Association between exposure to antidepressants and stimulants and age at onset of mania or psychosis: A retrospective population-based cohort study.

This study investigated the impact of prior antidepressant and stimulant exposure on the age at onset (AAO) of first episode mania (FEM) or psychosis (FEP). Patients with FEP and FEM born after 1985 in Olmsted County, Minnesota, were identified using the Rochester Epidemiology Project. Duration and peak dose of antidepressant and stimulant exposure were quantified by review of the electronic health record. Peak doses were converted to defined daily dose (DDD), and cumulative exposure was calculated as DDD multiplied by treatment duration. Linear models were used to assess relationships between AAO with any exposures, and cumulative antidepressant and stimulant exposures. A total of 190 FEM/FEP patients (mean AAO=20.8 ± 3.7 years) were included. There was no significant difference in AAO with vs. without exposure to antidepressants or stimulants. Cumulative antidepressant exposure correlated with a later AAO in overall sample (r = 0.28, p < 0.001), and in FEP (r = 0.33, p < 0.001). No significant correlation emerged between cumulative stimulant exposure and AAO. Multivariable modeling confirmed that cumulative antidepressant exposure (Estimate=2.42, 95 %CI=1.66-3.18, p < 0.001), but not cumulative stimulant exposure (Estimate=-0.04, 95 %CI=-1.10-1.02, p = 0.94), was associated with later AAO. Antidepressant and stimulant exposures were not associated with earlier AAO. However, cumulative antidepressant exposure was associated with later AAO. Limitations include retrospective design and relatively small sample size. Our findings may inform adolescent treatment recommendations when assessing risk for psychotropic-related adverse events. Further risk modeling investigations of antidepressants and stimulants with larger sample sizes are needed to explore the role of antidepressant and stimulant exposure in the trajectory leading to FEM/FEP.

Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results.

Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding.

Differential serum levels of CACNA1C, circadian rhythm and stress response molecules in subjects with bipolar disorder: Associations with genetic and clinical factors.

BACKGROUND: Many patients with bipolar disorder (BD) do not respond to or have difficulties tolerating lithium and/or other mood stabilizing agents. There is a need for personalized treatments based on biomarkers in guiding treatment options. The calcium voltage-gated channel CACNA1C is a promising candidate for developing personalized treatments. CACNA1C is implicated in BD by genome-wide association studies and several lines of evidence suggest that targeting L-type calcium channels could be an effective treatment strategy. However, before such individualized treatments can be pursued, biomarkers predicting treatment response need to be developed. METHODS: As a first step in testing the hypothesis that CACNA1C genotype is associated with serum levels of CACNA1C, we conducted ELISA measures on serum samples from 100 subjects with BD and 100 control subjects. RESULTS: We observed significantly higher CACNA1C (p < 0.01) protein levels in subjects with BD. The risk single nucleotide polymorpshism (SNP) (rs11062170) showed functional significance as subjects homozygous for the risk allele (CC) had significantly greater CACNA1C protein levels compared to subjects with one (p = 0.013) or no copies (p = 0.009). We observed higher somatostatin (SST) (p < 0.003) protein levels and lower levels of the clock protein aryl hydrocarbon receptor nuclear translocator-like (ARTNL) (p < 0.03) and stress signaling factor corticotrophin releasing hormone (CRH) (p < 0.001) in BD. SST and period 2 (PER2) protein levels were associated with both alcohol dependence and lithium response. CONCLUSIONS: Our findings represent the first evidence for increased serum levels of CACNA1C in BD. Along with altered levels of SST, ARNTL, and CRH our findings suggest CACNA1C is associated with circadian rhythm and stress response disturbances in BD.

Prediction of medical admissions after psychiatric inpatient hospitalization in bipolar disorder: a retrospective cohort study.

Objective: Bipolar Disorder (BD) is a severe mental illness associated with high rates of general medical comorbidity, reduced life expectancy, and premature mortality. Although BD has been associated with high medical hospitalization, the factors that contribute to this risk remain largely unexplored. We used baseline medical and psychiatric records to develop a supervised machine learning model to predict general medical admissions after discharge from psychiatric hospitalization. Methods: In this retrospective three-year cohort study of 71 patients diagnosed with BD (mean age=52.19 years, females=56.33%), lasso regression models combining medical and psychiatric records, as well as those using them separately, were fitted and their predictive power was estimated using a leave-one-out cross-validation procedure. Results: The proportion of medical admissions in patients with BD was higher compared with age- and sex-matched hospitalizations in the same region (25.4% vs. 8.48%). The lasso model fairly accurately predicted the outcome (area under the curve [AUC]=69.5%, 95%C.I.=55-84.1; sensitivity=61.1%, specificity=75.5%, balanced accuracy=68.3%). Notably, pre-existing cardiovascular, neurological, or osteomuscular diseases collectively accounted for more than 90% of the influence on the model. The accuracy of the model based on medical records was slightly inferior (AUC=68.7%, 95%C.I. = 54.6-82.9), while that of the model based on psychiatric records only was below chance (AUC=61.8%, 95%C.I.=46.2-77.4). Conclusion: Our findings support the need to monitor medical comorbidities during clinical decision-making to tailor and implement effective preventive measures in people with BD. Further research with larger sample sizes and prospective cohorts is warranted to replicate these findings and validate the predictive model.

