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1. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Costanzo, Maria C, von Grotthuss, Marcin, Massung, Jeffrey, Jang, Dongkeun, Caulkins, Lizz, Koesterer, Ryan, Gilbert, Clint, Welch, Ryan P, Kudtarkar, Parul, Hoang, Quy, Boughton, Andrew P, Singh, Preeti, Sun, Ying, Duby, Marc, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Alexander, Benjamin R, Brandes, MacKenzie, Carmichael, Mary, Dornbos, Peter, Green, Todd, Huellas-Bruskiewicz, Kenneth C, Ji, Yue, Kluge, Alexandria, McMahon, Aoife C, Mercader, Josep M, Ruebenacker, Oliver, Sengupta, Sebanti, Spalding, Dylan, Taliun, Daniel, Consortium, AMP-T2D, Abecasis, Gonçalo, Akolkar, Beena, Allred, Nicholette D, Altshuler, David, Below, Jennifer E, Bergman, Richard, Beulens, Joline WJ, Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Bowden, Donald, Brosnan, M Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P, Cebola, Inês, Chambers, John, Chen, Yii-Der Ida, Cherkas, Andriy, Chu, Audrey Y, Clark, Christopher, Claussnitzer, Melina, Cox, Nancy J, Hoed, Marcel den, Dong, Duc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra JM, Engreitz, Jesse M, Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C, Fox, Caroline S, Frayling, Timothy M, Frazer, Kelly A, Gaulton, Kyle J, Gloyn, Anna L, Hanis, Craig L, Hanson, Robert, Hattersley, Andrew T, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne BR, Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M, Kim, Seung K, Lage, Kasper, Lange, Leslie A, and Lazar, Mitchell

Subjects
Genetics, Diabetes, Human Genome, Metabolic and endocrine, Good Health and Well Being, Humans, Diabetes Mellitus, Type 2, Access to Information, Prospective Studies, Genomics, Phenotype, AMP-T2D Consortium, CMDKP, GWAS, T2DKP, data sharing, diabetes, effector genes, genetic associations, genetic support, genomics, portal, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Endocrinology & Metabolism
Abstract

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

Published
2023

2. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Abecasis, Gonçalo, Akolkar, Beena, Alexander, Benjamin R., Allred, Nicholette D., Altshuler, David, Below, Jennifer E., Bergman, Richard, Beulens, Joline W.J., Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Boughton, Andrew P., Bowden, Donald, Brosnan, M. Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P., Carmichael, Mary, Caulkins, Lizz, Cebola, Inês, Chambers, John, Ida Chen, Yii-Der, Cherkas, Andriy, Chu, Audrey Y., Clark, Christopher, Claussnitzer, Melina, Costanzo, Maria C., Cox, Nancy J., Hoed, Marcel den, Dong, Duc, Duby, Marc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra J.M., Engreitz, Jesse M., Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C., Fox, Caroline S., Frayling, Timothy M., Frazer, Kelly A., Gaulton, Kyle J., Gilbert, Clint, Gloyn, Anna L., Green, Todd, Hanis, Craig L., Hanson, Robert, Hattersley, Andrew T., Hoang, Quy, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne B.R., Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M., Kim, Seung K., Kluge, Alexandria, Koesterer, Ryan, Kudtarkar, Parul, Lage, Kasper, Lange, Leslie A., Lazar, Mitchell, Lehman, Donna, Liu, Ching-Ti, Loos, Ruth J.F., Ma, Ronald Ching-wan, MacDonald, Patrick, Massung, Jeffrey, Maurano, Matthew T., McCarthy, Mark I., McVean, Gil, Meigs, James B., Mercader, Josep M., Miller, Melissa R., Mitchell, Braxton, Mohlke, Karen L., Morabito, Samuel, Morgan, Claire, Mullican, Shannon, Narendra, Sharvari, Ng, Maggie C.Y., Nguyen, Lynette, Palmer, Colin N.A., Parker, Stephen C.J., Parrado, Antonio, Parsa, Afshin, Pawlyk, Aaron C., Pearson, Ewan R., Plump, Andrew, Province, Michael, Quertermous, Thomas, Redline, Susan, Reilly, Dermot F., Ren, Bing, Rich, Stephen S., Richards, J. Brent, Rotter, Jerome I., Ruebenacker, Oliver, Ruetten, Hartmut, Salem, Rany M., Sander, Maike, Sanders, Michael, Sanghera, Dharambir, Scott, Laura J., Sengupta, Sebanti, Siedzik, David, Sim, Xueling, Singh, Preeti, Sladek, Robert, Small, Kerrin, Smith, Philip, Stein, Peter, Spalding, Dylan, Stringham, Heather M., Sun, Ying, Susztak, Katalin, ’t Hart, Leen M., Taliun, Daniel, Taylor, Kent, Thomas, Melissa K., Todd, Jennifer A., Udler, Miriam S., Voight, Benjamin, von Grotthuss, Marcin, Wan, Andre, Welch, Ryan P., Wholley, David, Yuksel, Kaan, Zaghloul, Norann A., Jang, Dongkeun, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Brandes, MacKenzie, Dornbos, Peter, Huellas-Bruskiewicz, Kenneth C., Ji, Yue, McMahon, Aoife C., Fauman, Eric B., Kamphaus, Tania Nayak, and Abecasis, Gonçalo R.

Published
2023
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3. Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Author

Justice, Anne E, Karaderi, Tugce, Highland, Heather M, Young, Kristin L, Graff, Mariaelisa, Lu, Yingchang, Turcot, Valérie, Auer, Paul L, Fine, Rebecca S, Guo, Xiuqing, Schurmann, Claudia, Lempradl, Adelheid, Marouli, Eirini, Mahajan, Anubha, Winkler, Thomas W, Locke, Adam E, Medina-Gomez, Carolina, Esko, Tõnu, Vedantam, Sailaja, Giri, Ayush, Lo, Ken Sin, Alfred, Tamuno, Mudgal, Poorva, Ng, Maggie CY, Heard-Costa, Nancy L, Feitosa, Mary F, Manning, Alisa K, Willems, Sara M, Sivapalaratnam, Suthesh, Abecasis, Goncalo, Alam, Dewan S, Allison, Matthew, Amouyel, Philippe, Arzumanyan, Zorayr, Balkau, Beverley, Bastarache, Lisa, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bork-Jensen, Jette, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Broer, Linda, Burt, Amber A, Butterworth, Adam S, Caulfield, Mark J, Cesana, Giancarlo, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der Ida, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Collins, Francis S, Cook, James P, Cox, Amanda J, Crosslin, David S, Danesh, John, de Bakker, Paul IW, Denus, Simon de, Mutsert, Renée de, Dedoussis, George, Demerath, Ellen W, Dennis, Joe G, Denny, Josh C, Di Angelantonio, Emanuele, Dörr, Marcus, Drenos, Fotios, Dubé, Marie-Pierre, Dunning, Alison M, Easton, Douglas F, Elliott, Paul, Evangelou, Evangelos, Farmaki, Aliki-Eleni, Feng, Shuang, Ferrannini, Ele, Ferrieres, Jean, Florez, Jose C, Fornage, Myriam, Fox, Caroline S, Franks, Paul W, Friedrich, Nele, Gan, Wei, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Girotto, Giorgia, Gorski, Mathias, Grallert, Harald, Grarup, Niels, Grove, Megan L, Gustafsson, Stefan, Haessler, Jeff, Hansen, Torben, and Hattersley, Andrew T

Subjects
Clinical Research, Obesity, Genetics, Nutrition, Prevention, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Cardiovascular, Animals, Body Fat Distribution, Body Mass Index, Case-Control Studies, Drosophila, Exome, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Homeostasis, Humans, Lipids, Male, Proteins, Risk Factors, Waist-Hip Ratio, CHD Exome+ Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, InterAct, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF

Published
2019

4. Observational and Genetic Associations of Resting Heart Rate With Aortic Valve Calcium

Author

Whelton, Seamus P, Mauer, Andreas C, Pencina, Karol M, Massaro, Joseph M, D'Agostino, Ralph B, Fox, Caroline S, Hoffmann, Udo, Michos, Erin D, Peloso, Gina M, Dufresne, Line, Engert, James C, Kathiresan, Sekar, Budoff, Matthew, Post, Wendy S, Thanassoulis, George, and O'Donnell, Christopher J

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Cardiovascular, Atherosclerosis, Heart Disease, Genetics, Aging, Aged, Aortic Valve, Calcinosis, Cohort Studies, Female, Genome-Wide Association Study, Heart Rate, Heart Valve Diseases, Humans, Male, Prevalence, Risk Factors, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

It is unknown if lifelong exposure to increased hemodynamic stress from an elevated resting heart rate (HR) may contribute to aortic valve calcium (AVC). We performed multivariate regression analyses using data from 1,266 Framingham Heart Study (FHS) Offspring cohort participants and 6,764 Multi-Ethnic Study of Atherosclerosis (MESA) participants. We constructed a genetic risk score (GRS) for HR using summary-level data in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) AVC Consortium to investigate if there was evidence in favor of a causal relation. AVC was present in 39% of FHS Offspring cohort participants and in 13% of MESA cohort participants. In multivariate adjusted models, participants in the highest resting HR quartiles had significantly greater prevalence of AVC, with a prevalence ratio of 1.19 (95% confidence interval [CI] 0.99 to 1.44) for the FHS Offspring cohort and 1.32 (95% CI 1.12 to 1.63) for the MESA cohort, compared with those in the lowest quartile. There was a similar increase in the prevalence of AVC per standard deviation increase in resting HR in both FHS Offspring (prevalence ratio 1.08, 95% CI 1.01 to 1.15) and MESA (1.10, 95% CI 1.03 to 1.17). In contrast with these observational findings, a HR associated GRS was not significantly associated with AVC. Although our observational analysis indicates that a higher resting HR is associated with AVC, our genetic results do not support a causal relation. Unmeasured environmental and/or lifestyle factors associated with both increased resting HR and AVC that are not fully explained by covariates in our observational models may account for the association between resting HR and AVC.

Published
2018

5. Predictors and outcomes of heart failure with mid‐range ejection fraction

Author

Bhambhani, Vijeta, Kizer, Jorge R, Lima, Joao AC, van der Harst, Pim, Bahrami, Hossein, Nayor, Matthew, de Filippi, Christopher R, Enserro, Danielle, Blaha, Michael J, Cushman, Mary, Wang, Thomas J, Gansevoort, Ron T, Fox, Caroline S, Gaggin, Hanna K, Kop, Willem J, Liu, Kiang, Vasan, Ramachandran S, Psaty, Bruce M, Lee, Douglas S, Brouwers, Frank P, Hillege, Hans L, Bartz, Traci M, Benjamin, Emelia J, Chan, Cheeling, Allison, Matthew, Gardin, Julius M, Januzzi, James L, Levy, Daniel, Herrington, David M, van Gilst, Wiek H, Bertoni, Alain G, Larson, Martin G, de Boer, Rudolf A, Gottdiener, John S, Shah, Sanjiv J, and Ho, Jennifer E

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Cardiovascular, Clinical Research, Heart Disease, Good Health and Well Being, Aged, Cause of Death, Echocardiography, Female, Follow-Up Studies, Heart Failure, Heart Ventricles, Humans, Incidence, Male, Middle Aged, Prognosis, Prospective Studies, Risk Assessment, Stroke Volume, Survival Rate, United States, Heart failure, Risk factor, Ejection fraction, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

AimsWhile heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF) are well described, determinants and outcomes of heart failure with mid-range ejection fraction (HFmrEF) remain unclear. We sought to examine clinical and biochemical predictors of incident HFmrEF in the community.Methods and resultsWe pooled data from four community-based longitudinal cohorts, with ascertainment of new heart failure (HF) classified into HFmrEF [ejection fraction (EF) 41-49%], HFpEF (EF ≥50%), and HFrEF (EF ≤40%). Predictors of incident HF subtypes were assessed using multivariable Cox models. Among 28 820 participants free of HF followed for a median of 12 years, there were 200 new HFmrEF cases, compared with 811 HFpEF and 1048 HFrEF. Clinical predictors of HFmrEF included age, male sex, systolic blood pressure, diabetes mellitus, and prior myocardial infarction (multivariable adjusted P ≤ 0.003 for all). Biomarkers that predicted HFmrEF included natriuretic peptides, cystatin-C, and high-sensitivity troponin (P ≤ 0.0004 for all). Natriuretic peptides were stronger predictors of HFrEF [hazard ratio (HR) 2.00 per 1 standard deviation increase, 95% confidence interval (CI) 1.81-2.20] than of HFmrEF (HR 1.51, 95% CI 1.20-1.90, P = 0.01 for difference), and did not differ in their association with incident HFmrEF and HFpEF (HR 1.56, 95% CI 1.41-1.73, P = 0.68 for difference). All-cause mortality following the onset of HFmrEF was worse than that of HFpEF (50 vs. 39 events per 1000 person-years, P = 0.02), but comparable to that of HFrEF (46 events per 1000 person-years, P = 0.78).ConclusionsWe found overlap in predictors of incident HFmrEF with other HF subtypes. In contrast, mortality risk after HFmrEF was worse than HFpEF, and similar to HFrEF.

