Publications by authors named "Srdjan Djurovic"

254 Publications

Cardiometabolic risk factors associated with brain age and accelerate brain ageing.

Hum Brain Mapp 2021 Oct 9. Epub 2021 Oct 9.

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

The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross-sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue-specific BAGs. The results showed credible associations between DTI-based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1-based BAG and systolic blood pressure, smoking, pulse, and C-reactive protein (CRP), indicating older-appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low-grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist-to-hip ratio (WHR), and between DTI-based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing.
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http://dx.doi.org/10.1002/hbm.25680DOI Listing
October 2021

Plasma Levels of the Cytokines B Cell-Activating Factor (BAFF) and A Proliferation-Inducing Ligand (APRIL) in Schizophrenia, Bipolar, and Major Depressive Disorder: A Cross Sectional, Multisite Study.

Schizophr Bull 2021 Sep 9. Epub 2021 Sep 9.

Norwegian Centre for Mental Disorders Research, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.

Background: Immune dysfunction has been implicated in the pathogenesis of schizophrenia and other nonaffective psychosis (SCZ), bipolar spectrum disorder (BIP) and major depressive disorder (MDD). The cytokines B cell-activating factor (BAFF) and A proliferation-inducing ligand (APRIL) belong to the tumor necrosis factor (TNF) super family and are essential in orchestrating immune responses. Abnormal levels of BAFF and APRIL have been found in autoimmune diseases with CNS affection.

Methods: We investigated if plasma levels of BAFF and APRIL differed between patients with SCZ, BIP, and MDD with psychotic symptoms (n = 2009) and healthy control subjects (HC, n = 1212), and tested for associations with psychotic symptom load, controlling for sociodemographic status, antipsychotic and other psychotropic medication, smoking, body-mass-index, and high sensitivity CRP.

Results: Plasma APRIL level was significantly lower across all patient groups compared to HC (P < .001; Cohen's d = 0.33), and in SCZ compared to HC (P < .001; d = 0.28) and in BIP compared to HC (P < .001; d = 0.37). Lower plasma APRIL was associated with higher psychotic symptom load with nominal significance (P = .017), but not with any other clinical characteristics. Plasma BAFF was not significantly different across patient groups vs HC, but significantly higher in BIP compared to HC (P = .040; d = 0.12) and SCZ (P = .027; d = 0.10).

Conclusions: These results show aberrant levels of BAFF and APRIL and association with psychotic symptoms in patients with SCZ and BIP. This suggest that dysregulation of the TNF system, mediated by BAFF and APRIL, is involved in the pathophysiology of psychotic disorders.
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http://dx.doi.org/10.1093/schbul/sbab106DOI Listing
September 2021

Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking.

Transl Psychiatry 2021 09 8;11(1):466. Epub 2021 Sep 8.

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

Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315-466,751). Genomic loci were functionally annotated using FUMA. Of 8.6-8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2-10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.
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http://dx.doi.org/10.1038/s41398-021-01576-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426401PMC
September 2021

A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease.

Nat Genet 2021 09 7;53(9):1276-1282. Epub 2021 Sep 7.

Division of Genetic Medicine, Department of Medicine Vanderbilt University Medical Center Nashville, Nashville, TN, USA.

Late-onset Alzheimer's disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer's disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer's disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer's disease to identify further genetic variants that contribute to Alzheimer's pathology.
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http://dx.doi.org/10.1038/s41588-021-00921-zDOI Listing
September 2021

Characterizing the Genetic Overlap Between Psychiatric Disorders and Sleep-Related Phenotypes.

Biol Psychiatry 2021 Nov 14;90(9):621-631. Epub 2021 Jul 14.

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

Background: A range of sleep disturbances are commonly experienced by patients with psychiatric disorders, and genome-wide genetic analyses have shown some significant genetic correlations between these traits. Here, we applied novel statistical genetic methodologies to better characterize the potential shared genetic architecture between sleep-related phenotypes and psychiatric disorders.

Methods: Using the MiXeR method, which can estimate polygenic overlap beyond genetic correlation, the shared genetic architecture between major psychiatric disorders (bipolar disorder [N = 51,710], depression [N = 480,359], and schizophrenia [N = 77,096]) and sleep-related phenotypes (chronotype [N = 449,734], insomnia [N = 386,533] and sleep duration [N = 446,118]) were quantified on the basis of genetic summary statistics. Furthermore, the conditional/conjunctional false discovery rate framework was used to identify specific shared loci between these phenotypes, for which positional and functional annotation were conducted with FUMA.

