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Background: The production of autobiographical narratives requires linguistic structures and the ability to access and generate both semantic information and episodic details of personal events. Ai...

Background and Purpose: Many patients with ischemic stroke present with multiple comorbidities that threaten survival and recovery. This study sought to determine the risks of adverse long-term stroke outcomes associated with multimorbid diabetes mellitus and depression. Methods: Retrospective analysis of prospectively collected data on consecutive patients without premorbid dementia admitted from the community for a first-ever acute ischemic stroke to comprehensive stroke centers across Ontario, Canada (2003–2013). Premorbid histories of diabetes mellitus and depression were ascertained within 5 years before stroke admission. Adjusted hazard ratios (aHR [95% CI]) of admission to long-term care, incident dementia, readmission for stroke or transient ischemic attack and all-cause mortality, over time among those discharged back into the community poststroke. Results: Among 23 579 stroke admissions, n=20 201 were discharged back into the community. Diabetes mellitus and depression were associated with synergistic hazards of admission to long-term care (X 2 =5.4; P =0.02) over a median follow-up of 5.6 years. This interaction was observed among women specifically; depression multimorbidity showed particularly high hazards of admission to long-term care (aHR Depression =1.57 [1.24–1.98]) and incident dementia (aHR Depression =1.85 [1.40–2.44]) among women with diabetes mellitus. In the whole cohort, diabetes mellitus and depression were associated individually with long-term care admission (aHR Diabetes =1.20 [1.12–1.29]; aHR Depression =1.19 [1.04–1.37]), incident dementia (aHR Diabetes =1.14 [1.06–1.23]; aHR Depression =1.27 [1.08–1.49]), stroke/transient ischemic attack readmission (aHR Diabetes =1.18 [1.10–1.26]; aHR Depression =1.24 [1.07–1.42]), and all-cause mortality (aHR Diabetes =1.29 [1.23–1.36]; aHR Depression =1.16 [1.05–1.29]). Conclusions: The risks of dementia and needing long-term care in the years after surviving a stroke were particularly elevated among women when premorbid diabetes mellitus and depression occurred together. Long-term stroke recovery strategies might target high-risk patients with mood and metabolic multimorbidity.

We have provided an overview on the profound impact of COVID‐19 upon older people with Alzheimer's disease and other dementias and the challenges encountered in our management of dementia in different health‐care settings, including hospital, out‐patient, care homes, and the community during the COVID‐19 pandemic. We have also proposed a conceptual framework and practical suggestions for health‐care providers in tackling these challenges, which can also apply to the care of older people in general, with or without other neurological diseases, such as stroke or parkinsonism. We believe this review will provide strategic directions and set standards for health‐care leaders in dementia, including governmental bodies around the world in coordinating emergency response plans for protecting and caring for older people with dementia amid the COIVD‐19 outbreak, which is likely to continue at varying severity in different regions around the world in the medium term.

Physical activity (PA) participation provides functional and social benefits for persons with mild cognitive impairment (MCI) and Alzheimer’s disease (AD), but PA participation in these populations is low. To support health promotion initiatives for cognitively impaired older adults, this study explored the perceptions, experiences, and beliefs of older adults with cognitive impairment and their caregivers concerning PA. Ten care dyads (community-dwelling adult aged ≥65 years diagnosed with MCI or mild-to-moderate AD and their care partner) participated in semi-structured interviews informed by the Theoretical Domains Framework about their PA perceptions, experiences, and beliefs. Interpretive phenomenological analysis of interview transcripts yielded 4 emergent themes: (1) PA as a meaningful activity, (2) experience versus evidence as motivating, (3) participation is possible despite dementia, and (4) care partners as enablers. Findings from this study address a research gap concerning the PA perceptions, experiences, and beliefs of cognitively impaired older adults and their care partners. Novelty Older adults with MCI/AD want to and are capable of engaging in PA. Care partners are critical supporters of PA participation in MCI/AD. Adapted health promotion strategies could enhance PA in MCI/AD.

