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Record W2030794949 · doi:10.1158/1538-7445.am2014-5072

Abstract 5072: Meta-analysis of genome-wide association studies identifies novel susceptibility loci for follicular lymphoma

2014· article· en· W2030794949 on OpenAlexaff
Christine F. Skibola, Sonja I. Berndt, James R. Cerhan, Zhaoming Wang, Joseph Vijai, Lucía Conde, Paul I. W. de Bakker, Sophia Wang, Claire M. Vajdic, Brenda M. Birmann, Susan L. Slager, James McKay, Paige M. Bracci, Alexandra Nieters, Qing Lan, Angela Brooks‐Wilson, Martha S. Linet, Demetrius Albanes, John J. Spinelli, Roel Vermeulen, Mark P. Purdue, Meredith Yaeger, Lauren R. Teras, Silvia de Sanjosé, Alain Monnereau, Simon Crouch, Jia Nee Foo, Henrik Hjalgrim, Gianluca Severi, Brian K. Link, Kimberly A. Bertrand, Yawei Zhang, Karin E. Smedby, Stephen J. Chanock, Nathaniel Rothman

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer AgencySimon Fraser University
Fundersnot available
KeywordsGenome-wide association studyExpression quantitative trait lociFollicular lymphomaSingle-nucleotide polymorphismBiologyGenetic associationImputation (statistics)GeneticsHuman leukocyte antigen1000 Genomes ProjectLymphomaGeneImmunologyGenotype

Abstract

fetched live from OpenAlex

Abstract Background. Follicular lymphoma (FL) is an indolent B-cell malignancy with a variable clinical course that may transform to more aggressive forms of lymphoma. Previous modestly powered GWAS have reported multiple FL susceptibility loci in the HLA class I and II regions at 6p21.32-33, but novel non-HLA susceptibility loci and the genetic architecture of FL associations in the HLA region remain to be elucidated. Methods. We conducted the largest GWAS of FL to date consisting of 2,142 cases and 6,221 controls of European ancestry from 22 studies scanned on the Illumina OmniExpress. After imputation of common SNPs using IMPUTE2 and 1,000 Genomes Project v3 data, we conducted a meta-analysis of these data with two previous FL GWAS (n=586 cases, 1,537 controls) and replicated top hits in an additional 629 cases and 4,283 controls. Expression quantitative trait loci (eQTL) analyses were performed to evaluate the effects of associated variants on gene expression. Classical HLA allele imputations and stepwise regression analyses are underway to further characterize the HLA associations. Results. In the joint meta-analysis, the strongest association with FL risk was observed in the HLA region, where a large number of SNPs showed genome-wide significance (P<5x10-8 to P= 1.84x10-84), particularly in HLA class II at 6p21.32 where several HLA eQTLs were identified (P < 0.05). Outside HLA, we identified four novel loci associated with FL at 11q23.3 (CXCR5, rs4938573; P=3.14x10-15), 11q24.3 (ETS1, rs4937362; P=3.33x10-9), 3q13.33 (CD86, rs2681416; P=9.79x10-11) and 3q28 (LPP, rs6444305, P=2.55x10-8). These novel susceptibility loci were located in four biologically relevant genes involved in immune regulation: CXCR5 and its ligand, CXCL13, are involved in guiding B-cells into the B-cell zones of secondary lymphoid organs as well as T-cell migration. ETS1 is expressed in lymphoid cells and regulates immune cell function including differentiation, survival, and proliferation. CD86 and CD80 are classic members of the B7 costimulatory pathway that is important in maintaining immune function, suppression of autoimmunity and antitumor surveillance. LPP encodes a LIM domain-containing protein of the zyxin family and participates in cell adhesion, cell migration, proliferation and transcription dynamics. Conclusions. This large GWAS provides further support for the important role of common genetic variation in non-HLA genes and further evidence of the key role that HLA immune-regulatory genes play in the pathogenesis of FL. Citation Format: Christine F. Skibola, Sonja I. Berndt, James R. Cerhan, Zhaoming Wang, Joseph Vijai, Lucia Conde, Paul de Bakker, Sophia S. Wang, Claire M. Vajdic, Brenda M. Birmann, Susan L. Slager, James McKay, Paige M. Bracci, Alexandra Nieters, Qing Lan, Angela R. Brooks-Wilson, Martha S. Linet, Demetrius Albanes, John J. Spinelli, Roel C.H. Vermeulen, Mark P. Purdue, Meredith Yaeger, Lauren R. Teras, Silvia de Sanjose, Alain Monnereau, Simon Crouch, Jia Nee Foo, Henrik Hjalgrim, Gianluca Severi, Brian K. Link, Kimberly A. Bertrand, Yawei Zhang, Karin E. Smedby, Stephen J. Chanock, Nathaniel Rothman, NHL GWAS Consortium. Meta-analysis of genome-wide association studies identifies novel susceptibility loci for follicular lymphoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5072. doi:10.1158/1538-7445.AM2014-5072

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.025
Bibliometrics0.0050.008
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.219
GPT teacher head0.450
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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