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Despite numerous studies demonstrate that genetics and epigenetics factors play important roles on smoking behavior, our understanding of their functional relevance and coordinated regulation remains largely unknown. Here we present a multiomics study on smoking behavior for Chinese smoker population with the goal of not only identifying smoking-associated functional variants but also deciphering the pathogenesis and mechanism underlying smoking behavior in this under-studied ethnic population. After whole-genome sequencing analysis of 1329 Chinese Han male samples in discovery phase and OpenArray analysis of 3744 samples in replication phase, we discovered that three novel variants located near FOXP1 (rs7635815), and between DGCR6 and PRODH (rs796774020), and in ARVCF (rs148582811) were significantly associated with smoking behavior. Subsequently cis-mQTL and cis-eQTL analysis indicated that these variants correlated significantly with the differential methylation regions (DMRs) or differential expressed genes (DEGs) located in the regions where these variants present. Finally, our in silico multiomics analysis revealed several hub genes, like DRD2, PTPRD, FOXP1, COMT, CTNNAP2, to be synergistic regulated each other in the etiology of smoking.
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INTRODUCTION: Smoking (nicotine) has been reported to possibly be neuroprotective and conducive to patients with early Parkinson's disease (PD). However, the causal effect of smoking on PD and the molecular mechanisms of smoking-related genes (SRGs) are vague. METHODS: First, genome-wide association study summary data on smoking (ukb-b-6244) and PD (ieu-b-7) were retrieved from the Integrative Epidemiology Unit OpenGWAS database for Mendelian randomization (MR) analysis. Sensitivity analyses were performed to validate the results of the MR analyses. Subsequently, a differential analysis of PD patients and controls was performed to identify differentially expressed SRGs (DE-SRGs). Finally, the expression of DE-SRGs was analyzed in annotated cell types. RESULTS: The MR analysis revealed that smoking was a protective factor causally related to PD (P=0.008, odds ratio=0.288). Furthermore, a total of five DE-SRGs enriched in Toll-like receptor signaling pathways were identified in GSE7621 dataset. Regarding single-cell analysis of GSE184950 dataset, a total of nine cell types were annotated. The expression of LRRN1 in oligodendrocyte progenitor cells and oligodendrocytes, respectively, differed significantly between PD patients and controls. CONCLUSIONS: Our study supported a causal relationship between smoking and PD and found that five SRGs (MAPK8IP1, LRRN1, LINC00324, HIST1H2BK, and YOD1) enriched in Toll-like receptor signaling pathways might be beneficial in PD. In addition, single-cell sequencing indicated that four SRGs were differentially expressed in different cell types. All four genes except MAPK8IP1 were significantly correlated with the 10 genes calculated by scPagwas. Thus, this evidence provides a theoretical basis for further research on the effect of nicotine (smoking) on PD. IMPLICATIONS: In order to explore the potential etiology and pathogenesis of Parkinson's disease, this study combined Mendelian randomization, transcriptomics and single-cell sequencing analysis to explore the association between exposure factors and Parkinson's disease, observe and confirm the relationship and mechanism between the two from the perspective of genetics, and provide more reliable evidence for causal inference.
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Introduction: Nicotine degradation is a new strategy to block nicotine-induced pathology. The potential of human microbiota to degrade nicotine has not been explored. Aims: This study aimed to uncover the genomic potentials of human microbiota to degrade nicotine. Methods: To address this issue, we performed a systematic annotation of Nicotine-Degrading Enzymes (NDEs) from genomes and metagenomes of human microbiota. A total of 26,295 genomes and 1,596 metagenomes for human microbiota were downloaded from public databases and five types of NDEs were annotated with a custom pipeline. We found 959 NdhB, 785 NdhL, 987 NicX, three NicA1, and three NicA2 homologs. Results: Genomic classification revealed that six phylum-level taxa, including Proteobacteria, Firmicutes, Firmicutes_A, Bacteroidota, Actinobacteriota, and Chloroflexota, can produce NDEs, with Proteobacteria encoding all five types of NDEs studied. Analysis of NicX prevalence revealed differences among body sites. NicX homologs were found in gut and oral samples with a high prevalence but not found in lung samples. NicX was found in samples from both smokers and non-smokers, though the prevalence might be different. Conclusion: This study represents the first systematic investigation of NDEs from the human microbiota, providing new insights into the physiology and ecological functions of human microbiota and shedding new light on the development of nicotine-degrading probiotics for the treatment of smoking-related diseases.