001     304272
005     20250907022502.0
024 7 _ |a 10.1038/s41408-025-01351-4
|2 doi
024 7 _ |a pmid:40883272
|2 pmid
024 7 _ |a pmc:PMC12397487
|2 pmc
024 7 _ |a altmetric:180996171
|2 altmetric
037 _ _ |a DKFZ-2025-01813
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Güler, Murat
|0 P:(DE-He78)be2bee623c6815bb57b390a0ecb8072a
|b 0
|e First author
|u dkfz
245 _ _ |a Clustering of lymphoid neoplasms by cell of origin, somatic mutation and drug usage profiles: a multi-trait genome-wide association study.
260 _ _ |a [London]
|c 2025
|b Springer Nature
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1756716473_32343
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a #EA:C055#LA:C055#
520 _ _ |a Lymphoid neoplasms (LNs) are heterogeneous malignancies arising from lymphoid cells, displaying diverse clinical and molecular features. Although LNs are collectively frequent, individual subtypes are rare, posing challenges for genetic association studies. Indeed, genome-wide association studies (GWAS) explained only a fraction of the heritability. Shared genetic susceptibility and overlapping risk factors suggest a partially common etiology across subtypes. We employed a multi-trait GWAS strategy to improve discovery power by leveraging pleiotropy among LN subtypes. We defined LN phenoclusters based on cell of origin, somatic mutation profiles, and approved therapeutic agents. Using data from three large cohorts-the UK Biobank, Million Veteran Program, and FinnGen-we analyzed 31,937 LN cases and 1.2 million controls across 8 individual subtypes and 7 phenoclusters. We replicated the novel associations in two independent cohorts (All of Us and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial) with 2892 LN cases and 165,791 controls. We identified 76 genome-wide significant loci for individual subtypes or subtype clusters, including 20 novel associations. We identified the subtypes contributing to each locus, putative candidate causal variants, and genes underlying the associations, and found enrichment of specific cell types, biological processes, and drugs associated with LN risk genes. Overall, this study identified new LN genetic risk loci and candidate genes, providing insights that may inform novel therapeutic approaches.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Genome-Wide Association Study
|2 MeSH
650 _ 2 |a Mutation
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Genetic Predisposition to Disease
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
700 1 _ |a Canzian, Federico
|0 P:(DE-He78)5323704270b6393dcea70186ffd86bca
|b 1
|e Last author
|u dkfz
773 _ _ |a 10.1038/s41408-025-01351-4
|g Vol. 15, no. 1, p. 147
|0 PERI:(DE-600)2600560-8
|n 1
|p 147
|t Blood cancer journal
|v 15
|y 2025
|x 2044-5385
909 C O |o oai:inrepo02.dkfz.de:304272
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 0
|6 P:(DE-He78)be2bee623c6815bb57b390a0ecb8072a
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 1
|6 P:(DE-He78)5323704270b6393dcea70186ffd86bca
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2025
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b BLOOD CANCER J : 2022
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2024-04-10T15:34:04Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2024-04-10T15:34:04Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2024-04-10T15:34:04Z
915 _ _ |a Creative Commons Attribution CC BY (No Version)
|0 LIC:(DE-HGF)CCBYNV
|2 V:(DE-HGF)
|b DOAJ
|d 2024-04-10T15:34:04Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2024-12-18
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-18
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-18
915 _ _ |a IF >= 10
|0 StatID:(DE-HGF)9910
|2 StatID
|b BLOOD CANCER J : 2022
|d 2024-12-18
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2024-12-18
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2024-12-18
920 2 _ |0 I:(DE-He78)C055-20160331
|k C055
|l Genomische Epidemiologie
|x 0
920 1 _ |0 I:(DE-He78)C055-20160331
|k C055
|l Genomische Epidemiologie
|x 0
920 0 _ |0 I:(DE-He78)C055-20160331
|k C055
|l Genomische Epidemiologie
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C055-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21