bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determinants of hand grip strength among community dwelling older adults in southwestern Nigeria: Data from the VALIANT Study
Authors: Akinyemi Rufus O. , Olalusi Oludotun V , Akinyemi Tolulope O , Yaria Joseph O , Ogunde Gabriel O , Akinyemi Joshua O. , Lawlor Brian , Ogunniyi Adesola 
Published: January 2025

AbstractBackgroundHand‐grip strength (HGS) is known to be a surrogate marker of not only fitness and frailty, but of cognitive and cardiometabolic health. It is cheap, readily deployed and can be a valuable tool in resource‐limited settings. Little however is known about the determinants and correlates of HGS in sub‐Saharan Africa, where stroke and vascular cognitive disorders are projected to exponentially increase. We examined the determinants of HGS among older adults in a rural community in Ibadan, South West Nigeria.MethodVascular heAlth, fraiLty and cognition in Ageing Nigerians (VALIANT) Study is an ongoing longitudinal community‐based cohort study aimed at exploring the association between cardiovascular health, cognition and frailty in Nigeria. One thousand (1000) participants have so far been recruited (via a multistage, stratified cluster random sampling method) and have been taken through a battery of cardiovascular, cognitive and frailty assessment tools. Data on HGS, obtained using a digital hand dynamometer, was available for 480 men and women aged ≥50years. A multivariable adjusted linear regression analysis was used to assess the determinants of HGS. All associations were reported as coefficients with 95% confidence intervals (CI)ResultThe mean age was 64.5 (11.8) with 35% males. The mean HGS was higher among males (22.86 10.1) than in females (16.26 6.1) (p<0.001) and decreased with increasing age and in the left hand. Using the Rockwood frailty scale, 66 (13.8%) of the study participants were vulnerable to frail while 80% had cognitive impairment (MoCA <26). In the multivariable linear regression analysis, the independent determinants of hand grip strength with corresponding beta coefficients (95%CI) were attainment of tertiary/postgraduate education 5.19 (1.70; 8.68), being a widow/widower ‐2.75 (‐5.47; ‐0.03), lower MoCA score<19 ‐2.50 (‐4.42; ‐0.59) and higher IDEA‐IADL score 0.23 (0.02, 0.44)ConclusionAmongst older adults in rural Nigeria, attainment of tertiary/postgraduate education was independently associated with higher HGS; while being a widow/widower and presence of low cognitive reserve were independently associated with lower HGS. This study has identified unique determinants of HGS among West Africans.
Patterns of Association of Tau Across Cortical Regions Differ Between [18F]MK6240 and [18F]Flortaucipir
Authors: Hosseini Seyyed Ali , Rahmouni Nesrine , Therriault Joseph , Servaes Stijn , Tissot Cécile , Aumont Etienne , Arias Jaime Fernandez , Macedo Arthur C. , Wang Yi‐Ting , Stevenson Jenna , Lussier Firoza Z , Chan Tevy , Zheng Yansheng , Trudel Lydia , Gauthier Serge , Baker Suzanne L. , Pascoal Tharick A. , Rosa‐Neto Pedro 
Published: January 2025

AbstractBackgroundThis study aims to investigate the differential patterns of association in tau protein imaging across cortical regions using two distinct Tau imaging agents: [18F]MK6240 and [18F]Flortaucipir. The underlying hypothesis posits that variations in the properties of these tracers, such as affinity and off‐target effects, influence the observed patterns of association in neuroimaging.MethodTo test this hypothesis, a comprehensive study was conducted involving 104 subjects part of the HEAD study at McGill University: 53 cognitively normal (CN), 19 with mild cognitive impairment (MCI), 9 with Alzheimer's Disease (AD) and 23 non‐AD. A key methodological aspect of the study was the selection of seed cortical regions based on the highest standardized uptake value ratios (SUVR) obtained in population average images. These regions included the trans‐entorhinal area, parietal, posterior cingulate cortices, and two off‐target binding regions: the choroid plexus and substantial nigra. This approach allowed for a nuanced analysis of tracer associations in both target and off‐target regions.ResultThe results revealed notable differences between the two tracers. Specifically, [18F]MK6240 exhibited higher associations between cortical regions, with similar slopes in these associations across different areas. In contrast, the associations between the off‐target binding regions (Choroid Plexus and Substantia Nigra) and the established Braak regions were found to be non‐significant. This finding is particularly revealing, as it underscores the differential binding affinity and specificity of the two tracers.ConclusionIn conclusion, the study substantiates the initial hypothesis by demonstrating that distinct tau tracers exhibit unique patterns of cortical associations, which can be attributed to their specific properties. This insight has significant implications for the interpretation of tau imaging in neurodegenerative diseases, particularly in AD. It highlights the necessity of considering tracer‐specific characteristics when analyzing neuroimaging data and suggests that a one‐size‐fits‐all approach may not be appropriate in the nuanced field of neuroimaging. The findings of this study pave the way for more refined and accurate diagnostic practices in neurology, particularly in the context of neurodegenerative diseases where tau protein plays a pivotal role.
Relationship Between 18F‐AV‐1451 Binding in Human Brain and Tissue Alterations Defined by Quantitative Gradient Recalled Echo (qGRE) MRI Measurements
Authors: Kothapalli Satya V.V.N. , Benzinger Tammie L.S. , Gordon Brian A. , Eldeniz Cihat , Hildebolt Charles F , Goyal Manu S. , Morris John C. , Yablonskiy Dmitriy A. 
Published: January 2025

AbstractBackgroundThe 18F‐AV‐1451 radioligand enables in‐vivo identification of tau neurofibrillary tangles that are considered as biomarkers of neurodegeneration in Alzheimer Disease (AD). However, off‐target radioligand binding is also observed in basal ganglia, known as an iron‐rich region. Hence, it is important to distinguish between radioligand‐identified tissue neurodegeneration and iron‐related radioligand binding effects. Our aim is to answer this question by using previously developed quantitative Gradient Recalled Echo (qGRE) MRI technique sensitive to morphological and microstructural tissue neurodegeneration, as well as to iron deposition.MethodsSixty‐eight participants (ages: 72.1y ± 8.2y; 15 with amyloid status (Aß) positive and cognitive dementia rating (CDR®)>0; 16 with Aß‐positive and CDR® = 0; and 37 with Aß‐negative and CDR® = 0) recruited by Knight ADRC underwent 18F‐AV‐1451 PET imaging and qGRE MRI imaging (3T Siemens MRI scanners). As previously demonstrated, the R2t* metric of qGRE signal is sensitive to both, pre‐atrophic neuronal loss (low R2t*, a.k.a. Dark Matter (DM), and nonheme iron accumulation (High R2t*). The histogram characterizing distribution of R2t* values across the brain (Figure 1) allows the quantification of DM (R2t*<5.8s‐1) and Iron Deposition Score (IDS, R2t*>28s‐1). 18F‐AV‐1451 binding was characterized in terms of Standardized Uptake Value Ratio (SUVR). All results were summarized in brain regions segmented using FreeSurfer.Results(Figures 2 and 3): Tissue volumes exhibited moderate negative associations with 18F‐AV‐1451 SUVRs in MTL (R2 = 0.21), temporal lobe (R2 = 0.17), and parietal lobe (R2 = 0.11). The linear model that includes IDS and DM exhibited positive association with 18F‐AV‐1451 SUVRs only in MTL (R2 = 0.18). The linear mixed model that includes volume, IDS and DM metrics showed the improved association between predicted and actual 18F‐AV‐1451 tracer retention in the MTL (R2 = 0.34), the temporal lobe (R2 = 0.23), and the parietal lobe (R2 = 0.12).ConclusionOur results suggest that the 18F‐AV‐1451 binding is modulated not only by neurodegeneration but also by elevated levels of iron deposition. More detail studies are required to answer the question whether the iron effect is concomitant or contributes to neurodegeneration through ferroptosis. The qGRE‐based multiparametric approach allowing simultaneous identification of pre‐atrophic neurodegeneration and iron deposition has a potential to contribute to understanding of this intricate relationship.
A brain MRI estimate of whole‐body aging in midlife predicts late life risk for Alzheimer's disease
Authors: Whitman Ethan T. , Elliott Maxwell L. , Knodt Annchen R. , Moffitt Terrie E. , Caspi Avshalom , Hariri Ahmad R. 
Published: January 2025