Divergent visual ecology of Drosophila species drives object-tracking strategies matched to landscape sparsity.

Maintaining stable gaze while tracking moving objects is commonplace across animal taxa, yet how diverse ecological needs impact these processes is poorly understood. During flight, the fruit-eating fly Drosophila melanogaster maintains course by making smooth steering adjustments to fixate the image of the distant visual background on the retina, while executing body saccades to investigate nearby objects such as food sources. Cactophilic Drosophila mojavensis live where there is no canopy; rather, the flora forming visual "background" and "objects" are one and the same. We tested whether D. mojavensis have adapted their flight control strategies for a visually sparse landscape. We used a magnetic tether that allows free movement in the yaw axis. In response to a textured bar moving across a similarly textured stationary background, D. melanogaster fixates the background, thereby stabilizing gaze while integrating bar dynamics to trigger tracking saccades. By contrast, two mojavensis subspecies in the repleta subgroup and one species in the melanogaster subgroup steer to smoothly fixate the bar, seemingly ignoring the stationary surround. Desert flies execute frequent bar-tracking saccades, but theirs are triggered when rotational velocity lags the bar. Thus, D. melanogaster, which lives in visually cluttered cosmopolitan habitats, leverages the optical disparities between nearby objects and distant foliage for a hybrid control strategy: "ground-fixate, object-saccade." Flies in distant phylogenetic subgroups with similar visual ecology use a "fixate-and-saccade" strategy, which would be adaptive in a visually sparse environment where individual landscape features are both approached and used to maintain a straight course.

Bidirectional negative relationship between thyrotropin and kidney function during alcohol intoxication in males.

Introduction: Despite a well-established direct toxic effect of alcohol on renal cells, there is a salutary dose-dependent effect of alcohol consumption on common laboratory parameters related to kidney performance. Alcohol also impacts thyroid hormones, while thyroid status modulates kidney function. The modulation of kidney parameters with thyrotropin (TSH) and thyroid status indicates a possible interaction between alcohol, kidney, and thyroid functions. This retrospective study was conducted to test the hypothesis that the positive effect of alcohol use on the estimated glomerular filtration rate (eGFR) is mediated by alcohol's effect on thyroid hormones. Methods: We reviewed the electronic medical records of 767 hospitalized adult patients free of thyroid disorders who received medical care in the Mayo Clinic Health System from June 2019 through June 2022 and had blood alcohol concentration (BAC), serum TSH, and serum creatinine measured during the hospitalization. We calculated the eGFR using both the re-expressed Modification of Diet in Renal Disease (MDRD II) study equation and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Creatinine equation. Results: We found a significant relationship of BAC with eGFR (CKD-EPI) and TSH in males only. BAC had a positive association with eGFR (b = 0.24, p = 0.0001) and negative with TSH (b=-0.17, p = 0.006). The covariance between the two outcomes (eGFR and TSH) was negative (b = -0.12, p = 0.049). The path analyses using the eGFR MDRD II equation were not significant in males, whereas females had no significant path analyses with either of the eGFR equations. Discussion: We observed that BAC influences both eGFR and TSH, whereas eGFR and TSH influence each other. After considering important covariates (e.g., age, body mass index, diabetes mellitus, cardiovascular disease, chronic kidney disease, and chronic liver disease) and the negative bidirectional effect of TSH and eGFR, a positive impact of BAC on eGFR was observed in males.

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.

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.

Differential Serum Levels of CACNA1C, Circadian Rhythm and Stress Response Molecules in Subjects with Bipolar Disorder: Associations with Genetic and Clinical Factors.

Background: Many patients with bipolar disorder (BD) do not respond to or have difficulties tolerating lithium and/or other mood stabilizing agents. There is a need for personalized treatments based on biomarkers in guiding treatment options. The calcium voltage-gated channel CACNA1C is a promising candidate for developing personalized treatments. CACNA1C is implicated in BD by genome-wide association studies and several lines of evidence suggest that targeting L-type calcium channels could be an effective treatment strategy. However, before such individualized treatments can be pursued, biomarkers predicting treatment response need to be developed. Methods: As a first step in testing the hypothesis that CACNA1C genotype is associated with serum levels of CACNA1C, we conducted ELISA measures on serum samples from 100 subjects with BD and 100 control subjects. Results: We observed significantly higher CACNA1C (p<0.01) protein levels in subjects with BD. The risk SNP (rs11062170) showed functional significance as subjects homozygous for the risk allele (CC) had significantly greater CACNA1C protein levels compared to subjects with one (p=0.013) or no copies (p=0.009). We observed higher somatostatin (SST) (p<0.003) protein levels and lower levels of the clock protein ARTNL (p<0.03) and stress signaling factor corticotrophin releasing hormone (CRH) (p<0.001) in BD. SST and PER2 protein levels were associated with both alcohol dependence and lithium response. Conclusions: Our findings represent the first evidence for increased serum levels of CACNA1C in BD. Along with altered levels of SST, ARNTL, and CRH our findings suggest CACNA1C is associated with circadian rhythm and stress response disturbances in BD.

