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Baek JH, Lee D, Lee D, Jeong H, Cho EY, Ha TH, Ha K, Hong KS. Exploring intra-diagnosis heterogeneity and inter-diagnosis commonality in genetic architectures of bipolar disorders: association of polygenic risks of major psychiatric illnesses and lifetime phenotype dimensions. Psychol Med 2024:1-7. [PMID: 38813618 DOI: 10.1017/s003329172400120x] [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: 05/31/2024]
Abstract
BACKGROUND Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses. METHODS Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed. RESULTS Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028). CONCLUSION This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry.
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Affiliation(s)
- Ji Hyun Baek
- Department of Psychiatry, Sunkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea
- Dauten Family Center for Bipolar Treatment Innovation, Massachusetts General Hospital, Boston, USA
| | - Dongbin Lee
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, Korea
| | - Dongeun Lee
- Department of Psychiatry, Sunkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Hyewon Jeong
- Samsung Biomedical Research Institute, Seoul, Republic of Korea
| | - Eun-Young Cho
- Samsung Biomedical Research Institute, Seoul, Republic of Korea
| | - Tae Hyon Ha
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Kyooseob Ha
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Psychiatry, Lions Gate Hospital - Vancouver Coastal Health Authority, British Columbia, Canada
| | - Kyung Sue Hong
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Psychiatry, Lions Gate Hospital - Vancouver Coastal Health Authority, British Columbia, Canada
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2
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Chen J, Sun L, Yu K, Batmanghelich K. Extracting Disease-Relevant Features with Adversarial Regularization. PROCEEDINGS. IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE 2021; 2021:3464-3471. [PMID: 35198261 PMCID: PMC8863436 DOI: 10.1109/bibm52615.2021.9669878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Extracting hidden phenotypes is essential in medical data analysis because it facilitates disease subtyping, diagnosis, and understanding of disease etiology. Since the hidden phenotype is usually a low-dimensional representation that comprehensively describes the disease, we require a dimensionality-reduction method that captures as much disease-relevant information as possible. However, most unsupervised or self-supervised methods cannot achieve the goal because they learn a holistic representation containing both disease-relevant and disease-irrelevant information. Supervised methods can capture information that is predictive to the target clinical variable only, but the learned representation is usually not generalizable for the various aspects of the disease. Hence, we develop a dimensionality-reduction approach to extract Disease Relevant Features (DRFs) based on information theory. We propose to use clinical variables that weakly define the disease as so-called anchors. We derive a formulation that makes the DRF predictive of the anchors while forcing the remaining representation to be irrelevant to the anchors via adversarial regularization. We apply our method to a large-scale study of Chronic Obstructive Pulmonary Disease (COPD). Our experiment shows: (1) Learned DRFs are as predictive as the original representation in predicting the anchors, although it is in a significantly lower dimension. (2) Compared to supervised representation, the learned DRFs are more predictive to other relevant disease metrics that are not used during the training. (3) The learned DRFs are related to non-imaging biological measurements such as gene expressions, suggesting the DRFs include information related to the underlying biology of the disease.
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Affiliation(s)
- Junxiang Chen
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Li Sun
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Ke Yu
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Kayhan Batmanghelich
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
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3
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Pol-Fuster J, Cañellas F, Ruiz-Guerra L, Medina-Dols A, Bisbal-Carrió B, Ortega-Vila B, Llinàs J, Hernandez-Rodriguez J, Lladó J, Olmos G, Strauch K, Heine-Suñer D, Vives-Bauzà C, Flaquer A. The conserved ASTN2/BRINP1 locus at 9q33.1-33.2 is associated with major psychiatric disorders in a large pedigree from Southern Spain. Sci Rep 2021; 11:14529. [PMID: 34267256 PMCID: PMC8282839 DOI: 10.1038/s41598-021-93555-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 06/21/2021] [Indexed: 11/11/2022] Open
Abstract
We investigated the genetic causes of major mental disorders (MMDs) including schizophrenia, bipolar disorder I, major depressive disorder and attention deficit hyperactive disorder, in a large family pedigree from Alpujarras, South of Spain, a region with high prevalence of psychotic disorders. We applied a systematic genomic approach based on karyotyping (n = 4), genotyping by genome-wide SNP array (n = 34) and whole-genome sequencing (n = 12). We performed genome-wide linkage analysis, family-based association analysis and polygenic risk score estimates. Significant linkage was obtained at chromosome 9 (9q33.1–33.2, LOD score = 4.11), a suggestive region that contains five candidate genes ASTN2, BRINP1, C5, TLR4 and TRIM32, previously associated with MMDs. Comprehensive analysis associated the MMD phenotype with genes of the immune system with dual brain functions. Moreover, the psychotic phenotype was enriched for genes involved in synapsis. These results should be considered once studying the genetics of psychiatric disorders in other families, especially the ones from the same region, since founder effects may be related to the high prevalence.
