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1. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53949).

Author

Davies, G, Armstrong, N, Bis, JC, Bressler, J, Chouraki, V, Giddaluru, S, Hofer, E, Ibrahim-Verbaas, CA, Kirin, M, Lahti, J, van der Lee, SJ, Le Hellard, S, Liu, T, Marioni, RE, Oldmeadow, C, Postmus, I, Smith, AV, Smith, JA, Thalamuthu, A, Thomson, R, Vitart, V, Wang, J, Yu, L, Zgaga, L, Zhao, W, Boxall, R, Harris, SE, Hill, WD, Liewald, DC, Luciano, M, Adams, H, Ames, D, Amin, N, Amouyel, P, Assareh, AA, Au, R, Becker, JT, Beiser, A, Berr, C, Bertram, L, Boerwinkle, E, Buckley, BM, Campbell, H, Corley, J, De Jager, PL, Dufouil, C, Eriksson, JG, Espeseth, T, Faul, JD, Ford, I, Generation Scotland, Gottesman, RF, Griswold, ME, Gudnason, V, Harris, TB, Heiss, G, Hofman, A, Holliday, EG, Huffman, J, Kardia, SLR, Kochan, N, Knopman, DS, Kwok, JB, Lambert, J-C, Lee, T, Li, G, Li, S-C, Loitfelder, M, Lopez, OL, Lundervold, AJ, Lundqvist, A, Mather, KA, Mirza, SS, Nyberg, L, Oostra, BA, Palotie, A, Papenberg, G, Pattie, A, Petrovic, K, Polasek, O, Psaty, BM, Redmond, P, Reppermund, S, Rotter, JI, Schmidt, H, Schuur, M, Schofield, PW, Scott, RJ, Steen, VM, Stott, DJ, van Swieten, JC, Taylor, KD, Trollor, J, Trompet, S, Uitterlinden, AG, Weinstein, G, Widen, E, Windham, BG, Jukema, JW, and Wright, AF

Subjects
Generation Scotland, Humans, Genetic Predisposition to Disease, HMGN1 Protein, Cohort Studies, Cognition, Cognition Disorders, Neuropsychological Tests, Phenotype, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, Scotland, Female, Male, Atherosclerosis, Genome-Wide Association Study, and over, Polymorphism, Single Nucleotide, Psychiatry, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53,949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10(-9), MIR2113; rs17522122, P=2.55 × 10(-8), AKAP6; rs10119, P=5.67 × 10(-9), APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10(-6)). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10(-17)). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C.

Published
2015

2. Study protocol: a randomised controlled trial on the clinical effects of levothyroxine treatment for subclinical hypothyroidism in people aged 80 years and over

Author

Du Puy, R. S., Postmus, I., Stott, D. J., Blum, M. R., Poortvliet, R. K. E., Den Elzen, W. P. J., Peeters, R. P., van Munster, B. C., Wolffenbuttel, B. H. R., Westendorp, R. G. J., Kearney, P. M., Ford, I., Kean, S., Messow, C. M., Watt, T., Jukema, J. W., Dekkers, O. M., Smit, J. W. A., Rodondi, N., Gussekloo, J., and Mooijaart, S. P.

Published
2018
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4. Study protocol: a randomised controlled trial on the clinical effects of levothyroxine treatment for subclinical hypothyroidism in people aged 80 years and over

Author

Puy, R.S. Du, Postmus, I, Stott, D.J., Blum, M.R., Poortvliet, R.K.E., Elzen, W.P.J. Den, Dekkers, O.M., Smit, J.W.A., Gussekloo, J., Mooijaart, S.P., Puy, R.S. Du, Postmus, I, Stott, D.J., Blum, M.R., Poortvliet, R.K.E., Elzen, W.P.J. Den, Dekkers, O.M., Smit, J.W.A., Gussekloo, J., and Mooijaart, S.P.

Abstract

Contains fulltext : 196446.pdf (publisher's version ) (Open Access)

Published
2018

5. Study protocol:a randomised controlled trial on the clinical effects of levothyroxine treatment for subclinical hypothyroidism in people aged 80 years and over

Author

Du Puy, R S, Postmus, I, Stott, D J, Blum, M R, Poortvliet, R K E, Den Elzen, W P J, Peeters, R P, van Munster, B C, Wolffenbuttel, B H R, Westendorp, Rudolf Gerardus Johannes, Kearney, P M, Ford, I, Kean, S, Messow, C M, Watt, T., Jukema, J W, Dekkers, O M, Smit, J W A, Rodondi, N, Gussekloo, J, Mooijaart, S P, Du Puy, R S, Postmus, I, Stott, D J, Blum, M R, Poortvliet, R K E, Den Elzen, W P J, Peeters, R P, van Munster, B C, Wolffenbuttel, B H R, Westendorp, Rudolf Gerardus Johannes, Kearney, P M, Ford, I, Kean, S, Messow, C M, Watt, T., Jukema, J W, Dekkers, O M, Smit, J W A, Rodondi, N, Gussekloo, J, and Mooijaart, S P

Abstract

BACKGROUND: Subclinical hypothyroidism is common in older people and its contribution to health and disease needs to be elucidated further. Observational and clinical trial data on the clinical effects of subclinical hypothyroidism in persons aged 80 years and over is inconclusive, with some studies suggesting harm and some suggesting benefits, translating into equipoise whether levothyroxine therapy provides clinical benefits. This manuscript describes the study protocol for the Institute for Evidence-Based Medicine in Old Age (IEMO) 80-plus thyroid trial to generate the necessary evidence base.METHODS: The IEMO 80-plus thyroid trial was explicitly designed as an ancillary experiment to the Thyroid hormone Replacement for Untreated older adults with Subclinical hypothyroidism randomised placebo controlled Trial (TRUST) with a near identical protocol and shared research infrastructure. Outcomes will be presented separately for the IEMO and TRUST 80-plus groups, as well as a pre-planned combined analysis of the 145 participants included in the IEMO trial and the 146 participants from the TRUST thyroid trial aged 80 years and over. The IEMO 80-plus thyroid trial is a multi-centre randomised double-blind placebo-controlled parallel group trial of levothyroxine treatment in community-dwelling participants aged 80 years and over with persistent subclinical hypothyroidism (TSH ≥4.6 and ≤ 19.9 mU/L and fT4 within laboratory reference ranges). Participants are randomised to levothyroxine 25 or 50 micrograms daily or matching placebo with dose titrations according to TSH levels, for a minimum follow-up of one and a maximum of three years. Primary study endpoints: hypothyroid physical symptoms and tiredness on the thyroid-related quality of life patient-reported outcome (ThyPRO) at one year. Secondary endpoints: generic quality of life, executive cognitive function, handgrip strength, functional ability, blood pressure, weight, body mass index, and mortality. Advers

Published
2018

6. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Author

Teumer, A, Chaker, Layal, Groeneweg, Stefan, Li, Yi, Di Munno, Celia, Barbieri, C, Schultheiss, UT, Traglia, M, Ahluwalia, TS, Akiyama, M, Appel, EVR, Arking, DE, Arnold, A, Astrup, A, Beekman, M, Beilby, JP, Bekaert, S, Boerwinkle, E, Brown, SJ, de Buyzere, M, Campbell, PJ, Ceresini, G, Cerqueira, C, Cucca, F, Deary, IJ, Deelen, J, Eckardt, KU, Ekici, AB, Eriksson, JG, Ferrrucci, L, Fiers, T, Fiorillo, E, Ford, I, Fox, CS, Fuchsberger, C, Galesloot, TE, Gieger, C, Gogele, M, De Grandi, A, Grarup, N, Greiser, KH, Haljas, K, Hansen, T, Harris, SE, van Heemst, D, Heijer, M, Hicks, AA, den Hollander, W, Homuth, G, Hui, JN, Ikram, Arfan, Ittermann, T, Jensen, RA, Jing, J, Jukema, JW, Kajalltie, E, Kamatani, Y, Kasbohm, E, Kaufman, JM, Kiemeney, LA, Kloppenburg, M, Kronenberg, F, Kubo, M, Lahti, J, Lapauw, B, Li, S, Liewald, DCM, Lim, EM, Linneberg, A, Marina, M, Mascalzoni, D, Matsuda, K, Medenwald, D, Meisinger, C, Meulenbelt, I, Meyer, T, zu Schwabedissen, HEM, Mikolajczyk, R, Moed, M, Netea-Maier, RT, Nolte, IM, Okadah, Y, Pala, M, Pattaro, C, Pedersen, O, Petersmann, A, Porcu, E, Postmus, I, Pramstaller, PP, Psaty, BM, Ramos, YFM, Rawal, R, Redmond, P, Richards, JB, Rietzschel, ER, Rivadeneira, Fernando, Roef, G, Rotter, JI, Sala, CF, Schlessinger, D, Selvin, E, Slagboom, PE (Eline), Soranzo, N, Sorensen, TIA, Spector, TD, Starr, JM, Stott, DJ, Taes, Y, Taliun, D, Tanaka, T, Thuesen, B, Tiller, D, Toniolo, D, Uitterlinden, André, Visser, Edward, Walsh, JP, Wilson, SG, Wolffenbuttel, BHR, Yang, Q, Zheng, HF, Cappola, A, Peeters, Robin, Naitza, S, Volzke, H, Sanna, S, Kottgen, A, Visser, Theo, Medici, Marco, Teumer, A, Chaker, Layal, Groeneweg, Stefan, Li, Yi, Di Munno, Celia, Barbieri, C, Schultheiss, UT, Traglia, M, Ahluwalia, TS, Akiyama, M, Appel, EVR, Arking, DE, Arnold, A, Astrup, A, Beekman, M, Beilby, JP, Bekaert, S, Boerwinkle, E, Brown, SJ, de Buyzere, M, Campbell, PJ, Ceresini, G, Cerqueira, C, Cucca, F, Deary, IJ, Deelen, J, Eckardt, KU, Ekici, AB, Eriksson, JG, Ferrrucci, L, Fiers, T, Fiorillo, E, Ford, I, Fox, CS, Fuchsberger, C, Galesloot, TE, Gieger, C, Gogele, M, De Grandi, A, Grarup, N, Greiser, KH, Haljas, K, Hansen, T, Harris, SE, van Heemst, D, Heijer, M, Hicks, AA, den Hollander, W, Homuth, G, Hui, JN, Ikram, Arfan, Ittermann, T, Jensen, RA, Jing, J, Jukema, JW, Kajalltie, E, Kamatani, Y, Kasbohm, E, Kaufman, JM, Kiemeney, LA, Kloppenburg, M, Kronenberg, F, Kubo, M, Lahti, J, Lapauw, B, Li, S, Liewald, DCM, Lim, EM, Linneberg, A, Marina, M, Mascalzoni, D, Matsuda, K, Medenwald, D, Meisinger, C, Meulenbelt, I, Meyer, T, zu Schwabedissen, HEM, Mikolajczyk, R, Moed, M, Netea-Maier, RT, Nolte, IM, Okadah, Y, Pala, M, Pattaro, C, Pedersen, O, Petersmann, A, Porcu, E, Postmus, I, Pramstaller, PP, Psaty, BM, Ramos, YFM, Rawal, R, Redmond, P, Richards, JB, Rietzschel, ER, Rivadeneira, Fernando, Roef, G, Rotter, JI, Sala, CF, Schlessinger, D, Selvin, E, Slagboom, PE (Eline), Soranzo, N, Sorensen, TIA, Spector, TD, Starr, JM, Stott, DJ, Taes, Y, Taliun, D, Tanaka, T, Thuesen, B, Tiller, D, Toniolo, D, Uitterlinden, André, Visser, Edward, Walsh, JP, Wilson, SG, Wolffenbuttel, BHR, Yang, Q, Zheng, HF, Cappola, A, Peeters, Robin, Naitza, S, Volzke, H, Sanna, S, Kottgen, A, Visser, Theo, and Medici, Marco

Published
2018

7. Study protocol: a randomised controlled trial on the clinical effects of levothyroxine treatment for subclinical hypothyroidism in people aged 80 years and over

Author

Du Puy, RS, Postmus, I, Stott, DJ, Blum, MR, Poortvliet, RKE, den Elzen, WPJ, Peeters, Robin, van Munster, BC, Wolffenbuttel, BHR, Westendorp, RGJ, Kearney, PM, Ford, I, Kean, S, Messow, CM, Watt, T, Jukemal, JW, Dekkers, OM, Smit, JWA, Rodondi, N, Gussekloo, J, Mooijaart, SP, Du Puy, RS, Postmus, I, Stott, DJ, Blum, MR, Poortvliet, RKE, den Elzen, WPJ, Peeters, Robin, van Munster, BC, Wolffenbuttel, BHR, Westendorp, RGJ, Kearney, PM, Ford, I, Kean, S, Messow, CM, Watt, T, Jukemal, JW, Dekkers, OM, Smit, JWA, Rodondi, N, Gussekloo, J, and Mooijaart, SP

Published
2018

9. Genome-wide association study of genetic determinants of LDL-c response to atorvastatin therapy: importance of Lp(a)

Author

Deshmukh, H.A., Colhoun, H.M., Johnson, T., McKeigue, P.M., Betteridge, D.J., Durrington, P.N., Fuller, J.H., Livingstone, S., Charlton-Menys, V., Neil, A., Poulter, N., Sever, P., Shields, D.C., Stanton, A.V., Chatterjee, A., Hyde, C., Calle, R.A., DeMicco, D.A., Trompet, S., Postmus, I., Ford, I., Jukema, J.W., Caulfield, M., Hitman, G.A., CARDS, ASCOT, PROSPER Investigators, and National Institute for Health Research

Subjects
Oncology, Apolipoprotein E, Male, Atorvastatin, LDL/metabolism, Genome-wide association study, 030204 cardiovascular system & hematology, 0601 Biochemistry and Cell Biology, Biochemistry, chemistry.chemical_compound, 0302 clinical medicine, Endocrinology, lipoprotein(a), genetics, Receptors, Lysophosphatidic Acid, Randomized Controlled Trials as Topic, 0303 health sciences, biology, Lipoprotein(a), Middle Aged, 3. Good health, Treatment Outcome, 1101 Medical Biochemistry and Metabolomics, META ANALYSIS, DENSITY-LIPOPROTEIN CHOLESTEROL, CARDIOVASCULAR-DISEASE, LPA LOCUS, Glucosyltransferases, Hypertension, WHOLE-GENOME, Female, lipids (amino acids, peptides, and proteins), CARDS, ASCOT, and PROSPER Investigators, Life Sciences & Biomedicine, medicine.drug, Adult, Biochemistry & Molecular Biology, medicine.medical_specialty, Statin, Genotype, medicine.drug_class, Single-nucleotide polymorphism, QD415-436, CONTROLLED-TRIAL, Polymorphism, Single Nucleotide, statins, 03 medical and health sciences, Internal medicine, medicine, Humans, CORONARY-HEART-DISEASE, Pyrroles, Atorvastatin Calcium, 030304 developmental biology, Aged, Science & Technology, Cholesterol, business.industry, LIPID-LOWERING RESPONSE, Cell Biology, Cholesterol, LDL, PLASMA LIPOPROTEIN(A), Placebo Effect, chemistry, Diabetes Mellitus, Type 2, Heptanoic Acids, biology.protein, business, Patient-Oriented and Epidemiological Research, low density lipoprotein, Pravastatin, STATIN TREATMENT, Genome-Wide Association Study
Abstract

