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Identification of Aging-Associated Protein Biomarker Signatures in Plasma with NULISA™ Technology

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  • February 24, 2025
Topic/Product:
aging, Immunology, Neurology
Disease Area:
Sample Type:

Abstract

Purpose: Aging is associated with an increased susceptibility to cancer and many chronic autoimmune, neurodegenerative, and metabolic diseases. Characterizing the underlying mechanisms regulating the development and progression of these conditions demands a highly sensitive, non-invasive and multiplexed approach to study age-related proteomic changes.

Methods: We recently developed a high throughput and automated immunoassay platform, Nucleic-acid linked immunosandwich assay (NULISA), capable of detecting 100s of proteins simultaneously with attomolar sensitivity. NULISA combines a novel background suppression approach with the specificity of proximity ligation to achieve high sensitivity and wide dynamic range. Using two targeted panels, the NULISAseq 250-plex Inflammation Panel and 120-plex CNS Disease Panel, encompassing a broad range of cytokines, chemokines and key neurodegeneration-related proteins (pTau, β-amyloid proteins, synucleins), on the ARGO HT™ platform, we sought to profile plasma samples from a curated clinical cohort of >500 male and female subjects spanning over 7 decades of chronological age with diverse racial/ethnic backgrounds.

Results: The NULISAseq Inflammation and CNS Disease Panels demonstrated 98.9% and 96.8% target detectability in the plasma cohort, respectively. Linear model analysis by age and sex further revealed differential abundance with age of >250 targets including proinflammatory cytokines such as TNFα, TGFβ and IL6 and CNS markers like pTau-217, pTau-181, pTau-231 and amyloid beta proteins (38, 40 and 42). In addition, GDNF, CRH, FCN2, FLT1, IL24 and CXCL12 showed age-dependent downregulation. Further analyses with elastic net models demonstrated that <200 age-related proteins could accurately predict chronological age. Protein interaction analysis of these biomarker signatures revealed an intricate network of interconnected cytokines, consistent with inflammaging.

Conclusion: In summary, the high-plex NULISAseq dataset generated from analysis of >300 proteins in a large cohort of individuals with a broad age distribution provides a valuable resource to study changes in inflammation and neurodegeneration-related proteins with age and their association with age-related clinical outcomes.

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Authors & Affiliations

Xiao-Jun Ma1*, Niyati Jhaveri1, Li Wang1, Aparna Sahajan1, Karl Garcia1, Tsz Tam1, Sean Kim1, Henry Huang1, Jesse R. Poganik2, Mahdi Moqri2, Dane Gobel3, Seth Paulson3, Vadim N. Gladyshev2, Dwight Kuo1, Bingqing Zhang1, Yuling Luo1

1Alamar Biosciences, Inc., Fremont, CA 94538; 2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115; 3Methuselah Foundation, Springfield, VA 22153

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Steve Williams, MD, PhD

CSO

Dr. Willams serves as the company’s Chief Scientific Officer. He was previously Chief Medical Officer at Standard Biotools and at SomaLogic where he pioneered the discipline for discovery and validation of predictive, diagnostic and prognostic models using machine-learning applied to large-plex proteomics. 20 such tests were used for drug characterization, safety and efficacy when incorporated in clinical drug trials at Pharma/Biotech and 17 different multivariate tests were validated and translated into regulated healthcare uses. Prior to SomaLogic, Dr. Williams was at Pfizer in the UK and the USA as a clinical triallist in Translational Medicine, and subsequently as VP, Global Clinical Technology. He sat on the National Advisory Council for the National Institute of Biomedical Imaging and Bioengineering, the Executive Committee for the FNIH Biomarkers Consortium, and worked with FDA and PhRMA on developing evidentiary standards for biomarker qualification. Dr. William’s medical training was in London, at Charing Cross and Westminster Medical School, followed by a PhD in medicine/physiology at the same institution and training in Radiology at the University of Newcastle Upon Tyne. Steve is co-inventor on 26 proteomics patents and author/coauthor on multiple foundational proteomics manuscripts.

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Justin McAnear

CFO

Mr. McAnear serves as the company’s Chief Financial Officer. He brings over 25 years of operational and financial leadership experience across various sectors and was instrumental in taking 10x Genomics public in 2019, serving as its CFO for over five years. Mr. McAnear served for over 3 years as Tesla’s VP of Worldwide Finance and Operations, supporting landmark initiatives such as the Model X and Model 3 launches and Solar City acquisition.  He also held various roles at Apple and J&J earlier in his career and served as a naval officer and aviator for over 9 years.