Publications by authors named "Francesco Bettella"

78 Publications

Identification of pleiotropy at the gene level between psychiatric disorders and related traits.

Transl Psychiatry 2021 07 29;11(1):410. Epub 2021 Jul 29.

NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway.

Major mental disorders are highly prevalent and make a substantial contribution to the global disease burden. It is known that mental disorders share clinical characteristics, and genome-wide association studies (GWASs) have recently provided evidence for shared genetic factors as well. Genetic overlaps are usually identified at the single-marker level. Here, we aimed to identify genetic overlaps at the gene level between 7 mental disorders (schizophrenia, autism spectrum disorder, major depressive disorder, anorexia nervosa, ADHD, bipolar disorder and anxiety), 8 brain morphometric traits, 2 cognitive traits (educational attainment and general cognitive function) and 9 personality traits (subjective well-being, depressive symptoms, neuroticism, extraversion, openness to experience, agreeableness and conscientiousness, children's aggressive behaviour, loneliness) based on publicly available GWASs. We performed systematic conditional regression analyses to identify independent signals and select loci associated with more than one trait. We identified 48 genes containing independent markers associated with several traits (pleiotropy at the gene level). We also report 9 genes with different markers that show independent associations with single traits (allelic heterogeneity). This study demonstrates that mental disorders and related traits do show pleiotropy at the gene level as well as the single-marker level. The identification of these genes might be important for prioritizing further deep genotyping, functional studies, or drug targeting.
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http://dx.doi.org/10.1038/s41398-021-01530-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322263PMC
July 2021

Dose-dependent transcriptional effects of lithium and adverse effect burden in a psychiatric cohort.

Prog Neuropsychopharmacol Biol Psychiatry 2021 Jul 25:110408. Epub 2021 Jul 25.

NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. Electronic address:

Lithium is the first-line treatment for bipolar disorder (BD), but there is a large variation in response rate and adverse effects. Although the molecular effects of lithium have been studied extensively, the specific mechanisms of action remain unclear. In particular, the molecular changes underlying lithium adverse effects are little known. Multiple linear regression analyses of lithium serum concentrations and global gene expression levels in whole blood were carried out using a large case-control sample (n = 1450). Self-reported adverse effects of lithium were assessed with the "Udvalg for Kliniske Undersøgelser" (UKU) adverse effect rating scale, and regression analysis was used to identify significant associations between lithium-related genes and six of the most common adverse effects. Serum concentrations of lithium were significantly associated with the expression levels of 52 genes (FDR < 0.01), largely replicating previous results. We found 32 up-regulated genes and 20 down-regulated genes in lithium users compared to non-users. The down-regulated gene set was enriched for several processes related to the translational machinery. Two adverse effects were significantly associated (p < 0.01) with three or more lithium-associated genes: tremor (FAM13A-AS1, FAR2, ITGAX, RWDD1, and STARD10) and xerostomia (ANKRD13A, FAR2, RPS8, and RWDD1). The adverse effect association with the largest effect was between CAMK1D expression and nausea/vomiting. These results suggest putative transcriptional mechanisms that may predict lithium adverse effects, and could thus have a large potential for informing clinical practice.
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http://dx.doi.org/10.1016/j.pnpbp.2021.110408DOI Listing
July 2021

Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools.

Brain 2021 Jul 17. Epub 2021 Jul 17.

NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo, Norway.

Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine's polygenic architecture overlaps with bipolar disorder, depression, and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases=59,674; n controls=316,078), bipolar disorder (n cases=20,352; n controls=31,358), depression (n cases=170,756; n controls=328,443) and schizophrenia (n cases=40,675, n controls=64,643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterised to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8K disorder-influencing variants) compared to mental disorders (8.1K-12.3K disorder-influencing variants). Bivariate analysis estimated that 0.8K (0.3K), 2.1K (SD = 0.1K) and 2.3K (SD = 0.3K) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1.8K, SD = 0.3K) and educational attainment (2.1K, SD = 0.3K) but not height (1K, SD = 0.1K). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2, SLC9B1. Gene-set analysis identified several putative gene-sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of 'pleiotropic' variants which influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.
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http://dx.doi.org/10.1093/brain/awab267DOI Listing
July 2021

Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study.

