Differential contributions of circadian clock genes to cell survival in bipolar disorder patient derived neuronal progenitor cells distinguishes lithium responders and non-responders.

Bipolar disorder (BD) is characterized by disrupted circadian rhythms and neuronal loss. Lithium is neuroprotective and used to treat BD, but outcomes are variable. Past research identified that circadian rhythms in BD patient neurons are associated with lithium response (Li-R) or non-response (Li-NR). However, the underlying cellular mechanisms remain unknown. To study interactions among circadian clock genes and cell survival, and their role in BD and predicting lithium response, we tested selected genes (PER1, BMAL1 and REV-ERBα) and small molecule modulators of ROR/REV-ERB nuclear receptors in models of cell survival using mouse neurons and stem-cell derived neuronal progenitor cells (NPC) from BD patients and controls. In apoptosis assays using staurosporine (STS), lithium was neuroprotective. Knockdown of PER1, BMAL1 and REV-ERBα modified cell survival across models. In NPCs, reduced expression of PER1 and BMAL1 led to more extensive cell death in Li-NR vs. Li-R. Reduced REV-ERBα expression caused more extensive cell death in BD vs. control NPCs, without distinguishing Li-R and Li-NR. In IMHN, The REV-ERB agonist GSK4112 had strong effects on circadian rhythm amplitude, and was neuroprotective in mouse neurons and control NPCs, but not in BD NPCs. Expression of cell survival genes following STS and GSK4112 treatments revealed BD-associated, and Li-R associated differences in expression profiles. We conclude that the neuroprotective response to lithium is similar in NPCs from Li-R and Li-NR. However, knockdown of circadian clock genes or stimulation of REV-ERBs reveal distinct contributions to cell death in BD patient NPCs, some of which distinguish Li-R and Li-NR.

Trends in Telepsychiatry and In-Person Psychiatric Care for Depression in an Academic Health System, 2017-2022.

OBJECTIVE: The authors aimed to assess differences in appointment completion rates between telepsychiatry and in-person outpatient psychiatric care for patients with depression in an academic health system. METHODS: Electronic health records of encounters for patients (ages ≥10) with a depression diagnosis and at least one scheduled outpatient psychiatric appointment (N=586,266 appointments; November 2017-October 2022) were assessed for appointment volume and completion of telepsychiatry versus in-person sessions. RESULTS: Telepsychiatry became the dominant care modality after the onset of the COVID-19 pandemic, although the number of telepsychiatry and in-person appointments nearly converged by October 2022. Logistic regression showed that telepsychiatry appointments (July 2020-October 2022) were more likely (OR=1.30, 95% CI=1.27-1.34) to be completed than in-person appointments. CONCLUSIONS: Telepsychiatry appointments were less likely to be canceled or missed than in-person appointments, suggesting that telepsychiatry improved efficiency and continuity of care. As in-person operations resume following the pandemic, maintaining telepsychiatry services may optimize hospital-level and patient outcomes.

Patterns of pharmacotherapy for bipolar disorder: A GBC survey.

OBJECTIVES: To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well-characterized individuals with BD in North America, Europe, and Australia. METHODS: Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta-analyses with generalized linear mixed methods were conducted to identify prescription patterns. RESULTS: This study included 10,351 individuals from North America (n = 3985), Europe (n = 3822), and Australia (n = 2544). Overall, participants were predominantly female (60%) with BD-I (60%; vs. BD-II = 33%). Cross-sectionally, mood-stabilizing anticonvulsants (44%), second-generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First-generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD-II (47%) compared to BD-I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort. CONCLUSIONS: Mood-stabilizing anticonvulsants, second-generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first-generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence-based guidelines to help improve treatment practices in BD.

Family environment and polygenic risk in the bipolar high-risk context.

Background: The interaction of polygenic risk (PRS) and environmental effects on development of bipolar disorder (BD) is understudied, as are high-risk offspring perceptions of their family environment (FE). We tested the association of offspring-perceived FE in interaction with BD-PRS on liability for BD in offspring at high or low familial risk for BD. Methods: Offspring of a parent with BD (oBD; n = 266) or no psychiatric disorders (n = 174), aged 12-21 at recruitment, participated in the US and Australia. Empirically-derived profiles of FE classified offspring by their perceived levels of familial cohesion, flexibility, and conflict. Offspring BD-PRS were derived from Psychiatric Genomics Consortium BD-GWAS. Lifetime DSM-IV bipolar disorders were derived from the Schedule for Affective Disorders and Schizophrenia for School-Aged Children. We used a novel stepwise approach for latent class modeling with predictors and distal outcomes. Results: Fifty-two offspring were diagnosed with BD. For those with well-functioning FE (two-thirds of the sample), higher BD-PRS tracked positively with liability for BD. However, for those with high-conflict FEs, the relationship between BD-PRS and liability to BD was negative, with highest risk for BD observed with lower BD-PRS. In exploratory analyses, European-ancestry offspring with BD had elevated history of suicidal ideation in high-conflict FE compared to well-functioning-FE, and of suicide attempt with low-BD-PRS and high-conflict FE. Conclusions: The data suggest that the relationship of BD-PRS and offspring liability for BD differed between well-functioning versus high-conflict FE, potentially in line with a multifactorial liability threshold model and supporting future study of and interventions improving family dynamics.

Contributions of circadian clock genes to cell survival in fibroblast models of lithium-responsive bipolar disorder.

Bipolar disorder (BD) is characterized by mood episodes, disrupted circadian rhythms and gray matter reduction in the brain. Lithium is an effective pharmacotherapy for BD, but not all patients respond to treatment. Lithium has neuroprotective properties and beneficial effects on circadian rhythms that may distinguish lithium responders (Li-R) from non-responders (Li-NR). The circadian clock regulates molecular pathways involved in apoptosis and cell survival, but how this overlap impacts BD and/or lithium responsiveness is unknown. In primary fibroblasts from Li-R/Li-NR BD patients and controls, we found patterns of co-expression among circadian clock and cell survival genes that distinguished BD vs. control, and Li-R vs. Li-NR cells. In cellular models of apoptosis using staurosporine (STS), lithium preferentially protected fibroblasts against apoptosis in BD vs. control samples, regardless of Li-R/Li-NR status. When examining the effects of lithium treatment of cells in vitro, caspase activation by lithium correlated with period alteration, but the relationship differed in control, Li-R and Li-NR samples. Knockdown of Per1 and Per3 in mouse fibroblasts altered caspase activity, cell death and circadian rhythms in an opposite manner. In BD cells, genetic variation in PER1 and PER3 predicted sensitivity to apoptosis in a manner consistent with knockdown studies. We conclude that distinct patterns of coordination between circadian clock and cell survival genes in BD may help predict lithium response.

Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population.

Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.

National Network of Depression Centers' Recommendations on Harmonizing Clinical Documentation of Electroconvulsive Therapy.

ABSTRACT: Electroconvulsive therapy (ECT) is a highly therapeutic and cost-effective treatment for severe and/or treatment-resistant major depression. However, because of the varied clinical practices, there is a great deal of heterogeneity in how ECT is delivered and documented. This represents both an opportunity to study how differences in implementation influence clinical outcomes and a challenge for carrying out coordinated quality improvement and research efforts across multiple ECT centers. The National Network of Depression Centers, a consortium of 26+ US academic medical centers of excellence providing care for patients with mood disorders, formed a task group with the goals of promoting best clinical practices for the delivery of ECT and to facilitate large-scale, multisite quality improvement and research to advance more effective and safe use of this treatment modality. The National Network of Depression Centers Task Group on ECT set out to define best practices for harmonizing the clinical documentation of ECT across treatment centers to promote clinical interoperability and facilitate a nationwide collaboration that would enable multisite quality improvement and longitudinal research in real-world settings. This article reports on the work of this effort. It focuses on the use of ECT for major depressive disorder, which accounts for the majority of ECT referrals in most countries. However, most of the recommendations on clinical documentation proposed herein will be applicable to the use of ECT for any of its indications.

Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder.

Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis - prioritized by statistical association, predicted deleteriousness, and network centrality - was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAOG131, DaoG130V/+, we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture.

Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia.

We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10-9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD's polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.

Amygdala and anterior cingulate transcriptomes from individuals with bipolar disorder reveal downregulated neuroimmune and synaptic pathways.