Studies evaluating individuals for endothelial injury after endovascular thrombectomy (EVT) have been done by means of retrieved human thrombus, MR vessel-wall imaging, and animal histopathological studies. These techniques have limitations, because MR imaging has insufficient spatial resolution to directly visualize endothelium, and histopathological examinations are performed ex vivo and are unable to provide real-time patterns of injury. The purpose of the current study was to obtain in vivo intraluminal imaging after EVT by using optical coherence tomography (OCT), examining for evidence of endothelial injury in real time.Three consecutive patients with acute basilar artery occlusion underwent OCT imaging immediately after EVT. There were no complications and adequate images were obtained for all patients. Anatomical features of the vessel wall were discernible, including intima, media, adventitia, and internal/external elastic lamina. Basilar artery thick concentric plaque fibrosis was present, causing outward remodeling and loss of the internal/external lamina in certain regions. Evidence of significant residual thrombus was also visible, with mostly red thrombus present despite complete angiographic revascularization. The residual thrombus was not visible on CT, MR, or cerebral angiography and could certainly cause ongoing function-limiting strokes with occlusion of adjacent vital basilar perforators after EVT.

This article is the second part in our machine learning series. Part 1 provided a general overview of machine learning in nuclear medicine. Part 2 focuses on neural networks. We start with an example illustrating how neural networks work and a discussion of potential applications. Recognizing that there is a spectrum of applications, we focus on recent publications in the areas of image reconstruction, low-dose PET, disease detection, and models used for diagnosis and outcome prediction. Finally, since the way machine learning algorithms are reported in the literature is extremely variable, we conclude with a call to arms regarding the need for standardized reporting of design and outcome metrics and we propose a basic checklist our community might follow going forward.

In the present study, we tested the hypothesis that higher amyloid-beta (Aβ) burden at baseline is associated with greater longitudinal decline in body mass index (BMI) in clinically normal adults. Participants from the Harvard Aging Brain Study (n = 312) and the Alzheimer's Disease Neuroimaging Initiative (n = 336) underwent Aβ positron emission tomography at baseline. BMI was assessed longitudinally over a median of >4 years. Linear mixed models showed that higher baseline Aβ burden was significantly associated with greater decline in BMI in both the Harvard Aging Brain Study (t = −1.93; p = 0.05) and Alzheimer's Disease Neuroimaging Initiative cohorts (t = −2.54; p = 0.01), after adjusting for covariates, including cognitive performance and depressive symptoms. In addition, the association of Aβ burden with longitudinal decline in BMI persisted in both cohorts after excluding participants with diabetes/endocrine disturbances and participants classified as underweight or obese (BMI 30). These findings suggest that decline in BMI in clinically normal adults may be an early manifestation related to cerebral amyloidosis that precedes objective cognitive impairment. Therefore, unintentional BMI decline in otherwise healthy individuals might alert clinicians to increased risk of Alzheimer's disease.

Introduction Few studies have examined memory decline among patients with type 2 diabetes using different oral hypoglycemic drugs. Methods Participants with normal cognition (NC) or Alzheimer's disease (AD) dementia using a hypoglycemic medication (2005 to 2019) were identified from the National Alzheimer's Coordinating Center database. Delayed memory was assessed using the Wechsler Memory Scale Revised–Logical Memory test. Associations between oral drug classes and memory over time were examined using mixed‐effects models with inverse probability treatment weights. Results In NC (n = 1192), metformin use was associated with better memory performance over time, whereas in AD (n = 807), dipeptidyl peptidase‐4 (DPP4) inhibitor use was associated with a slower rate of memory decline. Interaction effects suggested greater benefit associated with DPP4 inhibitor use among APOE ε4 carriers. Discussion Associations between different oral hypoglycemic drugs and memory change were not consistent between cognitively normal elderly and those with AD dementia. APOE ε4 genotype modified some relationships.

It is notoriously difficult to identify peer effects within the family. Using administrative data on children from both Florida and Denmark, we examine the effects of having a disabled younger sibling. To address the identification challenge, we compare the differential effects for first- and second-born children in three-plus-child families, taking advantage of the fact that birth order influences the amount of time that a child spends in early childhood with their younger siblings,disabled or not. We find evidence that, relative to the first born, the second child in a family is differentially affected when the third child is disabled. It is notoriously difficult to identify peer effects within the family. Using administrative data on children from both Florida and Denmark, the paper examines the effects of having a disabled younger sibling. To address the identification challenge, the paper compares the differential effects for first- and second-born children in three-plus-child families, taking advantage of the fact that birth order influences the amount of time that a child spends in early childhood with their younger siblings, disabled or not. The paper finds evidence that, relative to the first born, the second child in a family is differentially affected when the third child is disabled.

