1
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Benstock SE, Weaver K, Hettema JM, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. Behav Genet 2024; 54:353-366. [PMID: 38869698 DOI: 10.1007/s10519-024-10187-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 05/29/2024] [Indexed: 06/14/2024]
Abstract
Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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Affiliation(s)
- Sarah E Benstock
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Katherine Weaver
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - John M Hettema
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Brad Verhulst
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA.
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2
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Carnegie R, Borges MC, Jones HJ, Zheng J, Haycock P, Evans J, Martin RM. Omega-3 fatty acids and major depression: a Mendelian randomization study. Transl Psychiatry 2024; 14:222. [PMID: 38811538 PMCID: PMC11136966 DOI: 10.1038/s41398-024-02932-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 05/31/2024] Open
Abstract
Omega-3 fatty acids have been implicated in the aetiology of depressive disorders, though trials supplementing omega-3 to prevent major depressive disorder (MDD) have so far been unsuccessful. Whether this association is causal remains unclear. We used two sample Mendelian randomization (MR) to investigate causality. Genetic variants associated with circulating omega-3 and omega-6 fatty acids in UK Biobank (UKBB, n = 115,078) were selected as exposures. The Psychiatric Genomics Consortium (PGC) genome-wide association studies (GWAS) of MDD (n = 430,775; cases = 116,209; controls = 314,566) and recurrent depression (rMDD, n = 80,933; cases = 17,451; controls = 62,482), were used as outcomes. Multivariable MR (MVMR) models were used to account for biologically correlated lipids, such as high- and low-density cholesterol and triglycerides, and to explore the relative importance of longer-chain omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) using data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE, n = 8866). Genetic colocalization analyses were used to explore the presence of a shared underlying causal variant between traits. Genetically predicted total omega-3 fatty acids reduced the odds of MDD (ORIVW 0.96 per standard deviation (SD, i.e. 0.22 mmol/l) (95% CIs 0.93-0.98, p = 0.003)). The largest point estimates were observed for eicosapentaenoic acid (EPA), a long-chain omega-3 fatty acid (OREPA 0.92; 95% CI 0.88-0.96; p = 0.0002). The effect of omega-3 fatty acids was robust to MVMR models accounting for biologically correlated lipids. 'Leave-one-out' analyses highlighted the FADS gene cluster as a key driver of the effect. Colocalization analyses suggested a shared causal variant using the primary outcome sample, but genomic confounding could not be fully excluded. This study supports a role for omega-3 fatty acids, particularly EPA, in the aetiology of depression, although pleiotropic mechanisms cannot be ruled out. The findings support guidelines highlighting the importance of EPA dose and ratio for MDD and question whether targeted interventions may be superior to universal prevention trials, as modest effect sizes will limit statistical power.
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Grants
- 212557/Z/18/Z Wellcome Trust (Wellcome)
- MR/P014054/1 RCUK | Medical Research Council (MRC)
- MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4 RCUK | Medical Research Council (MRC)
- MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4 RCUK | Medical Research Council (MRC)
- C18281/A29019 Cancer Research UK (CRUK)
- MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4 RCUK | MRC | Medical Research Foundation
- MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4 RCUK | MRC | Medical Research Foundation
- NIHR202411 DH | National Institute for Health Research (NIHR)
- NIHR Bristol Biomedical Research Centre
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Affiliation(s)
- R Carnegie
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - M C Borges
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - H J Jones
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - J Zheng
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - P Haycock
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - J Evans
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - R M Martin
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
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3
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Furrer RA, Barlevy D, Pereira S, Carmi S, Lencz T, Lázaro-Muñoz G. Public Attitudes, Interests, and Concerns Regarding Polygenic Embryo Screening. JAMA Netw Open 2024; 7:e2410832. [PMID: 38743425 PMCID: PMC11094562 DOI: 10.1001/jamanetworkopen.2024.10832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 03/11/2024] [Indexed: 05/16/2024] Open
Abstract
Importance Polygenic embryo screening (PES) is a novel technology that estimates the likelihood of developing future conditions (eg, diabetes or depression) and traits (eg, height or cognitive ability) in human embryos, with the goal of selecting which embryos to use. Given its commercial availability and concerns raised by researchers, clinicians, bioethicists, and professional organizations, it is essential to inform key stakeholders and relevant policymakers about the public's perspectives on this technology. Objective To survey US adults to examine general attitudes, interests, and concerns regarding PES use. Design, Setting, and Participants For this survey study, data were collected from 1 stratified sample and 1 nonprobability sample (samples 1 and 2, respectively) between March and July 2023. The surveys measured approval, interest, and concerns regarding various applications of PES. In the second sample, presentation of a list of potential concerns was randomized (presented at survey onset vs survey end). The survey was designed using Qualtrics and distributed to participants through Prolific, an online sampling firm. Sample 1 was nationally representative with respect to gender, age, and race and ethnicity; sample 2 was recruited without specific demographic criteria. Analyses were conducted between March 2023 and February 2024. Main Outcomes and Measures Participants reported their approval, interest, and concerns regarding various applications of PES and outcomes screened (eg, traits and conditions). Statistical analysis was conducted using independent samples t tests and repeated-measures analyses of variance. Results Of the 1435 respondents in sample 1, demographic data were available for 1427 (mean [SD] age, 45.8 [16.0] years; 724 women [50.7%]). Among these 1427 sample 1 respondents, 1027 (72.0%) expressed approval for PES and 1169 (81.9%) expressed some interest in using PES if already undergoing in vitro fertilization (IVF). Approval among these respondents for using PES for embryo selection was notably high for physical health conditions (1109 [77.7%]) and psychiatric health conditions (1028 [72.0%]). In contrast, there was minority approval for embryo selection based on PES for behavioral traits (514 [36.0%]) and physical traits (432 [30.3%]). Nevertheless, concerns about PES leading to false expectations and promoting eugenic practices were pronounced, with 787 of 1422 (55.3%) and 780 of 1423 (54.8%) respondents finding them very to extremely concerning, respectively. Sample 2 included 192 respondents (mean [SD] age 37.7 [12.2] years; 110 men [57.3%]). These respondents were presented concerns at survey onset (n = 95) vs survey end (n = 97), which was associated with less approval (28-percentage point decrease) and more uncertainty (24 percentage-point increase) but with only slightly higher disapproval (4 percentage-point increase). Conclusions and Relevance These findings suggest that it is critical for health care professionals and medical societies to consider and understand the perspectives of diverse stakeholders (eg, patients undergoing IVF, clinicians, and the general public), given the absence of regulation and the recent commercial availability of PES.
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Affiliation(s)
- Rémy A. Furrer
- Center for Bioethics, Harvard Medical School, Boston, Massachusetts
| | - Dorit Barlevy
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas
| | - Stacey Pereira
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Todd Lencz
- Institute of Behavioral Science, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Departments of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York
- Division of Research, Department of Psychiatry, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, New York
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, Massachusetts
- Department of Psychiatry, Massachusetts General Hospital, Boston
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4
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Lewis P, Gottlieb JF, Morfeld P, Hellmich M, Erren TC. Perinatal photoperiod associations with bipolar disorder and depression: A systematic literature review and cross-sectional analysis of the UK Biobank database. Psychiatry Res 2024; 335:115878. [PMID: 38581863 DOI: 10.1016/j.psychres.2024.115878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/07/2024] [Accepted: 03/24/2024] [Indexed: 04/08/2024]
Abstract
Season-of-birth associations with psychiatric disorders point to environmental (co-)aetiological factors such as natural photoperiod that, if clarified, may allow interventions toward prevention. We systematically reviewed the literature concerning season-of-birth and bipolar disorder and depression and explored associations between the perinatal natural photoperiod and these outcomes in a cross-sectional analysis of the UK Biobank database. We used mean daily photoperiod and relative photoperiod range (relative to the mean) in the 3rd trimester and, separately, in the first 3 months post birth as metrics. From review, increased risk of depression with late spring birth is compatible with increased odds of probable single episode-, probable recurrent-, and diagnosed depression (OR 2.85 95 %CI 1.6-5.08, OR 2.20 95 %CI 1.57-3.1, and OR 1.48 95 %CI 1.11-1.97, respectively) with increasing 3rd trimester relative photoperiod range for participants who experienced relatively non-extreme daily photoperiods. Risk of bipolar disorder with winter-spring birth contrasted with no consistent patterns of perinatal photoperiod metric associations with bipolar disorder in the UK Biobank. As natural photoperiod varies by both time-of-year and latitude, perinatal natural photoperiods (and a hypothesized mechanism of action via the circadian timing system and/or serotonergic circuitry associated with the dorsal raphe nucleus) may reconcile inconsistencies in season-of-birth associations. Further studies are warranted.
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Affiliation(s)
- Philip Lewis
- Institute and Policlinic for Occupational Medicie, Environmental Medicine, and Prevention Research, Medical Faculty and University Hospital of Cologne, University of Cologne, Cologne, Germany.
| | - John F Gottlieb
- Feinberg School of Medicine, Northwestern University, Chicago, IL USA
| | - Peter Morfeld
- Institute and Policlinic for Occupational Medicie, Environmental Medicine, and Prevention Research, Medical Faculty and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Martin Hellmich
- Institute of Medical Statistics and Computational Biology, Medical Faculty and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Thomas C Erren
- Institute and Policlinic for Occupational Medicie, Environmental Medicine, and Prevention Research, Medical Faculty and University Hospital of Cologne, University of Cologne, Cologne, Germany
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5
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Pisanu C, Congiu D, Meloni A, Paribello P, Patrinos GP, Severino G, Ardau R, Chillotti C, Manchia M, Squassina A. Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets. Neuropsychopharmacology 2024; 49:1033-1041. [PMID: 38402365 DOI: 10.1038/s41386-024-01822-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/17/2024] [Accepted: 02/04/2024] [Indexed: 02/26/2024]
Abstract
Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.
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Affiliation(s)
- Claudia Pisanu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
| | - Donatella Congiu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Anna Meloni
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Pasquale Paribello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - George P Patrinos
- Laboratory of Pharmacogenomics and Individualized Therapy, School of Health Sciences, Department of Pharmacy, University of Patras, Patras, Greece
- College of Medicine and Health Sciences, Department of Genetics and Genomics, United Arab Emirates University, Al‑Ain, Abu Dhabi, UAE
- Zayed Center for Health Sciences, United Arab Emirates University, Al‑Ain, Abu Dhabi, UAE
| | - Giovanni Severino
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Raffaella Ardau
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Caterina Chillotti
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, NS, Canada
| | - Alessio Squassina
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
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6
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Honk L, Stenfors CUD, Goldberg SB, Hendricks PS, Osika W, Dourron HM, Lebedev A, Petrovic P, Simonsson O. Longitudinal associations between psychedelic use and psychotic symptoms in the United States and the United Kingdom. J Affect Disord 2024; 351:194-201. [PMID: 38280572 PMCID: PMC10922895 DOI: 10.1016/j.jad.2024.01.197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 01/17/2024] [Accepted: 01/21/2024] [Indexed: 01/29/2024]
Abstract
It has long been speculated that psychedelic use could provoke the onset of psychosis, but there is little evidence to support this conjecture. Using a longitudinal research design with samples representative of the US and UK adult populations with regard to sex, age, and ethnicity (n = 9732), we investigated associations between psychedelic use and change in the number of psychotic symptoms during the two-month study period. In covariate-adjusted regression models, psychedelic use during the study period was not associated with a change in the number of psychotic symptoms unless it interacted with a personal or family history of bipolar disorder, in which case the number of symptoms increased, or with a personal (but not family) history of psychotic disorders, in which case the number of symptoms decreased. Taken together, these findings indicate that psychedelic use may affect psychotic symptoms in individuals with a personal or family history of certain disorders characterized by psychotic symptomatology.
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Affiliation(s)
- Ludwig Honk
- Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden.
| | | | - Simon B Goldberg
- Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | - Peter S Hendricks
- Department of Psychiatry and Behavioral Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Walter Osika
- Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Haley Maria Dourron
- Department of Psychiatry and Behavioral Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Alexander Lebedev
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Predrag Petrovic
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Otto Simonsson
- Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden; Department of Sociology, University of Oxford, Oxford, United Kingdom
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7
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Thiel K, Lemke H, Winter A, Flinkenflügel K, Waltemate L, Bonnekoh L, Grotegerd D, Dohm K, Hahn T, Förster K, Kanske P, Repple J, Opel N, Redlich R, David F, Forstner AJ, Stein F, Brosch K, Thomas-Odenthal F, Usemann P, Teutenberg L, Straube B, Alexander N, Jamalabadi H, Jansen A, Witt SH, Andlauer TFM, Pfennig A, Bauer M, Nenadić I, Kircher T, Meinert S, Dannlowski U. White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls - exploring associations with disease course and polygenic risk. Neuropsychopharmacology 2024; 49:814-823. [PMID: 38332015 PMCID: PMC10948847 DOI: 10.1038/s41386-024-01812-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/28/2023] [Accepted: 01/21/2024] [Indexed: 02/10/2024]
Abstract
Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.
