Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients 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 BPD and, importantly, BPD-D from MDD.

This study assesses the feasibility of biomedical informatics resources for efficient recruitment of rural residents with cancer to a clinical trial of a quality-of-life (QOL) mobile app. These resources have the potential to reduce costly, time-consuming, in-person recruitment methods.

A cohort was identified from the electronic health record data repository and cross-referenced with patients who consented to additional research contact. Rural–urban commuting area codes were computed to identify rurality. Potential participants were emailed study details, screening questions, and an e-consent link via REDCap. Consented individuals received baseline questionnaires automatically. A sample minimum of n = 80 [n = 40 care as usual (CAU) n = 40 mobile app intervention] was needed.

N = 1298 potential participants (n = 365 CAU; n = 833 intervention) were screened for eligibility. For CAU, 68 consented, 67 completed baseline questionnaires, and 54 completed follow-up questionnaires. For intervention, 100 consented, 97 completed baseline questionnaires, and 58 completed follow-up questionnaires. The CAU/intervention reached 82.5%/122.5% of the enrollment target within 2 days. Recruitment and retention rates were 15.3% and 57.5%, respectively. The mean age was 59.5 ± 13.5 years. The sample was 65% women, 20% racial/ethnic minority, and 35% resided in rural areas.

These results demonstrate that biomedical informatics resources can be highly effective in recruiting for cancer QOL research. Precisely identifying individuals likely to meet inclusion criteria who previously indicated interest in research participation expedited recruitment. Participants completed the consent and baseline questionnaires with zero follow-up contacts from the research team. This low-touch, repeatable process may be highly effective for multisite clinical trials research seeking to include rural residents.

Aging is associated with disruptions in functional connectivity within the default mode (DMN), frontoparietal control (FPCN), and cingulo-opercular (CON) resting-state networks. Greater within-network connectivity predicts better cognitive performance in older adults. Therefore, strengthening network connectivity, through targeted intervention strategies, may help prevent age-related cognitive decline or progression to dementia. Small studies have demonstrated synergistic effects of combining transcranial direct current stimulation (tDCS) and cognitive training (CT) on strengthening network connectivity; however, this association has yet to be rigorously tested on a large scale. The current study leverages longitudinal data from the first-ever Phase III clinical trial for tDCS to examine the efficacy of an adjunctive tDCS and CT intervention on modulating network connectivity in older adults.

This sample included 209 older adults (mean age = 71.6) from the Augmenting Cognitive Training in Older Adults multisite trial. Participants completed 40 hours of CT over 12 weeks, which included 8 attention, processing speed, and working memory tasks. Participants were randomized into active or sham stimulation groups, and tDCS was administered during CT daily for two weeks then weekly for 10 weeks. For both stimulation groups, two electrodes in saline-soaked 5x7 cm2 sponges were placed at F3 (cathode) and F4 (anode) using the 10-20 measurement system. The active group received 2mA of current for 20 minutes. The sham group received 2mA for 30 seconds, then no current for the remaining 20 minutes.

Participants underwent resting-state fMRI at baseline and post-intervention. CONN toolbox was used to preprocess imaging data and conduct region of interest (ROI-ROI) connectivity analyses. The Artifact Detection Toolbox, using intermediate settings, identified outlier volumes. Two participants were excluded for having greater than 50% of volumes flagged as outliers. ROI-ROI analyses modeled the interaction between tDCS group (active versus sham) and occasion (baseline connectivity versus postintervention connectivity) for the DMN, FPCN, and CON controlling for age, sex, education, site, and adherence.

Compared to sham, the active group demonstrated ROI-ROI increases in functional connectivity within the DMN following intervention (left temporal to right temporal [T(202) = 2.78, pFDR < 0.05] and left temporal to right dorsal medial prefrontal cortex [T(202) = 2.74, pFDR < 0.05]. In contrast, compared to sham, the active group demonstrated ROI-ROI decreases in functional connectivity within the FPCN following intervention (left dorsal prefrontal cortex to left temporal [T(202) = -2.96, pFDR < 0.05] and left dorsal prefrontal cortex to left lateral prefrontal cortex [T(202) = -2.77, pFDR < 0.05]). There were no significant interactions detected for CON regions.

These findings (a) demonstrate the feasibility of modulating network connectivity using tDCS and CT and (b) provide important information regarding the pattern of connectivity changes occurring at these intervention parameters in older adults. Importantly, the active stimulation group showed increases in connectivity within the DMN (a network particularly vulnerable to aging and implicated in Alzheimer’s disease) but decreases in connectivity between left frontal and temporal FPCN regions. Future analyses from this trial will evaluate the association between these changes in connectivity and cognitive performance post-intervention and at a one-year timepoint.

