32 research outputs found
Real time quaking-induced conversion analysis of cerebrospinal fluid in sporadic Creutzfeldt-Jakob disease
OBJECTIVE: Current cerebrospinal fluid (CSF) tests for sporadic Creutzfeldt-Jakob disease (sCJD) are based on the detection of surrogate markers of neuronal damage such as CSF 14-3-3 which are not specific for sCJD. A number of prion protein conversion assays have been developed, including real-time quaking induced conversion (RT-QuIC). The objective of this study is to investigate whether CSF RT-QuIC analysis could be used as a diagnostic test in sCJD. METHODS: An exploratory study was undertaken which analysed 108 CSF samples from patients with neuropathologically confirmed sCJD or from control patients. Of the 108 CSF samples 56 were from sCJD patients (30 female, 26 male, aged 31–84 years; 62.3 ± 13.5 years) and 52 were from control patients (26 female, 26 male, aged 43–84 years; 67.8 ± 10.4 years). A confirmatory group of 118 patients were subsequently examined which consisted of 67 cases of neuropathologically confirmed sCJD (33 female, 34 male, aged 39–82 years; 67.5 ± 9.0 years) and 51 control cases (26 female, 25 male, aged 36–87 years; 63.5 ± 11.6 years). RESULTS: The exploratory study showed that RT-QuIC analysis had a sensitivity of 91% and a specificity of 98% for the diagnosis of sCJD. These results were confirmed in the confirmatory study which showed that CSF RT-QuIC analysis had a sensitivity and specificity of 87% and 100% respectively. INTERPRETATION: This study shows that CSF RT-QuIC analysis has the potential to be a more specific diagnostic test for sCJD than current CSF tests
Alpha-synuclein RT-QuIC in the CSF of patients with alpha-synucleinopathies
We have developed a novel real-time quaking-induced conversion RT-QuICbased assay to detect alpha-synuclein aggregation in brain and cerebrospinal fluid from dementia with Lewy bodies and Parkinson’s disease patients. This assay can detect alpha-synuclein aggregation in Dementia with Lewy bodies and Parkinson’s disease cerebrospinal fluid with sensitivities of 92% and 95%, respectively, and with an overall specificity of 100% when compared to Alzheimer and control cerebrospinal fluid. Patients with neuropathologically confirmed tauopathies (progressive supranuclear palsy; corticobasal degeneration) gave negative results. These results suggest that RT-QuiC analysis of cerebrospinal fluid is potentially useful for the early clinical assessment of patients with alpha-synucleinopathies
Cerebrospinal fluid real-time quaking-induced conversion is a robust and reliable test for sporadic creutzfeldt–jakob disease:An international study
Real-time quaking-induced conversion (RT-QuIC) has been proposed as a sensitive diagnostic test for sporadic Creutzfeldt\u2013Jakob disease; however, before this assay can be introduced into clinical practice, its reliability and reproducibility need to be demonstrated. Two international ring trials were undertaken in which a set of 25 cerebrospinal fluid samples were analyzed by a total of 11 different centers using a range of recombinant prion protein substrates and instrumentation. The results show almost complete concordance between the centers and demonstrate that RT-QuIC is a suitably reliable and robust technique for clinical practice. Ann Neurol 2016;80:160\u2013165
Prion-specific and surrogate CSF biomarkers in Creutzfeldt-Jakob disease:diagnostic accuracy in relation to molecular subtypes and analysis of neuropathological correlates of p-tau and A beta 42 levels
The differential diagnosis of Creutzfeldt-Jakob disease (CJD) from other, sometimes treatable, neurological disorders is challenging, owing to the wide phenotypic heterogeneity of the disease. Real-time quaking-induced prion conversion (RT-QuIC) is a novel ultrasensitive in vitro assay, which, at variance with surrogate neurodegenerative biomarker assays, specifically targets the pathological prion protein (PrPSc). In the studies conducted to date in CJD, cerebrospinal fluid (CSF) RT-QuIC showed good diagnostic sensitivity (82\u201396%) and virtually full specificity. In the present study, we investigated the diagnostic value of both prion RT-QuIC and surrogate protein markers in a large patient population with suspected CJD and then evaluated the influence on CSF findings of the CJD type, and the associated amyloid-\u3b2 (A\u3b2) and tau neuropathology. RT-QuIC showed an overall diagnostic sensitivity of 82.1% and a specificity of 99.4%. However, sensitivity was lower in CJD types linked to abnormal prion protein (PrPSc) type 2 (VV2, MV2K and MM2C) than in typical CJD (MM1). Among surrogate proteins markers (14-3-3, total (t)-tau, and t-tau/phosphorylated (p)-tau ratio) t-tau performed best in terms of both specificity and sensitivity for all sCJD types. Sporadic CJD VV2 and MV2K types demonstrated higher CSF levels of p-tau when compared to other sCJD types and this positively correlated with the amount of tiny tau deposits in brain areas showing spongiform change. CJD patients showed moderately reduced median A\u3b242 CSF levels, with 38% of cases having significantly decreased protein levels in the absence of A\u3b2 brain deposits. Our results: (1) support the use of both RT-QuIC and t-tau assays as first line laboratory investigations for the clinical diagnosis of CJD; (2) demonstrate a secondary tauopathy in CJD subtypes VV2 and MV2K, correlating with increased p-tau levels in the CSF and (3) provide novel insight into the issue of the accuracy of CSF p-tau and A\u3b242 as markers of brain tauopathy and \u3b2-amyloidosis
Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.
To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC
Identification of six new susceptibility loci for invasive epithelial ovarian cancer.
Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 ] HEALTH ]F2 ]2009 ]223175). The CIMBA data management and data
analysis were supported by Cancer Research.UK grants 12292/A11174 and C1287/A10118. The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research
Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME ]ON Post ]GWAS Initiative (U19 ]CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data
generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The cBio portal is developed and maintained by the Computational Biology Center at Memorial Sloan ] Kettering Cancer Center. SH is supported by an NHMRC Program Grant to GCT. Details of the funding of individual investigators and studies are provided in the Supplementary Note. This study made use of data generated by the Wellcome Trust Case Control consortium, funding for which was provided by the Wellcome Trust under award 076113. The results published here are, in part, based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancerhttp://dx.doi.org/10.1038/ng.3185This is the Author Accepted Manuscript of 'Identification of six new susceptibility loci for invasive epithelial ovarian cancer' which was published in Nature Genetics 47, 164–171 (2015) © Nature Publishing Group - content may only be used for academic research
Finishing the euchromatic sequence of the human genome
The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead
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Variation in NF-Â B Signaling Pathways and Survival in Invasive Epithelial Ovarian Cancer
Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that impact prognosis are not known. The nuclear factor-kappa B (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance—p < 2.5×10−5). Results were statistically significant when assessed for patients of a single histology. Key associations were with CARD11 (caspase recruitment domain family, member 11) rs41324349 in patients with mucinous EOC (HR 1.82, 95% CI 1.41–2.35, p=4.13×10−6) and TNFRSF13B (tumor necrosis factor receptor superfamily, member 13B) rs7501462 in patients with endometrioid EOC (HR 0.68, 95% CI 0.56–0.82, p=2.33×10−5). Other associations of note included TRAF2 (TNF receptor-associated factor 2) rs17250239 in patients with high-grade serous EOC (HR 0.84, 95% CI 0.77–0.92, p=6.49×10−5) and PLCG1 (phospholipase C, gamma 1) rs11696662 in patients with clear cell EOC (HR 0.43, 95% CI 0.26–0.73, p=4.56×10−4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies
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Genome-wide Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes: Findings from the Ovarian Cancer Association Consortium
PURPOSE: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome.
EXPERIMENTAL DESIGN: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥ 4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis.
RESULTS: Five SNPs were significantly associated (P ≤ 1.0 × 10(-5)) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10(-6)). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤ 6 × 10(-3)).
CONCLUSIONS: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies.Other Research Uni
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Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk
BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations.
METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).
RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.
CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.
IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization