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- Ballantyne, CM, et al.
(author)
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Influence of low high-density lipoprotein cholesterol and elevated triglyceride on coronary heart disease events and response to simvastatin therapy in 4S
- 2001
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In: Circulation. - 0009-7322 .- 1524-4539. ; 104:25, s. 3046-3051
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Journal article (peer-reviewed)abstract
- Background - Patients with low HDL cholesterol (HDL-C) and elevated triglyceride had an increased risk for coronary heart disease (CHD) events and received the greatest benefit with fibrate therapy in substudy analyses of the Helsinki Heart Study and the Bezafibrate Infarction Prevention Study. Methods and Results - In this post hoc analysis of the Scandinavian Simvastatin Survival Study, which enrolled patients with elevated LDL cholesterol (LDL-C) and CHD, subgroups defined by HDL-C and triglyceride quartiles were compared to examine the influence of HDL-C and triglyceride on CHD events and response to therapy. Patients in the lowest HDL-C (<1.00 mmol/L [39 mg/dL]) and highest triglyceride (>1.80 mmol/L [159 mg/dL]) quartiles (lipid triad, n=458) had increased proportions of other features of the metabolic syndrome (increased body mass index, hypertension, diabetes), men, prior myocardial infarction, prior revascularization, and ▀-blocker use than patients in the highest HDL-C (>1.34 mmol/L [52 mg/dL]) and lowest triglyceride (<1.11 mmol/L [98 mg/dL]) quartiles (isolated LDL-C elevation, n=545). The major coronary event rate was highest in lipid triad patients on placebo (35.9%), and this subgroup had the greatest event reduction (relative risk 0.48, 95% CI 0.33 to 0.69), a significant treatment-by-subgroup interaction (P=0.03) indicated a greater treatment effect in the lipid triad subgroup than the isolated LDL-C elevation subgroup. Conclusions - Patients with elevated LDL-C, low HDL-C, and elevated triglycerides were more likely than patients with isolated LDL-C elevation to have other characteristics of the metabolic syndrome, had increased risk for CHD events on placebo, and received greater benefit with simvastatin therapy.
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- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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