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4. Disentangling the genetics of lean mass.

Author

Karasik, David, Zillikens, M Carola, Hsu, Yi-Hsiang, Aghdassi, Ali, Akesson, Kristina, Amin, Najaf, Barroso, Inês, Bennett, David A, Bertram, Lars, Bochud, Murielle, Borecki, Ingrid B, Broer, Linda, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos-Obando, Natalia, Cauley, Jane A, Cawthon, Peggy M, Chambers, John C, Chen, Zhao, Cho, Nam H, Choi, Hyung Jin, Chou, Wen-Chi, Cummings, Steven R, de Groot, Lisette CPGM, De Jager, Phillip L, Demuth, Ilja, Diatchenko, Luda, Econs, Michael J, Eiriksdottir, Gudny, Enneman, Anke W, Eriksson, Joel, Eriksson, Johan G, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Gieger, Christian, Grallert, Harald, Gudnason, Vilmundur, Lenore, Launer J, Hayward, Caroline, Hofman, Albert, Homuth, Georg, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Johnson, Toby, Biffar, Reiner, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koller, Daniel L, Kooner, Jaspal S, Kraus, William E, Kritchevsky, Stephen, Kutalik, Zoltán, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Lerch, Markus M, Lewis, Joshua R, Lill, Christina, Lind, Lars, Lindgren, Cecilia, Liu, Yongmei, Livshits, Gregory, Ljunggren, Östen, Loos, Ruth JF, Lorentzon, Mattias, Luan, Jian'an, Luben, Robert N, Malkin, Ida, McGuigan, Fiona E, Medina-Gomez, Carolina, Meitinger, Thomas, Melhus, Håkan, Mellström, Dan, Michaëlsson, Karl, Mitchell, Braxton D, Morris, Andrew P, Mosekilde, Leif, Nethander, Maria, Newman, Anne B, O'Connell, Jeffery R, Oostra, Ben A, Orwoll, Eric S, Palotie, Aarno, Peacock, Munro, and Perola, Markus

Subjects
Muscle, Skeletal, Adipose Tissue, Body Fluid Compartments, Humans, RNA-Binding Proteins, Receptor, Melanocortin, Type 4, Extracellular Matrix Proteins, Absorptiometry, Photon, Body Composition, Electric Impedance, Phenotype, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, European Continental Ancestry Group, Female, Male, Versicans, Genome-Wide Association Study, Young Adult, ADAMTS Proteins, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, body composition, skeletal muscle, body fat, meta-analysis of genome-wide association studies, metabolic profile, Prevention, Genetics, Human Genome, 2.1 Biological and endogenous factors, Nutrition & Dietetics, Engineering, Medical and Health Sciences
Abstract

BackgroundLean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass.ObjectivesTo determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci.MethodsWe performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms).ResultsSeven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection.ConclusionsIn conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass.

Published
2019

5. Higher Genetic Risk for Type 2 Diabetes Is Associated With a Faster Decline of β-Cell Function in an East Asian Population.

Author

Lee, Hyunsuk, Choi, Jaewon, Kim, Jong-Il, Watanabe, Richard M., Cho, Nam H., Park, Kyong Soo, and Kwak, Soo Heon

Subjects
EAST Asians, TYPE 2 diabetes, GENETIC risk score, GLUCOSE tolerance tests, GENETIC variation
Abstract

OBJECTIVE: While most genetic variants of type 2 diabetes (T2D) are suggested to be associated with β-cell dysfunction cross sectionally, their association with the longitudinal change of β-cell function remains largely unknown. RESEARCH DESIGN AND METHODS: We analyzed data from 6,311 participants without T2D at baseline (mean [SD] age 51.6 [8.7] years) from a community-based prospective cohort in Korea. Participants underwent biennial 2-h 75-g oral glucose tolerance tests (OGTTs) during 14 years of follow-up, and the OGTT-derived disposition index (DI) was used as a marker for β-cell function. Genetic risk was quantified using the genome-wide polygenic risk score (PRS) and was stratified into low (1st quintile), intermediate (2nd–4th quintiles), and high (5th quintile) genetic risk. Lifestyle was assessed according to Life's Essential 8. RESULTS: During a mean follow-up of 10.9 years, 374 (29.6%), 851 (22.5%), and 188 (14.9%) participants developed T2D in the high, intermediate, and low genetic risk groups, respectively. Compared with the low genetic risk group, participants in the high genetic risk group had a 25% lower DI at baseline. Furthermore, in longitudinal analysis, we observed a 1.83-fold faster decline in log2-transformed DI per year (−0.034 vs. −0.019, P = 2.1 × 10−3; per 1-SD increase in T2D PRS, P = 1.2 × 10−4). Healthy lifestyle attenuated the rate of decline in DI across all genetic risk groups. CONCLUSIONS: Individuals with a higher genetic risk for T2D exhibited not only a lower OGTT-derived β-cell function at baseline but also a notably more rapid decline during follow-up. This information could be used to enable a focused precision prevention with lifestyle intervention. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Author

Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics
Abstract

A correction to this article has been published and is linked from the HTML version of this article.

Published
2017

8. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Author

Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei

Subjects
Humans, Thinness, 17-Hydroxysteroid Dehydrogenases, Aldehyde Oxidoreductases, Extracellular Matrix Proteins, Body Composition, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Elements, Transcriptional, Versicans, Genome-Wide Association Study, Insulin Receptor Substrate Proteins, ADAMTS Proteins, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Human Genome, Genetics, 1.1 Normal biological development and functioning
Abstract

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p

Published
2017

9. Trajectory of lung function in diabetic adults: A 16‐year follow‐up study of community‐based prospective cohorts.

Author

Choi, Wonsuk, Moon, Joon Ho, Choi, Hayoung, Lee, Hyun, Kim, Hee Kyung, Kang, Ho‐Cheol, and Cho, Nam H.

Subjects
FORCED expiratory volume, PULMONARY function tests, LUNGS, VITAL capacity (Respiration), LONGITUDINAL method
Abstract

Background and Objective: To investigate the difference in lung function according to diabetes status in a community‐based prospective study. Methods: Individuals aged 40–69 years from two community‐based cohorts were followed prospectively for 16 years. A spirometer was used to evaluate lung function at baseline, and lung function tests were carried out biennially thereafter. Multivariable linear regression analysis was performed for the cross‐sectional and longitudinal analyses based on diabetes status. Results: Among the 6483 subjects, 2114 (32.6%) had prediabetes and 671 (10.4%) had diabetes. The prediabetes and diabetes groups had lower baseline % predicted values of forced expiratory volume in 1 s (FEV1) (mean, −1.853; 95% confidence interval [CI] –2.715 to −0.990 for prediabetes and mean, −4.088; 95% CI –5.424 to −2.752 for diabetes) and forced vital capacity (FVC) (mean, −2.087; 95% CI –2.837 to −1.337 for prediabetes and mean, −4.622; 95% CI –5.784 to −3.460 for diabetes) compared to the normoglycemia group after adjusting for relevant covariates. The rate of decline in FEV1% predicted (mean, −0.227; 95% CI –0.366 to −0.089) and FVC % predicted (mean, −0.232; 95% CI –0.347 to −0.117) during follow‐up were faster in the diabetes group than in the normoglycemia group. The diabetes group had a lower proportion of normal ventilation (ptrend = 0.048) and higher proportions of restrictive (ptrend = 0.001) and mixed (ptrend = 0.035) ventilatory disorders at the last follow‐up. Conclusion: Diabetes is associated with a lower baseline lung function and a faster rate of deterioration. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author

