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Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes.

Zhishan Chen | Xingyi Guo | Ran Tao | Jeroen R Huyghe | Philip J Law | Ceres Fernandez-Rozadilla | Jie Ping | Guochong Jia | Jirong Long | Chao Li | Quanhu Shen | Yuhan Xie | Maria N Timofeeva | Minta Thomas | Stephanie L Schmit | Virginia Díez-Obrero | Matthew Devall | Ferran Moratalla-Navarro | Juan Fernandez-Tajes | Claire Palles | Kitty Sherwood | Sarah E W Briggs | Victoria Svinti | Kevin Donnelly | Susan M Farrington | James Blackmur | Peter G Vaughan-Shaw | Xiao-Ou Shu | Yingchang Lu | Peter Broderick | James Studd | Tabitha A Harrison | David V Conti | Fredrick R Schumacher | Marilena Melas | Gad Rennert | Mireia Obón-Santacana | Vicente Martín-Sánchez | Jae Hwan Oh | Jeongseon Kim | Sun Ha Jee | Keum Ji Jung | Sun-Seog Kweon | Min-Ho Shin | Aesun Shin | Yoon-Ok Ahn | Dong-Hyun Kim | Isao Oze | Wanqing Wen | Keitaro Matsuo | Koichi Matsuda | Chizu Tanikawa | Zefang Ren | Yu-Tang Gao | Wei-Hua Jia | John L Hopper | Mark A Jenkins | Aung Ko Win | Rish K Pai | Jane C Figueiredo | Robert W Haile | Steven Gallinger | Michael O Woods | Polly A Newcomb | David Duggan | Jeremy P Cheadle | Richard Kaplan | Rachel Kerr | David Kerr | Iva Kirac | Jan Böhm | Jukka-Pekka Mecklin | Pekka Jousilahti | Paul Knekt | Lauri A Aaltonen | Harri Rissanen | Eero Pukkala | Johan G Eriksson | Tatiana Cajuso | Ulrika Hänninen | Johanna Kondelin | Kimmo Palin | Tomas Tanskanen | Laura Renkonen-Sinisalo | Satu Männistö | Demetrius Albanes | Stephanie J Weinstein | Edward Ruiz-Narvaez | Julie R Palmer | Daniel D Buchanan | Elizabeth A Platz | Kala Visvanathan | Cornelia M Ulrich | Erin Siegel | Stefanie Brezina | Andrea Gsur | Peter T Campbell | Jenny Chang-Claude | Michael Hoffmeister | Hermann Brenner | Martha L Slattery | John D Potter | Kostas K Tsilidis | Matthias B Schulze | Marc J Gunter | Neil Murphy | Antoni Castells | Sergi Castellví-Bel | Leticia Moreira | Volker Arndt | Anna Shcherbina | D Timothy Bishop | Graham G Giles | Melissa C Southey | Gregory E Idos | Kevin J McDonnell | Zomoroda Abu-Ful | Joel K Greenson | Katerina Shulman | Flavio Lejbkowicz | Kenneth Offit | Yu-Ru Su | Robert Steinfelder | Temitope O Keku | Bethany van Guelpen | Thomas J Hudson | Heather Hampel | Rachel Pearlman | Sonja I Berndt | Richard B Hayes | Marie Elena Martinez | Sushma S Thomas | Paul D P Pharoah | Susanna C Larsson | Yun Yen | Heinz-Josef Lenz | Emily White | Li Li | Kimberly F Doheny | Elizabeth Pugh | Tameka Shelford | Andrew T Chan | Marcia Cruz-Correa | Annika Lindblom | David J Hunter | Amit D Joshi | Clemens Schafmayer | Peter C Scacheri | Anshul Kundaje | Robert E Schoen | Jochen Hampe | Zsofia K Stadler | Pavel Vodicka | Ludmila Vodickova | Veronika Vymetalkova | Christopher K Edlund | W James Gauderman | David Shibata | Amanda Toland | Sanford Markowitz | Andre Kim | Stephen J Chanock | Franzel van Duijnhoven | Edith J M Feskens | Lori C Sakoda | Manuela Gago-Dominguez | Alicja Wolk | Barbara Pardini | Liesel M FitzGerald | Soo Chin Lee | Shuji Ogino | Stephanie A Bien | Charles Kooperberg | Christopher I Li | Yi Lin | Ross Prentice | Conghui Qu | Stéphane Bézieau | Taiki Yamaji | Norie Sawada | Motoki Iwasaki | Loic Le Marchand | Anna H Wu | Chenxu Qu | Caroline E McNeil | Gerhard Coetzee | Caroline Hayward | Ian J Deary | Sarah E Harris | Evropi Theodoratou | Stuart Reid | Marion Walker | Li Yin Ooi | Ken S Lau | Hongyu Zhao | Li Hsu | Qiuyin Cai | Malcolm G Dunlop | Stephen B Gruber | Richard S Houlston | Victor Moreno | Graham Casey | Ulrike Peters | Ian Tomlinson | Wei Zheng
Nature communications | 2024

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Pubmed ID: 38670944

Associated grants

  • Agency: NCI NIH HHS, United States
    Id: U01 CA206110
  • Agency: NCI NIH HHS, United States
    Id: R01 CA263318
  • Agency: NCI NIH HHS, United States
    Id: P01 CA196569
  • Agency: World Health Organization, International
    Id: 001
  • Agency: U.S. Department of Health & Human Services | National Institutes of Health (NIH),
    Id: R37CA227130
  • Agency: U.S. Department of Health & Human Services | National Institutes of Health (NIH),
    Id: R01CA188214
  • Agency: NCI NIH HHS, United States
    Id: P30 CA008748
  • Agency: NCI NIH HHS, United States
    Id: U01 CA272529

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This is a list of tools and resources that we have found mentioned in this publication.


ChIP-seq (tool)

RRID:SCR_001237

Set of software modules for performing common ChIP-seq data analysis tasks across the whole genome, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. The tools are designed to be simple, fast and highly modular. Each program carries out a well defined data processing procedure that can potentially fit into a pipeline framework. ChIP-Seq is also freely available on a Web interface.

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METAL (tool)

RRID:SCR_002013

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STAR (tool)

RRID:SCR_004463

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RNA-SeQC (tool)

RRID:SCR_005120

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Variant Effect Predictor (tool)

RRID:SCR_007931

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KEGG (tool)

RRID:SCR_012773

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SIFT (tool)

RRID:SCR_012813

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RRID:SCR_012815

Biobank provides data collected at Assessment Center and via online questionnaires on participants aged 40-69 years recruited throughout United Kingdom and provides summary information to improve prevention, diagnosis and treatment of serious and life threatening illnesses.

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ANNOVAR (tool)

RRID:SCR_012821

An efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)

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GENCODE (tool)

RRID:SCR_014966

Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.

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4D Genome (tool)

RRID:SCR_017489

Repository for chromatin interaction data. Records can be queried by genomic regions, gene names, organism, and detection technology. Database is continuously updated by curators. Contributions from scientific community.

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