Discovery of peptides as key regulators of metabolic and cardiovascular crosstalk.

Most peptide hormones were discovered between the early and late 20th century using biochemical methods, with the hypothalamus, gastrointestinal tract, and pancreas being the main organs of synthesis. The identification of gastrin in 1905, a 17-mer peptide made in the gastrointestinal tract, laid the foundation for understanding how peptides stimulate acid secretion. 14 Another early example is cholecystokinin (CCK), which was identified using classical biochemical and physiological methods in 1928 by Ivy and Oldberg. They generated crude extracts from the small intestine that demonstrated the capacity to stimulate the gallbladder to contract and release bile, suggesting the existence of a “secretin.” Edman degradation and immunohistochemical methods later revealed that CCK is a 33-mer peptide hormone not only produced in the small intestine but also present in the brain, where it regulates satiety and food intake in rats and rhesus monkeys. 15 In the early days, biochemical purification methods, often referred to as “bucket” biochemistry, were used to identify new peptides. The lack of advanced analytical techniques meant that purification was slow and prone to contamination, often requiring repeated fractionation using basic chromatography and centrifugation. For example, groundbreaking work to identify corticotropin-releasing hormone (CRH), led by Wylie Vale and his colleagues at the Salk Institute, undertook the overwhelming task of extracting 490,000 fragments of ovine (sheep) hypothalami. 16 This extensive effort allowed for the identification of CRH through fractionation. However, these experiments were difficult due to the instability of peptides, 17 , 18 difficulties in their purification, 19 and lack of sensitive detection techniques. 16 They required large tissue samples and were prone to contamination, leading to slow and inefficient identification processes. Modern approaches, including MS-based peptidomics 12 , 16 and bioinformatics-driven predictions, 20 , 21 have improved peptide identification but still face obstacles, which are described in detail in the following sections. Table 1 lists the known peptide hormones to date and their functions, receptors, and use as therapeutics.

Computational in silico methods also have the potential to speed up the discovery of new peptides and will likely become invaluable for predicting peptide sequences and structures, 72 but these methods are still in their infancy. 80 Several databases and tools are available for peptide hormone discovery, providing curated information on known peptides and their sequences, structures, and biological activities. 67 , 81 – 83 Algorithms based on machine learning, homology modeling, and molecular dynamics simulations can predict potential peptide hormones. 84 These in silico approaches can, in principle, rapidly screen large datasets, identifying candidates for further experimental validation. 85 Recent computational models, such as DeepNeuropePred 20 and MultiPep, 21 offer promising tools for predicting peptide cleavage sites. However, their accuracy is limited by incomplete datasets and a lack of experimental validation. 20 , 70 DeepNeuropePred 86 is a learning method for detecting cleavage sites in neuropeptide precursors by predicting the neuropeptide cleavage sites from precursors independent of species. Here, 717 precursors as the independent training dataset were used to predict the cleavage sites of a test set of 31 precursors. Five of the predicted peptides were validated against a published MS dataset of a stick insect, Carausius morosus , but no other peptides have been identified using this method. While the performance of this tool against a training dataset was excellent, this paper did not describe any new peptide candidates. MultiPep 20 , 21 is another machine learning method to predict peptide fragments by identifying cleavage sites. They first identified 75 neuropeptide precursors in the rhesus monkey genome and used a supervised machine learning algorithm for classification to predict cleavage sites. This algorithm separates data points into distinct categories—in this case, identifying where cleavage sites are likely to occur in precursor proteins. These predictions were then compared to assignments based on homology to human sequences, achieving a cleavage classification accuracy of over 97% for both human and rhesus datasets. Similar methods include methods for the prediction of peptides using cleavage site annotation. 59 , 87 , 88 While potentially useful, the above-mentioned methods have not been used to identify novel peptides. More recently, Secher et al. 89 developed an algorithm to streamline peptide complexity, facilitating the identification of biologically relevant peptides. When applied to the rat hypothalamus, this pipeline enabled the successful identification of thousands of neuropeptides, as well as their associated PTMs. In their approach, peptidomics was conducted under various conditions, and peptides were then selected based on their annotations as prohormones. Unlike PeptideAtlas, the samples were not trypsinized and were computationally filtered for known prohormones. However, a limitation of this method is that new, unannotated prohormones are excluded from the analysis. As a proof of concept, this method enabled large-scale neuropeptide identification in the rat hypothalamus, revealing a wide array of PTMs. The study presents 54 potentially novel peptides derived from 21 precursor proteins. Unfortunately, this promising study did not test the bioactivity of these peptides. In summary, while some tools and analytical frameworks for peptidomics primarily support the validation and mapping of known peptides, others have enabled the prediction of novel peptide fragments and cleavage variants. The major limitation is that peptide prediction needs to be combined not only with MS for detection but also with appropriate screening methods to identify the biologically relevant peptides.

