The objective was to identify the predictive markers and develop a diagnostic model with predictive markers for Parkinson’s disease (PD) and investigate the roles of immune cells in the disease pathology. Microarray datasets of PD and control samples were obtained from the Gene Expression Omnibus (GEO) database. We then performed a comprehensive analysis of differentially expressed genes (DEGs), functional enrichment, and protein-protein interactions to pinpoint a set of promising candidate genes. To establish a diagnosis model for PD, we utilized machine learning algorithms and evaluated the corresponding diagnostic performance using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). Additionally, the differential abundance of immune cell subsets between PD and control samples was evaluated using the single-sample Gene Set Enrichment Analysis (ssGSEA) method. A total of 264 DEGs were identified in GSE72267. The PPI network ultimately identified 30 hub genes for model construction. Seven genes, namely CD79B, CD40, CCR9, ADRA2A, SIGLEC1, FLT3LG, and THBD, were identified as diagnostic markers for PD, with an AUC of 0.870. This seven-gene signature model was subsequently validated in an independent cohort (GSE22491), demonstrating an AUC of 0.825. Ultimately, the infiltration of 28 immune cells showed that activated B cells, natural killer T cells, and regulatory T cells may contribute to the occurrence and progression of PD. We also found complex associations between these genes and immune cells. CD79B, CD40, CCR9, ADRA2A, SIGLEC1, FLT3LG, and THBD were identified as diagnostic markers for PD, and the infiltration of immune cells may contribute to the pathogenesis of the disease.

Max Nicholls had an almost unique experience as a medical practitioner, researcher and teacher of medical genetics. An earlier paper described his contribution to the etiology of neurofibromatosis. This was followed by Nicholls’ own experience as lecturer in the Faculty of Medicine, University of New South Wales, Australia. This note draws attention to his research in immunology. For example, he was instrumental in the study of the buffy coat leuko-agglutination (BCLA) test, a sensitive assay for cell-mediated immunity that he introduced to detect conditions (including cancer) in preclinical stages.

Patients with familial adenomatous polyposis (FAP) have increased risk of hepatoblastoma (HB). We report monozygotic twins with HB in a FAP family. To explore genetic alterations in the HBs of the twins, we carried out whole exome sequencing (WES), RNA-seq, and immunohistochemical analyses of the tumors. Additional multiregional digital PCR was performed to profile clonality of each tumor. To determine a pathogenic germline variant in APC, Sanger sequencing was applied for the twins, the father, and the siblings of the father. A pathogenic variant of the APC gene was identified in the father as well as the twins. The WES of the HBs in the twins identified somatic mutations, including an NRAS mutation in the tumor of the first infant (C1), and an ACVR2A mutation in the tumor of the second infant (C2). No somatic mutations were identified in the genes associated with the Wnt signaling pathway. However, accumulation of β-catenin was found in the C1 and C2 tumors by immunohistochemical staining, suggesting activation of the Wnt signaling pathway. Digital PCR analysis revealed that the NRAS mutation was found in multiregional specimens of C1 and those of C2. The ACVR2A mutation was found in multiregional specimens of C2, whereas the mutation was also identified in those of C1. The existence of a shared somatic mutation may suggest that microchimerism took place in the development of HBs through the utero-placental circulatory system. Importantly, the initiation of tumorigenesis is thought to occur during the fetal period after organ development of the liver.

This study explores whether DNA methylation (DNAm) mediates the association between lean body mass (LBM) and cognition, as well as whether LBM mediates the association between DNAm and cognition. Based on the data of 59 monozygotic twin pairs, mediation analyses were performed using causal inference test method and mediation analyses. Average causal mediation effect (ACME), average direct effect (ADE), and total effect (TE) were calculated. Among the CpGs associated with LBM, five located within PDGFRB and RP11 genes (ACME: −0.0972−0.0463, |ACME/ADE|: 10.44%−18.30%) negatively mediated the association between LBM and cognition, while one in the PAX2 gene (ACME: 0.3510, |ACME/TE|: 11.84%) positively mediated the association. Besides, the methylation risk score (MRS) of RP11 gene (ACME: −0.0517, |ACME/ADE|: 10.64%) and MRS of all CpGs (ACME: −0.0511, |ACME/ADE|: 10.53%) negatively mediated the association of LBM with cognition. For another, LBM negatively mediated the association between the DNAm level of one CpG within UBXN6 and cognition (ACME: −0.0732, |ACME/TE|: 20.78%), while positively mediated the association between the DNAm level of four CpGs within FOXI2 and cognition (ACME: 0.2812−0.4496, |ACME/TE|: 18.15%−27.29%). It was found the DNAm in PDGFRB, RP11 and PAX2 partially mediates the association between LBM and cognition, and the association between DNAm in UBXN6 and FOXI2 with cognition is also partially mediated by LBM.