2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:T4e3,Biomarkers identify Alzheimer's disease pathology in cognitively unimpaired adults, but the timing and rate of cognitive decline vary widely. This study aimed to identify subgroups of cognitive decline and baseline predictors of heterogeneity in preclinical progression. Data were drawn from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease Study, which enrolled amyloid beta-positive (Aβ+) participants, and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study, which enrolled amyloid beta-negative (Aβ-) individuals. Latent class mixed-effects models identified cognitive trajectory classes. Associations between class membership and demographic, clinical, and biomarker variables were evaluated. The primary outcome was change in the Preclinical Alzheimer Cognitive Composite. Three trajectory classes were identified: stable, slow decliners, and fast decliners. Higher phosphorylated tau at 217 (p-tau217), smaller hippocampal volume, and elevated tau positron emission tomography were associated with declining classes. About 70% of Aβ+ individuals were stable. Latent class modeling reveals substantial heterogeneity in preclinical trajectories with important implications for prevention trial design.31:T76d,Abstract INTRODUCTION Biomarkers identify Alzheimer's disease pathology in cognitively unimpaired adults, but the timing and rate of cognitive decline vary widely. This study aimed to identify subgroups of cognitive decline and baseline predictors of heterogeneity in preclinical progression. METHODS Data were drawn from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's Disease Study, which enrolled amyloid beta‐positive (Aβ+) participants, and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study, which enrolled amyloid beta‐negative (Aβ−) individuals. Latent class mixed‐effects models identified cognitive trajectory classes. Associations between class membership and demographic, clinical, and biomarker variables were evaluated. The primary outcome was change in the Preclinical Alzheimer Cognitive Composite. RESULTS Three trajectory classes were identified: stable, slow decliners, and fast decliners. Higher phosphorylated tau at 217 (p‐tau217), smaller hippocampal volume, and elevated tau positron emission tomography were associated with declining classes. About 70% of Aβ+ individuals were stable. DISCUSSION Latent class modeling reveals substantial heterogeneity in preclinical trajectories with important implications for prevention trial design. 25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Plasma Biomarker: modality Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Plasma Biomarker (modality). Clinician-written summaries and actionable practice insights. Updated daily.\",\"url\":\"https://www.reachrx.ai/hub/tag/modality/Plasma%20Biomarker\",\"breadcrumb\":{\"@type\":\"BreadcrumbList\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https://www.reachrx.ai\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Research Hub\",\"item\":\"https://www.reachrx.ai/hub\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Modalities\",\"item\":\"https://www.reachrx.ai/hub/tag/modality\"},{\"@type\":\"ListItem\",\"position\":4,\"name\":\"Plasma Biomarker\",\"item\":\"https://www.reachrx.ai/hub/tag/modality/Plasma%20Biomarker\"}]}}"}}]],["$","$L2f",null,{"title":"Plasma Biomarker: Research & Clinical Takeaways","description":"Review evidence by treatment modality: Plasma Biomarker — concise summaries and practical next steps.","papers":[{"doi":"10.1002/alz.71722","pmid":"42554285","title":"Temporal order of clinical, imaging, and biomarker changes in frontotemporal lobar degeneration–associated syndromes","journal_title":"Alzheimer's & Dementia","journal_issn":"1552-5260","published_at":"2026-08-05T00:00:00.000Z","url":"https://doi.org/10.1002/alz.71722","source_score":10,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-12T13:26:10.002Z","updated_at":"2026-08-12T13:26:10.002Z","tags":[{"paper_doi":"10.1002/alz.71722","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"condition","value":"Behavioral Variant Frontotemporal Dementia","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"condition","value":"Corticobasal Syndrome","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"condition","value":"Frontotemporal Lobar Degeneration","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"condition","value":"FTD-ALS","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"condition","value":"Primary Progressive Aphasia","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"condition","value":"Progressive Supranuclear Palsy","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"generic","value":"glial fibrillary acidic protein","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"generic","value":"neurofilament light chain","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"modality","value":"MRI Volumetry","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"modality","value":"Neuropsychological Assessment","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"sample_size","value":"n=489","value_numeric":489},{"paper_doi":"10.1002/alz.71722","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"study_design","value":"Retrospective Longitudinal Cohort Study","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"warning","value":"CBS, PSP, and FTD-ALS subgroups were too small for independent cascade modeling; generalization of results to motor-predominant FTLD syndromes is limited.","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"warning","value":"Plasma GFAP and NfL trajectories were flagged as non-monotonic in mixed-effects fitting (minor deviation <0.001 normalized units/time step); their early cascade positions are descriptive, not strictly sigmoidal, and require prospective confirmation.","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"warning","value":"Pre-symptomatic biomarker trajectories are model extrapolations based on sigmoid parametric assumptions, not direct observations — early estimates should be interpreted with caution.","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"warning","value":"The cohort includes 104 pathogenic variant carriers (GRN, C9orf72, TARDBP, MAPT, etc.); while excluding them did not materially alter ordering, the label 'sporadic FTLD' may be imprecise given this genetic admixture.","value_numeric":null},{"paper_doi":"10.1002/alz.71722","tag_type":"warning","value":"The