Pharmacogenomics J 2021 Apr 6. Epub 2021 Apr 6.

NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Selective serotonin reuptake inhibitors (SSRIs) are prescribed both to patients with schizophrenia and bipolar disorder. Previous studies have shown associations between SSRI treatment and cardiometabolic alterations. The aim of the present study was to investigate genetic variants associated with cardiometabolic adverse effects in patients treated with SSRIs in a naturalistic setting, using a genome-wide cross-sectional approach in a genetically homogeneous sample. We included and genotyped 1981 individuals with schizophrenia or bipolar disorder, of whom 1180 had information available on the outcomes low-density lipoprotein cholesterol (LDL-cholesterol), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, and body mass index (BMI) and investigated interactions between SNPs and SSRI use (N = 246) by conducting a genome-wide GxE analysis. We report 13 genome-wide significant interaction effects of SNPs and SSRI serum concentrations on LDL-cholesterol, HDL-cholesterol, and BMI, located in four distinct genomic loci. This study provides new insight into the pharmacogenetics of SSRI but warrants replication in independent populations.
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http://dx.doi.org/10.1038/s41397-021-00234-8DOI Listing
April 2021

Optimising classification of proximal arm strength impairment in wheelchair rugby: A proof of concept study.

J Sports Sci 2021 Feb 4:1-8. Epub 2021 Feb 4.

Peter Harrison Centre for Disability Sport, School of Sport, Exercise & Health Sciences, Loughborough University, UK.

This study examined the relationship between proximal arm strength and mobility performance in wheelchair rugby (WR) athletes and examined whether a valid structure for classifying proximal arm strength impairment could be determined. Fifty-seven trained WR athletes with strength impaired arms and no trunk function performed six upper body isometric strength tests and three 10 m sprints in their rugby wheelchair. All strength measures correlated with 2 m and 10 m sprint times (r ≥ -0.43; p ≤ 0.0005) and were entered into k-means cluster analyses with 4-clusters (to mirror the current International Wheelchair Rugby Federation [IWRF] system) and 3-clusters. The 3-cluster structure provided a more valid structure than both the 4-cluster and existing IWRF system, as evidenced by clearer differences in strength (Effect sizes [ES] ≥ 1.0) and performance (ES ≥ 1.1) between adjacent clusters and stronger mean silhouette coefficient (0.64). Subsequently, the 3-cluster structure for classifying proximal arm strength impairment would result in less overlap between athletes from adjacent classes and reduce the likelihood of athletes being disadvantaged due to their impairment. This study demonstrated that the current battery of isometric strength tests and cluster analyses could facilitate the evidence-based development of classifying proximal arm strength impairment in WR.
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http://dx.doi.org/10.1080/02640414.2021.1883291DOI Listing
February 2021

Genetic loci shared between major depression and intelligence with mixed directions of effect.

Nat Hum Behav 2021 Jun 18;5(6):795-801. Epub 2021 Jan 18.

NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.

Genome-wide association studies (GWAS) have identified several common genetic variants influencing major depression and general cognitive abilities, but little is known about whether the two share any of their genetic aetiology. Here we investigate shared genomic architectures between major depression (MD) and general intelligence (INT) with the MiXeR statistical tool and their overlapping susceptibility loci with conjunctional false discovery rate (conjFDR), which evaluate the level of overlap in genetic variants and improve the power for gene discovery between two phenotypes. We analysed GWAS data on MD (n = 480,359) and INT (n = 269,867) to characterize polygenic architecture and identify genetic loci shared between these phenotypes. Despite non-significant genetic correlation (r = -0.0148, P = 0.50), we observed large polygenic overlap and identified 92 loci shared between MD and INT at conjFDR < 0.05. Among the shared loci, 69 and 64 are new for MD and INT, respectively. Our study demonstrates polygenic overlap between these phenotypes with a balanced mixture of effect.
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http://dx.doi.org/10.1038/s41562-020-01031-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217082PMC
June 2021

Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls.

