| 1. |
- Birney, Ewan, et al.
(author)
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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project
- 2007
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 447:7146, s. 799-816
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Journal article (peer-reviewed)abstract
- We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
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| 2. |
- Euskirchen, Ghia M, et al.
(author)
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Mapping of transcription factor binding regions in mammalian cells by ChIP : comparison of array- and sequencing-based technologies.
- 2007
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In: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 17:6, s. 898-909
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Journal article (peer-reviewed)abstract
- Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides >/=50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%-86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies.
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| 3. |
- Jackson, C. E., et al.
(author)
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Albuminuria in chronic heart failure: prevalence and prognostic importance
- 2009
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In: Lancet. - 1474-547X. ; 374:9689, s. 543-50
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Journal article (peer-reviewed)abstract
- BACKGROUND: Increased excretion of albumin in urine might be a marker of the various pathophysiological changes that arise in patients with heart failure. Therefore our aim was to assess the prevalence and prognostic value of a spot urinary albumin to creatinine ratio (UACR) in patients with heart failure. METHODS: UACR was measured at baseline and during follow-up of 2310 patients in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) Programme. The prevalence of microalbuminuria and macroalbuminuria, and the predictive value of UACR for the primary composite outcome of each CHARM study--ie, death from cardiovascular causes or admission to hospital with worsening heart failure--and death from any cause were assessed. FINDINGS: 1349 (58%) patients had a normal UACR, 704 (30%) had microalbuminuria, and 257 (11%) had macroalbuminuria. The prevalence of increased UACR was similar in patients with reduced and preserved left ventricular ejection fractions. Patients with an increased UACR were older, had more cardiovascular comorbidity, worse renal function, and a higher prevalence of diabetes mellitus than did those with normoalbuminuria. However, a high prevalence of increased UACR was still noted among patients without diabetes, hypertension, or renal dysfunction. Elevated UACR was associated with increased risk of the composite outcome and death even after adjustment for other prognostic variables including renal function, diabetes, and haemoglobin A1c. The adjusted hazard ratio (HR) for the composite outcome in patients with microalbuminuria versus normoalbuminuria was 1.43 (95% CI 1.21-1.69; p<0.0001) and for macroalbuminuria versus normoalbuminuria was 1.75 (1.39-2.20; p<0.0001). The adjusted values for death were 1.62 (1.32-1.99; p<0.0001) for microalbuminuria versus normoalbuminuria, and 1.76 (1.32-2.35; p=0.0001) for macroalbuminuria versus normoalbuminuria. Treatment with candesartan did not reduce or prevent the development of excessive excretion of urinary albumin. INTERPRETATION: Increased UACR is a powerful and independent predictor of prognosis in heart failure. FUNDING: AstraZeneca.
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| 4. |
- Preiss, D., et al.
(author)
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Predictors of development of diabetes in patients with chronic heart failure in the Candesartan in Heart Failure Assessment of Reduction in Mortality and Morbidity (CHARM) program
- 2009
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In: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 32:5, s. 915-20
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Journal article (peer-reviewed)abstract
- OBJECTIVE: The purpose of this study was to identify predictors of incident diabetes during follow-up of nondiabetic patients with chronic heart failure (CHF) in the Candesartan in Heart Failure Assessment of Reduction in Mortality and Morbidity (CHARM) program. RESEARCH DESIGN AND METHODS: A total of 1,620 nondiabetic patients had full baseline datasets. We compared baseline demographic, medication, and laboratory data for patients who did or did not develop diabetes and conducted logistic regression and receiver operator characteristic curve analyses. RESULTS: Over a median period of 2.8 years, 126 of the 1,620 patients (7.8%) developed diabetes. In multiple logistic regression analysis, the following baseline characteristics were independently associated with incident diabetes in decreasing order of significance by stepwise selection: higher A1C (odds ratio [OR] 1.78 per 1 SD increase; P < 0.0001), higher BMI (OR 1.64 per 1 SD increase; P < 0.0001), lipid-lowering therapy (OR 2.05; P = 0.0005), lower serum creatinine concentration (OR 0.68 per 1 SD increase; P = 0.0018), diuretic therapy (OR 4.81; P = 0.003), digoxin therapy (OR 1.65; P = 0.022), higher serum alanine aminotransferase concentration (OR 1.15 per 1 SD increase; P = 0.027), and lower age (OR 0.81 per 1 SD increase; P = 0.048). Using receiver operating characteristic curve analysis, A1C and BMI yielded areas under the curve of 0.723 and 0.712, respectively, increasing to 0.788 when combined. Addition of other variables independently associated with diabetes risk minimally improved prediction of diabetes. CONCLUSIONS: In nondiabetic patients with CHF in CHARM, A1C and BMI were the strongest predictors of the development of diabetes. Other minor predictors in part reflected CHF severity or drug-associated diabetes risk. Identifying patients with CHF at risk of diabetes through simple criteria appears possible and could enable targeted preventative measures.
