• allelic association study;
  • ankyrin 3;
  • bipolar disorder;
  • DNA sequencing;
  • genetic;
  • L-type calcium channel


  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information


Genetic markers in the genes encoding ankyrin 3 (ANK3) and the α-calcium channel subunit (CACNA1C) are associated with bipolar disorder (BP). The associated variants in the CACNA1C gene are mainly within intron 3 of the gene. ANK3 BP-associated variants are in two distinct clusters at the ends of the gene, indicating disease allele heterogeneity.


In order to screen both coding and non-coding regions to identify potential aetiological variants, we used whole-genome sequencing in 99 BP cases. Variants with markedly different allele frequencies in the BP samples and the 1,000 genomes project European data were genotyped in 1,510 BP cases and 1,095 controls.


We found that the CACNA1C intron 3 variant, rs79398153, potentially affecting an ENCyclopedia of DNA Elements (ENCODE)-defined region, showed an association with BP (p = 0.015). We also found the ANK3 BP-associated variant rs139972937, responsible for an asparagine to serine change (p = 0.042). However, a previous study had not found support for an association between rs139972937 and BP. The variants at ANK3 and CACNA1C previously known to be associated with BP were not in linkage disequilibrium with either of the two variants that we identified and these are therefore independent of the previous haplotypes implicated by genome-wide association.


Sequencing in additional BP samples is needed to find the molecular pathology that explains the previous association findings. If changes similar to those we have found can be shown to have an effect on the expression and function of ANK3 and CACNA1C, they might help to explain the so-called ‘missing heritability’ of BP.

Bipolar disorder (BP) is a common disease with a worldwide average population prevalence of 1.4%, which rises to 2.4% if bipolar spectrum disorders are included [1]. Twin and family studies indicate that BP is genetically related to some types of unipolar affective disorder [2]. The genetic heritability of BP is thought to be between 79% and 93% [3-6], with a ten-fold increase in risk to the relatives of probands with BP [7]. Many linkage studies of specific chromosomal regions and whole genomes in multiply affected families support the presence of locus heterogeneity, with multiple susceptibility loci [8-10]. About half of the segregation analyses of systematically ascertained families imply that BP has an autosomal dominant mode of inheritance [11]. Other models have favoured a single major locus with a polygenic multifactorial background and pure polygenic transmission. Linkage and linkage disequilibrium (LD) analyses demonstrate locus heterogeneity [12, 13]. Genome-wide association studies (GWAS), meta-analyses, and replication studies focusing on BP have been carried out on combined cohort sizes of up to 7,481 cases and 9,250 controls [14-17]. These and other single-locus case–control association studies have repeatedly implicated the L-type calcium channel α1C subunit (CACNA1C) and ankyrin 3 (ANK3) genes in BP. The strongest allelic association signal in CACNA1C is localized entirely within intron 3 of the gene with the single nucleotide polymorphisms (SNPs) rs1006737 (p = 7.0 ×10−8) [14, 18, 19], rs4765913 (p = 1.52 × 10−8) [14], rs4765914 (p = 1.52 × 10−8) [20], and rs1024582 (p = 1.7 × 10−7) [17, 21]. GWAS results across five different psychiatric illnesses further implicate rs1024582 in susceptibility to both BP and schizophrenia, assuming that there has not been substantial misdiagnosis, especially where schizoaffective BP cases are included in the schizophrenia group [20]. Intron 3 of CACNA1C contains a chromosomal region with high levels of LD, strong mammalian conservation, and multiple sites designated by the ENCyclopedia of DNA Elements (ENCODE) project as being able to affect gene expression. Studies show that that the presence of the rs1006737 CACNA1C BP risk variant may have an impact on certain brain activities. One study showed that the rs1006737 risk variant in healthy males is associated with lower extraversion, trait anxiety, paranoid ideation, and higher harm avoidance [22]. The rs1006737 risk variant has been associated with increased amygdala functioning observed by magnetic resonance imaging during emotional processing; the enhancement of activation leads to impaired facial emotion recognition in BP patients [20, 23-26]. There has been conflicting evidence as to whether the presence of the CACNA1C variant results in brain volumetric alteration. Some reports state that this SNP has been associated with brainstem alterations, increased grey matter density, as well as a cortical volume increase [27-29]. A conflicting study did not report any association between this SNP and brain volumetric alterations [30]. Mutations/variants located in intronic regions can also affect the stability of RNA and protein expression, and can have a strong effect on the transcriptional regulation of the gene.

