Ion transport in polymerized ionic liquids: a comparison of polycation and polyanion systems.

The correlation among chemical structure, mesoscale structure, and ion transport in 1,2,3-triazole-based polymerized ionic liquids (polyILs) featuring comparable polycation and polyanion backbones is investigated by wide-angle X-ray scattering (WAXS), differential scanning calorimetry, and broadband dielectric spectroscopy (BDS). Above the glass transition temperature, Tg, higher ionic conductivity is observed in polycation polyILs compared to their polyanion counterparts, and ion conduction is enhanced by increasing the counterion volume in both polycation or polyanion polyILs. Below Tg, polyanions show lower activation energy associated with ion conduction. However, the validity of the Barton-Nakajima-Namikawa relation indicates that hopping conduction is the dominant charge transport mechanism in all the polyILs studied. While a significant transition from a Vogel-Fulcher-Tammann to Arrhenius type of thermal activation is observed below Tg, the decoupling index, often used to quantify the extent to which segmental dynamics and ion conduction are correlated, remains unaltered for the polyILs studied, suggesting that this index may not be a general parameter to characterize charge transport in polymerized ionic liquids. Furthermore, detailed analyses of the WAXS results indicate that both the mobile ion type and the structure of the pendant groups control mesoscale organization. These findings are discussed within the framework of recent models, which account for the subtle interplay between electrostatic and elastic forces in determining ion transport in polyILs. The findings demonstrate the intricate balance between the chemical structure and interactions in polyILs that determine ion conduction in this class of polymer electrolytes.

High Throughput Characterization of Organic Thin Film Transistors.

Automation is vital to accelerating research. In recent years, the application of self-driving labs to materials discovery and device optimization has highlighted many benefits and challenges inherent to these new technologies. Successful automated workflows offer tangible benefits to fundamental science and industrial scale-up by significantly increasing productivity and reproducibility all while enabling entirely new types of experiments. However, it's implemtation is often time-consuming and cost-prohibitive and necessitates establishing multidisciplinary teams that bring together domain-specific knowledge with specific skillsets in computer science and engineering. This perspective article provides a comprehensive overview of how the research group has adopted "hybrid automation" over the last 8 years by using simple automatic electrical testers (autotesters) as a tool to increase productivity and enhance reproducibility in organic thin film transistor (OTFT) research. From wearable and stretchable electronics to next-generation sensors and displays, OTFTs have the potential to be a key technology that will enable new applications from health to aerospace. The combination of materials chemistry, device manufacturing, thin film characterization and electrical engineering makes OTFT research challenging due to the large parameter space created by both diverse material roles and device architectures. Consequently, this research stands to benefit enormously from automation. By leveraging the multidisciplinary team and taking a user-centered design approach in the design and continued improvement of the autotesters, the group has meaningfully increased productivity, explored research avenues impossible with traditional workflows, and developed as scientists and engineers capable of effectively designing and leveraging automation to build the future of their fields to encourage this approach, the files for replicating the infrastructure are included, and questions and potential collaborations are welcomed.

Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry?

Some models for mental disorders or behaviors (eg, suicide) have been successfully developed, allowing predictions at the population level. However, current demographic and clinical variables are neither sensitive nor specific enough for making individual actionable clinical predictions. A major hope of the "Decade of the Brain" was that biological measures (biomarkers) would solve these issues and lead to precision psychiatry. However, as models are based on sociodemographic and clinical data, even when these biomarkers differ significantly between groups of patients and control participants, they are still neither sensitive nor specific enough to be applied to individual patients. Technological advances over the past decade offer a promising approach based on new measures that may be essential for understanding mental disorders and predicting their trajectories. Several new tools allow us to continuously monitor objective behavioral measures (eg, hours of sleep) and densely sample subjective measures (eg, mood). The promise of this approach, referred to as digital phenotyping, was recognized almost a decade ago, with its potential impact on psychiatry being compared to the impact of the microscope on biological sciences. However, despite the intuitive belief that collecting densely sampled data (big data) improves clinical outcomes, recent clinical trials have not shown that incorporating digital phenotyping improves clinical outcomes. This viewpoint provides a stepwise development and implementation approach, similar to the one that has been successful in the prediction and prevention of cardiovascular disease, to achieve clinically actionable predictions in psychiatry.

Cognitive Profiles in Treatment-Resistant Late-Life Depression and their Impact on Treatment Outcomes.

