bluuebunny/crossref_metadata_2025 huggingface dataset:
Higher systolic and diastolic blood pressures are associated with loss of white matter integrity in postmenopausal women of the KEEPS Continuation Study
Authors: Kara Firat , Reid Robert I. , Schwarz Christopher G. , Tosakulwong Nirubol , Lesnick Timothy G. , Zuk Samantha M. , Kendall‐Thomas June , Thostenson Kaely , Reyes Denise A. , Fields Julie A. , Senjem Matthew L. , Min Hoon‐Ki , Lowe Val J. , Jack Clifford R. , Bailey Kent R. , James Taryn T. , Lobo Rogerio A. , Manson JoAnn E. , Pal Lubna , Hammers Dustin B. , Malek‐Ahmadi Michael H. , Cedars Marcelle I. , Naftolin Frederick , Miller Virginia M. , Harman Sherman M. , Dowling N. Maritza , Gleason Carey E. , Kantarci Kejal
Published: February 2022

Background

Elevated systolic blood pressure (SBP) and diastolic blood pressure (DBP) are risk factors for white matter (WM) injury associated with cognitive decline and dementia. White matter hyperintensities (WMH) on MRI, markers of WM injury, increase with aging and are more common in women than in men after the age of 60. We examined SBP and DBP in relation to WMH volume and diffusion MRI measures of WM integrity in postmenopausal women.

Method

Women (n=144) with median age of 67 (range 58‐72) and of good cardiovascular health who were previously enrolled in the multi‐site randomized clinical trial, Kronos Early Estrogen Prevention Study (KEEPS), participated in the present observational KEEPS Continuation Study. SBP, DBP, and MRI data were collected approximately 9 years after the end of KEEPS menopausal hormones versus placebo 4‐year interventions. WM integrity was assessed with WMH volume measurements (log transformed) on structural MRI and with measures of WM microstructure on diffusion MRI. Multiple linear regression analyses, adjusted for age, were used to test for associations of SBP and DBP with MRI measures.

Result

The median SBP was 128 (range 86‐180) and DBP was 77 (range 47‐106). Higher SBP (r=0.332;p=0.015) and DBP (r=0.346;p=0.007) were associated with higher WMH volumes. Among the WM tracts, higher SBP was associated with lower fractional anisotropy (FA) in lateral orbitofrontal gyrus WM (r=0.198;p=0.039) and sagittal stratum (r=0.226;p=0.043), and higher DBP was associated with lower FA in the superior occipital gyrus WM (r=0.370;p=0.045). Higher SBP and DBP were associated with higher mean diffusivity (MD) in the external capsule [(r=0.311;p=0.007);(r=375;p<0.001)] and the fronto‐occipital fasciculus [(r=0.286;p=0.016); (r=0.303;p=0.008)]. Furthermore, higher DBP was associated with higher MD in the anterior corona radiata (r=0.233;p=0.039), internal capsule (r=0.303;p=0.042), and the middle (r=0.275; p=0.03) and superior frontal gyrus (r=0.269;p=0.03) WM.

Conclusion

Elevated SBP and DBP measurements are associated with greater WM injury in postmenopausal women. In particular, the frontal lobe WM and its connecting tracts may be more vulnerable to elevation in SBP and DBP. Whether BP control reduces the risk for WM injury, a risk factor for dementia, in post‐menopausal women warrants study.
PENSA study for the prevention of cognitive decline in APOE‐ɛ4 carriers with subjective cognitive decline: Baseline preliminary demographic and neuropsychological description of the study population
Authors: Forcano Laura , Soldevila‐Domenech Natalia , Cuenca Aida , Lorenzo Thais , Boronat Anna , Piera Iris , Puig‐Pijoan Albert , Knezevic Iva , Fauria Karine , Molinuevo Jose , de la Torre Rafael
Published: February 2022

Background

In the absence of effective treatments to reverse cognitive deterioration related to Alzheimer's disease (AD), nonpharmacological secondary prevention interventions at early preclinical stages have been found to be a promising strategy to prevent cognitive decline. In this context, the PENSA study, framed within the WW‐FINGERS consortium, is a randomized clinical trial involving cognitively normal elderly individuals with an increased risk of developing AD (meeting subjective cognitive decline, SCD‐plus criteria and being APOE‐ɛ4 carriers). The aim of the study is to evaluate the efficacy of a multimodal personalized lifestyle intervention (dietary and physical activity counseling and cognitive training) combined with a dietary supplement, epigallocatechin gallate (EGCG) in slowing down cognitive decline.

Method

In this work we present the baseline sociodemographic, mood and cognitive characteristics of the already enrolled sample. Cognitive function was measured with the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite (ADCS‐PACC) and adding to this original version the interference score from the Stroop Color and Word Test and the Five Digit Test (ADCS‐PACC‐Plus‐exe). Additionally, the Digit Span, the Boston Naming Test and the Animal Fluency Test were administered. Psychological distress was measured with the Hospital Anxiety and Depression Scale.

Result

On January 2021 the study had enrolled 68 individuals (62% women) with a mean (SD) age of 67.4 (4.6) years and the following APOE genotype: 83% ɛ3/ɛ4, 13% ɛ4/ɛ4 and 4% ɛ2/ɛ4. Most had higher education (66.2%) and 84% were retired (Table 1). Mild and moderate symptoms of psychological distress were present in 14.7% and 23.5% of participants, respectively. The mean (SD) number of cognitive domains affected (memory, concentration, language, visuospatial skills), measured by an ad‐hoc SCD questionnaire, were 2.54 (±0.9). 77.3% of participants referred memory centered complaints. Considering the different domains, participants reported alterations on memory (97.1%), concentration (73.5%), language (67.6%) and visuospatial skills (11.8%). SCD profiles are shown in Figure 1. Table 2 shows the ADCS‐PACC‐Plus‐exe scores.

Conclusion

The PENSA study will provide valuable information on the effect of a lifestyle intervention supplemented with EGCG to prevent cognitive decline and will aid to share light on the benefit of these strategies in people at‐risk of developing AD.
The role of Alzheimer’s disease pathology in frontotemporal dementia related syndromes
Authors: Cordero Indira Ruth Garcia , Snook Emily , Multani Namita , Taghdiri Foad , Salvo Cristina , Anor Cassandra Jessica , Vasilevskaya Anna , Varriano Brenda Maricela , Misquitta Karen , Tang‐Wai David F. , Trataglia Maria Carmela
Published: February 2022

Background

Corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are two syndromes associated with frontotemporal lobar degeneration (FTLD) with heterogeneous presentation and progression. Co‐pathology of FTLD and Alzheimer’s disease (AD) has been described and could influence the clinical presentation of CBS and PSP. The goal of this study is to evaluate the role of AD pathology in CBS and PSP, by analyzing functional and structural neuroimaging and memory performance.

Method

Patients with a clinical diagnosis of PSP and CBS (n=15) and AD (n=18) underwent functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). Patients were separated according to AD biomarker positivity (CBS‐PSP‐AD, n=6) and negativity (CBS‐PSP‐noAD, n=9) based on the presence of AD biomarkers in cerebrospinal fluid. FMRI images were preprocessed to assess connectivity differences in the default mode network (DMN). DTI was analyzed to trace the bilateral superior longitudinal fasciculus (SLF) and extract its fractional anisotropy and mean diffusivity. Verbal learning and memory were assessed with the California Verbal Learning Test (CVLT‐II) and the Consortium to Establish a Registry for Alzheimer’s disease (CERAD) of the Toronto Cognitive Assessment, and the z‐scores were compared between groups.

Result

The DMN showed reduced functional connectivity in the groups with AD biomarker positivity (CBS‐PSP‐AD and AD patients) relative to the CBS‐PSP‐noAD group. Specifically, reduced connectivity was observed between the left angular gyrus and the left (T(23) = ‐4.02, p‐FDR= 0.02) and right (T(23) = ‐3.48, p‐FDR=0.04) lateral parietal regions in AD vs CBS‐PSP‐noAD. Reduced connectivity was found between the left angular gyrus, the posterior cingulate cortex (T(11) = ‐4.72, p‐FDR=0.02) and the right hippocampus (T(11) = ‐3.94, p‐FDR=0.04) in CBS‐PSP‐AD vs CBS‐PSP‐noAD. No differences were found in DMN connectivity in AD vs CBS‐PSP‐AD. SLF tractography metrics showed no difference between groups. Both CBS‐PSP‐AD and AD patients had significantly worse delayed memory scores than the CBS‐PSP‐noAD group (post‐hoc p‐FDR=0.01).

Conclusion

There are similarities between AD positive biomarker groups (CBS‐PSP‐AD and AD patients) in functional connectivity and memory scores, with these groups differing from the CBS‐PSP‐noAD patients. These results suggest that pathology can mediate functional connectivity patterns and influence clinical manifestation.
Cognitive training in institutionalized older adults using telecommunication technology during social isolation
Authors: Alves Larissa Scoralich , Menezes Ana Clara Nogueira , Alves Gabrielle Sevidanes , Gonçalves Gabriel Henrique Velozo , de Oliveira Ian Peratelli , Silva Suzana Raquel Duque , Freitas Eduarda Rezende , Barbosa Altemir José , Shigaeff Nadia
Published: February 2022

Background

Since last year the world has faced a pandemic. In Brazil it caused one of the World´s highest rate of death and it is known that the older adults are in the risk group for having worse outcomes of the disease and therefore need to be in strict social isolation. Previous studies have indicated cognitive and mood performance improvement from cognitive training in older adults, but there isn´t enough scientific evidence on the effectiveness of these training performed remotely by telecommunication technology.

Methods

The study was developed with 12 older people from a public long term care institution who completed all the phases of this study. The individuals were included in a group according to cognitive performance: (1) cognitively preserved; (2) mild cognitive impairment; and (3) severe cognitive impairment. They were evaluated through a cognitive and depression assessment tools. The instruments were applied in two moments: before and five months after the cognitive training intervention.

Results

84% were female with a mean age of 78.0±9.3 years and 4.3±4.0 years of schooling (Table 1). There was no significant improvement in cognitive (20.6 ± 6.1 vs. 20.4 ± 7.6, p = 0.86) or mood performance (2.4 ± 1.7 vs. 2.5 ± 1.9, p = 0.80) (Table 2).

