Expression analysis of suppression of tumorigenicity 13 gene in patients with Parkinson's disease

Low-variance RNAs identify Parkinson's disease molecular signature in blood

The diagnosis of Parkinson's disease (PD) is usually not established until advanced neurodegeneration leads to clinically detectable symptoms. Previous blood PD transcriptome studies show low concordance, possibly resulting from the use of microarray technology, which has high measurement variation. The Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation predisposes to PD. Using preclinical and clinical studies, we sought to develop a novel statistically motivated transcriptomic-based approach to identify a molecular signature in the blood of Ashkenazi Jewish PD patients, including LRRK2 mutation carriers. Using a digital gene expression platform to quantify 175 messenger RNA (mRNA) markers with low coefficients of variation (CV), we first compared whole-blood transcript levels in mouse models (1) overexpressing wild-type (WT) LRRK2, (2) overexpressing G2019S LRRK2, (3) lacking LRRK2 (knockout), and (4) and in WT controls. We then studied an Ashkenazi Jewish cohort of 34 symptomatic PD patients (both WT LRRK2 and G2019S LRRK2) and 32 asymptomatic controls. The expression profiles distinguished the four mouse groups with different genetic background. In patients, we detected significant differences in blood transcript levels both between individuals differing in LRRK2 genotype and between PD patients and controls. Discriminatory PD markers included genes associated with innate and adaptive immunity and inflammatory disease. Notably, gene expression patterns in levodopa-treated PD patients were significantly closer to those of healthy controls in a dose-dependent manner. We identify whole-blood mRNA signatures correlating with LRRK2 genotype and with PD disease state. This approach may provide insight into pathogenesis and a route to early disease detection.

Emerging candidate biomarkers for Parkinson's disease: a review

Parkinson's disease is a chronic neurodegenerative disorder leading to progressive motor impairment affecting more than 1% of the over-65 population. In spite of considerable progress in identifying the genetic and biochemical basis of PD, to date the diagnosis remains clinical and disease-modifying therapies continue to be elusive. A cornerstone in recent PD research is the investigation of biological markers that could help in identifying at-risk population or to track disease progression and response to therapies. Although none of these parameters has been validated for routine clinical practice yet, however some biochemical candidates hold great promise for application in PD patients, especially in the early stages of disease, and it is likely that in the future the diagnosis of PD will require a combination of genetic, imaging and laboratory data. In this review we discuss the most interesting biochemical markers for PD (including the "-omics" techniques), focusing on the methodological challenges in using ex vivo blood/CSF/tissue-based biomarkers and suggesting alternative strategies to overcome the difficulties that still prevent their actual use.

Biomarkers of Parkinson's disease: current status and future perspectives

This review summarizes major advances in biomarker discovery for diagnosis, differential diagnosis and progression of Parkinson's disease (PD), with emphasis on neuroimaging and biochemical markers. Potential strategies to develop biomarkers capable of predicting PD in the prodromal stage before the appearance of motor symptoms or correlating with nonmotor symptoms, an active area of research, are also discussed.

Biochemical premotor biomarkers for Parkinson's disease

A biomarker is a biological characteristic that is objectively measured and evaluated as an indicator of normal biological or pathologic processes or of pharmacologic responses to a therapeutic intervention. We reviewed the current status of target protein biomarkers (eg, total/oligomeric α-synuclein and DJ-1) in cerebrospinal fluid, as well as on unbiased processes that can be used to discover novel biomarkers. We have also provide details about strategies toward potential populations/models and technologies, including the need for standardized sampling techniques, to pursue the identification of new biochemical markers in the premotor stage of Parkinson's disease in the future.