In ANK3, the strongest evidence for allelic association comes from SNPs rs10994338 (p = 1.20 ×10−7) [31], rs4948418 (p = 8.93 × 10−9) [15], rs10994336 (p = 9.1 × 10−9) [14, 26, 32-34], rs10994397 (p = 7.1 × 10−9) [17] at the 5′ end, and the SNP rs9804190 (p = 1.20 × 10−4) [17, 26, 35] at the 3′ end of the longest isoform (NM_001204403) of the gene. These regions are over 340 kb apart and appear to be independently associated with BP, with no significant interactions between SNPs from the two regions [32]. However, the existing data on ANK3 show that only low-frequency aetiological base-pair (bp) changes are present with an odds ratio less than 1.35 for BP [17]. The SNP associations are not replicated in every study [36-39]; however, the ANK3 association has been reported in several different ancestral populations [36, 40-42]. Several novel, rare potential aetiological bp changes have been identified by us through sequencing the gene in our samples. These were selected for having haplotypes associated with BP [43]. Doyle et al. [44] sequenced the 8 kb brain-expressed exon 48 of ANK3 but could not find potential aetiological bp changes that were associated with BP. This exon is of recent evolutionary history, and variation in the exon appears to be tolerated. Sequencing analysis of ANK3 demonstrated the impact of heterogeneity on replication of allelic associations, even within well-defined ancestral populations [43]. mRNA analysis has detected differential regulation of distinct ANK3 transcription start sites and coupling of specific 5′ ends with 3′ mRNA splicing events, suggesting that brain-specific cis-regulatory transcriptional changes might be relevant to BP molecular pathology [45]. Gene network analysis and test of epistasis have found further support for an association of ANK3 with BP [46, 47]. The genetic variants associated with disease have no known biological function. However, one study showed that the presence of the rs10994336 BP risk variant in healthy males might predict lower novelty seeking, lower behavioural activation scores, and high startle reactivity [22]. In healthy volunteers, rs10994336 may be associated with reduced white matter integrity in the anterior limb of the internal capsule, as well as with altered set-shifting and decision-making [48]. These findings may be consistent with previous diffusion tensor imaging studies in patients with BP [49-54] and core phenotypes of BP [55-58]. Lithium has been shown to alter Ank3 mRNA levels in the mouse brain [59], and lithium and sodium valproate have been shown to change Ank3 protein amounts in rat neuronal dendritic spines [60]. In another animal model, RNA interference of Ank3 in the hippocampus dentate gyrus induced a reduction of anxiety-related behaviours and increased activity during the light phase, which were attenuated by chronic treatment with the mood stabilizer, lithium. Similar behavioural alterations of reduced anxiety and increased motivation for reward were also exhibited by Ank3+/− heterozygous mice compared with wild-type Ank3+/+ mice [61].

Given the typical natural history of BP, which consists of episodes of both mania and depression with complete recovery very often between episodes, it can be argued that genetic susceptibility will involve aetiological bp changes influencing the control of gene expression and mRNA translation rather than mutations creating structural protein abnormalities. Therefore, we chose whole-genome sequencing (WGS) rather than exome sequencing in order to be able to investigate intronic and non-coding control regions of susceptibility genes along with the exonic coding regions.

Materials and methods

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information


This study included 1,510 affected research subjects with BP. These were sampled in three cohorts. The first cohort, UCL1, included 506 research subjects with bipolar I disorder (BP-I), defined by the presence of mania and hospitalization according to Research Diagnostic Criteria (RDC) [62]. UCL1 was included in the previously reported mega-analysis by the Psychiatric Genetic Consortium (PGC) BP GWAS [17]. The second and third cohorts, UCL2 and UCL3, consisted, respectively, of 593 and 411 subjects with BP-I or bipolar II disorder (BP-II). Ancestry screening was used as a selection criterion for the inclusion of cases. Samples were included if at least three out of four grandparents were English, Irish, Scottish, or Welsh and if the fourth grandparent was non-Jewish European, before the European Union enlargement in 2004. The sample of 1,095 controls comprised 614 screened subjects who had no first-degree family or personal history of psychiatric illness and an additional 481 unscreened normal British subjects, obtained from the European Collection of Animal Cell Cultures (ECACC). National Health Service (NHS) multicentre research ethics approval was obtained. All participants provided signed consent.

Research subjects with BP had been given an NHS clinical diagnosis of ICD-10 BP and then needed to fulfil RDC [62] for BP with clinical data collected by the lifetime version of the Schizophrenia and Affective Disorder Schedule (SADS-L) [63]. DNA samples were collected from blood samples from the UCL1 cohort, saliva samples for the UCL2 cohort, and a mixture of both blood and saliva for the UCL3 samples. DNA from blood samples was extracted using a standard phenol–chloroform method and from saliva samples using the Oragene protocol for DNA extraction (DNA Genotek, Ottawa, ON, Canada).


WGS was performed on 99 of the subjects with BP-I selected from all our cohorts who had a positive family history of BP or bipolar spectrum disorder and an early age at onset. The genomic DNA was sequenced using 100 bp paired-end reads on a Hi-Seq 1000 (Illumina Inc., San Diego, CA, USA). Sequence data alignment to the National Center for Biotechnology Information human reference genome 37.1 (hg19) and variant calling was performed using the CASAVA 1.8.2 pipeline at Illumina ( The sequence data from these individuals were further analysed and annotated using kGAP (Knome Inc., Boston, MA, USA).

