Displaying all 14 publications

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  1. Chakraborty D, Mazumdar P, Than M, Singh R
    Med J Malaysia, 2001 Jun;56(2):223-6.
    PMID: 11771083
    Dermatoglyphic is the study of the epidermal ridges and the pattern formed by them. It may be pointed out that genetic factors have a large share in determining the variations in dermatoglyphics. It is however, suggested by evidence that bipolar mood disorder factors are determined more by genetic factors than by the environmental factors. The experiment has been undertaken to look for the effects of the bipolar mood disorder on dermatoglyphics. The dermatoglyphic characteristics of subjects with bipolar mood disorder when compared with control group revealed significant differences. The radial loop were increased in bipolar mood disorder, but there were little changes in 'atd' angles between normal and bipolar mood disorder.
    Matched MeSH terms: Bipolar Disorder/genetics*
  2. Consortium on Lithium Genetics, Hou L, Heilbronner U, Rietschel M, Kato T, Kuo PH, et al.
    N Engl J Med, 2014 05 08;370(19):1857-9.
    PMID: 24806176 DOI: 10.1056/NEJMc1401817
    Matched MeSH terms: Bipolar Disorder/genetics*
  3. Nurnberger JI, Koller DL, Jung J, Edenberg HJ, Foroud T, Guella I, et al.
    JAMA Psychiatry, 2014 Jun;71(6):657-64.
    PMID: 24718920 DOI: 10.1001/jamapsychiatry.2014.176
    IMPORTANCE: Genome-wide investigations provide systematic information regarding the neurobiology of psychiatric disorders.

    OBJECTIVE: To identify biological pathways that contribute to risk for bipolar disorder (BP) using genes with consistent evidence for association in multiple genome-wide association studies (GWAS).

    DATA SOURCES: Four independent data sets with individual genome-wide data available in July 2011 along with all data sets contributed to the Psychiatric Genomics Consortium Bipolar Group by May 2012. A prior meta-analysis was used as a source for brain gene expression data.

    STUDY SELECTION: The 4 published GWAS were included in the initial sample. All independent BP data sets providing genome-wide data in the Psychiatric Genomics Consortium were included as a replication sample.

    DATA EXTRACTION AND SYNTHESIS: We identified 966 genes that contained 2 or more variants associated with BP at P

    Matched MeSH terms: Bipolar Disorder/genetics*
  4. Mohamed Saini S, Nik Jaafar NR, Sidi H, Midin M, Mohd Radzi A, Abdul Rahman AH
    Compr Psychiatry, 2014 Jan;55 Suppl 1:S76-81.
    PMID: 23410635 DOI: 10.1016/j.comppsych.2012.12.005
    The risk variants have been shown to vary substantially across populations and a genetic study in a heterogeneous population might shed a new light in the disease mechanism. This preliminary study aims to determine the frequency of the serotonin transporter gene polymorphism (5-HTTLPR) in the three main ethnic groups in Malaysia and its association with bipolar disorder.
    Matched MeSH terms: Bipolar Disorder/genetics*
  5. Lim CH, Zainal NZ, Kanagasundram S, Zain SM, Mohamed Z
    PMID: 27177356 DOI: 10.1002/ajmg.b.32457
    Although major progress has been achieved in research and development of antipsychotic medications for bipolar disorder (BPD), knowledge of the molecular mechanisms underlying this disorder and the action of atypical antipsychotics remains incomplete. The levels of microRNAs (miRNAs)-small non-coding RNA molecules that regulate gene expression, including genes involved in neuronal function and plasticity-are frequently altered in psychiatric disorders. This study aimed to examine changes in miRNA expression in bipolar mania patients after treatment with asenapine and risperidone. Using a miRNA microarray, we analyzed miRNA expression in the blood of 10 bipolar mania patients following 12 weeks of treatment with asenapine or risperidone. Selected miRNAs were validated by using real-time PCR. A total of 16 miRNAs were differentially expressed after treatment in the asenapine group, 14 of which were significantly upregulated and the other two significantly downregulated. However, all three differentially expressed miRNAs in the risperidone group were downregulated. MiRNA target gene prediction and gene ontology analysis revealed significant enrichment for pathways associated with immune system response and regulation of programmed cell death and transcription. Our results suggest that candidate miRNAs may be involved in the mechanism of action of both antipsychotics in bipolar mania. © 2016 Wiley Periodicals, Inc.
    Matched MeSH terms: Bipolar Disorder/genetics*
  6. Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Electronic address: douglas.ruderfer@vanderbilt.edu, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium
    Cell, 2018 Jun 14;173(7):1705-1715.e16.
    PMID: 29906448 DOI: 10.1016/j.cell.2018.05.046
    Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment.
    Matched MeSH terms: Bipolar Disorder/genetics*
  7. Bauer M, Glenn T, Alda M, Andreassen OA, Angelopoulos E, Ardau R, et al.
    J Affect Disord, 2014;167:104-11.
    PMID: 24953482 DOI: 10.1016/j.jad.2014.05.032
    The onset of bipolar disorder is influenced by the interaction of genetic and environmental factors. We previously found that a large increase in sunlight in springtime was associated with a lower age of onset. This study extends this analysis with more collection sites at diverse locations, and includes family history and polarity of first episode.
    Matched MeSH terms: Bipolar Disorder/genetics
  8. Psychiatric GWAS Consortium Bipolar Disorder Working Group
    Nat Genet, 2011 Sep 18;43(10):977-83.
    PMID: 21926972 DOI: 10.1038/ng.943
    We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 × 10(-7)). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci.
    Matched MeSH terms: Bipolar Disorder/genetics*
  9. Lim CH, Zain SM, Reynolds GP, Zain MA, Roffeei SN, Zainal NZ, et al.
    PMID: 24914473 DOI: 10.1016/j.pnpbp.2014.05.017
    Recent studies have shown that bipolar disorder (BPD) and schizophrenia (SZ) share some common genetic risk factors. This study aimed to examine the association between candidate single nucleotide polymorphisms (SNPs) identified from genome-wide association studies (GWAS) and risk of BPD and SZ. A total of 715 patients (244 BPD and 471 SZ) and 593 controls were genotyped using the Sequenom MassARRAY platform. We showed a positive association between LMAN2L (rs6746896) and risk of both BPD and SZ in a pooled population (P-value=0.001 and 0.009, respectively). Following stratification by ethnicity, variants of the ANK3 gene (rs1938516 and rs10994336) were found to be associated with BPD in Malays (P-value=0.001 and 0.006, respectively). Furthermore, an association exists between another variant of LMAN2L (rs2271893) and SZ in the Malay and Indian ethnic groups (P-value=0.003 and 0.002, respectively). Gene-gene interaction analysis revealed a significant interaction between the ANK3 and LMAN2L genes (empirical P=0.0107). Significant differences were shown between patients and controls for two haplotype frequencies of LMAN2L: GA (P=0.015 and P=0.010, for BPD and SZ, respectively) and GG (P=0.013 for BPD). Our study showed a significant association between LMAN2L and risk of both BPD and SZ.
    Matched MeSH terms: Bipolar Disorder/genetics*
  10. Maier R, Moser G, Chen GB, Ripke S, Cross-Disorder Working Group of the Psychiatric Genomics Consortium, Coryell W, et al.
    Am J Hum Genet, 2015 Feb 05;96(2):283-94.
    PMID: 25640677 DOI: 10.1016/j.ajhg.2014.12.006
    Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.
    Matched MeSH terms: Bipolar Disorder/genetics
  11. Byrne EM, Psychiatric Genetics Consortium Major Depressive Disorder Working Group, Raheja UK, Stephens SH, Heath AC, Madden PA, et al.
    J Clin Psychiatry, 2015 Feb;76(2):128-34.
    PMID: 25562672 DOI: 10.4088/JCP.14m08981
    OBJECTIVE: To test common genetic variants for association with seasonality (seasonal changes in mood and behavior) and to investigate whether there are shared genetic risk factors between psychiatric disorders and seasonality.