Transl Psychiatry 2020 11 30;10(1):416. Epub 2020 Nov 30.

NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Cognitive impairments are considered core features in schizophrenia and other psychotic disorders. Cognitive impairments are, to a lesser degree, also documented in healthy first-degree relatives. Although recent studies have shown (negative) genetic correlations between schizophrenia and general cognitive ability, the association between polygenic risk for schizophrenia and individual cognitive phenotypes remains unclear. We here investigated the association between a polygenic score for schizophrenia (SCZ) and six well-defined cognitive domains, in addition to a composite measure of cognitive ability and a measure of premorbid intellectual ability in 731 participants with a psychotic disorder and 851 healthy controls. We also investigated the association between a PGS for general cognitive ability (COG) and the same cognitive domains in the same sample. We found no significant associations between the SCZ and any cognitive phenotypes, in either patients with a psychotic disorder or healthy controls. For COG we observed stronger associations with cognitive phenotypes in healthy controls than in participants with psychotic disorders. In healthy controls, the association between COG (at the p value threshold of ≥0.01) and working memory remained significant after Bonferroni correction (β = 0.12, p = 8.6 × 10). Altogether, the lack of associations between SCZ and COG with cognitive performance in participants with psychotic disorders suggests that either environmental factors or unassessed genetic factors play a role in the development of cognitive impairments in psychotic disorders. Working memory should be further studied as an important cognitive phenotype.
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http://dx.doi.org/10.1038/s41398-020-01094-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705731PMC
November 2020

In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

Hum Brain Mapp 2020 Oct 19. Epub 2020 Oct 19.

Department of Psychiatry, University of Münster, Münster, Germany.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.
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http://dx.doi.org/10.1002/hbm.25249DOI Listing
October 2020

Personalized Tests in Paralympic Athletes: Aerobic and Anaerobic Performance Profile of Elite Wheelchair Rugby Players.

J Pers Med 2020 Sep 9;10(3). Epub 2020 Sep 9.

Department of Biomedical Sciences, University of Padua, 35131 Padua, Italy.

In Paralympic sports, the goal of functional classifications is to minimize the impact of impairment on the outcome of the competition. The present cross-sectional study aimed to investigate aerobic and anaerobic personalized tests in Paralympic athletes and to correlate them with the classification of the international wheelchair rugby federation (IWRF). Sixteen elite players of the Italian wheelchair rugby team volunteered for the study. Aerobic (incremental test to exhaustion) and anaerobic (Wingate 30s all-out test, 5 and 10-meter sprint test, shuttle test, isometric test) sport-performance measurements were correlated singularly or grouped (Z scores) with the classification point. Moreover, a multivariate permutation-based ranking analysis investigated possible differences in the overall level of performance among the adjacent classified groups of players, considering the scores of each test. A statistically significant correlation between the performance parameters and the IWRF functional classification considering both aerobic and anaerobic personalized tests was detected (0.58 ≤ r ≤ 0.88; 0.0260 ≤ ≤ 0.0001). The multivariate permutation-based ranking analysis showed differences only for the low-pointers versus mid-pointers ( = 0.0195) and high-pointers ( = 0.0075). Although single performance parameters correlated with athletes' classification point, results of the multivariate permutation-based ranking analysis seem to suggest considering only the most significant anaerobic and sport-specific performance parameters among athletes. These should be combined with the physical assessment and the qualitative observation, which are already part of the classification process to improve its effectiveness.
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http://dx.doi.org/10.3390/jpm10030118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563775PMC
September 2020

Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR.

Bioinformatics 2020 09;36(18):4749-4756

Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, 92037, USA.

Motivation: Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies.

Results: Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, <10% of the causal variants for schizophrenia, bipolar disorder and attention-deficit/hyperactivity disorder are located in protein-coding exons, indicating a more substantial role of regulatory mechanisms in the pathogenesis of these disorders.

