GWAS of Complete Blood Count (CBC) Measures in 13,403 Blood Donors in the Multi-Racial RBC-Omics Study Reveal Novel Genetic Loci in Minority Populations Which Provide Insights into the Pathways That May Connect Them to Disease
Notice bibliographique
Résumé
Abstract Background: Blood cells, which constitute ~85% of cells in the human body, make fundamental contributions to oxygen transport, hemostasis, healing, and innate and acquired immune responses. Abnormalities of blood cell production and physiological/functional properties in healthy individuals are associated with predisposition to disorders including immunodeficiency, anemia, bleeding disorder, and cancer. However, few causal relationships between blood cell indices, genetics and disease risks have been established. The goal of this study is to identify associations between genetic factors and CBC parameters to gain insight into their regulation. Methods: The REDS-III Red Blood Cell Omics (RBC-Omics) study enrolled 13,403 blood donors at 4 major US blood centers. CBC measures including RBC, HGB, HCT, MCV, RDW, WBC, and PLT, were successfully run among 13,036 subjects including 8,225 non-Hispanic Caucasians, 1,581 African American (AA), 1,600 Asians, which were further stratified into East Asians (likely Chinese, Japanese and Korean ancestry) and South Asians (likely Indian ancestry), 1,009 Caucasian Hispanics, and 621 other or multi-racial donors. DNA was isolated and genotyped using a custom Affymetrix Axiom Transfusion Medicine Array, which contained approximately 875,000 SNPs enriched for blood and transfusion related polymorphisms. Results: Genome wide association in RBC-Omics Caucasians revealed multiple genome wide significant hits for every CBC measure. Comparing our results in Caucasians to the UK Biobank and INTERVAL studies of the same phenotypes revealed significant (P< 0.001) replication of 158 of their 1,080 genome wide significant loci. Further, our results in all donors replicated 89 of the 115 GW significant loci reported in the GWAS catalog with p < 0.00001. Analyses of the GWA results and CBC parameters in RBC-Omics minority donors' samples revealed multiple novel significant genome wide hits as well. For WBC counts, AA were genome wide significant for the genes: SLC1A2; East Asians: BLC9; South Asians: VPS45. For HCT in AA: RBM7/REX02; in South Asians: ENTHD1. For RBC concentrations in AA there were genome wide significance for the genes GAB3 and LUC7L; in South Asians: TEF. For PLT, in AA: NEB; in South Asians: JMJD1C. Additionally, a number of genome wide hits were found in between genes some in highly evolutionarily conserved or regulatory regions. Conclusion: Genetics plays a significant role in the control and regulation of WBC, RBC, and PLT counts as well as other blood related measures such as HCT, RDW, and HGB. Our data strongly replicated the UK Biobank results in Caucasians. We have also identified several novel genes in minority populations. Interestingly genes such as JMJD1C, IFI16, AIM2, and BLC9 have been previously associated with various cancers and leukemia and should be studied for variation in susceptibility to cancers in these populations. Studies in minority populations, when combined with studies in Caucasians, will provide greater insight into the regulation of control of blood. Disclosures Mast: Novo Nordisk: Research Funding.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».