Biernacka, Joanna

Abstract Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������

AbstractObjectivesPersistent functional impairment is common in bipolar disorder (BD) and is influenced by a number of demographic, clinical, and cognitive features. The goal of this project was to estimate and compare the influence of key factors on community function in multiple cohorts of well‐characterized samples of individuals with BD.MethodsThirteen cohorts from 7 countries included n = 5882 individuals with BD across multiple sites. The statistical approach consisted of a systematic uniform application of analyses across sites. Each site performed a logistic regression analysis with empirically derived “higher versus lower function” as the dependent variable and selected clinical and demographic variables as predictors.ResultsWe found high rates of functional impairment, ranging from 41 to 75%. Lower community functioning was associated with depressive symptoms in 10 of 12 of the cohorts that included this variable in the analysis. Lower levels of education, a greater number of prior mood episodes, the presence of a comorbid substance use disorder, and a greater total number of psychotropic medications were also associated with low functioning.ConclusionsThe bipolar clinical research community is poised to work together to characterize the multi‐dimensional contributors to impairment and address the barriers that impede patients' complete recovery. We must also identify the core features which enable many to thrive and live successfully with BD. A large‐scale, worldwide, prospective longitudinal study focused squarely on BD and its heterogeneous presentations will serve as a platform for discovery and promote major advances toward optimizing outcomes for every individual with this illness.

AbstractInterest in analyzing X chromosome single nucleotide polymorphisms (SNPs) is growing and several approaches have been proposed. Prior studies have compared power of different approaches, but bias and interpretation of coefficients have received less attention. We performed simulations to demonstrate the impact of X chromosome model assumptions on effect estimates. We investigated the coefficient biases of SNP and sex effects with commonly used models for X chromosome SNPs, including models with and without assumptions of X chromosome inactivation (XCI), and with and without SNP–sex interaction terms. Sex and SNP coefficient biases were observed when assumptions made about XCI and sex differences in SNP effect in the analysis model were inconsistent with the data‐generating model. However, including a SNP–sex interaction term often eliminated these biases. To illustrate these findings, estimates under different genetic model assumptions are compared and interpreted in a real data example. Models to analyze X chromosome SNPs make assumptions beyond those made in autosomal variant analysis. Assumptions made about X chromosome SNP effects should be stated clearly when reporting and interpreting X chromosome associations. Fitting models with SNP × Sex interaction terms can avoid reliance on assumptions, eliminating coefficient bias even in the absence of sex differences in SNP effect.

AbstractIntroductionA key mechanism of lithium is the inhibition of glycogen synthase kinase‐3β (GSK3β) and activation of mammalian target of rapamycin (mTOR), two contributors to insulin signaling. We explored the relationship between these markers and clinical response to lithium in bipolar disorder (BD).MethodsThirty‐four subjects with BD who had been taking lithium for ≥2 years and had a maintenance lithium Alda score defined as either high (≥7; n = 20) or low (≤2; n = 14) were included in the study. Baseline protein expression of GSK3β and mTOR (total and phosphorylated (p)) was obtained from a buffy coat. Peripheral blood mononuclear cells (PBMCs) from a subset of each group (n = 11) were stimulated with insulin (10 µg) and change in protein expression was determined using Western blot.ResultsIn buffy coat samples, significantly higher levels of pmTOR were present in subjects with an Alda score ≤2 (lithium non‐responsive), relative to those with scores ≥7 (lithium‐responsive). No differences were observed for pGSK3β. In contrast, functional PBMC responses to 5 min of insulin stimulation demonstrated robust increases in pGSK3β (87.05 ± 43.41%) and pmTOR (105.7 ± 66.48%) in the lithium responsive group only. This contrasted observed decreases in pGSK3β (34.08 ± 16.12%) and pmTOR (37.84 ± 14.39%) 5 mins post‐insulin in non‐responders.ConclusionsDynamic increases in pmTOR and pGSK3β post‐insulin stimulation may reflect an immunometabolic state that facilitates lithium response. Further prospective analyses are needed to replicate and extend these preliminary findings and further investigate the role of insulin signaling in lithium response in BD.

AbstractBackgroundLithium is regarded as a first‐line treatment for bipolar disorder (BD), but partial response and non‐response commonly occurs. There exists a need to identify lithium non‐responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response.MethodsThe PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse.ResultsA total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness.ConclusionsIn this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy.