Results: Extensive genetic overlap between the sleep-related phenotypes and bipolar disorder (63%-77%), depression (76%-79%), and schizophrenia (64%-79%) was identified, with moderate levels of congruence between most investigated traits (47%-58%). Specific shared loci were identified for all bivariate analyses, and a subset of 70 credible genes were mapped to these shared loci.

Conclusions: The current results provide evidence for substantial polygenic overlap between psychiatric disorders and sleep-related phenotypes, beyond genetic correlation (|r| = 0.02 to 0.42). Moderate congruency within the shared genetic components suggests a complex genetic relationship and potential subgroups with higher or lower genetic concordance. This work provides new insights and understanding of the shared genetic etiology of sleep-related phenotypes and psychiatric disorders and highlights new opportunities and avenues for future investigation.
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http://dx.doi.org/10.1016/j.biopsych.2021.07.007DOI Listing
November 2021

Genome-wide analysis reveals genetic overlap between alcohol use behaviours, schizophrenia and bipolar disorder and identifies novel shared risk loci.

Addiction 2021 Sep 2. Epub 2021 Sep 2.

NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.

Background And Aim: Schizophrenia (SCZ) and bipolar disorder (BD) have a high comorbidity of alcohol use disorder (AUD), and both comorbid AUD and excessive alcohol consumption (AC) have been linked to greater illness severity. We aimed to identify genomic loci jointly associated with SCZ, BD, AUD and AC to gain further insights into their shared genetic architecture.

Design: We analysed summary data (P values and Z scores) from genome-wide association studies (GWAS) using conjunctional false discovery rate (conjFDR) analysis, which increases power to discover shared genomic loci. We functionally characterized the identified loci using publicly available biological resources.

Setting: AUD and AC data provided by the Million Veteran Program, derived from the United States Department of Veterans Affairs Healthcare System. SCZ and BD data provided by the Psychiatric Genomics Consortium, based on cohorts from countries in Europe, North America and Australia.

Participants: AUD (34 658 cases, 167 346 controls), AC (n = 200 680), SCZ (31 013 cases and 38 918 controls), BD (20 352 cases and 31 358 controls). All participants were of European ancestry.

Measurements: Genomic loci shared between alcohol traits, SCZ and BD at conjFDR <0.05.

Findings: Conditional Q-Q plots showed single-nucleotide polymorphism (SNP) enrichment for both alcohol traits across different levels of significance with SCZ and BD, and vice versa. Using conjFDR analysis we leveraged this genetic enrichment and identified several loci shared between SCZ and AUD (n = 28) and AC (n = 24), BD and AUD (n = 2) and AC (n = 8) at conjFDR <0.05. Among these loci, 24 are novel for AUD, 15 are novel for AC, three are novel for SCZ and one is novel for BD. There was a mixture of same and opposite effect directions among the shared loci.

Conclusions: Alcohol use disorder and alcohol consumption share genomic loci with the psychiatric disorders schizophrenia and bipolar disorder with a mixed pattern of effect directions, indicating a complex genetic relationship between the phenotypes.
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http://dx.doi.org/10.1111/add.15680DOI Listing
September 2021

Derivation and Molecular Characterization of a Morphological Subpopulation of Human iPSC Astrocytes Reveal a Potential Role in Schizophrenia and Clozapine Response.

Schizophr Bull 2021 Aug 5. Epub 2021 Aug 5.

Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.

Astrocytes are the most abundant cell type in the human brain and are important regulators of several critical cellular functions, including synaptic transmission. Although astrocytes are known to play a central role in the etiology and pathophysiology of schizophrenia, little is known about their potential involvement in clinical response to the antipsychotic clozapine. Moreover, astrocytes display a remarkable degree of morphological diversity, but the potential contribution of astrocytic subtypes to disease biology and drug response has received little attention. Here, we used state-of-the-art human induced pluripotent stem cell (hiPSC) technology to derive a morphological subtype of astrocytes from healthy individuals and individuals with schizophrenia, including responders and nonresponders to clozapine. Using functional assays and transcriptional profiling, we identified a distinct gene expression signature highly specific to schizophrenia as shown by disease association analysis of more than 10 000 diseases. We further found reduced levels of both glutamate and the NMDA receptor coagonist d-serine in subtype astrocytes derived from schizophrenia patients, and that exposure to clozapine only rescued this deficiency in cells from clozapine responders, providing further evidence that d-serine in particular, and NMDA receptor-mediated glutamatergic neurotransmission in general, could play an important role in disease pathophysiology and clozapine action. Our study represents a first attempt to explore the potential contribution of astrocyte diversity to schizophrenia pathophysiology using a human cellular model. Our findings suggest that specialized subtypes of astrocytes could be important modulators of disease pathophysiology and clinical drug response, and warrant further investigations.
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http://dx.doi.org/10.1093/schbul/sbab092DOI Listing
August 2021

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 2022 Jan 25;112:110408. 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
January 2022

Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes.

