Search

Your search keyword '"Pool R"' showing total 1,473 results
Start Over Author "Pool R"
1,473 results on '"Pool R"'

1. NMR metabolomics-guided DNA methylation mortality predictors

Author

Geleijnse, J.M., Boersma, E., van Spil, W.E., van Greevenbroek, M.M.J., Stehouwer, C.D.A., van der Kallen, C.J.H., Arts, I.C.W., Rutters, F., Beulens, J.W.J., Muilwijk, M., Elders, P.J.M., 't Hart, L.M., Ghanbari, M., Ikram, M.A., Netea, M.G., Kloppenburg, M., Ramos, Y.F.M., Bomer, N., Meulenbelt, I., Stronks, K., Snijder, M.B., Zwinderman, A.H., Heijmans, B.T., Lumey, L.H., Wijmenga, C., Fu, J., Zhernakova, A., Deelen, J., Mooijaart, S.P., Beekman, M., Slagboom, P.E., Onderwater, G.L.J., van den Maagdenberg, A.M.J.M., Terwindt, G.M., Thesing, C., Bot, M., Penninx, B.W.J.H., Trompet, S., Jukema, J.W., Sattar, N., van der Horst, I.C.C., van der Harst, P., So-Osman, C., van Hilten, J.A., Nelissen, R.G.H.H., Höfer, I.E., Asselbergs, F.W., Scheltens, P., Teunissen, C.E., van der Flier, W.M., van Dongen, J., Pool, R., Willemsen, A.H.M., Boomsma, D.I., Suchiman, H.E.D., Barkey Wolf, J.J.H., Cats, D., Mei, H., Slofstra, M., Swertz, M., Reinders, M.J.T., van den Akker, E.B., Bizzarri, Daniele, Reinders, Marcel J.T., Kuiper, Lieke, Beekman, Marian, Deelen, Joris, van Meurs, Joyce B.J., van Dongen, Jenny, Pool, René, Boomsma, Dorret I., Ghanbari, Mohsen, Franke, Lude, Slagboom, Pieternella E., and van den Akker, Erik B.

Published
2024
Full Text
View/download PDF

2. Metabolomics Profile in Depression: A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls

Author

Beekman, M., Suchiman, H.E.D., Deelen, J., Amin, N., Beulens, J.W., van der Bom, J.A., Bomer, N., Demirkan, A., van Hilten, J.A., Meessen, J.M.T.A., Pool, R., Moed, M.H., Fu, J., Onderwater, G.L.J., Rutters, F., So-Osman, C., van der Flier, W.M., van der Heijden, A.A.W.A., van der Spek, A., Asselbergs, F.W., Boersma, E., Elders, P.M., Geleijnse, J.M., Ikram, M.A., Kloppenburg, M., Meulenbelt, I., Mooijaart, S.P., Nelissen, R.G.H.H., Netea, M.G., Penninx, B.W.J.H., Stehouwer, C.D.A., Teunissen, C.E., Terwindt, G.M., ’t Hart, L.M., van den Maagdenberg, A.M.J.M., van der Harst, P., van der Horst, I.C.C., van der Kallen, C.J.H., van Greevenbroek, M.M.J., van Spil, W.E., Wijmenga, C., Zwinderman, A.H., Zhernikova, A., Jukema, J.W., Sattar, N., Bot, Mariska, Milaneschi, Yuri, Al-Shehri, Tahani, Amin, Najaf, Garmaeva, Sanzhima, Onderwater, Gerrit L.J., Pool, Rene, Thesing, Carisha S., Vijfhuizen, Lisanne S., Vogelzangs, Nicole, Arts, Ilja C.W., Demirkan, Ayse, van Duijn, Cornelia, van Greevenbroek, Marleen, van der Kallen, Carla J.H., Köhler, Sebastian, Ligthart, Lannie, van den Maagdenberg, Arn M.J.M., Mook-Kanamori, Dennis O., de Mutsert, Renée, Tiemeier, Henning, Schram, Miranda T., Stehouwer, Coen D.A., Terwindt, Gisela M., Willems van Dijk, Ko, Fu, Jingyuan, Zhernakova, Alexandra, Beekman, Marian, Slagboom, P. Eline, Boomsma, Dorret I., and Penninx, Brenda W.J.H.

Published
2020
Full Text
View/download PDF

5. A Potential Role for the STXBP5-AS1 Gene in Adult ADHD Symptoms

Author

Arias-Vásquez, A., Groffen, A. J., Spijker, S., Ouwens, K. G., Klein, M., Vojinovic, D., Galesloot, T. E., Bralten, J., Hottenga, J. J., van der Most, P. J., Kattenberg, V. M., Pool, R., Nolte, I. M., Penninx, B. W. J. H., Fedko, I. O., Dolan, C. V., Nivard, M. G., den Braber, A., van Duijn, C. M., Hoekstra, P. J., Buitelaar, J. K., Kiemeney, L. A., Hoogman, M., Middeldorp, C. M., Draisma, H. H. M., Vermeulen, S. H., Sánchez-Mora, C., Ramos-Quiroga, J. A., Ribasés, M., The EAGLE-ADHD Consortium, Hartman, C. A., Kooij, J. J. S., Amin, N., Smit, A. B., Franke, B., and Boomsma, D. I.

Published
2019
Full Text
View/download PDF

7. Meta-analysis of genome-wide association studies of hoarding symptoms in 27,537 individuals

Author

Strom, N.I., Smit, D.J.A., Silzer, T., Iyegbe, C., Burton, C.L., Pool, R., Lemire, M., Crowley, J.J., Hottenga, J.-J., Ivanov, V.Z., Larsson, H., Lichtenstein, P., Magnusson, P., Rück, C., Schachar, R.J., Wu, H.M., Meier, S.M., Crosbie, J., Arnold, P.D., Mattheisen, M., Boomsma, D.I., Mataix-Cols, D., Cath, D., Adult Psychiatry, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Amsterdam Reproduction & Development, APH - Mental Health, and APH - Methodology

Subjects
Obsessive-Compulsive Disorder, Hoarding Disorder, Autism Spectrum Disorder, Humans, Hoarding, Genome-Wide Association Study
Abstract

© 2022, The Author(s).Hoarding Disorder (HD) is a mental disorder characterized by persistent difficulties discarding or parting with possessions, often resulting in cluttered living spaces, distress, and impairment. Its etiology is largely unknown, but twin studies suggest that it is moderately heritable. In this study, we pooled phenotypic and genomic data from seven international cohorts (N = 27,537 individuals) and conducted a genome wide association study (GWAS) meta-analysis of parent- or self-reported hoarding symptoms (HS). We followed up the results with gene-based and gene-set analyses, as well as leave-one-out HS polygenic risk score (PRS) analyses. To examine a possible genetic association between hoarding symptoms and other phenotypes we conducted cross-trait PRS analyses. Though we did not report any genome-wide significant SNPs, we report heritability estimates for the twin-cohorts between 26–48%, and a SNP-heritability of 11% for an unrelated sub-cohort. Cross-trait PRS analyses showed that the genetic risk for schizophrenia and autism spectrum disorder were significantly associated with hoarding symptoms. We also found suggestive evidence for an association with educational attainment. There were no significant associations with other phenotypes previously linked to HD, such as obsessive-compulsive disorder, depression, anxiety, or attention-deficit hyperactivity disorder. To conclude, we found that HS are heritable, confirming and extending previous twin studies but we had limited power to detect any genome-wide significant loci. Much larger samples will be needed to further extend these findings and reach a “gene discovery zone”. To move the field forward, future research should not only include genetic analyses of quantitative hoarding traits in larger samples, but also in samples of individuals meeting strict diagnostic criteria for HD, and more ethnically diverse samples.

