Neuromelanin-sensitive MRI: development and validation of a novel dopamine biomarker for risk of schizophrenia and Parkinson’s disease

New MRI imaging technique may predict risk of developing Parkinson’s disease or schizophrenia

Guillermo Horga, M.D., Ph.D.

Research Foundation for Mental Hygiene

Funded in September, 2015: $200000 for 3 years
LAY SUMMARY . ABSTRACT .

LAY SUMMARY

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New MRI imaging technique may predict risk of developing Parkinson’s disease or schizophrenia

 A new molecular MRI imaging technique, called Neuromelanin-sensitive MRI (NM-MRI), may be able to identify early signs of illness in people who are at a high risk of developing Parkinson’s disease (PD) or schizophrenia.

 PD and schizophrenia each involve a problem with dopamine, an electrochemical “neurotransmitter” that brain cells use to communicate with one another. In PD, dopamine-producing cells in the brain’s “substantia nigra” degenerate and eventually die. In schizophrenia, cells in this same brain area synthesize excess dopamine, store it, and then release it into other regions throughout the brain. In both diseases, the problem begins long before patients experience symptoms.

Being able to diagnose either condition early in the disease process, when treatment is most likely to be effective, is essential but elusive. By the time movement symptoms occur in PD patients, the majority of their brain’s dopamine-producing cells have died.  Schizophrenia has no single profile of symptoms that reliably identify the disease, and if doctors prescribe powerful dopamine-blocking antipsychotic drugs to those who show some symptoms but do not actually develop the disease, the drugs can produce unnecessary harm.

Now though, both diseases could potentially be amenable to diagnosis at an early stage, due to a major advance in MRI imaging called “neuromelanin-sensitive” MRI (NM-MRI). This non-invasive molecular imaging technique measures neuromelanin, a by-product of dopamine metabolism. NM-MRI has already demonstrated an ability to detect abnormalities in the dopamine system in patients known to have PD or schizophrenia. Moreover, in PD patients, NM-MRI appears to measure dopamine cell degeneration.

The investigators hypothesize that NM-MRI, in comparison to clinical risk factors alone, will significantly improve the predictive accuracy of emerging active disease in people at risk of PD or schizophrenia. They anticipate that the NM-MRI signal will accurately measure neuromelanin concentration in the substantia nigra. A low signal from remaining dopamine neurons will be an early sign of PD; and a high signal will indicate that excess dopamine has been produced and accumulated, an early sign of schizophrenia.

 They will undertake three steps to test the sensitivity and specificity of NM-MRI as diagnostic screening tool for individuals at great risk of developing PD or schizophrenia. First, they will select the optimal imaging approach by determining how much neuromelanin is found in brain tissue from deceased patients and comparing that to the NM-MRI signal measured in the same tissue.

Then, they will perform NM-MRI imaging in patients and healthy volunteers to test the ability of NM-MRI to predict individual differences in abnormal and normal amounts of dopamine storage and release capacities. Thereafter, they image more than 70 adults at risk of developing PD or schizophrenia to obtain baseline information on whether the NM-MRI predictions of early disease correlate with the participants’ eventual development of disease.     

Significance: NM-MRI could become a standard screening tool for detecting PD or schizophrenia early in the dopamine disease process, facilitating early treatment with existing therapies and serving as a biomarker for identifying more effective experimental treatments.  

ABSTRACT

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Neuromelanin-sensitive MRI: development and validation of a novel dopamine biomarker for risk of schizophrenia and Parkinson’s disease

Neuromelanin-sensitive magnetic resonance (NM-MRI) is a novel, non-invasive, high-resolution, molecular MRI technique that may provide a unique readout of integrity and activity of dopamine neurons in the midbrain. This technique has been partially validated by showing consistently decreased signal in the substantia nigra (SN) of patients with manifest Parkinson’s disease (PD), an illness characterized by progressive degeneration of dopamine neurons in this region. However, a rigorous validation of the NM-MRI signal against the histochemical concentration of NM in SN dopamine neurons, and other imaging measures of dopaminergic activity, has not been performed. Furthermore, the usefulness of NM concentration as a marker for long-term dopamine activity in the absence of neurodegeneration, such as in psychiatric disorders involving a dopaminergic dysfunction, has not been established. Finally, the potential of this technique to provide a low-cost, non-invasive, widely available tool to predict risk for disorders of the dopaminergic system, as well as treatment responsiveness, has not been tested. A biomarker is critically needed for early detection of neuropsychiatric illnesses and prediction of clinical outcomes in at-risk populations, where imaging biomarkers may help clinicians by enhancing prognosis beyond the available clinical predictors. Our proposal thus aims at validating the method and exploring its full potential as a biomarker across a spectrum of neuropsychiatric disorders. We will for the first time validate different NM-MRI sequences against a gold-standard histochemical measure of NM concentration in post-mortem tissue in order to select an optimal NM-MRI sequence for determining tissue content of NM (Aim 1). We will also develop more fine-grained, multivariate statistical tools that exploit the anatomical distribution of NM within the SN. A second aim will be to establish the hypothesized relationship between NM-MRI signal and presynaptic dopamine activity in midbrain neurons in the absence of neurodegeneration by obtaining concurrent Positron Emission Tomography (PET) measures of dopamine storage and release capacity as well as Arterial Spin Labeling (ASL-MRI) measures of baseline blood flow and activity in the SN in healthy individuals and unmedicated patients with schizophrenia (Aim 2). Finally, we will test the clinical utility of the optimized NM-MRI-based measures by evaluating their potential for enhancing prediction of clinical outcome in at-risk individuals for schizophrenia and PD, respectively (Aim 3). If successful, this project will establish NM-MRI as a low-cost, non-invasive screening tool to predict risk of conversion to schizophrenia and PD, a tool which could ultimately promote earlier, more personalized and neurobiologically targeted treatments to mitigate the onset of these debilitating disorders.

INVESTIGATOR BIOGRAPHIES

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Guillermo Horga, M.D., Ph.D.

Guillermo Horga, M.D., Ph.D., is a psychiatric researcher focused on the neural substrates of psychotic disorders. He received his M.D. from the Miguel Hernandez University, Spain, and completed a psychiatry residency at the Hospital Clinic of Barcelona. After his residency he completed a Ph.D. project at the University of Barcelona using metabolic positron emission topography to study the neural bases of hallucinations. He also received an Alicia Koplowitz fellowship to conduct postdoctoral research in Dr. Bradley Peterson’s laboratory at Columbia University Medical Center. During this fellowship, he received extensive training in advanced methods of functional neuroimaging, cognitive neuroscience and neurobiology, and worked on several projects on the neural basis of normal cognition and learning. He now holds a position as assistant professor in the Division of Translational Imaging at the New York State Psychiatric Institute, where he focuses on computational mechanisms of learning abnormalities in relation to schizophrenia and dopamine dysregulations in this disorder.

KEYWORDS


Anatomy: Basal ganglia
Brainstem
Conditions: Motor diseases
Neurodegenerative disease
Parkinson's disease
Schizophrenia
Function: Brain and behavior
Technology: fMRI
MRI
PET