impact_flag 'practice_changing' was assigned because this is the first data-driven multimodal biomarker cascade for sporadic FTLD, offering a framework for trial design and early detection — but clinical implementation awaits prospective validation.","value_numeric":null}],"summaries":{"what_studied":"This retrospective longitudinal study modeled the temporal ordering of 10 multimodal biomarkers (plasma GFAP, plasma NfL, WMH volume, insular/frontal/gray matter atrophy on MRI, TMT-A, TMT-B, FBI, CDR-SoB) in 489 patients across the sporadic FTLD spectrum (bvFTD, PPA, CBS, PSP, FTD-ALS) over 1,904 patient-visit observations, using sigmoid trajectory modeling.","key_result":"Plasma GFAP departed from normality earliest (most gradual, pre-symptomatic trajectory), followed by TMT-B (earliest inflection point, θ = 0.3 years; only biomarker significantly abnormal 10–5 years before symptom onset), WMH volume, and plasma NfL. Insula atrophy had the steepest MRI transition (Smax = 0.137 pooled; 0.200 in PPA); CDR-SoB declined most steeply overall (Smax = 0.200). The cascade ordering was robust across 91% of biomarker pairs (precedence probability ≥0.80) and stable in non-carriers of pathogenic variants (Spearman ρ = 0.93).","limitations":"- Most participants were assessed at or after symptom onset, so pre-symptomatic trajectory estimates are model extrapolations (sigmoid assumptions) with wide confidence intervals, not direct observations.\n- Single-center design limits generalizability.\n- CBS, PSP, and FTD-ALS subgroups were too small for standalone cascade analyses; early biomarker positions are most firmly established for cortical phenotypes (bvFTD, PPA).","practice_takeaway":"Combining plasma GFAP with executive function testing (TMT-B) may offer the earliest detectable signal in sporadic FTLD, making them promising screening tools for prodromal disease. Biomarker sensitivity varies by disease stage and phenotype, so clinical trial designs should stratify by FTLD syndrome and target stage-specific endpoints."}},{"doi":"10.1002/alz.71567","pmid":"42522069","title":"Associations of dementia polyexposure scores to Alzheimer's disease endophenotypes in a diverse population","journal_title":"Alzheimer's & Dementia","journal_issn":"1552-5260","published_at":"2026-07-28T00:00:00.000Z","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13415752/","source_score":11,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-06T13:22:01.207Z","updated_at":"2026-08-06T13:22:01.207Z","tags":[{"paper_doi":"10.1002/alz.71567","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"condition","value":"Alzheimer's Disease","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"condition","value":"Dementia","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"condition","value":"Mild Cognitive Impairment","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"modality","value":"Clinical Risk Score","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"sample_size","value":"n=2627","value_numeric":2627},{"paper_doi":"10.1002/alz.71567","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"warning","value":"APOE ε4 carrier status was excluded from WHICAP scoring in this analysis to allow fairer comparison across CRSs — this differs from WHICAP's original validated form.","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"warning","value":"Higher AUC/R² in the Black/AA subgroup likely reflects more balanced case-control prevalence (41.7% CI) rather than true superior model performance in that group.","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"warning","value":"Several CRS components (diet, cognitive activity, atrial fibrillation, insomnia) were unavailable and omitted; this may underestimate true CRS performance, particularly for CogDRisk and LIBRA.","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"warning","value":"The paper's title uses 'polyexposure scores,' but the CRSs evaluated are standard clinical risk scores, not polygenic or polyexposure risk scores in the genomic sense — clinicians should not conflate these terms.","value_numeric":null},{"paper_doi":"10.1002/alz.71567","tag_type":"warning","value":"The study is cross-sectional, so associations between CRS and cognitive impairment may reflect reverse causality rather than prospective risk. The authors caution that cognitive outcome findings should be interpreted carefully.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional study evaluated four dementia clinical risk scores (CRSs) — mCAIDE, WHICAP, LIBRA, and CogDRisk — against AD endophenotypes (plasma biomarkers, neuroimaging, cognition) and pTau217/Aβ42-defined amyloid positivity in 2,627 adults (≥55 years) from the multiethnic HABS-HD cohort (23.5% Black/AA, 36.1% Hispanic/Latinx, 40.4% Non-Hispanic White).","key_result":"CogDRisk showed the strongest, most consistent associations across all endophenotypes and pTau217/Aβ42 positivity (OR ~1.63 overall; 63% NHW, 60% LA, 76% AA increased odds), and the highest AUC for dementia (0.65) among CRSs. Each SD increase in CRS corresponded to a 35–73% increase in odds of dementia. No CRS outperformed the demographics-only model (AUC 0.70) or demographics+APOE model. mCAIDE performed worst and lacked plasma biomarker associations.","limitations":"- Cross-sectional design prevents causal inference and cannot exclude reverse causality between CRS components and early AD pathology.\n- Some CRS components (diet, cognitive activity, atrial fibrillation, insomnia) were unavailable in HABS-HD and had to be omitted, potentially underestimating CRS performance.\n- Native American, Asian, and Pacific Islander groups were not included, limiting generalizability beyond Black, Hispanic/Latinx, and White populations.","practice_takeaway":"CogDRisk is the best-performing off-the-shelf risk score for flagging AD-related biological risk across Black, Hispanic/Latinx, and White patients in community settings, but should be paired with plasma biomarkers (e.g., pTau217/Aβ42) and APOE status rather than used as a standalone predictor. CRSs are most useful as low-cost, first-line screening tools to identify who warrants further biomarker or genetic workup."