bluuebunny/crossref_metadata_2025_split huggingface dataset:
Who is at risk of dementia? Trajectories of cognitive decline from mild cognitive impairment to dementia and the factors which mediate this decline
Authors: Robson Kaye Victoria , Slight Sarah , Mc Ardle Ríona 
Published: June 2023

AbstractBackgroundMild cognitive impairment (MCI) is generally referred to as the transitional zone between normal cognitive function and clinically probable dementia disease. Prevalence of MCI varies across international studies and ranges between 3% and 42% depending on the classification criteria used .(1) It is thought that 3‐15% of MCI patients will progress to dementia each year. (2) Individual differences have been reported in how quickly cognition deteriorates, with several factors contributing to this. A systematic review was conducted to understand the trajectories of progression from MCI to dementia due to Alzheimer’s or Lewy body disease, and the mediating factors which influence the rate of progression.MethodThis systematic review was conducted according to the Preferred reporting items for Systematic reviews (PRISMA) guidelines. Searches were conducted across four databases including Web of science, Medline, Embase and PsycInfo. Participants were diagnosed with MCI at baseline and progressed to dementia of either Alzheimer’s dementia (AD) or dementia with Lewy bodies (DLB). Studies included were longitudinal and published in English language between 2004‐2021. A data extraction form was prepared, and key data extracted from all eligible articles. This review was registered with PROSPERO (Reference: CRD42022289243)ResultSixteen studies were included. The sample size ranged from 56 to 7118 participants across the studies and participants had been followed between 2 to 12 years. Higher progression rates and quicker trajectories of decline were reported with DLB compared to AD. Characteristics found in the rapid declining groups, include participants with a positive APOE4 status, visual hallucinations, low baseline cognition score, lower education (< 6 years), REM sleep behaviour disorder (RBD), cognitive fluctuation, higher ‘Geriatric Depression Scale’ (GDS) score, and were mostly males. Having >1 DLB feature increased the trajectories of decline. Neuropsychiatric symptoms (NPS), in particular, apathy and irritability predict greater rates of conversion to dementia.ConclusionIncorporating NPS symptoms into a revised criteria for dementia is worth considering. Although these symptoms have previously been reported, presentation of different combination of symptoms and factors has yet to be explored in greater depth. Further studies are needed to retrieve an accurate result in deprivation decile and how this impacts MCI progression.
Mild behavioral impairment linked to phenoconversion to Alzheimer’s disease and cortical thinning in mild cognitive impairment
Authors: Jin Yoon Eun , Lee Jun‐Young , Kwak Seyul , Kim Heejung , Kim Yu Kyeong 
Published: June 2023

AbstractBackgroundMild Behavioral Impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at‐risk state for dementia (Ismail Z, Alzheimers Dement, 2016). However, the associations between MBI and a risk of phenocoversion to dementia and its neuroanatomical correlates in MCI are still unclear.MethodA total 1326 older adults with MCI was followed for a mean of 3.0 ± 2.0 years. MBI was approximated using a transformation algorithm for the neuropsychiatric inventory at baseline. Two‐step cluster analysis was used to explore classes of 5 MBI domains (decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content). A Cox regression analysis was applied to investigate the association between the clusters and phenoconversion to AD. A subset of participants (n = 225) underwent 3D T1‐weighted MRI scans and cortical thickness was compared among the clusters of MBI domains.ResultThe cluster analysis identified 3 groups of participants: (1) people without MBI (47.8%, asymptomatic); (2) people with only affective dysregulation (29.3%, affective dysregulation); (3) people with relatively high probability of affective dysregulation, followed by impulse dyscontrol and affective dysregulation (22.9%, multiple domains). Compared to the asymptomatic, multiple domains was associated with a higher risk of phenoconversion to AD (hazard ratio = 2.589 [1.981 – 3.385], p = < 0.001), but affective dysregulation did not predict phenoconversion (1.204 [0.896 – 1.620], p = 0.219) (Fig 1). MCI individuals with symptoms in multiple domains revealed thinning in the bilateral superior and inferior parietal, superior temporal, and prefrontal cortex, and the right precuneus compared to those with only affective dysregulation (Fig 2). We did not find differences in cortical thickness between phenocoverter and non‐phenoconverter, and interaction of clusters of MBI domains and phenoconversion.ConclusionThe multiple co‐occuring MBI domains in individuals with MCI are associated with a higher risk of phenoconversion to AD. Moreover, MCI individuals with symptoms in multiple domains revealed cortical thinning in the superior parietal and precuneus, which have suggested as AD signatures (Dickerson BC, Cereb Cortex, 2009). These results suggest that evaluation of MBI and neuroimaging characteristics could be useful for risk stratification in MCI individuals.
Differential diagnosis of neurodegenerative diseases using an innovative deep learning approach
Authors: Redolfi Alberto , De Francesco Silvia , Crema Claudio , Archetti Damiano , Muscio Cristina , Firbank Michael J , Taylor John‐Paul , Tiraboschi Pietro 
Published: June 2023

AbstractBackgroundNeurodegenerative diseases lead to memory disorders and cognitive impairments with major impacts on day‐to‐day function. Early detection of patients is essential for an efficient care approach, and differential diagnosis is essential for determining prognosis and tailoring management. Most research studies compare patients by pairwise comparison methods, but this does not correspond to daily clinical practice, in which clinicians need to distinguish many different possible types of dementia concomitantly. It has been shown that magnetic resonance imaging (MRI) can mark with good accuracy the different types of dementia, such as: Alzheimer’s disease (AD), Frontotemporal dementia (FTD), Parkinson’s disease (PD), dementia with Lewy bodies (DLB). Recently, Deep Learning approaches have started being used although differential diagnosis is still almost ignored. The aim of this study was to develop a Convolution Neural Network (CNN) to classify probable AD, FTD, DLB, PD and healthy elderly control (CN) subjects starting from Diffusion Tensor Imaging (DTI).MethodThe cohort used in this study came from six different initiatives: ADNI1, NIFD2, NACC3, PDBP4, PPMI5 and Newcastle University6,7,8,9. We analysed a total of 108 CN, 110 AD, 135 FTD, 150 DLB, 132 PD. Demographic and neuropsychological characterization is shown in Table 1. The DTI scans were pre‐processed using the FMRIB software library (FSL) with eddy current correction, skull‐stripping and diffusion tensor calculation. We post‐processed the Fractional Anisotropy (FA) map using 3D CNN. The proposed CNN structure consisted of an image input layer, convolutional filters, several batch normalization with max‐pooling layers and, finally, the classification layer. A data augmentation approach was adopted that ultimately resulted in a dataset of 26’450 brain scans. A hold‐out validation (70% training set 30% test set) was performed.ResultWe found excellent performance of the 3D CNN in discriminating the different neurodegenerative diseases. Figure 1 shows the confusion matrix with the following values for the area under the ROC curve in each class: 0.92 for CN, 0.90 for AD, 0.97 for DLB, 0.96 for FTD, 0.99 for PD.ConclusionThese results prove that Deep Learning and the 3D CCN method are suitable for clinical practice and provide additional clues that can help clinicians in diagnosis making.
Dementia mediates the association of life‐course depression with mortality: A nationwide twin study
Authors: Yang Wenzhe , Wang Zhiyu , Li Xuerui , Qi Xiuying , Zhang Lulu , Pan Kuan‐Yu , Xu Weili 
Published: June 2023

AbstractBackgroundAlthough the association between depression and mortality has been investigated, the impact of depression in different periods of life on mortality remains inconclusive. We aimed to examine the association of depression with all‐cause mortality from a life‐course perspective, and to explore the roles of dementia, as well as genetic and early‐life environmental factors shared by twins, in this association.MethodFrom the Swedish Twin Registry, 44,919 twin individuals were followed for up to 18 years. Depression and dementia were ascertained using the Swedish National Patient Registry. Early‐life (<45 years), midlife (45‐64 years), and late‐life (≥ 65 years) depression were categorized according to the age of the first depression diagnosis. Deaths were identified through the Cause of Death Register. Generalized estimating equation model was used for unmatched analysis among all individuals. The mediating effect of dementia on the depression‐mortality association was estimated using generalized structural equation modeling. Conditional logistic regression model was used for co‐twin matched analysis among death‐discordant twin pairs.ResultAmong all the participants (mean age 59.34 years), 1,179 had a history of depression at baseline and 12,761 died during the follow‐up. In the unmatched analysis, the multivariate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of all‐cause mortality were 1.71 (1.46–2.00) for depression at any age, 1.72 (1.36–2.17) for early‐life, 1.51 (1.19–1.90) for midlife, and 4.10 (2.02‐8.34) for late‐life depression. Mortality was significantly higher in individuals with late‐life depression than those with earlier‐life depression (P<0.05). Depression at any age was also associated with an increased risk of mortality with dementia (OR 1.62, 95% CI 1.28–2.05). In the mediation analysis, 56.74% of the depression‐mortality association was mediated by dementia. In the co‐twin matched analysis, the OR (95% CI) for the depression‐mortality association was 1.70 (1.22–2.38). No statistically significant difference in ORs between the unmatched and co‐twin matched analyses was observed (P = 0.09).ConclusionDepression, especially occurring in late life, is associated with an increased all‐cause mortality. Dementia in late life mediates over 50% of the depression‐mortality association, but genetic and early‐life environmental factors appear not to account for this association.
CSF neurodegeneration biomarkers predict MTL atrophy over time in cognitively healthy older adults
Authors: Vidal‐Piñeiro Didac , Capogna Elettra , Blennow Kaj , Halaas Nathalie , Idland Ane‐Victoria , Mowinckel Athanasia M , Pereira Joana B , Watne Leiv Otto , Zetterberg Henrik , Initiative Disease Neuroimaging , Walhovd Kristine B , Fjell Anders M 
Published: June 2023

