Project description:Dipeptidyl peptidase 3 (DPP3) is a zinc-dependent hydrolase involved in degrading oligopeptides with 4-12 amino acid residues. It has been associated with several pathophysiological processes, including blood pressure regulation, pain signaling, and cancer cell defense against oxidative stress. However, the physiological substrates and the cellular pathways that are potentially targeted by DPP3 to mediate these effects remain unknown. Here, we show that global DPP3 deficiency in mice (DPP3-/-) affects the renin-angiotensin system (RAS). LC-MS-based profiling of circulating angiotensin peptides revealed elevated levels of angiotensin II, III, IV, and 1-5 in DPP3-/- mice, whereas blood pressure, renin activity, and aldosterone levels remained unchanged. Activity assays using the purified enzyme confirmed that angiotensin peptides are substrates for DPP3. Aberrant angiotensin signaling was associated with substantially higher water intake and increased renal reactive oxygen species formation in the kidneys of DPP3-/- mice. The metabolic changes and altered angiotensin levels observed in male DPP3-/- mice were either absent or attenuated in female DPP3-/- mice, indicating sex-specific differences. Taken together, our observations suggest that DPP3 regulates the RAS pathway and water homeostasis by degrading circulating angiotensin peptides.
Project description:AimsRecently, dipeptidyl peptidase 3 (DPP3) has been discovered as the peptidase responsible for cleavage of angiotensin (1-7) [Ang (1-7)]. Ang (1-7) is part of the angiotensin-converting enzyme-Ang (1-7)-Mas pathway which is considered to antagonize the renin-angiotensin-aldosterone system (RAAS). Since DPP3 inhibits the counteracting pathway of the RAAS, we hypothesize that DPP3 might be deleterious in the setting of heart failure. However, no data are available on DPP3 in chronic heart failure. We therefore investigated the clinical characteristics and outcome related to elevated DPP3 concentrations in patients with worsening heart failure.Methods and resultsDipeptidyl peptidase 3 was measured in 2156 serum samples of patients with worsening heart failure using luminometric immunoassay (DPP3-LIA) by 4TEEN4 Pharmaceuticals GmbH, Hennigsdorf, Germany. Predictors of DPP3 levels were selected using multiple linear regression with stepwise backward selection. Median DPP3 concentration was 11.45 ng/mL with a range from 2.8 to 84.9 ng/mL. Patients with higher DPP3 concentrations had higher renin [78.3 (interquartile range, IQR 26.3-227.7) vs. 120.7 IU/mL (IQR 34.74-338.9), P < 0.001, for Q1-3 vs. Q4] and aldosterone [88 (IQR 44-179) vs. 116 IU/mL (IQR 46-241), P < 0.001, for Q1-3 vs. Q4] concentrations. The strongest independent predictors for higher concentration of DPP3 were log-alanine aminotransferase, log-total bilirubin, the absence of diabetes, higher osteopontin, fibroblast growth factor-23 and N-terminal pro-B-type natriuretic peptide concentrations (all P < 0.001). In univariable survival analysis, DPP3 was associated with mortality and the combined endpoint of death or heart failure hospitalization (P < 0.001 for both). After adjustment for confounders, this association was no longer significant.ConclusionsIn patients with worsening heart failure, DPP3 is a marker of more severe disease with higher RAAS activity. It may be deleterious in heart failure by counteracting the Mas receptor pathway. Procizumab, a specific antibody against DPP3, might be a potential future treatment option for patients with heart failure.
Project description:DPP (dipeptidyl peptidase)-4 inhibitors are antidiabetic drugs that may increase heart failure in high-risk patients. NPY (neuropeptide Y) is coreleased with norepinephrine, causes vasoconstriction via the Y1 receptor, and is degraded by DPP4 to NPY (3-36) in vitro. NPY (3-36) decreases release of norepinephrine via the Y2 receptor. We tested the hypothesis that DPP4 inhibition would potentiate the vasoconstrictor effect of NPY. Eighteen nonsmokers (12 healthy controls and 6 with type 2 diabetes mellitus) participated in 1 of 2 randomized, double-blind, placebo-controlled crossover studies. First, subjects were randomized to order of treatment with sitagliptin 100 mg/d versus placebo for 7 days separated by 4-week washout. On the last day of treatment, NPY was infused by brachial artery and forearm blood flow was measured using plethysmography. Blood samples were collected after each dose. NPY infusions were repeated after 90-minute washout and intra-arterial enalaprilat. Second, 5 healthy subjects were randomized to crossover treatment with sitagliptin 100 mg/d plus valsartan 160 mg/d versus placebo plus valsartan. NPY infusions were performed on the seventh day of treatment. NPY caused dose-dependent vasoconstriction. During enalaprilat, sitagliptin significantly potentiated NPY-induced vasoconstriction in controls and diabetics ( P≤0.02 for forearm blood flow in either group). Baseline norepinephrine release was increased during sitagliptin and enalaprilat, but not further by NPY. Sitagliptin increased the ratio of NPY to NPY (3-36). During valsartan, sitagliptin also significantly potentiated NPY-induced vasoconstriction ( P=0.009 for forearm blood flow). Potentiation of endogenous NPY could contribute to cardiovascular effects of DPP4 inhibitors in patients taking an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker.
Project description:Peripheral vision is fundamentally limited by the spacing between objects. When asked to report a target's identity, observers make erroneous reports that sometimes match the identity of a nearby distractor and sometimes match a combination of target and distractor features. The classification of these errors has previously been used to support competing 'substitution' [1] or 'averaging' [2] models of the phenomenon known as 'visual crowding'. We recently proposed a single model in which both classes of error occur because observers make their reports by sampling from a biologically-plausible population of weighted responses within a region of space around the target [3]. It is critical to note that there is no probabilistic substitution or averaging process in our model; instead, we argue that neither substitution nor averaging occur, but that these are misclassifications of the distribution of reports that emerge when a population response distribution is sampled. This is a fundamentally different way of thinking about crowding, and on this basis we claim to have provided a mechanism unifying categorically distinct perceptual errors. Our goal was not to model all crowding phenomena, such as the release from crowding when target and flanks differ in color or depth [4]. Pachai et al.[5] have suggested that our model is not unifying because it inaccurately predicts perceptual performance for a particular stimulus. Although we agree that our model does not predict their data, this specific demonstration overlooks the critical aspect of the model: perceptual reports are drawn from a weighted population code. We show that Pachai et al.'s [5] own data actually provide evidence for the population code we have described [3], and we suggest a biologically-plausible analysis of their stimuli that provides a computational basis for their 'grouping' account of crowding.