Transl Psychiatry 2021 07 23;11(1):407. Epub 2021 Jul 23.

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

Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208-795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20-22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR < 0.05, we identified 129 shared loci between BIP and CVD phenotypes, mainly BMI (n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.
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http://dx.doi.org/10.1038/s41398-021-01527-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8302675PMC
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

Shared genetic architecture between neuroticism, coronary artery disease and cardiovascular risk factors.

Transl Psychiatry 2021 06 17;11(1):368. Epub 2021 Jun 17.

NORMENT: Norwegian Centre for Mental Disorders Research, University of Oslo and Oslo University Hospital, Oslo, Norway.

Neuroticism is associated with poor health, cardiovascular disease (CVD) risk factors and coronary artery disease (CAD). The conditional/conjunctional false discovery rate method (cond/conjFDR) was applied to genome wide association study (GWAS) summary statistics on neuroticism (n = 432,109), CAD (n = 184,305) and 12 CVD risk factors (n = 188,577-339,224) to investigate genetic overlap between neuroticism and CAD and CVD risk factors. CondFDR analyses identified 729 genomic loci associated with neuroticism after conditioning on CAD and CVD risk factors. The conjFDR analyses revealed 345 loci jointly associated with neuroticism and CAD (n = 30), body mass index (BMI) (n = 96) or another CVD risk factor (n = 1-60). Several loci were jointly associated with neuroticism and multiple CVD risk factors. Seventeen of the shared loci with CAD and 61 of the shared loci with BMI are novel for neuroticism. 21 of 30 (70%) neuroticism risk alleles were associated with higher CAD risk. Functional analyses of the genes mapped to the shared loci implicated cell division, nuclear receptor, elastic fiber formation as well as starch and sucrose metabolism pathways. Our results indicate polygenic overlap between neuroticism and CAD and CVD risk factors, suggesting that genetic factors may partly cause the comorbidity. This gives new insight into the shared molecular genetic basis of these conditions.
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http://dx.doi.org/10.1038/s41398-021-01466-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257646PMC
June 2021

Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness.

JAMA Psychiatry 2021 Sep;78(9):1020-1030

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

Importance: Schizophrenia is a complex heritable disorder associated with many genetic variants, each with a small effect. While cortical differences between patients with schizophrenia and healthy controls are consistently reported, the underlying molecular mechanisms remain elusive.

Objective: To investigate the extent of shared genetic architecture between schizophrenia and brain cortical surface area (SA) and thickness (TH) and to identify shared genomic loci.

Design, Setting, And Participants: Independent genome-wide association study data on schizophrenia (Psychiatric Genomics Consortium and CLOZUK: n = 105 318) and SA and TH (UK Biobank: n = 33 735) were obtained. The extent of polygenic overlap was investigated using MiXeR. The specific shared genomic loci were identified by conditional/conjunctional false discovery rate analysis and were further examined in 3 independent cohorts. Data were collected from December 2019 to February 2021, and data analysis was performed from May 2020 to February 2021.

Main Outcomes And Measures: The primary outcomes were estimated fractions of polygenic overlap between schizophrenia, total SA, and average TH and a list of functionally characterized shared genomic loci.

Results: Based on genome-wide association study data from 139 053 participants, MiXeR estimated schizophrenia to be more polygenic (9703 single-nucleotide variants [SNVs]) than total SA (2101 SNVs) and average TH (1363 SNVs). Most SNVs associated with total SA (1966 of 2101 [93.6%]) and average TH (1322 of 1363 [97.0%]) may be associated with the development of schizophrenia. Subsequent conjunctional false discovery rate analysis identified 44 and 23 schizophrenia risk loci shared with total SA and average TH, respectively. The SNV associations of shared loci between schizophrenia and total SA revealed en masse concordant association between the discovery and independent cohorts. After removing high linkage disequilibrium regions, such as the major histocompatibility complex region, the shared loci were enriched in immunologic signature gene sets. Polygenic overlap and shared loci between schizophrenia and schizophrenia-associated regions of interest for SA (superior frontal and middle temporal gyri) and for TH (superior temporal, inferior temporal, and superior frontal gyri) were also identified.