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

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

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

Published
2014

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

Author

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

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

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

Published
2014

17. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

Author

Kwak, Soo Heon, primary, Hernandez-Cancela, Ryan B., additional, DiCorpo, Daniel A, additional, Condon, David E., additional, Merino, Jordi, additional, Wu, Peitao, additional, Brody, Jennifer A, additional, Yao, Jie, additional, Guo, Xiuqing, additional, Ahmadizar, Fariba, additional, Meyer, Mariah, additional, Sincan, Murat, additional, Mercader, Josep M., additional, Lee, Sujin, additional, Haessler, Jeffrey, additional, Vy, Ha My T., additional, Lin, Zhaotong, additional, Armstrong, Nicole D., additional, Gu, Shaopeng, additional, Tsao, Noah L., additional, Lange, Leslie A., additional, Wang, Ningyuan, additional, Wiggins, Kerri L., additional, Trompet, Stella, additional, Liu, Simin, additional, Loos, Ruth J.F., additional, Judy, Renae, additional, Schroeder, Philip H., additional, Hasbani, Natalie R., additional, Bos, Maxime M., additional, Morrison, Alanna C., additional, Jackson, Rebecca D., additional, Reiner, Alexander P., additional, Manson, JoAnn E., additional, Chaudhary, Ninad S., additional, Carmichael, Lynn K., additional, Chen, Yii-Der Ida, additional, Taylor, Kent D., additional, Ghanbari, Mohsen, additional, van Meurs, Joyce, additional, Pitsillides, Achilleas N, additional, Psaty, Bruce M., additional, Noordam, Raymond, additional, Do, Ron, additional, Park, Kyong Soo, additional, Jukema, J Wouter, additional, Kavousi, Maryam, additional, Correa, Adolfo, additional, Rich, Stephen S., additional, Damrauer, Scott M., additional, Hajek, Catherine, additional, Cho, Nam H., additional, Irvin, Marguerite R., additional, Pankow, James S., additional, Nadkarni, Girish N., additional, Sladek, Robert, additional, Goodarzi, Mark O., additional, Florez, Jose C., additional, Chasman, Daniel I., additional, Heckbert, Susan R., additional, Kooperberg, Charles, additional, Dupuis, Josée, additional, Malhotra, Rajeev, additional, de Vries, Paul S., additional, Liu, Ching-Ti, additional, Rotter, Jerome I., additional, and Meigs, James B., additional

Published
2023
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21. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

Author

RWE/Causal inference, Child Health, Kwak, Soo Heon, Hernandez-Cancela, Ryan B, DiCorpo, Daniel A, Condon, David E, Merino, Jordi, Wu, Peitao, Brody, Jennifer A, Yao, Jie, Guo, Xiuqing, Ahmadizar, Fariba, Meyer, Mariah, Sincan, Murat, Mercader, Josep M, Lee, Sujin, Haessler, Jeffrey, Vy, Ha My T, Lin, Zhaotong, Armstrong, Nicole D, Gu, Shaopeng, Tsao, Noah L, Lange, Leslie A, Wang, Ningyuan, Wiggins, Kerri L, Trompet, Stella, Liu, Simin, Loos, Ruth J F, Judy, Renae, Schroeder, Philip H, Hasbani, Natalie R, Bos, Maxime M, Morrison, Alanna C, Jackson, Rebecca D, Reiner, Alexander P, Manson, JoAnn E, Chaudhary, Ninad S, Carmichael, Lynn K, Chen, Yii-Der Ida, Taylor, Kent D, Ghanbari, Mohsen, van Meurs, Joyce, Pitsillides, Achilleas N, Psaty, Bruce M, Noordam, Raymond, Do, Ron, Park, Kyong Soo, Jukema, J Wouter, Kavousi, Maryam, Correa, Adolfo, Rich, Stephen S, Damrauer, Scott M, Hajek, Catherine, Cho, Nam H, Irvin, Marguerite R, Pankow, James S, Nadkarni, Girish N, Sladek, Robert, Goodarzi, Mark O, Florez, Jose C, Chasman, Daniel I, Heckbert, Susan R, Kooperberg, Charles, Dupuis, Josée, Malhotra, Rajeev, de Vries, Paul S, Liu, Ching-Ti, Rotter, Jerome I, Meigs, James B, RWE/Causal inference, Child Health, Kwak, Soo Heon, Hernandez-Cancela, Ryan B, DiCorpo, Daniel A, Condon, David E, Merino, Jordi, Wu, Peitao, Brody, Jennifer A, Yao, Jie, Guo, Xiuqing, Ahmadizar, Fariba, Meyer, Mariah, Sincan, Murat, Mercader, Josep M, Lee, Sujin, Haessler, Jeffrey, Vy, Ha My T, Lin, Zhaotong, Armstrong, Nicole D, Gu, Shaopeng, Tsao, Noah L, Lange, Leslie A, Wang, Ningyuan, Wiggins, Kerri L, Trompet, Stella, Liu, Simin, Loos, Ruth J F, Judy, Renae, Schroeder, Philip H, Hasbani, Natalie R, Bos, Maxime M, Morrison, Alanna C, Jackson, Rebecca D, Reiner, Alexander P, Manson, JoAnn E, Chaudhary, Ninad S, Carmichael, Lynn K, Chen, Yii-Der Ida, Taylor, Kent D, Ghanbari, Mohsen, van Meurs, Joyce, Pitsillides, Achilleas N, Psaty, Bruce M, Noordam, Raymond, Do, Ron, Park, Kyong Soo, Jukema, J Wouter, Kavousi, Maryam, Correa, Adolfo, Rich, Stephen S, Damrauer, Scott M, Hajek, Catherine, Cho, Nam H, Irvin, Marguerite R, Pankow, James S, Nadkarni, Girish N, Sladek, Robert, Goodarzi, Mark O, Florez, Jose C, Chasman, Daniel I, Heckbert, Susan R, Kooperberg, Charles, Dupuis, Josée, Malhotra, Rajeev, de Vries, Paul S, Liu, Ching-Ti, Rotter, Jerome I, and Meigs, James B