Classical purification techniques, along with transcriptomics and proteomics, have led to the discovery of previously unknown peptide functions and novel therapeutic targets. 13 For example, the development of GLP-1 receptor agonists, directly inspired by the role of GLP-1 in glucose homeostasis, has revolutionized the treatment of type 2 diabetes and obesity. 1 , 90 Many peptides function as hormones, traveling through the bloodstream to affect distant organs, while others act locally, serving as short-range signals between neighboring cells ( Table 1 ). This section focuses on apelin, obestatin, and amylin as three examples of metabolic and cardiovascular crosstalk. These peptides have been identified as mediators of interorgan crosstalk, particularly in the regulation of cardiovascular function, metabolic homeostasis, and energy balance. These peptides have also drawn increasing attention for their potential therapeutic applications in conditions such as heart failure, obesity, and diabetes. Understanding their signaling mechanisms provides valuable insights as examples of how these peptides can control systemic physiology. Apelin, a 77-amino-acid peptide, coordinates various physiological processes, including glucose metabolism, cardiovascular function, and fluid homeostasis ( Figure 1 ). Apelin binds to the apelin receptor (APJ), 91 a GPCR structurally similar to the angiotensin II receptor but with distinct physiological functions. The crystal structure of APJ complexed with G proteins has revealed insights into the molecular interactions that facilitate apelin binding and downstream signaling. Upon apelin binding, the APJ receptor undergoes a conformational change that allows coupling of the Gαi and Gq/i subtypes. 91 APJ activation leads to elevated intracellular calcium levels and activates many signaling pathways, including PI3K/AKT, MAPK/ERK, and AMPK, depending on the cell type, which play roles in cellular proliferation, survival, and migration. Apelin acts directly on vascular endothelial cells. This interaction stimulates several downstream effects, including the activation of endothelial nitric oxide synthase (eNOS) in endothelial cells, leading to nitric oxide (NO) production. NO acts as a vasodilator, contributing to the regulation of blood pressure and vascular tone, promoting vasodilation, and enhancing blood flow. The NO-mediated response is particularly beneficial in managing hypertension and heart failure. 92 Furthermore, apelin is also expressed in the kidney, where it interacts with vasopressin in renal tubules to enhance fluid absorption and sodium balance. In chronic heart failure, reduced cardiac output leads to decreased blood flow to the kidneys, which triggers the kidneys to retain more sodium and water in an attempt to increase blood volume and pressure. This compensatory mechanism often worsens fluid overload, contributing to edema and further stressing the heart. Apelin can help counteract the effects of fluid overload in chronic heart failure by promoting vasodilation and inhibiting sodium and water reabsorption in the kidneys. 93 In other peripheral metabolic tissues, apelin controls glucose homeostasis by increasing glucose uptake and insulin sensitivity, mainly in skeletal muscle and adipose tissue. 94 The mechanism proposed is direct activation of the AMPK pathway, leading to increased glucose transport and utilization in muscle cells, complementing insulin’s action. 7 Apelin can also improve lipid metabolism by promoting lipolysis, which could be useful in metabolic syndrome and diabetes management. 95 However, apelin-induced lipolysis could potentially lead to increased circulating free fatty acids, which, in prolonged activation, might contribute to lipotoxicity or insulin resistance in tissues sensitive to lipid overload, such as the liver or pancreas. Ongoing clinical trials of apelin receptor agonists include studies targeting heart failure, muscle atrophy, obesity, and chronic kidney disease (CKD). Another pressing question is the pharmacokinetics and safety of apelin analogs or agonists in clinical applications, as there are currently no robust trials assessing the long-term effects or potential desensitization of the APJ receptor. 48 A key area of debate is the specificity of apelin’s receptor interactions and signaling pathways. Although APJ is structurally similar to AT1R, it mediates distinct physiological effects that are not yet fully understood. This is particularly true for tissue-specific signaling. APJ activation promotes vasodilation, metabolic regulation, and fluid homeostasis, in contrast to the vasoconstrictive and pro-inflammatory effects of angiotensin II signaling. Some studies suggest that APJ may form heterodimers with AT1R, influencing angiotensin-mediated responses, 96 , 97 but the physiological relevance of this interaction remains unclear. Additionally, APJ exhibits ligand-dependent signaling bias, where different ligands or cellular contexts preferentially activate specific pathways, complicating efforts to develop selective therapeutics. 