AbstractBackgroundAging is the strongest risk factor for Alzheimer’s disease (AD). Accordingly, identifying biomarkers of accelerated aging is a major focus of AD prevention research. Current MRI‐based “aging clocks” (i.e., brain age) derive from cross‐sectional associations with chronological age. However, chronological age differs fundamentally from biological aging. We introduce a novel brain MRI proxy for biological aging in midlife developed in the Dunedin Study, a population‐representative longitudinal birth cohort, and demonstrate its ability to differentiate and predict AD in the Alzheimer’s Disease Neuroimaging Initiative (ADNI).MethodThe pace of whole‐body aging was determined by tracking physiological decline of 6 organ systems over 20 years in Dunedin Study members. An elastic‐net regression model was trained to estimate this pace of aging using a single T1‐weighted scan collected at age 45 from 860 Study members. We call this measure the Dunedin Pace of Aging Calculated from NeuroImaging or “DunedinPACNI.” We exported DunedinPACNI to ADNI and tested its association with current and future AD. Lastly, we compared DunedinPACNI to “brain age” using brainageR.ResultDunedinPACNI estimated whole‐body aging with a cross‐validated accuracy of r=0.43 in Dunedin Study members. Derived in 6,199 T1‐weighted ADNI scans, DunedinPACNI was on average 0.40 standard deviations higher in MCI patients and 1.13 standard deviations higher in AD patients compared to healthy participants (MCI 95% CI:[0.36‐0.45]; AD 95% CI:[1.08‐1.19]). DunedinPACNI outperformed brainageR in differentiating MCI and AD patients from controls (MCI: b=.25; 95% CI:[.14‐.35]; AD: b=.68; 95% CI:[.56‐.80]). In 1,326 ADNI participants followed up to 16 years, baseline DunedinPACNI was associated with a higher probability of AD conversion (HR=1.58, 95% CI:[1.36‐1.84]) as was brainageR (HR=1.61; 95% CI:[1.42‐1.84]). DunedinPACNI and brainageR together predicted conversion more accurately than either measure alone (combined HR=2.10, 95% CI:[1.76‐2.51).ConclusionDunedinPACNI, a novel MRI proxy for longitudinal whole‐body aging during midlife, offers advantage over “brain age” in detecting neurodegenerative disease and predicting AD conversion in late life. DunedinPACNI can be applied to existing neuroimaging datasets to estimate whole‐body aging to better gauge early AD risk.
Association of Objective Sleep Measures and White Matter Limbic System Integrity in Community‐Dwelling Cognitively Unimpaired Older Black and White Adults
Authors: Bubu Omonigho Michael , Gills Joshua L , Cesar Oliver , Kovbasyuk Zanetta , Sogade Anamarie , Dominguez Joanna , Browne Laurel Y , Valkanova Elena , Mbah Alfred , Figueredo Luisa F , Kam Korey , Mullins Anna E , Parekh Ankit , Masurkar Arjun V. , Varga Andrew , Osorio Ricardo 
Published: January 2025

AbstractBackgroundWe examined racial differences between measures of limbic white matter tracts and objective sleep parameters in cognitively unimpaired older‐adults.MethodThis cross‐sectional study included 170 community‐dwelling cognitively unimpaired older‐adults (mean±SD: age = 67.2±5.2y) participating in NYU studies of sleep, aging, and memory. Subjects completed polysomnography (NPSG) and brain MRI. Sleep measures of interest included total sleep time (TST), NREM stages 2, 3 and REM sleep duration, sleep latency and fragmentation, slow sleep spindles (SSP), sleep spindle density (SPD), AHI4% and REM AHI4%. Microstructural properties of the cingulum, uncinate fasciculus (UF), and fornix were estimated using diffusional tensor imaging (DTI) metrics including radial kurtosis (RK), radial diffusivity (RD), and fractional anisotropy (FA). Adjusted Linear mixed‐effects regression models examined associations between race, sleep, race*sleep and DTI metrics.ResultParticipants were 44.1% Black with 16.8±2.5y of education. Subjects were relatively matched on AHI4%, age, BMI and educational level. In the cingulum, increased fragmentation was associated with higher RD ß[Left] = 0.0026, p = 0.022), decreased RK (ß[Right] = ‐0.0069, p = 0.039) in Blacks. Additionally, increased sleep latency was associated with reduced FA (ß[Right] = ‐0.0010, p = 0.019), higher RD (ß [Right] = 0.0010, p = 0.008) in Blacks. In the UF, increased fragmentation was associated with higher RD(ß[Left] = 0.0052, p = 0.019) and lower RK (ß[Right] = ‐0.0010, p = 0.039) in Blacks; increased AHI4%REM was associated with reduced FA ß[Left] = 0.0007, p = 0.041), higher RD (ß[Right] = ‐0.0007, p = 0.027) and lower RK (ß[AHI4%, Left] = ‐0.0029, p = 0.001) in Blacks. Furthermore, higher SSP (ßRight] = 0.00031, p = 0.045 and SPD (ß[Right] = 0.045, p = 0.025) was associated with higher RK in Blacks. In the cingulum of white participants, higher AHI4%REM was associated with reduced FA ß[right] = ‐0.0006, p = 0.013), higher RD ß[Left] = 0.0005, p = 0.051), and reduced RK ß[Right] = ‐0.00198, p = 0.008). Additionally, NREM stage‐2 sleep duration was associated with higher FA ß[Right] = 0.0010, p = 0.037) and higher RK ß[Right] = 0.0031, p = 0.040). In the UF, increased fragmentation was associated with reduced RK ß[Left] = ‐0.017, p = 0.047) in Whites.ConclusionCognitively‐unimpaired Black and White older‐adults showed sleep disruption associations with limbic white matter integrity, with race‐specific associations observed across various microstructural properties of the cingulum, UF, and fornix. Thus, highlighting possible sleep‐related underpinnings of racial differences in Alzheimer disease‐risk.
Amyloid burden and APOE modify sex differences in estimated meta‐temporal region tau onset age
Authors: Heston Margo B. , Cody Karly , Teague Jordan P , De Chavez Elena Ruiz , Morse Jacob , Deming Yuetiva , Engelman Corinne D. , Chappell Richard J , Langhough Rebecca E. , Gleason Carey E. , Clark Lindsay R. , Zuelsdorff Megan L. , Betthauser Tobey J. 
Published: January 2025

