Using genetics and proteomics data to identify proteins causally related to COVID-19, healthspan and lifespan: a Mendelian randomization study.

BACKGROUND: COVID-19 pandemic poses a heavy burden on public health and accounts for substantial mortality and morbidity. Proteins are building blocks of life, but specific proteins causally related to COVID-19, healthspan and lifespan have not been systematically examined. METHODS: We conducted a Mendelian randomization study to assess the effects of 1,361 plasma proteins on COVID-19, healthspan and lifespan, using large GWAS of severe COVID-19 (up to 13,769 cases and 1,072,442 controls), COVID-19 hospitalization (32,519 cases and 2,062,805 controls) and SARS-COV2 infection (122,616 cases and 2,475,240 controls), healthspan (n = 300,477) and parental lifespan (~0.8 million of European ancestry). RESULTS: We identified 35, 43, and 63 proteins for severe COVID, COVID-19 hospitalization, and SARS-COV2 infection, and 4, 32, and 19 proteins for healthspan, father's attained age, and mother's attained age. In addition to some proteins reported previously, such as SFTPD related to severe COVID-19, we identified novel proteins involved in inflammation and immunity (such as ICAM-2 and ICAM-5 which affect COVID-19 risk, CXCL9, HLA-DRA and LILRB4 for healthspan and lifespan), apoptosis (such as FGFR2 and ERBB4 which affect COVID-19 risk and FOXO3 which affect lifespan) and metabolism (such as PCSK9 which lowers lifespan). We found 2, 2 and 3 proteins shared between COVID-19 and healthspan/lifespan, such as CXADR and LEFTY2, shared between severe COVID-19 and healthspan/lifespan. Three proteins affecting COVID-19 and seven proteins affecting healthspan/lifespan are targeted by existing drugs. CONCLUSIONS: Our study provided novel insights into protein targets affecting COVID-19, healthspan and lifespan, with implications for developing new treatment and drug repurposing.

ERStruct: a fast Python package for inferring the number of top principal components from whole genome sequencing data.

BACKGROUND: Large-scale multi-ethnic DNA sequencing data is increasingly available owing to decreasing cost of modern sequencing technologies. Inference of the population structure with such sequencing data is fundamentally important. However, the ultra-dimensionality and complicated linkage disequilibrium patterns across the whole genome make it challenging to infer population structure using traditional principal component analysis based methods and software. RESULTS: We present the ERStruct Python Package, which enables the inference of population structure using whole-genome sequencing data. By leveraging parallel computing and GPU acceleration, our package achieves significant improvements in the speed of matrix operations for large-scale data. Additionally, our package features adaptive data splitting capabilities to facilitate computation on GPUs with limited memory. CONCLUSION: Our Python package ERStruct is an efficient and user-friendly tool for estimating the number of top informative principal components that capture population structure from whole genome sequencing data.

Genome-wide cross-trait analysis and Mendelian randomization reveal a shared genetic etiology and causality between COVID-19 and venous thromboembolism.

Venous thromboembolism occurs in up to one-third of patients with COVID-19. Venous thromboembolism and COVID-19 may share a common genetic architecture, which has not been clarified. To fill this gap, we leverage summary-level genetic data from the latest COVID-19 host genetics consortium and UK Biobank and examine the shared genetic etiology and causal relationship between COVID-19 and venous thromboembolism. The cross-trait and co-localization analyses identify 2, 3, and 4 shared loci between venous thromboembolism and severe COVID-19, COVID-19 hospitalization, SARS-CoV-2 infection respectively, which are mapped to ABO, ADAMTS13, FUT2 genes involved in coagulation functions. Enrichment analysis supports shared biological processes between COVID-19 and venous thromboembolism related to coagulation and immunity. Bi-directional Mendelian randomization suggests that venous thromboembolism was associated with higher risk of three COVID-19 traits, and SARS-CoV-2 infection was associated with a higher risk of venous thromboembolism. Our study provides timely evidence for the genetic etiology between COVID-19 and venous thromboembolism (VTE). Our findings contribute to the understanding of COVID-19 and VTE etiology and provide insights into the prevention and comorbidity management of COVID-19.

Disentangling the common genetic architecture and causality of rheumatoid arthritis and systemic lupus erythematosus with COVID-19 outcomes: Genome-wide cross trait analysis and bidirectional Mendelian randomization study.

