Cerebral circulation - cognition and behavior最新文献

{"title":"Investigating the role of neuroinflammation and microglia on cerebrovascular function in Alzheimer's disease","authors":"Oliver Milner ,&nbsp;Robbie Fisher ,&nbsp;Daniel Asby ,&nbsp;James Armstrong ,&nbsp;Delphine Boche ,&nbsp;Scott Miners","doi":"10.1016/j.cccb.2025.100482","DOIUrl":"10.1016/j.cccb.2025.100482","url":null,"abstract":"<div><h3>Introduction</h3><div>Vessel-associated microglia (VAMs) have recently been identified as key regulators of cerebrovascular function implicated in blood-brain barrier (BBB) breakdown and impaired cerebral blood flow in Alzheimer’s disease (AD). We have explored the hypothesis that microglia migrate to the cerebral vasculature and exacerbate vascular damage associated with systemic infection and neuroinflammation.</div></div><div><h3>Methods</h3><div>We performed immunofluorescent labelling of FFPE sections from the superior temporal cortex of AD and control cases ± terminal systemic infection (N = 60). To characterise the density and phenotype of VAMs in each cohort, we immuno-labelled sections for CD31, CD68, Iba1 and HLA-DR. These measures were correlated with biochemical markers of cerebral perfusion, BBB integrity, and brain cytokine levels in corresponding frozen tissue from the same cases.</div><div>To explore microglial-cerebrovascular signalling, we exposed 3D co-cultures of HUVECs, pericytes, and microglia cultures to Aβ42 (1 uM), LPS (1 ug/mL) and Aβ42 and LPS in combination. Live cell imaging was used to assess microglial motility in response to vascular injury-conditioned media. Microarray analysis of the vascular co-culture media was conducted to identify signalling factors involved in microglial-cerebrovascular crosstalk.</div></div><div><h3>Results</h3><div>Immunofluorescence labelling showed an enrichment of Iba1+ve (p &lt; 0.05) and HLA-DR+ve (p &lt; 0.05) VAMs in AD. CD68 labelling revealed that VAMs were proportionally more phagocytic in AD alone (p &lt; 0.05) and in the presence of systemic infection (p &lt; 0.05). VAMs density was associated with markers of cerebral perfusion, BBB breakdown, and levels of brain cytokines. HMC3 microglia motility was increased upon exposure to HUVEC-pericyte media stimulated with AD-conditions. We will present data from the microarray to highlight specific signalling pathways influencing alterations in CAM motility.</div></div><div><h3>Conclusions</h3><div>We have shown that VAM density is increased in response to systemic infection and AD and is associated with neuroinflammation and markers of cerebral hypoperfusion and BBB breakdown. These studies provide further evidence that VAMs play an essential role in regulating cerebrovascular function in AD.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100482"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determinants of Vascular Cognitive Impairment: The Role of Biological Sex And Alzheimer’s Copathology","authors":"Anna Marseglia,&nbsp;Jonathan Graff-Radford,&nbsp;Scott A. Przybelski,&nbsp;Angela J. Fought,&nbsp;Mary M. Machulda,&nbsp;David S. Knopman,&nbsp;Ronald C. Petersen,&nbsp;Clifford R. Jack Jr,&nbsp;Eric Westman,&nbsp;Prashanthi Vemuri","doi":"10.1016/j.cccb.2025.100435","DOIUrl":"10.1016/j.cccb.2025.100435","url":null,"abstract":"<div><h3>Introduction</h3><div>Cerebrovascular disease (CVD) significantly contributes to dementia alongside Alzheimer’s disease (AD) and is primary etiology driving Vascular Cognitive Impairment (VCI). Preventing VCI requires understanding lifelong factors influencing its progression or potential reversal. This study’s primary goal was to use the new updated VASCOG-2 criteria for VCI and identify predictors in a longitudinal population-based sample with neuroimaging, plasma, and cognitive data. We also investigated sex-specific differences and the impact of AD pathology.</div></div><div><h3>Methods</h3><div>We selected 932 participants aged ≥50 with brain MRIs and cognitive testing from Mayo Clinic Study of Aging who had cognitive impairment (CI) based on criteria below. We classified CI into VCI negative/positive (VCI-/+) using the updated VASCOG-2 criteria, finalized in June 2024, incorporating white-matter hyperintensities (WMHs) and cognitive measures. Global cognition (z-global) was measured by averaging domain-specific z-scores for memory, language, attention, and visuospatial skills. Analyses were age- and sex- adjusted ANCOVA.