Variant selection

ANK3 and CACNA1C non-synonymous variants present in the coding exons were identified using the Knome VARIANTS software (Knome Inc.) (Supplementary Table 1). The same software was used to identify variants in the 5′ untranslated region (UTR), 3′UTR, splicing sites [donor site consists of 5 bp in the exon and 6 bp in the intron, acceptor site consist of 3 bp in the exon and 20 bp in the intron [64]], promoter region (1,000 bp from the first exon of every coding isoform), and the third intron of CACNA1C (Supplementary Table 1, Supplementary Fig. 1, Supplementary Fig. 2). Allele counts for each SNP in the BP samples were compared to those from the 372 European samples in the 1,000 Genomes (1,000G) Project (phase 1, version 3; SNPs for which the variant allele was more common in subjects with BP than in the 1,000G Project data, significant at p < 0.05 using Fisher's exact test, were chosen for genotyping in the complete UCL case–control sample. Variants which were present in poly-base regions and insertions in repeat regions were excluded from genotyping.

The variants in the third intron of CACNA1C were selected if they met four criteria:

  1. Located in the third intron of CACNA1C between flanking high recombination peaks (chr12:2271532-2425994 hg19);
  2. Located in a putative functional site defined by being an ENCODE-marked element (65);
  3. Located in a conserved non-coding sequence, determined using the mammalian conservation track on the University of California Santa Cruz (UCSC) genome browser ( or by their Genomic Evolutionary Rate Profiling (GERP) scores;
  4. Not in a repeat region.

Each variant was validated by confirming the bp call confidence using individual Binary Alignment/Map (BAM) files before genotyping. Bioinformatic analysis to determine potentially functional SNPs was carried out using the UCSC genome browser, Alibaba2.1 (, targetscan 6.2 (, miRanda (, PolyPhen-2 (, and Sorting Intolerant From Tolerant (SIFT) (


Genotyping for the selected SNPs in 1,510 BP cases (UCL1, UCL2, and UCL3 samples) and 1,095 ancestrally matched controls was performed in-house with allele-specific polymerase chain reaction (PCR) using KASPar reagents (KBiosciences, Hoddesdon, UK) on a LightCycler 480 (Roche, Burgess Hill, UK) real-time PCR machine. For all SNPs genotyped, 17% of samples were duplicated to detect error and confirm the reproducibility of genotypes. Allele-specific primers were designed for each of the SNPs using Primer Picker (KBiosciences), as shown in Supplementary Table 2. All these data were analysed to confirm Hardy–Weinberg equilibrium (HWE). Allelic associations for SNPs were performed using Fisher's Exact test. Significance values shown for all analyses are uncorrected for multiple testing, and a cutoff significance value of p < 0.05 was used.

Burden analysis

A burden analysis was performed on the data separately for ANK3 and CACNA1C. A chi-square test was used to compare the numbers of case and control individuals carrying one or more of the variant alleles against the numbers of case and control individuals who were found to be homozygous for the reference alleles at all of the loci tested.

Haplotype analysis

Haplotype analysis was performed using Haploview [66] to determine the LD between GWAS-associated SNPs and the rare variants reported here. Haplotype blocks were determined using a solid spine of LD (D′ = 1).


  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information

Variant calling and selection

WGS in 99 samples with BP produced a mean depth coverage of 37.0 with 90% of the genome sequenced. A total of 0.12% of bases were heterozygous and the transition/transversion (Ti/Tv) ratio was 2.0 (see Supplementary Table 3).

Using the criteria set out above, 82 ANK3 and 43 CACNA1C variants were identified in the coding exons, 5′UTR, 3′UTR, splicing sites, and promoter region; and a further 108 CACNA1C variants were identified in the intron 3 region 12:2271532-2425994 (Supplementary Table 1, Supplementary Fig. 1, Supplementary Fig. 2).

These variants were further filtered using a cutoff threshold of p < 0.05 using Fisher's exact test against the 1,000G Project [67] European allele frequencies. After filtering, three variants remained in ANK3 and these comprised two known SNPs, rs184389434 and rs139972937, and a previously unreported SNP at position ss825679002; ten CACNA1C variants remained after filtering and these comprised five known SNPs (rs146482058, rs79398153, rs191953785, rs112312080, and rs113414207) and four previously unreported variants (ss825679004, ss825679005, ss825679006, and ss825679007 (Table 1, Supplementary Fig. 1, Supplementary Fig. 2).

Table 1. Test of association with ANK3 and CACNA1C variants with bipolar disorder
GeneSNPLocation (hg19)Position in geneChangeEuropean 1,000G MAFMLP Number of samplesGenotype countsMAFp-valuea
  1. 1,000G = 1,000 Genomes; ANK3 = ankyrin 3; BP = bipolar disorder; CACNA1C = L-type calcium channel α1C subunit; MAF = minor allele frequency; SNP = single nucleotide polymorphism; UTR = untranslated region; European 1,000G MAF = MAF for European samples in the 1,000G Project [72]; MLP = minus log10 of Fisher's exact p-value comparing UCL whole-genome sequence allele frequency to the European 1,000G MAF.

  2. a

    p-significance value for a Fisher's exact test.

  3. b

    H3K4Me1, H3K4Me3, and H3K27Ac marks.

  4. c

    DNAse hypersensitivity cluster marks.

