The Biofluid Biomarkers Best Practices Workgroup of the National Alzheimer’s Coordinating Center-Alzheimer’s Disease Research Center (ADRC) Biomarker Core Steering Committee was convened to update pre-analytical handling guidelines for biofluid biomarkers, focusing on cerebrospinal fluid (CSF) and blood. We reviewed current literature pertinent to best practices for biomarker studies and surveyed the ADRCs for biomarker analytes, platforms, and protocols used at each center. Across 37 ADRCs, 16 CSF and 28 plasma/serum analytes were reported to be studied at multiple centers. The pre-analytical handling steps and concerns related to each, as supported by empirical studies and expert opinion, were integrated to generate a revised guideline document. The guideline aimed to standardize steps in biospecimen and biomarker analyte collection, storage, and pre-analytical handling across the ADRCs. The 2025 ADRC guidelines represent the current working knowledge on biomarker best practices, providing guidance and harmonized protocols, and promoting robust analysis and reporting of composite data.

Blood inflammatory marker studies in aging and Alzheimer’s disease (AD) research have faced numerous interpretative and methodological challenges that have hindered the field’s understanding of the relationship between immune network regulation/dysregulation and aging health factors. We examined how blood inflammation markers directly relate to each other in typical aging, cognitively unimpaired adults using a conditional network analytic modeling approach. We further evaluated how blood inflammation networks relate to key aging risk factors by decomposing the networks into eigenvectors with associated hub proteins and then evaluated the associations of the resulting eigenproteins with demographic information, core biomarkers of AD pathobiology in CSF and blood, and immune health history. Networks of blood inflammation markers showed both divergent and convergent relationships with outcomes, including strong associations between a CXCL5-driven blood inflammation network and age, sex, and CSF Aβ42/Aβ40, and an IL-6- and FGF-21-driven network and sex, CSF Aβ42/Aβ40, and Qalb (CSF-serum albumin ratio). An IFN-gamma- and CXCL9-driven network was associated with both age and CSF Aβ42/Aβ40, whereas blood inflammation networks with hub proteins of CXCL11/CXCL9 and CCL19/CCL4, respectively, were associated solely with sex. Finally, an MCP-3-, MCP-4-, and CXCL6-driven network was associated with cumulative surgical procedure exposures. Despite associations between CSF Aβ42/Aβ40 and multiple networks, plasma Aβ42/Aβ40 was not significantly associated with any blood inflammatory network. Our findings highlight the importance and the challenges of inferring immune pathophysiology from blood-based markers; mirroring the complex pleiotropic biology of inflammation, blood inflammatory markers show associations with multiple demographic and salient health factors in aging adults.

Introduction: α-Synuclein is the hallmark pathology of Parkinson’s disease and dementia with Lewy bodies, described together as Lewy body disease (LBD). We investigated effects of α-syn biomarker positivity in clinically unimpaired (CU) individuals.

Methods: We assessed α-syn status (α-syn ±) in 269 CU individuals using a cerebrospinal fluid (CSF) seed amplification assay (SAA). Fifty-six participants with AD and 85 LBD spectrum participants were included for comparison. We compared α-syn SAA results with demographics, fluid biomarkers, cognitive performance, and clinical measures.

Results: α -Syn positivity was detected in 9% of CU individuals, a lower rate than in clinically impaired participants with AD (16%) and LBD diagnoses (81%). Compared to α-syn-, α-syn+ CU individuals were older, showed lower synaptic integrity, performed worse on tests of executive function and working memory, and reported more LBD-related non-motor symptoms.

Discussion: Further work is needed to understand the timeline of neural and clinical changes in α-syn+ CU individuals and heterogeneity in disease progression.

Background
Multi-analyte plasma proteomic panels that can accurately detect initial Alzheimer’s disease (AD) pathology in preclinical populations and simultaneously measure related biological processes relevant for disease risk are critical for advancing early detection and prognosis.

Methods
Using the NULISAseq™ CNS panel, we measured plasma proteomics from 315 clinically unimpaired (CU) older adults across two independent cohorts: the Stanford Aging and Memory Study (SAMS; n = 193) with paired cerebrospinal fluid (CSF) and plasma analyzed with Lumipulse, and the Attention, Memory, and Aging Study at Stanford (AMASS; n = 122) with paired florbetaben (FBB) amyloid PET. We evaluated correspondence of core AD-relevant biomarkers pTau217, pTau181, Aβ42/Aβ40, pTau217/Aβ42, GFAP, and NfL measured using multiplex NULISAseq and single-plex Lumipulse immunoassays. ROC curve analyses compared performance for detecting amyloid-positivity (A+) (a) across platforms in SAMS and (b) across brain-derived (BD) and total-pTau assays in AMASS, leveraging novel NULISAseq immunoassays. Linear models were applied across all NULISAseq CNS proteins to explore proteomic abundance patterns associated with age, sex, APOE-ε4, amyloid burden (CSF Aβ42/Aβ40, amyloid PET), and tau burden (CSF pTau181, PI-2620 tau PET) using an FDR-corrected p-value of < 0.05 to identify significant targets. Results In SAMS, moderate to high correlations were observed between NULISAseq and Lumipulse plasma biomarkers. NULISAseq pTau217/Aβ42 (AUC: 0.940) and pTau217 (AUC: 0.879) performed as well as corresponding single-plex Lumipulse assays (pTau217/Aβ42, AUC: 0.907; pTau217, AUC: 0.838) for detecting CSF A+ in SAMS. In AMASS, BD-pTau217 (AUC: 0.920) and BD-pTau181 (AUC: 0.920) exhibited the highest performance in discriminating PET A+, providing significant performance gains compared to total-pTau measures (pTau217, AUC: 0.861; pTau181, AUC: 0.763). Exploratory proteomic abundance analyses across NULISA CNS targets revealed pTau isoforms as most differentially expressed with amyloid burden across cohorts, together with upregulation of GFAP and downregulation of Aβ42 in SAMS. Tau burden was associated with upregulation of plasma pTau217, independent of amyloid burden, together with proteins related to astrocyte activation, inflammation, and synaptic integrity. Conclusions NULISAseq multiplex immunoassays, including novel BD-pTau assays, accurately detect AD pathology among CU older adults and identify multiple biological pathways related to aging and early biomarker abnormality that may become dysregulated in preclinical AD.

Neurodegenerative diseases (NDs), including Alzheimer’s disease (AD), Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and Frontotemporal Dementia (FTD) share overlapping clinical and pathological features. We analyzed cerebrospinal fluid (CSF) and plasma proteomes from 2,705 and 3,009 samples, respectively, across these NDs, identifying disease-specific and shared molecular signatures. CSF showed more disease-associated proteins than plasma, with AD and DLB exhibiting the strongest cross-tissue similarity. Pathway analyses revealed shared dysregulation of immune-related processes in CSF and plasma across the NDs, as well as disease-specific impairment of glycosylation and apoptotic pathways in AD; ATF4 and PERK signaling in PD; FGFR and interleukin signaling in DLB; and glycoprotein hormones disruption in FTD. We developed disease-specific predictive models showing high accuracy (AUC: 0.81–0.95 in CSF and 0.80–0.89 in plasma). These findings reveal distinct and convergent mechanisms across NDs, highlighting potential biomarkers and pathways for diagnostic and therapeutic strategies in neurodegeneration.

Multiple proteinopathies commonly coexist in neurodegenerative diseases, making it essential to evaluate plasma biomarker performance in these complex diseases. While plasma biomarkers accurately detect amyloid-β pathology in Alzheimer’s disease (AD), their performance is unknown in neuronal synuclein disease (NSD). We aimed to determine the accuracy of plasma pTau217, pTau181, Aβ42/40, GFAP, and NfL to detect amyloid-β in NSD, then establish and validate cut points for the most promising marker. We included 253 participants (180 discovery; 73 validation). In the discovery cohort, NSD status was defined by CSF α-synuclein seed amplification assay and amyloid-β status by CSF Aβ42/40. Participants included individuals with clinical Lewy body disease (LBD), AD, and cognitively unimpaired. Validation cohorts consisted of clinically diagnosed LBD participants. In the discovery cohort, plasma pTau217, pTau181, Aβ42/40, and GFAP significantly differed by amyloid-β status regardless of NSD status, while NfL was highest in NSD+/Aβ+ participants. Among all biomarkers, plasma pTau217 showed the best diagnostic performance (AUC = 0.92, 95% CI = 0.81-0.98). Applying plasma pTau217 cut points to pre-screen clinically diagnosed LBD participants reduced the need for confirmatory amyloid-β PET or CSF in 41-56%. These findings support plasma pTau217 as a minimally-invasive tool for identifying pathological amyloid-β in neuronal synucleinopathies with mixed Alzheimer’s disease pathology.

Introduction: Alzheimer’s disease (AD) is characterized by the progressive accumulation of amyloid-beta (Aβ) plaques, tau tangles, and neurodegeneration (ATN framework). While neuroimaging detects these changes, it is costly and not widely accessible. Blood-based biomarkers offer scalable alternatives for early detection.

