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1. The Tehran longitudinal family-based cardiometabolic cohort study sheds new light on dyslipidemia transmission patterns

Author: Mahdi Akbarzadeh, Parisa Riahi, Amir Hossein Saeidian, Maryam Zarkesh, Sajedeh Masjoudi, Sara Asgarian, Kamran Guity, Hamed Moheimani, Homayoon Masoudi, Mahmoud Amiri Roudbar, Davood Khalili, Farhad Hosseinpanah, Maryam Barzin, Carolyn T. Hogan, Hakon Hakonarson, Mehdi Hedayati, Maryam S. Daneshpour, and Fereidoun Azizi
Subjects: Medicine, Science
Abstract: Abstract Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28–9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average.
Published: 2024
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2. Genome-wide association study on blood pressure traits in the Iranian population suggests ZBED9 as a new locus for hypertension

Author: Goodarz Kolifarhood, Siamak Sabour, Mahdi Akbarzadeh, Bahareh Sedaghati-khayat, Kamran Guity, Saeid Rasekhi Dehkordi, Mahmoud Amiri Roudbar, Farzad Hadaegh, Fereidoun Azizi, and Maryam S. Daneshpour
Subjects: Medicine, Science
Abstract: Abstract High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Hypertension (HTN) in 7694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study (TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for different sets of environmental predictors. Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. We found significant associations with similar direction of effects and allele frequency of genetic variants on ZBED9 with DBP (genome-wide threshold) and HTN (nominal threshold) in GWAS summary data of UK Biobank. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.
Published: 2021
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3. Familial genetic and environmental risk profile and high blood pressure event: a prospective cohort of cardio-metabolic and genetic study

Author: Goodarz Kolifarhood, Maryam S. Daneshpour, Asiyeh Sadat Zahedi, Nasim Khosravi, Bahareh Sedaghati-Khayat, Kamran Guity, Saeid Rasekhi Dehkordi, Mahmoud Amiri Roudbar, Forough Ghanbari, Farzad Hadaegh, Fereidoun Azizi, Mahdi Akbarzadeh, and Siamak Sabour
Subjects: hypertension, blood pressure, familial aggregation, genetics, linkage, epistasis, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background and aims High blood pressure is the heritable risk factor for cardiovascular diseases. We investigated whether the presence of familial genetic and environmental risk factors are associated with increased risk of high blood pressure. Methods A total of 4,559 individuals from 401 families were included in this study. Familial aggregation analysis was carried out on systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI) and waist circumference (WC), and heritability was estimated for SBP and DBP. The association between familial risk factors and blood pressure traits including, incidence of hypertension, SBP and DBP was estimated separately using regression-based two-level Haseman-Elston (HE) method, with individual and familial BMI and WC as environmental exposures and familial genetic profile of known variants as genetic risk factors in 210 index families (≥2 hypertensive cases). Models were adjusted for the two nested sets of covariates. Results During a follow-up of 15 years, the SBP, DBP, BMI and WC were highly correlated in inter class of mother-offspring and intraclass of sister-sister with heritability of 30 and 25% for DBP and SBP, respectively. Among index families, those whose members with higher familial BMI or WC had significantly increased risk of hypertension and consistent, strong signals of rs2493134 (AGT) linked with SBP and DBP, rs976683 (NLGN1) linked with SBP and HTN, and epistasis of rs2021783 (TNXB) and known genetic variants linked with all blood pressure traits. Conclusions Findings from this study show that familial genetic and environmental risk profile increase risk for high blood pressure beyond the effect of the individuals’ own risk factors.
Published: 2021
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4. GWAS findings improved genomic prediction accuracy of lipid profile traits: Tehran Cardiometabolic Genetic Study

Author: Mahdi Akbarzadeh, Saeid Rasekhi Dehkordi, Mahmoud Amiri Roudbar, Mehdi Sargolzaei, Kamran Guity, Bahareh Sedaghati-khayat, Parisa Riahi, Fereidoun Azizi, and Maryam S. Daneshpour
Subjects: Medicine, Science
Abstract: Abstract In recent decades, ongoing GWAS findings discovered novel therapeutic modifications such as whole-genome risk prediction in particular. Here, we proposed a method based on integrating the traditional genomic best linear unbiased prediction (gBLUP) approach with GWAS information to boost genetic prediction accuracy and gene-based heritability estimation. This study was conducted in the framework of the Tehran Cardio-metabolic Genetic study (TCGS) containing 14,827 individuals and 649,932 SNP markers. Five SNP subsets were selected based on GWAS results: top 1%, 5%, 10%, 50% significant SNPs, and reported associated SNPs in previous studies. Furthermore, we randomly selected subsets as large as every five subsets. Prediction accuracy has been investigated on lipid profile traits with a tenfold and 10-repeat cross-validation algorithm by the gBLUP method. Our results revealed that genetic prediction based on selected subsets of SNPs obtained from the dataset outperformed the subsets from previously reported SNPs. Selected SNPs’ subsets acquired a more precise prediction than whole SNPs and much higher than randomly selected SNPs. Also, common SNPs with the most captured prediction accuracy in the selected sets caught the highest gene-based heritability. However, it is better to be mindful of the fact that a small number of SNPs obtained from GWAS results could capture a highly notable proportion of variance and prediction accuracy.
Published: 2021
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5. Adolescent metabolic syndrome and its components associations with incidence of type 2 diabetes in early adulthood: Tehran lipid and glucose study

Author: Golaleh Asghari, Mitra Hasheminia, Abolfazl Heidari, Parvin Mirmiran, Kamran Guity, Mohammad Karim Shahrzad, Fereidoun Azizi, and Farzad Hadaegh
Subjects: Adolescent, Metabolic syndrome, Type 2 diabetes, Adulthood, Nutritional diseases. Deficiency diseases, RC620-627
Abstract: Abstract Aim To investigate the association of youth metabolic syndrome (MetS) and its components, individually and in combination with early adulthood incident type 2 diabetes (T2DM). Methods A total of 2798 adolescents aged 11–19 years enrolled in the study. At baseline, MetS, its components including blood pressure (BP), waist circumference (WC), triglycerides (TGs), fasting plasma glucose, and low HDL-C, and different combinations of MetS components were defined. After a mean 11.3 years of follow-up, T2DM was determined. Multivariable Cox proportional hazard regression analysis adjusted for age, sex, family history of T2DM, and adult BMI was used for data analysis. The hazard ratio (HR) and 95% confidence interval (CI) were reported. Results During the follow-up, 44 incidents T2DM were developed. Among different individual components, only high WC [HR = 2.63, 95% CI (1.39–4.97)] and high TGs [HR = 1.82, 95% CI (1.00–3.34)] remained as significant predictors only in the age and sex adjusted model. Regarding combinations of MetS components, ‘high TGs and high WC’ [HR = 2.70, 95% CI (1.27–5.77)], ‘high BP and high WC’ [HR = 2.52, 95% CI (1.00–6.33)], ‘high TGs and high BP’ [HR = 2.27, 95% CI (1.02–5.05)] as well as MetS per se [HR = 2.82, 95% CI (1.41–5.64)] had a significant relationship with incident T2DM in the multivariable adjusted model. Among different confounders, being female and having family history of T2DM were consistently associated with higher risk of T2DM, in different combinations of MetS components. Conclusions Adolescence MetS and some combinations of MetS components predicted early adulthood T2DM. Thus, adolescents, particularly female ones, with combinations of MetS components as well as those with family history of T2DM could be targeted for lifestyle intervention.
Published: 2021
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6. SARS-CoV-2 infection susceptibility influenced by ACE2 genetic polymorphisms: insights from Tehran Cardio-Metabolic Genetic Study

Author: Hossein Lanjanian, Maryam Moazzam-Jazi, Mehdi Hedayati, Mahdi Akbarzadeh, Kamran Guity, Bahareh Sedaghati-khayat, Fereidoun Azizi, and Maryam S. Daneshpour
Subjects: Medicine, Science
Abstract: Abstract The genetic variations among individuals are one of the notable factors determining disease severity and drug response. Nowadays, COVID-19 pandemic has been adversely affecting many aspects of human life. We used the Tehran Cardio-Metabolic Genetic Study (TCGS) data that is an ongoing genetic study including the whole-genome sequencing of 1200 individuals and chip genotyping of more than 15,000 participants. Here, the effect of ACE2 variations by focusing on the receptor-binding site of SARS-CoV-2 and ACE2 cleavage by TMPRSS2 protease were investigated through simulations study. After analyzing TCGS data, 570 genetic variations on the ACE2 gene, including single nucleotide polymorphisms (SNP) and insertion/deletion (INDEL) were detected. Interestingly, two observed missense variants, K26R and S331F, which only the first one was previously reported, can reduce the receptor affinity for the viral Spike protein. Moreover, our bioinformatics simulation of 3D structures and docking of proteins explains important details of ACE2-Spike and ACE2-TMPRSS2 interactions, especially the critical role of Arg652 of ACE2 for protease function of TMPRSS2 was uncovered. As our results show that the genetic variation of ACE2 can at least influence the affinity of this receptor to its partners, we need to consider the genetic variations on ACE2 as well as other genes in the pathways that contribute to the pathogenesis of COVID-19 for designing efficient drugs and vaccines.
Published: 2021
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7. Associations of autozygosity with a broad range of human phenotypes

Author: David W Clark, Yukinori Okada, Kristjan H S Moore, Dan Mason, Nicola Pirastu, Ilaria Gandin, Hannele Mattsson, Catriona L K Barnes, Kuang Lin, Jing Hua Zhao, Patrick Deelen, Rebecca Rohde, Claudia Schurmann, Xiuqing Guo, Franco Giulianini, Weihua Zhang, Carolina Medina-Gomez, Robert Karlsson, Yanchun Bao, Traci M Bartz, Clemens Baumbach, Ginevra Biino, Matthew J Bixley, Marco Brumat, Jin-Fang Chai, Tanguy Corre, Diana L Cousminer, Annelot M Dekker, David A Eccles, Kristel R van Eijk, Christian Fuchsberger, He Gao, Marine Germain, Scott D Gordon, Hugoline G de Haan, Sarah E Harris, Edith Hofer, Alicia Huerta-Chagoya, Catherine Igartua, Iris E Jansen, Yucheng Jia, Tim Kacprowski, Torgny Karlsson, Marcus E Kleber, Shengchao Alfred Li, Ruifang Li-Gao, Anubha Mahajan, Koichi Matsuda, Karina Meidtner, Weihua Meng, May E Montasser, Peter J van der Most, Matthias Munz, Teresa Nutile, Teemu Palviainen, Gauri Prasad, Rashmi B Prasad, Tallapragada Divya Sri Priyanka, Federica Rizzi, Erika Salvi, Bishwa R Sapkota, Daniel Shriner, Line Skotte, Melissa C Smart, Albert Vernon Smith, Ashley van der Spek, Cassandra N Spracklen, Rona J Strawbridge, Salman M Tajuddin, Stella Trompet, Constance Turman, Niek Verweij, Clara Viberti, Lihua Wang, Helen R Warren, Robyn E Wootton, Lisa R Yanek, Jie Yao, Noha A Yousri, Wei Zhao, Adebowale A Adeyemo, Saima Afaq, Carlos Alberto Aguilar-Salinas, Masato Akiyama, Matthew L Albert, Matthew A Allison, Maris Alver, Tin Aung, Fereidoun Azizi, Amy R Bentley, Heiner Boeing, Eric Boerwinkle, Judith B Borja, Gert J de Borst, Erwin P Bottinger, Linda Broer, Harry Campbell, Stephen Chanock, Miao-Li Chee, Guanjie Chen, Yii-Der I Chen, Zhengming Chen, Yen-Feng Chiu, Massimiliano Cocca, Francis S Collins, Maria Pina Concas, Janie Corley, Giovanni Cugliari, Rob M van Dam, Anna Damulina, Maryam S Daneshpour, Felix R Day, Graciela E Delgado, Klodian Dhana, Alexander S F Doney, Marcus Dörr, Ayo P Doumatey, Nduna Dzimiri, S Sunna Ebenesersdóttir, Joshua Elliott, Paul Elliott, Ralf Ewert, Janine F Felix, Krista Fischer, Barry I Freedman, Giorgia Girotto, Anuj Goel, Martin Gögele, Mark O Goodarzi, Mariaelisa Graff, Einat Granot-Hershkovitz, Francine Grodstein, Simonetta Guarrera, Daniel F Gudbjartsson, Kamran Guity, Bjarni Gunnarsson, Yu Guo, Saskia P Hagenaars, Christopher A Haiman, Avner Halevy, Tamara B Harris, Mehdi Hedayati, David A van Heel, Makoto Hirata, Imo Höfer, Chao Agnes Hsiung, Jinyan Huang, Yi-Jen Hung, M Arfan Ikram, Anuradha Jagadeesan, Pekka Jousilahti, Yoichiro Kamatani, Masahiro Kanai, Nicola D Kerrison, Thorsten Kessler, Kay-Tee Khaw, Chiea Chuen Khor, Dominique P V de Kleijn, Woon-Puay Koh, Ivana Kolcic, Peter Kraft, Bernhard K Krämer, Zoltán Kutalik, Johanna Kuusisto, Claudia Langenberg, Lenore J Launer, Deborah A Lawlor, I-Te Lee, Wen-Jane Lee, Markus M Lerch, Liming Li, Jianjun Liu, Marie Loh, Stephanie J London, Stephanie Loomis, Yingchang Lu, Jian’an Luan, Reedik Mägi, Ani W Manichaikul, Paolo Manunta, Gísli Másson, Nana Matoba, Xue W Mei, Christa Meisinger, Thomas Meitinger, Massimo Mezzavilla, Lili Milani, Iona Y Millwood, Yukihide Momozawa, Amy Moore, Pierre-Emmanuel Morange, Hortensia Moreno-Macías, Trevor A Mori, Alanna C Morrison, Taulant Muka, Yoshinori Murakami, Alison D Murray, Renée de Mutsert, Josyf C Mychaleckyj, Mike A Nalls, Matthias Nauck, Matt J Neville, Ilja M Nolte, Ken K Ong, Lorena Orozco, Sandosh Padmanabhan, Gunnar Pálsson, James S Pankow, Cristian Pattaro, Alison Pattie, Ozren Polasek, Neil Poulter, Peter P Pramstaller, Lluis Quintana-Murci, Katri Räikkönen, Sarju Ralhan, Dabeeru C Rao, Wouter van Rheenen, Stephen S Rich, Paul M Ridker, Cornelius A Rietveld, Antonietta Robino, Frank J A van Rooij, Daniela Ruggiero, Yasaman Saba, Charumathi Sabanayagam, Maria Sabater-Lleal, Cinzia Felicita Sala, Veikko Salomaa, Kevin Sandow, Helena Schmidt, Laura J Scott, William R Scott, Bahareh Sedaghati-Khayat, Bengt Sennblad, Jessica van Setten, Peter J Sever, Wayne H-H Sheu, Yuan Shi, Smeeta Shrestha, Sharvari Rahul Shukla, Jon K Sigurdsson, Timo Tonis Sikka, Jai Rup Singh, Blair H Smith, Alena Stančáková, Alice Stanton, John M Starr, Lilja Stefansdottir, Leon Straker, Patrick Sulem, Gardar Sveinbjornsson, Morris A Swertz, Adele M Taylor, Kent D Taylor, Natalie Terzikhan, Yih-Chung Tham, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Annika Tillander, Russell P Tracy, Teresa Tusié-Luna, Ioanna Tzoulaki, Simona Vaccargiu, Jagadish Vangipurapu, Jan H Veldink, Veronique Vitart, Uwe Völker, Eero Vuoksimaa, Salma M Wakil, Melanie Waldenberger, Gurpreet S Wander, Ya Xing Wang, Nicholas J Wareham, Sarah Wild, Chittaranjan S Yajnik, Jian-Min Yuan, Lingyao Zeng, Liang Zhang, Jie Zhou, Najaf Amin, Folkert W Asselbergs, Stephan J L Bakker, Diane M Becker, Benjamin Lehne, David A Bennett, Leonard H van den Berg, Sonja I Berndt, Dwaipayan Bharadwaj, Lawrence F Bielak, Murielle Bochud, Mike Boehnke, Claude Bouchard, Jonathan P Bradfield, Jennifer A Brody, Archie Campbell, Shai Carmi, Mark J Caulfield, David Cesarini, John C Chambers, Giriraj Ratan Chandak, Ching-Yu Cheng, Marina Ciullo, Marilyn Cornelis, Daniele Cusi, George Davey Smith, Ian J Deary, Rajkumar Dorajoo, Cornelia M van Duijn, David Ellinghaus, Jeanette Erdmann, Johan G Eriksson, Evangelos Evangelou, Michele K Evans, Jessica D Faul, Bjarke Feenstra, Mary Feitosa, Sylvain Foisy, Andre Franke, Yechiel Friedlander, Paolo Gasparini, Christian Gieger, Clicerio Gonzalez, Philippe Goyette, Struan F A Grant, Lyn R Griffiths, Leif Groop, Vilmundur Gudnason, Ulf Gyllensten, Hakon Hakonarson, Anders Hamsten, Pim van der Harst, Chew-Kiat Heng, Andrew A Hicks, Hagit Hochner, Heikki Huikuri, Steven C Hunt, Vincent W V Jaddoe, Philip L De Jager, Magnus Johannesson, Åsa Johansson, Jost B Jonas, J Wouter Jukema, Juhani Junttila, Jaakko Kaprio, Sharon L. R. Kardia, Fredrik Karpe, Meena Kumari, Markku Laakso, Sander W van der Laan, Jari Lahti, Matthias Laudes, Rodney A Lea, Wolfgang Lieb, Thomas Lumley, Nicholas G Martin, Winfried März, Giuseppe Matullo, Mark I McCarthy, Sarah E Medland, Tony R Merriman, Andres Metspalu, Brian F Meyer, Karen L Mohlke, Grant W Montgomery, Dennis Mook-Kanamori, Patricia B Munroe, Kari E North, Dale R Nyholt, Jeffery R O’connell, Carole Ober, Albertine J Oldehinkel, Walter Palmas, Colin Palmer, Gerard G Pasterkamp, Etienne Patin, Craig E Pennell, Louis Perusse, Patricia A Peyser, Mario Pirastu, Tinca J. C. Polderman, David J Porteous, Danielle Posthuma, Bruce M Psaty, John D Rioux, Fernando Rivadeneira, Charles Rotimi, Jerome I Rotter, Igor Rudan, Hester M Den Ruijter, Dharambir K Sanghera, Naveed Sattar, Reinhold Schmidt, Matthias B Schulze, Heribert Schunkert, Robert A Scott, Alan R Shuldiner, Xueling Sim, Neil Small, Jennifer A Smith, Nona Sotoodehnia, E-Shyong Tai, Alexander Teumer, Nicholas J Timpson, Daniela Toniolo, David-Alexandre Tregouet, Tiinamaija Tuomi, Peter Vollenweider, Carol A Wang, David R Weir, John B Whitfield, Cisca Wijmenga, Tien-Yin Wong, John Wright, Jingyun Yang, Lei Yu, Babette S Zemel, Alan B Zonderman, Markus Perola, Patrik K. E. Magnusson, André G Uitterlinden, Jaspal S Kooner, Daniel I Chasman, Ruth J. F. Loos, Nora Franceschini, Lude Franke, Chris S Haley, Caroline Hayward, Robin G Walters, John R. B. Perry, Tōnu Esko, Agnar Helgason, Kari Stefansson, Peter K Joshi, Michiaki Kubo, and James F Wilson
Subjects: Science
Abstract: Inbreeding depression has been observed in many different species, but in humans a systematic analysis has been difficult so far. Here, analysing more than 1.3 million individuals, the authors show that a genomic inbreeding coefficient (FROH) is associated with disadvantageous outcomes in 32 out of 100 traits tested.
Published: 2019
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8. Sex differences in the association between spousal metabolic risk factors with incidence of type 2 diabetes: a longitudinal study of the Iranian population

