Over the past decade, mtDNA-Server established itself as one of the most widely used variant calling web-services for human mitochondrial genomes. The service accepts sequencing data in BAM format ...and returns an annotated variant analysis report for both homoplasmic and heteroplasmic variants. In this work we present mtDNA-Server 2, which includes several new features highly requested by the community. Most importantly, it includes (a) the integration of a novel variant calling mode that accurately call insertions, deletions and single nucleotide variants at once, (b) the integration of additional quality control and input validation modules, (c) a method to estimate the required coverage to minimize false positives and (d) an interactive analytics dashboard. Furthermore, we migrated the complete analysis workflow to the Nextflow workflow manager for improved parallelization, reproducibility and local execution. Recognizing the importance of insertions and deletions as well as offering novel quality control, validation and reporting features, mtDNA-Server 2 provides researchers and clinicians a new state-of-the-art analysis platform for interpreting mitochondrial genomes. mtDNA-Server 2 is available via mitoverse, our analysis platform that offers a centralized place for mtDNA analysis in the cloud. The web-service, source code and its documentation are freely accessible at https://mitoverse.i-med.ac.at.
High-throughput genotyping and phenotyping projects of large epidemiological study populations require sophisticated laboratory information management systems. Most epidemiological studies include ...subject-related personal information, which needs to be handled with care by following data privacy protection guidelines. In addition, genotyping core facilities handling cooperative projects require a straightforward solution to monitor the status and financial resources of the different projects.
We developed a database system for an efficient combination and management of phenotypes and genotypes (eCOMPAGT) deriving from genetic epidemiological studies. eCOMPAGT securely stores and manages genotype and phenotype data and enables different user modes with different rights. Special attention was drawn on the import of data deriving from TaqMan and SNPlex genotyping assays. However, the database solution is adjustable to other genotyping systems by programming additional interfaces. Further important features are the scalability of the database and an export interface to statistical software.
eCOMPAGT can store, administer and connect phenotype data with all kinds of genotype data and is available as a downloadable version at (http://dbis-informatik.uibk.ac.at/ecompagt).
Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations ...(CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs.
CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data.
CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at http://genepi-conan.i-med.ac.at.
After an increase in
infections (CDI) until 2013 due to epidemic ribotypes such as 027 and 078, CDI incidence in Germany is now declining, as confirmed by recent epidemiological data. Despite this ...success through antimicrobial stewardship and hospital hygiene, the burden of disease remains high, especially in older patients (>65 years) with comorbidities. The main risk factor for CDI is the use of broad-spectrum antibiotics, which disrupt the gut microbiota, allowing
colonization. Coinfection with other intestinal pathogens such as enterococci can further increase the virulence of
. The updated 2021 ESCMID guidelines recommend fidaxomicin instead of vancomycin as the antibiotic of choice for the treatment of CDI because of its lower recurrence rate. Vancomycin remains a good alternative; however, metronidazole should only be used if neither antibiotic is available. In the future, ridinilazole may be available as another therapeutic option that has a narrow spectrum of activity and low intestinal absorption. For the treatment of recurrent CDI, the new guidelines also include the use of the monoclonal antibody bezlotoxumab. In addition, a new oral microbiome therapy, SER-109 (capsules containing purified Firmicutes spores), which showed promising results in a phase 3 study, may provide an easy-to-administer alternative to fecal microbiota transplantation. Hopes for a well-performing toxoid vaccine for primary and secondary prevention of CDI have unfortunately not been fulfilled in the CLOVER trial.
Background
Comorbidities including ischemic heart disease (IHD) worsen outcomes after SARS‐CoV‐2 infections. High lipoprotein(a) Lp(a) concentrations are a strong risk factor for IHD and possibly for ...thromboembolic events. We therefore evaluated whether SARS‐CoV‐2 infections modify the risk of high Lp(a) concentrations for IHD or thromboembolic events during the first 8.5 months follow‐up of the pandemic.
Method
Cohort study using data from the UK Biobank during the SARS‐CoV‐2 pandemic. Baseline Lp(a) was compared between SARS‐CoV‐2 positive patients and the population controls.
Results
SARS‐CoV‐2 positive patients had Lp(a) concentrations similar to the population controls. The risk for IHD increased with higher Lp(a) concentrations in both, the population controls (n = 435,104) and SARS‐CoV‐2 positive patients (n = 6937). The causality of the findings was supported by a genetic risk score for Lp(a). A SARS‐CoV‐2 infection modified the association with a steeper increase in risk for infected patients (interaction p‐value = 0.03). Although SARS‐CoV‐2 positive patients had a five‐times higher frequency of thromboembolic events compared to the population controls (1.53% vs. 0.31%), the risk was not influenced by Lp(a).
