Publications by authors named "Manuel Mattheisen"

153 Publications

The Genetic Architecture of Obsessive-Compulsive Disorder: Contribution of Liability to OCD From Alleles Across the Frequency Spectrum.

Am J Psychiatry 2021 Nov 18:appiajp202121010101. Epub 2021 Nov 18.

Seaver Autism Center for Research and Treatment (Mahjani, Reichenberg, Sandin, Buxbaum, Grice),Division of Tics, Obsessive-Compulsive Disorder (OCD), and Related Disorders (Mahjani, Grice),Department of Psychiatry (Mahjani, Reichenberg, Sandin, Buxbaum, Grice),Mindich Child Health and Development Institute (Reichenberg, Buxbaum, Grice),Department of Genetics and Genomic Sciences (Buxbaum),Department of Neuroscience (Buxbaum), and Friedman Brain Institute (Buxbaum, Grice), Icahn School of Medicine at Mount Sinai, New York; Department of Medical Epidemiology and Biostatistics (Mahjani, Mattheisen, Halvorsen, Pedersen, Bulik, Landén, Fundín, Sandin, Hultman, Crowley) andCenter for Psychiatry Research, Department of Clinical Neuroscience (Boberg, de Schipper, Mataix-Cols, Rück), Karolinska Institutet, Stockholm; Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Klei, Devlin); Department of Psychiatry and Department of Community Health and Epidemiology, Dalhousie University, Halifax, Canada (Mattheisen); Department of Biomedicine-Human Genetics and the iSEQ Center, Aarhus University, Aarhus, Denmark (Mattheisen); Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich (Mattheisen); Department of Genetics (Halvorsen, Crowley)Department of Psychiatry (Bulik), and Department of Nutrition (Bulik), University of North Carolina at Chapel Hill; Department of Statistics and the Computational Biology Department, Carnegie Mellon University, Pittsburgh (Roeder); Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden (Landén); Health Care Services, Region Stockholm, Stockholm (Rück).

Objective: Obsessive-compulsive disorder (OCD) is known to be substantially heritable; however, the contribution of genetic variation across the allele frequency spectrum to this heritability remains uncertain. The authors used two new homogeneous cohorts to estimate the heritability of OCD from inherited genetic variation and contrasted the results with those of previous studies.

Methods: The sample consisted of 2,090 Swedish-born individuals diagnosed with OCD and 4,567 control subjects, all genotyped for common genetic variants, specifically >400,000 single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥0.01. Using genotypes of these SNPs to estimate distant familial relationships among individuals, the authors estimated the heritability of OCD, both overall and partitioned according to MAF bins.

Results: Narrow-sense heritability of OCD was estimated at 29% (SE=4%). The estimate was robust, varying only modestly under different models. Contrary to an earlier study, however, SNPs with MAF between 0.01 and 0.05 accounted for 10% of heritability, and estimated heritability per MAF bin roughly followed expectations based on a simple model for SNP-based heritability.

Conclusions: These results indicate that common inherited risk variation (MAF ≥0.01) accounts for most of the heritable variation in OCD. SNPs with low MAF contribute meaningfully to the heritability of OCD, and the results are consistent with expectation under the "infinitesimal model" (also referred to as the "polygenic model"), where risk is influenced by a large number of loci across the genome and across MAF bins.
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http://dx.doi.org/10.1176/appi.ajp.2021.21010101DOI Listing
November 2021

A Mobile Sensing App to Monitor Youth Mental Health: Observational Pilot Study.

JMIR Mhealth Uhealth 2021 10 26;9(10):e20638. Epub 2021 Oct 26.

Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.

Background: Internalizing disorders are the most common psychiatric problems observed among youth in Canada. Sadly, youth with internalizing disorders often avoid seeking clinical help and rarely receive adequate treatment. Current methods of assessing internalizing disorders usually rely on subjective symptom ratings, but internalizing symptoms are frequently underreported, which creates a barrier to the accurate assessment of these symptoms in youth. Therefore, novel assessment tools that use objective data need to be developed to meet the highest standards of reliability, feasibility, scalability, and affordability. Mobile sensing technologies, which unobtrusively record aspects of youth behaviors in their daily lives with the potential to make inferences about their mental health states, offer a possible method of addressing this assessment barrier.

Objective: This study aims to explore whether passively collected smartphone sensor data can be used to predict internalizing symptoms among youth in Canada.

