Researchers at Dartmouth College, New Hampshire, have developed an algorithm that might someday be used to analyse blood for diagnostic purposes.
Using data from a mass spectrometer, a device that generates a molecular fingerprint of biological samples, the Dartmouth team’s calculations can distinguish healthy blood from diseased blood.
‘Our algorithm, named Q5, works on the assumption that the molecular composition of the blood changes between healthy and disease states,’ said Bruce Donald, the senior researcher on the project. ‘The goal of our work is to develop minimally invasive diagnostic methods with high predictive accuracy, and this is a promising first step.’
Mathematical computations are routinely developed, varied and refined to analyse mass spectrometry data. Q5 uses mathematical techniques called Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) to differentiate between the mass spectra of healthy and diseased blood samples.Q5 learns with each sample it tests, resulting in better accuracy. The algorithm compares the molecular fingerprint of each sample to identify features that differ between the healthy and disease states.
‘Our algorithm detected ovarian cancer with virtually 100% accuracy and prostate cancer with approximately 95% accuracy,’ explained Ryan Lilien, a Dartmouth MD/PhD student. ‘Q5 analyses the mass spec data and offers control over the threshold between healthy and disease classification. Although we only tested against ovarian and prostate cancer, we think it’s possible that Q5 may be used to test for other cancers and diseases.’
The researchers said that there is much still to be learned from the different types of information within a sample of blood, and Q5 is one means of extracting new and important data.
‘Most exciting to us, unlike previous mass spec disease diagnosis methods, Q5 provides clues about the molecular identities of abnormal proteins and peptides, which often cause disease. These altered proteins can serve as biomarkers, helping doctors make diagnosis and also helping researchers design better targeted drugs,’ said Donald.