Recent genetic studies have identified variants associated with bipolar disorder (BD), but it remains unclear how brain gene expression is altered in BD and how genetic risk for BD may contribute to these alterations. Here, we obtained transcriptomes from subgenual anterior cingulate cortex and amygdala samples from post-mortem brains of individuals with BD and neurotypical controls, including 511 total samples from 295 unique donors. We examined differential gene expression between cases and controls and the transcriptional effects of BD-associated genetic variants. We found two coexpressed modules that were associated with transcriptional changes in BD: one enriched for immune and inflammatory genes and the other with genes related to the postsynaptic membrane. Over 50% of BD genome-wide significant loci contained significant expression quantitative trait loci (QTL) (eQTL), and these data converged on several individual genes, including SCN2A and GRIN2A. Thus, these data implicate specific genes and pathways that may contribute to the pathology of BP.

Correction of depression-associated circadian rhythm abnormalities is associated with lithium response in bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is characterized by episodes of depression and mania and disrupted circadian rhythms. Lithium is an effective therapy for BD, but only 30%-40% of patients are fully responsive. Preclinical models show that lithium alters circadian rhythms. However, it is unknown if the circadian rhythm effects of lithium are essential to its therapeutic properties. METHODS: In secondary analyses of a multi-center, prospective, trial of lithium for BD, we examined the relationship between circadian rhythms and therapeutic response to lithium. Using standardized instruments, we measured morningness, diurnal changes in mood, sleep, and energy (circadian rhythm disturbances) in a cross-sectional study of 386 BD subjects with varying lithium exposure histories. Next, we tracked symptoms of depression and mania prospectively over 12 weeks in a subset of 88 BD patients initiating treatment with lithium. Total, circadian, and affective mood symptoms were scored separately and analyzed. RESULTS: Subjects with no prior lithium exposure had the most circadian disruption, while patients stable on lithium monotherapy had the least. Patients who were stable on lithium with another drug or unstable on lithium showed intermediate levels of disruption. Treatment with lithium for 12 weeks yielded significant reductions in total and affective depression symptoms. Lithium responders (Li-Rs) showed improvement in circadian symptoms of depression, but non-responders did not. There was no difference between Li-Rs and nonresponders in affective, circadian, or total symptoms of mania. CONCLUSIONS: Exposure to lithium is associated with reduced circadian disruption. Lithium response at 12 weeks was selectively associated with the reduction of circadian depressive symptoms. We conclude that stabilization of circadian rhythms may be an important feature of lithium's therapeutic effects. CLINICAL TRIALS REGISTRY: NCT0127253.

Cross-species Association Between Telomere Length and Glucocorticoid Exposure.

CONTEXT: Chronic exposure to glucocorticoids (GCs) or stress increases the risk of medical disorders, including cardiovascular and neuropsychiatric disorders. GCs contribute to accelerated aging; however, while the link between chronic GC exposure and disease onset is well established, the underpinning mechanisms are not clear. OBJECTIVE: We explored the potential nexus between GCs or stress exposure and telomere length. METHODS: In addition to rats exposed to 3 weeks of chronic stress, an iatrogenic mouse model of Cushing syndrome (CS), and a mouse neuronal cell line, we studied 32 patients with CS and age-matched controls and another cohort of 75 healthy humans. RESULTS: (1) Exposure to stress in rats was associated with a 54.5% (P = 0.036) reduction in telomere length in T cells. Genomic DNA (gDNA) extracted from the dentate gyrus of stressed and unstressed rats showed 43.2% reduction in telomere length (P = 0.006). (2) Mice exposed to corticosterone had a 61.4% reduction in telomere length in blood gDNA (P = 5.75 × 10-5) and 58.8% reduction in telomere length in the dentate gyrus (P = 0.002). (3) We observed a 40.8% reduction in the telomere length in patients with active CS compared to healthy controls (P = 0.006). There was a 17.8% reduction in telomere length in cured CS patients, which was not different from that of healthy controls (P = 0.08). For both cured and active CS, telomere length correlated significantly with duration of hypercortisolism (R2 = 0.22, P = 0.007). (4) There was a 27.6% reduction in telomere length between low and high tertiles in bedtime cortisol levels of healthy participants (P = 0.019). CONCLUSION: Our findings demonstrate that exposure to stress and/or GCs is associated with shortened telomeres, which may be partially reversible.

