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Mors, O.

Publications and source records attributed to Mors, O..

At least 19 recordsLinked to original sources
bioRxiv2022

Single molecule long-read real-time amplicon-based sequencing of CYP2D6: a proof-of-concept with hybrid haplotypes

CYP2D6 is a widely expressed human xenobiotic metabolizing enzyme, best known for its role in the hepatic phase I cytochrome P450 enzyme system, where it metabolizes [~]20% of medications. It is also expressed in other organs including the brain, where its potential role in physiology and mental health traits and disorders is under further investigation. Owing to the presence of homologous pseudogenes in the CYP2D locus and transposable repeat elements in the intergenic regions, the gene encoding the CYP2D6 enzyme, CYP2D6, is one of the most hypervariable known human genes - with more than 165 core haplotypes. Haplotypes include structural variants, with a subtype of these known as hybrid haplotypes or fusion genes comprising part of CYP2D6 and part of its adjacent pseudogene, CYP2D7. The fusion genes are particularly challenging to identify. High fidelity (HiFi) single molecule real-time (SMRT) long-read sequencing can cover whole CYP2D6 haplotypes in a single continuous sequence, and is therefore ideal for structural variant detection. In addition, it is highly accurate and suitable for novel haplotype identification, which is necessary as new CYP2D6 haplotypes are continuously being discovered, and many more likely remain to be identified in relatively understudied populations such as Indigenous Peoples. The aim of the present work was to develop an efficient and accurate HiFi SMRT amplicon-based method capable of detecting the full range of CYP2D6 haplotypes including fusion genes. We report proof-of-concept for 24 amplicons including three positive controls, aligned to fusion gene haplotypes, with prior cross-validation data. Amplicons with CYP2D7-D6 fusion genes, including positive controls, aligned to the *13 subhaplotypes predicted (*13F, *13A2) with 100% accuracy, with the exception of one that aligned at 99.9%. Alignment of the *68 was 100% and above 99.9% to the CYP2D6*68 partial sequences EU5300606 and JF307779, respectively. The best alignments for the remaining CYP2D6-2D7 fusion genes were [≥]99.7% (to 3 significant figures). Lower percentage alignment for CYP2D6-2D7 fusion genes may reflect imperfect PCR optimization and/or the possibility that we may have haplotypes not yet in public databases. Further work on these is in progress. Moreover, we have adapted this method for non-hybrid haplotypes. This technique could therefore suffice for the characterization of the full range of CYP2D6 haplotypes. The method that we have developed could be extended to other complex loci and to other species in a multiplexed high throughput assay.

genomics↗
bioRxiv2022

Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks

Sample recruitment for research consortia, hospitals, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies systematically, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH consortium dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied both by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can modestly bias association tests and reduce predictive utility of polygenic scores. This is the largest, most comprehensive comparison of data integration approaches in the context of a large psychiatric biobank.

bioinformatics↗
bioRxiv2021

Accounting for age-of-onset and family history improves power in genome-wide association studies

Genome-wide association studies (GWAS) have revolutionized human genetics, allowing researchers to identify thousands of disease-related genes and possible drug targets. However, case-control status does not account for the fact that not all controls may have lived through their period of risk for the disorder of interest. This can be quantified by examining the age-of-onset distribution and the age of the controls or the age-of-onset for cases. The age-of-onset distribution may also depend on information such as sex and birth year. In addition, family history is not routinely included in the assessment of control status. Here we present LT-FH++, an extension of the liability threshold model conditioned on family history (LT-FH), that jointly accounts for age-of-onset and sex, as well as family history. Using simulations, we show that, when family history and the age-of-onset distribution are available, the proposed approach yields large power gains over both LT-FH and genome-wide association study by proxy (GWAX). We applied our method to four psychiatric disorders available in the iPSYCH data, and to mortality in the UK Biobank, finding 20 genome-wide significant associations with LT-FH++, compared to 10 for LT-FH and 8 for a standard case-control GWAS. As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FH++, to become even more beneficial.

bioinformatics↗
bioRxiv2020

Association of educational attainment polygenic score with school grades in individuals with and without psychiatric disorders.

