Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Vipavee Niemsiri; Sara Brin Rosenthal; Caroline M Nievergelt; Adam X Maihofer; Maria C Marchetto; Renata Santos; Tatyana Shekhtman; Ney Alliey-Rodriguez; Amit Anand; Yokesh Balaraman; Wade H Berrettini; Holli Bertram; Katherine E Burdick; Joseph R Calabrese; Cynthia V Calkin; Carla Conroy; William H Coryell; Anna DeModena; Lisa T Eyler; Scott Feeder; Carrie Fisher; Nicole Frazier; Mark A Frye; Keming Gao; Julie Garnham; Elliot S Gershon; Fernando S Goes; Toyomi Goto; Gloria J Harrington; Petter Jakobsen; Masoud Kamali; Marisa Kelly; Susan G Leckband; Falk W Lohoff; Michael J McCarthy; Melvin G McInnis; David Craig; Caitlin E Millett; Francis Mondimore; Gunnar Morken; John I Nurnberger; Claire O' Donovan; Ketil J Øedegaard; Kelly Ryan; Martha Schinagle; Paul D Shilling; Claire Slaney; Emma K Stapp; Andrea Stautland; Bruce Tarwater; Peter P Zandi; Martin Alda; Kathleen M Fisch; Fred H Gage; John R Kelsoe

doi:10.1038/s41380-022-01909-9

Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Mol Psychiatry. 2023 Mar 29. doi: 10.1038/s41380-022-01909-9. Online ahead of print.

Authors

Vipavee Niemsiri¹, Sara Brin Rosenthal², Caroline M Nievergelt¹, Adam X Maihofer¹, Maria C Marchetto^{3

4}, Renata Santos^{4

5}, Tatyana Shekhtman¹, Ney Alliey-Rodriguez^{6

7}, Amit Anand^{8

9}, Yokesh Balaraman¹⁰, Wade H Berrettini¹¹, Holli Bertram¹², Katherine E Burdick⁹, Joseph R Calabrese^{13

14}, Cynthia V Calkin¹⁵, Carla Conroy^{13

14}, William H Coryell¹⁶, Anna DeModena¹⁷, Lisa T Eyler¹, Scott Feeder¹⁸, Carrie Fisher¹⁰, Nicole Frazier¹², Mark A Frye¹⁸, Keming Gao^{13

14}, Julie Garnham¹⁹, Elliot S Gershon⁶, Fernando S Goes²⁰, Toyomi Goto¹³, Gloria J Harrington¹², Petter Jakobsen²¹, Masoud Kamali^{8

12}, Marisa Kelly¹², Susan G Leckband¹⁷, Falk W Lohoff¹¹, Michael J McCarthy¹, Melvin G McInnis¹², David Craig²², Caitlin E Millett⁹, Francis Mondimore²⁰, Gunnar Morken²³, John I Nurnberger^{10

24}, Claire O' Donovan¹⁹, Ketil J Øedegaard²¹, Kelly Ryan¹², Martha Schinagle¹³, Paul D Shilling¹, Claire Slaney¹⁹, Emma K Stapp²⁵, Andrea Stautland²⁶, Bruce Tarwater¹⁶, Peter P Zandi²⁰, Martin Alda^{19

27}, Kathleen M Fisch^{2

28}, Fred H Gage⁴, John R Kelsoe^{29

30}

Affiliations

¹ Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.
² Center for Computational Biology and Bioinformatics, University of California, San Diego, La Jolla, CA, USA.
³ Department of Anthropology, University of California, San Diego, La Jolla, CA, USA.
⁴ Laboratory of Genetics, Salk Institute for Biological Studies, La Jolla, CA, USA.
⁵ University of Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1261266, Laboratory of Dynamics of Neuronal Structure in Health and Disease, Paris, France.
⁶ Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA.
⁷ Department of Psychiatry and Behavioral Neuroscience, Northwestern University, Chicago, IL, USA.
⁸ Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
⁹ Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
¹⁰ Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA.
¹¹ Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
¹² Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
¹³ Mood Disorders Program, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
¹⁴ Mood Disorders Program, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
¹⁵ Department of Psychiatry and Medical Neuroscience, Dalhousie University, Halifax, NS, Canada.
¹⁶ Department of Psychiatry, University of Iowa, Iowa City, IA, USA.
¹⁷ Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA.
¹⁸ Department of Psychiatry, The Mayo Clinic, Rochester, MN, USA.
¹⁹ Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
²⁰ Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA.
²¹ Norment, Division of Psychiatry, Haukeland University Hospital and Department of Clinical medicine, University of Bergen, Bergen, Norway.
²² Department of Translational Genomics, University of Southern California, Los Angeles, CA, USA.
²³ Division of Mental Health Care, St Olavs University Hospital, and Department of Mental Health, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
²⁴ Medical and Molecular Genetics, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA.
²⁵ Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
²⁶ Department of Clinical Medicine, University of Bergen, Bergen, Norway.
²⁷ National Institute of Mental Health, Klecany, Czech Republic.
²⁸ Department of Obstetrics, Gynecology & Reproductive Sciences, University of California, San Diego, La Jolla, CA, USA.
²⁹ Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA. jkelsoe@health.ucsd.edu.
³⁰ Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA. jkelsoe@health.ucsd.edu.

PMID: 36991131
DOI: 10.1038/s41380-022-01909-9

Abstract

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (P_{hypergeometric}= 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Abstract

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