bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between psychological factors, grey matter volume, and resistance and resilience to tau pathology in cognitively unimpaired older adults
Authors: Strikwerda‐Brown Cherie , St‐Onge Frederic , Yakoub Yara , Ozlen Hazal , Binette Alexa Pichet , Breitner John , Villeneuve Sylvia , Group PREVENT‐AD Research 
Published: December 2022

AbstractBackgroundModifiable factors may influence risk for Alzheimer’s disease (AD) via two distinct, though not mutually exclusive, pathways: resistance and resilience to pathology. Whereas cognitive ‘resilience’ is defined as the maintenance of better‐than‐expected cognitive performance in the face of Aβ and tau pathology, ‘resistance’ refers to an absence or delaying of the pathology itself. We explored the potential influence of psychological factors on resistance and resilience to tau pathology in older adults at risk of AD dementia, and whether grey matter volume mediates these relationships.MethodMeasures of psychological factors (including mindfulness, optimism, purpose in life, Big‐5 personality traits, and affective symptoms), longitudinal cognitive assessments, and structural MRI scans were collected in 259 nondemented older adults, along with Aβ‐ and tau‐ positron emission tomography (PET) scans in a subset of 156 individuals. Relationships between psychological factors and entorhinal tau pathology, and between psychological factors and cognitive resilience to entorhinal tau pathology (quantified using the residuals method), were explored, controlling for age, sex, and global Aβ burden. Principal components analysis was then performed to reduce the psychological factors that were associated with resistance/resilience down to their underlying components. Relationships between the psychological components and grey matter volume were explored using voxel‐based morphometry analyses. Finally, the potentially mediating effect of grey matter volume on the relationships between the psychological components and resistance/resilience to pathology were examined.ResultOne principal component was associated with resistance to pathology, comprising mindful acting with awareness, perseverative thinking, conscientiousness, neuroticism, depression, purpose in life, and optimism. Two principal components were associated with resilience to pathology, the first comprising mindful nonjudgment, anxiety, and stress, and the second comprising extraversion and openness. These three principal components were associated with partially distinct patterns of grey matter volume, which overlapped in medial prefrontal and posterior cingulate cortices (Figure 1). Grey matter volume partially mediated the relationship between psychological factors and resistance, but not resilience, to pathology.ConclusionPsychological functioning may influence resistance and resilience to AD pathology in cognitively unimpaired older adults. Increased grey matter associated with different combinations of protective psychological factors may assist in the delaying or prevention of AD pathology.
Definitions and characteristics of successful cognitive aging
Authors: Pezzoli Stefania , Giorgio Joseph , Harrison Theresa M. , Martersteck Adam , Jagust William J. 
Published: December 2022

AbstractBackgroundDifferent approaches have been used to define successful agers (SA), but there is currently no consensus on either the definition of SA or the underlying neural mechanisms. The aim of this study was to compare new and existing definitions, to understand whether SA are resistant to atrophy and Alzheimer’s disease pathology or resilient to their effects, and whether this varies by SA definition.MethodMachine learning algorithms were used to predict age from neuropsychological tests in 184 cognitively normal adults over the age of 70. Differences between cognitive‐predicted age and chronological age (cognitive age gap, CAG) were used as a novel measure of SA, defined as below the 20th percentile (SA‐CAG, n = 37). In the same sample, SA were also defined as individuals performing in the top 20% on composite scores for episodic memory (SA‐EM, n = 37) and non‐memory cognition (SA‐NM, n = 37), and participants with performance comparable to individuals aged 18‐32 years on the California Verbal Learning Test long delay free recall (SA‐CVLT, n = 31). The four definitions were used to compare SA to typical agers (TA, n = 109) in hippocampal volume, anterior cingulate cortex (ACC) thickness, APOE genotype, PET‐measured amyloid (11C‐Pittsburgh compound‐B, PiB) and, in a subsample (n = 114), PET‐measured tau (18F‐Flortaucipir, FTP). All analyses were age and sex adjusted.ResultSA‐CAG definition showed moderate agreement with SA‐EM (Cohen’s κ = 0.46), SA‐NM (κ = 0.49), but only fair agreement with SA‐CVLT (κ = 0.24). Fair agreement was found between the other definitions (Figure 1). Compared to TA, greater hippocampal volume was found in SA‐CAG (p = 0.005), SA‐EM (p = 0.02), and SA‐CVLT (p = 0.02). Greater ACC thickness was found in SA‐CAG (p = 0.01), SA‐EM (p = 0.02), and SA‐NM (p = 0.004). Lower entorhinal FTP uptake was found in SA‐CAG (p = 0.04), SA‐EM (p = 0.007), and SA‐NM (p = 0.008) (Figure 2). No between‐group differences were detected in the proportion of APOE ε4 carriers and PiB+ participants.ConclusionDespite imperfect overlap in SA groups identified by different definitions, common brain features were found in SA‐CAG, SA‐EM, and SA‐NM compared to TA. Greater hippocampal volume, greater ACC thickness and lower entorhinal tau deposition suggests that SA, regardless of its exact definition, may be resistant to tau pathology and its downstream effects.
The association between cognitive reserve, cognition and brain age in Midlife: The CARDIA Study
Authors: Dintica Christina S. , Habes Mohamad , Davatzikos Christos , Sidney Stephen , Yaffe Kristine 
Published: December 2022

AbstractBackgroundCognitive reserve (CR) factors have been suggested to be protective of cognitive function in older adults. Less is known about this relationship in midlife, and whether the protective effect of CR may depend on brain age (relative to chronological age) in midlife. We aimed to investigate whether CR factors are associated with cognition in midlife, independent of brain age.MethodsAs part of the ongoing prospective Coronary Artery Risk Development in Young Adults (CARDIA) study, we identified 612 Black and White participants (mean age 55 SD 3.5) with brain MRI and cognitive testing. We generated a CR composite score from structural equation modeling including four CR‐enhancing factors: education, cognitive activities, occupational cognitive complexity, and adult literacy. Cognitive function was assessed at Year 30 with a composite measure of tests of memory, processing speed, executive function, and language. Brain age was ascertained using a previously validated high dimensional neuroimaging pattern analysis, based on machine learning algorithms, that quantifies individual differences in age‐related atrophy using MRI‐derived structural brain characteristics. We used linear regression to assess the associations between CR composite above or below median (high versus low), brain aging, and cognitive function, adjusting for chronological age, sex, race, intracranial volume, and scanning site.ResultsThere was a modest association between the CR composite and brain age; higher CR was associated with lower brain age (β‐0.40, CI: ‐0.67 to ‐0.13). High CR was associated with better performance on all cognitive tests compared to low CR (p<0.001 for all). These associations remained with the inclusion of brain age as a covariate. Having high CR is associated with better cognitive performance regardless of brain age (Figure 1).ConclusionOur findings suggest that CR factors are associated with better cognitive function in midlife, and that brain aging and CR are two independent factors that may contribute to cognitive aging in midlife.
A whole‐genome‐sequencing study to identify genetic variants associated with Alzheimer’s disease progression
Authors: Shi Ruyu , Fan Kang‐Hsien , Lopez Oscar L. , Feingold Eleanor , Kamboh M. Ilyas 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) is an irreversible neurodegenerative brain disease with varying disease progression rates among individuals. This study aims to identify possible underlying genetic variants associated with AD progression using a whole‐genome sequencing approach.MethodWhole‐genome sequencing at 30x coverage was performed on 416 late‐onset AD patients (mean baseline age ± sd) = 76.47 ± 6.10) having at least two Mini‐Mental State Examination (MMSE) scores ranged from 0 to 30. Since the study subjects had varying time points of visit and MMSE records, we defined AD progression phenotypes in four ways, including differentially specified progression rates and time to pre‐defined events in genome‐wide association analyses. Genetic association analyses between single‐nucleotide variants (SNVs) and phenotypes were adjusted for baseline age, sex, year of education, baseline MMSE measures, and the first four principal components.ResultSix novel genome‐wide statistically significant associations (p<5E‐08) were observed in our study. Two associations were detected with the same SNVs on chromosomes 2 (SLC4A10/rs13036052) and 7 (chr7:58053009[Hg38] near ZNF716) with overall progression rates. One genetic variant on chromosome 6 (chr6:3127309[Hg38] near BPHL) was associated with annual progression rate. In addition, three associations were seen on chromosomes 1 (rs199560872), 14 (chr14:9600158[Hg38] near TUNAR), and 18 (rs34718969) with time‐to‐event phenotypes. All top variants were present either in introns or intergenic regions.ConclusionOur initial whole‐genome sequencing analyses have identified several independent associations with AD progression, which need to be confirmed in larger sequencing samples.
Depression in young adulthood to midlife and brain aging in midlife: A 30‐year follow‐up of The CARDIA Study
Authors: Dintica Christina S. , Habes Mohamad , Simone Tamar , Schreiner Pamela , Erus Guray , Yaffe Kristine 
Published: December 2022

AbstractBackgroundEvidence suggests that depression is a risk factor for dementia in older adults, but the link between depressive symptoms and brain health earlier in life is poorly understood. We aimed to investigate the relationship between depressive symptoms in early adulthood through midlife and brain aging in midlife.MethodsFrom the prospective study of Coronary Artery Risk Development in Young Adults, we identified 649 Black and White participants (age 18‐30 at baseline) with brain MRI and cognitive testing 30 years later (mean age 55, SD 3.5). The participants underwent 6 repeated assessments for depressive symptoms measured with the Center for Epidemiological Studies Depression scale (CES‐D) over 30 years. The CES‐D range is 0‐60, a score of 16 points or more is considered depressed. Cumulative exposure of depressive symptoms was estimated by time‐weighted averages (TWA). We used a previously validated high dimensional neuroimaging pattern analysis, based on machine learning algorithms, that quantifies individual differences in age‐related atrophy using MRI‐derived structural brain characteristics. Linear regression was used to test the association between average cumulative depressive symptoms, brain aging, and cognition, adjusted chronological age, sex, race, education, intracranial volume, and scanning siteResultsEvery standard deviation (5‐points) higher average cumulative depression symptoms was associated with approximately one‐year greater brain age (Table 1). Participants with higher average cumulative depressive symptoms greater than the clinically significant cutoff of 16 points over the 30 years, had on average 3‐years greater brain age (95% CI: 0.74 to 4.96) compared to below the clinical cutoff. Adjusting for anti‐depressive medication use at any time during the follow‐up, slightly attenuated the association (Table 1).ConclusionHigher depressive symptoms across 30 years from early to mid‐adulthood are associated with accelerated brain aging in midlife. This suggests that elevated depressive symptoms in early adulthood can have implications for brain aging as early as in midlife.
Impairment of cerebral CO2 dynamic vasoreactivity in MCI & AD patients: a multi‐center study of cerebral flow regulation
Authors: Marmarelis Vasilis , Billinger Sandra A , Chui Helena C , Joe Elizabeth B , Shin Dae , Cardim Danilo , Hashem Suhaib , Aaron Stacey E , Cullum Munro , Kelly Brendan , Zhang Rong 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease Centers in Los Angeles (USC), Dallas (UT‐SWMC) and Kansas City (KUMC) have joined together to study the regulation of cerebral perfusion through analysis of spontaneous time‐series data using a modeling methodology that previously yielded indications of reduced CO2 dynamic vasomotor reactivity (DVR) in amnestic MCI patients. We report initial results from this ongoing multi‐center study that confirm those preliminary findings and, furthermore, elucidate the effects of slow‐paced breathing.MethodFive‐minute spontaneous changes in arterial blood pressure (ABP), end‐tidal CO2 (etCO2) and cerebral blood flow velocity (CBFV) in middle cerebral arteries were obtained before and after 5‐min session of slow‐paced breathing (8 breaths/minute). Using data from 25 MCI patients, 7 AD patients and 45 age‐matched cognitively normal controls (NC), we obtained predictive models of the dynamic effects of ABP and etCO2 (proxy for blood CO2) upon CBFV via our kernel‐based modeling methodology. These predictive models were used to compute indices (physio‐markers) that quantify the DVR in each participant, as time‐average of the model‐predicted CBFV response to unit‐step change of etCO2 over the first 30 seconds.ResultThe obtained DVR indices were significantly different for the 32 patients (MCI and AD lumped together due to small number of AD) vs. 45 age‐matched controls (p= 0.0099). Notably, the delineation between patients and controls improved (p= 0.0011) after a 5‐min session of slow‐paced breathing. Figure 1 shows the average model‐predicted CBFV response to unit‐step change of etCO2 for 32 MCI/AD patients (red line) and 45 controls (blue line) before and after the 5‐min paced‐breathing session. Note the negative average steady‐state CBFV response of the patients (red) that indicates polarity reversal of the normal CO2 vasomotor reactivity (blue). Better delineation between patients and controls is achieved (p= 2x10‐5) when the DVR indices from the two sessions, before and after slow‐paced breathing, were averaged (see histograms in Figure 2).ConclusionSignificantly lower DVR indices under resting spontaneous conditions were observed in 32 MCI/AD patients relative to 45 age‐matched controls. This reduction is detected more reliably after 5‐min of slow‐paced breathing. Averaging of the DVR indices obtained before and after slow‐paced breathing improved further this delineation (p= 2x10‐5).
Advanced diffusion‐weighted MRI sensitively detects age and sex effects in 34,423 adults
Authors: Nabulsi Leila , Lawrence Katherine E , Laltoo Emily , Santhalingam Vigneshwaran , Abaryan Zvart , Villalon‐Reina Julio E , Nir Talia M , Gari Iyad Ba , Zhu Alyssa H , Haddad Elizabeth , Muir Alexandra M , Jahanshad Neda , Thompson Paul M 
Published: December 2022

AbstractBackgroundAging and Alzheimer’s disease (AD) are associated with alterations in the brain’s white matter (WM) microstructure. AD also exhibits significant sex differences and, similar to age, sex has also been associated with WM microstructural variability. A comprehensive characterization of how aging and sex impact WM microstructure may thus improve our understanding of processes involved in AD. Here we examined age and sex effects on traditional and advanced measures of WM microstructure in middle‐ to older‐aged adults.MethodCross‐sectional diffusion‐weighted MRI (dMRI) scans were analyzed from 34,423 UK Biobank participants (aged 45‐80 years; 53% female) using single‐shell models (DTI, TDF), and advanced multi‐shell models (NODDI, MAP). Metrics were projected to a standard WM skeleton using publicly available ENIGMA protocols, based on TBSS (FSL). Mean values for each dMRI metric were extracted from the whole WM skeleton, and age was modeled using fractional polynomial regressions, co‐varying for years of education, waist/hip ratio, population structure, and the Townsend index. Sex‐stratified centile curves were created for each dMRI metric to provide normative reference charts.ResultWM microstructure across the brain was significantly associated with participants’ age and sex for all dMRI models (main effects, ps<.001). Increasing age in our cross‐sectional sample was associated with lower anisotropy (DTI‐FA, TDF‐FA), neurite density (NODDI‐ICVF, MAP‐RTOP, MAPMRI‐RTAP), and restriction (MAP‐RTPP) as well as higher diffusivity (DTI‐AxD, DTI‐MD, DTI‐RD), free water (NODDI‐ISOVF), and white matter dispersion (NODDI‐OD) for both males and females (Figures 1 and 2). Some metrics showed a gentle decline until around age 60, followed by a precipitous decline thereafter (e.g., TDF‐FA, NODDI‐ICVF, MAP‐RTAP, Figures 1 and 2). Significant sex differences in aging were most sensitively detected by the advanced dMRI multi‐shell models NODDI and MAPMRI (age‐by‐sex interaction; males showing a steeper trajectory for NODDI‐OD, p<.001, females showing a steeper trajectory for MAPMRI‐RTPP, p<.01, with age).ConclusionParticipant age and sex are significantly associated with the brain’s WM microstructure; advanced dMRI models displayed the greatest sensitivity, strenghtening previous findings in a smaller UKB sample (15k). Along with our calculated centile curves, we offer an important normative reference to guide future studies of Alzheimer’s disease.
The longevity‐promoting intervention 17α‐Estradiol protects against aging phenotypes in APOE4 mice
Authors: McGill Cassandra J , Christensen Amy , Qian Wenjie , Benayoun Bérénice A. , Pike Christian J. 
Published: December 2022

AbstractBackgroundThe two primary risk factors for late onset Alzheimer’s Disease (AD) are aging and APOE4 genotype. While the causal relationship between aging and AD is not well defined, shared phenotypes, such as decreased metabolic function and increased inflammation, are strong leads. APOE genotype may be linked to AD phenotype through the regulation of aging processes. The NIA Interventions Testing Program found that 17α‐estradiol (17αE2) treatment can increase male mouse lifespan. Since 17αE2 has been shown to act upon systemic and neural pathways that have also been associated with AD pathology, we propose that 17αE2 may constitute a pleiotropic intervention strategy. Further, because APOE4 is associated with impaired healthspan and lifespan, 17αE2 may preferentially improve outcomes in the context of APOE4 genotype.MethodTo examine the effects at the earliest phases of AD development, we used 10‐month‐old APOE3 or APOE4 targeted replacement male mice maintained for 20 weeks on normal chow in the absence or presence of 14.4 ppm 17αE2. Mice were evaluated on various metabolic, behavioral, and molecular measures.ResultOur initial results indicate genotype differences in the impact of 17αE2 across multiple outcomes. APOE4 mice were impaired across metabolic measures including body weight, plasma leptin, and hepatic steatosis, and 17αE2 treatment significantly attenuated these metabolic phenotypes. APOE4 mice exhibited an aged phenotype compared to APOE3, notably with higher frailty indices; however, 17αE2 treatment reduced the frailty index more strongly in APOE4 mice compared to APOE3. Interestingly, transcriptomic analysis of isolated microglia from both APOE3 and APOE4 17αE2 treated mice displays a downregulation of genes relating to inflammation and upregulation of those in metabolic pathways.ConclusionThese data confirm and extend prior findings that APOE4 is linked to progeroid effects both peripherally and neurally, outcomes associated with AD risk. Importantly, although 17αE2 significantly improved a range of measure across genotypes, it showed the strongest effects in the APOE4 genotype.This research was funded by the Cure Alzheimer’s Fund.
Vascular dysfunction in health disparities – unraveling contributions to dementia and Alzheimer’s disease in South Alabama
Authors: Bauman Allison J. , Traylor Miranda K , Saiyasit Napatsorn , Butlig Evan‐Angelo R , Chaney Samantha D , Hawley Nanako A. , Randall Ryleigh B. , Bobinger Hanna V. , Frizell Carl A , Hill Benjamin D , Keller Joshua L , Nelson Amy R. 
Published: December 2022

AbstractBackgroundIt is estimated that nearly 100,000 Alabamians have Alzheimer’s disease (AD). There is strong evidence that neurovascular uncoupling, cerebral blood flow reductions and dysregulation, and breakdown of the blood‐brain barrier (BBB), including the loss of pericytes, are early events in the AD pathophysiological cascade. Health, lifestyle, and socioeconomic risk factors across racial groups, and/or genetic risk factors, may account for this increased AD risk. Aged Black Americans have twice the risk of experiencing AD or other dementias compared to aged Whites. 26.8% of the Alabama population is Black American. Furthermore, over a million people in Alabama live in rural areas (USDA‐ERS), leading to healthcare professional shortages, and in designated medically underserved areas. Relatively little is known about the role of cerebrovascular mechanisms in the pathogenesis of dementia and AD and potential therapeutic targets within the neurovascular system, especially as they relate to health disparities. Thus, determining whether health disparities via vascular or genetic risk factors leads to neurovascular dysfunction and ultimately AD is essential.MethodBlood was collected from middle‐aged diverse individuals (67% Black, n = 12 and 33% White, n = 6, 61% of participants were female) that reside in the South Alabama vicinity. Plasma and buffy coat were used for biomarker assays and APOE genotyping, respectively. We identified APOE genotype using DNA extraction and PCR‐RFLP. We used MesoScale Discovery’s MESO QuickPlex SQ to quantify vascular biomarkers, tau and neurofilament light chain. Measurements of amyloid‐beta, inflammatory cytokines and other biomarkers are underway.Result67% of Blacks and 17% of Whites were APOE‐ε4 carriers. 39% of participants reside in designated rural or medically underserved areas. Blacks had increased bFGF, Flt‐1, VEGF‐C and tau. APOE‐ε4 carriers had increased VEGF‐C and tau. Females had increased Flt‐1 and VEGF‐A. Individuals residing in rural/medically underserved areas had increased bFGF.ConclusionWe observed a large % of APOE‐ε4 carriers in Black participants. The increase in VEGF‐C and tau in Black participants may have been provoked by APOE‐ε4 genotype. Vascular health and peripheral tau may play a crucial role in the development of AD. Improving modifiable vascular risk factors early with interventions such as exercise may help prevent AD.