health endpoint

Application of omics techniques on various health endpoints, including prostate cancer and bone health are listed below:

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Prostates cancer, Metabolomics: Evaluating Differential Metabolic Profile by Prostate Cancer Grade among Prostate Cancer Patients
- Conducted metabolomics analysis on 22 urine samples from prostate cancer patients who were disgnozed with prostate cancer
- Developed and validated statistical models to compare metabolic profiles across high vs. low PCa risk group
- Lead author for a manuscript published on Metabolites(Liu et al., 2025)
Long COVID: Understanding Long COVID (LC) in Frontline and Essential Workers (FEWs) through Proteomic Profiling: A Longitudinal Cohort Study
- Led analytical team and developed statistical pipeline for proteomics analysis in AZHEROES
- Processed and analyzed proteomics data from 130+ frontline and essential workers with COVID-19 infection to identify biomarkers associated with Long COVID
- Applied bioinformatics techniques to map 20+ significant biological pathways
- Lead author for a manuscript currently under internal review (Liu et al., 2026)
COVID Breakthrough: Serum Proteomics in Omicron SARS-CoV-2 breakthrough: a nested case-control study within a prospective cohort of frontline workers from eight locations in the United States (US)
- Assisted in proteomics analysis for 100+ breakthrough cases to identify risk factors for Omicron breakthrough
- Contributed to a manuscript submitted to PLoS ONE (Liu et al., 2026)
Bone Health
- Multi-cohort spanning from adolescence, young adulthood, to senior adulthood
- Analyzed 304/250 plasma samples for metabolic signals in association with bone mineral densities
- Assessed PFAS-bone associations in older Hispanic adults (N=250)
- Lead author for 2 manuscripts (under peer review) (Liu et al., 2026) (Liu et al., 2026)

References

2026

TBD

Understanding Long COVID (LC) in Frontline and Essential Workers (FEWs) through Proteomic Profiling: A Longitudinal Cohort Study

Tuo Liu, Danielle Stea, Shawn C Beitel, and 3 more authors

BMC-Medicine, in prep, 2026

DOI
PLoS ONE

Unveiling Post-Vaccination Proteomic Signatures in Infection-Naïve Individuals Associated with Omicron Breakthrough Infections

Yiwen Liu, Eric Lu, Katherine D. Ellingson, and 6 more authors

PLoS ONE, 2026

DOI
BR

A Life-Course View of Bone Health Through Bone Mineral Density: Metabolomic Insights in Adolescents, Young Adults, and Older Adults

Tuo Liu, Zhenjiang Li, Douglas I. Walker, and 10 more authors

Bone Research, peer review, 2026

DOI
JBMR

Per- and polyfluoroalkyl Substances (PFAS) and Bone Health in Older Hispanic Adults on US-Mexico Border

Tuo Liu, Zhenjiang Li, Douglas I. Walker, and 8 more authors

Journal of Bone and Mineral Research, peer review, 2026

DOI

2025

Metabolites

Evaluating Differential Metabolic Profile by Prostate Cancer Risk among Prostate Cancer Patients

Tuo Liu, Jahnvi Roorkeewal, Melissa Furlong, and 6 more authors

Metabolites, 2025

Abs DOI

Background: Currently there are no clinically validated biomarkers recommended for prostate cancer (PCa) risk stratification other than prostate specific antigen (PSA). Objectives: This study aimed to identify urine metabolites that are associated with presence of high-grade PCa at the time of radical prostatectomy. Methods: Urine samples were collected from patients who underwent radical prostatectomy. High-resolution metabolomics were implemented using mass liquid-chromatography mass spectrometry (LC-MS). To enhance metabolic feature identification, sample extracts were analyzed in two modes, a C18 chromatography [reverse-phase (RP)] and a hydrophilic interaction chromatography (HILIC). Results: This analysis included a total of 22 patients with PCa (10 high-grade and 12 low-grade) and identified 52 differential metabolites, 40 in RP and 12 in HILIC, at p-value 0.05 level. Among these, methyl alpha-aspartyl phenylalaninate was most significantly differentiated, while 3-methylbutanoicacid had the largest difference (slope -3.488). In pathway analysis, the histidine metabolic pathway was significantly enriched with an enrichment factor of 3.5. Our research also identified alterations in vitamins B12, B7 (biotin), B6, and B3 (niacin) pathways. Conclusion: Urine metabolites have the potential to differentiate high-grade from low-grade PCa. Our study also highlights the metabolic reprogramming that occurs as PCa becomes more aggressive.