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Affiliation(s)
- Josep Pol-Fuster
- Department of Biology, University of Balearic Islands (UIB), Institut Universitari d'Investigacions en Ciències de la Salut (IUNICS), Palma, Spain.,Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain
| | - Francesca Cañellas
- Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain.,Department of Psychiatry, HUSE, IdISBa, Palma, Spain
| | - Laura Ruiz-Guerra
- Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain
| | - Aina Medina-Dols
- Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain
| | - Bàrbara Bisbal-Carrió
- Department of Biology, University of Balearic Islands (UIB), Institut Universitari d'Investigacions en Ciències de la Salut (IUNICS), Palma, Spain.,Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain
| | - Bernat Ortega-Vila
- Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain.,Molecular Diagnostics and Clinical Genetics Unit (UDMGC) and Genomics of Health Research Group, Hospital Universitari Son Espases (HUSE) and Institut d'Investigacions Sanitaries de Balears (IDISBA), Palma, Spain
| | - Jaume Llinàs
- Department of Biology, University of Balearic Islands (UIB), Institut Universitari d'Investigacions en Ciències de la Salut (IUNICS), Palma, Spain
| | - Jessica Hernandez-Rodriguez
- Molecular Diagnostics and Clinical Genetics Unit (UDMGC) and Genomics of Health Research Group, Hospital Universitari Son Espases (HUSE) and Institut d'Investigacions Sanitaries de Balears (IDISBA), Palma, Spain
| | - Jerònia Lladó
- Department of Biology, University of Balearic Islands (UIB), Institut Universitari d'Investigacions en Ciències de la Salut (IUNICS), Palma, Spain.,Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain
| | - Gabriel Olmos
- Department of Biology, University of Balearic Islands (UIB), Institut Universitari d'Investigacions en Ciències de la Salut (IUNICS), Palma, Spain.,Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain
| | - Konstantin Strauch
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, LMU Munich, Munich, Germany
| | - Damià Heine-Suñer
- Molecular Diagnostics and Clinical Genetics Unit (UDMGC) and Genomics of Health Research Group, Hospital Universitari Son Espases (HUSE) and Institut d'Investigacions Sanitaries de Balears (IDISBA), Palma, Spain
| | - Cristòfol Vives-Bauzà
- Department of Biology, University of Balearic Islands (UIB), Institut Universitari d'Investigacions en Ciències de la Salut (IUNICS), Palma, Spain. .,Neurobiology Laboratory, Research Unit, Son Espases University Hospital (HUSE), Health Research Institute of Balearic Islands (IdISBa), Floor -1, Module F, R-805, Palma, Spain.
| | - Antònia Flaquer
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, LMU Munich, Munich, Germany
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4
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Common variants in CREB1 gene confer risk for bipolar disorder in Han Chinese. Asian J Psychiatr 2021; 59:102648. [PMID: 33848807 DOI: 10.1016/j.ajp.2021.102648] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/23/2021] [Accepted: 04/05/2021] [Indexed: 12/25/2022]
Abstract
Recently, we have identified involvement of the gene encoding cAMP responsive element-binding 1 (CREB1) in risk of BD in European ancestry. CREB1 has significant genetic diversity between Europeans and Chinese, thereby resulting in diverged CREB1 genetic backgrounds. In this study, we aimed to determine whether CREB1 confers susceptibility to BD and cognitive dysfunction in Han Chinese. We recruited 572 patients with BD and 611 healthy controls for genetic study. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was used for cognitive evaluation. SNP rs10932201 and rs3770704 within CREB1 were genotyped. The frequency of the G allele of rs10932201 was significantly greater in BD patients (41.8 %) than that in control subjects (37.2 %), with P = 0.02, corrected P = 0.04. There were significant differences in the scores of RBANS attention and total scores between the patients with different genotypes of rs10932201 polymorphism (P = 0.002 and 0.003, corrected P = 0.012 and 0.018, respectively). Post-hoc comparisons showed that rs10932201 G/G or G/A carriers had lower RBANS attention and total scores than those with A/A carriers (P = 0.002 and 0.004, P = 0.002 and 0.006, respectively). We observed a significant association between the rs10932201 and CREB1 expression in intralobular white matter (P = 0.037). Carriers with G allele have significantly lower levels of CREB1 expression in intralobular white matter than those without G allele. In conclusion, this study identified a novel BD risk SNP rs10932201 in Han Chinese and this SNP may be a risk factor for cognitive dysfunction in patients with BD.
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Kibitov AO, Mazo GE. [Anhedonia in depression: neurobiological and genetic aspects]. Zh Nevrol Psikhiatr Im S S Korsakova 2021; 121:146-154. [PMID: 33834733 DOI: 10.17116/jnevro2021121031146] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Anhedonia is indeed a pathogenetically important clinical phenotype and a promising endophenotype for depressive symptoms with a very high contribution of biological and genetic factors. Neurobiological mechanisms of anhedonia are impaired functioning of the reward system of the brain, which is confirmed by many neuroimaging, genetic and experimental studies. Anhedonia has a trans-diagnoctic character and should be understood as a complex phenomenon, and it is important to correctly evaluate it within the framework of a particular research paradigm. It seems optimal to form several complementary research strategies that evaluate the most important «facets» of anhedonia, regardless of the nosological form of the disease, within the framework of one study using various methods to search for adequate biomarkers of anhedonia severity (genetic, neuroimaging, biochemical). Given the high-quality organization of such comprehensive studies based on the correct methodology of evidence-based medicine, it is likely that significant biomarker systems will be available in the near future, which, if replicated in independent samples, can be used to personalize the diagnosis and treatment of depression.