BACKGROUND White matter hyperintensities (WMH) on magnetic resonance imaging may influence clinical presentation in patients with Parkinson's disease (PD), although their significance and pathophysiological origins remain unresolved. Studies examining WMH have identified pathogenic variants in NOTCH3 as an underlying cause of inherited forms of cerebral small vessel disease. METHODS We examined NOTCH3 variants, WMH volumes, and clinical correlates in 139 PD patients in the Ontario Neurodegenerative Disease Research Initiative cohort. RESULTS We identified 13 PD patients (~9%) with rare (

Longitudinal invariance indicates that a construct is measured over time in the same way, and this fundamental scale property is a sine qua non to track change over time using ordinary mean comparisons. The Alzheimer’s Disease Assessment Scale–cognitive (ADAS-Cog) and its subscale scores are often used to monitor the progression of Alzheimer’s disease, but longitudinal invariance has not been formally evaluated. A configural invariance model was used to evaluate ADAS-Cog data as a three correlated factors structure for two visits over 6 months, and four visits over 2 years (baseline, 6, 12, and 24 months) among 341 participants with Alzheimer’s disease. We also attempted to model ADAS-Cog subscales individually, and furthermore added item-specific latent variables. Neither the three-correlated factors ADAS-Cog model, nor its subscales viewed unidimensionally, achieved longitudinal configural invariance under a traditional modeling approach. No subscale achieved scalar invariance when considered unidimensional across 6 months or 2 years of assessment. In models accounting for item-specific effects, configural and metric invariance were achieved for language and memory subscales. Although some of the ADAS-Cog individual items were reliable, comparisons of summed ADAS-Cog scores and subscale scores over time may not be meaningful due to a lack of longitudinal invariance.

Background/Objective: Structural brain magnetic resonance imaging (MRI) is not mandatory in Alzheimer's disease (AD) research or clinical guidelines. We aimed to explore the use of structural brain MRI in AD/mild cognitive impairment (MCI) trials over the past 10 years and determine the frequency with which inclusion of standardized structural MRI acquisitions detects comorbid vascular and non-vascular pathologies. Methods: We systematically searched ClinicalTrials.gov for AD clinical trials to determine their neuroimaging criteria and then used data from an AD/MCI cohort who underwent standardized MRI protocols, to determine type and incidence of clinically relevant comorbid pathologies. Results: Of 210 AD clinical trials, 105 (50%) included structural brain imaging in their eligibility criteria. Only 58 (27.6%) required MRI. 16,479 of 53,755 (30.7%) AD participants were in trials requiring MRI. In the observational AD/MCI cohort, 141 patients met clinical criteria; 22 (15.6%) had relevant MRI findings, of which 15 (10.6%) were exclusionary for the study. Discussion: In AD clinical trials over the last 10 years, over two-thirds of participants could have been enrolled without brain MRI and half without even a brain CT. In a study sample, relevant comorbid pathology was found in 15% of participants, despite careful screening. Standardized structural MRI should be incorporated into NIA-AA diagnostic guidelines (when available) and research frameworks routinely to reduce diagnostic heterogeneity.

Background and Purpose:Large prospective observational studies have cast doubt on the common assumption that endovascular thrombectomy (EVT) is superior to intravenous thrombolysis for patients with acute basilar artery occlusion (BAO). The purpose of this study was to retrospectively review our experience for patients with BAO undergoing EVT with modern endovascular devices.Methods:All consecutive patients undergoing EVT with either a second-generation stent retriever or direct aspiration thrombectomy for BAO at our regional stroke center from January 1, 2013 to March 1, 2019 were included. The primary outcome measure was functional outcome at 1 month using the modified Rankin Scale (mRS) score. Multivariable logistic regression was used to assess the association between patient characteristics and dichotomized mRS.Results:A total of 43 consecutive patients underwent EVT for BAO. The average age was 67 years with 61% male patients. Overall, 37% (16/43) of patients achieved good functional outcome. Successful reperfusion was achieved in 72% (31/43) of cases. The median (interquartile range) stroke onset to treatment time was 420 (270–639) minutes (7 hours) for all patients. The procedure-related complication rate was 9% (4/43). On multivariate analysis, posterior circulation Alberta stroke program early computed tomography score and Basilar Artery on Computed Tomography Angiography score were associated with improved functional outcome.Conclusion:EVT appears to be safe and feasible in patients with BAO. Our finding that time to treatment and successful reperfusion were not associated with improved outcome is likely due to including patients with established infarcts. Given the variability of collaterals in the posterior circulation, the paradigm of utilizing a tissue window may assist in patient selection for EVT. Magnetic resonance imaging may be a reasonable option to determine the extent of ischemia in certain situations.

