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Department of Neurology

Houston, Texas

BCM neurologists see patients through the Baylor Clinic and some of the world's leading specialty clinics.
Department of Neurology
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Translational Research

Discovery of biomarkers in PD

Mutations at least in five different genes (a-Syn, Parkin, UCH-L1, DJ-1, PINK) have been identified in familial PD. However, it is obvious that genetic factors determine the susceptibility for the sporadic forms of these diseases. The identification of disease-susceptibility genes is of utmost importance for the understanding of fundamental pathogenic mechanisms related to development of brain damage in these diseases.

Functional genomics and proteomics provide a promising tool to characterize the spectrum of molecular changes in PD. In complex diseases, such as PD, it is anticipated that alterations increasing the susceptibility are located to promoter or regulatory regions of the gene, which are subsequently affecting the expression or splicing status of the susceptibility gene. Therefore, functional approaches such as overexpression and RNA interference (RNAi) of candidate genes as well as studies conducted in animal models of PD (transgenic and knockout animal models) are needed. The key accumulating proteins in PD share the propensity to interact with many intracellular proteins, and the aberrant interactions with other proteins may contribute the pathogenesis of these diseases due to different reasons, for example due to genetic influences. Understanding the pathophysiology of these diseases at molecular level, influence of genetic background on disease process and outcome, and identification of surrogate markers that predict the prognosis and effect of treatment are of critical importance for prevention and cure of these illnesses.

  1. To find novel candidate genes involved in late onset PD using different genetic approaches.
    • We will use our large well-characterized case-control sample set for detailed SNP studies of positional candidate genes and subsequent statistical analyses to find novel late onset PD genes.
    • We will also use PD samples including familial and sporadic cases to search for disease-associated genes for PD. Screening for mutations of previously reported candidate genes for PD (UCH-L1, DJ-1, PINK, LRRK1) will be performed in China in our cohort of familial PD. We will then continue genetic screening of the positional candidate genes using case-control sample sets of PD. Single SNP and haplotype association tests will be applied for these studies.
    • SNP analyses. At first, a small amount of samples (30-50) will be tested to determine the minor allele frequency of each SNP, the pair-wise linkage disequilibrium (LD) between SNP pairs as well as haplotype block structure in the gene region. If necessary, sequencing analysis is used to determine the exact location of SNP or to verify DNA sequence of an amplified product. A final SNP analysis is used for the whole material with selected SNP markers. We use on average 5-10 SNPs/gene and the average spacing between SNPs depends on the general LD in the gene region, but it is usually ≤10 kb. We use a mini-sequencing method to employ several SNPs at known locations (up to 10 primer-template combinations in a single tube/single capillary). SNP identification is performed by ABI PRISM 3100 genetic analyzer and the allele calling is performed with the aid of Genemapper 3.0 software. TaqMan chemistry-based SNPing procedure is also used in genotyping (ABI PRISM 7000 and 7900 Sequence Detection Systems).
  2. To characterize functional role of new candidate genes, and to investigate the effects of dopamine deficiency as a result of lost of dopamine neurons on the pre-synaptic machinery on dopamine compartmentalization and release.
    • We will employ a new technique that combines real-time monitoring of dopamine release by in vivo voltammetry, and analyse pre-synaptic dopamine compartmentalization and release. We will compare the changes in our own PD mice with another PD-model, Nurr1/NR4A2 knockout mice, and examine age dependency in developing of dopamine compartmentalization and release dysfunction.
    • Mice are anaesthetized with chloral hydrate (450 mg/kg, i.p.) and fixed in a stereotaxic frame. The carbon-fiber working electrode (electrochemical probe for dopamine) is inserted through an opening in the skull to the caudate nucleus and a bipolar stimulating electrode is implanted in the medial forebrain bundle (MFB) according to mouse brain atlas (Franklin and Paxinos, 1997). A small Ag/AgCl reference electrode is placed on the skull. A stainless steel screw as the auxiliary electrode is fixed into occipital bone. Dopamine release following repeated stimulations of the MFB in striatum from both hemispheres will be determined after experiments by HPLC with electrochemical detection. Stimulated dopamine release is measured by constant potential amperometry as described earlier (Yavich et al., 2004). The working electrode is held at 0.5V against a Ag/AgCl reference electrode. Data from the potentiostat are digitized and analyzed by a personal computer.
  3. To develop new diagnostic markers for PD.
    • We will use ELISA and immunoblotting to examine levels of new biomarkers that will be revealed in the genetic studies in blood and CSF in our well characterized population-based and clinical series to test their value for the diagnosis of PD. We will use two-dimensional electrophoretic methods to search for new biomarkers. We will also employ a new metabolomic profiling method of biofluids using 1H NMR (Proton Nuclear Magnetic Resonance) spectroscopy and a computer software meant for preparation, analysis and interpretation of NMR spectra, developed by the University of Kuopio and PERCH Solutions Ltd. ( Kuopio). We will also compare CSF samples from patients with samples from transgenic models to compare disease-associated changes in the metabolite profiles.