</div></div><div><h3>Results</h3><div>Three groups were identified. VCI- included 391 CI (z-global ≤1.0) without CVD (WMH% &lt;1.3, no clinical stroke) (mean age 79.6±7.3 years, 41% female). Prevalent VCI+ (PVCI+) included 369 CI (z-global &gt;1.0) with CVD (clinical stroke or WMH% ≥1.3) at the first scan (mean age 82.6±5.6 years, 50% female). Incident VCI+ (IVCI+) included 172 who had CI and significant CVD during the visit but were not positive for both in a previous visit (mean age 84.0±5.1 years, 38% female). Differences between the three groups emerged in relation to sex, cardiometabolic comorbidities—particularly diabetes and hypertension—, late-life cognitive activities, excessive sleepiness, lipids levels (total and LDL-cholesterol), and abnormal amyloid PET SUVR.</div></div><div><h3>Conclusions</h3><div>Cardiometabolic comorbidities, lipids metabolism, and late-life engagement may be key predictors for VCI. Further investigation into sex-specific differences and the modifying role of AD co-pathology are needed.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100435"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Graphomotor Information Processing Speed and Process-Based Behavior: The Rowan Digital Cancellation Test","authors":"Ileana De Anda-Duran ,&nbsp;Shirine Moukaled ,&nbsp;Jessica G. Woo ,&nbsp;Vanessa Fonseca Lomeli ,&nbsp;Elaine M. Urbina ,&nbsp;Umayma Saifuddin ,&nbsp;Sabah Iqbal ,&nbsp;Thomas Auriemma ,&nbsp;Ganesh Baliga ,&nbsp;David J. Libon","doi":"10.1016/j.cccb.2025.100479","DOIUrl":"10.1016/j.cccb.2025.100479","url":null,"abstract":"<div><h3>Introduction</h3><div>The Rowan Digital Cancellation Tests (RDCT) is a suite of three computerized tests varying in stimulus complexity—letters, symbols, and mixed letter/symbol conditions. This study examined memory clinic patients and evaluated how RDCT outcome measures dissociate between diagnostic groups over four time epochs (30, 60, 90, and 120 seconds).</div></div><div><h3>Methods</h3><div>Ninety-eight patients (age=73.20±7.29; education=15.51±3.26; 46.3% female) were recruited from the Rowan University Memory Assessment Program (MAP). Cluster analysis classified participants into three groups: cognitively normal (CN; n=26, MMSE=28.73±1.07); mild cognitive impairment (MCI; n=61, MMSE=26.45±3.13); and dementia (DEM; n=11, MMSE=20.18±4.57).</div><div>RDCTs were administered on a 13-inch iPad Pro in landscape orientation. Sixteen targets appeared per quadrant for all tests. In the digital letter cancellation task, participants circled the letter “A”; in the symbol cancellation task, a designated geometric symbol; in the mixed condition, participants alternated between letter and symbol targets. Two primary outcome measures were analyzed: (1) correct hit/search time ratio (0–1.0), reflecting accuracy adjusted for search efficiency; and (2) mean drawing time (seconds) for correct targets.</div></div><div><h3>Results</h3><div>Analyses of the correct hit/search time ratio indicated that CN participants consistently outperformed MCI and DEM groups across nearly all tests and epochs (p&lt;0.050). At 120 seconds, all three groups were differentiated on the letter, symbol, and mixed tests (CN &gt; MCI &gt; DEM, p&lt;0.050). For mean drawing time, DEM participants were significantly slower than CN and MCI at 90 and 120 seconds across all test conditions (p&lt;0.030).</div></div><div><h3>Conclusions</h3><div>The Rowan Digital Cancellation Tests are easy to administer, well tolerated, and capture performance dimensions not typically available in standard assessments.</div><div>RDCT measures reliably distinguished between cognitively normal, MCI, and dementia participants, particularly at longer time intervals. These findings suggest that RDCTs may provide a sensitive and scalable approach for detecting early cognitive impairment and dementia in clinical and research settings.