Search

Your search keyword '"Baldassarre, Damiano"' showing total 468 results
Start Over Author "Baldassarre, Damiano"
468 results on '"Baldassarre, Damiano"'

2. Causal analysis of plasma IL-8 on carotid intima media thickness, a measure of subclinical atherosclerosis

Author

Velásquez, Ilais Moreno, Malarstig, Anders, Baldassarre, Damiano, Borne, Yan, de Faire, Ulf, Engström, Gunnar, Eriksson, Per, Giral, Philippe, Humphries, Steve E., Kurl, Sudhir, Leander, Karin, Lind, Lars, Lindén, Anders, Orsini, Nicola, Pirro, Matteo, Silveira, Angela, Smit, Andries J., Tremoli, Elena, Veglia, Fabrizio, Strawbridge, Rona J., and Gigante, Bruna

Published
2023
Full Text
View/download PDF

3. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.

Author

Franceschini, Nora, Giambartolomei, Claudia, de Vries, Paul S, Finan, Chris, Bis, Joshua C, Huntley, Rachael P, Lovering, Ruth C, Tajuddin, Salman M, Winkler, Thomas W, Graff, Misa, Kavousi, Maryam, Dale, Caroline, Smith, Albert V, Hofer, Edith, van Leeuwen, Elisabeth M, Nolte, Ilja M, Lu, Lingyi, Scholz, Markus, Sargurupremraj, Muralidharan, Pitkänen, Niina, Franzén, Oscar, Joshi, Peter K, Noordam, Raymond, Marioni, Riccardo E, Hwang, Shih-Jen, Musani, Solomon K, Schminke, Ulf, Palmas, Walter, Isaacs, Aaron, Correa, Adolfo, Zonderman, Alan B, Hofman, Albert, Teumer, Alexander, Cox, Amanda J, Uitterlinden, André G, Wong, Andrew, Smit, Andries J, Newman, Anne B, Britton, Annie, Ruusalepp, Arno, Sennblad, Bengt, Hedblad, Bo, Pasaniuc, Bogdan, Penninx, Brenda W, Langefeld, Carl D, Wassel, Christina L, Tzourio, Christophe, Fava, Cristiano, Baldassarre, Damiano, O'Leary, Daniel H, Teupser, Daniel, Kuh, Diana, Tremoli, Elena, Mannarino, Elmo, Grossi, Enzo, Boerwinkle, Eric, Schadt, Eric E, Ingelsson, Erik, Veglia, Fabrizio, Rivadeneira, Fernando, Beutner, Frank, Chauhan, Ganesh, Heiss, Gerardo, Snieder, Harold, Campbell, Harry, Völzke, Henry, Markus, Hugh S, Deary, Ian J, Jukema, J Wouter, de Graaf, Jacqueline, Price, Jacqueline, Pott, Janne, Hopewell, Jemma C, Liang, Jingjing, Thiery, Joachim, Engmann, Jorgen, Gertow, Karl, Rice, Kenneth, Taylor, Kent D, Dhana, Klodian, Kiemeney, Lambertus ALM, Lind, Lars, Raffield, Laura M, Launer, Lenore J, Holdt, Lesca M, Dörr, Marcus, Dichgans, Martin, Traylor, Matthew, Sitzer, Matthias, Kumari, Meena, Kivimaki, Mika, Nalls, Mike A, Melander, Olle, Raitakari, Olli, Franco, Oscar H, Rueda-Ochoa, Oscar L, Roussos, Panos, Whincup, Peter H, Amouyel, Philippe, and Giral, Philippe

Subjects
MEGASTROKE Consortium, Humans, Coronary Disease, Genetic Predisposition to Disease, Amino Acid Oxidoreductases, Protein-Lysine 6-Oxidase, Risk Factors, Lod Score, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Plaque, Atherosclerotic, Carotid Intima-Media Thickness, ADAMTS9 Protein, Plaque, Atherosclerotic, Polymorphism, Single Nucleotide
Abstract

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Published
2018

4. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Author

Scott, Robert A, Scott, Laura J, Mägi, Reedik, Marullo, Letizia, Gaulton, Kyle J, Kaakinen, Marika, Pervjakova, Natalia, Pers, Tune H, Johnson, Andrew D, Eicher, John D, Jackson, Anne U, Ferreira, Teresa, Lee, Yeji, Ma, Clement, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Qi, Lu, Van Zuydam, Natalie R, Mahajan, Anubha, Chen, Han, Almgren, Peter, Voight, Ben F, Grallert, Harald, Müller-Nurasyid, Martina, Ried, Janina S, Rayner, William N, Robertson, Neil, Karssen, Lennart C, van Leeuwen, Elisabeth M, Willems, Sara M, Fuchsberger, Christian, Kwan, Phoenix, Teslovich, Tanya M, Chanda, Pritam, Li, Man, Lu, Yingchang, Dina, Christian, Thuillier, Dorothee, Yengo, Loic, Jiang, Longda, Sparso, Thomas, Kestler, Hans A, Chheda, Himanshu, Eisele, Lewin, Gustafsson, Stefan, Frånberg, Mattias, Strawbridge, Rona J, Benediktsson, Rafn, Hreidarsson, Astradur B, Kong, Augustine, Sigurðsson, Gunnar, Kerrison, Nicola D, Luan, Jian'an, Liang, Liming, Meitinger, Thomas, Roden, Michael, Thorand, Barbara, Esko, Tõnu, Mihailov, Evelin, Fox, Caroline, Liu, Ching-Ti, Rybin, Denis, Isomaa, Bo, Lyssenko, Valeriya, Tuomi, Tiinamaija, Couper, David J, Pankow, James S, Grarup, Niels, Have, Christian T, Jørgensen, Marit E, Jørgensen, Torben, Linneberg, Allan, Cornelis, Marilyn C, van Dam, Rob M, Hunter, David J, Kraft, Peter, Sun, Qi, Edkins, Sarah, Owen, Katharine R, Perry, John RB, Wood, Andrew R, Zeggini, Eleftheria, Tajes-Fernandes, Juan, Abecasis, Goncalo R, Bonnycastle, Lori L, Chines, Peter S, Stringham, Heather M, Koistinen, Heikki A, Kinnunen, Leena, Sennblad, Bengt, Mühleisen, Thomas W, Nöthen, Markus M, Pechlivanis, Sonali, Baldassarre, Damiano, Gertow, Karl, Humphries, Steve E, Tremoli, Elena, Klopp, Norman, Meyer, Julia, and Steinbach, Gerald

Subjects
Human Genome, Diabetes, Obesity, Genetics, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Diabetes Mellitus, Type 2, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, White People, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Published
2017

5. Determinants of Carotid Wall Echolucency in a Cohort of European High Cardiovascular Risk Subjects: A Cross-Sectional Analysis of IMPROVE Baseline Data

Author

Frigerio, Beatrice, primary, Coggi, Daniela, additional, Bonomi, Alice, additional, Amato, Mauro, additional, Capra, Nicolò, additional, Colombo, Gualtiero I., additional, Sansaro, Daniela, additional, Ravani, Alessio, additional, Savonen, Kai, additional, Giral, Philippe, additional, Gallo, Antonio, additional, Pirro, Matteo, additional, Gigante, Bruna, additional, Eriksson, Per, additional, Strawbridge, Rona J., additional, Mulder, Douwe J., additional, Tremoli, Elena, additional, Veglia, Fabrizio, additional, and Baldassarre, Damiano, additional

Published
2024
Full Text
View/download PDF

7. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals.

Author

Ehret, Georg B, Ferreira, Teresa, Chasman, Daniel I, Jackson, Anne U, Schmidt, Ellen M, Johnson, Toby, Thorleifsson, Gudmar, Luan, Jian'an, Donnelly, Lousie A, Kanoni, Stavroula, Petersen, Ann-Kristin, Pihur, Vasyl, Strawbridge, Rona J, Shungin, Dmitry, Hughes, Maria F, Meirelles, Osorio, Kaakinen, Marika, Bouatia-Naji, Nabila, Kristiansson, Kati, Shah, Sonia, Kleber, Marcus E, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Fava, Cristiano, Eriksson, Niclas, Nolte, Ilja M, Magnusson, Patrik K, Salfati, Elias L, Rallidis, Loukianos S, Theusch, Elizabeth, Smith, Andrew JP, Folkersen, Lasse, Witkowska, Kate, Pers, Tune H, Joehanes, Roby, Kim, Stuart K, Lataniotis, Lazaros, Jansen, Rick, Johnson, Andrew D, Warren, Helen, Kim, Young Jin, Zhao, Wei, Wu, Ying, Tayo, Bamidele O, Bochud, Murielle, CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Absher, Devin, Adair, Linda S, Amin, Najaf, Arking, Dan E, Axelsson, Tomas, Baldassarre, Damiano, Balkau, Beverley, Bandinelli, Stefania, Barnes, Michael R, Barroso, Inês, Bevan, Stephen, Bis, Joshua C, Bjornsdottir, Gyda, Boehnke, Michael, Boerwinkle, Eric, Bonnycastle, Lori L, Boomsma, Dorret I, Bornstein, Stefan R, Brown, Morris J, Burnier, Michel, Cabrera, Claudia P, Chambers, John C, Chang, I-Shou, Cheng, Ching-Yu, Chines, Peter S, Chung, Ren-Hua, Collins, Francis S, Connell, John M, Döring, Angela, Dallongeville, Jean, Danesh, John, de Faire, Ulf, Delgado, Graciela, Dominiczak, Anna F, Doney, Alex SF, Drenos, Fotios, Edkins, Sarah, Eicher, John D, Elosua, Roberto, Enroth, Stefan, Erdmann, Jeanette, Eriksson, Per, Esko, Tonu, Evangelou, Evangelos, Evans, Alun, Fall, Tove, Farrall, Martin, Felix, Janine F, Ferrières, Jean, Ferrucci, Luigi, Fornage, Myriam, and Forrester, Terrence

Subjects
CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Cells, Cultured, Humans, Hypertension, Microarray Analysis, Blood Pressure, Polymorphism, Single Nucleotide, African Continental Ancestry Group, Asian Continental Ancestry Group, Genome-Wide Association Study, Cells, Cultured, Polymorphism, Single Nucleotide, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

Published
2016

8. Sex-specific predictors of PCSK9 levels in a European population: The IMPROVE study

Author

Ferri, Nicola, Ruscica, Massimiliano, Coggi, Daniela, Bonomi, Alice, Amato, Mauro, Frigerio, Beatrice, Sansaro, Daniela, Ravani, Alessio, Veglia, Fabrizio, Capra, Nicolò, Lupo, Maria G., Macchi, Chiara, Castelnuovo, Samuela, Savonen, Kai, Silveira, Angela, Kurl, Sudhir, Giral, Philippe, Pirro, Matteo, Strawbridge, Rona J., Gigante, Bruna, Smit, Andries J., Tremoli, Elena, Colombo, Gualtiero I., and Baldassarre, Damiano

Published
2020
Full Text
View/download PDF

10. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

Author

Gaulton, Kyle J, Ferreira, Teresa, Lee, Yeji, Raimondo, Anne, Mägi, Reedik, Reschen, Michael E, Mahajan, Anubha, Locke, Adam, William Rayner, N, Robertson, Neil, Scott, Robert A, Prokopenko, Inga, Scott, Laura J, Green, Todd, Sparso, Thomas, Thuillier, Dorothee, Yengo, Loic, Grallert, Harald, Wahl, Simone, Frånberg, Mattias, Strawbridge, Rona J, Kestler, Hans, Chheda, Himanshu, Eisele, Lewin, Gustafsson, Stefan, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Qi, Lu, Karssen, Lennart C, van Leeuwen, Elisabeth M, Willems, Sara M, Li, Man, Chen, Han, Fuchsberger, Christian, Kwan, Phoenix, Ma, Clement, Linderman, Michael, Lu, Yingchang, Thomsen, Soren K, Rundle, Jana K, Beer, Nicola L, van de Bunt, Martijn, Chalisey, Anil, Kang, Hyun Min, Voight, Benjamin F, Abecasis, Gonçalo R, Almgren, Peter, Baldassarre, Damiano, Balkau, Beverley, Benediktsson, Rafn, Blüher, Matthias, Boeing, Heiner, Bonnycastle, Lori L, Bottinger, Erwin P, Burtt, Noël P, Carey, Jason, Charpentier, Guillaume, Chines, Peter S, Cornelis, Marilyn C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Doney, Alex SF, Dorkhan, Mozhgan, Edkins, Sarah, Eriksson, Johan G, Esko, Tonu, Eury, Elodie, Fadista, João, Flannick, Jason, Fontanillas, Pierre, Fox, Caroline, Franks, Paul W, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Gottesman, Omri, Grant, George B, Grarup, Niels, Groves, Christopher J, Hassinen, Maija, Have, Christian T, Herder, Christian, Holmen, Oddgeir L, Hreidarsson, Astradur B, Humphries, Steve E, Hunter, David J, Jackson, Anne U, Jonsson, Anna, Jørgensen, Marit E, Jørgensen, Torben, Kao, Wen-Hong L, Kerrison, Nicola D, Kinnunen, Leena, Klopp, Norman, Kong, Augustine, Kovacs, Peter, Kraft, Peter, Kravic, Jasmina, and Langford, Cordelia

Subjects
Biological Sciences, Genetics, Liver Disease, Diabetes, Human Genome, Digestive Diseases, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Binding Sites, Case-Control Studies, Chromatin Immunoprecipitation, Chromosome Mapping, Diabetes Mellitus, Type 2, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Hepatocyte Nuclear Factor 3-beta, Humans, Islets of Langerhans, Liver, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Receptor, Melatonin, MT2, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Published
2015

11. The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

Author

Strawbridge, Rona J., Johnston, Keira J. A., Bailey, Mark E. S., Baldassarre, Damiano, Cullen, Breda, Eriksson, Per, deFaire, Ulf, Ferguson, Amy, Gigante, Bruna, Giral, Philippe, Graham, Nicholas, Hamsten, Anders, Humphries, Steve E., Kurl, Sudhir, Lyall, Donald M., Lyall, Laura M., Pell, Jill P., Pirro, Matteo, Savonen, Kai, Smit, Andries J., Tremoli, Elena, Tomainen, Tomi-Pekka, Veglia, Fabrizio, Ward, Joey, Sennblad, Bengt, and Smith, Daniel J.

Published
2021
Full Text
View/download PDF

12. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

Author

Swerdlow, Daniel I, Preiss, David, Kuchenbaecker, Karoline B, Holmes, Michael V, Engmann, Jorgen EL, Shah, Tina, Sofat, Reecha, Stender, Stefan, Johnson, Paul CD, Scott, Robert A, Leusink, Maarten, Verweij, Niek, Sharp, Stephen J, Guo, Yiran, Giambartolomei, Claudia, Chung, Christina, Peasey, Anne, Amuzu, Antoinette, Li, KaWah, Palmen, Jutta, Howard, Philip, Cooper, Jackie A, Drenos, Fotios, Li, Yun R, Lowe, Gordon, Gallacher, John, Stewart, Marlene CW, Tzoulaki, Ioanna, Buxbaum, Sarah G, van der A, Daphne L, Forouhi, Nita G, Onland-Moret, N Charlotte, van der Schouw, Yvonne T, Schnabel, Renate B, Hubacek, Jaroslav A, Kubinova, Ruzena, Baceviciene, Migle, Tamosiunas, Abdonas, Pajak, Andrzej, Topor-Madry, Romanvan, Stepaniak, Urszula, Malyutina, Sofia, Baldassarre, Damiano, Sennblad, Bengt, Tremoli, Elena, de Faire, Ulf, Veglia, Fabrizio, Ford, Ian, Jukema, J Wouter, Westendorp, Rudi GJ, de Borst, Gert Jan, de Jong, Pim A, Algra, Ale, Spiering, Wilko, der Zee, Anke H Maitland-van, Klungel, Olaf H, de Boer, Anthonius, Doevendans, Pieter A, Eaton, Charles B, Robinson, Jennifer G, Duggan, David, DIAGRAM Consortium, MAGIC Consortium, Kjekshus, John, Downs, John R, Gotto, Antonio M, Keech, Anthony C, Marchioli, Roberto, Tognoni, Gianni, Sever, Peter S, Poulter, Neil R, Waters, David D, Pedersen, Terje R, Amarenco, Pierre, Nakamura, Haruo, McMurray, John JV, Lewsey, James D, Chasman, Daniel I, Ridker, Paul M, Maggioni, Aldo P, Tavazzi, Luigi, Ray, Kausik K, Seshasai, Sreenivasa Rao Kondapally, Manson, JoAnn E, Price, Jackie F, Whincup, Peter H, Morris, Richard W, Lawlor, Debbie A, Smith, George Davey, Ben-Shlomo, Yoav, Schreiner, Pamela J, Fornage, Myriam, Siscovick, David S, Cushman, Mary, Kumari, Meena, Wareham, Nick J, Verschuren, WM Monique, Redline, Susan, Patel, Sanjay R, Whittaker, John C, and Hamsten, Anders

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Clinical Trials and Supportive Activities, Clinical Research, Genetics, Nutrition, Diabetes, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Metabolic and endocrine, Aged, Body Mass Index, Body Weight, Cholesterol, HDL, Cholesterol, LDL, Diabetes Mellitus, Type 2, Female, Genetic Testing, Humans, Hydroxymethylglutaryl CoA Reductases, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Male, Middle Aged, Polymorphism, Single Nucleotide, Randomized Controlled Trials as Topic, Risk Factors, DIAGRAM Consortium, MAGIC Consortium, InterAct Consortium, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundStatins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.MethodsWe used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.FindingsData were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials).InterpretationThe increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.FundingThe funding sources are cited at the end of the paper.