Conclusions And Relevance: This study demonstrated shared genetic loci between cortical morphometry and schizophrenia, among which a subset are associated with immunity. These findings provide an insight into the complex genetic architecture and associated with schizophrenia.
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http://dx.doi.org/10.1001/jamapsychiatry.2021.1435DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8223140PMC
September 2021

All-Optical Electrophysiology in hiPSC-Derived Neurons With Synthetic Voltage Sensors.

Front Cell Neurosci 2021 28;15:671549. Epub 2021 May 28.

Department of Biomedical Engineering, Boston University, Boston, MA, United States.

Voltage imaging and "all-optical electrophysiology" in human induced pluripotent stem cell (hiPSC)-derived neurons have opened unprecedented opportunities for high-throughput phenotyping of activity in neurons possessing unique genetic backgrounds of individual patients. While prior all-optical electrophysiology studies relied on genetically encoded voltage indicators, here, we demonstrate an alternative protocol using a synthetic voltage sensor and genetically encoded optogenetic actuator that generate robust and reproducible results. We demonstrate the functionality of this method by measuring spontaneous and evoked activity in three independent hiPSC-derived neuronal cell lines with distinct genetic backgrounds.
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http://dx.doi.org/10.3389/fncel.2021.671549DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8193062PMC
May 2021

Genome-wide association identifies the first risk loci for psychosis in Alzheimer disease.

Mol Psychiatry 2021 Jun 10. Epub 2021 Jun 10.

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

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD with psychosis, AD + P). AD + P affects ~50% of individuals with AD, identifies a subgroup with poor outcomes, and is associated with a greater degree of cognitive impairment and depressive symptoms, compared to subjects without psychosis (AD - P). Although the estimated heritability of AD + P is 61%, genetic sources of risk are unknown. We report a genome-wide meta-analysis of 12,317 AD subjects, 5445 AD + P. Results showed common genetic variation accounted for a significant portion of heritability. Two loci, one in ENPP6 (rs9994623, O.R. (95%CI) 1.16 (1.10, 1.22), p = 1.26 × 10) and one spanning the 3'-UTR of an alternatively spliced transcript of SUMF1 (rs201109606, O.R. 0.65 (0.56-0.76), p = 3.24 × 10), had genome-wide significant associations with AD + P. Gene-based analysis identified a significant association with APOE, due to the APOE risk haplotype ε4. AD + P demonstrated negative genetic correlations with cognitive and educational attainment and positive genetic correlation with depressive symptoms. We previously observed a negative genetic correlation with schizophrenia; instead, we now found a stronger negative correlation with the related phenotype of bipolar disorder. Analysis of polygenic risk scores supported this genetic correlation and documented a positive genetic correlation with risk variation for AD, beyond the effect of ε4. We also document a small set of SNPs likely to affect risk for AD + P and AD or schizophrenia. These findings provide the first unbiased identification of the association of psychosis in AD with common genetic variation and provide insights into its genetic architecture.
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http://dx.doi.org/10.1038/s41380-021-01152-8DOI Listing
June 2021

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Nat Commun 2021 06 7;12(1):3417. Epub 2021 Jun 7.

Servei de Neurologia, Hospital Universitari i Politècnic La Fe, Valencia, Spain.

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.
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http://dx.doi.org/10.1038/s41467-021-22491-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184987PMC
June 2021

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8458480PMC
March 2021

Lithium increases mitochondrial respiration in iPSC-derived neural precursor cells from lithium responders.

Mol Psychiatry 2021 Jun 1. Epub 2021 Jun 1.

Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.