}},{"doi":"10.1212/wnl.0000000000214712","pmid":"42441927","title":"Performance of Alzheimer Disease Plasma Biomarkers in Patients With Prion Diseases","journal_title":"Neurology","journal_issn":"0028-3878","published_at":"2026-07-13T00:00:00.000Z","url":"https://doi.org/10.1212/wnl.0000000000214712","source_score":19,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-08-23T07:33:14.184Z","updated_at":"2026-08-23T07:33:14.184Z","tags":[{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"condition","value":"Alzheimer Disease","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"condition","value":"Creutzfeldt-Jakob Disease","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"condition","value":"Prion Disease","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"generic","value":"amyloid beta 42/40 ratio","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"generic","value":"brain-derived tau","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"generic","value":"glial fibrillary acidic protein","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"generic","value":"neurofilament light chain","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"generic","value":"p-tau181","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"generic","value":"p-tau217","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"impact_flag","value":"safety_signal","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"sample_size","value":"n=278","value_numeric":278},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"study_design","value":"Prospective Cohort Study","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"warning","value":"p-tau217 was measured with two different assay platforms (Simoa ALZpath in main study; Lumipulse in validation), and the two platforms showed different discriminatory performance for p-tau217 alone — clinicians should be aware of platform-specific differences.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"warning","value":"The AD comparator group was relatively small (n=33 in the main study) and was drawn from a single specialist cognitive disorders clinic, which may not reflect typical primary care populations.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"warning","value":"The NfL/p-tau217 ratio elevation is not specific to prion disease; the authors note it may also be elevated in FTD and ALS — this ratio should be interpreted as a flag for further investigation, not a confirmatory prion disease test.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214712","tag_type":"warning","value":"The study classified evidence as Class II per the authors' own rubric (not an external body), based on prospective design with some diagnostic limitations. Generalizability to non-specialist clinic settings is uncertain.","value_numeric":null}],"summaries":{"what_studied":"This prospective cohort study from the UK National Prion Clinic evaluated six plasma AD biomarkers (p-tau217, p-tau181, Aβ42/40, BD-tau, NfL, GFAP) in 278 individuals — including 204 with prion diseases (various subtypes), 33 with CSF-confirmed sporadic AD, and 41 healthy controls — to determine how well these markers distinguish prion disease from AD.","key_result":"Plasma p-tau217 and p-tau181 could not differentiate prion disease from sporadic AD (AUC 0.605 and 0.554, respectively). By contrast, the NfL/p-tau217 ratio was near-perfect at discrimination (AUC 0.996 [95% CI 0.987–1.000] in the main study; AUC 0.986 [0.966–1.000] in an independent validation cohort of 35 sCJD vs 32 sAD patients). Using the current Alzheimer's Association criterion of a single abnormal p-tau result, 25% of all prion disease patients would be misclassified as AD.","limitations":"- Healthy controls were not screened for undisclosed neurological disease, which could affect reference ranges.\n- Serial plasma sampling for longitudinal analysis was available only in a subset of patients.\n- Some prion disease subgroups (e.g., vCJD, iCJD) had small numbers, limiting subgroup conclusions.","practice_takeaway":"Do not rely on a single abnormal plasma p-tau217 or p-tau181 result to diagnose AD — these markers are elevated across all prion disease subtypes and will misclassify roughly 1 in 4 prion patients as AD. When prion disease is a diagnostic possibility, add a plasma NfL/p-tau217 ratio: a high value should trigger urgent specialist evaluation for prion disease rather than an AD diagnosis."}},{"doi":"10.1212/wnl.0000000000218180","pmid":"42308436","title":"Clinical Impact and Prognostic Value of Alzheimer Disease Biomarkers in the Very Old","journal_title":"Neurology","journal_issn":"0028-3878","published_at":"2026-06-17T00:00:00.000Z","url":"https://doi.org/10.1212/wnl.0000000000218180","source_score":48,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-07-03T13:39:02.376Z","updated_at":"2026-07-03T13:39:02.376Z","tags":[{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"condition","value":"Alzheimer Disease","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"condition","value":"Mild Cognitive Impairment","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"generic","value":"amyloid-beta 42","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"generic","value":"CSF phosphorylated tau 181","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"generic","value":"plasma phosphorylated tau 217","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"modality","value":"CSF Biomarker","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"sample_size","value":"n=167","value_numeric":167},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"study_design","value":"Retrospective Longitudinal Cohort Study","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"warning","value":"No neuropathologic confirmation available; AD biology is defined by CSF p-Tau181/Aβ42 ratio as a surrogate, not autopsy.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"warning","value":"Previously validated p-Tau217 cutoffs from younger cohorts (<0.19 and >0.39 pg/mL) showed reduced sensitivity (47%) in this very old population; the age-specific cutoff of 0.19 pg/mL used here has not yet been externally validated.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000218180","tag_type":"warning","value":"The 'practice_changing' impact flag is applied cautiously — while findings are clinically compelling, the single-center design and modest sample size (particularly n=12 for age >85) limit immediate generalizability. External validation in larger, multicenter cohorts is needed.","value_numeric":null}],"summaries":{"what_studied":"Retrospective longitudinal cohort study (SPIN cohort, Barcelona) evaluating AD biomarkers — CSF p-Tau181/Aβ42 ratio and plasma p-Tau217 — in 167 memory clinic patients aged ≥80 years with MCI, over a mean follow-up of 35.8 months (October 2013–May 2024).","key_result":"Plasma p-Tau217 detected CSF-defined AD biology with AUC 0.93 (95% CI 0.88–0.98; cutoff 0.19 pg/mL; sensitivity 94.5%, specificity 84%). Participants with AD biology declined faster on MMSE (−0.47 vs −0.18 points/year; p<0.01), and higher plasma p-Tau217 (continuous) was independently associated with dementia progression (HR 1.49, 95% CI 1.05–2.13, p=0.026).","limitations":"- Single-center design limits generalizability.\n- Modest sample size, especially for those >85 years (only 12/167), precluding subgroup analyses.\n- No autopsy confirmation and no biomarkers for non-AD pathologies (e.g., LATE, Lewy body disease).","practice_takeaway":"Plasma p-Tau217 reliably identifies AD biology and predicts faster decline even in patients aged ≥80 years — don't withhold biomarker testing on the basis of age alone. Use a two-step approach: screen with plasma p-Tau217, then confirm in equivocal cases, while factoring in the broader geriatric context including comorbidities and frailty."}},{"doi":"10.1016/s0140-6736(26)00515-5","pmid":"42208562","title":"Alzheimer's disease neuropathology plasma biomarkers and cognition in midlife: a community-based cohort study","journal_title":"The Lancet","journal_issn":"0140-6736","published_at":"2026-05-28T00:00:00.000Z","url":"https://doi.org/10.1016/s0140-6736(26)00515-5","source_score":336,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-31T13:35:43.854Z","updated_at":"2026-05-31T13:35:43.854Z","tags":[{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"category","value":"Medicine, General & Internal","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"condition","value":"Alzheimer's Disease","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"condition","value":"Cognitive Decline","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"generic","value":"amyloid beta 40","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"generic","value":"amyloid beta 42","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"generic","value":"p-tau217","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"sample_size","value":"n=1350","value_numeric":1350},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"study_design","value":"Prospective Cohort Study","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"warning","value":"Effect modification by race and sex was noted as inconsistent — subgroup findings should be interpreted cautiously.","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"warning","value":"Participant age range (53–69 years) spans both middle-aged and older-adult categories; 'midlife' framing used in the paper may not fully align with standard age-group definitions.","value_numeric":null},{"paper_doi":"10.1016/s0140-6736(26)00515-5","tag_type":"warning","value":"The study excluded individuals with probable dementia, so findings apply to a pre-dementia community population and may not generalise to clinical settings.","value_numeric":null}],"summaries":{"what_studied":"This cohort study examined plasma biomarkers of Alzheimer's disease neuropathology (Aβ42/40, p-tau217, and p-tau217/Aβ42 ratio) and their associations with cognitive performance and accelerated decline across five domains in 1,350 midlife adults (mean age 61 years) from the CARDIA study, a racially diverse US community sample assessed at years 30 and 35 (2020–22).","key_result":"AD neuropathology positivity ranged from 4–15% depending on biomarker; it was associated with worse processing speed (standardised difference −0.54 to −0.25) and executive function (−0.42 to −0.19), and with increased odds of accelerated verbal memory decline (Aβ42/40 OR 4.31, 95% CI 1.71–10.9; p-tau217/Aβ42 OR 2.44, 95% CI 1.16–5.13) and processing speed decline (p-tau217 OR 3.98, 95% CI 1.71–9.3; p-tau217/Aβ42 OR 3.35, 95% CI 1.77–6.35), with no association for global cognition or verbal fluency.","limitations":"- Single time-point plasma biomarker measurement limits causal inference and longitudinal tracking of neuropathology progression.\n- Amyloid PET validation cutpoints were applied to a community midlife sample, where their calibration may differ from clinical or older-adult populations.\n- Effect modification findings (stronger associations in women, Black participants, and APOE ε4 carriers) were not consistent across all biomarkers, limiting firm subgroup conclusions.","practice_takeaway":"Plasma AD biomarkers (especially p-tau217/Aβ42) can identify neuropathology in midlife adults before dementia onset, and positivity is linked to measurable cognitive decline in processing speed and verbal memory. Clinicians may consider midlife plasma screening to enable earlier risk-reduction counselling and timely pharmacological intervention."}},{"doi":"10.1177/13872877261450646","pmid":"42199003","title":"Differential associations of core and non-core plasma biomarkers with cognitive performance in Black adults","journal_title":"Journal of Alzheimer’s Disease","journal_issn":"1387-2877","published_at":"2026-05-27T00:00:00.000Z","url":"https://doi.org/10.1177/13872877261450646","source_score":7,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-08T13:46:49.856Z","updated_at":"2026-06-08T13:46:49.856Z","tags":[{"paper_doi":"10.1177/13872877261450646","tag_type":"age_group","value":"mixed","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"category","value":"Neurosciences","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"condition","value":"Alzheimer's Disease","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"condition","value":"Cognitive Decline","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"generic","value":"glial fibrillary acidic protein","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"generic","value":"neurofilament light chain","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"generic","value":"phosphorylated tau181","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"sample_size","value":"n=334","value_numeric":334},{"paper_doi":"10.1177/13872877261450646","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"study_design","value":"Prospective Cohort Study","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"warning","value":"Follow-up duration was only 1 year; longitudinal findings should be interpreted cautiously as short-term trajectories may not reflect longer-term cognitive decline