Availability And Implementation: The software is available at: https://github.com/precimed/mixer.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa568DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750998PMC
September 2020

Kinematic bidimensional analysis of the propulsion technique in wheelchair rugby athletes.

Eur J Transl Myol 2020 Apr 1;30(1):8902. Epub 2020 Apr 1.

Physical medicine and rehabilitation School, Neuroscience Department, Padova University, Italy.

Wheelchair rugby is a sport ideated for individuals with cervical spinal cord injury (CSCI) which is extremely important for maintaining their neuromuscular abilities and improving their social and psychological wellbeing. However, due to the frequent changes in direction and speed it considerably stresses the players' upper limbs. 13 athletes have undergone two sports-related tests on an inertial drum bench and several kinematic parameters have been registered. Most athletes use a semi-circular pattern which is considered protective for the upper limb. With increasing speed, range of motion (ROM) increases. Release angles increment and contact angles reduce, displacing the push angle forward to increase speed. Instead, the more anterior late push angle used to increase velocity is a factor which further loads the shoulder joint. However, other factors affecting propulsion technique, such as posture and wheelchair set up should be studied to further reduce loading on the upper limb.
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http://dx.doi.org/10.4081/ejtm.2019.8902DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7254415PMC
April 2020

Genome-wide Association Analysis of Parkinson's Disease and Schizophrenia Reveals Shared Genetic Architecture and Identifies Novel Risk Loci.

Biol Psychiatry 2021 02 8;89(3):227-235. Epub 2020 Feb 8.

NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. Electronic address:

Background: Parkinson's disease (PD) and schizophrenia (SCZ) are heritable brain disorders that involve dysregulation of the dopaminergic system. Epidemiological studies have reported potential comorbidity between the disorders, and movement disturbances are common in patients with SCZ before treatment with antipsychotic drugs. Despite this, little is known about shared genetic etiology between the disorders.

Methods: We analyzed recent large genome-wide association studies on patients with SCZ (N = 77,096) and PD (N = 417,508) using a conditional/conjunctional false discovery rate (FDR) approach to evaluate overlap in common genetic variants and improve statistical power for genetic discovery. Using a variety of biological resources, we functionally characterized the identified genomic loci.

Results: We observed genetic enrichment in PD conditional on associations with SCZ and vice versa, indicating polygenic overlap. We then leveraged this cross-trait enrichment using conditional FDR analysis and identified 9 novel PD risk loci and 1 novel SCZ locus at conditional FDR < .01. Furthermore, we identified 9 genomic loci jointly associated with PD and SCZ at conjunctional FDR < .05. There was an even distribution of antagonistic and agonistic effect directions among the shared loci, in line with the insignificant genetic correlation between the disorders. Of 67 genes mapped to the shared loci, 65 are expressed in the human brain and show cell type-specific expression profiles.

Conclusions: Altogether, the study increases understanding of the genetic architectures underlying SCZ and PD, indicating that common molecular genetic mechanisms may contribute to overlapping pathophysiological and clinical features between the disorders.
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http://dx.doi.org/10.1016/j.biopsych.2020.01.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416467PMC
February 2021

Indicated association between polygenic risk score and treatment-resistance in a naturalistic sample of patients with schizophrenia spectrum disorders.

Schizophr Res 2020 04 11;218:55-62. Epub 2020 Mar 11.

NORMENT, Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Background: One third of people diagnosed with schizophrenia fail to respond adequately to antipsychotic medication, resulting in persisting disabling symptoms, higher rates of hospitalization and higher costs for society. In an effort to better understand the mechanisms behind resistance to antipsychotic treatment in schizophrenia, we investigated its potential relationship to the genetic architecture of the disorder.

Methods: Patients diagnosed with a schizophrenia spectrum disorder (N = 321) were classified as either being treatment-resistant (N = 108) or non-treatment-resistant (N = 213) to antipsychotic medication using defined consensus criteria. A schizophrenia polygenic risk score based on genome-wide association studies (GWAS) was calculated for each patient and binary logistic regression was performed to investigate the association between polygenetic risk and treatment resistance. We adjusted for principal components, batch number, age and sex. Additional analyses were performed to investigate associations with demographic and clinical variables.