Conclusion

Considering the need for social isolation the evaluated older persons were deprived for a long time of contact with family members and other activities at the institution, which could have caused a negative impact on their cognitive performance. The present results could be interpreted as if the remote cognitive training contributed to protect the cognitive performance from worsening. Also, it was only possible to carry out a few sessions of training and maybe, with more sessions, the effect could have shown significant results. The training effect could have been lost because of the time that passed between the end of the intervention and the second assessment in the groups. In addition, there is still no scientific evidence on the effectiveness of remote training as opposed to in person training. Thus, more studies are needed to validate remote cognitive training as an effective strategy.
Neurite density and free water concentration are associated with synaptic density in the hippocampus as assessed through NODDI and [C‐11]UCB‐J PET
Authors: Kohli Akshay , DiFilippo Alexandra H. , Gallagher Rigina L. , Davenport Nancy J. , Betthauser Tobey J. , Johnson Sterling C. , Christian Bradley T. , Bendlin Barbara B.
Published: February 2022

Background

Neurite Orientation Dispersion and Density Imaging (NODDI), derived through multi‐shell diffusion MRI, allows for the estimation of markers pertaining to multiple distinct components of neural tissue microstructure. Lower neurite density index (NDI), lower orientation dispersion index (ODI), and higher volume fraction of isotropic water (Viso), have all been significantly associated with biomarkers of AD pathology, as well as increase diagnostic model predictability. Recent studies employing [C‐11]UCB‐J PET to study synaptic vesicle glycoprotein 2A (SV2A) have found strong reductions in individuals with AD. Here we explore regional associations between cortical tissue microstructure (indexed by NODDI) and synaptic density (measured through [C‐11]UCB‐J PET). We hypothesize that increased NDI and ODI, and decreased Viso will associate with higher [C‐11]UCB‐J binding.

Method

Participants (N=24) included cognitively unimpaired and impaired older adults (Table 1) from the Wisconsin Alzheimer’s Disease Research Center who underwent [C‐11]UCB‐J PET and multi‐shell diffusion MRI. NODDI measures (including NDI, ODI, and Viso) were estimated and [11‐C]UCB‐J binding was quantified by calculating distribution volume ratios (DVR) using SRTM2 with the whole cerebellum as a reference region. Pearson correlations were conducted within Desikan‐Killiany‐derived regions of interest (ROI) including the hippocampus, entorhinal cortex, and parahippocampal gyrus, regions previously associated with altered NODDI metrics and [C‐11]UCB‐J binding in the AD population.

Result

Significant associations were found between [C‐11]UCB‐J DVR and both NDI and Viso in the hippocampus (NDI: r = 0.45, p=0.047; Viso: r = ‐0.46, p = 0.043). A trend was identified between [C‐11]UCB‐J DVR and ODI in the parahippocampus (r = 0.39, p = 0.098). No significant associations or trends were found in the entorhinal cortex.

Conclusion

This preliminary analysis identified associations between increased synaptic density and metrics of cortical tissue microstructure. Both NDI and Viso were correlated with [C‐11]UCB‐J DVR in the hippocampus, indicating dendritic complexity and synaptic density are possibly linked. Future analyses will include more participants, determine whether hippocampal [C‐11]UCB‐J DVR in addition to NODDI may increase diagnostic model predictability, as well as estimate the temporal progression of synaptic and dendritic loss in AD.
The Brain Health Champion study: A health coaching intervention with mobile technology in older adults with mild cognitive impairment or risk factors for dementia
Authors: Krivanek Taylor , McFeeley Brittany , Nicastri Casey M , Babazadeh Demsina , Daffner Kirk R , Gale Seth A
Published: February 2022

Background

There is growing evidence that adherence to brain‐healthy behaviors can reduce the rate of cognitive decline and risk of dementia. We previously demonstrated that a health coaching intervention, including weekly phone calls, facilitated adherence to these lifestyle recommendations in older adults with mild cognitive impairment (MCI) or mild dementia. The current study extends this research by including cognitively normal, at‐risk older adults and adding technologies, including a mobile health platform and wearable fitness trackers, to the health coaching intervention.

Method

Participants, age 60‐79, with MCI or dementia risk factors are being randomized to the Brain Health Champion (BHC) intervention or a counseling and education (CE) control. In BHC, with guidance from a health coach, participants set personalized goals, reinforced by weekly video calls, mobile messaging, one dietitian consult, and 30‐minute in‐person or virtual visits every six weeks. In CE, educational materials sent every six weeks supplement usual care. Changes in physical activity, diet, social/cognitive engagement, neuropsychological test scores, and metrics of behavioral health are being measured over a six‐month intervention period using validated questionnaires, wearable fitness trackers, and photographed food logs. Maintenance of behavior changes is also being assessed six months post‐intervention.

Result

Twenty participants have been enrolled in the study, with five BHC and six CE participants completing it to date. All participants successfully operated the mobile technology by themselves or with caregivers’ assistance. Data trends show that BHC participants had numerically increased scores on neuropsychological tests, cognitive activities, and photographed Mediterranean diet adherence compared to CE participants. Participation in the study, regardless of program, was associated with increased self‐reported Mediterranean diet adherence. Participants also reported enjoying their respective programs. Four of five BHC participants and four of six CE participants said that they would like if their program was implemented into their regular care. All but one participant reported foreseeing their program having a lasting impact on their health and wellbeing.

Conclusion

Older adults with MCI or dementia risk factors are able to manage the requirements of either the BHC or CE program. Trends in the data indicate that the BHC program is particularly well‐suited for promoting adherence to brain‐healthy behaviors.
The use of artificial intelligence and machine learning in the care of patients with dementia: A literature review
Authors: Belam Georgia , Nilforooshan Ramin
Published: February 2022

Background

The question as to how best to help people living with dementia, and their carers, is an ever pressing global health and social care concern. Emerging technologies may have the potential to help with this and we decided to perform a literature review on the existing research.

