A Food and Drug Administration (FDA) safety communication in August 2011 warned that citalopram was associated with a dose dependent risk of QT prolongation and recommended dose restriction in patients over the age of 60 but did not provide data for this age group.

Amiselimod (MT-1303) is a selective sphingosine 1-phosphate 1 (S1P1 ) receptor modulator which is currently being developed for the treatment of various autoimmune diseases. Unlike some other S1P receptor modulators, amiselimod seemed to show a favourable cardiac safety profile in preclinical, phase I and II studies. The aim of the current study was to characterize the cardiac effects of amiselimod by directly comparing it with fingolimod and placebo.

Episodic memory - composed of memory for unique spatiotemporal experiences - is known to decline with aging, and even more severely in Alzheimer 's disease (AD). Memory for trial-unique objects in spatial scenes depends on the integrity of the hippocampus and interconnected structures that are among the first areas affected in AD. We reasoned that memory for objects-in-scenes would be impaired with aging, and that further impairments would be observed in AD. We asked younger adults, healthy older adults, older adults at-risk for developing cognitive impairments, and older adults with probable early AD to find changing items ('targets') within images of natural scenes, measuring repeated-trial changes in search efficiency and pupil diameter. Compared to younger adults, older adults took longer to detect target objects in repeated scenes, they required more fixations and those fixations were more dispersed. Whereas individuals with AD showed some benefit of memory in this task, they had substantially longer detection times, and more numerous, dispersed fixations on repeated scenes compared to age-matched older adults. Correspondingly, pupillary responses to novel and repeated scenes were diminished with aging and further in AD, and the memory-related changes were weaker with aging and absent in AD. Our results suggest that several nonverbal measures from memory-guided visual search tasks can index aging and Alzheimer's disease status, including pupillary dynamics. The task measurements are sensitive to the integrity of brain structures that are associated with Alzheimer's-related neurodegeneration, the task is well tolerated across a range of abilities, and thus, it may prove useful in early diagnostics and longitudinal tracking of memory decline.

Deep brain stimulation (DBS) is used to modulate the activity of dysfunctional brain circuits. The safety and efficacy of DBS in dementia is unknown.

People with dementia (PWD) represent some of the highest-need and highest-cost individuals living in the community. Maximizing Independence (MIND) at Home is a potentially cost-effective and scalable home-based dementia care coordination program that uses trained, nonclinical community workers as the primary contact between the PWD and their care partner, supported by a multidisciplinary clinical team with expertise in dementia care.

To evaluate the impact of lasmiditan, an oral, centrally-penetrant, selective serotonin 1F (5-HT1F ) receptor agonist developed for the acute treatment of migraine, on simulated driving.

Although genetic factors are known to contribute to neurodegenerative disease susceptibility, there remains a large amount of heritability unaccounted for across the diagnoses. Copy number variants (CNVs) contribute to these phenotypes, but their presence and influence on disease state remains relatively understudied.

The recent advances in creating pluripotent stem cells from somatic cells and differentiating them into a variety of cell types is allowing us to study them without the caveats associated with disease-related changes. We generated induced Pluripotent Stem Cells (iPSCs) from eight Alzheimer's disease (AD) patients and six controls and used lentiviral delivery to differentiate them into excitatory glutamatergic neurons. We then performed RNA sequencing on these neurons and compared the Alzheimer's and control transcriptomes. We found that 621 genes show differences in expression levels at adjusted p < 0.05 between the case and control derived neurons. These genes show significant overlap and directional concordance with genes reported from a single-cell transcriptome study of AD patients; they include five genes implicated in AD from genome-wide association studies and they appear to be part of a larger functional network as indicated by an excess of interactions between them observed in the protein-protein interaction database STRING. Exploratory analysis with Uniform Manifold Approximation and Projection (UMAP) suggests distinct clusters of patients, based on gene expression, who may be clinically different. Our research outcomes will enable the precise identification of distinct biological subtypes among individuals with Alzheimer's disease, facilitating the implementation of tailored precision medicine strategies.

