Displaying publications 21 - 31 of 31 in total

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  1. Tee SF, Chow TJ, Tang PY, Loh HC
    Genet. Mol. Res., 2010;9(3):1274-8.
    PMID: 20623453 DOI: 10.4238/vol9-3gmr789
    The serotoninergic system has been implicated in the etiology of schizophrenia and other behavioral disorders. Association studies have focused on the tryptophan hydroxylase 2 gene (TPH2) and the 5-hydroxytryptamine receptor 2A gene (5-HTR2A). We genotyped two single-nucleotide polymorphisms, A1438G of 5-HTR2A and intronic rs1386494 of TPH2 in the Malay population, using a sample size of 289 schizophrenic patients and 130 healthy controls. We found a significant association of A1438G of 5-HTR2A with schizophrenia in Malays. On the other hand, TPH2 polymorphism was not associated with schizophrenia. This is the first genetic association study concerning schizophrenia in the Malay population.
    Matched MeSH terms: Schizophrenia/genetics*
  2. Razali SM, Abidin ZZ, Othman Z, Yassin MA
    Asian J Psychiatr, 2015 Aug;16:26-31.
    PMID: 26182843 DOI: 10.1016/j.ajp.2015.06.011
    The aim of the study is to screen and evaluate the efficacy of the screening tools in detecting subjects with sub-threshold psychosis among asymptomatic individuals at genetic risk, as compared with persons in the general public.
    Matched MeSH terms: Schizophrenia/genetics
  3. 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: Schizophrenia/genetics
  4. 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: Schizophrenia/genetics*
  5. Mohamed ZI, Tee SF, Tang PY
    Psychiatr Genet, 2018 12;28(6):110-119.
    PMID: 30252773 DOI: 10.1097/YPG.0000000000000210
    INTRODUCTION: In recent years, various studies have accumulated evidence of the involvement of single nucleotide polymorphisms (SNPs) in introns and exons in schizophrenia. The association of functional SNPs in the 3'-untranslated regions with schizophrenia has been explored in a number of studies, but the results are inconclusive because of limited meta-analyses. To systematically analyze the association between SNPs in 3'-untranslated regions and schizophrenia, we conducted a meta-analysis by combining all available studies on schizophrenia candidate genes.

    MATERIALS AND METHODS: We searched candidate genes from the schizophrenia database and performed a comprehensive meta-analysis using all the available data up to August 2017. The association between susceptible SNPs and schizophrenia was assessed by the pooled odds ratio with 95% confidence interval using fixed-effect and random-effect models.

    RESULTS: A total of 21 studies including 8291 cases and 9638 controls were used for meta-analysis. Three investigated SNPs were rs165599, rs3737597, and rs1047631 of COMT, DISC1, and DTNBP1, respectively. Our results suggested that rs3737597 showed a significant association with schizophrenia in Europeans (odds ratio: 1.584, P: 0.002, 95% confidence interval: 1.176-2.134) under a random-effect framework.

    CONCLUSION: This meta-analysis indicated that rs3737597 of DISC1 was significantly associated with schizophrenia in Europeans, and it can be suggested as an ethnic-specific risk genetic factor.

    Matched MeSH terms: Schizophrenia/genetics*
  6. 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: Schizophrenia/genetics
  7. 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: Schizophrenia/genetics*
  8. Roffeei SN, Mohamed Z, Reynolds GP, Said MA, Hatim A, Mohamed EH, et al.
    Pharmacogenomics, 2014 Mar;15(4):477-85.
    PMID: 24624915 DOI: 10.2217/pgs.13.220
    The occurrence of metabolic syndrome (MS) in schizophrenia patients receiving long-term antipsychotics (APs) contributes to their high mortality rate. We aimed to determine whether genetic polymorphisms of identified candidate genes are associated with MS in our study population.
    Matched MeSH terms: Schizophrenia/genetics
  9. 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: Schizophrenia/genetics*
  10. 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: Schizophrenia/genetics*
  11. Varma SL, Zain AM, Singh S
    Am. J. Med. Genet., 1997 Feb 21;74(1):7-11.
    PMID: 9033998
    There is increasing evidence that genetic factors play a role in the etiology of schizophrenic disorders. One thousand eighty-nine first-degree relatives of schizophrenics and 1,137 controls were studied to discover their psychiatric morbidity. Psychiatric morbidity was found in 16.34% of the first-degree relatives (FDR) of schizophrenics (parents, 5.69%; siblings, 7.71%; offspring, 2.94%) as compared to 6.9% in the controls (P < 0.001). Schizophrenia was found in 8.3% of the patient group, which was significantly higher (0.2%) as compared to the controls. Schizoid-schizotypal personality disorder was found in 3.03% of FDRs of the schizophrenic group. Depressive disorder was found in 4.4% and 2.1% in the control and patient group, respectively, which was statistically significant. Morbidity risk of schizophrenia was found in 16.97%, 6.22% and 5.79% of schizophrenia, schizoid-schizotypal personality disorder and depressive disorder, respectively, in the FDR of schizophrenic group.
    Matched MeSH terms: Schizophrenia/genetics*
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