The Neural Basis of Bipolar Disorder

Psychiatric TimesVol 32 No 2
Volume 32
Issue 2

Selected for clinical implications, here are some highlights from the recent acceleration in understanding of the mechanisms of bipolar disorder.

The Neural Basis of Bipolar Disorder


Like diabetes, bipolar disorder was described by Areteus of Cappadocia in the first century ad. But for bipolar disorder, no equivalent of insulin has emerged. How close are we to identifying the mechanisms of bipolar disorder? Selected for clinical implications, here are some highlights from the recent acceleration in understanding of those mechanisms. Findings range from genetics and neuroplasticity (plasticity-specific genes, epigenetics, neurotrophic factors) to brain imaging, brain networks, and broader processes (inflammation, clockworks).


Unlike Huntington disease, in which the number of nucleotide repeats in a single gene determine outcome, bipolar disorder appears to be influenced by several hundred genes: 266 in a recent meta-analysis.1 Some genes are more central to the development of bipolar disorder than others, suggesting that there are several main pathways to the development of this illness, not 266 different routes. For example, one of the most consistently identified genes is CACNA1C.2 This gene codes for a calcium channel subunit that affects amygdala processing of emotional events, which itself has been shown to be one of the central differences in brain function in bipolar disorder.3

The search for genes associated with bipolar disorder is complicated because many of the same genes, such as CACNA1C, are also associated with major depression and schizophrenia.4 This should not be surprising: given the large number of genes involved, the range of potential variations of mood and thought is vast. Just 2 variations at each of 266 genes allows 35,000 different permutations, and many of these genes have more than 2 variants. Although not all these variations would necessarily look different clinically, they are better mapped in continua rather than categories, as noted by Dr Ellen Leibenluft, Chief of the NIMH’s Section on Bipolar Spectrum Disorders. She commented that DSM categories “will remain somewhat arbitrary [italics added] because they will be imposed on fully continuous, smooth distributions.”5

The search for genes associated with bipolar disorder is further complicated by the overlap between genes that confer bipolar risk and genes that confer “plasticity.” The latter refers to genes that allow individuals to respond more directly to environmental experience, to mold themselves to their environment and potential future environments based on past experience.


Plasticity-specific genes. Multiple genes appear to confer an increased capacity to mold to or respond to one’s environment (particularly childhood environment). These genes include the serotonin transporter gene (SERT) and the brain-derived neurotrophic factor (BDNF) gene, among others.

Differences in the SERT gene length have been extensively investigated in relation to mood and anxiety disorders. The short version of the SERT gene is associated with an increased risk of depression in the face of life stresses, but only in the context of adverse childhood experiences. Benign childhoods appear to completely mask the gene length difference effects, as originally shown in the seminal work by Caspi and colleagues.6 These findings were recently replicated in bipolar disorder.7 Not all previous studies have found an association between bipolar disorder and the short SERT allele, however.8

The frequency of the short allele itself is highly variable across ethnic groups; none were found in one Chinese population.9 Overall, the findings originally shown by Caspi and colleagues have been consistent, particularly if age of adverse events is factored in (early childhood events have more impact, which to clinicians is of course no surprise).10,11

Similarly, a substantial literature associates the BDNF gene with mood disorders and bipolar disorder in particular. A base pair difference in the gene (single nucleotide polymorphism) leads to insertion of a methionine in the BDNF protein instead of a valine. The methionine variant is associated with increased susceptibility to Alzheimer disease, Parkinson disease, depression, eating disorders-and bipolar disorder.12 In bipolar disorder, carriers of the methionine-yielding allele have significantly higher suicide attempt rates.13

Although these alleles confer risk of a potentially lethal disorder, they must confer some benefit, or else they would have been selected out evolutionarily long ago (given that they act in young and middle age). Indeed, as psychiatrists must help patients and families understand, these are not “bad genes,” not even “susceptibility genes.” In some contexts, they are beneficial, or protective. For example, inheriting the Met allele of the BDNF gene looks like a bum deal: bipolar disorder, eating disorders, etc. But 2 studies have found that in the context of family maltreatment, inheriting the BDNF Met allele lowered susceptibility to adult depression-in individuals who carried 2 short versions of the SERT gene.14,15 Similarly, the short version of the SERT gene appears to confer a degree of vigilance and capacity to handle rapid changes in stress that is evolutionarily advantageous.16,17

Given that there are multiple “plasticity” genes (at least 4 beyond SERT and BDNF), the interactions are sure to be extremely complex. Nevertheless, one thing is clear: these genes interact with childhood environment to affect risk of developing mood disorders. And that factor comes as no surprise to clinicians. In bipolar disorders, childhood trauma is strongly associated with severity of illness, including earlier onset of the illness, a rapid cycling course, more psychotic features, and a higher number of lifetime mood episodes, as well as suicidal ideation and suicide attempts.