Anterior temporal lobectomy is a common surgical approach for medication-resistant temporal lobe epilepsy (TLE). Prior studies have shown inconsistent findings regarding the utility of presurgical intracarotid sodium amobarbital testing (IAT; also known as Wada test) and neuroimaging in predicting postoperative seizure control. In the present study, we evaluated the predictive utility of IAT, as well as structural magnetic resonance imaging (MRI) and positron emission tomography (PET), on long-term (3-years) seizure outcome following surgery for TLE.

Patients consisted of 107 adults (mean age=38.6, SD=12.2; mean education=13.3 years, SD=2.0; female=47.7%; White=100%) with TLE (mean epilepsy duration =23.0 years, SD=15.7; left TLE surgery=50.5%). We examined whether demographic, clinical (side of resection, resection type [selective vs. non-selective], hemisphere of language dominance, epilepsy duration), and presurgical studies (normal vs. abnormal MRI, normal vs. abnormal PET, correctly lateralizing vs. incorrectly lateralizing IAT) were associated with absolute (cross-sectional) seizure outcome (i.e., freedom vs. recurrence) with a series of chi-squared and t-tests. Additionally, we determined whether presurgical evaluations predicted time to seizure recurrence (longitudinal outcome) over a three-year period with univariate Cox regression models, and we compared survival curves with Mantel-Cox (log rank) tests.

Demographic and clinical variables (including type [selective vs. whole lobectomy] and side of resection) were not associated with seizure outcome. No associations were found among the presurgical variables. Presurgical MRI was not associated with cross-sectional (OR=1.5, p=.557, 95% CI=0.4-5.7) or longitudinal (HR=1.2, p=.641, 95% CI=0.4-3.9) seizure outcome. Normal PET scan (OR= 4.8, p=.045, 95% CI=1.0-24.3) and IAT incorrectly lateralizing to seizure focus (OR=3.9, p=.018, 95% CI=1.2-12.9) were associated with higher odds of seizure recurrence. Furthermore, normal PET scan (HR=3.6, p=.028, 95% CI =1.0-13.5) and incorrectly lateralized IAT (HR= 2.8, p=.012, 95% CI=1.2-7.0) were presurgical predictors of earlier seizure recurrence within three years of TLE surgery. Log rank tests indicated that survival functions were significantly different between patients with normal vs. abnormal PET and incorrectly vs. correctly lateralizing IAT such that these had seizure relapse five and seven months earlier on average (respectively).

Presurgical normal PET scan and incorrectly lateralizing IAT were associated with increased risk of post-surgical seizure recurrence and shorter time-to-seizure relapse.

Olfaction is a critical sensory function and changes in the ability to detect smells could affect quality of life by diminishing appreciation of food, drink, and other aroma-based experiences, increase danger of hazardous exposures, and cause a loss of employment. Additionally, decrements in olfaction have been related to onset of some neurodegenerative conditions. Olfactory impairments in military populations are highly prevalent and often attributed to the long-term effects of mild traumatic brain injury (mTBI) and chronic psychiatric disorders. The main goal of this investigation was to examine olfactory function in a cohort of combat veterans using a quantitative smell test.

Participants underwent a neurological examination using a revised version of the Neurological Outcome Scale for Traumatic Brain Injury. Olfactory function was examined using a set of essential oil vials with common odors. Based on the number of correctly identified odors, the following grading system was employed: no deficit; mild; moderate; severe deficit; and absence of smell detection. All study assessments were performed prior to March of 2020 (onset of COVID-19 pandemic). In addition, participants completed performance validity testing (PVT) and screening for ongoing substance misuse using the Alcohol Use Disorders Identification Test and Drug Abuse Screening Test-10. Lifetime history of brain injury, combat-related extracranial injuries, and deployment characteristics were assessed using structured interview. All available medical records were reviewed.

Participants were 38 veterans with a deployment-related mTBI who passed the PVT and did not have ongoing substance misuse issues. Olfactory examination revealed normosmia in 20 participants and various degrees of deficit in 18 (11= mild; 4=moderate; and 3=severe). The groups did not differ in demographics, post-injury interval, or current clinical (non-psychiatric) conditions. Participants with hyposmia frequently reported being exposed to a higher number of blasts and being positioned closer to the nearest primary blast, and more often endorsed a period of loss of consciousness after the most serious mTBI. In addition, they more often reported tympanic membrane perforation, extracranial injuries, and histories of both blast and blunt force mTBI. Comorbid diagnoses of posttraumatic stress disorder (PTSD), depression, chronic headaches, and pain were more common among these participants as well.

Several blast exposure and specific injury-related characteristics increase the likelihood of long-term olfactory impairments, comorbid psychiatric conditions, and chronic pain among veterans with a history of deployment-related mTBI. Notably, none of the participants with hyposmia had a clinical diagnosis of olfactory dysfunction or were receiving service-connected disability for a loss of sense of smell at the time of their assessment. Multidisciplinary rehabilitation care provided to combat veterans with history of mTBI and/or PTSD should include olfactory examination using both quantitative and qualitative smell tests, education regarding the adversities related to loss of smell, management of current psychiatric symptoms, and follow-up assessments. The lack of a comparison group without a history of mTBI and the small sample size were the main limitations of this investigation.

Nonpathological aging has been linked to decline in both verbal and visuospatial memory abilities in older adults. Disruptions in resting-state functional connectivity within well-characterized, higherorder cognitive brain networks have also been coupled with poorer memory functioning in healthy older adults and in older adults with dementia. However, there is a paucity of research on the association between higherorder functional connectivity and verbal and visuospatial memory performance in the older adult population. The current study examines the association between resting-state functional connectivity within the cingulo-opercular network (CON), frontoparietal control network (FPCN), and default mode network (DMN) and verbal and visuospatial learning and memory in a large sample of healthy older adults. We hypothesized that greater within-network CON and FPCN functional connectivity would be associated with better immediate verbal and visuospatial memory recall. Additionally, we predicted that within-network DMN functional connectivity would be associated with improvements in delayed verbal and visuospatial memory recall. This study helps to glean insight into whether within-network CON, FPCN, or DMN functional connectivity is associated with verbal and visuospatial memory abilities in later life.

330 healthy older adults between 65 and 89 years old (mean age = 71.6 ± 5.2) were recruited at the University of Florida (n = 222) and the University of Arizona (n = 108). Participants underwent resting-state fMRI and completed verbal memory (Hopkins Verbal Learning Test - Revised [HVLT-R]) and visuospatial memory (Brief Visuospatial Memory Test - Revised [BVMT-R]) measures. Immediate (total) and delayed recall scores on the HVLT-R and BVMT-R were calculated using each test manual’s scoring criteria. Learning ratios on the HVLT-R and BVMT-R were quantified by dividing the number of stimuli (verbal or visuospatial) learned between the first and third trials by the number of stimuli not recalled after the first learning trial. CONN Toolbox was used to extract average within-network connectivity values for CON, FPCN, and DMN. Hierarchical regressions were conducted, controlling for sex, race, ethnicity, years of education, number of invalid scans, and scanner site.

Greater CON connectivity was significantly associated with better HVLT-R immediate (total) recall (ß = 0.16, p = 0.01), HVLT-R learning ratio (ß = 0.16, p = 0.01), BVMT-R immediate (total) recall (ß = 0.14, p = 0.02), and BVMT-R delayed recall performance (ß = 0.15, p = 0.01). Greater FPCN connectivity was associated with better BVMT-R learning ratio (ß = 0.13, p = 0.04). HVLT-R delayed recall performance was not associated with connectivity in any network, and DMN connectivity was not significantly related to any measure.

Connectivity within CON demonstrated a robust relationship with different components of memory function as well across verbal and visuospatial domains. In contrast, FPCN only evidenced a relationship with visuospatial learning, and DMN was not significantly associated with memory measures. These data suggest that CON may be a valuable target in longitudinal studies of age-related memory changes, but also a possible target in future non-invasive interventions to attenuate memory decline in older adults.

Our objective was to evaluate the psychometric properties of the culturally adapted NIH Toolbox African Languages® when used in Swahili and Dholuo-speaking children in western Kenya.

Swahili-speaking participants were recruited from Eldoret and Dholuo-speaking participants from Ajigo; all were <14 years of age and enrolled in primary school. Participants completed a demographics questionnaire and five fluid cognition tests of the NIH Toolbox® African Languages program, including Flanker, Dimensional Change Card Sort (DCCS), Picture Sequence Memory, Pattern Comparison, and List Sorting tests. Statistical analyses examined aspects of reliability, including internal consistency (in both languages) and test–retest reliability (in Dholuo only).

Participants included 479 children (n = 239, Swahili-speaking; n = 240, Dholuo-speaking). Generally, the tests had acceptable psychometric properties for research use within Swahili- and Dholuo-speaking populations (mean age = 10.5; SD = 2.3). Issues related to shape identification and accuracy over speed limited the utility of DCCS for many participants, with approximately 25% of children unable to match based on shape. These cultural differences affected outcomes of reliability testing among the Dholuo-speaking cohort, where accuracy improved across all five tests, including speed.

There is preliminary evidence that the NIH Toolbox ® African Languages potentially offers a valid assessment of development and performance using tests of fluid cognition in Swahili and Dholuo among research settings. With piloting underway across other diverse settings, future research should gather additional evidence on the clinical utility and acceptability of these tests, specifically through the establishment of norming data among Kenyan regions and evaluating these psychometric properties.

Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.

One hundred and twenty-six persons aged 18–85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.

Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.

Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.