94 research outputs found

    C-reactive protein upregulates the whole blood expression of CD59 - an integrative analysis

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    Elevated C-reactive protein (CRP) concentrations in the blood are associated with acute and chronic infections and inflammation. Nevertheless, the functional role of increased CRP in multiple bacterial and viral infections as well as in chronic inflammatory diseases remains unclear. Here, we studied the relationship between CRP and gene expression levels in the blood in 491 individuals from the Estonian Biobank cohort, to elucidate the role of CRP in these inflammatory mechanisms. As a result, we identified a set of 1,614 genes associated with changes in CRP levels with a high proportion of interferon-stimulated genes. Further, we performed likelihood-based causality model selection and Mendelian randomization analysis to discover causal links between CRP and the expression of CRP-associated genes. Strikingly, our computational analysis and cell culture stimulation assays revealed increased CRP levels to drive the expression of complement regulatory protein CD59, suggesting CRP to have a critical role in protecting blood cells from the adverse effects of the immune defence system. Our results show the benefit of integrative analysis approaches in hypothesis-free uncovering of causal relationships between traits.</p

    Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome.

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    Comparing transcript levels between healthy and diseased individuals allows the identification of differentially expressed genes, which may be causes, consequences or mere correlates of the disease under scrutiny. We propose a method to decompose the observational correlation between gene expression and phenotypes driven by confounders, forward- and reverse causal effects. The bi-directional causal effects between gene expression and complex traits are obtained by Mendelian Randomization integrating summary-level data from GWAS and whole-blood eQTLs. Applying this approach to complex traits reveals that forward effects have negligible contribution. For example, BMI- and triglycerides-gene expression correlation coefficients robustly correlate with trait-to-expression causal effects (r &lt;sub&gt;BMI &lt;/sub&gt; = 0.11, P &lt;sub&gt;BMI &lt;/sub&gt; = 2.0 × 10 &lt;sup&gt;-51&lt;/sup&gt; and r &lt;sub&gt;TG &lt;/sub&gt; = 0.13, P &lt;sub&gt;TG &lt;/sub&gt; = 1.1 × 10 &lt;sup&gt;-68&lt;/sup&gt; ), but not detectably with expression-to-trait effects. Our results demonstrate that studies comparing the transcriptome of diseased and healthy subjects are more prone to reveal disease-induced gene expression changes rather than disease causing ones

    An exploratory phenome wide association study linking asthma and liver disease genetic variants to electronic health records from the Estonian Biobank

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    <div><p>The Estonian Biobank, governed by the Institute of Genomics at the University of Tartu (Biobank), has stored genetic material/DNA and continuously collected data since 2002 on a total of 52,274 individuals representing ~5% of the Estonian adult population and is increasing. To explore the utility of data available in the Biobank, we conducted a phenome-wide association study (PheWAS) in two areas of interest to healthcare researchers; asthma and liver disease. We used 11 asthma and 13 liver disease-associated single nucleotide polymorphisms (SNPs), identified from published genome-wide association studies, to test our ability to detect established associations. We confirmed 2 asthma and 5 liver disease associated variants at nominal significance and directionally consistent with published results. We found 2 associations that were opposite to what was published before (rs4374383:AA increases risk of NASH/NAFLD, rs11597086 increases ALT level). Three SNP-diagnosis pairs passed the phenome-wide significance threshold: rs9273349 and E06 (thyroiditis, p = 5.50x10<sup>-8</sup>); rs9273349 and E10 (type-1 diabetes, p = 2.60x10<sup>-7</sup>); and rs2281135 and K76 (non-alcoholic liver diseases, including NAFLD, p = 4.10x10<sup>-7</sup>). We have validated our approach and confirmed the quality of the data for these conditions. Importantly, we demonstrate that the extensive amount of genetic and medical information from the Estonian Biobank can be successfully utilized for scientific research.</p></div

    Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries (Nature, (2022), 611, 7934, (115-123), 10.1038/s41586-022-05165-3)

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    In the version of this article initially published, the name of the PRECISE4Q Consortium was misspelled as “PRECISEQ” and has now been amended in the HTML and PDF versions of the article. Further, data in the first column of Supplementary Table 55 were mistakenly shifted and have been corrected in the file accompanying the HTML version of the article

    Comparison of Antibody Repertoires Produced by HIV-1 Infection, Other Chronic and Acute Infections, and Systemic Autoimmune Disease

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    Background Antibodies (Abs) produced during HIV-1 infection rarely neutralize a broad range of viral isolates; only eight broadly-neutralizing (bNt) monoclonal (M)Abs have been isolated. Yet, to be effective, an HIV-1 vaccine may have to elicit the essential features of these MAbs. The V genes of all of these bNt MAbs are highly somatically mutated, and the VH genes of five of them encode a long (≄20 aa) third complementarity-determining region (CDR-H3). This led us to question whether long CDR-H3s and high levels of somatic mutation (SM) are a preferred feature of anti-HIV bNt MAbs, or if other adaptive immune responses elicit them in general. Methodology and Principal Findings We assembled a VH-gene sequence database from over 700 human MAbs of known antigen specificity isolated from chronic (viral) infections (ChI), acute (bacterial and viral) infections (AcI), and systemic autoimmune diseases (SAD), and compared their CDR-H3 length, number of SMs and germline VH-gene usage. We found that anti-HIV Abs, regardless of their neutralization breadth, tended to have long CDR-H3s and high numbers of SMs. However, these features were also common among Abs associated with other chronic viral infections. In contrast, Abs from acute viral infections (but not bacterial infections) tended to have relatively short CDR-H3s and a low number of SMs, whereas SAD Abs were generally intermediate in CDR-H3 length and number of SMs. Analysis of VH gene usage showed that ChI Abs also tended to favor distal germline VH-genes (particularly VH1-69), especially in Abs bearing long CDR-H3s. Conclusions and Significance The striking difference between the Abs produced during chronic vs. acute viral infection suggests that Abs bearing long CDR-H3s, high levels of SM and VH1-69 gene usage may be preferentially selected during persistent infection

    Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

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    Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits
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