Epigenetics. A study by Weaver and colleagues18 on maternal licking and grooming in rats has shown that epigenetic modifications (methylation of the glucocorticoid receptor gene) transmitted behaviorally in a single generation are passed on to subsequent generations. If this were also true in humans, it would demonstrate that it is possible to “break the chain” of childhood abuse that is otherwise epigenetically, as well as environmentally, propagated. Indeed, a probable human correlate has recently been described that shows increased methylation of some genetic sites in individuals with a history of childhood maltreatment.19 But the study of epigenetic modifications in bipolar disorder is still very young, with only a few involved genes tentatively identified and awaiting replication.20

Neurotrophic factors. By contrast, a large literature now supports the “neuroplasticity” model of mood disorders as mediated by neurotrophic factors, such as BDNF; Bcl-2 (originally characterized in research on B-cell lymphoma, now recognized as an important intermediary in one of the mechanisms of action of lithium); and atrophic factors, such as excessive glutamate and cortisol.

The intracellular pathways associated with neuroplasticity are now so well understood that newcomer antidepressant treatments, such as ketamine, and sleep deprivation have already been shown to increase BDNF.21 Evidence to date suggests that these treatments are also working through the same mechanisms as antidepressants and electroconvulsive therapy, namely, modulating trophic/atrophic balance and thus cellular resilience. Likewise, physical activity is associated with increases in BDNF. Interestingly, however, the BDNF Val66Met genotype may modulate this effect. Only Val/Val individuals showed a correlation between activity levels and brain volumes.22


Imagine if clinicians had a lab test that would differentiate unipolar depression from bipolar depression. Toward this end, a University of Pittsburgh team led by Dr Mary Phillips has contributed tremendously. In a recent review of their own and others’ work, Drs Cardoso de Almeida and Phillips23 noted that there are indeed differences that can be seen on MRI: more widespread abnormalities in white matter connectivity and white matter hyperintensities in bipolar depression than in unipolar depression, habenula volume reductions in bipolar depression but not in unipolar depression, and abnormally elevated amygdala activity to mild sad and neutral facial expressions in bipolar depression.

The white matter hyperintensities are often found and noted when patients have cranial MRIs. They have been associated with cardiovascular disease and are observed in both bipolar and unipolar patients, especially those with hypertension and/or diabetes. Thus, although they are more frequent in bipolar disorder and have been thought to reflect the severity and frequency of mood episodes, they are not specific enough to use as an “imaging test” for bipolar disorder.

The habenula is an evolutionarily ancient, small structure closely connected to the thalamus. Its cells fire when bad things happen or are anticipated. Interestingly, ketamine specifically dampens down habenula activity.24 The habenula modulates the reward systems of the ventral tegmentum; thus, atrophy of the habenula might underlie the heightened reward sensitivity seen in bipolar disorders.23

       Cardoso de Almeida and Phillips       23 emphasize the need for a spectrum approach to diagnosis because it “may better conform to clinical reality than categorical diagnoses.” They cite the research domain criteria approach at the NIMH, which is expressly dimensional (ie, a “spectrum” system as opposed to a categorical system such as DSM). The chairman of DSM-5, Dr David Kupfer, coauthored an article with Dr Phillips (ironically published at the same time as DSM-5) that stated, “The problem in detection of a clear boundary between these disorders suggests that they might be better represented as a continuum of affective disorders.”25 Nonetheless, this team also published a study using functional MRI that differentiated (categorical) unipolar from bipolar depression using differences in subgenual cingulate blood flow at rest, with 83% sensitivity and 78% specificity (replication still needed).26

Broader processes

Inflammation. Clinicians are all too familiar with the prevalence of behaviors associated with inflammation, such as exercise, sleep, alcohol abuse, and smoking, and the association of these behaviors with medical comorbidities, including coronary artery disease, obesity and insulin resistance, osteoporosis, and pain.27 Most studies have found that even in euthymia, patients with bipolar disorder have elevated levels of inflammatory cytokines, and during mood episodes, these differences, relative to controls, become more dramatic.28 Successful treatment with lithium pushes these levels toward normal.29 On the basis of these findings, might an anti-inflammatory medication-even just an NSAID-be of value in mood disorders? Although numerous studies have shown benefit with a variety of agents, with the possible exception of omega-3 fatty acids, none has shown a sufficiently clear benefit to warrant use as an adjunct.30

Gut inflammatory factors have also recently been investigated for their association with bipolar disorder.31 Such investigations are part of an upsurge of interest in gut microbiota and their possible role in mental illnesses, including the recent finding that yogurt-like products appeared to modulate brain responses to emotional faces, a variable also studied in bipolar disorder.32

Clockworks. Multiple lines of evidence clearly implicate the role of biological clocks and rhythms in bipolar disorder. At the genetic level, of the many clock genes studied, few have replicated associations with bipolar disorder, yet collectively, the findings are supportive, including differences in lithium responsivity based on specific genotypes.33 In the remarkably simple molecular mechanism of the clock itself, several key enzymes are strongly associated with bipolar disorder, including GSK-3β, which is now also implicated in Alzheimer disease and traumatic brain injury (further strengthening the tantalizing idea that lithium, which antagonizes GSK-3β, might have a role in these problematic conditions).34,35

Leaping from the genetic and molecular level to humans, another line of evidence demonstrating the importance of biological clocks in bipolar disorder is emerging in the use of light and darkness to manipulate biological rhythms. A research group in Norway is in the middle of a randomized trial of blue-light blockade as an adjunctive treatment for hospitalized manic patients. They have just published a strikingly positive case report on one patient.36 If borne out in the full trial, such results will further affirm a central role for light and darkness as the mechanism of mood disorders, particularly bipolar disorder.

A clock role in mood disorders is also demonstrated by the consistent positive results in trials of chronotherapies, ranging from simple and inexpensive (dawn simulators) to complex and requiring trained staff-summarized by leaders of this field in a manual for clinicians.37


1. Nurnberger JI Jr, Koller DL, Jung J, et al; Psychiatric Genomics Consortium Bipolar Group. Identification of pathways for bipolar disorder: a meta-analysis. JAMA Psychiatry. 2014;71:657-664.

2. Ferreira MA, O’Donovan MC, Meng YA, et al; Wellcome Trust Case Control Consortium. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet. 2008;40:1056-1058.

3. Tesli M, Skatun KC, Ousdal OT, et al. CACNA1C risk variant and amygdala activity in bipolar disorder, schizophrenia and healthy controls. PLoS One. 2013;8:e56970.

4. Green EK, Grozeva D, Jones I, et al; Wellcome Trust Case Control Consortium. The bipolar disorder risk allele at CACNA1C also confers risk of recurrent major depression and of schizophrenia. Mol Psychiatry. 2010;15:1016-1022.

5. Leibenluft E. Categories and dimensions, brain and behavior: the yins and yangs of psychopathology. JAMA Psychiatry. 2014;71:15-17.

6. Caspi A, Sugden K, Moffitt TE, et al. Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science. 2003;301:386-389.

7. Benedetti F, Riccaboni R, Poletti D, et al. The serotonin transporter genotype modulates the relationship between early stress and adult suicidality in bipolar disorder. Bipolar Disord. 2014;16:857-866.

8. Risch N, Herrell R, Lehner T, et al. Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: a meta-analysis [published correction appears in JAMA. 2009;302:492]. JAMA. 2009;301:2462-2471.

9. Mohamed Saini S, Nik Jaafar NR, Sidi H, et al. Serotonin transporter gene polymorphism and its association with bipolar disorder across different ethnic groups in Malaysia. Compr Psychiatry. 2014;55(suppl 1):S76-S81.

10. Karg K, Burmeister M, Shedden K, Sen S. The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: evidence of genetic moderation. Arch Gen Psychiatry. 2011;68:444-454.

11. Mueller M, Armbruster D, Moser DA, et al. Interaction of serotonin transporter gene-linked polymorphic region and stressful life events predicts cortisol stress response. Neuropsychopharmacology. 2011;36:1332-1339.

12. Bath KG, Lee FS. Variant BDNF (Val66Met) impact on brain structure and function. Cogn Affect Behav Neurosci. 2006;6:79-85.

13. Kim B, Kim CY, Hong JP, et al. Brain-derived neurotrophic factor Val/Met polymorphism and bipolar disorder. Association of the Met allele with suicidal behavior of bipolar patients. Neuropsychobiology. 2008;58:97-103.

14. Grabe HJ, Schwahn C, Mahler J, et al. Genetic epistasis between the brain-derived neurotrophic factor Val66Met polymorphism and the 5-HTT promoter polymorphism moderates the susceptibility to depressive disorders after childhood abuse. Prog Neuropsychopharmacol Biol Psychiatry. 2012;

15. Comasco E, Åslund C, Oreland L, Nilsson KW. Three-way interaction effect of 5-HTTLPR, BDNF Val66Met, and childhood adversity on depression: a replication study. Eur Neuropsychopharmacol. 2013;23:1300-1306.

