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Adduri RSR, Vasireddy R, Mroz MM, Bhakta A, Li Y, Chen Z, Miller JW, Velasco-Alzate KY, Gopalakrishnan V, Maier LA, Li L, Konduru NV. Realistic biomarkers from plasma extracellular vesicles for detection of beryllium exposure. Int Arch Occup Environ Health 2022; 95:1785-1796. [PMID: 35551477 PMCID: PMC9489591 DOI: 10.1007/s00420-022-01871-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 04/14/2022] [Indexed: 11/25/2022]
Abstract
Purpose Exposures related to beryllium (Be) are an enduring concern among workers in the nuclear weapons and other high-tech industries, calling for regular and rigorous biological monitoring. Conventional biomonitoring of Be in urine is not informative of cumulative exposure nor health outcomes. Biomarkers of exposure to Be based on non-invasive biomonitoring could help refine disease risk assessment. In a cohort of workers with Be exposure, we employed blood plasma extracellular vesicles (EVs) to discover novel biomarkers of exposure to Be. Methods EVs were isolated from plasma using size-exclusion chromatography and subjected to mass spectrometry-based proteomics. A protein-based classifier was developed using LASSO regression and validated by ELISA. Results We discovered a dual biomarker signature comprising zymogen granule protein 16B and putative protein FAM10A4 that differentiated between Be-exposed and -unexposed subjects. ELISA-based quantification of the biomarkers in an independent cohort of samples confirmed higher expression of the signature in the Be-exposed group, displaying high predictive accuracy (AUROC = 0.919). Furthermore, the biomarkers efficiently discriminated high- and low-exposure groups (AUROC = 0.749). Conclusions This is the first report of EV biomarkers associated with Be exposure and exposure levels. The biomarkers could be implemented in resource-limited settings for Be exposure assessment. Supplementary Information The online version contains supplementary material available at 10.1007/s00420-022-01871-7.
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Affiliation(s)
- Raju S R Adduri
- Department of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA
| | - Ravikiran Vasireddy
- Department of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA
| | - Margaret M Mroz
- Department of Medicine, National Jewish Health, Denver, CO, USA
| | - Anisha Bhakta
- Department of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA
| | - Yang Li
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Zhe Chen
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jeffrey W Miller
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Karen Y Velasco-Alzate
- Department of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA
| | - Vanathi Gopalakrishnan
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Lisa A Maier
- Department of Medicine, National Jewish Health, Denver, CO, USA
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado, Denver, CO, USA
| | - Li Li
- Department of Medicine, National Jewish Health, Denver, CO, USA
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado, Denver, CO, USA
| | - Nagarjun V Konduru
- Department of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA.
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