AbstractBackgroundRecent advances in Alzheimer’s disease (AD) temporal biomarker modeling have revealed considerable heterogeneity in age at amyloid onset, and recently we and others identified sex and APOE differences in tau onset age and subsequent dementia development. Here we assessed whether amyloid burden, APOE‐e4 dose, and sex interact to predict estimated T+ onset age (ETOA).MethodsAlzheimer’s Disease Neuroimaging Initiative participants (N = 911, Table 1) underwent serial PET imaging to quantify global cortical amyloid ([18F]Florbetapir SUVR50‐70, [18F]Florbetaben SUVR90‐110) and meta‐temporal tau ([18F]Flortaucipir SUVR80‐100) burden. Cortical amyloid SUVRs were harmonized using linear transformation to Centiloids (CL). Sampled iterative local approximation (SILA) was used to model ETOA and, separately, to estimate amyloid CL burden at ETOA. Kaplan‐Meier survival curves and Cox regression were used to test CL*APOE‐e4*sex interaction effects on ETOA. Event time was ETOA for T+ individuals and age at last tau PET scan (right censored) for T‐ individuals who could become T+.ResultsWe observed a significant CL*APOE‐e4*sex interaction on ETOA (p = 0.013, Table 2). APOE‐e4 was associated with earlier ETOA in a dose‐dependent manner and effects were greater in females compared to males. ETOA differences between sexes and across APOE‐e4 were attenuated at higher amyloid burden, largely due to the increased presence of T+ across all APOE‐e4 statuses and both sexes (Figure 1). Main effects also revealed that higher cortical amyloid burden at ETOA was associated with earlier ETOA and greater T+ risk, as was greater APOE‐e4 dose (Table 2).ConclusionsThese results suggest that amyloid burden, APOE‐e4, and sex may influence when temporal tau deposition becomes abnormal. Smaller sample size among APOE‐e4 carriers, and especially e4 homozygotes, limits the estimates in this cohort. Future extensions of this work will expand to a multicohort sample, to attempt replication of these findings and to investigate how these factors and their interaction predict time from amyloid and tau onset to dementia.
Addressing the gaps of the functional neuroimaging in young APOEe4 carriers: A systematic review and Graph Theoretical analysis of brain connectivity
Authors: Kucikova Ludmila , Brass Adam , Xiong Xing , Zeng Jianmin , Ritchie Craig , Muniz‐Terrera Graciela , O'Brien John T , Su Li 
Published: January 2025