Suboptimal school performance is often seen in children with psychiatric disorders and is influenced by both genetics and the environment. Educational attainment polygenic score (EA-PGS) has been shown to significantly predict school performance in the general population. Here we analyze the association of EA-PGS with school performance in 18,495 children with and 12,487, without one or more of six psychiatric disorders and show that variance explained in the school performance by the EA-PGS is substantially lower in children with attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Accounting for parents socioeconomic status obliterated the variance difference between ADHD-but not ASD-and controls. Given that a large proportion of the prediction performance of EA-PGS originate from family environment, our findings hint that family environmental influences on school performance might differ between ADHD and controls; studying the same further will open new avenues to improve the school performance of children with ADHD.

genetics↗
bioRxiv2020

Genome-wide association study of school grades identifies a genetic overlap between language ability, psychopathology and creativity

Individuals with psychiatric disorders perform differently in school compared to the general population. Genetic factors contribute substantially to such differences. It is however unclear if differential performance is seen across all cognitive domains such as math and language. Here we report a genome-wide association study (GWAS) of school grades in 30,982 individuals (18,495 with and 12,487 without one or more of six major psychiatric disorders) and a replication study in 4,547 individuals. GWAS of overall school performance yielded results that were highly similar to the results of a previous GWAS of educational attainment. Analyzing subject specific grades, we observed that math performance was severely affected whereas language performance (Danish and English) was relatively unaffected or enhanced in those with psychiatric disorders compared to controls. We found that the genetic variants associated with poor math performance, but better language performance were also associated with increased risk for multiple psychiatric disorders. The same variants were also associated with creativity, which we show through a polygenic score analysis of 2953 creative professionals and 164,622 controls. The results overall suggest that risk for psychiatric disorders, language ability and creativity might have overlapping genetic roots.

genomics↗
bioRxiv2019

Cross-validation of technologies for genotyping CYP2D6 and CYP2C19

BackgroundCYP2D6 and CYP2C19 are cytochrome P450 enzymes involved in the metabolism of many medications from multiple therapeutic classes. Associations between patterns of variants (known as haplotypes) in the genes encoding them (CYP2D6 and CYP2C19) and enzyme activities are well described. The genes in fact comprise 21% of biomarkers in drug labels. Despite this, genotyping is not common, partly attributable to its challenging nature (CYP2D6 having >100 haplotypes, including those with sequence from an adjacent pseudogene, and gene duplications). We cross-validated different methodologies for identifying haplotypes in these genes against each other. MethodsNinety-two samples with a variety of CYP2D6 and CYP2C19 genotypes according to prior AmpliChip CYP450 and TaqMan CYP2C19*17 data were selected from the Genome-based therapeutic drugs for depression (GENDEP) study. Genotyping was performed with TaqMan copy number variant (CNV) and single nucleotide variant (SNV) analysis, the next generation sequencing-based Ion S5 AmpliSeq Pharmacogenomics Panel, PharmacoScan, long-range polymerase chain reaction (L-PCR) followed by amplicon analysis, and Agena for CYP2C19. Variant pattern to haplotype translation was automated. ResultsThe inter-platform concordance for CYP2C19 was high (up to 100% for available data). For CYP2D6, the IonS5-PharmacoScan concordance was 94% for a range of variants tested apart from those with at least one extra copy of a CYP2D6 gene (occurring at a frequency of 3.8%, 33/853), or those with substantial sequence derived from pseudogene, known as hybrids (3%, 26/853). ConclusionsInter-platform concordance for CYP2C19 was high, and, moreover, the Ion S5 and PharmacoScan data were 100% concordant with that from a TaqMan CYP2C19*2 assay. We have also demonstrated feasibility of using an NGS platform for genotyping CYP2D6 and CYP2C19, with automated data interpretation methodology. This points the way to a method of making CYP2D6 and CYP2C19 genotyping more readily accessible.

genetics↗
bioRxiv2019

Meta-analysis of Scandinavian Schizophrenia Exomes

Rare genetic variants may play a prominent role in schizophrenia. We report on the to date largest whole exome sequencing study of schizophrenia case-control samples from related populations and combine with other available sequence data, analysing in total 34,084 individuals (14,302 cases). Three genes showed significant association at FDR < 0.10 (SETD1A, TAF13 and MKI67) and gene-set analyses highlighted the involvement of the synaptome and excitatory neurons, and demonstrated shared architecture with high-functioning autism.

