. Author manuscript; available in PMC: 2019 Jun 30.

Published in final edited form as: J Proteome Res. 2018 May 25;17(7):2460–2469. doi: 10.1021/acs.jproteome.8b00224

Table 1.

Summary of each feature used to develop the logistic regression predictive algorithm for prodromal Parkinson’s disease using brain tissue.

	Estimate	Std. Error	z value	Pr(>\|z\|)	Odds
(Intercept)	0.399	0.492	0.811	0.418	-
Serine	−1.824	0.769	−2.372	0.018	0.16
Taurine	1.902	0.752	2.529	0.011	6.7
3-Hydroxyisobutyrate	−2.232	0.662	−3.372	0.001	0.11
Threonine	2.164	0.821	2.634	0.008	8.7