AbstractAimsLong‐term lithium therapy (LTLT) has been associated with kidney insufficiency in bipolar disorder (BD). We aimed to investigate the risk factors of chronic kidney disease (CKD) development and progression among BD patients receiving LTLT.MethodsWe included adult patients with BD on LTLT (≥1 year) who were enrolled in the Mayo Clinic Bipolar Biobank, Rochester, Minnesota. We reviewed electronic medical records to extract information related to lithium therapy and kidney‐related data to assess changes in the estimated glomerular filtration rate (eGFR). CKD severity was assessed based on eGFR.ResultsAmong 154 patients who received LTLT, 41 patients (27%) developed CKD, of whom 20 (49%) patients continued lithium (continuers) and 19 (46%) discontinued it (discontinuers). The median time to stage 3 CKD development was 21.7 years from the start of Li treatment. Type‐2 diabetes mellitus and benzodiazepine use were independent predictors for CKD development in the survival analysis, after controlling for age. The subsequent CKD progression rate did not differ between continuers and discontinuers (mean GFR 48.6 vs. 44.1, p = 0.13) at the end of follow‐up duration (mean duration: 3.5 ± 4.4 years for continuers and 4.9 ± 5.3 years for discontinuers).ConclusionCKD was observed in one fourth of patients with BD receiving LTLT. There was no significant difference in the progression of CKD among Li continuers versus discontinuers, at the mean follow‐up duration of 4.2 years, after the CKD diagnosis. Progression of CKD could be influenced by existing comorbidities and may not necessarily be due to lithium alone.

Abstract Polygenic risk scores (PRSs) have become an increasingly popular approach for demonstrating polygenic influences on complex traits and for establishing common polygenic signals between different traits. PRSs are typically constructed using pruning and thresholding (P+T), but the best choice of parameters is uncertain; thus multiple settings are used and the best is chosen. Optimization can lead to inflated Type I error. Permutation procedures can correct this, but they can be computationally intensive. Alternatively, a single parameter setting can be chosen a priori for the PRS, but choosing suboptimal settings results in loss of power. We propose computing PRSs under a range of parameter settings, performing principal component analysis (PCA) on the resulting set of PRSs, and using the first PRS–PC in association tests. The first PC reweights the variants included in the PRS to achieve maximum variation over all PRS settings used. Using simulations and a real data application to study PRS association with bipolar disorder and psychosis in bipolar disorder, we compare the performance of the proposed PRS–PCA approach with a permutation test and an a priori selected p ‐value threshold. The PRS–PCA approach is simple to implement, outperforms the other strategies in most scenarios, and provides an unbiased estimate of prediction performance.

Abstract Objective The aim of this study was to evaluate the efficacy and safety of the dopaminergic‐enhancing agent modafinil/armodafinil (MoArm) as adjunctive treatment for bipolar depression. Methods A comprehensive search of major electronic databases was conducted to identify randomized controlled trials (RCTs) of adjunctive MoArm that included patients with bipolar I (BP‐I) or bipolar II (BP‐II) depression. Data for response/remission and all‐cause discontinuation were analyzed. Effect size was summarized by relative risk (RR) using a random effect model. Results Of 58 studies, five RCTs (N = 795 drug, N = 792 placebo) met inclusion criteria. Four armodafinil studies included only BP‐I patients and one modafinil study included both bipolar subtypes with limited heterogeneity ( I 2 = 34%, P = .19; I 2 = 18%, P = .30). Compared to placebo, augmentation with MoArm was associated with significantly greater rates of treatment response (RR, 1.18; 95% CI, 1.01‐1.37; P = .03) and remission (RR, 1.38; 95% CI, 1.10‐1.73; P = .005). All‐cause discontinuation was not different than placebo (RR, 1.08; 95% CI, 0.89‐1.30; P = .45) with no evidence of increased risk of mood switch or suicide attempts with MoArm (RR, 0.99; 95% CI, 0.39‐2.5; P = .98; RR, 1.02; 95% CI, 0.37‐2.85; P = .97). Conclusion This narrower scope meta‐analysis of one drug for one disease suggests that adjunctive MoArm may represent a novel therapeutic intervention. Further studies delineating the subtypes of bipolar depression responsive to these novel dopaminergic‐enhancing agents are encouraged.