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Updated: Dec 13, 2025
Molecular Imaging of Human Brain Organoids Using Mass Spectrometry
Published on: September 27, 2024
High-throughput investigation of molecular and cellular biomarkers in NMOSD
Soumya S Yandamuri1, Ruoyi Jiang1, Aditi Sharma1
1From the Department of Neurology (S.S.Y., A.S., E.C., C.Z., K.C.O.C.), Department of Immunobiology (R.J., K.C.O.C.), and Department of Pathology (A.K.M.), Yale School of Medicine, New Haven, CT; University of Utah School of Medicine (J.S.A., L.J.C.), Salt Lake City; Departments of Ophthalmology and Visual Sciences and Internal Medicine (T.J.S.), University of Michigan Medical School, Ann Arbor; Department of Medicine (M.R.Y.), David Geffen School of Medicine at the University of California, Los Angeles; Divisions of Molecular Medicine & Infectious Diseases (M.R.Y.), Harbor-UCLA Medical Center, Torrance; and Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center (M.R.Y.), Torrance.
Objective:
To identify candidate biomarkers associated with neuromyelitis optica spectrum disorder (NMOSD) using high-throughput technologies that broadly assay the concentrations of serum analytes and frequencies of immune cell subsets.
Methods:
Sera, peripheral blood mononuclear cells (PBMCs), and matched clinical data from participants with NMOSD and healthy controls (HCs) were obtained from the Collaborative International Research in Clinical and Longitudinal Experience Study NMOSD biorepository. Flow cytometry panels were used to measure the frequencies of 39 T-cell, B-cell, regulatory T-cell, monocyte, natural killer (NK) cell, and dendritic cell subsets in unstimulated PBMCs. In parallel, multiplex proteomics assays were used to measure 46 serum cytokines and chemokines in 2 independent NMOSD and HC cohorts. Multivariable regression models were used to assess molecular and cellular profiles in NMOSD compared with HC.
Results:
NMOSD samples had a lower frequency of CD16+CD56+ NK cells. Both serum cohorts and multivariable logistic regression revealed increased levels of B-cell activating factor associated with NMOSD. Interleukin 6, CCL22, and CCL3 were also elevated in 1 NMOSD cohort of the 2 analyzed. Multivariable linear regression of serum analyte levels revealed a correlation between CX3CL1 (fractalkine) levels and the number of days since most recent disease relapse.
Conclusions:
Integrative analyses of cytokines, chemokines, and immune cells in participants with NMOSD and HCs provide congruence with previously identified biomarkers of NMOSD and highlight CD16+CD56+ NK cells and CX3CL1 as potential novel biomarker candidates.
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