Author
Henrik B. Rasmussen
Other affiliations: Roskilde University
Bio: Henrik B. Rasmussen is an academic researcher from Copenhagen University Hospital. The author has contributed to research in topics: Endogenous retrovirus & Carboxylesterase 1. The author has an hindex of 28, co-authored 90 publications receiving 4515 citations. Previous affiliations of Henrik B. Rasmussen include Roskilde University.
Papers published on a yearly basis
Papers
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Maastricht University Medical Centre1, deCODE genetics2, Utrecht University3, University of California, Los Angeles4, 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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Bjarni J. Vilhjálmsson1, Jian Yang2, Hilary K. Finucane3, Alexander Gusev4 +391 more•Institutions (14)
TL;DR: LDpred is introduced, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel, and outperforms the approach of pruning followed by thresholding, particularly at large sample sizes.
Abstract: Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.
1,088 citations
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Copenhagen University Hospital1, deCODE genetics2, Ludwig Maximilian University of Munich3, University of Bonn4, Utrecht University5, GlaxoSmithKline6, University of Aberdeen7, King's College London8, Radboud University Nijmegen Medical Centre9, University of Verona10, University of Oslo11, University of California, Los Angeles12, Heidelberg University13, Broad Institute14, Wellcome Trust Sanger Institute15
TL;DR: It is concluded that duplications and perhaps also deletions of chromosome 16p13.1, previously reported to be associated with autism and MR, also confer risk of schizophrenia.
Abstract: Deletions and reciprocal duplications of the chromosome 16p13.1 region have recently been reported in several cases of autism and mental retardation (MR). As genomic copy number variants found in these two disorders may also associate with schizophrenia, we examined 4345 schizophrenia patients and 35,079 controls from 8 European populations for duplications and deletions at the 16p13.1 locus, using microarray data. We found a threefold excess of duplications and deletions in schizophrenia cases compared with controls, with duplications present in 0.30% of cases versus 0.09% of controls (P=0.007) and deletions in 0.12 % of cases and 0.04% of controls (P>0.05). The region can be divided into three intervals defined by flanking low copy repeats. Duplications spanning intervals I and II showed the most significant (P = 0.00010) association with schizophrenia. The age of onset in duplication and deletion carriers among cases ranged from 12 to 35 years, and the majority were males with a family history of psychiatric disorders. In a single Icelandic family, a duplication spanning intervals I and II was present in two cases of schizophrenia, and individual cases of alcoholism, attention deficit hyperactivity disorder and dyslexia. Candidate genes in the region include NTAN1 and NDE1. We conclude that duplications and perhaps also deletions of chromosome 16p13.1, previously reported to be associated with autism and MR, also confer risk of schizophrenia.
258 citations
01 Jan 2017
TL;DR: A centralized analysis pipeline was applied to a SCZ cohort of 21,094 cases and 20,227 controls and Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.
Abstract: Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10−15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.
173 citations
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deCODE genetics1, Aarhus University Hospital2, Aarhus University3, University of Oslo4, Copenhagen University Hospital5, University of Iceland6, Utrecht University7, University of California, Los Angeles8, University of Bonn9, University of Helsinki10, Wellcome Trust Sanger Institute11, National Institutes of Health12, Ludwig Maximilian University of Munich13, Glostrup Hospital14, Heidelberg University15, Semmelweis University16, University of Verona17, Radboud University Nijmegen Medical Centre18, Russian Academy19, King's College London20, Sichuan University21, Royal Cornhill Hospital22, Karolinska Institutet23
TL;DR: As it has been proposed that variants such as rs1344706[T]—common and with low relative risk—may also serve to identify regions harboring less common, higher-risk susceptibility alleles, ZNF804A is searched for large copy number variants (CNVs) in psychosis patients and patients with other psychiatric disorders and 39 481 controls.
Abstract: A trio of genome-wide association studies recently reported sequence variants at three loci to be significantly associated with schizophrenia. No sequence polymorphism had been unequivocally (P<5 × 10(-8)) associated with schizophrenia earlier. However, one variant, rs1344706[T], had come very close. This polymorphism, located in an intron of ZNF804A, was reported to associate with schizophrenia with a P-value of 1.6 × 10(-7), and with psychosis (schizophrenia plus bipolar disorder) with a P-value of 1.0 × 10(-8). In this study, using 5164 schizophrenia cases and 20,709 controls, we replicated the association with schizophrenia (odds ratio OR = 1.08, P = 0.0029) and, by adding bipolar disorder patients, we also confirmed the association with psychosis (added N = 609, OR = 1.09, P = 0.00065). Furthermore, as it has been proposed that variants such as rs1344706[T]-common and with low relative risk-may also serve to identify regions harboring less common, higher-risk susceptibility alleles, we searched ZNF804A for large copy number variants (CNVs) in 4235 psychosis patients, 1173 patients with other psychiatric disorders and 39,481 controls. We identified two CNVs including at least part of ZNF804A in psychosis patients and no ZNF804A CNVs in controls (P = 0.013 for association with psychosis). In addition, we found a ZNF804A CNV in an anxiety patient (P = 0.0016 for association with the larger set of psychiatric disorders).
164 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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Harvard University1, Broad Institute2, QIMR Berghofer Medical Research Institute3, Cardiff University4, North Carolina State University5, Trinity College, Dublin6, University of Edinburgh7, Karolinska Institutet8, Uppsala University9, University of Southern California10, University of North Carolina at Chapel Hill11, University College London12, National Health Service13, University of Oxford14, University of Aberdeen15, Strathclyde Institute of Pharmacy and Biomedical Sciences16, State University of New York Upstate Medical University17, University of Coimbra18
TL;DR: The extent to which common genetic variation underlies the risk of schizophrenia is shown, using two analytic approaches, and the major histocompatibility complex is implicate, which is shown to involve thousands of common alleles of very small effect.
Abstract: Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%(1,2). We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases.
4,573 citations
01 Jan 2011
TL;DR: The sheer volume and scope of data posed by this flood of data pose a significant challenge to the development of efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.
2,187 citations
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TL;DR: Genome-wide polygenic risk scores derived from GWAS data for five common diseases can identify subgroups of the population with risk approaching or exceeding that of a monogenic mutation.
Abstract: A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation1. Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature2-5, it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For coronary artery disease, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk6. We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.
1,962 citations