karolinska Institutet27, Hammersmith Hospital28, GlaxoSmithKline29, Sichuan University30
TL;DR: Findings implicating the MHC region are consistent with an immune component to schizophrenia risk, whereas the association with NRGN and TCF4 points to perturbation of pathways involved in brain development, memory and cognition.
Abstract: Schizophrenia is a complex disorder, caused by both genetic and environmental factors and their interactions. Research on pathogenesis has traditionally focused on neurotransmitter systems in the brain, particularly those involving dopamine. Schizophrenia has been considered a separate disease for over a century, but in the absence of clear biological markers, diagnosis has historically been based on signs and symptoms. A fundamental message emerging from genome-wide association studies of copy number variations (CNVs) associated with the disease is that its genetic basis does not necessarily conform to classical nosological disease boundaries. Certain CNVs confer not only high relative risk of schizophrenia but also of other psychiatric disorders. The structural variations associated with schizophrenia can involve several genes and the phenotypic syndromes, or the 'genomic disorders', have not yet been characterized. Single nucleotide polymorphism (SNP)-based genome-wide association studies with the potential to implicate individual genes in complex diseases may reveal underlying biological pathways. Here we combined SNP data from several large genome-wide scans and followed up the most significant association signals. We found significant association with several markers spanning the major histocompatibility complex (MHC) region on chromosome 6p21.3-22.1, a marker located upstream of the neurogranin gene (NRGN) on 11q24.2 and a marker in intron four of transcription factor 4 (TCF4) on 18q21.2. Our findings implicating the MHC region are consistent with an immune component to schizophrenia risk, whereas the association with NRGN and TCF4 points to perturbation of pathways involved in brain development, memory and cognition.
1,625 citations
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Lundbeck1, Aarhus University2, Harvard University3, Broad Institute4, Karolinska Institutet5, Cardiff University6, Statens Serum Institut7, QIMR Berghofer Medical Research Institute8, deCODE genetics9, University of Iceland10, Mental Health Services11, Charité12, University of California, Los Angeles13, Semel Institute for Neuroscience and Human Behavior14, University of Queensland15, Oslo University Hospital16, King's College London17, University of Toronto18, VU University Amsterdam19, Radboud University Nijmegen20, Yale University21, Veterans Health Administration22, Children's Hospital of Philadelphia23, Haukeland University Hospital24, University of Bergen25, University of Pennsylvania26, I.M. Sechenov First Moscow State Medical University27, University of Würzburg28, Maastricht University29, Goethe University Frankfurt30, Universidade Federal do Rio Grande do Sul31, Icahn School of Medicine at Mount Sinai32, University of North Carolina at Chapel Hill33, Emory University34, University of Copenhagen35, Aarhus University Hospital36, State University of New York Upstate Medical University37
TL;DR: A genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls identifies variants surpassing genome- wide significance in 12 independent loci and implicates neurodevelopmental pathways and conserved regions of the genome as being involved in underlying ADHD biology.
Abstract: 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.
1,436 citations
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Cardiff University1, Harvard University2, Charité3, King's College London4, Broad Institute5, University of Adelaide6, Centre for Mental Health7, University of Queensland8, University of Münster9, University of Edinburgh10, QIMR Berghofer Medical Research Institute11, University of Vigo12, University of California, Los Angeles13, Icahn School of Medicine at Mount Sinai14, University of Oviedo15, Aarhus University16, Lundbeck17, Oslo University Hospital18, University of Oslo19, Statens Serum Institut20, University of Bergen21, Aarhus University Hospital22, University of Copenhagen23, University of Belgrade24, Tbilisi State Medical University25, deCODE genetics26, University of Verona27, Mental Health Services28, Eli Lilly and Company29, Martin Luther University of Halle-Wittenberg30, Ludwig Maximilian University of Munich31
TL;DR: A new genome-wide association study of schizophrenia is reported, and through meta-analysis with existing data and integrating genomic fine-mapping with brain expression and chromosome conformation data, 50 novel associated loci and 145 loci are identified.
Abstract: Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population.
1,259 citations
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TL;DR: Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
6,809 citations
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5,173 citations
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TL;DR: In a meta-analysis, Julianne Holt-Lunstad and colleagues find that individuals' social relationships have as much influence on mortality risk as other well-established risk factors for mortality, such as smoking.
Abstract: Background
The quality and quantity of individuals' social relationships has been linked not only to mental health but also to both morbidity and mortality.
Objectives
This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk.
Data Extraction
Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships.
Results
Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44).
Conclusions
The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality.
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5,070 citations
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TL;DR: A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.
Abstract: Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases. A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.
4,913 citations