Published
2018

6. Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis

Author

van Rooij, Frank JA, Qayyum, Rehan, Smith, Albert V, Zhou, Yi, Trompet, Stella, Tanaka, Toshiko, Keller, Margaux F, Chang, Li-Ching, Schmidt, Helena, Yang, Min-Lee, Chen, Ming-Huei, Hayes, James, Johnson, Andrew D, Yanek, Lisa R, Mueller, Christian, Lange, Leslie, Floyd, James S, Ghanbari, Mohsen, Zonderman, Alan B, Jukema, J Wouter, Hofman, Albert, van Duijn, Cornelia M, Desch, Karl C, Saba, Yasaman, Ozel, Ayse B, Snively, Beverly M, Wu, Jer-Yuarn, Schmidt, Reinhold, Fornage, Myriam, Klein, Robert J, Fox, Caroline S, Matsuda, Koichi, Kamatani, Naoyuki, Wild, Philipp S, Stott, David J, Ford, Ian, Slagboom, P Eline, Yang, Jaden, Chu, Audrey Y, Lambert, Amy J, Uitterlinden, André G, Franco, Oscar H, Hofer, Edith, Ginsburg, David, Hu, Bella, Keating, Brendan, Schick, Ursula M, Brody, Jennifer A, Li, Jun Z, Chen, Zhao, Zeller, Tanja, Guralnik, Jack M, Chasman, Daniel I, Peters, Luanne L, Kubo, Michiaki, Becker, Diane M, Li, Jin, Eiriksdottir, Gudny, Rotter, Jerome I, Levy, Daniel, Grossmann, Vera, Patel, Kushang V, Chen, Chien-Hsiun, Project, The BioBank Japan, Ridker, Paul M, Tang, Hua, Launer, Lenore J, Rice, Kenneth M, Li-Gao, Ruifang, Ferrucci, Luigi, Evans, Michelle K, Choudhuri, Avik, Trompouki, Eirini, Abraham, Brian J, Yang, Song, Takahashi, Atsushi, Kamatani, Yoichiro, Kooperberg, Charles, Harris, Tamara B, Jee, Sun Ha, Coresh, Josef, Tsai, Fuu-Jen, Longo, Dan L, Chen, Yuan-Tsong, Felix, Janine F, Yang, Qiong, Psaty, Bruce M, Boerwinkle, Eric, Becker, Lewis C, Mook-Kanamori, Dennis O, Wilson, James G, Gudnason, Vilmundur, O'Donnell, Christopher J, Dehghan, Abbas, Cupples, L Adrienne, Nalls, Michael A, Morris, Andrew P, Okada, Yukinori, Reiner, Alexander P, and Zon, Leonard I

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Hematology, Africa, Alleles, Animals, Bayes Theorem, Erythrocytes, Erythropoiesis, Ethnicity, Europe, Asia, Eastern, Female, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, RNA-Binding Proteins, Racial Groups, Zebrafish, BioBank Japan Project, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.

Published
2017

7. Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Author

Chu, Audrey Y, Deng, Xuan, Fisher, Virginia A, Drong, Alexander, Zhang, Yang, Feitosa, Mary F, Liu, Ching-Ti, Weeks, Olivia, Choh, Audrey C, Duan, Qing, Dyer, Thomas D, Eicher, John D, Guo, Xiuqing, Heard-Costa, Nancy L, Kacprowski, Tim, Kent, Jack W, Lange, Leslie A, Liu, Xinggang, Lohman, Kurt, Lu, Lingyi, Mahajan, Anubha, O'Connell, Jeffrey R, Parihar, Ankita, Peralta, Juan M, Smith, Albert V, Zhang, Yi, Homuth, Georg, Kissebah, Ahmed H, Kullberg, Joel, Laqua, René, Launer, Lenore J, Nauck, Matthias, Olivier, Michael, Peyser, Patricia A, Terry, James G, Wojczynski, Mary K, Yao, Jie, Bielak, Lawrence F, Blangero, John, Borecki, Ingrid B, Bowden, Donald W, Carr, John Jeffrey, Czerwinski, Stefan A, Ding, Jingzhong, Friedrich, Nele, Gudnason, Vilmunder, Harris, Tamara B, Ingelsson, Erik, Johnson, Andrew D, Kardia, Sharon LR, Langefeld, Carl D, Lind, Lars, Liu, Yongmei, Mitchell, Braxton D, Morris, Andrew P, Mosley, Thomas H, Rotter, Jerome I, Shuldiner, Alan R, Towne, Bradford, Völzke, Henry, Wallaschofski, Henri, Wilson, James G, Allison, Matthew, Lindgren, Cecilia M, Goessling, Wolfram, Cupples, L Adrienne, Steinhauser, Matthew L, and Fox, Caroline S

Subjects
Nutrition, Human Genome, Genetics, Adipocytes, Animals, Body Fat Distribution, Cell Differentiation, Cohort Studies, Ethnicity, Female, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Mice, Mice, Inbred C57BL, Obesity, Phenotype, Polymorphism, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10-8; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Published
2017

8. Rare variant associations with waist-to-hip ratio in European-American and African-American women from the NHLBI-Exome Sequencing Project

Author

Kan, Mengyuan, Auer, Paul L, Wang, Gao T, Bucasas, Kristine L, Hooker, Stanley, Rodriguez, Alejandra, Li, Biao, Ellis, Jaclyn, Adrienne Cupples, L, Ida Chen, Yii-Der, Dupuis, Josée, Fox, Caroline S, Gross, Myron D, Smith, Joshua D, Heard-Costa, Nancy, Meigs, James B, Pankow, James S, Rotter, Jerome I, Siscovick, David, Wilson, James G, Shendure, Jay, Jackson, Rebecca, Peters, Ulrike, Zhong, Hua, Lin, Danyu, Hsu, Li, Franceschini, Nora, Carlson, Chris, Abecasis, Goncalo, Gabriel, Stacey, Bamshad, Michael J, Altshuler, David, Nickerson, Deborah A, North, Kari E, Lange, Leslie A, Reiner, Alexander P, and Leal, Suzanne M

Subjects
Biological Sciences, Genetics, Prevention, Human Genome, Obesity, Clinical Research, Diabetes, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Metabolic and endocrine, Adult, Black or African American, Aged, Aged, 80 and over, Alleles, Exome, Female, Humans, I-kappa B Kinase, Middle Aged, Polymorphism, Genetic, Transcription Factors, Waist-Hip Ratio, White People, NHLBI-Exome Sequencing Project, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

Waist-to-hip ratio (WHR), a relative comparison of waist and hip circumferences, is an easily accessible measurement of body fat distribution, in particular central abdominal fat. A high WHR indicates more intra-abdominal fat deposition and is an established risk factor for cardiovascular disease and type 2 diabetes. Recent genome-wide association studies have identified numerous common genetic loci influencing WHR, but the contributions of rare variants have not been previously reported. We investigated rare variant associations with WHR in 1510 European-American and 1186 African-American women from the National Heart, Lung, and Blood Institute-Exome Sequencing Project. Association analysis was performed on the gene level using several rare variant association methods. The strongest association was observed for rare variants in IKBKB (P=4.0 × 10(-8)) in European-Americans, where rare variants in this gene are predicted to decrease WHRs. The activation of the IKBKB gene is involved in inflammatory processes and insulin resistance, which may affect normal food intake and body weight and shape. Meanwhile, aggregation of rare variants in COBLL1, previously found to harbor common variants associated with WHR and fasting insulin, were nominally associated (P=2.23 × 10(-4)) with higher WHR in European-Americans. However, these significant results are not shared between African-Americans and European-Americans that may be due to differences in the allelic architecture of the two populations and the small sample sizes. Our study indicates that the combined effect of rare variants contribute to the inter-individual variation in fat distribution through the regulation of insulin response.

Published
2016

9. Past Decline Versus Current eGFR and Subsequent Mortality Risk

Author

Naimark, David MJ, Grams, Morgan E, Matsushita, Kunihiro, Black, Corri, Drion, Iefke, Fox, Caroline S, Inker, Lesley A, Ishani, Areef, Jee, Sun Ha, Kitamura, Akihiko, Lea, Janice P, Nally, Joseph, Peralta, Carmen Alicia, Rothenbacher, Dietrich, Ryu, Seungho, Tonelli, Marcello, Yatsuya, Hiroshi, Coresh, Josef, Gansevoort, Ron T, Warnock, David G, Woodward, Mark, and de Jong, Paul E

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Kidney Disease, Clinical Research, Prevention, Renal and urogenital, Good Health and Well Being, Aged, Cause of Death, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, Proportional Hazards Models, Renal Insufficiency, Chronic, Risk Factors, Time Factors, CKD Prognosis Consortium, chronic kidney disease, epidemiology, glomerular filtration rate, mortality, outcomes, Urology & Nephrology, Clinical sciences
Abstract

A single determination of eGFR associates with subsequent mortality risk. Prior decline in eGFR indicates loss of kidney function, but the relationship to mortality risk is uncertain. We conducted an individual-level meta-analysis of the risk of mortality associated with antecedent eGFR slope, adjusting for established risk factors, including last eGFR, among 1.2 million subjects from 12 CKD and 22 other cohorts within the CKD Prognosis Consortium. Over a 3-year antecedent period, 12% of participants in the CKD cohorts and 11% in the other cohorts had an eGFR slope 5 ml/min per 1.73 m(2) per year, respectively. Compared with a slope of 0 ml/min per 1.73 m(2) per year, a slope of -6 ml/min per 1.73 m(2) per year associated with adjusted hazard ratios for all-cause mortality of 1.25 (95% confidence interval [95% CI], 1.09 to 1.44) among CKD cohorts and 1.15 (95% CI, 1.01 to 1.31) among other cohorts during a follow-up of 3.2 years. A slope of +6 ml/min per 1.73 m(2) per year also associated with higher all-cause mortality risk, with adjusted hazard ratios of 1.58 (95% CI, 1.29 to 1.95) among CKD cohorts and 1.43 (95% CI, 1.11 to 1.84) among other cohorts. Results were similar for cardiovascular and noncardiovascular causes of death and stronger for longer antecedent periods (3 versus

Published
2016

10. Interaction Between Midlife Blood Glucose and APOE Genotype Predicts Later Alzheimer’s Disease Pathology

Author

Bangen, Katherine J, Himali, Jayandra J, Beiser, Alexa S, Nation, Daniel A, Libon, David J, Fox, Caroline S, Seshadri, Sudha, Wolf, Philip A, McKee, Ann C, Au, Rhoda, and Delano-Wood, Lisa

Subjects
Dementia, Alzheimer's Disease Related Dementias (ADRD), Brain Disorders, Heart Disease, Genetics, Aging, Cardiovascular, Alzheimer's Disease, Prevention, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Acquired Cognitive Impairment, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Neurological, Alzheimer Disease, Apolipoprotein E4, Blood Glucose, Brain, Cohort Studies, Female, Genotype, Humans, Male, Middle Aged, Neurofibrillary Tangles, Neuropsychological Tests, Predictive Value of Tests, Risk Factors, Vascular Diseases, Alzheimer's disease, apolipoprotein E, diabetes, glucose, neuropathology, vascular risk, Alzheimer’s disease, Clinical Sciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Elevated blood glucose and the apolipoprotein (APOE) ɛ4 allele have both been associated with increased dementia risk; however, the neuropathological mechanisms underlying these associations remain unclear. We examined the impact of APOE genotype and midlife blood glucose on post-mortem vascular and Alzheimer's disease (AD) neuropathology. Ninety-four participants from the Framingham Heart Study without diagnosed diabetes underwent health examination at midlife and brain autopsy at death. Histopathological measures of vascular and AD neuropathology were obtained and analyzed. Results demonstrated that, among APOE ɛ4 carriers, elevated blood glucose was associated with more severe AD pathology. There was no such relationship with vascular pathology. In a relatively healthy sample with low vascular risk burden, midlife elevated blood glucose was associated with greater AD pathology among APOE ɛ4 carriers. A better understanding of interactive effects of APOE genotype and vascular risk on neuropathology has implications for identification of individuals at risk for decline and long-term preventive treatment.

Published
2016

11. Genetic loci associated with ideal cardiovascular health: A meta-analysis of genome-wide association studies

Author

Allen, Norrina B, Lloyd-Jones, Donald, Hwang, Shih-Jen, Rasmussen-Torvik, Laura, Fornage, Myriam, Morrison, Alanna C, Baldridge, Abigail S, Boerwinkle, Eric, Levy, Daniel, Cupples, L Adrienne, Fox, Caroline S, Thanassoulis, George, Dufresne, Line, Daviglus, Martha, Johnson, Andrew D, Reis, Jared, Rotter, Jerome, Palmas, Walter, Allison, Mathew, Pankow, James S, and O'Donnell, Christopher J

Subjects
Human Genome, Aging, Genetics, Prevention, Atherosclerosis, Cardiovascular, Heart Disease, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Apolipoprotein C-I, Cardiovascular Diseases, Gene Expression Profiling, Genetic Loci, Genome-Wide Association Study, Humans, Protective Factors, Risk factors, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

BackgroundMultiple genetic loci are associated with clinical cardiovascular (CV) disease and individual CV risk factors. Individuals with ideal levels of all major CV risk factors have very low risk for CV disease morbidity or mortality. Ideal levels of risk factors can be attained by lifestyle modifications; however, little is known about gene variants associated with ideal CV health. Our objective was to carry out a genome-wide association study on the trait.Methods and resultsWe examined 2 dichotomous phenotypes of ideal CV health-clinical (untreated cholesterol

Published
2016

12. Metabolite Profiles Predict Acute Kidney Injury and Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement

Author

Elmariah, Sammy, Farrell, Laurie A, Daher, Maureen, Shi, Xu, Keyes, Michelle J, Cain, Carolyn H, Pomerantsev, Eugene, Vlahakes, Gus J, Inglessis, Ignacio, Passeri, Jonathan J, Palacios, Igor F, Fox, Caroline S, Rhee, Eugene P, and Gerszten, Robert E

Subjects
Transplantation, Kidney Disease, Clinical Research, Aging, Heart Disease, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Renal and urogenital, Good Health and Well Being, Acute Kidney Injury, Aged, Aged, 80 and over, Aortic Valve Stenosis, Biomarkers, Cardiac Catheterization, Chromatography, Liquid, Female, Heart Valve Prosthesis Implantation, Humans, Kaplan-Meier Estimate, Linear Models, Logistic Models, Male, Mass Spectrometry, Massachusetts, Metabolomics, Multivariate Analysis, Odds Ratio, Predictive Value of Tests, Prevalence, Risk Assessment, Risk Factors, S-Adenosylhomocysteine, Treatment Outcome, aortic stenosis, kidney, metabolomics, mortality, transcatheter aortic valve implantation, Cardiorespiratory Medicine and Haematology
Abstract

BackgroundAcute kidney injury (AKI) occurs commonly after transcatheter aortic valve replacement (TAVR) and is associated with markedly increased postoperative mortality. We previously identified plasma metabolites predictive of incident chronic kidney disease, but whether metabolite profiles can identify those at risk of AKI is unknown.Methods and resultsWe performed liquid chromatography-mass spectrometry-based metabolite profiling on plasma from patients undergoing TAVR and subjects from the community-based Framingham Heart Study (N=2164). AKI was defined by using the Valve Academic Research Consortium-2 criteria. Of 44 patients (mean age 82±9 years, 52% female) undergoing TAVR, 22 (50%) had chronic kidney disease and 9 (20%) developed AKI. Of 85 metabolites profiled, we detected markedly concordant cross-sectional metabolic changes associated with chronic kidney disease in the hospital-based TAVR and Framingham Heart Study cohorts. Baseline levels of 5-adenosylhomocysteine predicted AKI after TAVR, despite adjustment for baseline glomerular filtration rate (odds ratio per 1-SD increase 5.97, 95% CI 1.62-22.0; P=0.007). Of the patients who had AKI, 6 (66.7%) subsequently died, compared with 3 (8.6%) deaths among those patients who did not develop AKI (P=0.0008) over a median follow-up of 7.8 months. 5-adenosylhomocysteine was predictive of all-cause mortality after TAVR (hazard ratio per 1-SD increase 2.96, 95% CI 1.33-6.58; P=0.008), independent of baseline glomerular filtration rate.ConclusionsIn an elderly population with severe aortic stenosis undergoing TAVR, metabolite profiling improves the prediction of AKI. Given the multifactorial nature of AKI after TAVR, metabolite profiles may identify those patients with reduced renal reserve.

Published
2016

13. Update on Prevention of Cardiovascular Disease in Adults With Type 2 Diabetes Mellitus in Light of Recent Evidence

Author

Fox, Caroline S, Golden, Sherita Hill, Anderson, Cheryl, Bray, George A, Burke, Lora E, de Boer, Ian H, Deedwania, Prakash, Eckel, Robert H, Ershow, Abby G, Fradkin, Judith, Inzucchi, Silvio E, Kosiborod, Mikhail, Nelson, Robert G, Patel, Mahesh J, Pignone, Michael, Quinn, Laurie, Schauer, Philip R, Selvin, Elizabeth, and Vafiadis, Dorothea K

Subjects
Clinical Research, Heart Disease, Nutrition, Cardiovascular, Diabetes, Prevention, Metabolic and endocrine, Good Health and Well Being, American Heart Association, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Humans, Practice Guidelines as Topic, Primary Prevention, Randomized Controlled Trials as Topic, Risk Factors, United States, American Heart Association Diabetes Committee of the Council on Lifestyle and Cardiometabolic Health, Council on Clinical Cardiology, Council on Cardiovascular and Stroke Nursing, Council on Cardiovascular Surgery and Anesthesia, Council on Quality of Care and Outcomes Research, and the American Diabetes Association, AHA Scientific Statements, cardiovascular disease, diabetes, primary prevention, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

Cardiovascular disease risk factor control as primary prevention in patients with type 2 diabetes mellitus has changed substantially in the past few years. The purpose of this scientific statement is to review the current literature and key clinical trials pertaining to blood pressure and blood glucose control, cholesterol management, aspirin therapy, and lifestyle modification. We present a synthesis of the recent literature, new guidelines, and clinical targets, including screening for kidney and subclinical cardiovascular disease for the contemporary management of patients with type 2 diabetes mellitus.

Published
2015

14. Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies

Author

Appel, Lawrence J, Greene, Tom, Chen, Teresa K, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Nally, Joseph, Navaneethan, Sankar D, Schold, Jesse D, Weldegiorgis, Misghina, Herrington, William G, Smith, Margaret, Hsu, C Yenchih, Hwang, Shih-Jen, Chang, Alex R, Kirchner, H. Lester, Green, Jamie A, Ho, Kevin, Marks, Angharad, Prescott, Gordon, Clark, Laura E, Fluck, Nick, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Van Zuilen, Arjan, Van den Brand, Jan A, Sarnak, Mark J, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen G, Nadukuru, Rajiv, Metzger, Marie, Flamant, Martin, Houillier, Pascal, Haymann, Jean-Philippe, Froissart, Marc, Kenealy, Timothy, Elley, Raina C, Collins, John F, Drury, Paul L, Cuddeback, John K, Ciemins, Elizabeth L, Stempniewicz, Rich, Nelson, Robert G, Knowler, William C, Bakker, Stephen J, Major, Rupert W, Medcalf, James F, Shepherd, David, Barrett-Connor, Elizabeth, Bergstrom, Jaclyn, Ix, Joachim H, Molnar, Miklos Z, Sumida, Keiichi, de Zeeuw, Dick, Brenner, Barry, Qureshi, Abdul R, Elinder, Carl-Gustaf, Runesson, Bjorn, Evans, Marie, Segelmark, Marten, Stendahl, Maria, Schön, Staffan, Naimark, David M, Tangri, Navdeep, Sud, Maneesh, Hirayama, Atsushi, Ichikawa, Kazunobu, Bilo, Henk JG, Landman, Gijs WD, Van Hateren, Kornelis JJ, Kleefstra, Nanne, Hallan, Stein I, Ballew, Shoshana H, Chen, Jingsha, Kwak, Lucia, Surapaneni, Aditya, Parving, Hans-Henrik, Rodby, Roger A., Rohde, Richard D, Lewis, Julia B, Lewis, Edmund, Perrone, Ronald D, Abebe, Kaleab Z, Hou, Fan F, Xie, Di, Hunsicker, Lawrence G, Imai, Enyu, Kobayashi, Fumiaki, Makino, Hirofumi, Ito, Sadayoshi, Remuzzi, Giuseppe, Ruggenenti, Piero, Eckardt, Kai-Uwe, Gudmundsdottir, Hrefna, Maciulaitis, Romaldas, Manley, Tom, Smith, Kimberly, Stockbridge, Norman, Thompson, Aliza, Vetter, Thorsten, Willis, Kerry, Zhang, Luxia, Coresh, Josef, Heerspink, Hiddo J L, Sang, Yingying, Matsushita, Kunihiro, Arnlov, Johan, Astor, Brad C, Black, Corri, Brunskill, Nigel J, Carrero, Juan-Jesus, Feldman, Harold I, Fox, Caroline S, Inker, Lesley A, Ishani, Areef, Jassal, Simerjot, Konta, Tsuneo, Polkinghorne, Kevan, Romundstad, Solfrid, Solbu, Marit D, Stempniewicz, Nikita, Stengel, Benedicte, Tonelli, Marcello, Umesawa, Mitsumasa, Waikar, Sushrut S, Wen, Chi-Pang, Wetzels, Jack F M, Woodward, Mark, Grams, Morgan E, Kovesdy, Csaba P, Levey, Andrew S, and Gansevoort, Ron T

Published
2019
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15. Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

Author

Ibrahim-Verbaas, Carla A, Fornage, Myriam, Bis, Joshua C, Choi, Seung Hoan, Psaty, Bruce M, Meigs, James B, Rao, Madhu, Nalls, Mike, Fontes, Joao D, O'Donnell, Christopher J, Kathiresan, Sekar, Ehret, Georg B, Fox, Caroline S, Malik, Rainer, Dichgans, Martin, Schmidt, Helena, Lahti, Jari, Heckbert, Susan R, Lumley, Thomas, Rice, Kenneth, Rotter, Jerome I, Taylor, Kent D, Folsom, Aaron R, Boerwinkle, Eric, Rosamond, Wayne D, Shahar, Eyal, Gottesman, Rebecca F, Koudstaal, Peter J, Amin, Najaf, Wieberdink, Renske G, Dehghan, Abbas, Hofman, Albert, Uitterlinden, André G, Destefano, Anita L, Debette, Stephanie, Xue, Luting, Beiser, Alexa, Wolf, Philip A, Decarli, Charles, Ikram, M Arfan, Seshadri, Sudha, Mosley, Thomas H, Longstreth, WT, van Duijn, Cornelia M, and Launer, Lenore J

Subjects
Humans, Genetic Predisposition to Disease, Area Under Curve, Risk Factors, Regression Analysis, Case-Control Studies, Cohort Studies, ROC Curve, Age Factors, Sex Factors, Genotype, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, European Continental Ancestry Group, Female, Male, Stroke, Genome-Wide Association Study, genetic epidemiology, risk factors, stroke, Polymorphism, Single Nucleotide, and over, Neurology & Neurosurgery, Clinical Sciences, Cardiorespiratory Medicine and Haematology, Neurosciences
Abstract

Background and purposeBeyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors.MethodsThe study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke.ResultsIn the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P

Published
2014

16. Heart Disease and Stroke Statistics—2014 Update

Author

Go, Alan S, Mozaffarian, Dariush, Roger, Véronique L, Benjamin, Emelia J, Berry, Jarett D, Blaha, Michael J, Dai, Shifan, Ford, Earl S, Fox, Caroline S, Franco, Sheila, Fullerton, Heather J, Gillespie, Cathleen, Hailpern, Susan M, Heit, John A, Howard, Virginia J, Huffman, Mark D, Judd, Suzanne E, Kissela, Brett M, Kittner, Steven J, Lackland, Daniel T, Lichtman, Judith H, Lisabeth, Lynda D, Mackey, Rachel H, Magid, David J, Marcus, Gregory M, Marelli, Ariane, Matchar, David B, McGuire, Darren K, Mohler, Emile R, Moy, Claudia S, Mussolino, Michael E, Neumar, Robert W, Nichol, Graham, Pandey, Dilip K, Paynter, Nina P, Reeves, Matthew J, Sorlie, Paul D, Stein, Joel, Towfighi, Amytis, Turan, Tanya N, Virani, Salim S, Wong, Nathan D, Woo, Daniel, and Turner, Melanie B

Subjects
American Heart Association, Cardiology, Heart Diseases, Humans, Stroke, United States, AHA Scientific Statements, cardiovascular diseases, epidemiology, risk factors, statistics, stroke, American Heart Association Statistics Committee and Stroke Statistics Subcommittee, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update is a critical resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best available national data on heart disease, stroke, and other cardiovascular disease-related morbidity and mortality and the risks, quality of care, use of medical procedures and operations, and costs associated with the management of these diseases in a single document. Indeed, since 1999, the Statistical Update has been cited >10 500 times in the literature, based on citations of all annual versions. In 2012 alone, the various Statistical Updates were cited ≈3500 times (data from Google Scholar). In recent years, the Statistical Update has undergone some major changes with the addition of new chapters and major updates across multiple areas, as well as increasing the number of ways to access and use the information assembled. For this year's edition, the Statistics Committee, which produces the document for the AHA, updated all of the current chapters with the most recent nationally representative data and inclusion of relevant articles from the literature over the past year. This year's edition includes a new chapter on peripheral artery disease, as well as new data on the monitoring and benefits of cardiovascular health in the population, with additional new focus on evidence-based approaches to changing behaviors, implementation strategies, and implications of the AHA's 2020 Impact Goals. Below are a few highlights from this year's Update. © 2013 American Heart Association, Inc.

Published
2014

17. Executive Summary

Author

Go, Alan S, Mozaffarian, Dariush, Roger, Véronique L, Benjamin, Emelia J, Berry, Jarett D, Blaha, Michael J, Dai, Shifan, Ford, Earl S, Fox, Caroline S, Franco, Sheila, Fullerton, Heather J, Gillespie, Cathleen, Hailpern, Susan M, Heit, John A, Howard, Virginia J, Huffman, Mark D, Judd, Suzanne E, Kissela, Brett M, Kittner, Steven J, Lackland, Daniel T, Lichtman, Judith H, Lisabeth, Lynda D, Mackey, Rachel H, Magid, David J, Marcus, Gregory M, Marelli, Ariane, Matchar, David B, McGuire, Darren K, Mohler, Emile R, Moy, Claudia S, Mussolino, Michael E, Neumar, Robert W, Nichol, Graham, Pandey, Dilip K, Paynter, Nina P, Reeves, Matthew J, Sorlie, Paul D, Stein, Joel, Towfighi, Amytis, Turan, Tanya N, Virani, Salim S, Wong, Nathan D, Woo, Daniel, and Turner, Melanie B

Subjects
American Heart Association, Cardiology, Heart Diseases, Humans, Prevalence, Research Report, Risk Factors, Stroke, United States, AHA Scientific Statements, cardiovascular diseases, epidemiology, risk factors, statistics, stroke, American Heart Association Statistics Committee and Stroke Statistics Subcommittee, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update is a critical resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best available national data on heart disease, stroke, and other cardiovascular disease-related morbidity and mortality and the risks, quality of care, use of medical procedures and operations, and costs associated with the management of these diseases in a single document. Indeed, since 1999, the Statistical Update has been cited >10 500 times in the literature, based on citations of all annual versions. In 2012 alone, the various Statistical Updates were cited ≈3500 times (data from Google Scholar). In recent years, the Statistical Update has undergone some major changes with the addition of new chapters and major updates across multiple areas, as well as increasing the number of ways to access and use the information assembled. For this year's edition, the Statistics Committee, which produces the document for the AHA, updated all of the current chapters with the most recent nationally representative data and inclusion of relevant articles from the literature over the past year. This year's edition includes a new chapter on peripheral artery disease, as well as new data on the monitoring and benefits of cardiovascular health in the population, with additional new focus on evidence-based approaches to changing behaviors, implementation strategies, and implications of the AHA's 2020 Impact Goals. Below are a few highlights from this year's Update. © 2013 American Heart Association, Inc.

