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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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- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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- Marouli, Eirini, et al.
(author)
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Rare and low-frequency coding variants alter human adult height
- 2017
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 542:7640, s. 186-190
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Journal article (peer-reviewed)abstract
- Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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- McKeith, IG, et al.
(author)
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Diagnosis and management of dementia with Lewy bodies - Third report of the DLB consortium
- 2005
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In: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 1526-632X .- 0028-3878. ; 65:12, s. 1863-1872
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Research review (peer-reviewed)abstract
- The dementia with Lewy bodies (DLB) Consortium has revised criteria for the clinical and pathologic diagnosis of DLB incorporating new information about the core clinical features and suggesting improved methods to assess them. REM sleep behavior disorder, severe neuroleptic sensitivity, and reduced striatal dopamine transporter activity on functional neuroimaging are given greater diagnostic weighting as features suggestive of a DLB diagnosis. The 1-year rule distinguishing between DLB and Parkinson disease with dementia may be difficult to apply in clinical settings and in such cases the term most appropriate to each individual patient should be used. Generic terms such as Lewy body (LB) disease are often helpful. The authors propose a new scheme for the pathologic assessment of LBs and Lewy neurites (LN) using alpha-synuclein immunohistochemistry and semiquantitative grading of lesion density, with the pattern of regional involvement being more important than total LB count. The new criteria take into account both Lewy-related and Alzheimer disease (AD)-type pathology to allocate a probability that these are associated with the clinical DLB syndrome. Finally, the authors suggest patient management guidelines including the need for accurate diagnosis, a target symptom approach, and use of appropriate outcome measures. There is limited evidence about specific interventions but available data suggest only a partial response of motor symptoms to levodopa: severe sensitivity to typical and atypical antipsychotics in similar to 50%, and improvements in attention, visual hallucinations, and sleep disorders with cholinesterase inhibitors.
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- Murari, A., et al.
(author)
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A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors
- 2024
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In: Nature Communications. - 2041-1723 .- 2041-1723. ; 15:1
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Journal article (peer-reviewed)abstract
- The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.
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- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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- Asa, Sylvia L., et al.
(author)
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Pituitary neuroendocrine tumors : a model for neuroendocrine tumor classification
- 2021
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In: Modern Pathology. - : Springer Nature. - 0893-3952 .- 1530-0285. ; 34:9, s. 1634-1650
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Research review (peer-reviewed)abstract
- The classification of adenohypophysial neoplasms as "pituitary neuroendocrine tumors" (PitNETs) was proposed in 2017 to reflect their characteristics as epithelial neuroendocrine neoplasms with a spectrum of clinical behaviors ranging from small indolent lesions to large, locally invasive, unresectable tumors. Tumor growth and hormone hypersecretion cause significant morbidity and mortality in a subset of patients. The proposal was endorsed by a WHO working group that sought to provide a unified approach to neuroendocrine neoplasia in all body sites. We review the features that are characteristic of neuroendocrine cells, the epidemiology and prognosis of these tumors, as well as further refinements in terms used for other pituitary tumors to ensure consistency with the WHO framework. The intense study of PitNETs has provided information about the importance of cellular differentiation in tumor prognosis as a model for neuroendocrine tumors in different locations.
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- Blackwell, TA, et al.
(author)
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Transcriptomic analysis of the development of skeletal muscle atrophy in cancer-cachexia in tumor-bearing mice
- 2018
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In: Physiological genomics. - : American Physiological Society. - 1531-2267 .- 1094-8341. ; 50:12, s. 1071-1082
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Journal article (peer-reviewed)abstract
- Cancer-cachexia (CC) is a wasting condition directly responsible for 20–40% of cancer-related deaths. The mechanisms controlling development of CC-induced muscle wasting are not fully elucidated. Most investigations focus on the postcachectic state and do not examine progression of the condition. We recently demonstrated mitochondrial degenerations precede muscle wasting in time course progression of CC. However, the extent of muscle perturbations before wasting in CC is unknown. Therefore, we performed global gene expression analysis in CC-induced muscle wasting to enhance understanding of intramuscular perturbations across the development of CC. Lewis lung carcinoma (LLC) was injected into the hind-flank of C57BL6/J mice at 8 wk of age with tumor allowed to develop for 1, 2, 3, or 4 wk and compared with PBS-injected control. Muscle wasting was evident at 4 wk LLC. RNA sequencing of gastrocnemius muscle samples showed widespread alterations in LLC compared with PBS animals with largest differences seen in 4 wk LLC, suggesting extensive transcriptomic alterations concurrent to muscle wasting. Commonly altered pathways included: mitochondrial dysfunction and protein ubiquitination, along with other less studied processes in this condition regulating transcription/translation and cytoskeletal structure. Current findings present novel evidence of transcriptomic shifts and altered cellular pathways in CC-induced muscle wasting.
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