Parsing the Potential Neuroendocrine Actions of FGF21 in Primates

Old Paradoxes and New Opportunities for Appetite Control in Obesity

Human obesity is accompanied by alterations in the blood concentrations of multiple circulating appetite regulators. Paradoxically, most of the appetite-inhibitory hormones are elevated in nonsyndromic obesity, while most of the appetite stimulatory hormones are reduced, perhaps reflecting vain attempts of regulation by inefficient feedback circuitries. In this context, it is important to understand which appetite regulators exhibit a convergent rather than paradoxical behavior and hence are likely to contribute to the maintenance of the obese state. Pharmacological interventions in obesity should preferentially consist of the supplementation of deficient appetite inhibitors or the neutralization of excessive appetite stimulators. Here, we critically analyze the current literature on appetite-regulatory peptide hormones. We propose a short-list of appetite modulators that may constitute the best candidates for therapeutic interventions.

Humanized GPRC6AKGKY is a gain-of-function polymorphism in mice

GPRC6A is proposed to regulate energy metabolism in mice, but in humans a KGKY polymorphism in the third intracellular loop (ICL3) is proposed to result in intracellular retention and loss-of-function. To test physiological importance of this human polymorphism in vivo, we performed targeted genomic humanization of mice by using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated protein 9) system to replace the RKLP sequence in the ICL3 of the GPRC6A mouse gene with the uniquely human KGKY sequence to create Gprc6a-KGKY-knockin mice. Knock-in of a human KGKY sequence resulted in a reduction in basal blood glucose levels and increased circulating serum insulin and FGF-21 concentrations. Gprc6a-KGKY-knockin mice demonstrated improved glucose tolerance, despite impaired insulin sensitivity and enhanced pyruvate-mediated gluconeogenesis. Liver transcriptome analysis of Gprc6a-KGKY-knockin mice identified alterations in glucose, glycogen and fat metabolism pathways. Thus, the uniquely human GPRC6A-KGKY variant appears to be a gain-of-function polymorphism that positively regulates energy metabolism in mice.

Role of GPRC6A in Regulating Hepatic Energy Metabolism in Mice

GPRC6A is a widely expressed G-protein coupled receptor that regulates energy metabolism. Global deletion of Gprc6a in mice is reported to result in a metabolic syndrome-like phenotype and conditional deletion of Gprc6a in pancreatic β-cell and skeletal muscle respectively impair insulin secretion and glucose uptake. In the current study, we explore the hepatic functions of GPRC6A by conditionally deleting Gprc6a in hepatocytes by cross breeding Alb-Cre and Gprc6aflox/flox mice to obtain Gprc6aLiver-cko mice. Gprc6aLiver-cko mice on a normal diet showed excessive hepatic fat accumulation and glycogen depletion. These mice also exhibit impaired glucose and pyruvate tolerance, but normal insulin sensitivity. Decreased circulating FGF-21 levels and FGF-21 message expression in the liver were found in Gprc6aLiver-cko mice. Hepatic transcriptome analysis identified alterations in multiple pathways regulating glucose, fat and glycogen metabolism in Gprc6aLiver-cko mice. Taken together, our studies suggest that GPRC6A directly regulates hepatic metabolism as well as regulates the production and release of FGF-21 to control systemic energy homeostasis. GPRC6A's unique regulation of β-cell, skeletal muscle and hepatic function may represent a new therapeutic target for treating disordered energy metabolism metabolic syndrome and type 2 diabetes.

Regulation of Energy Metabolism by Receptor Tyrosine Kinase Ligands

Metabolic diseases, such as diabetes, obesity, and fatty liver disease, have now reached epidemic proportions. Receptor tyrosine kinases (RTKs) are a family of cell surface receptors responding to growth factors, hormones, and cytokines to mediate a diverse set of fundamental cellular and metabolic signaling pathways. These ligands signal by endocrine, paracrine, or autocrine means in peripheral organs and in the central nervous system to control cellular and tissue-specific metabolic processes. Interestingly, the expression of many RTKs and their ligands are controlled by changes in metabolic demand, for example, during starvation, feeding, or obesity. In addition, studies of RTKs and their ligands in regulating energy homeostasis have revealed unexpected diversity in the mechanisms of action and their specific metabolic functions. Our current understanding of the molecular, biochemical and genetic control of energy homeostasis by the endocrine RTK ligands insulin, FGF21 and FGF19 are now relatively well understood. In addition to these classical endocrine signals, non-endocrine ligands can govern local energy regulation, and the intriguing crosstalk between the RTK family and the TGFβ receptor family demonstrates a signaling network that diversifies metabolic process between tissues. Thus, there is a need to increase our molecular and mechanistic understanding of signal diversification of RTK actions in metabolic disease. Here we review the known and emerging molecular mechanisms of RTK signaling that regulate systemic glucose and lipid metabolism, as well as highlighting unexpected roles of non-classical RTK ligands that crosstalk with other receptor pathways.

