bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Conversion to Alzheimer Disease using Module‐Based Polygenic Risk Scores Informed by Brain Proteome Profiles
Authors: Hu Junming , Sahelijo Nathan , Priyadarshi Dhawal , Thompson Paul M , Saykin Andrew J. , Davatzikos Christos , Jun Gyungah R ,   Alzheimer’s Disease Neuroimaging Initiative(ADNI),AI4AD Consortium
Published: June 2023

AbstractBackgroundNeuropathologically confirmed Alzheimer disease (AD) patients are heterogeneous in their cognitive functions, brain atrophy patterns, and neuropathological traits. Genetic risk profiles informed by brain proteome signatures may predict the conversion of clinically normal individuals to AD.MethodWe discovered co‐expressed proteome networks using 201 AD brains from the prefrontal cortex area in the Religious Orders Study and Memory and Aging Project (ROSMAP) and validated the findings using 328 AD brains in the Emory study. Of the preserved modules, we selected modules with significant association (P<0.01) between neuropathologically and clinically confirmed AD (symptomatic) and neuropathologically confirmed AD but clinically unimpaired brains. We generated polygenic risk scores of the symptom‐associated modules (mbPRSs) using existing genome‐wide summary statistics for AD (Kunkle, 2019) in 309 AD, 483 mild cognitive impairment (MCI), and 301 cognitively normal (CN) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We investigated relationships between the derived mbPRSs and previously clustered brain atrophy patterns in the ADNI (Yang, 2021). We defined at‐risk CN and MCI subjects in the ADNI for each module if mbPRSs of the subject > the third quantile. Age‐adjusted Cox proportional hazard models were applied for conversion status to AD with at‐risk subjects of the symptom‐associated modules comparing with all CN and MCI subjects as a reference group.ResultWe detected 12 preserved modules that showed significant associations for symptomatic AD (P‐value<0.05). The mbPRSs of the yellow and the lightcyan modules were significantly associated with brain atrophy cluster 3 (P‐value: yellow‐mbPRS = 5.5e‐03; lightcyan‐mbPRS = 7.1e‐05). At the same time, Of the mbPRSs for the 12 symptom‐associated modules, the at‐risk subjects defined by the lightcyan‐mbPRS were also predicted to be earlier conversion from CN or MCI to AD (Hazard ratio = 1.63, P‐value = 3.8e‐02). Lightcyan‐mbPRS shows a good prediction of conversion to AD and also the association with MRI endophenotypes.ConclusionThis study demonstrates for the first time that PRSs informed by symptom‐associated protein networks may identify at‐risk CN and MCI subjects who will develop clinical symptoms and enable targeted prevention and treatment trials for AD for these at‐risk subjects in preclinical stages of AD.
High plasma Glial Fibrillary Acidic Protein levels are associated with an increased risk of dementia and Alzheimer’s disease over a 13‐year follow‐up period: Results from a prospective population‐based cohort
Authors: Linard Morgane , Martinuzzi Manuela , Samieri Cécilia , Dartigues Jean‐François , Glaichenhaus Nicolas , Féart Catherine , Helmer Catherine 
Published: June 2023

