Microduplication of 10q26.3 in a Chinese hypertriglyceridemia patient

Microduplication of 10q26.3 in a Chinese hypertriglyceridemia patient

Molecular and Cellular Probes xxx (xxxx) xxx–xxx Contents lists available at ScienceDirect Molecular and Cellular Probes journal homepage: www.elsev...

321KB Sizes 0 Downloads 20 Views

Molecular and Cellular Probes xxx (xxxx) xxx–xxx

Contents lists available at ScienceDirect

Molecular and Cellular Probes journal homepage: www.elsevier.com/locate/ymcpr

Microduplication of 10q26.3 in a Chinese hypertriglyceridemia patient Jing-Jing Lia,1, Ya-qin Chenb,1, Liang-Liang Fana, Jie-Yuan Jina, Shuai Guoa, Rong Xianga,b,∗ a b

The State Key Laboratory of Medical Genetics & School of Life Sciences, Central South University, Changsha 410013, China The Second Xiangya Hospital of Central South University, Changsha 410013, China

A R T I C L E I N F O

A B S T R A C T

Keywords: Hypertriglyceridemia CYP2E1 10q26.3 Duplication

Hypertriglyceridemia (HTG) plays an important role in the development and progression of atherosclerosis. It is inherited in an autosomal dominant pattern with a frequency of approximately 1:1,000,000 worldwide. Previous study has demonstrated that more than six genes underlie this disorder. In addition, copy number variants (CNVs) including disease-causing genes also play a crucial role in it. In this study, we have employed SNPARRAY chip technology to detect the pathogenic CNVs in a HTG patient who carried no meaningful mutations in HTG candidate genes. And we identified a de novo CNV interstitial 134.7 kb duplication of chromosome region 10q26.3 containing CYP2E1. And this CNV also has been confirmed by Real-time PCR. CYP2E1 is a member of cytochrome P450 superfamily of enzymes which play an important role in fatty acid metabolism. Our study is consistent with previous research and further claimes that CNVs containing CYP2E1 may be related to HTG and obesity. Our study not only further confirmes the hypothesis that the CYP2E1 is a plausible candidate gene for HTG, but also may contribute to the diagnosis and treatment of these genomic diseases.

1. Introduction

134.7 kb duplication of chromosome region 10q26.3 containing CYP2E1 (NM_000773). Real-time PCR was performed to confirm this CNV. Our finding suggests that the de novo CNV containing CYP2E1 may be the genetic factor of the HTG patient with obesity.

Hypertriglyceridemia (HTG) is a major public health problem and is one of the most severe lipid metabolism disorders, characterized by elevated levels of plasma triglyceride (TG > 1.7 mmol/L). HTG is an important contributory factor to development of atherosclerosis, and as such is recognized as a major risk factor for coronary artery disease. The prevalence of HTG has increased several times over the past few decades worldwide [1–3]. Previous study has demonstrated that both environment and genetic factors may increase the levels plasma TG [4]. When the levels of TG > 10 mmol/L, genetic factors may conduct a dominating role in HTG [5]. To date, more than five genes include APOA5 (NM_001166598), APOC2 (NM_000483), LPL (NM_000237), LMF1 (NM_022,773), GPIHBP1 (NM_001301772), GPD1(NM_001257199), etc [6–9] have been identified in HTG patients. In addition, several copy number variants (CNVs) also have been detected in HTG, obesity and obesityrelated syndromes, such as 1p21.3 deletion, 19q13.2 duplication and so on [10,11]. At the same time, some rare CNVs such as 10q26.3, 5q31.3 also have been reported to relate to HTG and obesity [12–14]. In this study, we employed SNP-ARRAY chip technology to detect pathogenic CNVs in a HTG patient who carried no meaningful mutations in HTG candidate genes including LPL, APOA5, APOC2, LMF1, GPD1 and GPIHBP1. And we identified a de novo CNV interstitial



