Prospective Evaluation of Fetal Haemoglobin Induction in Maternal Erythrocytes: A Preliminary Analysis of a Cohort of 345 Parturients
Notice bibliographique
Résumé
Abstract Introduction. The mechanisms of haemoglobin (Hb) subtype switch remain largely unknown even though it has a therapeutic potential (Bauer et al., 2012). In fact, reactivation of fetal haemoglobin (HbF) production in adult erythrocytes (F-cells) is protective in many Hb disorders. Pregnancy may represent the only physiological condition where HbF production increases transiently (Ibrahim et al, 2009; Yamada et al., 2012). Moreover, flow cytometry (FC), by intracellular staining using anti-HbF antibodies, has improved the evaluation of maternal F-cells (Corcoran et al., 2014; Chen et al., 2000). In this study, the objectives are: 1) to document HbF expression prospectively peri- and post-partum and confirm its maternal origin; 2) to assess potential causes of HbF modulation throughout pregnancy (i.e. β-hCG, EPO) and; 3) to identify gene differences between HbF-positive and HbF-negative pregnant women. Methods. In this observational, single institution, prospective study, 879 pregnant women were screened. A total of 345 participants were included in the study: the first consecutive 176 women with negative total HbF expression (<1%), and the first consecutive 169 women with positive total HbF expression (≥1%). Hb studies were conducted with high performance liquid chromatography (HPLC), and FC was performed if total HbF expression was ≥1%. Other assessments included DNA sampling, complete blood counts, β-hCG and EPO levels, and qualitative data (i.e. to account for other factors such as tobacco, progesterone use, etc.). Analyses were conducted at each trimester except DNA sampling, which was done during the first visit only. HbF-positive women had an additional post-partum visit to assess changes of HbF expression and account for hereditary persistence of HbF. Descriptive statistics and Pearson correlations were planned for this analysis. Results. At the time of analysis, 93 HbF-positive and 147 HbF-negative women had completed follow-up. Results revealed that, among all pregnant women screened, 22.07% (n = 194) had positive HbF expression. Of this percentage, 90.72% (n = 176) filled the inclusion criteria. Of all women with positive HbF expression during 1 or more of the first 3 visits, 72.04% showed a post-partum decrease of HbF below 1%. Furthermore, FC analyses in HbF-positive women confirmed the maternal origin of HbF in all cases and revealed an average of 13.28% (sd = 5.38%) F-cells when total HbF was ≥ 1%. Only modest correlations could be found so far between HbF levels and β-hCG (ρ = 0.25) or EPO (ρ = 0.07). Comparative DNA analyses of HbF-positive and HbF-negative women are currently underway and will be presented at the meeting. Conclusions. To our knowledge, this represents the largest prospective study evaluating HbF expression throughout pregnancy, as well as the first to evaluate post-partum HbF dynamics and the genetic background of HbF-negative and HbF-positive pregnant women. Preliminary data shows that: 1) a significant percentage of pregnant women have a transient elevation of HbF which cannot be explained by fetomaternal hemorrhage nor hereditary persistence of HbF; 2) the proportion of F-cells in women remains constant peri- and post-partum when HbF ≥ 1%; 3) a large proportion of maternal erythrocytes express HbF at low levels and; 4) HbF modulation during pregnancy is only modestly correlated to β-hCG and EPO. These data may lead to the study of a new paradigm of Hb subtype switch as well as HbF-induction therapeutics for the benefit of Hb disorders. Disclosures No relevant conflicts of interest to declare.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 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 ».