Author: Azra Ramezankhani, Kamran Guity, Fereidoun Azizi, and Farzad Hadaegh
Subjects: Metabolic risk factors, Spouse, Type 2 diabetes, Medicine, Physiology, QP1-981
Abstract: Abstract Background We investigated whether metabolic risk factors in one spouse were associated with an excessive risk of type 2 diabetes in the other. Methods The study cohort (1999–2018) included 1833 men and 1952 women, aged ≥ 20 years with information on both their own and their spouse’s diabetes status and metabolic risk factors including body mass index (BMI), waist circumference, systolic and diastolic blood pressure, triglyceride to high-density lipoprotein cholesterol ratio, and type 2 diabetes. The associations between spousal metabolic risk factors and type 2 diabetes were estimated using Cox regression models adjusted for the three nested sets of covariates. Results We found 714 (360 men and 354 women) incident cases of type 2 diabetes, after more than 15 years of follow-up. Among women, having a husband with diabetes was associated with a 38% (hazard ratio (HR) 1.38; 95% confidence interval (CI) 1.03, 1. 84) increased risk of type 2 diabetes, adjusted for age, socioeconomic status, individual’s own value of the respective spousal exposure variable, family history of diabetes, and physical activity level. After further adjustment for the woman’s own BMI level, the husband’s diabetes was associated with 23% (HR 1.23; 0.92, 1.64) higher risk of type 2 diabetes in wives, values which did not reach statistical significance. No significant associations were found between spousal metabolic risk factors and incidence of type 2 diabetes among index men. Conclusion We found a sex-specific effect of spousal diabetes on the risk of type 2 diabetes. Having a husband with diabetes increased an individual’s risk of type 2 diabetes. Our results might contribute to the early detection of individuals at high risk of developing type 2 diabetes, particularly, in women adversely affected by their partner’s diabetes.
Published: 2019
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9. Some dietary factors can modulate the effect of the zinc transporters 8 polymorphism on the risk of metabolic syndrome

Author: Firoozeh Hosseini-Esfahani, Parvin Mirmiran, Gelareh Koochakpoor, Maryam S. Daneshpour, Kamran Guity, and Fereidoun Azizi
Subjects: Medicine, Science
Abstract: Abstract There are conflicting data on the impact of zinc transporter 8 (ZNT8) gene variations on the metabolic syndrome (MetS). Hence, the effects of the interaction between rs13266634 and dietary factors on the risk of MetS were investigated in this study. Subjects of this nested case-control study were selected from the participants in Tehran Lipid and Glucose Study. Each of the cases (n = 817) was individually matched with a control. Dietary patterns were determined using factor analysis. The ZNT8 rs13266634 were genotyped by the Tetra-refractory mutation system-polymerase chain reaction analysis. Two dietary patterns were extracted. There were no significant interactions between the ZNT8 SNP and the dietary patterns on the risk of MetS or its components. An interaction was observed between rs13266634 and the omega-3 fatty acid intakes on the risk of MetS in subjects with the CC genotype (P interaction
Published: 2017
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10. Familial hypercholesterolemia in Tehran lipid and glucose study: A cross- sectional study