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Affiliation(s)
- A O Kibitov
- Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia.,Serbsky National Medical Research Center on Psychiatry and Addictions, Moscow, Russia
| | - G E Mazo
- Bekhterev National Medical Research Center for Psychiatry and Neurology, St. Petersburg, Russia
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6
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Baek JH, Ha K, Kim Y, Cho YA, Yang SY, Choi Y, Jang SL, Park T, Ha TH, Hong KS. Psychopathologic structure of bipolar disorders: exploring dimensional phenotypes, their relationships, and their associations with bipolar I and II disorders. Psychol Med 2019; 49:2177-2185. [PMID: 30326977 DOI: 10.1017/s003329171800301x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND Given its diverse disease courses and symptom presentations, multiple phenotype dimensions with different biological underpinnings are expected with bipolar disorders (BPs). In this study, we aimed to identify lifetime BP psychopathology dimensions. We also explored the differing associations with bipolar I (BP-I) and bipolar II (BP-II) disorders. METHODS We included a total of 307 subjects with BPs in the analysis. For the factor analysis, we chose six variables related to clinical courses, 29 indicators covering lifetime symptoms of mood episodes, and 6 specific comorbid conditions. To determine the relationships among the identified phenotypic dimensions and their effects on differentiating BP subtypes, we applied structural equation modeling. RESULTS We selected a six-factor solution through scree plot, Velicer's minimum average partial test, and face validity evaluations; the six factors were cyclicity, depression, atypical vegetative symptoms, elation, psychotic/irritable mania, and comorbidity. In the path analysis, five factors excluding atypical vegetative symptoms were associated with one another. Cyclicity, depression, and comorbidity had positive associations, and they correlated negatively with psychotic/irritable mania; elation showed positive correlations with cyclicity and psychotic/irritable mania. Depression, cyclicity, and comorbidity were stronger in BP-II than in BP-I, and they contributed significantly to the distinction between the two disorders. CONCLUSIONS We identified six phenotype dimensions; in addition to symptom features of manic and depressive episodes, various comorbidities and high cyclicity constructed separate dimensions. Except for atypical vegetative symptoms, all factors showed a complex interdependency and played roles in discriminating BP-II from BP-I.
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Affiliation(s)
- Ji Hyun Baek
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Kyooseob Ha
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
- Institute of Human Behavioral Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Yongkang Kim
- Department of Statistics, Seoul National University, Seoul, Korea
| | - Young-Ah Cho
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - So Yung Yang
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yujin Choi
- Samsung Biomedical Research Institute, Seoul, Korea
| | | | - Taesung Park
- Department of Statistics, Seoul National University, Seoul, Korea
| | - Tae Hyon Ha
- Department of Psychiatry, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
| | - Kyung Sue Hong
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Samsung Biomedical Research Institute, Seoul, Korea
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7
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Voinsky I, McCarthy MJ, Shekhtman T, Kelsoe JR, Gurwitz D. SCN11A mRNA levels in female bipolar disorder PBMCs as tentative biomarker for distinct patient sub-phenotypes. Drug Dev Res 2019; 80:1128-1135. [PMID: 31498915 DOI: 10.1002/ddr.21598] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 08/20/2019] [Accepted: 08/20/2019] [Indexed: 01/12/2023]
Abstract
Bipolar disorder (BD) is a complex neuropsychiatric disorder characterized by recurrent mania and depression episodes and requiring lifelong treatment with mood stabilizing drugs. Several lines of evidence, including with BD patient iPSC-derived neurons, suggest that neuronal hyperexcitability may underlie the key clinical symptoms of BD. Indeed, higher mRNA levels of SCN11A, coding for the voltage-gated sodium channel NaV 1.9 implicated in nociception, were detected in iPSC-derived neurons from BD patients, and were normalized by in vitro lithium. Here we studied SCN11A expression in peripheral blood mononuclear cells (PBMCs) from well-phenotyped female BD patients and controls and evaluated their association with several clinical sub-phenotypes. We observed higher mRNA levels of SCN11A in PBMCs from female BD patients with no records of alcohol dependence (p = .0050), no records of psychosis (p = .0097), or no records of suicide attempts (p = .0409). A trend was observed for higher SCN11A expression (FD = 1.91; p = .052) in BD PBMCs compared with controls. Datamining of published postmortem gene expression datasets indicated higher SCN11A expression in dorsolateral prefrontal cortex and orbitofrontal cortex tissues from BD patients compared with controls. Higher phenotype-associated expression levels in PBMC from BD patients were also observed for ID2 (alcohol dependence, suicide attempts) and HDGFRP3 (seasonal BD pattern). Our findings suggest that higher PBMC SCN11A expression levels may be associated with certain behavioral BD sub-phenotypes, including lack of alcohol dependence and psychosis, among BD patients. The NaV 1.9 voltage-gated sodium channel thus deserves consideration as a tentative phenotype modifier in BD.
