Subjective cognitive complaints (SCC) can precede cognitive decline and are associated with demographic, exposure, lifestyle, and psychological factors. Prevalences of SCC and their correlates in individuals with repetitive head impacts (RHI) are poorly understood. This study characterized SCC in former elite American football players by frequency, mood and behavioral correlates, concordance with informant reports, and associations with neuropsychological test performance, cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI) markers of neurodegeneration.

Former American football players (n = 180) completed measures of global and domain-specific SCC, neuropsychiatric symptom questionnaires, neuropsychological testing, lumbar puncture, and MRI. Elastic net regression evaluated the relative importance of potential SCC correlates. Intraclass correlation coefficients measured concordance between self and informant reports. Multiple linear regressions tested associations between SCC and verbal memory and executive functioning scores. CSF Aβ1-42, p-tau181, t-tau, neurofilament light (NfL), hippocampal volume, and regional cortical thickness were examined for their potential associations with SCC.

Rates of SCC ranged from 43 to 77% depending on the domain. Symptoms of depression, impulsivity, and anxiety were strongly associated with SCC. Self- and informant-reported SCC showed moderate inter-rater agreement. Adjusting for age, race, education, APOE ϵ4 carrier status, and depressive symptoms, SCC were associated with lower objective verbal memory and executive functioning performance. SCC were associated with lower parahippocampal cortical thickness but not with hippocampal volume or any of the measured CSF tests.

SCC are strongly associated with neuropsychiatric factors in former American football players. SCC may also be a marker of cognitive decline and neurodegeneration.

Distinguishing viral versus bacterial lower respiratory tract infection (LRTI) is challenging. We previously developed a rapid, host response-based test (Biomeme HR-B/V assay) using peripheral blood samples to identify viral versus bacterial infection. We assessed the performance of this assay when using nasopharyngeal (NP) samples.

Patients with LRTI were enrolled, and a NP swab sample was run using the HR-B/V assay (assessing 24 gene targets) on the FranklinTM platform. The performance of the prior classifier at identifying viral versus bacterial infection was assessed. A novel predictive model was generated for NP samples using the same 24 targets. Results were validated using external datasets with nasal/NP RNA sequence data.

Nineteen patients (median age 62 years, 52.1% male) were included. When using the prior HR-B/V classifier on NP samples of 19 patients with LRTI (12 viral, 7 bacterial), the area under the receiver operator curve (AUC) for viral versus bacterial infection was 0.786 (0.524–1), with accuracy 0.79 (95% CI 0.57–0.91), positive percent agreement (PPA) 0.43 (95% CI 0.16–0.75), and negative percent agreement (NPA) 1.00 (95% CI 0.76–1). The novel model had AUC 0.881 (95% CI 0.726–1), accuracy 0.84 (95% CI 0.62–0.94), PPA 0.86 (95% CI 0.49–0.97), and NPA 0.83 (95% CI 0.55–0.95) for bacterial infection. Validation in two external datasets showed AUC of 0.932 (95% CI 0.90–0.96) and 0.915 (95% CI 0.88–0.95).

We show that host response in the nasopharynx can distinguish viral versus bacterial LRTI. These findings need to be replicated in larger cohorts with diverse LRTI etiologies.

Antipsychotic (AP) medication in individuals at clinical high risk for psychosis (CHR-P) is not routinely recommended by clinical guidelines but is commonly prescribed. Since little is known about the predictors of AP inception in CHR-P, we analyzed data from two observational cohorts.

To avoid baseline predictors being confounded by previous treatment, participants were selected for analysis from the 764 participants at CHR-P enrolled in NAPLS-2 and the 710 enrolled in NAPLS-3 by excluding those with lifetime histories of AP use. Baseline clinical variables available in both studies were employed as predictors of subsequent AP inception over the next 6 months in univariable and multivariable analyses.

Preliminary analyses indicated no important effects of sample. The final combined population included 79 AP inception participants and 580 participants who did not have AP inception. The AP medications most commonly prescribed were risperidone, aripiprazole, and quetiapine. Univariable analyses identified seven significant predictors of AP inception. The final logistic regression model including these variables was highly significant (χ2 = 36.53, df = 7, p = <0.001). Three variables (current major depression, fewer education years, and current benzodiazepine use) emerged as significant independent predictors of AP inception.

This study is the first to determine baseline characteristics that predict subsequent AP initiation in CHR-P. Some AP use in CHR-P appears to be intended as augmentation of antidepressant treatment for comorbid major depression. Some prescribers may not have detected the attenuated positive symptoms characteristic of CHR-P since their severity did not significantly predict AP inception.

Stigma of mental health conditions hinders recovery and well-being. The Honest, Open, Proud (HOP) program shows promise in reducing stigma but there is uncertainty about the feasibility of a randomized trial to evaluate a peer-delivered, individual adaptation of HOP for psychosis (Let's Talk).

A multi-site, Prospective Randomized Open Blinded Evaluation (PROBE) design, feasibility randomised controlled trial (RCT) comparing the peer-delivered intervention (Let's Talk) to treatment as usual (TAU). Follow-up was 2.5 and 6 months. Randomization was via a web-based system, with permuted blocks of random size. Up to 10 sessions of the intervention over 10 weeks were offered. The primary outcome was feasibility data (recruitment, retention, intervention attendance). Primary outcomes were analyzed by intention to treat. Safety outcomes were reported by as treated status. The study was prospectively registered: https://doi.org/10.1186/ISRCTN17197043.

149 patients were referred to the study and 70 were recruited. 35 were randomly assigned to intervention + TAU and 35 to TAU. Recruitment was 93% of the target sample size. Retention rate was high (81% at 2.5 months primary endpoint), and intervention attendance rate was high (83%). 21% of 33 patients in Let's talk + TAU had an adverse event and 16% of 37 patients in TAU. One serious adverse event (pre-randomization) was partially related and expected.

This is the first trial to show that it is feasible and safe to conduct a RCT of HOP adapted for people with psychosis and individual delivery. An adequately powered trial is required to provide robust evidence.

It is well established that there is a substantial genetic component to eating disorders (EDs). Polygenic risk scores (PRSs) can be used to quantify cumulative genetic risk for a trait at an individual level. Recent studies suggest PRSs for anorexia nervosa (AN) may also predict risk for other disordered eating behaviors, but no study has examined if PRS for AN can predict disordered eating as a global continuous measure. This study aimed to investigate whether PRS for AN predicted overall levels of disordered eating, or specific lifetime disordered eating behaviors, in an Australian adolescent female population.

PRSs were calculated based on summary statistics from the largest Psychiatric Genomics Consortium AN genome-wide association study to date. Analyses were performed using genome-wide complex trait analysis to test the associations between AN PRS and disordered eating global scores, avoidance of eating, objective bulimic episodes, self-induced vomiting, and driven exercise in a sample of Australian adolescent female twins recruited from the Australian Twin Registry (N = 383).

After applying the false-discovery rate correction, the AN PRS was significantly associated with all disordered eating outcomes.

Findings suggest shared genetic etiology across disordered eating presentations and provide insight into the utility of AN PRS for predicting disordered eating behaviors in the general population. In the future, PRSs for EDs may have clinical utility in early disordered eating risk identification, prevention, and intervention.

Psychiatric drugs, including antipsychotics and antidepressants, are widely prescribed, even in young and adolescent populations at early or subthreshold disease stages. However, their impact on brain structure remains elusive. Elucidating the relationship between psychotropic medication and structural brain changes could enhance the understanding of the potential benefits and risks associated with such treatment.

Investigation of the associations between psychiatric drug intake and longitudinal grey matter volume (GMV) changes in a transdiagnostic sample of young individuals at early stages of psychosis or depression using an unbiased data-driven approach.

The study sample comprised 247 participants (mean [SD] age = 25.06 [6.13] years, 50.61% male), consisting of young, minimally medicated individuals at clinical high-risk states for psychosis, individuals with recent-onset depression or psychosis, and healthy control individuals. Structural magnetic resonance imaging was used to obtain whole-brain voxel-wise GMV for all participants at two timepoints (mean [SD] time between scans = 11.15 [4.93] months). The multivariate sparse partial least squares (SPLS) algorithm (Monteiro et al. JNMEDT 2016; 271:182-194) was embedded in a nested cross-validation framework to identify parsimonious associations between the cumulative intake of psychiatric drugs, including commonly prescribed antipsychotics and antidepressants, and change in GMV between both timepoints, while additionally factoring in age, sex, and diagnosis. Furthermore, we correlated the retrieved SPLS results to personality domains (NEO-FFI) and childhood trauma (CTQ).

SPLS analysis revealed significant associations between the antipsychotic classes of benzamides, butyrophenones and thioxanthenes and longitudinal GMV decreases in cortical regions including the insula, posterior superior temporal sulcus as well as cingulate, postcentral, precentral, orbital and frontal gyri (Figure 1A-C). These brain regions corresponded most closely to the dorsal and ventral attention, somatomotor, salience and default network (Figure 1D). Furthermore, the medication signature was negatively associated with the personality domains extraversion, agreeableness and conscientiousness and positively associated with the CTQ domains emotional and physical neglect.

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Psychiatric drug intake over a period of one year was linked to distinct GMV reductions in key cortical hubs. These patterns were already visible in young individuals at early or subthreshold stages of mental illness and were further linked to childhood neglect and personality traits. Hence, a better and more in-depth understanding of the structural brain implications of medicating young and adolescent individuals might lead to more cautious, sustainable and targeted treatment strategies.

None Declared

The clinical high-risk state for psychosis (CHR) is associated with alterations in grey matter volume (GMV) in various regions such as the hippocampus (Vissink et al. BP:GOS 2022; 2(2) 147-152). Within the scope of the North American Prodrome Longitudinal Study (NAPLS-2; Cannon et al. AM J Psychiatry 2016; 173(10), 980-988), a publicly available risk calculator based on clinical variables was developed to assess the likelihood of individuals to transition to psychosis within a 2-year period.

In the current study, we aim to examine the association between GMV and NAPLS-2 risk scores calculated for individuals with CHR and recent-onset depression (ROD), taking a transdiagnostic approach on the transition to psychosis.

The sample consisted of 315 CHR (M = 23.85, SD = ± 5.64; female: 164) and 295 ROD (M = 25.11, SD = ± 6.21; female: 144) patients from the multi-site Personalised Prognostic Tools for Early Psychosis Management (PRONIA) Study (Koutsouleris et al. JAMA Psychiatry 2018; 57(11), 1156-1172). Risk scores were calculated using the six clinical and neurocognitive variables included in the NAPLS-2 risk calculator that were significant for predicting psychosis. Further, we derived smoothed GMV maps from T1-weighted structural magnetic resonance imaging using a full width at half maximum kernel size of 8 mm. We employed a multiple regression design in SPM12 to examine associations between risk scores and GMV. On the whole-brain level, we calculated permutation-based threshold-free cluster enhancement (TFCE) contrasts using the TFCE toolbox. Additionally, we calculated t-contrasts within a region-of-interest (ROI) analysis encompassing the hippocampus. All results were thresholded at p < 0.05 with family wise error correction to address multiple comparisons.

Our analysis revealed that linear GMV increases in the right middle and superior frontal gyrus (kE= 2726 voxels) were significantly associated with higher risk for psychosis transition within two years (see figure 1, highlighted in blue). In the ROI analysis, we found a significant negative linear association between GMV decreases in the left hippocampus (kE = 353 voxels) and higher risk for psychosis transition (see figure 1, highlighted in red).

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GMV reductions in the hippocampus have frequently been observed in CHR and psychosis patients (Vissink et al. BP:GOS 2022; 2(2) 147-152), therefore our results further highlight the crucial role of this region in the progression of the disease. There is limited evidence on GMV increases in CHR patients. However, the GMV increase we found in the frontal pole may reflect compensatory mechanisms of the brain in the development of psychosis. In addition, we were able to provide biological validation of the NAPLS-2 risk calculator and its assessment of risk for transition to psychosis.

None Declared

Cognitive training is a non-pharmacological intervention aimed at improving cognitive function across a single or multiple domains. Although the underlying mechanisms of cognitive training and transfer effects are not well-characterized, cognitive training has been thought to facilitate neural plasticity to enhance cognitive performance. Indeed, the Scaffolding Theory of Aging and Cognition (STAC) proposes that cognitive training may enhance the ability to engage in compensatory scaffolding to meet task demands and maintain cognitive performance. We therefore evaluated the effects of cognitive training on working memory performance in older adults without dementia. This study will help begin to elucidate non-pharmacological intervention effects on compensatory scaffolding in older adults.

48 participants were recruited for a Phase III randomized clinical trial (Augmenting Cognitive Training in Older Adults [ACT]; NIH R01AG054077) conducted at the University of Florida and University of Arizona. Participants across sites were randomly assigned to complete cognitive training (n=25) or an education training control condition (n=23). Cognitive training and the education training control condition were each completed during 60 sessions over 12 weeks for 40 hours total. The education training control condition involved viewing educational videos produced by the National Geographic Channel. Cognitive training was completed using the Posit Science Brain HQ training program, which included 8 cognitive training paradigms targeting attention/processing speed and working memory. All participants also completed demographic questionnaires, cognitive testing, and an fMRI 2-back task at baseline and at 12-weeks following cognitive training.

Repeated measures analysis of covariance (ANCOVA), adjusted for training adherence, transcranial direct current stimulation (tDCS) condition, age, sex, years of education, and Wechsler Test of Adult Reading (WTAR) raw score, revealed a significant 2-back by training group interaction (F[1,40]=6.201, p=.017, η2=.134). Examination of simple main effects revealed baseline differences in 2-back performance (F[1,40]=.568, p=.455, η2=.014). After controlling for baseline performance, training group differences in 2-back performance was no longer statistically significant (F[1,40]=1.382, p=.247, η2=.034).

After adjusting for baseline performance differences, there were no significant training group differences in 2-back performance, suggesting that the randomization was not sufficient to ensure adequate distribution of participants across groups. Results may indicate that cognitive training alone is not sufficient for significant improvement in working memory performance on a near transfer task. Additional improvement may occur with the next phase of this clinical trial, such that tDCS augments the effects of cognitive training and results in enhanced compensatory scaffolding even within this high performing cohort. Limitations of the study include a highly educated sample with higher literacy levels and the small sample size was not powered for transfer effects analysis. Future analyses will include evaluation of the combined intervention effects of a cognitive training and tDCS on nback performance in a larger sample of older adults without dementia.

Health disparities among African Americans (AAs) in the United States are evident, especially among older adults and people living with HIV (PLWH). These health disparities include worse cognitive functioning among AAs than White counterparts. Though disparities in health literacy among AAs impact health outcomes across clinical populations, less is known on the mechanistic role health literacy may play in explaining racial differences in cognitive functioning among older PLWH. The current study investigated the association between health literacy and global cognitive functioning among middle-aged and older AA and White adults with and without HIV in the Deep South.

Two hundred and seventy-three people (170 PLWH: 146 AA, 24 White; 103 HIV-negative: 67 AA, 36 White) were enrolled in an observational study and completed measures of sociodemographic characteristics, as well as the reading subtest of the Wide Range Achievement Test-3rd Edition to assess verbal IQ. A composite score of socioeconomic status (SES) was created using total years of education and annual household income. Neurocognitive functioning was assessed using a comprehensive cognitive battery (i.e., verbal, attention/working memory, executive function, learning, recall, speed of processing, and motor), from which a sample-based global Z-score composite was created. Health literacy was measured using a sample-based composite Z-score derived from the Rapid Estimate of Adult Literacy in Medicine, Test of Functional Health Literacy in Adults Reading Comprehension, Newest Vital Sign, and Expanded Numeracy Scale. First, multivariable linear regression analyses were performed within both PLWH and HIV-negative samples examining the association between race, SES, verbal IQ, and health literacy with cognitive functioning. These results informed two bootstrap confidence interval mediation analyses to determine whether health literacy mediated the association between race and global cognitive functioning.

In both PLWH and HIV-negative individuals, linear regressions showed that Whites had better global cognitive functioning, health literacy, and verbal IQ than AAs. Linear regressions showed that health literacy had an independent association with cognitive function when accounting for verbal IQ and SES. Mediations showed that health literacy significantly mediated the association between race and global cognitive functioning in both samples, independent of verbal IQ (PLWH: b = .07, 95% CI [0.0096, 0.2149]; HIV-negative: b = .15, 95% CI [0.0518, 0.2877]), indicating that Whites were expected to obtain higher global cognitive Z-scores than AAs in both PLWH and HIV-negative samples, through the mediating effect of better health literacy.

Health literacy significantly mediated the association between race and global cognitive functioning among middle-aged and older adults with and without HIV, underscoring the importance of health literacy in explaining racial disparities in cognitive outcomes among AAs in the Deep South. Findings have implications for guiding clinicians and healthcare providers in developing interventions that promote health literacy in these underserved populations, which may have downstream impacts on cognitive functioning. Future work is needed to examine mechanisms whereby health literacy impacts neurocognition among AA PLWH.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.