  5. d

    Human mRNA.

  6. e

    Conserved region. The distributions of genotype data for all SNPs were in Hardy–Weinberg equilibrium in the cases and controls.

ANK3 rs18438943410: 62493837PromoterA/T01.39BP1,4690/15/14540.00510.41
ANK3 ss82567900210: 617886263′UTRC/A01.39BP1,4670/36/14310.0120.35
ANK3 rs13997293710: 61832711Exon (N2643S)A/G01.39BP1,4740/9/14650.00310.042
CACNA1C ss82567900412: 2161934PromoterG/A01.39BP1,4670/5/14620.00170.57
CACNA1C ss82567900512: 2694668Splice siteG/A01.39BP1,4730/3/14700.00100.7
CACNA1C rs14648205812: 2403077Intronb,e–/T010.9BP1,4863/134/13220.0480.31
CACNA1C rs7939815312: 2295156Intronb,eC/T0.011.57BP1,4983/88/13800.0320.015
CACNA1C rs19195378512: 2425097Intronb,eC/T02.29BP1,4750/25/14500.00850.34
CACNA1C rs11231208012: 2354510Intronb,c,eC/T0.0012.02BP1,5010/35/14390.0120.30
CACNA1C rs11341420712: 2292742-2292743Intronb,d,e–/C02.15BP1,4970/76/13940.0260.19
CACNA1C ss82567900612: 2329069Intronb,d,eG/T02.15BP1,4980/14/14570.00480.43
CACNA1C ss82567900712: 2423175Intronb,c,d,eG/C02.15BP1,5020/4/14710.00140.34

The ANK3 variant rs184389434 is located in the promoter region of the gene and was predicted to create a binding site for three new transcription factors [ETS-related gene (Erg-1), Ultrabithorax (Ubx) and Octamen-1 (Oct-1)]. rs139972937 causes a non-conservative amino acid change from asparagine to serine at position 2,643 (N2643S) in exon 34 of the alternative isoforms NM_020987.3 and CCDS7258.1. The N2643S amino acid substitution was predicted to be benign with a score of 0 (sensitivity 1, specificity 0) by PolyPhen-2 and tolerated with a score of 0.71 by SIFT. The previously unreported ANK3 variant, ss825679002, was located in the 3′UTR of the gene and was found to be in a microRNA binding site. Bioinformatic analysis using targetscan and miRanda predicted no effect on microRNA binding.

One of the novel variants in CACNA1C, ss825679004, was in the promoter region of the gene. Alibaba 2.1 analysis of ss825679004 predicted it to disrupt the binding sites for three transcription factors [Activating Enhancer Binding Protein-2alpha (AP-2alph), NF-muE1, Specificity Protein-1 (Sp1)] and to create a new one for a different transcription factor [GC Factor (GCF)]. CACNA1C variant ss825679005 is the sixth base in the intron of the splice donor site for exon 17. This exon is present in all known isoforms of the gene and this variant might alter splicing efficiency.

The CACNA1C intron 3 variants rs146482058, rs79398153, rs191953785, rs112312080, rs113414207, ss825679006, and ss825679007 were present in the region of high LD between chr12:2,230,353 and chr12:2,559,413. Each variant was also located in an ENCODE marked region [65]. All seven SNP regions are marked by H3 mono-methylation of lysine 4 (H3K4me1), H3 tri-methylation of lysine 4 (H3K4me3), and H3 acetylation of lysine 27 (H3K27ac), and active transcriptional enhancers with distinct chromatin signatures [68]. Enrichment for H3K4me1 and H3K27ac at a genetic level distinguishes active enhancers from inactive or poised enhancers [69, 70]. The presence of H3K4me1- and H3K27ac-marked chromatin, with low levels of H3K4me3 and an absence of another histone marker, H3K27me3, represent putative human embryonic stem cell (hESC) enhancers and have been shown to localize proximally to genes that are expressed during development in hESCs and in epiblast cells [70]. Additionally, rs112312080 and ss825679007 were found to be present on DNAse I hypersensitivity sites, as listed by the ENCODE project.


Assays were designed for 13 SNPs which passed filtering tests for genotyping in the complete UCL BP case–control sample. Genotype data were generated for 12 of these variants and the genotype distributions for each SNP followed HWE in the case and control cohorts. The non-synonymous ANK3 variant rs139972937 was found to be associated with BP (Fisher's exact test p = 0.042) (Table 1). Nine cases with BP and only one control were found to be heterozygous for this variant. None of the other ANK3 variants were found to be associated with BP, as shown in Table 1.

Of the SNPs found in the CACNA1C intronic region, rs79398153 was found to be associated with BP (Fisher's exact test p = 0.015). We detected 88 heterozygote and three homozygote cases for this variant and 44 heterozygote controls. The excess of homozygotes may possibly represent a recessive effect, as only one homozygote would be expected under HWE, but this excess is not statistically significant [71]. rs79398153 is located in an ENCODE-marked region for H3K4me1, H3K27ac, and H3Kme3. None of the other intronic CACNA1C SNPs were associated with BP. Imputation for rs79398153 in UCL1 using GWAS data showed that it was still significantly associated with BP (p = 0.022) [17]. Burden analysis showed that, overall, there was no excess of the variants genotyped in cases versus controls for either CACNA1C or ANK3.