Results: High levels of polygenic risk score for schizophrenia significantly predicted treatment resistance (p = 0.003). The positive predictive value of the model was 61.5% and the negative predictive value was 71.7%. The association was significant for one (p = 0.01) out of five tested SNP significance thresholds. Season of birth was able to predict treatment-resistance in the regression model (p = 0.05).

Conclusions: The study indicates that treatment-resistance to antipsychotic medication is associated with higher polygenetic risk of schizophrenia, suggesting a link between antipsychotics mechanism of action and the genetic underpinnings of the disorder.
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http://dx.doi.org/10.1016/j.schres.2020.03.006DOI Listing
April 2020

Identification of Genetic Loci Shared Between Attention-Deficit/Hyperactivity Disorder, Intelligence, and Educational Attainment.

Biol Psychiatry 2020 06 29;87(12):1052-1062. Epub 2019 Nov 29.

Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. Electronic address:

Background: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is consistently associated with lower levels of educational attainment. A recent large genome-wide association study identified common gene variants associated with ADHD, but most of the genetic architecture remains unknown.

Methods: We analyzed independent genome-wide association study summary statistics for ADHD (19,099 cases and 34,194 controls), educational attainment (N = 842,499), and general intelligence (N = 269,867) using a conditional/conjunctional false discovery rate (FDR) statistical framework that increases power of discovery by conditioning the FDR on overlapping associations. The genetic variants identified were characterized in terms of function, expression, and biological processes.

Results: We identified 58 linkage disequilibrium-independent ADHD-associated loci (conditional FDR < 0.01), of which 30 were shared between ADHD and educational attainment or general intelligence (conjunctional FDR < 0.01) and 46 were novel risk loci for ADHD.

Conclusions: These results expand on previous genetic and epidemiological studies and support the hypothesis of a shared genetic basis between these phenotypes. Although the clinical utility of the identified loci remains to be determined, they can be used as resources to guide future studies aiming to disentangle the complex etiologies of ADHD, educational attainment, and general intelligence.
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http://dx.doi.org/10.1016/j.biopsych.2019.11.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255939PMC
June 2020

Genetic control of variability in subcortical and intracranial volumes.

Mol Psychiatry 2020 Feb 11. Epub 2020 Feb 11.

NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.
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http://dx.doi.org/10.1038/s41380-020-0664-1DOI Listing
February 2020

Shared Genetic Loci Between Body Mass Index and Major Psychiatric Disorders: A Genome-wide Association Study.

JAMA Psychiatry 2020 05;77(5):503-512

NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Importance: People with major psychiatric disorders (MPDs) have a 10- to 20-year shorter life span than the rest of the population, and this difference is mainly due to comorbid cardiovascular diseases. Genome-wide association studies have identified common variants involved in schizophrenia (SCZ), bipolar disorder (BIP), and major depression (MD) and body mass index (BMI), a key cardiometabolic risk factor. However, genetic variants jointly influencing MPD and BMI remain largely unknown.

Objective: To assess the extent of the overlap between the genetic architectures of MPDs and BMI and identify genetic loci shared between them.

Design, Setting, And Participants: Using a conditional false discovery rate statistical framework, independent genome-wide association study data on individuals with SCZ (n = 82 315), BIP (n = 51 710), MD (n = 480 359), and BMI (n = 795 640) were analyzed. The UK Biobank cohort (n = 29 740) was excluded from the MD data set to avoid sample overlap. Data were collected from August 2017 to May 2018, and analysis began July 2018.

Main Outcomes And Measures: The primary outcomes were a list of genetic loci shared between BMI and MPDs and their functional pathways.

Results: Genome-wide association study data from 1 380 284 participants were analyzed, and the genetic correlation between BMI and MPDs varied (SCZ: r for genetic = -0.11, P = 2.1 × 10-10; BIP: r for genetic = -0.06, P = .0103; MD: r for genetic = 0.12, P = 6.7 × 10-10). Overall, 63, 17, and 32 loci shared between BMI and SCZ, BIP, and MD, respectively, were analyzed at conjunctional false discovery rate less than 0.01. Of the shared loci, 34% (73 of 213) in SCZ, 52% (36 of 69) in BIP, and 57% (56 of 99) in MD had risk alleles associated with higher BMI (conjunctional false discovery rate <0.05), while the rest had opposite directions of associations. Functional analyses indicated that the overlapping loci are involved in several pathways including neurodevelopment, neurotransmitter signaling, and intracellular processes, and the loci with concordant and opposite association directions pointed mostly to different pathways.

Conclusions And Relevance: In this genome-wide association study, extensive polygenic overlap between BMI and SCZ, BIP, and MD were found, and 111 shared genetic loci were identified, implicating novel functional mechanisms. There was mixture of association directions in SCZ and BMI, albeit with a preponderance of discordant ones.
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http://dx.doi.org/10.1001/jamapsychiatry.2019.4188DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6990967PMC
May 2020

Identification of genetic overlap and novel risk loci for attention-deficit/hyperactivity disorder and bipolar disorder.

Mol Psychiatry 2019 Dec 2. Epub 2019 Dec 2.

NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.

Differential diagnosis between childhood onset attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) remains a challenge, mainly due to overlapping symptoms and high rates of comorbidity. Despite this, genetic correlation reported for these disorders is low and non-significant. Here we aimed to better characterize the genetic architecture of these disorders utilizing recent large genome-wide association studies (GWAS). We analyzed independent GWAS summary statistics for ADHD (19,099 cases and 34,194 controls) and BD (20,352 cases and 31,358 controls) applying the conditional/conjunctional false discovery rate (condFDR/conjFDR) statistical framework that increases the power to detect novel phenotype-specific and shared loci by leveraging the combined power of two GWAS. We observed cross-trait polygenic enrichment for ADHD conditioned on associations with BD, and vice versa. Leveraging this enrichment, we identified 19 novel ADHD risk loci and 40 novel BD risk loci at condFDR <0.05. Further, we identified five loci jointly associated with ADHD and BD (conjFDR < 0.05). Interestingly, these five loci show concordant directions of effect for ADHD and BD. These results highlight a shared underlying genetic risk for ADHD and BD which may help to explain the high comorbidity rates and difficulties in differentiating between ADHD and BD in the clinic. Improving our understanding of the underlying genetic architecture of these disorders may aid in the development of novel stratification tools to help reduce these diagnostic difficulties.
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http://dx.doi.org/10.1038/s41380-019-0613-zDOI Listing
December 2019

Examining the association between genetic liability for schizophrenia and psychotic symptoms in Alzheimer's disease.

Transl Psychiatry 2019 10 22;9(1):273. Epub 2019 Oct 22.

Norwegian, Exeter and King's College Consortium for Genetics of Neuropsychiatric Symptoms in Dementia, Exeter, UK.

Psychosis (delusions or hallucinations) in Alzheimer's disease (AD + P) occurs in up to 50% of individuals and is associated with significantly worse clinical outcomes. Atypical antipsychotics, first developed for schizophrenia, are commonly used in AD + P, suggesting shared mechanisms. Despite this implication, little empirical research has been conducted to examine whether there are mechanistic similarities between AD + P and schizophrenia. In this study, we tested whether polygenic risk score (PRS) for schizophrenia was associated with AD + P. Schizophrenia PRS was calculated using Psychiatric Genomics Consortium data at ten GWAS p value thresholds (P) in 3111 AD cases from 11 cohort studies characterized for psychosis using validated, standardized tools. Association between PRS and AD + P status was tested by logistic regression in each cohort individually and the results meta-analyzed. The schizophrenia PRS was associated with AD + P at an optimum P of 0.01. The strongest association was for delusions where a one standard deviation increase in PRS was associated with a 1.18-fold increased risk (95% CI: 1.06-1.3; p = 0.001). These new findings point towards psychosis in AD-and particularly delusions-sharing some genetic liability with schizophrenia and support a transdiagnostic view of psychotic symptoms across the lifespan.
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http://dx.doi.org/10.1038/s41398-019-0592-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805870PMC
October 2019

Childhood maltreatment and polygenic risk in bipolar disorders.

