Summary Datasets Research Articles

Automated Abstractive Text Summarization using Deep Learning

A class of neural networks known as Recurrent Neural Networks (RNNs) are capable of processing sequential input, including time series and plain language. In the shortest possible time to find relevant and useful information, it is for sure very helpful if the information is summarized, but it typically requires a lot of effort, dedication, patience, and attention to detail for humans to go through and summarize the lengthy texts. This can be done using automated abstractive text summarization techniques by using deep learning which is the way of selecting the most significant information in a text, then condensing it while maintaining its underlying meaning. The objective is to construct an abstractive text summarizer using deep learning. It takes large meaning-full text data as input and gives the summary of the data as output. The algorithm which is been used here is the Long Short Term Memory model (LSTM) which is a type of RNN model. And then next the model which is been used is the Sequence to Sequence model (Seq2Seq). Seq2Seq learning is the training model that can modify the sequences of one input into the sequences of another output. The dataset used is News Summary dataset which is taken from Kaggle. Experimental results on the news summary dataset show that the proposed method results are appropriate and match with the other methods.

Bidirectional two-sample Mendelian randomization study of causality between rheumatoid arthritis and myocardial infarction.

Epidemiological evidence suggests an association between rheumatoid arthritis (RA) and myocardial infarction (MI). However, causality remains uncertain. Therefore, this study aimed to explore the causal association between RA and MI. Using publicly available genome-wide association study summary datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using inverse-variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods. The MR results for the causal effect of RA on MI (IVW, odds ratio [OR] = 1.041, 95% confidence interval [CI]: 1.007-1.076, P = 0.017; weighted median, OR = 1.027, 95% CI: 1.006-1.049, P = 0.012) supported a causal association between genetic susceptibility to RA and an increased risk of MI. MR results for the causal effect of MI on RA (IVW, OR = 1.012, 95% CI: 0.807-1.268, P = 0.921; weighted median, OR = 1.069, 95% CI: 0.855-1.338, P = 0.556) indicated that there was no causal association between genetic susceptibility to MI and an increased risk of RA. Bidirectional TSMR analysis supports a causal association between genetic susceptibility to RA and an increased risk of MI but does not support a causal association between genetic susceptibility to MI and an increased risk of RA.

Telomere Length and Development of Systemic Lupus Erythematosus: A Mendelian Randomization Study.

Previous observational studies demonstrated that a subset of patients with systemic lupus erythematosus (SLE) have markedly short telomere length in leukocytes. This study was undertaken to test whether leukocyte telomere length is causally associated with risk of SLE. A 2-sample Mendelian randomization (MR) analysis was conducted to estimate causality of telomere length on SLE in European populations. A replication 2-sample MR study using Asian genetic data was also conducted. A reverse MR analysis was then performed to test the effects of SLE on telomere length. The autoantibodies targeting telomere-associated protein (telomeric repeat-binding factor 1 [TERF1] autoantibodies) were detected in patients with SLE, healthy controls, and patients with rheumatoid arthritis. The results of the inverse variance-weighted method (odds ratio [OR] 2.96 [95% confidence interval (95% CI) 1.58-5.55], P < 0.001) showed strong evidence for a causal relationship between longer telomere length and risk of SLE in people with European ancestry. The outcomes of MR-Egger regression analysis (OR 29.46 [95% CI 3.02-287.60], P=0.033) and MR pleiotropy residual sum and outlier analysis (OR 3.62 [95% CI 2.03-6.46], P=0.002) also showed that longer telomere length was significantly associated with increased risk of SLE in a European population. Sensitivity analyses using different methods and summary data sets showed that the results were still broadly consistent. A replication MR study using Asian genetic data yielded similar findings. However, the reverse MR analysis showed that genetically predicted SLE was not causally associated with telomere length. In addition, we found that TERF1 autoantibodies were present in 2 of 40 SLE patients (5.0%). In contrast with previous observational studies, MR analyses show that longer telomere length is significantly associated with increased risk of SLE.

Type 2 diabetes mellitus and the risk of abnormal spermatozoa: A Mendelian randomization study.