Published
2022

8. Genome-wide study of DNA methylation shows alterations in metabolic, inflammatory, and cholesterol pathways in ALS

Author

Hop, P.J., Zwamborn, R.A.J., Hannon, E., Shireby, G.L., Nabais, M.F., Walker, E.M., van Rheenen, W., van Vugt, J.J.F.A., Dekker, A.M., Westeneng, H-J, Tazelaar, G.H.P., van Eijk, K.R., Moisse, M., Baird, D., Al Khleifat, A., Iacoangeli, A., Ticozzi, N., Ratti, A., Cooper-Knock, J., Morrison, K.E., Shaw, P.J., Basak, A.N., Chiò, A., Calvo, A., Moglia, C., Canosa, A., Brunetti, M., Grassano, M., Gotkine, M., Lerner, Y., Zabari, M., Vourc’h, P., Corcia, P., Couratier, P., Mora Pardina, J.S., Salas, T., Dion, P., Ross, J.P., Henderson, R.D., Mathers, S., McCombe, P.A., Needham, M., Nicholson, G., Rowe, D.B., Pamphlett, R., Mather, K.A., Sachdev, P.S., Furlong, S., Garton, F.C., Henders, A.K., Lin, T., Ngo, S.T., Steyn, F.J., Wallace, L., Williams, K.L., Neto, M.M., Cauchi, R.J., Blair, I.P., Kiernan, M.C., Drory, V., Povedano, M., de Carvalho, M., Pinto, S., Weber, M., Rouleau, G.A., Silani, V., Landers, J.E., Shaw, C.E., Andersen, P.M., McRae, A.F., van Es, M.A., Pasterkamp, R.J., Wray, N.R., McLaughlin, R.L., Hardiman, O., Kenna, K.P., Tsai, E., Runz, H., Al-Chalabi, A., van den Berg, L.H., Van Damme, P., Mill, J., Veldink, J.H., Heijmans, B.T., t Hoen, P.A.C., van Meurs, J., Jansen, R., Franke, L., Boomsma, D.I., Pool, R., van Dongen, J., Hottenga, J.J., van Greevenbroek, M.M.J., Stehouwer, C.D.A., van der Kallen, C.J.H., Schalkwijk, C.G., Wijmenga, C., Zhernakova, S., Tigchelaar, E.F., Slagboom, P.E., Beekman, M., Deelen, J., Van Heemst, D., van Duijn, C.M., Hofman, B.A., Isaacs, A., Uitterlinden, A.G., van Meurs, J.B.C., Jhamai, P.M., Verbiest, M., Suchiman, H.E.D., Verkerk, M., van der Breggen, R., van Rooij, J., Lakenberg, N., Mei, H., van Iterson, M., van Galen, M., Bot, J., Zhernakova, D.V., van ‘t Hof, P., Deelen, P., Nooren, I., Moed, M., Vermaat, M., Luijk, R., Jan Bonder, M., van Dijk, F., Arindrarto, W., Kielbasa, S.M., Swertz, M.A., van Zwet, E.W., Hoen, P.A.C., Bensimon, G., Chio, A., Smith, G.D., Hop, P.J., Zwamborn, R.A.J., Hannon, E., Shireby, G.L., Nabais, M.F., Walker, E.M., van Rheenen, W., van Vugt, J.J.F.A., Dekker, A.M., Westeneng, H-J, Tazelaar, G.H.P., van Eijk, K.R., Moisse, M., Baird, D., Al Khleifat, A., Iacoangeli, A., Ticozzi, N., Ratti, A., Cooper-Knock, J., Morrison, K.E., Shaw, P.J., Basak, A.N., Chiò, A., Calvo, A., Moglia, C., Canosa, A., Brunetti, M., Grassano, M., Gotkine, M., Lerner, Y., Zabari, M., Vourc’h, P., Corcia, P., Couratier, P., Mora Pardina, J.S., Salas, T., Dion, P., Ross, J.P., Henderson, R.D., Mathers, S., McCombe, P.A., Needham, M., Nicholson, G., Rowe, D.B., Pamphlett, R., Mather, K.A., Sachdev, P.S., Furlong, S., Garton, F.C., Henders, A.K., Lin, T., Ngo, S.T., Steyn, F.J., Wallace, L., Williams, K.L., Neto, M.M., Cauchi, R.J., Blair, I.P., Kiernan, M.C., Drory, V., Povedano, M., de Carvalho, M., Pinto, S., Weber, M., Rouleau, G.A., Silani, V., Landers, J.E., Shaw, C.E., Andersen, P.M., McRae, A.F., van Es, M.A., Pasterkamp, R.J., Wray, N.R., McLaughlin, R.L., Hardiman, O., Kenna, K.P., Tsai, E., Runz, H., Al-Chalabi, A., van den Berg, L.H., Van Damme, P., Mill, J., Veldink, J.H., Heijmans, B.T., t Hoen, P.A.C., van Meurs, J., Jansen, R., Franke, L., Boomsma, D.I., Pool, R., van Dongen, J., Hottenga, J.J., van Greevenbroek, M.M.J., Stehouwer, C.D.A., van der Kallen, C.J.H., Schalkwijk, C.G., Wijmenga, C., Zhernakova, S., Tigchelaar, E.F., Slagboom, P.E., Beekman, M., Deelen, J., Van Heemst, D., van Duijn, C.M., Hofman, B.A., Isaacs, A., Uitterlinden, A.G., van Meurs, J.B.C., Jhamai, P.M., Verbiest, M., Suchiman, H.E.D., Verkerk, M., van der Breggen, R., van Rooij, J., Lakenberg, N., Mei, H., van Iterson, M., van Galen, M., Bot, J., Zhernakova, D.V., van ‘t Hof, P., Deelen, P., Nooren, I., Moed, M., Vermaat, M., Luijk, R., Jan Bonder, M., van Dijk, F., Arindrarto, W., Kielbasa, S.M., Swertz, M.A., van Zwet, E.W., Hoen, P.A.C., Bensimon, G., Chio, A., and Smith, G.D.

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability between 40 and 50%. DNA methylation patterns can serve as proxies of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study meta-analysis in 9706 samples passing stringent quality control (6763 patients, 2943 controls). We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We then tested 39 DNA methylation–based proxies of putative ALS risk factors and found that high-density lipoprotein cholesterol, body mass index, white blood cell proportions, and alcohol intake were independently associated with ALS. Integration of these results with our latest genome-wide association study showed that cholesterol biosynthesis was potentially causally related to ALS. Last, DNA methylation at several DMPs and blood cell proportion estimates derived from DNA methylation data were associated with survival rate in patients, suggesting that they might represent indicators of underlying disease processes potentially amenable to therapeutic interventions.

Published
2022

9. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Author

Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., Hoed, Marcel Den, Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., and Hoed, Marcel Den

Abstract

Contains fulltext : 282313.pdf (Publisher’s version ) (Open Access), Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type II(A) muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Published
2022

10. Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Author

Pool, Rene, Hagenbeek, Fiona A., Hendriks, Anne M., van Dongen, Jenny, Willemsen, Gonneke, de Geus, Eco, van Dijk, Ko Willems, Verhoeven, Aswin, Suchiman, H. Eka, Beekman, Marian, Slagboom, P. Eline, Harms, Amy C., Hankemeier, Thomas, Boomsma, Dorret, I, Beekman, M., Suchiman, H. E. D., Amin, N., Beulens, J. W., van der Bom, J. A., Bomer, N., Demirkan, A., van Hilten, J. A., Meessen, J. M. T. A., Pool, R., Moed, M. H., Fu, J., Onderwater, G. L. J., Rutters, F., So-Osman, C., van der Flier, W. M., van der Heijden, A. A. W. A., van der Spek, A., Asselbergs, F. W., Boersma, E., Elders, P. M., Geleijnse, J. M., Ikram, M. A., Kloppenburg, M., Meulenbelt, I, Mooijaart, S. P., Nelissen, R. G. H. H., Netea, M. G., Penninx, B. W. J. H., Stehouwer, C. D. A., Teunissen, C. E., Terwindt, G. M., 't Hart, L. M., van den Maagdenberg, A. M. J. M., van der Harst, P., van der Horst, I. C. C., van der Kallen, C. J. H., van Greevenbroek, M. M. J., van Spil, W. E., Wijmenga, C., Zwinderman, A. H., Zhernikova, A., Jukema, J. W., Wolf, J. J. H. Barkey, Cats, D., Mei, H., Slofstra, M., Swertz, M., van den Akker, E. B., Deelen, J., Reinders, M. J. T., Boomsma, D., I, van Duijn, C. M., Slagboom, P. E., Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), MUMC+: MA Med Staf Artsass Interne Geneeskunde (9), MUMC+: MA Endocrinologie (9), MUMC+: MA Maag Darm Lever (9), MUMC+: MA Hematologie (9), MUMC+: MA Medische Oncologie (9), MUMC+: MA Nefrologie (9), MUMC+: MA Reumatologie (9), RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Molecular Neuroscience and Ageing Research (MOLAR), Cardiovascular Centre (CVC), Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE), Center for Liver, Digestive and Metabolic Diseases (CLDM), Medical Microbiology and Infection Prevention, Graduate School, Tytgat Institute for Liver and Intestinal Research, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Obstetrics and Gynaecology, Cardiology, Public and occupational health, Gastroenterology and Hepatology, Paediatric Endocrinology, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, APH - Methodology, Epidemiology and Data Science, Obstetrics and gynaecology, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, Anatomy and neurosciences, Anesthesiology, General practice, Internal medicine, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Laboratory Medicine, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Neuroinfection & -inflammation, Amsterdam Reproduction & Development (AR&D), AMS - Musculoskeletal Health, AMS - Tissue Function & Regeneration, Rheumatology, Gastroenterology and hepatology, APH - Aging & Later Life, and APH - Digital Health

Subjects
Male, Netherlands Twin Register (NTR), 0301 basic medicine, Shared environment, Metabolite, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Genome-wide association study, heritability, METABOLITES, Keywords: Classical twin design, chemistry.chemical_compound, 0302 clinical medicine, metabolite classes, Twins, Dizygotic, EPIDEMIOLOGY, Classical twin design, Genetics (clinical), Genetics, HERITABILITY, shared environment, Obstetrics and Gynecology, Phenotype, Quartile, Metabolome, Female, Adult, Dizygotic twin, POWER, TWIN, Environment, Biology, enrichment analysis, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, Metabolomics, AGE, Diseases in Twins, Humans, Family, GENOME-WIDE ASSOCIATION, Classical twin design [Keywords], Twins, Monozygotic, PROFILES, Heritability, Diet, Metabolomics data, 030104 developmental biology, chemistry, Pediatrics, Perinatology and Child Health, Gene-Environment Interaction, 030217 neurology & neurosurgery
Abstract