genetics↗
bioRxiv2019

Identification of risk variants and characterization of the polygenic architecture of disruptive behavior disorders in the context of ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). ADHD comorbid with DBDs (ADHD+DBDs) is a complex phenotype with a risk component that can be attributed to common genetic variants. Here we report a large GWAS meta-analysis of ADHD+DBDs based on seven cohorts in total including 3,802 cases and 31,305 controls. Three genome-wide significant loci were identified on chromosomes 1, 7, and 11. A GWAS meta-analysis including a Chinese cohort supported the locus on chromosome 11 to be a strong risk locus for ADHD+DBDs across European and Chinese ancestries (rs7118422, P=3.15x10-10, OR=1.17). This locus was not associated with ADHD without DBDs in a secondary GWAS of 13,583 ADHD cases and 22,314 controls, suggesting that the locus is a specific risk locus for the comorbid phenotype.\n\nWe found a higher SNP heritability for ADHD+DBDs (h2SNP =0.34) when compared to ADHD without DBDs (h2SNP =0.20). Genetic correlations of ADHD+DBDs with aggressive (rg =0.81) and anti-social behaviors (rg=0.82) were high, and polygenic risk score analyses revealed a significant increased burden of variants associated with ADHD and aggression in individuals with ADHD+DBDs compared to ADHD without DBDs. Our results suggests that ADHD+DBDs represent a more severe phenotype with respect to the genetic risk load than ADHD without DBDs, in line with previous studies, and that the risk load to some extent can be explained by variants associated with aggressive behavior.

genomics↗
bioRxiv2019

Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders - findings from a Danish population-based study

BackgroundPrevious studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders.\n\nMethodsWe used diagnostic information for patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on two diseases. The genetic factors were investigated using GWAS and HLA imputation data based on iPSYCH cohort.\n\nResultsAmong 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1,383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two diseases (P=2.67x10-7, OR=1.38, 95%CI=1.22-1.56), with an overall bidirectional association wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR=1.13, 95%CI: 1.07-1.21, P=7.95x10-5) and vice versa (HR=1.27, 95%CI=1.16-1.39, P=8.77x10-15). Though PRSs were significantly correlated with both types of diagnosis, PRSs had little effect on the bidirectional relationship. Importantly, we for the first time observed 12 human leukocyte antigen (HLA) loci and 20 HLA alleles strongly associated with overall autoimmune diseases, but we did not find significant evidence of their associations with overall mental disorders.\n\nConclusionsOur findings confirm the overall comorbidity and bidirectionality between autoimmune and mental disorders and discover HLA genes which are significantly associated with overall autoimmune diseases, but not with overall mental disorders.

bioinformatics↗
bioRxiv2018

Genetic variation in the Major Histocompatibility Complex and association with depression

BackgroundThe prevalence of depression is higher in individuals suffering from autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Epidemiological findings point to a bi-directional relationship - that depression increases the risk of developing an autoimmune disease, and vice-versa. Shared genetic etiology is a plausible explanation for the overlap between depression and autoimmune diseases. In this study we tested whether genetic variation in the Major Histocompatibility Complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression.\n\nMethodWe fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 Human Leukocyte Antigen (HLA) alleles and four Complement Component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium (PGC) Major Depressive Disorder (MDD) working group and the UK Biobank (UKB). In the 26 PGC-MDD studies, cases met a lifetime diagnosis of MDD, determined by a structured diagnostic interview. In the UKB, cases and controls were identified from an online mental health questionnaire. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants in each study and performed an inverse-variance weighted meta-analysis across the PGC-MDD and UKB samples, applying both a conservative region-wide significance threshold (3.9-e6) and a candidate threshold (1.6e-4).\n\nResultsNo HLA alleles or C4 haplotypes were associated with depression at the conservative threshold in the PGC, UKB or meta-analysis. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold in the meta-analysis. Under the conservative threshold, 70 SNPs were detected in the UKB and 143 SNPs were detected in the meta-analysis, mirroring previous findings from highly powered GWAS of depression.\n\nDiscussionWe found no evidence that HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia, confer risk for depression. These results indicate that autoimmune diseases and depression do not share common risk loci of moderate or large effect in the MHC.