Lithium (Li), valproate (VPA) and lamotrigine (LTG) are commonly used to treat bipolar disorder (BD). While their clinical efficacy is well established, the mechanisms of action at the molecular level are still incompletely understood. Here we investigated the molecular effects of Li, LTG and VPA treatment in induced pluripotent stem cell (iPSC)-derived neural precursor cells (NPCs) generated from 3 healthy controls (CTRL), 3 affective disorder Li responsive patients (Li-R) and 3 Li non-treated patients (Li-N) after 6 h and 1 week of exposure. Differential expression (DE) analysis after 6 h of treatment revealed a transcriptional signature that was associated with all three drugs and most significantly enriched for ribosome and oxidative phosphorylation (OXPHOS) pathways. In addition to the shared DE genes, we found that Li exposure was associated with 554 genes uniquely regulated in Li-R NPCs and enriched for spliceosome, OXPHOS and thermogenesis pathways. In-depth analysis of the treatment-associated transcripts uncovered a significant decrease in intron retention rate, suggesting that the beneficial influence of these drugs might partly be related to splicing. We examined the mitochondrial respiratory function of the NPCs by exploring the drugs' effects on oxygen consumption rate (OCR) and glycolytic rate (ECAR). Li improved OCR levels only in Li-R NPCs by enhancing maximal respiration and reserve capacity, while VPA enhanced maximal respiration and reserve capacity in Li-N NPCs. Overall, our findings further support the involvement of mitochondrial functions in the molecular mechanisms of mood stabilizers and suggest novel mechanisms related to the spliceosome, which warrant further investigation.
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http://dx.doi.org/10.1038/s41380-021-01164-4DOI Listing
June 2021

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics.

Neuropsychopharmacology 2021 09 25;46(10):1788-1801. Epub 2021 May 25.

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.
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http://dx.doi.org/10.1038/s41386-021-01023-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357785PMC
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

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

Pharmacogenomics J 2021 Oct 6;21(5):574-585. 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
October 2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Transl Psychiatry 2021 03 22;11(1):182. Epub 2021 Mar 22.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
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http://dx.doi.org/10.1038/s41398-021-01213-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985307PMC
March 2021

Association between complement component 4A expression, cognitive performance and brain imaging measures in UK Biobank.

Psychol Med 2021 Mar 3:1-11. Epub 2021 Mar 3.

Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.

Abstract.

Background: Altered expression of the complement component C4A gene is a known risk factor for schizophrenia. Further, predicted brain C4A expression has also been associated with memory function highlighting that altered C4A expression in the brain may be relevant for cognitive and behavioral traits.

Methods: We obtained genetic information and performance measures on seven cognitive tasks for up to 329 773 individuals from the UK Biobank, as well as brain imaging data for a subset of 33 003 participants. Direct genotypes for variants (n = 3213) within the major histocompatibility complex region were used to impute C4 structural variation, from which predicted expression of the C4A and C4B genes in human brain tissue were predicted. We investigated if predicted brain C4A or C4B expression were associated with cognitive performance and brain imaging measures using linear regression analyses.

Results: We identified significant negative associations between predicted C4A expression and performance on select cognitive tests, and significant associations with MRI-based cortical thickness and surface area in select regions. Finally, we observed significant inconsistent partial mediation of the effects of predicted C4A expression on cognitive performance, by specific brain structure measures.

Conclusions: These results demonstrate that the C4 risk locus is associated with the central endophenotypes of cognitive performance and brain morphology, even when considered independently of other genetic risk factors and in individuals without mental or neurological disorders.
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http://dx.doi.org/10.1017/S0033291721000179DOI Listing
March 2021

Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.

Hum Brain Mapp 2021 Feb 21. Epub 2021 Feb 21.

Center for Neuroimaging, Genetics and Genomics, School of Psychology, NUI Galway, Galway, Ireland.

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
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http://dx.doi.org/10.1002/hbm.25354DOI Listing
February 2021

Transcriptome analysis reveals disparate expression of inflammation-related miRNAs and their gene targets in iPSC-astrocytes from people with schizophrenia.

Brain Behav Immun 2021 05 9;94:235-244. Epub 2021 Feb 9.

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

Despite the high heritability of schizophrenia (SCZ), details of its pathophysiology and etiology are still unknown. Recent findings suggest that aberrant inflammatory regulation and microRNAs (miRNAs) are involved. Here we performed a comparative analysis of the global miRNome of human induced pluripotent stem cell (iPSC)-astrocytes, derived from SCZ patients and healthy controls (CTRLs), at baseline and following inflammatory modulation using IL-1β. We identified four differentially expressed miRNAs (miR-337-3p, miR-127-5p, miR-206, miR-1185-1-3p) in SCZ astrocytes that exhibited significantly lower baseline expression relative to CTRLs. Group-specific differential expression (DE) analyses exploring possible distinctions in the modulatory capacity of IL-1β on miRNA expression in SCZ versus CTRL astroglia revealed trends toward altered miRNA expressions. In addition, we analyzed peripheral blood samples from a large cohort of SCZ patients (n = 484) and CTRLs (n = 496) screening for the expression of specific gene targets of the four DE miRNAs that were identified in our baseline astrocyte setup. Three of these genes, LAMTOR4, IL23R, and ERBB3, had a significantly lower expression in the blood of SCZ patients compared to CTRLs after multiple testing correction. We also found nominally significant differences for ERBB2 and IRAK1, which similarly displayed lower expressions in SCZ versus CTRL. Furthermore, we found matching patterns between the expressions of identified miRNAs and their target genes when comparing our in vitro and in vivo results. The current results further our understanding of the pathobiological basis of SCZ.
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http://dx.doi.org/10.1016/j.bbi.2021.01.037DOI Listing
May 2021