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Affiliation(s)
- Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Translational Psychotherapy, Institute of Psychology, University of Göttingen, Göttingen, Germany
| | - Linda Bonnekoh
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Förster
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
- German Center for Mental Health (DZPG), Halle-Jena-Magdeburg, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- German Center for Mental Health (DZPG), Halle-Jena-Magdeburg, Germany
- Department of Psychology, University of Halle, Halle, Germany
- Center for Intervention and Research on adaptive and maladaptive brain circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Halle, Germany
| | - Friederike David
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Stephanie H Witt
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, TU Dresden University of Technology, Dresden, Germany
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, TU Dresden University of Technology, Dresden, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute of Translational Neuroscience, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
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8
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Rice RC, Gil DV, Baratta AM, Frawley RR, Hill SY, Farris SP, Homanics GE. Inter- and transgenerational heritability of preconception chronic stress or alcohol exposure: Translational outcomes in brain and behavior. Neurobiol Stress 2024; 29:100603. [PMID: 38234394 PMCID: PMC10792982 DOI: 10.1016/j.ynstr.2023.100603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/18/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024] Open
Abstract
Chronic stress and alcohol (ethanol) use are highly interrelated and can change an individual's behavior through molecular adaptations that do not change the DNA sequence, but instead change gene expression. A recent wealth of research has found that these nongenomic changes can be transmitted across generations, which could partially account for the "missing heritability" observed in genome-wide association studies of alcohol use disorder and other stress-related neuropsychiatric disorders. In this review, we summarize the molecular and behavioral outcomes of nongenomic inheritance of chronic stress and ethanol exposure and the germline mechanisms that could give rise to this heritability. In doing so, we outline the need for further research to: (1) Investigate individual germline mechanisms of paternal, maternal, and biparental nongenomic chronic stress- and ethanol-related inheritance; (2) Synthesize and dissect cross-generational chronic stress and ethanol exposure; (3) Determine cross-generational molecular outcomes of preconception ethanol exposure that contribute to alcohol-related disease risk, using cancer as an example. A detailed understanding of the cross-generational nongenomic effects of stress and/or ethanol will yield novel insight into the impact of ancestral perturbations on disease risk across generations and uncover actionable targets to improve human health.
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Affiliation(s)
- Rachel C. Rice
- Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniela V. Gil
- Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA, USA
| | - Annalisa M. Baratta
- Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA, USA
| | - Remy R. Frawley
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shirley Y. Hill
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sean P. Farris
- Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA, USA
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gregg E. Homanics
- Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA, USA
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, USA
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9
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Nuñez NA, Coombes BJ, Beaupre LM, Ozerdem A, Resendez MG, Romo-Nava F, Bond DJ, Veldic M, Singh B, Moore KM, Betcher HK, Kung S, Prieto ML, Fuentes M, Ercis M, Miola A, Sanchez Ruiz JA, Jenkins G, Batzler A, Leung JG, Cuellar-Barboza A, Tye SJ, McElroy SL, Biernacka JM, Frye MA. Pharmacogenomic overlap between antidepressant treatment response in major depression & antidepressant associated treatment emergent mania in bipolar disorder. Transl Psychiatry 2024; 14:93. [PMID: 38351009 PMCID: PMC10864308 DOI: 10.1038/s41398-024-02798-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 01/08/2024] [Accepted: 01/17/2024] [Indexed: 02/16/2024] Open
Abstract
There is increasing interest in individualizing treatment selection for more than 25 regulatory approved treatments for major depressive disorder (MDD). Despite an inconclusive efficacy evidence base, antidepressants (ADs) are prescribed for the depressive phase of bipolar disorder (BD) with oftentimes, an inadequate treatment response and or clinical concern for mood destabilization. This study explored the relationship between antidepressant response in MDD and antidepressant-associated treatment emergent mania (TEM) in BD. We conducted a genome-wide association study (GWAS) and polygenic score analysis of TEM and tested its association in a subset of BD-type I patients treated with SSRIs or SNRIs. Our results did not identify any genome-wide significant variants although, we found that a higher polygenic score (PGS) for antidepressant response in MDD was associated with higher odds of TEM in BD. Future studies with larger transdiagnostic depressed cohorts treated with antidepressants are encouraged to identify a neurobiological mechanism associated with a spectrum of depression improvement from response to emergent mania.
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Affiliation(s)
- Nicolas A Nuñez
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Brandon J Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Aysegul Ozerdem
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Manuel Gardea Resendez
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, México
| | | | - David J Bond
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Marin Veldic
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Balwinder Singh
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Katherine M Moore
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Hannah K Betcher
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Simon Kung
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Miguel L Prieto
- Department of Psychiatry, Faculty of Medicine, Universidad de Los Andes, Santiago, Chile
| | - Manuel Fuentes
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Mete Ercis
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Alessandro Miola
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Gregory Jenkins
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Anthony Batzler
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Susannah J Tye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Queensland Brain Institute, The University of Queensland, St. Lucia, QLD, Australia
| | - Susan L McElroy
- Lindner Center of HOPE/University of Cincinnati, Cincinnati, OH, USA
| | - Joanna M Biernacka
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Mark A Frye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
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10
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Benstock SE, Weaver K, Hettema J, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. RESEARCH SQUARE 2024:rs.3.rs-3858178. [PMID: 38352402 PMCID: PMC10862954 DOI: 10.21203/rs.3.rs-3858178/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Genome-wide association studies (GWAS) are underpowered due to small effect sizes of single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the most statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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11
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Panagiotaropoulou G, Hellberg KLG, Coleman JRI, Seok D, Kalman J, Mitchell PB, Schofield PR, Forstner AJ, Bauer M, Scott LJ, Pato CN, Pato MT, Li QS, Kirov G, Landén M, Jonsson L, Müller-Myhsok B, Smoller JW, Binder EB, Brückl TM, Czamara D, der Auwera SV, Grabe HJ, Homuth G, Schmidt CO, Potash JB, DePaulo RJ, Goes FS, MacKinnon DF, Mondimore FM, Weissman MM, Shi J, Frye MA, Biernacka JM, Reif A, Witt SH, Kahn RR, Boks MM, Owen MJ, Gordon-Smith K, Mitchell BL, Martin NG, Medland SE, Jones L, Knowles JA, Levinson DF, O'Donovan MC, Lewis CM, Breen G, Werge T, Schork AJ, Ophoff R, Ripke S, Loohuis LO. Identifying genetic differences between bipolar disorder and major depression through multiple GWAS. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.29.24301816. [PMID: 38410442 PMCID: PMC10896417 DOI: 10.1101/2024.01.29.24301816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Background Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD). Aims Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis. Methods Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses. Results While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD. Conclusions We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.
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Affiliation(s)
| | - Kajsa-Lotta Georgii Hellberg
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
| | - Darsol Seok
- Department of Psychiatry, University of California, Los Angeles, CA, USA
| | - Janos Kalman
- Institute for Psychiatric Phenomics and Genomics, Ludwig Maximilian University, Munich, Germany
| | - Philip B Mitchell
- Discipline of Psychiatry and Mental Health, School of Medicine and Health, University of New South Wales, Sydney, Australia
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, University of New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, University of New South Wales, Australia
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Dresden, Germany
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Carlos N Pato
- Department of Psychiatry, Rutgers University, Rutgers Health, Piscataway, NJ, USA
| | - Michele T Pato
- Department of Psychiatry, Rutgers University, Rutgers Health, Piscataway, NJ, USA
| | - Qingqin S Li
- Janssen Research and Development, Neuroscience, Titusville, NJ, USA
| | - George Kirov
- Cardiff University, Division of Psychological Medicine and Clinical Neuroscience, Cardiff, UK
| | - Mikael Landén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lina Jonsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | | | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Elisabeth B Binder
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich
| | - Tanja M Brückl
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich
| | - Darina Czamara
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute of Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Carsten O Schmidt
- Institute for Community Medicine, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - James B Potash
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Raymond J DePaulo
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dean F MacKinnon
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Francis M Mondimore
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Myrna M Weissman
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, US
- Division of Translational Epidemiology & Mental Health Equity, New York State Psychiatric Institute, New York, NY, US
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Joanna M Biernacka
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Andreas Reif
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Frankfurt am Main, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - René R Kahn
- Department of Psychiatry and Behavioral Health System, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Marco M Boks
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | | | - Brittany L Mitchell
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah E Medland
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Lisa Jones
- Psychological Medicine, University of Worcester, Worcester, UK
| | - James A Knowles
- Department of Genetics, Rutgers University, Piscataway, NJ, US
| | - Douglas F Levinson
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, US
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Roel Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- German Center for Mental Health (DZPG), Site Berlin-Potsdam, Germany
| | - Loes Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Genetics and Genomics, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
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12
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Lin F, Jun Li, Ziqi Wang, Zhang T, Lu T, Jiang M, Yang K, Jia M, Zhang D, Wang L. Replication of previous autism-GWAS hits suggests the association between NAA1, SORCS3, and GSDME and autism in the Han Chinese population. Heliyon 2024; 10:e23677. [PMID: 38234914 PMCID: PMC10792458 DOI: 10.1016/j.heliyon.2023.e23677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 11/25/2023] [Accepted: 12/09/2023] [Indexed: 01/19/2024] Open
Abstract
Background Autism is a severe neurodevelopmental disorder characterized by social interaction deficits, impairments in communication, and restricted and repetitive stereotyped behavior and activities. Family and twin studies suggested an essential role of genetic factors in the etiology of autism spectrum disorder (ASD). Also, other studies found SORCS3 and GSDME (DFNA5) might be involved in brain development and susceptible to ASD. Methods In this study, 17 genome-wide significant SNPs reported in previous ASD genome-wide association studies (GWAS) and 7 SNPs in strong linkage disequilibrium with known ASD GWAS hits were selected to investigate the association between these SNPs and autism in the Han Chinese population. Then, 10 tagSNPs in SORCS3 and 11 tagSNPs in GSDME were selected to analyze the association between these SNPs and autism. The selected 24 SNPs and tagSNPs were genotyped using the Agena MassARRAY SNP genotyping assay in 757 Han Chinese autism trios. Results Rs1484144 in NAA11 was significantly associated with autism; significance remained after the Bonferroni correction (P < 0.0022). Also, rs79879286, rs12154597, and rs12540919 near GSDME, as well as rs9787523 and rs3750261 in SORCS3, were nominally associated with autism. Conclusion Our study suggests that rs1484144 in NAA11 is a significant SNP for autism in the Han Chinese population, while SORCS3 and GSDME might be the susceptibility genes for autism in this population.
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Affiliation(s)
- Fen Lin
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Jun Li
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Ziqi Wang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Tian Zhang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Tianlan Lu
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Miaomiao Jiang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Kang Yang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Meixiang Jia
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Dai Zhang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, Institute for Brain Research and Rehabilitation (IBRR), South China Normal University, Guangzhou, China
| | - Lifang Wang
- National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
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13
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Cardoner N, Andero R, Cano M, Marin-Blasco I, Porta-Casteràs D, Serra-Blasco M, Via E, Vicent-Gil M, Portella MJ. Impact of Stress on Brain Morphology: Insights into Structural Biomarkers of Stress-related Disorders. Curr Neuropharmacol 2024; 22:935-962. [PMID: 37403395 PMCID: PMC10845094 DOI: 10.2174/1570159x21666230703091435] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/04/2023] [Accepted: 01/23/2023] [Indexed: 07/06/2023] Open
Abstract
Exposure to acute and chronic stress has a broad range of structural effects on the brain. The brain areas commonly targeted in the stress response models include the hippocampus, the amygdala, and the prefrontal cortex. Studies in patients suffering from the so-called stress-related disorders -embracing post-traumatic stress, major depressive and anxiety disorders- have fairly replicated animal models of stress response -particularly the neuroendocrine and the inflammatory models- by finding alterations in different brain areas, even in the early neurodevelopment. Therefore, this narrative review aims to provide an overview of structural neuroimaging findings and to discuss how these studies have contributed to our knowledge of variability in response to stress and the ulterior development of stress-related disorders. There are a gross number of studies available but neuroimaging research of stress-related disorders as a single category is still in its infancy. Although the available studies point at particular brain circuitries involved in stress and emotion regulation, the pathophysiology of these abnormalities -involving genetics, epigenetics and molecular pathways-, their relation to intraindividual stress responses -including personality characteristics, self-perception of stress conditions…-, and their potential involvement as biomarkers in diagnosis, treatment prescription and prognosis are discussed.
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Affiliation(s)
- Narcís Cardoner
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Raül Andero
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- Departament de Psicobiologia i de Metodologia de les Ciències de la Salut, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Marta Cano
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Ignacio Marin-Blasco
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
| | - Daniel Porta-Casteràs
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Maria Serra-Blasco
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Programa eHealth ICOnnecta't, Institut Català d'Oncologia, Barcelona, Spain
| | - Esther Via
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Muriel Vicent-Gil
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Maria J. Portella
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
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14
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Rabelo-da-Ponte FD, Marchionatti LE, Watts D, Roza TH, Amoretti S, Barros FC, Wehrmeister FC, Gonçalves H, B Menezes AM, Kunz M, Kapczinski F, Passos IC. Premorbid intelligence quotient and school failure as risk markers for bipolar disorder and major depressive disorder. J Psychiatr Res 2024; 169:160-165. [PMID: 38039690 DOI: 10.1016/j.jpsychires.2023.11.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 08/16/2023] [Accepted: 11/15/2023] [Indexed: 12/03/2023]
Abstract
Mood disorders significantly impact global health, with MDD ranking as the second leading cause of disability in the United States and BD ranking 18th. Despite their prevalence and impact, the relationship between premorbid intelligence and the subsequent development of BD and MDD remains inconclusive. This study investigates the potential of premorbid Intelligence Quotient (IQ) and school failure frequency as risk factors for Bipolar Disorder (BD) and Major Depressive Disorder (MDD) in a birth cohort setting. We analyze data from the Pelotas population-based birth cohort study, comprising 3580 participants aged 22, who had no prior mood disorder diagnoses. Utilizing regression models and accounting for potential confounders, we assess the impact of IQ and school failure, measured at age 18, on the emergence of BD and MDD diagnoses at age 22, using individuals without mood disorders as comparators. Results reveal that lower IQ (below 70) at 18 is associated with an increased risk of BD (Adjusted Odds Ratio [AOR] 1.75, 95%CI: 1.00-3.09, p < 0.05), while higher IQ (above 120) is linked to MDD (AOR 2.16, 95%CI: 1.24-3.75, p < 0.001). Moreover, an elevated number of school failures is associated with increased BD risk (AOR 1.23, 95%CI: 1.11-1.41, p < 0.001), particularly for BD type 1 (AOR 1.36, 95% CI: 1.17-1.58, p < 0.001). These findings offer insights into the distinct premorbid intellectual characteristics of BD and MDD and contribute to a deeper understanding of their developmental trajectories, potentially informing the development of risk assessment tools for mood disorders.