Methylomic and transcriptomic predictors of one-month exposure to cortisol in healthy individuals.

Allostatic load (AL) refers to the cumulative "wear and tear" on an organism throughout its lifetime. One of the primary contributing factors to AL is prolonged exposure to stress or its primary catabolic agent cortisol. Chronic exposure to stress or cortisol is associated with numerous diseases, including cardiovascular disease, metabolic disorders, and psychiatric disorders. Therefore, a molecular marker capable of integrating a past history of cortisol exposure would be of great utility for assessing disease risk. To this end, we recruited 87 healthy males and females of European ancestry between 18 and 60 years old, extracted genomic DNA and RNA from leukocytes, and implemented a gene-centric DNA enrichment method coupled with bisulfite sequencing and RNA-Seq of total RNA for the determination of genome-wide methylation and gene transcription, respectively. Sequencing data were analyzed against awakening and bedtime cortisol data to identify differentially methylated regions (DMRs) and CpGs (DMCs) and differentially expressed genes (DEGs). Six candidate DMCs (punadjusted < 0.005) and nine DEGs (punadjusted < 0.0005) were used to construct a prediction model that could capture past 30+ days of both bedtime and awakening cortisol levels. Utilizing a cross-validation approach, we obtained a regression coefficient of R2 = 0.308 for predicting continuous awakening cortisol and an area under the curve (AUC) = 0.753 for dichotomous (high vs. low tertile) awakening cortisol, and R2 = 0.224 and AUC = 0.723 for continuous and dichotomous bedtime cortisol levels, respectively. To our knowledge, the current study represents the first attempt to identify genome-wide predictors of cortisol exposure that utilizes both methylation and transcription targets. The utility of our approach needs to be replicated in an independent cohort of samples for which similar cortisol metrics are available.

A 7 Tesla Amygdalar-Hippocampal Shape Analysis of Lithium Response in Bipolar Disorder.

Research to discover clinically useful predictors of lithium response in patients with bipolar disorder has largely found them to be elusive. We demonstrate here that detailed neuroimaging may have the potential to fill this important gap in mood disorder therapeutics. Lithium treatment and bipolar disorder have both been shown to affect anatomy of the hippocampi and amygdalae but there is no consensus on the nature of their effects. We aimed to investigate structural surface anatomy changes in amygdala and hippocampus correlated with treatment response in bipolar disorder. Patients with bipolar disorder (N = 14) underwent lithium treatment, were classified by response status at acute and long-term time points, and scanned with 7 Tesla structural MRI. Large Deformation Diffeomorphic Metric Mapping was applied to detect local differences in hippocampal and amygdalar anatomy between lithium responders and non-responders. Anatomy was also compared to 21 healthy comparison participants. A patch of the ventral surface of the left hippocampus was found to be significantly atrophied in non-responders as compared to responders at the acute time point and was associated at a trend-level with long-term response status. We did not detect an association between response status and surface anatomy of the right hippocampus or amygdala. To the best of our knowledge, this is the first shape analysis of hippocampus and amygdala in bipolar disorder using 7 Tesla MRI. These results can inform future work investigating possible neuroimaging predictors of lithium response in bipolar disorder.

Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response: preliminary studies.

Bipolar disorder (BD) is a neuropsychiatric illness defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. Lithium is an effective drug for BD, but 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, circadian rhythms have not been evaluated in BD patient neurons from Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients characterized for lithium responsiveness and matched controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R, but NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein levels were higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

Developing Treatments for Alzheimer's and Related Disorders with Precision Medicine: A Vision.

Precision medicine, also known as personalized medicine, is concerned with finding the right treatment for the right patient at the right time. It is a way of thinking focused on parsing heterogeneity ultimately down to the level of the individual. Its main mission is to identify characteristics of heterogeneous clinical conditions so as to target tailored therapies to individuals. Precision Medicine however is not an agnostic collection of all manner of clinical, genetic and other biologic data in select cohorts. This is an important point. Simply collecting as much information as possible on individuals without applying this way of thinking should not be considered Precision Medicine.