Methods: In this study, the youth participants (N=122) completed self-report assessments of symptoms of anxiety, depression, and attention-deficit hyperactivity disorder. Next, the participants installed an app, which passively collected data about their mobility, screen time, sleep, and social interactions over 2 weeks. Then, we tested whether these passive sensor data could be used to predict internalizing symptoms among these youth participants.

Results: More severe depressive symptoms correlated with more time spent stationary (r=0.293; P=.003), less mobility (r=0.271; P=.006), higher light intensity during the night (r=0.227; P=.02), and fewer outgoing calls (r=-0.244; P=.03). In contrast, more severe anxiety symptoms correlated with less time spent stationary (r=-0.249; P=.01) and greater mobility (r=0.234; P=.02). In addition, youths with higher anxiety scores spent more time on the screen (r=0.203; P=.049). Finally, adding passively collected smartphone sensor data to the prediction models of internalizing symptoms significantly improved their fit.

Conclusions: Passively collected smartphone sensor data provide a useful way to monitor internalizing symptoms among youth. Although the results replicated findings from adult populations, to ensure clinical utility, they still need to be replicated in larger samples of youth. The work also highlights intervention opportunities via mobile technology to reduce the burden of internalizing symptoms early on.
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http://dx.doi.org/10.2196/20638DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579216PMC
October 2021

Polygenic Heterogeneity Across Obsessive-Compulsive Disorder Subgroups Defined by a Comorbid Diagnosis.

Front Genet 2021 31;12:711624. Epub 2021 Aug 31.

Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Among patients with obsessive-compulsive disorder (OCD), 65-85% manifest another psychiatric disorder concomitantly or at some other time point during their life. OCD is highly heritable, as are many of its comorbidities. A possible genetic heterogeneity of OCD in relation to its comorbid conditions, however, has not yet been exhaustively explored. We used a framework of different approaches to study the genetic relationship of OCD with three commonly observed comorbidities, namely major depressive disorder (MDD), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). First, using publicly available summary statistics from large-scale genome-wide association studies, we compared genetic correlation patterns for OCD, MDD, ADHD, and ASD with 861 somatic and mental health phenotypes. Secondly, we examined how polygenic risk scores (PRS) of eight traits that showed heterogeneous correlation patterns with OCD, MDD, ADHD, and ASD partitioned across comorbid subgroups in OCD using independent unpublished data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). The comorbid subgroups comprised of patients with only OCD ( = 366), OCD and MDD ( = 1,052), OCD and ADHD ( = 443), OCD and ASD ( = 388), and OCD with more than 1 comorbidity ( = 429). We found that PRS of all traits but BMI were significantly associated with OCD across all subgroups (neuroticism: = 1.19 × 10, bipolar disorder: = 7.51 × 10, anorexia nervosa: = 3.52 × 10, age at first birth: = 9.38 × 10, educational attainment: = 1.56 × 10, OCD: = 1.87 × 10, insomnia: = 2.61 × 10, BMI: = 0.15). For age at first birth, educational attainment, and insomnia PRS estimates significantly differed across comorbid subgroups ( = 2.29 × 10, = 1.63 × 10, and = 0.045, respectively). Especially for anorexia nervosa, age at first birth, educational attainment, insomnia, and neuroticism the correlation patterns that emerged from genetic correlation analysis of OCD, MDD, ADHD, and ASD were mirrored in the PRS associations with the respective comorbid OCD groups. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across OCD comorbid subgroups.
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http://dx.doi.org/10.3389/fgene.2021.711624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438210PMC
August 2021

Elevated common variant genetic risk for tourette syndrome in a densely-affected pedigree.

Mol Psychiatry 2021 Sep 15. Epub 2021 Sep 15.

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Tourette syndrome (TS) is a highly heritable neuropsychiatric disorder with complex patterns of genetic inheritance. Recent genetic findings in TS have highlighted both numerous common variants with small effects and a few rare variants with moderate or large effects. Here we searched for genetic causes of TS in a large, densely-affected British pedigree using a systematic genomic approach. This pedigree spans six generations and includes 122 members, 85 of whom were individually interviewed, and 53 of whom were diagnosed as "cases" (consisting of 28 with definite or probable TS, 20 with chronic multiple tics [CMT], and five with obsessive-compulsive behaviors [OCB]). A total of 66 DNA samples were available (25 TS, 15 CMT, 4 OCB cases, and 22 unaffecteds) and all were genotyped using a dense single nucleotide polymorphism (SNP) array to identify shared segments, copy number variants (CNVs), and to calculate genetic risk scores. Eight cases were also whole genome sequenced to test whether any rare variants were shared identical by descent. While we did not identify any notable CNVs, single nucleotide variants, indels or repeat expansions of near-Mendelian effect, the most distinctive feature of this family proved to be an unusually high load of common risk alleles for TS. We found that cases within this family carried a higher load of TS common variant risk similar to that previously found in unrelated TS cases. Thus far, the strongest evidence from genetic data for contribution to TS risk in this family comes from multiple common risk variants rather than one or a few variants of strong effect.
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http://dx.doi.org/10.1038/s41380-021-01277-wDOI Listing
September 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Antipsychotics in routine treatment are minor contributors to QT prolongation compared to genetics and age.

J Psychopharmacol 2021 Sep 28;35(9):1127-1133. Epub 2021 Mar 28.

Center for Mental Health, University Hospital of Würzburg, Würzburg, Germany.

Background: Drug-induced prolongation of cardiac repolarization limits the treatment with many psychotropic drugs. Recently, the contribution of polygenic variation to the individual duration of the QT interval was identified.

Aims: To explore the interaction between antipsychotic drugs and the individual polygenic influence on the QT interval.

Methods: Retrospective analysis of clinical and genotype data of 804 psychiatric inpatients diagnosed with a psychotic disorder. The individual polygenic influence on the QT interval was calculated according to the method of Arking et al.

Results: Linear regression modelling showed a significant association of the individual polygenic QT interval score (ß = 0.176, < 0.001) and age (ß = 0.139, < 0.001) with the QTc interval corrected according to Fridericia's formula. Sex showed a nominal trend towards significance (ß = 0.064, = 0.064). No association was observed for the number of QT prolonging drugs according to AZCERT taken. Subsample analysis ( = 588) showed a significant association of potassium serum concentrations with the QTc interval (ß = -0.104, = 0.010). Haloperidol serum concentrations were associated with the QTc interval only in single medication analysis ( = 26, ß = 0.101, = 0.004), but not in multivariate regression analysis. No association was observed for aripiprazole, clozapine, quetiapine and perazine, while olanzapine and the sum of risperidone and its metabolite showed a negative association.

Conclusions: Individual genetic factors and age are main determinants of the QT interval. Antipsychotic drug serum concentrations within the therapeutic range contribute to QTc prolongation on an individual level.
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http://dx.doi.org/10.1177/02698811211003477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8436313PMC
September 2021

Investigating Shared Genetic Basis Across Tourette Syndrome and Comorbid Neurodevelopmental Disorders Along the Impulsivity-Compulsivity Spectrum.

Biol Psychiatry 2021 09 8;90(5):317-327. Epub 2021 Jan 8.

Department of Biological Sciences, Purdue University, West Lafayette, Indiana. Electronic address:

Background: Tourette syndrome (TS) is often found comorbid with other neurodevelopmental disorders across the impulsivity-compulsivity spectrum, with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) as most prevalent. This points to the possibility of a common etiological thread along an impulsivity-compulsivity continuum.

Methods: Investigating the shared genetic basis across TS, ADHD, ASD, and OCD, we undertook an evaluation of cross-disorder genetic architecture and systematic meta-analysis, integrating summary statistics from the latest genome-wide association studies (93,294 individuals, 6,788,510 markers).

Results: As previously identified, a common unifying factor connects TS, ADHD, and ASD, while TS and OCD show the highest genetic correlation in pairwise testing among these disorders. Thanks to a more homogeneous set of disorders and a targeted approach that is guided by genetic correlations, we were able to identify multiple novel hits and regions that seem to play a pleiotropic role for the specific disorders analyzed here and could not be identified through previous studies. In the TS-ADHD-ASD genome-wide association study single nucleotide polymorphism-based and gene-based meta-analysis, we uncovered 13 genome-wide significant regions that host single nucleotide polymorphisms with a high posterior probability for association with all three studied disorders (m-value > 0.9), 11 of which were not identified in previous cross-disorder analysis. In contrast, we also identified two additional pleiotropic regions in the TS-OCD meta-analysis. Through conditional analysis, we highlighted genes and genetic regions that play a specific role in a TS-ADHD-ASD genetic factor versus TS-OCD. Cross-disorder tissue specificity analysis implicated the hypothalamus-pituitary-adrenal gland axis in TS-ADHD-ASD.

Conclusions: Our work underlines the value of redefining the framework for research across traditional diagnostic categories.
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http://dx.doi.org/10.1016/j.biopsych.2020.12.028DOI Listing
September 2021

Prediction of lithium response using genomic data.

Sci Rep 2021 01 13;11(1):1155. Epub 2021 Jan 13.

Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.
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http://dx.doi.org/10.1038/s41598-020-80814-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806976PMC
January 2021

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder.

Transl Psychiatry 2021 01 11;11(1):36. Epub 2021 Jan 11.

Department of Psychiatry, Charles University, Prague, Czech Republic.

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.
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http://dx.doi.org/10.1038/s41398-020-01148-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801503PMC
January 2021

Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia.

Front Psychiatry 2020 9;11:313. Epub 2020 Jun 9.

Department of Biomedicine, Aarhus University, Aarhus, Denmark.

Schizophrenia (SCZ) is a severe mental disorder with immense personal and societal costs; identifying individuals at risk is therefore of utmost importance. Genomic risk profile scores (GRPS) have been shown to significantly predict cases-control status. Making use of a large-population based sample from Sweden, we replicate a previous finding demonstrating that the GRPS is strongly associated with admission frequency and chronicity of SCZ. Furthermore, we were able to show a substantial gap in prediction accuracy between males and females. In sum, our results indicate that prediction accuracy by GRPS depends on clinical and demographic characteristics.
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http://dx.doi.org/10.3389/fpsyt.2020.00313DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297201PMC
June 2020

Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits.

Nat Neurosci 2020 07 25;23(7):809-818. Epub 2020 May 25.

Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.
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http://dx.doi.org/10.1038/s41593-020-0643-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485556PMC
July 2020

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Addict Biol 2021 01 16;26(1):e12880. Epub 2020 Feb 16.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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http://dx.doi.org/10.1111/adb.12880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429266PMC
January 2021

Autosomal-dominant hypotrichosis with woolly hair: Novel gene locus on chromosome 4q35.1-q35.2.

PLoS One 2019 2;14(12):e0225943. Epub 2019 Dec 2.

Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany.

Hypotrichosis simplex (HS) with and without woolly hair (WH) comprises a group of rare, monogenic disorders of hair loss. Patients present with a diffuse loss of scalp and/or body hair, which usually begins in early childhood and progresses into adulthood. Some of the patients also show hair that is tightly curled. Approximately 10 genes for autosomal recessive and autosomal dominant forms of HS have been identified in the last decade, among them five genes for the dominant form. We collected blood and buccal samples from 17 individuals of a large British family with HS and WH. After having sequenced all known dominant genes for HS in this family without the identification of any disease causing mutation, we performed a genome-wide scan, using the HumanLinkage-24 BeadChip, followed by a classical linkage analysis; and whole exome-sequencing (WES). Evidence for linkage was found for a region on chromosome 4q35.1-q35.2 with a maximum LOD score of 3.61. WES led to the identification of a mutation in the gene SORBS2, encoding sorbin and SH3 domain containing 2. Unfortunately, we could not find an additional mutation in any other patient/family with HS; and in cell culture, we could not observe any difference between cloned wildtype and mutant SORBS2 using western blotting and immunofluorescence analyses. Therefore, at present, SORBS2 cannot be considered a definite disease gene for this phenotype. However, the locus on chromosome 4q is a robust and novel finding for hypotrichosis with woolly hair. Further fine mapping and sequencing efforts are therefore warranted in order to confirm SORBS2 as a plausible HS disease gene.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225943PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886801PMC
March 2020

A major role for common genetic variation in anxiety disorders.

Mol Psychiatry 2020 12 20;25(12):3292-3303. Epub 2019 Nov 20.

King's College London; Social, Genetic and Developmental Psychiatry Centre; Institute of Psychiatry, Psychology & Neuroscience, London, UK.

Anxiety disorders are common, complex psychiatric disorders with twin heritabilities of 30-60%. We conducted a genome-wide association study of Lifetime Anxiety Disorder (n = 25 453, n = 58 113) and an additional analysis of Current Anxiety Symptoms (n = 19 012, n = 58 113). The liability scale common variant heritability estimate for Lifetime Anxiety Disorder was 26%, and for Current Anxiety Symptoms was 31%. Five novel genome-wide significant loci were identified including an intergenic region on chromosome 9 that has previously been associated with neuroticism, and a locus overlapping the BDNF receptor gene, NTRK2. Anxiety showed significant positive genetic correlations with depression and insomnia as well as coronary artery disease, mirroring findings from epidemiological studies. We conclude that common genetic variation accounts for a substantive proportion of the genetic architecture underlying anxiety.
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http://dx.doi.org/10.1038/s41380-019-0559-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7237282PMC
December 2020

Genome-wide association study of panic disorder reveals genetic overlap with neuroticism and depression.