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Affiliation(s)
- Francisco Diego Rabelo-da-Ponte
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
| | - Lauro Estivalete Marchionatti
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Experimental (CPE) and Centro de Pesquisa Clínica (CPC), Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil; Instituto Nacional de Ciência e Tecnologia Translacional em Medicina (INCT-TM), Porto Alegre, RS, Brazil; Universidade Federal do Rio Grande do Sul, School of Medicine, Graduate Program in Psychiatry and Behavioral Sciences, Department of Psychiatry, Porto Alegre, RS, Brazil.
| | - Devon Watts
- Department of Psychiatry, Harvard Medical School, USA; Center for Precision Psychiatry, Massachusetts General Hospital, USA.
| | - Thiago Henrique Roza
- Department of Psychiatry, Universidade Federal do Paraná (UFPR), Curitiba, Brazil.
| | - Silvia Amoretti
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, Biomedical Network Research Centre on Mental Health (CIBERSAM), 170 Villarroel st, 12-0, 08036, Barcelona, Catalonia, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addictions, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, CIBERSAM, Barcelona, Catalonia, Spain.
| | - Fernando C Barros
- Postgraduate Program in Epidemiology, Universidade Federal de Pelotas, Pelotas, Brazil.
| | | | - Helen Gonçalves
- Postgraduate Program in Epidemiology, Universidade Federal de Pelotas, Pelotas, Brazil.
| | - Ana Maria B Menezes
- Postgraduate Program in Epidemiology, Universidade Federal de Pelotas, Pelotas, Brazil.
| | - Maurício Kunz
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Experimental (CPE) and Centro de Pesquisa Clínica (CPC), Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil; Instituto Nacional de Ciência e Tecnologia Translacional em Medicina (INCT-TM), Porto Alegre, RS, Brazil; Universidade Federal do Rio Grande do Sul, School of Medicine, Graduate Program in Psychiatry and Behavioral Sciences, Department of Psychiatry, Porto Alegre, RS, Brazil
| | - Flávio Kapczinski
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Experimental (CPE) and Centro de Pesquisa Clínica (CPC), Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil; Instituto Nacional de Ciência e Tecnologia Translacional em Medicina (INCT-TM), Porto Alegre, RS, Brazil; Universidade Federal do Rio Grande do Sul, School of Medicine, Graduate Program in Psychiatry and Behavioral Sciences, Department of Psychiatry, Porto Alegre, RS, Brazil; Neuroscience Graduate Program, McMaster University, Hamilton, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
| | - Ives Cavalcante Passos
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Experimental (CPE) and Centro de Pesquisa Clínica (CPC), Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brazil; Instituto Nacional de Ciência e Tecnologia Translacional em Medicina (INCT-TM), Porto Alegre, RS, Brazil; Universidade Federal do Rio Grande do Sul, School of Medicine, Graduate Program in Psychiatry and Behavioral Sciences, Department of Psychiatry, Porto Alegre, RS, Brazil.
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15
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Ramírez-Martín A, Sirignano L, Streit F, Foo JC, Forstner AJ, Frank J, Nöthen MM, Strohmaier J, Witt SH, Mayoral-Cleries F, Moreno-Küstner B, Rietschel M, Guzmán-Parra J. Impulsivity, decision-making, and risk behavior in bipolar disorder and major depression from bipolar multiplex families. Brain Behav 2023; 14:e3337. [PMID: 38111335 PMCID: PMC10897498 DOI: 10.1002/brb3.3337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 12/20/2023] Open
Abstract
OBJECTIVES Bipolar disorder (BD) and major depressive disorder (MDD) are characterized by specific alterations of mood. In both disorders, alterations in cognitive domains such as impulsivity, decision-making, and risk-taking have been reported. Identification of similarities and differences of these domains in BD and MDD could give further insight into their etiology. The present study assessed impulsivity, decision-making, and risk-taking behavior in BD and MDD patients from bipolar multiplex families. METHODS Eighty-two participants (BD type I, n = 25; MDD, n = 26; healthy relatives (HR), n = 17; and healthy controls (HC), n = 14) underwent diagnostic interviews and selected tests of a cognitive battery assessing neurocognitive performance across multiple subdomains including impulsivity (response inhibition and delay aversion), decision-making, and risk behavior. Generalized estimating equations (GEEs) were used to analyze whether the groups differed in the respective cognitive domains. RESULTS Participants with BD and MDD showed higher impulsivity levels compared to HC; this difference was more pronounced in BD participants. BD participants also showed lower inhibitory control than MDD participants. Overall, suboptimal decision-making was associated with both mood disorders (BD and MDD). In risk-taking behavior, no significant impairment was found in any group. LIMITATIONS As sample size was limited, it is possible that differences between BD and MDD may have escaped detection due to lack of statistical power. CONCLUSIONS Our findings show that alterations of cognitive domains-while present in both disorders-are differently associated with BD and MDD. This underscores the importance of assessing such domains in addition to mere diagnosis of mood disorders.
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Affiliation(s)
- Almudena Ramírez-Martín
- Department of Mental Health, University General Hospital of Malaga, Biomedical Research Institute of Malaga (IBIMA), Malaga, Spain
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Jerome C Foo
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Andreas J Forstner
- School of Medicine & University Hospital Bonn, Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Mannheim, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Markus M Nöthen
- School of Medicine & University Hospital Bonn, Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Jana Strohmaier
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Fermin Mayoral-Cleries
- Department of Mental Health, University General Hospital of Malaga, Biomedical Research Institute of Malaga (IBIMA), Malaga, Spain
| | - Berta Moreno-Küstner
- Department of Personality, Assessment and Psychological Treatment, University of Málaga, Málaga, Spain
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Jose Guzmán-Parra
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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16
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Caiola HO, Wu Q, Soni S, Wang XF, Monahan K, Pang ZP, Wagner GC, Zhang H. Neuronal connectivity, behavioral, and transcriptional alterations associated with the loss of MARK2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.05.569759. [PMID: 38105965 PMCID: PMC10723285 DOI: 10.1101/2023.12.05.569759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Neuronal connectivity is essential for adaptive brain responses and can be modulated by dendritic spine plasticity and the intrinsic excitability of individual neurons. Dysregulation of these processes can lead to aberrant neuronal activity, which has been associated with numerous neurological disorders including autism, epilepsy, and Alzheimer's disease. Nonetheless, the molecular mechanisms underlying aberrant neuronal connectivity remains unclear. We previously found that the serine/threonine kinase Microtubule Affinity Regulating Kinase 2 (MARK2), also known as Partitioning Defective 1b (Par1b), is important for the formation of dendritic spines in vitro. However, despite its genetic association with several neurological disorders, the in vivo impact of MARK2 on neuronal connectivity and cognitive functions remains unclear. Here, we demonstrate that loss of MARK2 in vivo results in changes to dendritic spine morphology, which in turn leads to a decrease in excitatory synaptic transmission. Additionally, loss of MARK2 produces substantial impairments in learning and memory, anxiety, and social behavior. Notably, MARK2 deficiency results in heightened seizure susceptibility. Consistent with this observation, RNAseq analysis reveals transcriptional changes in genes regulating synaptic transmission and ion homeostasis. These findings underscore the in vivo role of MARK2 in governing synaptic connectivity, cognitive functions, and seizure susceptibility.
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17
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Thomaidis GV, Papadimitriou K, Michos S, Chartampilas E, Tsamardinos I. A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning. IBRO Neurosci Rep 2023; 15:77-89. [PMID: 38025660 PMCID: PMC10668096 DOI: 10.1016/j.ibneur.2023.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/19/2023] [Accepted: 06/29/2023] [Indexed: 12/01/2023] Open
Abstract
Background Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully automated machine learning algorithms can achieve extremely high classification scores and disease-related predictive biosignature identification, in short time frames and scaled down to small datasets. Method A fully automated machine learning platform, based on the most suitable algorithm selection and relevant set of hyper-parameter values, was applied on a preprocessed transcriptomics dataset, in order to produce a model for biosignature selection and to classify subjects into groups of patients and controls. The parent GEO datasets were originally produced from the cerebellar and parietal lobe tissue of deceased bipolar patients and healthy controls, using Affymetrix Human Gene 1.0 ST Array. Results Patients and controls were classified into two separate groups, with no close-to-the-boundary cases, and this classification was based on the cerebellar transcriptomic biosignature of 25 features (genes), with Area Under Curve 0.929 and Average Precision 0.955. The biosignature includes both genes connected before to bipolar disorder, depression, psychosis or epilepsy, as well as genes not linked before with any psychiatric disease. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed participation of 4 identified features in 6 pathways which have also been associated with bipolar disorder. Conclusion Automated machine learning (AutoML) managed to identify accurately 25 genes that can jointly - in a multivariate-fashion - separate bipolar patients from healthy controls with high predictive power. The discovered features lead to new biological insights. Machine Learning (ML) analysis considers the features in combination (in contrast to standard differential expression analysis), removing both irrelevant as well as redundant markers, and thus, focusing to biological interpretation.
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Affiliation(s)
- Georgios V. Thomaidis
- Greek National Health System, Psychiatric Department, Katerini General Hospital, Katerini, Greece
| | - Konstantinos Papadimitriou
- Greek National Health System, G. Papanikolaou General Hospital, Organizational Unit - Psychiatric Hospital of Thessaloniki, Thessaloniki, Greece
| | | | - Evangelos Chartampilas
- Laboratory of Radiology, AHEPA General Hospital, University of Thessaloniki, Thessaloniki, Greece
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18
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Williams CM, Poore H, Tanksley PT, Kweon H, Courchesne-Krak NS, Londono-Correa D, Mallard TT, Barr P, Koellinger PD, Waldman ID, Sanchez-Roige S, Harden KP, Palmer AA, Dick DM, Karlsson Linnér R. Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics. Behav Genet 2023; 53:404-415. [PMID: 37713023 PMCID: PMC10584908 DOI: 10.1007/s10519-023-10152-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 08/15/2023] [Indexed: 09/16/2023]
Abstract
Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, although down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci; the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses were found robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who generate and share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.
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Affiliation(s)
- Camille M Williams
- Department of Psychology, University of Texas at Austin, Austin, TX, USA.
- Population Research Center, University of Texas at Austin, Austin, TX, USA.
| | - Holly Poore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Peter T Tanksley
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | | | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Peter Barr
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Philipp D Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
| | - K Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
- Rutgers Addiction Research Centre, Brain Health Institute, Rutgers University, Piscataway, NJ, USA.
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Davyson E, Shen X, Gadd DA, Bernabeu E, Hillary RF, McCartney DL, Adams M, Marioni R, McIntosh AM. Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids. Biol Psychiatry 2023; 94:630-639. [PMID: 36764567 PMCID: PMC10804990 DOI: 10.1016/j.biopsych.2023.01.027] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 01/31/2023] [Accepted: 01/31/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Metabolic differences have been reported between individuals with and without major depressive disorder (MDD), but their consistency and causal relevance have been unclear. METHODS We conducted a metabolome-wide association study of MDD with 249 metabolomic measures available in the UK Biobank (n = 29,757). We then applied two-sample bidirectional Mendelian randomization and colocalization analysis to identify potentially causal relationships between each metabolite and MDD. RESULTS A total of 191 metabolites tested were significantly associated with MDD (false discovery rate-corrected p < .05), which decreased to 129 after adjustment for likely confounders. Lower abundance of omega-3 fatty acid measures and a higher omega-6 to omega-3 ratio showed potentially causal effects on liability to MDD. There was no evidence of a causal effect of MDD on metabolite levels. Furthermore, genetic signals associated with docosahexaenoic acid colocalized with loci associated with MDD within the fatty acid desaturase gene cluster. Post hoc Mendelian randomization of gene-transcript abundance within the fatty acid desaturase cluster demonstrated a potentially causal association with MDD. In contrast, colocalization analysis did not suggest a single causal variant for both transcript abundance and MDD liability, but rather the likely existence of two variants in linkage disequilibrium with one another. CONCLUSIONS Our findings suggest that decreased docosahexaenoic acid and increased omega-6 to omega-3 fatty acids ratio may be causally related to MDD. These findings provide further support for the causal involvement of fatty acids in MDD.
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Affiliation(s)
- Eleanor Davyson
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom; Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Danni A Gadd
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Elena Bernabeu
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Robert F Hillary
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Daniel L McCartney
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Riccardo Marioni
- Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom; Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom.
