Response to: “Clonal Hematopoiesis of Indeterminate Potential and Diabetic Kidney Disease: A Nested Case-Control Study”
Notice bibliographique
Résumé
We read the work of Denicolò et al.1Denicolò S. Vogi V. Keller F. et al.Clonal hematopoiesis of indeterminate potential and diabetic kidney disease: a nested case-control study.Kidney Int Rep. 2022; 7: 876-888https://doi.org/10.1016/j.ekir.2022.01.1064Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar with great interest, reporting a lack of association between clonal hematopoiesis of indeterminate potential (CHIP) and incident or progressive diabetic kidney disease published in KI Reports. A major challenge when investigating CHIP is variant interpretation. Identified variants can represent pathogenic CHIP driver mutations, passenger variants, and variants of uncertain significance, or sequencing artefacts. At present, there is no universal consensus for what variants should be included (or excluded) as CHIP driver variants in the correct clinical context.2Steensma D.P. Bejar R. Jaiswal S. et al.Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes.Blood. 2015; 126: 9-16https://doi.org/10.1182/blood-2015-03-631747Crossref PubMed Scopus (1228) Google Scholar Nevertheless, to minimize false positives, CHIP calling criteria typically prespecify a list of allowable missense variants based on their reported frequencies in CHIP and cancer databases.3Jaiswal S. Natarajan P. Silver A.J. et al.Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease.N Engl J Med. 2017; 377: 111-121https://doi.org/10.1056/NEJMoa1701719Crossref PubMed Scopus (1307) Google Scholar, 4Pascual-Figal D.A. Bayes-Genis A. Díez-Díez M. et al.Clonal hematopoiesis and risk of progression of heart failure with reduced left ventricular ejection fraction.J Am Coll Cardiol. 2021; 77: 1747-1759https://doi.org/10.1016/j.jacc.2021.02.028Crossref PubMed Scopus (75) Google Scholar, 5Dawoud A.A.Z. Gilbert R.D. Tapper W.J. Cross N.C.P. Clonal myelopoiesis promotes adverse outcomes in chronic kidney disease.Leukemia. 2022; 36: 507-515https://doi.org/10.1038/s41375-021-01382-3Crossref PubMed Scopus (30) Google Scholar As the pathogenicity of missense variants can be difficult to predict, in certain genes, only truncating (nonsense, frameshift, or splice site) variants are compatible with CHIP (e.g., BCOR, BCORL1, and CEBPA). By our estimation, 40 of the 127 variants reported by Denicolò et al.1Denicolò S. Vogi V. Keller F. et al.Clonal hematopoiesis of indeterminate potential and diabetic kidney disease: a nested case-control study.Kidney Int Rep. 2022; 7: 876-888https://doi.org/10.1016/j.ekir.2022.01.1064Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar would not be considered CHIP driver variants using the cited conventional criteria.3Jaiswal S. Natarajan P. Silver A.J. et al.Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease.N Engl J Med. 2017; 377: 111-121https://doi.org/10.1056/NEJMoa1701719Crossref PubMed Scopus (1307) Google Scholar, 4Pascual-Figal D.A. Bayes-Genis A. Díez-Díez M. et al.Clonal hematopoiesis and risk of progression of heart failure with reduced left ventricular ejection fraction.J Am Coll Cardiol. 2021; 77: 1747-1759https://doi.org/10.1016/j.jacc.2021.02.028Crossref PubMed Scopus (75) Google Scholar, 5Dawoud A.A.Z. Gilbert R.D. Tapper W.J. Cross N.C.P. Clonal myelopoiesis promotes adverse outcomes in chronic kidney disease.Leukemia. 2022; 36: 507-515https://doi.org/10.1038/s41375-021-01382-3Crossref PubMed Scopus (30) Google Scholar Inclusion of benign or misclassified variants would increase CHIP prevalence but may bias results toward the null hypothesis because they would be expected to be evenly represented across groups. Certainly, many challenges remain and there is much to learn about the classification and consequences of acquired variants in CHIP driver genes. Nevertheless, the conventional CHIP variant criteria have been used to establish various clinical consequences of CHIP.3Jaiswal S. Natarajan P. Silver A.J. et al.Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease.N Engl J Med. 2017; 377: 111-121https://doi.org/10.1056/NEJMoa1701719Crossref PubMed Scopus (1307) Google Scholar, 4Pascual-Figal D.A. Bayes-Genis A. Díez-Díez M. et al.Clonal hematopoiesis and risk of progression of heart failure with reduced left ventricular ejection fraction.J Am Coll Cardiol. 2021; 77: 1747-1759https://doi.org/10.1016/j.jacc.2021.02.028Crossref PubMed Scopus (75) Google Scholar, 5Dawoud A.A.Z. Gilbert R.D. Tapper W.J. Cross N.C.P. Clonal myelopoiesis promotes adverse outcomes in chronic kidney disease.Leukemia. 2022; 36: 507-515https://doi.org/10.1038/s41375-021-01382-3Crossref PubMed Scopus (30) Google Scholar The significance to human health of somatic variants that fall outside of this list are less well understood. We hope to highlight some of the challenges in determining the pathogenicity of putative CHIP variants and the need for sensitivity analyses using strict and liberal CHIP definitions. ResponseKidney International ReportsVol. 7Issue 11PreviewAs the authors of the letter mention, it is a major challenge to interpret variants when investigating clonal hematopoiesis of indeterminate potential (CHIP). Undoubtedly, there are possibilities to identify passenger variants, benign variants, variants of uncertain significance, and sequencing artifacts. However, as the authors also mention, we currently do not have a universal consensus on which variants should be included or excluded as CHIP driver variants in which disease context. Furthermore, CHIP is not defined by a certain range above a variant allele frequency of 2%. Full-Text PDF Open Access
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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 tête enseignante, 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 ».