Coronavirus Disease (COVID-19) may cause a dysregulation of the immune system and has complex relationships with multiple autoimmune diseases, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, little is known about their common genetic architecture. Using the latest data from COVID-19 host genetics consortium and consortia on RA and SLE, we conducted a genome-wide cross-trait analysis to examine the shared genetic etiology between COVID-19 and RA/SLE and evaluated their causal associations using bidirectional Mendelian randomization (MR). The cross-trait meta-analysis identified 23, 28, and 10 shared genetic loci for severe COVID-19, COVID-19 hospitalization, and SARS-CoV-2 infection with RA, and 14, 17, and 7 shared loci with SLE, respectively. Co-localization analysis identified five causal variants in TYK2, IKZF3, PSORS1C1, and COG6 for COVID-19 with RA, and four in CRHR1, FUT2, and NXPE3 for COVID-19 with SLE, involved in immune function, angiogenesis and coagulation. Bidirectional MR analysis suggested RA is associated with a higher risk of COVID-19 hospitalization, and COVID-19 is not related to RA or SLE. Our novel findings improved the understanding of the genetic etiology shared by COVID-19, RA and SLE, and suggested an increased risk of COVID-19 hospitalization in people with higher genetic liability to RA.

Analysis of QTLs and Candidate Genes for Tassel Symptoms in Maize Infected with Sporisorium reilianum.

Heat smut is a fungal soil-borne disease caused by Sporisorium reilianum, and affects the development of male and female tassels. Our previous research found that the tassel symptoms in maize infected with Sporisorium reilianum significantly differed in inbred lines with Sipingtou blood, and exhibited stable heredity over time at multiple locations. In this study, cytological analysis demonstrated that the cellular organization structures of three typical inbred lines (Huangzao4, Jing7, and Chang7-2) showed significant discrepancies at the VT stage. QTLs that control the different symptoms of maize tassels infected with Sporisorium reilianum were located in two F2 populations, which were constructed using three typical inbred lines. The BSA (bulked segregation analysis) method was used to construct mixed gene pools based on typical tassel symptoms. The QTLs of different symptoms of maize tassels infected with Sporisorium reilianum were detected with 869 SSR markers covering the whole maize genome. The mixed gene pools were screened with polymorphic markers between the parents. Additional SSR markers were added near the above marker to detect genotypes in partially single plants in F2 populations. The QTL controlling tassel symptoms in the Huangzao4 and Jing7 lines was located on the bin 1.06 region, between the markers of umc1590 and bnlg1598, and explained 21.12% of the phenotypic variation with an additive effect of 0.6524. The QTL controlling the tassel symptoms of the Jing7 and Chang7-2 lines was located on the bin 2.07 region, between the markers of umc1042 and bnlg1335, and explained 11.26% phenotypic variation with an additive effect of 0.4355. Two candidate genes (ZmABP2 and Zm00001D006403) were identified by a conjoint analysis of label-free quantification proteome sequencings.

CoxMKF: a knockoff filter for high-dimensional mediation analysis with a survival outcome in epigenetic studies.

MOTIVATION: It is of scientific interest to identify DNA methylation CpG sites that might mediate the effect of an environmental exposure on a survival outcome in high-dimensional mediation analysis. However, there is a lack of powerful statistical methods that can provide a guarantee of false discovery rate (FDR) control in finite-sample settings. RESULTS: In this article, we propose a novel method called CoxMKF, which applies aggregation of multiple knockoffs to a Cox proportional hazards model for a survival outcome with high-dimensional mediators. The proposed CoxMKF can achieve FDR control even in finite-sample settings, which is particularly advantageous when the sample size is not large. Moreover, our proposed CoxMKF can overcome the randomness of the unstable model-X knockoffs. Our simulation results show that CoxMKF controls FDR well in finite samples. We further apply CoxMKF to a lung cancer dataset from The Cancer Genome Atlas (TCGA) project with 754 subjects and 365 306 DNA methylation CpG sites, and identify four DNA methylation CpG sites that might mediate the effect of smoking on the overall survival among lung cancer patients. AVAILABILITY AND IMPLEMENTATION: The R package CoxMKF is publicly available at https://github.com/MinhaoYaooo/CoxMKF. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Shared genetic etiology and causality between COVID-19 and venous thromboembolism: evidence from genome-wide cross trait analysis and bi-directional Mendelian randomization study.

Venous thromboembolism (VTE) occurs in up to one third patients with COVID-19. VTE and COVID-19 may share a common genetic architecture, which has not been clarified yet. To fill this gap, we leveraged summary-level genetic data from the latest COVID-19 host genetics consortium and UK Biobank and examined the shared genetic etiology and causal relationship between COVID-19 and VTE. The cross-trait analysis identified 8, 11, and 7 shared loci between VTE and severe COVID-19, COVID-19 hospitalization, SARS-CoV-2 infection respectively, in 13 genes involved in coagulation and immune function and enriched in the lung. Co-localization analysis identified eight shared loci in ABO, ADAMTS13 and FUT2 genes. Bi-direction Mendelian randomization suggested that VTE was associated with higher risks of all COVID-19 related traits, and SARS-CoV-2 infection was associated with higher risk of VTE. Our study provided timely evidence and novel insights into the genetic etiology between COVID-19 and VTE.

Shared genetic etiology and causality between body fat percentage and cardiovascular diseases: a large-scale genome-wide cross-trait analysis.

