bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal Association of Imaging Biomarkers of Cerebrovascular Disease and Alzheimer’s Disease
Authors: Cogswell Petrice M , Lundt Emily S. , Therneau Terry M. , Wiste Heather J. , Graff‐Radford Jonathan , Schwarz Christopher G. , Senjem Matthew L. , Gunter Jeffrey L. , Vemuri Prashanthi , Petersen Ronald C. , Jack Clifford R. 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) pathologic changes (e.g. amyloid and tau aggregation), and cerebrovascular disease often coexist, and it remains unclear whether these are mechanistically linked processes (Graff‐Radford, Brain 2019; Provenzano, JAMA Neurol 2013). Most studies evaluating these associations are cross‐sectional; however, establishing temporal relationships may provide additional insight into potential mechanistic associations. One method to assess the temporal evolution of a biomarker is the Accelerated Failure Time (AFT) model, which assumes a common pattern of progression for a given biomarker that is shifted earlier or later in time for each individual (Therneau, Neuroimage 2021). In this work we investigate the relationship of disease trajectories of cerebrovascular disease (via white matter hyperintensity, WMH, volume) and AD biomarkers (via amyloid and tau PET).MethodsWe included Mayo Clinic Study of Aging (MCSA) and Mayo Alzheimer’s Disease Research Center (ADRC) participants with amyloid PET, tau PET, and MRI, age > 50 years, and a clinical diagnosis of cognitively unimpaired (CU), mild cognitive impairment (MCI) or Alzheimer’s disease dementia. The AFT model was fit with amyloid PET (PiB) global meta‐ROI SUVR, tau PET (flortaucipir) temporal meta‐ROI SUVR, and WMH volume as the tri‐variate endpoints, with APOE genotype, sex, education, total intracranial volume, and referral/population subject as covariates. A per subject/endpoint random effect represents individual adjustments for each biomarker to indicate if the subject's biomarker became abnormal earlier or later relative to their demographic peers, accounting for the covariates.ResultsThe study included 1144 participants (Table 1). There was a strong correlation between earlier onset of amyloid and earlier onset of tau (r=0.64, CI=0.60‐0.67) (Figure 1, Table 2); early/late amyloid timing explained nearly half (0.642 = 41%) of the variation in tau onset. There were only weak associations between an individual’s WMH and amyloid PET onset adjustments (r=0.10, 1.0%) and WMH and tau PET onset adjustments (r=‐0.07, 0.5%).ConclusionThis analysis supports a strong mechanistic relationship between amyloid and tau aggregation, as reported by others. However, our findings do not support a mechanistic association between WMH and amyloid or tau PET.
Clinical and genetic features of Lewy body pathology in autosomal dominant and sporadic Alzheimer disease
Authors: Vöglein Jonathan , Ryan Natalie S , Bateman Randall J. , Paumier Katrina L. , Cairns Nigel J , Franklin Erin E. , Perrin Richard J. , Xiong Chengjie , Jucker Mathias , Lashley Tammaryn , Arzberger Thomas , Herms Jochen , Dieterich Marianne , Höglinger Günter , Danek Adrian , Morris John C. , Fox Nick C , Levin Johannes 
Published: December 2022

AbstractBackgroundLewy body pathology (LBP) occurs in a substantial portion of individuals with autosomal dominant (ADAD) and sporadic Alzheimer disease (sAD) (Ringman, 2016; Cairns, 2015; Leverenz, 2007; Lippa, 1998). Whereas other non‐AD pathologies are frequent in sAD, LBP seems to be the most common co‐pathology in the relatively young ADAD population (Cairns, 2015). Knowledge of clinical and genetic characteristics of LBP in both ADAD and sAD is incomplete.MethodData from the National Alzheimer’s Coordinating Center, the Dominantly Inherited Alzheimer Network, the Queen Square Brain Bank at University College London and the Neurobiobank Munich were leveraged to compare individuals with ADAD and neuropathologically diagnosed sAD with and without LBP. Chi‐squared and Student’s t‐test were used for comparison of categorical and continuous variables respectively.ResultThe study included 139 ADAD and 4661 sAD autopsy cases. LBP occurred in 59% of ADAD and 38% of sAD cases. LBP was associated with a longer survival in both ADAD (10.1 vs. 8.6 years, p=0.024) and sAD (10.5 vs. 10.2 years, p=0.016). Memory disturbance occurred more frequently as the first clinical AD symptom in both AD variants when LBP was present (ADAD: 90 vs. 65%, p=0.005; sAD: 78 vs. 71%, p<0.001). In both ADAD and sAD, the presence of at least one APOE e4 allele was more common in individuals with LBP (ADAD: 40 vs. 21%, p=0.047; sAD: 57 vs. 46%, p<0.001). In ADAD, frequency of LBP did not differ between individuals with PSEN1 and APP mutations.ConclusionIn this investigation of 139 ADAD and 4661 sAD autopsy cases, LBP occurred in about 60% with ADAD and 40% with sAD. In both ADAD and sAD, the presence of LBP was associated with longer survival, higher frequency of memory disturbance as the first AD symptom and positive APOE e4 status. Further study of these associations may increase our understanding of the role of LBP in AD.
Prognostic utility of baseline [18F]GTP1 tau PET signal for subsequent cognitive and functional decline in prodromal‐to‐mild Alzheimer's disease
Authors: Ruiz‐Uribe Nancy E , Manser Paul T , Bohorquez Sandra Sanabria , Baker Suzanne L. , Monteiro Cecilia , Teng Edmond 
Published: December 2022

AbstractBackgroundPrior studies of tau PET tracers in participants with normal cognition and/or a broad range of Alzheimer’s disease (AD) severity suggest baseline tau PET signal is associated with subsequent rates of cognitive decline. However, the prognostic utility of tau PET imaging is less well‐established within more homogenous cohorts limited to specific AD stages and for cognitive versus functional decline. We addressed these questions by analyzing baseline [18F]GTP1 tau PET signal and longitudinal changes in cognitive and functional measures in the Phase 2 Tauriel study of semorinemab in prodromal‐to‐mild AD.MethodsWe analyzed data from a subset of Tauriel participants with prodromal AD (pAD; n=127) or mild AD (mAD; n=233) who underwent baseline [18F]GTP1 tau PET and longitudinal assessments with the Clinical Dementia Rating‐Sum of Boxes (CDR‐SB), Alzheimer’s Disease Assessment Scale‐Cognitive Subscale (ADAS‐Cog13), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and/or Alzheimer’s Disease Cooperative Study‐Activities of Daily Living (ADCS‐ADL). As no treatment effects were observed with semorinemab in Tauriel, data were pooled across semorinemab and placebo arms. Associations between baseline [18F]GTP1 SUVRs and annualized longitudinal change on each measure were explored using Pearson correlations and multiple linear mixed effects regression models adjusting for relevant baseline covariates.ResultsBaseline cortical [18F]GTP1 SUVRs and longitudinal decline on clinical measures were significantly greater in mAD relative to pAD cohort. Prognostic associations with baseline cortical [18F]GTP1 were similar in pAD and mAD and more robust for predominantly cognitive measures (ADAS‐Cog13: pAD rs=0.37, mAD rs=0.35; RBANS Total Index: pAD rs=‐0.40, mAD rs=‐0.41) than measures incorporating functional status (CDR‐SB: pAD rs=0.27, mAD rs=0.29; ADCS‐ADL: pAD rs=‐0.12, mAD rs=‐0.26). Analogous results were seen using temporal or Braak stage regions of interest. [18F]GTP1 associations with cognitive decline generally remained significant after adjusting for baseline cognitive score, age, hippocampal volume, and education.ConclusionsHigher baseline [18F]GTP1 tau PET signal was associated with faster subsequent clinical decline in both prodromal and mild AD. More robust associations were seen with cognitive relative to functional measures. These results bolster prior work that suggests a role for tau PET in patient selection/stratification in AD clinical trials.
Identification of ABCA7 SNP‐by‐CpG interactions associated with cognition in older African Americans
Authors: Chaar Dima Leila , Nguyen Kim , Wang Yi Zhe , Ratliff Scott , Mosley Thomas H , Kardia Sharon L R , Smith Jennifer A , Zhao Wei 
Published: December 2022

AbstractBackgroundThe ABCA7 gene confers the largest genetic risk for Alzheimer’s Disease (AD) in African Americans (AA) after APOE ε4. However, the relationship between ABCA7 and cognitive function has not been thoroughly examined in AA without dementia. We investigated the effect of genetic variants and epigenetic markers in ABCA7, as well as their interaction, on cognition in older AA without dementia.MethodThe sample included 629 cognitively normal AA from the Genetic Epidemiology Network of Arteriopathy (GENOA). Methylation at 72 CpG sites located within 5kb of ABCA7 were measured using the Illumina EPIC array. General cognitive function (cognition) was measured by taking the first principal component of five cognitive tests. The association between SNPs and cognition was assessed using linear mixed models controlling for age, sex, education, population structure and relatedness. The association between CpGs and cognition was assessed using the same model with further adjustment for white blood cell proportions, batch effects and smoking. We also evaluated SNP‐by‐CpG interactions.ResultNo SNPs were associated with cognition at p<0.05. A 1% change in methylation at three CpGs (cg22271697, cg11714200, cg12082025) was associated with a 0.02‐0.10 standard deviation (SD) increase in cognition (p<0.05; no associations significant at FDR q<0.1). Four SNP‐by‐CpG interactions were associated with cognition (FDR q<0.1). Contrast tests show that methylation is associated with cognition in some genotype groups (p<0.05): a 1% methylation increase at cg22271697 is associated with a 0.13 SD increase in cognition for those with the AA rs3764647 genotype, a 1% increase at cg06169110 is associated with a 0.35 SD decrease in cognition for those with the rs115550680 GG or AG genotype, and a 1% increase at cg00135882 is associated with a 1.19 SD decrease in cognition for those with a rs3764650 GG genotype.ConclusionWhile AD risk SNPs in ABCA7 are not associated with cognition in the full sample of older African Americans, some do interact with proximal methylation to influence cognition. This suggests that a complicated interplay between genetic and epigenetic factors in ABCA7 may influence cognition in cognitively normal AA. A similar mechanism may play a role in cognitive aging and decline.
An autopsy‐validated, easily deployable MRI predictor of Alzheimer’s disease tau pathology
Authors: Vogel Jacob W , Strandberg Olof , Gaiteri Chris , Cieslak Matthew , Covitz Sydney , Wolk David A. , Davatzikos Christos , Hansson Oskar , Satterthwaite Theodore 
Published: December 2022

AbstractBackgroundTau pathology is a hallmark of Alzheimer’s disease, but measuring this pathology in vivo with PET is expensive. MRI represents a low‐cost alternative for measuring in vivo disease progression, but is non‐specific. We present an MR‐based marker of tau‐specific pathology using machine learning (ML).Method1851 pairs of RO948 tau‐PET and T1‐weighted MRI scans were aggregated from 1262 BioFINDER II study participants. The Braak I‐IV ROI from Cho et al., 2016 was used to represent tau‐pathology. A tau‐positive threshold (SUVR=1.41) was defined using Gaussian mixture modeling, and Braak I‐IV SUVR was z‐scored using the mean and SD of the tau‐negative group. A grid search of 80 ML pipelines with 100 rounds of nested 5‐fold cross‐validation was performed while varying estimator, dimension reduction strategy, preregression of intracranial volume (ICV), and one vs multiple scans‐per‐subject. For all models, 294 features from Freesurfer were used. The best‐performing model was then applied to 1225 participants from the ROSMAP cohort, yielding MR‐predicted tau. A subset (n=159) of these participants had postmortem AT8‐immunostained tau pathology, Braak staging, TDP‐43 and lewy body pathology.ResultThe best pipeline involved random forest regression with FDR‐based feature selection (RMSE[95%CI]=3.67[3.6‐3.8]; R2[95%CI]=0.42[0.40‐0.45]; Figure1; Figure2A). (Lack of) ICV pre‐regression had the biggest positive impact across pipelines. This model significantly predicted zTau in both tau‐postive and tau‐negative individuals (Figure2B), and showed fair weighted precision (0.84) and recall (0.80) in tau‐positivity classification (Figure2C). Temporoparietal and medial temporal regions contributed most to predictions (Figure2D). When applied to ROSMAP, antemoretem MR‐predicted tau predicted postmortem tau pathology (p=0.001) and Braak stage (p=0.005; Figure3A) but not other pathologies (Figure3B), predicted clinical diagnosis and progression (Figure3C), and outperformed a common neurodegeneration marker (Figure3D‐F).ConclusionWe create an easily deployable tau‐specific MRI biomarker, which was validated using postmortem tau pathology in a separate dataset. MR‐predicted tau provides a more specific non‐invasive biomarker for researchers without access to PET.
Examining cerebrovascular burden across the cognitive continuum in older adults with and without evidence of amyloidosis
Authors: Rivera‐Rivera Leonardo A , Cody Karly Alex , Betthauser Tobey J , Koscik Rebecca Langhough , Jonaitis Erin M. , Cadman Robert V. , Hermann Bruce P , Rowley Howard A. , Carlsson Cynthia M. , Chin Nathaniel A. , Eisenmenger Laura , Johnson Sterling C. , Johnson Kevin M 
Published: December 2022

AbstractBackgroundThis work characterized cerebrovascular health in human subjects spanning the cognitive spectrum with and without presence of Aβ using different neuroimaging techniques (Fig1).MethodsSubjects (n=70) were clinically characterized into four groups: cognitively unimpaired (CU), CU‐Declining (at‐risk of progressing to clinical mild MCI based on traditional neuropsychological data), clinical MCI, and clinical dementia (Fig2). MRI: Vascular imaging: Whole‐brain 4D‐Flow data were acquired to characterize cerebrovascular health. pCASL with three post labeling delays was used to provide transit time corrected CBF maps. Structural imaging: T1‐weighted and T2‐FLAIR images were also collected for quantification of intracranial, hippocampal and white matter hyperintensity volumes. Hemodynamic measurements were extracted from intracranial arteries including the petrous ICAs, BA, MCAs, and veins SSS. Quantified flow parameters included: total cerebral blood flow, trans‐capillary pulse wave delay, and flow pulsatility index (PI). Trans‐capillary pulse wave delay was defined as the time shift between arterial and venous cardiac waveforms. PET: Aβ burden was assessed using 11C‐PiB PET imaging. Amyloid positivity (A‐, A+) was established as mean cortical PiB DVR >1.16. For A+ participants, amyloid time (i.e., estimated duration A+) was estimated using the sampled iterative local approximation algorithm. Differences were assessed using ANOVA followed by post‐hoc analysis (P<0.05 significance).ResultsMicro‐vascular tissue perfusion was statically higher in A+/CU when compared to other A+ groups in the GM, WM, and hippocampus (Fig3 and 4). Trans‐capillary pulse wave delay was statistically longer in A+/CU when compared to A+/CU‐Declining, A+/MCI, and A+/dementia (Fig5A). For A‐ groups trans‐capillary pulse wave delay was similar; yet, flow PI was statistically higher in A‐/CU‐Declining and A‐/MCI when compared to A‐/CU in the ICAs and MCAs (Fig5 C, D). Flow PI in A+/CU was higher than in A‐/CU.ConclusionsDecreased micro‐vascular tissue perfusion and shorter trans‐capillary pulse wave delay in A+ subjects with cognitive alterations (e.g. CU‐Declining, MCI, Dementia) compared to A+/CU indicates decreased metabolism and increased small vessel stiffness may contribute to cognitive decline and/or are induced by amyloidosis. In contrast, for A‐ subjects significant differences in arterial flow pulsatility index between A‐/CU, CU‐Declining, and MCI suggests macro‐vascular arterial stiffness contributes to cognitive decline.
Genome‐wide association study of plasma apolipoprotein E levels and risk of dementia in older adults
Authors: Aslam Muhammad Muaaz , Fan Kang‐Hsien , Lawrence Elizabeth C , Bedison Margaret A , Snitz Beth E , DeKosky Steven T , Lopez Oscar L. , Feingold Eleanor , Kamboh M. Ilyas 
Published: December 2022

AbstractBackgroundThe APOE 2/3/4 polymorphism is the greatest risk factor for Alzheimer’s disease (AD). This polymorphism is also associated with variation in plasma ApoE levels and explains about 20‐25% of its genetic variance; while APOE*4 lowers, APOE*2 increases ApoE levels. Lower plasma ApoE levels have also been reported to be a risk factor of future AD and all dementia, independent of the APOE 2/3/4 polymorphism (Ann Neurol 2015;77:301). To our knowledge, no genome‐wide association study (GWAS) has been reported on plasma ApoE levels. This study was aimed to identify novel genetic factors affecting plasma ApoE levels as well as to confirm if baseline plasma ApoE levels predict future AD dementia in an older and longitudinally followed cohort of the Ginkgo Evaluation of Memory (GEM) study.MethodBaseline plasma ApoE levels were measured using an immunoturbidimetric assay in 3,031 older subjects (aged 72 to 96 years; 94.1% White). Genome‐wide genotype was performed on the available 2,737 DNA samples (96% White). Due to the small number in other ethnicities, we only included the 2,852 White subjects (2,412 cognitively normal, 440 with incident AD dementia) for plasma ApoE analysis. GWAS analysis on plasma ApoE levels was performed on 2,580 White subjects where both genotype and ApoE level data were available.ResultAs expected, the risk for AD increased from E2/2 through to E4/4 genotypes (p for trend =1.7E‐10). There was no significant difference in plasma ApoE levels between cognitively normal and AD dementia subjects (p=0.55). GWAS analysis revealed the expected associations of APOE*2 (β= 1.12; p= 3.57E‐79) and APOE*4 (β= ‐0.35; p= 2.21E‐11) with plasma ApoE levels. In addition, we observed 5 novel genome‐wide significant associations on chromosomes 1 (β= 0.921; p= 5.36E‐10), 4 (β= 0.796; p= 4.31E‐08;), 7 (β= 0.722; p= 9.64E‐09), 11 (β= 0.268; p= 2.58E‐08), and 20 (β= 1.379; p=8.25E‐09).ConclusionWe have identified multiple novel associations affecting plasma ApoE levels in addition to the established APOE association. However, we could not replicate the reported association of plasma ApoE levels with future AD, probably because of the older nature of our cohort.
