Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health 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 = 2367) 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 < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.

Lithium and risk of cardiovascular disease, dementia and venous thromboembolism.

OBJECTIVE: To determine if long-term lithium treatment is associated with protective effects or increased risk of vascular, neurological, and renal disorders. METHODS: Using nationwide registers, we included all citizens of Finland with dispensations of lithium for three or more consecutive years between 1995 and 2016. We identified 9698 cases and matched 96,507 controls without lithium treatment. Studied outcomes were vascular, neurological, renal disorders, and suicide. Analyses were performed applying Cox proportional hazards modeling in full cohort and in further subcohort analysis of individuals with a comparable diagnosis of mood or psychotic disorder. RESULTS: Lithium users had a significantly higher overall disease burden compared to matched population controls, including a higher risk of cardiovascular and cerebrovascular disorders and dementia. However, compared to individuals with a diagnosis of mood or psychotic disorders without lithium treatment, we observed a lower risk of cardiovascular and cerebrovascular disorders (HR = 0.80, 99% CI = 0.73-0.89), and no significant difference for dementia (HR = 1.15, 99% CI = 0.99-1.33), in lithium users. Pulmonary embolism was more common in the lithium-treated cases both in comparison to the general population (HR = 2.86, 99% CI = 2.42-3.37) and in comparison to the psychiatric subcohort (HR = 1.68, 99% CI = 1.31-2.17). Similarly, the risks of Parkinson's disease and kidney disease were higher in both comparisons. CONCLUSIONS: We conclude that individuals prescribed lithium have a lower risk of cardiovascular and cerebrovascular disease, but no marked effect on dementia, compared to individuals with a mood or psychotic disorder not prescribed lithium. Venous thromboembolism, Parkinson's disease, and kidney disease were significantly more prevalent in individuals prescribed lithium.

Prevalence and characteristics of unipolar mania in a low-income country setting: population-based data from the Butajira cohort, rural Ethiopia.

PURPOSE: Previous research suggests unipolar mania, i.e., bipolar disorder without depression, to be more common in low-income countries. However, longitudinal population-based studies on unipolar mania from low-income countries are lacking. This study therefore examined unipolar mania, in Butajira, Ethiopia, and associations with possible determinants. METHODS: Key informants and 68,378 screenings with the Composite International Diagnostic Interviews (CIDI 2.1) identified suspected cases of bipolar disorder. Diagnosis was confirmed using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN 2.1) (n = 2,285). 315 participants with bipolar disorder were recruited and followed up for an average of 2.5 years. Unipolar mania was defined when illness episodes consisted of at least two manic relapses. 240 cases had sufficient data to ascertain course of disorder. RESULTS: 41.7% (100 of 240 cases) of participants had unipolar mania. Unipolar mania was associated with less suicidal ideation (0% vs. 26.4%, p < 0.001), less suicidal thoughts (occasionally/often: 1%/3% vs. 19.6%/21%, p < 0.001), and less history of suicide attempt (2% vs. 11.6%, p = 0.01). The participants with unipolar mania tended to have better social functioning (OR = 2.05, p = 0.07) and less alcohol use (20.8% vs. 31.4%, p = 0.07). The study was partly based on retrospective data liable to recall bias. Some cases defined as unipolar mania in our study may later develop depression. CONCLUSION: Previous cross-sectional studies finding high proportions of unipolar mania in low-income countries appear supported. Unipolar mania trended towards better social functioning and was associated with lower suicidality. Future unipolar mania specifications could inform treatment and prognostic estimates of bipolar disorder.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

BACKGROUND: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

Investigating polygenic burden in age at disease onset in bipolar disorder: Findings from an international multicentric study.

OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P = 5.87 × 10 - 9; odds ratio (OR) = 1.12) and markers within ERBB2 (rs2517959, P = 4.53 × 10 - 9; OR = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.

Genetic variants associated with response to lithium treatment in bipolar disorder: a genome-wide association study.

