Abstract 2686: Associations between a polygenic risk score and risk of multiple myeloma and its precursor
Notice bibliographique
Résumé
Abstract Genome-wide association studies (GWAS) conducted among populations of European ancestry (EA) have identified 23 common single nucleotide polymorphisms (SNPs) associated with multiple myeloma (MM) risk. We hypothesize that the combination of these SNPs in a polygenic risk score (PRS) is likely to be a strong risk factor for MM. However, it is unclear whether the genetic variation associated with MM susceptibility also predisposes to monoclonal gammopathy of undetermined significance (MGUS). Thus, we calculated a PRS and evaluated the association with risk of MM and its precursor, MGUS. We pooled genotype data for 2434 MM and 3446 controls from ten MM GWAS of individuals of EA within the Interlymph Consortium, for 23 MM risk SNPs identified by prior GWAS. An additional 754 MGUS cases were ascertained from Mayo Clinic and MD Anderson clinical practices. To calculate the PRS, we used the risk estimates corresponding to the 23 SNP associations from the largest published MM GWAS. The log of the odds ratio (OR) for each SNP was multiplied by the respective number of risk alleles and summed to generate a PRS for each individual. The PRS was examined continuously, per one standard deviation (SD), and as quintiles, based on the PRS distribution in the controls. Associations of PRS with MM and MGUS risk were examined separately, using multivariable logistic regression assuming an additive model to assess ORs and 95% confidence intervals adjusted for age, sex, and site. We also evaluated age and sex stratified models. The distribution of sex within MM cases, MGUS cases and controls were each ~60% male and ~40% female. The median age was 61, 66, and 66 years for MM cases, MGUS cases and controls, respectively. PRS ranged from 1.52-4.91, with a median PRS of 3.21 for MM cases, 3.19 for MGUS cases, and 3.05 for controls. PRS was significantly associated with MM risk when assessed continuously (OR=1.19 per SD, p=2.2x10-16) and categorically; compared with the middle quintile (Q3), individuals in the highest quintile (Q5) had a 66% increased MM risk (OR=1.66, p=2.3x10-9) and those in the lowest quintile (Q1) had a 38% decreased MM risk (OR=0.62, p=1.3x10-6). PRS was also significantly associated with MGUS risk (OR=1.19 per SD, p=1.7x10-11); individuals with the highest PRS (Q5) had a 77% increased risk (OR=1.77, p=4.0x10-4) and those with lowest PRS (Q1) had 30% decreased risk (OR=0.70, p=0.04), compared with Q3. When stratified by age and sex, similar associations and trends were found. Using an independent sample of MM / MGUS cases and controls, we showed that a PRS constructed from 23 common genetic variants for MM risk is associated with risk of both MM and MGUS, regardless of age or sex. A future direction of this work is testing associations with PRS and clinical characteristics of the MM cases, as well as differences between MGUS cases that progress and those that do not. Our results suggest that common genetic variation may predispose to MGUS as the precursor to MM. Citation Format: Alyssa I. Clay-Gilmour, Michelle A. Hildebrandt, Nicola J. Camp, Elad Ziv, Elizabeth E. Brown, Jonathan N. Hofmann, John J. Spinelli, Graham G. Giles, Parveen Bhatti, Wendy Cozen, Xifeng Wu, Dennis P. Robinson, Aaron D. Norman, Jason P. Sinnwell, Shaji K. Kumar, S Vincent Rajkumar, Susan L. Slager, Celine M. Vachon. Associations between a polygenic risk score and risk of multiple myeloma and its precursor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2686.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».