Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
Fachal, L
Aschard, H
Beesley, J
Barnes, DR
Allen, J
Kar, S
Pooley, KA
Dennis, J
Michailidou, K
Turman, C
Soucy, P
Lemaçon, A
Lush, M
Tyrer, JP
Ghoussaini, M
Marjaneh, MM
Jiang, X
Agata, S
Aittomäki, K
Alonso, MR
Andrulis, IL
Anton-Culver, H
Antonenkova, NN
Arason, A
Arndt, V
Aronson, KJ
Arun, BK
Auber, B
Auer, PL
Azzollini, J
Balmaña, J
Barkardottir, RB
Barrowdale, D
Beeghly-Fadiel, A
Benitez, J
Bermisheva, M
Białkowska, K
Blanco, AM
Blomqvist, C
Blot, W
Bogdanova, NV
Bojesen, SE
Bolla, MK
Bonanni, B
Borg, A
Bosse, K
Brauch, H
Brenner, H
Briceno, I
Brock, IW
Brooks-Wilson, A
Brüning, T
Burwinkel, B
Buys, SS
Cai, Q
Caldés, T
Caligo, MA
Camp, NJ
Campbell, I
Canzian, F
Carroll, JS
Carter, BD
Castelao, JE
Chiquette, J
Christiansen, H
Chung, WK
Claes, KBM
Clarke, CL
Mari, V
Berthet, P
Castera, L
Vaur, D
Lallaoui, H
Bignon, YJ
Uhrhammer, N
Bonadona, V
Lasset, C
Révillion, F
Vennin, P
Muller, D
Gomes, DM
Ingster, O
Coupier, I
Pujol, P
Collonge-Rame, MA
Mortemousque, I
Bera, O
Rose, M
Baurand, A
Bertolone, G
Faivre, L
Dreyfus, H
Leroux, D
Venat-Bouvet, L
Bézieau, S
Delnatte, C
Chiesa, J
Gilbert-Dussardier, B
Gesta, P
Prieur, FP
- Publication Type:
- Journal Article
- Citation:
- Nature Genetics, 2020, 52 (1), pp. 56 - 73
- Issue Date:
- 2020-01-01
Closed Access
Filename | Description | Size | |||
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Fachal et al_Nat Gen_2020.pdf | Published Version | 2.02 MB | Adobe PDF |
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Fachal, L | en_US |
dc.contributor.author | Aschard, H | en_US |
dc.contributor.author | Beesley, J | en_US |
dc.contributor.author | Barnes, DR | en_US |
dc.contributor.author | Allen, J | en_US |
dc.contributor.author | Kar, S | en_US |
dc.contributor.author | Pooley, KA | en_US |
dc.contributor.author | Dennis, J | en_US |
dc.contributor.author | Michailidou, K | en_US |
dc.contributor.author | Turman, C | en_US |
dc.contributor.author | Soucy, P | en_US |
dc.contributor.author | Lemaçon, A | en_US |
dc.contributor.author | Lush, M | en_US |
dc.contributor.author | Tyrer, JP | en_US |
dc.contributor.author | Ghoussaini, M | en_US |
dc.contributor.author | Marjaneh, MM | en_US |
dc.contributor.author | Jiang, X | en_US |
dc.contributor.author | Agata, S | en_US |
dc.contributor.author | Aittomäki, K | en_US |
dc.contributor.author | Alonso, MR | en_US |
dc.contributor.author | Andrulis, IL | en_US |
dc.contributor.author | Anton-Culver, H | en_US |
dc.contributor.author | Antonenkova, NN | en_US |
dc.contributor.author | Arason, A | en_US |
dc.contributor.author | Arndt, V | en_US |
dc.contributor.author | Aronson, KJ | en_US |
dc.contributor.author | Arun, BK | en_US |
dc.contributor.author | Auber, B | en_US |
dc.contributor.author | Auer, PL | en_US |
dc.contributor.author | Azzollini, J | en_US |
dc.contributor.author | Balmaña, J | en_US |
dc.contributor.author | Barkardottir, RB | en_US |
dc.contributor.author | Barrowdale, D | en_US |
dc.contributor.author | Beeghly-Fadiel, A | en_US |
dc.contributor.author | Benitez, J | en_US |
dc.contributor.author | Bermisheva, M | en_US |
dc.contributor.author | Białkowska, K | en_US |
dc.contributor.author | Blanco, AM | en_US |
dc.contributor.author | Blomqvist, C | en_US |
dc.contributor.author | Blot, W | en_US |
dc.contributor.author | Bogdanova, NV | en_US |
dc.contributor.author | Bojesen, SE | en_US |
dc.contributor.author | Bolla, MK | en_US |
dc.contributor.author | Bonanni, B | en_US |
dc.contributor.author | Borg, A | en_US |
dc.contributor.author | Bosse, K | en_US |
dc.contributor.author | Brauch, H | en_US |
dc.contributor.author | Brenner, H | en_US |
dc.contributor.author | Briceno, I | en_US |
dc.contributor.author | Brock, IW | en_US |
dc.contributor.author | Brooks-Wilson, A | en_US |
dc.contributor.author | Brüning, T | en_US |
dc.contributor.author | Burwinkel, B | en_US |
dc.contributor.author | Buys, SS | en_US |
dc.contributor.author | Cai, Q | en_US |
dc.contributor.author | Caldés, T | en_US |
dc.contributor.author | Caligo, MA | en_US |
