Time filter

Source Type

Steinhausen H.-C.,University of Aalborg | Steinhausen H.-C.,University of Basel | Steinhausen H.-C.,University of Zürich | Jakobsen H.,University of Aalborg | And 3 more authors.
International Journal of Eating Disorders | Year: 2015

Objective This nation-wide register-based study investigated how often anorexia nervosa (AN) and co-morbid disorders occur in affected families compared with control families. Furthermore, the study addressed the impact of sex, year of birth, and degree of urbanization in terms of risk factors.Method A total of N=2,370 child and adolescent psychiatric subjects born between 1951 and 1996 and registered in the Danish Psychiatric Central Research Register (DPCRR) had any mental disorder before the age of 18 and developed AN at some point during their life-time. In addition, N=7,035 controls without any psychiatric diagnosis before age 18 and matched for age, sex, and residential region were included. Psychiatric diagnoses were also obtained on the first-degree relatives as a part of the Danish Three Generation Study (3GS). A family load component was obtained by using various mixed regression models.Results AN occurred significantly more often in case than in control families. AN Risk factors included having a sibling with AN, affective disorders in family members, and co-morbid affective, anxiety, obsessive-compulsive, personality, or substance use disorders. Furthermore, female sex, and ascending year of birth were significantly associated with having AN. Urbanization was not related to the family load of AN and case-relatives did not develop AN earlier than control relatives.Discussion These findings based on a very large and representative dataset provide evidence for the family aggregation and further risk factors in AN. © 2014 Wiley Periodicals, Inc.


Thompson W.K.,Institute of Biological Psychiatry | Thompson W.K.,Lundbeck | Thompson W.K.,University of California at San Diego | Wang Y.,University of Oslo | And 10 more authors.
PLoS Genetics | Year: 2015

Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn’s disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of pervasive small but replicating effects in CD and SZ on genomic control and power. Finally, we conclude that, despite having very similar estimates of variance explained by genotyped SNPs, CD and SZ have a broadly dissimilar genetic architecture, due to differing mean effect size and proportion of non-null loci. © 2015 Thompson et al.


PubMed | Institute of Biological Psychiatry, DeCODE Genetics Inc., University of Oslo, University of Heidelberg and Copenhagen University
Type: Journal Article | Journal: Nordic journal of psychiatry | Year: 2016

The dopamine transporter, also known as solute carrier 6A3 (SLC6A3), plays an important role in synaptic transmission by regulating the reuptake of dopamine in the synapses. In line with this, variations in the gene encoding this transporter have been linked to both schizophrenia and affective disorders. Recently, copy number variants (CNVs) in SLC6A3 have been identified in healthy subjects but so far, the implication of CNVs affecting this gene in psychiatric diseases has not been addressed.In the present study, we aimed to investigate whether CNVs affecting SLC6A3 represent rare high-risk variants of psychiatric disorders.We performed a systematic screening for CNVs affecting SLC6A3 in 761 healthy controls, 672 schizophrenia patients, and 194 patients with bipolar disorder in addition to 253 family members from six large pedigrees affected by mental disorders using single nucleotide polymorphism arrays and subsequent verification by real-time polymerase chain reaction.We identified two duplications and one deletion affecting SLC6A3 in the patients, while no such CNVs were identified in any of the controls. The identified CNVs were of different sizes and two affected several genes in addition to SLC6A3.Our findings suggest that rare high-risk CNVs affecting the gene encoding the dopamine transporter contribute to the pathogenesis of schizophrenia and affective disorders.


PubMed | Karolinska Institutet, Finnish National Institute for Health and Welfare, University of Turku, St George's, University of London and 34 more.
Type: Journal Article | Journal: Nature genetics | Year: 2016

Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 10(-8)) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.