AbstractBackgroundReactive astrogliosis, an activation state that includes morphological, metabolic and functional changes of astrocytes, occurs in neurodegenerative diseases, including Alzheimer’s disease (AD). Increased plasma levels of glial fibrillary acidic protein (GFAP), a reactive astrogliosis biomarker, have been recently reported in the preclinical and symptomatic stages of AD. However, very few works have investigated its ability to predict long‐term AD risk. This study aimed to investigate the association between plasma GFAP levels and future risk of dementia and AD.MethodWithin the Bordeaux‐3C prospective population‐based cohort, we quantified plasma GFAP levels using V‐PLEX immunoassay among 1068 non‐demented participants aged 69 years or over. Dementia was screened over a follow‐up of 13 years. Associations of baseline plasma GFAP levels with the risk of incident AD and dementia were investigated using Cox models adjusted for socio‐demographic characteristics, cardio‐vascular comorbidities and APOE4 status.ResultThe mean age of the participants was 77.6 years (std 4.7) and 64% were women. Median GFAP level was 239 pg/ml [IQR 192‐321]. During the follow‐up (median 8.8 years, up to 14.3 years), 281 dementias occurred, including 120 probable AD. In multivariate models, the middle and high tertiles of GFAP were associated with an increased risk of dementia (aHR = 1.8, 95%CI: 1.3 to 2.5 and aHR = 2.0, 95%CI: 1.5 to 2.8 respectively, compared to the lower tertile, global p‐value<.0001). These risks were higher when considering only probable AD (aHR = 2.7, 95%CI: 1.5 to 4.7 and aHR = 3.0, 95%CI: 1.7 to 5.2 for the middle and high tertiles respectively, global p‐value 0.0004). The association was found regardless of the APOE4 status. There was no interaction with time meaning that baseline GFAP was associated with higher risk of AD at short as at long‐term.ConclusionThese results suggest that plasma GFAP levels are increased very early in the process of AD. GFAP could represent a useful means to identify people at high risk of AD for both an objective of prevention or to include them in clinical trials. The interest of such a marker, alone or in combination with other plasmatic biomarkers of AD, should be further studied.
Diffusion MRI indices of brain microstructure: Evaluating the Ball‐and‐Stick model in distinguishing Alzheimer’s disease
Authors: Snoussi Haykel , Rashid Tanweer , Seshadri Sudha , Habes Mohamad , Satizabal Claudia L. 
Published: June 2023

AbstractBackgroundDiffusion MRI is a valuable tool to assess white matter (WM) microstructure biomarkers of brain aging and Alzheimer’s disease (AD). The most common model used to extract diffusion properties is the diffusion tensor model (DTI). However, DTI cannot resolve complex WM microstructure and suffers from partial volume effects. Further, the majority of multi‐site imaging clinical studies, such as ADNI, are limited to single‐shell acquisitions due to time constraints. Therefore, multi‐compartment models are not feasible to overcome these limitations except multi‐tensor models, such as Ball‐and‐Stick (B&S) under some constraints. B&S offers a novel approach to derive biomarkers for early detection of AD because it splits the diffusion‐weighted MR signal into several anisotropic components (Stick) and a single isotropic component (Ball). This model is implemented in Anima software. Here, we propose a classification approach using four DTI and two B&S indices quantified in various anatomical regions of interest (ROIs) to assess and compare their ability to distinguish AD.MethodCross‐sectional data were available for 413 ADNI‐3 participants: 68 AD (age: 76.81±8.3; 50% women) and 345 cognitively normal (CN; age:72.91±7.27; 62% women). We processed T1‐weighted and diffusion sequences following the pipeline in Fig.1. We obtained four DTI maps: fractional anisotropy (FA), axial (AxD), mean (MD), radial (RD) diffusivity; and two B&S maps: free water weight (FWW) and Stick‐axial diffusivity (ST). Diffusion maps were quantified within a set of anatomical ROIs. Then, we performed a high‐dimensional pattern classification approach. For each metric, we consider all brain ROIs jointly and identify a minimal set of regions whose values jointly maximally differentiate between AD and CN.ResultB&S model with regional FWW and ST measures shows the greatest discrimination between AD and CN (FWW ROCAUC = 0.942; ST ROCAUC = 0.938) compared to DTI (Table 1). Left PHG Parahippocampal Gyrus and Right Hippocampus regions have the highest contribution in the classification (Table 2, Fig.2).ConclusionOur results suggest B&S measures are more sensitive to discriminate AD from CN than DTI measures, widely used in clinical research. B&S has the advantage of identifying and separating crossing fibers, and therefore, has the potential to offer greater and novel insights into the underlying pathology of AD.
Normalization methods for RT‐qPCR assessment of circulating microRNAs in Alzheimer’s and other aging‐related diseases
Authors: Wojda Urszula , Want Andrew , Staniak Karolina , Grabowska‐Pyrzewicz Wioleta 
Published: June 2023

