bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene co‐expression network analyses in Mild cognitive impairment
Authors: Dorsant‐Ardon Valerie , Sanjay Apoorva Bharthur , Rocha Luis M , Correia Rion Brattig , Apostolova Liana G. 
Published: December 2023

AbstractBackgroundMultiomic data analysis has been extensively developed in recent years. Particularly, microarray data can be used as biomarkers of disease of progression specially in pathologies as cancer, autoimmunity and others. (Dahinden et al., 2010; Soleimani Zakeri et al., 2020). This modality of data analysis can also be employed in other multifactorial diseases as Alzheimer’s disease including the progression from normal cognition to mild cognitive impairment and finally to dementia. These genes work in intricate relationship with each other. The establishment of computational gene interaction networks shows the intricacy of the biological systems but increases the complexity of the analysis, for this reason, the removal of redundant edges leaves a network backbone revealing important driver nodes that are essential for the observed interactions, reducing the number of genes of interest and narrowing potential diagnostic or therapeutic targets. (Gates et al., 2021).MethodWe used data from the ImaGENE study and the Weighted gene co‐expression network analysis (WGCNA) pipeline to analyze gene‐gene interactions of mRNA transcripts obtaining hierarchical clustering of genes and eigengenes in a sample of 160 individuals (Table 1). The backbones were obtained using the shortest path computation. (Gates et al., 2021; Simas et al., 2021). Gene ontology was used to classify processes associated with these genes.ResultWe identified 42 hubs of differentially expressed genes and we analyzed the top 5 groups with the strongest association with amnestic mild cognitive impairment (MCI) phenotype (pfdr<0.0001). This cluster consisting of 46 genes was further classified according to function and interactions with other nodes in the backbone identifying processes like calcium signaling, nucleotide excision repair, fatty acid metabolism among others.ConclusionThere is an identifiable difference in gene expression in individuals with MCI compared to normal controls. The analysis of the backbone of the gene hubs allowed to reduce the number of genes of interest. This approach can help to elucidate important biological interactions, potential therapeutic targets and could eventually be used as risk factors markers for the development of MCI and AD.
Association of plasma biomarkers with cognitive function in persons with dementia and cognitively healthy in the Democratic Republic of Congo
Authors: Ikanga Jean N , Patel Saranya Sundaram , Roberts Blaine Russell , Schwinne Megan , Hickle Sabrina , Verberk Inge M.W. , Epenge Emmanuel , Gikelekele Guy , Tshengele Nathan , Kavugho Immaculee , Mampunza Samuel , Yarasheski Kevin E. , Teunissen Charlotte E. , Stringer Anthony Y , Levey Allan I. , Alonso Alvaro 
Published: December 2023

AbstractBackgroundCross‐sectional and longitudinal measurements of plasma biomarkers of Alzheimer’s disease (AD) in Western countries are being applied in clinical practice, whereas their associations with culturally validated cognitive tests in other settings remain unknown. We aim to examine cross‐sectional association of plasma protein biomarker concentrations and APOE proteotype with cognitive function and explore the discriminative role of these AD biomarkers in such an association.MethodThis is a cross‐sectional retrospective study completed from 2018 to 2022 in the Democratic Republic of Congo (DRC). Subjects were recruited from clinics, hospitals, churches, and across DRC. The study started in January 2018 until December 2022. Data were analyzed from May 2022 to December 2022. The DRC Memory clinic team recruited 1430 individuals 65 years and over. Based on Community Screening Instruments for Dementia (CSID), and Alzheimer’s Questionnaire (AQ), and DSM‐5 diagnostic criteria, participants included 44 individuals classified as major neurocognitive disorder (dementia) and 41 as healthy controls (HC). Subjects underwent cognitive assessment with a validated, culturally‐tailored cognitive battery. AD plasma biomarkers (Aβ42, Aβ40, Aβ42/40, p‐tau 181), APS (derived from Aβ42/40, APOE status, and age), and APOE proteotype were utilized to assess for genetic risk.ResultIndividuals with dementia had significantly lower Aβ42/40 levels, higher APS, and higher APOE ε4 prevalence compared to HC. Linear regressions showed significantly associations between Aβ42/40 and APS with ANT, ALMT, and AVMT scores, while APOE ε4 presence was associated with ANT, ALMT, AVMT, and APT scores. APS showed the highest AUC value (AUC = 0.78, 95% CI: 0.68‐0.88) followed by Aβ42/40 (AUC = 0.75, 95% CI: 0.66‐0.86) and APOE ε4 (AUC = 0.69 (CI 0.57‐0.81) in discriminating dementia from HC.ConclusionSelect AD biomarkers were associated with cognition and differentiated dementia from HC, consistent with extant research. These findings may have implications for the assessment of AD biomarkers in DRC.
Investigations of Serum Metabolomic Relationships between Lung Cancer and Alzheimer’s Disease using Nuclear Magnetic Resonance Spectroscopy
Authors: Cheng Leo L. , Kobus Zuzanna , Bobus Marta , Su Li , Christiani David C. 
Published: December 2023

