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4 results on '"Siemelink, MA"'

1. Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques.

Author

van der Laan SW, Siemelink MA, Haitjema S, Foroughi Asl H, Perisic L, Mokry M, van Setten J, Malik R, Dichgans M, Worrall BB, Samani NJ, Schunkert H, Erdmann J, Hedin U, Paulsson-Berne G, Björkegrenn JLM, de Borst GJ, Asselbergs FW, den Ruijter FW, de Bakker PIW, and Pasterkamp G

Subjects
Adaptor Proteins, Vesicular Transport genetics, Aged, Alleles, Carotid Artery Diseases genetics, Female, Gene Expression Regulation, Genotype, High Mobility Group Proteins genetics, Humans, Male, Middle Aged, Plaque, Atherosclerotic genetics, Repressor Proteins genetics, Atherosclerosis genetics, Cardiovascular Diseases genetics, Genetic Loci genetics, Genetic Predisposition to Disease genetics, Polymorphism, Single Nucleotide
Abstract

Background: Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms., Methods: We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression., Results: A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10 -6 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood., Conclusions: Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics.

Published
2018
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2. Human Validation of Genes Associated With a Murine Atherosclerotic Phenotype.

Author

Pasterkamp G, van der Laan SW, Haitjema S, Foroughi Asl H, Siemelink MA, Bezemer T, van Setten J, Dichgans M, Malik R, Worrall BB, Schunkert H, Samani NJ, de Kleijn DP, Markus HS, Hoefer IE, Michoel T, de Jager SC, Björkegren JL, den Ruijter HM, and Asselbergs FW

Subjects
Animals, Computational Biology, Coronary Artery Disease pathology, Databases, Genetic, Disease Models, Animal, Gene Expression Regulation, Gene Regulatory Networks, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Intracranial Arteriosclerosis pathology, Mice, Phenotype, Plaque, Atherosclerotic, Quantitative Trait Loci, Reproducibility of Results, Risk Assessment, Risk Factors, Species Specificity, Stroke pathology, Coronary Artery Disease genetics, Gene Expression Profiling methods, Intracranial Arteriosclerosis genetics, Polymorphism, Single Nucleotide, Stroke genetics
Abstract

Objective: The genetically modified mouse is the most commonly used animal model for studying the pathogenesis of atherosclerotic disease. We aimed to assess if mice atherosclerosis-related genes could be validated in human disease through examination of results from genome-wide association studies., Approach and Results: We performed a systematic review to identify atherosclerosis-causing genes in mice and carried out gene-based association tests of their human orthologs for an association with human coronary artery disease and human large artery ischemic stroke. Moreover, we investigated the association of these genes with human atherosclerotic plaque characteristics. In addition, we assessed the presence of tissue-specific cis-acting expression quantitative trait loci for these genes in humans. Finally, using pathway analyses we show that the putative atherosclerosis-causing genes revealed few associations with human coronary artery disease, large artery ischemic stroke, or atherosclerotic plaque characteristics, despite the fact that the majority of these genes have cis-acting expression quantitative trait loci., Conclusions: A role for genes that has been observed in mice for atherosclerotic lesion development could scarcely be confirmed by studying associations of disease development with common human genetic variants. The value of murine atherosclerotic models for selection of therapeutic targets in human disease remains unclear., (© 2016 American Heart Association, Inc.)

Published
2016
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3. Common variants associated with blood lipid levels do not affect carotid plaque composition.

Author

Siemelink MA, van der Laan SW, van Setten J, de Vries JP, de Borst GJ, Moll FL, den Ruijter HM, Asselbergs FW, Pasterkamp G, and de Bakker PI

Subjects
Aged, Biological Specimen Banks, Biomarkers blood, Carotid Arteries metabolism, Carotid Arteries surgery, Carotid Artery Diseases blood, Carotid Artery Diseases diagnosis, Carotid Artery Diseases surgery, Endarterectomy, Carotid, Female, Genetic Association Studies, Genetic Markers, Genetic Predisposition to Disease, Humans, Linear Models, Logistic Models, Male, Middle Aged, Phenotype, Plaque, Atherosclerotic, Risk Assessment, Risk Factors, Carotid Arteries pathology, Carotid Artery Diseases genetics, Lipids blood, Polymorphism, Single Nucleotide
Abstract