Published
2015

13. CYP3A4*22 and CYP3A5*3 are associated with increased levels of plasma simvastatin concentrations in the cholesterol and pharmacogenetics study cohort

Author

Kitzmiller, Joseph P, Luzum, Jasmine A, Baldassarre, Damiano, Krauss, Ronald M, and Medina, Marisa W

Subjects
Clinical Research, Genetics, African Americans, Cholesterol, Cohort Studies, Crystallization, Cytochrome P-450 CYP3A, Female, Genetic Association Studies, Genotype, Humans, Male, Middle Aged, Self Report, Simvastatin, United States, Whites, White People, Black or African American, Pharmacology and Pharmaceutical Sciences, Pharmacology & Pharmacy
Abstract

ObjectiveSimvastatin is primarily metabolized by CYP3A4. A combined CYP3A4/5 genotype classification, combining the decrease-of-function CYP3A4*22 and the loss-of-function CYP3A5*3, has recently been reported. We aim to determine whether CYP3A4*22 and CYP3A5*3 alleles are associated with increased plasma concentrations of simvastatin lactone (SV) and simvastatin acid (SVA). This is the first report evaluating associations between in-vivo simvastatin concentrations and CYP3A4*22, alone or in a combined CYP3A4/5 genotype-defined classification.Participants and methodsGenotypes and simvastatin concentrations were determined for 830 participants (555 Whites and 275 African-Americans) in the Cholesterol and Pharmacogenomics clinical trial with 40 mg/day simvastatin for 6 weeks. Concentrations were determined in 12-h postdose samples. Associations between simvastatin concentrations and CYP3A4*22 and CYP3A5*3 alleles were tested separately and in a combined CYP3A4/5 genotype-defined classification system.ResultsIn Whites, CYP3A4*22 carriers (n=42) had 14% higher SVA (P=0.04) and 20% higher SV (P=0.06) compared with noncarriers (n=513). CYP3A5*3 allele status was not significantly associated with SV or SVA in Whites. In African-Americans, CYP3A4*22 carriers (n=8) had 170% higher SV (P

Published
2014

14. SMIM1 absence is associated with reduced energy expenditure and excess weight

Author

Banasik, Karina, Bay, Jakob, Boldsen, Jens Kjærgaard, Brodersen, Thorsten, Brunak, Søren, Burgdorf, Kristoffer, Chalmer, Mona Ameri, Didriksen, Maria, Dinh, Khoa Manh, Dowsett, Joseph, Erikstrup, Christian, Feenstra, Bjarke, Geller, Frank, Gudbjartsson, Daniel, Hansen, Thomas Folkmann, Hindhede, Lotte, Hjalgrim, Henrik, Jacobsen, Rikke Louise, Jemec, Gregor, Jensen, Bitten Aagaard, Kaspersen, Katrine, Kjerulff, Bertram Dalskov, Kogelman, Lisette, Hørup Larsen, Margit Anita, Louloudis, Ioannis, Lundgaard, Agnete, Susan, Mikkelsen, Christina, Nissen, Ioanna, Nyegaard, Mette, Ostrowski, Sisse Rye, Pedersen, Ole Birger, Henriksen, Alexander Pil, Rohde, Palle Duun, Rostgaard, Klaus, Schwinn, Michael, Stefansson, Kari, Stefánsson, Hreinn, Sørensen, Erik, þorsteinsdóttir, Unnur, Thørner, Lise Wegner, Bruun, Mie Topholm, Ullum, Henrik, Werge, Thomas, Westergaard, David, Chen, Ji, Spracklen, Cassandra N., Marenne, Gaëlle, Varshney, Arushi, Corbin, Laura J., Luan, Jian’an, Willems, Sara M., Wu, Ying, Zhang, Xiaoshuai, Horikoshi, Momoko, Boutin, Thibaud S., Mägi, Reedik, Waage, Johannes, Li-Gao, Ruifang, Katie Chan, Kei Hang, Yao, Jie, Anasanti, Mila D., Chu, Audrey Y., Claringbould, Annique, Heikkinen, Jani, Hong, Jaeyoung, Hottenga, Jouke-Jan, Huo, Shaofeng, Kaakinen, Marika A., Louie, Tin, März, Winfried, Moreno-Macias, Hortensia, Ndungu, Anne, Nelson, Sarah C., Nolte, Ilja M., North, Kari E., Raulerson, Chelsea K., Ray, Debashree, Rohde, Rebecca, Rybin, Denis, Schurmann, Claudia, Sim, Xueling, Southam, Loz, Stewart, Isobel D., Wang, Carol A., Wang, Yujie, Wu, Peitao, Zhang, Weihua, Ahluwalia, Tarunveer S., Appel, Emil V.R., Bielak, Lawrence F., Brody, Jennifer A., Burtt, Noël P., Cabrera, Claudia P., Cade, Brian E., Chai, Jin Fang, Chai, Xiaoran, Chang, Li-Ching, Chen, Chien-Hsiun, Chen, Brian H., Chitrala, Kumaraswamy Naidu, Chiu, Yen-Feng, de Haan, Hugoline G., Delgado, Graciela E., Demirkan, Ayse, Duan, Qing, Engmann, Jorgen, Fatumo, Segun A., Gayán, Javier, Giulianini, Franco, Gong, Jung Ho, Gustafsson, Stefan, Hai, Yang, Hartwig, Fernando P., He, Jing, Heianza, Yoriko, Huang, Tao, Huerta-Chagoya, Alicia, Hwang, Mi Yeong, Jensen, Richard A., Kawaguchi, Takahisa, Kentistou, Katherine A., Kim, Young Jin, Kleber, Marcus E., Kooner, Ishminder K., Lai, Shuiqing, Lange, Leslie A., Langefeld, Carl D., Lauzon, Marie, Li, Man, Ligthart, Symen, Liu, Jun, Loh, Marie, Long, Jirong, Lyssenko, Valeriya, Mangino, Massimo, Marzi, Carola, Montasser, May E., Nag, Abhishek, Nakatochi, Masahiro, Noce, Damia, Noordam, Raymond, Pistis, Giorgio, Preuss, Michael, Raffield, Laura, Rasmussen-Torvik, Laura J., Rich, Stephen S., Robertson, Neil R., Rueedi, Rico, Ryan, Kathleen, Sanna, Serena, Saxena, Richa, Schraut, Katharina E., Sennblad, Bengt, Setoh, Kazuya, Smith, Albert V., Southam, Lorraine, Sparsø, Thomas, Strawbridge, Rona J., Takeuchi, Fumihiko, Tan, Jingyi, Trompet, Stella, van den Akker, Erik, van der Most, Peter J., Verweij, Niek, Vogel, Mandy, Wang, Heming, Wang, Chaolong, Wang, Nan, Warren, Helen R., Wen, Wanqing, Wilsgaard, Tom, Wong, Andrew, Wood, Andrew R., Xie, Tian, Zafarmand, Mohammad Hadi, Zhao, Jing-Hua, Zhao, Wei, Amin, Najaf, Arzumanyan, Zorayr, Astrup, Arne, Bakker, Stephan J.L., Baldassarre, Damiano, Beekman, Marian, Bergman, Richard N., Bertoni, Alain, Blüher, Matthias, Bonnycastle, Lori L., Bornstein, Stefan R., Bowden, Donald W., Cai, Qiuyin, Campbell, Archie, Campbell, Harry, Chang, Yi Cheng, de Geus, Eco J.C., Dehghan, Abbas, Du, Shufa, Eiriksdottir, Gudny, Farmaki, Aliki Eleni, Frånberg, Mattias, Fuchsberger, Christian, Gao, Yutang, Gjesing, Anette P., Goel, Anuj, Han, Sohee, Hartman, Catharina A., Herder, Christian, Hicks, Andrew A., Hsieh, Chang-Hsun, Hsueh, Willa A., Ichihara, Sahoko, Igase, Michiya, Ikram, M. Arfan, Johnson, W. Craig, Jørgensen, Marit E., Joshi, Peter K., Kalyani, Rita R., Kandeel, Fouad R., Katsuya, Tomohiro, Khor, Chiea Chuen, Kiess, Wieland, Kolcic, Ivana, Kuulasmaa, Teemu, Kuusisto, Johanna, Läll, Kristi, Lam, Kelvin, Lawlor, Deborah A., Lee, Nanette R., Lemaitre, Rozenn N., Li, Honglan, Lin, Shih-Yi, Lindström, Jaana, Linneberg, Allan, Liu, Jianjun, Lorenzo, Carlos, Matsubara, Tatsuaki, Matsuda, Fumihiko, Mingrone, Geltrude, Mooijaart, Simon, Moon, Sanghoon, Nabika, Toru, Nadkarni, Girish N., Nadler, Jerry L., Nelis, Mari, Neville, Matt J., Norris, Jill M., Ohyagi, Yasumasa, Peters, Annette, Peyser, Patricia A., Polasek, Ozren, Qi, Qibin, Raven, Dennis, Reilly, Dermot F., Reiner, Alex, Rivideneira, Fernando, Roll, Kathryn, Rudan, Igor, Sabanayagam, Charumathi, Sandow, Kevin, Sattar, Naveed, Schürmann, Annette, Shi, Jinxiu, Stringham, Heather M., Taylor, Kent D., Teslovich, Tanya M., Thuesen, Betina, Timmers, Paul R.H.J., Tremoli, Elena, Tsai, Michael Y., Uitterlinden, Andre, van Dam, Rob M., van Heemst, Diana, van Hylckama Vlieg, Astrid, Van Vliet-Ostaptchouk, Jana V., Vangipurapu, Jagadish, Vestergaard, Henrik, Wang, Tao, Willems van Dijk, Ko, Zemunik, Tatijana, Abecasis, Goncalo R., Adair, Linda S., Aguilar-Salinas, Carlos Alberto, Alarcón-Riquelme, Marta E., An, Ping, Aviles-Santa, Larissa, Becker, Diane M., Beilin, Lawrence J., Bergmann, Sven, Bisgaard, Hans, Black, Corri, Boehnke, Michael, Boerwinkle, Eric, Böhm, Bernhard O., Bønnelykke, Klaus, Boomsma, D.I., Bottinger, Erwin P., Buchanan, Thomas A., Canouil, Mickaël, Caulfield, Mark J., Chambers, John C., Chasman, Daniel I., Ida Chen, Yii-Der, Cheng, Ching-Yu, Collins, Francis S., Correa, Adolfo, Cucca, Francesco, Janaka de Silva, H., Dedoussis, George, Elmståhl, Sölve, Evans, Michele K., Ferrannini, Ele, Ferrucci, Luigi, Florez, Jose C., Franks, Paul W., Frayling, Timothy M., Froguel, Philippe, Gigante, Bruna, Goodarzi, Mark O., Gordon-Larsen, Penny, Grallert, Harald, Grarup, Niels, Grimsgaard, Sameline, Groop, Leif, Gudnason, Vilmundur, Guo, Xiuqing, Hamsten, Anders, Hansen, Torben, Hayward, Caroline, Heckbert, Susan R., Horta, Bernardo L., Huang, Wei, Ingelsson, Erik, James, Pankow S., Jarvelin, Marjo-Ritta, Jonas, Jost B., Jukema, J. Wouter, Kaleebu, Pontiano, Kaplan, Robert, Kardia, Sharon L.R., Kato, Norihiro, Keinanen-Kiukaanniemi, Sirkka M., Kim, Bong-Jo, Kivimaki, Mika, Koistinen, Heikki A., Kooner, Jaspal S., Körner, Antje, Kovacs, Peter, Kuh, Diana, Kumari, Meena, Kutalik, Zoltan, Laakso, Markku, Lakka, Timo A., Launer, Lenore J., Leander, Karin, Li, Huaixing, Lin, Xu, Lind, Lars, Lindgren, Cecilia, Liu, Simin, Loos, Ruth J.F., Magnusson, Patrik K.E., Mahajan, Anubha, Metspalu, Andres, Mook-Kanamori, Dennis O., Mori, Trevor A., Munroe, Patricia B., Njølstad, Inger, O'Connell, Jeffrey R., Oldehinkel, Albertine J., Ong, Ken K., Padmanabhan, Sandosh, Palmer, Colin N.A., Palmer, Nicholette D., Pedersen, Oluf, Pennell, Craig E., Porteous, David J., Pramstaller, Peter P., Province, Michael A., Psaty, Bruce M., Qi, Lu, Raffel, Leslie J., Rauramaa, Rainer, Redline, Susan, Ridker, Paul M., Rosendaal, Frits R., Saaristo, Timo E., Sandhu, Manjinder, Saramies, Jouko, Schneiderman, Neil, Schwarz, Peter, Scott, Laura J., Selvin, Elizabeth, Sever, Peter, Shu, Xiao-Ou, Slagboom, P. Eline, Small, Kerrin S., Smith, Blair H., Snieder, Harold, Sofer, Tamar, Sørensen, Thorkild I.A., Spector, Tim D., Stanton, Alice, Steves, Claire J., Stumvoll, Michael, Sun, Liang, Tabara, Yasuharu, Tai, E. Shyong, Timpson, Nicholas J., Tönjes, Anke, Tuomilehto, Jaakko, Tusie, Teresa, Uusitupa, Matti, van der Harst, Pim, van Duijn, Cornelia, Vitart, Veronique, Vollenweider, Peter, Vrijkotte, Tanja G.M., Wagenknecht, Lynne E., Walker, Mark, Wang, Ya X., Wareham, Nick J., Watanabe, Richard M., Watkins, Hugh, Wei, Wen B., Wickremasinghe, Ananda R., Willemsen, Gonneke, Wilson, James F., Wong, Tien-Yin, Wu, Jer-Yuarn, Xiang, Anny H., Yanek, Lisa R., Yengo, Loïc, Yokota, Mitsuhiro, Zeggini, Eleftheria, Zheng, Wei, Zonderman, Alan B., Rotter, Jerome I., Gloyn, Anna L., McCarthy, Mark I., Dupuis, Josée, Meigs, James B., Scott, Robert A., Prokopenko, Inga, Leong, Aaron, Liu, Ching-Ti, Parker, Stephen C.J., Mohlke, Karen L., Langenberg, Claudia, Wheeler, Eleanor, Morris, Andrew P., Barroso, Inês, Stefanucci, Luca, Moslemi, Camous, Tomé, Ana R., Virtue, Samuel, Bidault, Guillaume, Gleadall, Nicholas S., Watson, Laura P.E., Kwa, Jing E., Burden, Frances, Farrow, Samantha, Võsa, Urmo, Burling, Keith, Walker, Lindsay, Ord, John, Barker, Peter, Warner, James, Frary, Amy, Renhstrom, Karola, Ashford, Sofie E., Piper, Jo, Biggs, Gail, Erber, Wendy N., Hoffman, Gary J., Schoenmakers, Nadia, Rieneck, Klaus, Dziegiel, Morten H., Azzu, Vian, Vacca, Michele, Aparicio, Hugo Javier, Hui, Qin, Cho, Kelly, Sun, Yan V., Wilson, Peter W., Bayraktar, Omer A., Vidal-Puig, Antonio, Ostrowski, Sisse R., Astle, William J., Olsson, Martin L., Storry, Jill R., Pedersen, Ole B., Ouwehand, Willem H., Chatterjee, Krishna, Vuckovic, Dragana, and Frontini, Mattia