Animal behavior: Mosquitos ride the wave.

Some insects have a frustrating knack for avoiding a swatter. A new study shows that mosquitos not only evade the visual image of the looming threat, they also surf the wave of air the swatter creates.

Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data.

Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.

Change in neurocognitive functioning in patients with treatment-resistant depression with serial intravenous ketamine infusions: The Bio-K multicenter trial.

This nonrandomized, multicenter, open-label clinical trial explored the impact of intravenous (IV) ketamine on cognitive function in adults (n = 74) with treatment-resistant depression (TRD). Patients received three IV ketamine infusions during the acute phase and, if remitted, four additional infusions in the continuation phase (Mayo site). Cognitive assessments using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were conducted at baseline, end of the acute phase, and end of the continuation phase (Mayo site). Results showed a significant 53 % (39/74) remission rate in depression symptoms after the acute phase. In adjusted models, baseline language domain score was associated with a higher odd of remission (Odds Ratio, 1.09, 95 % CI = 1.03-1.17, p = 0.004) and greater improvement in MADRS at the end of the acute phase (ß =-0.97; 95 % CI, -1.74 to -0.20; P = 0.02). The likelihood of remission was not significantly associated with baseline immediate or delayed memory, visuospatial/constructional, or attention scores. In the continuation phase, improvements in immediate and delayed memory and attention persisted, with additional gains in visuospatial and language domains. Limitations included an open-label design, potential practice effects, and ongoing psychotropic medication use. Overall, the study suggests cognitive improvement, not deterioration, associated with serial IV ketamine administrations for TRD. These findings encourage future studies with larger sample sizes and longer follow-up periods to examine any potential for deleterious effect with recurrent ketamine use for TRD. Trial Registration: ClinicalTrials.gov: NCT03156504.

Fine-mapping genomic loci refines bipolar disorder risk genes.

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 17 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, CRTC3, AP001453 . 3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, DPH1, GSDMB, MED24 and THRA in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of BD polygenic risk scores across diverse populations, and present a high-throughput fine-mapping pipeline ( https://github.com/mkoromina/SAFFARI ).

High Probability of Gene-Drug Interactions Associated with Medication Side Effects in Adolescent Depression: Results from a Randomized Controlled Trial of Pharmacogenetic Testing.

Introduction: Combinatorial pharmacogenetic testing panels are widely available in clinical practice and often separate medications into columns/bins associated with low, medium, or high probability of gene-drug interactions. The objective of the Adolescent Management of Depression (AMOD) study was to determine the clinical utility of combinatorial pharmacogenetic testing in a double-blind, randomized, controlled effectiveness study by comparing patients who had genetic testing results at time of medication initiation to those that did not have results until week 8. The objective of this post hoc analysis was to assess and report additional outcomes with respect to significant gene-drug interactions (i.e., a medication in the high probability gene-drug interaction bin as defined by a proprietary algorithm) compared with patients taking a medication with minimal to moderate gene-drug interactions (i.e., a medication from the low or medium probability gene-drug interaction bin, respectively). Methods: Adolescents 13-18 years (N = 170) with moderate to severe major depressive disorder received pharmacogenetic testing. Symptom improvement and side effects were assessed at baseline, week 4, week 8, and 6 months. Patients were grouped into three categories based on whether the medication they were prescribed was associated with low, medium, or high risk for gene-drug interactions. Patients taking a medication from the low/medium gene-drug interaction bin were compared with patients taking a medication from the high gene-drug interaction bin. Results: Patients taking a medication from the high gene-drug interaction bin were more likely to endorse side effects compared with patients taking a medication in the low/medium gene-drug interaction bin at week 8 (p = 0.001) and 6 months (p < 0.0001). Depressive symptom severity scores did not differ significantly across the medication bins. Conclusions: This study demonstrates the utility of gene-drug interaction testing to guide medication decisions to minimize side effect burden rather than solely prioritizing the search for the most efficacious medication. (Clinical Trials Registration Identifier: NCT02286440).

Identifying genetic differences between bipolar disorder and major depression through multiple GWAS.

Background: Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD). Aims: Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis. Methods: Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses. Results: While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD. Conclusions: We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.