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100479"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning applications in vascular neuroimaging for the diagnosis and prognosis of cognitive impairment and dementia: a systematic review and meta- analysis","authors":"Valerie Lohner ,&nbsp;Amanpreet Badhwar ,&nbsp;David J. Llewellyn ,&nbsp;Timothy Rittman ,&nbsp;Sheena Waters ,&nbsp;Jose Bernal ,&nbsp;Vascular Imaging Subgroup of the Imaging Working Group","doi":"10.1016/j.cccb.2025.100416","DOIUrl":"10.1016/j.cccb.2025.100416","url":null,"abstract":"<div><h3>Introduction</h3><div>Cerebral small vessel disease (CSVD) is a common neurological condition that contributes to strokes, dementia, disability, and mortality worldwide. We conducted a systematic review and meta-analysis to investigate the use of neuroimaging CSVD markers in machine learning (ML)-based diagnosis and prognosis of cognitive impairment and dementia and identify both methodological changes over time and barriers to clinical translation.</div></div><div><h3>Methods</h3><div>Following the PRISMA guidelines, we systematically searched for original studies using both neuroimaging CSVD markers and ML methods for diagnosing and prognosing neurodegenerative diseases (preregistration in PROSPERO: CRD42022366767). Each paper was independently reviewed by a pair of reviewers at all stages, with a third consulted to resolve conflicts. We meta-analysed the ability of ML models to distinguish healthy controls from Alzheimer’s dementia and cognitive impairment, using area under the curve (AUC) as the performance metric.</div></div><div><h3>Results</h3><div>We identified 75 studies: 43 on diagnosis, 27 on prognosis, and 5 on both. Nearly 60% of studies were published in the past two years, reflecting a growing interest in using CSVD markers in ML-based diagnosis and prognosis of neurodegenerative diseases, especially Alzheimer’s dementia. This rising interest may be linked to the strong performance of such models: according to our meta-analysis, ML approaches using CSVD markers perform well in differentiating healthy controls from Alzheimer’s dementia (AUC 0.88 [95%-CI 0.85–0.92]) and cognitive impairment (AUC 0.84 [95%-CI 0.74–0.95]). The growing interest has unfortunately not been matched by methodological rigour: only 16 studies met the criteria for inclusion in the meta-analysis due to inconsistent reporting, just five assessed the generalisability of their models on external datasets, and six lacked clear diagnostic criteria.</div></div><div><h3>Conclusions</h3><div>Interest in incorporating CSVD markers into ML models for neurodegenerative disease classification is on the rise, and their performance suggests that this is worth further exploration. Serious methodological issues, including inconsistent reporting, limited generalisability testing, and potential biases, are unfortunately common and hinder further adoption. Our targeted recommendations provide a roadmap to accelerate the integration of ML into clinical practice.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100416"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a risk prediction model for post-stroke dementia: a STROKOG collaboration study","authors":"Jessica W Lo,&nbsp;John D Crawford,&nbsp;Perminder S Sachdev,&nbsp;STROKOG collaborators","doi":"10.1016/j.cccb.2025.100464","DOIUrl":"10.1016/j.cccb.2025.100464","url":null,"abstract":"<div><h3>Introduction</h3><div>Stroke is a major risk factor for dementia, with studies reporting incidence rates of up to 20% in the first year post-stroke. However, post-stroke cognitive impairment and dementia often go underdiagnosed in clinical practice. Most existing dementia prediction models were developed for the general population and perform poorly in stroke cohorts. The few stroke-specific models rely on neuroimaging, which is costly and not routinely available.</div><div>This study aimed to develop a clinically useful model to predict 5-year dementia risk after stroke, using data from international cohorts from the Stroke and Cognition Consortium (STROKOG).