We assessed visuospatial abilities in PCA. Sequential display of two simple geometric figures enhanced detection and discrimination relative to simultaneous display (Exps 1 2). Comparing edges of a single object enhanced discrimination relative to comparing edges of two separate objects, consistent with object-based attention (Exp. 3). Recognition of complex line drawings was spared for a single object but disrupted by an attention-grabbing small circle (Exp. 4). A covert orienting task showed difficulty disengaging from previous locations and attentional bias toward the right visual field (Exp. 5). These findings shed light on the role of visual attention in perceptual awareness.

© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., A key symptom of frontotemporal dementia (FTD) is difficulty interacting socially with others. Social cognition problems in FTD include impaired emotion processing and theory of mind difficulties, and whilst these have been studied extensively in sporadic FTD, few studies have investigated them in familial FTD. Facial Emotion Recognition (FER) and Faux Pas (FP) recognition tests were used to study social cognition within the Genetic Frontotemporal Dementia Initiative (GENFI), a large familial FTD cohort of C9orf72, GRN, and MAPT mutation carriers. 627 participants undertook at least one of the tasks, and were separated into mutation-negative healthy controls, presymptomatic mutation carriers (split into early and late groups) and symptomatic mutation carriers. Groups were compared using a linear regression model with bootstrapping, adjusting for age, sex, education, and for the FP recognition test, language. Neural correlates of social cognition deficits were explored using a voxel-based morphometry (VBM) study. All three of the symptomatic genetic groups were impaired on both tasks with no significant difference between them. However, prior to onset, only the late presymptomatic C9orf72 mutation carriers on the FER test were impaired compared to the control group, with a subanalysis showing differences particularly in fear and sadness. The VBM analysis revealed that impaired social cognition was mainly associated with a left hemisphere predominant network of regions involving particularly the striatum, orbitofrontal cortex and insula, and to a lesser extent the inferomedial temporal lobe and other areas of the frontal lobe. In conclusion, theory of mind and emotion processing abilities are impaired in familial FTD, with early changes occurring prior to symptom onset in C9orf72 presymptomatic mutation carriers. Future work should investigate how performance changes over time, in order to gain a clearer insight into social cognitive impairment over the course of the disease.

Background & objective Contralesional 1-Hz repetitive transcranial magnetic stimulation (rTMS) over the right pars triangularis combined with speech-language therapy (SLT) has shown positive results on the recovery of naming in subacute (5–45 days) post-stroke aphasia. NORTHSTAR-CA is an extension of the previously reported NORTHSTAR trial to chronic aphasia (>6 months post-stroke) designed to compare the effectiveness of the same rTMS protocol in both phases. Methods Sixty-seven patients with left middle cerebral artery infarcts (28 chronic, 39 subacute) were recruited (01-2014 to 07-2019) and randomized to receive rTMS (N = 34) or sham stimulation (N = 33) with SLT for 10 days. Primary outcome variables were Z-score changes in naming, semantic fluency and comprehension tests and adverse event frequency. Intention-to-treat analyses tested between-group effects at days 1 and 30 post-treatment. Chronic and subacute results were compared. Results Adverse events were rare, mild, and did not differ between groups. Language outcomes improved significantly in all groups irrespective of treatment and recovery phase. At 30-day follow-up, there was a significant interaction of stimulation and recovery phase on naming recovery ( P Conclusions The addition of rTMS to SLT led to significant supplemental gains in naming recovery in the subacute phase only. While this needs confirmation in larger studies, our results clarify neuromodulatory vs training-induced effects and indicate a possible window of opportunity for contralesional inhibitory stimulation interventions in post-stroke aphasia. NORTHSTAR trial registration https://clinicaltrials.gov/ct2/show/NCT02020421 .