Author: Fatemeh Naghizadeh mooghari, Kamran Guity, Bahareh Sedaghatikhayat, Behzad Laamerad, Fereidoun Azizi, Maryam S Daneshpour, and Maryam Daneshpour
Subjects: familial hypercholesterolemia, polymorphism rs2228671, ldlr, tlgs, Medicine, Medicine (General), R5-920
Abstract: bjective (s): Familial hypercholesterolemia (FH) is one of the most common hereditary disorders in lipid metabolism that is distinguished by high plasma concentrations of low-density lipoprotein cholesterol (LDL-C) and cholesterol, can be considered tendon xanthomas and raised risk of premature coronary heart disease (CHD). This study aimed to assess the association between rs2228671 polymorphisms in the LDLR gene with familial hypercholesterolemia in a sample of Tehran Lipid and Glucose Study. Methods: This was a cross-sectional study in order to examine the association between rs2228671 common polymorphism of LDL-R gene with FH. The study sample consisted of 15005 participants of Tehran Lipid and Glucose Study. Genomic samples of the cases were extracted and the polymorphism of the considered gene was determined by the Tetra Primer ARMS-PCR method. The findings were analyzed by SPSS, FBAT, PLINK, PROGENY and POWER MARKER. Results: In all 206 cases (in 22 families) were identified. The results showed that there was no significant association between rs2228671 and FH disease (P=0.70). The minor allele frequency of T allele measured was 0.1016. No individuals carrying TT genotype were found in this population. Conclusion: The findings indicated that cases with rs2228671 polymorphisms had lesser minor allele frequency compared with other alleles. It seems that the absence of TT genotype can indicate protective role of T allele against familial hypercholesterolemia and cardiovascular diseases.
Published: 2016

11. Familial Clustering of Metabolic Syndrome and Its Risk Factors in Tehran Lipid and Glucose Study

Author: Maryam Zarkesh, Kamran Guity, Nima Hosseinzadeh, Freidoon Azizi, and Maryam Sadat Daneshpour
Subjects: Familial Clustering, Metabolic Syndrome, Tehran Lipid and Glucose Study, Medicine (General), R5-920
Abstract: Background & objectives: In this study, we aimed to determine the extent of possible genetic influence on cardio-metabolic risk factors and to evaluate the familial aggregation of metabolic syndrome (MetS) in a Tehranian population. Methods: In a cross-sectional observational study, the anthropometry, blood pressure andbiochemical measurements were examined in each member of 566 nuclear families. The role of risk factors in MetS and the Pearson partial correlation between MetS and lipid related factors were calculated. Results: The prevalence of MetS among the mothers and girls was 78.4 and 12.9%, respectively. Grandmothers had the highest incidence of atherosclerotic risk factors. Four factors were found which explained 77.7% of the overall variance. Recurrence risk ratio among siblings was 5.61 (95% conﬁdence interval [CI]: 3.15-9.97). The adjusted odds ratio (OR) of proband’s MetS status was 1.33 (95% CI: 1.06–1.67) and adjusted OR for the four factors to predict MetS were all signiﬁcant with the obesity factor having the highest risk (OR: 7.50, CI: 5.91–9.52) followed by dyslipidemia/hyperglycemia factor (OR: 4.86, CI: 4.03–5.87), and blood pressure factor (OR: 4.20, CI: 3.51-5.02). Conclusion: The present findings confirm the idea of familial aggregation and the recurrence risk ratio in MetS traits. Sibling correlations were higher than other relatives indicating the high genetic factors of these quantitative components in which a high risk of MetS (two-fold) was found
Published: 2016

12. Cohort profile update: Tehran cardiometabolic genetic study

Author: Maryam S. Daneshpour, Mahdi Akbarzadeh, Hossein Lanjanian, Bahar Sedaghati-khayat, Kamran Guity, Sajedeh Masjoudi, Asiyeh Sadat Zahedi, Maryam Moazzam-Jazi, Leila Najd Hassan Bonab, Bita Shalbafan, Sara Asgarian, Goodarz Koli Farhood, Niloofar Javanrooh, Maryam Zarkesh, Parisa Riahi, Mohammad Reza Moghaddas, Parvaneh Arbab Dehkordi, Azar Delbarpour Ahmadi, Firoozeh Hosseini, Sara Jalali Farahani, Farzad Hadaegh, Parvin Mirmiran, Fahimeh Ramezani Tehrani, Arash Ghanbarian, Mohammad Sadegh Fallah Mahboob Pasand, Parisa Amiri, Majid Valizadeh, Farhad Hosseipanah, Maryam Tohidi, Asghar Ghasemi, Azita Zadeh-Vakili, Mohammad Piryaei, Shahram Alamdari, Davood Khalili, Amirabbas Momenan, Maryam Barzin, Sirous Zeinali, Mehdi Hedayati, Fereidoun Azizi, and Internal Medicine
Subjects: SDG 3 - Good Health and Well-being, Epidemiology
Abstract: The Tehran cardiometabolic genetic study (TCGS) is a large population-based cohort study that conducts periodic follow-ups. TCGS has created a comprehensive database comprising 20,367 participants born between 1911 and 2015 selected from four main ongoing studies in a family-based longitudinal framework. The study's primary goal is to identify the potential targets for prevention and intervention for non-communicable diseases that may develop in mid-life and late life. TCGS cohort focuses on cardiovascular, endocrine, metabolic abnormalities, cancers, and some inherited diseases. Since 2017, the TCGS cohort has augmented by encoding all health-related complications, including hospitalization outcomes and self-reports according to ICD11 coding, and verifying consanguineous marriage using genetic markers. This research provides an update on the rationale and design of the study, summarizes its findings, and outlines the objectives for precision medicine.
Published: 2023

13. Title: Cohort profile update: Tehran Cardiometabolic Genetic Study, a path toward precision medicine

Author: Maryam S Daneshpour, Mahdi Akbarzadeh, Hossein Lanjanian, Bahar Sedaghati-khayat, Kamran Guity, Sajedeh Masjoudi, Asieh Sadat Zahedi, Maryam Moazzam-Jazi, Leila Najd Hassan Bonab, Bita Shalbafan, Sara Asgarian, Goodarz Koli Farhood, Niloofar Javanrooh, Maryam Zarkesh, Parisa Riahi, Mohammad Reza Moghaddas, Parvaneh Arbab Dehkordi, Azar Delbarpour Ahmadi, Firoozeh Hosseini, Sara Jalali Farahani, Farzad Hadaegh, Parvin Mirmiarn, Fahimeh Ramezani Tehrani, Arash Ghanbarian, Mohammad Sadegh Fallah Mahboob Pasand, Parisa Amiri, Majid Valizadeh, Farhad Hosseipanah, Maryam Tohidi, Asghar Ghasemi, Azita Zadeh Vakili, Shahram Alamdari, Davood Khalili, Amirabbas Momenan, Maryam Barzin, Sirous Zeinali, Mehdi Hedayati, and Fereidoun Azizi
Abstract: The Tehran Cardiometabolic Genetic Study (TCGS) is a large population-based cohort study with periodic follow-ups, which created a comprehensive database of 20,367 participants born between 1911-2015 selected from 4 different longitudinal, ongoing, and family-based studies. The study aims to identify the potential targets for prevention and intervention for non-communicable diseases in mid-life and late life. The study focuses on cardiovascular, endocrine, metabolic abnormalities, cancers, and some inherited diseases. Since 2017, the cohort expanded the information by coding all health-related complications (hospitalization outcomes and self-reports) based on ICD11 coding and confirming the consanguineous marriage with genetic markers. This article presents an update on the rationale and design of the study. We also present a summary of our findings and our goals toward precision medicine.
Published: 2022

14. Genome-wide association study on blood pressure traits in the Iranian population suggests ZBED9 as a new locus for hypertension

Author: Mahmoud Amiri Roudbar, Fereidoun Azizi, Siamak Sabour, Bahareh Sedaghati-khayat, Kamran Guity, Goodarz Kolifarhood, Mahdi Akbarzadeh, Farzad Hadaegh, Saeid Rasekhi Dehkordi, and Maryam S. Daneshpour
Subjects: 0301 basic medicine, Adult, Male, Science, Population, Diastole, Locus (genetics), Genome-wide association study, Blood Pressure, 030204 cardiovascular system & hematology, Biology, Arrhythmias, Iran, Article, 03 medical and health sciences, 0302 clinical medicine, Quantitative Trait, Heritable, Genetic linkage, Chronic kidney disease, Humans, Genetic Predisposition to Disease, cardiovascular diseases, education, Allele frequency, Genetic association, Genetics, education.field_of_study, Multidisciplinary, Middle Aged, 030104 developmental biology, Blood pressure, Cardiovascular diseases, Hypertension, Medicine, Female, Genome-Wide Association Study
Abstract: High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Hypertension (HTN) in 7694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study (TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for different sets of environmental predictors. Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. We found significant associations with similar direction of effects and allele frequency of genetic variants on ZBED9 with DBP (genome-wide threshold) and HTN (nominal threshold) in GWAS summary data of UK Biobank. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.
Published: 2021