</div></div><div><h3>Methods</h3><div>Twelve longitudinal studies from 10 countries contributed data. Dementia was diagnosed using one or more of the following approaches: expert panel consensus (n=5 studies), single expert clinician (n=4), algorithmic classification based on neuropsychological testing (n=4), medical record review (n=4), or cognitive screening (MoCA or MMSE; n=4).</div><div>Routinely collected baseline variables were considered as candidate predictors. Data were harmonised and pooled for one-stage individual participant data meta-analysis. Fine and Gray subdistribution hazard models were used to account for the competing risk of death. Variable selection was conducted using backward stepwise elimination. Model performance was assessed using the concordance index (C-index) and calibration plots.</div></div><div><h3>Results</h3><div>A total of 2,688 participants (mean age 67 years [SD 11]; 40% female) were followed for a median of 1.9 years (IQR 1.0–5.0), during which 648 developed dementia. The crude 1-year post-stroke dementia incidence rate was 19.9 per 100 person-years (range 0.5–55 across studies).</div><div>The final model included age, sex, education, history of prior stroke, diabetes, stroke severity (mild vs moderate/severe), and interactions of age with sex (males had decreasing hazards with age) and age with stroke severity. After adjusting for study-level heterogeneity, the model demonstrated good discrimination (C-index = 0.802; 95% CI: 0.736–0.867) and calibration (Figure 1).</div></div><div><h3>Conclusions</h3><div>This model showed strong performance in predicting 5-year dementia risk following stroke. Further evaluation, including internal-external cross-validation, is planned to assess generalisability. A user-friendly Excel-based tool to calculate individual dementia risk will be presented. The tool may support clinicians in identifying high-risk individuals and enabling more personalised follow-up care.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100464"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effects of cognitive impairment and frailty on dementia incidence in older adults: A nationwide cohort study","authors":"Seon Young Ryu ,&nbsp;So-Jeong Park","doi":"10.1016/j.cccb.2025.100465","DOIUrl":"10.1016/j.cccb.2025.100465","url":null,"abstract":"<div><h3>Introduction</h3><div>Cognitive frailty is a heterogeneous clinical condition characterized by the co-occurrence of physical frailty and cognitive impairment in the absence of dementia. This study aimed to determine whether cognitive frailty is associated with an increased risk of incident dementia in older adults.</div></div><div><h3>Methods</h3><div>This retrospective nationwide cohort study utilized data from the Korean National Health Insurance database. The study population included individuals who participated in the National Screening Program for Transitional Ages at age 66 between January 1, 2007, and December 31, 2012. Participants were categorized into four groups: robust, cognitive impairment alone, physical frailty alone, and cognitive frailty. Physical frailty was defined as a Timed Up and Go test result &gt;10 seconds, and cognitive impairment was defined by a Korean Dementia Screening Questionnaire–Prescreening score ≥4. The primary outcome was incident dementia, defined by a diagnosis with relevant International Statistical Classification of Diseases, Tenth Revision, codes and prescription of anti-dementia medication (≥2 outpatient or ≥1 inpatient records after the index date).</div></div><div><h3>Results</h3><div>Among 741,655 participants (54.7% women), with a mean (SD) follow-up of 10.91 (2.60) years, 84,220 individuals (11.4%) developed all-cause dementia. Compared to the robust group, the cognitive frailty group had the highest risk of dementia (adjusted subdistribution hazard ratio [aSHR] = 1.74; 95% CI: 1.67–1.81), followed by the cognitive impairment alone group (aSHR = 1.50; 95% CI: 1.47–1.53) and the physical frailty alone group (aSHR = 1.20; 95% CI: 1.17–1.23). Dementia subtype analysis showed that cognitive frailty was associated with increased risk for both Alzheimer’s disease (aSHR = 1.71; 95% CI: 1.64–1.78) and vascular dementia (aSHR = 1.88; 95% CI: 1.65–2.16).