115 research outputs found

    Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

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    Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior–posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = −0.02, SE = 0.004, P-value = 2.10 × 10(−8)). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10(−4)). In exome-array single-variant analysis (P-value threshold = 9 × 10(−7)), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10(−5)). In the gene-based analysis (P-value threshold = 1.85 × 10(−6)), PCSK5 showed an association with AAD (P-value = 8.03 × 10(−7)). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = −0.003, P-value = 0.02), triglycerides (beta = −0.16, P-value = 0.008) and height (beta = 0.03, P-value < 0.0001), known risk factors for AAA, consistent with a causal association with AAD. Our findings point to new biology as well as highlighting gene regions in mechanisms that have previously been implicated in the genetics of other vascular diseases

    A Factor Graph Nested Effects Model To Identify Networks from Genetic Perturbations

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    Complex phenotypes such as the transformation of a normal population of cells into cancerous tissue result from a series of molecular triggers gone awry. We describe a method that searches for a genetic network consistent with expression changes observed under the knock-down of a set of genes that share a common role in the cell, such as a disease phenotype. The method extends the Nested Effects Model of Markowetz et al. (2005) by using a probabilistic factor graph to search for a network representing interactions among these silenced genes. The method also expands the network by attaching new genes at specific downstream points, providing candidates for subsequent perturbations to further characterize the pathway. We investigated an extension provided by the factor graph approach in which the model distinguishes between inhibitory and stimulatory interactions. We found that the extension yielded significant improvements in recovering the structure of simulated and Saccharomyces cerevisae networks. We applied the approach to discover a signaling network among genes involved in a human colon cancer cell invasiveness pathway. The method predicts several genes with new roles in the invasiveness process. We knocked down two genes identified by our approach and found that both knock-downs produce loss of invasive potential in a colon cancer cell line. Nested effects models may be a powerful tool for inferring regulatory connections and genes that operate in normal and disease-related processes

    Rare germline copy number variants (CNVs) and breast cancer risk.

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    Funder: CIHRGermline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance

    Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

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    Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10 ) and AC058822.1 (P = 1.47 × 10 ), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10 ), demonstrating the importance of diversifying study cohorts. [Abstract copyright: © 2023. The Author(s).

    Early mobilisation in intensive care units in Australia and Scotland:A prospective, observational cohort study examining mobilisation practises and barriers

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    Introduction: Mobilisation of patients in the intensive care unit (ICU) is an area of growing research. Currently, there is\ud little data on baseline mobilisation practises and the barriers to them for patients of all admission diagnoses.\ud Methods: The objectives of the study were to (1) quantify and benchmark baseline levels of mobilisation in Australian\ud and Scottish ICUs, (2) compare mobilisation practises between Australian and Scottish ICUs and (3) identify barriers to\ud mobilisation in Australian and Scottish ICUs. We conducted a prospective, observational, cohort study with a 4-week\ud inception period. Patients were censored for follow-up upon ICU discharge or after 28 days, whichever occurred first.\ud Patients were included if they were >18 years of age, admitted to an ICU and received mechanical ventilation in the ICU.\ud Results: Ten tertiary ICUs in Australia and nine in Scotland participated in the study. The Australian cohort had a large\ud proportion of patients admitted for cardiothoracic surgery (43.3 %), whereas the Scottish cohort had none. Therefore,\ud comparison analysis was done after exclusion of patients admitted for cardiothoracic surgery. In total, 60.2 % of the 347\ud patients across 10 Australian ICUs and 40.1 % of the 167 patients across 9 Scottish ICUs mobilised during their ICU stay\ud (p < 0.001). Patients in the Australian cohort were more likely to mobilise than patients in the Scottish cohort (hazard\ud ratio 1.83, 95 % confidence interval 1.38–2.42). However, the percentage of episodes of mobilisation where patients\ud were receiving mechanical ventilation was higher in the Scottish cohort (41.1 % vs 16.3 %, p < 0.001). Sedation was the\ud most commonly reported barrier to mobilisation in both the Australian and Scottish cohorts. Physiological instability\ud and the presence of an endotracheal tube were also frequently reported barriers.\ud Conclusions: This is the first study to benchmark baseline practise of early mobilisation internationally, and it\ud demonstrates variation in early mobilisation practises between Australia and Scotland

    A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

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    Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10-8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers

    Measurements of ψ(2S) and X(3872) → J/ψπ+π− production in pp collisions at √s=8 TeV with the ATLAS detector

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    Differential cross sections are presented for the prompt and non-prompt production of the hidden-charm states X(3872) and ψ(2S), in the decay mode J/ψπ+π−, measured using 11.4 fb−1 of pp collisions at √s=8 TeV by the ATLAS detector at the LHC. The ratio of cross-sections X(3872)/ψ(2S) is also given, separately for prompt and non-prompt components, as well as the non-prompt fractions of X(3872) and ψ(2S). Assuming independent single effective lifetimes for non-prompt X(3872) and ψ(2S) production gives RB=B(B→X(3872)+any)B(X(3872)→J/ψπ+π−)B(B→ψ(2S)+any)B(ψ(2S)→J/ψπ+π−)=(3.95±0.32(stat)±0.08(sys))×10−2RB=B(B→X(3872)+any)B(X(3872)→J/ψπ+π−)B(B→ψ(2S)+any)B(ψ(2S)→J/ψπ+π−)=(3.95±0.32(stat)±0.08(sys))×10−2 separating short- and long-lived contributions, assuming that the short-lived component is due to Bc decays, gives RB = (3.57 ± 0.33(stat) ± 0.11(sys)) × 10−2, with the fraction of non-prompt X(3872) produced via Bc decays for pT(X(3872)) > 10 GeV being (25 ± 13(stat) ± 2(sys) ± 5(spin))%. The distributions of the dipion invariant mass in the X(3872) and ψ(2S) decays are also measured and compared to theoretical predictions
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