Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2024 Dec 1.
Published in final edited form as: Curr Opin Neurobiol. 2023 Oct 27;83:102801. doi: 10.1016/j.conb.2023.102801

Bipolar Disorder

Madeline R Scott 1, Colleen A McClung 1
PMCID: PMC10786345  NIHMSID: NIHMS1936170  PMID: 38223491

Abstract

This review focuses on recent advances made towards understanding the neurobiology of bipolar disorder (BD), a chronic neuropsychiatric illness characterized by altered mood and energy states. The past few years have seen the completion of the largest genetic studies by far, which have emphasized the polygenic nature of BD as well as it’s connection to other psychiatric illnesses. Furthermore, the use of inducible pluripotent stem cells has rapidly expanded. These studies support previous work that implicates dysregulation of neurodevelopment, mitochondria, and calcium homeostasis, while also allowing for investigation into the underlying mechanisms of individual responsivity to lithium. Sleep and circadian rhythms have also been heavily implicated in BD, from disruptions in activity patterns to molecular abnormalities.

Introduction

Bipolar disorders (BD) are complex, lifelong conditions characterized by periods of mania/hypomania and episodes of depression with euthymia between. BD I is distinguished by manic episodes while persons with BD II experience hypomania. While similar, mania is generally more severe and is sometimes associated with psychosis. During mania/hypomania, individuals have increased activity levels despite a decreased need for sleep and often experience an exaggerated sense of self-confidence and euphoria. Friends and family may notice unusual talkativeness, high distractibility, and risky decision making. Individuals with BD also experience periods of severe depression, which are marked by features like depressed mood, anhedonia, and extreme fatigue. These periods are often longer in BD II than in BD I, though overall symptoms are variable from person to person, as is the course of illness. In 2017, the global incidence rate of BD was 4.53 million and accounted for 9.29 million disability-adjusted life years[1]. This review focuses on recent advances made toward understanding the neurobiology of BD.

Genetic Risk

Classic studies demonstrated increased concordance from first degree relatives/dizygotic twins (5-10%) to monozygotic twins (40-70%) of BD diagnosis[2]. The strength of these epidemiological studies led to a long history of investigating genetic risk in BD[2]. Currently, the largest genome-wide association study (GWAS) (41,917 BD cases, 317,549 comparison subjects) identified 64 independent genomic loci significantly associated with increased risk of developing BD[3]. These were enriched for synaptic signaling genes, and genes highly expressed in prefrontal cortex (PFC) and hippocampal neurons[3]. Additionally, ~20% of phenotypic variance was explained by common SNPs using a polygenic risk score prediction model, consistent with other psychiatric illnesses[3]. Notably, the polygenic nature of BD has made creating genetic models with strong clinical relevance very difficult. However, recent advances in patient-derived inducible pluripotent stem cell (iPSC) techniques have dramatically expanded the toolset of scientists studying psychiatric illnesses. These studies support previous work implicating dysregulation of intracellular calcium[4,5], neurodevelopment[6–8], mitochondria/energy homeostasis[6,9,10], circadian rhythms[11,12], inflammation/immune function[6,13], and synaptic biology[6,14,15].

The Bipolar Exome (BipEx) sequencing project (13,933 BD cases, 14,422 comparison subjects) used whole exome sequencing (WES) to identify potential novel mutations, but did not observe any exome-wide significant genes associated with BD[16], consistent with previous, smaller WES studies[17–19]. However, when combined with data from subjects with schizophrenia (SZ), A-Kinase Anchoring Protein 11 (AKAP11) was identified as a definitive risk gene[16]. AKAP11 is known to interact with both protein kinase A (PKA) and glycogen synthase kinase 3 beta (GSK3β), a target of lithium, a pharmacological treatment for BD[20]. Intriguingly, AKAP11 knock-out (KO) mice have distinct electroencephalographic (EEG) abnormalities consistent with those seen in individuals with SZ[20] and changes in the synaptic proteomic signature of these mice (including upregulation of proteins associated with autophagy and vesicle transport and downregulation of proteins associated with mitochondria and ribosomes) are remarkably similar to differences observed in isolated synapses from the dorsolateral PFC of subjects with SZ and BD[21].

Extensive genetic overlap is observed between BD, major depression (MDD), and SZ[22,23], including in a GWAS meta-analysis of six datasets which estimated that >95% of risk variants for other psychiatric disorders, including BD and SZ, influences MDD risk[23]. Additionally, a 2019 study by the Cross-Disorder Group of the Psychiatric Genomics Consortium identified meaningful genome-wide structure of three groups of inter-related disorders within eight psychiatric disorders[24]. In this study, MDD, BD, and SZ clustered together and had the strongest genome-wide correlations between disorders[24]. 109 loci with pleiotropic effects across at least two psychiatric disorders were identified[24]. These loci were enriched for genes associated with neurodevelopment, neuronal signaling, and synaptic plasticity[24]. These findings are consistent with a long literature noting overlap in the genetics and phenotypes of MDD, BD, and SZ[2]. Overall, our understanding of the underlying genetics of BD has continued to deepen and while there are few definitive conclusions, the general themes of differences in mitochondria, neurodevelopment, and synaptic biology are supported by these studies.