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term ‘metabolomics’ refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

Published
2020

14. Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Author

Plaat, D. van der, Vonk, J.M., Terzikhan, N., Jong, K. de, Vries, M. de, Bastide-van Gemert, S. la, Diemen, C.C. van, Lahousse, L., Brusselle, G., Nedeljkovic, I., Amin, N., Kromhout, H., Vermeulen, R.C.H., Postma, D.S., Duijn, C.M. van, Boezen, H.M., Heijmans, B.T., Hoen, P.A.C.T., Meurs, J. van, Isaacs, A., Jansen, R., Franke, L., Boomsma, D.I., Pool, R., Dongen, J. van, Hottenga, J.J., Greevenbroek, M.M.J. van, Stehouwer, C.D.A., Kallen, C.J.H. van der, Schalkwijk, C.G., Wijmenga, C., Zhernakova, S., Tigchelaar, E.E., Slagboom, P.E., Beekman, M., Deelen, J., Heemst, D. van, Veldink, J.H., Berg, L.H. van den, Hofman, B.A., Uitterlinden, A.G., Jhamai, P.M., Verbiest, M., Suchiman, H.E.D., Verkerk, M., Breggen, R. van der, Rooij, J. van, Lakenberg, N., Mei, H., Iterson, M. van, Galen, M. van, Bot, J., Zhernakova, D.V., Hof, P.V., Deelen, P., Nooren, I., Moed, M., Vermaat, M., Luijk, R., Bonder, M.J., Dijk, F. van, Arindrarto, W., Kielbasa, S.M., Swertz, M.A., Zwet, E.W. van, Hoen, P.B. 't, BIOS Consortium, Groningen Research Institute for Asthma and COPD (GRIAC), Life Course Epidemiology (LCE), Interne Geneeskunde, RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome, RS: CARIM - R3 - Vascular biology, MUMC+: MA Interne Geneeskunde (3), RS: CARIM - R3.01 - Vascular complications of diabetes and the metabolic syndrome, Epidemiology, Pulmonary Medicine, APH - Methodology, APH - Mental Health, Amsterdam Reproduction & Development, Biological Psychology, APH - Personalized Medicine, and APH - Health Behaviors & Chronic Diseases

Subjects
Male, GASES, Rotterdam Study, FEV1, 0302 clinical medicine, Medicine and Health Sciences, Leukocytes, 030212 general & internal medicine, Association Studies Article, Genetics (clinical), 11 Medical and Health Sciences, Aged, 80 and over, Genetics & Heredity, RISK, 0303 health sciences, biology, Dust, General Medicine, Methylation, Middle Aged, Blood, DNA methylation, Female, BIOS Consortium, Life Sciences & Biomedicine, Adult, Biochemistry & Molecular Biology, Adolescent, Mineral dust, Young Adult, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Occupational Exposure, Genetics, GNAS complex locus, Humans, Epigenetics, Molecular Biology, Gene, Aged, 030304 developmental biology, DECLINE, Science & Technology, Sequence Analysis, RNA, Biology and Life Sciences, DNA Methylation, 06 Biological Sciences, respiratory tract diseases, Differentially methylated regions, Gene Expression Regulation, DISCOVERY, Immunology, biology.protein, Genome-Wide Association Study
Abstract

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2×)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted.

Published
2019

15. Skewed X-inactivation is common in the general female population

Author

Shvetsova, E, Sofronova, A, Monajemi, R, Gagalova, K, Draisma, HHM, White, SJ, Santen, GWE, Lopes, SMCDS, Heijmans, BT, Van Meurs, J, Jansen, R, Franke, L, Kielbasa, SM, Den Dunnen, JT, 't Hoen, PAC, Boomsma, DI, Pool, R, Van Dongen, J, Hottenga, JJ, Van Greevenbroek, MMJ, Da Stehouwer, C, Van der Kallen, CJH, Schalkwijk, CG, Wijmenga, C, Zhernakova, S, Tigchelaar, EF, Slagboom, PE, Beekman, M, Deelen, J, Van Heemst, D, Veldink, JH, Van den Berg, LH, Van Duijn, CM, Hofman, BA, Uitterlinden, AG, Jhamai, PM, Verbiest, M, Suchiman, HED, Verkerk, M, Van der Breggen, R, Van Rooij, J, Lakenberg, N, Mei, H, Bot, J, Zhernakova, DV, 't Hof, PV, Deelen, P, Nooren, I, Moed, M, Vermaat, M, Luijk, R, Bonder, MJ, Van Iterson, M, Van Dijk, F, Van Galen, M, Arindrarto, W, Swertz, MA, Van Zwet, EW, Isaacs, A, Francioli, LC, Menelaou, A, Pulit, SL, Palamara, PF, Elbers, CC, Neerincx, PB, Ye, K, Guryev, V, Kloosterman, WP, Abdellaoui, A, Van Leeuwen, EM, Van Oven, M, Li, M, Laros, JF, Karssen, LC, Kanterakis, A, Amin, N, Lameijer, EW, Kattenberg, M, Dijkstra, M, Byelas, H, Van Setten, J, Van Schaik, BD, Nijman, IJ, Renkens, I, Marschall, T, Schonhuth, A, Hehir-Kwa, JY, Handsaker, RE, Polak, P, Sohail, M, Vuzman, D, Hormozdiari, F, Van Enckevort, D, Koval, V, Moed, MH, Van der Velde, KJ, Rivadeneira, F, Estrada, K, Medina-Gomez, C, McCarroll, SA, De Craen, AJ, Suchiman, HE, Oostra, B, Willemsen, G, Platteel, M, Pitts, SJ, Potluri, S, Sundar, P, Cox, DR, Sunyaev, SR, Stoneking, M, De Knijff, P, Kayser, M, Li, Q, Li, Y, Du, Y, Chen, R, Cao, H, Li, N, Cao, S, Wang, J, Bovenberg, JA, Pe'er, I, Van Ommen, GJ, De Bakker, PI, Consortium, Bios, Consortium, Gonl, BIOS consortium, GoNL consortium, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Translational Immunology Groningen (TRIGR), Groningen Research Institute for Asthma and COPD (GRIAC), Stem Cell Aging Leukemia and Lymphoma (SALL), Epidemiology and Data Science, AII - Inflammatory diseases, APH - Methodology, Experimental Immunology, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, APH - Personalized Medicine, Biological Psychology, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome, Interne Geneeskunde, RS: CARIM - R3 - Vascular biology, MUMC+: MA Reumatologie (9), MUMC+: MA Nefrologie (9), MUMC+: MA Medische Oncologie (9), MUMC+: MA Hematologie (9), MUMC+: MA Maag Darm Lever (9), MUMC+: MA Endocrinologie (9), MUMC+: HVC Pieken Maastricht Studie (9), RS: CARIM - R3.01 - Vascular complications of diabetes and the metabolic syndrome, MUMC+: MA Interne Geneeskunde (3), RS: Carim - B01 Blood proteins & engineering, RS: FHML MaCSBio, RS: CARIM - R1 - Thrombosis and haemostasis, RS: CARIM - R1.01 - Blood proteins & engineering, Biochemie, Psychiatry, VU University medical center, Pediatric surgery, Amsterdam Reproduction & Development (AR&D), Internal Medicine, Epidemiology, Genetic Identification, and Clinical Genetics

Subjects
Netherlands Twin Register (NTR), Male, 0301 basic medicine, Receptors, Cytoplasmic and Nuclear/genetics, CHROMOSOME-INACTIVATION, BIOS consortium, Receptors, Cytoplasmic and Nuclear, Septins/genetics, Population genetics, GoNL consortium, Population/genetics, Negative selection, 0302 clinical medicine, X Chromosome Inactivation, Receptors, Non-U.S. Gov't, Genetics (clinical), Netherlands, Genetics & Heredity, Genetics, education.field_of_study, Membrane Glycoproteins, Dosage compensation, DMD LOCUS, Research Support, Non-U.S. Gov't, Receptors, Peptide/genetics, Intracellular Signaling Peptides and Proteins, Peptide/genetics, Single Nucleotide, CARRIERS, TRANSLOCATION, VARIABILITY, Female, Life Sciences & Biomedicine, EXPRESSION, Biochemistry & Molecular Biology, Receptors, Peptide, Population, ADRENOLEUKODYSTROPHY, Biology, Research Support, Polymorphism, Single Nucleotide, Article, X-inactivation, DUCHENNE MUSCULAR-DYSTROPHY, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, Journal Article, Humans, Polymorphism, Allele, education, Skewed X-inactivation, Gene, 0604 Genetics, Calcium-Binding Proteins/genetics, Science & Technology, CONSEQUENCES, Calcium-Binding Proteins, Membrane Glycoproteins/genetics, 030104 developmental biology, Cytoplasmic and Nuclear/genetics, PATTERNS, Intracellular Signaling Peptides and Proteins/genetics, Nanomedicine Radboud Institute for Molecular Life Sciences [Radboudumc 19], Septins, 030217 neurology & neurosurgery
Abstract

X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants.

Published
2019

23. Investigating the relationships between unfavorable sleep and metabolomic traits: Evidence from multi-cohort multivariable regression and mendelian randomization analyses

Author

Bos, M.M., primary, Goulding, N.J., additional, Lee, M., additional, Hofman, A., additional, Bot, M., additional, Pool, R., additional, Vijfhuizen, L., additional, Zhang, X., additional, Li, C., additional, Mustafa, R., additional, Neville, M.J., additional, Li-Gao, R., additional, Trompet, S., additional, Beekman, M., additional, Biermasz, N.R., additional, Boomsma, D.I., additional, De Boer, I., additional, Christodoulides, C., additional, Dehghan, A., additional, Van Dijk, K. Willems, additional, Ford, I., additional, Ghanbari, M., additional, Heijmans, B.T., additional, Ikram, M.A., additional, Jukema, J.W., additional, Mook-Kanamori, D.O., additional, Karpe, F., additional, Luik, A.I., additional, Lumey, L., additional, Van Den Maagdenberg, A.M., additional, Mooijaart, S.P., additional, De Mutsert, R., additional, Penninx, B.W.J.H., additional, Rensen, P.C.N., additional, Richmond, R.C., additional, Rosendaal, F.R., additional, Sattar, N., additional, Schoevers, R., additional, Slagboom, P.E., additional, Terwindt, G.M., additional, Thesing, C.S., additional, Wade, K., additional, Wijsman, C.A., additional, Willemsen, G., additional, Zinderman, A., additional, Verwoert, G.C., additional, Noordam, R., additional, and Lawlor, D.A., additional

Published
2021
Full Text
View/download PDF

24. Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

Author

Bos, Maxime, Goulding, NJ, Lee, MA, Hofman, Bert, Bot, M, Pool, R, Vijfhuizen, LS, Zhang, K, Li, CH, Mustafa, R, Neville, MJ, Li-Gao, R, Trompet, S, Beekman, M, Biermasz, NR, Boomsma, DI, Boer, I, Christodoulides, C, Dehghan, A, van Dijk, KW, Ford, I, Ghanbari, Mohsen, Heijmans, BT, Ikram, Arfan, Jukema, JW, Mook, Dennis, Karpe, F, Luik, Annemarie, Lumey, LH, van den Maagdenberg, A, Mooijaart, SP, de Mutsert, R, Penninx, B, Rensen, PCN, Richmond, Rebecca, Rosendaal, FR, Sattar, N, Schoevers, RA, Slagboom, PE, Terwindt, GM, Thesing, CS, Wade, KH, Wijsman, CA, Willemsen, G, Zwinderman, AH, van Heemst, D, Noordam, R, Lawlor, DA, Bos, Maxime, Goulding, NJ, Lee, MA, Hofman, Bert, Bot, M, Pool, R, Vijfhuizen, LS, Zhang, K, Li, CH, Mustafa, R, Neville, MJ, Li-Gao, R, Trompet, S, Beekman, M, Biermasz, NR, Boomsma, DI, Boer, I, Christodoulides, C, Dehghan, A, van Dijk, KW, Ford, I, Ghanbari, Mohsen, Heijmans, BT, Ikram, Arfan, Jukema, JW, Mook, Dennis, Karpe, F, Luik, Annemarie, Lumey, LH, van den Maagdenberg, A, Mooijaart, SP, de Mutsert, R, Penninx, B, Rensen, PCN, Richmond, Rebecca, Rosendaal, FR, Sattar, N, Schoevers, RA, Slagboom, PE, Terwindt, GM, Thesing, CS, Wade, KH, Wijsman, CA, Willemsen, G, Zwinderman, AH, van Heemst, D, Noordam, R, and Lawlor, DA

Abstract

Background: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. Methods: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. Results: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (− 0.08 standard deviation (SD)[95% confidence interval (CI) − 0.12, − 0.03] in AMV and − 0.03SD [− 0.07, − 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (− 0.04SD [− 0.08, 0.00] in AMV and − 0.05SD [− 0.09, − 0.02] in MR), and lower phospholipids in very large HDL particles (− 0.04SD [− 0.08, 0.002] in AMV and − 0.05SD [− 0.08, − 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures.

Published
2021

26. Correction to: Heritability estimates for 361 blood metabolites across 40 genome-wide association studies (vol 11, 39, 2020)

Author

Hagenbeek, F.A., Pool, R., Dongen, J. van, Draisma, H.M., Hottenga, J.J., Willemsen, G., Abdellaoui, A., Fedko, I.O., Braber, A. den, Visser, P.J., Geus, E.J.C.N. de, Duijn, C.M. van, Harms, A.C., Bartels, M., Nivard, M.G., Boomsma, D.I., Hankemeier, T., Beulens, J.W., Rutters, F., Flier, W.M. van der, Hart, L.M., Bom, J.A. van der, Kloppenburg, M., Harst, P. van der, Bomer, N., Hilten, J.A. van, So-Osman, C., Meessen, J.M.T.A., Fu, J., Wijmenga, C., Zhernikova, A., Slofstra, M., Swertz, M., Onderwater, G.L.J., Terwindt, G.M., Heijden, A.A.W.A. van der, Asselbergs, F.W., Boersma, E., Elders, P.M., Geleijnse, J.M., Ikram, M.A., Mooijaart, S.P., Nelissen, R.G.H.H., Netea, M.G., Penninx, B.W.J.H., Stehouwer, C.D.A., Kallen, C.J.H. van der, Greevenbroek, M.M.J. van, Teunissen, C.E., Maagdenberg, A.M.J.M. van den, Spil, W.E. van, Zwinderman, A.H., Jukema, J.W., Mei, H., Akker, E.B. van den, Deelen, J., Horst I.C.C. van der, Reinders M.J.T., and Abdel Abdellaoui

Abstract

Correction to: Nature Communications https://doi.org/10.1038/s41467-019-13770-6, published online 7 January 2020.The original version of the Supplementary Information associated with this Article included an incorrect Supplementary Data 1 file, in which additional delimiters were included in the first column for a number of rows, resulting in column shifts for some of these rows. The HTML has been updated to include a corrected version of Supplementary Data 1; the original incorrect version of Supplementary Data 1 can be found as Supplementary Information associated with this Correction.

Published
2020

27. A characterization of cis- and trans-heritability of RNA-Seq-based gene expression

Author

Ouwens, K.G., Jansen, R., Nivard, M.G., Dongen, J. van, Frieser, M.J., Hottenga, J.J., Arindrarto, W., Claringbould, A., Iterson, M. van, Mei, H.L., Franke, L., Heijmans, B.T., Hoen, P.A.C. 't, Meurs, J. van, Brooks, A.I., Penninx, B.W.J.H., Boomsma, D.I., Isaacs, A., Pool, R., Greevenbroek, M.M.J. van, Stehouwer, C.D.A., Kallen, C.J.H. van der, Schalkwijk, C.G., Wijmenga, C., Zhernakova, S., Tigchelaar, E.F., Slagboom, P.E., Beekman, M., Deelen, J., Heemst, D. van, Veldink, J.H., Berg, L.H. van den, Duijn, C.M. van, Hofman, B.A., Uitterlinden, A.G., Jhamai, P.M., Verbiest, M., Suchiman, H.E.D., Verkerk, M., Breggen, R. van der, Rooij, J. van, Lakenberg, N., Galen, M. van, Bot, J., Zhernakova, D.V., van't Hof, P., Deelen, P., Nooren, I., Moed, M., Vermaat, M., Luijk, R., Bonder, M.J., Dijk, F. van, Kielbasa, S.M., Swertz, M.A., Zwet, E.W. van, Hoen, P.B. 't, BIOS Consortium, Biological Psychology, APH - Mental Health, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, APH - Methodology, Internal Medicine, Epidemiology, Interne Geneeskunde, RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome, MUMC+: Centrum voor Chronische Zieken (3), MUMC+: MA Med Staf Artsass Interne Geneeskunde (9), MUMC+: HVC Pieken Maastricht Studie (9), MUMC+: MA Interne Geneeskunde (3), Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Digital Health, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Department of Health and Life Sciences, Translational Immunology Groningen (TRIGR), and Stem Cell Aging Leukemia and Lymphoma (SALL)

Subjects
Adult, Male, Netherlands Twin Register (NTR), Adolescent, Genotype, Dizygotic twin, Quantitative Trait Loci, Monozygotic twin, Genome-wide association study, Single-nucleotide polymorphism, Biology, Quantitative trait locus, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Quantitative Trait, Heritable, AGE, SDG 3 - Good Health and Well-being, Twins, Dizygotic, Genetics, Humans, RNA-Seq, Genetics (clinical), Aged, 0303 health sciences, 030305 genetics & heredity, Twins, Monozygotic, Middle Aged, Heritability, Twin study, Expression quantitative trait loci, Female, Gene-Environment Interaction, Nanomedicine Radboud Institute for Molecular Life Sciences [Radboudumc 19], Genome-Wide Association Study
Abstract

