bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic drivers of longevity provide protection against Alzheimer's disease pathology
Authors: Riedel Brandalyn C. , Dumitrescu Logan , Hohman Timothy J. , Saykin Andrew J. 
Published: December 2020

AbstractBackgroundGenome‐wide association studies (GWAS) have consistently found human longevity correlations within the APOE gene cluster (APOE, APOC1, TOMM40, PVRL2). Many variants in this cluster show inverse effects between longevity and Alzheimer’s disease (AD). This suggests genetic pleiotropy between AD and longevity, e.g., the APOE ε2 allele is associated with both protection from AD and increased longevity. Recent evidence supports the idea that certain aged individuals do not have significant AD pathology, exhibiting AD resistance. Here we sought to determine whether a genetic signal of AD resistance could be identified by leveraging previous GWAS of longevity and AD pathology.MethodWe used a large meta‐analysis of longevity, defined as reaching the 90th age percentile for a birth cohort compared to those who reach the 60th. Following p‐value informed LD‐clumping (r2 ≥ 0.1), we used random‐effects regression to meta‐analyze three GWAS on AD phenotypes: cerebrospinal fluid levels of amyloid, and phosphorylated tau, as well as amyloid PET imaging. Subsequent methods are shown in Figure 1 and involved mapping variants to genes and determining gene scores and pathway enrichment using PASCAL.ResultsVariants showing discordant effects between AD pathology and longevity (increased pathology/decreased longevity or decreased pathology/increased longevity) included APOE and others across the genome. The top Reactome pathways (p < 0.05) included those involved in axon growth and guidance (Signal transduction and recycling by L1, signalling of NGF, Neurotrophin signalling), cell survival and apoptosis (MAPK pathway, ERK/MAPK targets, NFKB/MAPK activation by TLR4), lipid metabolism (chylomicron‐mediated and HDL‐mediated lipid transport), and the immune system (innate and adaptive).ConclusionSignificant pleiotropy exists between longevity and AD pathology, implying that focus on discordant effects may yield novel insights relevant to AD resistance. Ongoing work seeks to map results from our discordance analysis to an AD‐specific transcriptional regulatory network created from the Harvard Brain Tissue Resource Center data, with hubs of known transcription factors. This will allow identification of functional modules via eQTL enrichment, will help to further characterize these effects, and may prove useful for downstream drug repurposing analyses.
A case report of a patient with mild cognitive impairment preceded by transient global amnesia with hypometabolism on FDG‐PET
Authors: Yu Justine Megan F. , Dominguez Jacqueline C 
Published: December 2020

AbstractBackgroundThis is the case of a 61‐year‐old Filipino female who presented with two episodes of transient global amnesia at the ages of 56 and 57.MethodThe patient underwent serial cranial MRI, cranial FDG‐PET/CT scan, and cognitive assessments over a period of five years.ResultCranial MRI at the time of the first episode in 2014 showed foci of restricted diffusion abnormality in the left hippocampus. Baseline cognitive assessment was negative for any impairment. On recurrence of TGA in 2015, brain FDG‐PET/CT scan was done which showed mild hypometabolism in the temporal and parietal cortices and hypometabolism in the posterior cingulate cortex. A second comprehensive cognitive assessment was negative for any impairment. Three years after the first episode (2017), she developed subtle changes in memory and thinking and had mild impairment in categorical fluency on neuropsychologic examination. Follow‐up cranial MRI (2017) showed slight decrease in hippocampal volumetry from the 43rd percentile to the 41st normative percentile. Follow‐up cranial FDG‐PET (2019) showed small mildly hypometabolic areas in the frontal, parietal and temporal lobes. The clinical assessment for the patient at this time is very mild cognitive impairment, non‐amnestic, probably secondary to a neurodegenerative process.ConclusionThis case study shows that transient global amnesia can recur and it may be a risk for cognitive impairment. It also illustrates that existing brain pathology related to a neurodegenerative process can be evident on neuroimaging despite very subtle clinical and neuropsychological cognitive changes. These findings also support aggressive preventive measures of delaying cognitive impairment.
Increased white matter MRI T1 hypointensity volume in young‐onset Alzheimer’s disease patients is not accounted for by age or cardiovascular risk factors
Authors: Flaherty Ryn , Ezzo Rania , Collins Jessica A. , Krivensky Samantha , Eckbo Ryan , Vemuri Prashanthi , Borowski Bret J. , Iaccarino Leonardo , La Joie Renaud , Lesman‐Segev Orit H. , Bourakova Viktoriya , Eloyan Ani , Aisen Paul S. , Fagan Anne , Foroud Tatiana M. , Gatsonis Constantine , Jack Clifford R. , Kramer Joel H. , Koeppe Robert A. , Saykin Andrew J. , Toga Arthur W. , Day Gregory S , Graff‐Radford Neill R. , Honig Lawrence S. , Jones David T. , Masdeu Joseph C. , Mendez Mario F. , Onyike Chiadi U. , Rogalski Emily J. , Salloway Stephen P. , Wolk David A. , Wingo Thomas S. , Carrillo Maria C. , Apostolova Liana G. , Rabinovici Gil D. , Dickerson Brad C. 
Published: December 2020