Published
2024
Full Text
View/download PDF

15. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author

Mahajan, Anubha, Go, Min Jin, Zhang, Weihua, Below, Jennifer E, Gaulton, Kyle J, Ferreira, Teresa, Horikoshi, Momoko, Johnson, Andrew D, Ng, Maggie CY, Prokopenko, Inga, Saleheen, Danish, Wang, Xu, Zeggini, Eleftheria, Abecasis, Goncalo R, Adair, Linda S, Almgren, Peter, Atalay, Mustafa, Aung, Tin, Baldassarre, Damiano, Balkau, Beverley, Bao, Yuqian, Barnett, Anthony H, Barroso, Ines, Basit, Abdul, Been, Latonya F, Beilby, John, Bell, Graeme I, Benediktsson, Rafn, Bergman, Richard N, Boehm, Bernhard O, Boerwinkle, Eric, Bonnycastle, Lori L, Burtt, Noël, Cai, Qiuyin, Campbell, Harry, Carey, Jason, Cauchi, Stephane, Caulfield, Mark, Chan, Juliana CN, Chang, Li-Ching, Chang, Tien-Jyun, Chang, Yi-Cheng, Charpentier, Guillaume, Chen, Chien-Hsiun, Chen, Han, Chen, Yuan-Tsong, Chia, Kee-Seng, Chidambaram, Manickam, Chines, Peter S, Cho, Nam H, Cho, Young Min, Chuang, Lee-Ming, Collins, Francis S, Cornelis, Marilyn C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Danesh, John, Das, Debashish, de Faire, Ulf, Dedoussis, George, Deloukas, Panos, Dimas, Antigone S, Dina, Christian, Doney, Alex SF, Donnelly, Peter J, Dorkhan, Mozhgan, van Duijn, Cornelia, Dupuis, Josée, Edkins, Sarah, Elliott, Paul, Emilsson, Valur, Erbel, Raimund, Eriksson, Johan G, Escobedo, Jorge, Esko, Tonu, Eury, Elodie, Florez, Jose C, Fontanillas, Pierre, Forouhi, Nita G, Forsen, Tom, Fox, Caroline, Fraser, Ross M, Frayling, Timothy M, Froguel, Philippe, Frossard, Philippe, Gao, Yutang, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Grallert, Harald, Grant, George B, Groop, Leif C, Groves, Christopher J, Grundberg, Elin, Guiducci, Candace, Hamsten, Anders, Han, Bok-Ghee, Hara, Kazuo, and Hassanali, Neelam

Subjects
Biological Sciences, Genetics, Human Genome, Diabetes, Metabolic and endocrine, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Polymorphism, Single Nucleotide, Risk Factors, White People, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Published
2014

16. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Author

DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Mahajan, Anubha, Go, Min Jin, Zhang, Weihua, Below, Jennifer E, Gaulton, Kyle J, Ferreira, Teresa, Horikoshi, Momoko, Johnson, Andrew D, Ng, Maggie CY, Prokopenko, Inga, Saleheen, Danish, Wang, Xu, Zeggini, Eleftheria, Abecasis, Goncalo R, Adair, Linda S, Almgren, Peter, Atalay, Mustafa, Aung, Tin, Baldassarre, Damiano, Balkau, Beverley, Bao, Yuqian, Barnett, Anthony H, Barroso, Ines, Basit, Abdul, Been, Latonya F, Beilby, John, Bell, Graeme I, Benediktsson, Rafn, Bergman, Richard N, Boehm, Bernhard O, Boerwinkle, Eric, Bonnycastle, Lori L, Burtt, Noël, Cai, Qiuyin, Campbell, Harry, Carey, Jason, Cauchi, Stephane, Caulfield, Mark, Chan, Juliana CN, Chang, Li-Ching, Chang, Tien-Jyun, Chang, Yi-Cheng, Charpentier, Guillaume, Chen, Chien-Hsiun, Chen, Han, Chen, Yuan-Tsong, Chia, Kee-Seng, Chidambaram, Manickam, Chines, Peter S, Cho, Nam H, Cho, Young Min, Chuang, Lee-Ming, Collins, Francis S, Cornelis, Marylin C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Danesh, John, Das, Debashish, de Faire, Ulf, Dedoussis, George, Deloukas, Panos, Dimas, Antigone S, Dina, Christian, Doney, Alex S, Donnelly, Peter J, Dorkhan, Mozhgan, van Duijn, Cornelia, Dupuis, Josée, Edkins, Sarah, Elliott, Paul, Emilsson, Valur, Erbel, Raimund, Eriksson, Johan G, Escobedo, Jorge, Esko, Tonu, Eury, Elodie, Florez, Jose C, Fontanillas, Pierre, Forouhi, Nita G, Forsen, Tom, Fox, Caroline, Fraser, Ross M, Frayling, Timothy M, Froguel, Philippe, Frossard, Philippe, Gao, Yutang, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Grallert, Harald, Grant, George B, Grrop, Leif C, and Groves, Chrisropher J

Subjects
DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Risk Factors, Case-Control Studies, Polymorphism, Single Nucleotide, Alleles, Asian Continental Ancestry Group, European Continental Ancestry Group, Hispanic Americans, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Published
2014

17. Rationale and design of the CV-PREVITAL study: an Italian multiple cohort randomised controlled trial investigating innovative digital strategies in primary cardiovascular prevention

Author

Baldassarre, Damiano, primary, Iacoviello, Licia, additional, Baetta, Roberta, additional, Roncaglioni, Maria Carla, additional, Condorelli, Gianluigi, additional, Remuzzi, Giuseppe, additional, Gensini, Gianfranco, additional, Frati, Luigi, additional, Ricciardi, Walter, additional, Conaldi, Pier Giulio, additional, Uccelli, Antonio, additional, Blandini, Fabio, additional, Bosari, Silvano, additional, Scambia, Giovanni, additional, Fini, Massimo, additional, Di Malta, Antonio, additional, Amato, Mauro, additional, Veglia, Fabrizio, additional, Bonomi, Alice, additional, Klersy, Catherine, additional, Colazzo, Francesca, additional, Pengo, Martino, additional, Gorini, Francesca, additional, Auteri, Luciana, additional, Ferrante, Giuseppe, additional, Baviera, Marta, additional, Ambrosio, Giuseppe, additional, Catapano, Alberico, additional, Gialluisi, Alessandro, additional, Malavazos, Alexis Elias, additional, Castelvecchio, Serenella, additional, Corsi-Romanelli, Massimiliano Marco, additional, Cardani, Rosanna, additional, Rovere, Maria Teresa La, additional, Agnese, Valentina, additional, Pane, Bianca, additional, Prati, Daniele, additional, Spinardi, Laura, additional, Liuzzo, Giovanna, additional, Arbustini, Eloisa, additional, Volterrani, Maurizio, additional, Visconti, Marco, additional, Werba, José Pablo, additional, Genovese, Stefano, additional, Bilo, Grzegorz, additional, Invitti, Cecilia, additional, Di Blasio, Anna, additional, Lombardi, Carolina, additional, Faini, Andrea, additional, Rosa, Debora, additional, Ojeda-Fernández, Luisa, additional, Foresta, Andreana, additional, De Curtis, Amalia, additional, Di Castelnuovo, Augusto, additional, Scalvini, Simonetta, additional, Pierobon, Antonia, additional, Gorini, Alessandra, additional, Valenti, Luca, additional, Luzi, Livio, additional, Racca, Annarosa, additional, Bandi, Manuela, additional, Tremoli, Elena, additional, Menicanti, Lorenzo, additional, Parati, Gianfranco, additional, and Pompilio, Giulio, additional

Published
2023
Full Text
View/download PDF

18. Association of lifelong occupation and educational level with subclinical atherosclerosis in different European regions. Results from the IMPROVE study

Author

Tedesco, Calogero C., Veglia, Fabrizio, de Faire, Ulf, Kurl, Sudhir, Smit, Andries J., Rauramaa, Rainer, Giral, Philippe, Amato, Mauro, Bonomi, Alice, Ravani, Alessio, Frigerio, Beatrice, Castelnuovo, Samuela, Sansaro, Daniela, Mannarino, Elmo, Humphries, Steve E., Hamsten, Anders, Tremoli, Elena, and Baldassarre, Damiano

Published
2018
Full Text
View/download PDF

19. Identification of a novel proinsulin-associated SNP and demonstration that proinsulin is unlikely to be a causal factor in subclinical vascular remodelling using Mendelian randomisation

Author

Strawbridge, Rona J., Silveira, Angela, Hoed, Marcel den, Gustafsson, Stefan, Luan, Jian'an, Rybin, Denis, Dupuis, Josée, Li-Gao, Ruifang, Kavousi, Maryam, Dehghan, Abbas, Haljas, Kadri, Lahti, Jari, Gådin, Jesper R., Bäcklund, Alexandra, de Faire, Ulf, Gertow, Karl, Giral, Phillipe, Goel, Anuj, Humphries, Steve E., Kurl, Sudhir, Langenberg, Claudia, Lannfelt, Lars L., Lind, Lars, Lindgren, Cecilia C.M., Mannarino, Elmo, Mook-Kanamori, Dennis O., Morris, Andrew P., de Mutsert, Renée, Rauramaa, Rainer, Saliba-Gustafsson, Peter, Sennblad, Bengt, Smit, Andries J., Syvänen, Ann-Christine, Tremoli, Elena, Veglia, Fabrizio, Zethelius, Björn, Björck, Hanna M., Eriksson, Johan G., Hofman, Albert, Franco, Oscar H., Watkins, Hugh, Jukema, J. Wouter, Florez, Jose C., Wareham, Nicholas J., Meigs, James B., Ingelsson, Erik, Baldassarre, Damiano, and Hamsten, Anders

Published
2017
Full Text
View/download PDF

21. Carotid plaque-thickness and common carotid IMT show additive value in cardiovascular risk prediction and reclassification

Author

Amato, Mauro, Veglia, Fabrizio, de Faire, Ulf, Giral, Philippe, Rauramaa, Rainer, Smit, Andries J., Kurl, Sudhir, Ravani, Alessio, Frigerio, Beatrice, Sansaro, Daniela, Bonomi, Alice, Tedesco, Calogero C., Castelnuovo, Samuela, Mannarino, Elmo, Humphries, Steve E., Hamsten, Anders, Tremoli, Elena, and Baldassarre, Damiano

Published
2017
Full Text
View/download PDF

23. A machine learning based approach to identify carotid subclinical atherosclerosis endotypes.

Author

Chen, Qiao Sen, Bergman, Otto, Ziegler, Louise, Baldassarre, Damiano, Veglia, Fabrizio, Tremoli, Elena, Strawbridge, Rona J, Gallo, Antonio, Pirro, Matteo, Smit, Andries J, Kurl, Sudhir, Savonen, Kai, Lind, Lars, Eriksson, Per, and Gigante, Bruna

Subjects
MACHINE learning, ATHEROSCLEROSIS, SYSTOLIC blood pressure, ATHEROSCLEROTIC plaque, CARDIOVASCULAR diseases risk factors
Abstract

Aims To define endotypes of carotid subclinical atherosclerosis. Methods and results We integrated demographic, clinical, and molecular data (n = 124) with ultrasonographic carotid measurements from study participants in the IMPROVE cohort (n = 3340). We applied a neural network algorithm and hierarchical clustering to identify carotid atherosclerosis endotypes. A measure of carotid subclinical atherosclerosis, the c-IMTmean-max, was used to extract atherosclerosis-related features and SHapley Additive exPlanations (SHAP) to reveal endotypes. The association of endotypes with carotid ultrasonographic measurements at baseline, after 30 months, and with the 3-year atherosclerotic cardiovascular disease (ASCVD) risk was estimated by linear (β , SE) and Cox [hazard ratio (HR), 95% confidence interval (CI)] regression models. Crude estimates were adjusted by common cardiovascular risk factors, and baseline ultrasonographic measures. Improvement in ASCVD risk prediction was evaluated by C -statistic and by net reclassification improvement with reference to SCORE2, c-IMTmean-max, and presence of carotid plaques. An ensemble stacking model was used to predict endotypes in an independent validation cohort, the PIVUS (n = 1061). We identified four endotypes able to differentiate carotid atherosclerosis risk profiles from mild (endotype 1) to severe (endotype 4). SHAP identified endotype-shared variables (age, biological sex, and systolic blood pressure) and endotype-specific biomarkers. In the IMPROVE, as compared to endotype 1, endotype 4 associated with the thickest c-IMT at baseline (β , SE) 0.36 (0.014), the highest number of plaques 1.65 (0.075), the fastest c-IMT progression 0.06 (0.013), and the highest ASCVD risk (HR, 95% CI) (1.95, 1.18–3.23). Baseline and progression measures of carotid subclinical atherosclerosis and ASCVD risk were associated with the predicted endotypes in the PIVUS. Endotypes consistently improved measures of ASCVD risk discrimination and reclassification in both study populations. Conclusions We report four replicable subclinical carotid atherosclerosis—endotypes associated with progression of atherosclerosis and ASCVD risk in two independent populations. Our approach based on endotypes can be applied for precision medicine in ASCVD prevention. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

24. PCSK6 Is a Key Protease in the Control of Smooth Muscle Cell Function in Vascular Remodeling

Author

Rykaczewska, Urszula, Suur, Bianca E., Röhl, Samuel, Razuvaev, Anton, Lengquist, Mariette, Sabater-Lleal, Maria, van der Laan, Sander W., Miller, Clint L., Wirka, Robert C., Kronqvist, Malin, Gonzalez Diez, Maria, Vesterlund, Mattias, Gillgren, Peter, Odeberg, Jacob, Lindeman, Jan H., Veglia, Fabrizio, Humphries, Steve E., de Faire, Ulf, Baldassarre, Damiano, Tremoli, Elena, Lehtiö, Janne, Hansson, Göran K., Paulsson-Berne, Gabrielle, Pasterkamp, Gerard, Quertermous, Thomas, Hamsten, Anders, Eriksson, Per, Hedin, Ulf, and Matic, Ljubica

Published
2020
Full Text
View/download PDF

27. Abstract P450: The Moli-Sani Risk Score, a New Algorithm for Measuring the Global Impact of Nine Modifiable Cardiovascular Risk Factors

Author

Di Castelnuovo, Augusto, primary, Bonaccio, Marialaura, additional, Costanzo, Simona, additional, De Curtis, Amalia, additional, Persichillo, Mariarosaria, additional, Panzera, Teresa, additional, Baldassarre, Damiano, additional, Roncaglioni, Maria Carla, additional, Baviera, Marta, additional, Cerletti, Chiara, additional, Donati, Maria Benedetta, additional, de Gaetano, Giovanni, additional, and Iacoviello, Licia, additional