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Affiliation(s)
- Irena Voinsky
- Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel
| | - Michael J McCarthy
- Department of Psychiatry, University of California San Diego, La Jolla, California.,VA San Diego Healthcare System, San Diego, California
| | - Tatyana Shekhtman
- Department of Psychiatry, University of California San Diego, La Jolla, California
| | - John R Kelsoe
- Department of Psychiatry, University of California San Diego, La Jolla, California
| | - David Gurwitz
- Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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8
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Anderson-Schmidt H, Gade K, Malzahn D, Papiol S, Budde M, Heilbronner U, Reich-Erkelenz D, Adorjan K, Kalman JL, Senner F, Comes AL, Flatau L, Gryaznova A, Hake M, Reitt M, Schmauß M, Juckel G, Reimer J, Zimmermann J, Figge C, Reininghaus E, Anghelescu IG, Konrad C, Thiel A, von Hagen M, Koller M, Stierl S, Scherk H, Spitzer C, Folkerts H, Becker T, Dietrich DE, Andlauer TFM, Degenhardt F, Nöthen MM, Witt SH, Rietschel M, Wiltfang J, Falkai P, Schulze TG. The influence of religious activity and polygenic schizophrenia risk on religious delusions in schizophrenia. Schizophr Res 2019; 210:255-261. [PMID: 30611655 DOI: 10.1016/j.schres.2018.12.025] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 11/28/2018] [Accepted: 12/16/2018] [Indexed: 01/12/2023]
Abstract
BACKGROUND Religious delusions are a common symptom in patients experiencing psychosis, with varying prevalence rates of religious delusions across cultures and societies. To enhance our knowledge of this distinct psychotic feature, we investigated the mutually-adjusted association of genetic and environmental factors with occurrence of religious delusions. METHODS We studied 262 adult German patients with schizophrenia or schizoaffective disorder. Association with lifetime occurrence of religious delusions was tested by multiple logistic regression for the following putative predictors: self-reported degree of religious activity, DSM-IV diagnosis, sex, age, education level, marital status, presence of acute delusion at the time of interview and an individual polygenic schizophrenia-risk score (SZ-PRS, available in 239 subjects). RESULTS Of the 262 patients, 101 (39%) had experienced religious delusions. The risk of experiencing religious delusions was significantly increased in patients with strong religious activity compared to patients without religious affiliation (OR = 3.6, p = 0.010). Low or moderate religious activity had no significant effect. The same analysis including the SZ-PRS confirmed the effect of high religious activity on occurrence of religious delusions (OR = 4.1, p = 0.008). Additionally, the risk of experiencing religious delusions increased with higher SZ-PRS (OR 1.4, p = 0.020, using pT = 0.05 for SZ-PRS calculation). None of the other variables were significantly associated with lifetime occurrence of religious delusions. CONCLUSIONS Our results suggest that strong religious activity and high SZ-PRS are independent risk factors for the occurrence of religious delusions in schizophrenia and schizoaffective disorder.
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Affiliation(s)
- Heike Anderson-Schmidt
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen 37075, Germany.
| | - Katrin Gade
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen 37075, Germany
| | - Dörthe Malzahn
- Department of Genetic Epidemiology, University Medical Center Göttingen, Georg-August-University, Göttingen 37099, Germany
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich 80336, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany
| | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich 80336, Germany
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich 80336, Germany; International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich 80336, Germany
| | - Ashley L Comes
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Laura Flatau
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany
| | - Anna Gryaznova
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany
| | - Maria Hake
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany
| | - Markus Reitt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen 37075, Germany
| | - Max Schmauß
- Department of Psychiatry and Psychotherapy, Bezirkskrankenhaus Augsburg, Augsburg 86156, Germany
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum 44791, Germany
| | - Jens Reimer
- Department of Psychiatry, Klinikum Bremen-Ost, Bremen 28325, Germany
| | - Jörg Zimmermann
- Department of Psychiatry, Klinikum Bremen-Ost, Bremen 28325, Germany; Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg 26160, Germany
| | - Christian Figge
- Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg 26160, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz 8036, Austria
| | | | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg 27356, Germany
| | - Andreas Thiel
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg 27356, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege 37269, Germany
| | - Manfred Koller
- Asklepios Specialized Hospital, Göttingen 37081, Germany
| | | | - Harald Scherk
- AMEOS Clinical Center Osnabrück, Osnabrück 49088, Germany
| | - Carsten Spitzer
- ASKLEPIOS Specialized Hospital Tiefenbrunn, Rosdorf 37124, Germany
| | - Here Folkerts
- Department of Psychiatry, Psychotherapy and Psychosomatics, Clinical Center Wilhelmshaven, Wilhelmshaven 26389, Germany
| | - Thomas Becker
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg 89312, Germany
| | - Detlef E Dietrich
- AMEOS Clinical Center Hildesheim, Hildesheim 31135, Germany; Center for Systems Neuroscience (ZSN), Hannover 30559, Germany
| | - Till F M Andlauer
- Department of Translational Psychiatry, Max Planck Institute of Psychiatry, Munich 80804, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn 53127, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn 53127, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn 53127, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn 53127, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim 68159, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim 68159, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen 37075, Germany; German Center for Neurodegenerative Diseases (DZNE), Göttingen 37075, Germany; iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich 80336, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich 80336, Germany; Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen 37075, Germany