Bipolar Disord 2020 03 13;22(2):174-181. Epub 2019 Nov 13.

Université Paris Diderot, Paris, France.

Background: Childhood maltreatment is a well-known risk factor for developing a more severe and complex form of bipolar disorders (BD). However, knowledge is scarce about the interactions between childhood maltreatment and underlying genetic vulnerability on the clinical expression of BD.

Method: We assigned a BD-polygenic risk score (BD-PRS), calculated from the Psychiatric Genomics Consortium, to each individual in a sample of 402 cases with BD. The lifetime clinical expression of BD was characterized using structured interviews and patients completed the Childhood Trauma Questionnaire (CTQ) to assess the severity of childhood maltreatment.

Results: Cases who reported more severe childhood maltreatment had a lower BD-PRS (rho = -0.12, P = .01), especially when considering emotional abuse (rho = -0.16, P = .001). An interaction between BD-PRS and childhood maltreatment was observed for the risk of rapid cycling (P = .01). No further interactions between BD-PRS and childhood maltreatment were observed for other clinical characteristics (age at onset, suicide attempts, number of mood episodes, mixed features, substance use disorders and psychotic symptoms).

Conclusion: Our study is the first to show that less genetic risk may be needed to develop a more unstable form of BD when exposed to childhood maltreatment. Our study supports childhood trauma as an independent risk factor for BD.
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http://dx.doi.org/10.1111/bdi.12851DOI Listing
March 2020

Autism spectrum disorder polygenic scores are associated with every day executive function in children admitted for clinical assessment.

Autism Res 2020 02 30;13(2):207-220. Epub 2019 Sep 30.

NORMENT Centre, University of Oslo, Oslo, Norway.

Autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDs) are behaviorally defined disorders with overlapping clinical features that are often associated with higher-order cognitive dysfunction, particularly executive dysfunction. Our aim was to determine if the polygenic score (PGS) for ASD is associated with parent-reported executive dysfunction in everyday life using the Behavior Rating Inventory of Executive Function (BRIEF). Furthermore, we investigated if PGS for general intelligence (INT) and attention deficit/hyperactivity disorder (ADHD) also correlate with BRIEF. We included 176 children, adolescents and young adults aged 5-22 years with full-scale intelligence quotient (IQ) above 70. All were admitted for clinical assessment of ASD symptoms and 68% obtained an ASD diagnosis. We found a significant difference between low and high ASD PGS groups in the BRIEF behavior regulation index (BRI) (P = 0.015, Cohen's d = 0.69). A linear regression model accounting for age, sex, full-scale IQ, Social Responsiveness Scale (SRS) total score, ASD, ADHD and INT PGS groups as well as genetic principal components, significantly predicted the BRI score; F(11,130) = 8.142, P < 0.001, R = 0.41 (unadjusted). Only SRS total (P < 0.001), ASD PGS 0.1 group (P = 0.018), and sex (P = 0.022) made a significant contribution to the model. This suggests that the common ASD risk gene variants have a stronger association to behavioral regulation aspects of executive dysfunction than ADHD risk or INT variants in a clinical sample with ASD symptoms. Autism Res 2020, 13: 207-220. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: People with autism spectrum disorder (ASD) often have difficulties with higher-order cognitive processes that regulate thoughts and actions during goal-directed behavior, also known as executive function (EF). We studied the association between genetics related to ASD and EF and found a relation between high polygenic score (PGS) for ASD and difficulties with behavior regulation aspects of EF in children and adolescents under assessment for ASD. Furthermore, high PGS for general intelligence was related to social problems.
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http://dx.doi.org/10.1002/aur.2207DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027890PMC
February 2020

Common brain disorders are associated with heritable patterns of apparent aging of the brain.

Nat Neurosci 2019 10 24;22(10):1617-1623. Epub 2019 Sep 24.

Centre for Psychiatry Research, Department of Clinical Neuroscience Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden.