genetics↗
bioRxiv2018

Statin treatment and the risk of depression

The effect of statin treatment on the risk of developing depression remains unclear. Therefore, we aimed to assess the association between statin treatment and depression in a nationwide register-based cohort study with up to 20 years of follow up. We identified all statin users among all individuals born in Denmark between 1920 and 1983. One non-user was matched to each statin user based on age, sex and a propensity score taking several potential confounders into account. Using Cox regression we investigated the association between statin use and: I) redemption of prescriptions for antidepressants, II) redemption of prescriptions for any other drug, III) depression diagnosed at psychiatric hospitals, IV) cardiovascular mortality and V) all-cause mortality. A total of 193,977 statin users and 193,977 non-users were followed for 2,621,282 person-years. Statin use was associated with I) increased risk of antidepressant use (hazard rate ratio (HRR)=1.33; 95% confidence interval (95%-CI)=1.31-1.36), II) increased risk of any other prescription drug use (HRR=1.33; 95%-CI=1.31-1.35), III) increased risk of receiving a depression diagnosis (HRR=1.22, 95%-CI=1.12-1.32) - but not after adjusting for antidepressant use (HRR=1.07, 95%-CI=0.99- 1.15), IV) reduced cardiovascular mortality (HRR=0.92, 95%-CI=0.87-0.97) and V) reduced all-cause mortality (HRR=0.90, 95%-CI=0.88-0.92). These results suggest that the association between statin treatment and antidepressant use was unspecific (equivalent association between statins and other drugs) and that the association between statin use and depression diagnoses was mediated by antidepressant use. Thus, statin users and non-users appear to be equally likely to develop depression, but the depression is more often detected/treated among statin users.

epidemiology↗
bioRxiv2018

Assessing 42 inflammatory markers in 321 control subjects and 887 major depressive disorder cases: BMI and other confounders and overall predictive ability for current depression

Inflammatory markers such as cytokines represent potential biomarkers for major depressive disorder (MDD). Many, generally small studies have examined the role of single markers and found significant associations. We assessed 42 inflammatory markers, namely cytokines, in the blood of 321 control subjects and 887 MDD cases. We tested whether individual inflammatory marker levels were significantly affected by MDD case/control status, current episode, or current depression severity, co-varying for age, sex, body mass index (BMI), smoking, current antidepressant use, ethnicity, assay batch and study effects. We further used machine learning algorithms to investigate if we could use our data to blindly discriminate MDD patients, or those in a current episode. We found broad and powerful influences of confounding factors on log-protein levels. Notably, IL-6 levels were very strongly influenced by BMI (p = 1.37 x 10-43, variance explained = 18%), while Interleukin-16 was the most significant predictor of current depressive episode (p = 0.003, variance explained = 0.9%, q < 0.1). No single inflammatory marker predicted MDD case/control status when a subject was not in a depressed episode, nor did any predict depression severity. Machine learning results revealed that using inflammatory marker data with clinical confounder information significantly increased precision for differentiating MDD patients who were in an episode. To conclude, a wide panel of inflammatory markers alongside clinical information may aid in predicting the onset of symptoms, but no single inflammatory protein is likely to represent a clinically useful biomarker for MDD diagnosis or prognosis. We note that the potential influence of physical health related and population stratification related confounders on inflammatory biomarker studies in psychiatry is considerable.

neuroscience↗
bioRxiv2018

Genome-wide Association Study of Anxiety and Stress-related Disorders in the iPSYCH Cohort

Anxiety and stress-related disorders (ASRD) are among the most common mental disorders with the majority of patients suffering from additional disorders. Family and twin studies indicate that genetic and environmental factors are underlying their etiology. As ASRD are likely to configure various expressions of abnormalities in the basic stress-response system, we conducted a genome-wide association study including 12,655 cases with various anxiety and stress-related diagnoses and 19,225 controls. Standard association analyses were performed supplemented by a framework of sensitivity analyses. Variants in PDE4B showed consistent association with ASRD across a wide range of our analyses. In mice models, alternations in PDE4B expression were observed in those mice displaying anxious behavior after exposure to chronic stress. We also showed that 28% of the variance in ASRD was accounted for by common variants and that the genetic signature of ASRD overlapped with psychiatric traits, educational outcomes, obesity-related phenotypes, smoking, and reproductive success.

genetics↗
bioRxiv2018

Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: meta-analysis of data from genome-wide association studies

