Sneha Mantri is Assistant Professor of Neurology at Duke University in Durham, North Carolina. John Duda is National Parkinson’s Disease Research, Education, and Clinical Center (PADRECC) Director and Chair of the National VA Parkinson’s Disease Consortium; and James Morley is Associate Director of Research, PADRECC; both at the Corporal Michael J. Crescenz VA Medical Center in Philadelphia, Pennsylvania. John Duda is Associate Professor of Neurology and James Morley is Assistant Professor of Neurology, both at the Perelman School of Medicine, University of Pennsylvania in Philadelphia. Correspondence: Sneha Mantri (sneha.mantri@duke.edu)
Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.
Disclaimer The opinions expressed herein are those of the authors and do not necessarily reflect those of Federal Practitioner, Frontline Medical Communications Inc., the US Government, or any of its agencies.
DIP usually is caused by blockade of postsynaptic dopamine receptors by antipsychotic medications, which are prescribed to as many as 1 in 4 older veterans; antiemetic agents such as metoclopramide are also potential offenders if used chronically. 41 The risk of DIP appears to be associated with the D2 binding affinity of the drug. Thus, of the newer atypical antipsychotics, clozapine and quetiapine appear to have the lowest risk, while ziprasidone and aripiprazole have the highest binding affinity and therefore the highest risk. 42 In many patients, parkinsonism persists even after discontinuation of the offending agent, suggesting that in at least a subset of patients, DIP may be an “unmasking” of latent PD rather than a true adverse effect of the medication. The prodromal features discussed above can be used to distinguish isolated DIP from unmasked latent PD. 43 In a study we conducted in veterans at the Michael J. Crescenz VA Medical Center in Philadelphia, Pennsylvania, hyposmia in particular was shown to be highly predictive of an underlying dopaminergic deficit with an odds ratio of 63. 44
Other important considerations in the differential diagnosis of PD are the atypical degenerative parkinsonian syndromes, formerly called Parkinson plus syndromes. These may be further divided into the synucleinopathies (MSA, DLB) or the tauopathies (PSP, CBS), depending on the predominant amyloidogenic protein. Early in the disease, the atypical syndromes and idiopathic PD may be clinically indistinguishable, although the atypical syndromes tend to progress more rapidly and often have a less robust response to levodopa.Radiologic and fluid biomarkers for the atypical syndromes are under active investigation; at present the most accessible study is magnetic resonance imaging (MRI), which may show characteristic features such as degeneration of the pontocerebellar fibers in MSA or midbrain atrophy in PSP. 45,46 By contrast, standard MRI sequences in idiopathic PD are usually normal, although high-resolution (7 tesla) imaging can reveal loss of neuromelanin in the substantia nigra. 47 MRI also can be useful in the workup of suspected normal pressure hydrocephalus or vascular parkinsonism, which would show disproportionate ventriculomegaly with transependymal flow, or white matter lesions in the basal ganglia, respectively.
Data-Based Identification of Preclinical PD
The integration of clinical motor or prodromal features with biomarker data has led to the development of several large-scale clinical and administrative databases to identify PD. The Parkinson Progression Markers Initiative initially enrolled only de novo clinically identified people with PD, but it expanded to include a prodromal cohort who are being assessed for rates of conversion to PD. 48 Similarly, metabolic imaging can be combined with prodromal symptoms, such as hyposmia or RBD, to predict risk for phenoconversion into manifest motor PD. 49
The PREDICT-PD study synthesizes mood symptoms, RBD, smell testing, genotyping, and keyboard-tapping tasks to divide individuals into high-, middle-, and low-risk groups; interim analysis at 3 years of follow-up (N = 842) demonstrated a hazard ratio of 4.39 (95% CI, 1.03-18.68) for the diagnosis of PD in the highrisk group compared with the low-risk group. 50 Lastly, administrative claims data for prodromal features, such as constipation, RBD, and mood symptoms, is highly predictive of eventual PD diagnosis. 51 VA databases accessed through the Corporate Data Warehouse are complementary sources of information to nonveteranspecific Medicare databases; to our knowledge there has not yet been a comprehensive search of VA databases to identify veterans with preclinical PD.