Haplotype and LD analysis at ANK3 and CACNA1C was performed separately in Haploview [66] to examine the co-occurrence of the BP GWAS SNP alleles [ANK3 rs10994285, rs2018783, rs10994336, rs10994397, rs10821792, rs1938526 [14, 26, 32-34]; CACNA1C rs1006737 [14]; rs4765913 [14]; rs476590 [31]; and rs4765914 [20]] with the BP risk variant alleles (rs139972937, allele G; rs79398153, allele T). For both sets of analyses, the BP risk variant alleles reported here were found to be associated with the GWAS SNP alleles that were more common in the control subjects. Thus, these variants could not be accounting for the GWAS signals. The results of the LD analysis are shown in Table 2.

Table 2. Pairwise linkage disequilibrium analysis between bipolar disorder-associated SNPs reported here and previous GWAS SNPs
GeneMarker 1Marker 2D′ r 2 LOD
  1. ANK3 = ankyrin; CACNA1C = L-type calcium channel α1C subunit; GWAS = genome-wide association studies; LOD = logarithm of the odds; SNPs = single nucleotide polymorphisms.

ANK3 rs139972937rs10994285100.17
ANK3 rs139972937rs201878310.0020.51
ANK3 rs139972937rs10994336100.03
ANK3 rs139972937rs10994397100.03
ANK3 rs139972937rs10821792100.21
ANK3 rs139972937rs1938526100.26
CACNA1C rs79398153rs10067370.7540.0161.06
CACNA1C rs79398153rs10245820.7290.0140.87
CACNA1C rs79398153rs47659130.8220.0292.12
CACNA1C rs79398153rs47659140.8290.0322.31


  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information

We have analysed genetic variation by WGS in two of the best-replicated bipolar susceptibility genes, CACNA1C and ANK3. This analysis has identified novel possible BP susceptibility variants in both of these genes. The CACNA1C intron 3 variant rs79398153 may impact CACNA1C gene expression by virtue of its presence in an ENCODE-marked transcriptional enhancer region.

The ANK3 amino acid changing variant, rs139972937 (N2643S), was associated with BP in our sample (p = 0.042). This rare variant was also found in two of 1,119 cases and one of 1,078 controls and in a family containing seven subjects with BP, a father and six offspring, where only the father and two of the offspring possessed the variant [44]. These conflicting findings are not uncommon in the genetics of complex diseases but this lack of support casts doubt on the true aetiological importance of this variant in BP.

It is of note that the allele frequencies of some of the variants selected for genotyping were found to be markedly different in our control samples compared to the frequencies in the European 1,000G Project. This underlies the importance of typing variants in matched control samples on the same platform rather than relying on publically available data such as the 1,000G Project in order to mitigate possible spurious association findings.

The variants we have found appear to be acting independently of the allelic and haplotypic associations found in the previous BP allelic association studies. Independent genetic replication and biological validation of intronic potential aetiological bp changes would support the argument for carrying out WGS as well as exome sequencing in BP. The biphasic nature of BP makes a compelling argument for the existence of genetically determined pathological switch mechanisms that may manifest themselves in the loss of control of gene expression. Findings such as ours may help to explain the ‘missing heritability’ in this common complex disorder. Further analyses in much larger samples are needed to find aetiological bp changes in the ANK3 and CACNA1C genes that are carried by the main haplotypes showing strong association with BP. The outcome could be personalized treatment for BP, based on susceptibility genotypes.


  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information

The UCL clinical and control samples were collected with the support from the Bipolar Organization, the Neuroscience Research Charitable Trust, the Central London NHS Blood Transfusion Service, The Stanley Medical Research Institute, Cheshire and Wirral Partnership NHS Foundation Trust, Cumbria Partnership NHS Foundation Trust, Cambridgeshire and Peterborough NHS Foundation Trust, Suffolk Mental Health Partnership NHS Trust, South Essex Partnership University NHS Foundation Trust (in services based in Bedfordshire and Luton), West London Mental Health NHS Trust, Camden and Islington NHS Foundation Trust, East London NHS Foundation Trust, North East London Mental Health NHS Trust, Hertfordshire Partnership NHS Foundation Trust, Berkshire Healthcare NHS Foundation Trust, North Essex Partnership NHS Foundation Trust, Oxfordshire and Buckinghamshire Mental Health NHS Foundation Trust, South Essex Partnership University NHS Foundation Trust, South London and Maudsley NHS Foundation Trust, Oxleas NHS Foundation Trust, Surrey and Borders Partnership NHS Foundation Trust, Kent and Medway NHS and Social Care Partnership Trust, South West London and St George's Mental Health NHS Trust, Sussex Partnership Trust, South Essex Partnership University NHS Foundation Trust, Cornwall Partnership NHS Trust, Somerset Partnership NHS Foundation Trust, Salisbury NHS Foundation Trust, Central and North West London NHS Foundation Trust, the National Institute for Health Research Mental Health Research Network, and the NIHR-supported Primary Care Research Network. Genetic analysis of the UCL cohort has been supported by UK Medical Research Council project grants G9623693N, G0500791, G0701007, and G1000708. NLOB is supported by a joint Ph.D. studentship funded by a UCL IMPACT award and Equilibrium, the Bipolar Foundation. RK was funded by a UK government Overseas Research Student award. The Stanley Foundation and the Stanley Psychiatric Research Center at the Broad Institute, Boston, MA, USA, funded the genome-wide association study.


