A novel method to identify high order gene-gene interactions in genome-wide association studies: Gene-based MDR

<p>Abstract</p> <p>Background</p> <p>Because common complex diseases are affected by multiple genes and environmental factors, it is essential to investigate gene-gene and/or gene-environment interactions to understand genetic architecture of complex diseases. After the great success of large scale genome-wide association (GWA) studies using the high density single nucleotide polymorphism (SNP) chips, the study of gene-gene interaction becomes a next challenge. Multifactor dimensionality reduction (MDR) analysis has been widely used for the gene-gene interaction analysis. In practice, however, it is not easy to perform high order gene-gene interaction analyses via MDR in genome-wide level because it requires exploring a huge search space and suffers from a computational burden due to high dimensionality.</p> <p>Results</p> <p>We propose dimensional reduction analysis, Gene-MDR analysis for the fast and efficient high order gene-gene interaction analysis. The proposed Gene-MDR method is composed of two-step applications of MDR: within- and between-gene MDR analyses. First, within-gene MDR analysis summarizes each gene effect via MDR analysis by combining multiple SNPs from the same gene. Second, between-gene MDR analysis then performs interaction analysis using the summarized gene effects from within-gene MDR analysis. We apply the Gene-MDR method to bipolar disorder (BD) GWA data from Wellcome Trust Case Control Consortium (WTCCC). The results demonstrate that Gene-MDR is capable of detecting high order gene-gene interactions associated with BD.</p> <p>Conclusion</p> <p>By reducing the dimension of genome-wide data from SNP level to gene level, Gene-MDR efficiently identifies high order gene-gene interactions. Therefore, Gene-MDR can provide the key to understand complex disease etiology.</p

Polarity of the First Episode and Time to Diagnosis of Bipolar I Disorder

Objective The current study explored the relationship between the polarity of the first episode and the timing of eventual diagnosis of bipolar I disorder, and associated clinical implications. Methods Twelve years of clinical data from the medical records of 258 inpatients meeting DSM-III-R or DSM-IV criteria for bipolar I disorder were analyzed. Subjects were divided into two groups according to the polarity of the first episode: those with depressive polarity (FE-D), and those with manic polarity (FE-M). Comparisons were made between the two groups on variables associated with the timing of diagnosis and related outcomes. Results In Population with bipolar I disorder, a significant longer time lapse from the first major mood episode to the confirmed diagnosis was associated with the FE-D group compared to the FE-M group [5.6 (+/- 6.1) vs. 2.5 (+/- 5.5) years, p<0.001]. FE-D subjects tended to have prior diagnoses of schizophrenia and major depressive disorder while FE-M subjects tended to have prior diagnoses of bipolar disorder and schizophrenia. A significantly higher rate of suicide attempts was associated with the FE-D group compared to the FE-M group (12.7 vs. 1.7%, p<0.001). Conclusion The results of this study indicate that first-episode depressive polarity is likely to be followed by a considerable delay until an eventual confirmed diagnosis of bipolar I disorder. Given that first-episode depressive patients are particularly vulnerable to unfavorable clinical Outcomes Such as suicide attempts, a more systematic approach is needed to differentiate bipolar disorder among depressed patients in their early stages.Rosa AR, 2008, J AFFECT DISORDERS, V107, P45, DOI 10.1016/j.jad.2007.07.021Chaudhury SR, 2007, J AFFECT DISORDERS, V104, P245, DOI 10.1016/j.jad.2007.02.022Berk M, 2007, J AFFECT DISORDERS, V103, P181, DOI 10.1016/j.jad.2007.01.027Benazzi F, 2007, LANCET, V369, P935GOODWIN FK, 2007, MANIC DEPRESSIVE ILLDaban C, 2006, COMPR PSYCHIAT, V47, P433, DOI 10.1016/j.comppsych.2006.03.009McElroy SL, 2006, BIPOLAR DISORD, V8, P596Kassem L, 2006, AM J PSYCHIAT, V163, P1754Colom F, 2006, J AFFECT DISORDERS, V93, P13, DOI 10.1016/j.jad.2006.01.032Perlis RH, 2005, AM J MANAG CARE, V11, pS271Perlis RH, 2005, BIOL PSYCHIAT, V58, P549, DOI 10.1016/j.biopsych.2005.07.029Gazalle FK, 2005, J AFFECT DISORDERS, V86, P313, DOI 10.1016/j.jad.2005.01.003Ghaemi SN, 2005, J AFFECT DISORDERS, V84, P273, DOI 10.1016/S0165-0327(03)00196-4Post JC, 2005, CURR OPIN ALLERGY CL, V5, P5Mitchell PB, 2004, BIPOLAR DISORD, V6, P530Goodwin FK, 2003, JAMA-J AM MED ASSOC, V290, P1467Morselli PL, 2003, BIPOLAR DISORD, V5, P265Daniels BA, 2003, J AFFECT DISORDERS, V75, P163, DOI 10.1016/S0165-0327(02)00041-1Baethge C, 2003, ACTA PSYCHIAT SCAND, V107, P260Hirschfeld RMA, 2003, J CLIN PSYCHIAT, V64, P161Goldberg JF, 2002, J CLIN PSYCHIAT, V63, P985Ghaemi SN, 2002, CAN J PSYCHIAT, V47, P125Suppes T, 2001, J AFFECT DISORDERS, V67, P45Hirsch M, 2001, YALE J CRIT, V14, P5Bowden CL, 2001, PSYCHIATR SERV, V52, P51Hirschfeld RMA, 2000, AM J PSYCHIAT, V157, P1873Ghaemi SN, 2000, J CLIN PSYCHIAT, V61, P804Perugi G, 2000, COMPR PSYCHIAT, V41, P13GHAEMI SN, 2000, J CLIN PSYCHIAT, V61, P809Ghaemi SN, 1999, J AFFECT DISORDERS, V52, P135Baldessarini RJ, 1999, J CLIN PSYCHIAT, V60, P77BALDESSARINI RJ, 1999, J CLIN PSYCHIAT S2, V60, P111LISH JD, 1994, J AFFECT DISORDERS, V31, P281WEHR TA, 1988, AM J PSYCHIAT, V145, P179

