ADNI Biomarker Core: A review of progress since 2004 and future challenges DOI Creative Commons
Leslie M. Shaw, Magdalena Korecka, Edward B. Lee

et al.

Alzheimer s & Dementia, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 30, 2024

Abstract BACKGROUND We describe the Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core major activities from October 2004 to March 2024, including biobanking ADNI cerebrospinal fluid (CSF), plasma, and serum biofluid samples, analyses for disease (AD) biomarkers in various non‐ADNI laboratories, continuous assessments of pre‐analytics. RESULTS Validated immunoassay mass spectrometry‐based assays were performed CSF with a shift more accessible biofluid, as qualified became available. Performance comparisons across different plasma AD biomarker measurement platforms have enriched substantially participant database enabling method performance determinations pathology detection longitudinal progression. DISCUSSION Close collaboration academic industrial partners validation implementation early treatment trials ultimately clinical practice is key factor success work done Core. Highlights Describe sample distribution 2007 2024. Discuss validated spectrometry methods analyses. Review collaborations detect challenges, progress date, co‐pathology detection. Implementation ATN scheme: modeling

Language: Английский

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity DOI Creative Commons
Burak Arslan, Wagner S. Brum, Ilaria Pola

et al.

Alzheimer s Research & Therapy, Journal Year: 2025, Volume and Issue: 17(1)

Published: Feb. 19, 2025

Abstract Background Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain in routine diagnostic work-up patients with suspected AD, knowledge impact comorbidities utility is important. We aimed to evaluate association between function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD biomarkers, as well their influence over predicting Aβ-positivity. Methods included 242 participants Translational Biomarkers Aging Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; 58), dementia ( 34), non-AD 26) all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 p -tau217), 231 (p-tau231) N-terminal containing fragments (NTA-tau) using Simoa technology. Kidney was eGFR mL/min/1.73 m 2 , based age, sex. Participants also stratified according eGFR-indexed stages chronic (CKD). evaluated levels linear models whether provided added predictive value determine Aβ-positivity logistic regression models. Results Biomarker concentrations highest CKD stage 3, followed 1, but differences only significant NfL, Aβ40 (not Aβ42/Aβ40). All investigated showed associations except NTA-tau, stronger relationships observed NfL. However, after adjusting either sex or Aβ-PET SUVr, no longer GFAP. When evaluating accounting could lead improved prediction Aβ-positivity, we improvements model fit (Akaike Information Criterion, AIC) discriminative performance (AUC) adding base each biomarker, While covariates like age fit, contributed minimally, there clinical discrimination AUC values. Conclusions found that seems be associated concentrations. these did not remain sex, such any biomarker. Our findings indicate renal within normal range, does seem have clinically relevant when highly accurate p-tau217, biomarker-supported diagnosis.

Language: Английский

Citations

0
The Impact of Kidney Function on Alzheimer’s Disease Blood Biomarkers: Implications for Predicting Amyloid-β Positivity DOI Creative Commons
Burak Arslan, Wagner S. Brum, Ilaria Pola

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 7, 2024

Abstract Background Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain in routine diagnostic work-up patients with suspected AD, knowledge impact comorbidities utility is important. We aimed to evaluate association between function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD biomarkers, as well their influence over predicting Aβ-positivity. Methods included 242 participants Translational Biomarkers Aging Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; 58), dementia (n 34), non-AD 26) all characterized by [18F] AZD-4694. Plasma samples were analyzed Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) N-terminal containing fragments (NTA-tau) using Simoa technology. Kidney was eGFR mL/min/1.73 m², based age, sex. Participants also stratified according eGFR-indexed stages chronic (CKD). evaluated levels linear models whether provided added predictive value determine Aβ-positivity logistic regression models. Results Biomarker concentrations highest CKD stage 3, followed 2 1, but differences only significant NfL, Aβ40 (not Aβ42/Aβ40). All investigated showed associations except NTA-tau, stronger relationships observed NfL. However, after adjusting either sex or Aβ-PET SUVr, no longer GFAP. When evaluating accounting could lead improved prediction Aβ-positivity, we improvements model fit (Akaike Information Criterion, AIC) discriminative performance (AUC) adding base each biomarker, While covariates like age fit, contributed minimally, there clinical discrimination AUC values. Conclusions found that seems be associated concentrations. these did not remain sex, such any biomarker. Our findings indicate renal does seem have clinically relevant when highly accurate p-tau217, biomarker-supported diagnosis.