patterns.","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"warning","value":"Study design is described as both cross-sectional and longitudinal; the longitudinal component is limited and based on baseline biomarker levels only.","value_numeric":null},{"paper_doi":"10.1177/13872877261450646","tag_type":"warning","value":"The study enrolled only Black adults from a community-based cohort (ARCHES), so results may not generalize to other racial/ethnic groups or clinical settings.","value_numeric":null}],"summaries":{"what_studied":"Cross-sectional and longitudinal associations between core (amyloid, phosphorylated tau181) and non-core (NfL, GFAP) plasma biomarkers and cognitive performance in 334 community-based Black adults (mean age 64.6 years) from the ARCHES study, with up to 1-year follow-up.","key_result":"Cross-sectionally, higher brain-derived p-tau181 was linked to lower MoCA scores (p=0.04) and higher NfL to lower PACC scores (p=0.04). Longitudinally, higher baseline NfL and GFAP were each independently associated with faster cognitive decline (p<0.001 and p=0.018, respectively).","limitations":"- Follow-up was limited to one year, which may underestimate longer-term biomarker-cognition relationships.\n- Cross-sectional design for the primary biomarker analyses limits causal inference.\n- Single-cohort, community-based sample of Black adults may limit generalizability to other settings or subgroups.","practice_takeaway":"In Black adults, non-core plasma biomarkers NfL and GFAP may be especially useful for tracking cognitive aging and decline—consider including them alongside standard amyloid/tau panels in ADRD screening and research. Efforts to increase representation of Black adults in biomarker studies are needed to ensure equitable ADRD detection."}},{"doi":"10.1007/s00702-026-03163-7","pmid":"42191917","title":"CogStrat: web-based tools for predicting incident cognitive impairment in cognitively normal older adults","journal_title":"Journal of Neural Transmission","journal_issn":"0300-9564","published_at":"2026-05-26T00:00:00.000Z","url":"https://doi.org/10.1007/s00702-026-03163-7","source_score":7,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-06T13:22:45.068Z","updated_at":"2026-06-06T13:22:45.068Z","tags":[{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"condition","value":"Alzheimer's Disease","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"condition","value":"Cognitive Impairment","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"generic","value":"florbetapir","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"generic","value":"neurofilament light chain","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"modality","value":"Amyloid PET","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"modality","value":"CSF Biomarker","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"modality","value":"FDG-PET","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"modality","value":"Neuropsychological Assessment","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"sample_size","value":"n=729","value_numeric":729},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"study_design","value":"Prognostic Model Development and Validation Study","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"warning","value":"Study design label 'Prognostic Model Development and Validation Study' is used as no standard single label covers this design; it is not a traditional RCT or observational cohort study.","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"warning","value":"The full text provided was almost entirely an ADNI investigator acknowledgement list; the abstract was the primary source for all clinical content. Methodological details (e.g., exact biomarker cutoffs, covariate handling, external validation sample size) could not be independently verified from the provided text.","value_numeric":null},{"paper_doi":"10.1007/s00702-026-03163-7","tag_type":"warning","value":"The 'practice_changing' impact flag reflects the novel delivery of validated prognostic models as freely accessible web tools, but generalizability is limited by the ADNI sample characteristics.","value_numeric":null}],"summaries":{"what_studied":"Cox proportional hazards models were developed to predict incident cognitive impairment in cognitively normal older adults (n=729 from ADNI, median age 73, 45% male), using clinical variables alone or combined with genetic, neuroimaging, and fluid biomarkers; models were internally and externally validated (Harvard Aging Brain Study).","key_result":"A clinical-only model (age, education, MoCA, delayed word recall) showed acceptable discrimination (C-index 0.721; 95% CI 0.672–0.772) and strong calibration (slope 0.940); adding FDG and florbetapir PET improved performance most (C-index 0.805; 95% CI 0.759–0.886). Five web tools (CogStrat) were built delivering individualized risk classifications, 5-year risk estimates, and 10-year cumulative incidence curves.","limitations":"- Internal validation used bootstrap resampling only; external validation was limited to one cohort (Harvard Aging Brain Study), and calibration was weaker for most plasma biomarker models.\n- ADNI participants are a volunteer, largely white, well-educated sample, limiting generalizability.\n- The full text provided was primarily an ADNI acknowledgement list, so finer methodological details could not be verified.","practice_takeaway":"Clinicians can use the free CogStrat web tools to stratify risk of cognitive impairment in cognitively normal older adults using routine clinical data, with the option to add biomarkers (particularly FDG/amyloid PET) when available to meaningfully improve prediction. A simple clinical model alone provides acceptable discrimination and may be practical in settings without biomarker access."