Published
2014

18. Association of a Cystatin C Gene Variant With Cystatin C Levels, CKD, and Risk of Incident Cardiovascular Disease and Mortality

Author

O'Seaghdha, Conall M, Tin, Adrienne, Yang, Qiong, Katz, Ronit, Liu, YongMei, Harris, Tamara, Astor, Brad, Coresh, Josef, Fox, Caroline S, Kao, WH Linda, and Shlipak, Michael G

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Aging, Genetics, Heart Disease, Kidney Disease, Prevention, Cardiovascular, Clinical Research, Renal and urogenital, Good Health and Well Being, Aged, Bias, Biomarkers, Cardiovascular Diseases, Creatinine, Cystatin C, Female, Genetic Variation, Glomerular Filtration Rate, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Renal Insufficiency, Chronic, Risk Assessment, Risk Factors, Severity of Illness Index, Statistics as Topic, Survival Rate, chronic kidney disease, genetics, single-nucleotide polymorphism, net reclassification improvement, Public Health and Health Services, Urology & Nephrology, Clinical sciences
Abstract

BackgroundCarriers of the T allele of the single-nucleotide polymorphism rs13038305 tend to have lower cystatin C levels and higher cystatin C-based estimated glomerular filtration rate (eGFRcys). Adjusting for this genetic effect on cystatin C concentrations may improve GFR estimation, reclassify cases of chronic kidney disease (CKD), and strengthen risk estimates for cardiovascular disease (CVD) and mortality.Study designObservational.Setting & population4 population-based cohorts: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health (CHS), Framingham Heart (FHS), and Health, Aging, and Body Composition (Health ABC) studies.PredictorsWe estimated the association of rs13038305 with eGFRcys and serum creatinine-based eGFR (eGFRcr) and performed longitudinal analyses of the associations of eGFRcys with mortality and cardiovascular events following adjustment for rs13038305.OutcomesWe assessed reclassification by genotype-adjusted eGFRcys across CKD categories:

Published
2014

19. Executive summary: heart disease and stroke statistics--2014 update: a report from the American Heart Association.

Author

Go, Alan S, Mozaffarian, Dariush, Roger, Véronique L, Benjamin, Emelia J, Berry, Jarett D, Blaha, Michael J, Dai, Shifan, Ford, Earl S, Fox, Caroline S, Franco, Sheila, Fullerton, Heather J, Gillespie, Cathleen, Hailpern, Susan M, Heit, John A, Howard, Virginia J, Huffman, Mark D, Judd, Suzanne E, Kissela, Brett M, Kittner, Steven J, Lackland, Daniel T, Lichtman, Judith H, Lisabeth, Lynda D, Mackey, Rachel H, Magid, David J, Marcus, Gregory M, Marelli, Ariane, Matchar, David B, McGuire, Darren K, Mohler, Emile R, Moy, Claudia S, Mussolino, Michael E, Neumar, Robert W, Nichol, Graham, Pandey, Dilip K, Paynter, Nina P, Reeves, Matthew J, Sorlie, Paul D, Stein, Joel, Towfighi, Amytis, Turan, Tanya N, Virani, Salim S, Wong, Nathan D, Woo, Daniel, Turner, Melanie B, and American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Subjects
American Heart Association Statistics Committee and Stroke Statistics Subcommittee, Humans, Heart Diseases, Prevalence, Risk Factors, Cardiology, American Heart Association, United States, Stroke, Research Report, AHA Scientific Statements, cardiovascular diseases, epidemiology, risk factors, statistics, stroke, Cardiovascular System & Hematology, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services
Published
2014

20. Genome-wide association of body fat distribution in African ancestry populations suggests new loci.

Author

Liu, Ching-Ti, Monda, Keri L, Taylor, Kira C, Lange, Leslie, Demerath, Ellen W, Palmas, Walter, Wojczynski, Mary K, Ellis, Jaclyn C, Vitolins, Mara Z, Liu, Simin, Papanicolaou, George J, Irvin, Marguerite R, Xue, Luting, Griffin, Paula J, Nalls, Michael A, Adeyemo, Adebowale, Liu, Jiankang, Li, Guo, Ruiz-Narvaez, Edward A, Chen, Wei-Min, Chen, Fang, Henderson, Brian E, Millikan, Robert C, Ambrosone, Christine B, Strom, Sara S, Guo, Xiuqing, Andrews, Jeanette S, Sun, Yan V, Mosley, Thomas H, Yanek, Lisa R, Shriner, Daniel, Haritunians, Talin, Rotter, Jerome I, Speliotes, Elizabeth K, Smith, Megan, Rosenberg, Lynn, Mychaleckyj, Josyf, Nayak, Uma, Spruill, Ida, Garvey, W Timothy, Pettaway, Curtis, Nyante, Sarah, Bandera, Elisa V, Britton, Angela F, Zonderman, Alan B, Rasmussen-Torvik, Laura J, Chen, Yii-Der Ida, Ding, Jingzhong, Lohman, Kurt, Kritchevsky, Stephen B, Zhao, Wei, Peyser, Patricia A, Kardia, Sharon LR, Kabagambe, Edmond, Broeckel, Ulrich, Chen, Guanjie, Zhou, Jie, Wassertheil-Smoller, Sylvia, Neuhouser, Marian L, Rampersaud, Evadnie, Psaty, Bruce, Kooperberg, Charles, Manson, Joann E, Kuller, Lewis H, Ochs-Balcom, Heather M, Johnson, Karen C, Sucheston, Lara, Ordovas, Jose M, Palmer, Julie R, Haiman, Christopher A, McKnight, Barbara, Howard, Barbara V, Becker, Diane M, Bielak, Lawrence F, Liu, Yongmei, Allison, Matthew A, Grant, Struan FA, Burke, Gregory L, Patel, Sanjay R, Schreiner, Pamela J, Borecki, Ingrid B, Evans, Michele K, Taylor, Herman, Sale, Michele M, Howard, Virginia, Carlson, Christopher S, Rotimi, Charles N, Cushman, Mary, Harris, Tamara B, Reiner, Alexander P, Cupples, L Adrienne, North, Kari E, and Fox, Caroline S

Subjects
Humans, Obesity, Waist-Hip Ratio, Polymorphism, Single Nucleotide, African Continental Ancestry Group, European Continental Ancestry Group, Female, Male, Adiposity, Body Fat Distribution, Genome-Wide Association Study, Genetic Loci, Polymorphism, Single Nucleotide, Developmental Biology, Genetics
Abstract

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values

Published
2013

21. Heart disease and stroke statistics--2013 update: a report from the American Heart Association.

Author

Go, Alan S, Mozaffarian, Dariush, Roger, Véronique L, Benjamin, Emelia J, Berry, Jarett D, Borden, William B, Bravata, Dawn M, Dai, Shifan, Ford, Earl S, Fox, Caroline S, Franco, Sheila, Fullerton, Heather J, Gillespie, Cathleen, Hailpern, Susan M, Heit, John A, Howard, Virginia J, Huffman, Mark D, Kissela, Brett M, Kittner, Steven J, Lackland, Daniel T, Lichtman, Judith H, Lisabeth, Lynda D, Magid, David, Marcus, Gregory M, Marelli, Ariane, Matchar, David B, McGuire, Darren K, Mohler, Emile R, Moy, Claudia S, Mussolino, Michael E, Nichol, Graham, Paynter, Nina P, Schreiner, Pamela J, Sorlie, Paul D, Stein, Joel, Turan, Tanya N, Virani, Salim S, Wong, Nathan D, Woo, Daniel, Turner, Melanie B, and American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Subjects
American Heart Association Statistics Committee and Stroke Statistics Subcommittee, Humans, Heart Diseases, Prevalence, Risk Factors, American Heart Association, United States, Stroke, AHA Scientific Statements, cardiovascular diseases, epidemiology, risk factors, statistics, stroke, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update*The Statistical Update is a valuable resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best national data available on heart disease, stroke, and other cardiovascular disease-related morbidity and mortality and the risks, quality of care, medical procedures and operations, and costs associated with the management of these diseases in a single document*Indeed, since 1999, the Statistical Update has been cited >10 500 times in the literature, based on citations of all annual versions*In 2011 alone, the various Statistical Updates were cited ≈1500 times (data from ISI Web of Science)*In recent years, the Statistical Update has undergone some major changes with the addition of new chapters and major updates across multiple areas, as well as increasing the number of ways to access and use the information assembled*For this year's edition, the Statistics Committee, which produces the document for the AHA, updated all of the current chapters with the most recent nationally representative data and inclusion of relevant articles from the literature over the past year*This year's edition also implements a new chapter organization to reflect the spectrum of cardiovascular health behaviors and health factors and risks, as well as subsequent complicating conditions, disease states, and outcomes*Also, the 2013 Statistical Update contains new data on the monitoring and benefits of cardiovascular health in the population, with additional new focus on evidence-based approaches to changing behaviors, implementation strategies, and implications of the AHA's 2020 Impact Goals*Below are a few highlights from this year's Update . © 2013 American Heart Association, Inc.

Published
2013

22. Executive summary: heart disease and stroke statistics--2013 update: a report from the American Heart Association.

Author

Go, Alan S, Mozaffarian, Dariush, Roger, Véronique L, Benjamin, Emelia J, Berry, Jarett D, Borden, William B, Bravata, Dawn M, Dai, Shifan, Ford, Earl S, Fox, Caroline S, Franco, Sheila, Fullerton, Heather J, Gillespie, Cathleen, Hailpern, Susan M, Heit, John A, Howard, Virginia J, Huffman, Mark D, Kissela, Brett M, Kittner, Steven J, Lackland, Daniel T, Lichtman, Judith H, Lisabeth, Lynda D, Magid, David, Marcus, Gregory M, Marelli, Ariane, Matchar, David B, McGuire, Darren K, Mohler, Emile R, Moy, Claudia S, Mussolino, Michael E, Nichol, Graham, Paynter, Nina P, Schreiner, Pamela J, Sorlie, Paul D, Stein, Joel, Turan, Tanya N, Virani, Salim S, Wong, Nathan D, Woo, Daniel, Turner, Melanie B, and American Heart Association Statistics Committee and Stroke Statistics Subcommittee

Subjects
American Heart Association Statistics Committee and Stroke Statistics Subcommittee, Humans, Heart Diseases, Obesity, Prevalence, Age Distribution, American Heart Association, United States, Stroke, AHA Scientific Statements, cardiovascular diseases, epidemiology, risk factors, statistics, stroke, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update.*The Statistical Update is a valuable resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best national data available on heart disease, stroke, and other cardiovascular disease-related morbidity and mortality and the risks, quality of care, medical procedures and operations, and costs associated with the management of these diseases in a single document Indeed, since 1999, the Statistical Update has been cited >10 500 times in the literature, based on citations of all annual versions. In 2011 alone, the various Statistical Updates were cited ∼1500 times (data from ISI Web of Science). In recent years, the Statistical Update has undergone some major changes with the addition of new chapters and major updates across multiple areas, as well as increasing the number of ways to access and use the information assembled. For this year's edition, the Statistics Committee, which produces the document for the AHA, updated all of the current chapters with the most recent nationally representative data and inclusion of relevant articles from the literature over the past year. This year's edition also implements a new chapter organization to reflect the spectrum of cardiovascular health behaviors and health factors and risks, as well as subsequent complicating conditions, disease states, and outcomes. Also, the 2013 Statistical Update contains new data on the monitoring and benefits of cardiovascular health in the population, with additional new focus on evidence-based approaches to changing behaviors, implementation strategies, and implications of the AHA's 2020 Impact Goals. Below are a few highlights from this year's Update. © 2013 American Heart Association, Inc.

Published
2013

24. No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels

Author

Scott, Robert A, Chu, Audrey Y, Grarup, Niels, Manning, Alisa K, Hivert, Marie-France, Shungin, Dmitry, Tönjes, Anke, Yesupriya, Ajay, Barnes, Daniel, Bouatia-Naji, Nabila, Glazer, Nicole L, Jackson, Anne U, Kutalik, Zoltán, Lagou, Vasiliki, Marek, Diana, Rasmussen-Torvik, Laura J, Stringham, Heather M, Tanaka, Toshiko, Aadahl, Mette, Arking, Dan E, Bergmann, Sven, Boerwinkle, Eric, Bonnycastle, Lori L, Bornstein, Stefan R, Brunner, Eric, Bumpstead, Suzannah J, Brage, Soren, Carlson, Olga D, Chen, Han, Chen, Yii-Der Ida, Chines, Peter S, Collins, Francis S, Couper, David J, Dennison, Elaine M, Dowling, Nicole F, Egan, Josephine S, Ekelund, Ulf, Erdos, Michael R, Forouhi, Nita G, Fox, Caroline S, Goodarzi, Mark O, Grässler, Jürgen, Gustafsson, Stefan, Hallmans, Göran, Hansen, Torben, Hingorani, Aroon, Holloway, John W, Hu, Frank B, Isomaa, Bo, Jameson, Karen A, Johansson, Ingegerd, Jonsson, Anna, Jørgensen, Torben, Kivimaki, Mika, Kovacs, Peter, Kumari, Meena, Kuusisto, Johanna, Laakso, Markku, Lecoeur, Cécile, Lévy-Marchal, Claire, Li, Guo, Loos, Ruth JF, Lyssenko, Valeri, Marmot, Michael, Marques-Vidal, Pedro, Morken, Mario A, Müller, Gabriele, North, Kari E, Pankow, James S, Payne, Felicity, Prokopenko, Inga, Psaty, Bruce M, Renström, Frida, Rice, Ken, Rotter, Jerome I, Rybin, Denis, Sandholt, Camilla H, Sayer, Avan A, Shrader, Peter, Schwarz, Peter EH, Siscovick, David S, Stančáková, Alena, Stumvoll, Michael, Teslovich, Tanya M, Waeber, Gérard, Williams, Gordon H, Witte, Daniel R, Wood, Andrew R, Xie, Weijia, Boehnke, Michael, Cooper, Cyrus, Ferrucci, Luigi, Froguel, Philippe, Groop, Leif, Kao, WH Linda, Vollenweider, Peter, Walker, Mark, Watanabe, Richard M, Pedersen, Oluf, and Meigs, James B

Subjects
Biomedical and Clinical Sciences, Clinical Research, Genetics, Diabetes, Prevention, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, 2.3 Psychological, social and economic factors, Metabolic and endocrine, Blood Glucose, Body Mass Index, Epigenesis, Genetic, Gene Expression Regulation, Genotype, Humans, Life Style, Motor Activity, Polymorphism, Single Nucleotide, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

Published
2012

25. A genome-wide association search for type 2 diabetes genes in African Americans.

Author

Palmer, Nicholette D, McDonough, Caitrin W, Hicks, Pamela J, Roh, Bong H, Wing, Maria R, An, S Sandy, Hester, Jessica M, Cooke, Jessica N, Bostrom, Meredith A, Rudock, Megan E, Talbert, Matthew E, Lewis, Joshua P, DIAGRAM Consortium, MAGIC Investigators, Ferrara, Assiamira, Lu, Lingyi, Ziegler, Julie T, Sale, Michele M, Divers, Jasmin, Shriner, Daniel, Adeyemo, Adebowale, Rotimi, Charles N, Ng, Maggie CY, Langefeld, Carl D, Freedman, Barry I, Bowden, Donald W, Voight, Benjamin F, Scott, Laura J, Steinthorsdottir, Valgerdur, Morris, Andrew P, Dina, Christian, Welch, Ryan P, Zeggini, Eleftheria, Huth, Cornelia, Aulchenko, Yurii S, Thorleifsson, Gudmar, McCulloch, Laura J, Ferreira, Teresa, Grallert, Harald, Amin, Najaf, Wu, Guanming, Willer, Cristen J, Raychaudhuri, Soumya, McCarroll, Steve A, Langenberg, Claudia, Hofmann, Oliver M, Dupuis, Josée, Qi, Lu, Segrè, Ayellet V, van Hoek, Mandy, Navarro, Pau, Ardlie, Kristin, Balkau, Beverley, Benediktsson, Rafn, Bennett, Amanda J, Blagieva, Roza, Boerwinkle, Eric, Bonnycastle, Lori L, Boström, Kristina Bengtsson, Bravenboer, Bert, Bumpstead, Suzannah, Burtt, Noël P, Charpentier, Guillaume, Chines, Peter S, Cornelis, Marilyn, Couper, David J, Crawford, Gabe, Doney, Alex SF, Elliott, Katherine S, Elliott, Amanda L, Erdos, Michael R, Fox, Caroline S, Franklin, Christopher S, Ganser, Martha, Gieger, Christian, Grarup, Niels, Green, Todd, Griffin, Simon, Groves, Christopher J, Guiducci, Candace, Hadjadj, Samy, Hassanali, Neelam, Herder, Christian, Isomaa, Bo, Jackson, Anne U, Johnson, Paul RV, Jørgensen, Torben, Kao, Wen HL, Klopp, Norman, Kong, Augustine, Kraft, Peter, Kuusisto, Johanna, Lauritzen, Torsten, Li, Man, Lieverse, Aloysius, Lindgren, Cecilia M, Lyssenko, Valeriya, Marre, Michel, Meitinger, Thomas, and Midthjell, Kristian

