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Reviewing the Clinical LandscapeFull Access

So Where Are the Genes for Bipolar Disorder?

Published Online:https://doi.org/10.1176/appi.focus.154S10

Over the past several years, large-scale genome association studies of schizophrenia have been notably successful in identifying a number of statistically significant risk loci in a variety of genes, many of which have been replicated in independent samples and meta-analyses (1). The effect sizes for individual genes, however, remain small, and how they might interact in a given individual or family to produce the syndrome remains obscure. Rather surprisingly, this progress has not been matched in the results reported for comparable efforts to identify risk variants in bipolar mood disorder. Why this should be the case is not entirely clear, and it is somewhat counterintuitive, given the strong heritability of bipolar mood disorder and its more specifically defined clinical phenotype.

One contributing reason may simply be the numbers of people studied; the cohorts accrued in the international consortia to date and the merged data sets are significantly larger for schizophrenia, and it has become clear that sample sizes of tens of thousands, and maybe more, are necessary for clear and replicable signals to emerge in the genetic analysis of complex diseases when heterogeneous populations are studied and the effect sizes of individual gene mutations small.

Another issue, not unique to bipolar disorder, is that the clinical phenotype, although more distinctly defined than many other psychiatric conditions, may still suffer from etiologic heterogeneity and the inclusion of phenocopies. To this end, numerous groups have begun to rely on quantitative assessment of relevant component traits of bipolar disorder, such as activity-level parameters, neurocognitive function and changes in brain structure, and dimensions of temperament, in the hope that defining genetic factors contributing to individual endophenotypic components may be more productive than continuing reliance on categorical diagnosis alone (2). The genetic exploration of lithium responsivity is yet another example of a strategy that may provide a key to unique insights of pathophysiology (3).

One alternative approach emerges from the finding that some of the risk variants that have been reported for schizophrenia have also been found in bipolar disorder, as well as some other psychiatric conditions. This may be indicative of a shared pathophysiology and reflected in components of a shared intermediate phenotype—for example, psychosis. To this end, some research groups have reported that both bipolar disorder and schizophrenia can be reclassified into differing subgroups encompassing both disorders, on the basis of biomarkers such as brain structure, cognition, and sensorimotor profiles (4).

Which of these approaches—brute force through greatly increased numbers of persons studied, or more selective dissection of the unique or shared phenotypes involved—will be more likely to achieve greater clarity in understanding the relation between genetic risk and our most serious psychiatric illnesses remains unresolved.

Dr. Reus is distinguished professor of psychiatry at the University of California, San Francisco School of Medicine, San Francisco.
References

1 Schizophrenia Working Group of the Psychiatric Genomics Consortium: Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014; 511:421–427CrossrefGoogle Scholar

2 Fears SC, Service SK, Kremeyer B, et al.: Multisystem component phenotypes of bipolar disorder for genetic investigations of extended pedigrees. JAMA Psychiatry 2014; 71:375–387CrossrefGoogle Scholar

3 Oedegaard KJ, Alda M, Anand A, et al.: The Pharmacogenomics of Bipolar Disorder Study (PGBD): identification of genes for lithium response in a prospective sample. BMC Psychiatry 2016; 16:129CrossrefGoogle Scholar

4 Ivleva EI, Clementz BA, Dutcher AM, et al.: Brain structure biomarkers in the psychosis biotypes: findings from the bipolar-schizophrenia network for intermediate phenotypes. Biol Psychiatry 2017; 82:26–39CrossrefGoogle Scholar