Measures of cerebrovascular reactivity (CVR) are used to judge the health of the brain vasculature. In this study, we report the use of several different analyses of blood oxygen dependent (BOLD) fMRI responses to CO2 to provide a number of metrics of CVR based on the sigmoidal resistance response to CO2. To assess possible differences in these metrics with age, we compiled atlases reflecting voxel-wise means and standard deviations for four different age ranges and for a group of patients with mild cognitive impairment (MCI) and compared them. Sixty-seven subjects were recruited for this study and scanned at 3T field strength. Of those, 51 healthy control volunteers between the ages of 18-83 were recruited, and 16 (MCI) subjects between the ages of 61-83 were recruited. Testing was carried out using an automated computer-controlled gas blender to induce hypercapnia in a step and ramp paradigm while monitoring end-tidal partial pressures of CO2. Surprisingly, some resistance sigmoid parameters in the oldest control group were increased compared to the youngest control group. Resistance amplitude maps showed increases in clusters within the temporal cortex, thalamus, corpus callosum and brainstem, and resistance reserve maps showed increases in clusters within the cingulate cortex, frontal gyrus, and corpus callosum. These findings suggest that some aspects of vascular reactivity in parts of the brain are initially maintained with age but then may increase in later years. We found significant reductions in all resistance sigmoid parameters (amplitude, reserve, sensitivity, midpoint, and range) when comparing MCI patients to controls. Additionally, in controls and in MCI patients, amplitude, range, reserve, and sensitivity in white matter (WM) was significantly reduced compared to gray matter (GM). WM midpoints were significantly above those of GM. Our general conclusion is that vascular regulation in terms of cerebral blood flow (CBF) responsiveness to CO2 is not significantly affected by age, but is reduced in MCI. These changes in cerebrovascular regulation demonstrate the value of resistance metrics for mapping areas of dysregulated blood flow in individuals with MCI. They may also be of value in the investigation of patients with vascular risk factors at risk for developing vascular dementia.

Alterations of the gray and white matter have been identified in Alzheimer's disease (AD) by structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). However, whether the combination of these modalities could increase the diagnostic performance is unknown.

This Phase I study aimed to assess the potential drug-drug interactions (pharmacokinetic [PK] and safety profile) of Δ9-tetrahydrocannabinol (THC)/cannabidiol (CBD) oromucosal spray (Sativex (®), nabiximols) in combination with cytochrome P450 (CYP450) inducer (rifampicin) or inhibitors (ketoconazole or omeprazole). Thirty-six healthy male subjects were divided into three groups of 12, and then randomized to one of two treatment sequences per group. Subjects received four sprays of THC/CBD (10.8/10 mg) alongside single doses of the CYP3A and 2C19 inducer rifampicin (600 mg), CYP3A inhibitor ketoconazole (400 mg) or CYP2C19 inhibitor omeprazole (40 mg). Plasma samples were analyzed for CBD, THC and its metabolite 11-hydroxy-THC (11-OH-THC). A single dose of four sprays of THC/CBD spray (10.8/10 mg) following repeated doses of rifampicin (600 mg) reduced the Cmax and AUC of all analytes. Cmax reduced from 2.94 to 1.88 ng/mL (-36%), 1.03 to 0.50 ng/mL (-52%) and 3.38 to 0.45 ng/mL (-87%) for THC, CBD and 11-OH-THC, respectively compared to single dose administration of THC/CBD spray alone. Ketoconazole co-administration with THC/CBD spray had the opposite effect, increasing the Cmax of the respective analytes from 2.65 to 3.36 ng/mL (+27%), 0.66 to 1.25 ng/mL (+89%) and 3.59 to 10.92 ng/mL (+204%). No significant deviations in Cmax or AUC for any analyte were observed when THC/CBD spray was co-administered with omeprazole. THC/CBD spray was well tolerated by the study subjects both alone and in combination with rifampicin, ketoconazole and omeprazole. Evaluation of the PKs of THC/CBD spray alone and in combination with CYP450 inhibitors/inducers suggests that all analytes are substrates for the isoenzyme CYP3A4, but not CYP2C19. On the basis of our findings, there is likely to be little impact on other drugs metabolized by CYP enzymes on the PK parameters of THC/CBD spray, but potential effects should be taken into consideration when co-administering THC/CBD spray with compounds which share the CYP3A4 pathway such as rifampicin or ketoconazole.

