A Commentary on Axon guidance pathway genes and Parkinson’s disease

Tomiyama, Hiroyuki

doi:10.1038/jhg.2010.153

Cited by 8 publications

(6 citation statements)

References 14 publications

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“…The physiological function of the axon guidance pathway includes neuronal network formation during central nervous system development and the maintenance and plasticity of neural synapses (Bae et al, 2021). Abnormal axon-guidancemolecule signaling can lead to loss of connectivity and eventually trigger PD (Lin et al, 2009;Tomiyama, 2011). In addition, peripheral immune cells infiltrate the brain, possibly because of blood-brain barrier breakdown, which may affect neuroinflammation in the central nervous system by modulating microglial and astrocyte functions.…”

Section: Discussionmentioning

confidence: 99%

Identification of Immune-Related Hub Genes in Parkinson’s Disease

et al. 2022

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Background: Parkinson’s disease (PD) is a common, age-related, and progressive neurodegenerative disease. Growing evidence indicates that immune dysfunction plays an essential role in the pathogenic process of PD. The objective of this study was to explore potential immune-related hub genes and immune infiltration patterns of PD.Method: The microarray expression data of human postmortem substantia nigra samples were downloaded from GSE7621, GSE20141, and GSE49036. Key module genes were screened via weighted gene coexpression network analysis, and immune-related genes were intersected to obtain immune-key genes. Functional enrichment analysis was performed on immune-key genes of PD. In addition to, immune infiltration analysis was applied by a single-sample gene set enrichment analysis algorithm to detect differential immune cell types in the substantia nigra between PD samples and control samples. Least absolute shrinkage and selection operator analysis was performed to further identify immune-related hub genes for PD. Receiver operating characteristic curve analysis of the immune-related hub genes was used to differentiate PD patients from healthy controls. Correlations between immune-related hub genes and differential immune cell types were assessed.Result: Our findings identified four hub genes (SLC18A2, L1CAM, S100A12, and CXCR4) and seven immune cell types (neutrophils, T follicular helper cells, myeloid-derived suppressor cells, type 1 helper cells, immature B cells, immature dendritic cells, and CD56 bright natural killer cells). The area under the curve (AUC) value of the four-gene-combined model was 0.92. The AUC values of each immune-related hub gene (SLC18A2, L1CAM, S100A12, and CXCR4) were 0.81, 0.78, 0.78, and 0.76, respectively.Conclusion: In conclusion, SLC18A2, L1CAM, S100A12, and CXCR4 were identified as being associated with the pathogenesis of PD and should be further researched.

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Section: Discussionmentioning

confidence: 99%

Identification of Immune-Related Hub Genes in Parkinson’s Disease

et al. 2022

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“…Nonetheless, their role in heifer fertility requires further validation, because assigning genes to significant SNPs purely on genomic location is imperfect. For example, the peak SNP in chromosome 3 could point to VAV3 as discussed above, or it could suggest the candidate gene NTNG1 that is involved with axon guidance and can disturb glutamatergic and dopaminergic signaling [ 98 ]. The axon guidance pathway coordinates migration of neurons and their connectivity, which influences GnRH neurons and therefore puberty.…”

Section: Discussionmentioning

confidence: 99%

Meta-Analysis of Heifer Traits Identified Reproductive Pathways in Bos indicus Cattle

