Genetic influence on within-person longitudinal change in anthropometric traits in the UK Biobank.

The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2-5% for height, sitting height, body mass index (BMI) and weight (P ≤ 2.4 × 10-3). We also analysed longitudinal trait change and show a loss of both average height and weight beyond about 70 years of age. A variant tracking the Alzheimer's risk APOE- E 4 allele (rs429358) was significantly associated with weight loss ( ß = -0.047 kg per yr, s.e. 0.007, P = 2.2 × 10-11), and using 2-sample Mendelian Randomisation we detected a relationship consistent with causality between decreased lumbar spine bone mineral density and height loss (bxy = 0.011, s.e. 0.003, P = 3.5 × 10-4). Finally, population-level variance quantitative trait loci (vQTL) were consistent with within-person variability for several traits, indicating an overlap between trait variability assessed at the population or individual level. Our findings help elucidate the genetic influence on trait-change within an individual and highlight disease risks associated with these changes.

Effects of a single subanesthetic dose of esketamine on postoperative subthreshold depressive symptoms in patients undergoing unilateral modified radical mastectomy: a randomised, controlled, double-blind trial.

BACKGROUND: Breast cancer is the most common malignant tumor in females worldwide. During disease development, breast cancer patients suffer anxious and depressed, which may lead to worse quality of life or even higher mortality. Esketamine has been regarded as an antidepressant in breast cancer patients with mild or moderate depression. Here, we wonder whether the administration of esketamine could reduce the postoperative depressive symptom score of breast cancer patients who have no preoperative depression. METHODS: A total of 64 patients treated with unilateral modified radical mastectomy were randomly divided into an experimental group (esketamine group, Group E) and a control group (Group C), with 32 cases in each one. After anesthesia induction, Group C received 0.2 ml/kg of normal saline intravenously and Group E was administered 0.2 mg/kg intravenous esketamine. The primary outcome was the Patient Health Questionnaire-9 (PHQ-9) scores. The secondary outcomes included the Visual Analogue Scale (VAS) scores for pain, inflammatory markers, perioperative-related indicators, and the incidence of postoperative delirium, nausea and vomiting. RESULTS: The PHQ-9 score on postoperative day (POD) 1 in Group E declined from the preoperative level, while the score in Group C was higher than before, and the former was far lower than the latter (P = 0.047). There is no statistically significant difference in PHQ-9 scores between Group E and Group C on POD 3, 7, and 30. Moreover, the postoperative leukocyte level of Group E was higher than that of Group C, and the difference was statistically significant (P = 0.030). CONCLUSIONS: A single subanesthetic dose of esketamine can result in lower postoperative score on subthreshold depressive symptoms compared to the Group C on POD 1, without increasing the occurrence of postoperative adverse reactions. TRIAL REGISTRATION: Registration number: Chinese Clinical Trial Registry ChiCTR2200057028. Date of registration: 26/02/2022.

Unravelling the complex causal effects of substance use behaviours on common diseases.

BACKGROUND: Substance use behaviours (SUB) including smoking, alcohol consumption, and coffee intake are associated with many health outcomes. However, whether the health effects of SUB are causal remains controversial, especially for alcohol consumption and coffee intake. METHODS: In this study, we assess 11 commonly used Mendelian Randomization (MR) methods by simulation and apply them to investigate the causal relationship between 7 SUB traits and health outcomes. We also combine stratified regression, genetic correlation, and MR analyses to investigate the dosage-dependent effects. RESULTS: We show that smoking initiation has widespread risk effects on common diseases such as asthma, type 2 diabetes, and peripheral vascular disease. Alcohol consumption shows risk effects specifically on cardiovascular diseases, dyslipidemia, and hypertensive diseases. We find evidence of dosage-dependent effects of coffee and tea intake on common diseases (e.g., cardiovascular disease and osteoarthritis). We observe that the minor allele effect of rs4410790 (the top signal for tea intake level) is negative on heavy tea intake ( b ̂ G W A S = - 0.091 , s . e . = 0.007 , P = 4.90 × 10 - 35 ) but positive on moderate tea intake ( b ̂ G W A S = 0.034 , s . e . = 0.006 , P = 3.40 × 10 - 8 ) , compared to the non-tea-drinkers. CONCLUSION: Our study reveals the complexity of the health effects of SUB and informs design for future studies aiming to dissect the causal relationships between behavioural traits and complex diseases.

Many people smoke or consume alcohol, coffee and tea. The relationship between using these types of substance and the development of different diseases is not well understood. Previous studies have suggested that differences in genetics, i.e. inherited characteristics, could have an impact on how each substance impacts a particular person's health. We used a method called Mendelian Randomization to look at the impact of consuming tobacco, alcohol, coffee and tea on the development of various common diseases using genetic information. We found that relationships were complicated and many were dosage-dependent, but that consumption of a large amount of all substances tended to have negative health impacts regardless of lifestyle, behavioural or inherited characteristics.

