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Record W2949800402 · doi:10.1038/s41431-019-0455-9

Sex specific associations in genome wide association analysis of renal cell carcinoma

2019· review· en· W2949800402 on OpenAlexaff
Ruhina Shirin Laskar, David C. Muller, Peng Li, Mitchell J. Machiela, Yuanqing Ye, Valérie Gaborieau, Matthieu Foll, Jonathan N. Hofmann, Leandro M. Colli, Joshua N. Sampson, Zhaoming Wang, Delphine Bacq‐Daian, Anne Boland, Behnoush Abedi‐Ardekani, Geoffroy Durand, Florence Le Calvez‐Kelm, Nivonirina Robinot, Hélène Blanché, Egor Prokhortchouk, K. G. Skryabin, Laurie Burdett, Meredith Yeager, Sanja Radojević-Škodrić, Slaviša Savić, Lenka Foretová, Ivana Holcátová, Vladimí­r Janout, Dana Mateș, Ștefan Rașcu, Anush Mukeria, Давид Заридзе, Vladimír Bencko, Cezary Cybulski, Eleonóra Fabiánová, Viorel Jinga, Jolanta Lissowska, Jan Lubiński, Marie Navrátilová, Péter Rudnai, Beata Świątkowska, Simone Benhamou, Géraldine Cancel‐Tassin, Olivier Cussenot, Antonia Trichopoulou, Elio Ríboli, Kim Overvad, Salvatore Panico, Börje Ljungberg, Raviprakash T. Sitaram, Graham G. Giles, Roger L. Milne, Gianluca Severi, Fiona Bruinsma, Tony Fletcher, Kvetoslava Koppová, Susanna C. Larsson, Alicja Wolk, Rosamonde E. Banks, Peter J. Selby, Douglas F. Easton, Paul D.P. Pharoah, Gabriella Andreotti, Laura E. Beane Freeman, Stella Koutros, Demetrius Albanes, Satu Männistö, Stephanie J. Weinstein, Peter E. Clark, Todd L. Edwards, Loren Lipworth, Hallie Carol, Matthew L. Freedman, Mark M. Pomerantz, Eunyoung Cho, Peter Kraft, Mark A. Preston, Kathryn M. Wilson, J. Michael Gaziano, Howard D. Sesso, Amanda Black, Neal D. Freedman, Wen‐Yi Huang, John Anema, Richard J. Kahnoski, Brian R. Lane, Sabrina L. Noyes, David Petillo, Bin Tean Teh, Ulrike Peters, Emily White, Garnet L. Anderson, Lisa Johnson, Juhua Luo, Wong‐Ho Chow, Lee E. Moore, Toni K. Choueiri, Christopher G. Wood, Mattias Johansson, James McKay, Kevin M. Brown, Nathaniel Rothman, Mark G. Lathrop, Jean‐François Deleuze, Xifeng Wu, Paul Brennan, Stephen J. Chanock, Mark P. Purdue, Ghislaine Scélo

Bibliographic record

VenueEuropean Journal of Human Genetics · 2019
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsMcGill University and Génome Québec Innovation Centre
FundersUniversity of Texas MD Anderson Cancer CenterMinisterstvo Zdravotnictví Ceské RepublikyDuncan Family Institute for Cancer Prevention and Risk AssessmentNational Institute for Health and Care ResearchNational Cancer InstituteNational Institutes of HealthU.S. Department of Health and Human ServicesCancer Research UKWorld Health Organization
KeywordsRenal cell carcinomaBiologyGenome-wide association studyGeneticsGenetic associationOncologyInternal medicineComputational biologyMedicineSingle-nucleotide polymorphismGeneGenotype

Abstract

fetched live from OpenAlex

Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (ORmale) = 0.83 [95% CI = 0.78-0.89], Pmale = 1.71 × 10−8 compared with female odds ratio (ORfemale) = 0.98 [95% CI = 0.90–1.07], Pfemale = 0.68) and 12q23.3 (intergenic, ORmale = 0.75 [95% CI = 0.68-0.83], Pmale = 1.59 × 10−8 compared with ORfemale = 0.93 [95% CI = 0.82–1.06], Pfemale = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.302
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations45
Published2019
Admission routes1
Has abstractyes

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