BACKGROUND: Late-life depression (LLD) is associated with cognitive impairment, yet substantial heterogeneity exists among patients. Data on the extent of cognitive impairments is inconclusive, particularly in patients with treatment-resistant depression (TRD). We investigated the cognitive profiles of patients with treatment-resistant vs. nonresistant LLD and aimed to identify distinct cognitive subgroups. Additionally, we examined whether cognitive subgroups differentially responded to treatment with bilateral repetitive transcranial magnetic stimulation (rTMS). METHODS: 165 patients with LLD were divided into treatment-resistant and nonresistant groups and compared to healthy controls (HC) on measures of executive function, information processing speed, verbal learning, and memory. Cluster analysis identified subgroups based on cognitive scores. Demographic and clinical variables, as well as outcomes with bilateral rTMS, were compared between cognitive subgroups. RESULTS: Patients with LLD, particularly TRD, exhibited significantly worse cognitive performance than HC. A three-cluster solution was found, including "Cognitively Intact" (n = 89), "Cognitively Diminished" (n = 29), and "Impaired Memory" (n = 47) subgroups. Both the "Cognitively Diminished" and "Impaired Memory" subgroups had more anxiety symptoms and a higher proportion of patients with TRD than the "Cognitively Intact" group, though the latter did not survive multiple comparison correction. No significant differences were observed in outcomes to rTMS treatment. CONCLUSIONS: Patients with LLD exhibited impairments across cognitive domains, which were more pronounced in TRD. Three identified cognitive subgroups responded similarly to rTMS treatment, indicating its effectiveness across cognitive profiles, especially when medications are not tolerated. Future research should examine the relationship among cognitive subgroups, cognitive decline, and neurodegeneration.

Alcohol and substance use in older adults with treatment-resistant depression.

INTRODUCTION: Alcohol and substance use are increasing in older adults, many of whom have depression, and treatment in this context may be more hazardous. We assessed alcohol and other substance use patterns in older adults with treatment-resistant depression (TRD). We examined patient characteristics associated with higher alcohol consumption and examined the moderating effect of alcohol on the association between clinical variables and falls during antidepressant treatment. METHODS: This secondary and exploratory analysis used baseline clinical data and data on falls during treatment from a large randomized antidepressant trial in older adults with TRD (the OPTIMUM trial). Multivariable ordinal logistic regression was used to identify variables associated with higher alcohol use. An interaction model was used to evaluate the moderating effect of alcohol on falls during treatment. RESULTS: Of 687 participants, 51% acknowledged using alcohol: 10% were hazardous drinkers (AUDIT-10 score ≥5) and 41% were low-risk drinkers (score 1-4). Benzodiazepine use was seen in 24% of all participants and in 21% of drinkers. Use of other substances (mostly cannabis) was associated with alcohol consumption: it was seen in 5%, 9%, and 15% of abstainers, low-risk drinkers, and hazardous drinkers, respectively. Unexpectedly, use of other substances predicted increased risk of falls during antidepressant treatment only in abstainers. CONCLUSIONS: One-half of older adults with TRD in this study acknowledged using alcohol. Use of alcohol concurrent with benzodiazepine and other substances was common. Risks-such as falls-of using alcohol and other substances during antidepressant treatment needs further study.

Neurophysiological and other features of working memory in older adults at risk for dementia.

Theta-gamma coupling (TGC) is a neurophysiological process that supports working memory. Working memory is associated with other clinical and biological features. The extent to which TGC is associated with these other features and whether it contributes to working memory beyond these features is unknown. Two-hundred-and-three older participants at risk for Alzheimer's dementia-98 with mild cognitive impairment (MCI), 39 with major depressive disorder (MDD) in remission, and 66 with MCI and MDD (MCI + MDD)-completed a clinical assessment, N-back-EEG, and brain MRI. Among them, 190 completed genetic testing, and 121 completed [11C] Pittsburgh Compound B ([11C] PIB) PET imaging. Hierarchical linear regressions were used to assess whether TGC is associated with demographic and clinical variables; Alzheimer's disease-related features (APOE ε4 carrier status and ß-amyloid load); and structural features related to working memory. Then, linear regressions were used to assess whether TGC is associated with 2-back performance after accounting for these features. Other than age, TGC was not associated with any non-neurophysiological features. In contrast, TGC (ß = 0.27; p = 0.006), age (ß = - 0.29; p = 0.012), and parietal cortical thickness (ß = 0.24; p = 0.020) were associated with 2-back performance. We also examined two other EEG features that are linked to working memory-theta event-related synchronization and alpha event-related desynchronization-and found them not to be associated with any feature or performance after accounting for TGC. Our findings suggest that TGC is a process that is independent of other clinical, genetic, neurochemical, and structural variables, and supports working memory in older adults at risk for dementia. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09938-y.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression.