Environmental Risk

A variety of environmental factors have been implicated in the etiology of BD. Pre- and peri-natal events have been repeatedly associated with increased risk of BD, and a recent Swedish register-based study utilizing 18,681 BD confirmed that seasonality (a.k.a. births during November and December), perinatal respiratory distress, abnormal growth & development, and other perinatal factors, were associated with the risk of developing BD[25]. Postnatal factors are also implicated in increased BD risk, particularly childhood mistreatment (reviewed in [26]), which is associated with more severe and frequent mood episodes, earlier onset of illness, increased risk of suicide, and comorbid substance misuse[26]. While these risk factors primarily occur during key neurodevelopmental periods, a notable lifelong environmental factor is air pollution exposure, which has been associated with increased risk of BD in populations from the United States, Denmark, and the United Kingdom[27,28]. In one analysis, this was specific to individuals with intermediate and high genetic risk for BD, suggesting a gene by environment interaction[28].

A new potential environmental risk factor to consider is the impact of COVID-19. During the height of the COVID-19 pandemic, persons with SZ spectrum disorders and BD experienced increased risk of hospitalization and mortality after contracting COVID-19[29], as confirmed by multiple large retrospective studies[30,31]. This increased risk may not be specific to COVID-19, as people with SZ spectrum disorders and BD also have higher rates of severe outcomes from other serious acute respiratory infections[32]. Going forward, understanding the long-term impact of the SARS-COV-2 virus will be important, from how Long COVID symptoms interact with BD to the impact of pre-natal exposure of SARS-COV-2 on risk of developing BD.

Neurodevelopment

The timing of pre- and post-natal risk factors implicates critical windows of increased vulnerability to environmental insults. Additionally, individuals with BD often present during late adolescence/young adulthood, an important neurodevelopmental period. Consistent with this, many studies have observed dysregulation of neurodevelopmental processes, and iPSC models support this. iPSC-derived neural progenitor cells (NPCs) from subjects with BD show a slower rate of proliferation, decreased size of neurosphere formations, and abnormal migration patterns[4,7], while human cortical spheroids (hCS) are smaller, have reduced proportion of neurons, decreased neuronal excitability and reduced neural network activity compared to control hCS[33]. Single-cell RNA-sequencing found enhanced GABAergic specification and reduced proliferation following dimensional WNT signaling, a fundamental neurodevelopmental process, in cerebral organoids from monozygotic twins discordant for BD with psychosis[14]. This is consistent with other studies of cerebral organoids from subjects with BD that show downregulation of genes associated with neurodevelopment[6]. Together these studies suggest that the processes involved in neurodevelopment are disrupted in BD, and that this may be a common mechanism between both genetic and environmental influences.

Neuroinflammation

Some environmental factors, such as pollution, are thought to impact BD risk through activation of inflammatory pathways, which have been increasingly implicated in the etiology of BD. Neuroinflammation is incredibly complex and the role it plays in BD is multifaceted (reviewed in [34]). Individuals with BD have increased comorbidity with inflammatory conditions, elevated levels of proinflammatory cytokines, and other inflammatory molecules[34]. Serum levels of specific pro-inflammatory cytokines have been associated with illness phase (manic, euthymic, depressed) and treatment response[34]. White matter integrity is associated with peripheral cytokine levels in subjects with BD, suggesting a relationship between neuroinflammation and dys or demyelination[35]. Neuroimaging studies also observe microglial overactivity, which is associated with inflammation, in the hippocampus and PFC of subjects with BD regardless of illness state[34].

Overall, evidence suggests that BD is accompanied by hyperactivation of the immune system[34] and the impact of this state can be seen in the metabolism of tryptophan. Tryptophan is the precursor for serotonin, but is also converted into kynurenine through an alternative pathway, which is promoted by a pro-inflammatory state[36]. A recent meta-analysis of 101 studies found an overall shift in tryptophan metabolism from serotonin production to the kynurenine pathway[36]. In subjects with BD this also resulted in increased quinolinic acid, which is potentially neurotoxic[36]. Suggesting a role for this pathway in familial risk, Benevenuto et al. [37] observed altered levels of kynurenine pathway metabolites in both youth with BD and unaffected high-risk offspring of individuals with BD compared to healthy comparison subjects, and that these levels predicted severity of depressive symptoms[37].