15. GWAS findings improved genomic prediction accuracy of lipid profile traits: Tehran Cardiometabolic Genetic Study

Author: Fereidoun Azizi, Kamran Guity, Saeid Rasekhi Dehkordi, Mahmoud Amiri Roudbar, Maryam S. Daneshpour, Mehdi Sargolzaei, Mahdi Akbarzadeh, Parisa Riahi, and Bahareh Sedaghati-khayat
Subjects: Science, Inheritance Patterns, Genome-wide association study, Single-nucleotide polymorphism, Computational biology, Biology, Best linear unbiased prediction, Significant snps, Iran, Article, Metabolic Diseases, Snp markers, Developmental biology, medicine, Genetics, SNP, Humans, Multidisciplinary, medicine.diagnostic_test, Molecular Sequence Annotation, Genomics, Heritability, Lipids, Computational biology and bioinformatics, Phenotype, Cardiovascular Diseases, Medicine, Lipid profile, Genome-Wide Association Study
Abstract: In recent decades, ongoing GWAS findings discovered novel therapeutic modifications such as whole-genome risk prediction in particular. Here, we proposed a method based on integrating the traditional genomic best linear unbiased prediction (gBLUP) approach with GWAS information to boost genetic prediction accuracy and gene-based heritability estimation. This study was conducted in the framework of the Tehran Cardio-metabolic Genetic study (TCGS) containing 14,827 individuals and 649,932 SNP markers. Five SNP subsets were selected based on GWAS results: top 1%, 5%, 10%, 50% significant SNPs, and reported associated SNPs in previous studies. Furthermore, we randomly selected subsets as large as every five subsets. Prediction accuracy has been investigated on lipid profile traits with a tenfold and 10-repeat cross-validation algorithm by the gBLUP method. Our results revealed that genetic prediction based on selected subsets of SNPs obtained from the dataset outperformed the subsets from previously reported SNPs. Selected SNPs’ subsets acquired a more precise prediction than whole SNPs and much higher than randomly selected SNPs. Also, common SNPs with the most captured prediction accuracy in the selected sets caught the highest gene-based heritability. However, it is better to be mindful of the fact that a small number of SNPs obtained from GWAS results could capture a highly notable proportion of variance and prediction accuracy.
Published: 2021

16. The role of childhood BMI in predicting early adulthood dysglycemia: Tehran lipid and glucose study

Author: Maryam Mahdavi, Majid Valizadeh, Fereidoun Azizi, Farhad Hosseinpanah, Maryam Barzin, Zahra Piri, and Kamran Guity
Subjects: Adult, Blood Glucose, Male, Pediatric Obesity, Pediatrics, medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, Population, Medicine (miscellaneous), 030209 endocrinology & metabolism, Type 2 diabetes, Iran, 030204 cardiovascular system & hematology, Overweight, Risk Assessment, Body Mass Index, Prediabetic State, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, medicine, Humans, Cumulative incidence, Prospective Studies, Prediabetes, Child, education, education.field_of_study, Nutrition and Dietetics, business.industry, Incidence, Incidence (epidemiology), Age Factors, nutritional and metabolic diseases, Prognosis, medicine.disease, Lipids, Obesity, Diabetes Mellitus, Type 2, Child, Preschool, Female, medicine.symptom, Cardiology and Cardiovascular Medicine, business, Biomarkers, Follow-Up Studies, Cohort study
Abstract: Background and Aim Increased adiposity is associated with insulin resistance and glycemic disturbances. We aimed to determine whether childhood overweight or obesity are independent factors in predicting adulthood dysglycemia (prediabetes or type 2 diabetes). Methods and Results In this population-based cohort study, 1290 normoglycemic subjects aged 3–11 years were followed for incidence of dysglycemia. Cox-proportional hazard models were employed to evaluate the association of obesity and overweight with incidence of dysglycemia by adjustments for age, sex, parental risk factors and baseline individual risk factors. The participants, with a mean age of 7.7 ± 2.5 years, were followed for a median of 14.9 years. During follow up, 158 subjects developed dysglycemia (18 type 2 diabetes, 140 prediabetes), contributing to a total cumulative incidence of 24.7%. The unadjusted HR for developing adult dysglycemia were 1.6 (95% CI; 1.0–2.4) and 1.7 (95% CI; 1.0–3.0) in overweight and obese children, respectively. Further adjustments for age, sex, parental risk factors and baseline individual risk factors changed the results in both overweight and obese children. Conclusion These findings show that overweight or obesity in childhood have no independent role for developing adulthood dysglycemia.
Published: 2020

17. Presence of CC Genotype for rs17773430 Could Affect the Percentage of Excess Weight Loss 1 Year After Bariatric Surgery: Tehran Obesity Treatment Study (TOTS)

Author: Kamran Guity, Bahareh Sedaghati-khayat, Majid Valizadeh, Niloufar Javanrouh, Maryam S. Daneshpour, Alireza Khalaj, and Maryam Barzin
Subjects: Adult, Male, medicine.medical_specialty, Time Factors, Adolescent, Genotype, Endocrinology, Diabetes and Metabolism, Excess weight, Bariatric Surgery, 030209 endocrinology & metabolism, Iran, Affect (psychology), Polymorphism, Single Nucleotide, Body Mass Index, Cohort Studies, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Weight loss, Weight Loss, medicine, Humans, Genetic Association Studies, Aged, Nutrition and Dietetics, business.industry, Middle Aged, medicine.disease, Obesity, Obesity, Morbid, Surgery, Treatment Outcome, Treatment study, Cohort, Receptor, Melanocortin, Type 4, Female, 030211 gastroenterology & hepatology, medicine.symptom, business, Follow-Up Studies, Cohort study
Abstract: Morbid obesity could last for a long period of life and increase the risk of morbidity as well as premature mortality. Although bariatric surgery benefits patients by quick weight loss, not all bariatric patients lose the same percentage of weight after a long time from surgery, which may be the result of diet, physical activity, and genetic components. In this study, we evaluated the association between the MC4R gene and both excess weight loss percentage (EWL%) and excess BMI loss percentage (EBMIL%) in a cohort of bariatric surgery patients after 6 and 12 months from surgery. A total of 424 bariatric surgery patients who had participated in the Tehran Obesity Treatment Study and had weight measurements after 6 and 12 months from surgery were included in the study. Four SNPs in the MC4R gene were selected for evaluating the associations. We found that rs17773430 had a significant effect on both EWL% and EBMIL%, especially after 12 months of bariatric surgery. Furthermore, three other SNPs, rs17782313, rs476828, and rs11152213, did not show any significant association with EWL% and EBMIL%. This study was the first to report on the association of rs17773430 with both EWL% and EBMIL% in a cohort of patients after bariatric surgery. We found that weight loss after surgery is influenced by genetic factors, and there were significant differences between the distribution of EWL% and EBMIL% in morbid obese bariatric patients who have two minor alleles of the rs17773430 and other SNPs.
Published: 2019

18. Gestational diabetes mellitus in mothers and long term cardiovascular disease in both parents: Results of over a decade follow-up of the Iranian population

