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Introduction
Bipolar disorder (BD) is a chronic and recurrent psychiatric disorder affecting ~1% of the population worldwide and presenting a major public health burden (Weissman et al., 1996; Eaton et al., 2008). It is characterized clinically by instability in mood resulting in manic and depressive episodes interspersed between neutral and euthymic states (Eaton et al., 2008). Risk for BD is highly genetic, with heritability estimates as high as 85% (McGuffin et al., 2003) and common genetic variation explaining up to a third of that (Cross-Disorder Group of the Psychiatric Genomics et al., 2013). Still, however, the pathophysiological characteristics of BD are not well understood. Investigating molecular phenotypes such as gene expression as intermediate measures between genetic variation and clinical variation is a viable strategy for uncovering disease mechanisms. Many such studies have been carried out for BD, and we present a summary that reveals a lack of consistency between findings likely owing to clinical heterogeneity, differing study designs, and the low numbers of samples investigated (N 62 BD subjects; online Supplementary Table S1) (Elashoff et al., 2007; Matigian et al., 2007; Choi et al., 2011; Akula et al., 2014; Beech et al., 2014; Mostafavi et al., 2014; Witt et al., 2014; Xiao et al., 2014; Cruceanu et al., 2015; Madison et al., 2015; Mertens et al., 2015; van Eijk et al., 2015; Zhao et al., 2015; Anand et al., 2016; Breen et al., 2016; Fromer et al., 2016; Hess et al., 2016; Jansen et al., 2016; Peterson et al., 2016; Fries et al., 2017; Kittel-Schneider et al., 2017; Pacifico and Davis, 2017; Vizlin-Hodzic et al., 2017). Moreover, there are many potential confounds that impact gene expression, including medication.
Therefore, to explore gene expression changes associated with BD, we generated RNA sequencing data from peripheral whole blood collected in a large case-control cohort from The Netherlands. We examined gene expression differences between groups both at the individual gene level and at the level of gene co-expression to shed light on disease-relevant molecular profiles. We also investigated the effects of lithium use, the most widely used prescription drug in...