1. |
- Campbell, PJ, et al.
(author)
-
Pan-cancer analysis of whole genomes
- 2020
-
In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
-
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.
|
|
2. |
- Ruilope, LM, et al.
(author)
-
Design and Baseline Characteristics of the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease Trial
- 2019
-
In: American journal of nephrology. - : S. Karger AG. - 1421-9670 .- 0250-8095. ; 50:5, s. 345-356
-
Journal article (peer-reviewed)abstract
- <b><i>Background:</i></b> Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. <b><i>Patients and</i></b> <b><i>Methods:</i></b> The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate ≥25 mL/min/1.73 m<sup>2</sup> and albuminuria (urinary albumin-to-creatinine ratio ≥30 to ≤5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level α = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. <b><i>Conclusions:</i></b> FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049.
|
|
3. |
|
|
4. |
- Vogel, Jacob W., et al.
(author)
-
Four distinct trajectories of tau deposition identified in Alzheimer’s disease
- 2021
-
In: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 27:5, s. 871-881
-
Journal article (peer-reviewed)abstract
- Alzheimer’s disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These ‘subtypes’ were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of ‘typical AD’ and a revisiting of tau pathological staging. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.
|
|
5. |
- Zhou, XP, et al.
(author)
-
Non-coding variability at the APOE locus contributes to the Alzheimer's risk
- 2019
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 3310-
-
Journal article (peer-reviewed)abstract
- Alzheimer’s disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis.
|
|
6. |
- Dornelas, M., et al.
(author)
-
BioTIME: A database of biodiversity time series for the Anthropocene
- 2018
-
In: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 27:7, s. 760-786
-
Journal article (peer-reviewed)abstract
- Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
|
|
7. |
|
|
8. |
|
|
9. |
- Yakneen, S, et al.
(author)
-
Butler enables rapid cloud-based analysis of thousands of human genomes
- 2020
-
In: Nature biotechnology. - : Springer Science and Business Media LLC. - 1546-1696 .- 1087-0156. ; 38:3, s. 288-
-
Journal article (peer-reviewed)abstract
- We present Butler, a computational tool that facilitates large-scale genomic analyses on public and academic clouds. Butler includes innovative anomaly detection and self-healing functions that improve the efficiency of data processing and analysis by 43% compared with current approaches. Butler enabled processing of a 725-terabyte cancer genome dataset from the Pan-Cancer Analysis of Whole Genomes (PCAWG) project in a time-efficient and uniform manner.
|
|
10. |
|
|