Comparison of serum protein profiles between major depressive disorder and bipolar disorder

Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders. Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted. Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p= 4.3 × 10− 6) and Rho-associated protein kinase 2 (t = 4.782, p= 8.0 × 10− 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t = -4.520, p= 1.5 × 10− 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different. Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.This study was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI17C0870), and a grant from the Ministry of Science, ICT, and Future Planning, Republic of Korea (grant number: NRF-2019M3C7A1030625). The funding body had no involvement in study design planning, data collection, analysis, interpretation of data in writing the manuscript

Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) collaborative update of CANMAT guidelines for the management of patients with bipolar disorder: Update 2013

The Canadian Network for Mood and Anxiety Treatments published guidelines for the management of bipolar disorder in 2005, with updates in 2007 and 2009. This third update, in conjunction with the International Society for Bipolar Disorders, reviews new evidence and is designed to be used in conjunction with the previous publications.The recommendations for the management of acute mania remain largely unchanged. Lithium, valproate, and several atypical antipsychotic agents continue to be first-line treatments for acute mania. Monotherapy with asenapine, paliperidone extended release (ER), and divalproex ER, as well as adjunctive asenapine, have been added as first-line options.For the management of bipolar depression, lithium, lamotrigine, and quetiapine monotherapy, as well as olanzapine plus selective serotonin reuptake inhibitor (SSRI), and lithium or divalproex plus SSRI/bupropion remain first-line options. Lurasidone monotherapy and the combination of lurasidone or lamotrigine plus lithium or divalproex have been added as a second-line options. Ziprasidone alone or as adjunctive therapy, and adjunctive levetiracetam have been added as not-recommended options for the treatment of bipolar depression. Lithium, lamotrigine, valproate, olanzapine, quetiapine, aripiprazole, risperidone long-acting injection, and adjunctive ziprasidone continue to be first-line options for maintenance treatment of bipolar disorder. Asenapine alone or as adjunctive therapy have been added as third-line options. © 2012 John Wiley and Sons A/S

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Management of bipolar depression

Patients with bipolar disorder spend more time in a depressed than manic state, even with individualized treatment. To date, bipolar depression is often misdiagnosed and ineffectively managed both for acute episodes and residual symptoms. This review attempts to summarize the current status of available treatment strategies in the treatment of bipolar depression. For acute and prophylactic treatment, a substantial body of evidence supports the antidepressive efficacy of lithium for bipolar disorders and its antisuicidal effects. Among numerous anticonvulsants with mood-stabilizing properties, valproate and lamotrigine could be first-line options for bipolar depression. Due to receptor profile, mood-stabilizing properties of second-generation antipsychotics have been explored, and up to date, quetiapine and olanzapine appear to be a reasonable option for bipolar depression. The usefulness of antidepressants in bipolar depression is still controversial. Current guidelines generally recommend the cautious antidepressant use in combination with mood stabilizers to reduce the risk of mood elevation or cycle acceleration. Results from clinical trials on psychosocial intervention are promising, especially when integrated with pharmacotherapy. Most patients with bipolar depression need individualized and combined treatment, although the published evidence on this type of treatment strategy is limited. Future studies on the utility of currently available agents and modalities including psychosocial intervention are required

Regional brain gray matter abnormalities in patients with bipolar II disorder: A comparison study with bipolar I patients and healthy controls