AbstractBackgroundIn the last decade, extensive research has emerged into understanding the impact of risk factors for Alzheimer’s Disease (AD) on brain function in pre‐symptomatic stages. Here, we focused on the apolipoprotein e4 (APOEe4) gene, the major genetic risk factor for sporadic AD, and its effect on brain function in early adulthood.MethodIn the first part of the study, we systematically reviewed the multimodal functional neuroimaging literature, exploring its relationship with cognition, and the potential effects of other variables including the demographics, other risk factors, and methodological and analytical choices. While the studies demonstrated consistent alterations of APOEe4 carriers in brain connectivity and activity; the results of fMRI studies covered mostly the differences in the directionality using standard connectivity and activity measures. In the second part of this study, we aimed to address this gap by using the graph theory analysis to explore the dynamic behaviour of the six resting‐state networks of interest in young APOEe4 carriers versus non‐carriers (n = 129, aged 17‐22).ResultAverage Path Length and Closeness Centrality were consistently disrupted, pointing to network reorganisation in multiple resting‐state networks, albeit using different mechanisms.ConclusionThis study is the first to demonstrate the restructuring of multiple resting‐state networks in young adults modulated by the APOE genotype.
Synapse loss in early‐ and late‐onset Alzheimer’s Disease assessed by 18F‐SynVest‐1
Authors: He Kun , Xie Fang , Huang Qi 
Published: January 2025

AbstractBackgroundWe aimed to investigate the loss of synaptic density in early‐onset and late‐onset Alzheimer’s Disease.MethodOne hundred and eighty‐two participants underwent synaptic density PET with 18F‐SynVesT‐1. Including 23 early‐onset Alzheimer‘s Disease (EOAD), 58 late‐onset Alzheimer’s Disease (LOAD), 16 EOnonAD, 28 LOnonAD, 31 younger normal control (age < 65) and 26 older normal control (age ⩾ 65). We analyzed the synaptic density loss in EOAD and LOAD relative to their control group respectively. Associations between age and synaptic loss were evaluated in different groups.ResultEOAD and LOAD groups both displayed significant synaptic density across most areas of cerebrum cortex. Relative to LOAD group, EOAD group showed severer synaptic loss in Lateral Parietal lobe. In EOAD group, synaptic density in occipital lobe had positive association with age. While, in LOAD group, synaptic density in most areas of the cerebrum cortex had a negative association with age.ConclusionOur study suggested that the areas of synaptic loss were different between EOAD and LOAD.
Elevated iron levels in the older adult brain are associated with higher R2 relaxation rate in gray matter and more white matter hyperintensities: An ex‐vivo MRI, pathology and mass spectrometry study
Authors: Yasar Md Tahmid , Bush Ashley I. , Ayton Scott , Agarwal Puja , Agrawal Sonal , Bennett David A. , Schneider Julie A. , Arfanakis Konstantinos 
Published: January 2025

AbstractBackgroundElevated iron in brain is a source of free radicals that causes oxidative stress which has been linked to neuropathologies and cognitive impairment among older adults. The aim of this study was to investigate the association of iron levels with transverse relaxation rate, R2, and white matter hyperintensities (WMH), independent of the effects of other metals and age‐related neuropathologies.MethodCerebral hemispheres from 437 older adults participating in the Rush Memory and Aging Project study (Table 1) were imaged ex‐vivo using 3T MRI scanners. R2 maps were generated from multi‐echo spin‐echo data and then registered to an ex‐vivo brain template. WMH were segmented based on T2‐weighted images. WMH volume was normalized by the total hemisphere volume and then log‐transformed. Following ex‐vivo MRI, all hemispheres underwent neuropathologic assessment including Aß plaques, neurofibrillary tangles, LATE‐NC, hippocampal sclerosis, Lewy bodies, cerebral amyloid angiopathy, gross infarcts, microscopic infarcts, atherosclerosis, and arteriolosclerosis (Table 1). Inductively coupled plasma mass spectrometry was used to measure brain trace metal levels. The assessed metals included iron, boron, titanium, manganese, copper, zinc, selenium, rubidium, molybdenum, and mercury (Table 1). Linear regression was used to test the association of R2 and WMH burden with iron levels. All models were controlled for all other metals and neuropathologies listed above, demographics (age at death, sex, years of education), the presence of the APOE‐e4 allele, postmortem interval to fixation and to imaging, and scanner. Statistical analysis was performed using PALM, with tail‐accelerated 5,000 permutations. Statistical significance was set at p<0.05 after family wise error rate correction.ResultThe voxel‐wise analysis revealed a spatial pattern of higher R2 for higher iron levels, particularly in gray matter (Fig. 1). The pattern included basal ganglia structures such as the globus pallidus and putamen, and cortical regions including the precentral, postcentral and cuneus cortex (Fig. 1). Higher lobar and total WMH burden were also associated with higher iron levels (Fig. 2). No negative associations were observed.ConclusionThis investigation combined ex‐vivo MRI, neuropathology and mass spectrometry in a community‐based older adults and showed that higher iron levels were independently associated with higher R2 in gray matter and higher WMH burden.