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| 5. |
- Royce, Thomas E., et al.
(author)
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Extrapolating traditional DNA microarray statistics to tiling and protein microarray technologies
- 2006
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In: Methods in Enzymology. - 0076-6879 .- 1557-7988. ; 411, s. 282-311
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Journal article (peer-reviewed)abstract
- A credit to microarray technology is its broad application. Two experiments--the tiling microarray experiment and the protein microarray experiment--are exemplars of the versatility of the microarrays. With the technology's expanding list of uses, the corresponding bioinformatics must evolve in step. There currently exists a rich literature developing statistical techniques for analyzing traditional gene-centric DNA microarrays, so the first challenge in analyzing the advanced technologies is to identify which of the existing statistical protocols are relevant and where and when revised methods are needed. A second challenge is making these often very technical ideas accessible to the broader microarray community. The aim of this chapter is to present some of the most widely used statistical techniques for normalizing and scoring traditional microarray data and indicate their potential utility for analyzing the newer protein and tiling microarray experiments. In so doing, we will assume little or no prior training in statistics of the reader. Areas covered include background correction, intensity normalization, spatial normalization, and the testing of statistical significance.
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| 6. |
- Yusuf, S., et al.
(author)
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Effects of candesartan on the development of a new diagnosis of diabetes mellitus in patients with heart failure
- 2005
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In: Circulation. - 1524-4539. ; 112:1, s. 48-53
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Journal article (peer-reviewed)abstract
- BACKGROUND: Diabetes is a risk factor for heart failure, and both conditions are increasing. Identifying treatments that prevent both conditions will be clinically important. We previously reported that candesartan (an angiotensin receptor blocker) reduces cardiovascular mortality and heart failure hospitalizations in heart failure patients (CHARM: Candesartan in Heart Failure-Assessment of Reduction in Mortality and Morbidity Program). METHODS AND RESULTS: We assessed the impact of candesartan versus placebo on the development of diabetes, a predefined secondary outcome in a randomized, controlled, double-blind study involving 5436 of the 7601 patients with heart failure, irrespective of ejection fraction, who did not have a diagnosis of diabetes at entry into the trial. Patients received candesartan (target of 32 mg once daily) or matching placebo for 2 to 4 years. One hundred sixty-three (6.0%) individuals in the candesartan group developed diabetes, as compared with 202 (7.4%) in the placebo group (hazard ratio [HR], 0.78 with a 95% confidence interval [CI] of 0.64 to 0.96; P=0.020). The composite end point of death or diabetes occurred in 692 (25.2%) and 779 (28.6%), respectively, in the candesartan and placebo groups (HR, 0.86; 95% CI, 0.78 to 0.95; P=0.004). The results were not statistically heterogeneous in the various subgroups examined, although the apparent magnitude of benefit appeared to be smaller among those treated concomitantly with angiotensin-converting enzyme inhibitors at trial entry (HR, 0.88; 95% CI, 0.65 to 1.20) compared with those not receiving these drugs (HR, 0.71; 95% CI, 0.53 to 0.93; P for heterogeneity, 0.28). CONCLUSIONS: The angiotensin receptor blocker candesartan appears to prevent diabetes in heart failure patients, suggesting that the renin-angiotensin axis is implicated in glucose regulation.
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