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20
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Huber M, Reuter L, Weitgasser L, Pletzer B, Rösch S, Illg A. Hearing loss, depression, and cognition in younger and older adult CI candidates. Front Neurol 2023; 14:1272210. [PMID: 37900591 PMCID: PMC10613094 DOI: 10.3389/fneur.2023.1272210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 09/04/2023] [Indexed: 10/31/2023] Open
Abstract
Background and Aim Hearing loss in old age is associated with cognitive decline and with depression. Our study aimed to investigate the relationship between hearing loss, cognitive decline, and secondary depressive symptoms in a sample of younger and older cochlear implant candidates with profound to severe hearing loss. Methods This study is part of a larger cohort study designated to provide information on baseline data before CI. Sixty-one cochlear implant candidates with hearing loss from adulthood onwards (>18 years) were enrolled in this study. All had symmetrical sensorineural hearing loss in both ears (four-frequency hearing threshold difference of no more than 20 dB, PTA). Individuals with primary affective disorders, psychosis, below-average intelligence, poor German language skills, visual impairment, and a medical diagnosis with potential impact on cognition (e.g., neurodegenerative diseases,) were excluded. Four-frequency hearing thresholds (dB, PTA, better ear) were collected. Using the Abbreviated Profile of Hearing Aid Benefit, we assessed subjective hearing in noise. Clinical and subclinical depressive symptoms were assessed with the Beck Depression Inventory (BDI II). Cognitive status was assessed with a neurocognitive test battery. Results Our findings revealed a significant negative association between subjective hearing in noise (APHAB subscale "Background Noise") and BDII. However, we did not observe any link between hearing thresholds, depression, and cognition. Additionally, no differences emerged between younger (25-54 years) and older subjects (55-75 years). Unexpectedly, further unplanned analyses unveiled correlations between subjective hearing in quiet environments (APHAB) and cognitive performance [phonemic fluency (Regensburg Word Fluency), cognitive flexibility (TMTB), and nonverbal episodic memory (Nonverbal Learning Test), as well as subjective hearing of aversive/loud sounds (APHAB)], cognitive performance [semantic word fluency (RWT), and inhibition (Go/Nogo) and depression]. Duration of hearing loss and speech recognition at quiet (Freiburg Monosyllables) were not related to depression and cognitive performance. Conclusion Impact of hearing loss on mood and cognition appears to be independent, suggesting a relationship with distinct aspects of hearing loss. These results underscore the importance of considering not only conventional audiometric measures like hearing thresholds but also variables related to hearing abilities during verbal communication in everyday life, both in quiet and noisy settings.
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Affiliation(s)
- Maria Huber
- Department of Otorhinolaryngology, Head and Neck Surgery, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Lisa Reuter
- Clinic for Otorhinolaryngology, Medical University of Hannover, Hannover, Germany
| | - Lennart Weitgasser
- Department of Otorhinolaryngology, Head and Neck Surgery, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Belinda Pletzer
- Department of Psychology, Center for Neurocognitive Research, University of Salzburg, Salzburg, Austria
| | - Sebastian Rösch
- Department of Otorhinolaryngology, Head and Neck Surgery, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Angelika Illg
- Clinic for Otorhinolaryngology, Medical University of Hannover, Hannover, Germany
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21
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Roca-Umbert A, Garcia-Calleja J, Vogel-González M, Fierro-Villegas A, Ill-Raga G, Herrera-Fernández V, Bosnjak A, Muntané G, Gutiérrez E, Campelo F, Vicente R, Bosch E. Human genetic adaptation related to cellular zinc homeostasis. PLoS Genet 2023; 19:e1010950. [PMID: 37747921 PMCID: PMC10553801 DOI: 10.1371/journal.pgen.1010950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 10/05/2023] [Accepted: 08/31/2023] [Indexed: 09/27/2023] Open
Abstract
SLC30A9 encodes a ubiquitously zinc transporter (ZnT9) and has been consistently suggested as a candidate for positive selection in humans. However, no direct adaptive molecular phenotype has been demonstrated. Our results provide evidence for directional selection operating in two major complementary haplotypes in Africa and East Asia. These haplotypes are associated with differential gene expression but also differ in the Met50Val substitution (rs1047626) in ZnT9, which we show is found in homozygosis in the Denisovan genome and displays accompanying signatures suggestive of archaic introgression. Although we found no significant differences in systemic zinc content between individuals with different rs1047626 genotypes, we demonstrate that the expression of the derived isoform (ZnT9 50Val) in HEK293 cells shows a gain of function when compared with the ancestral (ZnT9 50Met) variant. Notably, the ZnT9 50Val variant was found associated with differences in zinc handling by the mitochondria and endoplasmic reticulum, with an impact on mitochondrial metabolism. Given the essential role of the mitochondria in skeletal muscle and since the derived allele at rs1047626 is known to be associated with greater susceptibility to several neuropsychiatric traits, we propose that adaptation to cold may have driven this selection event, while also impacting predisposition to neuropsychiatric disorders in modern humans.
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Affiliation(s)
- Ana Roca-Umbert
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Jorge Garcia-Calleja
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - Marina Vogel-González
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Alejandro Fierro-Villegas
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Ill-Raga
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Víctor Herrera-Fernández
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Anja Bosnjak
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Gerard Muntané
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Hospital Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, Reus, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Esteban Gutiérrez
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Felix Campelo
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Rubén Vicente
- Laboratory of Molecular Physiology, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
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Brancati GE, Nunes A, Scott K, O'Donovan C, Cervantes P, Grof P, Alda M. Differential characteristics of bipolar I and II disorders: a retrospective, cross-sectional evaluation of clinical features, illness course, and response to treatment. Int J Bipolar Disord 2023; 11:25. [PMID: 37452256 PMCID: PMC10349025 DOI: 10.1186/s40345-023-00304-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND The distinction between bipolar I and bipolar II disorder and its treatment implications have been a matter of ongoing debate. The aim of this study was to examine differences between patients with bipolar I and II disorders with particular emphasis on the early phases of the disorders. METHODS 808 subjects diagnosed with bipolar I (N = 587) or bipolar II disorder (N = 221) according to DSM-IV criteria were recruited between April 1994 and March 2022 from tertiary-level mood disorder clinics. Sociodemographic and clinical variables concerning psychiatric and medical comorbidities, family history, illness course, suicidal behavior, and response to treatment were compared between the bipolar disorder types. RESULTS Bipolar II disorder patients were more frequently women, older, married or widowed. Bipolar II disorder was associated with later "bipolar" presentation, higher age at first (hypo)mania and treatment, less frequent referral after a single episode, and more episodes before lithium treatment. A higher proportion of first-degree relatives of bipolar II patients were affected by major depression and anxiety disorders. The course of bipolar II disorder was typically characterized by depressive onset, early depressive episodes, multiple depressive recurrences, and depressive predominant polarity; less often by (hypo)mania or (hypo)mania-depression cycles at onset or during the early course. The lifetime clinical course was more frequently rated as chronic fluctuating than episodic. More patients with bipolar II disorder had a history of rapid cycling and/or high number of episodes. Mood stabilizers and antipsychotics were prescribed less frequently during the early course of bipolar II disorder, while antidepressants were more common. We found no differences in global functioning, lifetime suicide attempts, family history of suicide, age at onset of mood disorders and depressive episodes, and lithium response. CONCLUSIONS Differences between bipolar I and II disorders are not limited to the severity of (hypo)manic syndromes but include patterns of clinical course and family history. Caution in the use of potentially mood-destabilizing agents is warranted during the early course of bipolar II disorder.
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Affiliation(s)
- Giulio Emilio Brancati
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Abraham Nunes
- Department of Psychiatry, QEII Health Sciences Centre, Dalhousie University, 5909 Veterans' Memorial Lane, Abbie J. Lane Memorial Building (room 3088), Halifax, NS, B3H 2E2, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
| | - Katie Scott
- Department of Psychiatry, QEII Health Sciences Centre, Dalhousie University, 5909 Veterans' Memorial Lane, Abbie J. Lane Memorial Building (room 3088), Halifax, NS, B3H 2E2, Canada
| | - Claire O'Donovan
- Department of Psychiatry, QEII Health Sciences Centre, Dalhousie University, 5909 Veterans' Memorial Lane, Abbie J. Lane Memorial Building (room 3088), Halifax, NS, B3H 2E2, Canada
| | - Pablo Cervantes
- Department of Psychiatry, McGill University Health Centre, Montreal, QC, Canada
| | - Paul Grof
- Mood Disorders Center of Ottawa, Ottawa, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Martin Alda
- Department of Psychiatry, QEII Health Sciences Centre, Dalhousie University, 5909 Veterans' Memorial Lane, Abbie J. Lane Memorial Building (room 3088), Halifax, NS, B3H 2E2, Canada.
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23
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Alnsasra H, Khalil F, Kanneganti Perue R, Azab AN. Depression among Patients with an Implanted Left Ventricular Assist Device: Uncovering Pathophysiological Mechanisms and Implications for Patient Care. Int J Mol Sci 2023; 24:11270. [PMID: 37511030 PMCID: PMC10379142 DOI: 10.3390/ijms241411270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 06/29/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023] Open
Abstract
Depression is a common and devastating mental illness associated with increased morbidity and mortality, partially due to elevated rates of suicidal attempts and death. Select patients with end-stage heart failure on a waiting-list for a donor heart undergo left ventricular assist device (LVAD) implantation. The LVAD provides a circulatory flow of oxygenated blood to the body, mimicking heart functionality by operating on a mechanical technique. LVAD improves functional capacity and survivability among patients with end-stage heart failure. However, accumulating data suggests that LVAD recipients suffer from an increased incidence of depression and suicide attempts. There is scarce knowledge regarding the pathological mechanism and appropriate treatment approach for depressed LVAD patients. This article summarizes the current evidence on the association between LVAD implantation and occurrence of depression, suggesting possible pathological mechanisms underlying the device-associated depression and reviewing the current treatment strategies. The summarized data underscores the need for a rigorous pre-(LVAD)-implantation psychiatric evaluation, continued post-implantation mental health assessment, and administration of antidepressant treatment as necessary.
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Affiliation(s)
- Hilmi Alnsasra
- Cardiology Division, Soroka University Medical Center, Beer-Sheva 8410501, Israel
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
| | - Fouad Khalil
- Department of Internal Medicine, University of South Dakota, Sioux Falls, SD 57105, USA
| | - Radha Kanneganti Perue
- Department of Cardiovascular Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Abed N Azab
- Cardiology Division, Soroka University Medical Center, Beer-Sheva 8410501, Israel
- Department of Nursing, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
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24
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Koido K, Malmgren CI, Pojskic L, Almos PZ, Bergen SE, Borg I, Božina N, Coviello DA, Degenhardt F, Ganoci L, Jensen UB, Durand-Lennad L, Laurent-Levinson C, McQuillin A, Navickas A, Pace NP, Paneque M, Rietschel M, Grigoroiu-Serbanescu M, Soller MJ, Suvisaari J, Utkus A, Van Assche E, Vissouze L, Zuckerman S, Chaumette B, Tammimies K. Lack of guidelines and translational knowledge is hindering the implementation of psychiatric genetic counseling and testing within Europe - A multi-professional survey study. Eur J Med Genet 2023; 66:104805. [PMID: 37406854 DOI: 10.1016/j.ejmg.2023.104805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/25/2023] [Accepted: 06/23/2023] [Indexed: 07/07/2023]
Abstract
Genetic research has identified a large number of genetic variants, both rare and common, underlying neurodevelopmental disorders (NDD) and major psychiatric disorders. Currently, these findings are being translated into clinical practice. However, there is a lack of knowledge and guidelines for psychiatric genetic testing (PsychGT) and genetic counseling (PsychGC). The European Union-funded COST action EnGagE (CA17130) network was started to investigate the current implementation status of PsychGT and PsychGC across 35 participating European countries. Here, we present the results of a pan-European online survey in which we gathered the opinions, knowledge, and practices of a self-selected sample of professionals involved/interested in the field. We received answers from 181 respondents. The three main occupational categories were genetic counselor (21.0%), clinical geneticist (24.9%), and researcher (25.4%). Of all 181 respondents, 106 provide GC for any psychiatric disorder or NDD, corresponding to 58.6% of the whole group ranging from 43.2% in Central Eastern Europe to 66.1% in Western Europe. Overall, 65.2% of the respondents reported that genetic testing is offered to individuals with NDD, and 26.5% indicated the same for individuals with major psychiatric disorders. Only 22.1% of the respondents indicated that they have guidelines for PsychGT. Pharmacogenetic testing actionable for psychiatric disorders was offered by 15%. Interestingly, when genetic tests are fully covered by national health insurance, more genetic testing is provided for individuals with NDD but not those with major psychiatric disorders. Our qualitative analyses of responses highlight the lack of guidelines and knowledge on utilizing and using genetic tests and education and training as the major obstacles to implementation. Indeed, the existence of psychiatric genetic training courses was confirmed by only 11.6% of respondents. The question on the relevance of up-to-date education and training in psychiatric genetics on everyday related practice was highly relevant. We provide evidence that PsychGC and PsychGT are already in use across European countries, but there is a lack of guidelines and education. Harmonization of practice and development of guidelines for genetic counseling, testing, and training professionals would improve equality and access to quality care for individuals with psychiatric disorders within Europe.