  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information

The authors of this paper do not have any commercial associations that might pose a conflict of interest in connection with this manuscript.


  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information
  • 1
    Merikangas KR, Jin R, He JP et al. Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Arch Gen Psychiatry 2011; 68: 241251.
  • 2
    Bertelsen A. A Danish twin study of manic-depressive disorders. Br J Psychiatry 1987; 130: 330351.
  • 3
    Barnett JH, Smoller JW. The genetics of bipolar disorder. Neurosci 2009; 164: 331343.
  • 4
    Kendler KS, Pedersen NL, Farahmand BY, Persson PG. The treated incidence of psychotic and affective illness in twins compared with population expectation: a study in the Swedish Twin and Psychiatric Registries. Psychol Med 1996; 26: 11351144.
  • 5
    Kieseppa T, Partonen T, Haukka J, Kaprio J, Lonnqvist J. High concordance of bipolar I disorder in a nationwide sample of twins. Am J Psychiatry 2004; 161: 18141821.
  • 6
    McGuffin P, Rijsdijk F, Andrew M et al. The heritability of bipolar affective disorder and the genetic relationship to unipolar depression. Arch Gen Psychiatry 2003; 60: 497502.
  • 7
    Shih RA, Belmonte PL, Zandi PP. A review of the evidence from family, twin and adoption studies for a genetic contribution to adult psychiatric disorders. Int Rev Psychiatry 2004; 16: 260283.
  • 8
    Badner JA, Gershon ES. Meta-analysis of whole-genome linkage scans of bipolar disorder and schizophrenia. Mol Psychiatry 2002; 7: 405411.
  • 9
    Segurado R, Detera-Wadleigh SD, Levinson DF et al. Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: bipolar disorder. Am J Hum Genet 2003; 73: 4962.
  • 10
    McQueen MB, Devlin B, Faraone SV et al. Combined analysis from eleven linkage studies of bipolar disorder provides strong evidence of susceptibility loci on chromosomes 6q and 8q. Am J Hum Genet 2005; 77: 582595.
  • 11
    Gurling H, Rifkin L. Genetic aspects of affective disorders. In: Horton KW, Katona C eds. Biological Aspects of Affective Disorders. London: Academic Press, 1991: 305329.
  • 12
    Spence MA, Flodman PL, Sadovnick AD et al. Bipolar disorder: evidence for a major locus. Am J Med Genet 1995; 60: 370376.
  • 13
    Craddock N, Khodel V, Van Eerdewegh P, Reich T. Mathematical limits of multilocus models: the genetic transmission of bipolar disorder. Am J Hum Genet 1995; 57: 690702.
  • 14
    Ferreira MA, O'Donovan MC, Meng YA et al. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 2008; 40: 10561058.
  • 15
    Chen DT, Jiang X, Akula N et al. Genome-wide association study meta-analysis of European and Asian-ancestry samples identifies three novel loci associated with bipolar disorder. Mol Psychiatry 2013; 18: 195205.
  • 16
    Wray NR, Pergadia ML, Blackwood DH et al. Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned. Mol Psychiatry 2012; 17: 3648.
  • 17
    Sklar P, Ripke S, Scott LJ et al. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet 2011; 43: 977983.
  • 18
    Sklar P, Smoller JW, Fan J et al. Whole-genome association study of bipolar disorder. Mol Psychiatry 2008; 13: 558569.
  • 19
    Consortium WTCC. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007; 447: 661678.
  • 20
    Smoller JW, Craddock N, Kendler K et al. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 2013; 381: 13711379.
  • 21
    Group PGCBDW. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet 2011; 43: 977983.
  • 22
    Roussos P, Giakoumaki SG, Georgakopoulos A, Robakis NK, Bitsios P. The CACNA1C and ANK3 risk alleles impact on affective personality traits and startle reactivity but not on cognition or gating in healthy males. Bipolar Disord 2011; 13: 250259.
  • 23
    Jogia J, Ruberto G, Lelli-Chiesa G et al. The impact of the CACNA1C gene polymorphism on frontolimbic function in bipolar disorder. Mol Psychiatry 2011; 16: 10701071.
  • 24
    Bhat S, Dao DT, Terrillion CE et al. CACNA1C (Cav1.2) in the pathophysiology of psychiatric disease. Prog Neurobiol 2012; 99: 114.
  • 25
    Small SA, Schobel SA, Buxton RB, Witter MP, Barnes CA. A pathophysiological framework of hippocampal dysfunction in ageing and disease. Nat Rev Neurosci 2011; 12: 585601.
  • 26
    Tesli M, Koefoed P, Athanasiu L et al. Association analysis of ANK3 gene variants in nordic bipolar disorder and schizophrenia case–control samples. Am J Med Genet B Neuropsychiatr Genet 2011; 156B: 969974.
  • 27
    Franke B, Vasquez AA, Veltman JA et al. Genetic variation in CACNA1C, a gene associated with bipolar disorder, influences brainstem rather than gray matter volume in healthy individuals. Biol Psychiatry 2010; 68: 586588.