Vessel distance mapping: a novel methodology for assessing vascular‐induced cognitive resilience
Authors: Garcia‐Garcia Berta , Mattern Hendrik , Vockert Niklas , Yakupov Renat , Schreiber Frank , Spallazzi Marco , Perosa Valentina , Speck Oliver , Duzel Emrah , Maass Anne , Schreiber Stefanie 
Published: December 2022

AbstractBackgroundThe association between cerebral blood supply and cognition has gained increasing interest, considering the remarkable anatomical variability of the circle of Willis. Thus, qualitative classifications of the arteries contributing to the hippocampal supply has been performed in previous studies to determine whether the additional presence of vessels might translate into cognitive differences and cerebral structural changes when coexisting with vascular pathology, to the extent of constituting a cognitive reserve. Nevertheless, the promising results in these regards are not without controversy. Hence, Vessel Distance Mapping (VDM) is here introduced, in order to ascertain the correlation of VDM‐metrics with each other and with cognitive status, as well as to elucidate which metrics have the greatest impact on cognition.MethodA battery of cognitive tests was used (including ADAScog and MoCA) in 51 subjects (71 ± 8.5yrs) with (n=20) and without (n=31) cerebral small vessel disease. Their hippocampal‐related vessels were manually segmented by using high‐resolution 7T Time‐of‐Flight‐MRI. Vessel distance maps were generated by computing the distances of each voxel to its nearest vessel, obtaining 3 VDM‐metrics: global‐VDM (vessel density surrogate), VS‐VDM (vessel‐specific supply), and COMD (distance to the center of mass, reflecting vessel distribution). Hippocampal masks were used to assess the whole and subregional hippocampus. Regression models were applied for evaluating the interrelation among the metrics, and their association with cognition.ResultHigh correlations were observed for intra‐metric comparisons, as well as when comparing whole hippocampal vs. sub‐hippocampal metrics. Greater values of VDM‐metrics reflecting higher distances among vessels were associated with poorer cognitive outcomes only in subjects affected by vascular pathology (global‐VDM R²=0.7248, p=0.0054; COMD R²=0.7248, p=0.0013). Metrics revealing vascular distribution (p=0,0053) and density (p=0,0169) were the most influential on cognition, and in this context those for the whole hippocampus predominated over the subregional ones.ConclusionA mixed contribution of vessel distribution and density is proposed to confer cognitive resilience, in a way consistent with anatomical fundamentals and with previous research findings. VDM provides a new, structure‐driven approach on which to raise new questions supported by the statistical robustness of a quantitative method with potential clinical implications.
Altered functional connectivity networks in logopenic progressive aphasia and posterior cortical atrophy
Authors: Singh Neha Atulkumar , Graff‐Radford Jonathan , Sintini Irene , Machulda Mary M. , Gunter Jeffrey L. , Lowe Val J. , Botha Hugo , Jones David T. , Jack Clifford R. , Josephs Keith A , Whitwell Jennifer L 
Published: December 2022

AbstractBackgroundResting state functional connectivity (rsfMRI) studies have shown functional network disruptions in logopenic progressive aphasia (LPA) (reduced connectivity within the left temporal language network) and posterior cortical atrophy (PCA) (reduced connectivity within ventral visual network). However, little is known about how these networks compare and how connectivity differs within and between networks in these atypical Alzheimer’s Disease (AD) phenotypes.MethodFifty‐nine amyloid‐positive PCA patients and eighty‐five amyloid‐positive LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent structural and resting state functional MRI. Spatially preprocessed data was analyzed using the CONN functional connectivity toolbox to explore the default mode network (DMN), salience, sensorimotor, left language, visual and memory networks, which were generated by averaging multiple regions‐of‐interest (ROI) within each network. The data was analyzed at both the voxel‐level and network‐level (ROI‐ROI).ResultVoxel‐level differences in functional connectivity between PCA and LPA were observed in all networks (p<0.05; cluster size, FWE=0.05). PCA showed reduced connectivity in the occipital lobe in visual and memory networks, parietal lobe in language and DMN, and sensorimotor strip in sensorimotor network, particularly on the right, compared to LPA. Conversely, LPA showed reduced connectivity in the frontal cortex in salience, memory, visual and sensorimotor networks, inferior parietal lobe in visual network, and anterior temporal pole and sensorimotor cortex in the language network, compared to PCA. Between network differences (p<0.05; cluster size, FDR=0.05) were observed between groups, with PCA showing reduced connectivity between the visual and sensorimotor networks, while LPA showed reduced connectivity between the language and sensorimotor networks. The DMN was anti‐correlated to the language network in PCA, while it was positively correlated to the language network in LPA. In both phenotypes, the DMN was anticorrelated with the salience network. The visual network in PCA showed connections to all networks, while in LPA, it was only connected to the salience, language and DMN.ConclusionThe atypical AD phenotypes were associated with multiple disruptions in connectivity, both within and between brain networks. Phenotype specific differences in connectivity patterns were noted in visual network for PCA and language network for LPA.