[Show abstract][Hide abstract] ABSTRACT: Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21 856) and multiple sclerosis (MS) (n=43 879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16 731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.
[Show abstract][Hide abstract] ABSTRACT: Background Individuals with a mental health disorder appear to be at increased risk of medical illness. Aims To examine rates of medical illnesses in patients with bipolar disorder (n = 1720) and to examine the clinical course of the bipolar illness according to lifetime medical illness burden. Method Participants recruited within the UK were asked about the lifetime occurrence of 20 medical illnesses, interviewed using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) and diagnosed according to DSM-IV criteria. Results We found significantly increased rates of several medical illnesses in our bipolar sample. A high medical illness burden was associated with a history of anxiety disorder, rapid cycling mood episodes, suicide attempts and mood episodes with a typically acute onset. Conclusions Bipolar disorder is associated with high rates of medical illness. This comorbidity needs to be taken into account by services in order to improve outcomes for patients with bipolar disorder and also in research investigating the aetiology of affective disorder where shared biological pathways may play a role.
The British journal of psychiatry: the journal of mental science 10/2014; 205(6). DOI:10.1192/bjp.bp.114.152249 · 7.99 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
[Show abstract][Hide abstract] ABSTRACT: We have conducted a genotyping study using a custom Illumina Infinium HD genotyping array, the ImmunoChip, in a new UK sample of 1218 bipolar disorder (BD) cases and 2913 controls that have not been used in any studies previously reported independently or in meta-analyses. The ImmunoChip was designed before the publication of the Psychiatric Genome-Wide Association Study Consortium Bipolar Disorder Working Group (PGC-BD) meta-analysis data. As such 3106 single-nucleotide polymorphisms (SNPs) with a P-value <1 × 10(-3) from the BD meta-analysis by Ferreira et al. were genotyped. We report support for two of the three most strongly associated chromosomal regions in the Ferreira study, CACNA1C (rs1006737, P=4.09 × 10(-4)) and 15q14 (rs2172835, P=0.043) but not ANK3 (rs10994336, P=0.912). We have combined our ImmunoChip data (569 quasi-independent SNPs from the 3016 SNPs genotyped) with the recently published PGC-BD meta-analysis data, using either the PGC-BD combined discovery and replication data where available or just the discovery data where the SNP was not typed in a replication sample in PGC-BD. Our data provide support for two regions, at ODZ4 and CACNA1C, with prior evidence for genome-wide significant (GWS) association in PGC-BD meta-analysis. In addition, the combined analysis shows two novel GWS associations. First, rs7296288 (P=8.97 × 10(-9), odds ratio (OR)=0.9), an intergenic polymorphism on chromosome 12 located between RHEBL1 and DHH. Second, rs3818253 (P=3.88 × 10(-8), OR=1.16), an intronic SNP on chromosome 20q11.2 in the gene TRPC4AP, which lies in a high linkage disequilibrium region along with the genes GSS and MYH7B.Molecular Psychiatry advance online publication, 16 October 2012; doi:10.1038/mp.2012.142.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: 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 x 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.
[Show abstract][Hide abstract] ABSTRACT: We have previously reported evidence that variation at GABA(A) receptor genes is associated with susceptibility to bipolar disorder with schizophrenia-like psychotic features (Research Diagnostic Criteria (RDC) schizoaffective disorder, bipolar type) with gene-wide significance at GABRB1, GABRA4, GABRB3, GABRA5, and GABRR3. Here we provide suggestive evidence implicating a sixth member of the gene family, GABRR1 (gene-wide P = 0.0058; experiment-wide corrected significance P 0.052). (c) 2010 Wiley-Liss, Inc.
American Journal of Medical Genetics Part B Neuropsychiatric Genetics 10/2010; 153B(7):1347-9. DOI:10.1002/ajmg.b.31108 · 3.42 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The under-recognition of hypomanic symptoms by both clinicians and patients is a major clinical problem which contributes to misdiagnosis and diagnostic delay in patients with bipolar disorder. The recent development of validated screening instruments for hypomania, such as the Hypomania Checklist (HCL-32), may help to improve the detection of bipolar disorder. In this study, we assess whether it is possible to reduce the number of items on the HCL-32 without any loss in the screening tool's ability to reliably differentiate between bipolar disorder (BD) and major depressive disorder (MDD).
Using our large samples of patients with DSM-IV defined bipolar I disorder (BD-I) (n=230) and recurrent MDD (n=322), we performed item correlations in order to identify potentially redundant items in the HCL-32. We then tested the performance of a shortened 16-item HCL questionnaire within a separate sample of patients with BD (including BD-I, BD-II and BD-NOS) (n=59) and MDD (n=76).
The structure of the 16-item HCL demonstrated two main factors similar to those identified for the HCL-32 (an 'active-elated' factor and a 'risk-taking/irritable' factor). A score of 8 or more on a shortened 16-item version of the HCL had excellent ability to distinguish between BD and MDD. The sensitivity (83%) and specificity (71%) of the 16-item version were very similar to those for the full 32-item HCL.
The HCL-16 was derived after subjects had completed the full HCL-32. It will be important to test the validity of a 'stand-alone' 16-item HCL questionnaire.
A shortened 16-item HCL (the HCL-16) is potentially a useful screening tool for hypomania within busy clinical settings.
[Show abstract][Hide abstract] ABSTRACT: Despite compelling evidence for a major genetic contribution to risk of bipolar mood disorder, conclusive evidence implicating specific genes or pathophysiological systems has proved elusive. In part this is likely to be related to the unknown validity of current phenotype definitions and consequent aetiological heterogeneity of samples. In the recent Wellcome Trust Case Control Consortium genome-wide association analysis of bipolar disorder (1868 cases, 2938 controls) one of the most strongly associated polymorphisms lay within the gene encoding the GABA A receptor Β1 subunit, GABRB1. Aiming to increase biological homogeneity, we sought the diagnostic subset that showed the strongest signal at this polymorphism and used this to test for independent evidence of association with other members of the GABA A receptor gene family. The index signal was significantly enriched in the 279 cases meeting Research Diagnostic Criteria for schizoaffective disorder, bipolar type (P3.8 × 10 -6). Independently, these cases showed strong evidence that variation in GABA A receptor genes influences risk for this phenotype (independent system-wide P6.6 × 10 -5) with association signals also at GABRA4, GABRB3, GABRA5 and GABRR1. Our findings have the potential to inform understanding of presentation, pathogenesis and nosology of bipolar disorders. Our method of phenotype refinement may be useful in studies of other complex psychiatric and non-psychiatric disorders.
[Show abstract][Hide abstract] ABSTRACT: There is currently a great deal of interest in the use of affective temperaments as possible intermediate phenotypes for bipolar disorder. However, much of the literature in this area is conflicting. Our aims were to test the hypothesis of a gradient in affective temperament scores, as measured by the Temperament Evaluation of Memphis, Pisa, Paris and San Diego (TEMPS-A), from bipolar disorder type I (BP-I), through bipolar disorder type II (BP-II), recurrent major depressive disorder (MDD-R), and a control group (CG) in the largest sample to date of 927 subjects.
Non parametric tests were used to compare TEMPS-A scores between diagnostic groups and multinomial logistic regression was used to test the association between TEMPS-A scores and diagnosis while controlling for current mood state, age and gender.
Although the BP-II group scored higher than the BP-I and MDD-R groups on several TEMPS-A subscales, these differences were not significant when confounding variables were controlled for. The dysthymic subscale differentiated between affected and controls and the anxious subscale differentiated the MDD-R group from controls.
The cross-sectional design did not allow us to evaluate potential longitudinal changes of temperament scores, which were assessed only with a self-report questionnaire.
We failed to find evidence of a gradient in affective temperament scores. Both unipolar and bipolar patients reported high dysthymic scores relative to controls, perhaps supporting a unitary view of depression across the bipolar-unipolar spectrum. Taking account of potential confounders will be important in future studies which seek to use affective temperaments as intermediate phenotypes in genetic research.