Author: Azra Ramezankhani, Mitra Hasheminia, Maryam Kabootari, Kamran Guity, Farzad Hadaegh, and Fereidoun Azizi
Subjects: Adult, Male, 0301 basic medicine, medicine.medical_specialty, Time Factors, Adolescent, Health Status, Maternal Health, Population, Iran, 030204 cardiovascular system & hematology, Risk Assessment, Miscarriage, Fathers, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Pregnancy, Risk Factors, Diabetes mellitus, Humans, Medicine, Longitudinal Studies, Prospective Studies, Risk factor, Spouses, education, education.field_of_study, business.industry, Obstetrics, Incidence, Hazard ratio, Confounding, Middle Aged, Prognosis, medicine.disease, Gestational diabetes, Diabetes, Gestational, Parity, 030104 developmental biology, Cardiovascular Diseases, Female, Cardiology and Cardiovascular Medicine, business, Body mass index, Follow-Up Studies
Abstract: Background and aims We aimed at evaluating whether the presence of gestational diabetes mellitus (GDM) in mothers is associated with increased risk of incident cardiovascular disease (CVD) in both mothers and fathers. Methods In this population-based study, 4308 Iranian women, aged 18–64 years, with at least 1 live-birth delivery, and free of CVD at baseline, were followed. Corresponding spouses were identified in 2547 cases. The association between history of GDM and incident CVD was assessed using multivariate Cox's proportional hazard in 3 models: model 1, unadjusted; model 2, adjusted for age, body mass index, smoking (for men), maternal parity, miscarriage, physical activity, hypertension and hypercholesterolemia, and model 3, further adjusted for diabetes mellitus. Results After a median follow-up of 14.1 years, 314 mothers and 424 fathers experienced CVD. Women with history of GDM had an adjusted hazard ratio (HR), 95% CI of 1.85 (1.38–2.48) and 1.29 (0.96–1.75) for CVD in models 1 and 2, respectively. Furthermore, an independent association with CVD was observed in fathers with an adjusted HR of 1.35 (1.02–1.79) in the confounder adjusted model and even after further controlling for diabetes [1.36 (1.03–1.80)]. Moreover, all traditional risk factors, excluding BMI, showed an independent risk for CVD in both genders. Conclusions Women with prior GDM showed an increased risk of CVD that was not independent of important CVD risk factors. However, among men, spousal history of GDM was an independent risk factor for incident CVD, even after considering important traditional risk factors, including diabetes.
Published: 2019

19. Sex differences in the association between spousal metabolic risk factors with incidence of type 2 diabetes: a longitudinal study of the Iranian population

Author: Farzad Hadaegh, Fereidoun Azizi, Azra Ramezankhani, and Kamran Guity
Subjects: 0301 basic medicine, Adult, Male, Longitudinal study, Metabolic risk factors, lcsh:Medicine, Type 2 diabetes, Iran, lcsh:Physiology, Gender Studies, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Risk Factors, Diabetes mellitus, Medicine, Humans, Longitudinal Studies, Spouses, Socioeconomic status, Sex Characteristics, lcsh:QP1-981, business.industry, Proportional hazards model, Research, Incidence, Hazard ratio, Spouse, lcsh:R, Middle Aged, medicine.disease, 030104 developmental biology, Diabetes Mellitus, Type 2, Cohort, Female, business, Body mass index, 030217 neurology & neurosurgery, Demography
Abstract: Background We investigated whether metabolic risk factors in one spouse were associated with an excessive risk of type 2 diabetes in the other. Methods The study cohort (1999–2018) included 1833 men and 1952 women, aged ≥ 20 years with information on both their own and their spouse’s diabetes status and metabolic risk factors including body mass index (BMI), waist circumference, systolic and diastolic blood pressure, triglyceride to high-density lipoprotein cholesterol ratio, and type 2 diabetes. The associations between spousal metabolic risk factors and type 2 diabetes were estimated using Cox regression models adjusted for the three nested sets of covariates. Results We found 714 (360 men and 354 women) incident cases of type 2 diabetes, after more than 15 years of follow-up. Among women, having a husband with diabetes was associated with a 38% (hazard ratio (HR) 1.38; 95% confidence interval (CI) 1.03, 1. 84) increased risk of type 2 diabetes, adjusted for age, socioeconomic status, individual’s own value of the respective spousal exposure variable, family history of diabetes, and physical activity level. After further adjustment for the woman’s own BMI level, the husband’s diabetes was associated with 23% (HR 1.23; 0.92, 1.64) higher risk of type 2 diabetes in wives, values which did not reach statistical significance. No significant associations were found between spousal metabolic risk factors and incidence of type 2 diabetes among index men. Conclusion We found a sex-specific effect of spousal diabetes on the risk of type 2 diabetes. Having a husband with diabetes increased an individual’s risk of type 2 diabetes. Our results might contribute to the early detection of individuals at high risk of developing type 2 diabetes, particularly, in women adversely affected by their partner’s diabetes.
Published: 2019

20. Identifying new associated pleiotropic SNPs with lipids by simultaneous test of multiple longitudinal traits: An Iranian family-based study

Author: Kamran Guity, Maryam S. Daneshpour, Fereidoun Azizi, Farid Zayeri, Yadollah Mehrabi, and Nima Hosseinzadeh
Subjects: Adult, Male, 0301 basic medicine, Single-nucleotide polymorphism, Iran, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, 03 medical and health sciences, 0302 clinical medicine, Chromosome 16, Pleiotropy, Plasma lipids, Genetics, Humans, SNP, Solute Carrier Family 12, Member 3, Gene, Triglycerides, Genetic association, Cholesterol, HDL, Intracellular Signaling Peptides and Proteins, RNA-Binding Proteins, Genetic Pleiotropy, General Medicine, Middle Aged, Lipids, Cholesterol Ester Transfer Proteins, Pedigree, 030104 developmental biology, 030220 oncology & carcinogenesis, Female, Family based, Chromosomes, Human, Pair 16, Genome-Wide Association Study
Abstract: A number of genome-wide association studies (GWASs) have identified several genetic determinants of plasma lipids in European populations, in which analytical approaches have often been based on the linear regression models and the association test between a SNP and each lipid component individually in cross-sectional designs. Since lipid variations are correlated, the consideration of pleiotropy is necessary and using methods that can perform simultaneous association test of multiple longitudinal traits provides more information about the recognition of the pleiotropic variants. To identify new pleiotropic variants and to determine whether loci identified in previous GWASs can also exert the same effect on lipid concentrations in Iranian population, longitudinal measurements of lipid variations were used in a sample of Iranian population (16,353 individuals within 3100 families) that followed up every 3 years and using a two-step model, the associations of 20,036 available SNPs on chromosome 16 were assessed. Twenty variants within the AC009035.1, SLC12A3, CETP, NLRC5, ESRP2 and, C16orf95 genes showed strong evidence for association with HDL-C, cholesterol, and triglycerides with p-values ranging from 1.7 × 10−102 to 6.6 × 10−5. Since many genetic variants associated with lipids still remain to be determined, the results of the present study may provide valuable information on identifying the associations of new genetic loci with lipid variations in other populations.
Published: 2019

21. Familial genetic and environmental risk profile and high blood pressure event: a prospective cohort of cardio-metabolic and genetic study

Author: Siamak Sabour, Asiyeh Sadat Zahedi, Saeid Rasekhi Dehkordi, Bahareh Sedaghati-khayat, Goodarz Kolifarhood, Forough Ghanbari, Kamran Guity, Farzad Hadaegh, Mahdi Akbarzadeh, Mahmoud Amiri Roudbar, Maryam S. Daneshpour, Fereidoun Azizi, and Nasim Khosravi
Subjects: Oncology, Male, medicine.medical_specialty, Cell Adhesion Molecules, Neuronal, Blood Pressure, 030204 cardiovascular system & hematology, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, Quantitative Trait, Heritable, Environmental risk, Cardio metabolic, Risk Factors, Internal medicine, Internal Medicine, Medicine, Humans, 030212 general & internal medicine, Prospective Studies, Risk factor, Prospective cohort study, Retrospective Studies, Models, Genetic, business.industry, Models, Cardiovascular, Family aggregation, Genetic Variation, Tenascin, General Medicine, Environmental Exposure, Blood pressure, Hypertension, Female, Waist Circumference, Cardiology and Cardiovascular Medicine, business, Genome-Wide Association Study
Abstract: High blood pressure is the heritable risk factor for cardiovascular diseases. We investigated whether the presence of familial genetic and environmental risk factors are associated with increased risk of high blood pressure.A total of 4,559 individuals from 401 families were included in this study. Familial aggregation analysis was carried out on systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI) and waist circumference (WC), and heritability was estimated for SBP and DBP. The association between familial risk factors and blood pressure traits including, incidence of hypertension, SBP and DBP was estimated separately using regression-based two-level Haseman-Elston (HE) method, with individual and familial BMI and WC as environmental exposures and familial genetic profile of known variants as genetic risk factors in 210 index families (≥2 hypertensive cases). Models were adjusted for the two nested sets of covariates.During a follow-up of 15 years, the SBP, DBP, BMI and WC were highly correlated in inter class of mother-offspring and intraclass of sister-sister with heritability of 30 and 25% for DBP and SBP, respectively. Among index families, those whose members with higher familial BMI or WC had significantly increased risk of hypertension and consistent, strong signals of rs2493134 (Findings from this study show that familial genetic and environmental risk profile increase risk for high blood pressure beyond the effect of the individuals' own risk factors.
Published: 2021