AbstractBackgroundCirculating miRNAs in blood plasma present significant potential for use as minimally‐invasive biomarkers for diagnosis of aging‐related diseases, such as cancer or Alzheimer’s disease (AD). The most sensitive and inexpensive analysis method of circulating miRNA is RT‐qPCR. However, lack of RT‐qPCR standardisation is one of the major causes of data inconsistency across different studies and it hinders progress towards widespread implementation of miRNA biomarkers in clinical use. Normalisation of RT‐qPCR data to stably expressed miRNAs is a key step in data analysis. Current methods of identifying optimal normalisers are lacking in their evaluation of the stability of normalisers and their combinations in aging populations. To address these needs, we created a novel, transparent, method for selecting optimal normalisers in aging populations, using the Python programming language (v. 3.7.3).MethodOur method uses the Python packages: pandas (v. 1.2.3), numpy (v. 1.17.1), scipy (v. 1.3.1). The method uses three measures to evaluate the miRNA Cq values for potential normalisers: Kolmogorov‐Smirnov score (KS‐score), average displacement from a mean of zero and mean standard deviation. In each case, the comparators are two distinct biological groups of interest (such as AD and cognitively normal controls). Before comparison, the group of potential normalisers were normalised according to the log2(2−ΔΔCq) method. The miRNA data were collected from Polish subjects including 44 AD patients and 70 similar‐aged, cognitively normal, controls). Circulating miRNA molecules were isolated from plasma, followed by RT‐qPCR with a selection of 7 miRNAs tested as potential normalisers, along with suitable controls for mRNA isolation and reverse transcription.ResultWe provide a novel method for identification of optimal normalisers with the advantages of: assessments of a greater number of combined potential normalisers (7 in this study), transparency of decision making and the ability for end users to weight that decision making according to their judgment of relative importance.ConclusionWe recommend assessment of plasma miRNA levels in an aging population employing a novel set of normalisers.Work supported by the Polish National Science Centre grant OPUS 2018/29/B/NZ7/02757and by the EU Horizon2020 FETOPEN grant no 737390 (ArrestAD).
Is depression in those with Alzheimer’s Disease different to depression in those without dementia?
Authors: Sinclair Lindsey I , Lawton Michael , Palmer Jennifer , Ballard Clive G ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: June 2023

AbstractBackgroundDepression in individuals with Alzheimer’s disease (AD) is common, distressing, difficult to treat, may increase carer burden and is inadequately understood. It occurs more frequently in AD than in older adults without dementia. The reasons why some patients develop depression during AD and others do not remain obscure.We aimed to identify risk factors for depression in AD using 3 large cohort studies and assess whether these risk factors differed from those for depression in people with normal cognition.MethodWe used data from 3 large dementia focused cohorts: ADNI (n = 665 with AD, 669 normal cognition), NACC (n = 698 with AD, 711 normal cognition) and BDR (n = 757 with AD). Depression ratings were available using the GDS & NPI and in addition for BDR the Cornell. Intermittent depression was defined as one episode above threshold and persistent as ≥ 2 episodes. A cut‐off of ≥8 was used for the GDS and the Cornell Scale for Depression in Dementia, ≥6 for the NPI depression sub‐scale and ≥2 for the NPI‐Q depression sub‐scale.We used logistic regression and a random‐effects meta‐analysis to examine potential risk factors and an interaction term to look for interactions between each risk factor and the presence of cognitive impairment. Because we aimed to study persistent depression any participants with only study visit were excluded from the analysis, as were those with treated depression who did not meet criteria for caseness at any point.ResultIn individual studies there was no evidence of a difference in risk factors for depression in AD but combining data with meta‐analysis suggested clear differences between risk factors for depression in AD and depression in those without dementia e.g. gender (figure 1). Previous depression increased the risk in the only study with this information (OR 7.78 95%CI 4.03‐15.03).ConclusionRisk factors for depression in AD appear to differ to those for depression per se supporting suggestions of a different pathological process. We have identified that a past history of depression is the strongest risk factor for the development of depression in AD, but information on this was only available for one cohort.
Longitudinal associations of emergent and persistent affective dysregulation symptoms with incident dementia in dementia‐free older adults
Authors: Ebrahim Inaara , Ghahremani Maryam , Smith Eric E. , Camicioli Richard , Ismail Zahinoor 
Published: June 2023

AbstractBackgroundNeuropsychiatric symptoms (NPS) are risk factors for dementia. Mild behavioral impairment (MBI) is a neurobehavioral syndrome that refines NPS assessment to improve dementia prognostication by identifying later‐life emergent and persistent NPS specifically as the at‐risk group. Affective dysregulation contributes to dementia risk and is an MBI domain characterized by the inability to regulate emotions. Here, we investigate the longitudinal association of MBI‐affective dysregulation with incident dementia in dementia‐free older adults from the National Alzheimer Coordinating Centre (NACC).MethodNACC participants with no history of psychiatric, neurological, or neurodevelopmental disorders were included. MBI‐affective dysregulation status was determined based on Neuropsychiatric Inventory Questionnaire (NPI‐Q) depression, anxiety, and elation scores at two consecutive visits. The comparator group involved participants with no NPS prior to dementia. Participants with dementia at baseline were excluded from the study. Kaplan‐Meier curves of dementia‐free survival over ten years were generated for MBI‐affective dysregulation versus no NPS. Cox proportional hazard models were implemented to assess the risk of dementia, adjusted for age, sex, years of education, race, APOE e4 status, and clinical cognitive diagnosis. Potential interactions were further explored for relevant model covariates.ResultThe final sample consisted of 3,446 participants with no NPS (mean age 73.1; 63.0% female), and 1,156 with MBI‐affective dysregulation (mean age 75.1; 53.9% female). MBI‐affective dysregulation was associated with lower chance of dementia‐free survival (log rank, p<0.001) and 1.67 times greater risk of dementia compared to no NPS (CI:1.4‐2, p<0.001). Moderation analysis revealed that in participants with normal cognition (NC), those with MBI‐affective dysregulation were at 2.56 times greater risk of dementia than those with no NPS (CI:1.87‐3.49, p<0.001). In mild cognitive impairment (MCI), the risk associated with MBI‐affective dysregulation was 1.4 times greater than no NPS (CI:1.14‐1.72, p = 0.02).ConclusionThe emergence of persistent affective dysregulation symptoms in dementia‐free older adults is associated with substantial risk for dementia. When emerging in individuals with NC, these persistent affective symptoms represent a greater risk compared to those with no NPS, compared to emergence of these symptoms in MCI. MBI‐affective dysregulation is an important risk factor for dementia and should be considered in clinical assessments.
Normative data for three physical frailty parameters in an aging, rural Indian population
Authors: Sundarakumar Jonas S. , Teja Karru Venkata Ravi , Muniz‐Terrera Graciela , Ravindranath Vijayalakshmi ,   SANSCOG
Published: June 2023

AbstractBackgroundPhysical frailty is associated with multiple adverse health outcomes. Since physical characteristics markedly vary with different populations, population‐specific norms for physical frailty parameters are necessary. Such norms are lacking for the Indian population, especially for older, rural Indians. We aimed to develop normative values for three quantitative, frailty parameters – hand grip strength, ‘Timed Up‐and‐Go’ (TUG) time and physical activity in an aging, rural Indian populationMethodThe study sample is from an ongoing, prospective, cohort (Srinivaspura NeuoSenescence and COGnition, SANSCOG) comprising of rural, community‐dwelling, cognitively healthy, aging Indians. Subjects are recruited through area sampling strategy, from villages of Srinivaspura, Kolar district, Karnataka state, India. Three physical frailty parameters of Fried’s phenotype – hand grip strength (n = 1787), TUG time (n = 1863) and physical activity (n = 1640) were assessed using digital hand dynamometry, TUG test and General Physical Activity Questionnaire (GPAQ), respectively.ResultThe 10th, 25th, 50th, 75th, 90th percentiles for age groups 45‐55, 56‐65, 66‐75 and >75 years were: right hand grip strength(kg): males–13.90, 18.60, 23.80, 28.70, 33.70 & females–7.80, 10.60, 14.20, 17.90, 21.30; left hand grip strength(kg): males–13.30, 18.30, 23.60, 28.90, 32.86 & females–7.90, 10.53, 14.30, 17.80, 21.20; TUG time(seconds): males–9.05, 10.09, 11.43, 13.38, 15.50 & females–9.51, 10.73, 12.40, 14.50, 16.57; physical activity(MET‐minutes/week): males–1680, 4320, 8880, 15840, 23352 & females–1680, 4320, 9240, 15120, 20160.ConclusionOur findings show that from 45 years onwards, overall grip strength decreases and TUG time increases, with women performing significantly poorer than men across all age groups, except >75 years, where no differences were seen. Physical activity did not show any consistent trend according to age or gender. Reference values for this aging, rural Indian population were substantially lower for grip strength and higher for TUG time than aging populations in several Western and other Asian countries
“Neuroprotective Potential of Limonene in LPS Induced Parkinson’s Disease in Rats”
Authors: Dhureja Maanvi 
Published: June 2023