We carried out a genome-wide association study (GWAS) of LDL-c response to statin using data from participants in the Collaborative Atorvastatin Diabetes Study (CARDS; n = 1,156), the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT; n = 895), and the observational phase of ASCOT (n = 651), all of whom were prescribed atorvastatin 10 mg. Following genome-wide imputation, we combined data from the three studies in a meta-analysis. We found associations of LDL-c response to atorvastatin that reached genome-wide significance at rs10455872 (P = 6.13 x 10(-9)) within the LPA gene and at two single nucleotide polymorphisms (SNP) within the APOE region (rs445925; P = 2.22 x 10(-16) and rs4420638; P = 1.01 x 10(-11)) that are proxies for the epsilon 2 and epsilon 4 variants, respectively, in APOE. The novel association with the LPA SNP was replicated in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial (P = 0.009). Using CARDS data, we further showed that atorvastatin therapy did not alter lipoprotein(a) [Lp(a)] and that Lp(a) levels accounted for all of the associations of SNPs in the LPA gene and the apparent LDL-c response levels. However, statin therapy had a similar effect in reducing cardiovascular disease (CVD) in patients in the top quartile for serum Lp(a) levels (HR = 0.60) compared with those in the lower three quartiles (HR = 0.66; P = 0.8 for interaction). The data emphasize that high Lp(a) levels affect the measurement of LDL-c and the clinical estimation of LDL-c response.jlr Therefore, an apparently lower LDL-c response to statin therapy may indicate a need for measurement of Lp(a). However, statin therapy seems beneficial even in those with high Lp(a).-Deshmukh, H. A., H. M. Colhoun, T. Johnson, P. M. McKeigue, D. J. Betteridge, P. N. Durrington, J. H. Fuller, S. Livingstone, V. Charlton-Menys, A. Neil, N. Poulter, P. Sever, D. C. Shields, A. V. Stanton, A. Chatterjee, C. Hyde, R. A. Calle, D. A. DeMicco, S. Trompet, I. Postmus, I. Ford, J. W. Jukema, M. Caulfield, and G. A. Hitman on behalf of the CARDS, ASCOT, and PROSPER investigators. Genome-wide association study of genetic determinants of LDL-c response to atorvastatin therapy: importance of Lp(a). J. Lipid Res. 2012. 53: 1000-1011.

Published
2012

10. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Van Leeuwen, EM, Karssen, LC, Deelen, J, Isaacs, A, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N, Van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Van Dijk, F, Willemsen, G, De Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, F, Hofman, A, Oostra, BA, Franco, OH, Leach, IM, Beekman, M, De Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, Van Der Harst, P, Sijbrands, EJ, Hottenga, JJ, Uitterlinden, AG, Swertz, MA, Van Ommen, GJB, De Bakker, PIW, Eline Slagboom, P, Boomsma, DI, Wijmenga, C, Van Duijn, CM, Neerincx, PBT, Elbers, CC, Palamara, PF, Peer, I, Abdellaoui, A, Kloosterman, WP, Van Oven, M, Vermaat, M, Li, M, Laros, JFJ, Stoneking, M, De Knijff, P, Kayser, M, Veldink, JH, Van Den Berg, LH, Byelas, H, Den Dunnen, JT, Dijkstra, M, Amin, N, Van Der Velde, KJ, and Van Setten, J

Abstract

© 2015 Macmillan Publishers Limited. All rights reserved. Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (∼35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value

Published
2015

11. Genetic contributions to variation in general cognitive function:a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

Author

Davies, G., Armstrong, N., Bis, J. C., Bressler, J., Chouraki, V., Giddaluru, S., Hofer, E., Ibrahim-Verbaas, C. A., Kirin, M., Lahti, J., van der Lee, S. J., Le Hellard, S., Liu, T., Marioni, R. E., Oldmeadow, C., Postmus, I., Smith, A. V., Smith, J. A., Thalamuthu, A., Thomson, R., Vitart, V., Wang, J., Yu, L., Zgaga, L., Zhao, W., Boxall, R., Harris, S. E., Hill, W. D., Liewald, D. C., Luciano, M., Adams, H., Ames, D., Amin, N., Amouyel, P., Assareh, A. A., Au, R., Becker, J. T., Beiser, A., Berr, C., Bertram, L., Boerwinkle, E., Buckley, B. M., Campbell, H., Corley, J., De Jager, P. L., Dufouil, C., Eriksson, J. G., Espeseth, T., Faul, J. D., Ford, I., Gottesman, R. F., Griswold, M. E., Gudnason, V., Harris, T. B., Heiss, G., Hofman, A., Holliday, E. G., Huffman, J., Kardia, S. L. R., Kochan, N., Knopman, D. S., Kwok, J. B., Lambert, J-C, Lee, T., Li, G., Li, S-C, Loitfelder, M., Lopez, O. L., Lundervold, A. J., Lundquist, Anders, Mather, K. A., Mirza, S. S., Nyberg, Lars, Oostra, B. A., Palotie, A., Papenberg, G., Pattie, A., Petrovic, K., Polasek, O., Psaty, B. M., Redmond, P., Reppermund, S., Rotter, J. I., Schmidt, H., Schuur, M., Schofield, P. W., Scott, R. J., Steen, V. M., Stott, D. J., Van Swieten, J. C., Taylor, K. D., Trollor, J., Trompet, S., Uitterlinden, A. G., Weinstein, G., Widen, E., Windham, B. G., Jukema, J. W., Wright, A. F., Wright, M. J., Yang, Q., Amieva, H., Attia, J. R., Bennett, D. A., Brodaty, H., de Craen, A. J. M., Hayward, C., Ikram, M. A., Lindenberger, U., Nilsson, Lars-Göran, Porteous, D. J., Raikkonen, K., Reinvang, I., Rudan, I., Sachdev, P. S., Schmidt, R., Schofield, P. R., Srikanth, V., Starr, J. M., Turner, S. T., Weir, D. R., Wilson, J. F., Van Duijn, C., Launer, L., Fitzpatrick, A. L., Seshadri, S., Jr, T. H. Mosley, Deary, I. J., Epidemiology, Neurology, Radiology & Nuclear Medicine, Clinical Genetics, and Internal Medicine

Subjects
Male, Neurologi, SUSCEPTIBILITY LOCI, Neuropsychological Tests, Polymorphism, Single Nucleotide, IDENTIFIES VARIANTS, APOLIPOPROTEIN-E, Cohort Studies, Cognition, OLD-AGE, SDG 3 - Good Health and Well-being, Humans, Genetic Predisposition to Disease, HUMAN INTELLIGENCE, Aged, TYPE-4 ALLELE, Aged, 80 and over, TEST BATTERIES, Middle Aged, Atherosclerosis, CPG-BINDING PROTEIN-2, ALZHEIMERS-DISEASE, Phenotype, Scotland, Neurology, Female, Cognition Disorders, Immediate Communication, HUMAN HEIGHT, HMGN1 Protein, Genome-Wide Association Study
Abstract

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer’s disease: TOMM40, APOE, ABCG1 and MEF2C.

Published
2015

12. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

Author

Davies, G., Armstrong, N., Bis, J.C., Bressler, J., Chouraki, V., Giddaluru, S., Hofer, E., Ibrahim-Verbaas, C.A., Kirin, M., Lahti, J., Lee, S.J. van der, Hellard, S. le, Liu, T., Marioni, R.E., Oldmeadow, C., Postmus, I., Smith, A.V., Smith, J.A., Thalamuthu, A., Thomson, R., Vitart, V., Wang, J., Yu, L., Zgaga, L., Zhao, W., Boxall, R., Harris, S.E., Hill, W.D., Liewald, D.C., Luciano, M., Adams, H., Ames, D., Amin, N., Amouyel, P., Assareh, A.A., Au, R., Becker, J.T., Beiser, A., Berr, C., Bertram, L., Boerwinkle, E., Buckley, B.M., Campbell, H., Corley, J., Jager, P.L. de, Dufouil, C., Eriksson, J.G., Espeseth, T., Faul, J.D., Ford, I., Gottesman, R.F., Griswold, M.E., Gudnason, V., Harris, T.B., Heiss, G., Hofman, A., Holliday, E.G., Huffman, J., Kardia, S.L.R., Kochan, N., Knopman, D.S., Kwok, J.B., Lambert, J.C., Lee, T., Li, G., Li, S.C., Loitfelder, M., Lopez, O.L., Lundervold, A.J., Lundqvist, A., Mather, K.A., Mirza, S.S., Nyberg, L., Oostra, B.A., Palotie, A., Papenberg, G., Pattie, A., Petrovic, K., Polasek, O., Psaty, B.M., Redmond, P., Reppermund, S., Rotter, J.I., Schmidt, H., Schuur, M., Schofield, P.W., Scott, R.J., Steen, V.M., Stott, D.J., Swieten, J.C. van, Taylor, K.D., Trollor, J., Trompet, S., Uitterlinden, A.G., Weinstein, G., Widen, E., Windham, B.G., Jukema, J.W., Wright, A.F., Wright, M.J., Yang, Q., Amieva, H., Attia, J.R., Bennett, D.A., Brodaty, H., Craen, A.J.M. de, Hayward, C., Ikram, M.A., Lindenberger, U., Nilsson, L.G., Porteous, D.J., Raikkonen, K., Reinvang, I., Rudan, I., Sachdev, P.S., Schmidt, R., Schofield, P.R., Srikanth, V., Starr, J.M., Turner, S.T., Weir, D.R., Wilson, J.F., Duijn, C. van, Launer, L., Fitzpatrick, A.L., Seshadri, S., Jr, T.H.M., Deary, I.J., and Generation Scotland

Subjects
Medisinske fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710::Medisinsk genetikk: 714 [VDP], Social sciences: 200::Psychology: 260::Cognitive psychology: 267 [VDP], Midical sciences: 700::Basic medical, dental and veterinary sciences: 710::Medical genetics: 714 [VDP], Samfunnsvitenskap: 200::Psykologi: 260::Kognitiv psykologi: 267 [VDP]
Abstract

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer’s disease: TOMM40, APOE, ABCG1 and MEF2C. publishedVersion

Published
2015

13. Genetics, statins, and lipid metabolism in cardiovascular disease

Author

Postmus, I., Jukema, J.W., Westendorp, R.G.J., Trompet, S., Craen, A.J.M. de, and Leiden University

Subjects
Aging, Lipid metabolism, Pharmacogenetics, Statins, Genetics, GWAS, lipids (amino acids, peptides, and proteins), Cardiovascular disease
Abstract

Aim of this thesis was to investigate pharmacogenetic effects on response to statin treatment and the genetics of lipid metabolism and cardiovascular disease. In chapter 4 the first results of the Genomic investigation of Statin Therapy (GIST) consortium are presented. We identified and validated two new GWAS loci to be associated with LDL-cholesterol response after statin treatment. In addition, we confirmed two previous identified loci. In chapter 5 we showed that we were not able to identify any loci associated with differential event reduction after statin therapy within the PROSPER study. The results presented in chapter 8 show that even at old age a genetic predisposition to high LDL-cholesterol is a risk factor for mortality. The results of this thesis show that currently the possibilities to personalize statin treatment based on genetic variants is limited. New research methods will hopefully give new opportunities to improve cardiovascular disease treatment and give more insight into the biological mechanisms of statin treatment.

Published
2015

14. Heavier smoking may lead to a relative increase in waist circumference: Evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium

Author

Morris, R.W., Taylor, A.E., Fluharty, M.E., Bjorngaard, J.H., Asvold, B.O., Elvestad Gabrielsen, M., Campbell, A., Marioni, R., Kumari, M., Korhonen, T., Männistö, S., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Husemoen, L.L.N., Skaaby, T., Ahluwalia, T.S., Treur, J.L., Willemsen, G., Dale, C., Wannamethee, S.G., Lahti, J., Palotie, A., Räikkönen, K., McConnachie, A., Padmanabhan, S., Wong, A., Dalgard, C., Paternoster, L., Ben-Shlomo, Y., Tyrrell, J., Horwood, J., Fergusson, D.M., Kennedy, M.A., Nohr, E.A., Christiansen, L., Kyvik, K.O., Kuh, D, Watt, G., Eriksson, J.G., Whincup, P.H., Vink, J.M., Boomsma, D.I., Davey Smith, G., Lawlor, D., Linneberg, A., Ford, I., Jukema, J.W., Power, C., Hyppönen, E., Jarvelin, M.R., Preisig, M., Borodulin, K., Kaprio, J., Kivimaki, M., Smith, B.H., Hayward, C., Romundstad, P.R., Sørensen, T.I.A., Munafò, M., Sattar, N., Medical Research Council (MRC), Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, and EMGO+ - Lifestyle, Overweight and Diabetes

Subjects
Adult, Male, Netherlands Twin Register (NTR), Adolescent, GENETICS, Aged, Body Mass Index, Female, Humans, Mendelian Randomization Analysis, Middle Aged, Obesity, Abdominal/complications, Sex Factors, Smoking/adverse effects, Smoking/genetics, Waist Circumference, Waist-Hip Ratio, Young Adult, Brain and Behaviour, Medicine, General & Internal, SDG 3 - Good Health and Well-being, General & Internal Medicine, EPIDEMIOLOGY, CORONARY-HEART-DISEASE, WEIGHT CONCERNS, Smoking and Tobacco, Science & Technology, MORTALITY, Research, Tobacco and Alcohol, Smoking, WOMEN, MEN, ASSOCIATION, BODY-MASS INDEX, Obesity, Abdominal, RISK-FACTORS, ADIPOSITY, CIGARETTE-SMOKING, Life Sciences & Biomedicine, Developmental Psychopathology
Abstract

OBJECTIVES: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity.DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes.PARTICIPANTS: 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA).PRIMARY OUTCOME MEASURES: Waist and hip circumferences, and waist-hip ratio.RESULTS: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele.CONCLUSIONS: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity. OBJECTIVES: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity.DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes.PARTICIPANTS: 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA).PRIMARY OUTCOME MEASURES: Waist and hip circumferences, and waist-hip ratio.RESULTS: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele.CONCLUSIONS: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity.