FGF21 and the Physiological Regulation of Macronutrient Preference

The ability to respond to variations in nutritional status depends on regulatory systems that monitor nutrient intake and adaptively alter metabolism and feeding behavior during nutrient restriction. There is ample evidence that the restriction of water, sodium, or energy intake triggers adaptive responses that conserve existing nutrient stores and promote the ingestion of the missing nutrient, and that these homeostatic responses are mediated, at least in part, by nutritionally regulated hormones acting within the brain. This review highlights recent research that suggests that the metabolic hormone fibroblast growth factor 21 (FGF21) acts on the brain to homeostatically alter macronutrient preference. Circulating FGF21 levels are robustly increased by diets that are high in carbohydrate but low in protein, and exogenous FGF21 treatment reduces the consumption of sweet foods and alcohol while alternatively increasing the consumption of protein. In addition, while control mice adaptively shift macronutrient preference and increase protein intake in response to dietary protein restriction, mice that lack either FGF21 or FGF21 signaling in the brain fail to exhibit this homeostatic response. FGF21 therefore mediates a unique physiological niche, coordinating adaptive shifts in macronutrient preference that serve to maintain protein intake in the face of dietary protein restriction.

FGF19 subfamily members: FGF19 and FGF21

Fibroblast growth factors (FGF) constitute a large family of proteins with pleiotropic effects on development, organogenesis, and metabolism. The FGF19 subclass includes growth factors circulating with the blood referred to as endocrine FGF. Representatives of the FGF19 subclass, including FGF19, FGF21, and FGF23, act via FGFR receptors. The proteins of FGF19 subfamily influence the enterohepatic circulation of bile, participate in glucose and lipid metabolism regulation, and maintenance of phosphorus and vitamin D3 homeostasis. FGF19 and FGF21 are activated under different physiological and pathological conditions.

Towards frailty biomarkers: Candidates from genes and pathways regulated in aging and age-related diseases

OBJECTIVE

Use of the frailty index to measure an accumulation of deficits has been proven a valuable method for identifying elderly people at risk for increased vulnerability, disease, injury, and mortality. However, complementary molecular frailty biomarkers or ideally biomarker panels have not yet been identified. We conducted a systematic search to identify biomarker candidates for a frailty biomarker panel.

METHODS

Gene expression databases were searched (http://genomics.senescence.info/genes including GenAge, AnAge, LongevityMap, CellAge, DrugAge, Digital Aging Atlas) to identify genes regulated in aging, longevity, and age-related diseases with a focus on secreted factors or molecules detectable in body fluids as potential frailty biomarkers. Factors broadly expressed, related to several "hallmark of aging" pathways as well as used or predicted as biomarkers in other disease settings, particularly age-related pathologies, were identified. This set of biomarkers was further expanded according to the expertise and experience of the authors. In the next step, biomarkers were assigned to six "hallmark of aging" pathways, namely (1) inflammation, (2) mitochondria and apoptosis, (3) calcium homeostasis, (4) fibrosis, (5) NMJ (neuromuscular junction) and neurons, (6) cytoskeleton and hormones, or (7) other principles and an extensive literature search was performed for each candidate to explore their potential and priority as frailty biomarkers.

RESULTS

A total of 44 markers were evaluated in the seven categories listed above, and 19 were awarded a high priority score, 22 identified as medium priority and three were low priority. In each category high and medium priority markers were identified.

CONCLUSION

Biomarker panels for frailty would be of high value and better than single markers. Based on our search we would propose a core panel of frailty biomarkers consisting of (1) CXCL10 (C-X-C motif chemokine ligand 10), IL-6 (interleukin 6), CX3CL1 (C-X3-C motif chemokine ligand 1), (2) GDF15 (growth differentiation factor 15), FNDC5 (fibronectin type III domain containing 5), vimentin (VIM), (3) regucalcin (RGN/SMP30), calreticulin, (4) PLAU (plasminogen activator, urokinase), AGT (angiotensinogen), (5) BDNF (brain derived neurotrophic factor), progranulin (PGRN), (6) α-klotho (KL), FGF23 (fibroblast growth factor 23), FGF21, leptin (LEP), (7) miRNA (micro Ribonucleic acid) panel (to be further defined), AHCY (adenosylhomocysteinase) and KRT18 (keratin 18). An expanded panel would also include (1) pentraxin (PTX3), sVCAM/ICAM (soluble vascular cell adhesion molecule 1/Intercellular adhesion molecule 1), defensin α, (2) APP (amyloid beta precursor protein), LDH (lactate dehydrogenase), (3) S100B (S100 calcium binding protein B), (4) TGFβ (transforming growth factor beta), PAI-1 (plasminogen activator inhibitor 1), TGM2 (transglutaminase 2), (5) sRAGE (soluble receptor for advanced glycosylation end products), HMGB1 (high mobility group box 1), C3/C1Q (complement factor 3/1Q), ST2 (Interleukin 1 receptor like 1), agrin (AGRN), (6) IGF-1 (insulin-like growth factor 1), resistin (RETN), adiponectin (ADIPOQ), ghrelin (GHRL), growth hormone (GH), (7) microparticle panel (to be further defined), GpnmB (glycoprotein nonmetastatic melanoma protein B) and lactoferrin (LTF). We believe that these predicted panels need to be experimentally explored in animal models and frail cohorts in order to ascertain their diagnostic, prognostic and therapeutic potential.