title: Risk Stratification Using Cerebrospinal Fluid Biomarkers in Patients with Mild Cognitive Impairment: An Exploratory Analysis.
abstract: BACKGROUND
  Cerebrospinal fluid (CSF) biomarkers can distinguish Alzheimer's disease (AD) patients from normal controls; however, their interpretation and potential for use in patients with mild cognitive impairment (MCI) remains unclear.
  
  
  OBJECTIVE
  To examine whether biomarker levels allow for risk stratification among MCI patients who are at increased risk to develop AD, thus allowing for improved targeting of early interventions for those whose risk are higher.
  
  
  METHODS
  We analyzed data from the Alzheimer's Disease Neuroimaging Initiative on MCI patients (n = 195) to estimate their risk of developing AD for up to 6 years on the basis of baseline CSF biomarkers. We used time-dependent receiver operating characteristic analysis to identify the best combination of biomarkers to discriminate those who converted to AD from those who remained stable. We used these data to construct a multi-biomarker score and estimated the risk of progression to AD for each quintile of the multi-biomarker score.
  
  
  RESULTS
  We found that Aβ(1-42) and P-tau(181p) were the best combination among CSF biomarkers to predict the overall risk of developing AD among MCI patients (area under the curve = 0.77). The hazard ratio of developing AD among MCI patients with high-risk (3rd-5th quintiles) biomarker levels was about 4 times greater than MCI patients with low-risk (1st quintile) levels (95% confidence interval, 1.93-7.26).
  
  
  CONCLUSIONS
  Our study identifies MCI patients at increased risk of developing AD by applying a multi-biomarker score using CSF biomarker results. Our findings may be of value to MCI patients and their clinicians for planning purposes and early intervention as well as for future clinical trials.
authors.affiliation: Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Tzeyu L
authors.initials: TL
authors.lastname: Michaud
authors.affiliation: Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Robert L
authors.initials: RL
authors.lastname: Kane
authors.affiliation: Geriatric Research, Education and Clinical Center, Minneapolis Veterans Affairs Medical Center, Minneapolis, MN, USA.|Departments of Neurology and Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA.
authors.forename: J Riley
authors.initials: JR
authors.lastname: McCarten
authors.affiliation: School of Nursing & Center on Aging, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Gaugler
authors.affiliation: Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Nyman
authors.affiliation: Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Karen M
authors.initials: KM
authors.lastname: Kuntz
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000134:cerebrospinal fluid / Q000175:diagnosis; D016229:Amyloid beta-Peptides / Q000134:cerebrospinal fluid*; D019540:Area Under Curve; D015415:Biomarkers / Q000134:cerebrospinal fluid; D060825:Cognitive Dysfunction / Q000134:cerebrospinal fluid* / Q000175:diagnosis; D016208:Databases, Factual; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D010446:Peptide Fragments / Q000134:cerebrospinal fluid*; D011379:Prognosis; D012306:Risk; D016875:tau Proteins / Q000134:cerebrospinal fluid*
chemical_list: D016229:Amyloid beta-Peptides; D015415:Biomarkers; C054369:MAPT protein, human; D010446:Peptide Fragments; C075222:amyloid beta-protein (1-42); D016875:tau Proteins
keywords: Alzheimer’s disease; cerebrospinal fluid; discriminatory ability; mild cognitive impairment; risk stratification