Methods: We integrated plasma biomarkers, neuroimaging, and cognitive data from two large cohorts. We examined multivariate patterns of plasma Aβ42/Aβ40, phosphorylated tau (p-tau) 217, p-tau181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) that predict amyloid, tau, neurodegeneration, and memory decline.

Results: Specific plasma biomarker combinations predicted amyloid burden in the precuneus, tau in the entorhinal cortex, hippocampal atrophy, and memory decline. Models trained in one cohort accurately predicted outcomes in the other, confirming cross-cohort generalizability.

Discussion: Distinct plasma signatures reflect underlying AD pathways, supporting the use of blood-based biomarkers as cost-effective, noninvasive tools for early detection, disease monitoring, and individualized risk profiling.

Introduction: In Alzheimer’s disease (AD), females have higher prevalence and faster progression, but sex-specific molecular findings in AD are limited.

Methods: We comprehensively examined 6162 proteins in cerebrospinal fluid (CSF) from 2496 participants to identify sex-specific proteomic alteration by CSF amyloid beta (Aβ)42 and phosphorylated tau (p-tau) levels.

Results: We identified and replicated 68 male-specific and 116 female-specific proteins associated with Aβ42 and/or p-tau levels. Apolipoprotein E ε4 carrier status modified sex-specific alterations of multiple proteins including S100A9 and NEFL for Aβ42 and MAPK9 and MAPKAPK2 for p-tau. Male-specific proteins, enriched in microglia, were involved in activating innate immune response. The male network exhibited direct connections among 30 proteins and highlighted MAPKAPK2 as a hub. Female-specific proteins, enriched in endothelial cells, were involved in regulating protein metabolic process. The female network exhibited direct connections among 43 proteins and highlighted CSNK2A2 and PRKCA as hubs.

Discussion: Our findings provide insights into mechanistic understanding of sex differences in AD risk.

Highlights: Our proteomic study of 6162 proteins (targeted by 7006 aptamers) in cerebrospinal fluid (CSF) from 2496 participants identified and replicated 68 male-specific and 116 female-specific proteins associated with cerebrospinal fluid amyloid beta 42 and/or phosphorylated tau levels. Male-specific proteins, enriched in microglia, were involved in activation of innate immune response. The male network highlighted MAPKAPK2 involved in chronic neuronal neuroinflammation as a hub. Female-specific proteins, enriched in endothelial cells, were involved in regulation of protein metabolic process and response to external stimuli. The female network highlighted PRKCA regulating synaptic plasticity and CSNK2A2 protein involved in neuroplasticity as hubs.

Recent studies demonstrate that Parkinson’s disease (PD) is associated with dysregulated metabolic flux through the kynurenine pathway (KP), in which tryptophan is converted to kynurenine (KYN), and KYN is subsequently metabolized to neuroactive compounds quinolinic acid (QA) and kynurenic acid (KA). Here, we used mass-spectrometry to compare blood and cerebral spinal fluid (CSF) KP metabolites between 158 unimpaired older adults and 177 participants with PD. We found increased neuroexcitatory QA/KA ratio in both plasma and CSF of PD participants associated with peripheral and cerebral inflammation and vitamin B₆ deficiency. Furthermore, increased QA tracked with CSF tau, CSF soluble TREM2 (sTREM2) and severity of both motor and non-motor PD clinical symptoms. Finally, PD patient subgroups with distinct KP profiles displayed distinct PD clinical features. These data validate the KP as a site of brain and periphery crosstalk, integrating B-vitamin status, inflammation and metabolism to ultimately influence PD clinical manifestation.