Despite the high prevalence and clinical significance of bipolar II disorder (BD II), the underlying pathophysiology is not well explored in previous studies. The purpose of the current study was to investigate brain gray matter abnormalities in BD II. High resolution magnetic resonance brain images from 23 BD II patients, 23 sex- and age-matched patients with bipolar I disorder (BD I) and 23 healthy controls were acquired and processed according to the optimized voxel-based morphometry protocol. The processed gray matter tissue volumes were compared among the three groups. Both the BD II and BD I group showed gray matter deficits in the ventromedial prefrontal regions, compared to controls. The BD I group had widespread gray matter reductions in the bilateral frontal, temporal, parietal and parahippocampal cortices, compared to controls. However, gray matter reductions in these regions were not found in the BD II group. With a less conservative statistical threshold, the BD II group showed additional gray matter deficits in the anterior limbic cortices. Our data suggest that gray matter deficits in the ventromedial prefrontal and anterior limbic cortices are common in both BD II and BD I. On the other hand, different pattern of gray matter abnormalities between BY II and BD I found in this study supports that two subtypes may have different neurobiological characteristics.Killgore WDS, 2008, NEUROREPORT, V19, P1523, DOI 10.1097/WNR.0b013e328310af58Kempton MJ, 2008, ARCH GEN PSYCHIAT, V65, P1017Konarski JZ, 2008, BIPOLAR DISORD, V10, P1SIMOENS S, 2008, J MED ECON, V11, P245Merikangas KR, 2007, ARCH GEN PSYCHIAT, V64, P543Maina G, 2007, J CLIN PSYCHIAT, V68, P207Torrent C, 2006, BRIT J PSYCHIAT, V189, P254, DOI 10.1192/bjp.bp.105.017269Kronhaus DM, 2006, BIPOLAR DISORD, V8, P28Cotter D, 2005, BIPOLAR DISORD, V7, P358Adler CM, 2005, BIOL PSYCHIAT, V58, P151, DOI 10.1016/j.biopsych.2005.03.022Haznedar MM, 2005, BIOL PSYCHIAT, V57, P733, DOI 10.1016/j.biopsych.2005.01.002Strakowski SM, 2005, MOL PSYCHIATR, V10, P105, DOI 10.1038/sj.mp.4001585McDonald C, 2004, BIOL PSYCHIAT, V56, P411, DOI 10.1016/j.biopsych.2004.06.021Wilke M, 2004, PSYCHIAT RES-NEUROIM, V131, P57, DOI 10.1016/j.pscychresns.2004.01.004MCGRATH BM, 2004, CAN J PSYCHIAT, V49, P794Lyoo IK, 2003, BIPOLAR DISORD, V5, P300Judd LL, 2003, ARCH GEN PSYCHIAT, V60, P261Lopez-Larson MP, 2002, BIOL PSYCHIAT, V52, P93Cardinal RN, 2002, NEUROSCI BIOBEHAV R, V26, P321Genovese CR, 2002, NEUROIMAGE, V15, P870, DOI 10.1006/nimg.2001.1037McMahon FJ, 2001, ARCH GEN PSYCHIAT, V58, P1025Good CD, 2001, NEUROIMAGE, V14, P21, DOI 10.1006/nimg.2001.0786Hauser P, 2000, J AFFECT DISORDERS, V60, P25Akiskal HS, 2000, J AFFECT DISORDERS, V59, pS5Elliott R, 2000, J NEUROSCI, V20, P6159Blumberg HP, 1999, AM J PSYCHIAT, V156, P1986Rihmer Z, 1999, PSYCHIAT CLIN N AM, V22, P667Drevets WC, 1999, ANN NY ACAD SCI, V877, P614Angst J, 1998, J AFFECT DISORDERS, V50, P143FIRST MB, 1996, STRUCTURED CLIN INTEALTSHULER LL, 1995, AM J PSYCHIAT, V152, P1139*AM PSYCH ASS, 1994, DIAGN STAT MAN MENTSIMPSON SG, 1993, AM J PSYCHIAT, V150, P901HEUN R, 1993, ACTA PSYCHIAT SCAND, V87, P279DUNNER DL, 1976, BIOL PSYCHIAT, V11, P31HAMILTON M, 1960, J NEUROL NEUROSUR PS, V23, P56HOLLINGSHEAD AB, 1958, SOCIAL CLASS MENTAL1

Impact of Anxiety Disorder on Gray Matter Volume Changes in Patients with Bipolar II Disorder

Background: Comorbid anxiety disorders are frequently found in patients with bipolar disorder and may complicate the treatment of the disorder. Little is known about the interplay between bipolar disorder and anxiety disorder. The purpose of the current study was to investigate the effects of comorbid anxiety disorders on volumetric changes in brain of patients with bipolar II disorder.