AbstractBackgroundStructural decline in the medial temporal lobe is an unspecific biomarker of neurodegeneration, assessed in normal older adults (OA) and Alzheimer’s Disease (AD). We investigated, in OA, whether CSF biomarkers of neurodegeneration (t‐tau, NFL, Ng, FABP3) predict longitudinal brain atrophy, whether this association is moderated by core AD biomarkers of beta‐amyloid (Aβ) and phosphorylated tau (p‐tau) and whether it is related to specific cellular and molecular mechanisms by using neurogenetic profiles.MethodLongitudinal structural MRI up to 7 years and baseline CSF biomarkers levels were collected in 189 OA (mean age = 74.8 years). Hippocampus (HC) and entorhinal cortex (EC) were selected as regions of interest. Linear mixed and generalized additive mixed models (GAMM) were used to assess the effects of Biomarker, Time, and Time×Biomarker on EC thickness and HC volume. Similar models were used to assess the interaction with core AD biomarkers. Correlation between cortical decline maps, associated with CSF biomarkers, and gene‐expression maps (Allen Human Brain Atlas https://human.brain‐map.org/) for specific cellular components, was assessed with BrainSMASH package (https://brainsmash.readthedocs.io/en/latest/)ResultHigher NFL, FABP3, and t‐tau CSF values were associated with steeper EC thinning and more HC atrophy (p<.05) over time (Figure 1a). GAMM showed significant non‐linear interactions with Time (except NG): NFL and FABP3 on EC (edf = 3.15, 3.81) and NFL and t‐tau on HC (edf = 3.09, 2.77) (Figure 1b). Aβ+ status (<550 pg/mL) did not significantly moderate the association with any biomarker (all tests p>.08) (Figure 2a). The relationships between CSF NFL with EC thinning (t = ‐3.27, p = 0.001) and HC atrophy (t = ‐2.91, p = 0.004), and FABP3 with EC thinning (t = ‐1.98, p = .05) remained significant, independently of p‐tau. The spatial pattern of cortical atrophy associated with the CSF biomarkers of neurodegeneration (Figure 2b) overlapped with distinct neurogenetic profiles: t‐tau with axonal growth cone (r = ‐.50, punc = .002); NFL with cortical cytoskeleton (r = ‐.61, pfdr<.001) and Ng with the dendritic shaft (r = ‐.40, punc<.009) components.ConclusionCSF NFL and FABP3 predict HC atrophy and EC thinning independently of Aβ/p‐tau. The neurodegenerative biomarkers may improve the accuracy of individual predictions of neurodegenerative changes in OA and identify those with a higher risk of future cognitive decline.
Diagnostic Value of Multi‐delay Multi‐parametric 3D pCASL in Early Alzheimer' Disease
Authors: Sun Mengfan , Wang Yanli , Li Runzhi , Jiang Jiwei , Zhang Yanlilng , Yao Zeshan , Li Wenyi , Zhang Yuan , Jia Ziyan , Xu Jun 
Published: June 2023