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Relationship between Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) total scores in older adults with major depressive disorder: An analysis of the OPTIMUM clinical trial.

BACKGROUND: The Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) are commonly used scales to measure depression severity in older adults. METHODS: We utilized data from the Optimizing Outcomes of Treatment-Resistant Depression in Older Adults (OPTIMUM) clinical trial to produce conversion tables relating PHQ-9 and MADRS total scores. We split the sample into training (N = 555) and validation samples (N = 187). Equipercentile linking was performed on the training sample to produce conversion tables for PHQ-9 and MADRS. We compared the original and estimated scores in the validation sample with Bland-Altman analysis. We compared the depression severity level using the original and estimated scores with Chi-square tests. RESULTS: The Bland-Altman analysis confirmed that differences between the original and estimated scores for at least 95 % of the sample fit within 1.96 standard deviations of the mean difference. Chi-square tests showed a significant difference in the proportion of participants at each depression severity category determined using the original and estimated scores. LIMITATIONS: The conversion tables should be used with caution when comparing depression severity at the individual level. CONCLUSIONS: Our conversion tables relating PHQ-9 and MADRS scores can be used to compare treatment outcomes using aggregate data in studies that only used one of these scales.

Water-Soluble Reversible Photo-Cross-Linking Polymer Dielectrics.

Effective recycling of mixed materials requires the separation of the different components without the need for toxic solvents. One approach involves utilizing a water-soluble coating with reversible photo-cross-linkers, making it robust until end of life where it can then be dissolved in water after de-cross-linking. Here, a novel coumarin methacrylate monomer and its nitroxide-mediated copolymerization to create poly((methacrylic acid)-co-(styrene sulfonate)-co-(coumarin methacrylate)) for water-soluble thin films are reported. Under exposure to light, the coumarin functional groups produce reversible [2+2] cycloadditions which cross-link the resulting polymer films, making them no longer water soluble. Characterization of reversible cross-linking behavior is reported through changes in contact angle and in situ rheological characterization. The resulting polymers are successfully integrated into metal-insulator-metal capacitors, demonstrating the potential use for water-soluble reversible photo-cross-linkable dielectric materials for organic electronics.

Not missing at random: Missing data are associated with clinical status and trajectories in an electronic monitoring longitudinal study of bipolar disorder.

There is limited information on the association between participants' clinical status or trajectories and missing data in electronic monitoring studies of bipolar disorder (BD). We collected self-ratings scales and sensor data in 145 adults with BD. Using a new metric, Missing Data Ratio (MDR), we assessed missing self-rating data and sensor data monitoring activity and sleep. Missing data were lowest for participants in the midst of a depressive episode, intermediate for participants with subsyndromal symptoms, and highest for participants who were euthymic. Over a mean ± SD follow-up of 246 ± 181 days, missing data remained unchanged for participants whose clinical status did not change throughout the study (i.e., those who entered the study in a depressive episode and did not improve, or those who entered the study euthymic and remained euthymic). Conversely, when participants' clinical status changed during the study (e.g., those who entered the study euthymic and experienced the occurrence of a depressive episode), missing data for self-rating scales increased, but not for sensor data. Overall missing data were associated with participants' clinical status and its changes, suggesting that these are not missing at random.

A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.

Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic or hypomanic episodes, and depressive episodes. While motor abnormalities are commonly seen during depressive or manic episodes, not much attention has been paid to postural abnormalities during periods of euthymia and their association with illness burden. We collected 24-hour posture data in 32 euthymic participants diagnosed with BD using a shirt-based wearable. We extracted a set of nine time-domain features, and performed unsupervised participant clustering. We investigated the association between posture variables and 12 clinical characteristics of illness burden. Based on their postural dynamics during the daytime, evening, or nighttime, participants clustered in three clusters. Higher illness burden was associated with lower postural variability, in particular during daytime. Participants who exhibited a mostly upright sitting/standing posture during the night with frequent nighttime postural transitions had the highest number of lifetime depressive episodes. Euthymic participants with BD exhibit postural abnormalities that are associated with illness burden, especially with the number of depressive episodes. Our results contribute to understanding the role of illness burden on posture changes and sleep consolidation in periods of euthymia.

