scispace - formally typeset
Search or ask a question
Institution

French Institute of Health and Medical Research

GovernmentParis, France
About: French Institute of Health and Medical Research is a government organization based out in Paris, France. It is known for research contribution in the topics: Population & Receptor. The organization has 109367 authors who have published 174236 publications receiving 8365503 citations.
Topics: Population, Receptor, Gene, Immune system, Antigen


Papers
More filters
Journal ArticleDOI
29 Oct 1992-Nature
TL;DR: A linkage map of the human genome has been constructed based on the segregation analysis of 814 newly characterized polymorphic loci containing short tracts of (C-A)n repeats in a panel of DNAs from eight large families.
Abstract: A linkage map of the human genome has been constructed based on the segregation analysis of 814 newly characterized polymorphic loci containing short tracts of (C-A)n repeats in a panel of DNAs from eight large families. Statistical linkage analysis placed 813 of the markers into 23 linkage groups corresponding to the 22 autosomes and the X chromosome; 605 show a heterozygosity above 0.7 and 553 could be ordered with odds ratios above 1,000:1. The distance spanned corresponds to ∼90% of the estimated length of the human genome.

1,742 citations

Journal ArticleDOI
TL;DR: The measurement of AOPP is proposed as a reliable marker to estimate the degree of oxidant-mediated protein damage in uremic patients and to predict the potential efficacy of therapeutic strategies aimed at reducing such an oxidative stress.

1,730 citations

Journal ArticleDOI
TL;DR: The dialogue between autophagy and cell death pathways influences the normal clearance of dying cells, as well as immune recognition of dead cell antigens, and the disruption of the relationship between autphagy and apoptosis has important pathophysiological consequences.
Abstract: Autophagy and apoptosis control the turnover of organelles and proteins within cells, and of cells within organisms, respectively, and many stress pathways sequentially elicit autophagy, and apoptosis within the same cell. Generally autophagy blocks the induction of apoptosis, and apoptosis-associated caspase activation shuts off the autophagic process. However, in special cases, autophagy or autophagy-relevant proteins may help to induce apoptosis or necrosis, and autophagy has been shown to degrade the cytoplasm excessively, leading to 'autophagic cell death'. The dialogue between autophagy and cell death pathways influences the normal clearance of dying cells, as well as immune recognition of dead cell antigens. Therefore, the disruption of the relationship between autophagy and apoptosis has important pathophysiological consequences.

1,721 citations

Journal ArticleDOI
04 Apr 2012-Nature
TL;DR: Results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors and support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold.
Abstract: Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

1,700 citations

Journal ArticleDOI
Serena Nik-Zainal1, Serena Nik-Zainal2, Helen Davies2, Johan Staaf3, Manasa Ramakrishna2, Dominik Glodzik2, Xueqing Zou2, Inigo Martincorena2, Ludmil B. Alexandrov2, Sancha Martin2, David C. Wedge2, Peter Van Loo2, Young Seok Ju2, Michiel M. Smid4, Arie B. Brinkman5, Sandro Morganella6, Miriam Ragle Aure7, Ole Christian Lingjærde7, Anita Langerød8, Markus Ringnér3, Sung-Min Ahn9, Sandrine Boyault, Jane E. Brock, Annegien Broeks10, Adam Butler2, Christine Desmedt11, Luc Dirix12, Serge Dronov2, Aquila Fatima13, John A. Foekens4, Moritz Gerstung2, Gerrit Gk Hooijer14, Se Jin Jang15, David Jones2, Hyung-Yong Kim16, Tari Ta King17, Savitri Krishnamurthy18, Hee Jin Lee15, Jeong-Yeon Lee16, Yang Li2, Stuart McLaren2, Andrew Menzies2, Ville Mustonen2, Sarah O’Meara2, Iris Pauporté, Xavier Pivot19, Colin Ca Purdie20, Keiran Raine2, Kamna Ramakrishnan2, Germán Fg Rodríguez-González4, Gilles Romieu21, Anieta M. Sieuwerts4, Peter Pt Simpson22, Rebecca Shepherd2, Lucy Stebbings2, Olafur Oa Stefansson23, Jon W. Teague2, Stefania Tommasi, Isabelle Treilleux, Gert Van den Eynden12, Peter B. Vermeulen12, Anne Vincent-Salomon24, Lucy R. Yates2, Carlos Caldas25, Laura Van't Veer10, Andrew Tutt26, Andrew Tutt27, Stian Knappskog28, Benita Kiat Tee Bk Tan29, Jos Jonkers10, Åke Borg3, Naoto T. Ueno18, Christos Sotiriou11, Alain Viari, P. Andrew Futreal2, Peter J. Campbell2, Paul N. Span5, Steven Van Laere12, Sunil R. Lakhani22, Jorunn E. Eyfjord23, Alastair M Thompson, Ewan Birney6, Hendrik G. Stunnenberg5, Marc J. van de Vijver14, John W.M. Martens4, Anne Lise Børresen-Dale8, Andrea L. Richardson13, Gu Kong16, Gilles Thomas, Michael R. Stratton2 
02 Jun 2016-Nature
TL;DR: This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.
Abstract: We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

1,696 citations


Authors

Showing all 109539 results

NameH-indexPapersCitations
Guido Kroemer2361404246571
Pierre Chambon211884161565
Peer Bork206697245427
Ronald M. Evans199708166722
Raymond J. Dolan196919138540
Matthew Meyerson194553243726
Charles A. Dinarello1901058139668
Julie E. Buring186950132967
Tadamitsu Kishimoto1811067130860
Didier Raoult1733267153016
Giuseppe Remuzzi1721226160440
Zena Werb168473122629
Nahum Sonenberg167647104053
Philippe Froguel166820118816
Gordon J. Freeman164579105193
Network Information
Related Institutions (5)
National Institutes of Health
297.8K papers, 21.3M citations

96% related

Johns Hopkins University School of Medicine
79.2K papers, 4.7M citations

95% related

University of Texas Southwestern Medical Center
75.2K papers, 4.4M citations

94% related

Icahn School of Medicine at Mount Sinai
76K papers, 3.7M citations

94% related

Karolinska Institutet
121.1K papers, 6M citations

94% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202368
2022306
20217,549
20207,367
20196,969
20186,607