16. Homberg JR, Lesch KP. Looking on the bright side of serotonin transporter gene variation. Biol Psychiatry. 2011;69:513-519.

17. Dobson SD, Brent LJ. On the evolution of the serotonin transporter linked polymorphic region (5-HTTLPR) in primates. Front Hum Neurosci. 2013;7:588.

18. Weaver IC, Cervoni N, Champagne FA, et al. Epigenetic programming by maternal behavior. Nat Neurosci. 2004;7:847-854.

19. Mehta D, Klengel T, Conneely KN, et al. Childhood maltreatment is associated with distinct genomic and epigenetic profiles in posttraumatic stress disorder. Proc Natl Acad Sci U S A. 2013;110:8302-8307.

20. Kato T, Iwamoto K. Comprehensive DNA methylation and hydroxymethylation analysis in the human brain and its implication in mental disorders. Neuropharmacology. 2014;80:133-139.

21. Gideons ES, Kavalali ET, Monteggia LM. Mechanisms underlying differential effectiveness of memantine and ketamine in rapid antidepressant responses. Proc Natl Acad Sci U S A. 2014;111:8649-8654.

22. Brown BM, Bourgeat P, Peiffer JJ, et al; AIBL Research Group. Influence of BDNF Val66Met on the relationship between physical activity and brain volume. Neurology. 2014;83:1345-1352.

23. Cardoso de Almeida JR, Phillips ML. Distinguishing between unipolar depression and bipolar depression: current and future clinical and neuroimaging perspectives. Biol Psychiatry. 2013;73:111-118.

24. Lawson RP, Seymour B, Loh E, et al. The habenula encodes negative motivational value associated with primary punishment in humans. Proc Natl Acad Sci U S A. 2014;111:11858-11863.

25. Phillips ML, Kupfer DJ. Bipolar disorder diagnosis: challenges and future directions. Lancet. 2013;381:1663-1671.

26. Almeida JR, Mourao-Miranda J, Aizenstein HJ, et al. Pattern recognition analysis of anterior cingulate cortex blood flow to classify depression polarity. Br J Psychiatry. 2013;203:310-311.

27. Goldstein BI, Kemp DE, Soczynska JK, et al. Inflammation and the phenomenology, pathophysiology, comorbidity, and treatment of bipolar disorder: a systematic review of the literature. J Clin Psychiatry. 2009;70:1078-1090.

28. Modabbernia A, Taslimi S, Brietzke E, Ashrafi M. Cytokine alterations in bipolar disorder: a meta-analysis of 30 studies. Biol Psychiatry. 2013;74:15-25.

29. Guloksuz S, Cetin EA, Cetin T, et al. Cytokine levels in euthymic bipolar patients. J Affect Disord. 2010;126:458-462.

30. Rosenblat JD, Cha DS, Mansur RB, McIntyre RS. Inflamed moods: a review of the interactions between inflammation and mood disorders. Prog Neuropsychopharmacol Biol Psychiatry. 2014;53:23-34.

31. Severance EG, Gressitt KL, Yang S, et al. Seroreactive marker for inflammatory bowel disease and associations with antibodies to dietary proteins in bipolar disorder. Bipolar Disord. 2014;16:230-240.

32. Tillisch K, Labus J, Kilpatrick L, et al. Consumption of fermented milk product with probiotic modulates brain activity. Gastroenterology. 2013;144:1394-1401.

33. McCarthy MJ, Nievergelt CM, Kelsoe JR, Welsh DK. A survey of genomic studies supports association of circadian clock genes with bipolar disorder spectrum illnesses and lithium response. PLoS One. 2012;7:e32091.

34. Diniz BS, Machado-Vieira R, Forlenza OV. Lithium and neuroprotection: translational evidence and implications for the treatment of neuropsychiatric disorders. Neuropsychiatr Dis Treat. 2013;9:493-500.

35. Leeds PR, Yu F, Wang Z, et al. A new avenue for lithium: intervention in traumatic brain injury. ACS Chem Neurosci. 2014 Apr 11; [Epub ahead of print].

36. Henriksen TE, Skrede S, Fasmer OB, et al. Blocking blue light during mania-markedly increased regularity of sleep and rapid improvement of symptoms: a case report. Bipolar Disord. 2014;16:894-898.

37. Wirz-Justice A, Benedetti F, Terman M. Chronotherapeutics for Affective Disorders: A Clinician’s Manual for Light and Wake Therapy. 2nd ed. Basel, Switzerland: S Karger; 2013.

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