1

2. Materials and methods This study was performed in accordance with the Helsinki Declaration and approval of the ethics boards of the Second Xiangya Hospital of the Central South University. All subjects have consented to this study. 2.1. Subjects We collected a female HTG patient with very high level of serum TG (TG = 11.2 mmol/L). Her body mass index (BMI) is 26.4 kg/m2. In addition, her four family members including her father and mother also have been enrolled in this study. 2.2. DNA extraction All subjects joined this study signed informed consent. Genomic DNA was extracted from peripheral blood of all patients using a DNeasy Blood & Tissue Kit (Qiagen, Valencia, CA) on the QIAcube automated

Corresponding author. The State Key Laboratory of Medical Genetics & School of Life Sciences, Central South University, Changsha, China. E-mail address: [email protected] (R. Xiang). Jing-jing Li and Ya-qin Chen contributed equally to this work.

https://doi.org/10.1016/j.mcp.2017.11.002 Received 9 June 2017; Received in revised form 6 November 2017; Accepted 6 November 2017 0890-8508/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Li, J.-J., Molecular and Cellular Probes (2017), https://doi.org/10.1016/j.mcp.2017.11.002

Molecular and Cellular Probes xxx (xxxx) xxx–xxx

J.-J. Li et al.

Table 1 Primer sequences used for mutation sequencing ofAPOA5, APOC2, GPIHBP1, LPL, GPD1 and LMF1 genes. Gene

Forward

Reverse

APOA5-1 APOA5-2 APOA5-3-1 APOA5-3-2 APOA5-3-3 APOC2-1 APOC2-2 APOC2-3 GPIHBP1-1 GPIHBP1-2 GPIHBP1-3 GPIHBP1-4 LPL-1 LPL-2 LPL-3 LPL-4 LPL-5 LPL-6 LPL-7 LPL-8 LPL-9 GPD1-1 GPD1-2 GPD1-3 GPD1-4 GPD1-5 GPD1-6 GPD1-7 GPD1-8 LMF1-1 LMF1-2 LMF1-3 LMF1-4 LMF1-5 LMF1-6 LMF1-7 LMF1-8 LMF1-9 LMF1-10 LMF1-11

TGTCCCTTCGTCTCCTTCTT CTGATTACCTAGTCCCTCTCCA GGGACAAAGGAGATGATGGA CTGAAGCCCTACACGATGGA GGCACTGGGACTGAGGAAG TGGGAAACTTGACTGGGACA CCTGGTATTGGGATTTGGT CCCCTCCTCCCTCTAACCA ATGCCCTTCATCCCACTTACC GTAGGGTGTTCAGGGTAGGG CTCACCAGGCTAGGCTTTGG CGCCCATCCTCAGCACTT GGAAAGCTGCCCACTTCTA TGGTTGCCTGTGAACCTAAA GACAAGTGGTAGGTGGGTATTT GGCAGAACTGTAAGCACCTT GCCAGTGCATTCAAATGATGAG ATGCCAAATGAAACACTC CTTCCGGTTTGAGTGCTAGT TGAGTTCTTTGTTGGACA TCCTGACAGAACTGTACCTTTG TCCTTTCCCTGGCTCTGC GGGACTATTTGTCATGGGAGT CCAAACAAGCCTTCCTGC TGGCCTCCTCACAGCAAA TAAGCCCAGGAGTTTGAG GTCACGGCTGATGAAATGA TCTGTAGGCATCCAGGTAG GGAGGGTTAGGCAGTGAG AACTGCGAAGGAGGCAGGC TGCCTCGCCCCGCATTCT GGTTGAAACAAGCCAAAGTGT CTTGCGTGTCGATGTTGA CCCTTCTCAAATTCTGCCTTCC CTCTTAGCGTGGCAGGTGG GGCACAGCTGGGTTTCA GCGTGCCAGGAACAAGGT GGGCCACAGTTCCCAAA GAACCCACCTCCAGGAAAG TTGCTGCGCTGTTCACT