dc.contributor.author | Camp, NJ | en_US |
dc.contributor.author | Campbell, I | en_US |
dc.contributor.author | Canzian, F | en_US |
dc.contributor.author | Carroll, JS | en_US |
dc.contributor.author | Carter, BD | en_US |
dc.contributor.author | Castelao, JE | en_US |
dc.contributor.author | Chiquette, J | en_US |
dc.contributor.author | Christiansen, H | en_US |
dc.contributor.author | Chung, WK | en_US |
dc.contributor.author | Claes, KBM | en_US |
dc.contributor.author | Clarke, CL | en_US |
dc.contributor.author | Mari, V | en_US |
dc.contributor.author | Berthet, P | en_US |
dc.contributor.author | Castera, L | en_US |
dc.contributor.author | Vaur, D | en_US |
dc.contributor.author | Lallaoui, H | en_US |
dc.contributor.author | Bignon, YJ | en_US |
dc.contributor.author | Uhrhammer, N | en_US |
dc.contributor.author | Bonadona, V | en_US |
dc.contributor.author | Lasset, C | en_US |
dc.contributor.author | Révillion, F | en_US |
dc.contributor.author | Vennin, P | en_US |
dc.contributor.author | Muller, D | en_US |
dc.contributor.author | Gomes, DM | en_US |
dc.contributor.author | Ingster, O | en_US |
dc.contributor.author | Coupier, I | en_US |
dc.contributor.author | Pujol, P | en_US |
dc.contributor.author | Collonge-Rame, MA | en_US |
dc.contributor.author | Mortemousque, I | en_US |
dc.contributor.author | Bera, O | en_US |
dc.contributor.author | Rose, M | en_US |
dc.contributor.author | Baurand, A | en_US |
dc.contributor.author | Bertolone, G | en_US |
dc.contributor.author | Faivre, L | en_US |
dc.contributor.author | Dreyfus, H | en_US |
dc.contributor.author | Leroux, D | en_US |
dc.contributor.author | Venat-Bouvet, L | en_US |
dc.contributor.author | Bézieau, S | en_US |
dc.contributor.author | Delnatte, C | en_US |
dc.contributor.author | Chiesa, J | en_US |
dc.contributor.author | Gilbert-Dussardier, B | en_US |
dc.contributor.author | Gesta, P | en_US |
dc.contributor.author | Prieur, FP | en_US |
dc.date.accessioned | 2020-04-23T14:06:55Z | |
dc.date.available | 2019-10-24 | en_US |
dc.date.available | 2020-04-23T14:06:55Z | |
dc.date.issued | 2020-01-01 | en_US |
dc.identifier.citation | Nature Genetics, 2020, 52 (1), pp. 56 - 73 | en_US |
dc.identifier.issn | 1061-4036 | en_US |
dc.identifier.uri | http://hdl.handle.net/10453/140219 | |
dc.description.abstract | © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes. | en_US |
dc.relation.ispartof | Nature Genetics | en_US |
dc.relation.isbasedon | 10.1038/s41588-019-0537-1 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject.classification | Developmental Biology | en_US |
dc.subject.mesh | Humans | en_US |
dc.subject.mesh | Breast Neoplasms | en_US |
dc.subject.mesh | Genetic Predisposition to Disease | en_US |
dc.subject.mesh | Bayes Theorem | en_US |
dc.subject.mesh | Risk Factors | en_US |
dc.subject.mesh | Chromosome Mapping | en_US |
dc.subject.mesh | Regulatory Sequences, Nucleic Acid | en_US |
dc.subject.mesh | Linkage Disequilibrium | en_US |
dc.subject.mesh | Polymorphism, Single Nucleotide | en_US |
dc.subject.mesh | Quantitative Trait Loci | en_US |
dc.subject.mesh | Female | en_US |
dc.subject.mesh | Genome-Wide Association Study | en_US |
dc.subject.mesh | Biomarkers, Tumor | en_US |
dc.title | Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes | en_US |
dc.type | Journal Article | |
utslib.citation.volume | 1 | en_US |
utslib.citation.volume | 52 | en_US |
utslib.for | 06 Biological Sciences | en_US |
utslib.for | 11 Medical and Health Sciences | en_US |
pubs.embargo.period | Not known | en_US |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Science | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Science/School of Life Sciences | |
pubs.organisational-group | /University of Technology Sydney/Strength - CHT - Health Technologies | |
utslib.copyright.status | closed_access | * |
pubs.issue | 1 | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 52 | en_US |
Abstract:
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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