Research on microRNAs (miRNAs) is becoming an increasingly attractive field, as these small RNA molecules are involved in several physiological functions and diseases. To date, only few studies have assessed the expression of blood miRNAs related to Parkinson’s disease (PD) using microarray and quantitative real-time PCR (qRT-PCR). Measuring miRNA expression involves normalization of qRT-PCR data using endogenous reference genes for calibration, but their choice remains a delicate problem with serious impact on the resulting expression levels. The aim of the present study was to evaluate the suitability of a set of commonly used small RNAs as normalizers and to identify which of these miRNAs might be considered reliable reference genes in qRT-PCR expression analyses on PD blood samples. Commonly used reference genes snoRNA RNU24, snRNA RNU6B, snoRNA Z30 and miR-103a-3p were selected from the literature. We then analyzed the effect of using these genes as reference, alone or in any possible combination, on the measured expression levels of the target genes miR-30b-5p and miR-29a-3p, which have been previously reported to be deregulated in PD blood samples. We identified RNU24 and Z30 as a reliable and stable pair of reference genes in PD blood samples.

Arrhythmogenic cardiomyopathy (ACM) is an inherited genetic disorder, characterized by the substitution of heart muscle with fibro-fatty tissue and severe ventricular arrhythmias, often leading to heart failure and sudden cardiac death. ACM is considered a monogenic disorder, but the low penetrance of mutations identified in patients suggests the involvement of additional genetic or environmental factors. We used whole exome sequencing to investigate digenic inheritance in two ACM families where previous diagnostic tests have revealed a PKP2 mutation in all affected and some healthy individuals. In family members with PKP2 mutations we determined all genes that harbor variants in affected but not in healthy carriers or vice versa. We computationally prioritized the most likely candidates, focusing on known ACM genes and genes related to PKP2 through protein interactions, functional relationships, or shared biological processes. We identified four candidate genes in family 1, namely DAG1, DAB2IP, CTBP2 and TCF25, and eleven candidate genes in family 2. The most promising gene in the second family is TTN, a gene previously associated with ACM, in which the affected individual harbors two rare deleterious-predicted missense variants, one of which is located in the protein’s only serine kinase domain. In this study we report genes that might act as digenic players in ACM pathogenesis, on the basis of co-segregation with PKP2 mutations. Validation in larger cohorts is still required to prove the utility of this model.

Autosomal dominant mutations in the gene encoding α-synuclein (SNCA) were the first to be linked with hereditary Parkinson’s disease (PD). Duplication and triplication of SNCA has been observed in PD patients, together with mutations at the N-terminal of the protein, among which A30P and A53T influence the formation of fibrils. By overexpressing human α-synuclein in the neuronal system of Drosophila, we functionally validated the ability of IP3K2, an ortholog of the GWAS identified risk gene, Inositol-trisphosphate 3-kinase B (ITPKB), to modulate α-synuclein toxicity in vivo. ITPKB mRNA and protein levels were also increased in SK-N-SH cells overexpressing wild-type α-synuclein, A53T or A30P mutants. Kinase overexpression was detected in the cytoplasmatic and in the nuclear compartments in all α-synuclein cell types. By quantifying mRNAs in the cortex of PD patients, we observed higher levels of ITPKB mRNA when SNCA was expressed more (p < 0.05), compared to controls. A positive correlation was also observed between SNCA and ITPKB expression in the cortex of patients, which was not seen in the controls. We replicated this observation in a public dataset. Our data, generated in SK-N-SH cells and in cortex from PD patients, show that the expression of α-synuclein and ITPKB is correlated in pathological situations.