Published
2015

15. Non-response to (statin) therapy: the importance of distinguishing non-responders from non-adherers in pharmacogenetic studies

Author

Trompet, S, Postmus, I, Slagboom, PE, Heijmans, BT, Smit, RAJ, Maier, AB, Buckley, BM, Sattar, N, Stott, DJ, Ford, I, Westendorp, RGJ, de Craen, AJM, Jukema, JW, Trompet, S, Postmus, I, Slagboom, PE, Heijmans, BT, Smit, RAJ, Maier, AB, Buckley, BM, Sattar, N, Stott, DJ, Ford, I, Westendorp, RGJ, de Craen, AJM, and Jukema, JW

Abstract

PURPOSE: In pharmacogenetic research, genetic variation in non-responders and high responders is compared with the aim to identify the genetic loci responsible for this variation in response. However, an important question is whether the non-responders are truly biologically non-responsive or actually non-adherent? Therefore, the aim of this study was to describe, within the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER), characteristics of both non-responders and high responders of statin treatment in order to possibly discriminate non-responders from non-adherers. METHODS: Baseline characteristics of non-responders to statin therapy (≤10 % LDL-C reduction) were compared with those of high responders (>40 % LDL-C reduction) through a linear regression analysis. In addition, pharmacogenetic candidate gene analysis was performed to show the effect of excluding non-responders from the analysis. RESULTS: Non-responders to statin therapy were younger (p = 0.001), more often smoked (p < 0.001), had a higher alcohol consumption (p < 0.001), had lower LDL cholesterol levels (p < 0.001), had a lower prevalence of hypertension (p < 0.001), and had lower cognitive function (p = 0.035) compared to subjects who highly responded to pravastatin treatment. Moreover, excluding non-responders from pharmacogenetic studies yielded more robust results, as standard errors decreased. CONCLUSION: Our results suggest that non-responders to statin therapy are more likely to actually be non-adherers, since they have more characteristics that are viewed as indicators of high self-perceived health and low disease awareness, possibly making the subjects less adherent to study medication. We suggest that in pharmacogenetic research, extreme non-responders should be excluded to overcome the problem that non-adherence is investigated instead of non-responsiveness.

Published
2016

16. Non-response to (statin) therapy:the importance of distinguishing non-responders from non-adherers in pharmacogenetic studies

Author

Trompet, S, Postmus, I, Slagboom, P E, Heijmans, B T, Smit, R A J, Maier, A B, Buckley, B M, Sattar, N, Stott, D J, Ford, I, Westendorp, R G J, de Craen, A J M, Jukema, J W, Trompet, S, Postmus, I, Slagboom, P E, Heijmans, B T, Smit, R A J, Maier, A B, Buckley, B M, Sattar, N, Stott, D J, Ford, I, Westendorp, R G J, de Craen, A J M, and Jukema, J W

Abstract

PURPOSE: In pharmacogenetic research, genetic variation in non-responders and high responders is compared with the aim to identify the genetic loci responsible for this variation in response. However, an important question is whether the non-responders are truly biologically non-responsive or actually non-adherent? Therefore, the aim of this study was to describe, within the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER), characteristics of both non-responders and high responders of statin treatment in order to possibly discriminate non-responders from non-adherers.METHODS: Baseline characteristics of non-responders to statin therapy (≤10 % LDL-C reduction) were compared with those of high responders (>40 % LDL-C reduction) through a linear regression analysis. In addition, pharmacogenetic candidate gene analysis was performed to show the effect of excluding non-responders from the analysis.RESULTS: Non-responders to statin therapy were younger (p = 0.001), more often smoked (p < 0.001), had a higher alcohol consumption (p < 0.001), had lower LDL cholesterol levels (p < 0.001), had a lower prevalence of hypertension (p < 0.001), and had lower cognitive function (p = 0.035) compared to subjects who highly responded to pravastatin treatment. Moreover, excluding non-responders from pharmacogenetic studies yielded more robust results, as standard errors decreased.CONCLUSION: Our results suggest that non-responders to statin therapy are more likely to actually be non-adherers, since they have more characteristics that are viewed as indicators of high self-perceived health and low disease awareness, possibly making the subjects less adherent to study medication. We suggest that in pharmacogenetic research, extreme non-responders should be excluded to overcome the problem that non-adherence is investigated instead of non-responsiveness.

Published
2016

17. Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

Author

Postmus, I, Warren, HR, Trompet, S, Arsenault, BJ, Avery, CL, Bis, JC, Chasman, DI, de Keyser, Toke, Deshmukh, HA, Evans, DS, Feng, Q, Li, X, Smit, RAJ, Smith, AV, Sun, F, Taylor, KD, Arnold, AM, Barnes, MR, Barratt, BJ, Betteridge, J, Boekholdt, SM, Boerwinkle, E, Buckley, BM, Chen, YDI, de Craen, AJM, Cummings, SR, Denny, JC, Dube, MP, Durrington, PN, Eiriksdottir, G, Ford, I, Guo, X, Harris, TB, Heckbert, SR, Hofman, Bert, Hovingh, GK, Kastelein, JJP, Launer, LJ, Liu, C-T, Liu, Y, Lumley, T, Mckeigue, PM, Munroe, PB, Neil, A, Nickerson, DA, Nyberg, F, O'Brien, E, O'Donnell, CJ, Post, W, Poulter, N, Vasan, RS, Rice, K, Rich, SS, Rivadeneira, Fernando, Sattar, N, Sever, P, Shaw-Hawkins, S, Shields, DC, Slagboom, PE (Eline), Smith, NL, Smith, JD, Sotoodehnia, N, Stanton, A, Stott, DJ, Stricker, Bruno, Sturmer, T, Uitterlinden, André, Wei, W-Q, Westendorp, RGJ, Whitsel, EA, Wiggins, KL, Wilke, RA, Ballantyne, CM, Colhoun, HM, Cupples, LA, Franco Duran, OH, Gudnason, V, Hitman, G, Palmer, CNA, Psaty, BM, Ridker, PM, Stafford, JM, Stein, CM, Tardif, J-C, Caulfield, MJ, Jukema, JW, Rotter, JI, Krauss, RM, Postmus, I, Warren, HR, Trompet, S, Arsenault, BJ, Avery, CL, Bis, JC, Chasman, DI, de Keyser, Toke, Deshmukh, HA, Evans, DS, Feng, Q, Li, X, Smit, RAJ, Smith, AV, Sun, F, Taylor, KD, Arnold, AM, Barnes, MR, Barratt, BJ, Betteridge, J, Boekholdt, SM, Boerwinkle, E, Buckley, BM, Chen, YDI, de Craen, AJM, Cummings, SR, Denny, JC, Dube, MP, Durrington, PN, Eiriksdottir, G, Ford, I, Guo, X, Harris, TB, Heckbert, SR, Hofman, Bert, Hovingh, GK, Kastelein, JJP, Launer, LJ, Liu, C-T, Liu, Y, Lumley, T, Mckeigue, PM, Munroe, PB, Neil, A, Nickerson, DA, Nyberg, F, O'Brien, E, O'Donnell, CJ, Post, W, Poulter, N, Vasan, RS, Rice, K, Rich, SS, Rivadeneira, Fernando, Sattar, N, Sever, P, Shaw-Hawkins, S, Shields, DC, Slagboom, PE (Eline), Smith, NL, Smith, JD, Sotoodehnia, N, Stanton, A, Stott, DJ, Stricker, Bruno, Sturmer, T, Uitterlinden, André, Wei, W-Q, Westendorp, RGJ, Whitsel, EA, Wiggins, KL, Wilke, RA, Ballantyne, CM, Colhoun, HM, Cupples, LA, Franco Duran, OH, Gudnason, V, Hitman, G, Palmer, CNA, Psaty, BM, Ridker, PM, Stafford, JM, Stein, CM, Tardif, J-C, Caulfield, MJ, Jukema, JW, Rotter, JI, and Krauss, RM

Published
2016

20. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Leeuwen, E.M. van, Karssen, L.C., Deelen, J., Isaacs, A., Medina-Gomez, C., Mbarek, H., Kanterakis, A., Trompet, S., Postmus, I., Verweij, N., Enckevort, D.J. van, Huffman, J.E., White, C.C., Feitosa, M.F., Bartz, T.M., Manichaikul, A., Joshi, P.K., Peloso, G.M., Deelen, P., Dijk, F. van, Willemsen, G., Geus, E.J. de, Milaneschi, Y., Penninx, B.W., Francioli, L.C., Menelaou, A., Pulit, S.L., Rivadeneira, F., Hofman, A., Oostra, B.A., Franco, O.H., Leach, I. Mateo, Beekman, M., Craen, A.J. de, Uh, H.W., Trochet, H., Hocking, L.J., Porteous, D.J., Sattar, N., Packard, C.J., Buckley, B.M., Brody, J.A., Bis, J.C., Rotter, J.I., Mychaleckyj, J.C., Campbell, H., Duan, Q., Lange, L.A., Wilson, J.F., Hayward, C., Polasek, O., Vitart, V., Rudan, I., Wright, A.F., Rich, S.S., Psaty, B.M., Borecki, I.B., Kearney, P.M., Stott, D.J., Cupples, L. Adrienne, Consortium, G.o.t.N., Jukema, J.W., Harst, P. van der, Sijbrands, E.J., Hottenga, J.J., Uitterlinden, A.G., Swertz, M.A., Ommen, G.J. van, Bakker, P.I. de, Slagboom, P., Boomsma, D.I., Wijmenga, C., Duijn, C.M. van, Hehir-Kwa, J.Y., et al., Leeuwen, E.M. van, Karssen, L.C., Deelen, J., Isaacs, A., Medina-Gomez, C., Mbarek, H., Kanterakis, A., Trompet, S., Postmus, I., Verweij, N., Enckevort, D.J. van, Huffman, J.E., White, C.C., Feitosa, M.F., Bartz, T.M., Manichaikul, A., Joshi, P.K., Peloso, G.M., Deelen, P., Dijk, F. van, Willemsen, G., Geus, E.J. de, Milaneschi, Y., Penninx, B.W., Francioli, L.C., Menelaou, A., Pulit, S.L., Rivadeneira, F., Hofman, A., Oostra, B.A., Franco, O.H., Leach, I. Mateo, Beekman, M., Craen, A.J. de, Uh, H.W., Trochet, H., Hocking, L.J., Porteous, D.J., Sattar, N., Packard, C.J., Buckley, B.M., Brody, J.A., Bis, J.C., Rotter, J.I., Mychaleckyj, J.C., Campbell, H., Duan, Q., Lange, L.A., Wilson, J.F., Hayward, C., Polasek, O., Vitart, V., Rudan, I., Wright, A.F., Rich, S.S., Psaty, B.M., Borecki, I.B., Kearney, P.M., Stott, D.J., Cupples, L. Adrienne, Consortium, G.o.t.N., Jukema, J.W., Harst, P. van der, Sijbrands, E.J., Hottenga, J.J., Uitterlinden, A.G., Swertz, M.A., Ommen, G.J. van, Bakker, P.I. de, Slagboom, P., Boomsma, D.I., Wijmenga, C., Duijn, C.M. van, Hehir-Kwa, J.Y., and et al.

Abstract

Contains fulltext : 155355.pdf (publisher's version ) (Open Access)

Published
2015

21. Effect of smoking on blood pressure and resting heart rate: A Mendelian randomization meta-analysis in the CARTA Consortium

Author

Linneberg, A., Jacobsen, R.K., Skaaby, T., Taylor, A.E., Fluharty, M.E., Jeppesen, J.L., Björngaard, J.H., Asvold, B.A., Gabrielsen, M.E., Campbell, A., Marioni, R.E., Kumari, M., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Ahluwalia, T.V.S., Wannamethee, S.G., Lahti, J., Raikkonen, K., Palotie, A., Wong, A., Dalgard, C., Ford, I., Ben-Shlomo, Y., Christiansen, L., Kyvik, K.O., Kuh, D., Eriksson, J.G., Whincup, P.H., Mbarek, H., Geus, E.J.C. de, Vink, J.M., Boomsma, D.I., Smith, G.D., Lawlor, D.A., Kisialiou, A., McConnachie, A., Padmanabhan, S., Jukema, J.W., Power, C., Hypponen, E., Preisig, M., Waeber, G., Vollenweider, P., Korhonen, T., Laatikainen, T., Salomaa, V., Kaprio, J., Kivimäki, M., Smith, B.H., Hayward, C., Sorensen, T.I.A., Thuesen, B.H., Sattar, N., Morris, R.W., Romundstad, P.R., Munafò, M.R., Jarvelin, M.R., Husemoen, L.L.N., Linneberg, A., Jacobsen, R.K., Skaaby, T., Taylor, A.E., Fluharty, M.E., Jeppesen, J.L., Björngaard, J.H., Asvold, B.A., Gabrielsen, M.E., Campbell, A., Marioni, R.E., Kumari, M., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Ahluwalia, T.V.S., Wannamethee, S.G., Lahti, J., Raikkonen, K., Palotie, A., Wong, A., Dalgard, C., Ford, I., Ben-Shlomo, Y., Christiansen, L., Kyvik, K.O., Kuh, D., Eriksson, J.G., Whincup, P.H., Mbarek, H., Geus, E.J.C. de, Vink, J.M., Boomsma, D.I., Smith, G.D., Lawlor, D.A., Kisialiou, A., McConnachie, A., Padmanabhan, S., Jukema, J.W., Power, C., Hypponen, E., Preisig, M., Waeber, G., Vollenweider, P., Korhonen, T., Laatikainen, T., Salomaa, V., Kaprio, J., Kivimäki, M., Smith, B.H., Hayward, C., Sorensen, T.I.A., Thuesen, B.H., Sattar, N., Morris, R.W., Romundstad, P.R., Munafò, M.R., Jarvelin, M.R., and Husemoen, L.L.N.

Abstract

Item does not contain fulltext, Background; Smoking is an important cardiovascular disease risk factor, but the mechanisms linking smoking to blood pressure are poorly understood.Methods and Results: Data on 141 317 participants (62 666 never, 40 669 former, 37 982 current smokers) from 23 population-based studies were included in observational and Mendelian randomization meta-analyses of the associations of smoking status and smoking heaviness with systolic and diastolic blood pressure, hypertension, and resting heart rate. For the Mendelian randomization analyses, a genetic variant rs16969968/rs1051730 was used as a proxy for smoking heaviness in current smokers. In observational analyses, current as compared with never smoking was associated with lower systolic blood pressure and diastolic blood pressure and lower hypertension risk, but with higher resting heart rate. In observational analyses among current smokers, 1 cigarette/day higher level of smoking heaviness was associated with higher (0.21 bpm; 95% confidence interval 0.19; 0.24) resting heart rate and slightly higher diastolic blood pressure (0.05 mm Hg; 95% confidence interval 0.02; 0.08) and systolic blood pressure (0.08 mm Hg; 95% confidence interval 0.03; 0.13). However, in Mendelian randomization analyses among current smokers, although each smoking increasing allele of rs16969968/rs1051730 was associated with higher resting heart rate (0.36 bpm/allele; 95% confidence interval 0.18; 0.54), there was no strong association with diastolic blood pressure, systolic blood pressure, or hypertension. This would suggest a 7 bpm higher heart rate in those who smoke 20 cigarettes/day.Conclusions: This Mendelian randomization meta-analysis supports a causal association of smoking heaviness with higher level of resting heart rate, but not with blood pressure. These findings suggest that part of the cardiovascular risk of smoking may operate through increasing resting heart rate.

Published
2015

22. Genetic contributions to variation in general cognitive function: A meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

Author

Davies, G, Armstrong, N, Bis, JC, Bressler, J, Chouraki, V, Giddaluru, S, Hofer, E, Ibrahim-Verbaas, CA, Kirin, M, Lahti, J, Van Der Lee, SJ, Le Hellard, S, Liu, T, Marioni, RE, Oldmeadow, C, Postmus, I, Smith, AV, Smith, JA, Thalamuthu, A, Thomson, R, Vitart, V, Wang, J, Yu, L, Zgaga, L, Zhao, W, Boxall, R, Harris, SE, Hill, WD, Liewald, DC, Luciano, M, Adams, H, Ames, D, Amin, N, Amouyel, P, Assareh, AA, Au, R, Becker, JT, Beiser, A, Berr, C, Bertram, L, Boerwinkle, E, Buckley, BM, Campbell, H, Corley, J, De Jager, PL, Dufouil, C, Eriksson, JG, Espeseth, T, Faul, JD, Ford, I, Scotland, G, Gottesman, RF, Griswold, ME, Gudnason, V, Harris, TB, Heiss, G, Hofman, A, Holliday, EG, Huffman, J, Kardia, SLR, Kochan, N, Knopman, DS, Kwok, JB, Lambert, JC, Lee, T, Li, G, Li, SC, Loitfelder, M, Lopez, OL, Lundervold, AJ, Lundqvist, A, Mather, KA, Mirza, SS, Nyberg, L, Oostra, BA, Palotie, A, Papenberg, G, Pattie, A, Petrovic, K, Polasek, O, Psaty, BM, Redmond, P, Reppermund, S, Rotter, JI, Schmidt, H, Schuur, M, Schofield, PW, Scott, RJ, Steen, VM, Stott, DJ, Van Swieten, JC, Taylor, KD, Trollor, J, Trompet, S, Uitterlinden, AG, Weinstein, G, Widen, E, Windham, BG, Jukema, JW, Wright, AF, Davies, G, Armstrong, N, Bis, JC, Bressler, J, Chouraki, V, Giddaluru, S, Hofer, E, Ibrahim-Verbaas, CA, Kirin, M, Lahti, J, Van Der Lee, SJ, Le Hellard, S, Liu, T, Marioni, RE, Oldmeadow, C, Postmus, I, Smith, AV, Smith, JA, Thalamuthu, A, Thomson, R, Vitart, V, Wang, J, Yu, L, Zgaga, L, Zhao, W, Boxall, R, Harris, SE, Hill, WD, Liewald, DC, Luciano, M, Adams, H, Ames, D, Amin, N, Amouyel, P, Assareh, AA, Au, R, Becker, JT, Beiser, A, Berr, C, Bertram, L, Boerwinkle, E, Buckley, BM, Campbell, H, Corley, J, De Jager, PL, Dufouil, C, Eriksson, JG, Espeseth, T, Faul, JD, Ford, I, Scotland, G, Gottesman, RF, Griswold, ME, Gudnason, V, Harris, TB, Heiss, G, Hofman, A, Holliday, EG, Huffman, J, Kardia, SLR, Kochan, N, Knopman, DS, Kwok, JB, Lambert, JC, Lee, T, Li, G, Li, SC, Loitfelder, M, Lopez, OL, Lundervold, AJ, Lundqvist, A, Mather, KA, Mirza, SS, Nyberg, L, Oostra, BA, Palotie, A, Papenberg, G, Pattie, A, Petrovic, K, Polasek, O, Psaty, BM, Redmond, P, Reppermund, S, Rotter, JI, Schmidt, H, Schuur, M, Schofield, PW, Scott, RJ, Steen, VM, Stott, DJ, Van Swieten, JC, Taylor, KD, Trollor, J, Trompet, S, Uitterlinden, AG, Weinstein, G, Widen, E, Windham, BG, Jukema, JW, and Wright, AF

Abstract

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10-9, MIR2113; rs17522122, P=2.55 × 10-8, AKAP6; rs10119, P=5.67 × 10-9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10-6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ∼1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10-17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C.

Published
2015

23. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Author

Leeuwen, Elisa, Karssen, Lennart, Deelen, J, Isaacs, Aaron, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N (Niek), van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Dijk, Femke, Willemsen, G, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, Fernando, Hofman, Bert, Oostra, Ben, Franco Duran, OH, Leach, IM, Beekman, M, de Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, van der Harst, P, Sijbrands, E.J.G., Hottenga, JJ (Jouke Jan), Uitterlinden, André, Swertz, MA, van Ommen, GJB, de Bakker, PIW, Slagboom, PE (Eline), Boomsma, DI, Wijmenga, C, Duijn, Cornelia, Leeuwen, Elisa, Karssen, Lennart, Deelen, J, Isaacs, Aaron, Medina-Gomez, C, Mbarek, H, Kanterakis, A, Trompet, S, Postmus, I, Verweij, N (Niek), van Enckevort, DJ, Huffman, JE, White, CC, Feitosa, MF, Bartz, TM, Manichaikul, A, Joshi, PK, Peloso, GM, Deelen, P, Dijk, Femke, Willemsen, G, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Francioli, LC, Menelaou, A, Pulit, SL, Rivadeneira, Fernando, Hofman, Bert, Oostra, Ben, Franco Duran, OH, Leach, IM, Beekman, M, de Craen, AJM, Uh, HW, Trochet, H, Hocking, LJ, Porteous, DJ, Sattar, N, Packard, CJ, Buckley, BM, Brody, JA, Bis, JC, Rotter, JI, Mychaleckyj, JC, Campbell, H, Duan, Q, Lange, LA, Wilson, JF, Hayward, C, Polasek, O, Vitart, V, Rudan, I, Wright, AF, Rich, SS, Psaty, BM, Borecki, IB, Kearney, PM, Stott, DJ, Cupples, LA, Jukema, JW, van der Harst, P, Sijbrands, E.J.G., Hottenga, JJ (Jouke Jan), Uitterlinden, André, Swertz, MA, van Ommen, GJB, de Bakker, PIW, Slagboom, PE (Eline), Boomsma, DI, Wijmenga, C, and Duijn, Cornelia

Abstract

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (similar to 35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value < 6.61 x 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (beta(LDL-C) = 0.135, beta(TC) = 0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

Published
2015

24. Non-response to (statin) therapy: the importance of distinguishing non-responders from non-adherers in pharmacogenetic studies

Author

Trompet, S., primary, Postmus, I., additional, Slagboom, P. E., additional, Heijmans, B. T., additional, Smit, R. A. J., additional, Maier, A. B., additional, Buckley, B. M., additional, Sattar, N., additional, Stott, D. J., additional, Ford, I., additional, Westendorp, R. G. J., additional, de Craen, A. J. M., additional, and Jukema, J. W., additional

Published
2015
Full Text
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28. Replication of LDL GWAs hits in PROSPER/PHASE as validation for future (pharmaco)genetic analyses

Author

Trompet, S., Craen, A.J.M. de, Postmus, I., Ford, I., Sattar, N., Caslake, M., Stott, D.J., Buckley, B.M., Sacks, F., Devlin, J.J., Slagboom, P.E., Westendorp, R.G.J., Jukema, J.W., and PROSPER Study Grp

Subjects
lcsh:Internal medicine, lcsh:QH426-470, Single-nucleotide polymorphism, Genome-wide association study, 030204 cardiovascular system & hematology, Biology, Population stratification, Polymorphism, Single Nucleotide, Pharmacogenetic Study, Placebos, 03 medical and health sciences, 0302 clinical medicine, Genetic variation, Genetics, Humans, Genetics(clinical), Prospective Studies, International HapMap Project, lcsh:RC31-1245, Genetics (clinical), Aged, Pravastatin, 030304 developmental biology, 0303 health sciences, 3. Good health, Lipoproteins, LDL, lcsh:Genetics, Pharmacogenetics, lipids (amino acids, peptides, and proteins), Hydroxymethylglutaryl-CoA Reductase Inhibitors, Imputation (genetics), Genome-Wide Association Study, Research Article
Abstract

Background The PHArmacogenetic study of Statins in the Elderly at risk (PHASE) is a genome wide association study in the PROspective Study of Pravastatin in the Elderly at risk for vascular disease (PROSPER) that investigates the genetic variation responsible for the individual variation in drug response to pravastatin. Statins lower LDL-cholesterol in general by 30%, however not in all subjects. Moreover, clinical response is highly variable and adverse effects occur in a minority of patients. In this report we first describe the rationale of the PROSPER/PHASE project and second show that the PROSPER/PHASE study can be used to study pharmacogenetics in the elderly. Methods The genome wide association study (GWAS) was conducted using the Illumina 660K-Quad beadchips following manufacturer's instructions. After a stringent quality control 557,192 SNPs in 5,244 subjects were available for analysis. To maximize the availability of genetic data and coverage of the genome, imputation up to 2.5 million autosomal CEPH HapMap SNPs was performed with MACH imputation software. The GWAS for LDL-cholesterol is assessed with an additive linear regression model in PROBABEL software, adjusted for age, sex, and country of origin to account for population stratification. Results Forty-two SNPs reached the GWAS significant threshold of p = 5.0e-08 in 5 genomic loci (APOE/APOC1; LDLR; FADS2/FEN1; HMGCR; PSRC1/CELSR5). The top SNP (rs445925, chromosome 19) with a p-value of p = 2.8e-30 is located within the APOC1 gene and near the APOE gene. The second top SNP (rs6511720, chromosome 19) with a p-value of p = 5.22e-15 is located within the LDLR gene. All 5 genomic loci were previously associated with LDL-cholesterol levels, no novel loci were identified. Replication in WOSCOPS and CARE confirmed our results. Conclusion With the GWAS in the PROSPER/PHASE study we confirm the previously found genetic associations with LDL-cholesterol levels. With this proof-of-principle study we show that the PROSPER/PHASE study can be used to investigate genetic associations in a similar way to population based studies. The next step of the PROSPER/PHASE study is to identify the genetic variation responsible for the variation in LDL-cholesterol lowering in response to statin treatment in collaboration with other large trials.

Published
2011

29. Replication of LDL SWAs hits in PROSPER/PHASE as validation for future (pharmaco)genetic analyses

Author

Trompet, S., de Craen, A.J.M., Postmus, I., Ford, I., Sattar, N., Caslake, M., Stott, D.J., Buckley, B.M., Sacks, F., Devlin, J.J., Slagboom, P.E., Westendorp, R.G.J., and Jukema, J.W.

Subjects
lipids (amino acids, peptides, and proteins)
Abstract

Background: The PHArmacogenetic study of Statins in the Elderly at risk (PHASE) is a genome wide association study in the PROspective Study of Pravastatin in the Elderly at risk for vascular disease (PROSPER) that investigates the genetic variation responsible for the individual variation in drug response to pravastatin. Statins lower LDL-cholesterol in general by 30%, however not in all subjects. Moreover, clinical response is highly variable and adverse effects occur in a minority of patients. In this report we first describe the rationale of the PROSPER/PHASE project and second show that the PROSPER/PHASE study can be used to study pharmacogenetics in the elderly.\ud \ud Methods: The genome wide association study (GWAS) was conducted using the Illumina 660K-Quad beadchips following manufacturer's instructions. After a stringent quality control 557,192 SNPs in 5,244 subjects were available for analysis. To maximize the availability of genetic data and coverage of the genome, imputation up to 2.5 million autosomal CEPH HapMap SNPs was performed with MACH imputation software. The GWAS for LDL-cholesterol is assessed with an additive linear regression model in PROBABEL software, adjusted for age, sex, and country of origin to account for population stratification.\ud \ud Results: Forty-two SNPs reached the GWAS significant threshold of p = 5.0e-08 in 5 genomic loci (APOE/APOC1; LDLR; FADS2/FEN1; HMGCR; PSRC1/CELSR5). The top SNP (rs445925, chromosome 19) with a p-value of p = 2.8e-30 is located within the APOC1 gene and near the APOE gene. The second top SNP (rs6511720, chromosome 19) with a p-value of p = 5.22e-15 is located within the LDLR gene. All 5 genomic loci were previously associated with LDL-cholesterol levels, no novel loci were identified. Replication in WOSCOPS and CARE confirmed our results.\ud \ud Conclusion: With the GWAS in the PROSPER/PHASE study we confirm the previously found genetic associations with LDL-cholesterol levels. With this proof-of-principle study we show that the PROSPER/PHASE study can be used to investigate genetic associations in a similar way to population based studies. The next step of the PROSPER/PHASE study is to identify the genetic variation responsible for the variation in LDL-cholesterol lowering in response to statin treatment in collaboration with other large trials.

Published
2011

30. Stratification by smoking status reveals an association of CHRNA5-A3-B4 genotype with body mass index in never smokers

Author

Taylor, A.E., Morris, R.W., Fluharty, M.E., Björngaard, J.H., Asvold, B.A., Gabrielsen, M.E., Campbell, A., Marioni, R.E., Kumari, M., Hällfors, J., Mannisto, S., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Husemoen, L.L.N., Skaaby, T., Ahluwalia, T.V.S., Treur, J.L., Willemsen, G., Dale, C.E., Wannamethee, S.G., Lahti, J., Palotie, A., Raikkonen, K., Kisialiou, A., McConnachie, A., Padmanabhan, S., Wong, A., Dalgard, C., Paternoster, L., Ben-Shlomo, Y., Tyrrell, J., Horwood, J., Fergusson, D.M., Kennedy, M.A., Frayling, T., Nohr, E.A., Christiansen, L., Kyvik, K.O., Kuh, D., Watt, G., Eriksson, J., Whincup, P.H., Vink, J.M., Boomsma, D.I., Smith, G.D., Lawlor, D.A., Linneberg, A., Ford, I., Jukema, J.W., Power, C., Hypponen, E., Jarvelin, M.R., Preisig, M., Borodulin, K., Kaprio, J., Kivimäki, M., Smith, B.H., Hayward, C., Romundstad, P.R., Sorensen, T.I.A., Munafò, M.R., Sattar, N., Taylor, A.E., Morris, R.W., Fluharty, M.E., Björngaard, J.H., Asvold, B.A., Gabrielsen, M.E., Campbell, A., Marioni, R.E., Kumari, M., Hällfors, J., Mannisto, S., Marques-Vidal, P., Kaakinen, M., Cavadino, A., Postmus, I., Husemoen, L.L.N., Skaaby, T., Ahluwalia, T.V.S., Treur, J.L., Willemsen, G., Dale, C.E., Wannamethee, S.G., Lahti, J., Palotie, A., Raikkonen, K., Kisialiou, A., McConnachie, A., Padmanabhan, S., Wong, A., Dalgard, C., Paternoster, L., Ben-Shlomo, Y., Tyrrell, J., Horwood, J., Fergusson, D.M., Kennedy, M.A., Frayling, T., Nohr, E.A., Christiansen, L., Kyvik, K.O., Kuh, D., Watt, G., Eriksson, J., Whincup, P.H., Vink, J.M., Boomsma, D.I., Smith, G.D., Lawlor, D.A., Linneberg, A., Ford, I., Jukema, J.W., Power, C., Hypponen, E., Jarvelin, M.R., Preisig, M., Borodulin, K., Kaprio, J., Kivimäki, M., Smith, B.H., Hayward, C., Romundstad, P.R., Sorensen, T.I.A., Munafò, M.R., and Sattar, N.

Abstract

Contains fulltext : 155640.PDF (publisher's version ) (Open Access), We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00x10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI + 0.18 to + 0.52, P = 6.38x10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95x10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.

Published
2014

31. Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins

Author

Postmus, I, Trompet, S, Deshmukh, HA, Barnes, MR, Li, XH, Warren, HR, Chasman, DI, Zhou, KX, Arsenault, BJ, Donnelly, LA, Wiggins, KL, Avery, CL, Griffin, P, Feng, QP, Taylor, KD, Li, G, Evans, DS, Smith, AV, de Keyser, Toke, Johnson, AD, de Craen, AJM, Stott, DJ, Buckley, BM, Ford, I, Westendorp, RGJ, Slagboom, PE (Eline), Sattar, N, Munroe, PB, Sever, P, Poulter, N, Stanton, A, Shields, DC, O'Brien, E, Shaw-Hawkins, S, Chen, YDI, Nickerson, DA, Smith, JD, Dube, MP, Boekholdt, SM, Hovingh, GK, Kastelein, JJP, Mckeigue, PM, Betteridge, J, Neil, A, Durrington, PN, Doney, A, Carr, F, Morris, A, McCarthy, MI, Groop, L, Ahlqvist, E, Bis, JC, Rice, K, Smith, NL, Lumley, T, Whitsel, EA, Sturmer, T, Boerwinkle, E, Ngwa, JS, O'Donnell, CJ, Vasan, RS, Wei, WQ, Wilke, RA, Liu, CT, Sun, FG, Guo, XQ, Heckbert, SR, Post, W, Sotoodehnia, N, Arnold, AM, Stafford, JM, Ding, JZ (Jing Zhong), Herrington, DM, Kritchevsky, SB, Eiriksdottir, G, Launer, LJ (Lenore), Harris, TB, Chu, AY, Giulianini, F, MacFadyen, JG, Barratt, BJ, Nyberg, F, Stricker, Bruno, Uitterlinden, André, Hofman, Bert, Rivadeneira, Fernando, Emilsson, V, Franco Duran, OH, Ridker, PM, Gudnason, V, Liu, YM, Denny, JC, Ballantyne, CM, Rotter, JI, Cupples, LA, Psaty, BM, Palmer, CNA, Tardif, JC, Colhoun, HM, Hitman, G, Krauss, RM, Jukema, JW, Caulfield, MJ, Postmus, I, Trompet, S, Deshmukh, HA, Barnes, MR, Li, XH, Warren, HR, Chasman, DI, Zhou, KX, Arsenault, BJ, Donnelly, LA, Wiggins, KL, Avery, CL, Griffin, P, Feng, QP, Taylor, KD, Li, G, Evans, DS, Smith, AV, de Keyser, Toke, Johnson, AD, de Craen, AJM, Stott, DJ, Buckley, BM, Ford, I, Westendorp, RGJ, Slagboom, PE (Eline), Sattar, N, Munroe, PB, Sever, P, Poulter, N, Stanton, A, Shields, DC, O'Brien, E, Shaw-Hawkins, S, Chen, YDI, Nickerson, DA, Smith, JD, Dube, MP, Boekholdt, SM, Hovingh, GK, Kastelein, JJP, Mckeigue, PM, Betteridge, J, Neil, A, Durrington, PN, Doney, A, Carr, F, Morris, A, McCarthy, MI, Groop, L, Ahlqvist, E, Bis, JC, Rice, K, Smith, NL, Lumley, T, Whitsel, EA, Sturmer, T, Boerwinkle, E, Ngwa, JS, O'Donnell, CJ, Vasan, RS, Wei, WQ, Wilke, RA, Liu, CT, Sun, FG, Guo, XQ, Heckbert, SR, Post, W, Sotoodehnia, N, Arnold, AM, Stafford, JM, Ding, JZ (Jing Zhong), Herrington, DM, Kritchevsky, SB, Eiriksdottir, G, Launer, LJ (Lenore), Harris, TB, Chu, AY, Giulianini, F, MacFadyen, JG, Barratt, BJ, Nyberg, F, Stricker, Bruno, Uitterlinden, André, Hofman, Bert, Rivadeneira, Fernando, Emilsson, V, Franco Duran, OH, Ridker, PM, Gudnason, V, Liu, YM, Denny, JC, Ballantyne, CM, Rotter, JI, Cupples, LA, Psaty, BM, Palmer, CNA, Tardif, JC, Colhoun, HM, Hitman, G, Krauss, RM, Jukema, JW, and Caulfield, MJ

Abstract

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

Published
2014

34. Mineral and bone disease - CKD 1-5

Author

Loh, Z. Y., primary, Yap, C. W., additional, Anantharaman, V., additional, How, P., additional, Hirata, M., additional, Aizawa, K., additional, Yogo, K., additional, Tashiro, Y., additional, Takeda, S., additional, Endo, K., additional, Fukagawa, M., additional, Serizawa, K.-I., additional, Fujii, H., additional, Kono, K., additional, Nakai, K., additional, Goto, S., additional, Shinohara, M., additional, Kitazawa, R., additional, Kitazawa, S., additional, Nishi, S., additional, Oruc, A., additional, Korkmaz, S., additional, Bal, O., additional, Yilmaztepe Oral, A., additional, Ersoy, A., additional, Gullulu, M., additional, Ketteler, M., additional, Martin, K., additional, Amdahl, M., additional, Cozzolino, M., additional, Goldsmith, D., additional, Sharma, A., additional, Khan, S., additional, Chitalia, N., additional, Afzali, B., additional, Edozie, F., additional, Manghat, P., additional, Wierzbicki, A., additional, Hampson, G., additional, Corradini, M., additional, Iannuzzella, F., additional, Manenti, L., additional, Ciarrocchi, A., additional, Albertazzi, L., additional, Somenzi, D., additional, Pasquali, S., additional, Calabria Baxmann, A., additional, Barcellos Menon, V., additional, Froeder, L., additional, Medina-Pestana, J. O., additional, Barbosa Carvalho, A., additional, Pfeferman Heilberg, I., additional, Sola, L., additional, De Souza, N., additional, Flores, J., additional, Perico, N., additional, Yuste, C., additional, Garcia DE Vinuesa, M. S., additional, Luno, J., additional, Goicoechea, M. A., additional, Barraca, D., additional, Panizo, N., additional, Quiroga, B., additional, Kim, S. M., additional, Kwon, S. K., additional, Kim, H.-Y., additional, Cournoyer, S., additional, Bell, R., additional, Berbiche, D., additional, Menard, L., additional, Viaene, L., additional, Evenepoel, P., additional, Meijers, B., additional, Overbergh, L., additional, Mathieu, C., additional, Pasquali, M., additional, Rotondi, S., additional, Conte, C., additional, Pirro, G., additional, Mazzaferro, S., additional, Frasheri, A., additional, Marangella, M., additional, Tartaglione, L., additional, Park, J.-S., additional, Koo, T. Y., additional, Kim, G.-H., additional, Kang, C. M., additional, Lee, C.-H., additional, Hiemstra, T. F., additional, Casian, A., additional, Boraks, P., additional, Jayne, D., additional, Schoenmakers, I., additional, Schmiedeke, B., additional, Niemann, M., additional, Schmiedeke, D., additional, Davydenko, I., additional, Emmert, A., additional, Pilz, S., additional, Obermayer-Pietsch, B., additional, Weidemann, F., additional, Breunig, F., additional, Wanner, C., additional, Drechsler, C., additional, Shiizaki, K., additional, Ito, C., additional, Onishi, A., additional, Nakazawa, E., additional, Ogura, M., additional, Kusano, E., additional, Ermolenko, V., additional, Mikhaylova, N., additional, Vartanjan, K., additional, Levchuk, D., additional, Dobrina, E., additional, Capusa, C., additional, Stancu, S., additional, Maria, D., additional, Vladu, I., additional, Barsan, L., additional, Garneata, L., additional, Mota, E., additional, Mircescu, G., additional, Ilyes, A., additional, Dorobantu, N., additional, Petrescu, L., additional, Martinez-Gallardo, R., additional, Ferreira, F., additional, Garcia-Pino, G., additional, Luna, E., additional, Caravaca, F., additional, De Jager, D. J., additional, Grootendorst, D. C., additional, Postmus, I., additional, De Goeij, M. C. M., additional, Boeschoten, E. W., additional, Sijpkens, Y. W. J., additional, Dekker, F. W., additional, Halbesma, N., additional, Wuthrich, R. P., additional, Covic, A., additional, Gaillard, S., additional, Rakov, V., additional, Louvet, L., additional, Buchel, J., additional, Steppan, S., additional, Passlick-Deetjen, J., additional, Massy, Z. A., additional, Akalin, N., additional, Altiparmak, M. R., additional, Trabulus, S., additional, Yalin, A. S., additional, Seyahi, N., additional, Ataman, R., additional, Serdengecti, K., additional, Donate-Correa, J., additional, Martinez-Sanz, R., additional, Muros-de-Fuentes, M., additional, Garcia, J., additional, Garcia, P., additional, Cazana, V., additional, Mora-Fernandez, C., additional, Navarro-Gonzalez, J. F., additional, Berutti, S., additional, Marranca, D., additional, Soragna, G., additional, Erroi, L., additional, Migliardi, M., additional, Belloni, L., additional, Parmeggiani, M., additional, Camerini, C., additional, Pezzotta, M., additional, Zani, R., additional, Movilli, E., additional, Cancarini, G., additional, Anwar, S., additional, Pruthi, R., additional, Kenchayikoppad, S., additional, Reyes, J., additional, Dasilva, I., additional, Furlano, M., additional, Calero, F., additional, Montanes, R., additional, Ayasreh, N., additional, Del Pozo, M., additional, Estorch, M., additional, Rousaud, F., additional, Ballarin, J. A., additional, Bover, J., additional, Resende, A., additional, Dias, C. B., additional, Dos Reis, L., additional, Jorgetti, V., additional, Woronik, V., additional, Panuccio, V., additional, Enia, G., additional, Tripepi, R., additional, Cutrupi, S., additional, Pizzini, P., additional, Aliotta, R., additional, Zoccali, C., additional, Yildiz, I., additional, Sagliker, Y., additional, Demirhan, O., additional, Tunc, E., additional, Inandiklioglu, N., additional, Tasdemir, D., additional, Acharya, V., additional, Zhang, L., additional, Golea, O., additional, Sabry, A., additional, Ookalkar, D., additional, Radulescu, D., additional, Ben Maiz, H., additional, Chen, C. H., additional, Rome, J. P., additional, Benzegoutta, M., additional, Paylar, N., additional, Eyupoglu, K., additional, Karatepe, E., additional, Esenturk, M., additional, Yavascan, O., additional, Grzegorzevska, A., additional, Shilo, V., additional, M-Mazdeh, M., additional, Francesco, R. C., additional, Gouda, Z., additional, Adam, S. M., additional, Emir, I., additional, Ocal, F., additional, Usta, E., additional, Kiralp, N., additional, Sagliker, C., additional, S Ozkaynak, P., additional, Sagliker, H. S., additional, Bassuoni, M., additional, El-Wakil, H. S., additional, Akar, H., additional, Yenicerioglu, Y., additional, Kose, E., additional, and Sekin, O., additional

Published
2012
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36. Genome-wide association meta-analysis of human longevity identifies a novel locus conferring survival beyond 90 years of age

