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Enregistrement W4312019809 · doi:10.1210/endocr/bqac211

β-Cell Stress Pathways in Diabetes: Potential Targets for Therapy?

2022· letter· en· W4312019809 sur OpenAlexafffundabout
S M Niazur Rahman, Adria Giacca

Notice bibliographique

RevueEndocrinology · 2022
Typeletter
Langueen
DomaineMedicine
ThématiquePancreatic function and diabetes
Établissements canadiensUniversity of Toronto
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésLibrary scienceDiabetes mellitusMedicineInternal medicineFamily medicineEndocrinologyComputer science

Résumé

récupéré en direct d'OpenAlex

Synthesis and release of insulin from β cells are essential for glucose homeostasis and overall metabolism. Insulin insufficiency (absolute or relative to insulin resistance) leads to the development of diabetes, which is a global epidemic affecting nearly 500 million people. Autoimmunity-mediated islet inflammation resulting in death of β cells is the major cause of insulin insufficiency in type 1 diabetes (T1D), whereas metabolic inflammation due to glucotoxicity and lipotoxicity is implicated in the progression of β-cell failure in type 2 diabetes (T2D). Oxidative stress, endoplasmic reticulum (ER) stress, mitochondrial dysfunction (1), and, more recently, senescence and dysfunctional autophagy have been identified as common to β-cell pathology of both T1D and T2D (2). The presence of these processes imposes stress on the β cells, which eventually fail to maintain the regulated insulin production, leading to the onset of diabetes. In a recent issue of Endocrinology, Kulkarni et al (2) reviewed major β-cell stress pathways involved in diabetes. Oxidative stress occurs due to imbalance between the formation and scavenging of reactive oxygen species (ROS). Physiological ROS production in mitochondria and peroxisomes during metabolic activity, hyperglycemia, and elevated free fatty acids trigger ROS formation. While ROS are important for cell physiology, excessive accumulation may cause widespread damage to cells and the progression of diabetes pathogenesis by activating extracellular signal-regulated kinase, and c-Jun N-terminal kinase–mediated β-cell apoptosis. Moreover, ROS can promote the production of the cytokines interleukin 6 and tumor necrosis factor α through the nuclear factor-κB and activator protein 1 pathway and induce inflammation in β cells (1). In turn, cytokines can produce ROS. Importantly, β cells are prone to oxidative damage due to weak antioxidant defense. Mitochondria are the primary site for ROS production and these organelles contain their own mitochondrial DNA (mtDNA). mtDNA is very susceptible to oxidative stress–induced mutation as it is not protected by histones and because mitochondrial DNA polymerase repair activity is low. Many reports in the literature indicate mitochondrial dysfunction as a major cause of hyperglycemia-mediated ROS generation through the electron transport chain, which triggers oxidative damage pathways (1). Another process described by Kulkarni et al is ER stress, which is a major contributor to β-cell dysfunction. ER is the key organelle that controls protein synthesis, folding, and overall quality. β Cells have widely distributed ER in their cytoplasm to meet the demand for insulin to maintain glucose homeostasis. ER stress is triggered by high insulin demands to compensate for insulin resistance and for the loss of β-cell mass. Glucotoxicity and lipotoxicity also cause β-cell ER stress (1). Misfolded proteins produced during ER stress can act as neoantigens that activate immune reactions in T1D. For survival during ER stress, cells initiate the unfolded protein response (UPR) pathway, which includes reducing protein synthesis, increasing the ER size, upregulation of chaperones to enhance protein folding, and activation of ER-associated degradation to increase unfolded protein clearance. During acute ER stress, UPR affords cytoprotection by activating ER resident sensors: activating transcription factor 6, inositol-requiring enzyme 1α, and protein kinase RNA-like endoplasmic reticulum kinase (PERK), which upregulates their downstream target genes leading to ER-associated degradation of defective proteins. However, chronic ER stress results in UPR sensor–mediated cellular apoptosis through the activation of proapoptotic genes and their downstream factors. The PERK pathway is shared between ER stress and the integrated stress response (ISR) that can be initiated by viral infections and nutrient deprivation. Not much is known about ISR and diabetes, although some viral infections have been implicated in the pathogenesis of T1D. Mitochondria and ER are tightly interconnected through mitochondria-associated ER membranes (MAMs). As MAMs allow the exchange of metabolites between both organelles to maintain homeostasis, each one is affected by the oxidative stress of the other. Oxidative stress can induce ER stress and vice versa and hyperglycemia, as mentioned above, can induce both (2, 3). If the β-cell stress remains unmitigated, UPR-mediated irreparable cellular damage leads to cellular senescence. Senescent cells are resistant to apoptosis and secrete mediators that promote immune cell migration to the islets in both T1D and T2D leading to insulin insufficiency (4, 5). Kulkarni et al also reviewed the role of autophagy in β-cell physiology. In general, autophagy plays a crucial role in maintaining cellular homeostasis through the self-digestion of cellular substances or proteins generated by stress. Mitochondrial ROS and misfolded protein in the ER act as modulators of autophagy activation that alleviates β-cell ER and oxidative stress. In both T1D and T2D, autophagy is dysfunctional (6, 7). All of these processes (oxidative stress, ER stress, senescence, dysfunctional autophagy) are interconnected as Kulkarni et al's review indicates, and are associated with inflammation, initiated in T1D by autoimmunity and metabolically mediated in T2D. Animal models have greatly contributed to the understanding of these mechanisms of β-cell dysfunction and loss that have increased our knowledge of the pathogenesis of both T1D and T2D. So far, however, this knowledge has not been translated into effective treatment, as general anti-inflammatory strategies have yielded marginal results in both T1D and T2D (8) whereas antioxidant and anti-ER stress agents effective in animals have failed in humans. Presumably, combined treatment and intervention in very early stages or preventive treatment is required. It is also possible that pathogenesis-based treatment is best effective only when key initiating factors of β-cell dysfunction and loss are addressed, such as cytotoxic T cells in T1D via teplizumab and nutrient overload via bariatric surgery in obesity-associated T2D. Nevertheless, limiting β-cell dysfunction and loss, however initiated, via directly addressing β-cell stress could also be of therapeutic value and the stress pathways elucidated by Kulkarni et al's interesting and comprehensive review could provide targets for future treatments. Research on β cells in the Giacca laboratory is supported by the Canadian Institutes of Health Research (Grant # 507485 to A.G.). S.M.N.R was supported by a Banting and Best Diabetes Centre-Novo Nordisk Scholarship. The authors have nothing to disclose. Data sharing does not apply to this article as no data sets were generated or analyzed during the present study. endoplasmic reticulum integrated stress response mitochondria-associated ER membrane mitochondrial DNA PKR-like endoplasmic reticulum kinase reactive oxygen species type 1 diabetes type 2 diabetes unfolded protein response

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,090
Score d'incertitude au seuil0,302

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0040,003
Science ouverte0,0010,002
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0900,034

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,245
Écart entre enseignants0,222 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2022
Routes d'admission3
Résumé présentoui

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