Site-specific selection reveals selective constraints and functionality of tumor somatic mtDNA mutations.

BACKGROUND: Previous studies have indicated that tumor mitochondrial DNA (mtDNA) mutations are primarily shaped by relaxed negative selection, which is contradictory to the critical roles of mtDNA mutations in tumorigenesis. Therefore, we hypothesized that site-specific selection may influence tumor mtDNA mutations. METHODS: To test our hypothesis, we developed the largest collection of tumor mtDNA mutations to date and evaluated how natural selection shaped mtDNA mutation patterns. RESULTS: Our data demonstrated that both positive and negative selections acted on specific positions or functional units of tumor mtDNAs, although the landscape of these mutations was consistent with the relaxation of negative selection. In particular, mutation rate (mutation number in a region/region bp length) in complex V and tRNA coding regions, especially in ATP8 within complex V and in loop and variable regions within tRNA, were significantly lower than those in other regions. While the mutation rate of most codons and amino acids were consistent with the expectation under neutrality, several codons and amino acids had significantly different rates. Moreover, the mutations under selection were enriched for changes that are predicted to be deleterious, further supporting the evolutionary constraints on these regions. CONCLUSION: These results indicate the existence of site-specific selection and imply the important role of the mtDNA mutations at some specific sites in tumor development

Artificial Intelligence Framework Identifies Candidate Targets for Drug Repurposing in Alzheimer’s Disease

Background: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer’s disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein–protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein–protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Results: Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861–0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862–0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. Conclusions: In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD

Genetic Polymorphism in a VEGF-Independent Angiogenesis Gene ANGPT1 and Overall Survival of Colorectal Cancer Patients after Surgical Resection

Background The VEGF-independent angiogenic signaling plays an important role in the development of colorectal cancer (CRC). However, its implication in the clinical outcome of CRC has not been reported. This study aimed to investigate the association between genetic variations in several major VEGF-independent signaling pathway genes and the overall survival of CRC patients. Methods Seven single nucleotide polymorphisms (SNPs) in four important VEGF-independent angiogenic genes (ANGPT1, AMOT, DLL4 and ENG) were genotyped in a Chinese population with 408 CRC patients. Results One SNP, rs1954727 in ANGPT1, was significantly associated with CRC overall survival. Compared to patients with the homozygous wild-type genotype of rs1954727, those with heterozygous and homozygous variant genotypes exhibited a favorable overall survival with a hazard ratio (HR) of 0.89 (95% confidence interval [CI] 0.55–1.43, P = 0.623), and 0.32 (95% CI 0.15–0.71, P = 0.005), respectively (P trend = 0.008). In stratified analysis, this association remained significant in patients receiving chemotherapy (P trend = 0.012), but not in those without chemotherapy. We further evaluated the effects of chemotherapy on CRC survival that was stratified by rs1954727 genotypes. We found that chemotherapy resulted in a significantly better overall survival in the CRC patients (HR = 0.44, 95% CI 0.26–0.75, P = 0.002), which was especially prominent in those patients with the heterozygous genotype of rs1954727 (HR = 0.45, 95%CI 0.22–0.92, P = 0.028). Conclusion Our data suggest that rs1954727 in ANGPT1 gene might be a prognostic biomarker for the overall survival of CRC patients, especially in those receiving chemotherapy, a finding that warrants validation in larger independent populations

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P <7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.Peer reviewe

Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants

Abstract: Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10−8. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women

Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants

Abstract: Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10−8. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p &lt; 5 × 10−9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies. Delineation of the genetic architecture of hematological traits in a multi-ethnic dataset allows identification of rare variants with strong effects specific to non-European populations and improved fine mapping of GWAS variants using the trans-ethnic approach

Correction: Zhang et al. Genotype–Environment Interaction and Horizontal and Vertical Distributions of Heartwood for <i>Acacia melanoxylon</i> R.Br. <i>Genes</i> 2023, <i>14</i>, 1299

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Design and Ground Verification of Space Station Manipulator Control Method for Orbital Replacement Unit Changeout

Chinese space station has been in construction phase, and it will be launched around 2020. Lots of orbital replacement units (ORUs) are installed on the space station, and they need to be replaced on orbit by a manipulator. In view of above application requirements, the control method for ORU changeout is designed and verified in this paper. Based on the analysis of the ORU changeout task flow, requirements of space station manipulator’s control algorithms are presented. The open loop path planning algorithm, close loop path planning algorithm based on visual feedback, and impedance control algorithm are researched. To verify the ORU changeout task flow and corresponding control algorithms, a ground experiment platform is designed, which includes a 6-DOF manipulator with a camera and a force/torque sensor, an end effector with clamp/release and screwing function, ORU module, and ORU store. At last, the task flow and control algorithms are verified on the test platform. Through the research, it is found that the ORU changeout task flow designed in this paper is reasonable and feasible, and the control method can be used to control a manipulator to complete the ORU changeout task