BACKGROUND: Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified. METHODS: Here, we report the results of a genome-wide association study of lithium response in 2563 patients collected by 22 participating sites from the International Consortium on Lithium Genetics (ConLiGen). Data from common single nucleotide polymorphisms (SNPs) were tested for association with categorical and continuous ratings of lithium response. Lithium response was measured using a well established scale (Alda scale). Genotyped SNPs were used to generate data at more than 6 million sites, using standard genomic imputation methods. Traits were regressed against genotype dosage. Results were combined across two batches by meta-analysis. FINDINGS: A single locus of four linked SNPs on chromosome 21 met genome-wide significance criteria for association with lithium response (rs79663003, p=1·37 × 10(-8); rs78015114, p=1·31 × 10(-8); rs74795342, p=3·31 × 10(-9); and rs75222709, p=3·50 × 10(-9)). In an independent, prospective study of 73 patients treated with lithium monotherapy for a period of up to 2 years, carriers of the response-associated alleles had a significantly lower rate of relapse than carriers of the alternate alleles (p=0·03268, hazard ratio 3·8, 95% CI 1·1-13·0). INTERPRETATION: The response-associated region contains two genes for long, non-coding RNAs (lncRNAs), AL157359.3 and AL157359.4. LncRNAs are increasingly appreciated as important regulators of gene expression, particularly in the CNS. Confirmed biomarkers of lithium response would constitute an important step forward in the clinical management of bipolar disorder. Further studies are needed to establish the biological context and potential clinical utility of these findings. FUNDING: Deutsche Forschungsgemeinschaft, National Institute of Mental Health Intramural Research Program.

Lithium treatment and cancer incidence in bipolar disorder.

OBJECTIVES: To investigate whether there is an increased risk of cancer associated with lithium treatment in patients with bipolar disorder compared to the general population. METHODS: A nationwide Swedish register study of incidence rate ratios (IRRs) of total cancer and site-specific cancer in the 50-84-year age range was carried out in patients with bipolar disorder (n = 5,442) with and without lithium treatment from July 2005 to December 2009 compared to the general population using linked information from The Swedish Cancer Register, The National Patient Register, and The Drug Prescription Register. RESULTS: The overall cancer risk was not increased in patients with bipolar disorder. There was no difference in risk of unspecified cancer, neither in patients with lithium treatment compared to the general population [IRR = 1.04, 95% confidence interval (CI): 0.89-1.23] nor in patients with bipolar disorder without lithium treatment compared to the general population (IRR = 1.03, 95% CI: 0.89-1.19). The cancer risk was significantly increased in patients with bipolar disorder without lithium treatment in the digestive organs (IRR = 1.47, 95% CI: 1.12-1.93), in the respiratory system and intrathoracic organs (IRR = 1.72, 95% CI: 1.11-2.66), and in the endocrine glands and related structures (IRR = 2.60, 95% CI: 1.24-5.47), but in patients with bipolar disorder with lithium treatment, there was no significantly increased cancer risk compared to the general population. CONCLUSIONS: Bipolar disorder was not associated with increased cancer incidence and neither was lithium treatment in these patients. Specifically, there was an increased risk of respiratory, gastrointestinal, and endocrine cancer in patients with bipolar disorder without lithium treatment.

Telomerase dysregulation in the hippocampus of a rat model of depression: normalization by lithium.