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Affiliation(s)
- Kati Koido
- Department of Physiology, Institute of Biomedicine and Translational Medicine, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Charlotta Ingvoldstad Malmgren
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden; Center for Research and Bioethics, CRB, Uppsala University, Uppsala, Sweden
| | - Lejla Pojskic
- Laboratory for Human Genetics, University of Sarajevo - Institute for Genetic Engineering and Biotechnology, Sarajevo, Bosnia and Herzegovina
| | - Peter Z Almos
- Department of Psychiatry, University of Szeged, Szeged, Hungary
| | - Sarah E Bergen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Isabella Borg
- Pathology Department, Faculty of Medicine and Surgery, University of Malta, Msida, Malta
| | - Nada Božina
- University of Zagreb School of Medicine, Department of Pharmacology, Zagreb, Croatia
| | | | - Franziska Degenhardt
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Lana Ganoci
- University Hospital Centre Zagreb, Department of Laboratory Diagnostics, Division for Pharmacogenomics and Therapy Individualization, Zagreb, Croatia
| | - Uffe B Jensen
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark
| | - Louise Durand-Lennad
- Université Paris Cité, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Paris, France
| | - Claudine Laurent-Levinson
- Faculté de Médecine-Sorbonne Université, Groupe de Recherche Clinique N°15 - Troubles Psychiatriques et Développement (PSYDEV) & Centre de Référence des Maladies Rares à Expression Psychiatrique, DMU ORYGINE Femmes-Mères-Enfants, Service de Psychiatrie de l'Enfant et de l'Adolescent, Assistance Publique-Hôpitaux de Paris, Sorbonne Université, Paris, France
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Alvydas Navickas
- Psychiatric Clinic, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | - Nikolai P Pace
- Centre for Molecular Medicine and Biobanking, University of Malta, Malta
| | - Milena Paneque
- Center for Predictive and Preventive Genetics, Institute of Molecular and Cellular Biology, Institute for Research and Innovation in Health, University of Porto, Porto, Portugal
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Maria Grigoroiu-Serbanescu
- Alexandru Obregia Clinical Psychiatric Hospital, Biometric Psychiatric Genetics Research Unit, Bucharest, Romania
| | - Maria Johansson Soller
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm and Karolinska Institutet, Stockholm, Sweden
| | - Jaana Suvisaari
- Finnish Institute for Health and Welfare, Department of Public Health and Welfare, Mental Health Team, Helsinki, Finland
| | - Algirdas Utkus
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | | | - Lily Vissouze
- Université Paris Cité, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, Paris, France
| | - Shachar Zuckerman
- Medical Genetic Institute, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Boris Chaumette
- Université Paris Cité, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris, GHU-Paris Psychiatrie et Neurosciences, Paris, France; Department of Psychiatry, McGill University, Montreal, Canada
| | - Kristiina Tammimies
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, Stockholm, Sweden; Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, Stockholm, Sweden.
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25
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Hu J, Ji Y, Lang X, Zhang XY. Prevalence and clinical correlates of abnormal lipid metabolism in first-episode and drug-naïve patients with major depressive disorder: A large-scale cross-sectional study. J Psychiatr Res 2023; 163:55-62. [PMID: 37201238 DOI: 10.1016/j.jpsychires.2023.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 04/03/2023] [Accepted: 05/01/2023] [Indexed: 05/20/2023]
Abstract
OBJECTIVE Studies have shown an association between abnormal lipid profiles and MDD, but there are few studies on the clinical correlates of lipid abnormalities in patients with major depressive disorder (MDD). The purpose of this study was to investigate the prevalence of abnormal lipid metabolism and its correlates in Chinese first-episode and drug-naïve MDD patients, which has not yet been reported. METHODS A total of 1718 outpatients with first-episode and drug-naïve MDD were included. Demographic data were collected by a standardized questionnaire and blood lipid levels were measured, including total cholesterol (TC), triglyceride (TG), low density lipoprotein (LDL-C), high density lipoprotein (HDL-C). The Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), Positive and Negative Syndrome Scale (PANSS) positive subscale, and Clinical Global Impression of Severity Scale (CGI-S) were assessed for each patient. RESULTS The prevalence of abnormal lipid metabolism was 72.73% (1301/1718), and the rates of high TC, high TG, high LDL-C and low HDL-C were 51.05% (877/1718), 61.18% (1051/1718), 30.09% (517/1718), 23.40% (402/1718), respectively. Logistic regression showed the risk factors for abnormal lipid metabolism were severe anxiety, HAMD score, CGI-S score, BMI and systolic blood pressure (SBP). Multiple linear regression analysis showed that age at onset, SBP, HAMD score, HAMA score, PANSS positive subscale score, and CGI-S were independently associated with TC levels. BMI, HAMD score, PANSS positive subscale score and CGI-S score were independently associated with TG levels. SBP, HAMD score, PANSS positive subscale score and CGI-S score were independently associated with LDL-C levels. Age of onset, SBP and CGI-S score were independently associated with HDL-C levels. CONCLUSIONS The prevalence of abnormal lipid metabolism in first-episode and drug-naïve MDD patients is quite high. The severity of psychiatric symptoms may be closely associated with the presence of abnormal lipid metabolism in patients with MDD.
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Affiliation(s)
- Jieqiong Hu
- Department of Psychosomatic Medicine, Ningbo First Hospital, Ningbo, Zhejiang, China
| | - Yunxin Ji
- Department of Psychosomatic Medicine, Ningbo First Hospital, Ningbo, Zhejiang, China
| | - XiaoE Lang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xiang-Yang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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26
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Gallo S, El-Gazzar A, Zhutovsky P, Thomas RM, Javaheripour N, Li M, Bartova L, Bathula D, Dannlowski U, Davey C, Frodl T, Gotlib I, Grimm S, Grotegerd D, Hahn T, Hamilton PJ, Harrison BJ, Jansen A, Kircher T, Meyer B, Nenadić I, Olbrich S, Paul E, Pezawas L, Sacchet MD, Sämann P, Wagner G, Walter H, Walter M, van Wingen G. Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies. Mol Psychiatry 2023; 28:3013-3022. [PMID: 36792654 PMCID: PMC10615764 DOI: 10.1038/s41380-023-01977-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 01/12/2023] [Accepted: 01/19/2023] [Indexed: 02/17/2023]
Abstract
The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.
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Affiliation(s)
- Selene Gallo
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Meibergdreef 9, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Ahmed El-Gazzar
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Meibergdreef 9, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Amsterdam, The Netherlands.
| | - Paul Zhutovsky
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Meibergdreef 9, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Rajat M Thomas
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Meibergdreef 9, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Nooshin Javaheripour
- Department Of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Meng Li
- Department Of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Lucie Bartova
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | | | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Christopher Davey
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
- German center for mental health, CIRC, Magdeburg, Germany
| | - Ian Gotlib
- Department of Psychology, Stanford University, Stanford, CA, 94305, USA
| | - Simone Grimm
- Department of Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Paul J Hamilton
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Ben J Harrison
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Andreas Jansen
- Department Of Psychiatry, University of Marburg, Marburg, Germany
| | - Tilo Kircher
- Department Of Psychiatry, University of Marburg, Marburg, Germany
| | - Bernhard Meyer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Igor Nenadić
- Department Of Psychiatry, University of Marburg, Marburg, Germany
| | - Sebastian Olbrich
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Zurich, Zurich, Switzerland
| | - Elisabeth Paul
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Lukas Pezawas
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Matthew D Sacchet
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | | | - Gerd Wagner
- Department Of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Henrik Walter
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charitéplatz 1, D-10117, Berlin, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
- German center for mental health, CIRC, Magdeburg, Germany
| | - Guido van Wingen
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Meibergdreef 9, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
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27
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Baltramonaityte V, Pingault JB, Cecil CAM, Choudhary P, Järvelin MR, Penninx BWJH, Felix J, Sebert S, Milaneschi Y, Walton E. A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity. PLoS Genet 2023; 19:e1010508. [PMID: 37390107 DOI: 10.1371/journal.pgen.1010508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 06/12/2023] [Indexed: 07/02/2023] Open
Abstract
Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.
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Affiliation(s)
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational, and Health Psychology, University College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Marjo-Riitta Järvelin
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Janine Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Sylvain Sebert
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, United Kingdom
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28
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Kazantseva A, Davydova Y, Enikeeva R, Mustafin R, Malykh S, Lobaskova M, Kanapin A, Prokopenko I, Khusnutdinova E. A Combined Effect of Polygenic Scores and Environmental Factors on Individual Differences in Depression Level. Genes (Basel) 2023; 14:1355. [PMID: 37510260 PMCID: PMC10379734 DOI: 10.3390/genes14071355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/14/2023] [Accepted: 06/22/2023] [Indexed: 07/30/2023] Open
Abstract
The risk of depression could be evaluated through its multifactorial nature using the polygenic score (PGS) approach. Assuming a "clinical continuum" hypothesis of mental diseases, a preliminary assessment of individuals with elevated risk for developing depression in a non-clinical group is of high relevance. In turn, epidemiological studies suggest including social/lifestyle factors together with PGS to address the "missing heritability" problem. We designed regression models, which included PGS using 27 SNPs and social/lifestyle factors to explain individual differences in depression levels in high-education students from the Volga-Ural region (VUR) of Eurasia. Since issues related to population stratification in PGS scores may lead to imprecise variant effect estimates, we aimed to examine a sensitivity of PGS calculated on summary statistics of depression and neuroticism GWAS from Western Europeans to assess individual proneness to depression levels in the examined sample of Eastern Europeans. A depression score was assessed using the revised version of the Beck Depression Inventory (BDI) in 1065 young adults (age 18-25 years, 79% women, Eastern European ancestry). The models based on weighted PGS demonstrated higher sensitivity to evaluate depression level in the full dataset, explaining up to 2.4% of the variance (p = 3.42 × 10-7); the addition of social parameters enhanced the strength of the model (adjusted r2 = 15%, p < 2.2 × 10-16). A higher effect was observed in models based on weighted PGS in the women group, explaining up to 3.9% (p = 6.03 × 10-9) of variance in depression level assuming a combined SNPs effect and 17% (p < 2.2 × 10-16)-with the addition of social factors in the model. We failed to estimate BDI-measured depression based on summary statistics from Western Europeans GWAS of clinical depression. Although regression models based on PGS from neuroticism (depression-related trait) GWAS in Europeans were associated with a depression level in our sample (adjusted r2 = 0.43%, p = 0.019-for unweighted model), the effect was mainly attributed to the inclusion of social/lifestyle factors as predictors in these models (adjusted r2 = 15%, p < 2.2 × 10-16-for unweighted model). In conclusion, constructed PGS models contribute to a proportion of interindividual variability in BDI-measured depression in high-education students, especially women, from the VUR of Eurasia. External factors, including the specificity of rearing in childhood, used as predictors, improve the predictive ability of these models. Implementation of ethnicity-specific effect estimates in such modeling is important for individual risk assessment.
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Affiliation(s)
- Anastasiya Kazantseva
- Institute of Biochemistry and Genetics-Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
- Laboratory of Neurocognitive Genomics, Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, 450076 Ufa, Russia
| | - Yuliya Davydova
- Institute of Biochemistry and Genetics-Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
- Laboratory of Neurocognitive Genomics, Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, 450076 Ufa, Russia
| | - Renata Enikeeva
- Institute of Biochemistry and Genetics-Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
- Laboratory of Neurocognitive Genomics, Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, 450076 Ufa, Russia
| | - Rustam Mustafin
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, 450008 Ufa, Russia
| | - Sergey Malykh
- Psychological Institute, Russian Academy of Education, 125009 Moscow, Russia
- Department of Psychology, Lomonosov Moscow State University, 125009 Moscow, Russia
| | - Marina Lobaskova
- Psychological Institute, Russian Academy of Education, 125009 Moscow, Russia
| | - Alexander Kanapin
- Laboratory of Neurocognitive Genomics, Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, 450076 Ufa, Russia
| | - Inga Prokopenko
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford GU2 7XH, UK
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics-Subdivision of the Ufa Federal Research Centre of the Russian Academy of Sciences, 450054 Ufa, Russia
- Laboratory of Neurocognitive Genomics, Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, 450076 Ufa, Russia
- Department of Psychology, Lomonosov Moscow State University, 125009 Moscow, Russia
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Yang Z, Li D, He Y, Chen X, Li Z. Unrevealing the shared genetic mechanisms underlying C-reactive protein and schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2023; 126:110785. [PMID: 37150315 DOI: 10.1016/j.pnpbp.2023.110785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 04/18/2023] [Accepted: 05/04/2023] [Indexed: 05/09/2023]
Abstract
Longitudinal observational studies and Mendelian randomization research have obtained contradictory conclusions regarding the association between C-reactive protein (CRP) level and schizophrenia risk. However, the shared genetic mechanisms underlying CRP and schizophrenia remain poorly understood. Here, we examined the global and local genetic correlations using summary statistics from large-scale genome-wide association studies (GWAS) on CRP level and schizophrenia. Furthermore, we identified their shared genetic variants by applying the conditional false discovery rate approach and performed functional analyses of shared variants to explore the shared genetic mechanisms underlying CRP level and schizophrenia. We found a significant negative genetic correlation at the whole genome level and five significant local genetic correlations between CRP level and schizophrenia. Eight-three shared genetic loci were identified, from which single-nucleotide polymorphism (SNP) presents mixed effects on the increased CRP level and schizophrenia risk. Additionally, we identified 64 and 73 candidate genes that were mapped from SNPs with"concordant effect"(ceSNPs) and"discordant effect"(deSNPs) on the CRP level and schizophrenia risk respectively. Functional analyses revealed that genes mapped from ceSNPs and deSNPs exhibited similar patterns of human brain developmental expression trajectories and biological processes, but differed in expression levels and cell-type-specific enrichment in brain tissues. Our findings demonstrated mixed effects of shared genetic architecture between CRP level and schizophrenia, proving a deeper insight into the shared genetic aetiology underlying the CRP level and schizophrenia.
