Relationship between family history of type 2 diabetes and serum FGF21

lncRNA UCA1 inhibits mitochondrial dysfunction of skeletal muscle in type 2 diabetes mellitus by sequestering miR-143-3p to release FGF21

Increasing evidence suggests that insulin resistance in type 2 diabetes mellitus (T2DM) is associated with mitochondrial dysfunction in skeletal muscle, while the underlying molecular mechanisms remain elusive. This study aims to construct a ceRNA regulatory network that is involved in mitochondrial dysfunction of skeletal muscle in T2DM. Based on GEO database analysis, differentially expressed lncRNA and mRNA profiles were identified in skeletal muscle tissues of T2DM. Next, LASSO regression analysis was conducted to predict the key lncRNAs related to T2DM, which was validated by receiver operating characteristic (ROC) analysis. Moreover, the miRNAs related to skeletal muscle in T2DM were identified by WGCNA, followed by construction of gene-gene interaction network and GO and KEGG enrichment analyses. It was found that 12 lncRNAs and 6 miRNAs were related to skeletal muscle in T2DM. Moreover, the lncRNA-miRNA-mRNA ceRNA network involving UCA1, miR-143-3p, and FGF21 was constructed. UCA1, and FGF21 were downregulated, while miR-143-3p was upregulated in skeletal muscle cells (SkMCs) exposed to palmitic acid. Additionally, ectopic expression experiments were performed in SkMCs to confirm the effects of UCA1/miR-143-3p/FGF21 on mitochondrial dysfunction by determining mitochondrial ROS, oxygen consumption rate (OCR), membrane potential, and ATP level. Overexpression of miR-143-3p increased ROS accumulation and reduced the OCR, fluorescence ratio of JC-1, and ATP level, which were reversed by upregulation of UCA1 or FGF21. Collectively, lncRNA UCA1 inhibited mitochondrial dysfunction of skeletal muscle in T2DM by sequestering miR-143-3p away from FGF21, therefore providing a potential therapeutic target for alleviating mitochondrial dysfunction of skeletal muscle in T2DM.

Advances in Biological Functions and Clinical Studies of FGF21

Fibroblast growth factor 21 (FGF21) regulates many crucial biological processes in human and mammals, particularly metabolic modulation and protective effect after injury. Therefore, determining complex regulatory mechanisms and elucidating the signaling pathway may greatly promote the prevention, diagnosis, and treatment of related injury and metabolic diseases. This review focused on the metabolic modulation and protective effect of FGF21 and summarized the molecular mechanisms and clinical research developments.

New Insights into Adipokines as Potential Biomarkers for Type-2 Diabetes Mellitus

A large number of studies have been focused on investigating serum biomarkers associated with risk or diagnosis of type-2 diabetes mellitus. In the last decade, promising studies have shown that circulating levels of adipokines could be used as a relevant biomarker for diabetes mellitus progression as well as therapeutic future targets. Here, we discuss the possible use of recently described adipokines, including apelin, omentin-1, resistin, FGF-21, neuregulin-4 and visfatin, as early biomarkers for diabetes. In addition, we also include recent findings of other well known adipokines such as leptin and adiponectin. In conclusion, further studies are needed to clarify the pathophysiological significance and clinical value of these biological factors as potential biomarkers in type-2 diabetes and related dysfunctions.

Role of myokines in the development of skeletal muscle insulin resistance and related metabolic defects in type 2 diabetes

Due to its mass, skeletal muscle is the major site of glucose uptake and an important tissue in the development of type 2 diabetes (T2D). Muscles of patients with T2D are affected with insulin resistance and mitochondrial dysfunction, which result in impaired glucose and fatty acid metabolism. A well-established method of managing the muscle metabolic defects occurring in T2D is physical exercise. During exercise, muscles contract and secrete factors called myokines which can act in an autocrine/paracrine fashion to improve muscle energy metabolism. In patients with T2D, plasma levels as well as muscle levels (mRNA and protein) of some myokines are upregulated, while others are downregulated. The signalling pathways of certain myokines are also altered in skeletal muscle of patients with T2D. Taken together, these findings suggest that myokine secretion is an important factor contributing to the development of muscle metabolic defects during T2D. It is also of interest considering that lack of physical activity is closely linked to the occurrence of this disease. The causal relationships between sedentary behavior, factors secreted by skeletal muscle at rest and during contraction and the development of T2D remain to be elucidated. Many myokines shown to influence muscle energy metabolism still have not been characterized in the context of T2D in skeletal muscle specifically. The purpose of this review is to highlight what is known and what remains to be determined regarding myokine secretion in patients with T2D to uncover potential therapeutic targets for the management of this disease.

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.