Comparative Mitogenomics Analysis Revealed Evolutionary Divergence among Neopestalotiopsis Species Complex (Fungi: Xylariales).

The genus Neopestalotiopsis consists of obligate parasites that cause ring spot, scab, and leaf blight diseases in higher plant species. We assembled the three complete mitogenomes for the guava fruit ring spot pathogen, Neopestalotiopsis cubana. The mitogenomes are circular, with sizes of 38,666 bp, 33,846 bp, and 32,593 bp. The comparative analyses with Pestalotiopsis fici showed that N. cubana differs greatly from it in the length of the mitogenomes and the number of introns. Moreover, they showed significant differences in the gene content and tRNAs. The two genera showed little difference in gene skewness and codon preference for core protein-coding genes (PCGs). We compared gene sequencing in the mitogenomes of the order Xylariales and found large-scale gene rearrangement events, such as gene translocations and the duplication of tRNAs. N. cubana shows a unique evolutionary position in the phylum Ascomycota constructed in phylogenetic analyses. We also found a more concentrated distribution of evolutionary pressures on the PCGs of Neopestalotiopsis in the phylum Ascomycota and that they are under little selective pressure compared to other species and are subjected to purifying selection. This study explores the evolutionary dynamics of the mitogenomes of Neopestalotiopsis and provides important support for genetic and taxonomic studies.

Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores.

Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.

The use of Esketamine in CT-guided percutaneous liver tumor ablation reduces the consumption of remifentanil: a randomized, controlled, double-blind trial.

Background: In the anesthesia management of percutaneous liver tumor ablation, the requirement of analgesia is very strict. Currently, intravenous anesthesia is commonly used, such as remifentanil combined with sedative drugs. However, the pain relief is not instantaneous after increasing the dosage of remifentanil. Esketamine, a medium- or long-term analgesic drug, does not inhibit respiration to maintain patient comfort during the ablation and reduces the consumption of remifentanil. Therefore, this experiment was designed to investigate the potential of combinational therapy and the most appropriate dose of esketamine. Methods: A total of 120 patients were randomly divided into three groups by SPSS. The regular anesthesia model included dexmedetomidine 0.5 µg/kg, intravenous glucose tolerance test, remifentanil continuous infusion, flurbiprofen 50 mg, i.v., palonosetron 0.225 mg, i.v., and 1% lidocaine for local anesthesia. Group A was the regular control group, only using the regular model; Group B also received with 0.1 mg/kg esketamine, i.v.; and Group C also received 0.2 mg/kg esketamine, i.v.. The whole experiment was double-blind. Results: From December 2020 to March 2021, 120 patients were randomized in total, and 108 were included in the analysis: 36, 37, 35 were allocated to Group A, Group B, and Group C, respectively. The total dosage of remifentanil in Group A, Group B, Group C was 179.38±123.37, 120.31±57.96 and 115.91±62.42 µg, respectively. We found the total dosage of remifentanil in Group B and Group C were significantly decreased in comparison to that of Group A (P=0.004, P=0.003, respectively). The maximum dosage of remifentanil in Group A, Group B, and Group C was 1.76±0.62, 1.37±0.47, and 1.33±0.56 ng/mL, respectively. The maximum dosage of remifentanil in Group B and Group C were significantly decreased in comparison to that of Group A (P=0.003, P=0.001, respectively). The incidence of severe pain during the ablation in Group B was significantly lower than that in Group A (3 vs. 12, P<0.05). Conclusions: The use of esketamine can reduce the dosage of opioids for liver tumor ablation and reduce the occurrence of severe pain. We found that 0.1 mg/kg esketamine, i.v. is the most suitable dose for liver tumor ablation. Trial Registration: Chinese Clinical Trial Registry ChiCTR2100049152.

The EBS-A* algorithm: An improved A* algorithm for path planning.

Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the traditional A* algorithm has some limitations, such as slow planning speed, close to obstacles. In this paper, we propose an improved A*-based algorithm, called the EBS-A* algorithm, that introduces expansion distance, bidirectional search, and smoothing into path planning. The expansion distance means keeping an extra space from obstacles to improve path reliability by avoiding collisions. Bidirectional search is a strategy searching path from the start node and the goal node simultaneously. Smoothing improves path robustness by reducing the number of right-angle turns. In addition, simulation tests for the EBS-A* algorithm are performed, and the effectiveness of the proposed algorithm is verified by transferring it to a robot operating system (ROS). The experimental results show that compared with the traditional A* algorithm, the proposed algorithm improves the path planning efficiency by 278% and reduces the number of critical nodes by 91.89% and the number of right-angle turns by 100%.