Subjects
DIAGRAM Consortium, MAGIC Investigators, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Case-Control Studies, Cohort Studies, Genotype, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, African Americans, Female, Male, Meta-Analysis as Topic, Validation Studies as Topic, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, General Science & Technology
Abstract

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P

Published
2012

26. Genome-Wide Association of Pericardial Fat Identifies a Unique Locus for Ectopic Fat

Author

Fox, Caroline S, White, Charles C, Lohman, Kurt, Heard-Costa, Nancy, Cohen, Paul, Zhang, Yingying, Johnson, Andrew D, Emilsson, Valur, Liu, Ching-Ti, Chen, Y-D Ida, Taylor, Kent D, Allison, Matthew, Budoff, Matthew, Rotter, Jerome I, Carr, J Jeffrey, Hoffmann, Udo, Ding, Jingzhong, Cupples, L Adrienne, and Liu, Yongmei

Subjects
Biological Sciences, Genetics, Atherosclerosis, Prevention, Heart Disease, Aging, Nutrition, Obesity, Cardiovascular, Metabolic and endocrine, Adipose Tissue, Adult, Animals, Asian People, Black People, Body Fat Distribution, Body Mass Index, Calcium-Calmodulin-Dependent Protein Kinases, Coronary Disease, Female, Gene Expression Regulation, Genome-Wide Association Study, Hispanic or Latino, Humans, Intra-Abdominal Fat, Intracellular Signaling Peptides and Proteins, Male, Mice, Middle Aged, Pericardium, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Tomography, X-Ray Computed, White People, CARDIoGRAM Consortium, Developmental Biology
Abstract

Pericardial fat is a localized fat depot associated with coronary artery calcium and myocardial infarction. We hypothesized that genetic loci would be associated with pericardial fat independent of other body fat depots. Pericardial fat was quantified in 5,487 individuals of European ancestry from the Framingham Heart Study (FHS) and the Multi-Ethnic Study of Atherosclerosis (MESA). Genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of pericardial fat adjusted for age, sex, weight, and height. A weighted z-score meta-analysis was conducted, and validation was obtained in an additional 3,602 multi-ethnic individuals from the MESA study. We identified a genome-wide significant signal in our primary meta-analysis at rs10198628 near TRIB2 (MAF 0.49, p = 2.7 × 10(-08)). This SNP was not associated with visceral fat (p = 0.17) or body mass index (p = 0.38), although we observed direction-consistent, nominal significance with visceral fat adjusted for BMI (p = 0.01) in the Framingham Heart Study. Our findings were robust among African ancestry (n = 1,442, p = 0.001), Hispanic (n = 1,399, p = 0.004), and Chinese (n = 761, p = 0.007) participants from the MESA study, with a combined p-value of 5.4E-14. We observed TRIB2 gene expression in the pericardial fat of mice. rs10198628 near TRIB2 is associated with pericardial fat but not measures of generalized or visceral adiposity, reinforcing the concept that there are unique genetic underpinnings to ectopic fat distribution.

Published
2012

27. Global kidney health 2017 and beyond: a roadmap for closing gaps in care, research, and policy

Author

Adu, Dwomoa, Agarwal, Sanjay Kumar, Alrukhaimi, Mona, Anders, Hans-Joachim, Ashuntantang, Gloria, Basnet, Shakti, Bello, Aminu K., Chailimpamontree, Worawon, Correa-Rotter, Ricardo, Craig, Jonathan, Douthat, Walter G., Feldman, Harold I., Ganji, Mohammad Reza, Garcia-Garcia, Guillermo, Gharbi, Mohammed Benghanem, Harris, David C., Jha, Vivekanand, Johnson, David W., Kazancioglu, Rumeyza, Langham, Robyn, Liu, Zhi-Hong, Massy, Ziad A., Nangaku, Masaomi, Nelson, Robert G., O'Donoghue, Donal, Okpechi, Ikechi, Pecoits-Filho, Roberto, Powe, Neil R., Remuzzi, Giuseppe, Roberts, Charlotte, Rossert, Jerome, Sola, Laura, Stengel, Benedicte, M, Ernest K. Sumaili, Suzuki, Yusuke, Tanaka, Tetsuhiro, Tatiyanupanwong, Sajja, Thomas, Bernadette, Uhlig, Katrin, Walker, Robert, White, Sarah L., Wiecek, Andrzej, Yang, Chih-Wei, Levin, Adeera, Tonelli, Marcello, Bonventre, Joseph, Coresh, Josef, Donner, Jo-Ann, Fogo, Agnes B, Fox, Caroline S, Gansevoort, Ron T, Heerspink, Hiddo J L, Jardine, Meg, Kasiske, Bertram, Köttgen, Anna, Kretzler, Matthias, Levey, Andrew S, Luyckx, Valerie A, Mehta, Ravindra, Moe, Orson, Obrador, Gregorio, Pannu, Neesh, Parikh, Chirag R, Perkovic, Vlado, Pollock, Carol, Stenvinkel, Peter, Tuttle, Katherine R, Wheeler, David C, and Eckardt, Kai-Uwe

Published
2017
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28. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

Author

Strawbridge, Rona J, Dupuis, Josée, Prokopenko, Inga, Barker, Adam, Ahlqvist, Emma, Rybin, Denis, Petrie, John R, Travers, Mary E, Bouatia-Naji, Nabila, Dimas, Antigone S, Nica, Alexandra, Wheeler, Eleanor, Chen, Han, Voight, Benjamin F, Taneera, Jalal, Kanoni, Stavroula, Peden, John F, Turrini, Fabiola, Gustafsson, Stefan, Zabena, Carina, Almgren, Peter, Barker, David JP, Barnes, Daniel, Dennison, Elaine M, Eriksson, Johan G, Eriksson, Per, Eury, Elodie, Folkersen, Lasse, Fox, Caroline S, Frayling, Timothy M, Goel, Anuj, Gu, Harvest F, Horikoshi, Momoko, Isomaa, Bo, Jackson, Anne U, Jameson, Karen A, Kajantie, Eero, Kerr-Conte, Julie, Kuulasmaa, Teemu, Kuusisto, Johanna, Loos, Ruth JF, Luan, Jian'an, Makrilakis, Konstantinos, Manning, Alisa K, Martínez-Larrad, María Teresa, Narisu, Narisu, Nastase Mannila, Maria, Ohrvik, John, Osmond, Clive, Pascoe, Laura, Payne, Felicity, Sayer, Avan A, Sennblad, Bengt, Silveira, Angela, Stancáková, Alena, Stirrups, Kathy, Swift, Amy J, Syvänen, Ann-Christine, Tuomi, Tiinamaija, van 't Hooft, Ferdinand M, Walker, Mark, Weedon, Michael N, Xie, Weijia, Zethelius, Björn, DIAGRAM Consortium, GIANT Consortium, MuTHER Consortium, CARDIoGRAM Consortium, C4D Consortium, Ongen, Halit, Mälarstig, Anders, Hopewell, Jemma C, Saleheen, Danish, Chambers, John, Parish, Sarah, Danesh, John, Kooner, Jaspal, Ostenson, Claes-Göran, Lind, Lars, Cooper, Cyrus C, Serrano-Ríos, Manuel, Ferrannini, Ele, Forsen, Tom J, Clarke, Robert, Franzosi, Maria Grazia, Seedorf, Udo, Watkins, Hugh, Froguel, Philippe, Johnson, Paul, Deloukas, Panos, Collins, Francis S, Laakso, Markku, Dermitzakis, Emmanouil T, Boehnke, Michael, McCarthy, Mark I, Wareham, Nicholas J, Groop, Leif, Pattou, François, Gloyn, Anna L, and Dedoussis, George V

Subjects
DIAGRAM Consortium, GIANT Consortium, MuTHER Consortium, CARDIoGRAM Consortium, C4D Consortium, Humans, Diabetes Mellitus, Type 2, Insulin, Proinsulin, Fasting, Genotype, Polymorphism, Single Nucleotide, Genome, Human, Adult, Female, Male, Genetic Variation, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, Genome, Human, Endocrinology & Metabolism, Medical and Health Sciences
Abstract

ObjectiveProinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology.Research design and methodsWe have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates.ResultsNine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets.ConclusionsWe have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

Published
2011

29. Association of eGFR-Related Loci Identified by GWAS with Incident CKD and ESRD.

Author

Böger, Carsten A, Gorski, Mathias, Li, Man, Hoffmann, Michael M, Huang, Chunmei, Yang, Qiong, Teumer, Alexander, Krane, Vera, O'Seaghdha, Conall M, Kutalik, Zoltán, Wichmann, H-Erich, Haak, Thomas, Boes, Eva, Coassin, Stefan, Coresh, Josef, Kollerits, Barbara, Haun, Margot, Paulweber, Bernhard, Köttgen, Anna, Li, Guo, Shlipak, Michael G, Powe, Neil, Hwang, Shih-Jen, Dehghan, Abbas, Rivadeneira, Fernando, Uitterlinden, André, Hofman, Albert, Beckmann, Jacques S, Krämer, Bernhard K, Witteman, Jacqueline, Bochud, Murielle, Siscovick, David, Rettig, Rainer, Kronenberg, Florian, Wanner, Christoph, Thadhani, Ravi I, Heid, Iris M, Fox, Caroline S, Kao, WH, and CKDGen Consortium

Subjects
CKDGen Consortium, Humans, Kidney Diseases, Kidney Failure, Chronic, Chronic Disease, Creatinine, Adaptor Proteins, Signal Transducing, Follow-Up Studies, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, European Continental Ancestry Group, Female, Male, Genetic Association Studies, Uromodulin, ErbB Receptors, Kidney Disease, Genetics, Clinical Research, Renal and urogenital, Developmental Biology
Abstract

Family studies suggest a genetic component to the etiology of chronic kidney disease (CKD) and end stage renal disease (ESRD). Previously, we identified 16 loci for eGFR in genome-wide association studies, but the associations of these single nucleotide polymorphisms (SNPs) for incident CKD or ESRD are unknown. We thus investigated the association of these loci with incident CKD in 26,308 individuals of European ancestry free of CKD at baseline drawn from eight population-based cohorts followed for a median of 7.2 years (including 2,122 incident CKD cases defined as eGFR

Published
2011

30. Genetic association for renal traits among participants of African ancestry reveals new loci for renal function.

Author

Liu, Ching-Ti, Garnaas, Maija K, Tin, Adrienne, Kottgen, Anna, Franceschini, Nora, Peralta, Carmen A, de Boer, Ian H, Lu, Xiaoning, Atkinson, Elizabeth, Ding, Jingzhong, Nalls, Michael, Shriner, Daniel, Coresh, Josef, Kutlar, Abdullah, Bibbins-Domingo, Kirsten, Siscovick, David, Akylbekova, Ermeg, Wyatt, Sharon, Astor, Brad, Mychaleckjy, Josef, Li, Man, Reilly, Muredach P, Townsend, Raymond R, Adeyemo, Adebowale, Zonderman, Alan B, de Andrade, Mariza, Turner, Stephen T, Mosley, Thomas H, Harris, Tamara B, CKDGen Consortium, Rotimi, Charles N, Liu, Yongmei, Kardia, Sharon LR, Evans, Michele K, Shlipak, Michael G, Kramer, Holly, Flessner, Michael F, Dreisbach, Albert W, Goessling, Wolfram, Cupples, L Adrienne, Kao, W Linda, and Fox, Caroline S

Subjects
CKDGen Consortium, Kidney, Animals, Zebrafish, Humans, Kidney Failure, Chronic, Adaptor Proteins, Signal Transducing, Adaptor Proteins, Vesicular Transport, Neoplasm Proteins, Glomerular Filtration Rate, Phenotype, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, African Continental Ancestry Group, Female, Male, KCNQ1 Potassium Channel, Genome-Wide Association Study, Gene Knockdown Techniques, Genetic Loci, Genetic Association Studies, Kidney Disease, Clinical Research, Genetics, Renal and urogenital, Developmental Biology
Abstract

Chronic kidney disease (CKD) is an increasing global public health concern, particularly among populations of African ancestry. We performed an interrogation of known renal loci, genome-wide association (GWA), and IBC candidate-gene SNP association analyses in African Americans from the CARe Renal Consortium. In up to 8,110 participants, we performed meta-analyses of GWA and IBC array data for estimated glomerular filtration rate (eGFR), CKD (eGFR 30 mg/g) and interrogated the 250 kb flanking region around 24 SNPs previously identified in European Ancestry renal GWAS analyses. Findings were replicated in up to 4,358 African Americans. To assess function, individually identified genes were knocked down in zebrafish embryos by morpholino antisense oligonucleotides. Expression of kidney-specific genes was assessed by in situ hybridization, and glomerular filtration was evaluated by dextran clearance. Overall, 23 of 24 previously identified SNPs had direction-consistent associations with eGFR in African Americans, 2 of which achieved nominal significance (UMOD, PIP5K1B). Interrogation of the flanking regions uncovered 24 new index SNPs in African Americans, 12 of which were replicated (UMOD, ANXA9, GCKR, TFDP2, DAB2, VEGFA, ATXN2, GATM, SLC22A2, TMEM60, SLC6A13, and BCAS3). In addition, we identified 3 suggestive loci at DOK6 (p-value = 5.3×10(-7)) and FNDC1 (p-value = 3.0×10(-7)) for UACR, and KCNQ1 with eGFR (p = 3.6×10(-6)). Morpholino knockdown of kcnq1 in the zebrafish resulted in abnormal kidney development and filtration capacity. We identified several SNPs in association with eGFR in African Ancestry individuals, as well as 3 suggestive loci for UACR and eGFR. Functional genetic studies support a role for kcnq1 in glomerular development in zebrafish.

Published
2011

31. Association of metabolic dysregulation with volumetric brain magnetic resonance imaging and cognitive markers of subclinical brain aging in middle-aged adults: the Framingham Offspring Study.