Insights into individual differences in gene expression and its heritability (h2) can help in understanding pathways from DNA to phenotype. We estimated the heritability of gene expression of 52,844 genes measured in whole blood in the largest twin RNA-Seq sample to date (1497 individuals including 459 monozygotic twin pairs and 150 dizygotic twin pairs) from classical twin modeling and identity-by-state-based approaches. We estimated for each gene h2total, composed of cis-heritability (h2cis, the variance explained by single nucleotide polymorphisms in the cis-window of the gene), and trans-heritability (h2res, the residual variance explained by all other genome-wide variants). Mean h2total was 0.26, which was significantly higher than heritability estimates earlier found in a microarray-based study using largely overlapping (>60%) RNA samples (mean h2 = 0.14, p = 6.15 × 10−258). Mean h2cis was 0.06 and strongly correlated with beta of the top cis expression quantitative loci (eQTL, ρ = 0.76, p −308) and with estimates from earlier RNA-Seq-based studies. Mean h2res was 0.20 and correlated with the beta of the corresponding trans-eQTL (ρ = 0.04, p −3) and was significantly higher for genes involved in cytokine-cytokine interactions (p = 4.22 × 10−15), many other immune system pathways, and genes identified in genome-wide association studies for various traits including behavioral disorders and cancer. This study provides a thorough characterization of cis- and trans-h2 estimates of gene expression, which is of value for interpretation of GWAS and gene expression studies.

Published
2020

28. Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Author

Hagenbeek, F.A., Pool, R., Dongen, J. van, Draisma, H.H.M., Hottenga, J.J., Willemsen, G., Abdellaoui, A., Fedko, I.O., Braber, A. den, Visser, P.J., Geus, E.J.C.N. de, Dijk, K.W. van, Verhoeven, A., Suchiman, H.E., Beekman, M., Slagboom, P.E., Duijn, C.M. van, Harms, A.C., Hankemeier, T., Bartels, M., Nivard, M.G., Boomsma, D.I., Wolf, J.J.H.B., Cats, D., Amin, N., Beulens, J.W., Bom, J.A. van der, Bomer, N., Demirkan, A., Hilten, J.A. van, Meessen, J.M.T.A., Moed, M.H., Fu, J., Onderwater, G.L.J., Rutters, F., So-Osman, C., Flier, W.M. van der, Heijden, A.A.W.A. van der, Spek, A. van der, Asselbergs, F.W., Boersma, E., Elders, P.M., Geleijnse, J.M., Ikram, M.A., Kloppenburg, M., Meulenbelt, I., Mooijaart, S.P., Nelissen, R.G.H.H., Netea, M.G., Penninx, B.W.J.H., Stehouwer, C.D.A., Teunissen, C.E., Terwindt, G.M., Hart, L.M. 't, Maagdenberg, A.M.J.M. van den, Harst, P. van der, Horst, I.C.C. van der, Kallen, C.J.H. van der, Greevenbroek, M.M.J. van, Spil, W.E. van, Wijmenga, C., Zwinderman, A.H., Zhernikova, A., Jukema, J.W., Mei, H., Slofstra, M., Swertz, M., Akker, E.B. van den, Deelen, J., Reinders, M.J.T., BBMRI Metabolomics Consortium, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE), Cardiovascular Centre (CVC), Center for Liver, Digestive and Metabolic Diseases (CLDM), Neurology, Epidemiology and Data Science, ACS - Heart failure & arrhythmias, APH - Health Behaviors & Chronic Diseases, General practice, APH - Methodology, Amsterdam Reproduction & Development (AR&D), APH - Mental Health, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, Laboratory Medicine, Other Research, APH - Aging & Later Life, APH - Personalized Medicine, APH - Digital Health, ACS - Diabetes & metabolism, Adult Psychiatry, Epidemiology, Cardiology, Radiology & Nuclear Medicine, Biological Psychology, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, MUMC+: HVC Pieken Maastricht Studie (9), MUMC+: MA Interne Geneeskunde (3), Interne Geneeskunde, MUMC+: Centrum voor Chronische Zieken (3), MUMC+: MA Med Staf Artsass Interne Geneeskunde (9), MUMC+: MA Endocrinologie (9), MUMC+: MA Maag Darm Lever (9), MUMC+: MA Hematologie (9), MUMC+: MA Medische Oncologie (9), MUMC+: MA Nefrologie (9), MUMC+: MA Reumatologie (9), and RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome

Subjects
Netherlands Twin Register (NTR), 0301 basic medicine, SELECTION, Quantitative trait loci, Nutrition and Disease, DATABASE, Metabolite, Science, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], General Physics and Astronomy, Genome-wide association study, VARIANCE-ESTIMATION, Biology, Quantitative trait locus, GENOTYPE IMPUTATION, METABOLOMICS, BIOBANK, Genome-wide association studies, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Metabolomics, All institutes and research themes of the Radboud University Medical Center, Missing heritability problem, MISSING HERITABILITY, Voeding en Ziekte, Genetic variation, Life Science, NETHERLANDS TWIN REGISTER, lcsh:Science, VLAG, Genetics, Multidisciplinary, General Chemistry, Heritability, Genetic architecture, 030104 developmental biology, chemistry, Lipidomics, lcsh:Q, 030217 neurology & neurosurgery
Abstract

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes., Blood metabolite levels are under the influence of environmental and genetic factors. Here, Hagenbeek et al. perform heritability estimations for metabolite measures and determine the contribution of known metabolite loci to metabolite levels using data from 40 genome-wide association studies.

Published
2020

29. Laundering the Profits of Ransomware: Money Laundering Methods for Vouchers and Cryptocurrencies

Author

Custers, B.H.M., Oerlemans, J.J., Pool, R., Sub Strafrecht Overig, Montaigne Centrum voor Rechtspleging en conflictoplossing, Sub Strafrecht Overig, and Montaigne Centrum voor Rechtspleging en conflictoplossing

Subjects
Cryptocurrency, money laundering, Sociology and Political Science, media_common.quotation_subject, computer.software_genre, Computer security, Payment, Money laundering, cryptoware, Cybercrime, Ransom, ransomware, bitcoins, Political Science and International Relations, cybercrime, Ransomware, Malware, money mules, Business, Law, computer, Anonymity, media_common
Abstract

Ransomware is malicious software (malware) that blocks access to someone’s computer system or files on the system and subsequently demands a ransom to be paid for unlocking the computer or files. Ransomware is considered one of the main threats in cybercrime today. Cryptoware is a specific type of ransomware, which encrypts files on computer systems. The ransom is often demanded in bitcoins. Based on desk research, a series of interviews, and the investigation of several police files, this paper investigates the modi operandi in which cybercriminals use ransomware and cryptoware to make profits and how they launder these profits. Two models, based on the payment of the ransom via vouchers and via bitcoins respectively, are identified and described. These methods allow criminals to launder profits in relative anonymity and prevent the seizure of the illegally obtained money.

Published
2020

30. Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Author

Pool, R, Hagenbeek, F.A., Hendriks, A.-M. (Anna-Marie), Dongen, J, Willemsen, G.A.H.M. (Gonneke), Geus, E.D. (Eveline) de, Pool, R, Hagenbeek, F.A., Hendriks, A.-M. (Anna-Marie), Dongen, J, Willemsen, G.A.H.M. (Gonneke), and Geus, E.D. (Eveline) de

Abstract

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term ‘metabolomics’ refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes.

Published
2020
Full Text
View/download PDF

31. Author Correction: Heritability estimates for 361 blood metabolites across 40 genome-wide association studies (Nature Communications, (2020), 11, 1, (39), 10.1038/s41467-019-13770-6)