Tahir

Porto-Neto

Gondro

et al. 2021

Genes

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Fertility traits measured early in life define the reproductive potential of heifers. Knowledge of genetics and biology can help devise genomic selection methods to improve heifer fertility. In this study, we used ~2400 Brahman cattle to perform GWAS and multi-trait meta-analysis to determine genomic regions associated with heifer fertility. Heifer traits measured were pregnancy at first mating opportunity (PREG1, a binary trait), first conception score (FCS, score 1 to 3) and rebreeding score (REB, score 1 to 3.5). The heritability estimates were 0.17 (0.03) for PREG1, 0.11 (0.05) for FCS and 0.28 (0.05) for REB. The three traits were highly genetically correlated (0.75–0.83) as expected. Meta-analysis was performed using SNP effects estimated for each of the three traits, adjusted for standard error. We identified 1359 significant SNPs (p-value < 9.9 × 10−6 at FDR < 0.0001) in the multi-trait meta-analysis. Genomic regions of 0.5 Mb around each significant SNP from the meta-analysis were annotated to create a list of 2560 positional candidate genes. The most significant SNP was in the vicinity of a genomic region on chromosome 8, encompassing the genes SLC44A1, FSD1L, FKTN, TAL2 and TMEM38B. The genomic region in humans that contains homologs of these genes is associated with age at puberty in girls. Top significant SNPs pointed to additional fertility-related genes, again within a 0.5 Mb region, including ESR2, ITPR1, GNG2, RGS9BP, ANKRD27, TDRD12, GRM1, MTHFD1, PTGDR and NTNG1. Functional pathway enrichment analysis resulted in many positional candidate genes relating to known fertility pathways, including GnRH signaling, estrogen signaling, progesterone mediated oocyte maturation, cAMP signaling, calcium signaling, glutamatergic signaling, focal adhesion, PI3K-AKT signaling and ovarian steroidogenesis pathway. The comparison of results from this study with previous transcriptomics and proteomics studies on puberty of the same cattle breed (Brahman) but in a different population identified 392 genes in common from which some genes—BRAF, GABRA2, GABR1B, GAD1, FSHR, CNGA3, PDE10A, SNAP25, ESR2, GRIA2, ORAI1, EGFR, CHRNA5, VDAC2, ACVR2B, ORAI3, CYP11A1, GRIN2A, ATP2B3, CAMK2A, PLA2G, CAMK2D and MAPK3—are also part of the above-mentioned pathways. The biological functions of the positional candidate genes and their annotation to known pathways allowed integrating the results into a bigger picture of molecular mechanisms related to puberty in the hypothalamus–pituitary–ovarian axis. A reasonable number of genes, common between previous puberty studies and this study on early reproductive traits, corroborates the proposed molecular mechanisms. This study identified the polymorphism associated with early reproductive traits, and candidate genes that provided a visualization of the proposed mechanisms, coordinating the hypothalamic, pituitary, and ovarian functions for reproductive performance in Brahman cattle.

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“…Hence, mmu_circ_0003292 and mmu_circ_0001320 might have roles in the pathogenesis of PD, as well as its development. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) investigations have revealed a possible role for mmu_circ_0005976, mmu_circ_0003328, mmu_circ_0005388, and mmu_circ_0012384 in PD's pathogenic mechanisms (Tomiyama, 2011; Valet et al, 2015). As a significant finding, the neurotrophin signaling pathway, the PI3K–Akt signaling, and the FoxO signaling were predicted as major pathways targeted by mmu_circ_0001320, mmu_circ_0005976, mmu_circ_0005388, and mmu_circ_0003292, respectively (Jia et al, 2020).…”

Section: Circrnas and Pd: How Do These Circular Rna Molecules Interfe...mentioning

confidence: 99%

Novel insights into the role of circular RNAs in Parkinson disease: An emerging renaissance in the management of neurodegenerative diseases

Dorostgou

Yadegar

Dorostgou

et al. 2022

J of Neuroscience Research

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Parkinson's disease (PD), as a debilitating neurodegenerative disease, particularly affects the elderly population, and is clinically identified by resting tremor, rigidity, and bradykinesia. Pathophysiologically, PD is characterized by an early loss of dopaminergic neurons in the Substantia nigra pars compacta, accompanied by the extensive aggregation of alpha-synuclein (α-Syn) in the form of Lewy bodies. The onset of PD has been reported to be influenced by multiple biological molecules. In this context, circular RNAs (circRNAs), as tissue-specific noncoding RNAs with closed structures, have been recently demonstrated to involve in a set of PD's pathogenic processes.These RNA molecules can either up-or downregulate the expression of α-Syn, as well as moderating its accumulation through different regulatory mechanisms, in which targeting microRNAs (miRNAs) is considered the most common pathway. Since circR-NAs have prominent structural and biological characteristics, they could also be considered as promising candidates for PD diagnosis and treatment. Unfortunately, PD has become a global health concern, and a large number of its pathogenic processes are still unclear; thus, it is crucial to elucidate the ambiguous aspects of PD pathophysiology to improve the efficiency of diagnostic and therapeutic strategies. In line with this fact, the current review aims to highlight the interplay between circRNAs and PD pathogenesis, and then discusses the diagnostic and therapeutic potential of circRNAs in PD progression. This study will thus be the first of its kind reviewing the relationship between circRNAs and PD.

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A Commentary on Axon guidance pathway genes and Parkinson’s disease

Cited by 8 publications

References 14 publications

Identification of Immune-Related Hub Genes in Parkinson’s Disease

Identification of Immune-Related Hub Genes in Parkinson’s Disease

Meta-Analysis of Heifer Traits Identified Reproductive Pathways in Bos indicus Cattle

Novel insights into the role of circular RNAs in Parkinson disease: An emerging renaissance in the management of neurodegenerative diseases

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