Variations in seasonal solar insolation are associated with a history of suicide attempts in bipolar I disorder

Background: Bipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries. Methods: Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries). Results: This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p < 0.01. Conclusion: A large change in solar insolation, both between winter and summer and between the minimum and maximum monthly values, may increase the risk of suicide attempts in bipolar I disorder. With frequent circadian rhythm dysfunction and suicidal behavior in bipolar disorder, greater understanding of the optimal roles of daylight and electric lighting in circadian entrainment is needed

Exploratory study of ultraviolet B (UVB) radiation and age of onset of bipolar disorder

Background: Sunlight contains ultraviolet B (UVB) radiation that triggers the production of vitamin D by skin. Vitamin D has widespread effects on brain function in both developing and adult brains. However, many people live at latitudes (about > 40 N or S) that do not receive enough UVB in winter to produce vitamin D. This exploratory study investigated the association between the age of onset of bipolar I disorder and the threshold for UVB sufficient for vitamin D production in a large global sample. Methods: Data for 6972 patients with bipolar I disorder were obtained at 75 collection sites in 41 countries in both hemispheres. The best model to assess the relation between the threshold for UVB sufficient for vitamin D production and age of onset included 1 or more months below the threshold, family history of mood disorders, and birth cohort. All coefficients estimated at P ≤ 0.001. Results: The 6972 patients had an onset in 582 locations in 70 countries, with a mean age of onset of 25.6 years. Of the onset locations, 34.0% had at least 1 month below the threshold for UVB sufficient for vitamin D production. The age of onset at locations with 1 or more months of less than or equal to the threshold for UVB was 1.66 years younger. Conclusion: UVB and vitamin D may have an important influence on the development of bipolar disorder. Study limitations included a lack of data on patient vitamin D levels, lifestyles, or supplement use. More study of the impacts of UVB and vitamin D in bipolar disorder is needed to evaluate this supposition

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

\ua9 The Author(s) 2024.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

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

An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response

Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance