Anti-HCAR2 monoclonal antibody, clone NN0430-7T35

Name: Anti-HCAR2 monoclonal antibody, clone NN0430-7T35
SKU: CABT-BL1760
Rating: 5 (1 reviews)

Rat Anti-Human HCAR2 monoclonal antibody for FC

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COA

SDS

Datasheet

Summary

Specifications

Antibody Isotype

IgG2

Clone

NN0430-7T35

Species Reactivity

Human

Immunogen

Recombinant full length Human Puma gamma protein

Conjugate

Unconjugated

Applications

Application Notes

FC: 1:50-1:200

Target

Alternative Names

HCAR2; hydroxycarboxylic acid receptor 2; G protein coupled receptor 109A, GPR109A; HCA2; HM74A; niacin receptor 1; NIACR1; Puma g; PUMAG; G protein coupled receptor 109A; G protein coupled receptor HM74a; G protein coupled receptor Hm74b; GPR 109A; GPR1

Entrez Gene ID

338442

UniProt ID

Q8TDS4

Citations

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Documents

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References

Fumarate decreases edema volume and improves functional outcome after experimental stroke

EXPERIMENTAL NEUROLOGY

Authors: Clausen, Bettina Hjelm; Lundberg, Louise; Yli-Karjanmaa, Minna; Martin, Nellie Anne; Svensson, Martina; Alfsen, Maria Zeiler; Flaeng, Simon Bertram; Lyngso, Kristina; Boza-Serrano, Antonio; Nielsen, Helle H.; Hansen, Pernille B.; Finsen, Bente; Deierborg, Tomas; Illes, Zsolt; Lambertsen, Kate Lykke

Abstract

Background: Oxidative stress and inflammation exacerbate tissue damage in the brain after ischemic stroke. Dimethyl-fumarate (DMF) and its metabolite monomethyl-fumarate (MMF) are known to stimulate anti-oxidant pathways and modulate inflammatory responses. Considering these dual effects of fumarates, we examined the effect of MMF treatment after ischemic stroke in mice. Methods: Permanent middle cerebral artery occlusion (pMCAO) was performed using adult, male C57BL/6 mice. Thirty minutes after pMCAO, 20 mg/kg MMF was administered intravenously. Outcomes were evaluated 6, 24 and 48 h after pMCAO. First, we examined whether a bolus of MMF was capable of changing expression of kelch-like erythroid cell-derived protein with CNC homology-associated protein 1 (Keap1) and nuclear factor erythroid 2-related factor (Nrf)2 in the infarcted brain. Next, we studied the effect of MMF on functional recovery. To explore mechanisms potentially influencing functional changes, we examined infarct volumes, edema formation, the expression of heat shock protein (Hsp)72, hydroxycarboxylic acid receptor 2 (Hcar2), and inducible nitric oxide synthase (iNOS) in the infarcted brain using real-time PCR and Western blotting. Concentrations of a panel of pro- and anti-inflammatory cytoldnes IL-1 gamma, IL-2 beta, IL-4, IL-5, IL-6, IL-10, IL-12p70,TNF) were examined in both the infarcted brain tissue and plasma samples 6, 24 and 48 h after pMCAO using multiplex electrochemoluminiscence analysis. Results: Administration of MMF increased the protein level of Nrf2 6 h after pMCAO, and improved functional outcome at 24 and 48 h after pMCAO. MMF treatment did not influence infarct size, however reduced edema volume at both 24 and 48 h after pMCAO. MMF treatment resulted in increased Hsp72 expression in the brain 6 h after pMCAO. Hcar2 mRNA levels increased significantly 24 h after pMCAO, but were not different between saline-and MMF-treated mice. MMF treatment also increased the level of the anti-inflammatory cytokine IL-10 in the brain and plasma 6 h after pMCAO, and additionally reduced the level of the pro-inflammatory cytokine IL-12p70 in the brain at 24 and 48 h after pMCAO. Conclusions: A single intravenous bolus of MMF improved sensory-motor function after ischemic stroke, reduced edema formation, and increased the levels of the neuroprotective protein Hsp72 in the brain. The early increase in IL-10 and reduction in IL-12p70 in the brain combined with changes in systemic cytokine levels may also contribute to the functional recovery after pMCAO. (C) 2017 Published by Elsevier Inc.

Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci

AMERICAN JOURNAL OF HUMAN GENETICS

Authors: Asselbergs, Folkert W.; Guo, Yiran; van Iperen, Erik P. A.; Sivapalaratnam, Suthesh; Tragante, Vinicius; Lanktree, Matthew B.; Lange, Leslie A.; Almoguera, Berta; Appelman, Yolande E.; Barnard, John; Baumert, Jens; Beitelshees, Amber L.; Bhangale, Tushar R.; Chen, Yii-Der Ida; Gaunt, Tom R.; Gong, Yan; Hopewell, Jemma C.; Johnson, Toby; Kleber, Marcus E.; Langaee, Taimour Y.; Li, Mingyao; Li, Yun R.; Liu, Kiang; McDonough, Caitrin W.; Meijs, Matthijs El.; Middelberg, Rita P. S.; Musunuru, Kiran; Nelson, Christopher P.; O'Connell, Jeffery R.; Padmanabhan, Sandosh; Pankow, James S.; Pankratz, Nathan; Rafelt, Suzanne; Rajagopalan, Ramakrishnan; Romaine, Simon P. R.; Schork, Nicholas J.; Shaffer, Jonathan; Shen, Haiqing; Smith, Erin N.; Tischfield, Sam E.; van der Most, Peter J.; van Vliet-Ostaptchouk, Jana V.; Verweij, Niek; Volcik, Kelly A.; Zhang, Li; Bailey, Kent R.; Bailey, Kristian M.; Bauer, Florianne; Boer, Jolanda M. A.; Braund, Peter S.; Burt, Amber; Burton, Paul R.; Buxbaum, Sarah G.; Chen, Wei; Cooper-DeHoff, Rhonda M.; Cupples, L. Adrienne; deJong, Jonas S.; Delles, Christian; Duggan, David; Fornage, Myriam; Furlong, Clement E.; Glazer, Nicole; Gums, John G.; Hastie, Claire; Holmes, Michael V.; Illig, Thomas; Kirkland, Susan A.; Kivimaki, Mika; Klein, Ronald; Klein, Barbara E.; Kooperberg, Charles; Kottke-Marchant, Kandice; Kumari, Meena; LaCroix, Andrea Z.; Mallela, Laya; Murugesan, Gurunathan; Ordovas, Jose; Ouwehand, Willem H.; Post, Wendy S.; Saxena, Richa; Scharnagl, Hubert; Schreiner, Pamela J.; Shah, Tina; Shields, Denis C.; Shimbo, Daichi; Srinivasan, Sathanur R.; Stolk, Ronald P.; Swerdlow, Daniel I.; Taylor, Herman A., Jr.; Topo, Eric J.; Toskala, Elina; van Pelt, Joost L.; van Setten, Jessica; Yusuf, Salim; Whittaker, John C.; Zwinderman, A. H.; Anand, Sonia S.; Balmforth, Anthony J.; Berenson, Gerald S.; Bezzina, Connie R.; Boehm, Bernhard O.; Boerwinkle, Eric; Casas, Juan P.; Caulfield, Mark J.; Clarke, Robert; Connell, John M.; Cruickshanks, Karen J.; Davidson, Karina W.; Day, Ian N. M.; de Bakker, Paul I. W.; Doevendans, Pieter A.; Dominiczak, Anna E.; Hall, Alistair S.; Hartman, Catharina A.; Hengstenberg, Christian; Hillege, Hans L.; Hofker, Marten H.; Humphries, Steve E.; Jarvik, Gail P.; Johnson, Julie A.; Kaess, Bernhard M.; Kathiresan, Sekar; Koenig, Wolfgang; Lawlor, Debbie A.; Maerz, Winfried; Melander, Olle; Mitchell, Braxton D.; Montgomery, Grant W.; Munroe, Patricia B.; Murray, Sarah S.; Newhouse, Stephen J.; Onland-Moret, N. Charlotte; Poulter, Neil; Psaty, Bruce; Redline, Susan; Rich, Stephen S.; Rotter, Jerome I.; Schunkert, Heribert; Sever, Peter; Shuldiner, Alan R.; Silverstein, Roy L.; Stanton, Alice; Thorand, Barbara; Trip, Mieke D.; Tsai, Michael Y.; van der Harst, Pim; van der Schoot, Ellen; van der Schouw, Yvonne T.; Verschuren, W. M. Monique; Watkins, Hugh; Wilde, Arthur A. M.; Wolffenbuttel, Bruce H. R.; Whitfield, John B.; Hovingh, G. Kees; Ballantyne, Christie M.; Wijmenga, Cisca; Reilly, Muredach P.; Martin, Nicholas G.; Wilson, James G.; Rader, Daniel J.; Samani, Nilesh J.; Reiner, Alex P.; Hegele, Robert A.; Kastelein, John J. P.; Hingorani, Aroon D.; Talmud, Philippa J.; Hakonarson, Hakon; Elbers, Clara C.; Keating, Brendan J.; Drenos, Fotios

Abstract

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.