AbstractBackgroundParkinson’s disease is 2nd most disabling neurodegenerative disorder characterized by progressive loss of dopaminergic neurons in basal ganglia. There are different pathologies that count for PD like neuro‐inflammation. This study highlights the role of oxidative stress and inflammation in progression of PD where limonene shows antioxidant and anti‐inflammatory response.MethodWistar rats (200‐250gm) of either sex were taken and divided into 6 groups. Animals were treated with three different doses of limonene i.e. (25, 50, 100 mg/kg p.o.) for 21 day, starting 1 day prior to LPS 5μl(1mg/ml PBS) infused stereotaxically into the SN of rats.ResultThe catalepsy technique was used to analyze the clinical signs of Parkinson’s disease in rats. LPS significantly increased oxidative stress indicators in the animals and decreased systemic antioxidant synthesis. Biochemically limonene significantly reduced the oxidative–nitrative stress, as evidenced by decrease in malondialdehyde and nitrite levels, and restored the reduced catalase, glutathione and Superoxide dismutase levels. The observed beneficial effects of limonene in motor defects may be due to its ability reduce oxidative burden.ConclusionLPS is potent inflammatory biomarker but this also has major role in development of oxidative stress. Interaction between reactive oxygen species and dopamine leads to its depletion & considered as one of the major mechanism for dopaminergic degeneration in PD. LPS caused significant elevation in malondialdehyde, nitrite and decline in SOD, catalase & glutathione, indicating development of oxidative‐nitrosative stress. Limonene treatment significantly reduced striatal MDA and nitrite concentration & restored antioxidant enzyme activities.
Cognitive control, interference inhibition and ordering of information during working memory in younger and older healthy adults
Authors: Mirjalili Mina , Zomorrodi Reza , Daskalakis Zafiris J. , Hill Sean , Kumar Sanjeev , Blumberger Daniel M. , Fischer Corinne E. , Flint Alastair , Herrmann Nathan , Lanctôt Krista L. , Mah Linda , Mulsant Benoit H. , Pollock Bruce G. , Rajji Tarek K. ,   PACt‐MD Study Group
Published: June 2023

AbstractBackgroundInvestigating effects of aging on neurophysiological mechanisms underlying working memory provides a better understanding of potential targets for brain intervention to prevent cognitive decline. Theta‐gamma coupling (TGC) indexes the ability to order information processed during working memory tasks. Frontal theta event‐related synchronization (ERS) and parietal alpha event‐related desynchronization (ERD) index cognitive control and interference inhibition, respectively. Relative contributions of TGC, theta ERS and alpha ERD in relation to stimulus presentation are not characterized. Further, differential effect of normal aging on pre or post‐stimulus processes is unknown.MethodElectroencephalography was recorded in 66 younger and 41 older healthy participants while performing 3‐back working memory task. We assessed relationships between 3‐back task performance and each of post‐stimulus TGC, pre‐stimulus parietal alpha ERD, and pre‐stimulus frontal theta ERS in each age group.ResultWhile older adults performed worse on 3‐back task than younger adults. TGC, alpha ERD or theta ERS did not differ between the two groups. TGC was positively associated with 3‐back performance in both age groups; pre‐stimulus alpha ERD was associated with performance among younger adults; and pre‐stimulus theta ERS was not associated with performance in either group.ConclusionOur findings suggest that both pre‐stimulus interference inhibition and post‐stimulus ordering of information are important for working memory in younger adults. In contrast, performance in older adults appears to depend only on post‐stimulus ordering of information. These specific contributions of neurophysiological resources may explain the poorer performance of older adults and suggest different targets to enhance working memory in age groups.