CTGTGGAGAGGGACTAGGTAAT AACAGCTACGGAGTTGTCAAG TCGGCGTATGGGTGGAAG GCGGAAAGCCTGAAGTCG GACAAGGAGCTGGGAATGG GGCTGGGAAGATGCTTGG AACTTCTGGGTCCTGGATG GTGCCATCCATGAGAAGCAA GCTTCCATCCATGCTGCTCT CAGAATGCTCCAGGCAGAT TGGAGTGGGTGGTCAGGAGG CGCCCAAGACACTCCAAATC TTCCTTCTTCTCATCCTCAGTTC CCTGAGCCAGAACTGTCTTTAT CCACGCTGATTCTGAAGATTTG CCTAATAAAGAGCCCTACAATGAGATA TGGGTCAATAAGGGTTAAGGATAAG TTAGAAGCCTCAGACAAA TGCTCAGACCAAGGGTTATG CTGAAATACAGCCCCTAG GGATGCCCAGTCAGCTTTA CCTCCTACCCACCTCTGTCTT GAGGCACCTGTTGAGTAAGG CTCCTTGCTTCACCCACC TCCCAGCCTCCTTCACCT CACGGTCTGATGATGAATAA CAAGCACCTCTACCTGGAT AGATTTGTGGCAGGTTTAG TTTCTGGCAAATGTGGTG GCGGAGGAGTCTCGAGGGAG AGCTCCGACCGCCCCATT AGATCACAAGCGCCCATC GGTTAGAAGAGCCACCGTTA TGATGCGACAGCTCACCAG CAAACGAAGGCTGGGGAG TGAGCCACCTACCGAATCT TGTCCAGGCCCGGTAGTG CGTTCTAGAAACCTGCCATCTAT TGATGCCAAGGCTGATGT GCTGGGTCTTCGCCTTTATT

(qPCR) was performed using the 7500 Fast Real-Time PCR systems (Applied Biosystems, Foster City, California). For potentially pathogenic CNV, two primer sets were designed within the boundaries of the CNV region. Primer pairs were designed by an online PrimerQuest tool of Integrated DNA Technology (IDT) (http://www.idtdna.com/ Primerquest/Home/Index). The forward and reverse primers are 5′-CTGGACTACAAGGACGAGTTC-3′ and 5′-CCTTCCAGGTAGGTCCAT TATT-3′, respectively. PCR reactions were prepared with the SYBR Premix Ex Taq II PCR reagent kit (TaKaRa Bio, Dalian, China) according to the manufacturer's protocol. Amplification levels were calculated with the 2−ΔΔCT method [16].

DNA extraction robot (Qiagen, Hilden, Germany). 2.3. Sanger sequencing Through polymerase chain reaction (PCR; primer sequences were shown in the Table 1), we amplified several genes, including LPL, APOA5, APOC2, LMF1, GPD1 and GPIHBP1. The sequences of the PCR products were obtained using the ABI 3100 genetic analyzer (Applied Biosystems; Thermo Fisher Scientific, Inc., Waltham, MA, USA). 2.4. SNP array analysis Genomic DNA samples of patients were adjusted to a final concentration of 50 ng/μL. The HumanOmni1-Quad Chip (Illumina Inc., San Diego, USA) and the Illumina BeadScan genotyping system (Beadstation Scanner) were employed to obtain the signal intensities of SNP probes. HumanOmni1-Quad Beadchip contains over 1.1 million loci across the human genome, including markers derived from the three HapMap, the 1000 Genomes Project and recently published studies. The GenomeStudio V2011 software was used to analyze the genotypes (human genome build 37/Hg19 for analysis) and evaluate the experimental quality as previously described [15]. The call rates of the samples are greater than 99.0%.