Mol Psychiatry 2021 Aug 11;26(8):4179-4190. Epub 2019 Nov 11.

Department of Psychology, Humboldt-University Berlin, Berlin, Germany.

Panic disorder (PD) has a lifetime prevalence of 2-4% and heritability estimates of 40%. The contributory genetic variants remain largely unknown, with few and inconsistent loci having been reported. The present report describes the largest genome-wide association study (GWAS) of PD to date comprising genome-wide genotype data of 2248 clinically well-characterized PD patients and 7992 ethnically matched controls. The samples originated from four European countries (Denmark, Estonia, Germany, and Sweden). Standard GWAS quality control procedures were conducted on each individual dataset, and imputation was performed using the 1000 Genomes Project reference panel. A meta-analysis was then performed using the Ricopili pipeline. No genome-wide significant locus was identified. Leave-one-out analyses generated highly significant polygenic risk scores (PRS) (explained variance of up to 2.6%). Linkage disequilibrium (LD) score regression analysis of the GWAS data showed that the estimated heritability for PD was 28.0-34.2%. After correction for multiple testing, a significant genetic correlation was found between PD and major depressive disorder, depressive symptoms, and neuroticism. A total of 255 single-nucleotide polymorphisms (SNPs) with p < 1 × 10 were followed up in an independent sample of 2408 PD patients and 228,470 controls from Denmark, Iceland and the Netherlands. In the combined analysis, SNP rs144783209 showed the strongest association with PD (pcomb = 3.10  × 10). Sign tests revealed a significant enrichment of SNPs with a discovery p-value of <0.0001 in the combined follow up cohort (p = 0.048). The present integrative analysis represents a major step towards the elucidation of the genetic susceptibility to PD.
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http://dx.doi.org/10.1038/s41380-019-0590-2DOI Listing
August 2021

1,25-Dihydroxyvitamin D modulates L-type voltage-gated calcium channels in a subset of neurons in the developing mouse prefrontal cortex.

Transl Psychiatry 2019 11 11;9(1):281. Epub 2019 Nov 11.

Queensland Brain Institute, University of Queensland, St. Lucia, QLD, 4072, Australia.

Schizophrenia has been associated with a range of genetic and environmental risk factors. Here we explored a link between two risk factors that converge on a shared neurobiological pathway. Recent genome-wide association studies (GWAS) have identified risk variants in genes that code for L-type voltage-gated calcium channels (L-VGCCs), while epidemiological studies have found an increased risk of schizophrenia in those with neonatal vitamin D deficiency. The active form of vitamin D (1,25(OH)D) is a secosteroid that rapidly modulates L-VGCCs via non-genomic mechanisms in a range of peripheral tissues, though its non-genomic effects within the brain remain largely unexplored. Here we used calcium imaging, electrophysiology and molecular biology to determine whether 1,25(OH)D non-genomically modulated L-VGCCs in the developing prefrontal cortex, a region widely implicated in schizophrenia pathophysiology. Wide-field Ca imaging revealed that physiological concentrations of 1,25(OH)D rapidly enhanced activity-dependent somatic Ca levels in a small subset of neurons in the developing PFC, termed vitamin D-responsive neurons (VDRNs). Somatic nucleated patch recordings revealed a rapid, 1,25(OH)D-evoked increase in high-voltage-activated (HVA) Ca currents. Enhanced activity-dependent Ca levels were mediated by L-VGCC but not associated with any changes to Cacna1c (L-VGCC pore-forming subunit) mRNA expression. Since L-VGCC activity is critical to healthy neurodevelopment, these data suggest that suboptimal concentrations of 1,25(OH)D could alter brain maturation through modulation of L-VGCC signalling and as such may provide a parsimonious link between epidemiologic and genetic risk factors for schizophrenia.
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http://dx.doi.org/10.1038/s41398-019-0626-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848150PMC
November 2019

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Genotype-phenotype feasibility studies on khat abuse, traumatic experiences and psychosis in Ethiopia.

Psychiatr Genet 2020 02;30(1):34-38

Department of Psychiatry, Psychosomatics, and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany and.

