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Tom Kindlon

New from Karl Morten group:

Developing a Blood Cell-Based Diagnostic Test for / Using Peripheral Blood Mononuclear Cells

Free:
onlinelibrary.wiley.com/doi/10

"Raman profiles of blood cells can distinguish between healthy individuals, disease controls, & ME/ patients with high accuracy (91%), & can further differentiate between mild, moderate, & severe patients (84%)"

Funding from ME Association; samples from @mecfsbiobank

@mecfs

Abstract Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by debilitating fatigue that profoundly impacts patients' lives. Diagnosis of ME/CFS remains challenging, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis, and many never receiving a clear diagnosis at all. In this study, a single-cell Raman platform and artificial intelligence are utilized to analyze blood cells from 98 human subjects, including 61 ME/CFS patients of varying disease severity and 37 healthy and disease controls. These results demonstrate that Raman profiles of blood cells can distinguish between healthy individuals, disease controls, and ME/CFS patients with high accuracy (91%), and can further differentiate between mild, moderate, and severe ME/CFS patients (84%). Additionally, specific Raman peaks that correlate with ME/CFS phenotypes and have the potential to provide insights into biological changes and support the development of new therapeutics are identified. This study presents a promising approach for aiding in the diagnosis and management of ME/CFS and can be extended to other unexplained chronic diseases such as long COVID and post-treatment Lyme disease syndrome, which share many of the same symptoms as ME/CFS.
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