Author

Hagenbeek, F.A. (Fiona A.), Pool, R. (Reńe), Dongen, J. (Jenny) van, Draisma, G. (Gerrit), Hottenga, J.J. (Jouke Jan), Willemsen, G. (Gonneke), Abdellaoui, A. (Abdel), Fedko, I.O. (Iryna O.), Braber, A. (Anouk) den, Visser, P. (Pim), Geus, E.J.C. (Eco) de, Willems van Dijk, K. (Ko), Verhoeven, A. (Aswin), Suchiman, H.E. (H. Eka), Beekman, M. (Marian), Slagboom, P.E. (Eline), Duijn, C.M. (Cornelia) van, Barkey Wolf, J.J.H. (J. J.H.), Cats, D. (D.), Amin, N. (N.), Beulens, J.W.J. (Joline), van der Bom, J.A. (J. A.), Bomer, N. (Nils), Demirkan, A. (Ayşe), van Hilten, J.A. (J. A.), Meessen, J.M.T.A. (J. M.T.A.), Moed, H. (Heleen), Fu, J. (J.), Onderwater, G.L.J. (G. L.J.), Rutters, F. (F.), So-Osman, C. (Cynthia), van der Flier, W.M. (W. M.), Heijden, A.A.W.A. (Amber A. W.) van der, Spek, A. (Ashley) van der, Asselbergs, F.W. (F. W.), Boersma, H. (Eric), Elders, P.M. (P. M.), Geleijnse, J.M. (J. M.), Ikram, M.A. (Arfan), Kloppenburg, M. (Margreet), Meulenbelt, I. (I.), Mooijaart, S.P. (Simon), Nelissen, R.G.H.H. (Rob), Netea, M.G. (Mihai), Penninx, B.W.J.H. (Brenda), Stehouwer, C.D.A. (C. D.A.), Teunissen, C.E. (Charlotte), Terwindt, G.M. (G. M.), ‘t Hart, L.M. (L. M.), van den Maagdenberg, A.M.J.M. (A. M.J.M.), Harst, P. (Pim) van der, van der Horst, I.C.C. (I. C.C.), Kallen, C.J. van der, van Greevenbroek, M.M.J. (M. M.J.), Spil, W.E. (Willem) van, Wijmenga, C. (Cisca), Zwinderman, A.H. (Ailko), Zhernikova, A. (A.), Jukema, J.W. (Jan Wouter), Mei, H. (H.), Slofstra, M. (M.), Swertz, M. (M.), Akker, E.B. (Erik) van den, Deelen, J. (Joris), Reinders, M.J.T. (M. J.T.), Harms, A.C. (Amy), Hankemeier, T. (Thomas), Bartels, M. (Meike), Nivard, M. (Michel), Boomsma, D.I. (Dorret), Hagenbeek, F.A. (Fiona A.), Pool, R. (Reńe), Dongen, J. (Jenny) van, Draisma, G. (Gerrit), Hottenga, J.J. (Jouke Jan), Willemsen, G. (Gonneke), Abdellaoui, A. (Abdel), Fedko, I.O. (Iryna O.), Braber, A. (Anouk) den, Visser, P. (Pim), Geus, E.J.C. (Eco) de, Willems van Dijk, K. (Ko), Verhoeven, A. (Aswin), Suchiman, H.E. (H. Eka), Beekman, M. (Marian), Slagboom, P.E. (Eline), Duijn, C.M. (Cornelia) van, Barkey Wolf, J.J.H. (J. J.H.), Cats, D. (D.), Amin, N. (N.), Beulens, J.W.J. (Joline), van der Bom, J.A. (J. A.), Bomer, N. (Nils), Demirkan, A. (Ayşe), van Hilten, J.A. (J. A.), Meessen, J.M.T.A. (J. M.T.A.), Moed, H. (Heleen), Fu, J. (J.), Onderwater, G.L.J. (G. L.J.), Rutters, F. (F.), So-Osman, C. (Cynthia), van der Flier, W.M. (W. M.), Heijden, A.A.W.A. (Amber A. W.) van der, Spek, A. (Ashley) van der, Asselbergs, F.W. (F. W.), Boersma, H. (Eric), Elders, P.M. (P. M.), Geleijnse, J.M. (J. M.), Ikram, M.A. (Arfan), Kloppenburg, M. (Margreet), Meulenbelt, I. (I.), Mooijaart, S.P. (Simon), Nelissen, R.G.H.H. (Rob), Netea, M.G. (Mihai), Penninx, B.W.J.H. (Brenda), Stehouwer, C.D.A. (C. D.A.), Teunissen, C.E. (Charlotte), Terwindt, G.M. (G. M.), ‘t Hart, L.M. (L. M.), van den Maagdenberg, A.M.J.M. (A. M.J.M.), Harst, P. (Pim) van der, van der Horst, I.C.C. (I. C.C.), Kallen, C.J. van der, van Greevenbroek, M.M.J. (M. M.J.), Spil, W.E. (Willem) van, Wijmenga, C. (Cisca), Zwinderman, A.H. (Ailko), Zhernikova, A. (A.), Jukema, J.W. (Jan Wouter), Mei, H. (H.), Slofstra, M. (M.), Swertz, M. (M.), Akker, E.B. (Erik) van den, Deelen, J. (Joris), Reinders, M.J.T. (M. J.T.), Harms, A.C. (Amy), Hankemeier, T. (Thomas), Bartels, M. (Meike), Nivard, M. (Michel), and Boomsma, D.I. (Dorret)

Abstract

The original version of the Supplementary Information associated with this Article included an incorrect Supplementary Data 1 file, in which additional delimiters were included in the first column for a number of rows, resulting in column shifts for some of these rows. The HTML has been updated to include a corrected version of Supplementary Data 1; the original incorrect version of Supplementary Data 1 can be found as Supplementary Information associated with this Correction. In addition, the original version of this Article contained an error in the author affiliations. An affiliation of Abdel Abdellaoui with Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands was inadvertently omitted. This has now been corrected in both the PDF and HTML versions of the Article.

Published
2020
Full Text
View/download PDF

32. Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Author

Hagenbeek, F.A. (Fiona A.), Pool, R. (Reńe), Dongen, J. (Jenny) van, Draisma, G. (Gerrit), Hottenga, J.J. (Jouke Jan), Willemsen, G. (Gonneke), Abdellaoui, A. (Abdel), Fedko, I.O. (Iryna O.), Braber, A. (Anouk) den, Visser, P.J. (Pieter Jelle), de Geus, E.J.C.N. (Eco J. C. N.), Willems van Dijk, K. (Ko), Verhoeven, A. (Aswin), Suchiman, H.E. (H. Eka), Beekman, M. (Marian), Slagboom, P.E. (Eline), Duijn, C.M. (Cornelia) van, Barkey Wolf, J.J.H. (J. J.H.), Cats, D. (D.), Amin, N. (N.), Beulens, J.W.J. (Joline), van der Bom, J.A. (J. A.), Bomer, N. (Nils), Demirkan, A. (Ayşe), van Hilten, J.A. (J. A.), Meessen, J.M.T.A. (J. M.T.A.), Moed, H. (Heleen), Fu, J. (J.), Onderwater, G.L.J. (G. L.J.), Rutters, F. (F.), So-Osman, C. (Cynthia), Flier, W.M. (Wiesje) van der, Heijden, A.A.W.A. (Amber A. W.) van der, Spek, A. (Ashley) van der, Asselbergs, F.W. (F. W.), Boersma, H. (Eric), Elders, P.M. (P. M.), Geleijnse, J.M. (Marianne), Ikram, M.A. (Arfan), Kloppenburg, M. (Margreet), Meulenbelt, I. (I.), Mooijaart, S.P. (Simon), Nelissen, R.G.H.H. (Rob), Netea, M.G. (Mihai), Penninx, B.W.J.H. (Brenda), Stehouwer, C.D. (Coen), Teunissen, C.E. (Charlotte), Terwindt, G.M. (Gisela), ‘t Hart, L.M. (L. M.), Maagdenberg, A.M.J.M. (Arn), Harst, P. (Pim) van der, van der Horst, I.C.C. (I. C.C.), Kallen, C.J. van der, van Greevenbroek, M.M.J. (M. M.J.), Spil, W.E. (Willem) van, Wijmenga, C. (C.), Zwinderman, A.H. (A. H.), Zhernikova, A. (A.), Jukema, J.W. (Jan Wouter), Mei, H. (H.), Slofstra, M. (M.), Swertz, M. (M.), Akker, E.B. (Erik) van den, Deelen, J. (Joris), Reinders, M.J.T. (M. J.T.), Harms, A.C. (Amy C.), Hankemeier, T. (Thomas), Bartels, M. (Meike), Nivard, M. (Michel), Boomsma, D.I. (Dorret), Hagenbeek, F.A. (Fiona A.), Pool, R. (Reńe), Dongen, J. (Jenny) van, Draisma, G. (Gerrit), Hottenga, J.J. (Jouke Jan), Willemsen, G. (Gonneke), Abdellaoui, A. (Abdel), Fedko, I.O. (Iryna O.), Braber, A. (Anouk) den, Visser, P.J. (Pieter Jelle), de Geus, E.J.C.N. (Eco J. C. N.), Willems van Dijk, K. (Ko), Verhoeven, A. (Aswin), Suchiman, H.E. (H. Eka), Beekman, M. (Marian), Slagboom, P.E. (Eline), Duijn, C.M. (Cornelia) van, Barkey Wolf, J.J.H. (J. J.H.), Cats, D. (D.), Amin, N. (N.), Beulens, J.W.J. (Joline), van der Bom, J.A. (J. A.), Bomer, N. (Nils), Demirkan, A. (Ayşe), van Hilten, J.A. (J. A.), Meessen, J.M.T.A. (J. M.T.A.), Moed, H. (Heleen), Fu, J. (J.), Onderwater, G.L.J. (G. L.J.), Rutters, F. (F.), So-Osman, C. (Cynthia), Flier, W.M. (Wiesje) van der, Heijden, A.A.W.A. (Amber A. W.) van der, Spek, A. (Ashley) van der, Asselbergs, F.W. (F. W.), Boersma, H. (Eric), Elders, P.M. (P. M.), Geleijnse, J.M. (Marianne), Ikram, M.A. (Arfan), Kloppenburg, M. (Margreet), Meulenbelt, I. (I.), Mooijaart, S.P. (Simon), Nelissen, R.G.H.H. (Rob), Netea, M.G. (Mihai), Penninx, B.W.J.H. (Brenda), Stehouwer, C.D. (Coen), Teunissen, C.E. (Charlotte), Terwindt, G.M. (Gisela), ‘t Hart, L.M. (L. M.), Maagdenberg, A.M.J.M. (Arn), Harst, P. (Pim) van der, van der Horst, I.C.C. (I. C.C.), Kallen, C.J. van der, van Greevenbroek, M.M.J. (M. M.J.), Spil, W.E. (Willem) van, Wijmenga, C. (C.), Zwinderman, A.H. (A. H.), Zhernikova, A. (A.), Jukema, J.W. (Jan Wouter), Mei, H. (H.), Slofstra, M. (M.), Swertz, M. (M.), Akker, E.B. (Erik) van den, Deelen, J. (Joris), Reinders, M.J.T. (M. J.T.), Harms, A.C. (Amy C.), Hankemeier, T. (Thomas), Bartels, M. (Meike), Nivard, M. (Michel), and Boomsma, D.I. (Dorret)