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Affiliation(s)
- Zihao Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - David Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Ying He
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China; China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiaogang Chen
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China; China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Zongchang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, PR China; China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, PR China.
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30
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Gao K, Ayati M, Kaye NM, Koyuturk M, Calabrese JR, Ganocy SJ, Lazarus HM, Christian E, Kaplan D. Differences in intracellular protein levels in monocytes and CD4 + lymphocytes between bipolar depressed patients and healthy controls: A pilot study with tyramine-based signal-amplified flow cytometry. J Affect Disord 2023; 328:116-127. [PMID: 36806598 DOI: 10.1016/j.jad.2023.02.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 01/30/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND Molecular biomarkers for bipolar disorder (BD) that distinguish it from other manifestations of depressive symptoms remain unknown. The aim of this study was to determine if a very sensitive tyramine-based signal-amplification technology for flow cytometry (CellPrint™) could facilitate the identification of cell-specific analyte expression profiles of peripheral blood cells for bipolar depression (BPD) versus healthy controls (HCs). METHODS The diagnosis of psychiatric disorders was ascertained with Mini International Neuropsychiatric Interview for DSM-5. Expression levels for eighteen protein analytes previously shown to be related to bipolar disorder were assessed with CellPrint™ in CD4+ T cells and monocytes of bipolar patients and HCs. Implementation of protein-protein interaction (PPI) network and pathway analysis was subsequently used to identify new analytes and pathways for subsequent interrogations. RESULTS Fourteen drug-naïve or -free patients with bipolar I or II depression and 17 healthy controls (HCs) were enrolled. The most distinguishable changes in analyte expression based on t-tests included GSK3β, HMGB1, IRS2, phospho-GSK3αβ, phospho-RELA, and TSPO in CD4+ T cells and calmodulin, GSK3β, IRS2, and phospho-HS1 in monocytes. Subsequent PPI and pathway analysis indicated that prolactin, leptin, BDNF, and interleukin-3 signal pathways were significantly different between bipolar patients and HCs. LIMITATION The sample size of the study was small and 2 patients were on medications. CONCLUSION In this pilot study, CellPrint™ was able to detect differences in cell-specific protein levels between BPD patients and HCs. A subsequent study including samples from patients with BPD, major depressive disorder, and HCs is warranted.
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Affiliation(s)
- Keming Gao
- Department of Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH, United States of America; Case Western Reserve University School of Medicine, Cleveland, OH, United States of America.
| | - Marzieh Ayati
- Department of Computer Science, University of Texas Rio Grande Valley, Edinburg, TX, United States of America
| | - Nicholas M Kaye
- CellPrint Biotechnology, Cleveland, OH, United States of America
| | - Mehmet Koyuturk
- Department of Computer and Data Sciences, Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, OH, United States of America
| | - Joseph R Calabrese
- Department of Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH, United States of America; Case Western Reserve University School of Medicine, Cleveland, OH, United States of America
| | - Stephen J Ganocy
- Department of Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH, United States of America; Case Western Reserve University School of Medicine, Cleveland, OH, United States of America
| | - Hillard M Lazarus
- Case Western Reserve University School of Medicine, Cleveland, OH, United States of America; CellPrint Biotechnology, Cleveland, OH, United States of America; Department of Medicine, University Hospitals Cleveland Medical Center, Cleveland, OH, United States of America
| | - Eric Christian
- CellPrint Biotechnology, Cleveland, OH, United States of America
| | - David Kaplan
- CellPrint Biotechnology, Cleveland, OH, United States of America
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31
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Hickie IB, Merikangas KR, Carpenter JS, Iorfino F, Scott EM, Scott J, Crouse JJ. Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder? Bipolar Disord 2023; 25:191-199. [PMID: 36661342 PMCID: PMC10947388 DOI: 10.1111/bdi.13304] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
OBJECTIVES Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder. METHODS We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high-/low-activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors? RESULTS Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high- or low-activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high-/low-activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised. CONCLUSION Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states and deserves prioritisation in research in bipolar disorders.
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Affiliation(s)
- Ian B. Hickie
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Kathleen R. Merikangas
- Genetic Epidemiology Research Branch, Division of Intramural Research ProgramNational Institute of Mental HealthBethesdaMarylandUSA
| | - Joanne S. Carpenter
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Frank Iorfino
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Elizabeth M. Scott
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Jan Scott
- Institute of NeuroscienceNewcastle UniversityNewcastle upon TyneUK
- Norwegian University of Science and TechnologyTrondheimNorway
- Université de ParisParisFrance
| | - Jacob J. Crouse
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
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32
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Moyakhe LB, Dalvie S, Mufford MS, Stein DJ, Koen N. Polygenic risk associations with developmental and mental health outcomes in childhood and adolescence: A systematic review. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.31.23287877. [PMID: 37034686 PMCID: PMC10081411 DOI: 10.1101/2023.03.31.23287877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Background Neurodevelopmental and mental health disorders in childhood constitute an emerging global concern, with adverse sequelae which span children's physical, psychological and social well-being. The aetiology of these disorders is likely complex, multifactorial and polygenic. Polygenic risk scores (PRS), an estimate of an individual's genetic liability toward a disorder, have been increasingly used in psychiatric research to explore genetic associations with disorders of interest. However, limited work delineates polygenic associations with development and mental health in childhood populations.We aimed to systematically review existing literature on associations between genetic risk (as measured by PRS) and neurodevelopmental and mental health outcomes in childhood and adolescence. Methods Following the recommended Preferred Reporting Items for Meta-Analyses (PRISMA) guidelines, databases were searched using key search terms. The search commenced in March 2021 and concluded in June 2021. The studies eligible for inclusion were full-text articles investigating polygenic risk associations with neurodevelopmental and/or mental health outcomes in childhood or adolescence. Results Fourteen studies were eligible for inclusion in this systematic review. The association between higher PRS for attention-deficit/hyperactivity disorder (ADHD) and adverse developmental/mental health outcomes in childhood and adolescence was reported by five studies. Additionally, associations between PRS for bipolar disorder or major depressive disorder and adverse outcomes of interest were also described by two studies; and two studies highlighted associations between schizophrenia PRS and mental health disorders in childhood. The remaining studies highlighted shared polygenic contributions between and within NDDs and mental health disorders in children. Conclusion The findings of this systematic review suggest that PRS for neurodevelopmental and mental health disorders may associate with adverse neurodevelopmental and mental health outcomes from early childhood to adolescence. In addition, these associations seemed not to be phenotype-specific, suggesting potential shared genetic variation across the phenotypes of interest.
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Affiliation(s)
- L B Moyakhe
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, South Africa; and UCT Neuroscience Institute
| | - S Dalvie
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, South Africa; and UCT Neuroscience Institute
- Biomedical Research and Innovation Platform, SAMRC
| | - M S Mufford
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, South Africa; and UCT Neuroscience Institute
- South African Medical Research Council Genomic and Precision Medicine Unit, Division of Human Genetics, Department of Pathology, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town
- Fellow, Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER) program, Harvard T.H Chan School of Public Health and the Stanley Center for Psychiatric Research at the Broad Institute of Harvard and MIT
| | - D J Stein
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, South Africa; and UCT Neuroscience Institute
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders
| | - N Koen
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, South Africa; and UCT Neuroscience Institute
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders
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33
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Williams CM, Poore H, Tanksley PT, Kweon H, Courchesne-Krak NS, Londono-Correa D, Mallard TT, Barr P, Koellinger PD, Waldman ID, Sanchez-Roige S, Harden KP, Palmer AA, Dick DM, Linnér RK. Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.21.533641. [PMID: 36993611 PMCID: PMC10055200 DOI: 10.1101/2023.03.21.533641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.
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Affiliation(s)
- Camille M Williams
- Department of Psychology and Population Research Center, University of Texas at Austin
| | - Holly Poore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University
| | | | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam
| | | | | | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Peter Barr
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University
| | | | | | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.; Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
| | - K Paige Harden
- Department of Psychology and Population Research Center, University of Texas at Austin
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego; Institute for Genomic Medicine, University of California San Diego
| | - Danielle M Dick
- Rutgers Addiction Research Center in the Brain Health Institute, Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University
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Dattilo V, Ulivi S, Minelli A, La Bianca M, Giacopuzzi E, Bortolomasi M, Bignotti S, Gennarelli M, Gasparini P, Concas MP. Genome-wide association studies on Northern Italy isolated populations provide further support concerning genetic susceptibility for major depressive disorder. World J Biol Psychiatry 2023; 24:135-148. [PMID: 35615967 DOI: 10.1080/15622975.2022.2082523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
OBJECTIVES Major depressive disorder (MDD) is a psychiatric disorder with pathogenesis influenced by both genetic and environmental factors. To date, the molecular-level understanding of its aetiology remains unclear. Thus, we aimed to identify genetic variants and susceptibility genes for MDD with a genome-wide association study (GWAS) approach. METHODS We performed a meta-analysis of GWASs and a gene-based analysis on two Northern Italy isolated populations (cases/controls n = 166/472 and 33/320), followed by replication and polygenic risk score (PRS) analyses in Italian independent samples (cases n = 464, controls n = 339). RESULTS We identified two novel MDD-associated genes, KCNQ5 (lead SNP rs867262, p = 3.82 × 10-9) and CTNNA2 (rs6729523, p = 1.25 × 10-8). The gene-based analysis revealed another six genes (p < 2.703 × 10-6): GRM7, CTNT4, SNRK, SRGAP3, TRAPPC9, and FHIT. No replication of the genome-wide significant SNPs was found in the independent cohort, even if 14 SNPs around CTNNA2 showed association with MDD and related phenotypes at the nominal level of p (<0.05). Furthermore, the PRS model developed in the discovery cohort discriminated cases and controls in the replication cohort. CONCLUSIONS Our work suggests new possible genes associated with MDD, and the PRS analysis confirms the polygenic nature of this disorder. Future studies are required to better understand the role of these findings in MDD.
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Affiliation(s)
- Vincenzo Dattilo
- Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Sheila Ulivi
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Alessandra Minelli
- Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Martina La Bianca
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
| | - Edoardo Giacopuzzi
- Wellcome Centre for Human Genetics, Oxford University, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford, UK
| | | | - Stefano Bignotti
- Unit of Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Massimo Gennarelli
- Genetics Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Paolo Gasparini
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy.,Department of Medicine, Surgery and Health Science, University of Trieste, Trieste, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health-IRCCS Burlo Garofolo, Trieste, Italy
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35
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Scangos KW, State MW, Miller AH, Baker JT, Williams LM. New and emerging approaches to treat psychiatric disorders. Nat Med 2023; 29:317-333. [PMID: 36797480 PMCID: PMC11219030 DOI: 10.1038/s41591-022-02197-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/21/2022] [Indexed: 02/18/2023]
Abstract
Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact the lives of millions of people worldwide. Although their etiological and diagnostic heterogeneity has long challenged drug discovery, an emerging circuit-based understanding of psychiatric illness is offering an important alternative to the current reliance on trial and error, both in the development and in the clinical application of treatments. Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.
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Affiliation(s)
- Katherine W Scangos
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Matthew W State
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew H Miller
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Justin T Baker
- McLean Hospital Institute for Technology in Psychiatry, Belmont, MA, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Mental Illness Research Education and Clinical Center (MIRECC), VA Palo Alto Health Care System, Palo Alto, CA, USA
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36
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Byg LM, Speed M, Speed D, Østergaard SD. Genetic liability to bipolar disorder and body mass index: A bidirectional two-sample Mendelian randomization study. Bipolar Disord 2023; 25:25-31. [PMID: 36377279 DOI: 10.1111/bdi.13267] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVES Bipolar disorder is associated with increased body mass index (BMI), but it remains undetermined if this association is causal and, if so, in which direction it goes. Here, we sought to answer these questions using bidirectional two-sample Mendelian randomization, a method from genetic epidemiology that uses data from genome-wide association studies (GWAS) to examine whether a risk factor is causal for an outcome METHODS: We used summary statistics from GWAS of bipolar disorder and BMI conducted using data collected by the Psychiatric Genomics Consortium and the UK Biobank, respectively. The genetic instrument for bipolar disorder contained 53 SNPs and explained 0.5% of phenotypic variance, while the genetic instrument for BMI contained 517 SNPs and explained 7.1% of phenotypic variance RESULTS: Our findings suggest that genetic liability to bipolar disorder reduces BMI (slope from Egger regression = -0.195, p = 0.004). It follows that a twofold increase in the genetic liability to bipolar disorder leads to a 0.6 (kg/m2 ) reduction in BMI, predominantly driven by reduced fat mass. Conversely, we found no evidence that BMI causes changes in the risk of developing bipolar disorder CONCLUSION: The results of this study suggest that the increased BMI observed among individuals with bipolar disorder is not a direct consequence of genetic liability to bipolar disorder, but may more likely represent the sum of downstream correlates of manifest bipolar disorder, such as side effects of pharmacological treatment, poor diet, and sedentary lifestyle. As these factors are all modifiable, they can be targeted as part of clinical management.
