Abstract
We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10−9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD’s polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
We display all of our results, from the variant and gene level, in a browser available at https://bipex.broadinstitute.org. Phenotype curation and QC are available at https://astheeggeggs.github.io/BipEx/. Data are available under the following EGS study accession numbers: EGAS00001005838, EGAS00001005841, EGAS00001005842, EGAS00001005843, EGAS00001005844, EGAS00001005845, EGAS00001005851, EGAS00001005852, EGAS00001005853, EGAS00001005854, EGAS00001005855, EGAS00001005856, EGAS00001005857, EGAS00001005858, EGAS00001005859 and EGAS00001005860. WES data generated under this study are also hosted via the Terra platform (https://app.terra.bio). The Terra environment, created by the Broad Institute, contains a system of workspace functionalities centered on data sharing and analysis. To gain access via Terra, please contact the corresponding authors directly. The GnomAD database can be accessed at gnomad.broadinstitute.org. We used the following pathway databases: Gene Ontology (geneontology.org), KEGG (https://www.genome.jp/kegg) and REACTOME (reactome.org/). GTEx tissue-specific enrichment gene sets are available at data.broadinstitute.org/alkesgroup/LDSCORE/LDSC_SEG_ldscores/.
Code availability
The code used to perform QC, analysis and plot creation is available at github.com/astheeggeggs/BipEx. Data were manipulated using Hail 0.2 and R (4.0.2) using data.table (1.13.0) and dplyr (1.0.1), and plotted with ggplot2 (3.3.2), ggsci (2.9), ggExtra (0.9), ggrepel (0.8.2), RColorBrewer (1.1–2) and gridExtra (2.3) in R (4.0.2).
References
Ferrari, A. J. et al. The prevalence and burden of bipolar disorder: findings from the Global Burden of Disease Study 2013. Bipolar Disord. 18, 440–450 (2016).
Polderman, T. J. C. et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 47, 702–709 (2015).
Stahl, E. A. et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat. Genet. 51, 793–803 (2019).
Brainstorm Consortium. et al. Analysis of shared heritability in common disorders of the brain. Science 360, eaap8757 (2018).
Mullins, N. et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.Nat. Genet. 53, 817–829 (2021).
Charney, A. W. et al. Contribution of rare copy number variants to bipolar disorder risk is limited to schizoaffective cases. Biol. Psychiatry 86, 110–119 (2019).
Ganna, A. et al. Quantifying the impact of rare and ultra-rare coding variation across the phenotypic spectrum. Am. J. Hum. Genet. 102, 1204–1211 (2018).
J., A., Crow, J. F. & Kimura, M. An introduction to population genetics theory. Popul. (Fr. Ed.). 26, 977 (1971).
Kryukov, G. V., Pennacchio, L. A. & Sunyaev, S. R. Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am. J. Hum. Genet. 80, 727–739 (2007).
Power, R. A. et al. Fecundity of patients with schizophrenia, autism, bipolar disorder, depression, anorexia nervosa, or substance abuse vs their unaffected siblings. JAMA Psychiatry 70, 22–30 (2013).
American Psychiatric Association, Task Force on DSM-IV. DSM-IV Sourcebook (American Psychiatric Publishing, 1998).
Janca, A., Ustün, T. B., Early, T. S. & Sartorius, N. The ICD-10 symptom checklist: a companion to the ICD-10 classification of mental and behavioural disorders. Soc. Psychiatry Psychiatr. Epidemiol. 28, 239–242 (1993).
Malaspina, D. et al. Schizoaffective disorder in the DSM-5. Schizophr. Res. 150, 21–25 (2013).
O’Connell, K. S. & Coombes, B. J. Genetic contributions to bipolar disorder: current status and future directions.Psychol. Med. 51, 2156–2167 (2021).
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5) (American Psychiatric Publishing, 2013).
Husson, T. et al. Identification of potential genetic risk factors for bipolar disorder by whole-exome sequencing. Transl. Psychiatry 8, 268 (2018).
Sul, J. H. et al. Contribution of common and rare variants to bipolar disorder susceptibility in extended pedigrees from population isolates. Transl. Psychiatry 10, 74 (2020).
Jia, X. et al. Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder. Mol. Psychiatry 26, 5239–5250 (2021).
Cruceanu, C. et al. Rare susceptibility variants for bipolar disorder suggest a role for G protein-coupled receptors. Mol. Psychiatry 23, 2050–2056 (2018).