Analysis of the Taxonomy and Pathogenic Factors of Pectobacterium aroidearum L6 Using Whole-Genome Sequencing and Comparative Genomics.

Soft rot pectobacteria are devastating plant pathogens with a global distribution and a broad host range. Pectobacterium aroidearum L6, previously isolated from leaves of Syngonium podophyllum, is a pectolytic bacterial pathogen that causes typical soft rot on S. podophyllum. There is a shortage for genome data of P. aroidearum, which seriously hinders research on classification and pathogenesis of Pectobacterium. We present here the complete genome sequence of P. aroidearum L6. The L6 strain carries a single 4,995,896-bp chromosome with 53.10% G + C content and harbors 4,306 predicted protein-coding genes. We estimated in silico DNA-DNA hybridization and average nucleotide identity values in combination with the whole-genome-based phylogeny from 19 Pectobacterium strains including P. aroidearum L6. The results showed that L6 and PC1 formed a population distinct from other populations of the Pectobacterium genus. Phylogenetic analysis based on 16S rRNA and genome sequences showed a close evolutionary relationship among Pectobacterium species. Overall, evolutionary analysis showed that L6 was in the same branch with PC1. In comparison with 18 Pectobacterium spp. reference pathogens, strain L6 had 2,712 gene families, among which 1,632 gene families were identified as orthologous to those strains, as well as 1 putative unique gene family. We discovered 478 genes, 10.4% of the total of predicted genes, that were potentially related to pathogenesis using the Virulence Factors of Pathogenic Bacteria database. A total of 25 genes were related to toxins, 35 encoded plant cell-wall degrading enzymes, and 122 were involved in secretion systems. This study provides a foundation for a better understanding of the genomic structure of P. aroidearum and particularly offers information for the discovery of potential pathogenic factors and the development of more effective strategies against this pathogen.

Widespread signatures of natural selection across human complex traits and functional genomic categories.

Understanding how natural selection has shaped genetic architecture of complex traits is of importance in medical and evolutionary genetics. Bayesian methods have been developed using individual-level GWAS data to estimate multiple genetic architecture parameters including selection signature. Here, we present a method (SBayesS) that only requires GWAS summary statistics. We analyse data for 155 complex traits (n = 27k-547k) and project the estimates onto those obtained from evolutionary simulations. We estimate that, on average across traits, about 1% of human genome sequence are mutational targets with a mean selection coefficient of ~0.001. Common diseases, on average, show a smaller number of mutational targets and have been under stronger selection, compared to other traits. SBayesS analyses incorporating functional annotations reveal that selection signatures vary across genomic regions, among which coding regions have the strongest selection signature and are enriched for both the number of associated variants and the magnitude of effect sizes.

Implementing a high-efficiency similarity analysis approach for firmware code.

The rapid expansion of the open-source community has shortened the software development cycle, but the spread of vulnerabilities has been accelerated, especially in the field of the Internet of Things. In recent years, the frequency of attacks against connected devices is increasing exponentially; thus, the vulnerabilities are more serious in nature. The state-of-the-art firmware security inspection technologies, such as methods based on machine learning and graph theory, find similar applications depending on the known vulnerabilities but cannot do anything without detailed information about the vulnerabilities. Moreover, model training, which is necessary for the machine learning technologies, requires a significant amount of time and data, resulting in low efficiency and poor extensibility. Aiming at the above shortcomings, a high-efficiency similarity analysis approach for firmware code is proposed in this study. First, the function control flow features and data flow features are extracted from the functions of the firmware and of the vulnerabilities, and the features are used to calculate the SimHash of the functions. The mass storage and fast query capabilities of the SimHash are implemented by the pigeonhole principle. Second, the similarity function pairs are analyzed in detail within and among the basic blocks. Within the basic blocks, the symbolic execution is used to generate the basic block semantic information, and the constraint solver is used to determine the semantic equivalence. Among the basic blocks, the local control flow graphs are analyzed to obtain their similarity. Then, we implemented a prototype and present the evaluation. The evaluation results demonstrate that the proposed approach can implement large-scale firmware function similarity analysis. It can also get the location of the real-world firmware patch without vulnerability function information. Finally, we compare our method with existing methods. The comparison results demonstrate that our method is more efficient and accurate than the Gemini and StagedMethod. More than 90% of the firmware functions can be indexed within 0.1 s, while the search time of 100,000 firmware functions is less than 2 s.

Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data.