Published
2023
Full Text
View/download PDF

28. Loci for insulin processing and secretion provide insight into type 2 diabetes risk

Author

Broadaway, K. Alaine, primary, Yin, Xianyong, additional, Williamson, Alice, additional, Parsons, Victoria A., additional, Wilson, Emma P., additional, Moxley, Anne H., additional, Vadlamudi, Swarooparani, additional, Varshney, Arushi, additional, Jackson, Anne U., additional, Ahuja, Vasudha, additional, Bornstein, Stefan R., additional, Corbin, Laura J., additional, Delgado, Graciela E., additional, Dwivedi, Om P., additional, Fernandes Silva, Lilian, additional, Frayling, Timothy M., additional, Grallert, Harald, additional, Gustafsson, Stefan, additional, Hakaste, Liisa, additional, Hammar, Ulf, additional, Herder, Christian, additional, Herrmann, Sandra, additional, Højlund, Kurt, additional, Hughes, David A., additional, Kleber, Marcus E., additional, Lindgren, Cecilia M., additional, Liu, Ching-Ti, additional, Luan, Jian’an, additional, Malmberg, Anni, additional, Moissl, Angela P., additional, Morris, Andrew P., additional, Perakakis, Nikolaos, additional, Peters, Annette, additional, Petrie, John R., additional, Roden, Michael, additional, Schwarz, Peter E.H., additional, Sharma, Sapna, additional, Silveira, Angela, additional, Strawbridge, Rona J., additional, Tuomi, Tiinamaija, additional, Wood, Andrew R., additional, Wu, Peitao, additional, Zethelius, Björn, additional, Baldassarre, Damiano, additional, Eriksson, Johan G., additional, Fall, Tove, additional, Florez, Jose C., additional, Fritsche, Andreas, additional, Gigante, Bruna, additional, Hamsten, Anders, additional, Kajantie, Eero, additional, Laakso, Markku, additional, Lahti, Jari, additional, Lawlor, Deborah A., additional, Lind, Lars, additional, März, Winfried, additional, Meigs, James B., additional, Sundström, Johan, additional, Timpson, Nicholas J., additional, Wagner, Robert, additional, Walker, Mark, additional, Wareham, Nicholas J., additional, Watkins, Hugh, additional, Barroso, Inês, additional, O’Rahilly, Stephen, additional, Grarup, Niels, additional, Parker, Stephen CJ., additional, Boehnke, Michael, additional, Langenberg, Claudia, additional, Wheeler, Eleanor, additional, and Mohlke, Karen L., additional

Published
2023
Full Text
View/download PDF

31. Cross-Sectional Gene-Smoking Interaction Analysis in Relation to Subclinical Atherosclerosis-Results From the IMPROVE Study

Author

Maitusong, Buamina, Laguzzi, Federica, Strawbridge, Rona J, Baldassarre, Damiano, Veglia, Fabrizio, Humphries, Steve E, Savonen, Kai, Kurl, Sudhir, Pirro, Matteo, Smit, Andries J, Giral, Philippe, Silveira, Angela, Tremoli, Elena, Hamsten, Anders, de Faire, Ulf, Gigante, Bruna, and Leander, Karin

Subjects
cardiovascular disease, carotid intima-media thickness, infarction, atherosclerosis, sample size
Published
2023

32. Genetic variation in CADM2 as a link between psychological traits and obesity

Author

Morris, Julia, Bailey, Mark E. S., Baldassarre, Damiano, Cullen, Breda, de Faire, Ulf, Ferguson, Amy, Gigante, Bruna, Giral, Philippe, Goel, Anuj, Graham, Nicholas, Hamsten, Anders, Humphries, Steve E., Johnston, Keira J. A., Lyall, Donald M., Lyall, Laura M., Sennblad, Bengt, Silveira, Angela, Smit, Andries J., Tremoli, Elena, Veglia, Fabrizio, Ward, Joey, Watkins, Hugh, Smith, Daniel J., and Strawbridge, Rona J.

Published
2019
Full Text
View/download PDF

33. Prevalence of Psychopathological Symptoms and Their Determinants in Four Healthcare Workers’ Categories during the Second Year of COVID-19 Pandemic

Author

Gorini, Alessandra, primary, Giuliani, Mattia, additional, Fiabane, Elena, additional, Bonomi, Alice, additional, Gabanelli, Paola, additional, Pierobon, Antonia, additional, Moretta, Pasquale, additional, Pagliarulo, Giovanna, additional, Spaccavento, Simona, additional, Vaudo, Gaetano, additional, Pirro, Matteo, additional, Mannarino, Massimo R., additional, Milani, Laura, additional, Caruso, Maria Paola, additional, Baiardi, Paola, additional, Dalla Vecchia, Laura Adelaide, additional, La Rovere, Maria Teresa, additional, Pistarini, Caterina, additional, and Baldassarre, Damiano, additional

Published
2022
Full Text
View/download PDF

36. Secretory Phospholipase A2-IIA and Cardiovascular Disease: A Mendelian Randomization Study

Author

Holmes, Michael V., Simon, Tabassome, Exeter, Holly J., Folkersen, Lasse, Asselbergs, Folkert W., Guardiola, Montse, Cooper, Jackie A., Palmen, Jutta, Hubacek, Jaroslav A., Carruthers, Kathryn F., Horne, Benjamin D., Brunisholz, Kimberly D., Mega, Jessica L., van Iperen, Erik P.A., Li, Mingyao, Leusink, Maarten, Trompet, Stella, Verschuren, Jeffrey J.W., Hovingh, G. Kees, Dehghan, Abbas, Nelson, Christopher P., Kotti, Salma, Danchin, Nicolas, Scholz, Markus, Haase, Christiane L., Rothenbacher, Dietrich, Swerdlow, Daniel I., Kuchenbaecker, Karoline B., Staines-Urias, Eleonora, Goel, Anuj, van 't Hooft, Ferdinand, Gertow, Karl, de Faire, Ulf, Panayiotou, Andrie G., Tremoli, Elena, Baldassarre, Damiano, Veglia, Fabrizio, Holdt, Lesca M., Beutner, Frank, Gansevoort, Ron T., Navis, Gerjan J., Mateo Leach, Irene, Breitling, Lutz P., Brenner, Hermann, Thiery, Joachim, Dallmeier, Dhayana, Franco-Cereceda, Anders, Boer, Jolanda M.A., Stephens, Jeffrey W., Hofker, Marten H., Tedgui, Alain, Hofman, Albert, Uitterlinden, André G., Adamkova, Vera, Pitha, Jan, Onland-Moret, N. Charlotte, Cramer, Maarten J., Nathoe, Hendrik M., Spiering, Wilko, Klungel, Olaf H., Kumari, Meena, Whincup, Peter H., Morrow, David A., Braund, Peter S., Hall, Alistair S., Olsson, Anders G., Doevendans, Pieter A., Trip, Mieke D., Tobin, Martin D., Hamsten, Anders, Watkins, Hugh, Koenig, Wolfgang, Nicolaides, Andrew N., Teupser, Daniel, Day, Ian N.M., Carlquist, John F., Gaunt, Tom R., Ford, Ian, Sattar, Naveed, Tsimikas, Sotirios, Schwartz, Gregory G., Lawlor, Debbie A., Morris, Richard W., Sandhu, Manjinder S., Poledne, Rudolf, Maitland-van der Zee, Anke H., Khaw, Kay-Tee, Keating, Brendan J., van der Harst, Pim, Price, Jackie F., Mehta, Shamir R., Yusuf, Salim, Witteman, Jaqueline C.M., Franco, Oscar H., Jukema, J. Wouter, de Knijff, Peter, Tybjaerg-Hansen, Anne, Rader, Daniel J., Farrall, Martin, Samani, Nilesh J., Kivimaki, Mika, Fox, Keith A.A., Humphries, Steve E., Anderson, Jeffrey L., Boekholdt, S. Matthijs, Palmer, Tom M., Eriksson, Per, Paré, Guillaume, Hingorani, Aroon D., Sabatine, Marc S., Mallat, Ziad, Casas, Juan P., and Talmud, Philippa J.

Published
2013
Full Text
View/download PDF

37. Neutrophil to lymphocyte ratio is not related to carotid atherosclerosis progression and cardiovascular events in the primary prevention of cardiovascular disease: results from the IMPROVE study

Author

Mannarino, Massimo R., Bianconi, Vanessa, Gigante, Bruna, Strawbridge, Rona J., Savonen, Kai, Kurl, Sudhir, Giral, Philippe, Smit, Andries, Eriksson, Per, Tremoli, Elena, Veglia, Fabrizio, Baldassarre, Damiano, Pirro, Matteo, and IMPROVE study group

Subjects
fungi, cardiovascular system, cardiovascular diseases
Abstract

Inflammation is a component of the pathogenesis of atherosclerosis and is associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). The neutrophil to lymphocyte ratio (NLR) is a possible inflammation metric for the detection of ASCVD risk, although results of prospective studies are highly inconsistent on this topic. We investigated the cross‐sectional relationship between NLR and carotid intima‐media thickness (cIMT) in subjects at moderate‐to‐high ASCVD risk. The prospective association between NLR, cIMT progression, and incident vascular events (VEs) was also explored. In 3341 subjects from the IMT‐Progression as Predictors of VEs (IMPROVE) study, we analyzed the association between NLR, cIMT, and its 15‐month progression. The association between NLR and incident VEs was also investigated. NLR was positively associated with cross‐sectional measures of cIMT, but not with cIMT progression. The association between NLR and cross‐sectional cIMT measures was abolished when adjusted for confounders. No association was found between NRL and incident VEs. Similarly, there were no significant differences in the hazard ratios (HRs) of VEs across NLR quartiles. NLR was neither associated with the presence and progression of carotid atherosclerosis, nor with the risk of VEs. Our findings do not support the role of NLR as a predictor of the risk of atherosclerosis progression and ASCVD events in subjects at moderate‐to‐high ASCVD risk, in primary prevention. However, the usefulness of NLR for patients at a different level of ASCVD risk cannot be inferred from this study.

Published
2022

39. Assessment of New Coronary Features on Quantitative Coronary Angiographic Images With Innovative Unsupervised Artificial Adaptive Systems: A Proof-of-Concept Study

Author

Amato, Mauro, Buscema, Massimo, Massini, Giulia, Maurelli, Guido, Grossi, Enzo, Frigerio, Beatrice, Ravani, Alessio L., Sansaro, Daniela, Coggi, Daniela, Ferrari, Cristina, Bartorelli, Antonio L., Veglia, Fabrizio, Tremoli, Elena, and Baldassarre, Damiano

Subjects
computer-assisted, diagnostic, ultrasonography, Cardiovascular Medicine, atherosclerosis, coronary angiography, artificial intelligence, Original Research, image processing
Abstract

Background and Purpose: The Active Connection Matrixes (ACMs) are unsupervised artificial adaptive systems able to extract from digital images features of interest (edges, tissue differentiation, etc.) unnoticeable with conventional systems. In this proof-of-concept study, we assessed the potentiality of ACMs to increase measurement precision of morphological structures (e.g., stenosis and lumen diameter) and to grasp morphological features (arterial walls) from quantitative coronary angiography (QCA), unnoticeable on the original images. Methods: Archive images of QCA and intravascular ultrasound (IVUS) of 10 patients (8 men, age 69.1 ± 9.7 years) who underwent both procedures for clinical reasons were retrospectively analyzed. Arterial features derived from “IVUS images,” “conventional QCA images,” and “ACM-reprocessed QCA images” were measured in 21 coronary segments. Portions of 1-mm length (263 for lumen and 526 for arterial walls) were head-to-head compared to assess quali-quantitative between-methods agreement. Results: When stenosis was calculated on “ACM-reprocessed QCA images,” the bias vs. IVUS (gold standard) did not improve, but the correlation coefficient of the QCA–IVUS relationship increased from 0.47 to 0.83. When IVUS-derived lumen diameters were compared with diameters obtained on ACM-reprocessed QCA images, the bias (−0.25 mm) was significantly smaller (p < 0.01) than that observed with original QCA images (0.58 mm). ACMs were also able to extract arterial wall features from QCA. The bias between the measures of arterial walls obtained with IVUS and ACMs, although significant (p < 0.01), was small [0.09 mm, 95% CI (0.03, 0.14)] and the correlation was fairly good (r = 0.63; p < 0.0001). Conclusions: This study provides proof of concept that ACMs increase the measurement precision of coronary lumen diameter and allow extracting from QCA images hidden features that mirror well the arterial walls derived by IVUS.

Published
2021

40. Relationship between Circulating PCSK9 and Markers of Subclinical Atherosclerosis—The IMPROVE Study

Author

Coggi, Daniela, Frigerio, Beatrice, Bonomi, Alice, Ruscica, Massimiliano, Ferri, Nicola, Sansaro, Daniela, Ravani, Alessio, Ferrante, Palma, Damigella, Manuela, Veglia, Fabrizio, Capra, Nicolò, Lupo, Maria Giovanna, Macchi, Chiara, Savonen, Kai, Silveira, Angela, Kurl, Sudhir, Giral, Philippe, Pirro, Matteo, Strawbridge, Rona Juliette, Gigante, Bruna, Smit, Andries Jan, Tremoli, Elena, Amato, Mauro, Baldassarre, Damiano, and Group, on behalf of the IMPROVE Study

Subjects
PCSK9, subclinical atherosclerosis, carotid artery, QH301-705.5, cardiovascular system, cardiovascular diseases, echolucency, Biology (General), intima-media thickness
Abstract

(1) Background and purpose: circulating proprotein convertase subtilisin/kexin type 9 (PCSK9) is one of the key regulators of cholesterol metabolism. Despite this, its role as a player in atherosclerosis development is still matter of debate. Here, we investigated the relationships between this protein and several markers of subclinical atherosclerosis. (2) Methods: the IMPROVE study enrolled 3703 European subjects (54–79 years, 48% men, with ≥3 vascular risk factors), asymptomatic for cardiovascular diseases. PCSK9 levels were measured by ELISA. B-mode ultrasound was used to measure markers of carotid subclinical atherosclerosis. (3) Results: in the crude analysis, PCSK9 levels were associated with several baseline measures of carotid intima-media thickness (cIMT) (all p &lt, 0.0001), with cIMT change over time (Fastest-IMTmax-progr) (p = 0.01), with inter-adventitia common carotid artery diameter (ICCAD) (p &lt, and with the echolucency (Grey Scale Median, GSM) of both carotid plaque and plaque-free common carotid IMT (both p &lt, 0.0001). However, after adjustment for age, sex, latitude, and pharmacological treatment, all the afore-mentioned correlations were no longer statistically significant. The lack of correlation was also observed after stratification for sex, latitude, and pharmacological treatments. (4) Conclusions: in subjects who are asymptomatic for cardiovascular diseases, PCSK9 plasma levels do not correlate with vascular damage and/or subclinical atherosclerosis of extracranial carotid arteries.

Published
2021

41. A serum 25-hydroxyvitamin D concentration-associated genetic variant in DHCR7 interacts with type 2 diabetes status to influence subclinical atherosclerosis (measured by carotid intima–media thickness)

Author

Strawbridge, Rona J., Deleskog, Anna, McLeod, Olga, Folkersen, Lasse, Kavousi, Maryam, Gertow, Karl, Baldassarre, Damiano, Veglia, Fabrizio, Leander, Karin, Gigante, Bruna, Kauhanen, Jussi, Rauramaa, Rainer, Smit, Andries J., Mannarino, Elmo, Giral, Philippe, Dehghan, Abbas, Hofman, Albert, Franco, Oscar H., Humphries, Steve E., Tremoli, Elena, de Faire, Ulf, Gustafsson, Sven, Östensson, Claes-Göran, Eriksson, Per, Öhrvik, John, and Hamsten, Anders

Published
2014
Full Text
View/download PDF

43. Genetic loci on chromosome 5 are associated with circulating levels of interleukin-5 and eosinophil count in a European population with high risk for cardiovascular disease

Author

McLeod, Olga, Silveira, Angela, Valdes-Marquez, Elsa, Björkbacka, Harry, Almgren, Peter, Gertow, Karl, Gådin, Jesper R., Bäcklund, Alexandra, Sennblad, Bengt, Baldassarre, Damiano, Veglia, Fabrizio, Humphries, Steve E., Tremoli, Elena, de Faire, Ulf, Nilsson, Jan, Melander, Olle, Hopewell, Jemma C., Clarke, Robert, Björck, Hanna M., Hamsten, Anders, Öhrvik, John, and Strawbridge, Rona J.

Published
2016
Full Text
View/download PDF

45. Intake of food rich in saturated fat in relation to subclinical atherosclerosis and potential modulating effects from single genetic variants

Author

Laguzzi, Federica, Maitusong, Buamina, Strawbridge, Rona J., Baldassarre, Damiano, Veglia, Fabrizio, Humphries, Steve E., Rauramaa, Rainer, Kurl, Sudhir, Smit, Andries J., Giral, Philippe, Silveira, Angela, Tremoli, Elena, Hamsten, Anders, de Faire, Ulf, Gigante, Bruna, Leander, Karin, Sirtori, C. R., Calabresi, L., Amato, M., Frigerio, B., Ravani, A., Sansaro, D., Tedesco, C., Coggi, D., Capra, N., Bonomi, A., Eriksson, P., Cooper, J., Acharya, J., Savonen, K., Huttunen, K., Rauramaa, E., Penttila, I. M., Törrönen, J., van Gessel, A. I., van Roon, A. M., Nicolai, A., Mulder, D. J., Kontush, A., Carrié, A., Gallo, A., Karppi, J., Nurmi, T., Nyyssönen, K., Tuomainen, T. P., Tuomainen, J., Kauhanen, J., Sennblad, B., Pirro, M., Vaudo, G., Siepi, D., Lupattelli, G., Mannarino, M. R., Bianconi, V., Groningen Kidney Center (GKC), Translational Immunology Groningen (TRIGR), Karolinska Institutet [Stockholm], Xinjiang University, University of Glasgow, Università degli Studi di Milano [Milano] (UNIMI), Centro Cardiologico Monzino [Milano], Dpt di Scienze Cliniche e di Comunità [Milano] (DISCCO), Università degli Studi di Milano [Milano] (UNIMI)-Università degli Studi di Milano [Milano] (UNIMI)-Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), University College of London [London] (UCL), University of Kuopio, University of Eastern Finland, University Medical Center Groningen [Groningen] (UMCG), Service d’Endocrinologie, Métabolisme et Prévention des Risques Cardio-Vasculaires [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
Male, medicine.medical_specialty, Multivariate analysis, Cross-sectional study, Science, [SDV]Life Sciences [q-bio], Saturated fat, Cardiology, Disease, 030204 cardiovascular system & hematology, Logistic regression, Carotid Intima-Media Thickness, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Genetics, Medicine, Humans, Genetic Predisposition to Disease, 030212 general & internal medicine, Aged, Multidisciplinary, business.industry, Middle Aged, Atherosclerosis, Dietary Fats, 3. Good health, Endocrinology, Blood pressure, Intima-media thickness, Cohort, cardiovascular system, Dietary Fats/adverse effects, Female, Atherosclerosis/epidemiology, business, Biomarkers
Abstract

