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

ABSTRACT: 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.

SUBMITTER: Chikina MD

PROVIDER: S-EPMC4439364 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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

Chikina Maria D MD Gerald Christophe P CP Li Xianting X Ge Yongchao Y Pincas Hanna H Nair Venugopalan D VD Nair Venugopalan D VD Wong Aaron K AK Krishnan Arjun A Troyanskaya Olga G OG Raymond Deborah D Saunders-Pullman Rachel R Bressman Susan B SB Yue Zhenyu Z Sealfon Stuart C SC

Movement disorders : official journal of the Movement Disorder Society 20150318 6

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 ...[more]

PMID: 25786808

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Project description:BackgroundThe search for biomarkers in Parkinson's disease (PD) is crucial to identify the disease early and monitor the effectiveness of neuroprotective therapies. We aim to assess whether a gene signature could be detected in blood from early/mild PD patients that could support the diagnosis of early PD, focusing on genes found particularly altered in the substantia nigra of sporadic PD.ResultsThe transcriptional expression of seven selected genes was examined in blood samples from 62 early stage PD patients and 64 healthy age-matched controls. Stepwise multivariate logistic regression analysis identified five genes as optimal predictors of PD: p19 S-phase kinase-associated protein 1A (odds ratio [OR] 0.73; 95% confidence interval [CI] 0.60-0.90), huntingtin interacting protein-2 (OR 1.32; CI 1.08-1.61), aldehyde dehydrogenase family 1 subfamily A1 (OR 0.86; 95% CI 0.75-0.99), 19?S proteasomal protein PSMC4 (OR 0.73; 95% CI 0.60-0.89) and heat shock 70-kDa protein 8 (OR 1.39; 95% CI 1.14-1.70). At a 0.5 cut-off the gene panel yielded a sensitivity and specificity in detecting PD of 90.3 and 89.1 respectively and the area under the receiving operating curve (ROC AUC) was 0.96. The performance of the five-gene classifier on the de novo PD individuals alone composing the early PD cohort (n?=?38), resulted in a similar ROC with an AUC of 0.95, indicating the stability of the model and also, that patient medication had no significant effect on the predictive probability (PP) of the classifier for PD risk. The predictive ability of the model was validated in an independent cohort of 30 patients at advanced stage of PD, classifying correctly all cases as PD (100% sensitivity). Notably, the nominal average value of the PP for PD (0.95 (SD?=?0.09)) in this cohort was higher than that of the early PD group (0.83 (SD?=?0.22)), suggesting a potential for the model to assess disease severity. Lastly, the gene panel fully discriminated between PD and Alzheimer's disease (n?=?29).ConclusionsThe findings provide evidence on the ability of a five-gene panel to diagnose early/mild PD, with a possible diagnostic value for detection of asymptomatic PD before overt expression of the disorder.

Project description:BackgroundThe clinicopathological phenotype of G2019S LRRK2-associated Parkinson's disease (L2PD) is similar to idiopathic Parkinson's disease (iPD), and G2019S LRRK2 nonmanifesting carriers (L2NMCs) are at increased risk for development of PD. With various therapeutic strategies in the clinical and preclinical pipeline, there is an urgent need to identify biomarkers that can aid early diagnosis and patient enrichment for ongoing and future LRRK2-targeted trials.ObjectiveThe objective of this work was to investigate differential protein and phospho-protein changes related to G2019S mutant LRRK2 in peripheral blood mononuclear cells from G2019S L2PD patients and G2019S L2NMCs, identify specific phospho-protein changes associated with the G2019S mutation and with disease status, and compare findings with patients with iPD.MethodsWe performed an unbiased phospho-proteomic study by isobaric label-based mass spectrometry using peripheral blood mononuclear cell group pools from a LRRK2 cohort from Spain encompassing patients with G2019S L2PD (n = 20), G2019S L2NMCs (n = 20), healthy control subjects (n = 30), patients with iPD (n = 15), patients with R1441G L2PD (n = 5), and R1441G L2NMCs (n = 3) (total N = 93).ResultsComparing G2019S carriers with healthy controls, we identified phospho-protein changes associated with the G2019S mutation. Moreover, we uncovered a specific G2019S phospho-signature that changes with disease status and can discriminate patients with G2019S L2PD, G2019S L2NMCs, and healthy controls. Although patients with iPD showed a differential phospho-proteomic profile, biological enrichment analyses revealed similar changes in deregulated pathways across the three groups.ConclusionsWe found a differential phospho-signature associated with LRRK2 G2019S for which, consistent with disease status, the phospho-profile from PD at-risk G2019S L2NMCs was more similar to healthy controls than patients with G2019S L2PD with the manifested disease. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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

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

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