Language: Английский

Citations

0
Exploratory Blood Biomarker Patterns in a Mixed Dementia Cohort DOI Creative Commons
Haşim Gezegen, Merve Alaylıoğlu, Erdi Şahin

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 8, 2024

Abstract Alzheimer’s disease (AD) diagnosis is challenging due to overlapping symptoms with other dementias. Current diagnostic methods are invasive and costly, highlighting the need for accessible biomarkers. This study investigates performance pathophysiological implications of a novel plasma biomarker panel in mixed dementia cohort, aiming enhance elucidate underlying pathogenic mechanisms. 120 biomarkers were analyzed using NULISA™ platform well-characterized mixt dementia. CSF measured via ELISA. Statistical analyses employed ANOVA, Kruskal-Wallis tests group comparisons. Spearman correlations assessed relationships between Diagnostic accuracy was evaluated regression models ROC curves. Feature importance selection performed random forest analysis. Protein interactions GO enrichment We 248 subjects (130 females, 118 males) 117 AD, 50 MCI, 39 FTD, 25 DLB, 17 Plasma pTau significantly elevated AD compared groups, DLB MCI. Aβ42 highest while NfL FTD. GFAP MCI levels showed negative correlation positive entire cohort. also highly correlated. These stronger amyloid-positive groups but weaker or absent group. pTau, GFAP, negatively correlated MMSE FTD DLB. pTau217 demonstrated best amyloid positivity (AUCs 0.9, 0.84, 0.79, 0.87, respectively). pTau181, pTau217, pTau231, total-tau had lower odds AD. AGRN, CXCL1, SCNB, TEK, UCHL1 higher SNAP25 ratio MAPT, PGF related progression. Random analysis incorporating all biomarkers, age, gender yielded an AUCs 0.85 0.84 0.75 Refining model by including identified as significant improved performance, resulting 0.88 0.87 0.81 demonstrates potential enhancing through targeted refinement.

Language: Английский

Citations

0
Alzheimer's disease—Biomarkers, clinical evaluation or both? DOI Creative Commons
Joel Simrén,

Nicholas J. Ashton,

Marc Suárez‐Calvet

et al.

Journal of Neuropsychology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 14, 2024