BACKGROUND: Accumulating evidences have suggested that high body fat percentage (BF%) often occurs in parallel with cardiovascular diseases (CVDs), implying a common etiology between them. However, the shared genetic etiology underlying BF% and CVDs remains unclear. METHODS: Using large-scale genome-wide association study (GWAS) data, we investigated shared genetics between BF% (N = 100,716) and 10 CVD-related traits (n = 6968-977,323) with linkage disequilibrium score regression, multi-trait analysis of GWAS, and transcriptome-wide association analysis, and evaluated causal associations using Mendelian randomization. RESULTS: We found strong positive genetic correlations between BF% and heart failure (HF) (Rg = 0.47, P = 1.27 × 10- 22) and coronary artery disease (CAD) (Rg = 0.22, P = 3.26 × 10- 07). We identified 5 loci and 32 gene-tissue pairs shared between BF% and HF, as well as 16 loci and 28 gene-tissue pairs shared between BF% and CAD. The loci were enriched in blood vessels and brain tissues, while the gene-tissue pairs were enriched in the nervous, cardiovascular, and exo-/endocrine system. In addition, we observed that BF% was causally related with a higher risk of HF (odds ratio 1.63 per 1-SD increase in BF%, P = 4.16 × 10-04) using a MR approach. CONCLUSIONS: Our findings suggest that BF% and CVDs have shared genetic etiology and targeted reduction of BF% may improve cardiovascular outcomes. This work advances our understanding of the genetic basis underlying co-morbid obesity and CVDs and opens up a new way for early prevention of CVDs.

Molecular characteristics of segment 5, a unique fragment encoding two partially overlapping ORFs in the genome of rice black-streaked dwarf virus.

Rice black-streaked dwarf virus (RBSDV), a ds-RNA virus in Fijivirus genus with family Reoviridae, which is transmitted by the small brown planthopper, is responsible for incidence of maize rough dwarf disease (MRDD) and rice black-streaked dwarf disease (RBSDD). To understand the variation and evolution of S5, a unique fragment in the genome of RBSDV which encodes two partially overlapping ORFs (ORF5-1 and ORF5-2), we analyzed 127 sequences from maize and rice exhibiting symptoms of dwarfism. The nucleotide diversity of both ORF5-1 (π = 0.039) and ORF5-2 (π = 0.027) was higher than that of the overlapping region (π = 0.011) (P < 0.05). ORF5-2 was under the greatest selection pressure based on codon bias analysis, and its activation was possibly influenced by the overlapping region. The recombinant fragments of three recombinant events (14NM23, 14BM20, and 14NM17) cross the overlapping region. Based on neighbor-joining tree analysis, the overlapping region could represent the evolutionary basis of the full-length S5, which was classified into three main groups. RBSDV populations were expanding and haplotype diversity resulted mainly from the overlapping region. The genetic differentiation of combinations (T127-B35, T127-J34, A58-B35, A58-J34, and B35-J34) reached significant or extremely significant levels. Gene flow was most frequent between subpopulations A58 and B35, with the smallest |Fst| (0.02930). We investigated interactions between 13 RBSDV proteins by two-hybrid screening assays and identified interactions between P5-1/P6, P6/P9-1, and P3/P6. We also observed self-interactive effects of P3, P6, P7-1, and P10. In short, we have proven that RBSDV populations were expanding and the overlapping region plays an important role in the genetic variation and evolution of RBSDV S5. Our results enable ongoing research into the evolutionary history of RBSDV-S5 with two partly overlapping ORFs.

Analysis of Cytology and Expression of Resistance Genes in Maize Infected with Sporisorium reilianum.

Head smut, caused by the fungus Sporisorium reilianum, is a devastating global disease of maize (Zea mays). In the present study, maize seedlings were artificially inoculated with compatible mating-type strains of S. reilianum by needle inoculation of mesocotyls (NIM) or by soaking inoculation of radicles (SIR). After NIM or SIR, Huangzao4 mesocotyls exhibited severe damage with brownish discoloration and necrosis, whereas Mo17 mesocotyls exhibited few lesions. Fluorescence and electron microscopy showed that S. reilianum infected maize within 0.5 day after SIR and mainly colonized the phloem. With longer incubation, the density of S. reilianum hyphae increased in the vascular bundles, concentrated mainly in the phloem. In Mo17, infected cells exhibited apoptosis-like features, and hyphae became sequestered within dead cells. In contrast, in Huangzao4, pathogen invasion resulted in autophagy that failed to prevent hyphal spreading. The growth of S. reilianum hyphae diminished at 6 days after inoculation when expression of the R genes ZmWAK and ZmNL peaked. Thus, 6 days after SIR inoculation might be an important time for inhibiting the progress of S. reilianum infection in maize. The results of this study will provide a basis for further analysis of the mechanisms of maize resistance to S. reilianum.