Abnormal spermatozoa can not only reduce the fertilization rate, but also prolong the natural conception time and even increase the risk of spontaneous miscarriage. Diabetes mellitus (DM) has become a major global health problem, and its incidence continues to rise, while affecting an increasing number of men in their reproductive years. Type 2 Diabetes Mellitus (T2DM), accounting for about 85-95% of DM, is closely related to the development of sperm. However, the exact association between T2DM and abnormal spermatozoa remains unclear. Herein, we designed a Two-sample Mendelian randomization (MR) study to explore the causal association between T2DM and abnormal spermatozoa risk in European population data which come from the GWAS summary datasets. We selected 9 single nucleotide polymorphisms (SNPs) of T2DM (exposure data) as instrumental variables (IVs), and then retrieved the suitable abnormal spermatozoa genome-wide association study (GWAS) data of European from Ieu Open GWAS Project database which includes 915 cases and 209,006 control as the outcome data. Our results indicate that strict T2DM might not result in a higher risk of abnormal spermatozoa genetically in Europeans (OR: 1.017, 95% confidence interval (CI): 0.771-1.342, p=0.902). Our findings demonstrate that only T2DM may not explain the relatively higher risk of abnormal spermatozoa in men with it in Europeans. In subsequent studies, more comprehensive and larger samples need to be studied to reveal the relationship and potential mechanism between T2DM and abnormal spermatozoa.

The association between vitamin D and uterine fibroids: A mendelian randomization study.

Uterine fibroids (UFs), the most common benign gynecological tumor, can bring severe negative impacts on a woman’s life quality. Vitamin D, is thought to play an important role in regulating cell proliferation and differentiation. In recent years, several studies suggested that higher level of vitamin D has a negative effect on the occurrence of UFs, but the results of studies on the relationship between them are conflicting and further evidence needs to be studied. Here in, we used a two-sample Mendelian Randomization (2SMR) study to explore the causal relationship between genetically predicted vitamin D levels and the risk of UFs. The exposure data comes from a genome-wide association study (GWAS) summary dataset consisting of 441,291 individuals, which includes datasets from United Kingdom Biobank, FinnGen Biobank and the corresponding consortia. Single-nucleotide polymorphisms (SNPs) associated with vitamin D at a significant level of p < 5 × 10−8 and low linkage disequilibrium (LD) level (r2 < 0.01) were selected. The outcome data comes from a GWAS dataset of IEU analysis of United Kingdom Biobank phenotypes consisting of 7,122 UFs cases and 455,811 controls. Our inverse-variance weight (IVW) analysis results support the causal association of genetically predicted vitamin D with the risk of UFs (OR = 0.995,95% CI = 0.990-0.999, p = 0.024). In addition, heterogeneity and pleiotropy were not observed in statistical models. In summary, our results indicate that elevated serum vitamin D levels are in strong relationship with reduction of the risk of UFs, which indicates that the clinical treatment of UFs may have a new and excellent option.

Thyroid Function and COVID-19 Susceptibility and Its Severity: A Two-Sample Mendelian Randomization Study.

Several observational studies have confirmed the relationship between thyroid hormones and coronavirus disease 2019 (COVID-19), but this correlation remains controversial. We performed a two-sample Mendelian randomization (MR) analysis based on the largest publicly available summary datasets. Summary statistics with 49 269 individuals for free thyroxine (FT4) and 54 288 for thyroid stimulating hormone (TSH) were used as exposure instruments. Genome-wide association studies of susceptibility (cases = 38 984; controls = 1 644 784), hospitalization (cases: 9986 = controls = 1 877 672), and very severe disease (cases = 5101; controls = 1 383 241) of COVID-19 were used as the outcome. We used the inverse-variance weighted (IVW) method as the primary analysis, and utilized MR-Egger regression, weighted median, and robust adjusted profile score (RAPS) for sensitivity analysis. Genetic predisposition to higher serum levels of FT4 within the normal range was negatively associated with the risk of COVID-19 hospitalization (odds ratio [OR] = 0.818; 95% CI, 0.718-0.932; P = 2.6 × 10-3) and very severe disease (OR = 0.758; 95% CI, 0.626-0.923; P = 5.8 × 10-3), but not susceptibility. There is no evidence that genetically predicted circulating TSH levels are associated with COVID-19 susceptibility and severity risk. Neither apparent pleiotropy nor heterogeneity were detected in the sensitivity analysis. In summary, we found that higher FT4 levels may reduce the risk of COVID-19 severity, suggesting that thyroid function testing may be required for patients with COVID-19.

Gene Set Enrichment Analysis Detected Immune Cell-Related Pathways Associated with Primary Sclerosing Cholangitis.

