Hamilton Se-Hwee Oh

Biological aging is heterogeneous across organ systems, and brain health may be influenced by biological processes extending beyond the central nervous system (CNS). This can be investigated using biological age measures that are increasingly used to estimate how biological systems deviate from chronological aging. However, organ level plasma proteomic metrics may capture different forms of biological variation depending on how they are defined. Here, we compared three complementary organ level proteomic metrics across 15 organ systems (and two global systems) in relation to age, organ-relevant physiological phenotypes, brain morphometry, and incident neurodegenerative disease, using plasma proteomics from 52,667 UK Biobank participants and brain MRI data from 5,078 of those individuals. We derived i) supervised age gap metrics using XGBoost models trained to predict chronological age, ii) unsupervised PC1 metrics capturing dominant organ-associated proteomic variation, and iii) phenotype guided PLS metrics linking plasma proteins to organ-relevant physiological traits. The three metric classes were related but not interchangeable. Global all-protein and all-organ-protein models showed strong age-related proteomic structure. However, organ-specific PC analyses showed that age was often but not always the dominant source of variation in protein signal across organs. Age gap metrics showed the most consistent associations with subsequent ICD-10-based neurodegenerative and vascular diagnoses, whereas all three metric classes showed distinct associations with brain structure and organ-relevant physiological phenotypes. Brain structure analyses revealed heterogeneous organ-brain association patterns across organs, suggesting that proteomic variation relates to brain structure in both a systemic and an organ-specific manner. Several systemic and organ-specific signals partially mediated the associations between disease specific genetic risk and incident diagnoses of Alzheimer's disease and stroke, albeit with small effect sizes (1-8%). Similarly, organ metrics provided modest incremental predictive improvement over baseline demographic models, with the largest increase in ROC-AUC observed for Alzheimer's disease when all organ age gap metrics were added jointly (delta ROC-AUC = 0.037). These results link brain related outcomes to proteomic variation across both CNS and non-CNS systems. Our work suggests that proteomic organ metrics capture complementary dimensions of biological variation rather than a single construct of organ aging. Although these measures may provide informative biological and potentially predictive signals, their incremental predictive value in the present analyses was modest.

Aging affects cellular organelles differently, but whether subcellular aging predicts human disease remains unknown. Here, we integrated organelle-enriched proteins in plasma and cerebrospinal fluid proteomes from 61,931 individuals to model aging of 10 organelles across the human lifespan. Organelle aging was heterogeneous with lysosomes, plasma membranes, and Golgi compartments accelerating rapidly after age 60. Individuals with four or more prematurely aged compartments exhibited up to 22-fold higher kidney disease risk and up to 8-fold higher mortality risk. Major diseases are characterized by distinct organelle aging signatures and disease risk increased with the number of accelerated organelles. APOE-ε4 dosage was associated with lysosomal and mitochondrial aging and reduced PDP1 levels, implicating altered energy metabolism. Decomposition of organelle signature coefficients into biological programs further showed that diseases are associated with distinct subcellular patterns. These findings establish organelle-resolved aging as a measurable dimension of human biology, revealing subcellular mechanisms underlying disease susceptibility and resilience. One sentence summary: Human organelles age at different rates, revealing distinct molecular signatures that predict disease risk, resilience and mortality.

Aims: To identify plasma proteins associated with all-cause mortality and determine their relationships with chronic disease burden and biological aging at both the organismal and organ-specific levels, thereby providing insights into the biological mechanisms underlying healthy aging and longevity. Methods: We conducted a prospective cohort study of 1,025 older adults from the LonGenity study, analyzing 4,265 plasma proteins. Associations between protein levels and all-cause mortality were evaluated using Cox proportional hazards regression over a mean follow-up of 8.05 years. Mortality-associated proteins were further examined for their relationships with chronic disease burden and proteome-derived measures of organismal and organ-specific biological aging. Findings were independently validated in 1,124 participants from the Baltimore Longitudinal Study of Aging (BLSA). Results: Seventeen plasma proteins were significantly associated with all-cause mortality. Higher levels of epidermal growth factor receptor (ERBB1) and anthrax toxin receptor 2 (ANTXR2) were associated with lower mortality risk and younger biological age across multiple organ systems. Conversely, higher levels of macrophage inhibitory cytokine 1 (MIC-1) (growth differentiation factor 15 (GDF15)), human epididymis protein 4 (HE4), and insulin-like growth factor-binding protein 2 (IGFBP-2) were associated with increased mortality and older biological age across multiple organ systems. Specifically, elevated MIC-1 was associated with older organismal biological age, whereas ERBB1 was associated with younger liver biological age. These associations were independently replicated in the BLSA cohort. Conclusion: Mortality-associated plasma proteins reflect key biological pathways involved in biological aging, physiological homeostasis, and systemic stress. These biomarkers may have potential utility for identifying individuals at increased mortality risk and advancing the development of biomarkers for healthy aging and longevity.

Menopause is a hallmark process in biological aging that has been implicated in later neurodegenerative risk, but the pathways underlying this connection remain unclear. Here we used blood proteomics data from several cohorts to identify biological changes associated with menopause and its links to brain aging. In n = 80 rigorously staged (STRAW+10) pre-, peri- and postmenopausal women (aged 43–58 years) with serum NULISAseq proteomics, we show that spontaneous menopause is characterized by dysregulation in inflammatory, synaptic, metabolic and Alzheimer’s disease biologic processes, which tracked more strongly with hormones than with age. Validation analyses in age-matched pre-/peri- and postmenopausal women ( n = 2,814) with plasma Olink proteomics replicated the observed proteomic shifts and revealed broader menopause-related upregulation of inflammatory and catabolic processes plus accelerated organ and cell aging, including brain aging. In four independent cohorts of older women (average age, 60.7–72.1 years; total n = 11,925), higher menopause proteomic scores associated consistently with cognitive aging and dementia risk. The molecular signatures of menopause may inform the selection of biomarkers or therapeutic targets for brain health in midlife women.

Frontotemporal lobar degeneration (FTLD) is a common cause of early-onset dementias marked by progressive declines in behavior, cognition, and/or movement. FTLD neuropathologies, including TDP-43 proteinopathies and primary tauopathies, do not have reliable fluid biomarkers for in-vivo diagnosis nor biomarkers that directly correspond to FTLD clinical features. Fluid biomarkers that forecast and track FTLD clinical progression, irrespective of pathology or clinical syndrome, are urgently needed to improve clinical trial designs. We previously identified the ratio between two cerebrospinal fluid (CSF) synaptic proteins, YWHAG and NPTX2, as a prognostic biomarker of cognitive decline in Alzheimer’s disease (AD), independent of core AD pathologies, amyloid and tau. Here, we evaluate its utility in sporadic and familial FTLD compared to other neurodegenerative diseases. Using CSF assays from four independent cohorts (UCSF-MAC, ALLFTD, GENFI, PDBP), we find CSF YWHAG:NPTX2 is substantially elevated across all sporadic and familial FTLD syndromes, AD, and dementia with Lewy bodies. CSF YWHAG:NPTX2 robustly correlates with clinical severity across sporadic and familial FTLD ( C9orf72 , GRN , or MAPT mutations), independent of current gold-standard neurodegeneration biomarker neurofilament light (NfL). In presymptomatic familial FTLD, CSF YWHAG:NPTX2 is estimated to rise roughly a decade before symptom onset and improves prediction of imminent symptomatic conversion by 1.7-fold compared to plasma NfL alone, more than halving the estimated sample size required for an FTLD prevention clinical trial. These findings underscore CSF YWHAG:NPTX2 as a cross-dementia synaptic biomarker of cognitive decline and a promising biomarker for disease staging and prognosis across the clinico-pathological continuum of FTLD.