48 For instance, while apelin binding typically activates Gαi and Gq/i pathways, synthetic agonists may trigger alternative downstream signaling responses with distinct physiological outcomes. 98 Furthermore, APJ has been proposed to function as a decoy receptor for angiotensin II, potentially regulating angiotensin-induced cardiovascular effects and protecting against hypertension and heart failure. 99 However, the mechanisms underlying this interaction remain speculative, with some studies reporting a modulatory role for APJ in angiotensin II signaling, while others suggest independent and distinct signaling pathways. 100 Therefore, there is a need to understand the molecular mechanisms governing APJ signaling and its therapeutic potential, particularly in the context of tissue-specific responses, biased agonism, and receptor crosstalk. Obestatin, a peptide hormone derived from the same precursor as ghrelin, primarily acts like a hormone, although its exact physiological role and mechanisms are still being clarified. Obestatin was initially identified for its antagonistic effects of ghrelin, primarily in the regulation of food intake. 37 , 101 However, recent studies suggest that the role of obestatin extends far beyond simple antagonism, contributing significantly to the coordination of various organ systems, particularly in inflammatory and metabolic pathways ( Figure 2 ). The role of obestatin in cardiovascular functions includes modulation of blood pressure and inflammation. Studies suggest that obestatin has vasodilatory effects, likely mediated through increased NO production, contributing to improved blood flow in both peripheral and central circulations. 102 Obestatin exerts protective effects within the gastrointestinal tract, particularly in reducing inflammation and promoting mucosal healing in conditions like colitis. 103 It achieves this through the downregulation of pro-inflammatory cytokines, suggesting a role in maintaining gut barrier integrity. 104 In adipose tissue, it inhibits lipogenesis and stimulates lipolysis through activation of GPR39 receptors, enhancing insulin sensitivity. 105 In the liver, obestatin has protective roles in non-alcoholic fatty liver disease, reducing lipid accumulation and improving insulin signaling. 106 These actions highlight the potential of obestatin in regulating both local tissue metabolism and systemic energy homeostasis, which is especially relevant to conditions like obesity and type 2 diabetes. Obestatin supports pancreatic β cell health, increasing insulin secretion and improving glucose tolerance in hyperglycemic conditions. 107 Studies have shown that obestatin’s interaction with incretin receptors, including GLP-1R, potentiates insulin release while also providing protective effects against β cell apoptosis. 108 This makes obestatin an interesting candidate for modulating glucose homeostasis and insulin resistance. Several controversies and unanswered questions remain about the physiological role of obestatin and its therapeutic potential. A major debate exists around obestatin’s receptor interactions, particularly its association with GPR39, which remains contested, as evidence on binding specificity and its signaling efficacy has been inconsistent. Another area of ambiguity is the extent to which obestatin functions independently versus synergistically or antagonistically with ghrelin, particularly in energy homeostasis and appetite regulation. Although obestatin was initially proposed as a ghrelin antagonist, subsequent studies suggest more complex, potentially context-dependent interactions that are not yet fully understood. Therapeutically, it is unclear whether long-term administration of obestatin would sustain its beneficial effects or lead to desensitization or downregulation of its signaling pathways. Thus, the exact mechanisms, receptor interactions, and therapeutic viability of obestatin require further studies to validate if it has any potential clinical applications. Amylin, a pancreatic peptide hormone, interacts with multiple organs, including the brain, kidneys, and pancreas. Amylin, co-secreted with insulin from pancreatic β cells, plays a vital role in glucose regulation and appetite control. 109 Amylin also works by slowing gastric emptying and inhibiting glucagon release, thereby stabilizing postprandial glucose levels. 