Co-pathology is frequent in Lewy body disease, which includes clinical diagnoses of both Parkinson’s disease and dementia with Lewy bodies. Measuring concomitant pathology in vivo can improve clinical and research diagnoses and prediction of cognitive trajectories. Tau PET imaging may serve a dual role in Lewy body disease by measuring cortical tau aggregation as well as assessing dopaminergic loss attributed to binding to neuromelanin within substantia nigra. We sought to characterize ¹⁸F-PI-2620, a next generation PET tracer, in individuals with Lewy body disease. We recruited 141 participants for ¹⁸F-PI-2620 PET scans from the Stanford Alzheimer’s Disease Research Center and the Stanford Aging and Memory Study, most of whom also had β-amyloid status available (139/141) from PET or cerebrospinal fluid. We compared ¹⁸F-PI-2620 uptake within entorhinal cortex, inferior temporal cortex, precuneus and lingual gyrus, as well as substantia nigra, across participants with Lewy body disease [Parkinson’s disease (n = 29), dementia with Lewy bodies (n = 14)] and Alzheimer’s disease (n = 28), in addition to cognitively unimpaired healthy older adults (n = 70). Mean bilateral signal was extracted from cortical regions of interest in ¹⁸F-PI-2620 standard uptake value ratio (inferior cerebellar grey reference) images normalized to template space. A subset of participants received cognitive testing and/or the Movement Disorders Society Unified Parkinson’s Disease Rating Scale Part III motor exam (off medication). ¹⁸F-PI-2620 uptake was low overall in Lewy body disease and correlated with β-amyloid PET in temporal lobe regions and precuneus. Moreover, inferior temporal ¹⁸F-PI-2620 uptake was significantly elevated in β-amyloid positive relative to β-amyloid negative participants with Lewy body disease. Temporal lobe ¹⁸F-PI-2620 signal was not associated with memory in Lewy body disease, but uptake within precuneus and lingual gyrus was associated with worse executive function and attention/working memory performance. Finally, substantia nigra ¹⁸F-PI-2620 signal was significantly reduced in participants with Parkinson’s disease, and lower substantia nigra signal was associated with greater motor impairment. These findings suggest that although levels are lower than in Alzheimer’s disease, small elevations in cortical tau are associated with cognitive function in Lewy body disease relevant domains, and that reduced ¹⁸F-PI-2620 binding in substantia nigra may represent loss of dopaminergic neurons. Cortical tau and neuromelanin binding within substantia nigra represent two unique signals in the same PET image that may be informative in the context of cognitive and motor deficits, respectively, in Lewy body disease.

Rates of cognitive decline in Alzheimer’s disease (AD) are extremely heterogeneous. Although biomarkers for amyloid-beta (Aβ) and tau proteins, the hallmark AD pathologies, have improved pathology-based diagnosis, they explain only 20-40% of the variance in AD-related cognitive impairment (CI). To discover novel biomarkers of CI in AD, we performed cerebrospinal fluid (CSF) proteomics on 3,397 individuals from six major prospective AD case-control cohorts. Synapse proteins emerged as the strongest correlates of CI, independent of Aβ and tau. Using machine learning, we derived the CSF YWHAG:NPTX2 synapse protein ratio, which explained 27% of the variance in CI beyond CSF pTau₁₈₁:Aβ₄₂, 11% beyond tau positron emission tomography, and 28% beyond CSF neurofilament, growth-associated protein 43 and neurogranin in Aβ⁺ and phosphorylated tau⁺ (A+T₁+) individuals. CSF YWHAG:NPTX2 also increased with normal aging and 20 years before estimated symptom onset in carriers of autosomal dominant AD mutations. Regarding cognitive prognosis, CSF YWHAG:NPTX2 predicted conversion from A+T₁+ cognitively normal to mild cognitive impairment (standard deviation increase hazard ratio = 3.0, P = 7.0 × 10^-4) and A+T₁+ mild cognitive impairment to dementia (standard deviation increase hazard ratio = 2.2, P = 8.2 × 10^-16) over a 15-year follow-up, adjusting for CSF pTau₁₈₁:Aβ₄₂, CSF neurofilament, CSF neurogranin, CSF growth-associated protein 43, age, APOE4 and sex. We also developed a plasma proteomic signature of CI, which we evaluated in 13,401 samples, which partly recapitulated CSF YWHAG:NPTX2. Overall, our findings underscore CSF YWHAG:NPTX2 as a robust prognostic biomarker for cognitive resilience versus AD onset and progression, highlight the potential of plasma proteomics in replacing CSF measurement and further implicate synapse dysfunction as a core driver of AD dementia.

Introduction: The availability of amyloid beta (Aβ) targeting therapies for Alzheimer’s disease (AD) is increasing the demand for scalable biomarkers that are sensitive to early cerebral Aβ accumulation.

Methods: We evaluated fully-automated Lumipulse plasma Aβ₄₂/Aβ₄₀ immunoassays for detecting cerebral Aβ in 457 clinically unimpaired (CU) and clinically impaired (CI) Stanford Alzheimer’s Disease Research Center (Stanford ADRC) participants and 186 CU in the Stanford Aging and Memory Study (SAMS). Longitudinal change in ADRC plasma Aβ₄₂/Aβ₄₀ and cognition and cross-sectional associations with SAMS memory and tau positron emission tomography (PET) were examined.