The large amount of evidence for immune/inflammatory dysfunction in BD has led to the use of anti-inflammatory treatments[34]. Individual agents have variable results, but meta-analyses suggest that this class of treatments has moderate-to-large antidepressant effects[38,39]. Anti-inflammatory approaches work best for individuals who have an elevated baseline of inflammatory markers and as an augmentation to conventional BD treatments[34], highlighting the need for precision medicine when considering this route.

Mitochondria

Alterations in energy homeostasis, abnormal mitochondrial expression, and atypical mitochondrial metabolism have been implicated in BD for many years (Figure 1) (Reviewed in [40]). Supporting differentially expressed mitochondria in BD, a comprehensive analysis of mitochondrial features in human postmortem brain tissue from subjects with SZ and BD found region-specific increases in mitochondria DNA copy number and mitochondria DNA total somatic deletions, and reductions in complex I activity, synapse number, and synaptic mitochondria number[41]. While some components, like reduced complex I activity, appear to be driven by presence of medication, this study supports an overall reduction in mitochondria expression, and synaptic localization in BD[41]. Lower mitochondrial membrane potential has also been observed in lymphoblastoid cell lines, NPCs, and hippocampal-like neurons derived from subjects with BD[10,42]. In NPCs, oxygen consumption rate (OCR) and glycolytic rate, are also lower[9]. Alternatively, there was no deficit in basal levels of OCR in cerebral organoids from subjects with BD[5]. Cells in these organoids did, however, have significantly fewer contact sites between mitochondria and the endoplasmic reticulum (ER)[5]. These contact sites are critical for maintaining calcium homeostasis, which itself is implicated in BD.

Figure 1. Factors contributing to the neurobiology of BD.

Figure 1.

Open in a new tab

Recent advances in the neurobiology of BD are discussed, some of which are highlighted here. (A) Environmental risk factors implicated in the neurobiology of BD, many of which are associated with neurodevelopmental time-periods. Later environmental factors, like childhood maltreatment and sleep/activity disruptions are associated with both a higher risk of a BD diagnosis as well as increased severity of symptoms. (B) A simplified, theoretical example of BD course of illness, in which individuals experience episodes of Mania (or Hypomania) and Depression, broken up by periods of Euthymia in which few/no mood symptoms are present. Notably, symptoms and course of illness varies greatly between individuals. (C) BD is highly heritable, and recent advances in the genetics of BD support a role for dysregulation in synaptic biology, calcium signaling, and neurodevelopment. CACNA1C is a gene that has been implicated for many years in BD, while AKAP11 was identified in the most recent WES as a shared risk factor for BD and SZ. (D) Sleep and circadian rhythms are associated with both genetic and environmental risk in BD. Disrupted sleep and activity rhythms are a key diagnostic feature of the illness, and studies have now observed abnormal molecular rhythms in human postmortem brain tissue, fibroblasts, and iPSC-derived NPCs. Animal models of genetic and environmental circadian disruptions lead to behaviors associated with mood disorders. A simplified model of the core transcriptional-translational clock is presented. BMAL1 dimerizes with CLOCK (or NPAS2), facilitating its’ transcription factor activity. This leads to transcription of core clock proteins like period (PER) and cryptochrome (CRY), as well as other clock-controlled genes (CCGs). Notably, CCGs can vary greatly depending on tissue, cell-type, and species. As PER and CRY accumulate in the cytosol, they dimerize and are shuttled back into the nucleus. In the nucleus, the PER:CRY dimer inhibits BMAL1:CLOCK promoter binding, leading to inhibition of BMAL1-regulated transcription. As this transcription decreases, so does PER and CRY expression, leading then to the disinhibition of BMAL1-meidated transcription. This overall process takes 24 h, creating a 24 h negative feedback loop. (E) The mood stabilizers lithium and valproate (VPA) have been in use as treatments in BD for decades, and while they have many targets, reduction of inositol is one they share. The inositol signaling pathway interacts with Gq -mediated signaling. Specifically, in response to a ligand, the αq subunit of a g-protein coupled receptor will bind to protein lipase C (PLC). This complex will then hydrolyse phosphatidylinositol 4,5-biposphate (PIP2) into inositol-1,4,5 triphosphate (IP3) and 1,2-dacylglycerol (DAG). DAG moves on to associate with Protein kinase A and stimulate a second messenger signaling cascade. IP3 is released into the cytosol, where it can stimulate Ca2+ release from the ER or be broken down into inositol biphosphates (IP2). IP2 is then broken down into inositol monophosphoate (IP) by inositol phosphatase (IPPase), and finally into myo-inositol by inositol monophosphatase (IMPase). Lithium acts by inhibiting the enzymes IPPase and IMPase, leading to depletion of myo-inositoll, which then has major consequence on downstream GPCR, IP3/DAG signaling. (F) Mitochondria have been implicated in BD in many studies. Collectively, these point reduced mitochondria-driven ATP production and a shift towards glycolysis. Created with Biorender.

