ABERRANT METABOLIC AND SIGNALING PATHWAYS UNDERLIE IMPAIRED STEM CELL FUNCTION IN HUMAN OBESITY
Notice bibliographique
Résumé
Obesity is a major health problem, and it is increasing at an alarming pace in developed and developing countries worldwide. Obesity increases the likelihood for many other diseases, such as type 2 diabetes, coronary heart disease, metabolic syndrome, hyperlipidemia, and some types of cancer. Chronic calorie-overload, genetic predisposition, and physical inactivity are the primary factors contributing to energy imbalance during obesity. In response to a positive energy balance, adipose tissues start expanding to store excessive nutrients in the form of lipids via two mechanisms: 1) by recruiting more adipocyte progenitors, resulting in increased adipocyte number – adipocyte hyperplasia; and 2) through an excessive accumulation of lipids in existing adipocytes – adipocyte hypertrophy. The former process is considered a metabolically healthy way to expand adipose tissue, while the latter is associated with the development of complications, such as insulin resistance. During conditions of chronic energy excess, as is found in obesity, adipose tissue loses its ability to recruit/activate progenitors, and adipose tissue expansion occurs primarily through adipocyte hypertrophy, ultimately resulting in inflamed and dysfunctional adipose tissue. Although studies have looked at hypertrophic and hyperplastic processes during adipocyte development, we still lack a meaningful understanding of the molecular mechanisms contributing to the reduced adipogenesis observed in obesity. In this thesis, I created a metabolic map of healthy and obese human adipogenesis in vitro by using global transcriptomics, proteomics and functional cellular bioenergetics tools, providing a more systematic understanding of normal and obesity-influenced human adipogenesis. I isolated and characterized adipose tissue-resident stem cells (ADSCs) from different healthy, overweight, and obese individuals to create an in vitro model for studying obesity. I found that cells from morbidly obese individuals inherently retained obesity-associated metabolic derangements, and hence, can serve as a cellular model that is very well-suited to study the factors contributing to the reduced adipogenesis that is observed in the context of obesity. By utilizing this model, I identified metabolic aberrations at molecular and functional levels in the two major cellular energy-generating pathways, glycolysis and oxidative phosphorylation. I demonstrate that these pathways drive impaired stem cell function during adipogenesis in obese patient-derived ADSCs. Further, I was able to rescue impaired stem cell function and adipogenesis by stimulating metabolism and improving mitochondrial health in obese cells. In addition, through “omics” approaches, I identified a number of signaling pathways that are aberrantly regulated during obese versus healthy adipogenesis. One such pathway, which was prominently dysregulated in obese cells was the Wnt signaling pathway, wherein observed dynamic changes in Wnt antagonist expression, required for normal adipogenesis, did not occur in these cells. Functional studies revealed that aberrant Wnt signaling closely associated with defects in metabolism, which paralleled my earlier observations obtained through functional metabolic studies in obese cells, suggesting that cellular metabolism can be potentially targeted to improve stem cell function in obese cells. Building on that notion, I developed and validated a novel high-throughput functional drug-screening assay targeting obese adipogenesis, based on functional measurements of metabolic parameters such as mitochondrial activity and induction of the browning of white adipocytes. Overall, this study presents novel insights into the mechanisms that modulate human adipogenic differentiation in obesity, by using disease-relevant in vitro models that can serve as a platform for the discovery of novel therapeutics, offering the opportunity to identify novel targetable pathways and biomarkers for the management of obesity and its associated metabolic complications.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».