}},{"doi":"10.1001/jamaneurol.2026.1405","pmid":"42189519","title":"Plasma eMTBR-tau243 and %p-tau217 for Biological Staging of Alzheimer Disease","journal_title":"JAMA Neurology","journal_issn":"2168-6149","published_at":"2026-05-26T00:00:00.000Z","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13213595/","source_score":28,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-31T13:35:28.466Z","updated_at":"2026-05-31T13:35:28.466Z","tags":[{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"condition","value":"Alzheimer Disease","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"condition","value":"Mild Cognitive Impairment","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"generic","value":"eMTBR-tau243","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"generic","value":"phosphorylated tau 217 (%p-tau217)","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"sample_size","value":"n=1028","value_numeric":1028},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"study_design","value":"Observational Longitudinal Study","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"warning","value":"eMTBR-tau243 is a relatively novel biomarker and may not yet be widely available on commercial platforms, which could limit immediate clinical translation.","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"warning","value":"The full text provided in the submission is from an unrelated machine learning paper (SHAP/NeurIPS 2017); the structured summary was derived exclusively from the abstract and results sections of the AD biomarker paper. Some details about longitudinal follow-up duration, assay platforms, and cohort demographics are limited to what was reported in the abstract.","value_numeric":null},{"paper_doi":"10.1001/jamaneurol.2026.1405","tag_type":"warning","value":"The 'practice_changing' impact flag is applied because this plasma-based staging model closely mirrors PET-based staging, but external validation in diverse real-world clinical settings is still needed.","value_numeric":null}],"summaries":{"what_studied":"This observational longitudinal study evaluated whether a plasma-based model combining %p-tau217 and eMTBR-tau243 could replicate PET-based biological staging of Alzheimer disease (AD) in 872 participants from BioFINDER-2 (cognitively unimpaired, MCI, AD dementia, and non-AD neurodegeneration) and 156 from the Knight ADRC validation cohort, with data collected from 2007–2025.","key_result":"The plasma model showed high concordance with PET-based stages in both the main cohort (C index 0.91; 95% CI 0.90–0.92) and validation cohort (C index 0.91; 95% CI 0.87–0.94). In a neuropathology subsample, plasma staging aligned with autopsy-confirmed AD pathology (AUC 0.96; 95% CI 0.91–1.00). The combined %p-tau217 + eMTBR-tau243 model outperformed %p-tau217 alone, especially for the intermediate A+TMOD+ stage.","limitations":"- Both cohorts are research-based and may not reflect the diversity of routine clinical populations.\n- The Knight ADRC neuropathology subsample was small, limiting generalizability of autopsy findings.\n- Longitudinal follow-up intervals and assay standardization across labs are not fully characterized in the abstract.","practice_takeaway":"Plasma %p-tau217 combined with eMTBR-tau243 can stage AD biologically with accuracy close to PET, using a minimally invasive blood test. Clinicians and trialists may consider this panel for patient selection for disease-modifying therapies, especially where PET is unavailable."}},{"doi":"10.1212/wnl.0000000000214983","pmid":"42133909","title":"The Role of Clinical, Plasma, and Imaging Biomarkers in Assessing Future Dementia Risk in Individuals With Subjective Cognitive Decline","journal_title":"Neurology","journal_issn":"0028-3878","published_at":"2026-05-14T00:00:00.000Z","url":"https://doi.org/10.1212/wnl.0000000000214983","source_score":28,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-23T13:25:19.669Z","updated_at":"2026-06-23T13:25:19.669Z","tags":[{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"condition","value":"Alzheimer Disease Dementia","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"condition","value":"Mild Cognitive Impairment","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"condition","value":"Subjective Cognitive Decline","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"generic","value":"phosphorylated tau 217","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"modality","value":"Genetic Risk Factor","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"modality","value":"Neuroimaging","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"sample_size","value":"n=469","value_numeric":469},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"study_design","value":"Longitudinal Observational Study","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"warning","value":"Plasma p-tau217 was measured using a Lilly Research Laboratories immunoassay on the MSD platform — findings may not directly translate to other commercial assay platforms currently in wider use.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"warning","value":"The impact_flag 'practice_changing' reflects the strong C-index performance of a clinically feasible model, but absence of external validation means results should be interpreted with appropriate caution.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214983","tag_type":"warning","value":"The study is from a Swedish memory clinic cohort; data on ethnicity and socioeconomic status are unavailable, which may limit generalizability to other populations.","value_numeric":null}],"summaries":{"what_studied":"This longitudinal observational study evaluated multimodal baseline biomarkers — cognitive scores, APOE4 status, plasma p-tau217, AD-signature cortical thickness, hippocampal volume, and white matter hyperintensities (WMHs) — for predicting progression to all-cause dementia, AD dementia, and MCI in 469 adults with subjective cognitive decline (SCD) from the BioFINDER-1 and BioFINDER-2 cohorts (mean age 69.1 years, 51.4% female) over a mean follow-up of 4.0 ± 2.1 years.","key_result":"84 of 469 SCD participants (17.9%) progressed to dementia; 66.7% of cases were AD dementia. Plasma p-tau217 alone was the strongest single predictor for AD dementia (C-index = 0.86). A parsimonious model combining plasma p-tau217 + cognitive scores + APOE4 achieved a C-index of 0.91 for AD dementia, with only marginal gain when MRI markers were added. For all-cause dementia, the full model (all variables) reached C-index = 0.89. MCI prediction was lower overall (C-index = 0.83 for the best model).","limitations":"- No external validation cohort; generalizability is uncertain.\n- MCI outcome analysis was limited to BioFINDER-2 only (n = 249), reducing statistical power.\n- Cognitive assessment covered only memory and executive domains, potentially missing language or visuospatial deficits relevant to non-AD dementias.","practice_takeaway":"In memory clinic patients with SCD, combining plasma p-tau217, standard cognitive testing (memory + executive), and APOE4 genotyping accurately predicts future AD dementia (C-index 0.91) — no MRI needed for this endpoint. Adding brain MRI (cortical thickness, hippocampal volume) provides incremental value mainly for predicting all-cause dementia, supporting a stepwise biomarker approach in clinical practice."