Uncovering genes associated with human cardiovascular risk
Notice bibliographique
Résumé
Because cardiovascular risk is determined for a great part by genetic factors, there is considerable interest in finding which allelic variants of which genes associate with either improved or worsened cardiovascular prospects. Up until now, most successes in gene identification have been obtained in genes with such strong effects that they affect the distribution of phenotypes within families in a Mendelian fashion. Unfortunately, susceptibility to most common diseases, including cardiovascular ones, is determined by the interactions between a host of genes (each with weak effects on their own) and environmental factors (which modulate the amplitude of the effect of each gene). By contrast to Mendelian traits, gene variants linked to complex traits are much more difficult to identify. Recent efforts have allowed for the identification of thousands of single nucleotide polymorphisms within all human genes, which should make it possible to perform genome-wide association studies. However, until a way is found to perform such studies in a cost-efficient manner, there is still the need to rely on other means to identify candidate genes whose role can be tested in more traditional association studies. Genetic studies with inbred animal models may be particularly valuable in this regard. It is indeed much easier to detect the phenotypic effects of allelic variants within the controlled background of animals derived from well-defined inbred strains. Moreover, these models provide means to test whether there is a mechanistic link between particular gene variants and a phenotype of interest. For example, in mice, it has been shown that inactivation of the genes coding either for the precursors of natriuretic peptides, or for their receptors, leads to the development of mild hypertension and, to a greater extent, of left ventricular hypertophy (LVH) [1–3]. Similarly, in rat models, there is evidence that naturally occurring variants of the natriuretic peptide precursor A (Nppa) gene are associated with both altered expression of atrial natriuretic factor (ANF) within cardiac ventricles and with LVH [4,5]. Similarly, a polymorphism within the Npr1 promoter correlates with diastolic blood pressure and Npr1 mRNA levels in recombinant inbred rats derived from SHR/BN rat crosses [6]. How about humans? In a Japanese human cohort, a polymorphism that decreases the transcriptional activity of Npr1 (the gene coding for the receptor via which ANF activates guanylate cyclase) was more prevalent in a group of patients with essential hypertension and LVH patients than in a control group [7]. To explore further the possible role of natriuretic peptide-mediated signalling, in this issue of the journal, Pitzalis et al. [8] studied a cohort of Italian patients who were tested for associations with variants of Npr1 and Npr3. The Npr1 polymorphism previously described in a Japanese population was not detected among their Italian patients, but they detected another polymorphism in the 3′-untranslated region of Npr1. Interestingly, the same polymorphism was recently described by others [9], and it appears to have a functional impact on the stability and/or translation of the corresponding mRNA transcript in transfected cells. The present study used young normotensive Italian subjects, and showed that the polymorphism, which was described to be associated with decreased concentration of Npr1 mRNA, was more prevalent in individuals with a positive family history of hypertension. Moreover, individuals who carry that variant of the polymorphism show an increase in isovolumic relaxation time (IVRT) [8]. IVRT is an echo-Doppler index of diastolic filling whose variance is determined for a great part by familial factors [10]. Alterations of diastolic function may constitute one of the earliest signs of ventricular dysfunction, before LVH becomes readily apparent. As with most case–control studies, it is expected that the current study will be followed by many others either confirming or failing to replicate this finding. The most common source of errors in such studies is that of unsuspected and uncontrolled stratification within the case and control populations [11]. One way to improve on the design is to use family-based controls, and such approaches will certainly be desirable in future studies. However, even when family-based controls are used, erroneous conclusions can be drawn because of inappropriate sample size. A good example may be that of the T235 allele of the angiotensinogen gene, which was found to be associated with hypertension in some studies, but not in others [12]. However, a careful review of these studies revealed that this association was rejected mostly in those studies that used inappropriate sample sizes, and thus had low statistical power [12]. Of note, the current study [8] used a fairly small sample size for both its case and control populations. Consequently, the proof will lie in the use of appropriately designed replication studies. Nonetheless, the study by Pitzalis et al. [8] is interesting because it announces an era where particular gene variants will be associated with either improved or worsened cardiovascular prospects. It will be particularly interesting to see whether further human studies confirm a cardioprotective role for natriuretic peptide-mediated signalling, as the latter appears to have important cardiovascular effects in animal models.
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 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».