Studying the relationship between mental illnesses and their environmental and genetic risk factors in low-income countries holds excellent promises. These studies will improve our understanding of how risk factors identified predominantly in high-income countries also apply to other settings and will identify new, sometimes population-specific risk factors. Here we report the successful completion of two intertwined pilot studies on khat abuse, trauma, and psychosis at the Gilgel Gibe Field Research Center in Ethiopia. We found that the Gilgel Gibe Field Research Center offers a unique opportunity to collect well-characterized samples for mental health research and to perform genetic studies that, at this scale, have not been undertaken in Ethiopia yet. We also supported service development, education, and research for strengthening the professional profile of psychiatry at the site.
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http://dx.doi.org/10.1097/YPG.0000000000000242DOI Listing
February 2020

A polygenic resilience score moderates the genetic risk for schizophrenia.

Mol Psychiatry 2021 03 6;26(3):800-815. Epub 2019 Sep 6.

Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA.

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.
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http://dx.doi.org/10.1038/s41380-019-0463-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058518PMC
March 2021

Nordic OCD & Related Disorders Consortium: Rationale, design, and methods.

Am J Med Genet B Neuropsychiatr Genet 2020 01 19;183(1):38-50. Epub 2019 Aug 19.

Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder, yet its etiology is unknown and treatment outcomes could be improved if biological targets could be identified. Unfortunately, genetic findings for OCD are lagging behind other psychiatric disorders. Thus, there is a pressing need to understand the causal mechanisms implicated in OCD in order to improve clinical outcomes and to reduce morbidity and societal costs. Specifically, there is a need for a large-scale, etiologically informative genetic study integrating genetic and environmental factors that presumably interact to cause the condition. The Nordic countries provide fertile ground for such a study, given their detailed population registers, national healthcare systems and active specialist clinics for OCD. We thus formed the Nordic OCD and Related Disorders Consortium (NORDiC, www.crowleylab.org/nordic), and with the support of NIMH and the Swedish Research Council, have begun to collect a large, richly phenotyped and genotyped sample of OCD cases. Our specific aims are geared toward answering a number of key questions regarding the biology, etiology, and treatment of OCD. This article describes and discusses the rationale, design, and methodology of NORDiC, including details on clinical measures and planned genomic analyses.
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http://dx.doi.org/10.1002/ajmg.b.32756DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6898732PMC
January 2020

RICOPILI: Rapid Imputation for COnsortias PIpeLIne.

Bioinformatics 2020 02;36(3):930-933

Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.

Summary: Genome-wide association study (GWAS) analyses, at sufficient sample sizes and power, have successfully revealed biological insights for several complex traits. RICOPILI, an open-sourced Perl-based pipeline was developed to address the challenges of rapidly processing large-scale multi-cohort GWAS studies including quality control (QC), imputation and downstream analyses. The pipeline is computationally efficient with portability to a wide range of high-performance computing environments. RICOPILI was created as the Psychiatric Genomics Consortium pipeline for GWAS and adopted by other users. The pipeline features (i) technical and genomic QC in case-control and trio cohorts, (ii) genome-wide phasing and imputation, (iv) association analysis, (v) meta-analysis, (vi) polygenic risk scoring and (vii) replication analysis. Notably, a major differentiator from other GWAS pipelines, RICOPILI leverages on automated parallelization and cluster job management approaches for rapid production of imputed genome-wide data. A comprehensive meta-analysis of simulated GWAS data has been incorporated demonstrating each step of the pipeline. This includes all the associated visualization plots, to allow ease of data interpretation and manuscript preparation. Simulated GWAS datasets are also packaged with the pipeline for user training tutorials and developer work.

Availability And Implementation: RICOPILI has a flexible architecture to allow for ongoing development and incorporation of newer available algorithms and is adaptable to various HPC environments (QSUB, BSUB, SLURM and others). Specific links for genomic resources are either directly provided in this paper or via tutorials and external links. The central location hosting scripts and tutorials is found at this URL: https://sites.google.com/a/broadinstitute.org/RICOPILI/home.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz633DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868045PMC
February 2020

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Nat Genet 2019 08 15;51(8):1207-1214. Epub 2019 Jul 15.

Clinical Genetics Unit, Department of Woman and Child Health, University of Padova, Padova, Italy.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness, affecting 0.9-4% of women and 0.3% of men, with twin-based heritability estimates of 50-60%. Mortality rates are higher than those in other psychiatric disorders, and outcomes are unacceptably poor. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
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http://dx.doi.org/10.1038/s41588-019-0439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779477PMC
August 2019

Genetic Variants Associated With Anxiety and Stress-Related Disorders: A Genome-Wide Association Study and Mouse-Model Study.

JAMA Psychiatry 2019 09;76(9):924-932

Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark.

Importance: Anxiety and stress-related disorders are among the most common mental disorders. Although family and twin studies indicate that both genetic and environmental factors play an important role underlying their etiology, the genetic underpinnings of anxiety and stress-related disorders are poorly understood.