3. Results

2.5. Real-time PCR

Sanger sequencing showed no meaningful mutations in LPL, APOA5, APOC2, LMF1, GPD1 and GPIHBP1. Then we suspected that CNVs may be the genetic lesion of this patient. So we applied SNP array system

3.1. Clinic data The proband, a 29-year-old officer from Hunan province of CentralSouth China, had extremely high serum level of HTG (TG = 11.2 mmol/L). Her BMI was 26.4 kg/m2 and had no diabetes mellitus and acute pancreatitis. All the four family members showed no HTG and obesity. 3.2. Genetic analysis

To validate variable copy numbers, real-time quantitative PCR 2

Molecular and Cellular Probes xxx (xxxx) xxx–xxx

J.-J. Li et al.

Fig. 1. Human Omni1-Quad SNP array results of 10q26.3 duplication in the proband.

synthesis and lipid synthesis, eventually result in increased level of lipids. There is evidence showing that a majority of people (96.07%) harbor two copies of CYP2E1 copy number. About 3.70% of people have CYP2E1 tri-copy, while the haplotype and tetratype are relatively rare among the population with a percentage of 0.09% and 0.14%, respectively [13]. Patients with tri-copy and tetratype of CYP2E1 often show obesity and HTG phenotypes. In our study, the proband who carried tri-copy of CYP2E1 also showed a HTG and obesity phenotype. Fibrates are well-used for the treatment of HTG, but sometimes with the problem of drug resistance. Previous study has demonstrated that genetic detection in combination with medication could effectively decrease serum TG [23]. It is indicated that genetic detection plays a crucial role in the treatment of HTG. In our study, we found a potential pathogenic gene of HTG which may possibly contribute to the diagnosis and accurately treatment of the genomic disease. In conclusion, we identified a de novo CNV interstitial 134.7 kb duplication of chromosome region 10q26.3 containing CYP2E1 (NM_000773) in a HTG patient by SNP-ARRAY chip technology. The patient carried no meaningful mutations in HTG candidate genes including LPL, APOA5, APOC2, LMF1, GPD1 and GPIHBP1. Real-time PCR was performed to confirm this CNV. It is consistent with previous study that CYP2E1 may be a genetic factor of HTG. Our study not only further confirmed the hypothesis that the CYP2E1 is a plausible candidate gene for HTG, but also may contribute to the diagnosis and treatment of the genomic diseases.

(HumanOmni1-Quad Chip) to analyze the whole genome CNVs in this patient. A de novo 134.7 kb duplication in 10q26.3 (chr10:135242873–135377570; Hg19) was identified (Fig. 1), which included CYP2E1 gene. Real-time PCR further confirmed this CNV but found no 10q26.3 duplication in other four family members. These discoveries indicate that the de novo 10q26.3 duplication containing CYP2E1 may underlie HTG and obesity in this patient. 4. Discussion In this study, we have employed SNP-ARRAY chip technology to explore the pathogenic CNVs in a HTG patient who carried no meaningful mutations in HTG candidate genes including LPL, APOA5, APOC2, LMF1, GPD1 and GPIHBP1. A de novo CNV containing CYP2E1 was identified in this patient which may be the causative factor of HTG disorder. Our study is consistent with previous reports that duplications containing CYP2E1 may be the genetic reason of HTG and obesity. CYP2E1 encodes protein CYP2E1, an enzyme belongs to cytochrome P450 family 2 subfamily [17]. It catalyzes many reactions involving drug metabolism and synthesis of cholesterol, steroids and other lipids. CYP2E1 carries out the metabolism of endogenous fatty acids including ω-1 hydroxylation of fatty acids such as arachidonic acid, suggesting its importantance in signaling pathways related to diabetes and obesity [18]. CYP2E1 is inducible by many of its substrates, for instance, ethanol and acetone [19]. Physiologically, this enzyme participates in the propane diol pathway, an alternative pathway of gluconeogenesis, which serves to generate glucose during starvation via hydroxylation of acetone, hydroxyacetone and pyruvate [20–22]. Fluctuation of CYP2E1 levels and activities might break the balance, therefore the TG metabolism are likely to be affected. Tremmel et al. thought CYP2E1 copy number variants are not leading to changes in enzyme activity, they hypothesized that one SNP or a combination of linked SNPs could compensate CYP2E1 expression in subjects carrying additional CYP2E1 copies [20]. However, in our study, we didn't identify any significative SNPs in the patient. Also the difference could be due to the genetic heterogeneity between the white sample and Chinese samples. Yang T L et al. thought 10q26.3 duplications have been associated with obesity in white and African-American subjects [13]. This is consistent with our research. It's more convincing than Tremmel et al.'s viewpoint owning to much greater volumes of data and ethnicity. Previous studies revealed that overexpression of CYP2E1 may increase the level of blood glucose, followed by elevated glycogen