AbstractBackgroundAlzheimer’s Disease (AD) and Lung cancer (LuCa) are among the leading causes of mortality in the United States. Remarkably, several studies demonstrated a potential inverse co‐morbidity of AD with LuCa. Possible explanations related to the cell cycle (dys)regulation include presence of specific neuropathological features, immune checkpoint functions and increased circular RNA levels. Metabolomic profiles for LuCa or AD alone have been proposed. Here, using high‐resolution magic angle spinning (HRMAS) MRS, we aim to study metabolomic relationship between the two diseases with serum metabolomic profiles for matched LuCa patients, with and without AD, by comparing serum profiles measured from matched healthy controls.MethodsLuCa sera from of patients with (LCAD, n = 10, 3M, 7F, 77.3±7.7yrs) and without (LCnonAD, n = 10, 3M, 7F, 77.4±5.2yrs) clinically defined AD were obtained from Harvard/MGH Lung Cancer Susceptibility Study (a.k.a. BLCS) Repository, with individually age‐ and gender‐matched healthy controls (Ctrl‐LCAD and Ctrl‐LCnonAD, n = 10/each) obtained from the MGB BioBank. HRMAS proton NMR for these 40 samples were measured on 10 µl, at 4°C with a spin rate of 5000 Hz using a Bruker Avance 600 MHz spectrometer. Spectra were analyzed with Bruker Topspin 3.6.2. Statistical analysis was performed using JMP Pro on 18 spectral regions identified from HRMAS proton NMR.ResultsAs a survey of the entire data ensemble of 18 spectral regions measured from 40 samples, the hierarchical clustering analysis (Fig. 1) seems to associate different groups into different clusters. Unsupervised principal component analysis (PCA) conducted on all spectral regions generate PCs (PC1 and PC2) that can differentiate among groups (Fig. 2). Further noticed that, four out of 18 regions can significantly differentiate LCAD from LCnonAD. Calculations of PCA using these four regions result in PC1_4regions that can significantly differentiate LCAD from LCnonAD (Fig. 3). Collectively evaluating potential contributing metabolites towards PC1_4regions indicate increases in myo‐inositol suggesting towards LCAD, which increases in creatine, phosphocreatine, serine, aspartate, tyrosine, proline, glutamine, and 2‐oxoglutarate suggesting towards LCnonAD.ConclusionOur findings, whilst preliminary, seem promising in guiding further investigations into serum NMR metabolomics for better understanding LuCa‐AD metabolic relationships.
Comparative efficacy of cognitive training and physical activity interventions delivered using technology‐based or face‐to‐face approaches in patients with cognitive impairment: A systematic review and network meta‐analysis
Authors: Ye Yifan , Zhang Lifeng , Huang Likui , Lei Ming , Chen Liangying , Song Rui , Wang Jia 
Published: December 2023