Abstract

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and 5

Published
2020
Full Text
View/download PDF

34. Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug-metabolite atlas

Author

Liu, J., Liu, J., Lahousse, L., Nivard, M.G., Bot, M., Chen, L.M., van Klinken, J.B., Thesing, C.S., Beekman, M., van den Akker, E.B., Slieker, R.C., Waterham, E., van der Kallen, C.J.H., de Boer, I., Li-Gao, R.F., Vojinovic, D., Amin, N., Radjabzadeh, D., Kraaij, R., Alferink, L.J.M., Murad, S.D., Uitterlinden, A.G., Willemsen, G., Pool, R., Milaneschi, Y., van Heemst, D., Suchiman, H.E.D., Rutters, F., Elders, P.J.M., Beulens, J.W.J., van der Heijden, A.A.W.A., van Greevenbroek, M.M.J., Arts, I.C.W., Onderwater, G.L.J., van den Maagdenberg, A.M.J.M., Mook-Kanamori, D.O., Hankemeier, T., Terwindt, G.M., Stehouwer, C.D.A., Geleijnse, J.M., 't Hart, L.M., Slagboom, P.E., van Dijk, K.W., Zhernakova, A., Fu, J.Y., Penninx, B.W.J.H., Boomsma, D.I., Demirkan, A., Stricker, B.H.C., van Duijn, C.M., Liu, J., Liu, J., Lahousse, L., Nivard, M.G., Bot, M., Chen, L.M., van Klinken, J.B., Thesing, C.S., Beekman, M., van den Akker, E.B., Slieker, R.C., Waterham, E., van der Kallen, C.J.H., de Boer, I., Li-Gao, R.F., Vojinovic, D., Amin, N., Radjabzadeh, D., Kraaij, R., Alferink, L.J.M., Murad, S.D., Uitterlinden, A.G., Willemsen, G., Pool, R., Milaneschi, Y., van Heemst, D., Suchiman, H.E.D., Rutters, F., Elders, P.J.M., Beulens, J.W.J., van der Heijden, A.A.W.A., van Greevenbroek, M.M.J., Arts, I.C.W., Onderwater, G.L.J., van den Maagdenberg, A.M.J.M., Mook-Kanamori, D.O., Hankemeier, T., Terwindt, G.M., Stehouwer, C.D.A., Geleijnse, J.M., 't Hart, L.M., Slagboom, P.E., van Dijk, K.W., Zhernakova, A., Fu, J.Y., Penninx, B.W.J.H., Boomsma, D.I., Demirkan, A., Stricker, B.H.C., and van Duijn, C.M.

Abstract

Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug-metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug-metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).

Published
2020

35. Recent increase of ulcerative lesions caused by Anisakis spp. in cetaceans from the north-east Atlantic

Author

Pons-Bordas, Claudia, Hazenberg, Amber, Hernandez-Gonzalez, A., Pool, R., Covelo, Pablo, Sánchez-Hermosin, Pablo, López, A., Saavedra, Camilo, Fraija-Fernández, Natalia, Fernández, M., Aznar, F.J., Pons-Bordas, Claudia, Hazenberg, Amber, Hernandez-Gonzalez, A., Pool, R., Covelo, Pablo, Sánchez-Hermosin, Pablo, López, A., Saavedra, Camilo, Fraija-Fernández, Natalia, Fernández, M., and Aznar, F.J.

Abstract

Species of Anisakis typically infect the stomach of cetaceans worldwide, often causing ulcerative lesions that may compromise the host's health. These nematodes also cause anisakiasis or allergic reactions in humans. To assess the risks of this emerging zoonosis, data on long-term changes in Anisakis infections in cetaceans are necessary. Here, we compare the prevalence and severity of ulcerative lesions caused by Anisakis spp. in five cetacean species stranded along the north-west Spanish coast in 2017-2018 with published data from 1991-1996. Open ulcers were found in 32/43 short-beaked common dolphins, Delphinus delphis; 3/5 striped dolphins, Stenella coeruleoalba; 1/7 bottlenose dolphins, Tursiops truncatus; and 1/3 harbour porpoises, Phocoena phocoena meridionalis; a single individual of long-finned pilot whale, Globicephala melas, was found uninfected. In common dolphins, the mean abundance of open ulcers per host was 1.1 (95% confidence interval: 0.8-1.3), with a maximum diameter (mean ± standard deviation) of 25.4 ± 16.9 mm. Stomachs with scars or extensive fibrosis putatively associated with Anisakis were detected in 14 and five animals, respectively. A molecular analysis based on the mitochondrial cytochrome c oxidase II gene using 18 worms from three cetacean species revealed single or mixed infections of Anisakis simplex sensu stricto and Anisakis pegreffii. Compared with the period 1991-1996, we found a strong increase of prevalence, abundance and extension of ulcerative lesions in most cetacean species. Anisakis populations could have increased in the study area over the last decades, although we cannot rule out that a higher environmental stress has also boosted the pathological effects of these parasites.

Published
2020

36. Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Author

Hagenbeek, FA, Pool, R, Dongen, J, Draisma, HHM, Hottenga, JJ, Willemsen, G, Duijn, Cornelia, Amin, Najaf, Demirkan, Ayse, van der Spek, Ashley, Boersma, Eric, Ikram, Arfan, Deelen, J, Reinders, MJ, Hagenbeek, FA, Pool, R, Dongen, J, Draisma, HHM, Hottenga, JJ, Willemsen, G, Duijn, Cornelia, Amin, Najaf, Demirkan, Ayse, van der Spek, Ashley, Boersma, Eric, Ikram, Arfan, Deelen, J, and Reinders, MJ

Published
2020

45. Metabolomics Profile in Depression: A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls

Author

Bot, Mariska, primary, Milaneschi, Yuri, additional, Al-Shehri, Tahani, additional, Amin, Najaf, additional, Garmaeva, Sanzhima, additional, Onderwater, Gerrit L.J., additional, Pool, Rene, additional, Thesing, Carisha S., additional, Vijfhuizen, Lisanne S., additional, Vogelzangs, Nicole, additional, Arts, Ilja C.W., additional, Demirkan, Ayse, additional, van Duijn, Cornelia, additional, van Greevenbroek, Marleen, additional, van der Kallen, Carla J.H., additional, Köhler, Sebastian, additional, Ligthart, Lannie, additional, van den Maagdenberg, Arn M.J.M., additional, Mook-Kanamori, Dennis O., additional, de Mutsert, Renée, additional, Tiemeier, Henning, additional, Schram, Miranda T., additional, Stehouwer, Coen D.A., additional, Terwindt, Gisela M., additional, Willems van Dijk, Ko, additional, Fu, Jingyuan, additional, Zhernakova, Alexandra, additional, Beekman, Marian, additional, Slagboom, P. Eline, additional, Boomsma, Dorret I., additional, Penninx, Brenda W.J.H., additional, Beekman, M., additional, Suchiman, H.E.D., additional, Deelen, J., additional, Amin, N., additional, Beulens, J.W., additional, van der Bom, J.A., additional, Bomer, N., additional, Demirkan, A., additional, van Hilten, J.A., additional, Meessen, J.M.T.A., additional, Pool, R., additional, Moed, M.H., additional, Fu, J., additional, Onderwater, G.L.J., additional, Rutters, F., additional, So-Osman, C., additional, van der Flier, W.M., additional, van der Heijden, A.A.W.A., additional, van der Spek, A., additional, Asselbergs, F.W., additional, Boersma, E., additional, Elders, P.M., additional, Geleijnse, J.M., additional, Ikram, M.A., additional, Kloppenburg, M., additional, Meulenbelt, I., additional, Mooijaart, S.P., additional, Nelissen, R.G.H.H., additional, Netea, M.G., additional, Penninx, B.W.J.H., additional, Stehouwer, C.D.A., additional, Teunissen, C.E., additional, Terwindt, G.M., additional, ’t Hart, L.M., additional, van den Maagdenberg, A.M.J.M., additional, van der Harst, P., additional, van der Horst, I.C.C., additional, van der Kallen, C.J.H., additional, van Greevenbroek, M.M.J., additional, van Spil, W.E., additional, Wijmenga, C., additional, Zwinderman, A.H., additional, Zhernikova, A., additional, Jukema, J.W., additional, and Sattar, N., additional