4 Pramlintide, a synthetic analog of amylin, has been approved for the treatment of both type 1 and type 2 diabetes mellitus since 2005. Amylin does not have a unique receptor but instead binds to calcitonin receptors. It acts by mediating signaling through these GPCRs modified by receptor activity-modifying proteins (RAMPs). Different RAMP subtypes give rise to amylin’s diverse physiological roles by modulating receptor binding and signaling. 110 However, the exact binding specificity and tissue distribution of amylin receptors are not entirely clear, especially since different RAMP subtypes (e.g., RAMP1, RAMP2, and RAMP3) appear to generate distinct receptor responses and signaling outcomes. Amylin also affects cardiovascular health and energy expenditure by having an effect on sympathetic nervous activity. Amylin has been shown to promote thermogenesis in brown adipose tissue in mice, which increases total energy expenditure and protects against obesity in a RAMP1-dependent manner. 111 , 112 In the cardiovascular system, amylin indirectly affects blood pressure and heart rate through sympathetic activation, thus contributing to an integrated response in stressful or energy-demanding situations. 113 Amylin also works as a satiety hormone, mainly in the area postrema (AP) of the brainstem, to control meal size and promote satiety. 114 However, pramlintide has been shown to promote only modest weight loss, primarily by reducing food intake. This has led to an increased interest in combining it with other weight-loss medications, such as GLP-1 receptor agonists. Next-generation amylin-GLP-1RA analogs, such as cagrilintide, 115 have been designed with improved pharmacokinetics to allow for once-weekly dosing and have shown promise in achieving more robust weight loss. These candidates are being evaluated for their enhanced receptor binding, prolonged half-life, and improved tolerability profiles. In summary, small peptides like apelin, obestatin, and amylin play crucial roles in interorgan crosstalk, coordinating physiological processes essential for maintaining metabolic and cardiovascular health. These peptides exemplify the diverse ways in which interorgan peptide signaling supports systemic energy balance and opens pathways for novel therapeutic interventions.

Peptides have large translational potential, and because of this, the field is now rapidly evolving, with discoveries and technological advancements continuously emerging. There is still a significant gap in understanding how many peptides are made and modified, their specific receptors, and the downstream signaling pathways they modulate. Despite their established existence in biomarker studies, our understanding of their diverse functions and mechanisms remains incomplete. Given the difficulty in finding the most relevant biological context for these new peptides, most of the peptides we study today for their mechanisms and functions were discovered decades ago. The growing prevalence of metabolic diseases, including obesity, diabetes, and cardiovascular disorders, necessitates a better understanding of the underlying mechanisms of metabolic regulation, including peptides that regulate obesity and cardiovascular disease. Since peptide hormones are key regulators in these processes, elucidating their roles could lead to new pharmacology.

Peptides are potent regulators of numerous biological functions, and many peptides have already been developed into therapeutic drugs. Peptides can act as signaling molecules that coordinate cellular processes such as metabolism, 1 immune response, 2 and neuroendocrine regulation. 3 They can be secreted by a variety of tissues, including the pancreas, 4 gastrointestinal tract, 5 hypothalamus, 6 and adipose tissue, 7 making them essential for interorgan communication. Historically, the discovery of peptide hormones has largely been dependent on classical biochemical methods, such as chromatography-based fractionation guided by bioactivity and Edman degradation to determine the exact sequence. 8 These early studies were dependent on the isolation and structural characterization of peptides from biological extracts. 9 However, as our techniques advanced, molecular biology approaches, including mRNA expression analysis 10 and recombinant protein technology, 11 provided deeper insights into peptide biosynthesis, post-translational modifications (PTMs), and receptor interactions. More recently, mass spectrometry (MS)-based peptidomics and computational modeling have expanded our ability to identify novel peptides. 12 , 13 In this review, we will discuss the approaches to the discovery of the peptides known to date, as well as highlight key examples of how interorgan metabolic and cardiovascular crosstalk is mediated by peptide hormones.