Conclusions
SARS‐CoV‐2 infections enforce the association between high Lp(a) and IHD but the risk for thromboembolic events is not influenced by Lp(a).
Genetic risk scores for common diseases as myocardial infarction (MI) gain increasing attention for individual's risk prediction. One might wonder if assessing family history becomes redundant. It ...was the aim of this study to evaluate the amount of shared information between family history and genetic risk scores and to assess their independent and combined effects on prevalent and incident MI risk.
A genome wide polygenic risk score (PGS) and one family risk score (FamRS) were calculated in a population-based study from Southern Germany (n = 3071) with up to 11 years of follow-up. Logistic and Cox Regression models were used adjusting for lifestyle and classical risk factors.
A right shift in MI risk for increasing values of PGS was found, with.
considerably increasing ORs along the top quantiles of PGS (OR = 3.03 for top 10%; OR = 5.55 for top 2.5%). The PGS was not associated with incident MI cases, though. The FamRS was significantly associated with both prevalent and incident MI cases with an OR of 2.9 for participants with a strong positive family history compared to average. ORs and HRs did hardly change in a combined model including both measures, indicating independent contribution to MI risk. The simultaneous addition of PGS and FamRS to a model including classical risk factors significantly enhanced prediction for prevalent cases and non-cases (p = 3.28 × 10−5).
These findings emphasize that both genetic information and family history are relevant for the determination of MI risk and that neither of them can replace the other.
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•A genome-wide polygenic risk score (PGS) was shown to be a strong risk predictor for especially “early” prevalent myocardial infarction (MI) cases.•A family risk score (FamRS) was a stronger predictor than simpler family history measures as “diseased parents”.•The FamRS was highly informative for both prevalence and incidence.•Addition of PGS and FamRS to a model including classical risk factors enhanced prediction for prevalent cases and non-cases.
Abstract
The detection of contamination is key in all types of sequencing studies, especially for mitochondrial (mtDNA) studies. Contamination can lead to genotype misclassification and ultimately ...false-positive associations. In mtDNA studies, contamination is usually detected by applying computational expensive approaches using nuclear DNA (nDNA) reads. Here, we describe a novel approach that relies on the unique properties of the small mitochondrial genome to detect contamination fast and accurately.
Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with ...the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.
High lipoprotein(a) Lp(a) concentrations are associated with increased coronary artery disease (CAD) risk. Lp(a) is regulated mainly genetically by the LPA gene but involved genetic variants have not ...been fully elucidated. Improved understanding of the entanglements of genetic Lp(a) regulation may enhance genetic prediction of Lp(a) and CAD risk. We investigated an interaction between the well-known LPA missense SNP rs41272110 (known as Thr3888Pro) and the frequent LPA splicing mutation KIV-2 4925G>A.
Effects on Lp(a) concentrations were investigated by multiple quantile regression in the German Chronic Kidney Disease (GCKD) study, KORA-F3 and KORA-F4 (ntotal = 10,405) as well as in the UK Biobank (UKB) 200k exome dataset (n = 173,878). The impact of the interaction on CAD risk was assessed by survival analysis in UKB.
We observed a significant SNP-SNP interaction in all studies (p = 1.26e-05 to 3.03e-04). In quantile regression analysis, rs41272110 as a predictor shows no impact on Lp(a) (β = −0.06 -0.79; 0.68, p = 0.879), but in a joint model including both SNPs as predictors, rs41272110 is associated with markedly higher Lp(a) (β = +9.40 mg/dL 6.45; 12.34, p = 4.07e-10). Similarly, rs41272110 shows no effect on CAD in UKB (HR = 1.01 0.97; 1.04, p = 0.731), while rs41272110 carriers not carrying 4925G>A show an increased CAD risk (HR = 1.10 1.04; 1.16, p = 6.9e-04). This group corresponds to 4% of the population. Adjustment for apolipoprotein(a) isoforms further modified the effect estimates markedly.
This work emphasizes the complexity of the genetic regulation of Lp(a) and the importance to account for genetic subgroups in Lp(a) association studies and when interpreting genetic cardiovascular risk profiles.
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•Effect of rs41272110 on Lp(a) and coronary artery disease (CAD) depends on the genotype of the 4925G>A.•Adjusting for 4925G>A reveals a missed Lp(a)-increasing effect of rs41272110.•Lp(a)-increasing effect increases CAD risk and affects 4% of the population.•Not accounted interactions of LPA variants can hide effects on CAD risk.
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with ...circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta-GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations.
We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis.
Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9, APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16-1.72, p < 0.001) higher risk for incident CAD.
We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected.
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