Background: 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. Methods: Here, we applied a depth of coverage approach to detect CNVs in 80 genes previously associated with neurodegenerative disease within participants of the Ontario Neurodegenerative Disease Research Initiative (n = 519). Results: In total, we identified and validated four CNVs in the cohort, including: (1) a heterozygous deletion of exon 5 in OPTN in an Alzheimer's disease participant; (2) a duplication of exons 1–5 in PARK7 in an amyotrophic lateral sclerosis participant; (3) a duplication of >3 Mb, which encompassed ABCC6, in a cerebrovascular disease (CVD) participant; and (4) a duplication of exons 7–11 in SAMHD1 in a mild cognitive impairment participant. We also identified 43 additional CNVs that may be candidates for future replication studies. Conclusion: The identification of the CNVs suggests a portion of the apparent missing heritability of the phenotypes may be due to these structural variants, and their assessment is imperative for a thorough understanding of the genetic spectrum of neurodegeneration.

Although previously thought to be asymptomatic, recent studies have suggested that magnetic resonance imaging-visible perivascular spaces (PVS) in the basal ganglia (BG-PVS) of patients with Parkinson's disease (PD) may be markers of motor disability and cognitive decline. In addition, a pathogenic and risk profile difference between small (≤3-mm diameter) and large (3-mm diameter) PVS has been suggested.The aim of this study was to examine associations between quantitative measures of large and small BG-PVS, global cognition, and motor/nonmotor features in a multicenter cohort of patients with PD.We performed a cross-sectional study examining the association between large and small BG-PVS with Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts I-IV and cognition (Montreal Cognitive Assessment) in 133 patients with PD enrolled in the Ontario Neurodegenerative Disease Research Initiative study.Patients with PD with small BG-PVS demonstrated an association with MDS-UPDRS Parts I (P = 0.008) and II (both P = 0.02), whereas patients with large BG-PVS demonstrated an association with MDS-UPDRS Parts III (P 0.0001) and IV (P 0.001). BG-PVS were not correlated with cognition.Small BG-PVS are associated with motor and nonmotor aspects of experiences in daily living, while large BG-PVS are associated with the motor symptoms and motor complications. © 2022 International Parkinson and Movement Disorder Society.

The Ontario Brain Institute's “Brain-CODE” is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).

Type 2 diabetes mellitus (T2DM) is an important risk factor for dementia. The possibility to mitigate this risk by controlling T2DM is compelling; however, different glucose-lowering drugs have different effects on the brain by virtue of their different mechanisms of action. The clinical and epidemiological data appear mixed, warranting careful critical evaluation of the human studies. Here we examine the evidence in the context of dementia prevention and treatment, both for people with and without T2DM. We discuss the evidence on this scaffold of research directions, identifying methodological complexities in the extant literature (e.g. comparator discrepancies, changes in the therapeutic landscape), and the implications of different outcome measures (e.g. neuropsychological). We consider possible implications of cerebrovascular protection vs. effects on progression of neurodegenerative proteinopathy, and we present a research roadmap for glucose-lowering drugs in cognitive neurology, including neuroimaging, and fluid biomarkers. We conclude that there is great potential to advance personalized strategies to prevent and treat dementia with glucose-lowering drugs.

Disability is common across Alzheimer's disease (AD) and dementia with Lewy bodies (DLB). White matter hyperintensities (WMHs) are prevalent in both diagnoses and associated with disability; both diagnoses show neuropsychiatric symptoms (NPS) and impaired cognition.In AD and DLB, we examined if WMHs, NPS, and cognition associate with basic and/or instrumental activities of daily living (BADLs and/or IADLs) cross-sectionally, and longitudinally over ≈1.4 years.Across both diagnoses, NPS were not only associated with greater disability in performing both BADLs and IADLs, but were also associated with a decline in the ability to perform BADLs in the AD group. In the DLB group only, higher WMH volume was associated with greater disability in performing both BADLs and IADLs, and was associated with a decline in the ability to perform BADL over time.Management of NPS and WMHs, particularly in DLB, might help maintain functionality in dementia patients for longer.