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas-image misregistration, is used to capture the anatomical features of target images. As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

For patients with cognitive disorders and dementia, accurate prognosis of cognitive worsening is critical to their ability to prepare for the future, in collaboration with health-care providers. Despite multiple efforts to apply computational brain magnetic resonance image (MRI) analysis in predicting cognitive worsening, with several successes, brain MRI is not routinely quantified in clinical settings to guide prognosis and clinical decision-making. To encourage the clinical use of a cutting-edge image segmentation method, we developed a prediction model as part of an established web-based cloud platform, MRICloud. The model was built in a training dataset from Alzheimer's Disease Neuroimaging Initiative (ADNI) where baseline MRI scans were combined with clinical data over time. Each MRI was parcellated into 265 anatomical units based on the MRICloud fully automated image segmentation function, to measure the volume of each parcel. The Mini Mental State Examination (MMSE) was used as a measure of cognitive function. The normalized volume of 265 parcels, combined with baseline MMSE score, age, and sex were input variables for a Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, with MMSE change in the subsequent two years as the target for prediction. A leave-one-out analysis performed on the training dataset estimated a correlation coefficient of 0.64 between true and predicted MMSE change. A receiver operating characteristic (ROC) analysis estimated a sensitivity of 0.88 and a specificity of 0.76 in predicting substantial cognitive worsening after two years, defined as MMSE decline of ≥4 points. This MRICloud prediction model was then applied to a test dataset of clinically acquired MRIs from the Johns Hopkins Memory and Alzheimer's Treatment Center (MATC), a clinical care setting. In the latter setting, the model had both sensitivity and specificity of 1.0 in predicting substantial cognitive worsening. While the MRICloud prediction model demonstrated promise as a platform on which computational MRI findings can easily be extended to clinical use, further study with a larger number of patients is needed for validation.

Pittsburgh compound B ([11C]-PIB) identifies amyloid-β (Aβ) deposition in vivo. Asymptomatic Aβ deposition has been reported consistently in some healthy older subjects. Of patients with frontotemporal dementia, those who have later onset have a higher potential for Aβ deposition.

Degraded social function, disinhibition, and stereotypy are defining characteristics of frontotemporal dementia (FTD), manifesting in both the behavioral variant of frontotemporal dementia (bvFTD) and semantic dementia (SD) subtypes. Recent neuroimaging research also associates FTD with alterations in the brain's intrinsic connectivity networks. The present study explored the relationship between neural network connectivity and specific behavioral symptoms in FTD.

White matter disruption has been suggested as one of anatomical features associated with Alzheimer's disease (AD). Diffusion tensor imaging (DTI), which has been widely used in AD studies, obtains new insights into the white matter structure.

Genetic factors contribute to neurodegenerative diseases, with high heritability estimates across diagnoses; however, a large portion of the genetic influence remains poorly understood. Many previous studies have attempted to fill the gaps by performing linkage analyses and association studies in individual disease cohorts, but have failed to consider the clinical and pathological overlap observed across neurodegenerative diseases and the potential for genetic overlap between the phenotypes. Here, we leveraged rare variant association analyses (RVAAs) to elucidate the genetic overlap among multiple neurodegenerative diagnoses, including Alzheimer's disease, amyotrophic lateral sclerosis, frontotemporal dementia (FTD), mild cognitive impairment, and Parkinson's disease (PD), as well as cerebrovascular disease, using the data generated with a custom-designed neurodegenerative disease gene panel in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). As expected, only ~3% of ONDRI participants harboured a monogenic variant likely driving their disease presentation. Yet, when genes were binned based on previous disease associations, we observed an enrichment of putative loss of function variants in PD genes across all ONDRI cohorts. Further, individual gene-based RVAA identified significant enrichment of rare, nonsynonymous variants in PARK2 in the FTD cohort, and in NOTCH3 in the PD cohort. The results indicate that there may be greater heterogeneity in the genetic factors contributing to neurodegeneration than previously appreciated. Although the mechanisms by which these genes contribute to disease presentation must be further explored, we hypothesize they may be a result of rare variants of moderate phenotypic effect contributing to overlapping pathology and clinical features observed across neurodegenerative diagnoses.

To examine whether associations between individual neuropsychiatric symptoms (NPS) and incident Alzheimer's dementia (AD) differ in men versus women.

The Ascertain Dementia 8-item Questionnaire (AD8) is a screening tool for cognitive impairment that can be administered to older persons and/or their informants.

There is strong association of Alzheimer's disease (AD) pathology with gait disorder and falls in older adults without dementia. The goal of the study was to examine the prevalence and severity of AD pathology in older adults without dementia who fall and sustain hip fracture.