  • 28
    Perrier E, Pompei F, Ruberto G et al. Initial evidence for the role of CACNA1C on subcortical brain morphology in patients with bipolar disorder. Eur Psychiatry 2011; 26: 135137.
  • 29
    Kempton MJ, Ruberto G, Vassos E et al. Effects of the CACNA1C risk allele for bipolar disorder on cerebral gray matter volume in healthy individuals. Am J Psychiatry 2009; 166: 14131414.
  • 30
    Tesli M, Egeland R, Sønderby IE et al. No evidence for association between bipolar disorder risk gene variants and brain structural phenotypes. J Affect Disord 2013; 151: 291297.
  • 31
    Liu Y, Blackwood DH, Caesar S et al. Meta-analysis of genome-wide association data of bipolar disorder and major depressive disorder. Mol Psychiatry 2011; 16: 24.
  • 32
    Schulze TG, Detera-Wadleigh SD, Akula N et al. Two variants in Ankyrin 3 (ANK3) are independent genetic risk factors for bipolar disorder. Mol Psychiatry 2009; 14: 487491.
  • 33
    Scott LJ, Muglia P, Kong XQ et al. Genome-wide association and meta-analysis of bipolar disorder in individuals of European ancestry. Proc Natl Acad Sci U S A 2009; 106: 75017506.
  • 34
    Lett TA, Zai CC, Tiwari AK et al. ANK3, CACNA1C and ZNF804A gene variants in bipolar disorders and psychosis subphenotype. World J Biol Psychiatry 2011; 12: 392397.
  • 35
    Smith EN, Bloss CS, Badner JA et al. Genome-wide association study of bipolar disorder in European American and African American individuals. Mol Psychiatry 2009; 14: 755763.
  • 36
    Belmonte Mahon P, Pirooznia M, Goes FS et al. Genome-wide association analysis of age at onset and psychotic symptoms in bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2011; 156B: 370378.
  • 37
    Green EK, Hamshere M, Forty L et al. Replication of bipolar disorder susceptibility alleles and identification of two novel genome-wide significant associations in a new bipolar disorder case–control sample. Mol Psychiatry 2013; 18: 13021307.
  • 38
    Gella A, Segura M, Durany N et al. Is Ankyrin a genetic risk factor for psychiatric phenotypes? BMC Psychiatry 2011; 11: 103.
  • 39
    Kloiber S, Czamara D, Karbalai N et al. ANK3 and CACNA1C–missing genetic link for bipolar disorder and major depressive disorder in two German case–control samples. J Psychiatr Res 2012; 46: 973979.
  • 40
    Takata A, Kim SH, Ozaki N et al. Association of ANK3 with bipolar disorder confirmed in East Asia. Am J Med Genet B Neuropsychiatr Genet 2011; 156B: 312315.
  • 41
    Lee MT, Chen CH, Lee CS et al. Genome-wide association study of bipolar I disorder in the Han Chinese population. Mol Psychiatry 2011; 16: 548556.
  • 42
    Gonzalez SD, Xu C, Ramirez ME et al. Family-based association of an ANK3 haplotype with bipolar disorder in Latino populations. Transl Psychiatry 2013; 3: e265.
  • 43
    Dedman A, McQuillin A, Kandaswamy R et al. Sequencing of the ANKYRIN 3 gene (ANK3) encoding ankyrin G in bipolar disorder reveals a non-conservative amino acid change in a short isoform of ankyrin G. Am J Med Genet B Neuropsychiatr Genet 2012; 159B: 328335.
  • 44
    Doyle GA, Lai AT, Chou AD et al. Re-sequencing of ankyrin 3 exon 48 and case–control association analysis of rare variants in bipolar disorder type I. Bipolar Disord 2012; 14: 809821.
  • 45
    Rueckert EH, Barker D, Ruderfer D et al. Cis-acting regulation of brain-specific ANK3 gene expression by a genetic variant associated with bipolar disorder. Mol Psychiatry 2013; 18: 922929.
  • 46
    Pandey A, Davis NA, White BC et al. Epistasis network centrality analysis yields pathway replication across two GWAS cohorts for bipolar disorder. Transl Psychiatry 2012; 2: e154.
  • 47
    Judy JT, Seifuddin F, Pirooznia M et al. Converging evidence for epistasis between ANK3 and potassium channel gene KCNQ2 in bipolar disorder. Front Genet 2013; 4: 87.
  • 48
    Linke J, Witt SH, King AV et al. Genome-wide supported risk variant for bipolar disorder alters anatomical connectivity in the human brain. Neuroimage 2012; 59: 32883296.
  • 49
    Chaddock CA, Barker GJ, Marshall N et al. White matter microstructural impairments and genetic liability to familial bipolar I disorder. Br J Psychiatry 2009; 194: 527534.
  • 50
    Sussmann JE, Lymer GK, McKirdy J et al. White matter abnormalities in bipolar disorder and schizophrenia detected using diffusion tensor magnetic resonance imaging. Bipolar Disord 2009; 11: 1118.
  • 51
    McIntosh AM, Muñoz Maniega S, Lymer GK et al. White matter tractography in bipolar disorder and schizophrenia. Biol Psychiatry 2008; 64: 10881092.