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9
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Szczepankiewicz A, Narozna B, Rybakowski JK, Kliwicki S, Czerski P, Dmitrzak-Węglarz M, Skibińska M, Twarowska-Hauser J, Pawlak J. Genes involved in stress response influence lithium efficacy in bipolar patients. Bipolar Disord 2018; 20:753-760. [PMID: 29578315 DOI: 10.1111/bdi.12639] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVES In mood disorders, chronic stimulation with stress results in aberrant regulation of the hypothalamic-pituitary-adrenal (HPA) axis. Lithium was shown to influence HPA axis function. The underlying genetic background as well as environmental context may influence the stress response, and therefore lithium efficacy. The aim of the present study was to analyze if genetic variants located in genes involved in HPA axis regulation affect the response to long-term lithium treatment in bipolar patients. METHODS We included 93 patients with bipolar disorder (32 males and 61 females), aged 31-80 years. The patients had been treated with lithium carbonate for at least 5 years. The magnitude of the lithium response was assessed using the Alda scale. Genotyping was performed for 28 polymorphisms in the genes encoding the following proteins involved in HPA axis regulation: corticotropin-releasing hormone receptor 1 (CRHR1), arginine vasopressin receptor 1B (AVPR1b), FK506 binding protein (FKBP) 5, FKBP4, BCL2-associated athanogene 1 (BAG1), stress induced phosphoprotein 1 (STIP1), glucocorticoid-induced transcript 1 (GLCC1), dual specificity phosphatase 1 (DUSP1) serine and arginine rich splicing factor (SRSF) 3, SRSF9, SRSF5, and acid phosphatase 1 (ACP1). Linkage disequilibrium and haplotype analysis were then performed, followed by statistical analysis (Statistica v.12; Stasoft, Krakow, Poland). RESULTS We found a correlation between stressful life events at first episode and worse response to lithium (P=.019). In single marker analysis, we observed a significant association between three FKBP5 polymorphisms (rs1360780, rs7748266 and rs9296158), one ACP1 variant (rs300774) and one glucocorticoid-induced transcript 1 gene (GLCC1) variant (rs37972) and the degree of lithium response. Five out of seven FKBP5 polymorphisms showed strong linkage with one haplotype demonstrating an association with lithium efficacy (P=.008). No relationship was found between the other analyzed polymorphisms and lithium response. CONCLUSION The response to lithium may depend on the variants of genes regulating the HPA axis and stressful life events in bipolar patients.
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Affiliation(s)
| | - Beata Narozna
- Laboratory of Molecular and Cell Biology, Poznan University of Medical Sciences, Poznan, Poland
| | - Janusz K Rybakowski
- Department of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland
| | - Sebastian Kliwicki
- Department of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland
| | - Piotr Czerski
- Deparment of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland
| | | | - Maria Skibińska
- Deparment of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland
| | | | - Joanna Pawlak
- Deparment of Psychiatric Genetics, Poznan University of Medical Sciences, Poznan, Poland
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10
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Abstract
BACKGROUND Genetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. METHODS We assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). RESULTS We identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). LIMITATIONS Since confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. CONCLUSIONS We conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety.
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11
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The interaction of GSK3B and FXR1 genotypes may influence the mania and depression dimensions in mood disorders. J Affect Disord 2017; 213:172-177. [PMID: 28242499 DOI: 10.1016/j.jad.2017.02.023] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 02/15/2017] [Indexed: 11/24/2022]
Abstract
BACKGROUND Previous evidence in healthy subjects suggested that functional polymorphisms GSK3B rs12630592 and FXR1 rs496250 interact in regulating mood and emotional processing. We attempted to replicate this interaction primarily on manic and depressive dimensions in mood disorder patients, and secondarily on schizophrenia patients, diagnosis itself and age of onset. METHODS Symptom dimensions were derived from the Comprehensive Assessment of Symptoms and History 82 items rated lifetime in acute episodes and stabilized interepisode intervals in 384 patients from the Schizophrenia and Bipolar Disorder Eastern Quebec Kindred Study. Linear mixed effect models of symptom dimensions included rs12630592-rs496250 main and interaction fixed effects (obtained from TaqMan genotypes), and a polygenic random effect. The distribution of lifetime best-estimate DSM-IV diagnosis of 855 kindred members was studied versus genotype under a polytomous logistic model. RESULTS In mood disorder patients, the level of mania (in both acute and stabilized periods) and depression in stabilized periods was positively associated with GSK3B rs12630592 T only in FXR1 rs496250 A-allele carriers (Bonferroni-corrected interaction p=0.024, 0.052 and 0.017 respectively). The two polymorphisms explained 11% of mania variance and 5% of interepisode depression variance. The association was observed neither in schizophrenia patients nor with the psychotic dimension in mood disorder patients. Interaction with the diagnosis distribution (p=0.03) was driven by the decreasing prevalence of recurrent major depression with rs12630592 T also only in carriers of rs496250 A. LIMITATIONS Sample size was limited, but power was sufficient to detect the tested interaction effect in this replication sample. CONCLUSIONS We replicate in affective patients an interaction between the FXR1 rs496250 and GSK3B rs12630592 polymorphisms in regulating mood dimensions.
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12
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Jiang J, Long J, Ling W, Huang G, Su L. Genetic variation in the 3'-untranslated region of PAK1 influences schizophrenia susceptibility. Exp Ther Med 2017; 13:1101-1108. [PMID: 28450949 DOI: 10.3892/etm.2017.4039] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2013] [Accepted: 08/23/2016] [Indexed: 12/23/2022] Open
Abstract
The present study aimed to investigate the association of two polymorphisms (rs2844337 and rs11237200) in the P21 protein (cell division control protein 42/Rac)-activated kinase 1 gene with susceptibility to schizophrenia (SCZ) in Chinese Zhuang and Chinese Han populations. A total of 700 patients with SCZ and 700 healthy controls were recruited. Rs2844337 and rs11237200 polymorphisms were genotyped using Sequenom technology. A total of 591 patients completed the Positive and Negative Syndrome Scale (PANSS) assessment. Data were statistically analyzed using PLINK version 1.07 and SPSS version 17.0. In the Chinese Han population, the genotypic (P=0.038) and allelic (P=0.033) frequencies of the 3'-untranslated region (UTR) genetic variation of rs2844337 in patients were significantly decreased compared to that in controls; these frequencies were significantly associated with SCZ susceptibility in the additive model (Padj=0.032) and in the recessive model (Padj=0.031). Moreover, the TG haplotype constructed by rs2844337 and rs11237200 polymorphisms remained significantly associated with SCZ risk following adjustment for gender and age and applying a Bonferroni correction in the Chinese Han population (Padj=0.003, PBC=0.009). The adjacent 5'-UTR genetic variation of rs11237200 was significantly associated with the total score (Padj=0.006), positive scale score (Padj=0.014) and general psychopathology scale scores (Padj=0.009) in the recessive model of the Chinese Han population. However, these polymorphisms were not significantly associated with SCZ susceptibility or the PANSS scores in the Chinese Zhuang population. In conclusion, variations in the PAK1 gene influenced the susceptibility and severity of the clinical symptoms of SCZ in the Chinese Han population investigated in the present study.
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Affiliation(s)
- Juan Jiang
- Department of Epidemiology, School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jianxiong Long
- Department of Epidemiology, School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Weijun Ling
- Department of Epidemiology, School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Guifeng Huang
- Department of Epidemiology, School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Li Su
- Department of Epidemiology, School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
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13
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Beaulieu-Jones BK, Greene CS. Semi-supervised learning of the electronic health record for phenotype stratification. J Biomed Inform 2016; 64:168-178. [PMID: 27744022 DOI: 10.1016/j.jbi.2016.10.007] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Revised: 10/05/2016] [Accepted: 10/08/2016] [Indexed: 12/12/2022]
Abstract
Patient interactions with health care providers result in entries to electronic health records (EHRs). EHRs were built for clinical and billing purposes but contain many data points about an individual. Mining these records provides opportunities to extract electronic phenotypes, which can be paired with genetic data to identify genes underlying common human diseases. This task remains challenging: high quality phenotyping is costly and requires physician review; many fields in the records are sparsely filled; and our definitions of diseases are continuing to improve over time. Here we develop and evaluate a semi-supervised learning method for EHR phenotype extraction using denoising autoencoders for phenotype stratification. By combining denoising autoencoders with random forests we find classification improvements across multiple simulation models and improved survival prediction in ALS clinical trial data. This is particularly evident in cases where only a small number of patients have high quality phenotypes, a common scenario in EHR-based research. Denoising autoencoders perform dimensionality reduction enabling visualization and clustering for the discovery of new subtypes of disease. This method represents a promising approach to clarify disease subtypes and improve genotype-phenotype association studies that leverage EHRs.
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Affiliation(s)
- Brett K Beaulieu-Jones
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, United States; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, United States.
| | - Casey S Greene
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States; Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Perelman School of Medicine, University of Pennsylvania, United States.
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14
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Frydecka D, Beszłej JA, Pawlak-Adamska E, Misiak B, Karabon L, Tomkiewicz A, Partyka A, Jonkisz A, Szewczuk-Bogusławska M, Zawadzki M, Kiejna A. CTLA4 and CD28 Gene Polymorphisms with Respect to Affective Symptom Domain in Schizophrenia. Neuropsychobiology 2016; 71:158-67. [PMID: 25998553 DOI: 10.1159/000379751] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 02/02/2015] [Indexed: 11/19/2022]
Abstract
BACKGROUND Accumulating evidence indicates that immune alterations in schizophrenia are due to genetic underpinnings. Here, we aimed at investigating whether polymorphisms in CTLA4 and CD28 genes, encoding molecules that regulate T-cell activity, influence schizophrenia symptomatology. METHOD We recruited 120 schizophrenia patients and 380 healthy age- and sex-matched controls. We divided the patients into two groups: one with no co-occurrence between psychotic and affective symptoms and the second one with psychotic symptoms dominating in the clinical manifestation, although also with occasional affective disturbances in the course of illness. RESULTS Among the patients with co-occurring affective symptoms, there were significantly more CTLA4 c.49A>G[A] alleles (p = 0.018, odds ratio (OR) 2.03, 95% confidence interval (CI) 1.2-3.66) and more CTLA4 g.319C>T[T] alleles (p = 0.07, OR 1.93, 95% CI 0.94-4.13) in comparison to the second group. Additionally, we have shown that CD28 c.17 + 3T>C[C+] were more significantly overrepresented among patients with co-occurring psychotic and affective symptoms (p = 0.0003, OR 3.36, 95% CI 1.69-6.68) than in patients without co-occurence between these symptoms (p = 0.012, OR 1.88, 95% CI 1.15-3.10). CONCLUSION CTLA4 and CD28 gene polymorphisms may not only act in immune deregulation observed in schizophrenia, but may also influence the course of the illness by modifying the susceptibility to the co-occurrence of psychotic and affective symptoms.