AbstractBackgroundSingle post‐labeling delay (PLD) pseudo‐continuous arterial spin‐labeling (pCASL) measures cerebral blood Flow (CBF). The altered CBF is associated with cognitive decline in early Alzheimer’s disease (AD). However, multi‐delay pCASL that measures multi‐parametric measurements including CBF, arterial cerebral blood volume (aCBV) and arterial transit time (ATT) has rarely been applied to AD studies and its diagnostic performance to recognize AD in early stage remains unclear. The purpose of this study is to compare the diagnostic value between the CBF measured by single PLD pCASL and the CBF/aCBV/ATT measured by multi‐PLD pCASL for early‐stage AD.MethodBoth 1 PLD and 7 PLD 3D pCASL protocols on 3T GE scanner were performed within one MR session for 26 cognitively normal (CN), 37 mild cognitive impairment (MCI) and 39 AD subjects who were recruited in Chinese Imaging, Biomarkers, and Lifestyle Study of Ageing Project (CIBL) from April to October 2021. Comparisons on CBF/aCBV/ATT in 10 regions of interest (ROIs), including left and right regions of olfactory, post cingulate, hippocampus, cuneus and precuneus, were performed across different groups. The area under the curve (AUC) were assessed through receiver operating characteristic (ROC) analysis.ResultAll ROIs showed significant decrease in CBF and increase in ATT of AD groups compared with that of CN and MCI groups (P < 0.05). There was no significant difference in aCBV between groups and CBF/ATT between CN and MCI (P > 0.05). The area under the ROC curve (AUC) of CBF in ROIs for both3D pCASL protocols was similar for discriminating AD against HC (0.949 vs. 0.965 for 1 PLD vs. 7 PLD, respectively), AD against MCI (0.836 vs. 0.830), MCI against HC (0.686 vs. 0.786). However, the combination of CBF/aCBV/ATT in ROIs measured by 7 PLD 3D pCASL could significantly improve diagnostic performance, which AUC was 1.000, 0.967 and 0.918 for identifying AD against HC, AD against MCI and MCI against HC respectively.ConclusionMulti‐parametric perfusion data from multi‐delay pCASL can improve the diagnostic value of AD in early stage, which could be a promising imaging biomarker in AD patients.
Association of inflammatory proteins with cognitive aging, brain MRI markers, and incident dementia
Authors: Fang Yuan , Doyle Margaret F , Mez Jesse B. , Alosco Michael L , Satizabal Claudia L. , Qiu Wendy , Chen Jiachen , Lunetta Kathryn L. , Murabito Joanne M 
Published: June 2023

AbstractBackgroundInflammatory cytokines and chemokines related to the innate and adaptive immune system have been linked to neuroinflammation in Alzheimer’s Disease (AD) dementia. We hypothesized that individual blood‐based inflammatory biomarkers would associate with cognitive function, brain magnetic resonance imaging (MRI) volumes, and risk for dementia in Framingham Heart Study (FHS) participants.MethodProtein biomarkers related to immune cells or associated with inflammatory responses including CD14, CD163, CD5L, CD56, CD40L, CXCL16, SDF1, DPP4, SGP130, sRAGE, and MPO were measured at FHS Offspring exam 7. We identified FHS Offspring participants who underwent neuropsychological (NP) testing (n = 2394) or brain MRI (n = 2135) within five years of the examination; and who were followed up 10 years after age 60 for incident all‐cause dementia (n = 1650). We used linear mixed effect models accounting for family relationships to investigate the associations between the protein biomarkers and NP test performance and brain MRI volumes and Cox proportional hazards models to examine the association with incident dementia. A false discovery rate (FDR) within each outcome set was computed to adjust for multiple testing and FDR ≤ 0.1 indicated significance.ResultParticipants from the NP and MRI samples were on average 61 years old and 54% female. Participants from the incident dementia sample (mean age 68 years) included 126 incident dementia cases within 10 years. In addition to CD14 which has an established association, we observed significant associations between higher CD40L and MPO with poorer NP performance from the executive function domain. Higher CD5L levels were significantly associated with smaller total brain volumes (TCBV), whereas higher sRAGE was associated with larger TCBV. Associations persisted after further adjusting for APOE ϵ4 carrier status and cardiovascular risk factors. None of the protein biomarkers included were significantly associated with risk of incident dementia, with trend towards an association for CD5L.ConclusionSince the proinflammatory factors CD5L, CD40L, sRAGE and MPO are associated with immune cells and are involved in vascular pathology, our study suggests the immune‐vascular axis is associated with cognitive and brain aging. If confirmed in other samples, our findings may provide informative biomarkers of abnormal brain aging.
Is there link between hypoxemia severity and impaired functional connectivity? electrophysiological evidence from patients with obstructive sleep apnea syndrome
Authors: Yerlikaya Deniz , Bircan Behice , Öztura Ibrahim , Yener Görsev 
Published: June 2023