Expression of Nurr1 mRNA in lymphocytes as a biomarker of PD

We found that NURR1 gene expression in peripheral blood lymphocytes (PBL) was decreased by 66%-73% in patients with PD and related disorders compared to healthy controls and patients with other non-movement disorders. So it is very promising to explore it as a biomarker of PD. However, we still need to know: (1) whether this reduction of NURR1 gene expression in PBL is specific for PD or it reflects systematic dopaminergic dysfunction, (2) whether it can be used to detect the early stage of the disease or to predict the progression of the disease, (3) whether it can be employed to identify at-risk individuals who may have high chance to develop PD; and (4) whether it is associated with disease severity, anti-PD medications, genetic factors, age, and gender. Therefore, in this study, we plan to enroll a total 1,200 patients and controls including 400 PD (250 with sporadic PD, 150 with familial PD; among them 100 are new diagnosed de novo PD and 300 are middle-late stage PD), 250 patients with parkinsonism syndrome and other dopaminergic dysfunction-related disorders, 200 age-matched health controls, 200 patients with non-movement disorders, and 150 first–degree relatives of familial PD to quantitatively assay the NURR1 mRNA levels and perform multiple correlation analyses in these subjects.

  1. To validate whether NURR1 gene expression in PBL is significantly and specifically reduced in patients with PD we plan to enroll a larger population of research subjects and to employ a more restrict method to ensure assay quality. The PD patients include 400 PD in different disease stages; the controls include 250 patients with parkinsonism syndrome and other dopaminergic dysfunction-related disorders, 200 age-matched healthy subjects, and 200 patients with non-movement disorders (stroke, AD, ALS, MS, migraine, epilepsy, etc). NURR1 mRNA assay will be conducted in a blind manner and multiple comparison analyses will be performed in these subjects to seek statistical significance. By comparing the data of 400 PD to 200 healthy controls and 450 disease controls we are able to determine whether the specificity of the assay is able to assist in early diagnosis of PD; by comparing 400 PD with 100 parkinsonism (40 cases of PSP, 40 cases of MSA and 20 cases of CBD) and 150 other dopaminergic dysfunction related disorders (100 cases of ET, and 50 cases of RLS) we are able to determine whether using the assay we can differentiate PD from other parkinsonism and dopaminergic dysfunction related disorders.
  2. To determine whether assay of NURR1 expression levels in PBL can be used to identify the early stage of the disease or to predict the progression of the disease, we plan to assay NURR1 expression in 100 newly diagnosed de novol PD patients and compare their data to 300 PD patients with the disease in middle-late stages. A correlation and regression analysis of NURR1 mRNA levels with disease stages and severity will be conducted to determine whether the reduced NURR1 expression is an early sign of PD or a marker of disease progression.
  3. To identify at-risk individuals who may have high chance to develop PD. We have collected PBL from over 150 first-degree relatives of 38 familial PD (21 recessive and 17 dominant) families. These family members of PD (38.2±11.4 yr old; 82 male and 68 female) have no apparent PD symptoms. We plan to assay these family members’ NURR1 expression and screen them for the possibility that they carry any known hot-spot gene mutations (α-synuclein, Parkin, PINK1, DJ1, NURR1). In addition, these family members will be examined once a year for 5 years by neurologists in our three clinic facilities for any symptom of PD. The information of this investigation may help determine the value of NURR1 expression assay in PBL can be used to identify at-risk individuals who may have high chance to develop PD.
  4. To differentiate whether the reduction of NURR1 gene expression results from the disease itself or results from the effects of anti-PD medications, we will assay the NURR1 mRNA levels in PBL from 100 de novo PD patients and compare them to 300 PD patients taking medications (PD treated with L-dopa or DA agonists vs. untreated de novo PD; L-dopa-treated vs. DA-agonist treated). With this information we are able to know whether anti-PD medications can influence NURR1 expression. In addition, we will employ multiple correlation analyses to evaluate any association between NURR1 expression levels and genetic factors, age and gender in patients with PD.