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood ([Formula: see text]), we predict 34,797 PAIs which show strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites are enriched in enhancers or near expression QTLs. Genes whose promoters are involved in PAIs are more actively expressed, and gene pairs with promoter-promoter interactions are enriched for co-expression. Integration of the predicted PAIs with GWAS data highlight interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration.

Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identify 143 independent loci in 112 1-Mb regions, providing insights into the physiology of vitamin D and implicating genes involved in lipid and lipoprotein metabolism, dermal tissue properties, and the sulphonation and glucuronidation of 25OHD. Mendelian randomization models find no robust evidence that 25OHD concentration has causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes have (direct or indirect) causal effects on 25OHD concentration, clarifying the epidemiological relationship between 25OHD status and the health outcomes examined in this study.

Improved polygenic prediction by Bayesian multiple regression on summary statistics.

Accurate prediction of an individual's phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. We extend a powerful individual-level data Bayesian multiple regression model (BayesR) to one that utilises summary statistics from genome-wide association studies (GWAS), SBayesR. In simulation and cross-validation using 12 real traits and 1.1 million variants on 350,000 individuals from the UK Biobank, SBayesR improves prediction accuracy relative to commonly used state-of-the-art summary statistics methods at a fraction of the computational resources. Furthermore, using summary statistics for variants from the largest GWAS meta-analysis (n ≈ 700, 000) on height and BMI, we show that on average across traits and two independent data sets that SBayesR improves prediction R2 by 5.2% relative to LDpred and by 26.5% relative to clumping and p value thresholding.

Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank.

Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank and identified 75 significant vQTLs with P < 2.0 × 10-9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

Genome-wide studies identify a novel interplay between AML1 and AML1/ETO in t(8;21) acute myeloid leukemia.

The AML1/ETO fusion protein is essential to the development of t(8;21) acute myeloid leukemia (AML) and is well recognized for its dominant-negative effect on the coexisting wild-type protein AML1. However, the genome-wide interplay between AML1/ETO and wild-type AML1 remains elusive in the leukemogenesis of t(8;21) AML. Through chromatin immunoprecipitation sequencing and computational analysis, followed by a series of experimental validations, we report here that wild-type AML1 is able to orchestrate the expression of AML1/ETO targets regardless of being activated or repressed; this is achieved via forming a complex with AML1/ETO and via recruiting the cofactor AP-1 on chromatin. On chromatin occupancy, AML1/ETO and wild-type AML1 largely overlap and preferentially bind to adjacent and distinct short and long AML1 motifs on the colocalized regions, respectively. On physical interaction, AML1/ETO can form a complex with wild-type AML1 on chromatin, and the runt homology domain of both proteins are responsible for their interactions. More importantly, the relative binding signals of AML1 and AML1/ETO on chromatin determine which genes are repressed or activated by AML1/ETO. Further analysis of coregulators indicates that AML1/ETO transactivates gene expression through recruiting AP-1 to the AML1/ETO-AML1 complex. These findings enrich our knowledge of understanding the significance of the interplay between the wild-type protein and the oncogenic fusion protein in the development of leukemia.

Preferential eradication of acute myelogenous leukemia stem cells by fenretinide.

Leukemia stem cells (LSCs) play important roles in leukemia initiation, progression, and relapse, and thus represent a critical target for therapeutic intervention. However, relatively few agents have been shown to target LSCs, slowing progress in the treatment of acute myelogenous leukemia (AML). Based on in vitro and in vivo evidence, we report here that fenretinide, a well-tolerated vitamin A derivative, is capable of eradicating LSCs but not normal hematopoietic progenitor/stem cells at physiologically achievable concentrations. Fenretinide exerted a selective cytotoxic effect on primary AML CD34(+) cells, especially the LSC-enriched CD34(+)CD38(-) subpopulation, whereas no significant effect was observed on normal counterparts. Methylcellulose colony formation assays further showed that fenretinide significantly suppressed the formation of colonies derived from AML CD34(+) cells but not those from normal CD34(+) cells. Moreover, fenretinide significantly reduced the in vivo engraftment of AML stem cells but not normal hematopoietic stem cells in a nonobese diabetic/SCID mouse xenotransplantation model. Mechanistic studies revealed that fenretinide-induced cell death was linked to a series of characteristic events, including the rapid generation of reactive oxygen species, induction of genes associated with stress responses and apoptosis, and repression of genes involved in NF-κB and Wnt signaling. Further bioinformatic analysis revealed that the fenretinide-down-regulated genes were significantly correlated with the existing poor-prognosis signatures in AML patients. Based on these findings, we propose that fenretinide is a potent agent that selectively targets LSCs, and may be of value in the treatment of AML.