Author

Tan, Zaldy S, Beiser, Alexa S, Fox, Caroline S, Au, Rhoda, Himali, Jayandra J, Debette, Stephanie, Decarli, Charles, Vasan, Ramachandran S, Wolf, Philip A, and Seshadri, Sudha

Subjects
Brain, Humans, C-Reactive Protein, Apolipoproteins E, Interleukin-6, Magnetic Resonance Imaging, Aging, Aged, Middle Aged, Female, Male, Endocrinology & Metabolism, Medical and Health Sciences
Abstract

ObjectiveDiabetic and prediabtic states, including insulin resistance, fasting hyperglycemia, and hyperinsulinemia, are associated with metabolic dysregulation. These components have been individually linked to increased risks of cognitive decline and Alzheimer's disease. We aimed to comprehensively relate all of the components of metabolic dysregulation to cognitive function and brain magnetic resonance imaging (MRI) in middle-aged adults.Research design and methodsFramingham Offspring participants who underwent volumetric MRI and detailed cognitive testing and were free of clinical stroke and dementia during examination 7 (1998-2001) constituted our study sample (n = 2,439; 1,311 women; age 61 ± 9 years). We related diabetes, homeostasis model assessment of insulin resistance (HOMA-IR), fasting insulin, and glycohemoglobin levels to cross-sectional MRI measures of total cerebral brain volume (TCBV) and hippocampal volume and to verbal and visuospatial memory and executive function. We serially adjusted for age, sex, and education alone (model A), additionally for other vascular risk factors (model B), and finally, with the inclusion of apolipoprotein E-ε4, plasma homocysteine, C-reactive protein, and interleukin-6 (model C).ResultsWe observed an inverse association between all indices of metabolic dysfunction and TCBV in all models (P < 0.030). The observed difference in TCBV between participants with and without diabetes was equivalent to approximately 6 years of chronologic aging. Diabetes and elevated glycohemoglobin, HOMA-IR, and fasting insulin were related to poorer executive function scores (P < 0.038), whereas only HOMA-IR and fasting insulin were inversely related to visuospatial memory (P < 0.007).ConclusionsMetabolic dysregulation, especially insulin resistance, was associated with lower brain volumes and executive function in a large, relatively healthy, middle-aged, community-based cohort.

Published
2011

32. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.

Author

Speliotes, Elizabeth K, Yerges-Armstrong, Laura M, Wu, Jun, Hernaez, Ruben, Kim, Lauren J, Palmer, Cameron D, Gudnason, Vilmundur, Eiriksdottir, Gudny, Garcia, Melissa E, Launer, Lenore J, Nalls, Michael A, Clark, Jeanne M, Mitchell, Braxton D, Shuldiner, Alan R, Butler, Johannah L, Tomas, Marta, Hoffmann, Udo, Hwang, Shih-Jen, Massaro, Joseph M, O'Donnell, Christopher J, Sahani, Dushyant V, Salomaa, Veikko, Schadt, Eric E, Schwartz, Stephen M, Siscovick, David S, NASH CRN, GIANT Consortium, MAGIC Investigators, Voight, Benjamin F, Carr, J Jeffrey, Feitosa, Mary F, Harris, Tamara B, Fox, Caroline S, Smith, Albert V, Kao, WH Linda, Hirschhorn, Joel N, Borecki, Ingrid B, and GOLD Consortium

Subjects
NASH CRN, GIANT Consortium, MAGIC Investigators, GOLD Consortium, Humans, Fatty Liver, Insulin, Lipase, Blood Glucose, Adaptor Proteins, Signal Transducing, Lectins, C-Type, Membrane Proteins, Nerve Tissue Proteins, Tomography, X-Ray Computed, Case-Control Studies, Cohort Studies, Mutation, Missense, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Adult, Aged, Aged, 80 and over, Middle Aged, Male, Genome-Wide Association Study, Chondroitin Sulfate Proteoglycans, Non-alcoholic Fatty Liver Disease, Prevention, Human Genome, Digestive Diseases, Liver Disease, Hepatitis, Chronic Liver Disease and Cirrhosis, Genetics, Clinical Research, 2.1 Biological and endogenous factors, Developmental Biology
Abstract

Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p

Published
2011

33. Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

Author

Lanktree, Matthew B, Guo, Yiran, Murtaza, Muhammed, Glessner, Joseph T, Bailey, Swneke D, Onland-Moret, N Charlotte, Lettre, Guillaume, Ongen, Halit, Rajagopalan, Ramakrishnan, Johnson, Toby, Shen, Haiqing, Nelson, Christopher P, Klopp, Norman, Baumert, Jens, Padmanabhan, Sandosh, Pankratz, Nathan, Pankow, James S, Shah, Sonia, Taylor, Kira, Barnard, John, Peters, Bas J, Maloney, Cliona M, Lobmeyer, Maximilian T, Stanton, Alice, Zafarmand, M Hadi, Romaine, Simon PR, Mehta, Amar, van Iperen, Erik PA, Gong, Yan, Price, Tom S, Smith, Erin N, Kim, Cecilia E, Li, Yun R, Asselbergs, Folkert W, Atwood, Larry D, Bailey, Kristian M, Bhatt, Deepak, Bauer, Florianne, Behr, Elijah R, Bhangale, Tushar, Boer, Jolanda MA, Boehm, Bernhard O, Bradfield, Jonathan P, Brown, Morris, Braund, Peter S, Burton, Paul R, Carty, Cara, Chandrupatla, Hareesh R, Chen, Wei, Connell, John, Dalgeorgou, Chrysoula, de Boer, Anthonius, Drenos, Fotios, Elbers, Clara C, Fang, James C, Fox, Caroline S, Frackelton, Edward C, Fuchs, Barry, Furlong, Clement E, Gibson, Quince, Gieger, Christian, Goel, Anuj, Grobbee, Diederik E, Hastie, Claire, Howard, Philip J, Huang, Guan-Hua, Johnson, W Craig, Li, Qing, Kleber, Marcus E, Klein, Barbara EK, Klein, Ronald, Kooperberg, Charles, Ky, Bonnie, LaCroix, Andrea, Lanken, Paul, Lathrop, Mark, Li, Mingyao, Marshall, Vanessa, Melander, Olle, Mentch, Frank D, Meyer, Nuala J, Monda, Keri L, Montpetit, Alexandre, Murugesan, Gurunathan, Nakayama, Karen, Nondahl, Dave, Onipinla, Abiodun, Rafelt, Suzanne, Newhouse, Stephen J, Otieno, F George, Patel, Sanjey R, Putt, Mary E, Rodriguez, Santiago, Safa, Radwan N, Sawyer, Douglas B, Schreiner, Pamela J, Simpson, Claire, Sivapalaratnam, Suthesh, Srinivasan, Sathanur R, and Suver, Christine

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Adult, Black or African American, Asian People, Body Height, Cardiovascular System, Female, Gene Frequency, Genetic Heterogeneity, Genetic Loci, Genome-Wide Association Study, Hispanic or Latino, Humans, Interleukin-11, Male, Polymorphism, Single Nucleotide, Smad3 Protein, White People, Hugh Watkins on behalf of PROCARDIS, Meena Kumari on behalf of the Whitehall II Study and the WHII 50K Group, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.

Published
2011

34. The relation of C - reactive protein to chronic kidney disease in African Americans: the Jackson Heart Study

Author

Fox, Ervin R, Benjamin, Emelia J, Sarpong, Daniel F, Nagarajarao, Harsha, Taylor, Jason K, Steffes, Michael W, Salahudeen, Abdullah K, Flessner, Michael F, Akylbekova, Ermeg L, Fox, Caroline S, Garrison, Robert J, and Taylor, Herman A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Aging, Kidney Disease, Cardiovascular, Clinical Research, Heart Disease, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Renal and urogenital, Good Health and Well Being, Adult, Black or African American, Aged, Albuminuria, C-Reactive Protein, Female, Glomerular Filtration Rate, Humans, Incidence, Kidney Function Tests, Longitudinal Studies, Male, Middle Aged, Multivariate Analysis, Prevalence, Renal Insufficiency, Chronic, Risk Factors, Urology & Nephrology, Clinical sciences, Health services and systems, Nursing
Abstract

BackgroundAfrican Americans have an increased incidence and worse prognosis with chronic kidney disease (CKD--estimated glomerular filtration rate [eGFR] 30 mg/g).ResultsParticipants (n = 4320, 63.2% women) had a mean age +/- SD of 54.0 +/- 12.8 years. The prevalence of CKD was 5.2% (n = 228 cases). In multivariable regression, CRP concentrations were higher in those with CKD compared to those without CKD (mean CRP 3.2 +/- 1.1 mg/L vs. 2.4 +/- 1.0 mg/L, respectively p < 0.0001). CRP was significantly associated with albuminuria in sex and age adjusted model however not in the multivariable adjusted model (p > 0.05).ConclusionCRP was associated with CKD however not albuminuria in multivariable-adjusted analyses. The study of inflammation in the progression of renal disease in African Americans merits further investigation.

Published
2010

35. Comparison of On-Site Versus Remote Mobile Device Support in the Framingham Heart Study Using the Health eHeart Study for Digital Follow-up: Randomized Pilot Study Set Within an Observational Study Design

Author

Spartano, Nicole L, Lin, Honghuang, Sun, Fangui, Lunetta, Kathryn L, Trinquart, Ludovic, Valentino, Maureen, Manders, Emily S, Pletcher, Mark J, Marcus, Gregory M, McManus, David D, Benjamin, Emelia J, Fox, Caroline S, Olgin, Jeffrey E, and Murabito, Joanne M

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundNew electronic cohort (e-Cohort) study designs provide resource-effective methods for collecting participant data. It is unclear if implementing an e-Cohort study without direct, in-person participant contact can achieve successful participation rates. ObjectiveThe objective of this study was to compare 2 distinct enrollment methods for setting up mobile health (mHealth) devices and to assess the ongoing adherence to device use in an e-Cohort pilot study. MethodsWe coenrolled participants from the Framingham Heart Study (FHS) into the FHS–Health eHeart (HeH) pilot study, a digital cohort with infrastructure for collecting mHealth data. FHS participants who had an email address and smartphone were randomized to our FHS-HeH pilot study into 1 of 2 study arms: remote versus on-site support. We oversampled older adults (age ≥65 years), with a target of enrolling 20% of our sample as older adults. In the remote arm, participants received an email containing a link to enrollment website and, upon enrollment, were sent 4 smartphone-connectable sensor devices. Participants in the on-site arm were invited to visit an in-person FHS facility and were provided in-person support for enrollment and connecting the devices. Device data were tracked for at least 5 months. ResultsCompared with the individuals who declined, individuals who consented to our pilot study (on-site, n=101; remote, n=93) were more likely to be women, highly educated, and younger. In the on-site arm, the connection and initial use of devices was ≥20% higher than the remote arm (mean percent difference was 25% [95% CI 17-35] for activity monitor, 22% [95% CI 12-32] for blood pressure cuff, 20% [95% CI 10-30] for scale, and 43% [95% CI 30-55] for electrocardiogram), with device connection rates in the on-site arm of 99%, 95%, 95%, and 84%. Once connected, continued device use over the 5-month study period was similar between the study arms. ConclusionsOur pilot study demonstrated that the deployment of mobile devices among middle-aged and older adults in the context of an on-site clinic visit was associated with higher initial rates of device use as compared with offering only remote support. Once connected, the device use was similar in both groups.

Published
2019
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41. Genomic atlas of the human plasma proteome

Author

Sun, Benjamin B., Maranville, Joseph C., Peters, James E., Stacey, David, Staley, James R., Blackshaw, James, Burgess, Stephen, Jiang, Tao, Paige, Ellie, Surendran, Praveen, Oliver-Williams, Clare, Kamat, Mihir A., Prins, Bram P., Wilcox, Sheri K., Zimmerman, Erik S., Chi, An, Bansal, Narinder, Spain, Sarah L., Wood, Angela M., Morrell, Nicholas W., Bradley, John R., Janjic, Nebojsa, Roberts, David J., Ouwehand, Willem H., Todd, John A., Soranzo, Nicole, Suhre, Karsten, Paul, Dirk S., Fox, Caroline S., Plenge, Robert M., Danesh, John, Runz, Heiko, and Butterworth, Adam S.

Published
2018
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45. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author