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Affiliation(s)
- Lars Meinertz Byg
- Department of Affective Disorders, Aarhus University Hospital, Psychiatry, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Maria Speed
- Department of Affective Disorders, Aarhus University Hospital, Psychiatry, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Doug Speed
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Søren Dinesen Østergaard
- Department of Affective Disorders, Aarhus University Hospital, Psychiatry, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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37
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Haghighatfard A, Ghaderi AH, Mostajabi P, Kashfi SS, Mohabati Somehsarayee H, Shahrani M, Mehrasa M, Haghighat S, Farhadi M, Momayez Sefat M, Shiryazdi AA, Ezzati N, Qazvini MG, Alizadenik A, Moghadam ER. The first genome-wide association study of internet addiction; Revealed substantial shared risk factors with neurodevelopmental psychiatric disorders. RESEARCH IN DEVELOPMENTAL DISABILITIES 2023; 133:104393. [PMID: 36566681 DOI: 10.1016/j.ridd.2022.104393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/02/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Internet addiction disorder (IAD) is listed as a disorder requiring further studies in the diagnostic and statistical manual of mental disorders (DSM-V). Psychological studies showed significant co-morbidity of IAD with depression, alcohol abuse, and anxiety disorder. Etiology and genetic bases of IAD are unclear. AIMS Present study aimed to investigate the genetic, psychological, and cognitive bases of a tendency to internet addiction. METHODS AND PROCEDURES DNA was extracted from blood samples of IADs (N = 16,520) and 18,000 matched non-psychiatric subjects. Genotyping for the subjects was performed using SNP Array. Psychological, neuropsychological, and neurological characteristics were conducted. OUTCOMES AND RESULTS Seventy-two SNPs in 24 genes have been detected significantly associated with IAD. Most of these SNPs were risk factors for psychiatric disorders. Most similarity detected with autism spectrum disorder, bipolar disorder and schizophrenia. Higher anxiety, stress, and neuroticism and deficits in working memory, attention, planning, and processing speed were detected in IADs. CONCLUSIONS This study is the first genome-wide association study of IAD that showed strong shared genetic bases with neurodevelopmental disabilities and psychiatric disorders. IMPLICATIONS Genetic risk factors in IADs may cause several cognitive and neurodevelopmental brain function abnormalities, which lead to excessive Internet usage. It may suggest that IAD could be a marker for vulnerability to developmental psychiatric disorders.
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Affiliation(s)
- Arvin Haghighatfard
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Sleep Education and Research Laboratory, UCL Institute of Education, London, UK; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran; Department of Biology, North Tehran Branch, Islamic Azad University, Tehran, Islamic Republic of Iran.
| | - Amir Hossein Ghaderi
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Vision: ScienCe First to Applications (VISTA), York University, Toronto, Canada; Department of Psychology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Parmida Mostajabi
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Seyedeh Sara Kashfi
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Hediyeh Mohabati Somehsarayee
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Maryam Shahrani
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Mahla Mehrasa
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Saba Haghighat
- Neuroimaging Genetic Laboratory, Arvin Gene Company, Tehran, Islamic Republic of Iran; Department of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Islamic Republic of Iran; Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Mahdi Farhadi
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Maryam Momayez Sefat
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Atena Alsadat Shiryazdi
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | - Naghmeh Ezzati
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Islamic Republic of Iran
| | | | - Atie Alizadenik
- Department of Biology, Damghan Branch, Islamic Azad University, Damghan, Islamic Republic of Iran
| | - Elham Rastegari Moghadam
- Department of Biology, Damghan Branch, Islamic Azad University, Damghan, Islamic Republic of Iran
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Lin BD, Pinzón-Espinosa J, Blouzard E, van der Horst MZ, Okhuijsen-Pfeifer C, van Eijk KR, Guloksuz S, Peyrot WJ, Luykx JJ. Associations Between Polygenic Risk Score Loading, Psychosis Liability, and Clozapine Use Among Individuals With Schizophrenia. JAMA Psychiatry 2023; 80:181-185. [PMID: 36542388 PMCID: PMC9857760 DOI: 10.1001/jamapsychiatry.2022.4234] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/18/2022] [Indexed: 12/24/2022]
Abstract
Importance Predictors consistently associated with psychosis liability and course of illness in schizophrenia (SCZ) spectrum disorders (SSD), including the need for clozapine treatment, are lacking. Longitudinally ascertained medication use may empower studies examining associations between polygenic risk scores (PRSs) and pharmacotherapy choices. Objective To examine associations between PRS-SCZ loading and groups with different liabilities to SSD (individuals with SSD taking clozapine, individuals with SSD taking other antipsychotics, their parents and siblings, and unrelated healthy controls) and between PRS-SCZ and the likelihood of receiving a prescription of clozapine relative to other antipsychotics. Design, Setting, and Participants This genetic association study was a multicenter, observational cohort study with 6 years of follow-up. Included were individuals diagnosed with SSD who were taking clozapine or other antipsychotics, their parents and siblings, and unrelated healthy controls. Data were collected from 2004 until 2021 and analyzed between October 2021 and September 2022. Exposures Polygenic risk scores for SCZ. Main Outcomes and Measures Multinomial logistic regression was used to examine possible differences between groups by computing risk ratios (RRs), ie, ratios of the probability of pertaining to a particular group divided by the probability of healthy control status. We also computed PRS-informed odd ratios (ORs) for clozapine use relative to other antipsychotics. Results Polygenic risk scores for SCZ were generated for 2344 participants (mean [SD] age, 36.95 years [14.38]; 994 female individuals [42.4%]) who remained after quality control screening (557 individuals with SSD taking clozapine, 350 individuals with SSD taking other antipsychotics during the 6-year follow-up, 542 parents and 574 siblings of individuals with SSD, and 321 unrelated healthy controls). All RRs were significantly different from 1; RRs were highest for individuals with SSD taking clozapine (RR, 3.24; 95% CI, 2.76-3.81; P = 2.47 × 10-46), followed by individuals with SSD taking other antipsychotics (RR, 2.30; 95% CI, 1.95-2.72; P = 3.77 × 10-22), parents (RR, 1.44; 95% CI, 1.25-1.68; P = 1.76 × 10-6), and siblings (RR, 1.40; 95% CI, 1.21-1.63; P = 8.22 × 10-6). Polygenic risk scores for SCZ were positively associated with clozapine vs other antipsychotic use (OR, 1.41; 95% CI, 1.22-1.63; P = 2.98 × 10-6), suggesting a higher likelihood of clozapine prescriptions among individuals with higher PRS-SCZ. Conclusions and Relevance In this study, PRS-SCZ loading differed between groups of individuals with SSD, their relatives, and unrelated healthy controls, with patients taking clozapine at the far end of PRS-SCZ loading. Additionally, PRS-SCZ was associated with a higher likelihood of clozapine prescribing. Our findings may inform early intervention and prognostic studies of the value of using PRS-SCZ to personalize antipsychotic treatment.
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Affiliation(s)
- Bochao D. Lin
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, School of Basic Medical Sciences, Henan University, Kaifeng, China
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Justo Pinzón-Espinosa
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
- Sant Pau Mental Health Group, Institut d’Investigació Biomèdica Sant Pau (IBB-Sant Pau), Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, Catalonia, Spain
- Department of Medicine, School of Medicine, University of Barcelona, Barcelona, Spain
- Department of Clinical Psychiatry, School of Medicine, University of Panama, Panama City, Panama
| | - Elodie Blouzard
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Marte Z. van der Horst
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
- GGNet Mental Health, Warnsveld, the Netherlands
| | - Cynthia Okhuijsen-Pfeifer
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Kristel R. van Eijk
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Wouter J. Peyrot
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
| | - Jurjen J. Luykx
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht, Utrecht University, Brain Center Rudolf Magnus, Utrecht, the Netherlands
- GGNet Mental Health, Warnsveld, the Netherlands
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Bonacina G, Carollo A, Esposito G. The Genetic Side of the Mood: A Scientometric Review of the Genetic Basis of Mood Disorders. Genes (Basel) 2023; 14:genes14020352. [PMID: 36833279 PMCID: PMC9956267 DOI: 10.3390/genes14020352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/22/2023] [Accepted: 01/27/2023] [Indexed: 01/31/2023] Open
Abstract
Mood disorders are highly heritable psychiatric disorders. Over the years, many genetic polymorphisms have been identified to pose a higher risk for the development of mood disorders. To overview the literature on the genetics of mood disorders, a scientometric analysis was performed on a sample of 5342 documents downloaded from Scopus. The most active countries and the most impactful documents in the field were identified. Furthermore, a total of 13 main thematic clusters emerged in the literature. From the qualitative inspection of clusters, it emerged that the research interest moved from a monogenic to a polygenic risk framework. Researchers have moved from the study of single genes in the early 1990s to conducting genome-wide association studies around 2015. In this way, genetic overlaps between mood disorders and other psychiatric conditions emerged too. Furthermore, around the 2010s, the interaction between genes and environmental factors emerged as pivotal in understanding the risk for mood disorders. The inspection of thematic clusters provides a valuable insight into the past and recent trends of research in the genetics of mood disorders and sheds light onto future lines of research.
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Preconception paternal mental disorders and child health: Mechanisms and interventions. Neurosci Biobehav Rev 2023; 144:104976. [PMID: 36435393 DOI: 10.1016/j.neubiorev.2022.104976] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 11/19/2022] [Accepted: 11/22/2022] [Indexed: 11/25/2022]
Abstract
Mental illness is a significant global health issue with a steady prevalence. High heritability is suspected, but genome-wide association studies only identified a small number of risk genes associated with mental disorders. This 'missing inheritance' can be partially explained by epigenetic heredity. Evidence from numerous animal models and human studies supports the possibility that preconception paternal mental health influences their offspring's mental health via nongenetic means. Here, we review two potential pathways, including sperm epigenetics and seminal plasma components. The current review highlights the role of sperm epigenetics and explores epigenetic message origination and susceptibility to chronic stress. Meanwhile, possible spatiotemporal windows and events that induce sexually dimorphic modes and effects of paternal stress transmission are inferred in this review. Additionally, we discuss emerging interventions that could potentially block the intergenerational transmission of paternal psychiatric disorders and reduce the incidence of mental illness. Understanding the underlying mechanisms by which preconception paternal stress impacts offspring health is critical for identifying strategies supporting healthy development and successfully controlling the prevalence of mental illness.
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Núñez NA, Miola A, Frye MA. Examining age of onset phenotype in the spectrum of mood disorders. Int Clin Psychopharmacol 2023; 38:66-67. [PMID: 36373788 DOI: 10.1097/yic.0000000000000445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Nicolas A Núñez
- Department of Psychiatry and Psychology, Mayo Clinic Rochester, Rochester, Minnesota, USA
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Abstract
PURPOSE OF REVIEW Due to bipolar disorder clinical heterogeneity, a plethora of studies have provided new genetic, epigenetic, molecular, and cellular findings associated with its pathophysiology. RECENT FINDINGS Genome-wide association studies and epigenetic evidence points to genotype-phenotype interactions associated with inflammation, oxidative stress, abnormalities in signaling pathways, hypothalamic-pituitary-adrenal axis, and circadian rhythm linked to mitochondrial dysfunction in bipolar disorder. Although the literature is constantly increasing, most of the genetic variants proposed as biomarkers remain to be validated by independent groups and use bigger samples and longitudinal approaches to enhance their power and predictive ability. SUMMARY Regardless of which of the mechanisms described here plays a primary or secondary role in the pathophysiology of bipolar disorder, all of these interact to worsen clinical outcomes for patients. Identifying new biomarkers for early detection, prognosis, and response to treatment might provide novel targets to prevent progression and promote general well being.
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Levchenko A, Plotnikova M. Genomic regulatory sequences in the pathogenesis of bipolar disorder. Front Psychiatry 2023; 14:1115924. [PMID: 36824672 PMCID: PMC9941178 DOI: 10.3389/fpsyt.2023.1115924] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/23/2023] [Indexed: 02/10/2023] Open
Abstract
The lifetime prevalence of bipolar disorder is estimated to be about 2%. Epigenetics defines regulatory mechanisms that determine relatively stable patterns of gene expression by controlling all key steps, from DNA to messenger RNA to protein. This Mini Review highlights recent discoveries of modified epigenetic control resulting from genetic variants associated with bipolar disorder in genome-wide association studies. The revealed epigenetic abnormalities implicate gene transcription and post-transcriptional regulation. In the light of these discoveries, the Mini Review focuses on the genes PACS1, MCHR1, DCLK3, HAPLN4, LMAN2L, TMEM258, GNL3, LRRC57, CACNA1C, CACNA1D, and NOVA2 and their potential biological role in the pathogenesis of bipolar disorder. Molecular mechanisms under control of these genes do not translate into a unified picture and substantially more research is needed to fill the gaps in knowledge and to solve current limitations in prognosis and treatment of bipolar disorder. In conclusion, the genetic and functional studies confirm the complex nature of bipolar disorder and indicate future research directions to explore possible targeted treatment options, eventually working toward a personalized approach.