Recent developments in fluid and imaging biomarkers that reflect the key pathological hallmarks of Alzheimer's disease (AD)—deposits extracellular amyloid-β (Aβ) intracellular tau proteins—have transformed perception living individuals from a clinical syndrome to biological continuum begins prior onset symptoms (Scheltens et al., 2021). Over past two decades, biomarker research has revealed Aβ deposition abnormal metabolism begin years before appear, following predictable sequence changes (Bateman 2012; Villemagne 2013). This suggests prolonged preclinical phase disease. Biomarkers, which have greatly expanded our understanding progression, are now routinely applied settings. These include Food Drug Administration (FDA)-approved positron emission tomography (PET) agents plaques aggregates, cerebrospinal (CSF) measures phosphorylated (p-tau), soon, plasma forms at amino acid 217 (p-tau217). As AD neuropathology is defining hallmark (Hyman 2012), as well being target emerging treatments, recently approved some countries (Cummings 2023), it reasoned directly these should be features view was formally articulated recent publication novel Association diagnostic staging criteria for AD, suggest can diagnosed when so-called 'Core 1' proteinopathy or secreted abnormal, resulting purely definition (Jack 2024). In years, studies shown PET detect (Clark 2012) (Fleisher 2020) with high (~90%) accuracy. CSF tests Aβ42/40 Aβ42/p-tau (Janelidze 2017) been validated against amyloid similar accuracy, subsequently also (Mattsson-Carlgren 2022). 5 an expanding body indicates p-tau217 pathology accuracy (Ashton 2023, 2024; Schindler 2024), will improve access diagnoses settings beyond what health care systems currently scaled accommodate. The published 2024) development by National Institute Aging (NIA-AA) 2018, aimed establish common language further evolution its relation symptomatology 2018). document, scheme added adjunct scheme, suggesting ('Core 2 biomarker'; including promising albeit explorative aggregates; Horie 2023) used conjunction biologically stage disease, due closer relationship aggregates (Ossenkoppele Another preceded full regulatory approval lecanemab (van Dyck donanemab (Sims FDA, several other bodies parts world well. trials relied on careful use biomarker-based inclusion, ensuring had targeted treatment (i.e. pathology). not case earlier failed trials, where dementia defined clinically, meaning diagnosis agnostic status. one significant proportion study participants were found negative (Salloway 2014), thus likely misdiagnosed. words, successfully treat biology must based underlying biology. Furthermore, such glial fibrillary acidic protein (GFAP; astroglial reflecting actviation) showed response anti-Aβ drugs they could engagement (Pontecorvo 2022; Sims 2023). Further supporting this, progress biomarkers, molecular neuropathology, enabled field gain greater knowledge between neuropsychological measures, biomarker/neuropathological findings. classical amnestic usually associated may instead limbic-predominant age-related TDP-43 encephalopathy (LATE) (Nelson 2019) cases, particularly oldest old patients. Conversely, syndromes primary progressive aphasia (Bergeron 2018), behavioural/dysexecutive 2015), corticobasal (Lee 2011) posterior cortical atrophy (Alladi 2007) pathology. It known present multiple pathologies (Robinson different cognitive resilience (Stern, genetic modifiers progression (Van Cauwenberghe 2016), typically (e.g. fluctuations symptoms, Lewy bodies), reflected dissociation Once again, however, does mean if positive consistent manifestations. On hand, judgement needed determine most explains symptomatology. Critics expressed new would enable detecting asymptomatic pathology, even though certain whether eventually develop Nevertheless, emphasizes can, but not, without (clinical 1) same reasoning applicable subjective complaints no objective impairment; 2), there treatments this group, prevalence cases low, hence, predictive values lower, higher falsely results unnecessary investigations anxiety (Hansson & Jack, change ongoing successful (Rafii leading scenario comparable cardiovascular hypertension lipid lowering) type diabetes (treatment hyperglycemia). absence we believe diagnosing conducted only symptomatic individuals, tandem evaluation, pre-test probability actionable consequences disease-modifying, treatments). Specific workflows scenario-based guidelines how under development. Future great importance increase confidence cause patient validation provide information PET). Promising microtubule-binding region (MTBR) (Horie 2023; Salvado p-tau 205 (p-tau205) (Gobom Lantero-Rodriguez Montoliu-Gaya, Alosco, Benedet, better than markers Aβ. Yet, biofluid accurately individual level yet proven. Further, possibility testing patients outside highly specialized contexts require large education efforts general practitioners interpret communicate test categories, close collaboration expert centres providers. Emphasis put around predefined cut-offs, continuous their nature, dichotomous categorization superimposed Therefore, values, strategies developed, intermediate range, grey zone, example (Brum any chemistry test, interpreted complete context more harm good. For example, slightly depressed problems very important consider depression causes positivity bother coming 10 years. Whenever doubt, judgement, follow-up potential reconsider ever. We changing step towards effective therapies, biology, although evaluation crucial both gatekeeping function ensure given relevant populations, inform likelihood contributing symptoms. Integrating provides foundation make meaningful current entity. Joel Simrén: Writing – original draft; writing review editing. Nicholas J. Ashton: Marc Suárez-Calvet: editing; draft. Henrik Zetterberg: MS-C receives funding European Research Council (ERC) Union's Horizon 2020 innovation programme (Grant agreement No. 948677); ERA PerMed (ERAPERMED2021-184); Project "PI19/00155" "PI22/00456, funded Instituto de Salud Carlos III (ISCIII) co-funded Union; fellowship "la Caixa" Foundation (ID 100010434) Marie Skłodowska-Curie grant No 847648 (LCF/BQ/PR21/11840004). HZ Wallenberg Scholar Distinguished Professor Swedish supported grants (#2023-00356, #2022-01018 #2019-02397), Europe 101053962, State Support Clinical (#ALFGBG-71320), Alzheimer Discovery (ADDF), USA (#201809-2016862), Strategic Fund (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, #ADSF-24-1284328-C), Partnership Metrology, co-financed Innovation Programme Participating States (NEuroBioStand, #22HLT07), Bluefield Project, Cure Fund, Olav Thon Foundation, Erling-Persson Family Familjen Rönströms Stiftelse, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), 860197 (MIRIADE), Union Joint Neurodegenerative Disease (JPND2021-00694), Health Care University College London Hospitals Biomedical Centre, UK Dementia UCL (UKDRI-1003). JS reports conflicts interest. NJA served scientific advisory boards and/or consultant Alamar Biosciences, Biogen, TauRx, TargetALS, Quanterix lectures sponsored BioArctic, Lilly ad VJDementia. received 36mo consultancy/speaker fees (paid institution) Almirall, Eli Lilly, Novo Nordisk, Roche Diagnostics. He consultancy Grifols granted project site investigator trial (funded In-kind support (to ADx Neurosciences, ALZPath, Avid Radiopharmaceuticals, Fujirebio, Janssen Development, Meso Scale Discovery, Diagnostics; did receive personal compensation organizations for-profit organization. Abbvie, Acumen, Alector, Alzinova, ALZpath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito CogRx, Denali, Eisai, LabCorp, Merry Life, Nervgen, Optoceutics, Passage Bio, Pinteon Prothena, Quanterix, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Wave, Alzecure, Cellectricon, WebMD, co-founder Brain Biomarker Solutions Gothenburg AB (BBS), part GU Ventures Incubator Program (outside submitted work). There data.