</div></div><div><h3>Conclusions</h3><div>In this large-scale nationwide cohort, cognitive frailty at age 66 was associated with a significantly increased risk of dementia, including Alzheimer’s disease and vascular dementia. Cognitive frailty may serve as a useful early screening marker for dementia risk in populations transitioning into old age. Further research is needed to validate its clinical utility in diverse settings.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100465"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145796929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single cell epigenetic profiling of vascular and immune brain cells in Alzheimer’s disease","authors":"Baptiste Brulé,&nbsp;Charbel Gergian,&nbsp;Janna D van Dalen,&nbsp;Aydan Askarova,&nbsp;Kevin Chris Ziegler,&nbsp;Alexi Nott","doi":"10.1016/j.cccb.2025.100485","DOIUrl":"10.1016/j.cccb.2025.100485","url":null,"abstract":"<div><h3>Introduction</h3><div>Brain vascular dysfunction, implicating immune brain cells, is one of the earliest pathological changes associated with late-onset Alzheimer’s disease (AD).</div><div>Dysfunction and damage to the neurovascular unit activate microglial inflammation, while microglial dysfunction causes vascular Aβ deposition and damage, which support AD onset. Recently, single-cell analyses of purified brain blood vessels found that over two thirds of the top AD risk genes are enriched in brain vascular cell types and map onto neuroimmune processes, suggesting that AD risk variants could dysregulate brain vascular cells and genes regulating homeostatic neuro-immunity. Thus vascular-immune interaction is key to AD, and it remains essential to determine how epigenetic -and the associated transcriptomic- regulation is compromised in those cells, driving AD onset.</div></div><div><h3>Methods</h3><div>To decipher the epigenetic profile of vascular and immune brain cells, we use a single nuclei multiomic approach combining single nuclei CUT&amp;Tag targeting H3K27ac histone mark, with single nuclei RNA sequencing, in nuclei enriched from vascular cells.</div><div>Particularly, we are comparing the epigenetic signature in cortical tissue, from control and AD donors diagnosed with and without cerebral amyloid angiopathy.</div></div><div><h3>Results</h3><div>Our preliminary H3K27ac CUT&amp;Tag data generated on control samples show that AD GWAS risk variants loci are localized at enhancers (distal regulatory regions of gene expression, enriched in H3K27ac) in endothelial cells, providing support for the implication of epigenome in the brain vascular cells’ dysregulation. We have optimized the nuclei isolation and single nuclei CUT&amp;Tag protocols, to select and preserve blood-brain barrier associated cells, which enable us to profile H3K27ac at the single cell level in brain vasculature.</div></div><div><h3>Conclusions</h3><div>Analysis of post-mortem brains from AD donors will enable to identify key molecular mechanisms and epigenetic factors implicated in AD’s brain vascular dysfunction. We aim that this work will contribute to the development of therapeutical approaches targeting brain vasculature to act on vascular and neurodegenerative diseases.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100485"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Molecular Biomarker Panel for the Diagnosis of Vascular Cognitive Impairment and Dementia: A Multi-Cohort Study","authors":"Gurpreet Kaur Hansra ,&nbsp;Tharusha Jayasena ,&nbsp;Anne Poljak ,&nbsp;Perminder Sachdev ,&nbsp;Collaborators","doi":"10.1016/j.cccb.2025.100408","DOIUrl":"10.1016/j.cccb.2025.100408","url":null,"abstract":"<div><h3>Introduction</h3><div>Vascular Cognitive Impairment and Dementia (VCID) are a heterogenous group of disorders arising from cerebrovascular insufficiency to the brain. There has been limited progress in identifying blood biomarkers for its diagnosis. As several salient pathways are involved in VCID including endothelial dysfunction, neurovascular unit dysfunction, cardiac dysfunction and neuroinflammation, a targeted panel of biomarkers were measured in human plasma samples using multiplex and single plex assays.