Methamphetamine-Induced Risk for Parkinson's Disease: Mechanisms of Pathogenesis

  • Graves, Steven Michael (PD/PI)

Project: Research project

Project Details


Parkinson’s disease (PD) is the most common neurodegenerative movement disorder wherein dopamine (DA) neurons in the substantia nigra pars compacta (SNc) progressively degenerate leading to the primary motor symptoms (rigidity, bradykinesia).1 Numerous hypotheses have evolved to explain disease etiopathogenesis; however, no single hypothesis is without controversy. Recent evidence indicates that a compound, taken by millions worldwide, can increase the risk of developing PD by almost two-fold in human patients.2 Moreover, in rodents this compound leads to a progressive loss of tyrosine hydroxylase,3 cell death,3 increased α-synuclein expression (including pathological forms),4-7 and can even result in increased α-synuclein in the distal colon of rats.8 In humans, this compound leads to deficits in motor skills that emulate early-stage PD.9,10 Thus, this compound doesn’t appear to just increase risk, but seems to be inducing a genuine PD. The compound being referred to is methamphetamine (meth), a potent and highly addictive psychostimulant abused by 12 million people in the US at least once (NSDUH, 2012). Just as important and concerning is the fact that meth is also FDA-approved to treat ADHD and exogenous obesity (i.e. obesity due to overeating without a metabolic disorder). Based on the illicit and clinical use of meth, there may be a large population at risk for developing PD. It is therefore of great societal and socioeconomic importance to understand the mechanisms leading to this increased risk. The current proposal will pursue two longstanding yet controversial hypotheses of PD etiopathogenesis within the context of meth; i) DA toxicity and ii) Ca2+-induced mitochondrial oxidant stress.
Effective start/end date1/1/1512/31/16


  • Northwestern Memorial Hospital (Agmt Signed 3/9/15)


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.