Elevated senescence-associated secretory phenotype index in late-life bipolar disorder.

BACKGROUND: The senescence-associated secretory phenotype (SASP) is a biomarker index based on the profile of 22 blood proteins associated with cellular senescence. The SASP index has not been assessed in older patients with bipolar disorder (BD). We hypothesized that older adults with BD will have elevated cellular senescence burden as measured by the SASP index. METHODS: We measured the 22 SASP proteins to calculate the SASP index in 38 older patients with BD and 34 non-psychiatric comparison individuals (HC). RESULTS: The SASP index scores were significantly higher in BD than HC after controlling for age, sex, psychopathology, and physical health (F(1,8) = 5.37, p = 0.024, η2 = 0.08). SASP index scores were also associated with higher age, more severe depressive symptoms, and physical illness burden (p < 0.05) in the whole sample. LIMITATION: Cross-sectional study and small sample size. CONCLUSION: This is the first report of increased SASP index scores in older adults with BD. Our results suggest that dysregulation of age-related biological processes may contribute to more severe depressive symptoms and worse physical health in older adults with BD.

Axial Phenoxylation of Aluminum Phthalocyanines for Improved Cannabinoid Sensitivity in OTFT Sensors.

Cannabis producers, consumers, and regulators need fast, accurate, point-of-use sensors to detect Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) from both liquid and vapor source samples, and phthalocyanine-based organic thin-film transistors (OTFTs) provide a cost-effective solution. Chloro aluminum phthalocyanine (Cl-AlPc) has emerged as a promising material due to its unique coordinating interactions with cannabinoids, allowing for superior sensitivity. This work explores the molecular engineering of AlPc to tune and enhance these interactions, where a series of novel phenxoylated R-AlPcs are synthesized and integrated into OTFTs, which are then exposed to THC and CBD solution and vapor samples. While the R-AlPc substituted molecules have a comparable baseline device performance to Cl-AlPc, their new crystal structures and weakened intermolecular interactions increase sensitivity to THC. Grazing-incidence wide-angle X-ray scattering (GIWAXS) and atomic force microscopy (AFM) are used to investigate this film restructuring, where a significant shift in the crystal structure, grain size, and film roughness is detected for the R-AlPc molecules that do not occur with Cl-AlPc. This significant crystal reorganization and film restructuring are the driving force behind the improved sensitivity to cannabinoids relative to Cl-AlPc and demonstrate that analyte-semiconductor interactions can be enhanced through chemical modification to create more responsive OTFT sensors.

Prescribed psychostimulants and other pro-cognitive medications in bipolar disorder: A systematic review and meta-analysis of recurrence of manic symptoms.

OBJECTIVES: Clinicians are often hesitant to prescribe psychostimulants in bipolar disorder (BD) due to concerns of inducing (hypo)mania, despite limited published evidence on associations between prescribed psychostimulant use and recurrence of mood episodes in BD. The current systematic review and meta-analysis evaluated the emergence of (hypo)manic symptoms in patients with BD receiving prescribed psychostimulants or other pro-cognitive medications in euthymic or depressive states. METHODS: A systematic search was performed of MEDLINE, Embase, and PsychINFO from inception to April 5, 2023 and search of Clinicaltrials.gov and Clinicaltrialsregister.eu for unpublished data. References of included studies were hand-searched. Randomized trials and prospective longitudinal studies that evaluated psychostimulants and non-stimulant medications recommended for the treatment of ADHD by the Canadian ADHD practice guidelines were included. The review was reported in line with PRISMA guidelines and was preregistered on PROSPERO (CRD42022358588). RESULTS: After screening 414 unique records, we included 27 studies, of which five reported data that was quantitatively synthesized (n = 1653). The use of psychostimulants in BD was not associated with increased scores on the Young Mania Rating Scale in patients who were in a euthymic or depressed state (SMD IV -0.17; 95% CI, -0.40 to 0.06) compared to placebo. There was a high degree of study-level heterogeneity (I2 = 80%). A qualitative synthesis of studies revealed a limited risk of medication-induced manic symptoms. CONCLUSIONS: Our review provides preliminary evidence to suggest psychostimulants and non-stimulant ADHD medications have a limited risk of precipitating (hypo)mania symptoms. More extensive studies evaluating the safety and efficacy of these medications are warranted.

An experimental paradigm for triggering a depressive syndrome.