AbstractBackgroundIn recent years, there has been a growing development of cognitive training and physical activity interventions delivered through technology‐based or face‐to‐face approaches for patients with cognitive impairment. However, it remains unclear which combination of approaches is effective and preferred.MethodsWe searched Pubmed, Web of Science, Embase, the Cochrane Library, MEDLINE, and PsycInfo through November 2022 and included randomized controlled trials that examined the effectiveness of CT+PA‐T (combining cognitive training and physical activity using a technology‐based approach), CT+PA‐F (combining cognitive training and physical activity using a face‐to‐face approach), CT‐T (technology‐based cognitive training), CT‐F (face‐to‐face cognitive training), PA‐T (technology‐based physical activity), and PA‐F (face‐to‐face physical activity) in patients with cognitive impairment. The primary outcomes included global cognitive function, executive function, memory cognition, Activities of Daily Life (ADL), depression, and Quality of Life (QOL). Network meta‐analyses were performed using a random effects model.ResultsA total of 141 studies with 12060 patients were included. CT+PA‐T was the most effective for improving global cognitive function (SUCRA = 89.9%, SMD = 0.91, 95%CI = 0.41 to 1.40), ADL (SUCRA = 97.1%, SMD = 1.19, 95%CI 0.39 to 1.98), and reducing depression (SUCRA = 93.8%, SMD = ‐1.11, 95%CI ‐2.09 to ‐0.13). CT‐T had the highest probability in developing memory function (SUCRA = 94.4%, SMD = 0.62, 95%CI 0.39 to 0.85) and QOL (SUCRA = 75.3%, SMD = 0.53, 95%CI 0.00 to 1.07) in patients with cognitive impairment. For executive function, CT+PA‐F had the highest probability in all patients with cognitive impairment (SUCRA = 86.1%, SMD = 0.49, 95%CI 0.26 to 0.72), while CT+PA‐T and CT‐T were best in patients with MCI (SMD = 0.59, 95%CI 0.30 to 0.88) and dementia (SMD = 0.87, 95%CI 0.37 to 1.36), respectively.ConclusionsThese preliminary findings suggest that technology‐based intervention is an effective approach to improving the well‐being of patients with cognitive impairment. CT+PA‐T and CT‐T had the highest probability of being the most effective intervention for slowing global cognitive function decline and improving memory function among patients with cognitive impairment, respectively.
Cross‐Sectional and Longitudinal Associations of Mild Behavioural Impairment‐Apathy and Alzheimer’s Disease‐Related Biomarkers
Authors: Vellone Daniella Alicia , Ismail Zahinoor 
Published: December 2023

AbstractBackgroundApathy, characterized by decreased interest, initiative, and emotional reactivity, is amongst the most common neuropsychiatric symptoms in Alzheimer’s Disease (AD) dementia, but it can also manifest in prodromal, and even preclinical disease stages. Apathy in individuals who are cognitively normal and who have mild cognitive impairment (MCI), is associated with accelerated progression to AD, and apathy in AD has been associated with greater disability, lower quality of life, poorer health, greater caregiver distress and burden, as well as higher morbidity and mortality. The multitude of negative outcomes associated with apathy highlight the importance of research whose primary goal is to identify mild behavioural impairment(MBI)‐apathy in non‐dementia samples and combine this behavioural syndrome with well‐established AD‐biomarkers, such as beta‐amyloid (Aβ), phosphorylated tau (p‐tau), and total tau (t‐tau), to better predict AD dementia risk.MethodDementia‐free participants in the Alzheimer’s Disease Neuroimaging Initiative were stratified as MBI‐apathy and no neuropsychiatric symptoms (no‐NPS) based on Neuropsychiatric Inventory (NPI) and NPI‐Questionnaire (NPI‐Q) scores at two consecutive visits. Covariates of interest included age, sex, apolipoprotein ε4 carriership, years of education, Mini Mental State Examination scores, and the questionnaire NPS status was derived from. Linear regressions assessed the association of MBI‐apathy (predictor) with Aβ40, Aβ42, p‐tau181, t‐tau, Aβ40/Aβ42, p‐tau181/Aβ42, and t‐tau/Aβ42 (outcome variables). We also used linear mixed effect models for repeated measures to investigate change in our outcome variables across a two‐year period.ResultsOf the 253 participants (127 CN); 51 had MBI‐apathy. MBI‐apathy was found to be significantly associated with baseline p‐tau181/Aβ42 (p<0.05) and t‐tau/Aβ42 (p<0.05) ratios. MBI‐apathy was also found to be significantly associated with changes in Aβ42 (p = 0.001), Aβ40/Aβ42 (p<0.01), p‐tau181/Aβ42 (p = 0.001), and t‐tau/Aβ42 (p = 0.001) levels and ratios over a two‐year period.ConclusionTo our knowledge, this is the first study examining the relationship between MBI‐apathy and AD‐related biomarkers. Results suggest that MBI‐apathy is significantly associated with several AD‐related biomarkers both cross‐sectionally and longitudinally. Combining the presence of persistent and emergent apathy with these biomarkers might serve as a prognostically useful approach for predicting AD dementia at a time when there is opportunity for intervention.
Impact of White Matter Hyperintensities on domain‐specific cognition in Southeast Asians
Authors: Wang Jia Dong James , Leow Yi Jin , Vipin Ashwati , Kumar Dilip , Kandiah Nagaendran 
Published: December 2023

AbstractBackgroundDementia affects 55 million people worldwide, with 60% of the burden in Asia. White Matter Hyperintensities (WMH) is a key marker of small vessel disease, with high prevalence in Asian populations with prodromal and clinical dementia. WMH is described as: Deep White Matter Hyperintensities (DWMH), Periventricular Hyperintensities (PVH) or Fazekas‐Total (DWMH and PVH).However, association between WMH topography and performance in specific cognitive domains remains unexplored. Thus, this study aims to characterise the impact of Fazekas‐Total, DWMH and PVH on different cognitive domains.Method304 participants (mean age 60.6, mean education years 14.2, mean Montreal Cognitive Assessment 25.99, 43.8% males) from Biomarkers and Cognition Study, Singapore (Dementia Research Centre (Singapore)) met the inclusion criteria.Eight domains of cognition were tested: global cognition, learning and memory, language, executive function, complex‐attention, perceptual‐motor, social‐cognition, and processing speed.Normality tests, correlation analysis and stepwise regression (with Benjamini and Hochberg False Discovery Rate correction) were performed to understand association between Fazekas‐Total, DWMH, PVH on domains of cognition tested, accounting for age, education, and gender.Two approaches were used for data analysis: (1) by grouping participants as Mild Cognitive Impairment (MCI), Subjective Cognitive Decline (SCD) and Cognitively Normal (CN) as per the National Institute on Aging‐Alzheimer’s Association (NIA‐AA) criteria and (2) by grouping participants’ WMH as confluent (DWMH ≥2 and PVH ≥3) and non‐confluent.ResultHigher Fazekas‐Total was associated with slower processing speed (p = 0.0255, R = ‐0.039) in prodromal participants (MCI and SCD). Higher PVH was associated with slower processing speed in MCI (p = 0.017, R = ‐0.32) and CN (p = 0.017, R = ‐0.663) participants. Higher PVH was significantly associated with poorer learning and memory (p = 0.045, R = ‐0.043) in SCD participants. Higher DWMH was significantly associated with poorer learning and memory (p = 0.017, R = ‐0.765) in CN participants.ConclusionThese results demonstrate differential association between PVH, DWMH and cognitive domains, thus the location of WMH determines the affected cognitive domains. Therefore, it is worthwhile to assess PVH and DWMH in clinical cognitive outcomes separately and to understand the upstream pathobiology of DWMH and PVH.Furthermore, higher Fazekas‐Total was strongly associated with slower processing speed in prodromal participants and could be a marker of cognitive decline.
α‐Synuclein in Blood CNS‐originating Extracellular Vesicles For Parkinsonian Disorders: Systematic Review and Meta‐analysis
Authors: Taha Hash Brown , Ati Shomik S. 
Published: December 2023

AbstractBackgroundParkinsonian disorders, including Parkinson’s disease (PD), multiple system atrophy (MSA), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS), present shared early motor symptoms but differing cellular and regional pathophysiology. Accurate premortem diagnosis remains challenging. Extracellular vesicles (EVs) contain cell‐state‐specific biomolecules and can cross the blood‐brain barrier to the peripheral circulation, providing a unique central nervous system (CNS) insight. Measuring biomarkers in blood CNS‐originating EVs have become a promising avenue for minimally invasive diagnostics. This study evaluated the potential the levels of blood‐isolated neuronal and oligodendroglial EVs (nEVs and oEVs) α‐synuclein (α‐syn) proteoforms in parkinsonian disorders.MethodWe searched PUBMED, EMBASE, google scholar and recent reviews of the literature to include studies that have measured mean ± SD of α‐syn in putative nEVs and oEVs in patients with PD and at least one other parkinsonian disorder or healthy controls (HCs). Thirteen studies were included in the final meta‐analysis and demographic and clinical variables were collected for meta‐regressions. We quantified the effect size (SMD) using an inverse‐variance random‐effects model. QUADAS‐2 was used to assess risk of bias. Begg’s rank correlation and Egger’s regression tests were used to assess publication bias.ResultThe studies included 1,565 patients with PD, 206 with MSA, 21 with DLB, 172 with PSP, 152 with CBS and 967 HCs. Findings suggest that a combination of nEVs and oEVs α‐syn concentrations are higher in patients with PD vs. HCs (k = 14, SMD = 0.21; 95% CI 0.01, 0.42 p = 0.021), while nEVs α‐syn is lower in patients with PSP and CBS vs. PD (k = 6, SMD = ‐1.04; p = 0.0017) or HCs (k = 4, SMD = ‐0.41, p < 0.001). Additionally, α‐syn levels in oEVs didn’t effectively differ among PD, MSA, or HCs, contradicting the literature. Meta‐regressions showed demographic/ clinical were not significant predictors of nEVs or oEVs α‐syn concentrations.ConclusionThese findings highlight the need for adopting more rigorous, standardized procedures and independent validations across all laboratories studying biomarkers in CNS‐originating EVs. Additionally, there is a pressing need for improved biomarkers to distinguish among parkinsonian disorders more effectively.
Caregiver Enablement Training to Support Homecare: A Study from India
Authors: Tandon Ravina , N Navya , Dasgupta Jayashree 
Published: December 2023

AbstractHomecare is the prevalent model of dementia care in India and ‘attendants,’ who are non‐trained lay workers are often employed in Indian households to assist with personal care, ADL and other support which the family may need. Providing training to these attendants can support continued dementia care at home. We present initial data from a caregiver enablement program (CEP) being provided in India.MethodsThe (CEP) consists of a minimum of 6‐8 individually tailored sessions beginning with a clinical evaluation. Using a collaborative approach, challenging areas of caregiving are identified and prioritized. Across the sessions, information about what may be contributing to these challenges and tips for providing care are provided by a dementia trained specialist. Attendants and family members are encouraged to use these approaches and feedback was discussed in an iterative manner to improve the caregiving process and address emerging issues.ResultsTen families availed the caregiver enablement program, out of those 2 patients were living with their 24 hours attendant and 8 patients were living with family and attendants. The caregiver enablement program was conducted online, offline and in hybrid mode, 5 of them were online sessions, 4 offline sessions and one hybrid session (session conducted at home and online). Patients had moderate to severe stage dementia (Hindi MMSE Mn = 13.3, SD = 5.7; Caregiver burden: Zarit burden interview Mn = 29.8 SD = 19.6).Key areas where enablement was required were basic understanding of dementia, acceptance of the illness by the family and that they need external support, how to manage challenging behaviours like toileting, bathing, dressing, incontinence, transferring and feeding, how to engage the patient in meaningful activities and the need for environment modifications to improve safety and managing challenging behaviours. Psycho educational skill building, multi component intervention was found to be effective in the present study to combat the concerns shared by the attendants/family members.ConclusionThis study demonstrates how up‐skilling lay workers through training on dementia and management of challenging behaviours can support home care. Supporting the informal care system with specialised training can be an effective way of providing dementia care in low resource settings.
Head‐to‐head comparison of aptamer‐ and antibody‐based proteomic platforms in CSF samples of a real‐world large cohort of a memory clinic
Authors: Puerta Raquel , Cano Amanda , Smets Bart , García‐González Pablo , Haidar Mansour , Olivé Clàudia , Emon Asif , de Rojas Itziar , Sung Yun Ju , Frikke‐Schmidt Ruth , Marchant Natalie L , Lambert Jean‐Charles , Valero Sergi , Ramirez Alfredo , Cruchaga Carlos , Boada Mercè , Socorro Alfredo Cabrera , Ruiz Agustin 
Published: December 2023

AbstractBackgroundHigh‐throughput proteomic platforms are an useful strategy to detect novel biomarkers and pathways involved in Alzheimer’s disease (AD) development. Due to the novelty of these techniques, an extensive quality control assessment is needed to ensure the reliability of those protein measurements. In this study, we aimed to assess the reproducibility and reliability of SomaScan and Olink proteomic platforms and select top‐performing proteins for further analysis.MethodTo assess CSF proteomic measurements, we used the SomaScan 7k platform (an aptamer‐based technique) measuring 7335 human proteins, and Olink proteomics platform (Explore panel, an antibody‐based technique), measuring 3072 proteins in a subset of 509 individuals from ACE Alzheimer Center Barcelona (Spain). To assess intra‐ and inter‐platform reproducibility and reliability, we evaluated 1) the correlations of aptamers of two studies carried out in the same samples with SomaScan platform and 2) the correlation between SomaScan vs Olink proteomics, respectively. Then, we created a metric of 6 categories of reproducibility combining both intra and inter‐ correlation analysis, considering good (r > 0.5), modest (0.2 > r ≥ 0.5), poor (r ≤ 0.2) correlation. We considered proteins in the top 3 categories as potential candidates to further analysis.ResultFrom the intra‐platform analysis, only 2402 proteins (35.45%) showed a Pearson’s correlation higher than 0.5. Regarding inter‐platform assessment, 2160 proteins were overlapping between both platforms. From these overlapping proteins, 712 proteins exhibited a Pearson’s r > 0.5 (26.67%). We considered potential candidate proteins those with good intra‐ and inter‐platform correlation (n = 687, 9.02%), only good intra‐platform correlation (n = 2015, 26.45%) and modest intra‐ and inter‐platform correlation (n = 5, 0.06%) for analysis.ConclusionThe validation of the reproducibility and reliability of the new proteomics platforms is essential for the correct analysis of the results. The classification of measured proteins in different categories could be useful to increase the confidence in these highly multiplexed proteomic panels.