Dr Lahiru Handunnetthi
Clinical Lecturer
Neuro-immune Interactions
Lahiru Handunnetthi aims to understand how inflammation and infections contribute to the development of psychiatric and neurological disease. He combines genomics methodology with stem cell derived model systems to better understand neuro-immune interactions and to identify therapeutic targets for neuroinflammatory disease.
Lahiru is involved in the functional characterisation of genetic risk alleles discovered through genome wide association studies. This involves gene editing techniques, induced pluripotent stem cell (IPSC) derived neuronal and glial model systems, as well as working with biological samples from patients.
Lahiru has a specific interest in understanding how the immune system contributes to psychosis. He is actively involved in discovering the roles that autoantibodies and viral infections play in psychosis.
Lahiru completed his DPhil at the Wellcome Centre for Human Genetics, University of Oxford. His work focused on understanding the interactions between genetic and environmental risk factors in neuroimmunological disorders. He studied medicine at the University of Cambridge and currently holds a NIHR funded Clinical Lectureship in Neurology.
Key words: Stem Cells, Neuroimmunology, Immunopsychiatry, Neuroinfectious diseases
Recent publications
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Single-cell immune survey identifies a novel pathogenic role for T cells in anti-NMDA receptor encephalitis
Preprint
Kwok AJ. et al, (2024)
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Identifying and reducing risks of neurological complications associated with vaccination.
Journal article
Handunnetthi L. et al, (2024), Nat Rev Neurol, 20, 541 - 554
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Analysis of 125DVD3- and 17β-estradiol (17βE2)-regulated transcriptomes in lymphoblastoid cells
Dataset
Ramagopalan S., (2019)
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Time course analysis of 125DVD3-regulated transcriptomes in lymphoblastoid cells, fibroblasts and other cell types
Dataset
Ramagopalan S., (2019)
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Faculty Opinions recommendation of Vitamin D status is associated with relapse rate in pediatric-onset multiple sclerosis.
Dataset
Ramagopalan S. and Handunnetthi L., (2010)