Aim To explore various immune cell-related causal pathways for primary sclerosing cholangitis (PSC). Methods Immune cell-related pathway association study was conducted via integrative analysis of PSC GWAS summary and five immune cell-related eQTL datasets. The GWAS summary data of PSC was driven from 4,796 PSC cases and 19,955 healthy controls. The eQTL datasets of CD4+ T cells, CD8+ T cells, B cells, natural killer cells (NK), monocytes, and peripheral blood cells (PB) were collected from recently eQTL study. The PSC GWAS summary dataset was first aligned with eQTL datasets of six blood cells to obtain the GWAS summary data at overlapped eQTL loci, separately. For each type of cell, the obtained PSC GWAS summary dataset of eQTLs was subjected to pathway enrichment analysis. 853 biological pathways from Kyoto Encyclopedia of Genes and Genomes, BioCarta, and Reactome pathway databases were analyzed. Results We identified 36 pathways for B cells, 33 pathways for CD4+ T cells, 28 pathways for CD8+ T cells, 33 pathways for monocytes (MN), 35 pathways for NK cells, and 33 for PB cells (all empirical P values <5.0 × 10−5). Comparing the pathway analysis results detected 25 pathways shared by five immune cells, such as KEGG_CELL_ADHESION_MOLECULES_CAMS (P value <5.0 × 10−5) and REACTOME_MHC_CLASS_II_ANTIGEN_ PRESENTATION (P value <5.0 × 10−5). Several cell-specific pathways were also identified, including BIOCARTA_INFLAM_PATHWAY (P value <5 × 10−5) for B cell. Conclusion Our study holds potential to identify novel candidate causal pathways and provides clues for revealing the complex genetic mechanism of PSC.

Systematic evaluation for the causal effects of blood metabolites on osteoporosis: Genetic risk score and Mendelian randomization.

PurposeOsteoporosis is associated with metabolic alterations, but the causal roles of serum metabolites on osteoporosis have not been identified.MethodsBased on the large individual-level datasets from UK Biobank as well as GWAS summary datasets, we first constructed genetic risk scores (GRSs) for 308 of 486 human serum metabolites and evaluated the effect of each GRS on 2 major osteoporosis phenotypes, i.e., estimated bone miner density (eBMD) and fracture, respectively. Then, two-sample Mendelian Randomization (MR) was performed to validate the casual metabolites on osteoporosis. Multivariable MR analysis tested whether the effects of metabolites on osteoporosis are independent of possible confounders. Finally, we conducted metabolic pathway analysis for the metabolites involved in bone metabolism.ResultsWe identified causal effects of 18 metabolites on eBMD and 1 metabolite on fracture with the GRS method after adjusting for multiple tests. Then, 9 of them were further validated with MR as replication, where comprehensive sensitive analyses proved robust of the causal associations. Although not identified in GRS, 3 metabolites were associated with at least three osteoporosis traits in MR results. Multivariable MR analysis determined the independent causal effect of several metabolites on osteoporosis. Besides, 23 bone metabolic pathways were detected, such as valine, leucine, isoleucine biosynthesis (p = 0.053), and Aminoacyl-tRNA biosynthesis (p = 0.076), and D-glutamine and D-glutamate metabolism (p = 0.004).ConclusionsThe systematic causal analyses strongly suggested that blood metabolites have causal effects on osteoporosis risk.

The Causal Evidence of Birth Weight and Female-Related Traits and Diseases: A Two-Sample Mendelian Randomization Analysis.

Objectives : A large meta-analysis indicated a more pronounced association between lower birth weight (BW) and diseases in women but less concern about the causality between BW and female-related phenotypes and diseases. Methods: Mendelian randomization (MR) analysis was used to estimate the causal relationship between two traits or diseases using summary datasets from genome-wide association studies. Exposure instrumental variables are variants that are strongly associated with traits and are tested using four different statistical methods, including the inverse variance weighting, MR-Egger, weighted median, and weighted mode in MR analysis. Next, sensitivity analysis and horizontal pleiotropy were assessed using leave-one-out and MR-PRESSO packages. Results: The body mass index (BMI) in adulthood was determined by BW (corrected β = 0.071, p = 3.19E-03). Lower BW could decrease the adult sex hormone-binding globulin (SHBG) level (β = −0.081, p = 2.08E-06), but it resulted in increased levels of bioavailable testosterone (bio-T) (β = 0.105, p = 1.25E-05). A potential inverse effect was observed between BW and menarche (corrected β = −0.048, p = 4.75E-03), and no causal association was confirmed between BW and the risk of endometriosis, leiomyoma, and polycystic ovary syndrome. Conclusion: Our results suggest that BW may play an important role and demonstrates a significant direct influence on female BMI, SHBG and bio-T levels, and menarche.