The thalamus is a key brain hub that is globally connected to many cortical regions. Previous work highlights thalamic contributions to multiple cognitive functions, but few studies have measured thalamic volume changes or cognitive correlates. This study investigates associations between thalamic volumes and post-stroke cognitive function.Participants with non-thalamic brain infarcts (3-42 months) underwent MRI and cognitive testing. Focal infarcts and thalami were traced manually. In cases with bilateral infarcts, the side of the primary infarct volume defined the hemisphere involved. Brain parcellation and volumetrics were extracted using a standardized and previously validated neuroimaging pipeline. Age and gender-matched healthy controls provided normal comparative thalamic volumes. Thalamic atrophy was considered when the volume exceeded 2 standard deviations greater than the controls.Thalamic volumes ipsilateral to the infarct in stroke patients (n=55) were smaller than left (4.4 ± 1.4 vs. 5.4 ± 0.5 cc, p0.001) and right (4.4 ± 1.4 vs. 5.5 ± 0.6 cc, p0.001) thalamic volumes in the controls. After controlling for head-size and global brain atrophy, infarct volume independently correlated with ipsilateral thalamic volume (β= -0.069, p=0.024). Left thalamic atrophy correlated significantly with poorer cognitive performance (β = 4.177, p = 0.008), after controlling for demographics and infarct volumes.Our results suggest that the remote effect of infarction on ipsilateral thalamic volume is associated with global post-stroke cognitive impairment.

White matter hyperintensities (WMHs) are frequently observed on structural neuroimaging of elderly populations and are associated with cognitive decline and increased risk of dementia. Many existing WMH segmentation algorithms produce suboptimal results in populations with vascular lesions or brain atrophy, or require parameter tuning and are computationally expensive. Additionally, most algorithms do not generate a confidence estimate of segmentation quality, limiting their interpretation. MRI-based segmentation methods are often sensitive to acquisition protocols, scanners, noise-level, and image contrast, failing to generalize to other populations and out-of-distribution datasets. Given these concerns, we propose a novel Bayesian 3D convolutional neural network with a U-Net architecture that automatically segments WMH, provides uncertainty estimates of the segmentation output for quality control, and is robust to changes in acquisition protocols. We also provide a second model to differentiate deep and periventricular WMH. Four hundred thirty-two subjects were recruited to train the CNNs from four multisite imaging studies. A separate test set of 158 subjects was used for evaluation, including an unseen multisite study. We compared our model to two established state-of-the-art techniques (BIANCA and DeepMedic), highlighting its accuracy and efficiency. Our Bayesian 3D U-Net achieved the highest Dice similarity coefficient of 0.89 ± 0.08 and the lowest modified Hausdorff distance of 2.98 ± 4.40 mm. We further validated our models highlighting their robustness on "clinical adversarial cases" simulating data with low signal-to-noise ratio, low resolution, and different contrast (stemming from MRI sequences with different parameters). Our pipeline and models are available at: https://hypermapp3r.readthedocs.io.

Background: Differential cognitive trajectories in Alzheimer’s disease (AD) may be predicted by biomarkers from multiple domains. Objective: In a longitudinal sample of AD and AD-related dementias patients (n = 312), we tested whether 1) change in brain morphometry (ventricular enlargement) predicts differential cognitive trajectories, 2) further risk is contributed by genetic (Apolipoprotein E [APOE] ɛ4+) and vascular (pulse pressure [PP]) factors separately, and 3) the genetic + vascular risk moderates this pattern. Methods: We applied a dynamic computational approach (parallel process models) to test both concurrent and change-related associations between predictor (ventricular size) and cognition (executive function [EF]/attention). We then tested these associations as stratified by APOE (ɛ4–/ɛ4+), PP (low/high), and APOE+ PP (low/intermediate/high) risk. Results: First, concurrently, higher ventricular size predicted lower EF/attention performance and, longitudinally, increasing ventricular size predicted steeper EF/attention decline. Second, concurrently, higher ventricular size predicted lower EF/attention performance selectively in APOE ɛ4+ carriers, and longitudinally, increasing ventricular size predicted steeper EF/attention decline selectively in the low PP group. Third, ventricular size and EF/attention associations were absent in the high APOE+ PP risk group both concurrently and longitudinally. Conclusion: As AD progresses, a threshold effect may be present in which ventricular enlargement in the context of exacerbated APOE+ PP risk does not produce further cognitive decline.

Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Supplementary Information: Additional file 1 of A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study; Additional file 2 of A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study; both files are available online at https://doi.org/10.1186/s13024-021-00499-4 Copyright © The Author(s) 2021. Background: A detailed understanding of the pathological processes involved in genetic frontotemporal dementia is critical in order to provide the patients with an optimal future treatment. Protein levels in CSF have the potential to reflect different pathophysiological processes in the brain. We aimed to identify and evaluate panels of CSF proteins with potential to separate symptomatic individuals from individuals without clinical symptoms (unaffected), as well as presymptomatic individuals from mutation non-carriers. Methods: A multiplexed antibody-based suspension bead array was used to analyse levels of 111 proteins in CSF samples from 221 individuals from families with genetic frontotemporal dementia. The data was explored using LASSO and Random forest. Results: When comparing affected individuals with unaffected individuals, 14 proteins were identified as potentially important for the separation. Among these, four were identified as most important, namely neurofilament medium polypeptide (NEFM), neuronal pentraxin 2 (NPTX2), neurosecretory protein VGF (VGF) and aquaporin 4 (AQP4). The combined profile of these four proteins successfully separated the two groups, with higher levels of NEFM and AQP4 and lower levels of NPTX2 in affected compared to unaffected individuals. VGF contributed to the models, but the levels were not significantly lower in affected individuals. Next, when comparing presymptomatic GRN and C9orf72 mutation carriers in proximity to symptom onset with mutation non-carriers, six proteins were identified with a potential to contribute to a separation, including progranulin (GRN). Conclusion: In conclusion, we have identified several proteins with the combined potential to separate affected individuals from unaffected individuals, as well as proteins with potential to contribute to the separation between presymptomatic individuals and mutation non-carriers. Further studies are needed to continue the investigation of these proteins and their potential association to the pathophysiological mechanisms in genetic FTD. This study has received support from the Swedish FTD initiative funded by the Schörling Family Foundation. This work was also funded by KTH Center for Applied Precision Medicine (KCAP) funded by the Erling-Persson Family Foundation, grants from Vetenskapsrådet Dnr 529-2014-7504, VR 2015-02926 and 2018-02754, Swedish Alzheimer Foundation, Swedish Brain Foundation, Åhlén foundation, Demensfonden, Stohnes foundation, Gamla Tjänarinnor and Stockholm County Council ALF. Furthermore, support was received by the MRC UK GENFI grant (MR/M023664/1), the Bluefield Project, the JPND GENFI-PROX grant (2019-02248), the Dioraphte Foundation [grant numbers 09-02-00]; the Association for Frontotemporal Dementias Research Grant 2009; The Netherlands Organization for Scientific Research (NWO) (grant HCMI 056-13-018); ZonMw Memorabel (Deltaplan Dementie), (project numbers 733 050 103 and 733 050 813); JPND PreFrontAls consortium (project number 733051042). JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases - Project ID No 739510. M.S. was supported by the JPND grant “GENFI-prox” (by DLR/BMBF to M. S, joint with JDR., J.vS., M.O., B.B. and C.G.). Open Access funding provided by Royal Institute of Technology.

The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW‐ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public‐private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI‐1, ADNI‐GO, ADNI‐2, and ADNI‐3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW‐ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW‐ADNI researchers who shared updates from ADNI‐3 and their vision for ADNI‐4.

Objective: Some features of attention-deficit/hyperactivity disorder (ADHD) may resemble those of mild cognitive impairment (MCI) in older adults, contributing to diagnostic uncertainty in individuals seeking assessment in memory clinics. We systematically compared cognition and brain structure in ADHD and MCI to clarify the extent of overlap and identify potential features unique to each. Method: Older adults from a Cognitive Neurology clinic (40 ADHD, 29 MCI, 37 controls) underwent neuropsychological assessment. A subsample ( n = 80) underwent structural neuroimaging. Results: Memory was impaired in both patient groups, but reflected a storage deficit in MCI (supported by relatively smaller hippocampi) and an encoding deficit in ADHD (supported by frontal lobe thinning). Both groups displayed normal executive functioning. Semantic retrieval was uniquely impaired in MCI. Conclusion: Although ADHD has been proposed as a dementia risk factor or prodrome, we propose it is rather a pathophysiologically-unique phenotypic mimic acting via overlap in memory and executive performance.