    METHOD: Genome-wide association studies (GWASs) were conducted in Australian (between 1988 and 1990 and between 2010 and 2013) and Amish (between May 2010 and December 2011) samples in whom the Seasonal Pattern Assessment Questionnaire (SPAQ) had been administered, and the results were meta-analyzed in a total sample of 4,156 individuals. Genetic risk scores based on results from prior large GWAS studies of bipolar disorder, major depressive disorder (MDD), and schizophrenia were calculated to test for overlap in risk between psychiatric disorders and seasonality.

    RESULTS: The most significant association was with rs11825064 (P = 1.7 × 10⁻⁶, β = 0.64, standard error = 0.13), an intergenic single nucleotide polymorphism (SNP) found on chromosome 11. The evidence for overlap in risk factors was strongest for schizophrenia and seasonality, with the schizophrenia genetic profile scores explaining 3% of the variance in log-transformed global seasonality scores. Bipolar disorder genetic profile scores were also associated with seasonality, although at much weaker levels (minimum P value = 3.4 × 10⁻³), and no evidence for overlap in risk was detected between MDD and seasonality.

    CONCLUSIONS: Common SNPs of large effect most likely do not exist for seasonality in the populations examined. As expected, there were overlapping genetic risk factors for bipolar disorder (but not MDD) with seasonality. Unexpectedly, the risk for schizophrenia and seasonality had the largest overlap, an unprecedented finding that requires replication in other populations and has potential clinical implications considering overlapping cognitive deficits in seasonal affective disorders and schizophrenia.

    Matched MeSH terms: Bipolar Disorder/genetics*
  12. Zain MA, Roffeei SN, Zainal NZ, Kanagasundram S, Mohamed Z
    Psychiatr Genet, 2013 Dec;23(6):258-61.
    PMID: 24064681 DOI: 10.1097/YPG.0000000000000015
    Two single nucleotide polymorphisms of PDLIM5, rs7690296 and rs11097431, were genotyped using Mass-Array SNP genotyping by Sequenom technology in 244 bipolar disorder patients, 471 schizophrenia patients, and 601 control individuals who were Malay, Chinese, and Indian ethnic groups in the Malaysian population. A significant association was observed in allele frequency between the rs7690296 polymorphism and bipolar disorder in the Indian ethnic group [P=0.02, adjusted odds ratio (OR) 0.058, 95% confidence interval (CI) 0.36-0.93]. A significant association was also observed between the rs7690296 polymorphism and schizophrenia under the recessive model for both Malay (P=0.02, adjusted OR 1.86, 95% CI 1.12-3.10) and Indian (P=0.02, adjusted OR 1.92, 95% CI 1.10-3.37) ethnic groups. However, no association was detected between the rs11097431 polymorphism either with bipolar disorder or with schizophrenia. Therefore, it can be deduced that the nonsynonymous rs7690296 polymorphism could play an important role in the pathophysiology of both bipolar disorder and schizophrenia.
    Matched MeSH terms: Bipolar Disorder/genetics*
  13. Cross-Disorder Group of the Psychiatric Genomics Consortium
    Lancet, 2013 Apr 20;381(9875):1371-9.
    PMID: 23453885 DOI: 10.1016/S0140-6736(12)62129-1
    BACKGROUND: Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia.

    METHODS: We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples.

    FINDINGS: SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers.

    INTERPRETATION: Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause.

    FUNDING: National Institute of Mental Health.

    Matched MeSH terms: Bipolar Disorder/genetics*
  14. Zain MA, Jahan SN, Reynolds GP, Zainal NZ, Kanagasundram S, Mohamed Z
    BMC Med Genet, 2012;13:91.
    PMID: 23031404 DOI: 10.1186/1471-2350-13-91
    One of the genes suggested to play an important role in the pathophysiology of bipolar disorder (BPD) is PDLIM5, which encodes LIM domain protein. Our main objective was to examine the effect of olanzapine treatment on PDLIM5 mRNA expression in the peripheral blood leukocytes of BPD patients.
    Matched MeSH terms: Bipolar Disorder/genetics*
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