Funding This study was supported by the National Natural Science Foundation of China (81370394) and the Fundamental Research Funds for Central Universities of Central South University (2016zzts163, 2016zzts581, 2017zzts348).

Conflicts of interest None.

Acknowledgements We thank the patients and their families for participating in this study. 3

Molecular and Cellular Probes xxx (xxxx) xxx–xxx

J.-J. Li et al.

References [1] E.A. Brinton, Management of hypertriglyceridemia for prevention of atherosclerotic cardiovascular disease, Endocrinol. Metabol. Clin. N. Am. 45 (1) (2016) 185–204. [2] E.S. Ford, C. Li, G. Zhao, W.S. Pearson, A.H. Mokdad, Hypertriglyceridemia and its pharmacologic treatment among US adults, Archives Intern. Med. 169 (6) (2009) 572–578. [3] J.B. Christian, N. Bourgeois, R. Snipes, K.A. Lowe, Prevalence of severe (500 to 2,000 mg/dl) hypertriglyceridemia in United States adults, Am. J. Cardiol. 107 (6) (2011) 891–897. [4] G.F. Lewis, C. Xiao, R.A. Hegele, Hypertriglyceridemia in the genomic era: a new paradigm, Endocr. Rev. 36 (1) (2015) 131–147. [5] P. Stahel, C. Xiao, R.A. Hegele, et al., Polygenic risk for hypertriglyceridemia can mimic a major monogenic mutation, Ann. Intern. Med. 167 (5) (2017) 360–361. [6] U. Kassner, B. Salewsky, M. Wuhle-Demuth, I.A. Szijarto, T. Grenkowitz, P. Binner, W. Marz, E. Steinhagen-Thiessen, I. Demuth, Severe hypertriglyceridemia in a patient heterozygous for a lipoprotein lipase gene allele with two novel missense variants, Eur. J. Hum. Genet. EJHG 23 (9) (2015) 1259–1261. [7] C. Rabacchi, L. Pisciotta, A.B. Cefalu, D. Noto, R. Fresa, P. Tarugi, M. Averna, S. Bertolini, S. Calandra, Spectrum of mutations of the LPL gene identified in Italy in patients with severe hypertriglyceridemia, Atherosclerosis 241 (1) (2015) 79–86. [8] R.P. Surendran, M.E. Visser, S. Heemelaar, J. Wang, J. Peter, J.C. Defesche, J.A. Kuivenhoven, M. Hosseini, M. Peterfy, J.J. Kastelein, C.T. Johansen, R.A. Hegele, E.S. Stroes, G.M. Dallinga-Thie, Mutations in LPL, APOC2, APOA5, GPIHBP1 and LMF1 in patients with severe hypertriglyceridaemia, J. Intern. Med. 272 (2) (2012) 185–196. [9] J. Nocon-Bohusz, B. Wikiera, A. Basiak, R. Smigiel, A. Noczynska, LPL gene mutation as the cause of severe hypertriglyceridemia in the course of ketoacidosis in a patient with newly diagnosed type 1 diabetes mellitus, Pediatr. Endocrinol. diabetes, Metabol. 