[Show abstract][Hide abstract] ABSTRACT: Molecular genetic analysis offers opportunities to advance our understanding of the nosological relationship between psychiatric diagnostic categories in general, and the mood and psychotic disorders in particular. Strong evidence (P=7.0 × 10(-7)) of association at the polymorphism rs1006737 (within CACNA1C, the gene encoding the α-1C subunit of the L-type voltage-gated calcium channel) with the risk of bipolar disorder (BD) has recently been reported in a meta-analysis of three genome-wide association studies of BD, including our BD sample (N=1868) studied within the Wellcome Trust Case Control Consortium. Here, we have used our UK case samples of recurrent major depression (N=1196) and schizophrenia (N=479) and UK non-psychiatric comparison groups (N=15316) to examine the spectrum of phenotypic effect of the bipolar risk allele at rs1006737. We found that the risk allele conferred increased risk for schizophrenia (P=0.034) and recurrent major depression (P=0.013) with similar effect sizes to those previously observed in BD (allelic odds ratio ∼1.15). Our findings are evidence of some degree of overlap in the biological underpinnings of susceptibility to mental illness across the clinical spectrum of mood and psychotic disorders, and show that at least some loci can have a relatively general effect on susceptibility to diagnostic categories, as currently defined. Our findings will contribute to a better understanding of the pathogenesis of major psychiatric illness, and such knowledge should be useful in providing an etiological rationale for shaping psychiatric nosology, which is currently reliant entirely on descriptive clinical data.
[Show abstract][Hide abstract] ABSTRACT: Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to know whether any of the various diagnostic categories in current use identify cases that are particularly helpful for biological-genetic research.
To use genome-wide genetic association data to explore the relative genetic utility of seven different descriptive operational diagnostic categories relevant to bipolar illness within a large UK case-control bipolar disorder sample.
We analysed our previously published Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder genome-wide association data-set, comprising 1868 individuals with bipolar disorder and 2938 controls genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met stringent criteria for genotype quality. For each SNP we performed a test of association (bipolar disorder group v. control group) and used the number of associated independent SNPs statistically significant at P<0.00001 as a metric for the overall genetic signal in the sample. We next compared this metric with that obtained using each of seven diagnostic subsets of the group with bipolar disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic disorder; bipolar II disorder; schizoaffective disorder, bipolar type; DSM-IV: bipolar I disorder; bipolar II disorder; schizoaffective disorder, bipolar type.
The RDC schizoaffective disorder, bipolar type (v. controls) stood out from the other diagnostic subsets as having a significant excess of independent association signals (P<0.003) compared with that expected in samples of the same size selected randomly from the total bipolar disorder group data-set. The strongest association in this subset of participants with bipolar disorder was at rs4818065 (P = 2.42 x 10(-7)). Biological systems implicated included gamma amniobutyric acid (GABA)(A) receptors. Genes having at least one associated polymorphism at P<10(-4) included B3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 and CDH12.
Our findings show that individuals with broadly defined bipolar schizoaffective features have either a particularly strong genetic contribution or that, as a group, are genetically more homogeneous than the other phenotypes tested. The results point to the importance of using diagnostic approaches that recognise this group of individuals. Our approach can be applied to similar data-sets for other psychiatric and non-psychiatric phenotypes.
The British journal of psychiatry: the journal of mental science 08/2009; 195(1):23-9. DOI:10.1192/bjp.bp.108.061424 · 7.99 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To assess whether bipolar disorder type I segregates into three clinically distinct sub-groups defined by age-at-onset.
Clinical data were available on 1369 individuals with DSM-IV bipolar I disorder. Mixture analysis was performed on the age-at-onset (AAO) data to determine whether they were composed of more than one normal distribution. Individuals were allocated to groups according to the results of the mixture analysis. Categorical logistic regression was then used to investigate relationships between AAO and nine clinical characteristics.
The distribution of AAOs in our sample comprised a mixture of three normal distributions with means of 18.7 (SD=3.7), 28.3 (SD=5.5) and 43.3 (SD=9.1) years, with relative proportions of 0.47, 0.39 and 0.14 respectively. Individuals were allocated into three groups dependent on their AAO: < or = 22; 25-37; and > or = 40 years, producing a sample of 1225 individuals (144 with borderline values were excluded). Eight out of the nine clinical characteristics showed evidence for a statistical association with AAO group.
Systematic and non-systematic recruitment of participants. Some data relied on retrospective recall.
Our results provide further robust evidence to suggest that the AAO distribution of individuals affected with bipolar disorder is composed of three normal distributions. Substantial clinical heterogeneity between the three AAO groups may reflect genetic heterogeneity within bipolar I disorder. Future genetic studies should consider AAO grouping as potential sub-phenotypes.