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.

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.

The blood-brain barrier (BBB) poses a major obstacle to the delivery of therapeutics into the central nervous system (CNS) due to its highly restrictive permeability. Here, we introduce glycan-targeted delivery vehicles, or GlycoShuttles, that traverse the BBB by harnessing the cerebrovascular glycocalyx, a carbohydrate-rich layer lining the BBB lumen. We discover that mucin-domain glycoproteins within this structure serve as novel entry portals for brain delivery and engineer mucin-binding protein shuttles that enable efficient transport of diverse molecular cargo across the BBB into multiple key brain cell types. This modular platform facilitates enhanced brain delivery of a variety of payloads, including antibodies and lysosomal proteins, and demonstrates therapeutic efficacy in mouse models of dementia. Our findings establish mucin-targeted GlycoShuttles as a versatile platform for noninvasive brain delivery of therapeutics, opening new avenues for the treatment of CNS diseases.

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.

Changes in β-amyloid (Aβ) and hyperphosphorylated tau (T) in brain and cerebrospinal fluid (CSF) precede Alzheimer’s disease (AD) symptoms, making the CSF proteome a potential avenue to understand disease pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 analytes (2,029 unique proteins) dysregulated in AD. Of these, 865 (43%) were previously reported, and 1,164 (57%) are novel. The identified proteins cluster in four different pseudo-trajectories groups spanning the AD continuum and were enriched in pathways including neuronal death, apoptosis, and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfunction (mid stages), brain plasticity and longevity (mid stages), and microglia-neuron crosstalk (late stages). Using machine learning, we created and validated highly accurate and replicable (area under the curve [AUC] > 0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD.

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.

Impaired cerebral glucose metabolism is a pathologic feature of Alzheimer’s disease (AD), with recent proteomic studies highlighting disrupted glial metabolism in AD. We report that inhibition of indoleamine-2,3-dioxygenase 1 (IDO1), which metabolizes tryptophan to kynurenine (KYN), rescues hippocampal memory function in mouse preclinical models of AD by restoring astrocyte metabolism. Activation of astrocytic IDO1 by amyloid β and tau oligomers increases KYN and suppresses glycolysis in an aryl hydrocarbon receptor-dependent manner. In amyloid and tau models, IDO1 inhibition improves hippocampal glucose metabolism and rescues hippocampal long-term potentiation in a monocarboxylate transporter-dependent manner. In astrocytic and neuronal cocultures from AD subjects, IDO1 inhibition improved astrocytic production of lactate and uptake by neurons. Thus, IDO1 inhibitors presently developed for cancer might be repurposed for treatment of AD.

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.