22. Parental Transmission Plays the Major Role in High Aggregation of Type 2 Diabetes in Iranian Families: Tehran Lipid and Glucose Study

Author: Maryam Zarkesh, Mahmoud Amiri Roudbar, Davood Khalili, Saeid Rasekhi Dehkordi, Asiyeh Sadat Zahedi, Azra Ramezankhani, Fereidoun Azizi, Maryam S. Daneshpour, Parisa Riahi, Kamran Guity, and Mahdi Akbarzadeh
Subjects: Parents, business.industry, Endocrinology, Diabetes and Metabolism, Parenteral transmission, Family aggregation, Pedigree chart, General Medicine, Complex segregation analysis, Heritability, Iran, Lipids, Endocrinology, Glucose, Diabetes Mellitus, Type 2, Cohort, Internal Medicine, Inheritance Mode, Medicine, Humans, Family history, business, Demography
Abstract: This study is the first to evaluate familial aggregation, heritability and inheritance mode of type 2 diabetes (T2D) in Tehran Lipid Glucose Study (TLGS) participants as a representative sample of the Iranian population.From the ongoing family-based TLGS cohort, 13,741 individuals at least 20 years of age (mean ± standard deviation, 39.71±16.56) were assessed. After correcting family structures using genomic information from the Tehran Cardiometabolic Genetic Study, 2,594 constituent pedigrees were constructed. Familial aggregation was assessed based on genealogic index testing, familial intraclass correlation and positive family history. Family-based heritability was checked with 2 linear mixed models, including 2 different random components: the kinship matrix and the genomic relationship matrix. The mode of inheritance of T2D was investigated by complex segregation analysis (CSA).Familial aggregation of T2D was significant (p0.05), and family-based heritability showed a high degree of genetic variation in T2D between individuals at 65% (standard error, 0.034). Within first-degree relatives (parent/offspring and siblings), the likelihood of a parental affect was higher than in siblings (odds ratio, 4.11 vs 1.65). Family history of T2D among first-degree relatives was more noteworthy than for second-degree relatives (odds ratio, 3.84 vs 0.59). CSA revealed that the polygenic model is best to illustrate the mode of inheritance of T2D for TLGS participants.Our findings demonstrate that the heritability of T2D with polygenic mode in the Iranian population is higher than the global average. We also found that T2D is transmitted equally into siblings, with parental affect the leading risk factor. These data suggest that policymakers should change individual-level to family-level prevention.
Published: 2021

23. Adolescent metabolic syndrome and its components associations with incidence of type 2 diabetes in early adulthood: Tehran lipid and glucose study

Author: Farzad Hadaegh, Mohammad Karim Shahrzad, Mitra Hasheminia, Abolfazl Heidari, Fereidoun Azizi, Parvin Mirmiran, Kamran Guity, and Golaleh Asghari
Subjects: medicine.medical_specialty, Waist, Adolescent, business.industry, Research, Endocrinology, Diabetes and Metabolism, Hazard ratio, Confounding, nutritional and metabolic diseases, Type 2 diabetes, Adulthood, medicine.disease, Metabolic syndrome, Confidence interval, lcsh:Nutritional diseases. Deficiency diseases, Internal medicine, Diabetes mellitus, Internal Medicine, Medicine, Family history, business, lcsh:RC620-627
Abstract: Aim To investigate the association of youth metabolic syndrome (MetS) and its components, individually and in combination with early adulthood incident type 2 diabetes (T2DM). Methods A total of 2798 adolescents aged 11–19 years enrolled in the study. At baseline, MetS, its components including blood pressure (BP), waist circumference (WC), triglycerides (TGs), fasting plasma glucose, and low HDL-C, and different combinations of MetS components were defined. After a mean 11.3 years of follow-up, T2DM was determined. Multivariable Cox proportional hazard regression analysis adjusted for age, sex, family history of T2DM, and adult BMI was used for data analysis. The hazard ratio (HR) and 95% confidence interval (CI) were reported. Results During the follow-up, 44 incidents T2DM were developed. Among different individual components, only high WC [HR = 2.63, 95% CI (1.39–4.97)] and high TGs [HR = 1.82, 95% CI (1.00–3.34)] remained as significant predictors only in the age and sex adjusted model. Regarding combinations of MetS components, ‘high TGs and high WC’ [HR = 2.70, 95% CI (1.27–5.77)], ‘high BP and high WC’ [HR = 2.52, 95% CI (1.00–6.33)], ‘high TGs and high BP’ [HR = 2.27, 95% CI (1.02–5.05)] as well as MetS per se [HR = 2.82, 95% CI (1.41–5.64)] had a significant relationship with incident T2DM in the multivariable adjusted model. Among different confounders, being female and having family history of T2DM were consistently associated with higher risk of T2DM, in different combinations of MetS components. Conclusions Adolescence MetS and some combinations of MetS components predicted early adulthood T2DM. Thus, adolescents, particularly female ones, with combinations of MetS components as well as those with family history of T2DM could be targeted for lifestyle intervention.
Published: 2021

24. The Role of Different Linkage Disequilibrium Patterns in Genomic Prediction: The gBULP Based Exploratory Method in Tehran Cardiometabolic Genetic Study

Author: Kamran Guity, Mahmoud Amiri Roudbar, Mehdi Sargolzaei, Maryam S. Daneshpour, Saeid Rasekhi Dehkordi, Hossein Lanjanian, Mahdei Akbarzadeh, Fereidoun Azizi, Parisa Riahi, and Bahareh Sedaghati-khayat
Subjects: Linkage disequilibrium, Evolutionary biology, Biology
Abstract: Background: Current GWAS discoveries have discovered novel clinical improvements in recent decades, such as estimating whole-genome risk. Genetic prediction of traits has substantial impacts on public health care and disease prevention. This study aimed to investigate the effects of different linkage disequilibrium (LD) patterns on genomic prediction accuracy and SNP-based heritability estimation for four lipid profile traits.Results: This family-based study included 11,798 individuals ranging from 3 to 80 ys, extracted from Tehran Cardiometabolic Genetic Study (TCGS). LD patterns were considered on different thresholds (0.01, 0.03, 0.05, 0.07, 0.09, 0.1, 0.2, 0.3, 0.5, 0.6, 0.7, 0.8, and 0.9) to create subsets of SNPs. We have compared the prediction accuracy and SNP-based heritability estimation of the selected SNPs within these patterns as well as randomly selected SNPs with equal sizes. Subsets of SNPs selected based on LD patterns had a higher prediction accuracy level than subsets of SNPs selected randomly, and when the LD threshold increases, the difference tends to zero. The results were consistent when the prediction accuracy of subsets were adjusted for their SNP numbers in all traits. For all traits, when the number of SNPs was adjusted, between LD threshold 0.01 and 0.2, both prediction accuracy and SNP-based heritability have a dramatic rise. After substantial growth, there was a steady decline, and they reach a peak at an LD threshold between 0.2 and 0.3.Conclusions: This research indicated that having selected subsets of SNPs based on the LD threshold always outperform randomly selected SNPs for prediction objectives. However, determining the specific LD threshold for prediction purposes might be controversial since achieving the highest level of prediction accuracy, when the number of SNPs is adjusted, prompts different results (in our case, 0.3 when the SNP number was adjusted and 0.9 when the SNP number is not adjusted). Finally, we concluded that choosing the LD threshold as a tool to boost genetic prediction accuracy should be used with intense care.
Published: 2020

