We performed ultra-deep methylation analysis at single molecule level of the promoter region of developmentally regulated D-Aspartate oxidase (Ddo), as a model gene, during brain development and embryonic stem cell neural differentiation. Single molecule methylation analysis enabled us to establish the effective epiallele composition within mixed or pure brain cell populations. In this framework, an epiallele is defined as a specific combination of methylated CpG within Ddo locus and can represent the epigenetic haplotype revealing a cell-to-cell methylation heterogeneity. Using this approach, we found a high degree of polymorphism of methylated alleles (epipolymorphism) evolving in a remarkably conserved fashion during brain development. The different sets of epialleles mark stage, brain areas, and cell type and unravel the possible role of specific CpGs in favoring or inhibiting local methylation. Undifferentiated embryonic stem cells showed non-organized distribution of epialleles that apparently originated by stochastic methylation events on individual CpGs. Upon neural differentiation, despite detecting no changes in average methylation, we observed that the epiallele distribution was profoundly different, gradually shifting toward organized patterns specific to the glial or neuronal cell types. Our findings provide a deep view of gene methylation heterogeneity in brain cell populations promising to furnish innovative ways to unravel mechanisms underlying methylation patterns generation and alteration in brain diseases.

Phospholipases (PLA2s) are a superfamily of enzymes characterized by the ability to specifically hydrolyze the sn-2 ester bond of phospholipids generating arachidonic acid, utilized in inflammatory responses, and lysophospholipids involved in the control of cell membrane remodeling and fluidity. PLA2s have been so far considered a crucial element in the etiopathogenesis of several neurological diseases such as cerebral ischemia, multiple sclerosis, Parkinson's disease, and Alzheimer's disease (AD). In AD, the role of beta-amyloid (Aβ) fragments is well established although still more elusive are the molecular events of the cascade that from the Aβ accumulation leads to neurodegeneration with its clinical manifestations. However, it is well known that inflammation and alteration of lipid metabolism are common features of AD brains. Findings obtained from in vitro studies, animal models, and human brain imaging analysis point towards cPLA2 as a key molecule in the onset and maintenance of the neurodegenerative mechanism(s) of AD. In this review, we have focused on the molecular and biological evidence of the involvement of cPLA2s in the pathogenesis of AD. An insight into the molecular mechanism(s) underlying the action and the regulation of cPLA2 is of tremendous interest in the pharmaceutical and biotechnology industry in developing selective and potent inhibitors able to modulate the onset and/or the outcome of AD.

Background Parkinson’s disease (PD) is a neurodegenerative movement disorder affecting 1–5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. Methods The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). Results Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10− 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. Conclusions Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment.

This is the first report of a disease phenotype associated with mutation in humans.

No abstract