Objectives

To identify, appraise and synthesise the literature to assess the existing research landscape of the area of machine learning and artificial intelligence, with relation to the care of people with dementia.

Methods

A literature search was conducted, searching the PsychInfo, Medline, PubMed and Embase databases. With the papers identified, we assessed the quality of the research and considered what overall findings there were in the existing literature.

Results

619 papers were initially identified, of which 28 related to the use of AI and machine learning in the care of people with dementia. The papers were divided into categories to show the utility and effectiveness these technologies may have: 1: to alert caregivers and professionals to problems that people with dementia may have 2: to facilitate activities and treatment for people with dementia, both health and social care related 3: to help decide on and plan care for people with dementia 4: to consider the ethical implications of the use of artificial intelligence and machine learning in this patient group

Conclusion

There is a paucity of literature about the use of AI and machine learning in dementia care, but the existing studies show some potential, if used well, for these technologies to be a useful addition to the care of people living well with dementia. In particular there is potential for the use in terms of location sensors which may in the future assist with helping to keep patients safe. As is always the case with technology as applied to medicine, the experience of people living with dementia and their carers must be integral to their development and use.
Automatic prediction of cognitive and functional decline using baseline MRI and cognitive scores
Authors: Shafiee Neda , Dadar Mahsa , Ducharme Simon , Collins Louis
Published: February 2022

Background

Patients in the early stages of AD dementia experience decline in their cognitive abilities at different rates. Accurately predicting the progression rate would enable the enrichment of patient populations in clinical trials. Using the early AD‐related pattern of atrophy and cognitive scores from a baseline visit, we trained a model to predict cognitive and functional decline in early stages of AD.

Method

Data included 312 patients with mild Alzheimer’s disease from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset and were chosen based on amyloid positivity, the Clinical Dementia Rating (CDR=0.5) and the Mini‐Mental State Exam (MMSE, range 24‐30) scores. SNIPE (Scoring by Nonlocal Image Patch Estimator) was used to measure AD‐related atrophy patterns in the hippocampi (HC) and entorhinal cortex (EC) (Coupé et al. 2019). A balanced random forest was used to train models with feature sets including MR‐based z‐scored features (SNIPE scores for HC and EC), and cognitive test scores (Alzheimer’s Disease Assessment Scale (ADAS‐13), MoCA (Montreal Cognitive Assessment), and MMSE) from baseline data. Classifiers were trained using different combinations of features plus age. The classification performance was evaluated based on the measured sensitivity, specificity, and accuracy to predict future functional and cognitive decline (defined as a 2‐point change in CSD‐SB).

Result

Table 1 shows the classification performance of all trained models for two and three year follow up periods. Using hippocampal grading scores in addition to MoCA, ADAS‐13 and MMSE, yields the highest accuracy (76.9%) in predicting cognitive decline at 2 years. Figure 1 shows the ROC curve for two models: One consisting of all cognitive features and the other using both cognitive and MRI features. Comparing results between the classifier using only the baseline cognitive score and the corresponding classifier with the added MRI features showed that for both follow‐up periods, the accuracy of prediction is increased when adding MRI features.

Conclusion

Microscopic changes due to AD pathology that occur in the HC and EC can be used as a feature in a predict the cognitive decline and increase the accuracy of prediction, even at the early stages of the AD trajectory.
The challenges of aging in place for older adults at risk of self‐neglect and expectations regarding smart environments: Perspectives of older adults and their caregivers
Authors: Aboujaoudé Aline , Couture Mélanie , Moreau Maxim , Lussier Maxime , Laliberté Catherine , Bottari Carolina , Giroux Sylvain , Belchior Patricia , Paré Guy , Bier Nathalie
Published: February 2022

Background

Self‐neglect is a behavior found in older adults with cognitive deficits. It manifests through the refusal, or inability, to care for themselves and puts them at higher risk for institutionalization. In Quebec, administrators in home care services are increasingly open to offering smart environments as part of their services to this clientele as it can help identify unfulfilled needs. However, little information is available about the implementation of technology in home care services, including the perspective of this clientele and their family. An embedded case‐study was conducted to provide insight on their perception of obstacles for home care and their expectations of technological solutions.

Method

Through individual interviews, qualitative data regarding the perspectives of older adults at risk of self‐neglect (n = 5) and their caregivers (n = 3) was collected in regard to: 1) current obstacles at home; and 2) expectations toward technology to optimize their functional autonomy. Data was analyzed using the approach of Miles, Huberman and Saldana.

Result

Despite the fact that some older adults (n = 3) presenting self‐neglect perceive themselves as functioning well at home and not needing more help than they already receive from home care service, all older adults (n = 5) perceived risks in their home environment and described difficulties with their memory (e.g. forgetting appointments) and mobility (e.g. falls). Similar difficulties were described by their caregivers, who also perceived some risks with remaining at home due to a deteriorating functional capacity. With respect to technology, it was identified that it could support the autonomy of the older adults in some aspects, but not replace current home services available. Technology also had to be easy to use and learn.

Conclusion

This study suggests that older adults at risk of self‐neglect and their caregivers believe that technology can support aging in place but in combination with other solutions. When implemented, technology should be adapted to the needs, values, and preference of clients and their family, to address as many of the individual’s perceived risks as possible.
Association of enlarged perivascular spaces (ePVS) and MRI markers of small vessel disease (SVD) and neurodegeneration in the Florida Vascular Imaging Phenotypes (FL‐VIP) Study of AD Risk
Authors: Haq Ihtsham U. , Del Brutto Andrade Victor , Goryawala Mohammed , Saporta Anita Seixas Dias , Merritt Stacy S. , Camargo Christian , Agudelo Christian , Ariko Taylor , Dong Chuanhui , Loewenstein David , Duara Ranjan , Rundek Tatjana
Published: February 2022

Background

PVS are fluid filled compartments surrounding small intracerebral vessels. They are conduits for fluid transport, exchange, and waste clearance. ePVS are observed in AD, but their relation to SVD markers and neurodegeneration is unknown. We tested whether ePVS are correlated with markers of SVD but not cortical atrophy.

Method

We analyzed subjects’ brains from the FL‐VIP (comprised of all 1Florida ADRC participants with high quality 3T MRI). ePVS were defined as parenchymal hypo/hyperintensities of <3 mm seen on a single axial T1,T2, or FLAIR section through the basal ganglia (BG) and centrum semiovale (CSO). ePVS were graded as 0 (none), 1 (<10), 2 (11‐20), 3 (21‐40), and 4 (>40). The side with highest ePVS count was graded. BGBG and CSO scores were summed to yield a 0‐8 ePVS total. Generalized linear models were used to estimate ePVS score associations with White‐Matter Hyperintensity Volume (WMHV), silent brain infarcts (SBIs), cerebral microbleeds (CMBs), and mean total cortical thickness. We adjusted for demographics, vascular risk factors and comorbidities, and ApoE4 status.

Result

Of 228 non‐demented participants (mean age 72±8 years; 61% women, 60% Hispanic, mean education 15±4 years, 33% ApoE4 carriers), 59% were hypertensive, 21% diabetic, 66% hypercholesteremic, and 30% obese. Mean VASCom score was 2.3±1.6. 73% of subjects had a total ePVS score >1. Scores ranged from 0‐7 total (mean 2.5±1.4), 0‐4 for BG (mean 1.3±0.7) and CSO (1.2 ±0.9). In unadjusted analyses, total ePVS correlated with WMHV (r=0.46, p<0001), SBI (r=0.17, p=0.009), and CMB (r=0.16, p=0.016). BG ePVS correlated with WMHV, SBI and CMB. CSO ePVS correlated only with WMHV (r=0.32, p=0.002). In multivariable analyses, ePVS correlated with WMHV (β=4.97, p<0.001), SBI (OR=1.36, p=0.027), and CMB (OR=1.43, p=0.019). BG ePVS remained associated with WMHV, SBI and CMB; and CSO ePVS only with WMHV (β=4.70, p=0.039). Total, BG, and CSO ePVS were not associated with cortical thickness.

Conclusion

BG ePVS are highly related to MRI markers of SVD, but not total cortical thickness, and therefore may be considered hallmark features of small vessel disease. CSO ePVS may not have as a prominent role in SVD.
Decreased purine metabolite levels in cerebrospinal fluid of transgenic cerebral amyloid angiopathy rats
Authors: van den Berg Emma , Van Nostrand William E. , Peters Tessa M.A. , de Boer Siebolt , Coene Karlien L.M. , Engelke Udo F.H. , Kuiperij H. Bea , Verbeek Marcel M.
Published: February 2022

Background

Cerebral amyloid angiopathy (CAA) is a major cause of intracerebral hemorrhages and contributes to cognitive decline. The currently applied modified Boston criteria fall short in detecting early‐stage disease and biomarkers to track disease progression are lacking. In the CAA Fluid Biomarker Evaluation (CAFE) study we aim to identify novel CAA‐specific biomarkers. We hypothesize that levels of metabolites in cerebrospinal fluid (CSF) are altered due to amyloid‐β deposits.

Method

High‐resolution liquid chromatography quadrupole time‐of‐flight mass spectrometry was used to analyze metabolite levels in an untargeted fashion (Coene et al., 2018; Peters et al., 2020) in CSF derived from small‐vessel CAA transgenic (rTg‐DI) and wild‐type (WT) rats. Candidate features identified in a discovery study (n=8 WT; n=10 rTg; 6 months old) were validated in larger groups of rats including various ages (n=30 WT; n=29 rTg; 3‐6‐12 months old). Features were annotated based on accurate mass, specific retention time and semi‐quantitative intensity by comparison with reference standard compounds and online database matching.

Result

Of the 48 significantly different features discovered in the pilot, 27 could be validated in the second study. Several features corresponded with reference compounds of metabolites involved in the purine metabolism pathway, which included guanosine, guanine, inosine, xanthine and hypoxanthine. All these levels were significantly decreased in all groups of the rTg rats compared to WT, some progressing with older age (Figure 1). An additional n=605 features were identified with significantly different levels between the various groups. Molecular formulas for other possible interesting features could be computed, whose metabolite identities are currently being confirmed by using standard compounds.

Conclusion

Metabolomics analyses of the CSF of transgenic rats shows promise in discovering novel potential biomarkers for CAA. Using a robust animal model allows us to study biomarkers along the trajectory of disease progression. Our results suggest a global down‐regulation of the purine pathway (Figure 2), a finding previously observed in early‐stage Alzheimer’s disease (Alonso‐Andrés et al., 2017).
Engaging people with lived experience in peer review: Expanding the role of citizen reviewers
Authors: Jaggers Kaitlyn , Badali Jocelyn , Guimond Josée , Sivananthan Saskia
Published: February 2022

Background

Research shows that including the voices of people with lived experience (PWLE) in the full research process ensures that the research is both relevant and meaningful in real‐life contexts. However, operationalizing this in a meaningful way can be challenging, particularly in the context of dementia. Since 2014, the Alzheimer Society of Canada (ASC) has included PWLE in the Alzheimer Society Research Program’s (ASRP) peer review process through the role of the citizen reviewer, however, this has been limited in scope. In 2019, a pilot study expanded this role to a broader panel of citizen reviewers who are equal participants in the peer review process, scoring applications and providing valuable contextual feedback. In 2020, this process was further formalized, allowing greater participation and enhanced engagement.

Method

Qualitative feedback was collected from panelists following the 2019 pilot which demonstrated a collective desire to improve overall engagement while formalizing a systematic process. The data was thematically assessed and used to create several resources to recruit, maintain, and train citizen reviewers as equal and valued participants in the peer review process. This was conducted within the context of the pandemic, in which the full process was adapted to a virtual peer review process.

Result

Data from the 2019 pilot resulted in a four‐step process for recruitment, orientation, and training of citizen reviewers. Semi‐structured interviews were conducted with potential candidates, followed by a comprehensive orientation package, and a virtual orientation session designed for PWLE that included role playing and case studies. Lastly, technical support meetings were created to support the virtual nature of the process. Twenty‐five citizen reviewers were recruited, an increase of 44% participation from the previous year. This, in turn, has led to the creation of a new resource guide for engaging PWLE in peer review, which demonstrates how to operationalize meaningfully engaging and valuing the experiences of people living with dementia.

Conclusion

The pilot and subsequent expansion of the citizen reviewer role has created a new way to operationalize lived experiences within the research funding process. While requiring significant upfront work, the value of real‐life experience in prioritizing research is unparalleled.
Diversity considerations of white matter hyperintensities and connectivity in normal aging and MCI
Authors: Misiura Maria , Igwe Kay , Howell J. Christina , Tannahill Amber , Brickman Adam M. , Turner Jessica A. , Hu William T.
Published: February 2022

Background

Alzheimer’s disease (AD) is twice as likely to occur in African Americans than in Non‐Hispanic Whites. However, current neuroimaging models of AD do not accurately overlay onto the African American profile of this disease. One variable that could contribute to more accurate modeling is the inclusion of vascular factors into models of AD, as African Americans are more likely to have vascular as well as AD. Functional MRI is a widely used method to measure brain activity in individuals with AD. Connectivity in the form of correlated between regions can be used to determine neurological dysfunction. Fronto‐striatal connectivity, while understudied in AD, has shown to be affected by AD and vascular disease. This study attempts to determine if there are connectivity measures that relate to vascular lesions(White Matter Hyperintensities (WMH)) across the disease spectrum, and whether these relationships are uniform across race.

Method

We analyzed data from 88 people (54= NC, 34=MCI). We conducted functional connectivity using DPARSFA toolbox with connectivity calculated between the following fronto‐striatal regions within each hemisphere: anterior putamen, middle frontal gyrus, superior frontal gyrus (putamen output regions), pre‐ and postcentral gyri (putamen input regions). To calculate regional white matter hyperintensity we used in‐house code to overlay a regional atlas onto a WMH mask extracted from a T2 weighted FLAIR image, and assigned a score to each individual representing load (0=no WMH in any regions, 1=WMH in 1 or the other region, 2=present in both regions.

Result

Across race and diagnostic categories, WMH were related negatively to right anterior putamen connectivity to the pre and post central gyri such that as WMH load increased, connectivity also decreased. This relationship continued for connectivity measures between the right anterior putamen and the superior and middle frontal gyri, but only within African Americans.

Conclusion

Fronto‐striatal connectivity did correlate with regional WMH load in a uniform manner across races for cortical input regions to the putamen, and this relationship extended to Africans Americans within cortical output regions. This relationship was identified across diagnostic categories, and could be useful in studies investigating vascular relationships to AD biomarkers.
Dementia, fall risk and routine clinical care: Opportunities to enhance care by incorporation of examiner‐independent analytics — Computerized cognitive evaluation and quantified digital gait analysis including dual tasking
Authors: Rosenfeld Yulia , Kaczmarek Olivia , Chee Jordan , Bumstead Barbara , Zarif Myassar , Anand Bhupinder , Ofori Edward , Gudesblatt Mark
Published: February 2022

Background

Dementia is an encompassing term referring to conditions characterized by progressive cognitive impairment (CI) that impairs ability to function independently and simultaneously results in increased risk of falling. Falls are common and their consequence costly in cognitively impaired individuals. Clinical reports suggest that falls and gait performance during dual tasking (DT) are particularly related to executive function. Additional reports propose that DT gait abilities predict future fall risk and that interventions designed to improve DT will decrease future fall risk. Analysis of DT gait function to non‐DT gait function has been shown to be superior in discerning those at higher fall risk, in comparison to previous measures. Clinically, CI varies in degree and combination of cognitive deficits and gait disturbance but clinician recognition of such varied types/degrees of CI is likely problematic.

Methods

Cross sectional analysis of PwDaD who underwent both validated computerized cognitive assessment battery (CAB) and digital gait analysis in the course of routine patient care and were screened for risk of falls.

Results

120 PwDaD, 57.5% female, average age 74+/‐ 10 years. T‐tests were performed between gait domains scored from PKMAS for PwDaD groups for step length, stride length, stride width, velocity and total double support. All individual gait domains showed a significant change in score for t‐tests performed between preferred walking speed (PWS) and DT gait function (p<0.01). Regression analysis of PwDaD cognitive profile against DT velocity was performed as well. CAB regressions of multiple cognitive domain scores against dual task velocity which were significant included: global summary score, executive function, visuo‐spatial and motor skills’ scores (p<0.05).

Conclusion

The addition of a cognitive factor to gait, i.e. dual task, demonstrates a decrease in gait parameter functions in comparison to PwDaD gait at PWS. Earlier objective patient centric identification of increased fall risk provides clinicians an opportunity to effectively and pre‐emptively intervene to reduce such increased disability consequence and costs associated with this disease related impact.
Comparative analysis of cerebrospinal fluid markers and multimodal imaging in predicting Alzheimer’s disease progression
Authors: Romano Michael F. , Balachandra Akshara , Zhou Xiao , Jadick Michalina , Qiu Shangran , Nijhawan Diya , Chin Sang P. , Au Rhoda , Kolachalama Vijaya B.
Published: February 2022

Background

Cerebrospinal fluid (CSF) levels of p‐tau, t‐tau, and Aβ42 are widely accepted in vivo biomarkers for Alzheimer’s Disease (AD). However, lumbar puncture comes with limitations, including severe infection, headache, bleeding at the site, a lack of spatial information about regions of neurodegeneration, and substantial inter‐lab variability. A less invasive method based on imaging for assessing AD progression can lead to insights on AD subtypes, decrease lumbar puncture‐related morbidity, and lower the psychological burden on misdiagnosed patients.

Method

We developed deep learning models composed of a fully convolutional network (FCN) linked with a multi‐layer perceptron (MLP) to predict the 2‐year risk of AD progression in individuals with mild cognitive impairment (MCI) using T1‐weighted MRI, fluorodeoxyglucose (FDG) PET, and florbetapir (amyloid) PET images, respectively, from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (n=328). Images were all co‐registered within‐subject, normalized to MNI space, and skull‐stripped utilizing SPM‐12 prior to incorporating them in the model. A fusion model incorporating all three imaging modalities was evaluated to utilize the additive benefits of each imaging modality. An MLP utilizing only the above three CSF biomarkers was trained for comparison.

Result

Our FCN‐MLP model trained on FDG data alone achieved the highest accuracy of all three single imaging modality models. The model based on the amyloid scans alone was the most sensitive of all three single modalities, though it was the least specific. The MLP model constructed from CSF biomarkers was more specific than all imaging modalities. The fusion model had the highest accuracy out of all models, comparable sensitivity to the amyloid model, and similar specificity to the CSF model. It also had a higher F1 score than all other models.

Conclusion

Our fusion model predicts AD progression risk with superior accuracy and sensitivity, and a comparable specificity to a model constructed from CSF biomarkers alone. The FCN‐MLP framework could be extended to incorporate non‐invasive features that are easily obtainable in a memory clinic to develop more accurate risk models. Future studies can focus on augmenting the deep learning model performance by including tau‐based PET images as development of more disease specific tau tracers continues to evolve.
Neurochemical levels measured by 1H MR spectroscopy are associated with amyloid‐β and tau deposition in cognitively unimpaired older adults
Authors: Kara Firat , Joers James M. , Deelchand Dinesh K. , Park Young Woo , Przybelski Scott A. , Lesnick Timothy G. , Knopman David S. , Lowe Val J. , Vemuri Prashanthi , Machulda Mary M. , Mielke Michelle M. , Jack Clifford R. , Petersen Ronald C. , Öz Gülin , Kantarci Kejal
Published: February 2022

Background

Proton MR Spectroscopy (1H MRS) provides non‐invasive measurements of alterations in brain biochemistry associated with neuronal and glial abnormalities in neurodegeneration. 1H MRS with along with automated voxel placement (AVP) improves the precision of 1H MRS metabolite measurements. Our objective was to investigate the association of 1H MRS metabolites obtained by the advanced sLASER single voxel 1H MRS protocol with early tau deposition as measured by AV‐1451 PET and Aβ deposition as measured by 11C‐Pittsburgh compound B (PiB) PET in cognitively unimpaired older adults.

Method

Cognitively unimpaired adults with median (range) age of 77 (66, 94) from the population‐based Mayo Clinic Study of Aging (MCSA) participated in the single‐voxel 1H MRS study (n=40). All participants had an MRI, 11C‐PiB and AV‐1451 PET examinations. The posterior cingulate cortex (PCC) and the left hippocampus (LHC) were chosen for the 1H MRS voxel locations because of their vulnerability to early AD pathology. Right hippocampus was not studied due to time constraints of the MR examination. 1H MRS was performed at 3T (Siemens) using an optimized sLASER protocol with AVP. Standardized uptake value ratios (SUVR) were calculated for global cortical and regional (PCC, LHC) PiB and AV‐1451. Associations between log transformed SUVRs and the concentration of MRS‐measured metabolites (µmol/g) were assessed using age‐adjusted Pearson correlations.

