Parkinson’s disease (PD) is a neurodegenerative synucleinopathy that has a not yet fully understood molecular pathomechanism behind it. The role of risk genes regulated by small non-coding RNAs, or microRNAs (miRNAs), has also been highlighted in PD, where they may influence disease progression and comorbidities. In this case-control study, we analyzed miRNAs on peripheral blood mononuclear cells by means of RNA-seq in 30 participants, with the aim of identifying miRNAs differentially expressed in PD compared to age-matched healthy controls. Additionally, we investigated the pathways influenced by differentially expressed miRNAs and assessed whether a specific pathway could potentially be associated with PD susceptibility (enrichment analyses performed using the Ingenuity Pathway Analysis tools). Overall, considering that the upregulation of miRNAs might be related with the downregulation of their messenger RNA targets, and vice versa, we found several putative targets of dysregulated miRNAs (i.e., upregulated: hsa-miR-1275, hsa-miR-23a-5p, hsa-miR-432-5p, hsa-miR-4433b-3p, and hsa-miR-4443; downregulated: hsa-miR-142-5p, hsa-miR-143-3p, hsa-miR-374a-3p, hsa-miR-542-3p, and hsa-miR-99a-5p). An inverse connection between cancer and neurodegeneration, called “inverse comorbidity”, has also been noted, showing that some genes or miRNAs may be expressed oppositely in neurodegenerative disorders and in some cancers. Therefore, it may be reasonable to consider these miRNAs as potential diagnostic markers and outcome measures.

Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. LOAD has a complex and largely unknown etiology with strong genetic determinants. Genetics of LOAD is known to involve several genetic risk factors among which the Apolipoprotein E (APOE) gene seems to be the major recognized genetic determinant. Recent efforts have been made to identify other genetic factors involved in the pathophysiology of LOAD such as genes associated with a deficit of neurotrophic factors in the AD brain. Genetic variations of neurotrophic factors, such as brain-derived neurotrophic factor (BDNF), and transforming-growth-factor-β1 (TGF-β1) are known to increase the risk to develop LOAD and have also been related to depression susceptibility in LOAD. Transforming-Growth-Factor-β1 (TGF- β1) is a neurotrophic factor that exerts neuroprotective effects against β-amyloid-induced neurodegeneration. Recent evidence suggests that a specific impairment in the signaling of TGF-β is an early event in the pathogenesis of AD. TGF-β1 protein levels are predominantly under genetic control, and the TGF-β1 gene, located on chromosome 19q13.1–3, contains several single nucleotide polymorphisms (SNPs) upstream and in the transcript region, such as the SNP at codon +10 (T/C) and +25 (G/C), which is known to influence the level of expression of TGF-β1. In the present review, we summarize the current literature on genetic risk factors for LOAD, focusing on the role of the TGF-β1 gene, finally discussing the possible implications of these genetic studies for the selection of patients eligible for neuroprotective strategies in AD.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder. The number of cases of PD is expected to double by 2030, representing a heavy burden on the healthcare system. Clinical symptoms include the progressive loss of dopaminergic neurons in the substantia nigra of the midbrain, which leads to striatal dopamine deficiency and, subsequently, causes motor dysfunction. Certainly, the study of the transcriptome of the various RNAs plays a crucial role in the study of this neurodegenerative disease. In fact, the aim of this study was to evaluate the transcriptome in a cohort of subjects with PD compared with a control cohort. In particular we focused on mRNAs and long non-coding RNAs (lncRNA), using the Illumina NextSeq 550 DX System. Differential expression analysis revealed 716 transcripts with padj ≤ 0.05; among these, 630 were mRNA (coding protein), lncRNA, and MT_tRNA. Ingenuity pathway analysis (IPA, Qiagen) was used to perform the functional and pathway analysis. The highest statistically significant pathways were: IL-15 signaling, B cell receptor signaling, systemic lupus erythematosus in B cell signaling pathway, communication between innate and adaptive immune cells, and melatonin degradation II. Our findings further reinforce the important roles of mitochondria and lncRNA in PD and, in parallel, further support the concept of inverse comorbidity between PD and some cancers.

Analytical methods for the early detection of the neurodegenerative biomarker for Parkinson’s disease (PD), α-synuclein, are time-consuming and invasive, and require skilled personnel and sophisticated and expensive equipment. Thus, a pain-free, prompt and simple α-synuclein biosensor for detection in plasma is highly demanded. In this paper, an α-synuclein electrochemical biosensor based on hierarchical polyglutamic acid/ZnO nanowires decorated by gold nanoparticles, assembled as nanostars (NSs), for the determination of α-synuclein in human plasma is proposed. ZnO NSs were prepared by chemical bath deposition (CBD) and decorated with electrodeposited Au nanoparticles (Au NPs). Then, electro-polymerized glutamic acid was grown and functionalized with anti-α-synuclein. A synergistic enhancement of electrode sensitivity was observed when Au NPs were embedded into ZnO NSs. The analytical performance of the biosensor was evaluated by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), using the Fe(II)(CN)₆⁴⁻/Fe(III)(CN)₆³⁻ probe. The charge transfer resistance after α-synuclein recognition was found to be linear, with a concentration in the range of 0.5 pg·mL⁻¹ to 10 pg·mL⁻¹, a limit of detection of 0.08 pg·mL⁻¹, and good reproducibility (5% variation) and stability (90%). The biosensor was also shown to reliably discriminate between healthy plasma and PD plasma. These results suggest that the proposed biosensor provides a rapid, quantitative and high-sensitivity result of the α-synuclein content in plasma, and represents a feasible tool capable of accelerating the early and non-invasive identification of Parkinson’s disease.