A Cross-Tissue Transcriptome-Wide Association Study Identifies Novel Susceptibility Genes for Juvenile Idiopathic Arthritis in Asia and Europe.

BackgroundJuvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children, and its pathogenesis is still unclear. Genome-wide association studies (GWASs) of JIA have identified hundreds of risk factors, but few of them implicated specific biological mechanisms.MethodsA cross-tissue transcriptome-wide association study (TWAS) was performed with the functional summary-based imputation software (FUSION) tool based on GWAS summary datasets (898 JIA patients and 346,102 controls from BioBank Japan (BBJ)/FinnGen). The gene expression reference weights of skeletal muscle and the whole blood were obtained from the Genotype-Tissue Expression (GTExv8) project. JIA-related genes identified by TWAS findings genes were further compared with the differentially expressed genes (DEGs) identified by the mRNA expression profile of JIA from the Gene Expression Omnibus (GEO) database (accession number: GSE1402). Last, candidate genes were analyzed using functional enrichment and annotation analysis by Metascape to examine JIA-related gene sets.ResultsThe TWAS identified 535 significant genes with P < 0.05 and contains 350 for Asian and 195 for European (including 10 genes both expressed in Asian and European), such as CDC16 (P = 1.72E-03) and PSMD5-AS1 (P = 3.65E-02). Eight overlapping genes were identified based on TWAS results and DEGs of JIA patients, such as SIRPB1 (P TWAS = 4.21E-03, P DEG = 1.50E-04) and FRAT2 (P TWAS = 2.82E-02, P DEG = 1.43E-02). Pathway enrichment analysis of TWAS identified 183 pathways such as cytokine signaling in the immune system and cell adhesion molecules. By integrating the results of DEGs pathway and process enrichment analyses, 19 terms were identified such as positive regulation of T-cell activation.ConclusionBy conducting two populations TWAS, we identified a group of JIA-associated genes and pathways, which may provide novel clues to uncover the pathogenesis of JIA.

Changes in the National Endovascular Management of Femoropopliteal Arterial Disease: An Analysis of the 2011–2019 Medicare Data

PurposeTo describe national trends in the utilization of endovascular approaches (including balloon angioplasty, atherectomy, and stent placement) for the management of femoropopliteal peripheral arterial disease (PAD). Materials and MethodsThe Medicare Physician/Supplier Procedure Summary dataset containing 100% of Part B claims was interrogated for years 2011–2019. The Current Procedural Terminology codes specific for femoropopliteal angioplasty, stent placement, and atherectomy were used to create summary statistics for utilization by year, place of service (hospital inpatient, hospital outpatient, and office-based laboratory), and provider specialty (cardiology, radiology, and surgery). ResultsThe use of atherectomy increased from 34,732 (33%) procedures in 2011 to 75,435 (53%) procedures in 2019, and atherectomy became the dominant treatment strategy for femoropopliteal PAD. The relative utilization of stent placement (36,793 [35%] to 28,899 [20%]) and angioplasty only (34,398 [32%] to 38,228 [27%]) decreased concomitantly from 2011 to 2019. By 2019, the use of atherectomy was twofold higher in office-based laboratories than in the outpatient hospital setting (44,767 and 20,901, respectively). Treatment strategy varied by provider specialty in 2011 when cardiologists used atherectomy most frequently (17,925 [43%]), whereas radiologists used angioplasty alone (5,928 [6%]) and surgeons stented (18,009 [37%]) most frequently. By 2019, all specialties utilized atherectomy most frequently (29,564 [59%] for cardiology, 10,912 [58%] radiology, and 33,649 [47%] surgery). ConclusionsThe national approach to endovascular management of femoropopliteal PAD has changed since 2011 toward an implant-free strategy, including a multifold increase in the use of atherectomy. Discordant rates of atherectomy use between the ambulatory hospital and office-based settings highlight the need for comparative effectiveness studies to guide management.

Large-scale genetic correlation scanning and causal association between deep vein thrombosis and human blood metabolites

Deep vein thrombosis (DVT) refers to the abnormal coagulation of blood in a deep vein. Recently, some studies have found that metabolites are related to the occurrence of DVT and may serve as new markers for the diagnosis of DVT. In this study, we used the GWAS summary dataset of blood metabolites and DVT to perform a large-scale genetic correlation scan of DVT and blood metabolites to explore the correlation between blood metabolites and DVT. We used GWAS summary data of DVT from the UK Biobank (UK Biobank fields: 20002) and GWAS summary data of blood metabolites from a previously published study (including 529 metabolites in plasma or serum from 7824 adults from two European population studies) for genetic correlation analysis. Then, we conducted a causal study between the screened blood metabolites and DVT by Mendelian randomization (MR) analysis. In the first stage, genetic correlation analysis identified 9 blood metabolites that demonstrated a suggestive association with DVT. These metabolites included Valine (correlation coefficient = 0.2440, P value = 0.0430), Carnitine (correlation coefficient = 0.1574, P value = 0.0146), Hydroxytryptophan (correlation coefficient = 0.2376, P value = 0.0360), and 1-stearoylglycerophosphoethanolamine (correlation coefficient = − 0.3850, P value = 0.0258). Then, based on the IVW MR model, we analysed the causal relationship between the screened blood metabolites and DVT and found that there was a suggestive causal relationship between Hydroxytryptophan (exposure) and DVT (outcome) (β = − 0.0378, se = 0.0163, P = 0.0204). Our study identified a set of candidate blood metabolites that showed a suggestive association with DVT. We hope that our findings will provide new insights into the pathogenesis and diagnosis of DVT in the future.

The relationship between central obesity and bone mineral density: a Mendelian randomization study

BackgroundThe relationship between obesity and osteoporosis is an important public health issue. The goal of this study was to investigate whether and to what extent central obesity traits affect bone mineral density (BMD).MethodsWe conducted a two-sample Mendelian randomization analysis. Genomewide significant single nucleotide polymorphisms associated with waist circumference, hip circumference, waist-to-hip ratio, waist circumference adjusted by body mass index (WCadjBMI), hip circumference adjusted by BMI (HCadjBMI) and waist-to-hip ratio adjusted by BMI (WHRadjBMI) were obtained from a large-scale database containing 224,459 samples. The BMD summary dataset was obtained from a UK Biobank database including 265,627 participants.ResultsThe results provided strong evidence that the HCadjBMI trait was causally and negatively associated with BMD (β: − 0.135, 95% CI − 0.216 to − 0.054; P = 0.001), while the WHR trait was causally and positively associated with BMD (β: 0.194, 95% CI 0.062 to 0.325, P = 0.004). No significant effects were observed for other traits on BMD.ConclusionsThis study indicates variations in the abilities of different central obesity traits to influence BMD. These results should be considered in further studies and public health measures on obesity and osteoporosis prevention strategies.

Higher Genetically Predicted Triglycerides, LDL, and HDL Increase the Vitamin D Deficiency: A Mendelian Randomization Study.

IntroductionIt has been proven that high body mass index (BMI) levels can cause vitamin D deficiency, but the mechanism is still unclear. Therefore, this study attempts to explain this phenomenon from the perspective of blood lipid by using mendelian randomization (MR).MethodsGenome-wide association studies (GWAS) summary datasets for serum lipids were obtained from the Global Lipids Genetics Consortium (GLGC). Vitamin D deficiency outcome data were acquired from the UK Biobank samples. Single-variable MR (SVMR) and multi-variable MR (MVMR) analyses were conducted using the TwoSampleMR package based on R 4.0.3. The four main methods were the random-effect inverse-variance weighted (IVW), MR-Egger, weighted-median method, and weighted mode.ResultsIn the SVMR of serum lipid/apolipoprotein levels on serum vitamin D level, it was found that elevated serum triacylglycerol (IVW, OR = 0.85, 95%CI:0.81–0.89, P < 0.001), low-density lipoprotein (LDL) (IVW, OR = 0.93, 95%CI:0.90–0.95, P < 0.001), and high-density lipoprotein (HDL) (IVW, OR = 0.95, 95%CI:0.91–0.98, P < 0.001) levels all had a causal relationship with vitamin D deficiency, but significant pleiotropy was detected in the triacylglycerol (P = 0.001) and HDL (P = 0.003) analysis. MVMR analysis results were consistent with SVMR.ConclusionBy using single-variable mendelian randomization and multi-variable mendelian randomization methods, we identified that the elevated serum triacylglycerol, LDL, and HDL levels all had a causal relationship with vitamin D deficiency. Taking into account the significant pleiotropy demonstrated in this study, the conclusions of this study should be treated with caution.