Result

The median (range) global PiB SUVR was 1.42 (1.20‐2.81) and AV‐1451 SUVR was 1.20 (0.94, 1.46). In the PCC, higher AV‐1451 SUVR was associated with lower N‐acetylaspartate (NAA) (r=‐0.375; p=0.019) and glutamate (r=‐0.354; p=0.027) concentrations. Higher global PIB SUVR was associated with higher myo‐inositol in the LHC (r=0.361; p=0.039).

Conclusion

Lower levels of NAA, a marker of neuronal health, and the neurotransmitter glutamate are associated with local tau pathology in the PCC, suggesting early neuronal dysfunction in relation to tau accumulation. The association of hippocampal myo‐inositol, a putative glial marker, with the global cortical Aβ pathology suggests that myo‐inositol elevation may be an indicator of neuroinflammatory response to Aβ related pathology.
Automatic identification of MCI progressors significantly reduces the number of subjects in clinical trials
Authors: Shafiee Neda , Dadar Mahsa , Ducharme Simon , Collins Louis
Published: February 2022

Background

Accurately predicting the progression rate in patients with mild cognitive impairment and mild dementia due to AD enables enrichment of trial populations. Here, we evaluate the potential use of our prognostic model (Abstract #54217) as a screening tool for enrichment in clinical trials in early AD.

Method

Data included 312 patients with mild AD from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and were chosen based on the Clinical Dementia Rating (CDR=0.5) and the Mini‐Mental State Exam (MMSE, range 24‐30) scores. We classified subjects into stable and progressive (defined by at least a 2‐point increase in CDR‐SB) using our automatic classification tool. Required sample sizes to detect a reduction in the mean annual rate of cognitive decline based on CDR‐SB score were estimated. We corrected for the annualized decline due to normal aging so as not to overestimate the benefit of enrichment when computing the treatment effect. We estimated and compared sample sizes for two groups of subjects: Using data from the mild AD subjects in the ADNI dataset that fit the selection criteria above (the unenriched group) and using only the subset of those ADNI MCI subjects identified as pMCI using baseline data and the classifier described above (the enriched group).

Result

Figure 1 shows the required sample sizes for different treatment effects for both unenriched and enriched MCI cohorts. Using the unenriched group of MCI subjects, power analysis shows that 1075 subjects are required in a 2‐year (764 subjects for a 3‐year) trial of therapy with a hypothesized 25% effect size (80% power and 5% significance level) to reduce cognitive decline. When using the enriched cohort of MCI subjects, only 279 subjects are required for a 2‐year (373 for 3‐year) trial (solid lines in Fig. 3). These results demonstrate that enrichment using baseline HC, MoCA, ADAS‐13 and MMSE yields a 3.8‐fold decrease in the sample size for a 2‐year study (2.8‐fold decrease for a 3‐year study).

Conclusion

Enriching clinical trial cohorts of subjects in the early stages of AD with a higher chance of functional and cognitive decline will improve efficiency with smaller, faster, less expensive trials.
Effective feature learning of multi‐modal genetic and neuroimaging data for prediction of future conversion to Alzheimer’s disease: A machine learning based study
Authors: Mirabnahrazam Ghazal , Ma Da , Lee Sieun , Popuri Karteek , Cao Jiguo , Wang Lei , Galvin James E. , Beg Mirza Faisal
Published: February 2022

Background

Due to the high dimensionality of Single Nucleotide Polymorphism (SNP) data, current imaging genetic studies of Dementia of Alzheimer’s Type (DAT) usually only select a limited number of candidate SNPs that are reported in the literature, while there might be potentially important AD‐related risk factors in the remaining genes. In this study, we harness a robust feature selection technique that utilizes all available SNPs in the human genome to identify the relevant MRI and genetic features while overcoming feature redundancy.

Method

A total of 543 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) that had both MRI and genetic data available are included in the study. These subjects are divided into seven novel stratified groups [Table 1] based on their longitudinal clinical diagnosis. A subject is categorized as DAT+ if it has a follow‐up diagnosis of DAT, and is categorized as DAT‐ otherwise. We utilize a 2‐stage probabilistic multi‐kernel classifier. In the first stage, using 10‐fold cross‐validation: In each fold we select discriminative features by applying Fisher's Exact test on SNP data and Welch's t‐test on MRI data using subjects in the subgroups with the most certain longitudinal diagnosis (sNC in DAT‐ and sDAT in DAT+). In the second stage, using only the most frequently selected features above, we retrain on 80% of sNC and sDAT, validate on the remaining 20%, and test on subjects in the other subgroups with milder longitudinal diagnosis results.

Result

Our study showed that although genetic features have a lower prediction power than MRI features, combining both modalities can improve the prediction of future conversion to AD. For subjects in pNC group, MRI features fail to indicate potential risk of developing AD while genetic data can accurately identify the risk [Figure 1]. Our feature selection method has successfully identified significant AD risk factors for both modalities.

Conclusion

Our study demonstrated that using effective feature selection methods eliminate the need for heuristic selection of AD‐related genes used for machine‐learning studies for image genetics. Our proposed method reveals genetic risk factors already mentioned in literature as well as some novel risk factors that could advance clinical diagnostics in the future.