Calcium and mood stabilizers

Various findings point to dysregulation of calcium in BD. CACNA1C, an L-type voltage-gated calcium channel, is a risk gene for BD, and a meta-analysis found that basal levels of free intracellular calcium is 29% higher in platelets and lymphocytes from individuals with BD[43]. Moreover, these cells have an enhanced calcium response to stimulation with 5-HT or thrombin[43]. In cerebral organoids, genes involved in calcium binding, ion binding, and regulation of calcium transport are upregulated in cells from individuals with BD[5]. Additionally, the mood stabilizers lithium and valproate reduce inositol signaling, though through different targets, likely impairing inositol triphosphate 3 (IP3)-stimulated calcium release from the ER (Figure 1).

Notably, research into the underlying mechanism of action of mood stabilizers has been a key feature of BD research, as it provides insight into both BD neurobiology and ways in which improved pharmacological treatments may be designed. Recently, patient-derived iPSCs have allowed an expansion of experiments that seek to determine why a patient responds to lithium (Li-R) (and/or other mood stabilizers), or not (Li-NR). Notable studies have observed that focal adhesion and the extracellular matrix are the top functions of genes that differentiate Li-R and Li-NR in iPSC-derived neurons[44], that Li-R and Li-NR NPCs are differentially vulnerable to methamphetamine neurotoxicity[12], and that lithium improves OCR only in Li-R NPCs[9]. Conversely, valproate improves OCR only in Li-NR NPCs, suggesting that OCR improvement may be important to the benefits of both drugs, but through alternative mechanisms[9]. The use of this approach in psychiatric illness research has incredible potency to not only provide essential information on the underlying mechanisms that determine individual differences in drug efficacy but also to determine biomarkers for future precision medicine approaches.

Sleep and Circadian Rhythms

Changes in energy states and activity are key diagnostic features of BD and patients frequently report worse subjective sleep. Objective reports confirm that BD is associated with longer sleep onset latency and lower overall daily activity[45]. These measures are both associated with depressive episodes, while longer sleep onset latency also has predictive value for worsening of future manic symptoms[45]. Prospective and retrospective studies find that sleep disturbances frequently appear before the onset of BD, often during childhood or adolescence[45]. While rates of insomnia occur prior to both manic and depressive episodes, decreased need for sleep anticipates manic episodes and hypersomnia precedes depressive episodes in individuals with BD, indicating sleep patterns specific to mood state[46]. These striking disruptions in sleep and energy states have led to investigations into the potential underlying molecular mechanisms.

Early genetic studies implicated the molecular clock, a transcription-translation feedback loop driving circadian rhythms within the cell (Figure 1), in BD[47]. While these were not confirmed by GWAS, when analyzed as a network rather than as individual genes, genetic differences in core clock genes are associated with risk of a BD-associated illness (BD, MDD, SZ, and ADHD) and responsiveness to lithium[47]. Differences in twenty-four hour rhythmic gene expression have been identified in the striatum of subjects with psychosis, suggesting dampening of circadian rhythms within this region[48]. Fibroblasts and iPSCs from individuals with BD also have weaker, more desynchronized circadian rhythms[11,12,49]. Importantly, lithium treatment lengthens the observed destabilized molecular circadian period in iPSC-derived NPCs and neurons, but only in cells derived from Li-R subjects[11]. This is consistent with previous literature demonstrating a role for circadian rhythms in the mechanism by which lithium works as a treatment[47].

Animal studies of genetic or environmental disruptions to circadian rhythms consistently show behavioral phenotypes associated with BD and other psychiatric illnesses. A primary example of this are mice with the ClockΔ19 mutation, which results in dominant-negative CLOCK function and severely dysregulates the molecular clock. Over a decade of research has demonstrated that these mice have hyperlocomotion and increased exploratory drive, impulsivity, and response to reward – consistent with a mania-like phenotype[47]. This phenotype is associated with altered dopaminergic signaling and expression, consistent with longstanding findings of dysregulated dopaminergic signaling in BD[47]. Importantly, knock-out models of other primary molecular clock components, including Bmal1, Rev-erbα, Per1/2, also lead to mood-related behavior phenotypes, suggesting a fundamental role for the whole molecular clock, rather than CLOCK alone[47]. Advances in CRISPR/Cas9 technology has resulted in a Bmal1 KO cynomolgus monkey[50]. These monkeys have higher nocturnal locomotion and reduced sleep, display phenotypes consistent with anxiety and depression, and have defects in auditory oddball tests, a measure of sensory processing disrupted in SZ[50]. While there is much to learn about the exact mechanisms by which circadian rhythms contribute to mood disorders, various studies have demonstrated a role for circadian rhythms in regulating and being regulated by many of the biological pathways implicated in BD (reviewed in [47]), suggesting that the interaction of these systems may be fundamental to understanding the neurobiology underlying BD.

