Integrative analysis of potential biomarkers and immune cell infiltration in Parkinson's disease

Analysis of microisolated frontal cortex excitatory layer III and V pyramidal neurons reveals a neurodegenerative phenotype in individuals with Down syndrome

We elucidated the molecular fingerprint of vulnerable excitatory neurons within select cortical lamina of individuals with Down syndrome (DS) for mechanistic understanding and therapeutic potential that also informs Alzheimer's disease (AD) pathophysiology. Frontal cortex (BA9) layer III (L3) and layer V (L5) pyramidal neurons were microisolated from postmortem human DS and age- and sex-matched controls (CTR) to interrogate differentially expressed genes (DEGs) and key biological pathways relevant to neurodegenerative programs. We identified > 2300 DEGs exhibiting convergent dysregulation of gene expression in both L3 and L5 pyramidal neurons in individuals with DS versus CTR subjects. DEGs included over 100 triplicated human chromosome 21 genes in L3 and L5 neurons, demonstrating a trisomic neuronal karyotype in both laminae. In addition, thousands of other DEGs were identified, indicating gene dysregulation is not limited to trisomic genes in the aged DS brain, which we postulate is relevant to AD pathobiology. Convergent L3 and L5 DEGs highlighted pertinent biological pathways and identified key pathway-associated targets likely underlying corticocortical neurodegeneration and related cognitive decline in individuals with DS. Select key DEGs were interrogated as potential hub genes driving dysregulation, namely the triplicated DEGs amyloid precursor protein (APP) and superoxide dismutase 1 (SOD1), along with key signaling DEGs including mitogen activated protein kinase 1 and 3 (MAPK1, MAPK3) and calcium calmodulin dependent protein kinase II alpha (CAMK2A), among others. Hub DEGs determined from multiple pathway analyses identified potential therapeutic candidates for amelioration of cortical neuron dysfunction and cognitive decline in DS with translational relevance to AD.

Novel gene signatures predicting and immune infiltration analysis in Parkinson's disease: based on combining random forest with artificial neural network

BACKGROUND

Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, and its incidence is rapidly rising. The diagnosis of PD relies on clinical characteristics. Although current treatments aim to alleviate symptoms, they do not effectively halt the disease's progression. Early detection and intervention hold immense importance. This study aimed to establish a new PD diagnostic model.

METHODS

Data from a public database were adopted for the construction and validation of a PD diagnostic model with random forest and artificial neural network models. The CIBERSORT platform was applied for the evaluation of immune cell infiltration in PD. Quantitative real-time PCR was performed to verify the accuracy and reliability of the bioinformatics analysis results.

RESULTS

Leveraging existing gene expression data from the Gene Expression Omnibus (GEO) database, we sifted through differentially expressed genes (DEGs) in PD and identified 30 crucial genes through a random forest classifier. Furthermore, we successfully designed a novel PD diagnostic model using an artificial neural network and verified its diagnostic efficacy using publicly available datasets. Our research also suggests that mast cells may play a significant role in the onset and progression of PD.

CONCLUSION

This work developed a new PD diagnostic model with machine learning techniques and suggested the immune cells as a potential target for PD therapy.

Atopic dermatitis-associated genetic variants regulate LOC100294145 expression implicating interleukin-27 production and type 1 interferon signaling

Background

Atopic dermatitis (AD) is a complex inflammatory disease with a strong genetic component. A singular approach of genome wide association studies (GWAS) can identify AD-associated genetic variants, but is unable to explain their functional relevance in AD. This study aims to characterize AD-associated genetic variants and elucidate the mechanisms leading to AD through a multi-omics approach.

Methods

GWAS identified an association between genetic variants at 6p21.32 locus and AD. Genotypes of 6p21.32 locus variants were evaluated against LOC100294145 expression in peripheral blood mononuclear cells (PBMCs). Their influence on LOC100294145 promoter activity was measured in vitro via a dual-luciferase assay. The function of LOC100294145 was then elucidated through a combination of co-expression analyses and gene enrichment with g:Profiler. Mendelian randomization was further used to assess the causal regulatory effect of LOC100294145 on its co-expressed genes.

Results

Minor alleles of rs116160149 and rs115388857 at 6p21.32 locus were associated with increased AD risk (p = 2.175 × 10-8, OR = 1.552; p = 2.805 × 10-9, OR = 1.55) and higher LOC100294145 expression in PBMCs (adjusted p = 0.182; 8.267 × 10-12). LOC100294145 expression was also found to be increased in those with AD (adjusted p = 3.653 × 10-2). The genotype effect of 6p21.32 locus on LOC100294145 promoter activity was further validated in vitro. Co-expression analyses predicted LOC100294145 protein's involvement in interleukin-27 and type 1 interferon signaling, which was further substantiated through mendelian randomization.