AbstractBackgroundWhite matter (WM) hypointensity volume in T1 MRI correlates strongly with T2 hyperintensities and both are typically associated with advancing age and vascular brain injury (VBI). Recent research has suggested that Alzheimer’s Disease (AD) neuropathologic changes (ADNC) also increases WM hypointensity volume. Sporadic early onset AD (EOAD) patients provide a unique model to examine the relationship between ADNC biomarkers and WM hypointensity volume in the absence of advanced age, cardiovascular injury, or autosomal dominant genetic mutations.MethodIncluded in the analysis were sporadic EOAD patients (n = 75) and cognitively normal controls (n = 39) from the Longitudinal Alzheimer’s Disease Study (LEADS) for whom full demographic and health information were available. WM hypointensity volume in T1 MRI was segmented by Freesurfer and corrected for total white matter volume. Multiple‐factor ANOVA models with logarithmic transformations were used to determine the effects of age, cohort, and presence of cardiovascular conditions on WM hypointensity volume. Further multiple‐factor ANOVA models assessed whether the addition of covariates improved the model fit.ResultIn a reproduction of prior research, WM hypointensity volume was correlated with age for controls (p < 0.05), but not for EOAD patients. We additionally found an effect of cohort, such that EOAD patients had a higher mean WM hypointensity volume than controls when accounting for age (p < 0.05). No difference in the presence or number of cardiovascular conditions was found between groups. Additionally, no correlation was found between WM hypointensity volume and the presence or number of cardiovascular conditions. Including cardiovascular condition as a covariate failed to improve the model fit, even when accounting for interaction effects.ConclusionThese results support the hypothesis that patients with ADNC have higher WM hypointensity volume beyond what would be expected based on aging or cardiovascular risk factors. Further research is needed to assess the co‐localization of WM hypointensities with cortical degradation, amyloid pathology, and tau pathology.
Collection of genetic data in population‐based studies across urban and rural areas: The challenges of the Mexican Health and Aging Study
Authors: Reyes‐Dumeyer Dolly , Samper‐Ternent Rafael , Obregon Alejandra Michaels , Arango Silvia Mejia , Mayeux Richard , Tosto Giuseppe , Barral Sandra , Wong Rebeca 
Published: December 2020

AbstractBackgroundThe Mexican Health and Aging Study is a longitudinal study aimed to evaluate the impact of age‐related diseases among adults 50 years and older in both urban and rural areas of Mexico. Over a 20‐year follow‐up period the study has collected data on cognitive function, health and socio‐economic factors among the study participants. In addition, blood and saliva samples are available from 2,800 and 7,862 participants respectively. The DNA extracted from blood and saliva samples will be used to conduct downstream genetic analyses.MethodThe saliva collection cohort consisted of participants aged 60 and older from the Mexican Health and Aging Study willing and able to provide a sample. Interviewers across Mexico were trained to collect and ship the saliva samples to the headquarters of the National Institute of Statistics (INEGI) in Aguascalientes, Mexico. Saliva samples passing quality control process were sent to the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) in Indiana, for DNA extraction and storage. DNA samples were distributed to different institutions for genetic analysis: APOE genotyping was conducted at LGC Genomics and genome wide genotyping at the Children’s Hospital of Philadelphia. A subset of the samples were subject to whole genome sequencing conducted by the Uniformed Services University of the Health Sciences.ResultA total of 8,156 saliva samples were collected of which 279 failed customs clearance for shipment from Mexico to the USA. 0.23% samples were dropped at extraction and 0.23% failed DNA quality standards for genotyping. A total of 7,832 samples were used for APOE, genome‐wide genotyping and whole genome sequencing.ConclusionSample collection for genetic studies in remote rural areas of developing countries such as Mexico present important logistical challenges. The use of saliva as a main source of DNA provides a non‐invasive, low cost, effective and feasible alternative to blood sample collection. Our results suggest that similar protocols can take place in other under‐represented populations of Latin America. Future work will aim to augment the analytical power of the cohort by collecting saliva samples from additional subjects of the MHAS cohort.
A network‐based, multi‐omics atlas for target identification and prioritization in Alzheimer’s disease
Authors: Wörheide Maria , Krumsiek Jan , Nho Kwangsik , Huynh Kevin , Meikle Peter J. , Saykin Andrew J. , Kaddurah‐Daouk Rima F. , Kastenmüller Gabi , Arnold Matthias 
Published: December 2020