Published
2023

24. Triglyceride-Glucose Index Predicts Future Atherosclerotic Cardiovascular Diseases: A 16-Year Follow-up in a Prospective, Community-Dwelling Cohort Study.

Author

Joon Ho Moon, Yongkang Kim, Tae Jung Oh, Jae Hoon Moon, Soo Heon Kwak, Kyong Soo Park, Hak Chul Jang, Sung Hee Choi, and Cho, Nam H.

Subjects
STOCK index futures, CARDIOVASCULAR diseases, RECEIVER operating characteristic curves, PROPORTIONAL hazards models, MYOCARDIAL infarction
Abstract

Background: While the triglyceride-glucose (TyG) index is a measure of insulin resistance, its association with cardiovascular disease (CVD) has not been well elucidated. We evaluated the TyG index for prediction of CVDs in a prospective large communitybased cohort. Methods: Individuals 40 to 70 years old were prospectively followed for a median 15.6 years. The TyG index was calculated as the Ln [fasting triglycerides (mg/dL)×fasting glucose (mg/dL)/2]. CVDs included any acute myocardial infarction, coronary artery disease or cerebrovascular disease. We used a Cox proportional hazards model to estimate CVD risks according to quartiles of the TyG index and plotted the receiver operating characteristics curve for the incident CVD. Results: Among 8,511 subjects (age 51.9±8.8 years; 47.5% males), 931 (10.9%) had incident CVDs during the follow-up. After adjustment for age, sex, body mass index, diabetes mellitus, hypertension, total cholesterol, smoking, alcohol, exercise, and C-reactive protein, subjects in the highest TyG quartile had 36% increased risk of incident CVD compared with the lowest TyG quartile (hazard ratio, 1.36; 95% confidence interval, 1.10 to 1.68). Carotid plaque, assessed by ultrasonography was more frequent in subjects in the higher quartile of TyG index (P for trend=0.049 in men and P for trend <0.001 in women). The TyG index had a higher predictive power for CVDs than the homeostasis model assessment of insulin resistance (HOMA-IR) (area under the curve, 0.578 for TyG and 0.543 for HOMA-IR). Adding TyG index on diabetes or hypertension alone gave sounder predictability for CVDs. Conclusion: The TyG index is independently associated with future CVDs in 16 years of follow-up in large, prospective Korean cohort. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Multistage genome-wide association meta-analyses identified two new loci for bone mineral density

