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Table 1 Participant demographics

From: Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

Participant characteristic

Cognitively unimpaired (CU)

Mild cognitive impairment (MCI-AD)

Alzheimer’s disease dementia (dementia-AD)

Statistical method

p-value

N = 296

N = 285

N = 6

N = 5

  

CSF Biomarker Status (A − T − /A + T − /A + T +)

231/26/28

(81.0%|9.1%|9.8%)

0/1/5

(0%|16.7%|83.3%)

0/1/4

(0%|20.0%|80.0%)

Fisher

1.07 × 10–8

APOE ε4 genotype

(% positive)

103(36%)

NA = 10

3 (50%)

4(80%)

Fisher

0.026

Sex

(% female)

186 (65%)

5 (83%)

2 (40%)

Fisher

0.41

Age (years)

Mean, SD

65.10 ± 7.81

71.77 ± 9.73

71.36 ± 2.52

ANOVA

0.0121

  1. Two hundred ninety-six participants from the Wisconsin Alzheimer’s Disease Research Center (ADRC) and the Wisconsin Registry for Alzheimer’s Prevention (WRAP) studies at UW-Madison were included in the study. Participants underwent lumbar puncture (LP) for cerebrospinal fluid (CSF) collection and assays for Aβ42/40 and p-Tau, clinical diagnosis, MRI studies, and NODDI modeling. Exclusion criteria included a diagnosis other than AD-Dementia, MCI-AD, or CU. Participants were selected if they had a clinical diagnosis of CU with A − /T − , A + /T − , or A + /T + CSF or a diagnosis of MCI or AD and A + /T − or A + /T + CSF. CSF was analyzed using the Roche NeuroToolKit (NTK) assay. CSF cutoffs were determined in-house using previously published receiver operator curve (ROC) methods
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Alzheimer's Research & Therapy

ISSN: 1758-9193