AbstractBackgroundAlzheimer’s disease (AD) is an untreatable neurodegenerative disorder that represents a major global health burden. Large investments in the generation and analysis of increasing amounts of multi‐omics data have provided us with multi‐layered molecular imprints of pathogenic processes in AD. To identify the most promising targets for translating these readouts into development of novel therapies, it is crucial to take into account the complex biology underlying this heterogeneous disease via evaluating potential targets utilizing the entirety of multi‐omics evidences. However, integrated cross‐omics analyses are complicated and often lack intuitive and interpretable representation.MethodWe propose a network‐based, multi‐omics framework that allows for large‐scale analysis of data on biological entities across omics, as well as their associations with AD and related biomarker changes. Using Neo4j, a graph database, we store and interconnect these diverse biological domains in accessible network structures. Known biological relationships available in public databases such as gene‐transcript‐protein relations and pathway annotations constitute the backbone of this multi‐layered network. Large‐scale quantitative data from population‐based studies are included to establish data‐driven relationships within and across omics as a reference. To identify entities within this network that are relevant to AD pathomechanisms, the framework is finally overlaid with a comprehensive set of association data from multi‐omics screens in large AD cohorts generated through the AMP‐AD initiative.ResultThe resulting heterogeneous meta‐network is comprised of protein‐coding genes annotated with differential abundance in AD, readouts on more than 1000 metabolites and a large set of AD biomarkers and related phenotypes. Genes, proteins, metabolites, and AD phenotypes are interconnected by more than one million statistical links, including genetic and phenotype associations as well as gene/metabolite coexpression and co‐regulation data. We provide access to this comprehensive resource through an intuitive web‐interface, along with interactive visualizations and query and analysis tools of phenotype‐associated multi‐omics subnetworks.ConclusionThe AD Atlas is a comprehensive and intuitive framework that facilitates the integration, exploration, and exploitation of large‐scale multi‐omics data. Applications of this resource include the network‐based identification of multi‐omics modules centrally linked to AD pathogenesis, followed by the prioritization of identified potential therapeutic targets for AD.
Circulating cell‐free DNA of mitochondrial origin connects cognitive and physical decline in aging and is associated with increased mortality
Authors: Nidadavolu Lolita S. , Feger Danielle M. , Gross Alden L. , Bennett David A. , Walston Jeremy , Abadir Peter , Oh Esther S. 
Published: December 2020