}},{"doi":"10.1002/alz.71223","pmid":"42023677","title":"Diabetes, hyperglycemia, and ATN blood biomarkers in Hispanic/Latino populations: SOL‐INCA study","journal_title":"Alzheimer's & Dementia","journal_issn":"1552-5260","published_at":"2026-04-23T00:00:00.000Z","url":"https://doi.org/10.1002/alz.71223","source_score":63,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-07T22:49:24.734Z","updated_at":"2026-05-07T22:49:24.734Z","tags":[{"paper_doi":"10.1002/alz.71223","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"condition","value":"Alzheimer's Disease","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"condition","value":"Dementia","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"condition","value":"Diabetes Mellitus","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"generic","value":"amyloid beta 42/40","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"generic","value":"glial fibrillary acidic protein","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"generic","value":"hemoglobin A1c","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"generic","value":"neurofilament light chain","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"generic","value":"phosphorylated tau 181","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"sample_size","value":"n=6264","value_numeric":6264},{"paper_doi":"10.1002/alz.71223","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"warning","value":"Cross-sectional design: associations cannot establish causality between diabetes and ATN biomarker changes.","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"warning","value":"Diabetes status and HbA1c were measured at visit 1 (up to ~7 years before plasma biomarker collection at visit 2); temporal mismatch may affect exposure-outcome interpretation.","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"warning","value":"p-tau181 was used rather than the more sensitive p-tau217; findings may underestimate AD-specific tau associations.","value_numeric":null},{"paper_doi":"10.1002/alz.71223","tag_type":"warning","value":"Sample spans mid-life to older adults (≥50 years) across only four U.S. cities; may not represent all Hispanic/Latino subgroups or other ethnicities.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional study examined associations between diabetes status (no diabetes, prediabetes, diabetes) and continuous HbA1c percentage with plasma ATN biomarkers (Aβ42/40, p-tau181, NfL, GFAP) in N=6,264 mid-to-late-life Hispanic/Latino adults from the SOL-INCA ancillary study of HCHS/SOL.","key_result":"Diabetes (vs. no diabetes) was associated with higher NfL (β=0.253, p<0.001) and p-tau181 (β=0.091, p<0.001), and lower Aβ42/40 (β=−0.002, p<0.05) — equivalent to ~9 years of age-related Aβ42/40 decline. Each 1-point rise in HbA1c was linked to higher NfL (β=0.138), p-tau181 (β=0.063), GFAP (β=0.023), and lower Aβ42/40 (β=−7.0×10⁻⁴; all p<0.05). Prediabetes showed no significant associations. Diabetes-related p-tau181 elevation was stronger in men than women.","limitations":"- No PET or CSF validation; plasma ATN biomarkers are less specific than gold-standard imaging or lumbar puncture.\n- Cross-sectional design prevents causal inference; baseline cognitive status was not adjusted for.\n- Generalizability limited to urban U.S. Hispanic/Latino adults across four cities.","practice_takeaway":"In Hispanic/Latino patients, diabetes — but not prediabetes — is linked to plasma signatures of both AD-specific (amyloid, tau) and non-specific (NfL) neurodegeneration, underscoring the value of tight glycemic control as a potential lever for dementia risk reduction in this high-risk population. Plasma ATN panels may offer a practical, low-cost tool to monitor ADRD risk in diabetic patients when PET or CSF is not feasible."}},{"doi":"10.1002/alz.71366","pmid":"42015324","title":"Divergent patterns of cognitive decline in preclinical Alzheimer's disease: Implications for secondary prevention trials","journal_title":"Alzheimer's & Dementia","journal_issn":"1552-5260","published_at":"2026-04-22T00:00:00.000Z","url":"https://doi.org/10.1002/alz.71366","source_score":153,"is_retracted":false,"is_open_access":true,"raw_metadata":{"ooir":{"day":"2026-04-23","doi":"10.1002/alz.71366","days":"30","issn":"1552-5260","rank":"7","field":"Clinical Medicine","score":"153","category":"Clinical Neurology","categories":["Clinical Neurology"],"_categories":["Clinical Neurology"]},"pubmed":{"doi":"10.1002/alz.71366","title":"Divergent patterns of cognitive decline in preclinical Alzheimer's disease: Implications for secondary prevention trials.","journal":"Alzheimer's & dementia : the journal of the Alzheimer's Association","methods":"","results":"Three trajectory classes were identified: stable, slow decliners, and fast decliners. Higher phosphorylated tau at 217 (p-tau217), smaller hippocampal volume, and elevated tau positron emission tomography were associated with declining classes. 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The modality/brand tags reflect the parent trial context.","value_numeric":null},{"paper_doi":"10.1002/alz.71366","tag_type":"warning","value":"The 'practice_changing' impact flag was applied because the power analysis findings directly challenge standard trial design assumptions for preclinical AD, with quantitative implications for enrollment and outcome selection.","value_numeric":null},{"paper_doi":"10.1002/alz.71366","tag_type":"warning","value":"The study design is primarily a secondary analysis of RCT (A4) and observational (LEARN) data using latent class modeling—not a traditional RCT or prospective cohort; level of evidence reflects this hybrid design.","value_numeric":null}],"summaries":{"what_studied":"This study applied latent class mixed-effects models (LCMM) to data from 1,629 cognitively unimpaired older adults (A4 Study: n=1,110 Aβ+; LEARN Study: n=519 Aβ−; median follow-up 6.0 years) to identify subgroups of cognitive trajectory and evaluate baseline biomarkers—including plasma p-tau217, amyloid PET, tau PET, and hippocampal volume—as predictors of class membership, using the Preclinical Alzheimer Cognitive Composite (PACC) as the primary outcome.","key_result":"Three trajectory classes emerged: stable (77%), slow decliners (16%), and fast decliners (7%). About 70% of Aβ+ individuals were cognitively stable. Higher plasma p-tau217 (OR 3.2), greater hippocampal atrophy (OR 3.9), and elevated tau PET (OR 3.6 for fast decliners) were the strongest predictors of declining classes. Power analysis showed trials enrolling Aβ+ stable individuals had only 30–44% power at 2–4 years even assuming 100% treatment benefit, while trials targeting decliners had 93–98% power detecting just 20% of maximum benefit.","limitations":"- Tau PET was available in only 427 of 1,629 participants, limiting generalizability of tau PET findings.