BACKGROUND: Telomeres are protective DNA-protein complexes at the ends of each chromosome, maintained primarily by the enzyme telomerase. Shortening of the blood leukocyte telomeres is associated with aging, several chronic diseases, and stress, eg, major depression. Hippocampus is pivotal in the regulation of cognition and mood and the main brain region of telomerase activity. Whether there is telomere dysfunction in the hippocampus of depressed subjects is unknown. Lithium, used in the treatment and relapse prevention of mood disorders, was found to protect against leukocyte telomere shortening in humans, but the mechanism has not been elucidated. To answer the questions whether telomeres are shortened and the telomerase activity changed in the hippocampus and whether lithium could reverse the process, we used a genetic model of depression, the Flinders Sensitive Line rat, and treated the animals with lithium. METHODS: Telomere length, telomerase reverse transcriptase (Tert) expression, telomerase activity, and putative mediators of telomerase activity were investigated in the hippocampus of these animals. RESULTS: The naïve Flinders Sensitive Line had shorter telomere length, downregulated Tert expression, reduced brain-derived neurotrophic factor levels, and reduced telomerase activity compared with the Flinders Resistant Line controls. Lithium treatment normalized the Tert expression and telomerase activity in the Flinders Sensitive Line and upregulated ß-catenin. CONCLUSION: This is the first report showing telomere dysregulation in hippocampus of a well-defined depression model and restorative effects of lithium treatment. If replicated in other models of mood disorder, the findings will contribute to understanding both the telomere function and the mechanism of lithium action in hippocampus of depressed patients.

Exploring the genetics of lithium response in bipolar disorders.

BACKGROUND: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. RESULTS: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. CONCLUSIONS: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Determination of lithium concentration in capillary blood using volumetric dried blood spots.

BACKGROUND: Lithium is a cornerstone in the treatment of bipolar disorder and is considered one of the most effective treatments in psychiatry at large. Lithium treatment requires individual dosing with frequent serum concentration measurements due to the narrow therapeutic window and risk of toxicity. There is need for patient-centric methods for lithium monitoring and the use of dried blood spots has recently been proposed for determination of lithium concentration. The purpose of the current study was to assess feasibility of this method by introducing a volumetric technique developed for home-sampling. MATERIALS AND METHODS: Laboratory: Capillary blood was sampled by finger-prick using a volumetric device that collects 10 µL volumes as a dried blood spot. Lithium was measured in the dried blood spots using a validated atomic absorption spectroscopy method. CLINICAL: Thirty-nine lithium-treated patients were recruited, and dried blood spots and venous blood samples were collected. Routine serum analysis was performed for comparison. RESULTS: The range of serum lithium concentrations was 0.41-1.22 mmol/L, and the dried blood spot/serum ratio was 0.78. A strong linear correlation between the two specimens was shown with Pearson's R = 0.95 (r2 = 0.90). Adding hematocrit as a variable only minimally improved prediction. CONCLUSION: Volumetric dried blood spots is a promising technique for measurement of lithium concentrations. This will enable home-sampling and could potentially save resources, improve compliance, and make treatment safer. This may facilitate the use of lithium treatment in regions where monitoring via venous blood sampling remains difficult. However, the usability of dried blood spots for monitoring lithium treatment longitudinally remains to be examined.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3ß. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.

Lithium Response in Bipolar Disorder is Associated with Focal Adhesion and PI3K-Akt Networks: A Multi-omics Replication Study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2,039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Exploring the genetics of lithium response in bipolar disorders.

Background: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.

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<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.

Symptoms and treatment of bipolar patients in Sweden.

OBJECTIVE: The objective of the study was to investigate affective symptoms and pharmacological treatment in bipolar I disorder patients, and to test whether self-rated symptoms could predict hospital admissions during a 12-month follow-up period. METHODS: A total of 231 outpatients with clinical bipolar I disorder were recruited. The clinical diagnoses were reassessed by a semi-structured interview. Twenty-four patients (10%) was reclassified as bipolar disorder type II or schizoaffective disorder (bipolar type). Medication status was recorded and symptoms were assessed with the self-rating scale AS-18. Patients were prospectively followed for 12 months and hospitalizations during that time were recorded. RESULTS: More than half (60%) rated themselves as normothymic. Mixed affective symptoms were more common than either depressive or manic/hypomanic symptoms. The admission rate during 1 year of follow-up was 13% (95% C.I. 8-17%). Patients which at baseline rated themselves high in either mania or in depression had a significantly increased risk for hospitalization (OR = 3.15; 95% C.I. 1.38-7.19). CONCLUSIONS: The findings should encourage clinicians to use patient self ratings in order to identify patients with a high risk for hospitalization for targeted interventions.

Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden.

BACKGROUND: Lithium is the most effective treatment for bipolar disorder, resulting in strong suicide prevention effects. The therapeutic range of lithium, however, is narrow and treatment initiation requires individual titration to address inter-individual variability. We aimed to improve lithium dose prediction using clinical and genomic data. METHODS: We performed a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two clinical Swedish cohorts. Participants in cohort 1 were from specialised outpatient clinics at Huddinge Hospital, in Stockholm, Sweden, and participants in cohort 2 were identified using the Swedish National Quality Registry for Bipolar disorder (BipoläR). Patients who received a lithium dose corresponding to at least one tablet of lithium sulphate (6 mmol) per day and had clinically relevant plasma concentrations of lithium were included in the study. Data on age, sex, bodyweight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of tablets of lithium per day, serum lithium concentration, and medications affecting kidney function (C09 antihypertensives, C03 [except C03D] sodium-retaining diuretics, and non-steroidal anti-inflammatory drugs) were obtained retrospectively for several timepoints when possible from electronic health records, BipoläR, and the Swedish prescription registry. The median time between timepoints was 1·07 years for cohort 1 and 1·09 years for cohort 2. The primary outcome of interest was the natural logarithm of total body clearance for lithium (CLLi) associated with the clinical variables. The residual effects after accounting for age and sex, representing the individual-level effects (CLLi,age/sex), were used as the dependent variable in a GWAS. FINDINGS: 2357 patients who were administered lithium (1423 women [60·4%] and 934 men [39·6%]; mean age 53·6 years [range 17-89], mainly of European descent) were included and 5627 data points were obtained. Age (variance explained [R2]: R2cohort1=0·41 and R2cohort2=0·31; both p<0·0001), sex (R2cohort1=0·0063 [p=0·045] and R2cohort2=0·026 [p<0·0001]), eGFR (R2cohort1=0·38 and R2cohort2=0·20; both p<0·0001), comedication with diuretics (R2cohort1=0·0058 [p=0·014] and R2cohort2=0·0026 [p<0·0001]), and agents acting on the renin-aldosterone-angiotensin system (R2cohort1=0·028 and R2cohort2=0·015; both p<0·0001) were clinical predictors of CLLi. Notably, an association between CLLi and serum lithium was observed, with a lower CLLi being associated with higher serum lithium (R2cohort1=0·13 and R2cohort2=0·15; both p<0·0001). In a GWAS of CLLi,age/sex, one locus was associated with a change in CLLi (rs583503; ß=-0·053 [95% CI -0·071 to -0·034]; p<0·00000005). We also found enrichment of the associations with genes expressed in the medulla (p=0·0014, corrected FDR=0·04) and cortex of the kidney (p=0·0015, corrected FDR=0·04), as well as associations with polygenic risk scores for eGFR (p value threshold: 0·05, p=0·01), body-mass index (p value threshold: 0·05, p=0·00025), and blood urea nitrogen (p value threshold: 0·001, p=0·00043). The model based on six clinical predictors explained 61·4% of the variance in CLLi in cohort 1 and 49·8% in cohort 2. Adding genetic markers did not lead to major improvement of the models: within the subsample of genotyped individuals, the variance explained only increased from 59·32% to 59·36% in cohort 1 and from 49·21% to 50·03% in cohort 2 when including rs583503 and the four first principal components. INTERPRETATION: Our model predictors could be used clinically to better guide lithium dosage, shortening the time to reach therapeutic concentrations, thus improving care. Identification of the first genomic locus and PRS to be associated with CLLi introduces the opportunity of individualised medicine in lithium treatment. FUNDING: Stanley Medical Research Institute, Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Swedish Research Council, Söderström-Königska Foundation, Bror Gadelius Minnesfond, Swedish Mental Health Fund, Karolinska Institutet and Hospital.