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Affiliation(s)
- Dorota Frydecka
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
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15
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Kennedy KP, Cullen KR, DeYoung CG, Klimes-Dougan B. The genetics of early-onset bipolar disorder: A systematic review. J Affect Disord 2015; 184:1-12. [PMID: 26057335 PMCID: PMC5552237 DOI: 10.1016/j.jad.2015.05.017] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Revised: 04/20/2015] [Accepted: 05/07/2015] [Indexed: 01/19/2023]
Abstract
BACKGROUND Early-onset bipolar disorder has been associated with a significantly worse prognosis than late-onset BD and has been hypothesized to be a genetically homogenous subset of BD. A sizeable number of studies have investigated early-onset BD through linkage-analyses, candidate-gene association studies, genome-wide association studies (GWAS), and analyses of copy number variants (CNVs), but this literature has not yet been reviewed. METHODS A systematic review was conducted using the PubMed database on articles published online before January 15, 2015 and after 1990. Separate searches were made for linkage studies, candidate gene-association studies, GWAS, and studies on CNVs. RESULTS Seventy-three studies were included in our review. There is a lack of robust positive findings on the genetics of early-onset BD in any major molecular genetics method. LIMITATIONS Early-onset populations were quite small in some studies. Variance in study methods hindered efforts to interpret results or conduct meta-analysis. CONCLUSIONS The field is still at an early phase for research on early-onset BD. The largely null findings mirror the results of most genetics research on BD. Although most studies were underpowered, the null findings could mean that early-onset BD may not be as genetically homogenous as has been hypothesized or even that early-onset BD does not differ genetically from adult-onset BD. Nevertheless, clinically the probabilistic developmental risk trajectories associated with early-onset that may not be primarily genetically determined continued to warrant scrutiny. Future research should dramatically expand sample sizes, use atheoretical research methods like GWAS, and standardize methods.
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16
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TPH2 genotype is associated with PTSD’s avoidance symptoms in Chinese female earthquake survivors. Psychiatr Genet 2014; 24:257-61. [DOI: 10.1097/ypg.0000000000000048] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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17
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Cao C, Wang L, Wang R, Qing Y, Zhang J, Wu GWY. The COMT gene variant is associated with depression's decreased positive affect symptoms in Chinese adults. Psych J 2014; 3:264-72. [DOI: 10.1002/pchj.63] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Accepted: 07/15/2014] [Indexed: 11/07/2022]
Affiliation(s)
- Chengqi Cao
- Key Laboratory of Mental Health; Institute of Psychology; Chinese Academy of Sciences; Beijing China
- University of Chinese Academy of Sciences; Beijing China
| | - Li Wang
- Key Laboratory of Mental Health; Institute of Psychology; Chinese Academy of Sciences; Beijing China
| | - Richu Wang
- Key Laboratory of Mental Health; Institute of Psychology; Chinese Academy of Sciences; Beijing China
- University of Chinese Academy of Sciences; Beijing China
| | - Yulan Qing
- Key Laboratory of Mental Health; Institute of Psychology; Chinese Academy of Sciences; Beijing China
- University of Chinese Academy of Sciences; Beijing China
| | - Jianxin Zhang
- Key Laboratory of Mental Health; Institute of Psychology; Chinese Academy of Sciences; Beijing China
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Gonzalez S, Camarillo C, Rodriguez M, Ramirez M, Zavala J, Armas R, Contreras SA, Contreras J, Dassori A, Almasy L, Flores D, Jerez A, Raventós H, Ontiveros A, Nicolini H, Escamilla M. A genome-wide linkage scan of bipolar disorder in Latino families identifies susceptibility loci at 8q24 and 14q32. Am J Med Genet B Neuropsychiatr Genet 2014; 165B:479-91. [PMID: 25044503 DOI: 10.1002/ajmg.b.32251] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 05/27/2014] [Indexed: 12/14/2022]
Abstract
A genome-wide nonparametric linkage screen was performed to localize Bipolar Disorder (BP) susceptibility loci in a sample of 3757 individuals of Latino ancestry. The sample included 963 individuals with BP phenotype (704 relative pairs) from 686 families recruited from the US, Mexico, Costa Rica, and Guatemala. Non-parametric analyses were performed over a 5 cM grid with an average genetic coverage of 0.67 cM. Multipoint analyses were conducted across the genome using non-parametric Kong & Cox LOD scores along with Sall statistics for all relative pairs. Suggestive and significant genome-wide thresholds were calculated based on 1000 simulations. Single-marker association tests in the presence of linkage were performed assuming a multiplicative model with a population prevalence of 2%. We identified two genome-wide significant susceptibly loci for BP at 8q24 and 14q32, and a third suggestive locus at 2q13-q14. Within these three linkage regions, the top associated single marker (rs1847694, P = 2.40 × 10(-5)) is located 195 Kb upstream of DPP10 in Chromosome 2. DPP10 is prominently expressed in brain neuronal populations, where it has been shown to bind and regulate Kv4-mediated A-type potassium channels. Taken together, these results provide additional evidence that 8q24, 14q32, and 2q13-q14 are susceptibly loci for BP and these regions may be involved in the pathogenesis of BP in the Latino population.
