Nirmala Akula

A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder

The genetic basis of bipolar disorder has long been thought to be complex, with the potential involvement of multiple genes, but methods to analyze populations with respect to this complexity have only recently become available. We have carried out a genome-wide association study of bipolar disorder by genotyping over 550 000 single-nucleotide polymorphisms (SNPs) in two independent case-control samples of European origin. The initial association screen was performed using pooled DNA, and selected SNPs were confirmed by individual genotyping. While DNA pooling reduces power to detect genetic associations, there is a substantial cost saving and gain in efficiency. A total of 88 SNPs, representing 80 different genes, met the prior criteria for replication in both samples. Effect sizes were modest: no single SNP of large effect was detected. Of 37 SNPs selected for individual genotyping, the strongest association signal was detected at a marker within the first intron of diacylglycerol kinase eta (DGKH; P=1.5 × 10−8, experiment-wide P<0.01, OR=1.59). This gene encodes DGKH, a key protein in the lithium-sensitive phosphatidyl inositol pathway. This first genome-wide association study of bipolar disorder shows that several genes, each of modest effect, reproducibly influence disease risk. Bipolar disorder may be a polygenic disease.

Cancer regression and neurological toxicity following anti-MAGE-A3 TCR gene therapy.

Nine cancer patients were treated with adoptive cell therapy using autologous anti-MAGE-A3 T-cell receptors (TCR)-engineered T cells. Five patients experienced clinical regression of their cancers including 2 on-going responders. Beginning 1–2 days postinfusion, 3 patients (#’s 5, 7, and 8) experienced mental status changes, and 2 patients (5 and 8) lapsed into comas and subsequently died. Magnetic resonance imagining analysis of patients 5 and 8 demonstrated periventricular leukomalacia, and examination of their brains at autopsy revealed necrotizing leukoencephalopathy with extensive white matter defects associated with infiltration of CD3+/CD8+ T cells. Patient 7, developed Parkinson-like symptoms, which resolved over 4 weeks and fully recovered. Immunohistochemical staining of patient and normal brain samples demonstrated rare positively staining neurons with an antibody that recognizes multiple MAGE-A family members. The TCR used in this study recognized epitopes in MAGE-A3/A9/A12. Molecular assays of human brain samples using real-time quantitative-polymerase chain reaction, Nanostring quantitation, and deep-sequencing indicated that MAGE-A12 was expressed in human brain (and possibly MAGE-A1, MAGE-A8, and MAGE-A9). This previously unrecognized expression of MAGE-A12 in human brain was possibly the initiating event of a TCR-mediated inflammatory response that resulted in neuronal cell destruction and raises caution for clinical applications targeting MAGE-A family members with highly active immunotherapies.

Meta-analysis of genome-wide association data identifies a risk locus for major mood disorders on 3p21.1.

The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 × 10−8; odds ratio = 0.87; 95% confidence interval, 0.83–0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

Two variants in Ankyrin 3 ( ANK3 ) are independent genetic risk factors for bipolar disorder

Two recent reports have highlighted ANK3 as a susceptibility gene for bipolar disorder (BD). We first reported association between BD and the ANK3 marker rs9804190 in a genome-wide association study (GWAS) of two independent samples (Baum et al., 2008). Subsequently, a meta-analysis of GWAS data based on samples from the US and the UK reported association with a different ANK3 marker, rs10994336 (Ferreira et al., 2008). The markers lie about 340 kb apart in the gene. Here, we test both markers in additional samples and characterize the contribution of each marker to BD risk. Our previously reported findings at rs9804190, which had been based on DNA pooling, were confirmed by individual genotyping in the National Institute of Mental Health (NIMH) waves 1–4 (P=0.05; odds ratio (OR)=1.24) and German (P=0.0006; OR=1.34) samples. This association was replicated in an independent US sample known as NIMH wave 5 (466 cases, 212 controls; P=0.017; OR=1.38). A random-effects meta-analysis of all three samples was significant (P=3 × 10−6; OR=1.32), with no heterogeneity. Individual genotyping of rs10994336 revealed a significant association in the German sample (P=0.0001; OR=1.70), and similar ORs in the NIMH 1–4 and NIMH 5 samples that were not significant at the P<0.05 level. Meta-analysis of all three samples supported an association with rs10994336 (P=1.7 × 10−5; OR=1.54), again with no heterogeneity. There was little linkage disequilibrium between the two markers. Further analysis suggested that each marker contributed independently to BD, with no significant marker × marker interaction. Our findings strongly support ANK3 as a BD susceptibility gene and suggest true allelic heterogeneity.

Findings in an independent sample support an association between bipolar affective disorder and the G72/G30 locus on chromosome 13q33

Markers near the nested genes G72 and G30 on chromosome 13q33 have been implicated in the etiology of schizophrenia and, recently, bipolar affective disorder (BPAD). Hattori et al (2003) reported that single-nucleotide polymorphisms (SNPs) near the G72/G30 locus were associated with BPAD in a sample of 22 pedigrees, and that SNP haplotypes were associated in a second, larger sample of triads. The present study attempts to replicate this finding in an independent case–control sample. Six SNPs near the G72/G30 locus, including the most strongly associated markers in the previous study, were tested in 139 cases and 113 ethnically matched controls. Significant association was detected between BPAD and two adjacent SNPs (smallest P=0.007; global P=0.024). Haplotype analysis produced additional support for association (smallest P=0.004; global P=0.004). Analysis of 31 unlinked microsatellite markers detected no population stratification in the cases or controls studied. Although the associated alleles and haplotypes differ from those previously reported, these new results provide further evidence, in an independent sample, for an association between BPAD and genetic variation in the vicinity of the genes G72 and G30.

Genome-wide association study meta-analysis of European and Asian-ancestry samples identifies three novel loci associated with bipolar disorder

Meta-analyses of bipolar disorder (BD) genome-wide association studies (GWAS) have identified several genome-wide significant signals in European-ancestry samples, but so far account for little of the inherited risk. We performed a meta-analysis of ∼750 000 high-quality genetic markers on a combined sample of ∼14 000 subjects of European and Asian-ancestry (phase I). The most significant findings were further tested in an extended sample of ∼17 700 cases and controls (phase II). The results suggest novel association findings near the genes TRANK1 (LBA1), LMAN2L and PTGFR. In phase I, the most significant single nucleotide polymorphism (SNP), rs9834970 near TRANK1, was significant at the P=2.4 × 10−11 level, with no heterogeneity. Supportive evidence for prior association findings near ANK3 and a locus on chromosome 3p21.1 was also observed. The phase II results were similar, although the heterogeneity test became significant for several SNPs. On the basis of these results and other established risk loci, we used the method developed by Park et al. to estimate the number, and the effect size distribution, of BD risk loci that could still be found by GWAS methods. We estimate that >63 000 case–control samples would be needed to identify the ∼105 BD risk loci discoverable by GWAS, and that these will together explain <6% of the inherited risk. These results support previous GWAS findings and identify three new candidate genes for BD. Further studies are needed to replicate these findings and may potentially lead to identification of functional variants. Sample size will remain a limiting factor in the discovery of common alleles associated with BD.

The International Consortium on Lithium Genetics (ConLiGen): An Initiative by the NIMH and IGSLI to Study the Genetic Basis of Response to Lithium Treatment

For more than half a decade, lithium has been successfully used to treat bipolar disorder. Worldwide, it is considered the first-line mood stabilizer. Apart from its proven antimanic and prophylactic effects, considerable evidence also suggests an antisuicidal effect in affective disorders. Lithium is also effectively used to augment antidepressant drugs in the treatment of refractory major depressive episodes and prevent relapses in recurrent unipolar depression. In contrast to many psychiatric drugs, lithium has outlasted various pharmacotherapeutic ‘fashions’, and remains an indispensable element in contemporary psychopharmacology. Nevertheless, data from pharmacogenetic studies of lithium are comparatively sparse, and these studies are generally characterized by small sample sizes and varying definitions of response. Here, we present an international effort to elucidate the genetic underpinnings of lithium response in bipolar disorder. Following an initiative by the International Group for the Study of Lithium-Treated Patients (www.IGSLI.org) and the Unit on the Genetic Basis of Mood and Anxiety Disorders at the National Institute of Mental Health,lithium researchers from around the world have formed the Consortium on Lithium Genetics (www.ConLiGen.org) to establish the largest sample to date for genome-wide studies of lithium response in bipolar disorder, currently comprising more than 1,200 patients characterized for response to lithium treatment. A stringent phenotype definition of response is one of the hallmarks of this collaboration. ConLiGen invites all lithium researchers to join its efforts.

Genome-wide association study of suicidal ideation emerging during citalopram treatment of depressed outpatients

Objectives Suicidal ideation is an uncommon but worrisome symptom than can emerge during antidepressant treatment. We have described earlier the association between treatment-emergent suicidal ideation (TESI) and markers in genes encoding glutamate receptor subunits GRIK2 and GRIA3. The present genome-wide association study was conducted to identify additional genetic markers associated with TESI that may help identify individuals at high risk who may benefit from closer monitoring, alternative treatments, and/or specialty care. Methods A clinically representative cohort of outpatients with nonpsychotic major depressive disorder enrolled in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial were treated with citalopram under a standard protocol for up to 14 weeks. DNA samples from 90 White participants who developed TESI and a sex-matched and race-matched equal number of treated participants who denied any suicidal ideas were genotyped with 109 365 single nucleotide polymorphisms on the Illuminas Human-1 BeadChip. Results One marker was found to be associated with TESI in this sample at the experiment-wide adjusted P less than 0.05 level (marker rs11628713, allelic P = 6.2×10−7, odds ratio = 4.7, permutation P = 0.01). A second marker was associated at the experiment-wide adjusted P = 0.06 level (rs10903034, allelic P = 3.02×10−6, odds ratio = 2.7, permutation P = 0.06). These markers reside within the genes PAPLN and IL28RA, respectively. PAPLN encodes papilin, a protoglycan-like sulfated glycoprotein. IL28RA encodes an interleukin receptor. Conclusion Together with our earlier report, these findings may shed light on the biological basis of TESI and may help identify patients at increased risk of this potentially serious adverse event.

Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Objective The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the “Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder” scale currently used in the Consortium on Lithium Genetics (ConLiGen) study. Materials and Methods Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (κ)] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling. Results Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (κ = 0.66 and κ = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (ICC1 = 0.71 and ICC2 = 0.75, respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders). Conclusions We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.

Accuracy of CNV Detection from GWAS Data

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites—Birdsuite, Partek, HelixTree, and PennCNV-Affy—in the identification of both rare and common CNVs. Each programs performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuites call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two “gold standards,” the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a “gold standard” for detection of CNVs remains to be established.