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Record W4220754350 · doi:10.1101/2022.03.06.22271725

A multi-phenotype analysis reveals 19 novel susceptibility loci for basal cell carcinoma and 15 for squamous cell carcinoma

2022· preprint· en· W4220754350 on OpenAlexaboutno aff
Mathias Seviiri, Matthew H. Law, Jue‐Sheng Ong, Puya Gharahkhani, Pierre Fontanillas, Catherine M. Olsen, David C. Whiteman, Stuart MacGregor

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsnot available
FundersMedical Research Council
KeywordsBasal cell carcinomaBiologyGenome-wide association studyPhenotypeLinkage disequilibriumInternal medicineImmunologyGeneticsCancer researchOncologyBasal cellSingle-nucleotide polymorphismMedicineGeneGenotype

Abstract

fetched live from OpenAlex

ABSTRACT Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common forms of skin cancer. There is genetic overlap between skin cancers, pigmentation traits, and autoimmune diseases. We use linkage disequilibrium score regression to identify 20 traits (melanoma, pigmentation traits, autoimmune diseases, and blood biochemistry biomarkers) with a high genetic correlation ( r g > 10%, P < 0.05) with BCC (20,791 cases and 286,893 controls in the UK Biobank) and SCC (7,402 cases and 286,892 controls in the UK Biobank), and use a multi-trait genetic analysis to identify 78 and 69 independent genome-wide significant (P < 5 × 10 -8 ) susceptibility loci for BCC and SCC respectively; 19 BCC and 15 SCC loci are both novel and replicated (P < 0.05) in a large independent cohort; 23andMe, Inc (BCC: 251,963 cases and 2,271,667 controls, and SCC: 134,700 cases and 2,394,699 controls. Novel loci are implicated in BCC/SCC development and progression (e.g. CDKL1 ), pigmentation (e.g. DSTYK ), cardiometabolic pathways (e.g. FADS2 ), and immune-regulatory pathways including; innate immunity against coronaviruses (e.g. IFIH1 ), and HIV-1 viral load modulation and disease progression (e.g. CCR5 ). We also report a powerful and optimised BCC polygenic risk score that enables effective risk stratification for keratinocyte cancer in a large prospective Canadian Longitudinal Study of Aging (794 cases and 18139 controls); e.g. percentage of participants reclassified; MTAG PRS = 36.57%, 95% CI = 35.89-37.26% versus UKB PRS = 33.23%, 95% CI=32.56-33.91%).

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.047
GPT teacher head0.307
Teacher spread0.260 · 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
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

Citations3
Published2022
Admission routes1
Has abstractyes

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