An atlas of genetic correlations between gestational age and common psychiatric disorders.

We aim to systematically explore the potential genetic correlations between five major psychiatric disorders and gestational ages. Genome-wide association study (GWAS) summary datasets of attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) in discovery were downloaded from the Psychiatric GWAS Consortium (PGC) website. Suggestive (Raw p < 0.05) genetic associations in the discovery phrase were further replicated in independent GWASs which downloaded from PGC, the FinnGen study or Integrative Psychiatric Research (iPSYCH) website. GWASs of gestational duration, preterm and post-term birth were derived from previous studies of infants from the Early Growth Genetics (EGG) Consortium, the iPSYCH study, and the Genomic and Proteomic Network for Preterm Birth Research (GPN). We calculated genetic correlations using linkage disequilibrium score (LDSC) regression. Mendelian randomization (MR) analyses were performed to investigate the causal effects. We identified four suggestive genetic correlations between psychiatric disorders and gestational age factors in discovery LDSC and two replicated in a confirmation LDSC: gestational duration and ADHD (rg =-0.1405, FDR p=0.0406), post-term birth and SCZ (rg =-0.2003, FDR p=0.0042). We also observed causal effect of post-term birth on SCZ by MR (PWeighted median =0.037, PInverse variance weighted =0.007). Our analysis suggested no significant evidence of horizontal pleiotropy and heterogeneity. This study showed the genetic correlation evidences between gestational age phenotypes and psychiatric disorders, providing novel clues for understanding the pathogenic factors of common psychiatric disorders. LAY SUMMARY: Whereas gestational age factors were reported to be associated with psychiatric disorders, the genetic relationship and causality remain to be revealed. The present study reported the first large-scale genetic correlations investigation of the associations between gestational age phenotypes and psychiatric disorders. Results indicate causal relationships between post-term birth and schizophrenia (SCZ), as well as suggestive genetic correlations between gestational duration and attention deficit/hyperactivity disorder (ADHD). This study provided novel clues for understanding the pathogenic factors of common psychiatric disorders.

Gene-based association tests using GWAS summary statistics and incorporating eQTL

Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases via single marker tests, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose a powerful and computationally efficient gene-based association test, called Overall. Using extended Simes procedure, Overall aggregates information from three types of traditional gene-based association tests and also incorporates expression quantitative trait locus (eQTL) information into a gene-based association test using GWAS summary statistics. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the p values of Overall can be calculated analytically. Simulation studies show that Overall can control type I error rates very well and has higher power than the tests that we compared with. We also apply Overall to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that this newly developed method can identify more significant genes than other methods we compared with.

Assessing the role of blood pressure in amyotrophic lateral sclerosis: a Mendelian randomization study

BackgroundObservational studies have suggested a close but controversial relationship between blood pressure (BP) and amyotrophic lateral sclerosis (ALS). It remains unclear whether this association is causal. The authors employed a bidirectional two-sample Mendelian randomization (MR) approach to evaluate the causal relationship between BP and ALS. Genetic proxies for systolic blood pressure (SBP), diastolic blood pressure (DBP), antihypertensive drugs (AHDs), ALS, and their corresponding genome-wide association study (GWAS) summary datasets were obtained from the most recent studies with the largest sample sizes. The inverse variance weighted (IVW) method was adopted as the main approach to examine the effect of BP on ALS and four other MR methods were used for sensitivity analyses. To exclude the interference between SBP and DBP, a multivariable MR approach was used.ResultsWe found that genetically determined increased DBP was a protective factor for ALS (OR = 0.978, 95% CI 0.960–0.996, P = 0.017) and that increased SBP was an independent risk factor for ALS (OR = 1.014, 95% CI 1.003–1.025, P = 0.015), which is supported by sensitivity analyses. The use of calcium channel blocker (CCB) showed a causal relationship with ALS (OR = 0.985, 95% CI 0.971–1.000, P = 0.049). No evidence was revealed that ALS caused changes in BP.ConclusionsThis study provides genetic support for a causal effect of BP and ALS that increased DBP has a protective effect on ALS, and increased SBP is a risk factor for ALS, which may be related to sympathetic excitability. Blood pressure management is essential in ALS, and CCB may be a promising candidate.