25. Genome-Wide Association Study on Blood Pressure Traits in the Iranian Population Suggests ZBED9 as A New Locus for Hypertension

Author: Goodarz Kolifarhood, Siamak Sabour, Mahdi Akbarzadeh, Bahareh Sedaghati-khayat, Kamran Guity, Saeid Rasekhi Dehkordi, Mahmoud Amiri Roudbar, Farzad Hadaegh, Fereidoun Azizi, and Maryam Daneshpour
Abstract: High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure(SBP), Diastolic Blood Pressure(DBP), and Hypertension(HTN) in 7,694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study(TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for two different sets of environmental predictors(P value=2.21×10-7). Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.
Published: 2020

26. Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors

Author: Soheila Khodakarim, Maryam S. Daneshpour, Parisa Naseri, and Kamran Guity
Subjects: Adult, Male, 0301 basic medicine, Genetic Linkage, Quantitative Trait Loci, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Single-nucleotide polymorphism, Iran, Biology, Quantitative trait locus, Logistic regression, Polymorphism, Single Nucleotide, Young Adult, 03 medical and health sciences, Genetic linkage, Genetics, medicine, Humans, Risk factor, Metabolic Syndrome, Linkage (software), Cholesterol, HDL, Family aggregation, General Medicine, Middle Aged, medicine.disease, Cholesterol Ester Transfer Proteins, Cross-Sectional Studies, Logistic Models, 030104 developmental biology, Female, Metabolic syndrome
Abstract: Background Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). Materials and methods The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. Results The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. Conclusions In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates.
Published: 2018

27. Associations of autozygosity with a broad range of human phenotypes

Author: Dennis O. Mook-Kanamori, Salma M. Wakil, Lisa R. Yanek, Dominique P.V. de Kleijn, Gert J. de Borst, Alison D. Murray, Kamran Guity, Vincent W. V. Jaddoe, Mario Pirastu, Carole Ober, Giuseppe Matullo, Charles N. Rotimi, Daniela Ruggiero, Teresa Tusié-Luna, Wolfgang Lieb, Chew-Kiat Heng, John R. B. Perry, Hortensia Moreno-Macías, Jie Zhou, John M. Starr, Juhani Junttila, Lei Yu, Danielle Posthuma, Marcus Dörr, Yingchang Lu, Jonathan P. Bradfield, Einat Granot-Hershkovitz, Karina Meidtner, Wouter van Rheenen, T Esko, Maris Alver, Wen-Jane Lee, Zhengming Chen, Jennifer A. Brody, Paolo Gasparini, Yii-Der Ida Chen, Cinzia Sala, Peter P. Pramstaller, Gauri Prasad, Nana Matoba, Natalie Terzikhan, Simonetta Guarrera, Bjarke Feenstra, Peter Vollenweider, Smeeta Shrestha, Yi-Jen Hung, Lilja Stefansdottir, David R. Weir, Felix R. Day, Antonietta Robino, Liang Zhang, Lluis Quintana-Murci, Nicholas J. Timpson, Robyn E Wootton, Xue W. Mei, Dharambir K. Sanghera, Gisli Masson, Debbie A Lawlor, Thomas Meitinger, Sharon L.R. Kardia, Peter K. Joshi, Frank J. A. van Rooij, Claude Bouchard, Cassandra N. Spracklen, Ken K. Ong, Taulant Muka, Guanjie Chen, Laura J. Scott, Walter Palmas, Daniel I. Chasman, Sarah E. Medland, Krista Fischer, Blair H. Smith, Jon K. Sigurdsson, Leon Straker, Clara Viberti, Yuan Shi, Louis Pérusse, Peter J. van der Most, Timo Tõnis Sikka, Chris Haley, Kuang Lin, Leif Groop, Hester M. den Ruijter, Hakon Hakonarson, Masato Akiyama, Stephan J. L. Bakker, Sonja I. Berndt, Jeffery R. O'Connell, Cisca Wijmenga, Daniele Cusi, Lorena Orozco, Kristjan H. S. Moore, Kevin Sandow, Stephen S. Rich, Stephanie J. Loomis, George Davey Smith, Cornelia M. van Duijn, Sharvari Rahul Shukla, Agnar Helgason, Thorsten Kessler, Anuj Goel, Dan Mason, David W. Clark, James S. Pankow, Simona Vaccargiu, Uwe Völker, Tamara B. Harris, Matthew A. Allison, Clicerio Gonzalez, Sarju Ralhan, I-Te Lee, Matthias Laudes, Yen-Feng Chiu, Neil Poulter, Benjamin Lehne, John Wright, Lawrence F. Bielak, Philip L. De Jager, Reinhold Schmidt, Ya Xing Wang, Matthias Nauck, Diana L. Cousminer, Patrick Deelen, Ani Manichaikul, Stephen J. Chanock, Anders Hamsten, Barry I. Freedman, Gudmar Thorleifsson, Peter Kraft, Ozren Polasek, Jie Yao, Yoshinori Murakami, Paul M. Ridker, Anubha Mahajan, Struan F.A. Grant, Claudia Schurmann, Bjarni Gunnarsson, Catriona L. K. Barnes, Jessica van Setten, Sandosh Padmanabhan, Alena Stančáková, Markus M. Lerch, Anuradha Jagadeesan, Franco Giulianini, Daniel F. Gudbjartsson, Dwaipayan Bharadwaj, Shengchao Alfred Li, Peter S. Sever, Trevor A. Mori, Albertine J. Oldehinkel, Koichi Matsuda, Xueling Sim, Evangelos Evangelou, André G. Uitterlinden, Pekka Jousilahti, Yukihide Momozawa, Ioanna Tzoulaki, Chao A. Hsiung, Ginevra Biino, Murielle Bochud, Hannele Mattsson, Ilja M. Nolte, Sarah H. Wild, Patricia B. Munroe, Jianjun Liu, Bruce M. Psaty, Giriraj R. Chandak, Masahiro Kanai, Tony R. Merriman, Teemu Palviainen, Rodney A. Lea, Janie Corley, Nicholas J. Wareham, Alan B. Zonderman, Makoto Hirata, Matthew J. Bixley, Caroline Hayward, Nora Franceschini, Kristel R van Eijk, Etienne Patin, Daniel Shriner, Niek Verweij, Xiuqing Guo, Fredrik Karpe, Ruth J. F. Loos, Tiinamaija Tuomi, Ashley van der Spek, Patricia A. Peyser, Jessica D. Faul, Christian Fuchsberger, David Cesarini, Alex S. F. Doney, Janine F. Felix, Cornelius A. Rietveld, Jagadish Vangipurapu, Tanguy Corre, Line Skotte, Rajkumar Dorajoo, Catherine Igartua, Meena Kumari, Nona Sotoodehnia, Leonard H. van den Berg, Najaf Amin, Dale R. Nyholt, Harry Campbell, Massimiliano Cocca, Scott D. Gordon, Patrik K. E. Magnusson, John C. Chambers, Traci M. Bartz, Mike A. Nalls, Tin Aung, Nduna Dzimiri, Colin N. A. Palmer, Rob M. van Dam, Johanna Kuusisto, Russell P. Tracy, Anna Damulina, Pierre-Emmanuel Morange, Sylvain Foisy, Jing Hua Zhao, Nicholas G. Martin, Ching-Yu Cheng, Mariaelisa Graff, Rashmi B. Prasad, Alice Stanton, David-Alexandre Trégouët, Yu Guo, Helen R. Warren, Lyn R. Griffiths, Weihua Meng, Annika Tillander, Christa Meisinger, Albert V. Smith, Mark I. McCarthy, Jingyun Yang, Marine Germain, Neil Small, Linda Broer, Vilmundur Gudnason, Gunnar K. Pálsson, Michele K. Evans, Alexander Teumer, Mark J. Caulfield, Giorgia Girotto, Thomas Lumley, Tinca J. C. Polderman, Wei Zhao, Carlos A. Aguilar-Salinas, Jari Lahti, Matthew L. Albert, Yechiel Friedlander, Veikko Salomaa, Iona Y Millwood, Jan H. Veldink, Archie Campbell, Andres Metspalu, