This paper presents a novel metric to serve as a bio-marker for understanding and detecting progression of Parkinson's disease (PD). Proposed metric, termed as `Mediolateral Stability (MLS) index' has been derived from processing insole gait data using graph connectivity analysis. The proposed metric focuses on variability of mediolateral pressure in foot during gait progression. Vertical Ground Reaction Force (VGRF) and stride time information derived from a wearable insole for PD subjects as well as healthy controls are processed to create a connectivity graph. The insole contains eight pressure sensitive sensors for each foot and these sensors serve as the nodes of the connectivity graph. The proposed MLS index shows significant difference (p <; 0.05) in between control and PD groups and also in between progressive stages of PD, such as mild and moderate PD groups with p <; 0.05. Proposed graph connectivity based feature can act as a bio marker to correctly classify PD, identify early onset of PD and trace changes due to disease progression and can also provide information about dynamic pressure distribution during gait.