Using iPSC Models to Understand the Role of Estrogen in Neuron-Glia Interactions in Schizophrenia and Bipolar Disorder.

Cells 2021 01 21;10(2). Epub 2021 Jan 21.

NORMENT, Institute of Clinical Medicine, University of Oslo & Division of Mental Health and Addiction, Oslo University Hospital, 0450 Oslo, Norway.

Schizophrenia (SCZ) and bipolar disorder (BIP) are severe mental disorders with a considerable disease burden worldwide due to early age of onset, chronicity, and lack of efficient treatments or prevention strategies. Whilst our current knowledge is that SCZ and BIP are highly heritable and share common pathophysiological mechanisms associated with cellular signaling, neurotransmission, energy metabolism, and neuroinflammation, the development of novel therapies has been hampered by the unavailability of appropriate models to identify novel targetable pathomechanisms. Recent data suggest that neuron-glia interactions are disturbed in SCZ and BIP, and are modulated by estrogen (E2). However, most of the knowledge we have so far on the neuromodulatory effects of E2 came from studies on animal models and human cell lines, and may not accurately reflect many processes occurring exclusively in the human brain. Thus, here we highlight the advantages of using induced pluripotent stem cell (iPSC) models to revisit studies of mechanisms underlying beneficial effects of E2 in human brain cells. A better understanding of these mechanisms opens the opportunity to identify putative targets of novel therapeutic agents for SCZ and BIP. In this review, we first summarize the literature on the molecular mechanisms involved in SCZ and BIP pathology and the beneficial effects of E2 on neuron-glia interactions. Then, we briefly present the most recent developments in the iPSC field, emphasizing the potential of using patient-derived iPSCs as more relevant models to study the effects of E2 on neuron-glia interactions.
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http://dx.doi.org/10.3390/cells10020209DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909800PMC
January 2021

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

Nat Hum Behav 2021 06 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 overlap and shared genetic loci between loneliness, severe mental disorders, and cardiovascular disease risk factors suggest shared molecular mechanisms.

Transl Psychiatry 2021 01 5;11(1). Epub 2021 Jan 5.

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

Clinical and epidemiological evidence suggest that loneliness is associated with severe mental disorders (SMDs) and increases the risk of cardiovascular disease (CVD). However, the mechanisms underlying the relationship between loneliness, SMDs, and CVD risk factors remain unknown. Here we explored overlapping genetic architecture and genetic loci shared between SMDs, loneliness, and CVD risk factors. We analyzed large independent genome-wide association study data on schizophrenia (SCZ), bipolar disorder (BD), major depression (MD), loneliness and CVD risk factors using bivariate causal mixture mode (MiXeR), which estimates the total amount of shared variants, and conditional false discovery rate to evaluate overlap in specific loci. We observed substantial genetic overlap between SMDs, loneliness and CVD risk factors, beyond genetic correlation. We identified 149 loci jointly associated with loneliness and SMDs (MD n = 67, SCZ n = 54, and BD n = 28), and 55 distinct loci jointly associated with loneliness and CVD risk factors. A total of 153 novel loneliness loci were found. Most of the shared loci possessed concordant effect directions, suggesting that genetic risk for loneliness may increase the risk of both SMDs and CVD. Functional analyses of the shared loci implicated biological processes related to the brain, metabolic processes, chromatin and immune system. Altogether, the study revealed polygenic overlap between loneliness, SMDs and CVD risk factors, providing new insights into their shared genetic architecture and common genetic mechanisms.
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http://dx.doi.org/10.1038/s41398-020-01142-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790035PMC
January 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

Correction: Identification of a novel polymorphism associated with reduced clozapine concentration in schizophrenia patients-a genome-wide association study adjusting for smoking habits.

Transl Psychiatry 2020 Nov 2;10(1):366. Epub 2020 Nov 2.

Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway.

An amendment 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/s41398-020-01061-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608619PMC
November 2020
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