Objectives: To estimate the single-nucleotide polymorphism-based heritability of anxiety and stress-related disorders; to identify novel genetic risk variants, genes, or biological pathways; to test for pleiotropic associations with other psychiatric traits; and to evaluate the association of psychiatric comorbidities with genetic findings.

Design, Setting, Participants: This genome-wide association study included individuals with various anxiety and stress-related diagnoses and controls derived from the population-based Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) study. Lifetime diagnoses of anxiety and stress-related disorders were obtained through the national Danish registers. Genes of interest were further evaluated in mice exposed to chronic social defeat. The study was conducted between June 2016 and November 2018.

Main Outcomes And Measures: Diagnoses of a relatively broad diagnostic spectrum of anxiety and stress-related disorders.

Results: The study sample included 12 655 individuals with various anxiety and stress-related diagnoses and 19 225 controls. Overall, 17 740 study participants (55.6%) were women. A total of 7308 participants (22.9%) were born between 1981-1985, 8840 (27.7%) between 1986-1990, 8157 (25.6%) between 1991-1995, 5918 (18.6%) between 1996-2000, and 1657 (5.2%) between 2001-2005. Standard association analysis revealed variants in PDE4B to be associated with anxiety and stress-related disorder (rs7528604; P = 5.39 × 10-11; odds ratio = 0.89; 95% CI, 0.86-0.92). A framework of sensitivity analyses adjusting for mental comorbidity supported this result showing consistent association of PDE4B variants with anxiety and stress-related disorder across analytical scenarios. In mouse models, alterations in Pde4b expression were observed in those mice displaying anxiety-like behavior after exposure to chronic stress in the prefrontal cortex (P = .002; t = -3.33) and the hippocampus (P = .001; t = -3.72). We also found a single-nucleotide polymorphism heritability of 28% (standard error = 0.027) and that the genetic signature of anxiety and stress-related overlapped with psychiatric traits, educational outcomes, obesity-related phenotypes, smoking, and reproductive success.

Conclusions And Relevance: This study highlights anxiety and stress-related disorders as complex heritable phenotypes with intriguing genetic correlations not only with psychiatric traits, but also with educational outcomes and multiple obesity-related phenotypes. Furthermore, we highlight the candidate gene PDE4B as a robust risk locus pointing to the potential of PDE4B inhibitors in treatment of these disorders.
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http://dx.doi.org/10.1001/jamapsychiatry.2019.1119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537792PMC
September 2019

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Nat Genet 2019 05 1;51(5):793-803. Epub 2019 May 1.

Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
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http://dx.doi.org/10.1038/s41588-019-0397-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956732PMC
May 2019

Genetic Markers of ADHD-Related Variations in Intracranial Volume.

Am J Psychiatry 2019 03;176(3):228-238

The Department of Human Genetics, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands (Klein, Bralten, Roth Mota, Arias-Vasquez, Franke); University Medical Center Utrecht, UMC Utrecht Brain Center, Department of Psychiatry, Utrecht, the Netherlands (Klein); the Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston (Walters, Neale); Program in Medical and Population Genetics (Walters) and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Mass (Walters, Neale); the Department of Biomedicine and the Center for Integrative Sequencing, Aarhus University, Aarhus, Denmark (Demontis, Mattheisen, Børglum); the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Denmark (Demontis, Børglum); the Department of Genetics and the Neuroscience Center, University of North Carolina, Chapel Hill (Stein); the Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles (Hibar, Thompson); the Department of Epidemiology and the Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands (Adams); the Department of Psychiatry and the Research Institute, Hospital for Sick Children, University of Toronto, Toronto (Schachar); the Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Sonuga-Barke); the Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany (Mattheisen); the Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institute, Stockholm (Mattheisen); Stockholm Health Care Services, Stockholm County Council, Stockholm (Mattheisen); the Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles (Thompson); the Quantitative Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia (Medland); the Department of Psychiatry and the Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, N.Y. (Faraone); the K.G. Jebsen Center for Neuropsychiatric Disorders, University of Bergen, Bergen, Norway (Faraone); and the Department of Psychiatry, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands (Roth Mota, Arias-Vasquez, Franke).

Objective: Attention deficit hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology. Intracranial volume (ICV) and volumes of the nucleus accumbens, amygdala, caudate nucleus, hippocampus, and putamen are smaller in people with ADHD compared with healthy individuals. The authors investigated the overlap between common genetic variation associated with ADHD risk and these brain volume measures to identify underlying biological processes contributing to the disorder.