</div></div><div><h3>Methods</h3><div>Plasma samples were obtained from nine multinational cohorts (Singapore, USA and Australia) after phenotyping was performed using data from neuroimaging markers such as white matter hyperintensities, neuropsychological assessment results (MoCA or MMSE) and diagnosis. Over 1000 cases and controls from the following cohorts- Sydney Memory and Ageing Study, Older Australian Twins Study, Sydney Stroke Study, National Alzheimer’s Coordinating Centres, The Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing, MarkVCID, The Biomarkers and Consortium Study and Harmonisation cohort will be analysed. Plasma levels of 16 protein biomarkers -D-dimer, YKL40, VE- cadherin, ICAM-1, VCAM-1, Interleukin 6 and 18, Lipocalin 2, Matrix metalloproteinases-2 and 9, Lipoprotein-associated phospholipase A2, Placental growth factor 1, N-terminal (NT)- pro hormone BNP, TIMP metallopeptidase inhibitor 1, Vascular endothelial growth factor and Platelet-derived growth factor receptor ligand were measured using a two- plate design by multiplexing using the Luminex instrument platform (Bio-rad, California, USA). Myelin Basic Protein, Oligodendrocyte myelin glycoprotein and platelet-derived growth factor receptor beta were measured by ELISA assays. GFAP and NfL measurements were provided by respective study coordinators where available.</div></div><div><h3>Results</h3><div>Preliminary results from 4 out of 9 cohort show significant differences = for 8 of the plasma proteins: VE-cadherin (p &lt; 0.001), NT-proBNP (p = 0.01), VEGF-A (p = 0.01), YKL-40 (P&lt;0.001), D-dimer (p = 0.01), ICAM-1 (p = 0.002) NGAL (p = 0.001) and TIMP-1 (p&lt;0.001) were found to be significantly elevated in cases vs controls. A preliminary analysis of claudin-5 and occludin found no significant differences between cases and controls (p &gt;0.05).</div></div><div><h3>Conclusions</h3><div>Our findings suggest that the nine biomarkers may indeed be upregulated in VCID. Further longitudinal analyses and measurements using more sensitive assays like SIMOA may improve the prognosis of these markers in prediction and monitoring.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100408"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between retinal microvasculature, cerebral small vessel disease, and cognition among middle-aged adults with type 1 diabetes","authors":"Iiris Kyläheiko ,&nbsp;Aleksi Tarkkonen ,&nbsp;Linda Kuusela ,&nbsp;Juha Martola ,&nbsp;Teemu I. Paajanen ,&nbsp;Per- Henrik Groop ,&nbsp;Lena M. Thorn ,&nbsp;Jukka Putaala ,&nbsp;Hanna Jokinen ,&nbsp;Daniel Gordin ,&nbsp;on behalf of the FinnDiane Study Group","doi":"10.1016/j.cccb.2025.100409","DOIUrl":"10.1016/j.cccb.2025.100409","url":null,"abstract":"<div><h3>Introduction</h3><div>Type 1 diabetes (T1D) is a risk factor for retinal microvascular pathology, cerebral small vessel disease (cSVD), and cognitive symptoms already in middle age. In older adults with long T1D duration, decreased vessel densities of superficial (SCP) and deep (DCP) retinal capillary plexuses have been associated with cognition. We assessed whether these associations are evident already in midlife in patients without overt neurological symptoms. We also assessed whether cSVD brain markers moderate these associations.</div></div><div><h3>Methods</h3><div>As part of Finnish Diabetic Nephropathy Study, we examined 155 adults with T1D (age 46.4±7.5 years, 52% women, T1D duration 30.7±10.1 years). Vessel densities of the SCP and DCP, and area of foveal avascular zone (FAZ) were measured with macular 3 × 3 mm optical coherence tomography angiography (OCTA) imaging. We also performed an extensive neuropsychological assessment and brain MRI, from which we analyzed number of cerebral microbleeds and white matter hyperintensity volumes. The statistical analyses focused on cognitive processing speed and executive function subdomains of inhibitory control, cognitive flexibility, and working memory, assessed with WAIS-IV Coding subtask, Stroop test, and computerized Flexible Attention Test (FAT).