bluuebunny/crossref_metadata_2025 huggingface dataset:
Midlife infarct burden and risk of dementia: The Atherosclerosis Risk in Communities Neurocognitive Study
Authors: Sullivan Kevin J , Ghelani Kunali , Rajesh Aishwarya , Shrestha Srishti , Gottesman Rebecca F , Knopman David S. , Mosley Thomas H , Griswold Michael E , Windham B Gwen
Published: December 2021

Background

Imaging‐based markers of cerebrovascular disease are associated with adverse health events, including incident dementia. However, only infarcts ≥3mm are typically considered in clinical and research settings. Recent evidence demonstrates that smaller infarcts in individuals during mid‐life, particularly when co‐occurring with larger infarcts, may be clinically relevant to cognitive decline, incident stroke, and stroke mortality. We aimed to determine if there was a similar compounding of risk for incident dementia among those with both smaller and larger infarcts at midlife.

Method

The ARIC study is a multi‐site longitudinal cohort study which began in 1987. At visit 3 (1993‐95), brain 1.5T MRI scans were completed in 1881 participants with self‐reported Black/White race and no history of stroke (Mean age=62.9±4.9, 40% Male, 50% Black). Infarcts were identified on T2 and proton density weighted images, with smaller infarcts defined as those <3mm and larger infarcts defined as ≥3mm. All participants were followed prospectively for incident dementia using a combination of medical record surveillance, telephone interviews, in‐person assessments, and expert adjudicated dementia status at three in‐person exams (2011‐2013, 2015‐17, 2018‐19). Cox regression was used to determine the association between infarct group [none(referent), smaller only, larger only, both] and incident dementia adjusted for age, sex, education, site‐race, APOE4, and competing risk of mortality.

Result

Among 1881 participants, 539 incident dementia cases were identified over 25 years of follow‐up. 1611 participants were infarct‐free, 50 participants had only smaller infarcts, 185 had only larger infarcts, and 35 participants had both. Compared to those with no infarcts, participants with both smaller and larger infarcts were over 2.5 times more likely to develop dementia [Hazard Ratio(HR)=2.61; 95% Confidence Interval(CI)=1.44, 4.72]. Associations were in similar directions but had wider and indeterminate confidence intervals when comparing the smaller infarcts only (HR=1.22; 95%CI=0.70, 2.13) or larger infarcts only (HR=1.27; 95%CI=0.92, 1.74) to the no infarct group. Of the 35 participants with both smaller and larger infarcts, all but two either died or developed dementia.

Conclusion

A midlife infarct burden including both smaller and larger lesions may represent a vulnerability to dementia beyond the risk conferred by either smaller or larger infarcts alone.
Are developmental learning disorders risk factors for late‐onset Alzheimer's disease?
Authors: Leiman Marina , Guinjoan Salvador Martín , Brusco Luis Ignacio , Villarreal Mirta Fabiana , Fiorentini Leticia
Published: December 2021

Background

Factors associated with early life educational performance can be related to neurodevelopment, cognitive functioning and, consequently, the risk for dementia, but have received less attention than adult biomarkers.

Method

A systematic review of the evidence available up to October 2020 in PubMed and Scopus was carried out. Original articles addressing both developmental learning disorders (LD) and late‐onset neurodegenerative diseases (NDD) were included.

Result

A significant prevalence of LD was found in patients with atypical variants of Alzheimer's disease (AD). Furthermore, an association was found between primary progressive aphasia ‐ logopenic variant and language‐related LD, and also between posterior cortical atrophy and non‐language‐related LD. These results could be explained by the selective vulnerability hypothesis, which states that the vulnerability of a particular brain network or area could predispose both to developmental LD and late‐onset NDD.

Conclusion

Developmental LDs can be considered as risk factors for late‐onset NDD, especially for atypical AD variants. Given the scarcity of results and the limitations reported, a greater number of studies are required, with larger samples and, preferably, of longitudinal design in order to address this issue.
Target populations for behavioral and clinical interventions to protect cognitive function and brain structure: A two‐age, two‐cohort comparison
Authors: Zhang Xuan , Mbangdadji Djass , Gudnason Vilmundur , Launer Lenore J
Published: December 2021

Background

Many multi‐modal lifestyle and cardiovascular risk reduction trials to lower the burden of Alzheimer’s Disease and Related Dementias (ADRD) are on‐going or planned. The optimal target populations for specific interventions are not established. We compared the association of behavioral and clinical risk factors to cognitive and brain MRI outcomes in two target groups from the same source population: an older [late age, LA] non‐demented participants in the Age, Gene/Environment Susceptibility – Reykjavik Study (AGES‐RS; n=4218, 76 yrs. old) and a middle‐aged (MA) cohort of Offspring, (n= 372, 63 yrs. old) to AGES‐RS AD cases.

Method

Outcomes were the Digit Symbol Substitution Test (DSST) and total brain volume (TBV percent of intracranial volume). Protective factors were based on the American Heart Association (AHA) “simple 7”: moderate‐to‐vigorous physical activity (PA;>0 hours/week), no alcohol, no smoking, meeting socially≥1 time/week; low blood pressure (BP;<120/80mmHg), low cholesterol<200 mg/dl), and normal BMI<25kg/m2. Comparisons were made within and between two cohorts using age and sex‐adjusted logistic or linear regression. Between‐cohort effects were tested by an interaction term in the model. P‐values were Bonferroni corrected.

Result

Compared to the LA, MA were significantly more likely to be physically active; among drinkers, consume more alcohol; more likely to smoke; but less likely to be social or have high BP. Cholesterol and BMI levels were similar. As expected, MA compared to LA cohort had a higher DSST and TBV. PA was significantly positively associated with the DSST and TBV (Table 1) in both cohorts; among the active MA, compared to LA, DSST was significantly higher (delta=3.7, p=0.02). In the MA, no smoking, social activity, and normal BMI were associated with better cognition but not to MRI. In the LA, no smoking, alcohol intake, and normal BMI were associated with better cognition and TBV. High cholesterol of MA was significantly associated with better cognition compared to LA (delta=2.9, p=0.02).

Conclusion

The magnitude or directionality of associations varied between cohorts and outcomes, suggesting behavioral or clinical intervention needs to be tailored to specific target groups.
Self‐reported poor sleep accelerates hippocampal volume loss in cognitively normal healthy elderly
Authors: Alperin Noam
Published: December 2021

Background

Poor sleep quality is a known risk factor for the development of Alzheimer’s disease (AD). However, minimal data is available on the rate of brain tissue volume loss related to self‐reported poor sleep. Our previous cross‐sectional study in cognitively normal elderly adults age 60 and over, demonstrated that poor sleepers exhibited significantly smaller volumes, approximately 7%, in the bilateral hippocampi, superior parietal lobules and left amygdala and smaller cortical thicknesses, over 3%, in the right superior frontal, medial orbitofrontal cortices and frontal pole, compared to normal sleepers (Alperin et al, 2019). Current study is a follow‐up longitudinal investigation comparing rates of tissue loss in these brain regions of interest (ROIs) between elderly good and poor sleepers with normal cognition.

Method

Forty‐eight cognitively normal elderly individuals age 60 to 92 years were classified into two groups: 23 normal sleepers with self‐reported Pittsburgh Sleep Quality Index (PSQI) < 5 and 25 poor sleepers with PSQI ≥ 5. The two groups were equivalent in terms of age, gender, years of education and white matter hyperintensity (WMH) load. The volumes and thickness of the ROIs were measured at baseline and at follow‐up scans to assess rates of tissue loss using FreeSurfer software. Rates of tissue loss over 2 years were compared between two groups.

Result

No significant association was found between sleep quality, WMH load and rates of thickness loss. Compared to normal sleepers, poor sleepers exhibited 2.8 times higher rates of volume loss in the hippocampus, and 3.3 times higher rate in the posterior cingulate. Global PSQI at baseline was significantly and negatively associated with rates of volume loss in the right hippocampus (rs=‐0.33) and right posterior cingulate cortex (rs=‐0.47). Scores in verbal memory was negatively associated with rates of volume loss in the right hippocampus (r≥0.388).

Conclusion

Poor sleep quality is associated with significantly accelerated volume loss in the hippocampus and the posterior cingulate cortex in cognitively normal elderly individuals. Intervention for improving sleep quality should be highly considered in cognitively normal elderly adults to delay onset of cognitive impairment and onset of AD.
LifeBio memory's technology advancements for capturing life stories and seeing the whole person
Authors: Sanders Beth , Williams Becky
Published: December 2021

Background

Capturing the complexity of an individual's uniqueness and life experiences is difficult. New technology approaches are needed to simplify the process of knowing the person’s story to improve care and communication.

Method

LifeBio is currently developing a cross‐platform application (tablet, phone, web‐based), called LifeBio MemoryTM for people living with Alzheimer’s Disease or mild cognitive impairment. Utilizing groundbreaking technologies (including artificial intelligence, natural language processing, and speech to text conversions), LifeBio Memory is a novel machine‐learning‐based application that converts speech to text and generates life stories. LifeBio Memory will serve as an interactive tool to cultivate communication between people living with dementia, their family, and professional care partners. The LifeBio Memory application uses a new voice‐based application to prompt and store individuals’ stories, photos, and videos—resulting in a personalized, therapeutic reminiscence experience. Auto‐summarization technology will make a "quick read" version of the story possible; knowing the person improves quality.

Result

Current results show a speech to text conversion accuracy of ∼99% with standard audio captures, and conversion rate accuracy above 90% in multiple voice files, which are the more difficult scenarios. Human parity is considered to be above 94%. LifeBio Memory has the initial automation of the extraction of keywords and phrases that will be utilized to summarize the life story. LifeBio and its research partner, Benjamin Rose Institute on Aging, have recently completed focus groups and people living with Alzheimer's Disease were the first to see, use, and evaluate the new application. Professionals in memory care and family members of people living with dementia were also included in focus groups.

Conclusion

Initial focus groups have evaluated the new LifeBio Memory software. These first focus groups gave valuable feedback on preferences, likes and dislikes, and ease‐of‐use for the application. Including people living with dementia in focus groups (online focus groups during COVID) for technology products like LifeBio Memory has been a valuable experience, and more details on lessons learned and next steps will be shared. NOTE: LifeBio Memory is supported by an SBIR grant from the National Institute on Aging of the National Institutes of Health under Federal Award Identification Number R44AG069566.
Accountable care organizations and preventable hospitalization among patients with Alzheimer’s disease
Authors: Chen Jie
Published: December 2021

Background

System‐level care coordination strategies can be the most effective to promote continuity of care among people with Alzheimer disease (AD); however, the evidence is lacking. To motivate providers to coordinate the care they provide and shift their focus upstream to prevention, major public and private payers are utilizing novel reimbursement mechanisms, like accountable care organizations (ACOs). The objective of this study is to determine if ACOs are associated with lower rates of potentially preventable hospitalizations for people with AD and if hospital ACO affiliation is associated with reduced racial and ethnic disparities in preventable hospitalizations among patients with AD.

Method

This study employed a cross‐sectional study design and used 2015 Healthcare Cost and Utilization Project inpatient claims data from 11 states and the 2015 American Hospital Association Annual Survey. This study focused on community‐dwelling adults with AD aged ≥65 years. Logistic regression and the Blinder–Oaxaca decomposition method were used.

Result

African American patients with AD were less likely to be hospitalized at ACO‐affiliated hospitals than White patients. Among patients with AD that were hospitalized, hospital ACO affiliation was associated with lower odds of potentially preventable hospitalizations (OR=0.86, p=0.02; OR=0.66, p<0.001 with propensity score matching) after controlling for patient characteristics, hospital characteristics, and state indicators. Hospital ACO affiliation explained 3.01% (p<0.01) of the disparity in potentially preventable hospitalizations between White and African American patients but could not explain disparities between White and Latinx patients.

Conclusion

As the U.S. population ages, it will become increasingly diverse, as will the population with AD. It is crucial to identify cost‐saving strategies that effectively promote coordination and quality care for this high‐need group, particularly among minorities. This study is the first to provide evidence that ACOs may be effective at preventing PPHs for chronic conditions for people with AD and could reduce racial disparities. Results suggest that future research should explore the impacts of other value‐based payment models on quality of care for people with AD and risk factors as well as the ability of these payment models to reduce disparities.
The Boston Naming Test identifies presymptomatic anomia in MAPT mutation carriers
Authors: Bouzigues Arabella , Russell Lucy L , Peakman Georgia , Convery Rhian S , Greaves Caroline V , Bocchetta Martina , Todd Emily G , Cash David M , Rohrer Jonathan D ,   the Genetic Frontotemporal dementia Initiative (GENFI)
Published: December 2021

Background

Prior studies of prodromal genetic frontotemporal dementia (FTD) have identified impaired executive function and social cognition in C9orf72 and GRN mutation carriers but few cognitive deficits have been found in MAPT mutation carriers.

Method

We investigated performance on the Boston Naming Test (BNT) in the GENetic Frontotemporal dementia Initiative (GENFI) cohort of 499 mutation carriers and 248 mutation negative controls divided across three genetic groups: C9orf72, MAPT and GRN. Mutation carriers were further divided into 3 groups according to their global CDR plus NACC FTLD score: 0 (asymptomatic), 0.5 (prodromal) and 1+ (fully symptomatic). Mutation carrier groups were compared to each other and to mutation‐negative controls using a bootstrapped linear regression model, adjusting for age and education.

Result

We found that all of the symptomatic (1+) groups performed significantly worse on the BNT than controls, and worse than the prodromal and asymptomatic mutation carriers within the same genetic group. The MAPT symptomatic group also performed significantly worse than the GRN and C9orf72 symptomatic groups. Furthermore, both the MAPT asymptomatic and prodromal groups performed significantly worse than controls which was not the case in the other genetic groups.

Conclusion

These results suggest a specific deficit in naming in MAPT mutation carriers consistent with previous literature, likely to be due to impaired semantic knowledge. Notably, this study shows that the BNT can be used to detect very early deficits in the disease course, allowing dissociation of MAPT mutation carriers from controls and from other genetic groups. Clinical trials focused on the prodromal period within individuals with MAPT mutations should use language tasks such as the BNT for patient stratification and as outcome measures.
CSF sphingomyelin metabolites in Alzheimer’s disease, neurodegeneration, and neuroinflammation
Authors: Morrow Autumn Rose , Panyard Daniel J. , Deming Yuetiva , Dong Ruocheng , Vasiljevic Eva , Betthauser Tobey J. , Jonaitis Erin M. , Kollmorgen Gwendlyn , Suridjan Ivonne , Zetterberg Henrik , Blennow Kaj , Hulle Carol A. , Carlsson Cynthia M. , Asthana Sanjay , Johnson Sterling C. , Engelman Corinne D.
Published: December 2021

Background

Several Alzheimer’s disease (AD) metabolomics studies in cerebrospinal fluid (CSF) and plasma identified associations between sphingomyelin metabolites (SMs) and AD. However, the results were inconsistent, potentially due to small sample sizes. They were limited in the AD, neurodegeneration, and neuroinflammation biomarkers available for additional analyses. Leveraging two longitudinal preclinical and clinical AD cohorts with CSF metabolomics data, we analyzed the relationship between CSF SMs and biomarkers and measures of AD (PET Pittsburgh Compound B [PiB], amyloid‐β42/40, phosphorylated‐tau181, phosphorylated‐tau181/amyloid‐β42), neurodegeneration (neurofilament light [NFL], neurogranin, α‐synuclein), and neuroinflammation (soluble triggering receptor expressed on myeloid cells 2 [sTREM2], interleukin‐6 [IL‐6], chitinase‐3‐like protein 1 [YKL‐40]).

Method

We used data from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) and the Wisconsin Alzheimer’s Disease Research Center (ADRC). Participants were aged 45‐91 years with available CSF metabolomics and biomarker data (n = 493 individuals [726 visits]; 44 individuals had diagnosed AD, 40 had mild cognitive impairment [MCI], and 409 were cognitively unimpaired). CSF biomarkers were measured with the Roche NeuroToolKit assays, a panel of automated robust prototype immunoassays. Associations between 12 SMs and MCI and AD diagnoses were analyzed using logistic regressions. Cross‐sectional global amyloid burden in the brain, measured by PiB‐PET, was regressed on the SMs using linear regression models. The nine other longitudinal CSF biomarkers for AD, neurodegeneration, and neuroinflammation were regressed on SMs using linear mixed models. All models were adjusted for sex and age. A Bonferroni correction (p<3.47×10‐4) was used to determine statistical significance.

Result

No SMs were significantly associated with MCI or AD diagnosis (Table 1) or amyloid markers (Table 2). Phosphorylated‐tau181 was significantly, positively associated with six SMs. NFL and neurogranin were significantly, positively associated with 11 SMs. α‐synuclein was significantly, positively associated with 6 SMs (Table 3). sTREM2 and YKL40 were significantly, positively associated with 9 and 5 SMs, respectively (Table 4). Stearoyl SM had the strongest association for each set of SM‐biomarker regressions.

Conclusion

Associations between SMs and biomarkers of neurodegeneration and neuroinflammation, but not markers of amyloid or diagnoses of MCI or AD implicate SMs as potential biomarkers for neurodegeneration and neuroinflammation that may not be AD‐specific.
Properties of the cognitive function battery for the MIND diet intervention to prevent Alzheimer’s disease
Authors: Krueger Kristin R. , Dhana Klodian , Aggarwal Neelum T. , Arfanakis Konstantinos , Carey Vincent , Sacks Frank , Barnes Lisa L.
Published: December 2021

Background

Over the last several years, evidence has increasingly demonstrated the strong potential for dietary interventions to improve cognitive function over time. Nonetheless, our ability to measure this progress is limited by variability in cognitive assessments across studies. We evaluated the properties of the cognitive battery used in The MIND Diet Intervention to Prevent Alzheimer’s Disease. The MIND Diet Intervention is a randomized control trial designed to examine the efficacy of the MIND diet to slow cognitive decline and reduce brain atrophy in older adults at risk for Alzheimer’s dementia.

Method

Participants were 604 adults between 65 and 84 years old without cognitive impairment, who had a body mass index > 25 k/m2, a family history of dementia and a suboptimal diet. They had an average of 17 years of education and were mostly white (89%) women (65%). Before randomization into one of two dietary intervention counseling sessions, participants completed an in‐person administration of the MIND cognitive battery of tests. The battery included 12 cognitive tests, measuring the four cognitive domains of executive function, perceptual speed, episodic memory, and semantic memory. We conducted a principal component analysis to examine the consistency between our theoretical domains and statistical performance of participants on each domain. In order to further establish validity of each domain, we regressed the domain scores against the covariates of age, and years of education, and late life cognitive activity.

Result

Four factors emerged in the principal component analyses that were similar to the theoretical domains. Rand’s statistic was 0.82 (p<0.001), indicating a good fit between the factor analytic results and the hypothesized grouping. In regression analyses, we found the expected associations with age and late life cognitive activity with each of the four cognitive domains.

Conclusion

These results suggest that the MIND cognitive battery is a comprehensive and efficient battery, which may perform well as an outcome measure in future intervention trials for older adults.
The association between brain‐derived neurotrophic factor and improved cognition in mild cognitive impairment and Alzheimer's disease patients in an exercise‐primed transcranial‐direct current stimulation study
Authors: Koo Grace KY , Herrmann Nathan , Gallagher Damien , Rapoport Mark , Charles Jocelyn , Papneja Purti , Rajji Tarek K. , Andreazza Ana C. , Oh Paul I. , Marzolini Susan , Kiss Alex , Swardfager Walter , Liu Celina , Vieira Danielle , Kim Doyoung , Song Bing Xin , Lanctôt Krista L.
Published: December 2021

Background

Brain derived neurotrophic factor (BDNF) has been associated with cognitive decline in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Transcranial direct current stimulation (tDCS), a non‐invasive brain stimulation, has been found to improve cognitive functions in AD/MCI, particularly after priming. While the mechanism of tDCS response remains unclear, BDNF has been proposed to be involved with the beneficial effects of tDCS. However, few studies have investigated the direct relationship between cognition and BDNF in individuals receiving tDCS. With data from an ongoing clinical trial (the EXPRESS study), we examined the relationship between BDNF and changes in cognition before and after intervention in individuals with MCI/mild AD.

Method

Participants completed a 5‐week, blinded, randomized trial investigating the effects of exercise priming on tDCS. The Montreal Cognitive Asssessment (MoCA), to assess global cognition, was administered and blood samples were collected to quantify serum BDNF at baseline and endpoint visits. Baseline BDNF concentrations were log‐transformed prior to analyses. A Pearson’s partial correlation was used to assess the relationship between baseline BDNF and change in MoCA (ΔMoCA) over time across all participants.

Result

In 18 participants (10 males [55.6%], mean [±SD] age 73.9±8.5 years, education 17.1±2.0 years, and baseline MoCA score 21.5 ± 3.5), mean baseline BDNF concentration was 116.0 ± 40.9 (ng/mL). A Pearson’s partial correlation, controlling for age, showed a significant positive correlation between baseline BDNF concentrations and ΔMoCA score over time (rpartial(15) = .517, p = 0.034).

Conclusion

Higher baseline BDNF levels were correlated with greater improvement in global cognition over time in MCI/mild AD patients. This finding contributes to current literature that suggests BDNF as a therapeutic target in AD treatment. Further analyses upon unblinding will be done to evaluate the predictive capacity of baseline BDNF concentrations on cognitive improvement across treatment groups.
Acceptability of an online training program for dementia caregivers: Results from a mixed‐methods pilot randomized controlled trial
Authors: Teles Soraia , Paúl Constança , Ferreira Ana ,   Center for Health Technology and Services Research (CINTESIS)
Published: December 2021

Background

iSupport is an online knowledge and skills training program developed by the World Health Organization to prevent and/or minimize caregiving‐associated health problems. iSupport was culturally adapted to Portugal.

Method

A mixed‐methods two arm RCT was carried. Participants were recruited through the Alzheimer’s Association. Inclusion criteria are being a non‐paid caregiver; for at least six months; experiencing a clinically relevant level of burden (≥ 21 on ZBI) or depression or anxiety symptoms (≥ 8 on HADS). Eligible participants were randomized to either iSupport‐Portugal or the control arm (e‐book). Repeated measurements were collected at baseline, three (T1) and six months after baseline. Semi‐structured interviews were conducted. Usage data until T1 was extracted from iSupport’s platform. A content analysis was performed for interview data.

Results

Forty‐two participants were allocated to the intervention (n=21) and control (n=21) arms. Caregivers in the intervention arm are mostly female (81%), middle‐aged (M 49 years) and highly educated (M 15.8 years of schooling). Most (81%) are children of the person with dementia, provide long‐term (Mdn 3 years) and intensive care (Mdn 29 hrs/week). Scores on ZBI (Mdn 38) and HADS‐anxiety (Mdn 12) suggest moderate to high levels of burden and anxiety. Positive attitudes towards online psychoeducation were revealed (Mdn 24 on OPI‐BAS scale). Twelve caregivers were interviewed, including dropouts. At T1, 85.7% of participants have used the program; 38.9% discontinued its use within two weeks, 66.7% within ten. On average, iSupport was accessed 8 times and 12.5 lessons were visited (in 23). One‐time‐only visitors printed the lessons (n=2); offline use is possible. Lessons on communication and shared decision making were the most visited (>90%). The qualitative data informs on the motivations and deterrents to use iSupport, usage styles, and perceived results.

Conclusion

A moderate acceptability of iSupport‐Portugal is suggested and might be improved with minor content and interface adjustments. Despite heterogeneous usage patterns, iSupport was mostly used intensively and during a few weeks. Conducting a re‐assessment (T1) earlier might be adequate. When nationally releasing iSupport, research on usage data must consider potential biases from unknown offline use. This pilot may inform improvements on iSupport country‐specific versions.
Longitudinal evaluation of total tau and physical activity on cognitive decline in a population‐based study
Authors: Desai Pankaja , Evans Denis A. , Dhana Klodian , Aggarwal Neelum T. , Wilson Robert S. , Rajan Kumar B.
Published: December 2021

Background

Little is known about the longitudinal relationships of physical activity (PA) and serum total tau (tau) on cognitive decline. We examined if PA moderated the association of tau and cognitive decline in a biracial, population‐based sample of older adults.

Method

We studied 1,159 participants in the Chicago Health and Aging Project (CHAP), who provided blood and completed neuropsychological tests of episodic memory, perceptual speed, and the Mini‐Mental State Examination (MMSE). A standardized global cognitive function test score was computed using individual tests. Self‐report PA was categorized into three groups‐ No PA (responded to at least four of five specified activity items and reported no activity for all responses), low PA (< 150 minutes/week), and high PA ( > 150 minutes/week). Tau concentrations were measured by ultrasensitive immunoassay and classified as low (<0.40 pg/mL) and high (>0.40 pg/mL).

Result

The average age of study participants (63% females and 60% African Americans) was 77 years, with a mean education of 13 years. After adjusting for demographic characteristics and APOE‐ε4 allele, among participants with high tau concentrations, the rate of cognitive decline for participants with high PA (β= ‐0.047, 95% CI= ‐0.067, ‐0.027) was 70% slower than for participants with no PA (β= ‐0.080, 95% CI= ‐0.101, ‐0.058). Similar associations were observed for individual cognitive tests. Specifically, comparing participants with high PA to no PA among those with high tau concentrations, the rate of annual decline in episodic memory was slower by 92%, perceptual speed by 62%, and MMSE by 80%. Among participants with low tau concentrations, high PA (β= ‐0.035, 95% CI= ‐0.052, ‐0.019) was associated with a 77% slower cognitive decline in annual rate compared to no PA (β= ‐0.046, 95% CI= ‐0.066, ‐0.026). Individual tests of those with low tau concentrations showed the annual rate of decline in episodic memory was slower by 76%, perceptual speed by 78%, and MMSE by 68% for high versus low PA.

Conclusion

PA significantly slowed cognitive decline in participants with high and low concentrations of tau. These findings may inform the development of prevention trials tailored to at‐risk characteristics with long‐term follow‐up measurement.
Electrophysiological disruptions and cerebrospinal fluid biomarkers in mild cognitive impairment patients
Authors: Vilca Brenda Chino , Rojo Inmaculada Concepción Rodríguez , Torres Lucia , Cuesta Pablo , Carnes Anna , Piñol‐Ripoll Gerard , Huerto Raquel , Maestú Fernando
Published: December 2021

Background

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder characterized, at the neuropathological level, by the accumulation of amyloid‐β (Aβ) neuritic plaques and neurofibrillary tangles formed by hyperphosphorylated tau protein. A key aspect of AD’s is focused on its early detection. In recent years, cerebrospinal fluid (CSF) has been established as a sensible and validated biomarker that could help to provide an accurate diagnosis of the disease. It is known that lower CSF Aβ‐42 concentrations and higher CSF levels of total and phosphorylated tau (t‐tau and p‐tau respectively), have been extensively replicated parameters among AD patients. Similarly, electrophysiological signatures, as analyzed by the electroencephalography (EEG) technique, seem to be a non‐invasive useful tool for evaluating the progressive loss of efficiency of neuronal networks. Given that, the purpose of this study was to explore the correlation between power EEG values derived from clusters of sensors and CSF markers in a sample of mild cognitive impairment (MCI) patients.

Method

7 MCI participants (aged from 61 to 85) were recruited from the Cognitive Disorders Unit of the Hospital Universitari Santa Maria (Lleida, Spain). All of them underwent a neuropsychological evaluation, CSF lumbar puncture, and EEG recordings.

Result

Amyloid. Male population showed a significant negative correlation (rho = ‐0.754, p < 0.003) between amyloid load and theta power in antero‐posterior regions of the brain. The average power of the cluster correlated significatively with ADAS (rho = 0.562, p < 0.037), total tau (rho = 0.538, p < 0.049) and delayed recall (rho = ‐0.612, p < 0.020). Total tau. A widespread alpha power cluster was found in the male population whose oscillatory activity correlated negatively with t‐tau CSF load (rho = ‐0.653, p < 0.014). When assessing the female population, we found a relationship (rho = ‐0.864, p < 0.001) between total‐tau and beta power in a widespread cluster. Additionally, the beta cluster average power significatively correlated with p‐tau load (rho = ‐0.800, p < 0.005) and age (rho = ‐0.621, p < 0.041).

Conclusion

Electrophysiological activity seems to be depicting a clear sex‐based pattern of associations with neuropathological markers of AD.
Integrating multimodal data to support Alzheimer’s disease target prioritization
Authors: Cary Gregory A. , Gockley Jake , Lehallier Benoit , Leal Karina , Greenwood Anna K , Shulman Joshua M , Longo Frank M , Levey Allan I , Mangravite Lara M , Logsdon Benjamin A , Carter Gregory W
Published: December 2021

Background

The limited success of therapeutics targeting the amyloid hypotheses of Alzheimer’s Disease (AD) suggests the need to examine additional and potentially complementary therapeutic approaches. Recent efforts to amass genome‐scale data from diverse cohorts have revealed thousands of new therapeutic targets and highlighted previously underappreciated molecular and cellular dysfunction associated with disease states. Our understanding of the mechanistic relevance of individual targets and the inter‐relationships of groups of targets remains limited. Here we combine evidence across multiple independent studies to prioritize specific targets for further resource and reagent generation in the Target Enablement to Accelerate Therapy Development for Alzheimer’s Disease (TREAT‐AD) consortium.

Method

We propose a gene‐level scoring method that synthesizes evidence from diverse studies and data modalities. Genetic scores are derived from genome‐wide association studies of large AD cohorts as well as genetic evidence from model systems. Multi‐omic scores combine evidence from transcriptomic and proteomic studies of human post‐mortem brain tissue in the Accelerating Medicine Partnership in Alzheimer’s Disease (AMP‐AD) cohorts. We also use scores based on high‐throughput functional screens in D. melanogaster and scores based on term associations from indexed publications. These subscores from each category are combined in a final target score that is used for target prioritization and hypothesis evaluation.

Result

We have scored over 17,500 targets using these scoring metrics including four pilot hypotheses implicated by recent work in the AMP‐AD consortium. The most significant functional annotations associated with high‐scoring targets include cellular respiration, regulation of trans‐synaptic signaling, neuron death, and activation of immune response. Using the highest‐priority targets within each pilot hypothesis, ten targets were further prioritized for immediate development of resources by the TREAT‐AD consortium.

Conclusion

This prioritization provides an integrative and evidence‐based metric for the assessment of novel therapeutic targets and hypotheses. High‐priority targets will be considered for further assay development, structural biology, and medicinal chemistry studies in the TREAT‐AD consortium. These resources will be openly shared with the research community, which will help to de‐risk the evaluation of understudied candidate targets and therapeutic hypotheses.
Longitudinal study on subjective cognitive complains from patients and informants: Differences between stable and worsening SCD and MCI participants and prediction of cognitive decline
Authors: Pérez‐Blanco Lucía , Felpete Alba , Mallo Sabela C. , Campos‐Magdaleno Maria , Nieto‐Vieites Ana , Lojo‐Seoane Cristina , Facal David , Pereiro Arturo X
Published: December 2021

Background

Subjective cognitive complaints (SCCs) are a risk factor to dementia. Self‐ and informant‐reports may have different predictive validity along the cognitive decline continuum. We aimed to analyze longitudinal differences between self‐ and informant‐reports in stable(‐s) and worsening(‐w) SCD and MCI participants, and the predictive value of these reports on cognitive worsening at different stages of cognitive decline.

Method

A total of 216 participants with SCCs from the CompAS study were longitudinally assessed three times (intervals 18‐24 months). SCD (190) and MCI (26) participants were classified as stable or worsening at the last follow‐up.

SCCs from participants and informants were evaluated through the QAM, and depressive symptoms through the GDS‐15. SCD participants were classified as Low (L‐SCD=119) and High (H‐SCD=71) complainers (below and above 5%ile in self QAM scores).

Mixed‐ANOVAs tested differences between the stable and worsening groups (L‐SCD‐s; H‐SCD‐s; L‐SCD‐w; H‐SCD‐w; MCI‐s; MCI‐w) in the three QAM measurements for participants and informant. Logistic regressions were performed to analyze if QAM scoring of participants and informants at each assessment time predicts worsening.

Results

Significant main effect of Group [F(1,5)=40.15, p< .001, ηp2
=.489] showed QAM self‐reports (Figure 1A) were lower for L‐SCD‐s than for H‐SCD‐s, H‐SCD‐w, MCI‐s, MCI‐w; and higher for H‐SCD‐s than for L‐SCD‐s H‐SCD‐w, MCI‐s, MCI‐w. For QAM informant‐reports (Figure 1B) significant Group*Measurement interaction was found, [F(10,294)=2.91, p=.002, ηp2
=.090] indicating (Bonferroni tests) that QAM‐3 was higher than QAM‐1 and QAM‐2 for MCI‐w; and only QAM‐3 was higher for MCI‐w than for L‐SCD‐s, H‐SCD‐s, and MCI‐s. Covariate GDS‐15 score did not alter the results.

Neither self‐ nor the informant‐reports predicted L‐SCD‐w. Self‐report‐QAM‐2 [β=.300; SE=.088; p=.001; 95%CI=1.35(1.13–1.60)] and informant‐report‐QAM‐3 [β= .314; SE=.119; p=.008; 95%CI=1.36(1.08–1.73)] significantly predicted H‐SCD‐w and MCI‐w [self‐report‐QAM‐2: β=.197; SE=.087; p=.023; 95%CI=1.21(1.02–1.44); informant‐report‐QAM‐3: β=.301; SE=.109; p=.006; 95%CI=1.35(1.09–1.67)].

Conclusions

Cognitive complains from informants increased at the end of follow‐up for SCD and MCI participants who worsened compared to those who were stable, although significance was only achieved for the MCI‐w. Neither the self‐ nor the informant‐report showed predictive validity at baseline assessment. Self‐reports predicted progression earlier (QAM‐2) and informant‐reports later (QAM‐3).
A three‐dimensional neuroimaging based deep learning model to predict Alzheimer’s disease progression for clinical trial design
Authors: Gladstein Scott , Yang Liuqing , Wooten Dustin W , Florian Hana , Huang Xin , Comley Robert A. , Guo Qi
Published: December 2021

Background

In order to detect drug effects, in many instances, it is important to enroll patients in clinical trials whose symptoms will progress within the trial time frame. Here we aim to develop deep learning models combining multi‐modal imaging, demographic, genetic, and cognitive data to identify Alzheimer’s Disease (AD) patients who will progress within 2 years in terms of a change in diagnosis and/or cognition assessed by CDRSB.

Method

Separate models were trained to predict 1) whether a subject will progress from mild cognitive impairment (MCI) to AD, and 2) whether their CDRSB will increase by >=1 within 2 years. 5718 T1 MRI, 1537 [18F]AV45 amyloid, and 1958 [18F]FDG images from ADNI were used for model development. First, convolutional neural networks (CNNs) based on a modified 3D VGG16 architecture (Figure 1) were trained to classify AD vs healthy controls (CN) for the diagnosis model, and CDRglobal=0 vs >=1 for the cognition model using each imaging modality separately. Images from MCIs or subjects with CDRglobal=0.5 at baseline were fed into these pre‐trained CNNs to output probabilities for diagnosis and CDRSB changes respectively. Finally, these CNN‐predicted probabilities were combined with age, APOE4, ADAS13, CDRSB, FAQ, and MMSE at baseline into an ensemble model using “Super Learner” in R to predict diagnosis change or cognitive decline. Model development using tau PET images is ongoing.

Result

For the CNN, using imaging data only, the FDG model best discriminated AD vs CN, or CDRglobal of 0 vs >=1, with AUCs of 0.96 and 0.97 respectively followed by the MRI, and amyloid models. To predict progression, the amyloid CNNs performed best with AUCs of 0.82 and 0.78 for the diagnosis and CDRSB changes respectively (Figure 2). The ensemble model further improved progression predictions with the amyloid PET ensemble model performing best with AUCs of 0.92 and 0.86 for diagnosis and CDRSB change respectively (Table 1).

Conclusion

The development of deep learning models to identify patients who will progress rapidly has the potential to be a valuable tool to support patient stratification, facilitate the design of future AD clinical trials, and treatment planning.
Cognitive functioning in Florida’s oldest old: A successful aging analysis of individuals living over the age of 90
Authors: Anton Stephen , Miller Amber H , Marra David E , Maraganore Demetrius M , Smith Glenn E
Published: December 2021

Background

As our population ages, many individuals are surpassing the age of 90 and living independent lives free of major diseases. It is critical to identify healthy lifestyle and genetic factors that contribute to “Successful Aging” (SA) in the population’s oldest‐old. This pilot study utilizes a unique dataset, the OneFlorida Clinical Research Consortium, to identify and recruit ‘Successfully Aged’ nonagenarians using electronic health records (EHR).

Method

A consensus panel of experts created SA criterion, while taking EHR bioinformatics into consideration, to identify individuals 90 years and older who would be considered “Successful Agers”. To validate this cohort, researchers conducted a three‐phase recruitment period that included two contact letters and a third phone call attempt. Interested participants were screened by telephone and administered the Telephone Interview for Cognitive Status (TICS‐M) and the Geriatric Depression Scale (GDS).

Result

Using OneFlorida and EHR data from the University of Florida Health Systems, 1,901 individuals were identified as a virtual SA cohort. Of the 1,901 identified virtual cohort, 103 participants consented to the study (Mean Age = 92.11; 47.57% Female; 91.26% White). Of these, 18 individuals were excluded due to health conditions not captured in the EHR and thus were not administered the TICS‐M or GDS. Of the 85 participants who were administered the TICS‐M (Mean TICS‐M = 31.45, SD = 5.09), 16 participants scored below the cut‐off of ≤27/50 indicating cognitive impairment, 26 participants fell within the MCI range (28‐31/50), and 43 participants scored in the cognitively normal range (≥32/50). Of the 77 participants who were administered the GDS, 2 participant endorsed significant symptoms of depression (Mean GDS = 1.36, SD = 1.42). Together, this resulted in 69 (67%) participants who completed the full assessment battery and were classified as Successfully Aged.

Conclusion

Utilizing this three‐phase recruitment process, researchers were able to further investigate the demographic characteristic of our “Over 90s” population from the OneFlorida identified cohort. Future research is underway to conduct whole‐genome sequencing and identify a new Over 85 cohort. This study uniquely utilized an EHR registry to identify and assess a population of over 90‐year‐old persons considered SA, living independently and free of cognitive impairment.
The effect of microglial genes on network diffusion of pathology in mouse models of tauopathy
Authors: Anand Chaitali , Maia Pedro D. , Torok Justin , Mezias Christopher , Raj Ashish
Published: December 2021

Background

Misfolded tau and amyloid, the hallmark pathologies of Alzheimer’s disease, undergo “prion‐like” trans‐synaptic transmission along the brain’s anatomic connectivity network (Frost, et al,2010). Our lab has previously shown that Alzheimer’s neuropathology progression is well‐approximated by a network diffusion model (NDM) (Raj, et al,2012). However, other processes in the brain may affect the neuropathology progression by mediating intraregional clearance/amplification and interregional spread. For instance, microglial activation is a common pathological feature of Alzheimer’s disease, with TREM2‐expressing microglia being integral to the inflammatory response. We show here that the NDM can be extended to include effects of microglial mediation of pathology.

Method

We modified the NDM to an extended NDM (eNDM) with additional model parameters related to microglia‐mediated spread/clearance and applied it to the 426×426 region mouse connectome. The eNDM included datasets of longitudinal spatiotemporal tau pathology in PS19 mice, expression levels of five microglial homeostatic signature genes (Cx3Cr1, C1qa, P2ry12, Fcrls, Olfml3) as well as TREM2 and CD33, microglial surface‐markers and phagocytosis regulators (Li, et al,2018). We compared the fits of the NDM to those of the eNDM using each gene individually as well as the first two principal components of spatial gene expression (Lein, et al,2007) after optimizing model parameters using a constrained nonlinear optimization algorithm.

Results

Inclusion of microglial gene expression improved the predictive power of the model beyond that of the NDM (R2=0.46). Using the principal components of gene expression generally provided better model fits than individual genes. Notably, exclusion of TREM2 before performing PCA had a significant effect on model fit (p<0.001, R2=0.5) (Table 1, Figure 1), increasing the values of the optimal diffusion and spread parameters.

Conclusion

Although network spread models capture well the spread of pathology between brain regions, there are other factors that mediate this process. We demonstrated that an eNDM with microglial genes had an improved model fit even after accounting for differences in model parsimony. We also showed that exclusion of TREM2 from the model resulted in higher diffusivity parameter values, thus supporting the biological observation of TREM2‐knockout resulting in increased spread of pathology, putatively by affecting microglial phagocytic potential (Griciuc, et al, 2019).