The Effects of Agrin Isoforms on Diabetic Neuropathic Pain in a Rat Streptozotocin Model

Dihydromyricetin Alleviates Diabetic Neuropathic Pain and Depression Comorbidity Symptoms by Inhibiting P2X7 Receptor

Diabetic neuropathic pain (DNP) and major depressive disorder (MDD) are common complications of diabetes mellitus and mutually affect each other. As a member of the ATP-gated ion channel family, P2X₇ receptor is associated with the transduction of pain signal and the onset of depression. The aim of this study was to investigate the effects of dihydromyricetin (DHM) on rats with comorbid DNP and MDD. After the comorbid model was established, rat behavior changes were monitored by measuring the mechanical withdrawal threshold, thermal withdrawal latency, sugar water preference, immobility time in the forced-swim test, and open-field test parameters. The expressions of P2X₇ receptor in the dorsal root ganglia (DRGs), spinal cord, and hippocampus were assessed by quantitative real-time PCR, Western blotting, and double immunofluorescence. We found that hyperalgesia, allodynia, and depressive behaviors of rats with comorbid DNP and MDD were relieved by treatment with DHM or application of a short-hairpin RNA for P2X₇ receptor. The expression levels of P2X₇, phosphorylated extracellular signal-regulated kinase 1/2, tumor necrosis factor α, and interleukin 1ß were increased in the DRGs, spinal cord, and hippocampus of rats in the model group but restored after DHM or P2X₇ short-hairpin RNA treatment. In conclusion, P2X₇ receptor in the DRGs, spinal cord, and hippocampus participates in the transduction of DNP and MDD signals. DHM seems to relieve comorbid DNP and MDD by reducing the expression of P2X₇ receptor in the DRGs, spinal cord, and hippocampus and may be an effective new drug for the treatment of patients with both DNP and MDD.

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.