Published
2020
Full Text
View/download PDF

48. Circulating metabolites and general cognitive ability and dementia: Evidence from 11 cohort studies (vol 14, pg 707, 2018)

Author

Lee, S.J. van der, Teunissen, C.E., Pool, R., Shipley, M.J., Teumer, A., Chouraki, V., Lent, D.M. van, Tynkkynen, J., Fischer, K., Hernesniemi, J., Haller, T., Singh-Manoux, A., Verhoeven, A., Willemsen, G., Leeuw, F.A. de, Wagner, H., Dongen, J. van, Hertel, J., Budde, K., Dijk, K.W. van, Weinhold, L., Ikram, M.A., Pietzner, M., Perola, M., Wagner, M., Friedrich, N., Slagboom, P.E., Scheltens, P., Yang, Q., Gertzen, R.E., Egert, S., Li, S., Hankemeier, T., Beijsterveldt, C.E.M. van, Vasan, R.S., Maier, W., Peeters, C.F.W., Grabe, H.J., Ramirez, A., Seshadri, S., Metspalu, A., Kivimaki, M., Salomaa, V., Demirkan, A., Boomsma, D.I., Flier, W.M. van der, Amin, N., and Duijn, C.M. van

Published
2019

49. Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Author

Porcu, E. (Eleonora), Rueger, S. (Sina), Lepik, K. (Kaido), Agbessi, M. (Mawusse), Ahsan, H. (Habibul), Alves, I. (Isabel), Andiappan, A. (Anand), Arindrarto, W. (Wibowo), Awadalla, P. (Philip), Battle, A. (Alexis), Beutner, F. (Frank), Bonder, M. J. (Marc Jan), Boomsma, D. (Dorret), Christiansen, M. (Mark), Claringbould, A. (Annique), Deelen, P. (Patrick), Esko, T. (Tonu), Fave, M.-J. (Marie-Julie), Franke, L. (Lude), Frayling, T. (Timothy), Gharib, S. A. (Sina A.), Gibson, G. (Gregory), Heijmans, B. T. (Bastiaan T.), Hemani, G. (Gibran), Jansen, R. (Rick), Kahonen, M. (Mika), Kalnapenkis, A. (Anette), Kasela, S. (Silva), Kettunen, J. (Johannes), Kim, Y. (Yungil), Kirsten, H. (Holger), Kovacs, P. (Peter), Krohn, K. (Knut), Kronberg-Guzman, J. (Jaanika), Kukushkina, V. (Viktorija), Lee, B. (Bernett), Lehtimaki, T. (Terho), Loeffler, M. (Markus), Marigorta, U. M. (Urko M.), Mei, H. (Hailang), Milani, L. (Lili), Montgomery, G. W. (Grant W.), Mueler-Nurasyid, M. (Martina), Nauck, M. (Matthias), Nivard, M. (Michel), Penninx, B. (Brenda), Perola, M. (Markus), Pervjakova, N. (Natalia), Pierce, B. L. (Brandon L.), Powell, J. (Joseph), Prokisch, H. (Holger), Psaty, B. M. (Bruce M.), Raitakari, O. T. (Olli T.), Ripatti, S. (Samuli), Rotzschke, O. (Olaf), Saha, A. (Ashis), Scholz, M. (Markus), Schramm, K. (Katharina), Seppala, I. (Ilkka), Slagboom, E. P. (Eline P.), Stehouwer, C. D. (Coen D. A.), Stumvoll, M. (Michael), Sullivan, P. (Patrick), Teumer, A. (Alexander), Thiery, J. (Joachim), Tong, L. (Lin), Tonjes, A. (Anke), van Dongen, J. (Jenny), van Iterson, M. (Maarten), van Meurs, J. (Joyce), Veldink, J. H. (Jan H.), Verlouw, J. (Joost), Visscher, P. M. (Peter M.), Volker, U. (Uwe), Vosa, U. (Urmo), Westra, H.-J. (Harm-Jan), Wijmenga, C. (Cisca), Yaghootkar, H. (Hanieh), Yang, J. (Jian), Zeng, B. (Biao), Zhang, F. (Futao), Beekman, M. (Marian), Boomsma, D. I. (Dorret I.), Bot, J. (Jan), Deelen, J. (Joris), Hofman, B. A. (Bert A.), Hottenga, J. J. (Jouke J.), Isaacs, A. (Aaron), Jhamai, P. M. (P. Mila), Kielbasa, S. M. (Szymon M.), Lakenberg, N. (Nico), Luijk, R. (Rene), Mei, H. (Hailiang), Moed, M. (Matthijs), Nooren, I. (Irene), Pool, R. (Rene), Schalkwijk, C. G. (Casper G.), Slagboom, P. E. (P. Eline), Suchiman, H. E. (H. Eka D.), Swertz, M. A. (Morris A.), Tigchelaar, E. F. (Ettje F.), Uitterlinden, A. G. (Andre G.), van den Berg, L. H. (Leonard H.), van der Breggen, R. (Ruud), van der Kallen, C. J. (Carla J. H.), van Dijk, F. (Freerk), van Duijn, C. M. (Cornelia M.), van Galen, M. (Michiel), van Greevenbroek, M. M. (Marleen M. J.), van Heemst, D. (Diana), van Rooij, J. (Jeroen), Van't Hof, P. (Peter), van Zwet, E. W. (Erik. W.), Vermaat, M. (Martijn), Verbiest, M. (Michael), Verkerk, M. (Marijn), Zhernakova, D. V. (Dasha V.), Zhernakova, S. (Sasha), Santoni, F. A. (Federico A.), Reymond, A. (Alexandre), and Kutalik, Z. (Zoltan)

Abstract

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.

Published
2019

50. A linear mixed-model approach to study multivariate gene–environment interactions

Author

't Hoen, P.A., van Meurs, Joyce B J, Isaacs, Aaron, Jansen, Rick, Franke, Lude, Boomsma, D.I., Pool, R., van Dongen, J., Hottenga, J.J., Van Greevenbroek, Marleen J., Stehouwer, Coen D A, van der Kallen, Carla J H, Schalkwijk, Casper G, Wijmenga, Cisca, Zhernakova, Alexandra, Tigchelaar, Ettje F, Slagboom, P. Eline, Beekman, Marian, Deelen, Joris, van Heemst, Diana, Veldink, Jan H, van den Berg, Leonard H, van Duijn, Cornelia M, Hofman, Bert A., Uitterlinden, Andre G, Jhamai, P Mila, Verbiest, Michael, Suchiman, H. Eka D., Verkerk, Marijn, van der Breggen, Ruud, van Rooij, Jeroen, Lakenberg, Nico, Mei, Hailiang, van Iterson, Maarten, van Galen, Michiel, Bot, Jan, van’t Hof, Peter, Deelen, Patrick, Nooren, Irene, Moed, Matthijs, Vermaat, Martijn, Zhernakova, Dasha V., Luijk, René, Jan Bonder, Marc, van Dijk, Freerk, Arindrarto, Wibowo, Kielbasa, P. Szymon M., Swertz, Morris a., van Zwet, Erik W, APH - Methodology, APH - Mental Health, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Internal Medicine, Epidemiology, Psychiatry, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), and Stem Cell Aging Leukemia and Lymphoma (SALL)

Subjects
Mixed model, Netherlands Twin Register (NTR), Multivariate statistics, Genotype, Computer science, Quantitative Trait Loci, LOCI, Physical activity, Computational biology, VARIANTS, Environment, Biology, computer.software_genre, Article, Environmental data, BMI, 03 medical and health sciences, 0302 clinical medicine, MULTIPLE, Genetics, Humans, Computer Simulation, GENOME-WIDE ASSOCIATION, Gene–environment interaction, 030304 developmental biology, 0303 health sciences, Models, Genetic, fungi, Linear model, BODY-MASS INDEX, OBESITY, TESTS, Expression quantitative trait loci, Linear Models, Gene-Environment Interaction, Data mining, SET, computer, TRAITS, Algorithms, 030217 neurology & neurosurgery
Abstract

Different environmental factors, including diet, physical activity, or external conditions can contribute to genotype-environment interactions (GxE). Although high-dimensional environmental data are increasingly available, and multiple environments have been implicated with GxE at the same loci, multi-environment tests for GxE are not established. Such joint analyses can increase power to detect GxE and improve the interpretation of these effects. Here, we propose the structured linear mixed model (StructLMM), a computationally efficient method to test for and characterize loci that interact with multiple environments. After validating our model using simulations, we apply StructLMM to body mass index in UK Biobank, where our method detects previously known and novel GxE signals. Finally, in an application to a large blood eQTL dataset, we demonstrate that StructLMM can be used to study interactions with hundreds of environmental variables.

Published
2019

Catalog

Books, media, physical & digital resources
See catalog results