Conclusion

BD is an incredibly heterogenous and complex disorder for which the underlying neurobiology is not fully understood. Recent genetic analyses emphasize the polygenic nature of the illness and further define genetic links between BD, SZ, and MDD. Multiple lines of evidence, from genetics to functional assays in iPSCs, converge on dysregulation of neurodevelopment, neuroinflammation, mitochondria, and calcium homeostasis. Intriguingly, disruptions in sleep and circadian rhythms are strongly linked to BD, and molecular circadian rhythms have been implicated in the regulation of the cellular pathways associated with BD. Overall, these findings and the development of new techniques contribute to a deeper understanding of the underlying mechanisms of BD.

Highlights.

  • BD is highly polygenic and shares genetic risk with SZ and MDD.

  • Support for altered neurodevelopment, inflammation, mitochondria, and calcium homeostasis in BD.

  • Disruptions in sleep/activity rhythms are a fundamental component of BD.

  • Molecular findings support a key role for circadian rhythm dysfunction in BD.

Acknowledgements

Work from our lab was supported by the National Institutes of Health (R01MH111601; R01DA039865; P50DA046346; R01MH106460; R21NS127064; T32HL082610) The Baszucki Brain Research Fund and the WoodNext Foundation.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  • 1.He H, Hu C, Ren Z, Bai L, Gao F, Lyu J: Trends in the incidence and DALYs of bipolar disorder at global, regional, and national levels: Results from the global burden of Disease Study 2017. Journal of Psychiatric Research 2020, 125:96–105. [DOI] [PubMed] [Google Scholar]
  • 2.Hara T, Owada Y, Takata A: Genetics of bipolar disorder: insights into its complex architecture and biology from common and rare variants. J Hum Genet 2023, 68:183–191.* [DOI] [PubMed] [Google Scholar]; • Very thorough review of the history of, and current advances in, research on the genetics of BD.
  • 3.Mullins N, Forstner AJ, O’Connell KS, Coombes B, Coleman JRI, Qiao Z, Als TD, Bigdeli TB, Børte S, Bryois J, et al. : Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet 2021, 53:817–829.** [DOI] [PMC free article] [PubMed] [Google Scholar]; • Largest, most recent genome-wide association study of BD cases.
  • 4.Hewitt T, Alural B, Tilak M, Wang J, Becke N, Chartley E, Perreault M, Haggarty SJ, Sheridan SD, Perlis RH, et al. : Bipolar disorder-iPSC derived neural progenitor cells exhibit dysregulation of store-operated Ca2+ entry and accelerated differentiation. Mol Psychiatry 2023, doi: 10.1038/s41380-023-02152-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Kathuria A, Lopez-Lengowski K, McPhie D, Cohen BM, Karmacharya R: Disease-specific differences in gene expression, mitochondrial function and mitochondria-endoplasmic reticulum interactions in iPSC-derived cerebral organoids and cortical neurons in schizophrenia and bipolar disorder. Discov Ment Health 2023, 3:8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kathuria A, Lopez-Lengowski K, Jagtap SS, McPhie D, Perlis RH, Cohen BM, Karmacharya R: Transcriptomic Landscape and Functional Characterization of Induced Pluripotent Stem Cell-Derived Cerebral Organoids in Schizophrenia. JAMA Psychiatry 2020, 77:745–754. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Sukumaran SK, Paul P, Guttal V, Holla B, Vemula A, Bhatt H, Bisht P, Mathew K, Nadella RK, Varghese AM, et al. : Abnormalities in the migration of neural precursor cells in familial bipolar disorder. Dis Model Mech 2022, 15:dmm049526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Ishima T, Illes S, Iwayama Y, Dean B, Yoshikawa T, Ågren H, Funa K, Hashimoto K: Abnormal gene expression of BDNF, but not BDNF-AS, in iPSC, neural stem cells and postmortem brain samples from bipolar disorder. J Affect Disord 2021, 290:61–64. [DOI] [PubMed] [Google Scholar]
  • 9.Osete JR, Akkouh IA, de Assis DR, Szabo A, Frei E, Hughes T, Smeland OB, Steen NE, Andreassen OA, Djurovic S: Lithium increases mitochondrial respiration in iPSC-derived neural precursor cells from lithium responders. Mol Psychiatry 2021, 26:6789–6805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Paul P, Iyer S, Nadella RK, Nayak R, Chellappa AS, Ambardar S, Sud R, Sukumaran SK, Purushottam M, Jain S, et al. : Lithium response in bipolar disorder correlates with improved cell viability of patient derived cell lines. Sci Rep 2020, 10:7428. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Mishra HK, Ying NM, Luis A, Wei H, Nguyen M, Nakhla T, Vandenburgh S, Alda M, Berrettini WH, Brennand KJ, et al. : Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response: preliminary studies. Mol Psychiatry 2021, 26:3383–3394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Mishra HK, Wei H, Rohr KE, Ko I, Nievergelt CM, Maihofer AX, Shilling PD, Alda M, Berrettini WH, Brennand KJ, et al. : Contributions of circadian clock genes to cell survival in fibroblast models of lithium-responsive bipolar disorder. Eur Neuropsychopharmacol 2023, 74:1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Vadodaria KC, Mendes APD, Mei A, Racha V, Erikson G, Shokhirev MN, Oefner R, Heard KJ, McCarthy MJ, Eyler L, et al. : Altered Neuronal Support and Inflammatory Response in Bipolar Disorder Patient-Derived Astrocytes. Stem Cell Reports 2021, 16:825–835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Sawada T, Chater TE, Sasagawa Y, Yoshimura M, Fujimori-Tonou N, Tanaka K, Benjamin KJM, Paquola ACM, Erwin JA, Goda Y, et al. : Developmental excitation-inhibition imbalance underlying psychoses revealed by single-cell analyses of discordant twins-derived cerebral organoids. Mol Psychiatry 2020, 25:2695–2711. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Attili D, Schill DJ, DeLong CJ, Lim KC, Jiang G, Campbell KF, Walker K, Laszczyk A, McInnis MG, O’Shea KS: Astrocyte-Derived Exosomes in an iPSC Model of Bipolar Disorder. Adv Neurobiol 2020, 25:219–235. [DOI] [PubMed] [Google Scholar]
  • 16.Palmer DS, Howrigan DP, Chapman SB, Adolfsson R, Bass N, Blackwood D, Boks MP, Chen C-Y, Churchhouse C, Corvin AP, et al. : Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia. Nat Genet 2022, 54:541–547.** [DOI] [PMC free article] [PubMed] [Google Scholar]; • Large whole exome sequencing study of BD that also identifies a shared risk gene with SZ.
  • 17.Jia X, Goes FS, Locke AE, Palmer D, Wang W, Cohen-Woods S, Genovese G, Jackson AU, Jiang C, Kvale M, et al. : Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder. Mol Psychiatry 2021, 26:5239–5250. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Husson T, Duboc J-B, Quenez O, Charbonnier C, Rotharmel M, Cuenca M, Jegouzo X, Richard A-C, Frebourg T, Deleuze J-F, et al. : Identification of potential genetic risk factors for bipolar disorder by whole-exome sequencing. Transl Psychiatry 2018, 8:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Lescai F, Als TD, Li Q, Nyegaard M, Andorsdottir G, Biskopstø M, Hedemand A, Fiorentino A, O’Brien N, Jarram A, et al. : Whole-exome sequencing of individuals from an isolated population implicates rare risk variants in bipolar disorder. Transl Psychiatry 2017, 7:e1034–e1034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Herzog LE, Wang L, Yu E, Choi S, Farsi Z, Song BJ, Pan JQ, Sheng M: Mouse mutants in schizophrenia risk genes GRIN2A and AKAP11 show EEG abnormalities in common with schizophrenia patients. Transl Psychiatry 2023, 13:1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Aryal S, Bonanno K, Song B, Mani DR, Keshishian H, Carr SA, Sheng M, Dejanovic B: Deep proteomics identifies shared molecular pathway alterations in synapses of patients with schizophrenia and bipolar disorder and mouse model. Cell Rep 2023, 42:112497. [DOI] [PubMed] [Google Scholar]
  • 22.Hindley G, Frei O, Shadrin AA, Cheng W, O’Connell KS, Icick R, Parker N, Bahrami S, Karadag N, Roelfs D, et al. : Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation. AJP 2022, 179:833–843. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Als TD, Kurki MI, Grove J, Voloudakis G, Therrien K, Tasanko E, Nielsen TT, Naamanka J, Veerapen K, Levey DF, et al. : Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses. Nat Med 2023, 29:1832–1844. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Lee PH, Anttila V, Won H, Feng Y-CA, Rosenthal J, Zhu Z, Tucker-Drob EM, Nivard MG, Grotzinger AD, Posthuma D, et al. : Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders. Ce// 2019, 179:1469–1482.e11.** [DOI] [PMC free article] [PubMed] [Google Scholar]; • Large-scale study determining meaningful groups from genetic correlation analyses and identifying pleiotropic loci shared across psychiatric disorders. This study emphasizes that genetic influences on psychiatric disorders transcend diagnostic boundaries, and that better understanding of these disorders may come from considering shared and/or antagonistic molecular differences.