Introduction: Although plasma lipid levels are known to influence the risk of cardiovascular disease (CVD), little is known about their effect on atherosclerotic plaque composition. To date, large-scale genome-wide association studies have identified 157 common single-nucleotide polymorphisms (SNPs) that influence plasma lipid levels, providing a powerful tool to investigate the effect of plasma lipid levels on atherosclerotic plaque composition., Methods: In this study, we included 1443 carotid endarterectomy patients from the Athero-Express Biobank Study with genotype data. Plasma concentrations of high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC) and triglycerides (TG) were determined at the time of endarterectomy. Atherosclerotic plaques, obtained during surgery, were histologically examined. For all patients, we calculated weighted genetic burden scores (GBS) for all lipid traits on the basis of the available genotype data. Plasma lipid levels and GBS were tested for association with 7 histological features using linear and logistic regression models., Results: All GBS were associated with their respective plasma lipid concentrations (pHDL-C = 2.4 × 10(-14), pLDL-C = 0.003, pTC = 2.1 × 10(-6), pTG = 3.4 × 10(-8)). Neither the measured plasma lipids, nor the GBS, were associated with histological features of atherosclerotic plaque composition. In addition, neither the plasma lipids nor the GBS were associated with clinical endpoints within 3 years of follow-up, with the notable exception of a negative association between HDL-C and composite cardiovascular endpoints., Conclusion: This study found no evidence that plasma lipid levels or their genetic determinants influence carotid plaque composition., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Published
2015
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4. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author

