PD is the second-most prevalent neurodegenerative disease worldwide. Its prevalence is increasing (e.g., the number of patients is expected to rise to 1.2 million by 2030; nearly 90,000 people in the U.S. are diagnosed with PD each year). Parkinson's is the second-most common neurodegenerative disease after Alzheimer's disease. Nearly 90,000 people in the U.S. are diagnosed with PD each year. Increased risk of PD has been associated with exposure to pesticides, consumption of dairy products, a history of melanoma, and traumatic brain injury, whereas a reduced risk has been reported in association with smoking, caffeine consumption, higher serum urate concentrations, physical activity, and use of ibuprofen and other common medications [1].

Notably, tremor exists in only 15% of patients, and the symptoms are similar to those of other diseases (e.g., essential tremor); thus, it is important to develop molecularly accurate identification methods for early detection of the disease, potentially through blood tests on patients prior to and as compared to following DBS [2]. Additionally, DBS may induce infection in some cases and is not always effective (e.g., due to age or cognitive function); however, in most cases, it is more effective than the conventional dopamine-based medical treatment. MicroRNAs may serve as such markers. Several genes and molecular pathways have been related to PD (e.g., SNCA, Park1, Park7, LRRK, and GBH [3], pathways: metal ion binding, alternative splicing, apoptosis, neuro-inflammation, cellular stress, and cell-to-cell communication [4]).

In my study, I profiled microRNAs in patients' blood leukocytes using Affymetrix microarrays. I detected expression levels for about 800 microRNAs in total and expression changes in several of these using bioinformatics and statistical tests. Figure 1 shows box plots of the expression data of the samples' miRNAs. My study included overall samples from three patients and three controls. I also classified the samples using PCA and hierarchical classification (HCL) using Mat lab and a MySQL database. Previously, I also quantified miRNAs in patients pre- and post-DBS and compared them with controls using Solid sequencing technology [5]. I also generated maps of microRNAs targeting genes using targeted online databases (e.g., miRBase [6] and Targets can [7]). MiRNAs are short (21 nucleotide-long) genes that typically regulate target genes by binding to the samples' 3' untranslated region (UTR); however, in my analyses, I discovered potential binding to the target genes' 5' UTR and coding sequences [8].

Microarrays and RNA sequencing allow the study of miRNAs involved in PD patients’ blood leukocytes. Several other recent studies have profiled miRNAs in patients' blood leukocytes (e.g., [9], [10]). Future studies may enlarge the cohort to enable more significant statistical analyses.

Figure: Box plots on the PD and control miRNA arrays expression data (one sample was rescanned). Y axis, log fold change.

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