PubMed | University of Michigan, University of Oslo, University Utrecht, Australian Department of Primary Industries and Fisheries and 16 more.
Type: Journal Article | Journal: Nature genetics | Year: 2015

Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 10(-8); BMI, P < 5.95 10(-4)), and we find an among-population genetic correlation for tall and slender individuals (r = -0.80, 95% CI = -0.95, -0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).


PubMed | Institute of Biological Psychiatry, University of Oslo and University of California at San Diego
Type: Journal Article | Journal: PLoS genetics | Year: 2015

Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohns disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of pervasive small but replicating effects in CD and SZ on genomic control and power. Finally, we conclude that, despite having very similar estimates of variance explained by genotyped SNPs, CD and SZ have a broadly dissimilar genetic architecture, due to differing mean effect size and proportion of non-null loci.


Cruger A.-M.T.,Bispebjerg Hospital | Kaur-Knudsen D.,Gentofte Hospital | Zachariae C.,Gentofte Hospital | Rasmussen H.B.,Institute of Biological Psychiatry | Thomsen S.F.,Bispebjerg Hospital
Danish Medical Journal | Year: 2015

Introduction: The aim of this study was to examine risk factors and mortality among patients with erythema multiforme (EM), Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Methods: This was a retrospective evaluation of the medical records of 250 patients from two Danish tertiary dermatological departments during a ten-year period. Results: In a total of 192 cases (77.4%), the primary diagnosis of EM (66.5%), SJS (62.2%) and TEN (100%) was confirmed, whereas the remaining cases (22.6%) were diagnosed differently. Antibiotics and allopurinol were predominantly associated with TEN, whereas SJS was associated with a broad spectrum of drugs. EM was related mainly to viral infections, predominantly herpes (30.6%); 38.2% of the causes of EM remained unknown. Patients with TEN had the highest mortality; i.e. 60% in the course of the ten-year study period: adjusted hazard ratio (HR) = 11.2 (95% confidence interval (CI): 3.65-34.35); p < 0.001 compared with EM patients. The risk of death was also increased among patients with SJS relative to patients with EM: HR = 2.60 (95% CI: 1.10-6.16); p = 0.030; however, this did not remain statistically significant after adjustment for age, co-morbidity, infection, cancer and polypharmacy, HR = 0.99 (95% CI: 0.38-2.57); p = 0.976. ConclusionS: We validated diagnoses in 250 patients with EM, SJS and TEN diagnosed during a ten-year period. The survival of patients with TEN was expectedly low compared with patients with EM. We extend previous findings by showing that after adjustment for confounders, the survival rates of SJS and EM are comparable. Funding: not relevant. Trial registration: not relevant. © 2015, Danish Medical Association. All rights reserved.


Farrell M.S.,University of North Carolina at Chapel Hill | Werge T.,Institute of Biological Psychiatry | Werge T.,Copenhagen University | Werge T.,Lundbeck | And 11 more authors.
Molecular Psychiatry | Year: 2015

Prior to the genome-wide association era, candidate gene studies were a major approach in schizophrenia genetics. In this invited review, we consider the current status of 25 historical candidate genes for schizophrenia (for example, COMT, DISC1, DTNBP1 and NRG1). The initial study for 24 of these genes explicitly evaluated common variant hypotheses about schizophrenia. Our evaluation included a meta-analysis of the candidate gene literature, incorporation of the results of the largest genomic study yet published for schizophrenia, ratings from informed researchers who have published on these genes, and ratings from 24 schizophrenia geneticists. On the basis of current empirical evidence and mostly consensual assessments of informed opinion, it appears that the historical candidate gene literature did not yield clear insights into the genetic basis of schizophrenia. A likely reason why historical candidate gene studies did not achieve their primary aims is inadequate statistical power. However, the considerable efforts embodied in these early studies unquestionably set the stage for current successes in genomic approaches to schizophrenia. © 2015 Macmillan Publishers Limited.

Loading Institute of Biological Psychiatry collaborators
Loading Institute of Biological Psychiatry collaborators