معرفی
Dr Brett McKinnon is a Senior Research Fellow at the Institute for Molecular Bioscience, University of Queensland. His research focuses on understanding the cellular and genetic mechanisms underlying endometriosis and related reproductive disorders. He completed his PhD in 2008 at UQ and pursued postdoctoral training at the University of Bern, Switzerland, investigating endometriosis, ovarian cancer, and inflammatory pathways. Since returning to Australia in 2016, he has led projects such as the Endometriosis Research Queensland Study (ERQS), integrating genetic and clinical data to improve diagnostics and treatments. His work includes developing patient-derived organoid models and spatial transcriptomics to study disease mechanisms. Dr McKinnon collaborates with the Royal Brisbane and Women’s Hospital and is actively involved in translational research, aiming to translate findings into clinical applications.
Education:
- Doctor of Philosophy (PhD), University of Queensland (2008)
- Bachelor (Honours) of Physiology, University of Queensland
Research Interests:
Dr McKinnon’s research emphasizes the role of individual cells and genetic architecture in disease initiation, particularly in endometriosis. He investigates inflammatory and metabolic components of reproductive tissues, develops in vitro models for disease modeling, and explores the interaction between genetics and environment. His work highlights the importance of cellular differentiation, microenvironmental changes, and hormonal influences in disease progression.
Grants & Funding:
- Current grants include projects on organoid-based precision medicine (Endometriosis Australia), hormonal influences on inflammation (NIH), and stem cell maturation mapping (NHMRC).
- Past funding supported projects on environmental risk factors and organoid sphere generation.
Labs & Collaborations:
He leads studies within the Genomics of Reproductive Disorders laboratory and collaborates with the Royal Brisbane and Women’s Hospital. His lab focuses on spatial transcriptomics, histopathological analysis, and computational modeling to advance endometriosis research.