AbstractBackgroundApneas occur more than 30 times per hour in severe obstructive sleep apnea syndrome (OSAS) patients. Each apnea results in decrease of oxygen saturation that leads to recurring intermittent hypoxemia (IH). IH was suggested as a possible factor to contribute cognitive impairment in OSAS. In the present study, we aimed to investigate the functional connectivity in low and high hypoxemia OSAS sub‐groups.MethodThe study included 56 severe OSAS patients and age‐, gender‐ and education matched 33 healthy controls (HC). The OSAS group was divided into two subgroups according to their minimum SO2 level: low‐hypoxemia OSAS (SO2 dropped never below 80%, LHO, n = 29) and high‐hypoxemia OSAS (SO2 dropped below 80%, HHO, n = 27). All participants underwent detailed neuropsychological testing and an EEG recording, using auditory classical oddball paradigm. Imaginary coherency (ICOH) was calculated for intra‐hemispheric, inter‐hemispheric and midline electrode pairs in delta, theta, alpha, beta, and gamma frequency bands.ResultLHO patients did not differ from HC in any frequency band. HHO patients showed reduced intra hemispheric ICOH values at delta, theta and beta frequency bands compared to LHO patients. HHO patients also showed decreased intra hemispheric ICOH values at theta, alpha and beta frequency bands compered to HC. Inter hemispheric group differences were found at beta band indicating decreased ICOH values in HHO patients compared to LHO patients. Midline gamma ICOH values decreased in HHO patients compared to both HC and LHO patients. HHO patients showed decreased memory scores compared to both HC and LHO groups and decreased attention scores compared only to HC.ConclusionAs far as we know, this is the first study to investigate event‐related ICOH changes in OSAS. Above results indicates that decreased connectivity in OSAS may be due to increased IH. Patients with low levels of hypoxemia did not differ from healthy controls, yet patients with high hypoxemia showed diffuse functional connectivity changes. Coherency measures revealed a parallel pattern with the neuropsychological tests underpinning the adverse effect of IH on cognitive functions. Considering OSAS as a modifiable risk factor for developing Alzheimer’s disease, treatment methods to prevent intermittent hypoxemia (i.e., positive airway pressure treatment) gains additional importance.
Prediction of amyloid‐beta accumulating normal cognitive elderly
Authors: Kim Young Ju , Chun Min Young , Jang Hyemin , Kim Hee Jin , Woo Sook‐Young , Jeong Jee Hyang , Seo Sang Won 
Published: June 2023

AbstractBackgroundAmyloid‐β (Aβ) accumulation, a major biomarker in Alzheimer’s disease (AD), induces tau accumulation, eventually resulting in cognitive decline. However, Aβ trajectory in cognitively normal participants has not been extensively investigated, yet. Modeling of Aβ trajectory remains an important goal, as future treatments targeting Aβ are expected to be developed. In the present study, we therefore investigated whether they might be divided into the normal aging group and the pathological group with increased amyloid. We also compared the differences between the non‐accumulating group and accumulating group.MethodWe included 297 subjects from the Alzheimer’s Disease Neuroimaging Initiative database, who showed normal cognition at baseline. All subjects underwent neuropsychological test, apolipoprotein E (APOE) genotype test, brain MRI, and an average of 3.03 follow‐up 18F‐florbetapir (AV45) PET scans. The original dataset was divided by 6:4 to create a training set and a validation set. Latent Class Growth Analysis was used for statistical analysis.ResultBased on the information criterion, the model consisting of three classes was found to be the best with a high entropy of 0.979: class 1 (non‐accumulating group; n = 117, 65.7%), class 2 (accumulating group; n = 46, 25.8%), and class 3 (high accumulation group; n = 15, 8.4%) (Figure). The accumulating group had more APOE ε4 carriers and a higher tau burden than the non‐accumulating group (Table).ConclusionOur study showed that there is the heterogeneity of Aβ trajectories according to aging in the normal cognitive elderly. Heterogeneity of Aβ accumulation and early detection of accumulating group may be helpful in early diagnosis and treatment of AD.