Language: Английский

Citations

0
Targeted Proteomic Biomarker Profiling Using NULISA in a cohort enriched with risk for Alzheimer's Disease and Related Dementias DOI Creative Commons
Ramiro Eduardo Rea Reyes, Rachael E Wilson,

Rebecca E. Langhough

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 29, 2024

Structured Abstract INTRODUCTION Targeted proteomic assays may be useful for diagnosing and staging Alzheimer’s disease related dementias (ADRD). We evaluated the performance of a 120-marker central nervous system (CNS) NUcleic acid-Linked Immuno-Sandwich Assay (NULISA) panel in samples spanning AD spectrum. METHODS Cross-sectional plasma (n=252) were analyzed using Alamar’s NULISAseq CNS panel. ROC analyses demonstrated NULISAseq-pTau217 accuracy detecting amyloid (A) tau (T) PET positivity. Differentially expressed proteins identified volcano plots. RESULTS accurately classified A/T status with AUCs 0.92/0.86. pTau217 was upregulated A+, T+, impaired groups log2-fold changes 1.21, 0.57 4.63, respectively, compared to A-. Interestingly, pTDP43-409 also group correlated declining hippocampal volume cognitive trajectories. DISCUSSION This study shows potential targeted proteomics characterizing brain pertinent ADRD. The promising findings require further replication.

Language: Английский

Citations

0
ADNI Biomarker Core: A review of progress since 2004 and future challenges DOI Creative Commons
Leslie M. Shaw, Magdalena Korecka, Edward B. Lee

et al.

Alzheimer s & Dementia, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 30, 2024

Abstract BACKGROUND We describe the Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core major activities from October 2004 to March 2024, including biobanking ADNI cerebrospinal fluid (CSF), plasma, and serum biofluid samples, analyses for disease (AD) biomarkers in various non‐ADNI laboratories, continuous assessments of pre‐analytics. RESULTS Validated immunoassay mass spectrometry‐based assays were performed CSF with a shift more accessible biofluid, as qualified became available. Performance comparisons across different plasma AD biomarker measurement platforms have enriched substantially participant database enabling method performance determinations pathology detection longitudinal progression. DISCUSSION Close collaboration academic industrial partners validation implementation early treatment trials ultimately clinical practice is key factor success work done Core. Highlights Describe sample distribution 2007 2024. Discuss validated spectrometry methods analyses. Review collaborations detect challenges, progress date, co‐pathology detection. Implementation ATN scheme: modeling

Language: Английский

Citations

0