AbstractBackgroundMitochondrial dysfunction and subsequently impaired energetics triggering cell death have been observed in both dementia and frailty. Cell death releases circulating cell‐free DNA (ccf‐DNA) from mitochondrial (ccf‐mtDNA) and nuclear (ccf‐nDNA) sources. Size and relative abundance of ccf‐mtDNA fragments is suggestive of mechanism of cell death; long ccf‐mtDNA fragments originate from cell necrosis and short ccf‐mtDNA fragments from apoptosis. Our hypothesis is that in aging there is common pathophysiology contributing to development of physical and cognitive decline and that ccf‐mtDNA are potential mediators of these changes.MethodUsing ultra‐sensitive digital PCR, mitochondrial and nuclear ccf‐DNA was measured in serum from community‐dwelling individuals from the Rush Alzheimer’s Disease Center Religious Orders Study/Rush Memory and Aging Project (median age 80.4, N = 670). Multiple regression analysis, adjusting for age, sex, race and education, associated ccf‐DNA with cognitive and physical measures, including neuropsychological testing and frailty including hand grip strength.ResultHigher levels of short ccf‐mtDNA fragments were associated with lower global cognitive scores, with a 0.09 decrease in global cognitive score per one copy increase in short fragment (p < 0.05). Higher levels of short ccf‐mtDNA normalized to serum ccf‐nDNA (ccf‐mtDNA/ccf‐nDNA) was associated with increased mortality (hazard ratio HR = 1.11) Longitudinal analysis demonstrated higher levels of long ccf‐mtDNA fragments at baseline was associated with greater frailty over time, with frailty score increasing 0.21 per year for every one copy increase in long fragment (p< 0.05). Cross‐sectional analysis demonstrated higher integrity ratio, defined as long ccf‐mtDNA relative to short ccf‐mtDNA, associated with increased handgrip strength (β= 0.14; 95% CI 0.01 – 0.26; p<0.05). Integrity ratio was associated with 0.14 increase in global cognition and 0.12 decrease in frailty score per increase in integrity ratio.ConclusionMitochondrial dysfunction is a primary theory of aging and we demonstrate that quantity and relative size of ccf‐mtDNA are associated with cognitive and physical trajectories over time. This study highlights the utility of ccf‐mtDNA fragments in identifying and risk stratifying older patients who are more likely to develop frailty and dementia. Further directions include identifying mechanisms by which ccf‐mtDNA fragments are generated and regulate downstream pathways.
Spatiotemporal imaging phenotypes of tau pathology in Alzheimer’s disease
Authors: Vogel Jacob W. , Young Alexandra L. , Oxtoby Neil P. , Smith Ruben , Ossenkoppele Rik , Aksman Leon M. , Strandberg Olof , La Joie Renaud , Grothe Michel , Medina Yasser Iturria , Rabinovici Gil D. , Alexander Daniel C. , Evans Alan C. , Hansson Oskar 
Published: December 2020

AbstractBackgroundThe Braak staging scheme describes a stereotypical spread of tau pathology in Alzheimer’s disease (AD). However, apparent subtypes described at autopsy and clinical variants of AD both suggest variability in the pattern of tau spreading across the population. To address this discrepancy, we applied a validated spatiotemporal clustering algorithm to a large, multisite dataset of tau‐PET images. We verified these findings both longitudinally and on a separate tau‐PET dataset using a different radiotracer, and we characterized the phenotype and potential biological determinants of each subtype.MethodSubtype and Stage Inference (SuStaIn, Young et al., 2018 ) is a data‐driven, probabilistic algorithm that combines disease progression modeling with clustering to extract distinct spatiotemporal patterns (subtypes) from large cross‐sectional datasets. We applied SuStaIn to a multisite dataset (n=1143) of [18F]‐flortaucipir tau‐PET baseline scans to identify spatiotemporal subtypes of tau spreading. We investigated differences in demographic, cognitive and genetic measures. In a subsample of individuals with multiple tau‐PET scans over time (n=536), we tested longitudinal subtype stability and change in disease stage over time. We verified these subtypes in a second single‐site dataset (n=509) of [18F]‐RO948 tau‐PET scans. Finally we used the Epidemic Spreading Model (ESM, Iturria‐Medina et al., 2014) and imaging or transcriptomic analysis to determine if anatomical brain networks or specific cell‐types, respectively, could explain the differing spatial patterns across subtypes.ResultIn those subjects with significant tau‐PET signal in the brain, SuStaIn identified four spatiotemporal subtypes of tau‐PET spreading: Typical (worse memory, more APOE4 carriers), limbic‐sparing (younger, less APOE4 carriers), posterior (worse visuospatial cognition), and lateral‐temporal (worse language and executive function scores; Fig 1A, Fig 2). These same four subtypes were observed in a separate cohort using a different radiotracer (similarity 0.7–0.9; Fig 1B). 86% of subjects exhibited the same subtype at multiple visits (Fig 1C), and of that group, 83% advanced in disease stage or remained stable within model uncertainty. The ESM suggested different epicenters for each subtype, and each subtype pattern exhibited a different profile of cell‐type enrichment (Fig 3).ConclusionFour stable tau‐spreading phenotypes were observed with distinct cognitive profiles, which may be characterized by vulnerability of different corticolimbic networks involving distinct cell classes.
Investigating retinal blood flow characteristics and amyloid formation in patients with type 2 diabetes and mild cognitive impairment
Authors: DeBuc Delia Cabrera , Sapahia Rishav , Watane Arjun , Cho Kyoung‐A , Rege Abhishek 
Published: December 2020

AbstractBackgroundPatients with type 2 diabetes (T2D) have almost a two‐fold greater risk of developing Alzheimer’s disease. Recent studies suggest that one link between the two conditions may be the processes underlying amyloidosis. Our previous studies have demonstrated that cognitive impairment (CI) is not limited to the brain but also affects the retina. In this pilot study, we quantified blood flow within the optic nerve head (ONH) using the XyCAM RI (Vasoptic Medical Inc.), an investigational non‐invasive, laser speckle‐based retinal imager, in cognitively healthy subjects (HC) and patients with mild cognitive impairment (MCI) and T2D.MethodThirty‐six individuals (8 HC, 16 T2D, and 12 MCI) were imaged using the XyCAM RI. One imaging session of 6 seconds duration was conducted on each eye of each subject. Only one eye (OS) was used in the analysis. Retinal blood flow (RBF) was agregated in a circular region of interest (ROI), spanning all vessels around the optic nerve head (ONH) (Figure 1). RBF was determined for one complete cardiac cycle without motion artifacts at its trough, mean, and peak per eye. The details of the RBF metrics extracted are included in the Table 1 legend.ResultPatients with MCI had a longer TtS and SSVI than HC (p=0.007 and p=0.046 as per the independent sample t‐test, respectively, Table 1). Also, a significantly higher SSVI in MCI subjects demonstrated increased contractility compared to HC and T2D subjects. The Kruskal‐Wallis test confirmed that there is a statistically significant difference in the TtS between HC, MCI, and T2D (p=0.043). The average BFVI results are reported in Table 2.ConclusionIndividuals with MCI and T2D have different RBF characteristics compared to cognitively healthy subjects. These results may be related to systemic changes in parameters such as arterial stiffness and increased blood pressure, which have been correlated with declined cognition. While our results obtained from a limited study population are suggestive, larger studies are needed to confirm the clinical applicability of our approach and the use of RBF‐based metrics as potential biomarkers of amyloidosis status.
Resting state functional connectivity associated with financial capacity in mild cognitive impairment
Authors: Nowrangi Milap , Naaz Farah , Chen Liuyi , Outen John D. , Bakker Arnold , Rosenberg Paul B. 
Published: December 2020

AbstractBackgroundFinancial capacity (FC) is a complex, multi‐dimensional neurocognitive construct that is commonly impaired and disables older individuals with cognitive impairment but the underlying mechanisms are not well understood. Resting state functional connectivity was measured in individuals with mild cognitive impairment (MCI) and impaired FC compared to cognitively normal controls (NC) in order to identify relevant network components that may help drive future interventions.MethodResting state functional MRI scans were obtained from individuals with MCI (N=17) and age, gender, and education matched NC (N=15). Table 1. All participants completed the Financial Capacity Instrument (FCI) and neuropsychological assessment. Based on previously reported imaging findings in this population, the left Angular Gyrus (lAG) was used as the seed region in functional connectivity measurements. Connectivity beta values (Fisher transformed correlation coefficients) were calculated for each connection that showed significantly altered connectivity between control and MCI cases. A Pearson’s correlation was calculated between the connectivity beta values from relevant regions and cognitive measures.ResultA total of 26 brain regions showed significant increased functional connectivity (p <0.05 uncorrected) with the lAG in NC compared to MCI. Of these regions 14 were identified as relevant to higher‐level cognitive function and carried forward in the correlation analysis (Fig. 1). Pearson’s correlation showed significant negative association between the FCI and increased connectivity with the right temporal fusiform cortex (rTFC, r = ‐0.455, p = 0.009); negative correlation between Clock drawing and increased connectivity with the intraparietal sulcus (r = ‐0.38, p = 0.03); positive correlation between Trails B and increased connectivity with postcentral gyrus (r = 0.39, p = 0.03) and left central operculum (r = 0.36, p = 0.04). Table 2.ConclusionThere is a significant correlation between a well‐validated measure of FC and increased functional connectivity between the lAG and the rTFC in controls compared to MCI. This novel finding suggests that integration of visuoperception, memory, and mathematical function is critical for FC. No other significant correlation between the lAG and rTFC was found with other tests of executive function or visuospatial cognition.