The relationship between intake of saturated fats and subclinical atherosclerosis, as well as the possible influence of genetic variants, is poorly understood and investigated. We aimed to investigate this relationship, with a hypothesis that it would be positive, and to explore whether genetics may modulate it, using data from a European cohort including 3,407 participants aged 54–79 at high risk of cardiovascular disease. Subclinical atherosclerosis was assessed by carotid intima-media thickness (C-IMT), measured at baseline and after 30 months. Logistic regression (OR; 95% CI) was employed to assess the association between high intake of food rich in saturated fat (vs. low) and: (1) the mean and the maximum values of C-IMT in the whole carotid artery (C-IMTmean, C-IMTmax), in the bifurcation (Bif-), the common (CC-) and internal (ICA-) carotid arteries at baseline (binary, cut-point ≥ 75th), and (2) C-IMT progression (binary, cut-point > zero). For the genetic-diet interaction analyses, we considered 100,350 genetic variants. We defined interaction as departure from additivity of effects. After age- and sex-adjustment, high intake of saturated fat was associated with increased C-IMTmean (OR:1.27;1.06–1.47), CC-IMTmean (OR:1.22;1.04–1.44) and ICA-IMTmean (OR:1.26;1.07–1.48). However, in multivariate analysis results were no longer significant. No clear associations were observed between high intake of saturated fat and risk of atherosclerotic progression. There was no evidence of interactions between high intake of saturated fat and any of the genetic variants considered, after multiple testing corrections. High intake of saturated fats was not independently associated with subclinical atherosclerosis. Moreover, we did not identify any significant genetic-dietary fat interactions in relation to risk of subclinical atherosclerosis.

Published
2021

46. Mapping genetic determinants of 184 circulating proteins in 26,494 individuals to connect proteins and diseases

Author

Macdonald-Dunlop, Erin, primary, Klarić, Lucija, additional, Folkersen, Lasse, additional, Timmers, Paul R.H.J., additional, Gustafsson, Stefan, additional, Zhao, Jing Hua, additional, Eriksson, Niclas, additional, Richmond, Anne, additional, Enroth, Stefan, additional, Mattsson-Carlgren, Niklas, additional, Zhernakova, Daria V., additional, Kalnapenkis, Anette, additional, Magnusson, Martin, additional, Wheeler, Eleanor, additional, Hwang, Shih-Jen, additional, Chen, Yan, additional, Morris, Andrew P, additional, Prins, Bram, additional, Võsa, Urmo, additional, Wareham, Nicholas J., additional, Danesh, John, additional, Sundstrom, Johan, additional, Gigante, Bruna, additional, Baldassarre, Damiano, additional, Strawbridge, Rona J., additional, Campbell, Harry, additional, Gyllensten, Ulf, additional, Yao, Chen, additional, Zanetti, Daniela, additional, Assimes, Themistocles L., additional, Eriksson, Per, additional, Levy, Daniel, additional, Langenberg, Claudia, additional, Smith, J. Gustav, additional, Esko, Tõnu, additional, Fu, Jingyuan, additional, Hansson, Oskar, additional, Johansson, Åsa, additional, Hayward, Caroline, additional, Wallentin, Lars, additional, Siegbahn, Agneta, additional, Lind, Lars, additional, Butterworth, Adam S., additional, Michaëlsson, Karl, additional, Peters, James E., additional, Mälarstig, Anders, additional, Joshi, Peter K., additional, and Wilson, James F., additional

Published
2021
Full Text
View/download PDF

47. Aortic Valve Sclerosis in High-Risk Coronary Artery Disease Patients

Author

Myasoedova, Veronika A., primary, Genovese, Stefano, additional, Cavallotti, Laura, additional, Bonomi, Alice, additional, Chiesa, Mattia, additional, Campodonico, Jeness, additional, Rondinelli, Maurizio, additional, Cosentino, Nicola, additional, Baldassarre, Damiano, additional, Veglia, Fabrizio, additional, Pepi, Mauro, additional, Alamanni, Francesco, additional, Colombo, Gualtiero I., additional, Marenzi, Giancarlo, additional, and Poggio, Paolo, additional

Published
2021
Full Text
View/download PDF

48. The Association between HDL-C and Subclinical Atherosclerosis Depends on CETP Plasma Concentration: Insights from the IMPROVE Study

Author

Colombo, Gualtiero, Bianconi, Vanessa, Bonomi, Alice, Simonelli, Sara, Amato, Mauro, Frigerio, Beatrice, Ravani, Alessio, Vitali, Cecilia, Sansaro, Daniela, Coggi, Daniela, Mannarino, Massimo, Savonen, Kai, Kurl, Sudhir, Gigante, Bruna, Smit, Andries, Giral, Philippe, Tremoli, Elena, Calabresi, Laura, Veglia, Fabrizio, Pirro, Matteo, Baldassarre, Damiano, Group, on behalf of the IMPROVE Study, Centro Cardiologico Monzino [Milano], Dpt di Scienze Cliniche e di Comunità [Milano] (DISCCO), Università degli Studi di Milano [Milano] (UNIMI)-Università degli Studi di Milano [Milano] (UNIMI)-Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Università degli Studi di Perugia (UNIPG), Università degli Studi di Milano [Milano] (UNIMI), Perelman School of Medicine, University of Pennsylvania [Philadelphia], University of Eastern Finland, Karolinska Institutet [Stockholm], University Medical Center Groningen [Groningen] (UMCG), Service d’Endocrinologie, Métabolisme et Prévention des Risques Cardio-Vasculaires [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Sorbonne Université - Faculté de Médecine (SU FM), Sorbonne Université (SU), and Groningen Kidney Center (GKC)

Subjects
Carotid intima‐media thickness, carotid intima-media thickness, [SDV]Life Sciences [q-bio], cholesteryl ester transfer protein, Single‐nucleotide polymorphisms, Article, carbohydrates (lipids), HDL‐C, lcsh:Biology (General), single-nucleotide polymorphisms, cardiovascular system, lipids (amino acids, peptides, and proteins), HDL-C, cardiovascular diseases, atherosclerosis, lcsh:QH301-705.5
Abstract

The impact of cholesteryl ester transfer protein (CETP) on atherosclerosis is highly debated. This study aimed to investigate the associations between plasma CETP or CETP genotypes and carotid intima-media thickness (cIMT) and the influence of high-density lipoprotein cholesterol (HDL-C) on these associations. Plasma CETP and HDL-C concentrations were measured in 552 subjects free of any pharmacological treatment from the IMPROVE cohort, which includes 3711 European subjects at high cardiovascular risk. CETP single-nucleotide polymorphisms (SNPs) and cIMT measures (cIMTmax, cIMTmean–max of bifurcations, common and internal carotids, plaque-free common carotid [PF CC]-IMTmean) were available for the full cohort. In drug-free subjects, plasma CETP correlated with HDL-C levels (r = 0.19, p &lt, 0.0001), but not with cIMT variables. When stratified according to HDL-C quartiles, CETP positively correlated with cIMTmax and cIMTmean–max, but not with PF CC-IMTmean, in the top HDL-C quartile only. Positive associations between the CETP concentration and cIMTmax or cIMTmean–max were found in the top HDL-C quartile, whereas HDL-C levels were negatively correlated with cIMTmax and cIMTmean–max when the CETP concentration was below the median (HDL-C × CETP interaction, p = 0.001 and p = 0.003 for cIMTmax and cIMTmean–max, respectively). In the full cohort, three CETP SNPs (rs34760410, rs12920974, rs12708968) were positively associated with cIMTmax. rs12444708 exhibited a significant interaction with HDL-C levels in the prediction of cIMTmax. In conclusion, a significant interplay was found between plasma CETP and/or CETP genotype and HDL-C in the prediction of carotid plaque thickness, as indexed by cIMTmax. This suggests that the association of HDL-C with carotid atherosclerosis is CETP-dependent.

Published
2021

50. Association Between Uric Acid, Carotid Intima‐Media Thickness, and Cardiovascular Events: Prospective Results From the IMPROVE Study

Author

Mannarino, Massimo R., primary, Pirro, Matteo, additional, Gigante, Bruna, additional, Savonen, Kai, additional, Kurl, Sudhir, additional, Giral, Philippe, additional, Smit, Andries, additional, Veglia, Fabrizio, additional, Tremoli, Elena, additional, Baldassarre, Damiano, additional, Amato, M., additional, Frigerio, B., additional, Ravani, A., additional, Sansaro, D., additional, Coggi, D., additional, Tedesco, C., additional, Capra, N., additional, Bonomi, A., additional, Calabresi, Laura, additional, Sirtori, C. R., additional, Eriksson, Per, additional, Silveira, Angela, additional, Leander, Karin, additional, Laguzzi, Federica, additional, Hamsten, Anders, additional, de Faire, Ulf, additional, Humphries, Steve E., additional, Cooper, J., additional, Acharya, J., additional, Huttunen, K., additional, Rauramaa, E., additional, Penttila, I. M., additional, Törrönen, J., additional, van Gessel, A. I., additional, van Roon, A. M., additional, Nicolai, A., additional, Mulder, D. J., additional, Smeets, G. H., additional, Kontush, Anatole, additional, Carrié, Alain, additional, Gallo, Antonio, additional, Karppi, J., additional, Nurmi, T., additional, Nyyssönen, K., additional, Tuomainen, T. P., additional, Tuomainen, J., additional, Kauhanen, J., additional, Vaudo, G., additional, Bianconi, V., additional, Siepi, D., additional, and Lupattelli, G., additional

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results