Chauhan, Ganesh, Adams, Hieab H.H., Satizabal, Claudia L., Bis, Joshua C., Teumer, Alexander, Sargurupremraj, Muralidharan, Hofer, Edith, Trompet, Stella, Hilal, Saima, Smith, Albert Vernon, Jian, Xueqiu, Malik, Rainer, Traylor, Matthew, Pulit, Sara L., Amouyel, Philippe, Mazoyer, Bernard, Zhu, Yi-Cheng, Kaffashian, Sara, Schilling, Sabrina, Beecham, Gary W., Montine, Thomas J., Schellenberg, Gerard D., Kjartansson, Olafur, Guðnason, Vilmundur, Knopman, David S., Griswold, Michael E., Windham, B. Gwen, Gottesman, Rebecca F., Mosley, Thomas H., Schmidt, Reinhold, Saba, Yasaman, Schmidt, Helena, Takeuchi, Fumihiko, Yamaguchi, Shuhei, Nabika, Toru, Kato, Norihiro, Rajan, Kumar B., Aggarwal, Neelum T., De Jager, Philip L., Evans, Denis A., Psaty, Bruce M., Rotter, Jerome I., Rice, Kenneth, Lopez, Oscar L., Liao, Jiemin, Chen, Christopher, Cheng, Ching-Yu, Wong, Tien Y., Ikram, Mohammad K., van der Lee, Sven J., Amin, Najaf, Chouraki, Vincent, DeStefano, Anita L., Aparicio, Hugo J., Romero, Jose R., Maillard, Pauline, DeCarli, Charles, Wardlaw, Joanna M., Hernández, Maria del C. Valdés, Luciano, Michelle, Liewald, David, Deary, Ian J., Starr, John M., Bastin, Mark E., Muñoz Maniega, Susana, Slagboom, P. Eline, Beekman, Marian, Deelen, Joris, Uh, Hae-Won, Lemmens, Robin, Brodaty, Henry, Wright, Margaret J., Ames, David, Boncoraglio, Giorgio B., Hopewell, Jemma C., Beecham, Ashley H., Blanton, Susan H., Wright, Clinton B., Sacco, Ralph L., Wen, Wei, Thalamuthu, Anbupalam, Armstrong, Nicola J., Chong, Elizabeth, Schofield, Peter R., Kwok, John B., van der Grond, Jeroen, Stott, David J., Ford, Ian, Jukema, J. Wouter, Vernooij, Meike W., Hofman, Albert, Uitterlinden, André G., van der Lugt, Aad, Wittfeld, Katharina, Grabe, Hans J., Hosten, Norbert, von Sarnowski, Bettina, Völker, Uwe, Levi, Christopher, Jimenez-Conde, Jordi, Sharma, Pankaj, Sudlow, Cathie L.M., Rosand, Jonathan, Woo, Daniel, Cole, John W., Meschia, James F., Slowik, Agnieszka, Thijs, Vincent, Lindgren, Arne, Melander, Olle, Grewal, Raji P., Rundek, Tatjana, Rexrode, Kathy, Rothwell, Peter M., Arnett, Donna K., Jern, Christina, Johnson, Julie A., Benavente, Oscar R., Wasssertheil-Smoller, Sylvia, Lee, Jin-Moo, Wong, Quenna, Mitchell, Braxton D., Rich, Stephen S., McArdle, Patrick F., Geerlings, Mirjam I., van der Graaf, Yolanda, de Bakker, Paul I.W., Asselbergs, Folkert W., Srikanth, Velandai, Thomson, Russell, McWhirter, Rebekah, Moran, Chris, Callisaya, Michele, Phan, Thanh, Rutten-Jacobs, Loes C.A., Bevan, Steve, Tzourio, Christophe, Mather, Karen A., Sachdev, Perminder S., van Duijn, Cornelia M., Worrall, Bradford B., Dichgans, Martin, Kittner, Steven J., Markus, Hugh S., Ikram, Mohammad A., Fornage, Myriam, Launer, Lenore J., Seshadri, Sudha, Longstreth, W.T., Jr, Debette, Stéphanie, Almgren, Peter, Anderson, Christopher D., Arnett, Donna K., Attia, John, Ay, Hakan, Benavente, Oscar R., Bevan, Steve, Brown, Robert D., Bustamante, Mariana, Cheng, Yu-Ching, Cole, John W., Cotlarciuc, Ioana, Cruchaga, Carlos, de Bakker, Paul IW., Delavaran, Hossein, Dichgans, Martin, Engström, Gunnar, Fornage, Myriam, Grewal, Raji P., Heitsch, Laura, Holliday, Elizabeth, Ibanez, Laure, Ilinca, Andreea, Irvin, Marguerite R., Jackson, Rebecca D., Jern, Christina, Jimenez-Conde, Jordi, Johnson, Julie A., Jood, Katarina, Kissela, Brett M., Kittner, Steven J., Kleindorfer, Dawn O., Labovitz, Daniel, Laurie, Cathy C., Lee, Jin-Moo, Lemmens, Robin, Levi, Christopher, Li, Linxin, Lindgren, Arne G., Maguire, Jane, Markus, Hugh S., McArdle, Patrick F., Melander, Olle, Meschia, James F., Mitchell, Braxton D., Müller-Nurasyid, Martina, Norrving, Bo, Peddareddygari, Leema Reddy, Pera, Joanna, Pulit, Sara L., Rexrode, Kathryn, Ribasés, Marta, Roquer, Jaume, Rost, Natalia S., Rothwell, Peter M., Rundek, Tatjana, Sacco, Ralph L., Schmidt, Reinhold, Sharma, Pankaj, Slowik, Agnieszka, Soriano-Tárraga, Carolina, Stanne, Tara, Stauch, Konstantin, Stine, O C., Sudlow, Cathie LM., Thijs, Vincent N.S., Wasssertheil-Smoller, Sylvia, Weir, David, Williams, Stephen R., Wong, Quenna, Woo, Daniel, Worrall, Bradford B., Xu, Huichun, Seshadri, Sudha, Hyacinth, Hyacinth I, Marini, Sandro, Nyquist, Paul, Lewis, Cathryn, Hansen, Bjorn, Norrving, Bo, Rosand, Jonathan, Biffi, Alessandro, Kourkoulis, Christina, Anderson, Chris, Giese, Anne-Katrin, Sacco, Ralph, Sharma, Pankaj, Chung, Jong-Won, Kim, Gyeong-Moon, Lubitz, Steven, Bourcier, Romain, Howson, Joanna, Granata, Alessandra, Drazyk, Anna, Markus, Hugh, Wardlaw, Joanna, Mitchell, Braxton, Cole, John, Hopewell, Jemma, Walters, Robin, Turnbull, Iain, Worrall, Bradford, Bis, Josh, Reiner, Alex, Dhar, Raj, Heitsch, Laura, Lee, Jin-Moo, Prasad, Kameshwar, Sarnowski, Chloé, Aparicio, Hugo Javier, Yang, Qiong, Chasman, Daniel, Rexrode, Kathryn, Phuah, Chia-Ling, Liu, Guiyou, Elkind, Mitchell, Lange, Leslie, Rost, Natalia, James, Michael, Stewart, Jill, Vojinovic, Dina, Thijs, Vincent, Parati, Eugenio, Boncoraglio, Giorgio, Zand, Ramin, Bijlenga, Philippe, Selim, Magdy, Grond-Ginsbach, Caspar, Strbian, Daniel, Tomppo, Liisa, Sallinen, Hanne, Pfeiffer, Dorothea, Torres, Nuria, Barboza, Miguel, Laarman, Melanie, Carriero, Roberta, Holliday, Elizabeth, Jimenez-Conde, Jordi, Soriano, Carolina, Gill, Dipender, Debette, Stephanie, Mishra, Aniket, Wu, Jer-Yuarn, Ko, Tai-Ming, Bione, Silvia, Jood, Katarina, Tatlisumak, Turgut, Holmegaard, Lukas, Yue, Suo, bersano, Anna, Pera, Joanna, Slowik, Agnieszka, Levi, Christopher, Schlicht, Kristina, Lemmens, Robin, Ninomiya, Toshiharu, Oberstein, Saskia Lesnik, Lee, Tsong-Hai, Malik, Rainer, Dichgans, Martin, Lindgren, Arne, Wasselius, Johan, Drake, Mattias, Melander, Olle, Stenman, Martin, Ilinca, Andreea, Crawford, Katherine, Lena, Umme, Mateen, Farrah, Ay, Hakan, Wu, Ona, Schirmer, Markus, Cramer, Steve, Golland, Polina, Brown, Robert, Meschia, James, Ross, Owen A., Pare, Guillaume, Chong, Mike, Rundek, Tatjana, Gwinn, Katrina, Chen, Christopher, Koenig, Jim, Giralt, Eva, Saleheen, Danish, de Leeuw, Frank-Erik, Klijn, Karin, Kamatani, Yoichiro, Kubo, Michiaki, Okada, Yukinori, Pedersen, Annie, Olsson, Maja, Martín, Juan José, Xu, Huichun, Tan, Eng King, Frid, Petrea, Lee, Chaeyoung, Tregouet, David, Leung, Thomas, Choy, Richard, Jern, Christina, Loo, Keat Wei, Rinkel, Gabriel, Franca, Paulo, Cendes, Iscia, Carrera, Caty, Fernandez-Cadenas, Israel, Montaner, Joan, Kim, Helen, Owolabi, Mayowa, Sofat, Reecha, Bakker, Mark, Ruigrok, Ynte, Hauer, Allard, Pulit, Sara L., van der Laan, Sander W., Irvin, Ryan, Sargurupremraj, Murali, Pezzini, Alessandro, Abd-Allah, Foad, Liebeskind, David, Traylor, Matthew, Tan, Rhea, Danesh, John, Rutten-Jacobs, Loes, Donatti, Amanda, Avelar, Wagner, Broderick, Joseph, Woo, Daniel, Sudlow, Cathie, Rannikmae, Kristiina, McDonough, Caitrin Wheeler, van Agtmael, Tom, Walters, Matthew, Söderholm, Martin, Lorentzen, Erik, Olsson, Sandra, Stanne, Tara, Olsson, Martina, Akinyemi, Rufus, Cotlatciuc, Ioana, McArdle, Patrick, Dave, Tushar, Kittner, Steven, Attia, John, Faber, James E, Millwood, Iona, Márquez, Elsa Valdés, Mancuso, Michelangelo, Vibo, Riina, Korv, Janika, Maguire, Jane, Fornage, Myriam, Majersik, Jennifer, DeHavenon, Adam, Alexander, Matthew, Sale, Michele, Southerland, Andrew, Owens, Debra, Psaty, Bruce, Longstreth, W. T., Jr, Wolfe, Stacey Quintero, Langefeld, Carl, Cruchaga, Carlos, Konrad, Jan, Sheth, Kevin, Falcone, Guido, Donahue, Kathleen, Simpkins, Alexis N, Liang Byorn, Tan Wei, Chan, Bernard, Clatworthy, Phil, Florez, Jose, Harshfield, Eric, Hozawa, Atsushi, Hsu, Chung, Hu, Chaur-Jong, Ibanez, Laure, Ihara, Masafumi, Lange, Marcos, Lee, Soo Ji, Lee, I-Hui, Musolino, Patricia, Nakatomi, Hirofumi, Park, Kwang-Yeol, Rich, Stephen S, Riley, Chris, Sung, Joohon, Suzuki, Hideaki, Vo, Katie, Washida, Kazuo, Ibenez, Laura Garcia, Slowik, Agnieszka, Hofman, Albert, Algra, Ale, Reiner, Alex P, Doney, Alexander S F, Gschwendtner, Andreas, Ilinca, Andreea, Giese, Anne-Katrin, Lindgren, Arne, Vicente, Astrid M, Norrving, Bo, Nordestgaard, Børge G, Mitchell, Braxton D, Worrall, Bradford B, Psaty, Bruce M, Carty, Cara L, Sudlow, Cathie, Anderson, Christopher D, Levi, Christopher, Satizabal, Claudia L, Palmer, Colin N A, Gamble, Dale M, Woo, Daniel, Saleheen, Danish, Ringelstein, E Bernd, Valdimarsson, Einar, Holliday, Elizabeth, Davies, Gail, Chauhan, Ganesh, Pasterkamp, Gerard, Boncoraglio, Giorgio, Kuhlenbäumer, Gregor, Thorleifsson, Gudmar, Falcone, Guido J, Pare, Guillame, Schmidt, Helena, Delavaran, Hossein, Markus, Hugh S, Aparicio, Hugo J, Deary, Ian, Cotlarciuc, Ioana, Fernandez-Cadenas, Israel, Meschia, James, Hopewell, Jemma C, Liu, Jingmin, Montaner, Joan, Pera, Joanna, Cole, John, Attia, John R, Rosand, Jonathan, Ferro, Jose M, Bis, Joshua, Furie, Karen, Stefansson, Kari, Berger, Klaus, Kostulas, Konstantinos, Rannikmae, Kristina, Ikram, M Arfan, Benn, Marianne, Dichgans, Martin, Farrall, Martin, Pandolfo, Massimo, Traylor, Matthew, Walters, Matthew, Sale, Michele, Nalls, Mike, Fornage, Myriam, van Zuydam, Natalie R, Sharma, Pankaj, Abrantes, Patricia, de Bakker, Paul IW, Higgins, Peter, Lichtner, Peter, Rothwell, Peter M, Amouyel, Philippe, Yang, Qiong, Malik, Rainer, Schmidt, Reinhold, Clarke, Robert, Lemmens, Robin, van der Laan, Sander W, Pulit, Sara L, Abboud, Sherine, Oliveira, Sofia A, Gretarsdottir, Solveig, Debette, Stephanie, Williams, Stephen R, Bevan, Steve, Kittner, Steven J, Seshadri, Sudha, Mosley, Thomas, Battey, Thomas WK, Tatlisumak, Turgut, Thorsteinsdottir, Unnur, Thijs, Vincent NS, Longstreth, W T, Zhao, Wei, Chen, Wei-Min, Cheng, Yu-Ching, Albert, Marilyn S., Albin, Roger L., Apostolova, Liana G., Arnold, Steven E., Asthana, Sanjay, Atwood, Craig S., Baldwin, Clinton T., Barmada, M. Michael, Barnes, Lisa L., Barral, Sandra, Beach, Thomas G., Becker, James T., Beecham, Gary W., Beekly, Duane, Bennett, David A., Bigio, Eileen H., Bird, Thomas D., Blacker, Deborah, Boeve, Bradley F., Boxer, Adam, Burke, James R., Burns, Jeffrey M., Buxbaum, Joseph D., Byrd, Goldie S., Cai, Guiqing, Cairns, Nigel J., Cantwell, Laura B., Cao, Chuanhai, Carlsson, Cynthia M., Carney, Regina M., Carrasquillo, Minerva M., Carroll, Steven L., Chui, Helena C., Clark, David G., Cribbs, David H., Crocco, Elizabeth A., Cruchaga, Carlos, De Jager, Philip L., DeCarli, Charles, Demirci, F. Yesim, Dick, Malcolm, Dickson, Dennis W., Duara, Ranjan, Ertekin-Taner, Nilufer, Evans, Denis A., Faber, Kelley M., Fallin, M. Daniele, Fallon, Kenneth B., Fardo, David W., Farlow, Martin R., Farrer, Lindsay A., Ferris, Steven, Foroud, Tatiana M., Frosch, Matthew P., Galasko, Douglas R., Gearing, Marla, Geschwind, Daniel H., Ghetti, Bernardino, Gilbert, John R., Go, Rodney C.P., Goate, Alison M., Graff-Radford, Neill R., Green, Robert C., Griffith, Patrick, Growdon, John H., Haines, Jonathan L., Hakonarson, Hakon, Hamilton, Ronald L., Hamilton-Nelson, Kara L., Haroutunian, Vahram, Harrell, Lindy E., Honig, Lawrence S., Huebinger, Ryan M., Hulette, Christine M., Hyman, Bradley T., Jicha, Gregory A., Jin, Lee-Way, Jun, Gyungah, Kamboh, M. Ilyas, Karydas, Anna, Kauwe, John S.K., Kaye, Jeffrey A., Kim, Ronald, Kowall, Neil W., Kramer, Joel H., Kukull, Walter A., Kunkle, Brian W., LaFerla, Frank M., Lah, James J., Lang-Walker, Rosalyn, Larson, Eric B., Leverenz, James B., Levey, Allan I., Li, Ge, Lieberman, Andrew P., Logue, Mark W., Lopez, Oscar L., Lunetta, Kathryn L., Lyketsos, Constantine G., Mack, Wendy J., Manly, Jennifer J., Marson, Daniel C., Martin, Eden R., Martiniuk, Frank, Mash, Deborah C., Masliah, Eliezer, Mayeux, Richard, McKee, Ann C., Mesulam, Marsel, Miller, Bruce L., Miller, Carol A., Miller, Joshua W., Montine, Thomas J., Morris, John C., Murrell, Jill R., Naj, Adam C., Obisesan, Thomas O., Olichney, John M., Pankratz, Vernon S., Parisi, Joseph E., Partch, Amanda, Paulson, Henry L., Pericak-Vance, Margaret A., Perry, William, Peskind, Elaine, Petersen, Ronald C., Pierce, Aimee, Poon, Wayne W., Potter, Huntington, Quinn, Joseph F., Raj, Ashok, Raj, Towfique, Raskind, Murray, Reiman, Eric M., Reisberg, Barry, Reitz, Christiane, Ringman, John M., Roberson, Erik D., Rosen, Howard J., Rosenberg, Roger N., Sager, Mark A., Sano, Mary, Saykin, Andrew J., Schellenberg, Gerard D., Schneider, Julie A., Schneider, Lon S., Seeley, William W., Smith, Amanda G., Sonnen, Joshua A., Spina, Salvatore, Stern, Robert A., Swerdlow, Russell H., Tanzi, Rudolph E., Thornton-Wells, Tricia A., Trojanowski, John Q., Troncoso, Juan C., Tsuang, Debby W., Valladares, Otto, Van Deerlin, Vivianna M., Van Eldik, Linda J., Vardarajan, Badri N., Vinters, Harry V., Vonsattel, Jean Paul, Wang, Li-San, Weintraub, Sandra, Welsh-Bohmer, Kathleen A., Williamson, Jennifer, Wingo, Thomas S., Wishnek, Sarah, Woltjer, Randall L., Wright, Clinton B., Younkin, Steven G., Yu, Chang-En, Yu, Lei, Chauhan, Ganesh, Chu, Audrey Y., Fornage, Myriam, Bis, Joshua C., Havulinna, Aki S., Sargurupremraj, Muralidharan, Smith, Albert Vernon, Adams, Hieab H.H., Choi, Seung Hoan, Trompet, Stella, Garcia, Melissa E., Manichaikul, Ani, Teumer, Alexander, Gustafsson, Stefan, Bartz, Traci M., Bellenguez, Céline, Vidal, Jean Sebastien, Jian, Xueqiu, Kjartansson, Olafur, Wiggins, Kerri L., Satizabal, Claudia L., Xue, Flora, Ripatti, Samuli, Liu, Yongmei, Deelen, Joris, Hoed, Marcel den, Heckbert, Susan R., Rice, Kenneth, Smith, Nicholas L., Wong, Quenna, Aparicio, Hugo J., Buring, Julie E., Ridker, Paul M, Berr, Claudine, Dartigues, Jean-François, Hamsten, Anders, Magnusson, Patrik K., Pedersen, Nancy L., Lannfelt, Lars, Lind, Lars, Lindgren, Cecilia M., Morris, Andrew P., Hofman, Albert, Koudstaal, Peter J., Portegies, Marileen LP., Uitterlinden, André G., de Craen, Anton JM, Ford, Ian, Jukema, J. Wouter, Stott, David J, Allen, Norrina B., Sale, Michele M., Johnson, Andrew D, Bennett, David A., De Jager, Philip L., White, Charles C., Grabe, Hans Jörgen, Paulista Markus, Marcello Ricardo, Lopez, Oscar L, Rotter, Jerome I., Nalls, Michael A., Gottesman, Rebecca F., Griswold, Michael E., Knopman, David S., Windham, B. Gwen, Beiser, Alexa, Vartiainen, Erkki, French, Curtis R., Kurth, Tobias, Psaty, Bruce M., Harris, Tamara B., Rich, Stephen S, deStefano, Anita L., Schmidt, Carsten Oliver, Salomaa, Veikko, Mosley, Thomas H., Ingelsson, Erik, van Duijn, Cornelia M., Tzourio, Christophe, Launer, Lenore J, Ikram, M. Arfan, Chasman, Daniel I., Longstreth, W. T., Jr, Seshadri, Sudha, Debette, Stéphanie, Verhaaren, Benjamin F.J., Debette, Stéphanie, Bis, Joshua C., Smith, Jennifer A., Ikram, M. Kamran, Adams, Hieab H., Beecham, Ashley H., Rajan, Kumar B., Lopez, Lorna M., Barral, Sandra, van Buchem, Mark A., van der Grond, Jeroen, Smith, Albert V., Hegenscheid, Katrin, Aggarwal, Neelum T., de Andrade, Mariza, Atkinson, Elizabeth J., Beekman, Marian, Beiser, Alexa S., Blanton, Susan H., Boerwinkle, Eric, Brickman, Adam M., Bryan, R. Nick, Chauhan, Ganesh, Chen, Christopher P.L.H., Chouraki, Vincent, de Craen, Anton J.M., Crivello, Fabrice, Deary, Ian J., Deelen, Joris, De Jager, Philip L., Dufouil, Carole, Elkind, Mitchell S.V., Evans, Denis A., Freudenberger, Paul, Gottesman, Rebecca F., Guðnason, Vilmundur, Habes, Mohamad, Heckbert, Susan R., Heiss, Gerardo, Hilal, Saima, Hofer, Edith, Hofman, Albert, Ibrahim-Verbaas, Carla A., Knopman, David S., Lewis, Cora E., Liao, Jiemin, Liewald, David C.M., Luciano, Michelle, van der Lugt, Aad, Martinez, Oliver O., Mayeux, Richard, Mazoyer, Bernard, Nalls, Mike, Nauck, Matthias, Niessen, Wiro J., Oostra, Ben A., Psaty, Bruce M., Rice, Kenneth M., Rotter, Jerome I., von Sarnowski, Bettina, Schmidt, Helena, Schreiner, Pamela J., Schuur, Maaike, Sidney, Stephen S., Sigurdsson, Sigurdur, Slagboom, P. Eline, Stott, David J.M., van Swieten, John C., Teumer, Alexander, Töglhofer, Anna Maria, Traylor, Matthew, Trompet, Stella, Turner, Stephen T., Tzourio, Christophe, Uh, Hae-Won, Uitterlinden, André G., Vernooij, Meike W., Wang, Jing J., Wong, Tien Y., Wardlaw, Joanna M., Windham, B. Gwen, Wittfeld, Katharina, Wolf, Christiane, Wright, Clinton B., Yang, Qiong, Zhao, Wei, Zijdenbos, Alex, Jukema, J. Wouter, Sacco, Ralph L., Kardia, Sharon L.R., Amouyel, Philippe, Mosley, Thomas H., Longstreth, W. T., Jr, DeCarli, Charles C., van Duijn, Cornelia M., Schmidt, Reinhold, Launer, Lenore J., Grabe, Hans J., Seshadri, Sudha S., Ikram, M. Arfan, Fornage, Myriam, Bis, Joshua C., Kavousi, Maryam, Franceschini, Nora, Isaacs, Aaron, Abecasis, Gonçalo R, Schminke, Ulf, Post, Wendy, Smith, Albert V., Cupples, L. Adrienne, Markus, Hugh S, Schmidt, Reinhold, Huffman, Jennifer E., Lehtimäki, Terho, Baumert, Jens, Münzel, Thomas, Heckbert, Susan R., Dehghan, Abbas, North, Kari, Oostra, Ben, Bevan, Steve, Stoegerer, Eva-Maria, Hayward, Caroline, Raitakari, Olli, Meisinger, Christa, Schillert, Arne, Sanna, Serena, Völzke, Henry, Cheng, Yu-Ching, Thorsson, Bolli, Fox, Caroline S., Rice, Kenneth, Rivadeneira, Fernando, Nambi, Vijay, Halperin, Eran, Petrovic, Katja E., Peltonen, Leena, Wichmann, H. Erich, Schnabel, Renate B., Dörr, Marcus, Parsa, Afshin, Aspelund, Thor, Demissie, Serkalem, Kathiresan, Sekar, Reilly, Muredach P., Taylor, Kent, Uitterlinden, Andre, Couper, David J., Sitzer, Matthias, Kähönen, Mika, Illig, Thomas, Wild, Philipp S., Orru, Marco, Lüdemann, Jan, Shuldiner, Alan R., Eiriksdottir, Gudny, White, Charles C., Rotter, Jerome I., Hofman, Albert, Seissler, Jochen, Zeller, Tanja, Usala, Gianluca, Ernst, Florian, Launer, Lenore J., DʼAgostino, Ralph B., Sr, OʼLeary, Daniel H., Ballantyne, Christie, Thiery, Joachim, Ziegler, Andreas, Lakatta, Edward G., Chilukoti, Ravi Kumar, Harris, Tamara B., Wolf, Philip A., Psaty, Bruce M., Polak, Joseph F, Li, Xia, Rathmann, Wolfgang, Uda, Manuela, Boerwinkle, Eric, Klopp, Norman, Schmidt, Helena, Wilson, James F, Viikari, Jorma, Koenig, Wolfgang, Blankenberg, Stefan, Newman, Anne B., Witteman, Jacqueline, Heiss, Gerardo, van Duijn, Cornelia, Scuteri, Angelo, Homuth, Georg, Mitchell, Braxton D., Gudnason, Vilmundur, and O’Donnell, Christopher J.

