Saturday, June 20, 2020

AD Biomarker Identifies PD w/ Dementia

Correlations among candidate biomarkers for cognition.

(A) Pairwise Spearman correlation coefficients were calculated for the candidate biomarkers for cognition in PD across the entire cohort. With a few exceptions (e.g. MODHY and UPDRS-III scores (ρ = 0.51), candidate biomarkers did not show high correlations. Shades of red indicate a positive correlation coefficient, white indicates a correlation coefficient of zero, and shades of blue indicate a negative correlation coefficient. The correlation coefficient for each pairwise comparison is reported in the corresponding box. Only 12 candidate biomarkers are shown because five markers are categorical variables with relatively few categories. 

(B) Hierarchical clustering of biomarker candidates does not suggest a high degree of internal correlation among the 17 markers assessed. Both patients and biomarkers were clustered by Euclidean distance using average linkage, with the patient dendrogram shown to the left of the heatmap and the biomarker dendrogram shown above the heatmap. Each column represents one of 17 biomarkers, and each row represents a patient, with PD-CN (white), PD-MCI (black), and PDD (red) individuals indicated by color. On the heatmap, darker red indicates higher marker levels, and darker blue indicates lower marker levels relative to the mean. A branch that captured all the PDD subjects is highlighted in yellow.

An Alzheimer’s Disease-derived classifier for PDD.

(A) Hierarchical clustering of five AD-derived biomarkers (CSF Aβ42, CSF t-tau, CSF p-tau, SPARE-AD score, and APOE genotype) using data from AD and normal controls (NC) in the ADNI cohort. In AD, these five markers are highly correlated with each other. Moreover, clustering of individuals using these five markers produces a branch highly enriched in AD (yellow highlight). 

(B) Hierarchical clustering of the same five biomarkers using data from the full UPenn Udall cohort (n = 75). In PD, these five markers demonstrate less internal correlation. 

(C) Hierarchical clustering of the five AD-derived biomarkers using data from only PD-CN and PDD patients (n = 55). Even when only the extreme ends of the PD cognitive spectrum are included, less internal correlation is seen among these five markers in PD than in AD. 

(D) A logistic regression classifier (black curve) using the five AD-derived biomarkers discriminates AD from NC in the ADNI cohort with high accuracy. Accuracy, area under the curve, sensitivity, and specificity were assessed by ten-fold cross-validation, using the training cohort of ADNI subjects. Applying the exact same AD-derived classifier to the UPenn Udall cohort discriminates PD-CN from PDD patients with 80% accuracy as well (red curve).

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