21 (2) (2016) 89–92. [10] B.M. Herrera, S. Keildson, C.M. Lindgren, Genetics and epigenetics of obesity, Maturitas 69 (1) (2011) 41–49. [11] E.K. Speliotes, C.J. Willer, S.I. Berndt, K.L. Monda, G. Thorleifsson, A.U. Jackson, H. Lango Allen, C.M. Lindgren, J. Luan, R. Magi, J.C. Randall, S. Vedantam, T.W. Winkler, L. Qi, T. Workalemahu, I.M. Heid, V. Steinthorsdottir, H.M. Stringham, M.N. Weedon, E. Wheeler, A.R. Wood, T. Ferreira, R.J. Weyant, A.V. Segre, K. Estrada, L. Liang, J. Nemesh, J.H. Park, S. Gustafsson, T.O. Kilpelainen, J. Yang, N. Bouatia-Naji, T. Esko, M.F. Feitosa, Z. Kutalik, M. Mangino, S. Raychaudhuri, A. Scherag, A.V. Smith, R. Welch, J.H. Zhao, K.K. Aben, D.M. Absher, N. Amin, A.L. Dixon, E. Fisher, N.L. Glazer, M.E. Goddard, N.L. Heard-Costa, V. Hoesel, J.J. Hottenga, A. Johansson, T. Johnson, S. Ketkar, C. Lamina, S. Li, M.F. Moffatt, R.H. Myers, N. Narisu, J.R. Perry, M.J. Peters, M. Preuss, S. Ripatti, F. Rivadeneira, C. Sandholt, L.J. Scott, N.J. Timpson, J.P. Tyrer, S. van Wingerden, R.M. Watanabe, C.C. White, F. Wiklund, C. Barlassina, D.I. Chasman, M.N. Cooper, J.O. Jansson, R.W. Lawrence, N. Pellikka, I. Prokopenko, J. Shi, E. Thiering, H. Alavere, M.T. Alibrandi, P. Almgren, A.M. Arnold, T. Aspelund, L.D. Atwood, B. Balkau, A.J. Balmforth, A.J. Bennett, Y. Ben-Shlomo, R.N. Bergman, S. Bergmann, H. Biebermann, A.I. Blakemore, T. Boes, L.L. Bonnycastle, S.R. Bornstein, M.J. Brown, T.A. Buchanan, F. Busonero, H. Campbell, F.P. Cappuccio, C. Cavalcanti-Proenca, Y.D. Chen, C.M. Chen, P.S. Chines, R. Clarke, L. Coin, J. Connell, I.N. Day, M. den Heijer, J. Duan, S. Ebrahim, P. Elliott, R. Elosua, G. Eiriksdottir, M.R. Erdos, J.G. Eriksson, M.F. Facheris, S.B. Felix, P. Fischer-Posovszky, A.R. Folsom, N. Friedrich, N.B. Freimer, M. Fu, S. Gaget, P.V. Gejman, E.J. Geus, C. Gieger, A.P. Gjesing, A. Goel, P. Goyette, H. Grallert, J. Grassler, D.M. Greenawalt, C.J. Groves, V. Gudnason, C. Guiducci, A.L. Hartikainen, N. Hassanali, A.S. Hall, A.S. Havulinna, C. Hayward, A.C. Heath, C. Hengstenberg, A.A. Hicks, A. Hinney, A. Hofman, G. Homuth, J. Hui, W. Igl, C. Iribarren, B. Isomaa, K.B. Jacobs, I. Jarick, E. Jewell, U. John, T. Jorgensen, P. Jousilahti, A. Jula, M. Kaakinen, E. Kajantie, L.M. Kaplan, S. Kathiresan, J. Kettunen, L. Kinnunen, J.W. Knowles, I. Kolcic, I.R. Konig, S. Koskinen, P. Kovacs, J. Kuusisto, P. Kraft, K. Kvaloy, J. Laitinen, O. Lantieri, C. Lanzani, L.J. Launer, C. Lecoeur, T. Lehtimaki, G. Lettre, J. Liu, M.L. Lokki, M. Lorentzon, R.N. Luben, B. Ludwig, Magic, P. Manunta, D. Marek, M. Marre, N.G. Martin, W.L. McArdle, A. McCarthy, B. McKnight, T. Meitinger, O. Melander, D. Meyre, K. Midthjell, G.W. Montgomery, M.A. Morken, A.P. Morris, R. Mulic, J.S. Ngwa, M. Nelis, M.J. Neville, D.R. Nyholt, C.J. O'Donnell, S. O'Rahilly, K.K. Ong, B. Oostra, G. Pare, A.N. Parker, M. Perola, I. Pichler, K.H. Pietilainen, C.G. Platou, O. Polasek, A. Pouta, S. Rafelt, O. Raitakari, N.W. Rayner, M. Ridderstrale, W. Rief, A. Ruokonen, N.R. Robertson, P. Rzehak, V. Salomaa,

[12]

[13]

[14]

[15]

[16]

[17]

[18]

[19]

[20]

[21] [22]

[23]

4

A.R. Sanders, M.S. Sandhu, S. Sanna, J. Saramies, M.J. Savolainen, S. Scherag, S. Schipf, S. Schreiber, H. Schunkert, K. Silander, J. Sinisalo, D.S. Siscovick, J.H. Smit, N. Soranzo, U. Sovio, J. Stephens, I. Surakka, A.J. Swift, M.L. Tammesoo, J.C. Tardif, M. Teder-Laving, T.M. Teslovich, J.R. Thompson, B. Thomson, A. Tonjes, T. Tuomi, J.B. van Meurs, G.J. van Ommen, V. Vatin, J. Viikari, S. Visvikis-Siest, V. Vitart, C.I. Vogel, B.F. Voight, L.L. Waite, H. Wallaschofski, G.B. Walters, E. Widen, S. Wiegand, S.H. Wild, G. Willemsen, D.R. Witte, J.C. Witteman, J. Xu, Q. Zhang, L. Zgaga, A. Ziegler, P. Zitting, J.P. Beilby, I.S. Farooqi, J. Hebebrand, H.V. Huikuri, A.L. James, M. Kahonen, D.F. Levinson, F. Macciardi, M.S. Nieminen, C. Ohlsson, L.J. Palmer, P.M. Ridker, M. Stumvoll, J.S. Beckmann, H. Boeing, E. Boerwinkle, D.I. Boomsma, M.J. Caulfield, S.J. Chanock, F.S. Collins, L.A. Cupples, G.D. Smith, J. Erdmann, P. Froguel, H. Gronberg, U. Gyllensten, P. Hall, T. Hansen, T.B. Harris, A.T. Hattersley, R.B. Hayes, J. Heinrich, F.B. Hu, K. Hveem, T. Illig, M.R. Jarvelin, J. Kaprio, F. Karpe, K.T. Khaw, L.A. Kiemeney, H. Krude, M. Laakso, D.A. Lawlor, A. Metspalu, P.B. Munroe, W.H. Ouwehand, O. Pedersen, B.W. Penninx, A. Peters, P.P. Pramstaller, T. Quertermous, T. Reinehr, A. Rissanen, I. Rudan, N.J. Samani, P.E. Schwarz, A.R. Shuldiner, T.D. Spector, J. Tuomilehto, M. Uda, A. Uitterlinden, T.T. Valle, M. Wabitsch, G. Waeber, N.J. Wareham, H. Watkins, C. Procardis, J.F. Wilson, A.F. Wright, M.C. Zillikens, N. Chatterjee, S.A. McCarroll, S. Purcell, E.E. Schadt, P.M. Visscher, T.L. Assimes, I.B. Borecki, P. Deloukas, C.S. Fox, L.C. Groop, T. Haritunians, D.J. Hunter, R.C. Kaplan, K.L. Mohlke, J.R. O'Connell, L. Peltonen, D. Schlessinger, D.P. Strachan, C.M. van Duijn, H.E. Wichmann, T.M. Frayling, U. Thorsteinsdottir, G.R. Abecasis, I. Barroso, M. Boehnke, K. Stefansson, K.E. North, M.I. McCarthy, J.N. Hirschhorn, E. Ingelsson, R.J. Loos, Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index, Nat. Genet. 42 (11) (2010) 937–948. S. Moon, M.Y. Hwang, H.B. Jang, S. Han, Y.J. Kim, J.Y. Hwang, H.J. Lee, S.I. Park, J. Song, B.J. Kim, Whole-exome sequencing study reveals common copy number variants in protocadherin genes associated with childhood obesity in Koreans, Int. J. Obes. 41 (4) (2017) 660–663. T.L. Yang, Y. Guo, H. Shen, J. Li, J.T. Glessner, C. Qiu, F.Y. Deng, Q. Tian, P. Yu, Y.Z. Liu, Y.J. Liu, H. Hakonarson, S.F. Grant, H.W. Deng, Copy number variation on chromosome 10q26.3 for obesity identified by a genome-wide study, J. Clin. Endocrinol. Metabol. 