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Record W4362534013 · doi:10.1158/1538-7445.am2023-5223

Abstract 5223: Circulating lipoprotein lipids and colorectal cancer risk: A Mendelian randomization analysis from the GECCO consortium

2023· article· en· W4362534013 on OpenAlexaff
Lili Liu, Wanqing Wen, Jirong Long, Themistocles L. Assimes, Luís Bujanda, Stephen B. Gruber, Sébastien Küry, Brigid M. Lynch, Conghui Qu, Minta Thomas, Emily White, Michael O. Woods, Ulrike Peters, Wei Zheng

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMendelian randomizationGenome-wide association studySingle-nucleotide polymorphismColorectal cancerApolipoprotein BInternal medicineBlood lipidsMedicineGeneticsHigh-density lipoproteinTriglycerideApolipoprotein A1Genetic associationCholesterolLipoproteinOncologyCancerBiologyEndocrinologyGenotypeGeneGenetic variants

Abstract

fetched live from OpenAlex

Abstract Background Conventional observational studies have reported conflicting results regarding the association between low density lipoprotein cholesterol (LDL-C) and risk of colorectal cancer (CRC). We conducted a Mendelian randomization analysis to address this association. Methods Single-nucleotide polymorphisms (SNPs) associated with five blood lipids (total cholesterol, HDL-C, high-density lipoprotein cholesterol [HDL-C], non-HDL-C, and triglyceride) were obtained from a genome-wide association study (GWAS) meta-analysis of European ancestry in the Global Lipids Genetics Consortium (GLGC, N ≤ 1 319 982), and two lipids (apolipoprotein A1 and apolipoprotein B) from a GWAS in the UK Biobank (UKB, N ≤ 441 016). Summary statistics were obtained for these SNPs from a GWAS of CRC in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) including 34,869 cases and 29,051 controls. Associations with CRC risk per one standard deviation increase in the genetically predicted lipids level were generated using inverse-variance weighted random-effects models. Results No overall association was observed between genetically predicted levels of blood lipids and CRC risk. However, increased risks were observed for all LDL-C related traits among women, including total cholesterol (OR = 1.10; 95%CI = 1.02, 1.18), LDL-C (1.07; 1.00, 1.14), non-HDL-C (1.09; 1.02, 1.16), and apolipoprotein B (1.11; 1.02, 1.21); whereas no significant association was found among men. Similar but ostensibly stronger associations of these traits were seen with distal colon cancer cases, with no significant association showing on proximal colon or rectum cancer cases. We also observed similar positive associations of LDL-C related traits among those having CRC before their 50 years. Of note, risk reduction was found for apolipoprotein A1, a major component of HDL-C, in these early-onset cases (0.87; 0.78, 0.98). Conclusion Results from this study suggest that high circulating LDL-C levels may increase the risk of CRC, particularly cancer of the distal colon, and the association may differ by sex and age at CRC onset. Key words: Blood lipids; colorectal cancer; Mendelian randomization. Citation Format: Lili Liu, Wanqing Wen, Jirong Long, Themistocles L Assimes, Luis Bujanda, Stephen B Gruber, Sébastien Küry, Brigid Lynch, Conghui Qu, Minta Thomas, Emily White, Michael O. Woods, Ulrike Peters, Wei Zheng. Circulating lipoprotein lipids and colorectal cancer risk: A Mendelian randomization analysis from the GECCO consortium. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5223.

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)0.057
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0570.112
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.033
GPT teacher head0.351
Teacher spread0.318 · 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 designObservational
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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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