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.
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http://dx.doi.org/10.1038/s41593-019-0471-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823048PMC
October 2019

Biophysical Psychiatry-How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders.

Front Psychiatry 2019 6;10:534. Epub 2019 Aug 6.

NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options.
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http://dx.doi.org/10.3389/fpsyt.2019.00534DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691488PMC
August 2019

Correction: Genome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence.

Mol Psychiatry 2020 Apr;25(4):914

NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.

A correction to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41380-019-0456-7DOI Listing
April 2020

GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study.

Sci Rep 2019 05 7;9(1):7013. Epub 2019 May 7.

Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders.
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http://dx.doi.org/10.1038/s41598-019-43458-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6504850PMC
May 2019

Brain Heterogeneity in Schizophrenia and Its Association With Polygenic Risk.

JAMA Psychiatry 2019 07;76(7):739-748

Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Norway.

Importance: Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature.

Objectives: To compare brain structural variability between individuals with schizophrenia and healthy controls and to test whether respective variability reflects the polygenic risk score (PRS) for schizophrenia in an independent sample of healthy controls.

Design, Setting, And Participants: This case-control and polygenic risk analysis compared MRI-derived cortical thickness and subcortical volumes between healthy controls and patients with schizophrenia across 16 cohorts and tested for associations between PRS and MRI features in a control cohort from the UK Biobank. Data were collected from October 27, 2004, through April 12, 2018, and analyzed from December 3, 2017, through August 1, 2018.

Main Outcomes And Measures: Mean and dispersion parameters were estimated using double generalized linear models. Vertex-wise analysis was used to assess cortical thickness, and regions-of-interest analyses were used to assess total cortical volume, total surface area, and white matter, subcortical, and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, test of robustness of the PRS threshold, population covariates, outlier removal, and control for image quality.

Results: A comparison of 1151 patients with schizophrenia (mean [SD] age, 33.8 [10.6] years; 68.6% male [n = 790] and 31.4% female [n = 361]) with 2010 healthy controls (mean [SD] age, 32.6 [10.4] years; 56.0% male [n = 1126] and 44.0% female [n = 884]) revealed higher heterogeneity in schizophrenia for cortical thickness and area (t = 3.34), cortical (t = 3.24) and ventricle (t range, 3.15-5.78) volumes, and hippocampal subfields (t range, 2.32-3.55). In the UK Biobank sample of 12 490 participants (mean [SD] age, 55.9 [7.5] years; 48.2% male [n = 6025] and 51.8% female [n = 6465]), higher PRS was associated with thinner frontal and temporal cortices and smaller left CA2/3 (t = -3.00) but was not significantly associated with dispersion.

Conclusions And Relevance: This study suggests that schizophrenia is associated with substantial brain structural heterogeneity beyond the mean differences. These findings may reflect higher sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of schizophrenia. A higher PRS was associated with thinner frontotemporal cortices and smaller hippocampal subfield volume, but not heterogeneity. This finding suggests that brain variability in schizophrenia results from interactions between environmental and genetic factors that are not captured by the PRS. Factors contributing to heterogeneity in frontotemporal cortices and hippocampus are key to furthering our understanding of how genetic and environmental factors shape brain biology in schizophrenia.
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http://dx.doi.org/10.1001/jamapsychiatry.2019.0257DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6583664PMC
July 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

Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk.

Nat Genet 2019 03 7;51(3):404-413. Epub 2019 Jan 7.

MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK.

Alzheimer's disease (AD) is highly heritable and recent studies have identified over 20 disease-associated genomic loci. Yet these only explain a small proportion of the genetic variance, indicating that undiscovered loci remain. Here, we performed a large genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 cases, 383,378 controls). AD-by-proxy, based on parental diagnoses, showed strong genetic correlation with AD (r = 0.81). Meta-analysis identified 29 risk loci, implicating 215 potential causative genes. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver, and microglia). Gene-set analyses indicate biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomization results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD.
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http://dx.doi.org/10.1038/s41588-018-0311-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6836675PMC
March 2019
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