Rachel E. Stamateris

Bio: Rachel E. Stamateris is an academic researcher from University of Massachusetts Medical School. The author has contributed to research in topics: Insulin & Cyclin D2. The author has an hindex of 6, co-authored 6 publications receiving 516 citations.

Insulin demand regulates β cell number via the unfolded protein response

Abstract: Although stem cell populations mediate regeneration of rapid turnover tissues, such as skin, blood, and gut, a stem cell reservoir has not been identified for some slower turnover tissues, such as the pancreatic islet. Despite lacking identifiable stem cells, murine pancreatic β cell number expands in response to an increase in insulin demand. Lineage tracing shows that new β cells are generated from proliferation of mature, differentiated β cells; however, the mechanism by which these mature cells sense systemic insulin demand and initiate a proliferative response remains unknown. Here, we identified the β cell unfolded protein response (UPR), which senses insulin production, as a regulator of β cell proliferation. Using genetic and physiologic models, we determined that among the population of β cells, those with an active UPR are more likely to proliferate. Moreover, subthreshold endoplasmic reticulum stress (ER stress) drove insulin demand-induced β cell proliferation, through activation of ATF6. We also confirmed that the UPR regulates proliferation of human β cells, suggesting that therapeutic UPR modulation has potential to expand β cell mass in people at risk for diabetes. Together, this work defines a stem cell-independent model of tissue homeostasis, in which differentiated secretory cells use the UPR sensor to adapt organ size to meet demand.

Adaptive β-cell proliferation increases early in high-fat feeding in mice, concurrent with metabolic changes, with induction of islet cyclin D2 expression

Abstract: Type 2 diabetes (T2D) is caused by relative insulin deficiency, due in part to reduced β-cell mass (11, 62). Therapies aimed at expanding β-cell mass may be useful to treat T2D (14). Although feedi...

Glucose Induces Mouse β-Cell Proliferation via IRS2, MTOR, and Cyclin D2 but Not the Insulin Receptor

Abstract: An important goal in diabetes research is to understand the processes that trigger endogenous β-cell proliferation. Hyperglycemia induces β-cell replication, but the mechanism remains debated. A prime candidate is insulin, which acts locally through the insulin receptor. Having previously developed an in vivo mouse hyperglycemia model, we tested whether glucose induces β-cell proliferation through insulin signaling. By using mice lacking insulin signaling intermediate insulin receptor substrate 2 (IRS2), we confirmed that hyperglycemia-induced β-cell proliferation requires IRS2 both in vivo and ex vivo. Of note, insulin receptor activation was not required for glucose-induced proliferation, and insulin itself was not sufficient to drive replication. Glucose and insulin caused similar acute signaling in mouse islets, but chronic signaling differed markedly, with mammalian target of rapamycin (MTOR) and extracellular signal-related kinase (ERK) activation by glucose and AKT activation by insulin. MTOR but not ERK activation was required for glucose-induced proliferation. Cyclin D2 was necessary for glucose-induced β-cell proliferation. Cyclin D2 expression was reduced when either IRS2 or MTOR signaling was lost, and restoring cyclin D2 expression rescued the proliferation defect. Human islets shared many of these regulatory pathways. Taken together, these results support a model in which IRS2, MTOR, and cyclin D2, but not the insulin receptor, mediate glucose-induced proliferation.

CDKN2A/B T2D GWAS Risk-SNPs Impact Locus Gene Expression and Proliferation in Human Islets

Abstract: Genome-wide association studies link the CDKN2A/B locus with type 2 diabetes (T2D) risk, but mechanisms increasing risk remain unknown. The CDKN2A/B locus encodes cell cycle inhibitors p14, p15, and p16; MTAP; and ANRIL, a long noncoding RNA. The goal of this study was to determine whether CDKN2A/B T2D risk SNPs impact locus gene expression, insulin secretion, or β-cell proliferation in human islets. Islets from donors without diabetes (n = 95) were tested for SNP genotype (rs10811661, rs2383208, rs564398, and rs10757283), gene expression (p14, p15, p16, MTAP, ANRIL, PCNA, KI67, and CCND2), insulin secretion (n = 61), and β-cell proliferation (n = 47). Intriguingly, locus genes were coregulated in islets in two physically overlapping cassettes: p14-p16-ANRIL, which increased with age, and MTAP-p15, which did not. Risk alleles at rs10811661 and rs2383208 were differentially associated with expression of ANRIL, but not p14, p15, p16, or MTAP, in age-dependent fashion, such that younger homozygous risk donors had higher ANRIL expression, equivalent to older donor levels. We identified several risk SNP combinations that may impact locus gene expression, suggesting possible mechanisms by which SNPs impact locus biology. Risk allele carriers at ANRIL coding SNP rs564398 had reduced β-cell proliferation index. In conclusion, CDKN2A/B locus SNPs may impact T2D risk by modulating islet gene expression and β-cell proliferation.

Metabolic syndrome: a closer look at the growing epidemic and its associated pathologies.

Abstract: Summary Obesity is reaching epidemic proportions with recent worldwide figures estimated at 1.4 billion and rising year-on-year. Obesity affects all socioeconomic backgrounds and ethnicities and is a pre-requisite for metabolic syndrome. Metabolic syndrome is a clustering of risk factors, such as central obesity, insulin resistance, dyslipidaemia and hypertension that together culminate in the increased risk of type 2 diabetes mellitus and cardiovascular disease. As these conditions are among the leading causes of deaths worldwide and metabolic syndrome increases the risk of type 2 diabetes mellitus fivefold and cardiovascular disease threefold, it is of critical importance that a precise definition is agreed upon by all interested parties. Also of particular interest is the relationship between metabolic syndrome and cancer. Metabolic syndrome has been associated with a plethora of cancers including breast, pancreatic, colon and liver cancer. Furthermore, each individual risk factor for metabolic syndrome has also an association with cancer. Our review collates internationally generated information on metabolic syndrome, its many definitions and its associations with life-threatening conditions including type 2 diabetes mellitus, cardiovascular disease and cancer, providing a foundation for future advancements on this topic.

A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.

Abstract: Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare epsilon-cells; exocrine cell types; vascular cells; Schwann cells; quiescent and activated stellate cells; and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles and validated their existence with immuno-histochemistry stains. Moreover, among human beta- cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress. Finally, we deconvolved bulk gene expression samples using the single-cell data to detect disease-associated differential expression. Our dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.

The genetic architecture of type 2 diabetes

Abstract: The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

SGLT2 Inhibitors May Predispose to Ketoacidosis

Abstract: Context: Sodium glucose cotransporter 2 (SGLT2) inhibitors are antidiabetic drugs that increase urinary excretion of glucose, thereby improving glycemic control and promoting weight loss. Since approval of the first-in-class drug in 2013, data have emerged suggesting that these drugs increase the risk of diabetic ketoacidosis. In May 2015, the Food and Drug Administration issued a warning that SGLT2 inhibitors may lead to ketoacidosis. Evidence Acquisition: Using PubMed and Google, we conducted Boolean searches including terms related to ketone bodies or ketoacidosis with terms for SGLT2 inhibitors or phlorizin. Priority was assigned to publications that shed light on molecular mechanisms whereby SGLT2 inhibitors could affect ketone body metabolism. Evidence Synthesis: SGLT2 inhibitors trigger multiple mechanisms that could predispose to diabetic ketoacidosis. When SGLT2 inhibitors are combined with insulin, it is often necessary to decrease the insulin dose to avoid hypoglycemia. The lower dose of insuli...