Despite the wide application of the magnetic resonance imaging (MRI) technique, there are no widely used standards on naming and describing MRI sequences. The absence of consistent naming conventions presents a major challenge in automating image processing since most MRI software require a priori knowledge of the type of the MRI sequences to be processed. This issue becomes increasingly critical with the current efforts toward open-sharing of MRI data in the neuroscience community. This manuscript reports an MRI sequence detection method using imaging metadata and a supervised machine learning technique. Three datasets from the Brain Center for Ontario Data Exploration (Brain-CODE) data platform, each involving MRI data from multiple research institutes, are used to build and test our model. The preliminary results show that a random forest model can be trained to accurately identify MRI sequence types, and to recognize MRI scans that do not belong to any of the known sequence types. Therefore the proposed approach can be used to automate processing of MRI data that involves a large number of variations in sequence names, and to help standardize sequence naming in ongoing data collections. This study highlights the potential of the machine learning approaches in helping manage health data.

Background: The neuropsychological features of older adults with ADHD are largely unknown. This retrospective chart review aims to elucidate their cognitive trajectories using a case series of six older adults with ADHD presenting with memory complaints to a cognitive neurology clinic, whom we argue are a particularly relevant group to study due to their potential to mimic neurodegenerative syndromes.Methods: Participants were included if they were age 40 or older at intake, had ADHD based on DSM-5 criteria, and had cognitive data collected prior to 2014 with follow-up at least 5 years later.Results: Five men and one woman were included (M = 53.8 years at intake) and had an average of 135.0 months of follow-up data available. Despite notable between- and within-subject variability, cognition generally improved or remained stable across visits. Two participants experienced notable memory decline, but a global consideration of their performance in other domains suggests these deficits may be frontally-mediated.Conclusion: In this small sample, cognition remained generally unchanged across 5–21 years. Isolated impairments likely reflect substantial intra-individual variability across time and measures.

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.

Background Leukotriene receptor antagonists (LTRAs) alleviate Alzheimer’s disease (AD) pathology and improve cognition in animal models; however, clinical evidence is limited. This study aimed to explore the associations between the use of LTRAs (montelukast or zafirlukast) and cognitive performance in people with normal cognition, mild cognitive impairment (MCI), or AD dementia. We hypothesized that LTRA use would be associated with better cognitive performance over time. Methods This longitudinal observational study used data from the National Alzheimer’s Coordinating Center. Within groups of participants with normal cognition, MCI, or AD dementia, LTRA users were matched 1:3 to non-users using propensity score matching. Cognitive domains including immediate and delayed memory (Wechsler Memory Scale Revised-Logical Memory IA and IIA), psychomotor processing speed (Digit Symbol Substitution Test), and language (animal naming, vegetable naming, and Boston Naming Test) were compared between users and non-users in mixed-effects linear or Poisson regression models. Results In AD dementia, LTRA use was associated with a slower decline in psychomotor processing speed, as measured by the Digit Symbol Substitution Test (Β = 1.466 [0.253, 2.678] symbols/year, n = 442), and language, as measured by animal naming (Β = 0.541 [0.215, 0.866] animals/year, n = 566), vegetable naming (B = 0.309 [0.056, 0.561] vegetables/year, n = 565), and the Boston Naming Test (B = 0.529 [0.005, 1.053] items/year, n = 561). Effect sizes were small but persisted after controlling for a 10% false discovery rate. LTRA use was not associated with changes in memory performance in AD, nor was it associated with changes in cognitive performance in people with normal cognition or MCI. In a post hoc analysis, LTRA use was associated with a slower decline in clinical progression in MCI (B = −0.200 [−0.380, −0.019] points/year, n = 800) and AD dementia (B = −0.321 [−0.597, −0.046] points/year, n = 604) as measured by CDR Sum of Boxes. Conclusions The use of LTRAs was associated with preserved function in non-amnestic cognitive domains in AD dementia. The role of leukotrienes and their receptors in cognitive decline warrants further investigation and the leukotriene pathway may represent a target for AD treatment.