Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6–2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.
References
[1]
Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science. 2007;316(5830):1491–3. pmid:17478679 doi: 10.1126/science.1142842
[2]
Gieger C, Geistlinger L, Altmaier E, Hrabe de Angelis M, Kronenberg F, Meitinger T, et al. Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum. PLoS genetics. 2008;4(11):e1000282. doi: 10.1371/journal.pgen.1000282. pmid:19043545
[3]
Shah AA, Craig DM, Sebek JK, Haynes C, Stevens RC, Muehlbauer MJ, et al. Metabolic profiles predict adverse events after coronary artery bypass grafting. The Journal of thoracic and cardiovascular surgery. 2012;143(4):873–8. doi: 10.1016/j.jtcvs.2011.09.070. pmid:22306227
[4]
Shah SH, Bain JR, Muehlbauer MJ, Stevens RD, Crosslin DR, Haynes C, et al. Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events. Circulation Cardiovascular genetics. 2010;3(2):207–14. doi: 10.1161/CIRCGENETICS.109.852814. pmid:20173117
[5]
Shah SH, Sun JL, Stevens RD, Bain JR, Muehlbauer MJ, Pieper KS, et al. Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease. American heart journal. 2012;163(5):844–50 e1. doi: 10.1016/j.ahj.2012.02.005. pmid:22607863
[6]
Shah SH, Hauser ER, Bain JR, Muehlbauer MJ, Haynes C, Stevens RD, et al. High heritability of metabolomic profiles in families burdened with premature cardiovascular disease. Molecular systems biology. 2009;5:258. doi: 10.1038/msb.2009.11. pmid:19357637
[7]
Bhattacharya S, Granger CB, Craig D, Haynes C, Bain J, Stevens RD, et al. Validation of the association between a branched chain amino acid metabolite profile and extremes of coronary artery disease in patients referred for cardiac catheterization. Atherosclerosis. 2014;232(1):191–6. doi: 10.1016/j.atherosclerosis.2013.10.036. pmid:24401236
[8]
Szebenyi G, Wigley WC, Hall B, Didier A, Yu M, Thomas P, et al. Hook2 contributes to aggresome formation. BMC cell biology. 2007;8:19. pmid:17540036 doi: 10.1186/1471-2121-8-19
[9]
Wang Y, Wan B, Li D, Zhou J, Li R, Bai M, et al. BRSK2 is regulated by ER stress in protein level and involved in ER stress-induced apoptosis. Biochemical and biophysical research communications. 2012;423(4):813–8. doi: 10.1016/j.bbrc.2012.06.046. pmid:22713462
[10]
Liu S, Lv J, Han L, Ichikawa T, Wang W, Li S, et al. A pro-inflammatory role of deubiquitinating enzyme cylindromatosis (CYLD) in vascular smooth muscle cells. Biochemical and biophysical research communications. 2012;420(1):78–83. doi: 10.1016/j.bbrc.2012.02.118. pmid:22406061
[11]
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America. 2005;102(43):15545–50. pmid:16199517 doi: 10.1073/pnas.0506580102
[12]
Maeda Y, Ito T, Suzuki A, Kurono Y, Ueta A, Yokoi K, et al. Simultaneous quantification of acylcarnitine isomers containing dicarboxylic acylcarnitines in human serum and urine by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry. Rapid communications in mass spectrometry: RCM. 2007;21(5):799–806. pmid:17279485 doi: 10.1002/rcm.2905
[13]
Johnson DW. Synthesis of dicarboxylic acylcarnitines. Chemistry and physics of lipids. 2004;129(2):161–71. pmid:15081857 doi: 10.1016/j.chemphyslip.2004.01.001
[14]
Reyes-Turcu FE, Ventii KH, Wilkinson KD. Regulation and cellular roles of ubiquitin-specific deubiquitinating enzymes. Annual review of biochemistry. 2009;78:363–97. doi: 10.1146/annurev.biochem.78.082307.091526. pmid:19489724
[15]
Smith NL, Felix JF, Morrison AC, Demissie S, Glazer NL, Loehr LR, et al. Association of genome-wide variation with the risk of incident heart failure in adults of European and African ancestry: a prospective meta-analysis from the cohorts for heart and aging research in genomic epidemiology (CHARGE) consortium. Circulation Cardiovascular genetics. 2010;3(3):256–66. doi: 10.1161/CIRCGENETICS.109.895763. pmid:20445134
[16]
McKeown L, Moss NK, Turner P, Li J, Heath N, Burke D, et al. Platelet-derived growth factor maintains stored calcium through a nonclustering Orai1 mechanism but evokes clustering if the endoplasmic reticulum is stressed by store depletion. Circulation research. 2012;111(1):66–76. doi: 10.1161/CIRCRESAHA.111.263616. pmid:22556336
[17]
Jang JW, Lee WY, Lee JH, Moon SH, Kim CH, Chung HM. A novel Fbxo25 acts as an E3 ligase for destructing cardiac specific transcription factors. Biochemical and biophysical research communications. 2011;410(2):183–8. doi: 10.1016/j.bbrc.2011.05.011. pmid:21596019
[18]
Kitagawa K, Skowyra D, Elledge SJ, Harper JW, Hieter P. SGT1 encodes an essential component of the yeast kinetochore assembly pathway and a novel subunit of the SCF ubiquitin ligase complex. Molecular cell. 1999;4(1):21–33. pmid:10445024 doi: 10.1016/s1097-2765(00)80184-7
[19]
Libert R, Van Hoof F, Laus G, De Nayer P, Habib Jiwan JL, de Hoffmann E, et al. Identification of ethylsuccinylcarnitine present in some human urines. Clinica chimica acta; international journal of clinical chemistry. 2005;355(1–2):145–51. pmid:15820489 doi: 10.1016/j.cccn.2004.12.020
[20]
Ranek MJ, Terpstra EJ, Li J, Kass DA, Wang X. Protein kinase g positively regulates proteasome-mediated degradation of misfolded proteins. Circulation. 2013;128(4):365–76. doi: 10.1161/CIRCULATIONAHA.113.001971. pmid:23770744
[21]
Herrmann J, Lerman LO, Lerman A. On to the road to degradation: atherosclerosis and the proteasome. Cardiovascular research. 2010;85(2):291–302. doi: 10.1093/cvr/cvp333. pmid:19815565
[22]
Vieira O, Escargueil-Blanc I, Jurgens G, Borner C, Almeida L, Salvayre R, et al. Oxidized LDLs alter the activity of the ubiquitin-proteasome pathway: potential role in oxidized LDL-induced apoptosis. FASEB journal: official publication of the Federation of American Societies for Experimental Biology. 2000;14(3):532–42.
[23]
Kikuchi J, Furukawa Y, Kubo N, Tokura A, Hayashi N, Nakamura M, et al. Induction of ubiquitin-conjugating enzyme by aggregated low density lipoprotein in human macrophages and its implications for atherosclerosis. Arteriosclerosis, thrombosis, and vascular biology. 2000;20(1):128–34. pmid:10634809 doi: 10.1161/01.atv.20.1.128
[24]
Herrmann J, Saguner AM, Versari D, Peterson TE, Chade A, Olson M, et al. Chronic proteasome inhibition contributes to coronary atherosclerosis. Circulation research. 2007;101(9):865–74. pmid:17823377 doi: 10.1161/circresaha.107.152959
[25]
Herrmann J, Wohlert C, Saguner AM, Flores A, Nesbitt LL, Chade A, et al. Primary proteasome inhibition results in cardiac dysfunction. European journal of heart failure. 2013;15(6):614–23. doi: 10.1093/eurjhf/hft034. pmid:23616520
[26]
Feng B, Zhang Y, Mu J, Ye Z, Zeng W, Qi W, et al. Preventive effect of a proteasome inhibitor on the formation of accelerated atherosclerosis in rabbits with uremia. Journal of cardiovascular pharmacology. 2010;55(2):129–38. doi: 10.1097/FJC.0b013e3181c87f8e. pmid:19935080
[27]
Versari D, Herrmann J, Gossl M, Mannheim D, Sattler K, Meyer FB, et al. Dysregulation of the ubiquitin-proteasome system in human carotid atherosclerosis. Arteriosclerosis, thrombosis, and vascular biology. 2006;26(9):2132–9. pmid:16778122 doi: 10.1161/01.atv.0000232501.08576.73
[28]
Marfella R, D'Amico M, Di Filippo C, Baldi A, Siniscalchi M, Sasso FC, et al. Increased activity of the ubiquitin-proteasome system in patients with symptomatic carotid disease is associated with enhanced inflammation and may destabilize the atherosclerotic plaque: effects of rosiglitazone treatment. Journal of the American College of Cardiology. 2006;47(12):2444–55. pmid:16781372 doi: 10.1016/j.jacc.2006.01.073
[29]
Dombroski BA, Nayak RR, Ewens KG, Ankener W, Cheung VG, Spielman RS. Gene expression and genetic variation in response to endoplasmic reticulum stress in human cells. American journal of human genetics. 2010;86(5):719–29. doi: 10.1016/j.ajhg.2010.03.017. pmid:20398888
[30]
Shah SH, Granger CB, Hauser ER, Kraus WE, Sun JL, Pieper K, et al. Reclassification of cardiovascular risk using integrated clinical and molecular biosignatures: Design of and rationale for the Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis (MURDOCK) Horizon 1 Cardiovascular Disease Study. American heart journal. 2010;160(3):371–9 e2. doi: 10.1016/j.ahj.2010.06.051. pmid:20826242
[31]
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics. 2007;81(3):559–75. pmid:17701901 doi: 10.1086/519795
[32]
Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26(17):2190–1. doi: 10.1093/bioinformatics/btq340. pmid:20616382
[33]
Chen W, Gao G, Nerella S, Hultman CM, Magnusson PK, Sullivan PF, et al. MethylPCA: a toolkit to control for confounders in methylome-wide association studies. BMC bioinformatics. 2013;14:74. doi: 10.1186/1471-2105-14-74. pmid:23452721
[34]
Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008;24(13):1547–8. doi: 10.1093/bioinformatics/btn224. pmid:18467348
[35]
Pidsley R, CC YW, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC genomics. 2013;14:293. doi: 10.1186/1471-2164-14-293. pmid:23631413
[36]
Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013;29(2):189–96. doi: 10.1093/bioinformatics/bts680. pmid:23175756
[37]
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic acids research. 2015;43(7):e47. doi: 10.1093/nar/gkv007. pmid:25605792
[38]
Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics. 2012;13:86. doi: 10.1186/1471-2105-13-86. pmid:22568884