Justice, AE, Winkler, TW, Feitosa, MF, Graff, M, Fisher, VA, Young, K, Barata, L, Deng, X, Czajkowski, J, Hadley, D, Ngwa, JS, Ahluwalia, TS, Chu, AY, Heard-Costa, NL, Lim, E, Perez, J, Eicher, JD, Kutalik, Z, Xue, L, Mahajan, A, Renström, F, Wu, J, Qi, Q, Ahmad, S, Alfred, T, Amin, N, Bielak, LF, Bonnefond, A, Bragg, J, Cadby, G, Chittani, M, Coggeshall, S, Corre, T, Direk, N, Eriksson, J, Fischer, K, Gorski, M, Neergaard Harder, M, Horikoshi, M, Huang, T, Huffman, JE, Jackson, AU, Justesen, JM, Kanoni, S, Kinnunen, L, Kleber, ME, Komulainen, P, Kumari, M, Lim, U, Luan, J, Lyytikäinen, L-P, Mangino, M, Manichaikul, A, Marten, J, Middelberg, RPS, Müller-Nurasyid, M, Navarro, P, Pérusse, L, Pervjakova, N, Sarti, C, Smith, AV, Smith, JA, Stančáková, A, Strawbridge, RJ, Stringham, HM, Sung, YJ, Tanaka, T, Teumer, A, Trompet, S, Van Der Laan, SW, Van Der Most, PJ, Van Vliet-Ostaptchouk, JV, Vedantam, SL, Verweij, N, Vink, JM, Vitart, V, Wu, Y, Yengo, L, Zhang, W, Hua Zhao, J, Zimmermann, ME, Zubair, N, Abecasis, GR, Adair, LS, Afaq, S, Afzal, U, Bakker, SJL, Bartz, TM, Beilby, J, Bergman, RN, Bergmann, S, Biffar, R, Blangero, J, Boerwinkle, E, Bonnycastle, LL, Bottinger, E, Braga, D, Buckley, BM, Buyske, S, Campbell, H, Chambers, JC, Collins, FS, Curran, JE, De Borst, GJ, De Craen, AJM, De Geus, EJC, Dedoussis, G, Delgado, GE, Den Ruijter, HM, Eiriksdottir, G, Eriksson, AL, Esko, T, Faul, JD, Ford, I, Forrester, T, Gertow, K, Gigante, B, Glorioso, N, Gong, J, Grallert, H, Grammer, TB, Grarup, N, Haitjema, S, Hallmans, G, Hamsten, A, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, ND, Heath, AC, Hernandez, D, Hindorff, L, Hocking, LJ, Hollensted, M, Holmen, OL, Homuth, G, Jan Hottenga, J, Huang, J, Hung, J, Hutri-Kähönen, N, Ingelsson, E, James, AL, Jansson, J-O, Jarvelin, M-R, Jhun, MA, Jørgensen, ME, Juonala, M, Kähönen, M, Karlsson, M, Koistinen, HA, Kolcic, I, Kolovou, G, Kooperberg, C, Krämer, BK, Kuusisto, J, Kvaløy, K, Lakka, TA, Langenberg, C, Launer, LJ, Leander, K, Lee, NR, Lind, L, Lindgren, CM, Linneberg, A, Lobbens, S, Loh, M, Lorentzon, M, Luben, R, Lubke, G, Ludolph-Donislawski, A, Lupoli, S, Madden, PAF, Männikkö, R, Marques-Vidal, P, Martin, NG, McKenzie, CA, McKnight, B, Mellström, D, Menni, C, Montgomery, GW, Musk, AB, Narisu, N, Nauck, M, Nolte, IM, Oldehinkel, AJ, Olden, M, Ong, KK, Padmanabhan, S, Peyser, PA, Pisinger, C, Porteous, DJ, Raitakari, OT, Rankinen, T, Rao, DC, Rasmussen-Torvik, LJ, Rawal, R, Rice, T, Ridker, PM, Rose, LM, Bien, SA, Rudan, I, Sanna, S, Sarzynski, MA, Sattar, N, Savonen, K, Schlessinger, D, Scholtens, S, Schurmann, C, Scott, RA, Sennblad, B, Siemelink, MA, Silbernagel, G, Slagboom, PE, Snieder, H, Staessen, JA, Stott, DJ, Swertz, MA, Swift, AJ, Taylor, KD, Tayo, BO, Thorand, B, Thuillier, D, Tuomilehto, J, Uitterlinden, AG, Vandenput, L, Vohl, M-C, Völzke, H, Vonk, JM, Waeber, G, Waldenberger, M, Westendorp, RGJ, Wild, S, Willemsen, G, Wolffenbuttel, BHR, Wong, A, Wright, AF, Zhao, W, Zillikens, MC, Baldassarre, D, Balkau, B, Bandinelli, S, Böger, CA, Boomsma, DI, Bouchard, C, Bruinenberg, M, Chasman, DI, Chen, Y-D, Chines, PS, Cooper, RS, Cucca, F, Cusi, D, Faire, UD, Ferrucci, L, Franks, PW, Froguel, P, Gordon-Larsen, P, Grabe, H-J, Gudnason, V, Haiman, CA, Hayward, C, Hveem, K, Johnson, AD, Wouter Jukema, J, Kardia, SLR, Kivimaki, M, Kooner, JS, Kuh, D, Laakso, M, Lehtimäki, T, Marchand, LL, März, W, McCarthy, MI, Metspalu, A, Morris, AP, Ohlsson, C, Palmer, LJ, Pasterkamp, G, Pedersen, O, Peters, A, Peters, U, Polasek, O, Psaty, BM, Qi, L, Rauramaa, R, Smith, BH, Sørensen, TIA, Strauch, K, Tiemeier, H, Tremoli, E, Van Der Harst, P, Vestergaard, H, Vollenweider, P, Wareham, NJ, Weir, DR, Whitfield, JB, Wilson, JF, Tyrrell, J, Frayling, TM, Barroso, I, Boehnke, M, Deloukas, P, Fox, CS, Hirschhorn, JN, Hunter, DJ, Spector, TD, Strachan, DP, Van Duijn, CM, Heid, IM, Mohlke, KL, Marchini, J, Loos, RJF, Kilpeläinen, TO, Liu, C-T, Borecki, IB, North, KE, and Cupples, LA

Subjects
Adult, Waist-Hip Ratio, Quantitative Trait Loci, Smoking, Epistasis, Genetic, Polymorphism, Single Nucleotide, 3. Good health, Body Mass Index, Phenotype, Body Fat Distribution, Humans, Genetic Predisposition to Disease, Obesity, Waist Circumference, Adiposity, Genome-Wide Association Study
Abstract

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

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