| 61. |
- Chang, H., et al.
(författare)
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The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders
- 2018
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 23:2, s. 400-412
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Tidskriftsartikel (refereegranskat)abstract
- Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.
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| 62. |
- Charney, Alexander W, et al.
(författare)
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Contribution of Rare Copy Number Variants to Bipolar Disorder Risk Is Limited to Schizoaffective Cases.
- 2019
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Ingår i: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 86:2, s. 110-119
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Tidskriftsartikel (refereegranskat)abstract
- Genetic risk for bipolar disorder (BD) is conferred through many common alleles, while a role for rare copy number variants (CNVs) is less clear. Subtypes of BD including schizoaffective disorder bipolar type (SAB), bipolar I disorder (BD I), and bipolar II disorder (BD II) differ according to the prominence and timing of psychosis, mania, and depression. The genetic factors contributing to the combination of symptoms among these subtypes are poorly understood.Rare large CNVs were analyzed in 6353 BD cases (3833 BD I [2676 with psychosis, 850 without psychosis, and 307 with unknown psychosis history], 1436 BD II, 579 SAB, and 505 BD not otherwise specified) and 8656 controls. CNV burden and a polygenic risk score (PRS) for schizophrenia were used to evaluate the relative contributions of rare and common variants to risk of BD, BD subtypes, and psychosis.CNV burden did not differ between BD and controls when treated as a single diagnostic entity. However, burden in SAB was increased relative to controls (p = .001), BD I (p = .0003), and BD II (p = .0007). Burden and schizophrenia PRSs were increased in SAB compared with BD I with psychosis (CNV p = .0007, PRS p = .004), and BD I without psychosis (CNV p = .0004, PRS p = 3.9 × 10-5). Within BD I, psychosis was associated with increased schizophrenia PRSs (p = .005) but not CNV burden.CNV burden in BD is limited to SAB. Rare and common genetic variants may contribute differently to risk for psychosis and perhaps other classes of psychiatric symptoms.
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| 63. |
- Charney, A. W., et al.
(författare)
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Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder
- 2017
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Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- We performed a genome-wide association study of 6447 bipolar disorder (BD) cases and 12 639 controls from the International Cohort Collection for Bipolar Disorder (ICCBD). Meta-analysis was performed with prior results from the Psychiatric Genomics Consortium Bipolar Disorder Working Group for a combined sample of 13 902 cases and 19 279 controls. We identified eight genome-wide significant, associated regions, including a novel associated region on chromosome 10 (rs10884920; P = 3.28 x 10(-8)) that includes the brain-enriched cytoskeleton protein adducin 3 (ADD3), a non-coding RNA, and a neuropeptide-specific aminopeptidase P (XPNPEP1). Our large sample size allowed us to test the heritability and genetic correlation of BD subtypes and investigate their genetic overlap with schizophrenia and major depressive disorder. We found a significant difference in heritability of the two most common forms of BD (BD I SNP-h(2) = 0.35; BD II SNP-h(2) = 0.25; P = 0.02). The genetic correlation between BD I and BD II was 0.78, whereas the genetic correlation was 0.97 when BD cohorts containing both types were compared. In addition, we demonstrated a significantly greater load of polygenic risk alleles for schizophrenia and BD in patients with BD I compared with patients with BD II, and a greater load of schizophrenia risk alleles in patients with the bipolar type of schizoaffective disorder compared with patients with either BD I or BD II. These results point to a partial difference in the genetic architecture of BD subtypes as currently defined.
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| 64. |
- Chen, C. Y., et al.
(författare)
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Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records
- 2018
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Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 8:1, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363-372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h 2 g) and genetic correlation (r g) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency-"coded-strict", "coded-broad", and "coded-broad based on a single clinical encounter" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h 2 g were 0.24 (p = 0.015), 0.09 (p = 0.064), 0.13 (p = 0.003), 0.00 (p = 0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h 2 g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h 2 g) was 0.12 (p = 0.004). These h 2 g were lower or similar to the h 2 g observed by the ICCBD + PGCBD (0.23, p = 3.17E-80, total N = 33,181). However, the r g between ICCBD + PGCBD and the EHR-based cases were high for 95-NLP (0.66, p = 3.69 × 10-5), coded-strict (1.00, p = 2.40 × 10-4), and coded-broad (0.74, p = 8.11 × 10-7). The r g between EHR-based BD definitions ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.
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| 65. |
- Ching, C. R. K., et al.
(författare)
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What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group
- 2022
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 56-82
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Tidskriftsartikel (refereegranskat)abstract
- MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.
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| 66. |
- Clements, C. C., et al.
(författare)
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Genome-wide association study of patients with a severe major depressive episode treated with electroconvulsive therapy
- 2021
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26:10
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Tidskriftsartikel (refereegranskat)abstract
- Although large genome-wide association studies (GWAS) of major depressive disorder (MDD) have identified many significant loci, the SNP-based heritability remains notably low, which might be due to etiological heterogeneity in existing samples. Here, we test the utility of targeting the severe end of the MDD spectrum through genome-wide SNP genotyping of 2725 cases who received electroconvulsive therapy (ECT) for a major depressive episode (MDE) and 4035 controls. A subset of cases (n = 1796) met a narrow case definition (MDE occurring in the context of MDD). Standard GWAS quality control procedures and imputation were conducted. SNP heritability and genetic correlations with other traits were estimated using linkage disequilibrium score regression. Results were compared with MDD cases of mild-moderate severity receiving internet-based cognitive behavioral therapy (iCBT) and summary results from the Psychiatric Genomics Consortium (PGC). The SNP-based heritability was estimated at 29-34% (SE: 6%) for the narrow case definition, considerably higher than the 6.5-8.0% estimate in the most recent PGC MDD study. Our severe MDE cases had smaller genetic correlations with neurodevelopmental disorders and neuroticism than PGC MDD cases but higher genetic risk scores for bipolar disorder than iCBT MDD cases. One genome-wide significant locus was identified (rs114583506, P = 5e-8) in an intron of HLA-B in the major histocompatibility locus on chr6. These results indicate that individuals receiving ECT for an MDE have higher burden of common variant risk loci than individuals with mild-moderate MDD. Furthermore, severe MDE shows stronger relations with other severe adult-onset psychiatric disorders but weaker relations with personality and stress-related traits than mild-moderate MDD. These findings suggest a different genetic architecture at the severest end of the spectrum, and support further study of the severest MDD cases as an extreme phenotype approach to understand the etiology of MDD.
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| 67. |
- Coleman, Jonathan R I, et al.
(författare)
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The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls.
- 2020
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Ingår i: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 88:2, s. 169-184
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Tidskriftsartikel (refereegranskat)abstract
- Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder.The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.
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| 68. |
- Coombes, Brandon J, et al.
(författare)
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Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study.
- 2021
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Ingår i: Complex psychiatry. - : S. Karger AG. - 2673-3005 .- 2673-298X. ; 7:3-4, s. 80-89
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Tidskriftsartikel (refereegranskat)abstract
- Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.
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| 69. |
- Cremaschi, Laura, et al.
(författare)
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Prevalences of autoimmune diseases in schizophrenia, bipolar I and II disorder, and controls
- 2017
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Ingår i: Psychiatry Research. - : Elsevier BV. - 0165-1781 .- 1872-7123. ; 258, s. 9-14
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Tidskriftsartikel (refereegranskat)abstract
- Previous studies on the relationship between autoimmune diseases, schizophrenia, and bipolar disorder are mainly based on hospital discharge registers with insufficient coverage of outpatient data. Furthermore, data is scant on the prevalence of autoimmune diseases in bipolar subgroups. Here we estimate the self-reported prevalences of autoimmune diseases in schizophrenia, bipolar disorder type I and II, and controls. Lifetime prevalence of autoimmune diseases was assessed through a structured interview in a sample of 9076 patients (schizophrenia N = 5278, bipolar disorder type I N = 1952, type II N = 1846) and 6485 controls. Comparative analyses were performed using logistic regressions. The prevalence of diabetes type 1 did not differ between groups. Hyperthyroidism, hypothyroidism regardless of lithium effects, rheumatoid arthritis, and polymyalgia rheumatica were most common in bipolar disorder. Systemic lupus erythematosus was less common in bipolar disorder than in the other groups. The rate of autoimmune diseases did not differ significantly between bipolar subgroups. We conclude that prevalences of autoimmune diseases show clear differences between schizophrenia and bipolar disorder, but not between the bipolar subgroups. © 2017 Elsevier B.V.
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| 70. |
- Damberg, Mattias, et al.
(författare)
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Investigation of transcription factor AP-2 beta genotype in women with premenstrual dysphoric disorder.
- 2005
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Ingår i: Neuroscience letters. - : Elsevier BV. - 0304-3940. ; 377:1, s. 49-52
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Tidskriftsartikel (refereegranskat)abstract
- It has repeatedly been shown that the serotonergic system is involved in the symptomatology of premenstrual dysphoric disorder (PMDD). Women with PMDD are reported to differ from symptom-free controls with regard to serotonin-related biological markers. Evidence from family and twin studies suggests a genetic contribution to the aetiology of PMDD. The expression of human transcription factor AP-2beta in neural crest cell lineages and neuroectodermal cells suggests that this protein may be of importance for functional characteristics of neurons by regulating the expression of target genes. Within the monoaminergic systems, several genes have binding sites for AP-2beta in regulatory regions, suggesting an involvement of AP-2beta in these systems. The gene encoding AP-2beta is located on chromosome 6p12-p21.1 and includes a polymorphic region consisting of a variable number of [CAAA] repeats located in the second intron. We have earlier shown that AP-2beta genotype is associated with serotonergic phenotypes and that brainstem levels of AP-2beta correlate positively to serotonin metabolism in rat frontal cortex. The aim of this study was to investigate the relationship between PMDD and transcription factor AP-2beta genotype. The participants included 176 women with PMDD and 91 healthy controls. Genotyping was performed by polymerase chain reactions. We did not observe any differences in AP-2beta genotype frequencies between PMDD subjects and controls. Our results suggest that AP-2beta genotype is not a risk factor for PMDD. To our knowledge, this is the first study investigating transcription factor AP-2beta genotype in women with PMDD. Hence, these results should be considered preliminary until replicated.
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