</div></div><div><h3>Results</h3><div>In univariate linear regression models, associations were found between declined vessel density of SCP and processing speed (FAT subtest of Reaction Time [FAT-RT]) and cognitive flexibility (FAT subtask of Number Month Forward [FAT-NMF]) (stand. β=–0.25 for both, p&lt;0.05). Decreased vessel density of DCP was associated with worse performance in processing speed (Coding, Stroop-II, and FAT-RT), cognitive flexibility (FAT-NMF), and inhibitory control (Stroop-III) (stand. β=–0.27 to –0.20, p&lt;0.05). Larger FAZ was associated with poorer working memory (FAT Memory Backward subtask [FAT-MB]; stand. β=–0.28, p&lt;0.05). After adjusting for age, the association between FAZ and FAT-MB remained significant (stand. β=–0.26, p&lt;0.05). No interaction effects were found between brain MRI and OCTA markers.</div></div><div><h3>Conclusions</h3><div>Noninvasive retinal microvascular OCTA markers were associated with poorer cognitive performance in middle-aged individuals with T1D. While most of these associations were related to age, poorer working memory performance was associated independently of age with enlarged FAZ as a marker of retinal vascular disease. Brain MRI markers did not moderate these associations.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100409"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disentangling the contributions of cerebrovascular-related white matter integrity markers to cognitive aging","authors":"Elmira Agah ,&nbsp;Sarah T. Farias ,&nbsp;David K. Johnson ,&nbsp;Charles DeCarli ,&nbsp;Pauline Maillard","doi":"10.1016/j.cccb.2025.100395","DOIUrl":"10.1016/j.cccb.2025.100395","url":null,"abstract":"<div><h3>Objective</h3><div>To determine the independent and joint associations of five markers of white matter integrity, including white matter hyperintensities (WMH), extracellular free water (FW), fractional anisotropy (FA), peak width of skeletonized mean diffusivity (PSMD), and Diffusion tensor image analysis along the perivascular space index (ALPS) on cognitive performance and its trajectory in cognitively diverse individuals.</div></div><div><h3>Methods</h3><div>574 participants from the University of California, Davis Alzheimer’s Disease Research Center (UCD ADRC) longitudinal cohort, aged 77 ± 7 years received yearly comprehensive clinical evaluations and a baseline MRI exam. Baseline MRI measures, including WMH, FW, FA, PSMD, and ALPS, were computed for each individual and used as independent variables to explain baseline and change in episodic memory (EM) and executive function (EF) using linear regression with stepwise adjustment. Bayesian Model Averaging (BMA) was then applied to derive robust estimates of each marker’s contribution to cognition and its longitudinal trajectory, accounting for their joint inclusion in the same model.</div></div><div><h3>Results</h3><div>Analyses showed that higher baseline WMH, FW, and PSMD, as well as lower FA and ALPS, were significantly associated with poorer cognitive performance (<em>p</em> &lt; 0.05). These associations remained robust after adjusting for relevant covariates—including age, sex, education, hypertension, diabetes, and hippocampal volume—except for FA and ALPS, which were no longer associated with EM (p &gt; 0.05). Higher baseline WMH, FW, and PSMD, and lower FA, were also significantly associated with annual decline in EF and EM, whereas ALPS showed no association with cognitive change (p &gt; 0.05). After covariate adjustment, these associations remained significant, except for PSMD and FA which were no longer significantly associated with EM trajectory. Joint modeling using BMA identified FW and WMH as the most likely contributors to both baseline performance and change in EF and EM, with posterior inclusion probabilities exceeding 50 %.</div></div><div><h3>Conclusions</h3><div>This study identified both cross-sectional and longitudinal associations between five markers of white matter integrity and cognitive performance and decline. Using BMA—a method designed to disentangle the specific contribution of each marker while accounting for multicollinearity—we found that, among the five markers, FW and WMH emerged as the most probable candidates to explain the course of cognitive decline in EM and EF.</div></div>","PeriodicalId":72549,"journal":{"name":"Cerebral circulation - cognition and behavior","volume":"9 ","pages":"Article 100395"},"PeriodicalIF":2.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}