  • 25.Robinson N, Ploner A, Leone M, Lichtenstein P, Kendler KS, Bergen SE: Impact of Early-Life Factors on Risk for Schizophrenia and Bipolar Disorder. Schizophr Bull 2023, 49:768–777. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Rowland TA, Marwaha S: Epidemiology and risk factors for bipolar disorder. Ther Adv Psychopharmacol 2018, 8:251–269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Khan A, Plana-Ripoll O, Antonsen S, Brandt J, Geels C, Landecker H, Sullivan PF, Pedersen CB, Rzhetsky A: Environmental pollution is associated with increased risk of psychiatric disorders in the US and Denmark. PLoS Biol 2019, 17:e3000353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Li D, Ma Y, Cui F, Yang Y, Liu R, Tang L, Wang J, Tian Y: Long-term exposure to ambient air pollution, genetic susceptibility, and the incidence of bipolar disorder: A prospective cohort study. Psychiatry Research 2023, 327:115396. [DOI] [PubMed] [Google Scholar]
  • 29.Fond G, Nemani K, Etchecopar-Etchart D, Loundou A, Goff DC, Lee SW, Lancon C, Auquier P, Baumstarck K, Llorca P-M, et al. : Association Between Mental Health Disorders and Mortality Among Patients With COVID-19 in 7 Countries: A Systematic Review and Meta-analysis. JAMA Psychiatry 2021, 78:1208–1217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Schultebraucks K, Blekic W, Basaraba C, Corbeil T, Khan Z, Henry BF, Krawczyk N, Rivera BD, Allen B, Arout C, et al. : The impact of preexisting psychiatric disorders and antidepressant use on COVID-19 related outcomes: a multicenter study. Mol Psychiatry 2023, doi: 10.1038/s41380-023-02049-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Bowersox NW, Browne J, Grau PP, Merrill SL, Haderlein TP, Llorente MD, Washington DL: COVID-19 mortality among veterans with serious mental illness in the veterans health administration. J Psychiatr Res 2023, 163:222–229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Ranger TA, Clift AK, Patone M, Coupland CAC, Hatch R, Thomas K, Watkinson P, Hippisley-Cox J: Preexisting Neuropsychiatric Conditions and Associated Risk of Severe COVID-19 Infection and Other Acute Respiratory Infections. JAMA Psychiatry 2023, 80:57–65.* [DOI] [PMC free article] [PubMed] [Google Scholar]; • A longitudinal cohort study from the QResearch database of UK primary care records that compares outcomes in neuropsychiatric populations associated with severe acute respiratory infections prepandemic and those incurred during the COVID-19 pandemic. This study provides essential context to understanding the relationship between severe psychiatric illnesses, severe acute respiratory infections, and COVID-19.
  • 33.Osete JR, Akkouh IA, Ievglevskyi O, Vandenberghe M, de Assis DR, Ueland T, Kondratskaya E, Holen B, Szabo A, Hughes T, et al. : Transcriptional and functional effects of lithium in bipolar disorder iPSC-derived cortical spheroids. Mol Psychiatry 2023, doi: 10.1038/s41380-023-01944-0.** [DOI] [PMC free article] [PubMed] [Google Scholar]; • Characterization of the basal differences in iPSC-derived cortical spheroids from individuals with BD from comparison cortical spheroids, as well as the differential impact of lithium. The study emphasizes neurodevelopmental dysregulation in BD as well as the techniques being used to test mechanisms underlying lithium responsivity.
  • 34.Jones GH, Vecera CM, Pinjari OF, Machado-Vieira R: Inflammatory signaling mechanisms in bipolar disorder. Journal of Biomedical Science 2021, 28:45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Aronica R, Enrico P, Squarcina L, Brambilla P, Delvecchio G: Association between Diffusion Tensor Imaging, inflammation and immunological alterations in unipolar and bipolar depression: A review. Neuroscience & Biobehavioral Reviews 2022, 143:104922. [DOI] [PubMed] [Google Scholar]
  • 36.Marx W, McGuinness AJ, Rocks T, Ruusunen A, Cleminson J, Walker AJ, Gomes-da-Costa S, Lane M, Sanches M, Diaz AP, et al. : The kynurenine pathway in major depressive disorder, bipolar disorder, and schizophrenia: a meta-analysis of 101 studies. Mol Psychiatry 2021,26:4158–4178. [DOI] [PubMed] [Google Scholar]
  • 37.Benevenuto D, Saxena K, Fries GR, Valvassori SS, Kahlon R, Saxena J, Kurian S, Zeni CP, Kazimi IF, Scaini G, et al. : Alterations in plasma kynurenine pathway metabolites in children and adolescents with bipolar disorder and unaffected offspring of bipolar parents: A preliminary study. Bipolar Disorders 2021, 23:689–696. [DOI] [PubMed] [Google Scholar]