98 (1) (2013) E191–E195. C. Serra-Juhe, G.A. Martos-Moreno, F. Bou de Pieri, R. Flores, J.R. Gonzalez, B. Rodriguez-Santiago, J. Argente, L.A. Perez-Jurado, Novel genes involved in severe early-onset obesity revealed by rare copy number and sequence variants, PLoS Genet. 13 (5) (2017) e1006657. J.L. Chen, Y.F. Yang, C. Huang, J. Wang, J.F. Yang, Z.P. Tan, Clinical and molecular delineation of 16p13.3 duplication in a patient with congenital heart defect and multiple congenital anomalies, Am. J. Med. Genet. Part A 158A (3) (2012) 685–688. K.J. Livak, T.D. Schmittgen, Analysis of relative gene expression data using realtime quantitative PCR and the 2(-Delta Delta C(T)) Method, Methods 25 (4) (2001) 402–408. J.H. Hartman, G.P. Miller, A.A. Caro, et al., 1,3-Butadiene-induced mitochondrial dysfunction is correlated with mitochondrial CYP2E1 activity in collaborative cross mice, Toxicology 378 (2017) 114–124. P.R. Porubsky, K.M. Meneely, E.E. Scott, Structures of human cytochrome P-450 2E1. Insights into the binding of inhibitors and both small molecular weight and fatty acid substrates, J. Biol. Chem. 283 (48) (2008) 33698–33707. H.M. Bolt, P.H. Roos, R. Thier, The cytochrome P-450 isoenzyme CYP2E1 in the biological processing of industrial chemicals: consequences for occupational and environmental medicine, Int. archives Occup. Environ. health 76 (3) (2003) 174–185. R. Tremmel, K. Klein, S. Winter, E. Schaeffeler, U.M. Zanger, Gene copy number variation analysis reveals dosage-insensitive expression of CYP2E1, Pharmacogenomics J. 16 (6) (2016) 551–558. F.J. Gonzalez, The 2006 Bernard B. Brodie Award Lecture. Cyp2e1, Drug Metabol. Dispos. Biol. fate Chem. 35 (1) (2007) 1–8. D.R. Koop, J.P. Casazza, Identification of ethanol-inducible P-450 isozyme 3a as the acetone and acetol monooxygenase of rabbit microsomes, J. Biol. Chem. 260 (25) (1985) 13607–13612. A.B. Cefalu, D. Noto, M.L. Arpi, F. Yin, R. Spina, H. Hilden, C.M. Barbagallo, A. Carroccio, P. Tarugi, S. Squatrito, R. Vigneri, M.R. Taskinen, M. Peterfy, M.R. Averna, Novel LMF1 nonsense mutation in a patient with severe hypertriglyceridemia, J. Clin. Endocrinol. Metabol. 94 (11) (2009) 4584–4590.