Predicting Clinical Dementia Rating Using Blood RNA Levels

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSThe Clinical Dementia Rating (CDR) is commonly used to assess cognitive decline in Alzheimers disease patients. METHODSWe divided 741 participants with blood microarray data in the Alzheimers Disease Neuroimaging Initiative (ADNI) into three groups based on their most recent CDR assessment: cognitive normal (CDR=0), mild dementia (CDR=0.5), and probable AD (CDR[≥]1.0). We then used machine learning to predict cognitive status using only blood RNA levels. RESULTSOne chloride intracellular channel 1 (CLIC1) probe was significant. By combining nonsignificant probes with p-values less than 0.1, we averaged 87.87 (s = 1.02)% predictive accuracy in classifying the three groups, compared to a 55.46% baseline for this study. DISCUSSIONWe identified one significant probe in CLIC1. However, CLIC1 levels alone were not sufficient to determine dementia status. We propose that combining individually suggestive, but nonsignificant, blood RNA levels can significantly improve diagnostic accuracy.