Genovese, G. et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat. Neurosci. 19, 1433–1441 (2016).
Singh, T. et al. The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat. Genet. 49, 1167–1173 (2017).
McLaren, W. et al. The Ensembl variant effect predictor. Genome Biol. 17, 122 (2016).
Singh, T. et al. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature https://doi.org/10.1038/s41586-022-04556-w (2022).
Samocha, K. E., Kosmicki, J. A. & Karczewski, K. J. Regional missense constraint improves variant deleteriousness prediction. Preprint at bioRxiv https://doi.org/10.1101/148353 (2017).
Aguet, F. et al. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).
Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).
Hibar, D. P. et al. Subcortical volumetric abnormalities in bipolar disorder. Mol. Psychiatry 21, 1710–1716 (2016).
Ganna, A. et al. Ultra-rare disruptive and damaging mutations influence educational attainment in the general population. Nat. Neurosci. 19, 1563–1565 (2016).
Cotney, J. et al. The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment. Nat. Commun. 6, 6404 (2015).
Weyn-Vanhentenryck, S. M. et al. HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism. Cell Rep. 6, 1139–1152 (2014).
Sanders, S. J. et al. Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron 87, 1215–1233 (2015).
Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium & Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell 173, 1705–1715 (2018).
Trubetskoy, V. et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature https://doi.org/10.1038/s41586-022-04434-5 (2022).
Freland, L. & Beaulieu, J.-M. Inhibition of GSK3 by lithium, from single molecules to signaling networks. Front. Mol. Neurosci. 5, 14 (2012).
Kishore, B. K. & Ecelbarger, C. M. Lithium: a versatile tool for understanding renal physiology. Am. J. Physiol. Ren. Physiol. 304, F1139–F1149 (2013).
Jope, R. S. Lithium and GSK-3: one inhibitor, two inhibitory actions, multiple outcomes. Trends Pharmacol. Sci. 24, 441–443 (2003).
Satterstrom, F. K. et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of Autism. Cell 180, 568–584.e23 (2020).
Satterstrom, F. K. et al. Autism spectrum disorder and attention deficit hyperactivity disorder have a similar burden of rare protein-truncating variants. Nat. Neurosci. 22, 1961–1965 (2019).
Epi25 Collaborative. Ultra-rare genetic variation in the epilepsies: a whole-exome sequencing study of 17,606 individuals. Am. J. Hum. Genet. 105, 267–282 (2019).
Firth, H. V. et al. DECIPHER: database of chromosomal imbalance and phenotype in humans using ensembl resources. Am. J. Hum. Genet. 84, 524–533 (2009).
Tanji, C. et al. A-kinase anchoring protein AKAP220 binds to glycogen synthase kinase-3beta (GSK-3beta) and mediates protein kinase A-dependent inhibition of GSK-3beta. J. Biol. Chem. 277, 36955–36961 (2002).
Beurel, E., Grieco, S. F. & Jope, R. S. Glycogen synthase kinase-3 (GSK3): regulation, actions, and diseases. Pharmacol. Ther. 148, 114–131 (2015).
Howrigan, D. P. et al. Exome sequencing in schizophrenia-affected parent-offspring trios reveals risk conferred by protein-coding de novo mutations. Nat. Neurosci. 23, 185–193 (2020).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57, 289–300 (1995).
Van der Auwera, G. A. et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinforma. 43, 11.10.1–11.10.33 (2013).
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).
Ng, P. C. & Henikoff, S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 31, 3812–3814 (2003).
Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).
Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).
Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J. & Kircher, M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res. 47, D886–D894 (2019).
Chen, C.-Y. et al. Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records. Transl. Psychiatry 8, 86 (2018).
Murphy, S. et al. Instrumenting the health care enterprise for discovery research in the genomic era. Genome Res. 19, 1675–1681 (2009).
Wing, J. SCAN (Schedules for Clinical Assessment in Neuropsychiatry) and the PSE (Present State Examination) Tradition. Mental Health Outcome Measures 123–130 (Springer, 1996).
McGuffin, P., Farmer, A. & Harvey, I. A polydiagnostic application of operational criteria in studies of psychotic illness. Development and reliability of the OPCRIT system. Arch. Gen. Psychiatry 48, 764–770 (1991).