  • 38.Husain MI, Strawbridge R, Stokes PR, Young AH: Anti-inflammatory treatments for mood disorders: Systematic review and meta-analysis. J Psychopharmacol 2017, 31:1137–1148. [DOI] [PubMed] [Google Scholar]
  • 39.Rosenblat JD, Kakar R, Berk M, Kessing LV, Vinberg M, Baune BT, Mansur RB, Brietzke E, Goldstein BI, McIntyre RS: Anti-inflammatory agents in the treatment of bipolar depression: a systematic review and meta-analysis. Bipolar Disord 2016, 18:89–101. [DOI] [PubMed] [Google Scholar]
  • 40.Scaini G, Andrews T, Lima CNC, Benevenuto D, Streck EL, Quevedo J: Mitochondrial dysfunction as a critical event in the pathophysiology of bipolar disorder. Mitochondrion 2021, 57:23–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Das SC, Hjelm BE, Rollins BL, Sequeira A, Morgan L, Omidsalar AA, Schatzberg AF, Barchas JD, Lee FS, Myers RM, et al. : Mitochondria DNA copy number, mitochondria DNA total somatic deletions, Complex I activity, synapse number, and synaptic mitochondria number are altered in schizophrenia and bipolar disorder. Transl Psychiatry 2022, 12:353.* [DOI] [PMC free article] [PubMed] [Google Scholar]; • A comprehensive analysis of mitochondrial features across multiple brain regions in human postmortem brain tissue from individuals with SZ, BD, and comparison subjects. This study allows for direct comparison of various mitochondria features (genetics, protein expression, oxygen consumption, synaptic localization/expression, etc) across regions within the same set of subjects. This is particularly important in context of a long history of individual findings suggesting mitochondrial alteration sin these disorders.
  • 42.Mertens J, Wang Q-W, Kim Y, Yu DX, Pham S, Yang B, Zheng Y, Diffenderfer KE, Zhang J, Soltani S, et al. : Differential responses to lithium in hyperexcitable neurons from patients with bipolar disorder. Nature 2015, 527:95–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Harrison PJ, Hall N, Mould A, Al-Juffali N, Tunbridge EM: Cellular calcium in bipolar disorder: systematic review and meta-analysis. Mol Psychiatry 2021,26:4106–4116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Niemsiri V, Rosenthal SB, Nievergelt CM, Maihofer AX, Marchetto MC, Santos R, Shekhtman T, Alliey-Rodriguez N, Anand A, Balaraman Y, et al. : Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis. Mol Psychiatry 2023, doi: 10.1038/s41380-022-01909-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Panchal P, de Queiroz Campos G, Goldman DA, Auerbach RP, Merikangas KR, Swartz HA, Sankar A, Blumberg HP: Toward a Digital Future in Bipolar Disorder Assessment: A Systematic Review of Disruptions in the Rest-Activity Cycle as Measured by Actigraphy. Front Psychiatry 2022, 13:780726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Pancheri C, Verdolini N, Pacchiarotti I, Samalin L, Delle Chiaie R, Biondi M, Carvalho AF, Valdes M, Ritter P, Vieta E, et al. : A systematic review on sleep alterations anticipating the onset of bipolar disorder. Eur Psychiatry 2019, 58:45–53. [DOI] [PubMed] [Google Scholar]
  • 47.Scott MR, McClung CA: Circadian Rhythms in Mood Disorders. Adv Exp Med Biol 2021, 1344:153–168. [DOI] [PubMed] [Google Scholar]
  • 48.Ketchesin KD, Zong W, Hildebrand MA, Scott MR, Seney ML, Cahill KM, Shankar VG, Glausier JR, Lewis DA, Tseng GC, et al. : Diurnal alterations in gene expression across striatal subregions in psychosis. Biological Psychiatry 2022, doi: 10.1016/j.biopsych.2022.08.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Nudell V, Wei H, Nievergelt C, Maihofer AX, Shilling P, Alda M, Berrettini WH, Brennand KJ, Calabrese JR, Coryell WH, et al. : Entrainment of Circadian Rhythms to Temperature Reveals Amplitude Deficits in Fibroblasts from Patients with Bipolar Disorder and Possible Links to Calcium Channels. Molecular Neuropsychiatry 2019, 5:115–124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Qiu P, Jiang J, Liu Z, Cai Y, Huang T, Wang Y, Liu Q, Nie Y, Liu F, Cheng J, et al. : BMAL1 knockout macaque monkeys display reduced sleep and psychiatric disorders. Natl Sci Rev 2019, 6:87–100.** [DOI] [PMC free article] [PubMed] [Google Scholar]; • Disruption of the circadian molecular clock through BMAL1 knockout leads to abnormal activity rhythms and behavior associated with psychiatric illness in the macaque. This is consistent with a growing literature on rodent models of genetic and environmental circadian disruptions that develop behaviors associated with psychiatric illnesses.

RESOURCES