Author

Zhang, Lei, Choi, Hyung Jin, Estrada, Karol, Leo, Paul J., Li, Jian, Pei, Yu-Fang, Zhang, Yinping, Lin, Yong, Shen, Hui, Liu, Yao-Zhong, Liu, Yongjun, Zhao, Yingchun, Zhang, Ji-Gang, Tian, Qing, Wang, Yu-ping, Han, Yingying, Ran, Shu, Hai, Rong, Zhu, Xue-Zhen, Wu, Shuyan, Yan, Han, Liu, Xiaogang, Yang, Tie-Lin, Guo, Yan, Zhang, Feng, Guo, Yan-fang, Chen, Yuan, Chen, Xiangding, Tan, Lijun, Zhang, Lishu, Deng, Fei-Yan, Deng, Hongyi, Rivadeneira, Fernando, Duncan, Emma L, Lee, Jong Young, Han, Bok Ghee, Cho, Nam H., Nicholson, Geoffrey C., McCloskey, Eugene, Eastell, Richard, Prince, Richard L., Eisman, John A., Jones, Graeme, Reid, Ian R., Sambrook, Philip N., Dennison, Elaine M., Danoy, Patrick, Yerges-Armstrong, Laura M., Streeten, Elizabeth A., Hu, Tian, Xiang, Shuanglin, Papasian, Christopher J., Brown, Matthew A., Shin, Chan Soo, Uitterlinden, André G., and Deng, Hong-Wen

Published
2014
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45. Association of obstructive sleep apnea and glucose metabolism in subjects with or without obesity

Author

Kim, Nan Hee, Cho, Nam H., Yun, Chang-Ho, Lee, Seung Ku, Yoon, Dae Wui, Cho, Hyun Joo, Ahn, Jae Hee, Seo, Ji. A., Kim, Sin Gon, Choi, Kyung Mook, Baik, Sei Hyun, Choi, Dong Seop, and Shin, Choi

Subjects
Cholesterol -- Physiological aspects -- Reports, Obesity -- Physiological aspects -- Reports, Dextrose -- Physiological aspects -- Reports, Diabetes -- Physiological aspects -- Reports, Insulin resistance -- Physiological aspects -- Reports, Glucose -- Physiological aspects -- Reports, Glucose metabolism -- Physiological aspects -- Reports, Sleep apnea syndromes -- Physiological aspects -- Reports, Health
Abstract

OBJECTIVE--The purpose of this study was to investigate whether the impact of obstructive sleep apnea (OSA) on glucose metabolism was different according to the presence or absence of obesity. RESEARCH [...]

Published
2013
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47. Metabolic Dysfunction-Associated Fatty Liver Disease Predicts Long-term Mortality and Cardiovascular Disease.

Author

Moon, Joon Ho, Kim, Won, Koo, Bo Kyung, and Cho, Nam H.

Subjects
FATTY liver, CARDIOVASCULAR disease related mortality, NON-alcoholic fatty liver disease, TYPE 2 diabetes, METABOLIC disorders
Abstract

Background/Aims: We investigated the effect of metabolic dysfunction-associated fatty liver disease (MAFLD) on future mortality and cardiovascular disease (CVD) using a prospective community-based cohort study. Methods: Individuals from two community-based cohorts who were 40 to 70 years old were prospectively followed for 16 years. MAFLD was defined as a high fatty liver index (FLI ≥60) plus one of the following conditions: overweight/obesity (body mass index ≥23 kg/m2 ), type 2 diabetes mellitus, or ≥2 metabolic risk abnormalities. Nonalcoholic fatty liver disease (NAFLD) was defined as FLI ≥60 without any secondary cause of hepatic steatosis. Results: Among 8,919 subjects (age 52.2±8.9 years, 47.7% of males), 1,509 (16.9%) had MAFLD. During the median follow-up of 15.7 years, MAFLD independently predicted overall mortality after adjustment for confounders (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.05 to 1.69) but NAFLD did not (HR, 1.20; 95% CI, 0.94 to 1.53). MAFLD also predicted CVD after adjustment for age, sex, and body mass index (HR, 1.35; 95% CI, 1.13 to 1.62), which lost its statistical significance by further adjustments. Stratified analysis indicated that metabolic dysfunction contributed to mortality (HR, 1.51; 95% CI, 1.21 to 1.89) and CVD (HR, 1.27; 95% CI, 1.02 to 1.59). Among metabolic dysfunctions used for defining MAFLD, type 2 diabetes mellitus in MAFLD increased the risk of both mortality (HR, 2.07; 95% CI, 1.52 to 2.81) and CVD (HR, 1.42; 95% CI, 1.09 to 1.85). Conclusions: MAFLD independently increased overall mortality. Heterogeneity in mortality and CVD risk of subjects with MAFLD may be determined by the accompanying metabolic dysfunctions. [ABSTRACT FROM AUTHOR]

Published
2022
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