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

Author

Teumer, Alexander, Chaker, Layal, Groeneweg, Stefan, Li, Yong, Di Munno, Celia, Barbieri, Caterina, Schultheiss, Ulla T., Traglia, Michela, Ahluwalia, Tarunveer S., Akiyama, Masato, Appel, Emil Vincent R., Arking, Dan E., Arnold, Alice, Astrup, Arne, Beekman, Marian, Beilby, John P., Bekaert, Sofie, Boerwinkle, Eric, Brown, Suzanne J., De Buyzere, Marc, Campbell, Purdey J., Ceresini, Graziano, Cerqueira, Charlotte, Cucca, Francesco, Deary, Ian J., Deelen, Joris, Eckardt, Kai-Uwe, Ekici, Arif B., Eriksson, Johan G., Ferrrucci, Luigi, Fiers, Tom, Fiorillo, Edoardo, Ford, Ian, Fox, Caroline S., Fuchsberger, Christian, Galesloot, Tessel E., Gieger, Christian, Gögele, Martin, De Grandi, Alessandro, Grarup, Niels, Greiser, Karin Halina, Haljas, Kadri, Hansen, Torben, Harris, Sarah E., van Heemst, Diana, den Heijer, Martin, Hicks, Andrew A., den Hollander, Wouter, Homuth, Georg, Hui, Jennie, Ikram, M. Arfan, Ittermann, Till, Jensen, Richard A., Jing, Jiaojiao, Jukema, J. Wouter, Kajantie, Eero, Kamatani, Yoichiro, Kasbohm, Elisa, Kaufman, Jean-Marc, Kiemeney, Lambertus A., Kloppenburg, Margreet, Kronenberg, Florian, Kubo, Michiaki, Lahti, Jari, Lapauw, Bruno, Li, Shuo, Liewald, David C. M., Lifelines Cohort Study, Lim, Ee Mun, Linneberg, Allan, Marina, Michela, Mascalzoni, Deborah, Matsuda, Koichi, Medenwald, Daniel, Meisinger, Christa, Meulenbelt, Ingrid, De Meyer, Tim, Meyer zu Schwabedissen, Henriette E., Mikolajczyk, Rafael, Moed, Matthijs, Netea-Maier, Romana T., Nolte, Ilja M., Okada, Yukinori, Pala, Mauro, Pattaro, Cristian, Pedersen, Oluf, Petersmann, Astrid, Porcu, Eleonora, Postmus, Iris, Pramstaller, Peter P., Psaty, Bruce M., Ramos, Yolande F. M., Rawal, Rajesh, Redmond, Paul, Richards, J. Brent, Rietzschel, Ernst R., Rivadeneira, Fernando, Roef, Greet, Rotter, Jerome I., Sala, Cinzia F., Schlessinger, David, Selvin, Elizabeth, Slagboom, P. Eline, Soranzo, Nicole, Sørensen, Thorkild I. A., Spector, Timothy D., Starr, John M., Stott, David J., Taes, Youri, Taliun, Daniel, Tanaka, Toshiko, Thuesen, Betina, Tiller, Daniel, Toniolo, Daniela, Uitterlinden, Andre G., Visser, W. Edward, Walsh, John P., Wilson, Scott G., Wolffenbuttel, Bruce H. R., Yang, Qiong, Zheng, Hou-Feng, Cappola, Anne, Peeters, Robin P., Naitza, Silvia, Völzke, Henry, Sanna, Serena, Köttgen, Anna, Visser, Theo J., and Medici, Marco

Published
2018
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47. Phenome-wide association studies across large population cohorts support drug target validation

Author

Diogo, Dorothée, Tian, Chao, Franklin, Christopher S., Alanne-Kinnunen, Mervi, March, Michael, Spencer, Chris C. A., Vangjeli, Ciara, Weale, Michael E., Mattsson, Hannele, Kilpeläinen, Elina, Sleiman, Patrick M. A., Reilly, Dermot F., McElwee, Joshua, Maranville, Joseph C., Chatterjee, Arnaub K., Bhandari, Aman, Nguyen, Khanh-Dung H., Estrada, Karol, Reeve, Mary-Pat, Hutz, Janna, Bing, Nan, John, Sally, MacArthur, Daniel G., Salomaa, Veikko, Ripatti, Samuli, Hakonarson, Hakon, Daly, Mark J., Palotie, Aarno, Hinds, David A., Donnelly, Peter, Fox, Caroline S., Day-Williams, Aaron G., Plenge, Robert M., and Runz, Heiko

Published
2018
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48. Large-scale whole-exome sequencing association studies identify rare functional variants influencing serum urate levels

Author

Tin, Adrienne, Li, Yong, Brody, Jennifer A., Nutile, Teresa, Chu, Audrey Y., Huffman, Jennifer E., Yang, Qiong, Chen, Ming-Huei, Robinson-Cohen, Cassianne, Macé, Aurélien, Liu, Jun, Demirkan, Ayşe, Sorice, Rossella, Sedaghat, Sanaz, Swen, Melody, Yu, Bing, Ghasemi, Sahar, Teumer, Alexanda, Vollenweider, Peter, Ciullo, Marina, Li, Meng, Uitterlinden, André G., Kraaij, Robert, Amin, Najaf, van Rooij, Jeroen, Kutalik, Zoltán, Dehghan, Abbas, McKnight, Barbara, van Duijn, Cornelia M., Morrison, Alanna, Psaty, Bruce M., Boerwinkle, Eric, Fox, Caroline S., Woodward, Owen M., and Köttgen, Anna

Published
2018
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