De novo variation in bipolar disorder.

Bipolar disorder (BD) is a common, highly heritable disorder that affects 1-2% of the world's population. To date, most genetic studies of BD have focused on common gene variation, and while robustly associated loci have been identified, a substantial proportion of the heritability remains missing and could be partially attributable to rare variation. In this study, we apply a de novo paradigm in BD to identify newly arisen variants that have yet to undergo natural selection and may represent highly pathogenic variants. We performed whole genome sequencing of 97 trios of Ashkenazi Jewish descent, selecting "simplex" families with no family history of BD and an early age of onset. We found a total of 6882 de novo variants (an average of 70.9 ± 12.9 S.D. variants per trio), including 107 variants within protein-coding genes. We combined our exonic variations with the results of 79 previously published BD trios, identifying 20 loss-of-function (LoF) and 77 missense damaging de novo variants in BD. These variants showed significant enrichment for constrained genes and for genes located to the postsynaptic density (PSD) (all Bonferroni corrected p < 0.05). Pathway analyses showed enrichment in several pathways, including "Phosphoinositides (PI) and their downstream targets" (Bonferroni p = 4.2 × 10-6), a pathway prominently featured in lithium's hypothesized mechanism of action. In addition, while we found overall evidence for transmission of common variant polygenic risk of BD in our full sample (pTDT p = 2.21 × 10-4), specific trios with LoF variants showed no evidence of polygenic transmission. In sum, our findings support the de novo paradigm as a contributor to the genetic architecture of BD and provide evidence that constrained genes, as well as genes within the PSD and PI pathway harbor rare variation associated with BD.

A learning algorithm for predicting mental health symptoms and substance use.

Learning health systems use data to generate knowledge that informs clinical care, but few studies have evaluated how to leverage patient-reported mental health symptoms and substance use data to make patient-specific predictions. We developed a general Bayesian prediction algorithm that uses self-reported psychiatric symptoms and substance use within a population to predict future symptoms and substance use for individuals in that population. We validated our approach in 2444 participants from two clinical cohorts - the National Network of Depression Centers and the Johns Hopkins HIV Clinical Cohort - by predicting symptoms of depression, anxiety, and mania as well as alcohol, heroin, and cocaine use and comparing our predictions to observed symptoms and substance use. When we dichotomized mental health symptoms as moderate-severe vs. none-mild, individual predictions yielded areas under the ROC curve (AUCs) of 0.84 [95% confidence interval 0.80-0.88] and 0.85 [0.82-0.88] for symptoms of depression in the two cohorts, AUCs of 0.84 [0.79-0.88] and 0.85 [0.82-0.88] for symptoms of anxiety, and an AUC of 0.77 [0.72-0.82] for manic symptoms. Predictions of substance use yielded an AUC of 0.92 [0.88-0.97] for heroin use, 0.90 [0.82-0.97] for cocaine use, and 0.90 [0.88-092] for alcohol misuse. This rigorous, mathematically grounded approach could provide patient-specific predictions at the point of care. It can be applied to other psychiatric symptoms and substance use indicators, and is customizable to specific health systems. Such approaches can realize the potential of a learning health system to transform ever-increasing quantities of data into tangible guidance for patient care.

lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,199 human lncRNA (224,286 transcripts). The user-friendly knowledgebase covers a comprehensive breadth and depth of lncRNA annotation. lncRNAKB is a compendium of expression patterns, derived from analysis of RNA-seq data in thousands of samples across 31 solid human normal tissues (GTEx). Thousands of co-expression modules identified via network analysis and pathway enrichment to delineate lncRNA function are also accessible. Millions of expression quantitative trait loci (cis-eQTL) computed using whole genome sequence genotype data (GTEx) can be downloaded at lncRNAKB that also includes tissue-specificity, phylogenetic conservation and coding potential scores. Tissue-specific lncRNA-trait associations encompassing 323 GWAS (UK Biobank) are also provided. LncRNAKB is accessible at http://www.lncrnakb.org/ , and the data are freely available through Open Science Framework ( https://doi.org/10.17605/OSF.IO/RU4D2 ).