bluuebunny/crossref_metadata_2025_split 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

AbstractBackgroundThe 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.ObjectiveTo 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.MethodWe 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).ResultWe 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.ConclusionWe 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

AbstractBackgroundOscillatory 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.MethodsWe 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.ResultsAn 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.ConclusionsOur 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

AbstractBackgroundDetection 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.MethodAb42 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).ResultUsing 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.ConclusionThese 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

AbstractBackgroundMethods 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.
MethodsA 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.ResultsThere 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.ConclusionsPreliminary 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

AbstractBackgroundAfrican 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.MethodA 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.ResultThe 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.ConclusionFindings 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

AbstractBackgroundBiomarker 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.MethodWe 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.ResultAmong 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).ConclusionThis 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

AbstractBackgroundPlasma 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.MethodsEighty‐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.ResultsPtau‐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).ConclusionsIn 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

AbstractBackgroundAccumulation 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.MethodWe 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.ResultFigure 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%).ConclusionOptimal 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.