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Affiliation(s)
- Anastasia Levchenko
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Maria Plotnikova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
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Bahremand M, Komasi S. Which symptoms are the psychopathological core affecting the manifestation of pseudo-cardiac symptoms and poor sleep quality in young adults? Symptoms of personality disorders versus clinical disorders. Front Psychol 2022; 13:1011737. [PMID: 36571031 PMCID: PMC9784461 DOI: 10.3389/fpsyg.2022.1011737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 11/28/2022] [Indexed: 12/13/2022] Open
Abstract
Background Diagnosing and identifying the psychological origin of pseudo-cardiac symptoms and comorbid conditions such as poor sleep quality is very difficult due to its extensive and complex nature. The present study was conducted to determine the contribution of symptoms of personality disorders (PDs) and clinical disorders (CDs; i.e., psychological symptoms measured using the Symptom Checklist-90) to the manifestation of pseudo-cardiac symptoms and poor sleep quality. Methods Subjects in this cross-sectional study were 953 (64.3% female; 28.8 ± 6.2 years) community samples in the west of Iran who were selected by convenience sampling. After applying the inclusion criteria, data were collected using the Symptom Checklist-90 (SCL-90-R), the Personality Diagnostic Questionnaire (PDQ-4), and the Scale for Pseudo-Cardiac Symptoms and Poor Sleep Quality (SPSQ). Pearson correlations, factor analytical techniques, and hierarchical regression models were used to examine associations between symptoms of PDs/CDs and outcome factors. Results Factor analytical techniques confirmed both the integrated structure of symptoms of PDs and CDs. Both pseudo-cardiac symptoms and poor sleep quality were more strongly associated with symptoms of CDs than PDs. The results of the hierarchical analysis show that the CDs factor alone could explain the total variance of both pseudo-cardiac symptoms (change in R2 = 0.215 vs. 0.009; p < 0.001) and poor sleep quality (change in R2 = 0.221 vs. 0.001; p < 0.001). Conclusion The different capabilities of two unique factors for the symptoms of PDs and CDs were confirmed by factor analytical methods and regression analysis techniques. Although each of the symptoms of PDs and CDs independently contributes to the manifestation of pseudo-cardiac symptoms and poor sleep quality, the CDs factor is the psychopathological core.
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Affiliation(s)
- Mostafa Bahremand
- Department of Cardiology, Faculty of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Saeid Komasi
- Department of Neuroscience and Psychopathology Research, Mind GPS Institute, Kermanshah, Iran,*Correspondence: Saeid Komasi,
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Pålsson E, Melchior L, Lindwall Sundel K, Karanti A, Joas E, Nordenskjöld A, Agestam M, Runeson B, Landén M. Cohort profile: the Swedish National Quality Register for bipolar disorder(BipoläR). BMJ Open 2022; 12:e064385. [PMID: 36600380 PMCID: PMC9743376 DOI: 10.1136/bmjopen-2022-064385] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
PURPOSE The Swedish National Quality Register for bipolar affective disorder, BipoläR, was established in 2004 to provide nationwide indicators for quality assessment and development in the clinical care of individuals with bipolar spectrum disorder. An ancillary aim was to provide data for bipolar disorder research. PARTICIPANTS Inclusion criteria for registration in BipoläR is a diagnosis of bipolar spectrum disorder (ICD codes: F25.0, F30.1-F30.2, F30.8-F31.9, F34.0) and treatment at an outpatient clinic in Sweden. BipoläR collects data from baseline and annual follow-up visits throughout Sweden. Data is collected using questionnaires administered by healthcare staff. The questions cover sociodemographic, diagnostic, treatment, outcomes and patient reported outcome variables. The register currently includes 39 583 individual patients with a total of 75 423 baseline and follow-up records. FINDINGS TO DATE Data from BipoläR has been used in several peer-reviewed publications. Studies have provided knowledge on effectiveness, side effects and use of pharmacological and psychological treatment in bipolar disorder. In addition, findings on the diagnosis of bipolar disorder, risk factors for attempted and completed suicide and health economics have been reported. The Swedish Bipolar Collection project has contributed to a large number of published studies and provides important information on the genetic architecture of bipolar disorder, the impact of genetic variation on disease characteristics and treatment outcome. FUTURE PLANS Data collection is ongoing with no fixed end date. Currently, approximately 5000 new registrations are added each year. Cohort data are available via a formalised request procedure from Centre of Registers Västra Götaland (e-mail: registercentrum@vgregion.se). Data requests for research purposes require an entity responsible for the research and an ethical approval.
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Affiliation(s)
- Erik Pålsson
- Psychiatry and Neurochemistry, University of Gothenburg, Goteborg, Sweden
| | - Lydia Melchior
- Bipolarmottagning, Sahlgrenska University Hospital, Goteborg, Sweden
| | | | - Alina Karanti
- Psychiatry and Neurochemistry, University of Gothenburg, Goteborg, Sweden
| | - Erik Joas
- Psychiatry and Neurochemistry, University of Gothenburg, Goteborg, Sweden
| | - Axel Nordenskjöld
- University Health Care Research Centre, Faculty of Medicine and Health, Orebro Universitet, Orebro, Sweden
| | | | - Bo Runeson
- Psychiatry, Karolinska Institute, Stockholm, Sweden
| | - Mikael Landén
- Psychiatry and Neurochemistry, University of Gothenburg, Goteborg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Nguyen T, Gao H, Liu D, Philips TJ, Ye Z, Lee JH, Shi GX, Copenhaver K, Zhang L, Wei L, Yu J, Zhang H, Barath A, Luong M, Zhang C, Gaspar-Maia A, Li H, Wang L, Ordog T, Weinshilboum R. Glucocorticoids unmask silent non-coding genetic risk variants for common diseases. Nucleic Acids Res 2022; 50:11635-11653. [PMID: 36399508 PMCID: PMC9723631 DOI: 10.1093/nar/gkac1045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/26/2022] [Indexed: 11/19/2022] Open
Abstract
Understanding the function of non-coding genomic sequence variants represents a challenge for biomedicine. Many diseases are products of gene-by-environment interactions with complex mechanisms. This study addresses these themes by mechanistic characterization of non-coding variants that influence gene expression only after drug or hormone exposure. Using glucocorticoid signaling as a model system, we integrated genomic, transcriptomic, and epigenomic approaches to unravel mechanisms by which variant function could be revealed by hormones or drugs. Specifically, we identified cis-regulatory elements and 3D interactions underlying ligand-dependent associations between variants and gene expression. One-quarter of the glucocorticoid-modulated variants that we identified had already been associated with clinical phenotypes. However, their affected genes were 'unmasked' only after glucocorticoid exposure and often with function relevant to the disease phenotypes. These diseases involved glucocorticoids as risk factors or therapeutic agents and included autoimmunity, metabolic and mood disorders, osteoporosis and cancer. For example, we identified a novel breast cancer risk gene, MAST4, with expression that was repressed by glucocorticoids in cells carrying the risk genotype, repression that correlated with MAST4 expression in breast cancer and treatment outcomes. These observations provide a mechanistic framework for understanding non-coding genetic variant-chemical environment interactions and their role in disease risk and drug response.
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Affiliation(s)
- Thanh Thanh L Nguyen
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic; Rochester, MN, USA
| | - Huanyao Gao
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Duan Liu
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Trudy Janice Philips
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Zhenqing Ye
- Department of Health Sciences Research, Mayo Clinic; Rochester, MN, USA
- Current affiliation: Greehey Children's Cancer Research Institute, University of Texas Health San Antonio; San Antonio, TX 78229, USA
| | - Jeong-Heon Lee
- Epigenomics Program, Center for Individualized Medicine, Mayo Clinic; Rochester, MN, USA
| | - Geng-xian Shi
- Epigenomics Program, Center for Individualized Medicine, Mayo Clinic; Rochester, MN, USA
| | - Kaleigh Copenhaver
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Lingxin Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Lixuan Wei
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Jia Yu
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Huan Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | | | - Maggie Luong
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Cheng Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Alexandre Gaspar-Maia
- Epigenomics Program, Center for Individualized Medicine, Mayo Clinic; Rochester, MN, USA
- Department of Laboratory Medicine and Pathology, Division of Experimental Pathology and Lab Medicine, Mayo Clinic; Rochester, MN, USA
| | - Hu Li
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Liewei Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
| | - Tamas Ordog
- Epigenomics Program, Center for Individualized Medicine, Mayo Clinic; Rochester, MN, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic; Rochester, MN, USA
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic; Rochester, MN, USA
| | - Richard M Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic; Rochester, MN, USA
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Barriers to genetic testing in clinical psychiatry and ways to overcome them: from clinicians' attitudes to sociocultural differences between patients across the globe. Transl Psychiatry 2022; 12:442. [PMID: 36220808 PMCID: PMC9553897 DOI: 10.1038/s41398-022-02203-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 09/15/2022] [Accepted: 09/23/2022] [Indexed: 11/08/2022] Open
Abstract
Genetic testing has evolved rapidly over recent years and new developments have the potential to provide insights that could improve the ability to diagnose, treat, and prevent diseases. Information obtained through genetic testing has proven useful in other specialties, such as cardiology and oncology. Nonetheless, a range of barriers impedes techniques, such as whole-exome or whole-genome sequencing, pharmacogenomics, and polygenic risk scoring, from being implemented in psychiatric practice. These barriers may be procedural (e.g., limitations in extrapolating results to the individual level), economic (e.g., perceived relatively elevated costs precluding insurance coverage), or related to clinicians' knowledge, attitudes, and practices (e.g., perceived unfavorable cost-effectiveness, insufficient understanding of probability statistics, and concerns regarding genetic counseling). Additionally, several ethical concerns may arise (e.g., increased stigma and discrimination through exclusion from health insurance). Here, we provide an overview of potential barriers for the implementation of genetic testing in psychiatry, as well as an in-depth discussion of strategies to address these challenges.
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Ditmars HL, Logue MW, Toomey R, McKenzie RE, Franz CE, Panizzon MS, Reynolds CA, Cuthbert KN, Vandiver R, Gustavson DE, Eglit GML, Elman JA, Sanderson-Cimino M, Williams ME, Andreassen OA, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Hauger RL, Jak AJ, Neale MC, Tu XM, Whitsel N, Xian H, Kremen WS, Lyons MJ. Associations between depression and cardiometabolic health: A 27-year longitudinal study. Psychol Med 2022; 52:3007-3017. [PMID: 33431106 PMCID: PMC8547283 DOI: 10.1017/s003329172000505x] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems. METHODS The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse ('baseline') and the longitudinal Vietnam Era Twin Study of Aging ('follow-up'). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)]. RESULTS Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07-1.57), erectile dysfunction (OR 1.32, 95% CI 1.10-1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04-1.53), and sleep apnea (OR 1.40, 95% CI 1.13-1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09-1.60). CONCLUSIONS A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
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Affiliation(s)
- Hillary L. Ditmars
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Mark W. Logue
- Research Service, VA Boston Healthcare System, Boston, MA
- Biomedical Genetics Program, Boston University School of Medicine, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Ruth E. McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Carol E. Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Matthew S. Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA
| | - Kristy N. Cuthbert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Richard Vandiver
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | | | - Graham M. L. Eglit
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- VA San Diego Healthcare System, San Diego, CA
| | - Jeremy A. Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - McKenna E. Williams
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - Ole A. Andreassen
- NORMENT, 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, Oslo, Norway
| | - Anders M. Dale
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Lisa T. Eyler
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Christine Fennema-Notestine
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Nathan A. Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Richard L. Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Amy J. Jak
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael C. Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Xin M. Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA
| | - Nathan Whitsel
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice
| | - William S. Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
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49
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Zhang MJ, Hou K, Dey KK, Sakaue S, Jagadeesh KA, Weinand K, Taychameekiatchai A, Rao P, Pisco AO, Zou J, Wang B, Gandal M, Raychaudhuri S, Pasaniuc B, Price AL. Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data. Nat Genet 2022; 54:1572-1580. [PMID: 36050550 PMCID: PMC9891382 DOI: 10.1038/s41588-022-01167-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 07/19/2022] [Indexed: 02/03/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an approach that links scRNA-seq with polygenic disease risk at single-cell resolution, independent of annotated cell types. scDRS identifies cells exhibiting excess expression across disease-associated genes implicated by genome-wide association studies (GWASs). We applied scDRS to 74 diseases/traits and 1.3 million single-cell gene-expression profiles across 31 tissues/organs. Cell-type-level results broadly recapitulated known cell-type-disease associations. Individual-cell-level results identified subpopulations of disease-associated cells not captured by existing cell-type labels, including T cell subpopulations associated with inflammatory bowel disease, partially characterized by their effector-like states; neuron subpopulations associated with schizophrenia, partially characterized by their spatial locations; and hepatocyte subpopulations associated with triglyceride levels, partially characterized by their higher ploidy levels. Genes whose expression was correlated with the scDRS score across cells (reflecting coexpression with GWAS disease-associated genes) were strongly enriched for gold-standard drug target and Mendelian disease genes.
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Affiliation(s)
- Martin Jinye Zhang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Kushal K Dey
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Saori Sakaue
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Karthik A Jagadeesh
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kathryn Weinand
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Aris Taychameekiatchai
- Department of Medicine and Liver Center, University of California, San Francisco, San Francisco, CA, USA
- Developmental and Stem Cell Biology Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Poorvi Rao
- Department of Medicine and Liver Center, University of California, San Francisco, San Francisco, CA, USA
| | | | - James Zou
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, USA
- Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA
| | - Bruce Wang
- Department of Medicine and Liver Center, University of California, San Francisco, San Francisco, CA, USA
| | - Michael Gandal
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Soumya Raychaudhuri
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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50
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Keyes KM, Susser E. Uses and misuses of sibling designs. Int J Epidemiol 2022; 52:336-341. [PMID: 36130236 DOI: 10.1093/ije/dyac187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 09/19/2022] [Indexed: 11/15/2022] Open
Affiliation(s)
- Katherine M Keyes
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ezra Susser
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.,New York State Psychiatric Institute, New York, NY, USA
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