A large-scale genetic correlation scan between rheumatoid arthritis and human plasma protein.

AimsThe aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA).MethodsBased on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls.ResultsWe found that seven kinds of plasma proteins had genetic correlations with RA, such as Soluble Receptor for Advanced Glycation End Products (sRAGE) (correlation coefficient = 0.2582, p = 0.049), vesicle transport protein USE1 (correlation coefficient = 0.1337, p = 0.018), and spermatogenesis-associated protein 20 (correlation coefficient = 0.3706, p = 0.018). There was a significant causal relationship between sRAGE and RA. By comparing the genes encoding seven plasma proteins, we found that only USE1 was a DEG associated with RA.ConclusionOur study identified a set of candidate plasma proteins that showed signals correlated with RA. Since the results of this study need further experimental verification, they should be interpreted with caution. However, we hope that this paper will provide new insights for the discovery of pathogenic genes and RA pathogenesis in the future.Cite this article: Bone Joint Res 2022;11(2):134–142.

Ribose-Map: A bioinformatics toolkit for ribonucleotide sequencing experiments

<h2>Abstract</h2> Current ribonucleotide mapping software is customized for data generated using only one type of ribonucleotide sequencing technique. To standardize the analysis of ribonucleotide sequencing experiments, we developed the bioinformatics toolkit, Ribose-Map. Through a series of analytical modules, Ribose-Map transforms raw sequencing data into summary datasets and publication-ready visualizations of results, allowing researchers to locate the genomic coordinates of ribonucleotides to single-nucleotide resolution, study the nucleotide sequence context of ribonucleotides, explore their genome-wide distribution, and identify hotspots of ribonucleotide incorporation. Ribose-Map does not require background knowledge of ribonucleotide sequencing analysis and assumes only basic command-line skills. Ribose-Map is available at https://github.com/agombolay/ribose-map.

Global reference seismological data sets: multimode surface wave dispersion

SUMMARYGlobal variations in the propagation of fundamental-mode and overtone surface waves provide unique constraints on the low-frequency source properties and structure of the Earth’s upper mantle, transition zone and mid mantle. We construct a reference data set of multimode dispersion measurements by reconciling large and diverse catalogues of Love-wave (49.65 million) and Rayleigh-wave dispersion (177.66 million) from eight groups worldwide. The reference data set summarizes measurements of dispersion of fundamental-mode surface waves and up to six overtone branches from 44 871 earthquakes recorded on 12 222 globally distributed seismographic stations. Dispersion curves are specified at a set of reference periods between 25 and 250 s to determine propagation-phase anomalies with respect to a reference Earth model. Our procedures for reconciling data sets include: (1) controlling quality and salvaging missing metadata; (2) identifying discrepant measurements and reasons for discrepancies; (3) equalizing geographic coverage by constructing summary rays for travel-time observations and (4) constructing phase velocity maps at various wavelengths with combination of data types to evaluate inter-dataset consistency. We retrieved missing station and earthquake metadata in several legacy compilations and codified scalable formats to facilitate reproducibility, easy storage and fast input/output on high-performance-computing systems. Outliers can be attributed to cycle skipping, station polarity issues or overtone interference at specific epicentral distances. By assessing inter-dataset consistency across similar paths, we empirically quantified uncertainties in traveltime measurements. More than 95 per cent measurements of fundamental-mode dispersion are internally consistent, but agreement deteriorates for overtones especially branches 5 and 6. Systematic discrepancies between raw phase anomalies from various techniques can be attributed to discrepant theoretical approximations, reference Earth models and processing schemes. Phase-velocity variations yielded by the inversion of the summary data set are highly correlated (R ≥ 0.8) with those from the quality-controlled contributing data sets. Long-wavelength variations in fundamental-mode dispersion (50–100 s) are largely independent of the measurement technique with high correlations extending up to degree ∼25. Agreement degrades with increasing branch number and period; highly correlated structure is found only up to degree ∼10 at longer periods (T &amp;gt; 150 s) and up to degree ∼8 for overtones. Only 2ζ azimuthal variations in phase velocity of fundamental-mode Rayleigh waves were required by the reference data set; maps of 2ζ azimuthal variations are highly consistent between catalogues ( R = 0.6–0.8). Reference data with uncertainties are useful for improving existing measurement techniques, validating models of interior structure, calculating teleseismic data corrections in local or multiscale investigations and developing a 3-D reference Earth model.