Methods: The authors combined genome-wide association results from the largest available studies of ADHD (N=55,374) and brain volumes (N=11,221-24,704), using a set of complementary methods to investigate overlap at the level of global common variant genetic architecture and at the single variant level.

Results: Analyses revealed a significant negative genetic correlation between ADHD and ICV (r=-0.22). Meta-analysis of single variants revealed two significant loci of interest associated with both ADHD risk and ICV; four additional loci were identified for ADHD and volumes of the amygdala, caudate nucleus, and putamen. Exploratory gene-based and gene-set analyses in the ADHD-ICV meta-analytic data showed association with variation in neurite outgrowth-related genes.

Conclusions: This is the first genome-wide study to show significant genetic overlap between brain volume measures and ADHD, both on the global and the single variant level. Variants linked to smaller ICV were associated with increased ADHD risk. These findings can help us develop new hypotheses about biological mechanisms by which brain structure alterations may be involved in ADHD disease etiology.
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http://dx.doi.org/10.1176/appi.ajp.2018.18020149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780894PMC
March 2019

Identification of common genetic risk variants for autism spectrum disorder.

Nat Genet 2019 03 25;51(3):431-444. Epub 2019 Feb 25.

The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.
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http://dx.doi.org/10.1038/s41588-019-0344-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454898PMC
March 2019

Quantifying between-cohort and between-sex genetic heterogeneity in major depressive disorder.

Am J Med Genet B Neuropsychiatr Genet 2019 09 1;180(6):439-447. Epub 2019 Feb 1.

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.

Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.
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http://dx.doi.org/10.1002/ajmg.b.32713DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6675638PMC
September 2019

Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP.

Pharmacogenomics J 2020 04 31;20(2):329-341. Epub 2019 Jan 31.

Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, EH10 5HF, Edinburgh, UK.

Antidepressants demonstrate modest response rates in the treatment of major depressive disorder (MDD). Despite previous genome-wide association studies (GWAS) of antidepressant treatment response, the underlying genetic factors are unknown. Using prescription data in a population and family-based cohort (Generation Scotland: Scottish Family Health Study; GS:SFHS), we sought to define a measure of (a) antidepressant treatment resistance and (b) stages of antidepressant resistance by inferring antidepressant switching as non-response to treatment. GWAS were conducted separately for antidepressant treatment resistance in GS:SFHS and the Genome-based Therapeutic Drugs for Depression (GENDEP) study and then meta-analysed (meta-analysis n = 4213, cases = 358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n = 3452). Additionally, we conducted gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis. We did not identify any significant loci, genes or gene sets associated with antidepressant treatment resistance or stages of resistance. Significant positive genetic correlations of antidepressant treatment resistance and stages of resistance with neuroticism, psychological distress, schizotypy and mood disorder traits were identified. These findings suggest that larger sample sizes are needed to identify the genetic architecture of antidepressant treatment response, and that population-based observational studies may provide a tractable approach to achieving the necessary statistical power.
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http://dx.doi.org/10.1038/s41397-019-0067-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096334PMC
April 2020

The association between neonatal vitamin D status and risk of schizophrenia.

Sci Rep 2018 12 6;8(1):17692. Epub 2018 Dec 6.

Queensland Brain Institute, University of Queensland, St. Lucia, Queensland, Australia.

Clues from the epidemiology of schizophrenia, such as the increased risk in those born in winter/spring, have led to the hypothesis that prenatal vitamin D deficiency may increase the risk of later schizophrenia. We wish to explore this hypothesis in a large Danish case-control study (n = 2602). The concentration of 25 hydroxyvitamin D (25OHD) was assessed from neonatal dried blood samples. Incidence rate ratios (IRR) were calculated when examined for quintiles of 25OHD concentration. In addition, we examined statistical models that combined 25OHD concentration and the schizophrenia polygenic risk score (PRS) in a sample that combined the new sample with a previous study (total n = 3464; samples assayed and genotyped between 2008-2013). Compared to the reference (fourth) quintile, those in the lowest quintile (<20.4 nmol/L) had a significantly increased risk of schizophrenia (IRR = 1.44, 95%CI: 1.12-1.85). None of the other quintile comparisons were significantly different. There was no significant interaction between 25OHD and the PRS. Neonatal vitamin D deficiency was associated with an increased risk for schizophrenia in later life. These findings could have important public health implications related to the primary prevention of schizophrenia.
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http://dx.doi.org/10.1038/s41598-018-35418-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283870PMC
December 2018
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