Conclusion

Genetic variants at 6p21.32 locus increase AD susceptibility through raising LOC100294145 expression. A multi-omics approach enabled the deduction of its pathogenesis model comprising dysregulation of hub genes involved in type 1 interferon and interleukin 27 signaling.

Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status

Current diagnostic algorithms are insufficient for the optimal clinical and therapeutic management of cutaneous spitzoid tumors, particularly atypical spitzoid tumors (AST). Therefore, it is crucial to identify new markers that allow for reliable and reproducible diagnostic assessment and can also be used as a predictive tool to anticipate the individual malignant potential of each patient, leading to tailored individual therapy. Using Reduced Representation Bisulfite Sequencing (RRBS), we studied genome-wide methylation profiles of a series of Spitz nevi (SN), spitzoid melanoma (SM), and AST. We established a diagnostic algorithm based on the methylation status of seven cg sites located in TETK4P2 (Tektin 4 Pseudogene 2), MYO1D (Myosin ID), and PMF1-BGLAP (PMF1-BGLAP Readthrough), which allows the distinction between SN and SM but is also capable of subclassifying AST according to their similarity to the methylation levels of Spitz nevi or spitzoid melanoma. Thus, our epigenetic algorithm can predict the risk level of AST and predict its potential clinical outcomes.

Vitamin D deficiency and genetic polymorphisms of vitamin D-associated genes in Parkinson's disease

Parkinson's disease (PD) and vitamin D share a unique link as vitamin D deficiency (VDD) prevails in PD. Thus, an in-depth understanding of vitamin D biology in PD might be crucial for therapeutic strategies emphasising vitamin D. Specifically, explicating the effect of VDD and genetic polymorphisms of vitamin D-associated genes in PD, like VDR (vitamin D receptor) or GC (vitamin D binding protein) may aid the process along with polymorphisms of vitamin D metabolising genes (e.g., CYP2R1 and CYP27A1) in PD. Literature review of single nucleotide polymorphisms (SNPs) related to vitamin D levels [GC (GC1-rs7041 and GC2-rs4588), CYP2R1, CYP24A1 and CYP27B1] and vitamin D function [VDR (FokI - rs2228570 and rs10735810; ApaI - rs7976091, rs7975232BsmI and rs1544410; and TaqI - rs731236)] was conducted to explore their relationship with PD severity globally. VDR-FokI polymorphism was reported to be significantly associated with PD in Hungarian, Chinese and Japanese populations, whereas VDR-ApaI polymorphism was found to affect PD in the Iranian population. However, VDR-TaqI and BsmI polymorphisms had no significant association with PD severity. Conversely, GC1 polymorphisms reportedly affected vitamin D levels without influencing the disease severity. CYP2R1 (excluding rs1993116) was also reportedly linked to clinical manifestations of PD. Genetic polymorphisms might cause VDD despite enough sunlight exposure and vitamin D-rich food intake, enhancing inflammation, there by influencing PD pathophysiology. Knowledge of the polymorphisms associated with VDD appears promising for developing precision vitamin D-dosing therapeutic strategies against PD.

Identification of Cuproptosis Clusters and Integrative Analyses in Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disease; it mainly occurs in the elderly population. Cuproptosis is a newly discovered form of regulated cell death involved in the progression of various diseases. Combining multiple GEO datasets, we analyzed the expression profile and immunity of cuproptosis-related genes (CRGs) in PD. Dysregulated CRGs and differential immune responses were identified between PD and non-PD substantia nigra. Two CRG clusters were defined in PD. Immune analysis suggested that CRG cluster 1 was characterized by a high immune response. The enrichment analysis showed that CRG cluster 1 was significantly enriched in immune activation pathways, such as the Notch pathway and the JAK-STAT pathway. KIAA0319, AGTR1, and SLC18A2 were selected as core genes based on the LASSO analysis. We built a nomogram that can predict the occurrence of PD based on the core genes. Further analysis found that the core genes were significantly correlated with tyrosine hydroxylase activity. This study systematically evaluated the relationship between cuproptosis and PD and established a predictive model for assessing the risk of cuproptosis subtypes and the outcome of PD patients. This study provides a new understanding of PD-related molecular mechanisms and provides new insights into the treatment of PD.