Over the years, my devotion to unraveling the intricacies of osteoporosis, especially among underrepresented populations, has driven my independent and collaborative research endeavors. My work is anchored in the belief that a deep understanding of genomics, coupled with robust data analysis, can significantly enhance the precision and equity of healthcare.

Independent Research

My independent research primarily orbits around equitable fracture risk assessment, aiming to transcend the conventional one-size-fits-all models that have perpetuated healthcare disparities. Through comprehensive studies, I’ve developed personalized medicine tools that consider race, ethnicity, and genetic profiles to improve osteoporosis diagnosis and fracture risk assessment. My innovative methodologies in integrating genomics with machine learning have substantially augmented the predictive accuracy of osteoporotic fracture risks, garnering recognition through the University Faculty Opportunity Award.

Collaborative Research

In collaborative settings, I’ve had the privilege to work with brilliant minds from diverse fields. These collaborative efforts span various clinical and translational projects, with over 50 jointly funded research endeavors. The synergy in these collaborations has yielded transformative insights in osteoporosis, depression, and translational bioinformatics, among other fields, amplifying the impact of our collective scientific inquiry.

Equity Bone Lab

The Equity Bone Lab, under my helm, serves as a nexus where innovative ideas meet meticulous research to challenge and reshape the current paradigms in osteoporosis research. Our mission is to elucidate and address the health disparities in osteoporosis diagnosis and fracture risk assessment. Through rigorous research and community engagement, we aim to create personalized tools that significantly reduce healthcare disparities, particularly among minority women. Our lab’s achievements underscore the promise of personalized medicine in fostering healthcare equity.

Funding and Grants

My research endeavors have been generously supported by various funding sources, including the National Institutes of Health (NIH), the Department of Defense (DOD), and the Centers for Disease Control and Prevention (CDC). The grants awarded, like the NIH R01, R15 and R21, have been instrumental in disrupting traditional osteoporosis diagnosis models and birthing ethnicity-specific bone density reference thresholds. These funds have fueled our research and emboldened our resolve to diminish healthcare disparities in osteoporosis diagnosis.

Highlighted Grants

For a detailed overview of my  grants, please visit the Projects and Grants page.


My academic journey has been documented through numerous peer-reviewed publications reflecting my sustained engagement in pioneering research to transform osteoporosis diagnosis and promote healthcare equity. Below is a curated list of selected peer-reviewed publications, links to my profiles on various academic and research platforms, and features of my work in national news outlets.

Selected Peer-Reviewed Publications

  1. Wu, Q., Nasoz, F., Jung, J., Bhattarai, B., Han, M.V., Greenes, R.A., & Saag, K.G. (2021). Machine learning approaches for the prediction of bone mineral density by using genomic and phenotypic data of 5130 older men. Scientific Reports, 11(1), 4482.
  2. Xiao, X., Wu, Q. (2023). Ethnic disparities in fracture risk assessment using polygenic scores. Osteoporosis International. DOI: 10.1007/s00198-023-06712-y.
  3. Wu, Q., Nasoz, F., Jung, J., Bhattarai, B., and Han, M.V. (2020). Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men. Calcified Tissue International, 107, 353–361.
  4. Wu, Q., Xiao, X., Xu, Y. (2020). Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles. Journal of Clinical Medicine, 9(1): 285.

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Academic and Research Profiles

Google Scholar Profile

ORCID Profile

PubMed Bibliography