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects.\n\nCYP2C19 phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was percentage symptom improvement and remission. Side effect data were available at weeks 2-4, 6 and 9 in three of the investigated samples. A fixed-effects meta-analysis was performed using EM as the reference group.\n\nAnalysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD=0.43, CI=0.19-0.66) and higher remission rates (OR=1.55, CI=1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR=1.26, CI=1.08-1.47), neurological (OR=1.28, CI=1.07-1.53) and sexual side effects (OR=1.52, CI=1.23-1.87; week 6 values similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups.\n\nCYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs are relatively rare among Caucasians (~2%).

genetics↗
bioRxiv2018

The behavioral and neurobiological effects of reduced Brd1 expression in mice are sex-biased and implicate gender dependent dysregulation of nuclear receptor mediated signaling in mental disorders

The schizophrenia and bipolar disorder associated gene, BRD1, encodes a scaffold protein that in complex with epigenetic modifiers regulate gene sets enriched for psychiatric disorder risk. Preclinical evidence from male Brd1+/- mice has previously implicated BRD1 with phenotypes of translational relevance to schizophrenia. Here we describe the phenotype of female Brd1+/- mice and report attenuated dendritic architecture and monoaminergic dysregulation accompanied by sex-specific changes in affective behaviors. In accordance, global gene expression profiling reveals regional dysregulation of gene sets enriched with major depressive disorder and schizophrenia risk in female and male Brd1+/- mice, respectively. Independent of sex, however, differentially expressed genes cluster in common functional pathways associated with psychiatric disorders, including mitochondrial dysfunction and oxidative phosphorylation as well as G-protein coupled-, and nuclear receptor mediated signaling. Accordingly, we provide in vitro evidence that BRD1 modulates the transcriptional drive of a subset of nuclear receptors (e.g. the vitamin D and glucocorticoid receptors). Moreover, we demonstrate enrichment of psychiatric disorder risk in the target genes of nuclear receptors, sex-biased expression of several nuclear receptor genes in the adult brain of Brd1+/- mice, and that sex-biased genes in general are enriched with nuclear receptor genes particularly at the earliest developmental stage of the human brain. Overall, our data suggests that the spatio-temporal interaction between BRD1 and subsets of nuclear receptors in the brain is sex-biased and that hampered BRD1 mediated regulation of target genes governed by certain nuclear receptors may significantly contribute to sex differences in psychopathology.

neuroscience↗
bioRxiv2017

A genome-wide association study for shared risk across major psychiatric disorders in a nation-wide birth cohort implicates fetal neurodevelopment as a key mediator

There is mounting evidence that seemingly diverse psychiatric disorders share genetic etiology, but the biological substrates mediating this overlap are not well characterized. Here, we leverage the unique iPSYCH study, a nationally representative cohort ascertained through clinical psychiatric diagnoses indicated in Danish national health registers. We confirm previous reports of individual and cross-disorder SNP-heritability for major psychiatric disorders and perform a cross-disorder genome-wide association study. We identify four novel genome-wide significant loci encompassing variants predicted to regulate genes expressed in radial glia and interneurons in the developing neocortex during midgestation. This epoch is supported by partitioning cross-disorder SNP-heritability which is enriched at regulatory chromatin active during fetal neurodevelopment. These findings indicate that dysregulation of genes that direct neurodevelopment by common genetic variants results in general liability for many later psychiatric outcomes.

genetics↗
bioRxiv2017

Genome-wide association study implicates CHRNA2 in cannabis use disorder

Introductory paragraphCannabis is the most frequently used illicit psychoactive substance worldwide1. Life time use has been reported among 35-40% of adults in Denmark2 and the United States3. Cannabis use is increasing in the population4-6 and among users around 9% become dependent7. The genetic risk component is high with heritability estimates of 518-70%9. Here we report the first genome-wide significant risk locus for cannabis use disorder (CUD, P=9.31x10-12) that replicates in an independent population (Preplication=3.27x10-3, Pmetaanalysis=9.09x10-12). The finding is based on a genome-wide association study (GWAS) of 2,387 cases and 48,985 controls followed by replication in 5,501 cases and 301,041 controls. The index SNP (rs56372821) is a strong eQTL for CHRNA2 and analyses of the genetic regulated gene expressions identified significant association of CHRNA2 expression in cerebellum with CUD. This indicates a potential therapeutic use in CUD of compounds with agonistic effect on the neuronal acetylcholine receptor alpha-2 subunit encoded by CHRNA2. At the polygenic level analyses revealed a significant decrease in the risk of CUD with increased load of variants associated with cognitive performance.

genomics↗