Acknowledgements
This study was supported by the Stanley Family Foundation; Kent and Elizabeth Dauten; National Institutes of Health grants R01 CA194393 (B.M.N.), R37 MH107649 (B.M.N.) and R01 MH085542 (J.W.S.); National Institute of Mental Health grants R01 MH090553 (R.O.), R01 MH095034 (E.A.S.) and U01 MH105578 (N.B.F.); UK Medical Research Council grants G1000708 (A.M.), MR/L010305/1 (M.J.O.) and MR/P005748/1 (M.J.O., M.C.O. and J.W.); ongoing grant support from Stanley Medical Research Institute (F.D., and R.Y.); and The Dalio Foundation (B.M.N.), who have enabled us to rapidly expand our data generation collections with the goal of moving toward better treatments for BD, schizophrenia and other psychiatric disorders. BSC grant support was provided by the National Institutes of Health grants R01 MH110437 (P.Z.), R01 MH085543 (C.S.) and RC2 AG036607 (C.S. and N.R.). We thank W. Ouwehand for contributing control samples for exome sequencing and E. Wigdor for thoughtful comments.
Author information
Authors and Affiliations
Contributions
B.M.N. initiated the project. A.R., A.M.M., A.M., N.B., D.C., R.Y., F.D., D.P., D.S.C., D.W.M., A.C., D.B., F.S.G., J.W.S., M.C.O., M.J.O., M.L., N.L.P., N.C., A.D.F., I.J., L.J., J.W., R.O., M.P.M.B., R.S.K. and R.A. led sample recruitment of the BipEx cohort collection. P.Z., F.S.G., W.W., E.A.S., X.J., C.S., N.R., L.S. and A.E.L. led sample recruitment and curation of the BSC cohorts. X.J., L.S. and A.E.L. curated sample genetic and phenotypic data in the BSC collection. S.B.C. managed sample collections, exome sequencing and data hosting. D.S.P. processed and curated exome sequence data, with assistance from D.P.H., T.S. and B.M.N. D.S.P. processed and curated phenotype data in coordination with A.V. and N.B.F. D.S.P. performed the core analyses in close coordination with B.M.N. and D.P.H. The main findings were interpreted by D.S.P., D.P.H. and B.M.N. M.S. and N.A.W created the bipex.broadinstitute.org browser. A.L. performed gene-based analyses in the BSC dataset. D.S.P. drafted the manuscript in close coordination with D.P.H. and B.M.N., with editing assistance from C.C., A.D.F., A.M., N.A.W., I.J., L.J., L.S., W.W., R.Y., R.O., L.J., M.L., C.-Y.C., D.C., A.V. and F.D. D.S.P., A.D.F., D.C., N.B.F., L.J., R.O., S.B.C., D.P.H. and B.M.N. addressed and responded to reviewer comments.
Corresponding authors
Ethics declarations
Competing interests
B.M.N. is a member of the scientific advisory board at Deep Genomics and Neumora and a consultant for Camp4 Therapeutics, Takeda Pharmaceutical and Biogen. A.M.M. has received speaker fees from Illumina and Janssen and research grant support from The Sackler Trust. M.L. has received speakers fees from Lundbeck Pharmaceuticals. M.J.O., M.C.O. and J.W. have received a research grant from Takeda Pharmaceuticals outside the scope of the present study. F.S.G. has received a research grant from Janssen Pharmaceuticals outside the scope of the present study. C.-Y.C. is an employee of Biogen. F.D. is an employee of Sheppard Pratt. A.E.L. and E.A.S. are now employees of Regeneron. X.J. is now an employee of Genentech. All other authors declare no competing interests.
Peer review
Peer review information
Nature Genetics thanks Kathryn Roeder and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary Figures 1–18, Supplementary Tables 1–13 and Supplementary Note.
Rights and permissions
About this article
Cite this article
Palmer, D.S., Howrigan, D.P., Chapman, S.B. et al. Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia. Nat Genet 54, 541–547 (2022). https://doi.org/10.1038/s41588-022-01034-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41588-022-01034-x
This article is cited by
-
Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression
Nature Communications (2024)
-
Bipolar patients display stoichiometric imbalance of gene expression in post-mortem brain samples
Molecular Psychiatry (2024)
-
Rare genetic brain disorders with overlapping neurological and psychiatric phenotypes
Nature Reviews Neurology (2024)
-
Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults
Nature Human Behaviour (2024)
-
Integrated proteomics reveals autophagy landscape and an autophagy receptor controlling PKA-RI complex homeostasis in neurons
Nature Communications (2024)
