Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.

Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.

RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.

These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.

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.

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.

Preclinical evidence has identified the trace amine-associated receptor 1 (TAAR1) as a novel regulator of metabolic control. Ulotaront is a TAAR1 and 5-HT1A agonist currently in Phase 3 clinical trials for the treatment of schizophrenia. Here we summarize preclinical results assessing the effects of ulotaront on weight and metabolic parameters.

Effects of ulotaront administration were evaluated on oral glucose tolerance (oGTT), gastric emptying, and in rodent models of weight gain (high-fat diet [HFD]-, corticosterone-, and olanzapine-induced).

Following 15-day oral administration of ulotaront, rats on HFD showed dose-dependent reduction in body weight, food intake, and liver triglyceride content compared to controls. In addition, a more rapid reversal of olanzapine-induced weight gain and food intake was observed in rats switched to ulotaront (vs. vehicle). Consistent with weight-lowering effects in rats, chronic ulotaront treatment normalized corticosterone-induced weight gain in mice. Assessment of oGTT showed a dose-dependent reduction of glucose excursion in response to acute ulotaront administration in naive and diabetic db/db mice. Ulotaront administration also delayed gastric emptying in mice—a likely mechanism driving reductions in glucose excursions during the oGTT. Whole-brain c-fos imaging of ulotaront-treated mice revealed increased neuronal activity in several brain regions associated with regulation of food intake and metabolic signals.

The data indicate that ulotaront not only lacks metabolic liabilities typically associated with antipsychotics but can reduce body weight and improve glucose tolerance in rodent models. The underlying mechanisms may include TAAR1-mediated peripheral effects on glucose homeostasis and/or direct modulation of homeostatic and hedonic neurocircuits regulating energy balance. The beneficial metabolic effects of ulotaront may suggest a substantially improved risk-benefit profile compared to established antipsychotics.

Sunovion Pharmaceuticals Inc. and Otsuka Pharmaceutical Development & Commercialization, Inc.

An increasing number of studies have described the relationship between celiac disease and schizophrenia. Based on the reported correlations and the overlapping linkage regions on 19p13, the myosin IXB gene (MYO9B) can be considered a highly relevant positional and functional candidate gene for schizophrenia. The present work was undertaken to investigate the association of the MYO9B gene with schizophrenia in a Chinese population.

A total of 329 patients with schizophrenia and 350 healthy control subjects in a Chinese population were recruited. A PCR-based RFLP protocol was applied to genotype 7 single nucleotide polymorphisms (SNPs), including rs7249490, rs7256689, rs2279007, rs8113494, rs2305767, rs1545620 and rs2305764, in the MYO9B gene to investigate their association with schizophrenia.

The X2 goodness-of-fit test showed that the genotypic distributions of all 7 SNPs were in Hardy-Weinberg equilibrium in both the patient group and the control group. Disease association was shown for rs8113494 (X2=12.77, P=0.0003, OR=1.89, 95% CI 1.33-2.68) and rs1545620 (X2=15.44, P=8.379e-5, OR=1.65, 95% CI 1.29-2.12), while rs2279007 was associated with schizophrenia in the female subjects (X2=4.637, P=0.031, OR=0.69, 95% CI 0.49-0.97) but not in the male subjects (X2=1.082, P=0.299, OR=0.85, 95% CI 0.63-1.15).

The present work shows that the polymorphisms of the MYO9B gene are likely to confer susceptibility to schizophrenia. Because the MYO9B gene has been found to be highly expressed in the tight junction gate, it could be considered as a meeting point for the interaction between environmental and genetic factors in the pathogenesis of schizophrenia.

An increasing number of studies have described the relationship between velo-cardio-facial syndrome (VCFS) and schizophrenia. in a family-based study, we found that rs10314, a single nucleotide polymorphism (SNP) present in the 3’-flanking region of the CLDN5 gene, was associated with schizophrenia among a Chinese population. High false positive rate is a common problem with the association study of human diseases. It is very important to replicate an initial finding with different samples and experimental designs.

A total of 749 patients with schizophrenia and 383 age and sex matched healthy control subjects in Chinese population were recruited. PCR-based RFLP protocol was applied to genotype rs10314 to see its disease association.

The χ2 goodness-of-fit test showed that the genotypic distributions of rs10314 were in Hardy-Weinberg equilibrium in both the patient group (χ2=1.12, P=0.289) and the control group (χ2=0.22, P=0.639). rs10314 was associated with schizophrenia with an odds ratio (OR) of 1.32 in the male subjects (χ2=5.45, P=0.02, 95% CI 1.05-1.67) but not in the female subjects (χ2=0.64, P=0.425, OR=1.14, 95% CI 0.83-1.57). the χ2 test showed a genotypic association only for combined samples (χ2=7.80, df=2, P=0.02). SNP rs10314 is a G to C base change. Frequency of the genotypes containing the C allele was significantly higher in the patient group than in the control group.

The present work shows that the CLDN5 gene polymorphism is more likely to be involved in schizophrenic men than women, suggesting that this gene may contribute to the gender differences in schizophrenia.

Several questions still exist in the literature on the relationship between cumulative exposure to work-related incidents and posttraumatic stress disorder (PTSD) in First Responders (FR).

To address three unanswered questions in the field.

1. (1) Are different cumulative exposure scoring algorithms similarly related to PTSD?

2. (2) Is PTSD associated only with incidents rated as severe and traumatic?

3. (3) Can we identify cut-off scores of cumulative exposure that maximize sensitivity and specificity to predict PTSD?

To better characterize the relationship between cumulative exposure and PTSD in FR.

The association between exposure and PTSD was examined with logistic and linear regression and with receiver operating characteristic analysis in 349 FR.

1. (1) The strength of the association between PTSD and total cumulative exposure indexes varied across different scoring algorithms.

2. (2) Compared to total cumulative exposure indexes and to sub-scores of exposure to non-traumatic and/or less severe incidents, sub-scores indexing exposure to severe traumatic events only were more strongly and significantly associated with PTSD.

3. (3) The use of two cut-off scores maximizes sensitivity and specificity to predict PTSD.

1. (1) The relationship between current PTSD and cumulative exposure is partially dependent on the approach used to quantify exposure.

2. (2) Focusing on the assessment of cumulative exposure to severe traumatic events is sufficient to predict PTSD, and might be more useful and effective in research and clinical decision-making.

3. (3) Sensitivity and specificity of exposure scores might help improve secondary prevention (early detection and effective intervention) of individuals at risk.