Author

Doris Lechner, Miriam Capri, Stefan Böhringer, Stefan Schreiber, Gonneke Willemsen, Paolo Garagnani, Irene Maeve Rea, Andres Metspalu, Palmi V. Jonsson, Thomas B. L. Kirkwood, Lene Christiansen, Fernando Rivadeneira, Giuseppina Rose, J. Wouter Jukema, Serena Dato, Owen A. Ross, Almut Nebel, Cornelia M. van Duijn, Gary Saunders, Bernard Jeune, David J. Stott, Jeanine J. Houwing-Duistermaat, A. Murphy, Anton J. M. de Craen, Friederike Flachsbart, Karen Andersen-Ranberg, Albert Hofman, Ian Ford, Ellen A. Nohr, Giuseppe Passarino, Krista Fischer, Elisa Cevenini, Carmen Martin-Ruiz, Jutta Gampe, Iris Postmus, Christopher P. Nelson, Stefano Salvioli, Alberto Montesanto, Mark Lathrop, Marianne Nygaard, Marie E. Breen, Jennifer Harrow, Hae-Won Uh, Erik B. van den Akker, Thorkild I. A. Sørensen, André G. Uitterlinden, Alexander Viktorin, Bastiaan T. Heijmans, Susan E. McNerlan, Quinta Helmer, Naveed Sattar, Claudio Franceschi, Eco J. C. de Geus, E. Mihailov, Jouke-Jan Hottenga, Qihua Tan, Kari Stefansson, Yoichiro Kamatani, Paolina Crocco, Henning Tiemeier, Stella Trompet, Patrik K. E. Magnusson, Marian Beekman, Riin Tamm, Amke Caliebe, Maris Alver, Femke-Anouska Heinsen, Pilar Galan, Daníel F. Guðbjartsson, Joris Deelen, Linda Broer, Ruud van der Breggen, Kristin L. Ayers, Anna M. Bennet, Dorret I. Boomsma, P. Eline Slagboom, Kaare Christensen, Diana van Heemst, Joanna Collerton, Karen Davies, Rudi G. J. Westendorp, Hélène Blanché, Lavinia Paternoster, Nilesh J. Samani, Hreinn Stefansson, Simon P. Mooijaart, Heather J. Cordell, Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), LeidenUniversity Medical Centre, Department of Epidemiology, The Netherlands Cancer Institute, Institute of Genetic Medicine, Newcastle University [Newcastle], National Institute of Public Health, University of Southern Denmark (SDU), Department of Clinical Genetics, Odense University Hospital, Fondation Jean Dausset - Centre d’Étude du Polymorphisme Humain, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], University of Tartu, Institute of Molecular and Cell Biology, Department of Gerontology and Geriatrics, Leiden University Medical Center (LUMC), deCODE genetics [Reykjavik], Christian-Albrechts University of Kiel, University of Calabria, Delft University of Technology (TU Delft), Department of Cardiovascular Sciences, Université Catholique de Louvain = Catholic University of Louvain (UCL), University Hospitals Leicester, Genome Campus, The Wellcome Trust Sanger Institute [Cambridge], School of Medicine, Dentistry and Biomedical Sciences [Belfast], Queen's University [Belfast] (QUB), University of Iowa [Iowa City], DIMES: Department of Experimental, Diagnostic and Specialty Medicine, Bologna University Hospital, Institute for Ageing and Health, University of Glasgow, Max Planck Institute for Demographic Research (MPIDR), Max-Planck-Gesellschaft, Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), EMGO Institute for Health and Care Research, VU University Amsterdam Medical Center, Landspitali National University Hospital of Iceland, University of Iceland, McGill University = Université McGill [Montréal, Canada], Genome Quebec Innovation Centre, Institut de Génomique, Belfast Health and Social Care Trust, Estonian Biocentre, Partenaires INRAE, Aarhus University [Aarhus], School of Social and Community Medicine, Erasmus University Rotterdam, Mayo Clinic, BHF Glasgow Cardiovascular Research Centre, University Medical Center Schleswig-Holstein, Institute of Cardiovascular and Medical Sciences, Sophia Children's Hospital, Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Augustinus Foundation, Avera Institute for Human Genetics (AIHG), AXA Research Fund, Belfast City Hospital Trust Fund, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI -NL) [184.021.007], Biotechnology and Biological Sciences Research Council (BBSRC), Bristol-Myers Squibb, Center for Inherited Disease Research (CIDR), Centre for Medical Systems Biology (CMSB), CERA Foundation, Commissariat a L'Energie Atomique (CEA)-Centre National de Genotypage (CNG), Danish Agency for Science, Technology and Innovation (DASTI)/The Danish Council for Independent Research (DCIR) [11-107308], Danish National Research Foundation (DNRF), Department of Health and Social Services (Northern Ireland), DFG-Cluster of Excellence 'Inflammation at Interfaces', Dunhill Medical Trust [R124/0509], Egmont Foundation, Estonian Science Foundation [7859], Estonian Government [SF0180142s08], European Research Council (ERC) [230374], European Science Foundation (ESF) [EU/QLRT-2001-01254], European Union [FP5-QLK6-CY-2001-00128, FP6-LIFESCIHEALTH-36894, FP6-LSH M-CT-2004-503270, FP7-HEALTH-2007-B-223004, FP7-HEALTH-F4-2007-201413, FP7-HEALTH-F4-2008-202047, FP7-HEALTH-2009-single-stage-242244, FP7-HEALTH-2010-two-stage-259679], Fondation Caisse d'Epargne Rhone-Alpes Lyon CERAL, Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health (NIMH) [MH081802], GenomEUtwin [EU/QLRT-2001-01254, QLG2-CT-2002-01254], Guy's & St Thomas' NHS Foundation Trust, Health Foundation, Heart and Lung foundation [20070481], Innovation-Oriented Research Program on Genomics (SenterNovem) [IGE05007], Institut National de la Recherche Agronomique (INRA), Institut National de la Sante et de la Recherche Medicale (INSERM), King's College London, Medical Research Council (MRC) [G0500997, G0601333], Ministere de l'Enseignement superieur et de la Recherche (MESR), National Institutes of Health (NIH)/National Institute of Aging (NIA) [P01AG08761, R01D0042157-01A, U01DK066134], National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre, NBIC BioAssist [NWO-NBIC/BioAssist/RK/2008.024], Netherlands Consortium for Healthy Ageing (NCHA) [050-060-810], Netherlands Genomics Initiative (NGI), Netherlands Heart Foundation (NHF) [2001 D 032], Netherlands Organization for Scientific Research (NWO, MagW/ZonMW) [904-61-090, 904-61-193, 480-04-004, 400-05-717, Spinozapremie 56-464-14192, 175.010.2005.011, 911-03-012, 985-10-002, Addiction-31160008, Middelg-root-911-09-032], Netspar - Living longer for a good health, NHS North of Tyne (Newcastle Primary Care Trust), Pharmacy Foundation, Regione Autonoma della Sardegna, Rutgers University Cell and DNA Repository [NIMH U24 MH068457-06], Swedish Research Council [M-2005-1112], Tampere University Hospital and Academy of Finland, Danish Interdisciplinary Research Council, Health Foundation (Helsefonden), Ministry for Higher Education, National Program for Research Infrastructure [09-063256], March of Dimes Birth Defects Foundation, Swedish Foundation for Strategic Research (SSF), Unilever Discover Colworth, Universite Paris 13, University of Tartu [SP1GVAR-ENG], Velux Foundation, VU University's Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA), Wellcome Trust [084762, 085475, 087436], IDEAL [FP7-HEALTH-2010-two-stage-259679], Research and Education into Ageing-0153, European Regional Development Fund, Deelen J, Beekman M, Uh HW, Broer L, Ayers KL, Tan Q, Kamatani Y, Bennet AM, Tamm R, Trompet S, Guðbjartsson DF, Flachsbart F, Rose G, Viktorin A, Fischer K, Nygaard M, Cordell HJ, Crocco P, van den Akker EB, Böhringer S, Helmer Q, Nelson CP, Saunders GI, Alver M, Andersen-Ranberg K, Breen ME, van der Breggen R, Caliebe A, Capri M, Cevenini E, Collerton JC, Dato S, Davies K, Ford I, Gampe J, Garagnani P, de Geus EJ, Harrow J, van Heemst D, Heijmans BT, Heinsen FA, Hottenga JJ, Hofman A, Jeune B, Jonsson PV, Lathrop M, Lechner D, Martin-Ruiz C, McNerlan SE, Mihailov E, Montesanto A, Mooijaart SP, Murphy A, Nohr EA, Paternoster L, Postmus I, Rivadeneira F, Ross OA, Salvioli S, Sattar N, Schreiber S, Stefánsson H, Stott DJ, Tiemeier H, Uitterlinden AG, Westendorp RG, Willemsen G, Samani NJ, Galan P, Sørensen TI, Boomsma DI, Jukema JW, Rea IM, Passarino G, de Craen AJ, Christensen K, Nebel A, Stefánsson K, Metspalu A, Magnusson P, Blanché H, Christiansen L, Kirkwood TB, van Duijn CM, Franceschi C, Houwing-Duistermaat JJ, Slagboom PE., Leiden Univ, Dept Mol Epidemiol, NL-2300 RC Leiden, Netherlands [ 2 ] Leiden Univ, Netherlands Consortium Healthy Ageing, NL-2300 RC Leiden, Netherlands [ 3 ] Leiden Univ, Dept Med Stat & Bioinformat, NL-2300 RC Leiden, Netherlands [ 4 ] Leiden Univ, Dept Cardiol, NL-2300 RC Leiden, Netherlands [ 5 ] Leiden Univ, Dept Gerontol & Geriatr, NL-2300 RC Leiden, Netherlands [ 6 ] Erasmus MC, Dept Epidemiol, NL-3000 CA Rotterdam, Netherlands [ 7 ] Erasmus MC, Dept Internal Med, NL-3000 CA Rotterdam, Netherlands [ 8 ] Newcastle Univ, Int Ctr Life, Inst Med Genet, Newcastle Upon Tyne NE1 3BZ, Tyne & Wear, England [ 9 ] Univ So Denmark, Inst Publ Hlth, DK-5000 Odense C, Denmark [ 10 ] Univ So Denmark, Inst Clin Res, Dept Gynecol & Obstet, DK-5000 Odense C, Denmark [ 11 ] Odense Univ Hosp, Dept Clin Genet, DK-5000 Odense C, Denmark [ 12 ] Odense Univ Hosp, Clin Biochem & Pharmacol, DK-5000 Odense C, Denmark [ 13 ] Fdn Jean Dausset CEPH, F-75010 Paris, France [ 14 ] Karolinska Inst, Dept Med Epidemiol & Biostat, SE-17177 Stockholm, Sweden [ 15 ] Univ Tartu, Estonian Genome Ctr, Tartu 51010, Estonia [ 16 ] Univ Tartu, Inst Mol & Cell Biol, EE-51010 Tartu, Estonia [ 17 ] deCODE Genet, Populat Gen, IS-101 Reykjavik, Iceland [ 18 ] Univ Kiel, Inst Clin Mol Biol, D-24105 Kiel, Germany [ 19 ] Univ Kiel, Inst Med Informat & Stat, D-24105 Kiel, Germany [ 20 ] Univ Calabria, Dept Biol Ecol & Earth Sci, I-87036 Arcavacata Di Rende, Italy [ 21 ] Delft Univ Technol, Delft Bioinformat Lab, NL-2600 GA Delft, Netherlands [ 22 ] Univ Leicester, Dept Cardiovasc Sci, Leicester LE3 9QP, Leics, England [ 23 ] Glenfield Hosp, Cardiovasc Biomed Res Unit, Natl Inst Hlth Res, Leicester LE3 9QP, Leics, England [ 24 ] Wellcome Trust Sanger Inst, Wellcome Trust Genome Campus, Cambridge CB10 1SA, England [ 25 ] Queens Univ Belfast, Sch Med Dent & Biomed Sci, Belfast BT9 7BL, Antrim, North Ireland [ 26 ] Univ Iowa, Dept Psychiat, Iowa City, IA 52242 USA [ 27 ] Univ Bologna, Dept Expt Diagnost & Specialty Med, I-40126 Bologna, Italy [ 28 ] Univ Bologna, Interdepartmental Ctr L Galvani, I-40126 Bologna, Italy [ 29 ] Newcastle Univ, Inst Ageing & Hlth, Newcastle Upon Tyne NE4 5PL, Tyne & Wear, England [ 30 ] Univ Glasgow, Robertson Ctr Biostat, Glasgow G12 8QQ, Lanark, Scotland [ 31 ] Univ Glasgow, Inst Cardiovasc & Med Sci, Glasgow G12 8QQ, Lanark, Scotland [ 32 ] Max Planck Inst Demograf Forsch, Lab Stat Demog, D-18057 Rostock, Germany [ 33 ] Vrije Univ Amsterdam, Dept Biol Psychol, NL-1081 BT Amsterdam, Netherlands [ 34 ] Vrije Univ Amsterdam Med Ctr, EMGO Inst Hlth & Care Res, NL-1081 BT Amsterdam, Netherlands [ 35 ] Landspitali Univ Hosp, IS-101 Reykjavik, Iceland [ 36 ] Univ Iceland, Fac Med, IS-101 Reykjavik, Iceland [ 37 ] CEA, Inst Genom, F-91057 Evry, France [ 38 ] McGill Univ, Montreal, PQ H3G 1A4, Canada [ 39 ] Genome Quebec Innovat Ctr, Montreal, PQ H3G 1A4, Canada [ 40 ] Belfast Hlth & Social Care Trust, Cytogenet Lab, Belfast BT8 8BH, Antrim, North Ireland [ 41 ] Estonian Bioctr, EE-51010 Tartu, Estonia [ 42 ] Aarhus Univ, Dept Publ Hlth, Epidemiol Sect, DK-8000 Aarhus C, Denmark [ 43 ] Univ Bristol, Sch Social & Community Med, MRC Ctr Causal Anal Translat Epidemiol, Bristol BS8 2BN, Avon, England [ 44 ] Mayo Clin, Dept Neurosci, Jacksonville, FL 32224 USA [ 45 ] Univ Glasgow, Fac Med, BHF Glasgow Cardiovasc Res Ctr, Glasgow G12 8TA, Lanark, Scotland [ 46 ] Univ Kiel, PopGen Biobank, D-24105 Kiel, Germany [ 47 ] Univ Hosp Schleswig Holstein, D-24105 Kiel, Germany [ 48 ] Sophia Childrens Univ Hosp, Erasmus Med Ctr, Dept Child & Adolescent Psychiat, NL-3000 CA Rotterdam, Netherlands [ 49 ] Univ Paris 04, UREN, U557, INSERM, F-93017 Bobigny, France [ 50 ] U1125 Inra, F-93017 Bobigny, France [ 51 ] Cnam, F-93017 Bobigny, France [ 52 ] Univ Paris 13, CRNH IdF, F-93017 Bobigny, France [ 53 ] Univ Copenhagen, Fac Hlth & Med Sci, Sect Metab Genet, Novo Nordisk Fdn Ctr, DK-2200 Copenhagen N, Denmark [ 54 ] Inst Prevent Med, DK-2000 Copenhagen, Denmark [ 55 ] Frederiksberg Univ Hosp, DK-2000 Copenhagen, Denmark [ 56 ] Interuniv Cardiol Inst Netherlands, NL-3501 DG Utrecht, Netherlands [ 57 ] Bellaria Hosp, IRCCS Inst Neurol Sci, I-40139 Bologna, Italy [ 58 ] CNR, ISOF, I-40129 Bologna, Italy, Epidemiology, Surgery, Internal Medicine, Child and Adolescent Psychiatry / Psychology, ProdInra, Migration, Vrije Universiteit Amsterdam [Amsterdam] (VU), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), VU University Amsterdam, Biological Psychology, and EMGO+ - Lifestyle, Overweight and Diabetes