The rapid expansion of plasma proteomic data and protein quantitative trait loci (pQTLs) provides an opportunity to identify genes that confer disease risk through their effect on plasma protein abundance. We conducted an Alzheimer’s disease (AD) proteome-wide association study (PWAS) integrating publicly available plasma cis-pQTL data (1348 European American and 1385 African American genetically determined protein models) with AD dementia GWAS summary statistics. Whereas the African American PWAS identified one candidate [apolipoprotein E (APOE)] and multiple suggestive genes, the European American PWAS identified 18 genes with putative causal relationships with AD through cis regulation of plasma protein abundance. Thirteen of these candidate genes were additionally supported by colocalization and complementary causal-inference analyses such as summary data–based Mendelian randomization. Four of these proteins were not previously detected in AD GWAS [complement decay-accelerating factor (CD55), leukocyte immunoglobulin-like receptor B1 (LILRB1), scavenger receptor class A member 5 (SCARA5), and signal regulatory protein alpha (SIRPA)]. A subset of candidate gene-associated proteins was associated with 8- and 20-year dementia risk, markers of AD pathology, and a CSF proteomic signature enriched for immune and metabolic processes. Putative causal proteins were enriched for adaptive (lymphocyte-mediated) immunity and, compared with GWAS candidates, showed less enrichment for synaptic and amyloid regulatory processes. LILRB1 and SIRPA, two immunoregulatory proteins not previously implicated in AD GWAS, showed the strongest mechanistic link to AD in the European American PWAS. These results shed additional light on AD etiology and enable the prioritization of potential AD therapeutic targets in peripheral circulation.

Aging is asynchronous across cells and organs. Here we tested whether plasma proteomics can be used to analyze cell type-specific aging. From analyses of over 7,000 plasma proteins measured in 60,542 individuals, we developed machine learning models to estimate the biological age of over 40 cell types spanning neuronal, immune, glial, endocrine, epithelial and musculoskeletal origins. We observed that 20–25% of individuals exhibited accelerated aging in a single cell type and 1–3% in 10 or more cell types. Cellular aging signatures were associated with disease status and predicted incident disease and mortality over 15 years of follow-up. Individuals with the APOE4 genotype showed older astrocytes but younger macrophages compared to APOE3 carriers, whereas the APOE2 genotype had inverse associations. Moreover, extreme astrocyte aging tripled the risk of incident Alzheimer’s Disease in individuals with two APOE4 alleles, while youthful astrocytes reduced risk. Individuals with extremely aged compared to youthful skeletal myocytes exhibited a 12.7-fold higher risk of developing amyotrophic lateral sclerosis. In individuals who smoked, extreme respiratory epithelial cell aging was associated with a 58% higher lung cancer risk compared to smoking alone. Specific cellular vulnerabilities and cumulative cellular aging burden influenced survival, with youthful immune and neuronal cell types conferring protective effects. Finally, we developed a polycellular aging risk score that stratified mortality risk across cohorts and proteomics platforms. These findings establish a framework for quantifying human physiology at cellular resolution, revealing heterogeneous aging trajectories and their impact on disease susceptibility and resilience.

SUMMARY: Neurodegenerative diseases are often accompanied by systemic comorbidities, including changes in bone health, but the molecular relationship between neurodegeneration, skeletal decline, and cellular senescence remains poorly understood. In this study, we investigated sex-specific changes in circulating bone- and senescence-related proteins across the spectrum of Alzheimer’s disease(AD), Lewbody dementia(LB) and Parkinson’s disease(PD). Plasma proteomic profiling was performed on samples from 408 participants deeply phenotyped for neurodegenerative diseases, followed by differential protein and pathway analyses. This study reveals sex-dependent alterations in bone and senescence-related circulating proteins in AD-related, PD and LB-related neurodegenerative diseases, providing insights into the complex relationship between neurodegeneration and bone health. Several candidate proteins were also associated with established plasma neurodegeneration biomarkers, particularly pTau181. Pathway analyses revealed shared mitochondrial and metabolic dysfunction across neurodegenerative diseases, with disease-specific features including vesicle trafficking disruption in AD and inflammatory-senescence pathways in LB, plus sex-divergent patterns in inflammatory signaling and bone-related pathways.