  • 52
    McIntosh AM, Job DE, Moorhead TW et al. White matter density in patients with schizophrenia, bipolar disorder and their unaffected relatives. Biol Psychiatry 2005; 58: 254257.
  • 53
    Lin F, Weng S, Xie B, Wu G, Lei H. Abnormal frontal cortex white matter connections in bipolar disorder: a DTI tractography study. J Affect Disord 2011; 131: 299306.
  • 54
    Sui J, Adali T, Pearlson GD, Calhoun VD. An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques. Neuroimage 2009; 46: 7386.
  • 55
    Adida M, Jollant F, Clark L et al. Trait-related decision-making impairment in the three phases of bipolar disorder. Biol Psychiatry 2011; 70: 357365.
  • 56
    Bora E, Yucel M, Pantelis C. Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. J Affect Disord 2009; 113: 120.
  • 57
    Chandler RA, Wakeley J, Goodwin GM, Rogers RD. Altered risk-aversion and risk-seeking behavior in bipolar disorder. Biol Psychiatry 2009; 66: 840846.
  • 58
    McKirdy J, Sussmann JE, Hall J et al. Set shifting and reversal learning in patients with bipolar disorder or schizophrenia. Psychol Med 2009; 39: 12891293.
  • 59
    McQuillin A, Rizig M, Gurling HM. A microarray gene expression study of the molecular pharmacology of lithium carbonate on mouse brain mRNA to understand the neurobiology of mood stabilization and treatment of bipolar affective disorder. Pharmacogenet Genomics 2007; 17: 605617.
  • 60
    Nanavati D, Austin DR, Catapano LA et al. The effects of chronic treatment with mood stabilizers on the rat hippocampal post-synaptic density proteome. J Neurochem 2011; 119: 617629.
  • 61
    Leussis MP, Berry-Scott EM, Saito M et al. The ANK3 bipolar disorder gene regulates psychiatric-related behaviors that are modulated by lithium and stress. Biol Psychiatry 2013; 73: 683690.
  • 62
    Spitzer RL, Endicott J, Robins E. Research diagnostic criteria: rationale and reliability. Arch Gen Psychiatry 1978; 35: 773782.
  • 63
    Spitzer R, Endicott J. The Schedule for Affective Disorder and Schizophrenia, Lifetime Version. New York, NY: New York State Psychiatric Institute, 1977.
  • 64
    Stephens RM, Schneider TD. Features of spliceosome evolution and function inferred from an analysis of the information at human splice sites. J Mol Biol 1992; 228: 11241136.
  • 65
    Consortium TEP. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science 2004; 306: 636640.
  • 66
    Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformat 2005; 21: 263265.
  • 67
    Jia P, Wang L, Fanous AH et al. A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia. J Med Genet 2012; 49: 96103.
  • 68
    Heintzman ND, Stuart RK, Hon G et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nat Genet 2007; 39: 311318.
  • 69
    Creyghton MP, Cheng AW, Welstead GG et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci U S A 2010; 107: 2193121936.
  • 70
    Rada-Iglesias A, Bajpai R, Swigut T et al. A unique chromatin signature uncovers early developmental enhancers in humans. Nature 2011; 470: 279283.
  • 71
    Curtis D. Consideration of plausible genetic architectures for schizophrenia and implications for analytic approaches in the era of next generation sequencing. Psychiatr Genet 2013; 23: 110.
  • 72
    Clarke L, Zheng-Bradley X, Smith R et al. The 1000 Genomes Project: data management and community access. Nat Methods 2012; 9: 459462.

Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Disclosures
  8. References
  9. Supporting Information
bdi12203-sup-0001-FigureS1.docWord document33K

Figure S1. The introns and exons of the different splice variants of the ANK3 gene are shown, along with the genomic regions of the gene that were analysed for variant selection. The locations of the variants detected by sequencing are shown, as are the variants that were selected for genotyping in the full case control sample.

bdi12203-sup-0002-FigureS2.docWord document50K

Figure S2. The introns and exons of the different splice variants of the CACNA1C gene are shown, along with the genomic regions of the gene that were analysed for variant selection. The locations of the variants detected by sequencing are shown, as are the variants that were selected for genotyping in the full case–control sample.


Table S1. Variants identified using the Knome VARIANTS software (Knome). VAF = variant allele(s) frequency.


Table S2. Allele-specific primers designed using Primer Picker (KBiosciences) for genotyping.


Table S3. Next Generation Sequencing Control information.

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.