Results: Plasma Aβ₄₂/Aβ₄₀ exhibited high performance in detecting amyloid positivity defined by PET (area under the curve [AUC]: 0.885, 95% confidence interval [CI]: 0.816-0.955). Once abnomal, plasma Aβ₄₂/Aβ₄₀ remained low and predicted cognitive decline in both CU and CI individuals. Among SAMS CU, plasma Aβ₄₂/Aβ₄₀ was associated with poorer hippocampal-dependent memory and elevated tau accumulation.

Discussion: Lumipulse plasma Aβ₄₂/Aβ₄₀ is a scalable assay for detection of cerebral Aβ and prediction of risk for cognitive decline across the AD continuum.

Highlights: Lumipulse plasma amyloid beta (Aβ)₄₂/Aβ₄₀ exhibited high accuracy in detecting amyloid positivity. Plasma amyloid-positive (Aβ+) individuals exhibited stability of Aβ₄₂/Aβ₄₀ over time. Plasma Aβ₄₂/Aβ₄₀ predicted future cognitive decline across the Alzheimer’s disease (AD) spectrum. Plasma Aβ₄₂/Aβ₄₀ was sensitive to memory and tau burden in clinically unimpaired older adults.

Human genetics implicate defective myeloid responses in the development of late-onset Alzheimer disease. A decline in peripheral and brain myeloid metabolism, triggering maladaptive immune responses, is a feature of aging. The role of TREM1, a pro-inflammatory factor, in neurodegenerative diseases is unclear. Here we show that Trem1 deficiency prevents age-dependent changes in myeloid metabolism, inflammation and hippocampal memory function in mice. Trem1 deficiency rescues age-associated declines in ribose 5-phosphate. In vitro, Trem1-deficient microglia are resistant to amyloid-β₄₂ oligomer-induced bioenergetic changes, suggesting that amyloid-β₄₂ oligomer stimulation disrupts homeostatic microglial metabolism and immune function via TREM1. In the 5XFAD mouse model, Trem1 haploinsufficiency prevents spatial memory loss, preserves homeostatic microglial morphology, and reduces neuritic dystrophy and changes in the disease-associated microglial transcriptomic signature. In aging APP^Swe mice, Trem1 deficiency prevents hippocampal memory decline while restoring synaptic mitochondrial function and cerebral glucose uptake. In postmortem Alzheimer disease brain, TREM1 colocalizes with Iba1⁺ cells around amyloid plaques and its expression is associated with Alzheimer disease clinical and neuropathological severity. Our results suggest that TREM1 promotes cognitive decline in aging and in the context of amyloid pathology.

Objective: More than half of neurodegenerative disease patients have multiple pathologies at autopsy; however, most receive one diagnosis during life. We used the α-synuclein seed amplification assay (αSyn-SAA) and CSF biomarkers for amyloidosis and Alzheimer’s disease (AD) neuropathological change (ADNC) to determine the frequency of co-pathologies in participants clinically diagnosed with Lewy body (LB) disease or AD.

Methods: Using receiver operating characteristic analyses on retrospective CSF samples from 150 participants determined αSyn-SAA accuracy, sensitivity, and specificity for identifying clinically defined LB disease and predicting future change in clinical diagnosis. CSF biomarkers helped determine the frequency of concomitant Lewy body pathology, ADNC, and/or amyloidosis in participants with LB disease and AD, across clinical spectra.

Results: Following a decade-long follow-up, the clinically or autopsy-defined diagnosis changed for nine participants. αSyn-SAA demonstrated improved accuracy (91.3%), sensitivity (89.3%), and specificity (93.3%) for identifying LB disease compared to all non-LB disease, highlighting the limitations of clinical diagnosis alone. When examining biomarkers of co-pathology, amyloidosis was present in 18%, 48%, and 71% (χ²(2) = 13.56, p = 0.001) and AD biomarkers were present in 0%, 8.7%, and 42.9% (χ²(2) = 18.44, p < 0.001) of LB disease participants with different stages of cognitive impairment respectively. Co-occurring biomarkers for αSyn-SAA and amyloidosis were present in 12% and 14% of AD compared to 43% and 57% LB disease participants with different stages of cognitive impairment (χ²(3) = 13.87, p = 0.003).

Interpretation: Our study shows that using a combination of αSyn-SAA and AD biomarkers can identify people with αSyn, ADNC, and co-pathology better and earlier than traditional clinical diagnostic criteria alone.

Animal studies show aging varies between individuals as well as between organs within an individual^1-4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20-50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer’s disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. ⁵), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.