Subjects
Male, Netherlands Twin Register (NTR), Disease/genetics, Lífslíkur, Longevity/genetics, [SDV.MHEP.PHY] Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Genetic Linkage, Genome-wide association study, 0302 clinical medicine, Prospective Studies, Genetics (clinical), Genetics, Aged, 80 and over, 0303 health sciences, education.field_of_study, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Association Studies Articles, Age Factors, Chromosome Mapping, Genetic Loci/physiology, General Medicine, 3. Good health, Europe, Phenotype, Cardiovascular Diseases, Hypertension, Chromosomes, Human, Pair 5, Female, Human Longevity, genetics, meta-analysis, Aging/genetics, Cardiology and Cardiovascular Medicine, HUMAN AGING, Longevity, European Continental Ancestry Group, Population, HUMAN GENETICS, Single-nucleotide polymorphism, Locus (genetics), Biology, FAMILIAL LONGEVITY, White People, 03 medical and health sciences, Gene mapping, SDG 3 - Good Health and Well-being, Cardiovascular Diseases/genetics, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Humans, Allele, education, Molecular Biology, Aged, 030304 developmental biology, Genetic association, Öldrun, Genome, Human, Arfgengi, Minor allele frequency, Ageing, Genetic Loci, Chromosomes, Human, Pair 19, Hypertension/genetics, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. The genetic contribution to the variation in human lifespan is ∼ 25%. Despite the large number of identified disease-susceptibility loci, it is not known which loci influence population mortality. We performed a genome-wide association meta-analysis of 7729 long-lived individuals of European descent (≥ 85 years) and 16 121 younger controls (

Published
2014

37. A potential harmful effect of dexamethasone in non-severe COVID-19: results from the COPPER-pilot study.

Author

Kocks J, Kerkhof M, Scherpenisse J, van de Maat A, van Geer-Postmus I, le Rütte T, Schaart J, Gans ROB, and Kerstjens HAM

Abstract

This study suggests caution when prescribing systemic corticosteroids to patients with #COVID19 who show mild-to-moderate pulmonary symptoms because a harmful effect cannot be excluded https://bit.ly/3P4nOjQ., Competing Interests: Conflict of interest: J. Kocks, M. Kerkhof, A. van de Maat, I. van Geer-Postmus and T. le Rütte were employed by the General Practitioners Research Institute (GPRI) at the time of the study. In the past 3 years (2019–2022), the GPRI conducted investigator- and sponsor-initiated research funded by noncommercial organisations, academic institutes and pharmaceutical companies (including AstraZeneca, Boehringer Ingelheim, Chiesi, GSK, Mundipharma, Novartis and Teva). H. Kerstjens reports no conflicts of interest for this study; unrelated to this study, his institution has received funding for his studies and payments for his consultancy from AstraZeneca, Boehringer Ingelheim, Chiesi, GSK and Novartis. R. Gans, J. Scherpenisse and J. Schaart report no conflicts of interest for this study., (Copyright ©The authors 2022.)

Published
2022
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38. Factors associated with health status and exacerbations in COPD maintenance therapy with dry powder inhalers.

Author

W H Kocks J, Wouters H, Bosnic-Anticevich S, van Cooten J, Correia de Sousa J, Cvetkovski B, Dekhuijzen R, Dijk L, Dvortsin E, Garcia Pardo M, Gardev A, Gawlik R, van Geer-Postmus I, van der Ham I, Harbers M, de la Hoz A, Janse Y, Kerkhof M, Lavorini F, Maricoto T, Meijer J, Metz B, Price D, Roman-Rodriguez M, Schuttel K, Stoker N, Tsiligianni I, Usmani O, and Leving MT

Subjects
Aged, Cross-Sectional Studies, Dry Powder Inhalers, Female, Health Status, Humans, Male, Asthma drug therapy, Pulmonary Disease, Chronic Obstructive drug therapy
Abstract

The study aimed to determine the associations of Peak Inspiratory Flow (PIF), inhalation technique and adherence with health status and exacerbations in participants with COPD using DPI maintenance therapy. This cross-sectional multi-country observational real-world study included COPD participants aged ≥40 years using a DPI for maintenance therapy. PIF was measured three times with the In-Check DIAL G16: (1) typical PIF at resistance of participant's inhaler, (2) maximal PIF at resistance of participant's inhaler, (3) maximal PIF at low resistance. Suboptimal PIF (sPIF) was defined as PIF lower than required for the device. Participants completed questionnaires on health status (Clinical COPD Questionnaire (CCQ)), adherence (Test of Adherence to Inhalers (TAI)) and exacerbations. Inhalation technique was assessed by standardised evaluation of video recordings. Complete data were available from 1434 participants (50.1% female, mean age 69.2 years). GOLD stage was available for 801 participants: GOLD stage I (23.6%), II (54.9%), III (17.4%) and IV (4.1%)). Of all participants, 29% had a sPIF, and 16% were shown able to generate an optimal PIF but failed to do so. sPIF was significantly associated with worse health status (0.226 (95% CI 0.107-0.346), worse units on CCQ; p = 0.001). The errors 'teeth and lips sealed around mouthpiece', 'breathe in', and 'breathe out calmly after inhalation' were related to health status. Adherence was not associated with health status. After correcting for multiple testing, no significant association was found with moderate or severe exacerbations in the last 12 months. To conclude, sPIF is associated with poorer health status. This study demonstrates the importance of PIF assessment in DPI inhalation therapy. Healthcare professionals should consider selecting appropriate inhalers in cases of sPIF., (© 2022. The Author(s).)

Published
2022
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39. The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction.

Author

Trompet S, Postmus I, Warren HR, Noordam R, Smit RAJ, Theusch E, Li X, Arsenault B, Chasman DI, Hitman GA, Munroe PB, Rotter JI, Psaty BM, Caulfield MJ, Krauss RM, Cupples AL, and Jukema WJ

Abstract

Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction. Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p -values <5.0 × 10 -4 in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI. Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results ( p < 5.0 × 10 -8 ). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis. Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice., Competing Interests: The authors declare that this study received funding from Pfizer USA and Bristol-Myers Squibb USA., (Copyright © 2022 Trompet, Postmus, Warren, Noordam, Smit, Theusch, Li, Arsenault, Chasman, Hitman, Munroe, Rotter, Psaty, Caulfield, Krauss, Cupples and Jukema.)

Published
2022
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40. Design and rationale of a routine clinical care pathway and prospective cohort study in older patients needing intensive treatment.

Author

van Holstein Y, van Deudekom FJ, Trompet S, Postmus I, Uit den Boogaard A, van der Elst MJT, de Glas NA, van Heemst D, Labots G, Altena M, Slingerland M, Liefers GJ, van den Bos F, van der Bol JM, Blauw GJ, Portielje JEA, and Mooijaart SP

Subjects
Aged, Geriatric Assessment, Humans, Netherlands epidemiology, Prospective Studies, Frailty diagnosis, Frailty epidemiology, Frailty therapy, Quality of Life
Abstract

Background: Treatment decisions concerning older patients can be very challenging and individualised treatment plans are often required in this very heterogeneous group. In 2015 we have implemented a routine clinical care pathway for older patients in need of intensive treatment, including a comprehensive geriatric assessment (CGA) that was used to support clinical decision making. An ongoing prospective cohort study, the Triaging Elderly Needing Treatment (TENT) study, has also been initiated in 2016 for participants in this clinical care pathway, to study associations between geriatric characteristics and outcomes of treatment that are relevant to older patients. The aim of this paper is to describe the implementation and rationale of the routine clinical care pathway and design of the TENT study., Methods: A routine clinical care pathway has been designed and implemented in multiple hospitals in the Netherlands. Patients aged ≥70 years who are candidates for intensive treatments, such as chemotherapy, (chemo-)radiation therapy or major surgery, undergo frailty screening based on the Geriatric 8 (G-8) questionnaire and the Six-Item Cognitive Impairment Test (6CIT). If screening reveals potential frailty, a CGA is performed. All patients are invited to participate in the TENT study. Clinical data and blood samples for biomarker studies are collected at baseline. During follow-up, information about treatment complications, hospitalisations, functional decline, quality of life and mortality is collected. The primary outcome is the composite endpoint of functional decline or mortality at 1 year., Discussion: Implementation of a routine clinical care pathway for older patients in need of intensive treatment provides the opportunity to study associations between determinants of frailty and outcomes of treatment. Results of the TENT study will support individualised treatment for future patients., Trial Registration: The study is retrospectively registered at the Netherlands Trial Register (NTR), trial number NL8107 . Date of registration: 22-10-2019.

Published
2021
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41. Statin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study.

Author

Smit RAJ, Trompet S, Leong A, Goodarzi MO, Postmus I, Warren H, Theusch E, Barnes MR, Arsenault BJ, Li X, Feng Q, Chasman DI, Cupples LA, Hitman GA, Krauss RM, Psaty BM, Rotter JI, Cessie SL, Stein CM, and Jukema JW

Subjects
Cholesterol, LDL blood, Cholesterol, LDL drug effects, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 chemically induced, Female, Genome-Wide Association Study methods, Humans, Male, Cholesterol, LDL genetics, Diabetes Mellitus, Type 2 genetics, Genetic Predisposition to Disease genetics, Genetic Variation genetics, Hydroxymethylglutaryl-CoA Reductase Inhibitors adverse effects, Mendelian Randomization Analysis methods
Abstract

It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, n max  = 40,914) and DIAGRAM (n max  = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (r genetic  = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

Published
2020
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42. Association Between Levothyroxine Treatment and Thyroid-Related Symptoms Among Adults Aged 80 Years and Older With Subclinical Hypothyroidism.

Author

Mooijaart SP, Du Puy RS, Stott DJ, Kearney PM, Rodondi N, Westendorp RGJ, den Elzen WPJ, Postmus I, Poortvliet RKE, van Heemst D, van Munster BC, Peeters RP, Ford I, Kean S, Messow CM, Blum MR, Collet TH, Watt T, Dekkers OM, Jukema JW, Smit JWA, Langhorne P, and Gussekloo J

Abstract

Importance: It is unclear whether levothyroxine treatment provides clinically important benefits in adults aged 80 years and older with subclinical hypothyroidism., Objective: To determine the association of levothyroxine treatment for subclinical hypothyroidism with thyroid-related quality of life in adults aged 80 years and older., Design, Setting, and Participants: Prospectively planned combined analysis of data involving community-dwelling adults aged 80 years and older with subclinical hypothyroidism. Data from a randomized clinical trial were combined with a subgroup of participants aged 80 years and older from a second clinical trial. The trials were conducted between April 2013 and May 2018. Final follow-up was May 4, 2018., Exposures: Participants were randomly assigned to receive levothyroxine (n = 112; 52 participants from the first trial and 60 from the second trial) or placebo (n = 139; 53 participants from the first trial and 86 from the second trial)., Main Outcomes and Measures: Co-primary outcomes were Thyroid-Related Quality of Life Patient-Reported Outcome (ThyPRO) questionnaire scores for the domains of hypothyroid symptoms and tiredness at 1 year (range, 0-100; higher scores indicate worse quality of life; minimal clinically important difference, 9)., Results: Of 251 participants (mean age, 85 years; 118 [47%] women), 105 were included from the first clinical trial and 146 were included from the second clinical trial. A total of 212 participants (84%) completed the study. The hypothyroid symptoms score decreased from 21.7 at baseline to 19.3 at 12 months in the levothyroxine group vs from 19.8 at baseline to 17.4 at 12 months in the placebo group (adjusted between-group difference, 1.3 [95% CI, -2.7 to 5.2]; P = .53). The tiredness score increased from 25.5 at baseline to 28.2 at 12 months in the levothyroxine group vs from 25.1 at baseline to 28.7 at 12 months in the placebo group (adjusted between-group difference, -0.1 [95% CI, -4.5 to 4.3]; P = .96). At least 1 adverse event occurred in 33 participants (29.5%) in the levothyroxine group (the most common adverse event was cerebrovascular accident, which occurred in 3 participants [2.2%]) and 40 participants (28.8%) in the placebo group (the most common adverse event was pneumonia, which occurred in 4 [3.6%] participants)., Conclusions and Relevance: In this prospectively planned analysis of data from 2 clinical trials involving adults aged 80 years and older with subclinical hypothyroidism, treatment with levothyroxine, compared with placebo, was not significantly associated with improvement in hypothyroid symptoms or fatigue. These findings do not support routine use of levothyroxine for treatment of subclinical hypothyroidism in adults aged 80 years and older., Trial Registration: ClinicalTrials.gov Identifier: NCT01660126; Netherlands Trial Register: NTR3851.

Published
2019
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43. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Author

Teumer A, Chaker L, Groeneweg S, Li Y, Di Munno C, Barbieri C, Schultheiss UT, Traglia M, Ahluwalia TS, Akiyama M, Appel EVR, Arking DE, Arnold A, Astrup A, Beekman M, Beilby JP, Bekaert S, Boerwinkle E, Brown SJ, De Buyzere M, Campbell PJ, Ceresini G, Cerqueira C, Cucca F, Deary IJ, Deelen J, Eckardt KU, Ekici AB, Eriksson JG, Ferrrucci L, Fiers T, Fiorillo E, Ford I, Fox CS, Fuchsberger C, Galesloot TE, Gieger C, Gögele M, De Grandi A, Grarup N, Greiser KH, Haljas K, Hansen T, Harris SE, van Heemst D, den Heijer M, Hicks AA, den Hollander W, Homuth G, Hui J, Ikram MA, Ittermann T, Jensen RA, Jing J, Jukema JW, Kajantie E, Kamatani Y, Kasbohm E, Kaufman JM, Kiemeney LA, Kloppenburg M, Kronenberg F, Kubo M, Lahti J, Lapauw B, Li S, Liewald DCM, Lim EM, Linneberg A, Marina M, Mascalzoni D, Matsuda K, Medenwald D, Meisinger C, Meulenbelt I, De Meyer T, Meyer Zu Schwabedissen HE, Mikolajczyk R, Moed M, Netea-Maier RT, Nolte IM, Okada Y, Pala M, Pattaro C, Pedersen O, Petersmann A, Porcu E, Postmus I, Pramstaller PP, Psaty BM, Ramos YFM, Rawal R, Redmond P, Richards JB, Rietzschel ER, Rivadeneira F, Roef G, Rotter JI, Sala CF, Schlessinger D, Selvin E, Slagboom PE, Soranzo N, Sørensen TIA, Spector TD, Starr JM, Stott DJ, Taes Y, Taliun D, Tanaka T, Thuesen B, Tiller D, Toniolo D, Uitterlinden AG, Visser WE, Walsh JP, Wilson SG, Wolffenbuttel BHR, Yang Q, Zheng HF, Cappola A, Peeters RP, Naitza S, Völzke H, Sanna S, Köttgen A, Visser TJ, and Medici M

Subjects
2-Aminoadipate Transaminase genetics, Animals, Biological Transport, COS Cells, Chlorocebus aethiops, Genome-Wide Association Study, Humans, Hyperthyroidism genetics, Hyperthyroidism physiopathology, Hypothyroidism genetics, Hypothyroidism physiopathology, Polymorphism, Single Nucleotide, Risk Factors, Sodium-Phosphate Cotransporter Proteins, Type I genetics, Thyroid Gland metabolism, Thyroid Gland physiopathology, Thyroid Hormones metabolism, White People, 2-Aminoadipate Transaminase metabolism, Gene Expression Regulation genetics, Sodium-Phosphate Cotransporter Proteins, Type I metabolism, Thyroid Hormones genetics, Thyrotropin metabolism
Abstract

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets.

