Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

KST5468, a new T-type calcium channel antagonist, has an antinociceptive effect on inflammatory and neuropathic pain models

The T-type Ca2+ channel is a low-voltage-activated Ca2+ channel related to nociceptive stimuli. Increases in Ca2+ due to calcium channel activation enhance pain sensitivity through both peripheral and central pain pathways. We have developed a novel compound, KST5468, which is a T-type calcium channel antagonist. The new synthetic compound may have an antinociceptive effect, and thus we evaluated KST5468 as a putative analgesic in a hot plate test, a formalin test, and two neuropathic pain models. KST5468 caused a significant increase in latency in the hot plate test at 30min after a 10mg/kg peritoneal injection of the compound. Interestingly, in the second phase of formalin test, KST5468 decreased pain behaviors in a dose-dependent manner. Moreover, in two neuropathic pain models induced by chronic constriction and spared nerve injury, KST5468 significantly increased the mechanical pain threshold. Using immunohistochemistry, expression of two well known pain-related molecular markers, c-Fos and calcitonin gene-related peptide (CGRP), and phosphorylated extracellular signal-related kinase (p-ERK) were found to be decreased in the laminae I-II layers of the ipsilateral L4-L5 spinal dorsal horn in KST5468 treated mice. Taken together, the results of this study suggest that KST5468 may be an effective antinociceptive agent for neuropathic pain.We acknowledged the Korea Institute of Science and Technology and the Korea Science and Engineering Foundation (KOSEF) for sponsoring this research through the SRC/ERC Program of MOST/ KOSEF (R11-2005-065) and Bio-Green

KST5468, a new T-type calcium channel antagonist, has an antinociceptive effect on inflammatory and neuropathic pain models

The T-type Ca(2+) channel is a low-voltage-activated Ca(2+)d channel related to nociceptive stimuli. Increases in Ca(2+) due to calcium channel activation enhance pain sensitivity through both peripheral and central pain pathways. We have developed a novel compound. KST5468, which is a T-type calcium channel antagonist. The new synthetic compound may have an antinociceptive effect, and thus we evaluated KST5468 as a putative analgesic in a hot plate test, a formalin test, and two neuropathic pain models. KST5468 caused a significant increase in latency in the hot plate test at 30 min after a 10 mg/kg peritoneal injection of the compound. Interestingly, in the second phase of formalin test, KST5468 decreased pain behaviors in a dose-dependent manner. Moreover, in two neuropathic pain models induced by chronic constriction and spared nerve injury, KST5468 significantly increased the mechanical pain threshold. Using immunohistochemistry, expression of two well known pain-related molecular markers, c-Fos and calcitonin gene-related peptide (CGRP), and phosphorylated extracellular signal-related kinase (p-ERK) were found to be decreased in the laminae I-II layers of the ipsilateral L4-L5 spinal dorsal horn in KST5468 treated mice. Taken together, the results of this study suggest that KST5468 may be an effective antinociceptive agent for neuropathic pain. (C) 2010 Elsevier Inc. All rights reserved.Choi S, 2007, GENES BRAIN BEHAV, V6, P425, DOI 10.1111/j.1601-183X.2006.00268.xMukhida K, 2007, STEM CELLS, V25, P2874, DOI 10.1634/stemcells.2007-0326Todorovic SM, 2007, CHANNELS, V1, P238Lin YR, 2007, LIFE SCI, V81, P1071, DOI 10.1016/j.lfs.2007.08.014Cheng JK, 2007, BEHAV PHARMACOL, V18, P1Ahn SN, 2006, SPINAL CORD, V44, P547, DOI 10.1038/sj.sc.3101862Cheng JK, 2006, J PHARMACOL SCI, V100, P471, DOI 10.1254/jphs.CR0050020Catterall WA, 2005, PHARMACOL REV, V57, P411, DOI 10.1124/pr.57.4.5Zelcer N, 2005, P NATL ACAD SCI USA, V102, P7274, DOI 10.1073/pnas.0502530102Conlee KM, 2005, LAB ANIM-UK, V39, P137, DOI 10.1258/0023677053739747Jung HK, 2004, BIOORGAN MED CHEM, V12, P3965, DOI 10.1016/j.bmc.2004.06.011Blackburn-Munro G, 2004, TRENDS PHARMACOL SCI, V25, P299, DOI 10.1016/j.tips.2004.04.008EDDY NB, 1953, J PHARMACOL EXP THER, V107, P385PERRIER D, 1974, J PHARMACOL EXP THER, V191, P17PERRIER D, 1982, J PHARM SCI, V71, P474ZIMMERMANN M, 1983, PAIN, V16, P109Maneuf YP, 2004, BRIT J PHARMACOL, V141, P574, DOI 10.1038/sj.bjp.0705579Kim D, 2003, SCIENCE, V302, P117Fehrenbacher JC, 2003, PAIN, V105, P133, DOI 10.1016/S0304-3959(03)00173-8Gold MS, 2003, J NEUROSCI, V23, P158Shin JB, 2003, NAT NEUROSCI, V6, P724, DOI 10.1038/nn1076Ikeda H, 2003, SCIENCE, V299, P1237Ghelardini C, 2002, NEUROPHARMACOLOGY, V43, P1180, DOI 10.1016/S0028-3908(02)00225-3Lawson SN, 2002, EXP PHYSIOL, V87, P239Ito S, 2001, NEUROSCI RES, V41, P299Kim CH, 2001, MOL BRAIN RES, V95, P153Decosterd I, 2000, PAIN, V87, P149Ji RR, 1999, NAT NEUROSCI, V2, P1114Impey S, 1999, NEURON, V23, P11Herdegen T, 1998, BRAIN RES REV, V28, P370Sgambato V, 1998, J NEUROSCI, V18, P8814SoRelle R, 1998, CIRCULATION, V98, P831JU G, 1987, CELL TISSUE RES, V247, P417HUNSKAAR S, 1987, PAIN, V30, P103DICKENSON AH, 1987, PAIN, V30, P349OPIE LH, 1988, CARDIOVASC DRUG THER, V2, P177BENNETT GJ, 1988, PAIN, V33, P87LINDGREN S, 2008, J PHARMACOL TOXICOL, V58, P99, DOI 10.1016/j.vascn.2008.07.001Tsuda M, 2008, GLIA, V56, P50, DOI 10.1002/glia.20591Shin HS, 2008, CURR OPIN PHARMACOL, V8, P33, DOI 10.1016/j.coph.2007.12.003TOWART R, 2009, J PHARMACOL TOXICOL, V60, P1, DOI 10.1016/j.vascn.2009.04.197Truin M, 2009, PAIN, V145, P312, DOI 10.1016/j.pain.2009.06.034Billups SJ, 1998, ANN PHARMACOTHER, V32, P841RADULOVIC LL, 1995, DRUG METAB DISPOS, V23, P441TAL M, 1994, PAIN, V57, P375TJOLSEN A, 1992, PAIN, V51, P5ROSLAND JH, 1990, PAIN, V42, P235COULTER DA, 1989, ANN NEUROL, V25, P582