Research investigating whether depression is an adaptation or a disorder has been hindered by the lack of an experimental paradigm that can test causal relationships. Moreover, studies attempting to induce the syndrome often fail to capture the suite of feelings, thoughts, and behaviors that characterize depression. An experimental paradigm for triggering depressive symptoms can improve our etiological understanding of the syndrome. The present study attempts to induce core symptoms of depression, particularly those related to rumination, in a healthy, nonclinical sample through a controlled social experiment. These symptoms are sad or depressed mood, anhedonia, feelings of worthlessness or guilt, and difficulty concentrating. One hundred and thirty-four undergraduate students were randomly assigned to either an exclusion (E) or control (C) group. Participants in the exclusion group were exposed to a modified Cyberball paradigm, designed to make them feel socially excluded, followed by a dual-interference task to assess whether their exclusion interfered with their working memory. Excluded participants: (a) self-reported a significant increase in sadness and decrease in happiness, but not anxiety or calmness; (b) scored significantly higher in four of five variables related to depressive rumination; and (c) performed significantly worse on a dual-interference task, suggesting an impaired ability to concentrate. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effect of olanzapine exposure on relapse and brain structure in patients with major depressive disorder with psychotic features.

Some data suggest that antipsychotics may adversely affect brain structure. We examined the relationship among olanzapine exposure, relapse, and changes in brain structure in patients with major depressive disorder with psychotic features. We analyzed data from the Study of the Pharmacotherapy of Psychotic Depression II trial (STOP-PD II), a randomized, placebo-controlled trial in patients with psychotic depression who attained remission on sertraline and olanzapine and were randomized to continue sertraline plus olanzapine or placebo for 36 weeks. Olanzapine steady state concentration (SSC) were calculated based on sparsely-sampled levels. Rates of relapse and changes in brain structure were assessed as outcomes. There were significant associations between dosage and relapse rates (N = 118; HR = 0.94, 95% CI [0.897, 0.977], p = 0.002) or changes in left cortical thickness (N = 44; B = -2.0 × 10-3, 95% CI [-3.1 × 10-3, -9.6 × 10-4], p < 0.001) and between SSC and changes in left cortical thickness (N = 44; B = -8.7 × 10-4, 95% CI [-1.4 × 10-3, -3.6 × 10-4], p = 0.001). Similar results were found for the right cortex. These associations were no longer significant when the analysis was restricted to participants treated with olanzapine. Our findings suggest that, within its therapeutic range, the effect of olanzapine on relapse or cortical thickness does not depend on its dosage or SSC. Further research is needed on the effect of olanzapine and other antipsychotics on mood symptoms and brain structure.

Cognitive function based on theta-gamma coupling vs. clinical diagnosis in older adults with mild cognitive impairment with or without major depressive disorder.

Whether individuals with mild cognitive impairment (MCI) and a history of major depressive disorder (MDD) are at a higher risk for cognitive decline than those with MCI alone is still not clear. Previous work suggests that a reduction in prefrontal cortical theta phase-gamma amplitude coupling (TGC) is an early marker of cognitive impairment. This study aimed to determine whether using a TGC cutoff is better at separating individuals with MCI or MCI with remitted MDD (MCI+rMDD) on cognitive performance than their clinical diagnosis. Our hypothesis was that global cognition would differ more between TGC-based groups than diagnostic groups. We analyzed data from 128 MCI (mean age: 71.8, SD: 7.3) and 85 MCI+rMDD (mean age: 70.9, SD: 4.7) participants. Participants completed a comprehensive neuropsychological battery; TGC was measured during the N-back task. An optimal TGC cutoff was determined during the performance of the 2-back. This TGC cutoff was used to classify participants into low vs. high-TGC groups. We then compared Cohen's d of the difference in global cognition between the high and low TGC groups to Cohen's d between the MCI and MCI+rMDD groups. We used bootstrapping to determine 95% confidence intervals for Cohen's d values using the whole sample. As hypothesized, Cohen's d for the difference in global cognition between the TGC groups was larger (0.64 [0.32, 0.88]) than between the diagnostic groups (0.10 [0.004, 0.37]) with a difference between these two Cohen's d's of 0.54 [0.10, 0.80]. Our findings suggest that TGC is a useful marker to identify individuals at high risk for cognitive decline, beyond clinical diagnosis. This could be due to TGC being a sensitive marker of prefrontal cortical dysfunction that would lead to an accelerated cognitive decline.