Published
2018
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44. Visit-to-visit lipid variability: Clinical significance, effects of lipid-lowering treatment, and (pharmaco) genetics.

Author

Smit RAJ, Jukema JW, Postmus I, Ford I, Slagboom PE, Heijmans BT, Le Cessie S, and Trompet S

Subjects
Acid Sensing Ion Channels genetics, Adaptor Proteins, Signal Transducing, Chemokines, Humans, Intercellular Signaling Peptides and Proteins genetics, Outcome Assessment, Health Care, Ribonuclease P genetics, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Hypolipidemic Agents therapeutic use, Vascular Diseases drug therapy, Vascular Diseases genetics
Abstract

In recent years, visit-to-visit variability of serum lipids has been linked to both clinical outcomes and surrogate markers for vascular disease. In this article, we present an overview of the current evidence connecting this intraindividual variability to these outcome measures, discuss its interplay with lipid-lowering treatment, and describe the literature regarding genetic factors of possible interest. In addition, we undertook an explorative genome-wide association analysis on visit-to-visit variability of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol, examining additive effects in 2530 participants from the placebo arm of the PROspective Study of Pravastatin in the Elderly at Risk trial. While we identified suggestive associations (P < 1 × 10 -6 ) at 3 different loci (KIAA0391, amiloride-sensitive cation channel 1 neuronal [ACCN1], and Dickkopf WNT signaling pathway inhibitor 3 [DKK3]), previously published data from the genome-wide association study literature did not suggest plausible mechanistic pathways. Given the large degree of both clinical and methodological heterogeneity in the literature, additional research is needed to harmonize visit-to-visit variability parameters across studies and to definitively assess the possible role of (pharmaco)genetic factors., (Copyright © 2018 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Published
2018
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46. PCSK9 Loss-of-Function Variants, Low-Density Lipoprotein Cholesterol, and Risk of Coronary Heart Disease and Stroke: Data From 9 Studies of Blacks and Whites.

Author

Kent ST, Rosenson RS, Avery CL, Chen YI, Correa A, Cummings SR, Cupples LA, Cushman M, Evans DS, Gudnason V, Harris TB, Howard G, Irvin MR, Judd SE, Jukema JW, Lange L, Levitan EB, Li X, Liu Y, Post WS, Postmus I, Psaty BM, Rotter JI, Safford MM, Sitlani CM, Smith AV, Stewart JD, Trompet S, Sun F, Vasan RS, Woolley JM, Whitsel EA, Wiggins KL, Wilson JG, and Muntner P

Subjects
Aged, Aged, 80 and over, Cholesterol, LDL blood, Cohort Studies, Coronary Disease pathology, Coronary Disease prevention & control, Female, Genetic Variation, Genotype, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Male, Odds Ratio, Polymorphism, Single Nucleotide, Proportional Hazards Models, Risk Factors, Stroke genetics, Stroke pathology, Black People genetics, Coronary Disease genetics, Proprotein Convertase 9 genetics, White People genetics
Abstract

Background: PCSK9 loss-of-function (LOF) variants allow for the examination of the effects of lifetime reduced low-density lipoprotein cholesterol (LDL-C) on cardiovascular events. We examined the association of PCSK9 LOF variants with LDL-C and incident coronary heart disease and stroke through a meta-analysis of data from 8 observational cohorts and 1 randomized trial of statin therapy., Methods and Results: These 9 studies together included 17 459 blacks with 403 (2.3%) having at least 1 Y142X or C679X variant and 31 306 whites with 955 (3.1%) having at least 1 R46L variant. Unadjusted odds ratios for associations between PCSK9 LOF variants and incident coronary heart disease (851 events in blacks and 2662 events in whites) and stroke (523 events in blacks and 1660 events in whites) were calculated using pooled Mantel-Haenszel estimates with continuity correction factors. Pooling results across studies using fixed-effects inverse-variance-weighted models, PCSK9 LOF variants were associated with 35 mg/dL (95% confidence interval [CI], 32-39) lower LDL-C in blacks and 13 mg/dL (95% CI, 11-16) lower LDL-C in whites. PCSK9 LOF variants were associated with a pooled odds ratio for coronary heart disease of 0.51 (95% CI, 0.28-0.92) in blacks and 0.82 (95% CI, 0.63-1.06) in whites. PCSK9 LOF variants were not associated with incident stroke (odds ratio, 0.84; 95% CI, 0.48-1.47 in blacks and odds ratio, 1.06; 95% CI, 0.80-1.41 in whites)., Conclusions: PCSK9 LOF variants were associated with lower LDL-C and coronary heart disease incidence. PCSK9 LOF variants were not associated with stroke risk., (© 2017 American Heart Association, Inc.)

Published
2017
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47. External validity of randomized controlled trials in older adults, a systematic review.

Author

van Deudekom FJ, Postmus I, van der Ham DJ, Pothof AB, Broekhuizen K, Blauw GJ, and Mooijaart SP

Subjects
Aged, Aged, 80 and over, Aging, Female, Frail Elderly, Humans, Male, Mental Competency, Middle Aged, Physical Fitness, Social Environment, Geriatric Assessment methods, Randomized Controlled Trials as Topic methods
Abstract

Background: To critically assess the external validity of randomized controlled trials (RCTs) it is important to know what older adults have been enrolled in the trials. The aim of this systematic review is to study what proportion of trials specifically designed for older patients report on somatic status, physical and mental functioning, social environment and frailty in the patient characteristics., Methods: PubMed was searched for articles published in 2012 and only RCTs were included. Articles were further excluded if not conducted with humans or only secondary analyses were reported. A random sample of 10% was drawn. The current review analyzed this random sample and further selected trials when the reported mean age was ≥ 60 years. We extracted geriatric assessments from the population descriptives or the in- and exclusion criteria., Results: In total 1396 trials were analyzed and 300 trials included. The median of the reported mean age was 66 (IQR 63-70) and the median percentage of men in the trials was 60 (IQR 45-72). In 34% of the RCTs specifically designed for older patients somatic status, physical and mental functioning, social environment or frailty were reported in the population descriptives or the in- and exclusion criteria. Physical and mental functioning was reported most frequently (22% and 14%). When selecting RCTs on a mean age of 70 or 80 years the report of geriatric assessments in the patient characteristics was 46% and 85% respectively but represent only 5% and 1% of the trials., Conclusion: Somatic status, physical and mental functioning, social environment and frailty are underreported even in RCTs specifically designed for older patients published in 2012. Therefore, it is unclear for clinicians to which older patients the results can be applied. We recommend systematic to transparently report these relevant characteristics of older participants included in RCTs.

Published
2017
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48. Effect of intranasally administered insulin on cerebral blood flow and perfusion; a randomized experiment in young and older adults.

Author

Akintola AA, van Opstal AM, Westendorp RG, Postmus I, van der Grond J, and van Heemst D

Subjects
Administration, Intranasal, Adult, Age Factors, Aged, Brain diagnostic imaging, Female, Humans, Magnetic Resonance Angiography, Male, Middle Aged, Young Adult, Cerebrovascular Circulation drug effects, Hypoglycemic Agents administration & dosage, Insulin administration & dosage
Abstract

Insulin, a vasoactive modulator regulating peripheral and cerebral blood flow, has been consistently linked to aging and longevity. In this proof of principle study, using a randomized, double-blinded, placebo-controlled crossover design, we explored the effects of intranasally administered insulin (40IU) on cerebral blood flow (CBF) and perfusion in older (60-69 years, n=11) and younger (20-26 years, n=8) adults. Changes in CBF through the major cerebropetal arteries were assessed via phase contrast MR-angiography, and regional cortical tissue perfusion via pseudo-continuous arterial spin labelling. Total flow through the major cerebropetal arteries was unchanged in both young and old. In the older participants, intranasal insulin compared to placebo increased perfusion through the occipital gray matter (65.2±11.0 mL/100g/min vs 61.2±10.1 mL/100g/min, P=0.001), and in the thalamus (68.28±6.75 mL/100g/min versus 63.31±6.84 mL/100g/min, P=0.003). Thus, intranasal insulin improved tissue perfusion of the occipital cortical brain region and the thalamus in older adults.

Published
2017
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49. Assessment of causality between serum gamma-glutamyltransferase and type 2 diabetes mellitus using publicly available data: a Mendelian randomization study.

Author

Noordam R, Smit RA, Postmus I, Trompet S, and van Heemst D

Subjects
Bias, Blood Glucose, Genome-Wide Association Study, Glycated Hemoglobin analysis, Humans, Insulin blood, Meta-Analysis as Topic, Observational Studies as Topic, Odds Ratio, Polymorphism, Single Nucleotide, Regression Analysis, Risk Factors, gamma-Glutamyltransferase genetics, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 genetics, Genetic Variation genetics, Mendelian Randomization Analysis, gamma-Glutamyltransferase blood
Abstract

Background: In observational studies, high levels of gamma-glutamyltransferase (GGT) have been associated with a higher risk of type 2 diabetes mellitus (T2D). We aimed to assess whether this association is causal, using Mendelian randomization., Methods: A Mendelian randomization study was conducted using publicly available data from a genome-wide association study (GWAS) on T2D (12 171 cases of T2D and 56 862 controls), and additionally from GWAS on glycaemic traits ( N = 46 186) and HbA1c ( N = 46 368) in nondiabetic participants. Independent genetic variants (26 in total), identified in the largest GGT GWAS comprising studies of European ancestry, were used as genetic instruments. Inverse-variance weighted and MR-Egger regression analyses were used to estimate the effect of the combined genetic instrumental variables on T2D and glycaemic traits and HbA1c., Results: F-statistics of the 26 genetic instrumental variables, as a measure of instrumental strength, ranged from 23.4 ( ATP8B1 ) to 258.3 ( GGT1 ). Using inverse-variance analyses, we found no evidence of an association between the combined genetic instrumental variables for GGT and the risk of T2D, or glucose-, insulin- or HbA1c-levels. More specifically, a 10% higher genetically determined GGT was not associated with a higher risk of T2D (odds ratio: 0.99; 95% confidence interval: 0.95; 1.02). Results were similar for MR-Egger regression analyses, which did not show evidence for directional pleiotropy., Conclusion: The previously observed association between high levels of serum GGT and T2D in observational studies might not be causal. Likely, results from the observational studies can be explained by reverse causality and/or residual confounding., (© The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association)

Published
2016
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50. Meta-analysis of genome-wide association studies of HDL cholesterol response to statins.

Author

Postmus I, Warren HR, Trompet S, Arsenault BJ, Avery CL, Bis JC, Chasman DI, de Keyser CE, Deshmukh HA, Evans DS, Feng Q, Li X, Smit RA, Smith AV, Sun F, Taylor KD, Arnold AM, Barnes MR, Barratt BJ, Betteridge J, Boekholdt SM, Boerwinkle E, Buckley BM, Chen YI, de Craen AJ, Cummings SR, Denny JC, Dubé MP, Durrington PN, Eiriksdottir G, Ford I, Guo X, Harris TB, Heckbert SR, Hofman A, Hovingh GK, Kastelein JJ, Launer LJ, Liu CT, Liu Y, Lumley T, McKeigue PM, Munroe PB, Neil A, Nickerson DA, Nyberg F, O'Brien E, O'Donnell CJ, Post W, Poulter N, Vasan RS, Rice K, Rich SS, Rivadeneira F, Sattar N, Sever P, Shaw-Hawkins S, Shields DC, Slagboom PE, Smith NL, Smith JD, Sotoodehnia N, Stanton A, Stott DJ, Stricker BH, Stürmer T, Uitterlinden AG, Wei WQ, Westendorp RG, Whitsel EA, Wiggins KL, Wilke RA, Ballantyne CM, Colhoun HM, Cupples LA, Franco OH, Gudnason V, Hitman G, Palmer CN, Psaty BM, Ridker PM, Stafford JM, Stein CM, Tardif JC, Caulfield MJ, Jukema JW, Rotter JI, and Krauss RM

Subjects
Cholesterol, HDL drug effects, Cholesterol, HDL metabolism, Female, Genome-Wide Association Study, Humans, Male, Treatment Outcome, White People genetics, Cholesterol Ester Transfer Proteins genetics, Cholesterol, HDL genetics, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Pharmacogenomic Variants, Polymorphism, Single Nucleotide
Abstract

Background: In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation., Methods and Results: We performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p<1×10 -4 from the 16 769 statin-treated participants in the first analysis stage were followed up in an independent group of 10 951 statin-treated individuals, providing a total sample size of 27 720 individuals. The only associations of genome-wide significance (p<5×10 -8 ) were between minor alleles at the CETP locus and greater HDL-C response to statin treatment., Conclusions: Based on results from this study that included a relatively large sample size, we suggest that CETP may be the only detectable locus with common genetic variants that influence HDL-C response to statins substantially in individuals of European descent. Although CETP is known to be associated with HDL-C, we provide evidence that this pharmacogenetic effect is independent of its association with baseline HDL-C levels., Competing Interests: Competing financial interests: BMP serves on the Data and Safety Monitoring Board of a clinical trial funded by the device manufacturer (Zoll LifeCor) and serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. NP and AS received funding from Pfizer for the extended follow-up of the ASCOT UK participants. DIC and PMR received research support for independent genetic analysis in JUPITER from AstraZeneca. FN and BJB have employment, stock and stock options in AstraZeneca, a for-profit company engaged in the discovery, development, manufacture and marketing of proprietary therapeutics such as rosuvastatin, but do not consider that this creates any conflict of interest with the subject-matter of this publication. RMK serves on the Merck Global Atherosclerosis Advisory Board. The remaining authors declare no competing financial interests., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Published
2016
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