\n- Latent class assignments are probabilistic and sensitive to model specification; follow-up may be insufficient to capture long-term change in stable individuals.\n- Highly selected trial-eligible sample may not represent community-dwelling older adults, and unmeasured confounders (comorbidities, lifestyle) were not accounted for.","practice_takeaway":"Most amyloid-positive cognitively unimpaired adults remain stable over a 6-year window, so enriching prevention trials with plasma p-tau217 and tau PET—rather than relying on amyloid positivity alone—may improve power by targeting the minority who actually decline. Trial designs should use simulation-based power calculations that account for this trajectory heterogeneity, not single-effect-size assumptions."}},{"doi":"10.1212/wnl.0000000000214833","pmid":"41980229","title":"Cognitive and Brain Reserve as Modifiers of Early Alzheimer Disease–Related Cognitive Vulnerability","journal_title":"Neurology","journal_issn":"0028-3878","published_at":"2026-04-14T00:00:00.000Z","url":"https://doi.org/10.1212/wnl.0000000000214833","source_score":99,"is_retracted":false,"is_open_access":true,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-05-24T13:23:16.956Z","updated_at":"2026-05-24T13:23:16.956Z","tags":[{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"age_group","value":"older_adult","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"category","value":"Clinical Neurology","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"condition","value":"Alzheimer Disease","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"condition","value":"Preclinical Alzheimer Disease","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"generic","value":"p-tau217","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"impact_flag","value":"confirms_prior","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"level_of_evidence","value":"3","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"modality","value":"MRI Brain Age Estimation","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"modality","value":"PET Imaging","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"modality","value":"Plasma Biomarker","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"sample_size","value":"n=621","value_numeric":621},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"study_design","value":"Cross-Sectional Study","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"warning","value":"p-tau217 may not be entirely specific to AD brain pathology (e.g., elevated in ALS); authors address this by including PET Centiloid as convergent validation.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"warning","value":"The PET Centiloid subsample (n=355) was heavily weighted toward two of three study sites (Pittsburgh 53%, Kansas 46%), which may limit generalizability of secondary PET analyses.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"warning","value":"The SES moderation finding for episodic memory did not survive multiple-comparisons correction and should be considered exploratory.","value_numeric":null},{"paper_doi":"10.1212/wnl.0000000000214833","tag_type":"warning","value":"This is a cross-sectional analysis of baseline data from an RCT (IGNITE); causal conclusions cannot be drawn despite the RCT source. The study design tag reflects the nature of this analysis, not the parent trial.","value_numeric":null}],"summaries":{"what_studied":"This cross-sectional study (n=621 cognitively unimpaired adults, mean age 69.9±3.8 years, 71% female) tested whether proxies of cognitive reserve (years of education, objective SES) and brain reserve (brain-predicted age difference [brain-PAD], volumetric AD signature) moderated the association between AD pathology (plasma p-tau217; PET Centiloid in a subset of n=355) and performance across 5 cognitive domains at baseline of the IGNITE trial.","key_result":"Brain-PAD significantly moderated the p-tau217–cognition relationship across 4 domains — episodic memory (β=−0.09), processing speed (β=−0.08), working memory (β=−0.10), and executive function/attentional control (β=−0.08) — with weaker pathology-cognition links in those with younger-appearing brains; these effects survived false discovery rate correction. Objective SES moderated the p-tau217–episodic memory association (β=0.08) but did not survive correction. Years of education and the volumetric AD signature did not moderate any pathology-cognition relationship.","limitations":"- Cross-sectional design prevents causal inference; directionality between brain-PAD and AD pathology accumulation cannot be determined.\n- Sample was relatively well-educated (mean 16.3 years) and predominantly non-Hispanic White (75%), limiting generalizability and possibly reducing power to detect an education moderation effect.\n- PET Centiloid data were available in only a subset (n=355), and that subgroup was disproportionately from two of three sites.","practice_takeaway":"Patients who maintain a 'younger-appearing' brain (lower brain-PAD) show less cognitive impact from early AD pathology, suggesting that lifestyle strategies that preserve broad brain health may build reserve against emerging tau burden. Objective SES — not just years of education — may be a more informative proxy for cognitive reserve and warrants routine consideration in risk assessment."}}],"initialOffset":12,"fetchConfig":{"kind":"tags","tags":[{"tag_type":"modality","value":"Plasma Biomarker"}]},"breadcrumbItems":[{"name":"Home","href":"/"},{"name":"Research Hub","href":"/hub"},{"name":"Modalities","href":"/hub/tag/modality"},{"name":"Plasma Biomarker"}],"hrefConfig":{"basePath":"/hub/papers","webViewQueryParams":{"hub_ctx":"tag","hub_tag_type":"modality","hub_tag_value":"Plasma Biomarker"}}}]]

Papers