bluuebunny/crossref_metadata_2025 huggingface dataset:
The Association between Multimorbidity and Cognitive Decline: A Systematic Review
Authors: Vargas‐González Juan‐Camilo , Stranges Saverio , Speechley Mark R. , Daley Mark J. , Were Jason , Sharma Ishor , Hachinski Vladimir
Published: December 2022

Background

The worldwide population ageing is a major driver for the increasing prevalence of multimorbidity, which is the co‐occurrence/ coexistence of multiple chronic conditions in the same individual. Simultaneously, cognitive decline has become a worldwide burden. Previous research has shown that there might be an association between multimorbidity as a risk for cognitive decline but no systematic review has evaluated this association.

Objective

To quantify the association between multimorbidity and cognitive decline through a systematic review, defining cognitive decline as a change in neuropsychological test scores or clinical diagnosis of mild cognitive impairment or dementia.

Method

We followed the PRISMA guidelines. We searched Medline/Pubmed, EMBASE, PsychINFO, CINAHL, LILACS, Scopus and ProQuest for studies published between January 1996 and May 2021. We evaluated study references for additional studies. We selected studies with a clear definition of multimorbidity, and cognitive decline, defined as cognitive impairment, dementia, or change in cognitive test scores. With one exception, all data were from high‐income countries and largely Caucasian populations. We employed the critical appraisal tools from the Joanna Briggs Institute to assess the risk of bias. We present a narrative data synthesis from each study in conjunction with key design information. PROSPERO register (CRD42020167253).

Result

We initially identified 1433 references, of which 16 studies fulfilled inclusion criteria, and were included; we found three additional studies through studies references. These studies encompassed a total of 90606 participants. Thirteen studies were cohorts, four cross‐sectional and two case‐control designs. Ten studies were population registers, five memory clinics cohorts, two population‐based surveys and one from administrative data. We found a high degree of heterogeneity among studies, driven by the use of multiple definitions of multimorbidity and cognitive decline that precluded a meta‐analysis. In general, all studies noticed an increased risk of cognitive decline or diminishing test scores with increasing accumulation of chronic disease. Future research will need to address a standardized definition of multimorbidity and cognitive decline/scores as well as obtain and evaluate data from low‐ and middle‐income countries.

Conclusion

We found an association between suffering multimorbidity and increasing risk of cognitive decline measured as cognitive test scores or diagnosis of MCI or dementia.
Spectral signatures associated with cognitive aging, APOE4, amyloid‐β and measures of axonal integrity in cognitively unimpaired adults
Authors: Ranasinghe Kamalini G , Casaletto Kaitlin B , Kudo Kiwamu , Lerner Hannah M , Mizuiri Danielle , La Joie Renaud , Miller Bruce L. , Vossel Keith , Kramer Joel H. , Jagust William J. , Rankin Katherine P , Rabinovici Gil D. , Nagarajan Srikantan S
Published: December 2022

Background

Oscillatory brain rhythms are a defining feature of neuronal activity that support cognition in humans. Previous studies that showed associations of spectral changes in individuals who harbor high risk for Alzheimer’s disease (AD) were limited to identify abnormalities within select brain regions defined apriori. Comprehensive whole‐brain spatiotemporal patterns of oscillatory changes associated with cognitive‐aging and with AD risk are only partly known. Our main goals were to understand how frequency specific spectral changes relate to cognitive abilities in normal aging and to identify oscillatory signatures that indicate pre‐symptomatic AD pathophysiological processes in cognitively unimpaired elderly.

Methods

We used magnetoencephalography (MEG) to study the spectral signatures within delta‐theta (2‐7Hz), alpha (8‐12Hz) and beta (13‐35Hz) oscillations, in cognitively unimpaired adults (n=70). Using a partial‐least‐square regression, we correlated spectral patterns to executive, memory, and processing‐speed abilities (n=40). Next, we compared the spectral signatures between amyloid‐β (Aβ)+ vs. Aβ‐ and between APOE‐Ɛ4+ vs. APOE‐Ɛ4‐, in sub‐cohorts evaluated with Aβ‐PET (n=46) and APOE4 (n=65), respectively. In a subset of participants (n=19), we also examined associations between spectral signatures and cerebrospinal fluid (CSF) markers indicating damage to: presynaptic (growth‐associated protein‐43, GAP43); postsynaptic (neurogranin, NG); axonal (neurofilament light chain, NFL), levels.

Results

An age dependent, low‐grade, increase in alpha power and decrease in delta‐theta power were associated with better cognitive performance in memory, executive and processing speed (Figure‐1). APOE4+ individuals showed reduced alpha power within bilateral medial temporal and right precuneus, compared to APOE4‐. Aβ+ individuals showed a dual pattern of alpha change with increased frontal and reduced medial and lateral temporal cortex pattern and a frontally distributed increased delta‐theta power (Figure‐2). Higher CSF‐NFL was correlated with lower alpha power.

Conclusions

Our findings demonstrate that higher alpha power indicates a positive spectral change towards better cognitive health in aging. Importantly, a reduced alpha power signature indicated early neurodegenerative changes, as demonstrated by: (1)Aβ+ individuals and APOE‐Ɛ4+ individuals showing reduced alpha power within the regions known for earliest tau accumulations; (2) lower alpha correlating with higher NFL, which reflects Aβ‐independent neurodegeneration. Collectively alpha signatures may indicate tau related neuropathology with aging and in early AD.
Derivation and evaluation of signatures using plasma β‐amyloid and pTau‐181 for brain amyloid‐β detection
Authors: Devanarayan Viswanath , Dhadda Shobha , Koyama Akihiko , Swanson Chad J , Hampel Harald , Irizarry Michael C , Kramer Lynn D
Published: December 2022

Background

Detection of brain amyloid‐b (Ab) pathology using blood‐based tests would be considerably more convenient for patients, in addition to being a faster and more cost‐effective method for screening and monitoring patients in clinical trials. Using patient screening data from internal clinical trials, we derive signatures for brain Ab detection using plasma Ab42, Ab40, and pTau‐181, and evaluate their performance accuracy in an independent dataset.

Method

Ab42 and Ab40 were measured using immunoprecipitation coupled with LC‐MS/MS by C2N diagnostics in plasma samples from 513 patients at screening and pTau‐181 was measured in plasma samples from 398 patients (n=273 overlap) using Simoa Advantage V2 assay kit (immunoassay) by Quanterix Corp. Over 90% of these patients had mild cognitive impairment (MCI), and approximately 50% had brain Ab pathology based on Florbetapir‐PET visual read.

Signatures using these plasma markers for detecting brain Ab were derived using Bayesian elastic‐net, resampled lasso, and gradient boosting models. Additional signatures were derived for assessing the added value of ApoE4 status, cognitive function scores and brain volumetric measures from magnetic resonance imaging (MRI). Performance of these signatures was assessed via 10‐fold cross‐validation within the training set, and further tested in an independent cohort from ADNI (Alzheimer’s disease neuroimaging initiative).

Result

Using currently available data, signatures derived using plasma Ab42/Ab40 ratio achieved 76% overall accuracy for detecting brain Ab. Similar accuracy was achieved using plasma pTau‐181 alone, which improved to 78% when including Ab42/Ab40, to 80% when adding ApoE4, and to 82% when adding cognitive scores. Inclusion of MRI brain volumetric measures did not improve the accuracy.

When testing in the independent ADNI cohort, 75.7% accuracy was achieved by signatures based on plasma Ab42/Ab40 ratio. Signatures using plasma pTau‐181 alone achieved 75% accuracy, which improved to 78% when combined with Ab42 to Ab40 ratio.

Conclusion

These results demonstrate the potential of blood‐based amyloid/tau signatures as promising patient screening tools for detecting brain amyloid burden in clinical trials and patient care. Results reported here will be refined further prior to final presentation using impending additional data.
Associations between plasma Neurofilament Light Chain (NfL), Sleep Quality and Cognition in individuals with autosomal‐dominant Alzheimer's Disease (ADAD): Findings from the Colombia‐Boston (COLBOS) biomarker study
Authors: Noriega Daisy , Pardilla‐Delgado Enmanuelle , Baena Ana Y. , Londono Natalia , Ramirez‐Gomez Liliana A. , Guzman‐Velez Edmarie , Fox‐Fuller Joshua T , Aduen Paula , Vila‐Castelar Clara , Lopera Francisco , Quiroz Yakeel T.
Published: December 2022

Background

Methods available for in‐vivo diagnosis of Alzheimer's disease (AD) are expensive and invasive. Neurofilament light chain (NfL), a plasma‐based biomarker for neurodegeneration, is a promising marker for early detection in individuals at increased risk. We previously reported that Presenilin1 (PSEN1) E280A carriers have increased levels of plasma NfL relative to non‐carrier family members twenty years before the onset of clinical symptoms. Here, we examined whether baseline levels of plasma NfL predict self‐reported sleep quality and cognition 10 years later in non‐demented PSEN1‐E280A carriers and non‐carriers.

Methods

A total of 51 PSEN1‐E280A carriers (mean age = 30.06, SD = 4.63), including 2 mildly impaired carriers and 49 age‐matched non‐carriers (mean age = 35.55, SD = 6.16) from the Colombia‐Boston (COLBOS) longitudinal biomarker study were included. Participants underwent blood sampling at baseline and completed the Pittsburgh Sleep Quality Index (PSQI), Mini Mental State Exam (MMSE), and memory testing (CERAD Word List) at follow‐up approximately 10 years later. Self‐reported sleep quality was assessed by calculating the PSQI score. Plasma NfL concentrations were measured with a single molecule array (Simoa) method. Linear regressions were used to examine associations among NfL levels, sleep quality, and memory.

Results

There were no group differences, between carriers and non‐carriers, in baseline NfL levels, memory performance, or total PSQI scores (p>0.05). However, carriers had lower MMSE scores than non‐carriers (carriers M=27.90; non‐carriers M=28.47; p = 0.05). Among the entire sample, baseline NfL levels predicted recall scores on the CERAD word list (p = 0.03) and MMSE performance (p = 0.02). Additionally, associations between NfL levels and age trended toward significance (p = 0.06). Sleep quality (PSQI) was not associated with age, memory performance, or NfL levels.

Conclusions

Preliminary findings support the hypothesis that plasma NfL levels may predict memory function and overall cognitive status in ADAD. However, our findings suggest that NfL levels may not be associated with self‐reported sleep quality in individuals in prodromal stages of ADAD. Future work using objective sleep metrics and larger samples across the preclinical/prodromal spectrum will allow a more comprehensive examination of these associations.
Attitudes and Beliefs About Brain Donation Among Black Americans
Authors: Caban‐Holt Allison M , Lloyd Shawnta' , Starks Takiyah D. , Ford Tayla , Adams Larry D. , Haines Jonathan L. , Beecham Gary W. , Beecham Gary W. , Reitz Christiane , Cuccaro Michael L. , Vance Jeffery M. , Pericak‐Vance Margaret A. , Byrd Goldie S.
Published: December 2022

Background

African Americans (AA) are underrepresented in Alzheimer’s disease (AD) brain donation research, making up approximately 2% of brain donations to the National Alzheimer’s Coordinating Center (NACC). The objective of this study is to gain insights into the attitudes of Black∖AA individuals toward brain donation and perceptions of medical research that may hinder or facilitate brain donation.

Method

A 35‐item survey was developed to understand the attitudes and beliefs about brain donation in a sample of AA, using survey items validated in prior investigations. Electronic and paper and pencil surveys were administered in Florida, New York and North Carolina, United States between November 2021‐January 2022. Descriptive analysis of demographic data and was conducted using SAS® software version 9.4.

Result

The racial composition of the 135 respondents was primarily Black/African American (97.58%), with the remaining responses for race as “missing” or “prefer not to answer”. Most respondents were women (73.6%). The majority of respondents report having a positive view about medical research (85.5%), while 72.1% believe that medical researchers can be trusted to protect the interests of participants. Many respondents reported wanting to learn more about AD (93.1%). Whereas, 82.0% report not knowing how researchers use a brain for research, 58.9% report knowing that study of the brain is important for advances in AD. Despite 53.1% of respondents reporting being either unlikely or unsure whether they would donate a loved one’s brain even if that was their loved ones’ wish, only 21.4% of the sample believe that the decision to donate one’s brain is mostly a family decision. Overall, 63.8% of the respondents are either unsure or unlikely to donate their own brain.

Conclusion

Findings suggest that 1) awareness of brain donation research procedures and processes should be focused on whole family education, and 2) increasing knowledge about AD will be fruitful areas for an educational intervention. Including families in the consenting processes will be pivotal in ensuring that brain donation occurs. Results will be utilized to develop a community‐informed educational program for Black communities about AD research and brain donation.
Factors that affect decisions whether to undergo biomarker testing among older adults with mild cognitive impairment and their family members
Authors: Cox Chelsea G. , Salazar Christian R. , Gillen Daniel L. , Grill Joshua
Published: December 2022

Background

Biomarker tests are used in clinical and research settings to identify individuals at increased risk for progression to Alzheimer’s disease (AD) dementia. Little is known about how people with mild cognitive impairment (MCI) and their family members decide whether to undergo AD biomarker testing.

Method

We examined factors that influence the decision to undergo AD biomarker testing among patients recently diagnosed with MCI by dementia specialists at an academic medical center. We provided education on MCI and biomarker testing to patients and their family members, followed by a structured questionnaire with 6 Likert‐type responses to assess the importance of 8 factors on their decision to undergo AD biomarker testing: (1) cost of the test, (2) fears related to testing procedures, (3) opportunity for result to inform diagnosis, (4) concerns that result could influence health insurance, (5) to help instruct future financial and legal planning, (6) to assist with treatment decisions, (7) family opinions around testing, and (8) physician recommendations. We performed Friedman tests to evaluate differences among the factors and subsequent Wilcoxon signed‐rank tests for posthoc pairwise comparisons. Intraclass correlation coefficients (ICC) assessed the level of agreement across factors within dyads.

Result

Among 65 MCI patients enrolled, most were male (66%) and non‐Hispanic White (88%). Their average age was 75 (SD = 8). Among 57 family members enrolled, most were spouses (84%). Two‐thirds of MCI patients (65%, n = 42) did not have or did not know whether they had a previous biomarker test. Of those patients, 55% (n = 23) reported that they would probably or definitely want a biomarker test for AD. We observed 3 factors that rated highest in importance in the decision to undergo testing and were statistically different from the other 5 factors (all pairwise p‐values <0.01): (1) to assist with treatment decisions, (2) physician recommendations, and (3) to instruct future financial and legal planning. These factors had excellent dyadic concordance (all ICCs>0.95).

Conclusion

This is among few studies to assess AD biomarker decision‐making in people with MCI and their family members. We found that a majority are interested in biomarker testing to help inform treatment and planning decisions.
Head‐to‐head comparison between plasma ptau‐217 and Flortaucipir‐PET in amyloid‐positive patients with cognitive impairment
Authors: Mundada Nidhi S. , Thijssen Elisabeth H , Iaccarino Leonardo , Okoye Obiora C , Shankar Ranjani , Soleimani‐Meigooni David N. , VandeVrede Lawren , Lago Argentina Lario , Miller Bruce L. , Teunissen Charlotte E. , Rojas Julio C. , Dage Jeffrey L , Rabinovici Gil D. , Boxer Adam L. , La Joie Renaud
Published: December 2022

Background

Plasma measurements of phosphorylated tau (ptau) have emerged as promising biomarkers for Alzheimer’s disease (AD). Studies have shown strong associations between ptau and tau‐PET that are mainly driven by the difference between amyloid‐positive and amyloid‐negative patients. However, the relationship between ptau and tau‐PET is not well characterized within patients with AD. We conducted a head‐to‐head comparison between plasma ptau‐217 and tau‐PET in patients at the clinical stage of AD and assessed biomarker relationships with demographic and clinical variables.

Methods

Eighty‐seven amyloid‐positive patients (age=66±10, 48% women) with mild cognitive impairment (n=53) or dementia (n=34) underwent structural MRI, amyloid‐PET (11C‐PIB), tau‐PET (18F‐flortaucipir, FTP), Mini‐Mental State Examination (MMSE, with 28 patients having longitudinal measures 1.5±0.7 years after baseline) and blood draw within a year. Mean cortical PET‐Standardized Uptake Value Ratio (SUVR) were extracted using FreeSurfer5.3. Plasma ptau‐217 concentrations were measured using an electrochemiluminescence‐based assay on the Meso Scale Discovery platform.

Results

Ptau‐217 and cortical FTP‐SUVR were strongly correlated (r=0.61, p<.001, Figure 1). Younger age and female sex, but not APOE4, were associated with higher ptau‐217 and FTP‐SUVR (Figure 2). Amyloid‐PET levels were mildly associated with FTP‐SUVR (r=0.26, p=0.02), not ptau‐217 (r=0.10, p=0.36, Figure 2). The relationship between ptau‐217 and cortical FTP‐SUVR was not modified by age, sex, APOE4, or PIB‐PET (interactions: p’s>0.25). In the whole group, ptau‐217 was associated with FTP‐SUVR in temporo‐parietal and dorsal prefrontal cortices (Figure 3A). However, ptau‐217‐FTP association patterns varied with amyloid burden: in patients with moderate amyloid (<97.7 Centiloids), ptau‐217 was more strongly associated with temporal FTP‐SUVR whereas associations were stronger in primary cortices in patient with higher amyloid levels (Figure 3B). Cross‐sectionally, higher ptau‐217 and FTP‐SUVR were independently associated with lower MMSE (Table 1; Figure 4A). In separate mixed effect models, higher baseline ptau‐217 and FTP‐SUVR were associated with more severe longitudinal decline in MMSE (Figure 4B); when both biomarkers were entered in the same model, only FTP‐SUVR remained significant (Table 2).

Conclusions

In amyloid‐PET‐positive patients with cognitive deficits, ptau‐217 and tau‐PET had comparable patterns of association with demographic and clinical variables. However, cross‐modal and clinical associations tended to be stronger for tau‐PET than ptau‐217.
Predicting Amyloid Positivity from Hippocampal and Entorhinal Cortex Volume and APOE Genotype
Authors: Chattopadhyay Tamoghna , Thomopoulos Sophia I , Thompson Paul M
Published: December 2022

Background

Accumulation of brain amyloid – an early indicator of AD – is assessed using PET or CSF samples, but such procedures are highly invasive. There is interest in using less invasive data, such as brain MRI, to predict β‐amyloid (Aβ) positivity, as a precursor to more invasive screening.

Here we assessed different predictive models based on logistic regression, using readily measured indices from T1‐weighted MRI (T1w). We hypothesized that entorhinal cortex measures would outperform hippocampal measures in predicting amyloid positivity, given its role as a cortical area with early amyloid accumulation.

Method

We analyzed T1w from 724 subjects (Table 1) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). One cut‐off, for determining amyloid levels, was used based on PET cortical SUVR uptake (Αβ_1) determined by either mean 18F‐florbetapir (Aβ+ defined as >1.11) or florbetaben (Aβ+ defined as >1.20), normalized by using whole cerebellum reference region. After registering the T1w image to a common template, we split the data into independent training and testing sets. A logistic regression classifier was used, and test performance was assessed using balanced accuracy to compare the different predictive models.

Result

Figure 1 shows classification results from the models. The balanced accuracy was highest (74.9%) for the logistic regression model including both left and right entorhinal cortex volumes, APOE status, age, and sex. This model outperformed models using hippocampal volume as the main imaging predictor (balanced accuracy 70.8%).

Conclusion

Optimal accuracy was obtained when predicting Aβ positivity from brain MRI using entorhinal cortical measures. Future work will test deep learning methods for Aβ prediction based on paired training data, and will use voxel‐based data and features from other imaging modalities, such as diffusion MRI, to predict amyloid status.
TRIAD multi‐dimensional biobank for biomarker discovery
Authors: Stevenson Jenna , Rahmouni Nesrine , Chamoun Mira , Benedet Andréa Lessa , Stevenson Alyssa , Pallen Vanessa , Therriault Joseph , Lussier Firoza Z , Tissot Cécile , Bezgin Gleb , Pascoal Tharick A , Vitali Paolo , Gauthier Serge , Rosa‐Neto Pedro
Published: December 2022

Background

The Translational Biomarkers in Aging and Dementia (TRIAD) is a longitudinal, biomarker‐based cohort designed to study interactions between the pathophysiological processes driving to dementia. Currently, 50 million people worldwide have dementia [1]. PET and MRI imaging have been widely used to assess disease stage, though expensive and not readily accessible [2]. More recently though, breakthroughs in blood‐based biomarkers have proven a useful, available, and more cost‐effective way of evaluating amyloid and tau positivity. The TRIAD Biobank provides a unique framework to study disease stage using blood‐based biomarkers in conjunction with PET and CSF studies. Our cohort allows for validation of novel biomarkers as we simultaneously acquire gold standard second generation imaging acquisitions with full spectrum fluid biomarkers (CSF, saliva, plasma, urine). Importantly, the data acquired is integrated in a database compliant to multi‐dimensional biomarker analysis.

Method

Figure 1 depicts the cohort's banked fluids by diagnostic group. Figure 2 depicts the cohort's banked fluids by sex grouping.

Result

The TRIAD Biobank stores 1,034 blood samples from 655 participants, 658 of these being follow‐up collections. Additionally, cerebrospinal fluid has been collected from 381 individuals accounting for 520 collections in the bank, 812 urine collections from 662 individuals and 591 saliva samples from 432 individuals.

Additionally, the cohort has collected 761 tau PET scans using [18F]MK6240, 644 amyloid PET scans using [18F]AZD4694 and 804 MRI using 3 Tesla.

Conclusion

With dementia being one of the leading, most costly causes of death, the need for early detection, more affordable, less invasive, and more readily available ways to determine disease stage is apparent [2]. The TRIAD multi‐dimensional biobank provides a wealth of resources to discover affordable biomarkers needed for early diagnosis and Alzheimer’s disease prevention.

[1] Patterson, C. 2018. World Alzheimer Report 2018: The state of the art of dementia research, new frontiers. London, England: Alzheimer's Disease International

[2] Gauthier S, Rosa‐Neto P, Morais JA, & Webster C. 2021. World Alzheimer Report 2021: Journey through the diagnosis of dementia. London, England: Alzheimer’s Disease International.
Genetic characterization of a Turkish dementia cohort: a focus on leukodystrophy genes
Authors: Dehghani Nadia , Guven Gamze , Westra Kaitlyn , Gardner Eve , Paquette Kimberly , Gibbons Elizabeth , Hanagasi Hasmet , Lohmann Ebba , Samancı Bedia , Gurvit Hakan , Bilgiç Başar , Bras Jose , Guerreiro Rita
Published: December 2022

Background

Leukodystrophies broadly affect the brain white matter. As such, diseases including cerebral autosomal dominant/ recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL/CARASIL) are included in this group. NOTCH3 and HTRA1 variants are a known cause of CADASIL and CARASIL, respectively. Studies have reported NOTCH3 variants in Alzheimer’s disease, and heterozygous HTRA1 variants in cerebral small vessel disease. Therefore, there is growing evidence of leukodystrophy gene variants in neurodegenerative diseases.

Method

We screened a whole‐exome sequenced Turkish dementia cohort for rare variants in a panel of leukodystrophy genes. Where familial samples were available, we tested for segregation. We also consulted the exome data available from the Turkish Variome to gauge a better estimate of population frequency for candidate variants.

Result

We identified rare variants in leukodystrophy genes in individuals from this Turkish dementia cohort. Variants in NOTCH3 include a known pathogenic gain‐of‐cysteine variant in a family presenting with CADASIL (NOTCH3 p.Arg133Cys); a novel loss‐of‐cysteine variant (NOTCH3 p.Cys65Tyr) in an atypic dementia case, and a novel cysteine‐sparing missense variant (NOTCH3 p.Ala818Thr) in a family with Alzheimer’s disease and mild cognitive impairment.

Conclusion

Considering the increased consanguinity of the Turkish population we were expecting to identify bi‐allelic variants in HTRA1 with potential roles in disease. Instead, NOTCH3 presented a higher burden of variability, including known and novel variants expected to be involved in disease.
Plasma Amyloid‐β 40 as a Potential Biomarker in Cerebral Amyloid Angiopathy
Authors: Lee Jin San , Park Key‐Chung , Rhee Hak Young , Hwang Kyo Seon
Published: December 2022

Background

We aimed to analyze plasma amyloid‐β (Aβ) using a highly sensitive nano‐biosensing platform to demonstrate the possibility of precise cerebral amyloid angiopathy (CAA) diagnosis in participants classified according to amyloid PET positivity and the neuroimaging criteria for CAA.

Method

A total of 25 normal controls (NC) and 19 patients with Alzheimer’s disease (AD), which were further classified into the CAA− and CAA+ groups according to the modified Boston criteria were recruited in this study. All participants underwent plasma Aβ analysis using a highly sensitive nano‐biosensing platform, amyloid PET scanning, and detailed neuropsychological testing.

Result

The average signal levels of plasma Aβ42/40 differed significantly between the NC and AD groups, and the CAA+ group exhibited significantly higher plasma Aβ40 signal levels than the CAA− group in both NC and AD groups. The concordance between the plasma Aβ40 signal level and the neuroimaging criteria for CAA was nearly perfect. Higher plasma Aβ40 signal levels were significantly associated with the presence of CAA based on the regression analyses, and the neuroimaging pattern analysis partly supported this result.

Conclusion

Our findings suggest that measuring plasma Aβ40 using a highly sensitive nano‐biosensing platform could be a useful non‐invasive diagnostic method for detecting CAA.
Translational potential of JAX humanized‐APOE mice model: Accelerated midlife endocrine aging in hAPOEε4/4 females
Authors: Wang Tian , Mao Zisu , Delatorre Nicole , Wiegand Jean‐Paul L. , Brinton Roberta Diaz
Published: December 2022

Background

Age, female sex and APOEε4 genotype are the greatest Alzheimer’s (AD) risk factors, with a stronger APOEε4 link to AD in women. The APOE‐sex interaction is also evident in hAPOE mouse models where APOEε4 induces more severe neurodegeneration and cognitive deficits in female mice. However, the mechanisms by which these two risk factors converge to disrupt brain function remain elusive.

Method

To investigate effect of APOE genotype on midlife endocrine aging, 6‐, 9‐ and 15‐month hAPOEε3/3 and hAPOEε4/4 female mice were stratified into 3 different endocrine aging groups based on vaginal cytology profiles: regular cyclers (consistent 4–5 day cycles), irregular cyclers (of 6–9 day cycles), and acyclic (no cycling >9 days). Plasma levels of metabolomic makers were measured. Brain mitochondrial function was quantified.

Result

hAPOEε4/4 females exhibited accelerated endocrine aging evidenced by increased magnitude of brain metabolic defect coupled with inability to mount an adaptive bioenergetic response. Systems biology of endocrine aging initially identified in perimenopausal rat model were replicated in the hAPOEε3/3 mouse model. In contrast, hAPOEε4/4 females exhibited accumulation of adipose tissue with high plasma triglyceride and accelerated ketone body dysregulation during perimenopausal transition, indicating deficits in adaptive metabolic response required for sustaining brain metabolic demand during aging. Further, hAPOEε4/4 females exhibited greater perimenopause‐ and menopause‐induced brain mitochondrial dysfunction.

Conclusion

Outcomes of these analyses provide a plausible mechanistic pathway underlying the greater risk of AD in APOEε4 females. Further, these data indicate that the bioenergetic crisis underlying metabolic reprogramming in brain are greater in the APOEε4 female brain while compensatory adaptive responses are compromised. These findings provide a rational mechanistic precision medicine approach to intervene during midlife to prevent or delay the onset of the prodromal / preclinical stage of AD.

This work was supported by NIA grants P01‐AG026572 Project 2 to RDB and Animal Core to TW.
PPA Tele‐Savvy: Piloting an Online Intervention with Care Partners of Persons Living with Primary Progressive Aphasia
Authors: Morhardt Darby , Dyslin‐Kman Deborah Nicole , Maley Kate , Roberts Angela C , Weintraub Sandra
Published: December 2022

Background

Primary Progressive Aphasia (PPA) brings unique challenges for caregiving families. Most evidence‐based interventions available to dementia caregivers do not match their needs for tailored psychosocial support.

Method

This pilot study funded by the Emory University Roybal Center is an adaptation of the evidence‐based on‐line psychoeducation program (Tele‐Savvy) to address the unique challenges facing informal caregivers of those living with PPA and to help these caregivers achieve competence in their role. Using focus group data from PPA caregivers previously enrolled in Tele‐Savvy, the program curriculum was adapted to address caring for persons living with PPA. The intervention consists of seven 90‐minute weekly videoconference sessions with weekly homework, coaching and debriefing sessions. Pre/post measures look at the effects of the program on PPA knowledge, mood, caregiver burden, perceived stress, competence, quality of life and couple relationship for 9 spouse caregivers followed by a focus group 2 weeks post‐intervention to obtain additional feedback.

Result

The 7‐week course was not complete by the time of abstract submission. Results will be available at the time of the conference.

Conclusion

We aim to demonstrate the feasibility of offering an online PPA caregiver intervention tailored to meet their specific needs. Future research will be conducted based on what is learned from this pilot program.
Beyond the Uniform Data Set (UDS): Benefits of incorporating additional items for the measurement of memory, executive functioning, and language from the University of Pittsburgh Alzheimer’s Disease Research Center
Authors: Choi Seo‐Eun , Mukherjee Shubhabrata , Gibbons Laura E , Trittschuh Emily H. , Lee Michael L. , Scollard Phoebe , Sanders R. Elizabeth , Snitz Beth E , Sweet Robert , Lopez Oscar L. , Mez Jesse B. , Saykin Andrew J. , Hohman Timothy J. , Crane Paul K.
Published: December 2022

Background

Alzheimer’s Disease Research Centers (ADRCs) administer prescribed cognitive batteries – the Uniform Data Set (UDS) – and report UDS data to the National Alzheimer’s Coordinating Center (NACC). ADRCs may administer other items beyond the UDS. We used data from the University of Pittsburgh ADRC (Pitt) to determine psychometric implications of UDS items alone versus UDS items plus additional Pitt‐specific items.

Method

We used confirmatory factor analyses to co‐calibrate Uniform Data Set 1 and 2 (UDS1/2, broadly overlapping, 2005–2015) and UDS3 (2015‐2020) data for memory, executive functioning, and language. We added Pitt‐specific items for each domain. We compared measurement properties of UDS scores vs. UDS plus Pitt scores, including measurement precision and projected sample sizes needed to show a 25% reduction in rate of decline over 12 months for people with Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD).

Result

There were 2,726 participants with 8,602 visits across UDS1, 2, and 3 (Table 1). Figure 1 summarizes findings for memory. Figure 1a shows boxplots for memory scores for normal cognition (NC), MCI, and AD for UDS1/2 (green) and UDS3 (purple). Figure 1b shows corresponding boxplots and standard error of measurement (SEM) curves for UDS1/2 (left) and UDS3 (right). Incremental improvements in measurement precision can be seen with the lower SEM curve for the UDS plus Pitt curves. Figures 2 and 3 summarize similar findings for executive functioning and for language. In each case UDS Plus Pitt has less measurement error than UDS alone. Proportions of scores with standard errors >0.30 (a commonly used threshold for individual decision‐making) during UDS1/2 and UDS3 are in Table 2. Pitt‐specific items reduced the proportion with imprecise scores for every comparison with the exception of executive functioning in UDS1/2. Sample sizes needed to show a 25% reduction in the rate of decline are shown in Table 3. Improved precision from additional items was associated with greater power to show change over time.

Conclusion

Integrating additional data beyond UDS1/2 and UDS3 results in better measurement precision and increased statistical power.
Investigating the role of lysosomal exocytosis in Alzheimer’s disease
Authors: Tsang Adrianna R , Seah Claudia , Krupa Jordan M , Pasternak Stephen H
Published: December 2022

Background

Many studies have implicated the endosomal‐lysosomal system in the production of beta‐amyloid (Aβ), but the actual compartments involved in Aβ secretion have never been visualized. Although lysosomes are expected to be a site of Aβ clearance, studies have also shown them to be a site of Aβ accumulation. Lysosomal exocytosis is well recognized as a major secretory pathway in non‐neuronal cells but is virtually unstudied in neurons. This project investigates the role and mechanism of lysosomal secretion in neurons. We hypothesize that lysosomal exocytosis is a pathway for Aβ release and could be modulated by Rab27b in iPSC‐derived human neurons.

Method

To study lysosomal exocytosis in a neuronal system, our lab established normal and mutant APP Swedish expressing iPSC‐neurons. The involvement of lysosome‐related secretory proteins (Rab27b, Munc13‐4 and synaptotagmin‐7) were examined using siRNA, dominant‐negative or shRNA constructs. Cells were co‐transduced with a pH‐sensitive dual‐fluorescent lysosomal marker (pHluorin‐LAMP1‐mAppleFP) to identify and track lysosomes. Cells were also loaded with fluorescent exogenous Aβ or a dye to mark endogenous Aβ, and then treated with ionomycin to induce exocytosis. Total internal reflection fluorescence (TIRF) microscopy was performed to capture videos of molecular events occurring within 250nm from the plasma membrane. Imaris software was used to analyze co‐localization of LAMP‐1 with Aβ, and the number and timing of lysosomal secretory events.

Result

In untreated cells, loaded Aβ accumulated in lysosomes. After treatment with ionomycin, a dramatic decrease of lysosomal Aβ was observed. In live cells, TIRF microscopy captured lysosomes docking and fusing with the plasma membrane over 150 seconds after ionomycin treatment. This was visualized by pHluorin‐LAMP1 (which is normally dark in an acidic pH) fluorescing green upon lysosomal fusion with the plasma membrane. Overexpression of Rab27b N133I mutant significantly increased lysosomal exocytosis of Aβ compared to wild‐type, and Rab27b shRNA dramatically reduced lysosomal exocytosis and Aβ secretion.

Conclusion

Our results demonstrate that lysosomal exocytosis is a novel secretion pathway in human neurons and identify potential pharmacological targets that regulate clearance of toxic Aβ.
Cardiometabolic multimorbidity, genetic risk and dementia
Authors: Tai Xin You , Veldsman Michele , Lyall Donald M , Littlejohns Thomas J , Langa Kenneth M , Husain Masud , Ranson Janice M , Llewellyn David J
Published: December 2022

Background

The extent to which multiple cardiovascular and metabolic co‐morbidity and genetic factors combine or interact to increase dementia risk is unknown.

Method

We analysed 435 105 participants from the UK Biobank prospective cohort of European ancestry, aged 40 to 72 years, without dementia at baseline (2006‐2010), followed until 2021. A cardiometabolic multimorbidity index with a point given for co‐morbid stroke, diabetes and heart disease (myocardial infarction, atrial fibrillation or heart failure) was calculated for each participant along with a polygenic risk score for dementia with low (lowest quintile), intermediate (quintiles 2 to 4) and high (highest quintile) risk categories. The primary outcome was incident all‐cause dementia during follow‐up.

Result

Participants with both a high genetic risk and a cardiometabolic multimorbidity index of two or greater had an increased risk of developing dementia, hazard ratio of 5.01(95% confidence interval 3.35 ‐ 7.49), compared to those with a low genetic risk and no cardiometabolic conditions. The risk of developing dementia increased monotonically with increasing cardiometabolic morbidity. Crucially, there was no interaction between cardiometabolic multimorbidity and polygenic risk (P = 0.11).

Conclusion

Cardiometabolic multimorbidity was independently associated with higher dementia risk, compared with genetic dementia risk. Addressing cardiometabolic multimorbidity may help to reduce dementia risk regardless of genetic risk.
Perceived discrimination and cognition in a middle age, racially diverse cohort
Authors: Likos Kelly D. S. , Swieboda Dominika , Williams McKayla , Dotson Vonetta M , Hu William T. , Verble Danielle D , Wharton Whitney
Published: December 2022

Background

Risk factors for Alzheimer’s disease (AD) include biologic (e.g. vascular), economic, and socio‐cultural factors. AD incidence and prevalence has been linked to race, and African American/Black individuals (AA/B) are at greater risk compared to non‐Hispanic Whites (NHW), due to physiological and social factors, however few clinical research studies are dedicated to prospective and thoughtful data collection on both physiology (biomarkers) and social/structural risk factors, including discrimination.

Methods

We enrolled 49 middle‐age, cognitively normal B/AA (n = 29) and NHW (n = 20) participants with a family history of AD, and examined correlations between cognition and a perceived discrimination. Cognitive assessments included tests of global cognition, executive function, verbal and visuospatial memory, and language. Six discrimination factors were derived from a larger battery of individually validated assessments of perceived discrimination including, Expanded Everyday Discrimination (EED), Major Experiences of Discrimination (MED), Chronic Work Discrimination and Harassment (WORK), and the Heightened Vigilance (HVIGIL). Factor scores derived from these assessments included ‘Disrespect’, ‘Aggression’, ‘Housing’, ‘Avoidance’, ‘Professional’, and ‘Personal’. Models controlled for education, income, race, and age.

Results

Perceived discrimination had an influence on cognitive scores in a race‐independent manner in this cohort. It was also found that this relationship maybe stratified by educational level. Participants were mostly women (73.5%) highly educated (42.9% post‐Graduate education) and B/AA participants reported more perceived discrimination compared to NHWs across all 6 composite discrimination factors. We observed a positive association between episodic memory score and the 'housing’ discrimination factor (p = 0.34 (0.03)), such that increased housing discrimination was associated with increased cognition. A negative correlation was observed between working memory and the discrimination factor ‘Professional’ (p = ‐0.3 (0.05)).

Conclusion

Discrimination negatively affects health outcomes and disease risk. Here we report a negative correlation between working memory and ‘professional’ factor score. We also report a positive correlation between cognition and housing discrimination. This latter is likely explained by the relationship between discrimination and geographic mobility, highlighting the presence of systemic and situational racism across all levels of socioeconomic status. Future AD research should incorporate historical and current data collection on redlining, Area Deprivation Index (ADI), and social and housing mobility.
Improved automated cerebral microbleed (CMB) detection
Authors: Gunter Jeffrey L. , Mead Aaron K , Bermudez Camilo L , Wiste Heather J. , Gebre Robel K , Vemuri Prashanthi , Knopman David S. , Petersen Ronald C. , Jack Clifford R. , Graff‐Radford Jonathan , Cogswell Petrice M
Published: December 2022

Background

Cerebral Microbleeds (CMBs) are tracked in anti‐amyloid drug safety monitoring. T2*GRE or SWI MRI images are visually assessed for the presence of CMBs. Automated methods tuned for sensitivity often have unacceptably high false positive rates requiring extensive human cleanup.

Method

Assume contemporaneous T2*GRE and T1‐weighted images. CMB detection (Figures 1,2) has three steps: 1) Segmentation outputs from the T1‐weighted image are resampled into the T2*GRE image voxel raster; 2) Normalized cross‐correlation of the T2*GRE with a CMB template identifies “candidate CMBs”; 3) a neural network using voxel patches centered on each candidate CMB rejects false positives. Patches presented to the network are 4D and include five contrasts drawn from the T2*GRE, correlation, T1‐weighted, WM probability and CSF probability images. The simple network architecture consists of convolutional blocks followed by dense blocks. The system is trained using images from ADNI, ARIC, MCSA, and the Mayo Clinic ADRC that have been previously visually graded for CMBs (Table in Figure 3). Importantly, we include participants with and without CMBs in our data reflecting the fact that the majority of people (even the elderly) have no CMBs. Data is split 70:10:20 by subject for training, validation, and testing. Various network configurations were evaluated.

Result

High candidate detection sensitivity can be achieved at the expense of presenting hundreds to thousands of false positive candidates per input image to the rejection network. Our best performing network configuration to date has AUC 0.982 (95% bootstrap CI 0.971 to 0.990 based on the 10% validation subset). Choosing an operating point with 95% sensitivity in the validation set and admits, on average, 0.6 false positive CMB candidates per input T2*GRE image. Sensitivity is hindered by a small number of obvious errors in the ground truth visual assessment. Validation loss tracks training loss with no indication of over‐fitting. Example patches are shown in Figure 4.

Conclusion

Excessive false positive detection requires significant human correction and effort, preventing automated CMB detection from being widely adopted. We have an automated detection system that is sensitive (95%) and provides excellent false positive rejection (<1 false positive CMB/input image) reducing needed human effort.
Defining the ATN framework using longitudinal biomarker trajectories reveals an emerging amyloid accumulation group
Authors: Boyle Rory Thomas , Coughlan Gillian T , Properzi Michael J , Archdeacon Claire , Chou Hsiang‐Chin Lori , Klinger Hannah , Jacobs Heidi I.L. , Papp Kathryn V. , Amariglio Rebecca E. , Farrell Michelle E. , Donohue Michael C. , Hohman Timothy J. , Mormino Elizabeth C. , Hanseeuw Bernard J , Chhatwal Jasmeer P. , Rentz Dorene M. , Price Julie C , Johnson Keith A. , Schultz Aaron P. , Sperling Reisa A. , Buckley Rachel F. ,   The Harvard Aging Brain Study
Published: December 2022

Background

The ATN framework is defined by cross‐sectional biomarkers of β‐amyloid (Aβ), tau and neurodegeneration. Given that prevention trials, e.g., AHEAD 3‐45, are focused on individuals who have lower Aβ than established thresholds, we investigated whether defining the ATN framework using longitudinal biomarker trajectories might better identify an at‐risk sample within this boundary. Here, we applied a data‐driven method to re‐define the ATN with longitudinal biomarker data from the Harvard Aging Brain Study (HABS) and we then replicated this longitudinal framework in ADNI.

Method

157 HABS participants were clinically‐normal at baseline and underwent at least two Pittsburgh Compound‐B [PiB]‐PET, Flortaucipir‐PET, and T1‐weighted MRI scans. To define longitudinal ATN, we applied latent class mixture models (LCMM) to each biomarker (global Aβ DVR, entorhinal tau SUVr, ICV‐adjusted hippocampal volume) separately, adjusting for age, and including random intercept and slopes. Akaike information criteria (AIC) determined the best‐fitting models out of two‐group or three‐group solutions with linear or spline‐link functions. We compared longitudinal ATN profiles on demographics and an optimized estimate of cognitive change (derived from longitudinal Preclinical Alzheimer Cognitive Composite (PACC) data).

Result

Aβ trajectories (Fig.1a) were best categorized by one stable (A→) and two accumulating subgroups, a predominantly amyloid‐negative at baseline subgroup (A‐↑) and an entirely amyloid positive at baseline subgroup (A+↑). Tau (Fig.1b) and neurodegeneration (Fig.1c) were optimally defined by stable (T→/N→) vs accumulating/atrophying (T↑/N↑) groups, respectively. These groups were replicated in ADNI (Fig.2). The entire A‐↑ subgroup were stable on T and N (A‐↑/T→/N→) and were predominantly A‐/T‐/N‐ at baseline (86%; Table 1). By contrast, 38% of A+↑ individuals changed on T, or T&N. A‐↑/T→/N→ demographically most closely resembled the longitudinally‐stable ATN group (A→/T→/N→), but were older, more likely to carry e4+ and exhibited higher baseline Aβ (Table 2). Although demonstrating Aβ accumulation, A‐↑/T→/N→ did not exhibit greater cognitive decline versus the stable group (A→/T→/N→; Fig. 3).

Conclusion

Our findings suggest that a longitudinal biomarker run‐in of Aβ‐PET may be useful for the identification of early‐risk groups for prevention trials. Future work will establish whether other features (e.g. genetics, neuroinflammatory markers, functional imaging) can help to distinguish this cohort.