Inflammatory biomarkers in Alzheimer's disease plasma.
Morgan AR., Touchard S., Leckey C., O'Hagan C., Nevado-Holgado AJ., NIMA Consortium None., Barkhof F., Bertram L., Blin O., Bos I., Dobricic V., Engelborghs S., Frisoni G., Frölich L., Gabel S., Johannsen P., Kettunen P., Kłoszewska I., Legido-Quigley C., Lleó A., Martinez-Lage P., Mecocci P., Meersmans K., Molinuevo JL., Peyratout G., Popp J., Richardson J., Sala I., Scheltens P., Streffer J., Soininen H., Tainta-Cuezva M., Teunissen C., Tsolaki M., Vandenberghe R., Visser PJ., Vos S., Wahlund L-O., Wallin A., Westwood S., Zetterberg H., Lovestone S., Morgan BP., Annex: NIMA–Wellcome Trust Consortium for Neuroimmunology of Mood Disorders and Alzheimer's Disease None.
INTRODUCTION: Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers. METHODS: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. RESULTS: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). DISCUSSION: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.