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Affiliation(s)
- Suzanne Gonzalez
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas; Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas
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Lilienfeld SO. DSM‐5: Centripetal scientific and centrifugal antiscientific forces. CLINICAL PSYCHOLOGY-SCIENCE AND PRACTICE 2014. [DOI: 10.1111/cpsp.12075] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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20
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Yang Y, Li W, Yang G, Xiao B, Wang X, Ding M, Zhao J, Song X, Yue W, Zhang D, Zhang H, Lv L. Evaluation of the relationship between the ZNF804A single nucleotide polymorphism rs1344706 A/C variant and schizophrenia subtype in Han Chinese patients. Int J Psychiatry Med 2013; 45:269-78. [PMID: 24066410 DOI: 10.2190/pm.45.3.f] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Recent genome wide association studies (GWASs) assessing the relationship between schizophrenia (SZ) and the ZNF804A gene, particularly the single nucleotide polymorphism (SNP) rs1344706, have yielded conflicting results. Schizophrenia is a heterogeneous disorder, so it is possible that an association may be restricted to specific SZ subtypes and that population heterogeneity may obscure a contribution of ZNF804A allelic variation to SZ risk. We thus evaluated the association between rs1344706 and different clinical SZ subtypes in a large Han Chinese patient population. METHOD The rs1344706 genotype was determined in 1,025 SZ patients and 977 healthy controls using polymerase chain reaction restriction fragment length polymorphisms (PCR-RFLPs). The clinical SZ subtypes included paranoid, catatonic, disintegrated, and undifferentiated, diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition IV (DSM-IV). RESULTS No significant differences in genotype and allele frequencies were found between controls and either the total SZ population (A > C, chi2 = 4.339, 2.994; p = 0.227, 0.087, respectively) or paranoid SZ patients (chi2 = 2.053, 0.002; p = 0.562, 0.973, respectively). However, there was a significant association between genotype frequency and SZ subtype (chi2 = 12.632, p = 0.049). CONCLUSIONS We found no evidence that the ZNF804A SNP rs1344706 is a susceptibility locus for SZ. However, conflicting results from previous association studies may be due to genetic heterogeneity between different patient SZ subtypes.
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Affiliation(s)
- Yongfeng Yang
- The Second Affiliated Hospital of Xinxiang Medical University, China
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21
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Di Nicola M, De Risio L, Battaglia C, Camardese G, Tedeschi D, Mazza M, Martinotti G, Pozzi G, Niolu C, Di Giannantonio M, Siracusano A, Janiri L. Reduced hedonic capacity in euthymic bipolar subjects: a trait-like feature? J Affect Disord 2013; 147:446-50. [PMID: 23122985 DOI: 10.1016/j.jad.2012.10.004] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2012] [Revised: 10/04/2012] [Accepted: 10/05/2012] [Indexed: 11/27/2022]
Abstract
BACKGROUND The aim of our study was to assess hedonic capacity in euthymic bipolar subjects, identifying possible differences compared to remitted unipolar depressed patients and healthy controls. METHODS 107 subjects with bipolar disorders, 86 with major depressive disorder and 106 healthy controls, homogeneous with respect to demographic characteristics, were enrolled. The following scales were administered: the Snaith-Hamilton pleasure scale (SHAPS), the subscale for 'anhedonia/asociality' of the scale for the assessment of negative symptoms (SANS) and the visual analogue scale (VAS) for hedonic capacity. RESULTS Scores on SHAPS total, interests and social interactions, SANS 'anhedonia/asociality' and VAS were all significantly higher in affective disorder patients compared to healthy controls. No difference was found between clinical groups. 20.5% (n=22) of bipolar disorder subjects and 24.5% (n=21) of major depressed subjects showed a significant reduction in hedonic capacity (SHAPS total score ≥ 3), compared to 7.5% (n=8) of healthy controls (χ(2)=12.03; p=.002). LIMITATIONS Limitations include heterogeneity with respect to pharmacological status and longitudinal course (i.e., 'single' vs. 'recurrent' affective episodes). CONCLUSIONS The major finding of our study is that euthymic bipolar patients and remitted major depressed patients display residual anhedonic symptoms. This suggests that, in affective disorder patients, altered hedonic capacity could represent an enduring trait and that, possibly, dysfunctions in the neurobiological mechanisms underlying hedonic response and reward processing persist, irrespective of mood state.
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Affiliation(s)
- Marco Di Nicola
- Institute of Psychiatry and Psychology, Catholic University Medical School, Rome, Italy.
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