Predictors of remission after repetitive transcranial magnetic stimulation for the treatment of late-life depression.

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment in patients with depression, yet treatment response remains variable. While previous work has identified predictors of remission in younger adults, relatively little data exists in late-life depression (LLD). To address this gap, data from 164 participants with LLD from a randomized non-inferiority treatment trial comparing standard bilateral rTMS to bilateral theta burst stimulation (TBS) (ClinicalTrials.gov identifier: NCT02998580) were analyzed using binary logistic regression and conditional inference tree (CIT) modeling. Lower baseline depression symptom severity, fewer prior antidepressant treatment failures, and higher global cognition predicted remission following rTMS treatment. The CIT predicted a higher likelihood of achieving remission for patients with a total score of 19 or lower on the Montgomery-Åsberg Depression Rating Scale, 1 or fewer prior antidepressant treatment failures, and a total score of 23 or higher on the Montreal Cognitive Assessment. Our results indicate that older adults with lower severity of depression, fewer antidepressant treatment failures, and higher global cognition benefit more from current forms of rTMS. The results suggest that there is potentially higher value in using rTMS earlier in the treatment pathway for depression in older adults.

Cognition in older age bipolar disorder: An analysis of archival data across the globe.

BACKGROUND: Cognitive deficits in bipolar disorder (BD) impact functioning and are main contributors to disability in older age BD (OABD). We investigated the difference between OABD and age-comparable healthy comparison (HC) participants and, among those with BD, the associations between age, global cognitive performance, symptom severity and functioning using a large, cross-sectional, archival dataset harmonized from 7 international OABD studies. METHODS: Data from the Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) database, spanning various standardized measures of cognition, functioning and clinical characteristics, were analyzed. The sample included 662 euthymic to mildly symptomatic participants aged minimum 50years (509 BD, 153 HC), able to undergo extensive cognitive testing. Linear mixed models estimated associations between diagnosis and global cognitive performance (g-score, harmonized across studies), and within OABD between g-score and severity of mania and depressive symptoms, duration of illness and lithium use and of global functioning. RESULTS: After adjustment for study cohort, age, gender and employment status, there was no significant difference in g-score between OABD and HC, while a significant interaction emerged between employment status and diagnostic group (better global cognition associated with working) in BD. Within OABD, better g-scores were associated with fewer manic symptoms, higher education and better functioning. LIMITATIONS: Cross-sectional design and loss of granularity due to harmonization. CONCLUSION: More research is needed to understand heterogenous longitudinal patterns of cognitive change in BD and understand whether particular cognitive domains might be affected in OABD in order to develop new therapeutic efforts for cognitive dysfunction OABD.

Heterogeneity of Cognition in Older Adults with Remitted Major Depressive Disorder: A Latent Profile Analysis.

OBJECTIVES: To identify data-driven cognitive profiles in older adults with remitted major depressive disorder (rMDD) with or without mild cognitive impairment (MCI) and examine how the profiles differ regarding demographic, clinical, and neuroimaging measures. DESIGN: Secondary cross-sectional analysis using latent profile analysis. SETTING: Multisite clinical trial in Toronto, Canada. PARTICIPANTS: One hundred seventy-eight participants who met DSM-5 criteria for rMDD without MCI (rMDD-MCI; n = 60) or with MCI (rMDD + MCI; n = 118). MEASUREMENTS: Demographic, clinical, neuroimaging measures, and domain scores from a neuropsychological battery assessing verbal memory, visuospatial memory, processing speed, working memory, language, and executive function. RESULTS: We identified three latent profiles: Profile 1 (poor cognition; n = 75, 42.1%), Profile 2 (intermediate cognition; n = 75, 42.1%), and Profile 3 (normal cognition; n = 28, 15.7%). Compared to participants with Profile 3, those with Profile 1 or 2 were older, had lower education, experienced a greater burden of medical comorbidities, and were more likely to have MCI. The profiles did not differ on the severity of residual symptoms, age of onset of rMDD, number of depressive episodes, psychotropic medication, cerebrovascular risk, ApoE4 carrier status, or family history of depression, dementia, or Alzheimer's disease. The profiles differed in cortical thickness of 15 regions, with the most prominent effects for left precentral and pars opercularis, and right inferior parietal and supramarginal. CONCLUSION: Older patients with rMDD can be grouped cross-sectionally based on data-driven cognitive profiles that differ from the absence or presence of a diagnosis of MCI. Future research should determine the differential risk for dementia of these data-driven subgroups.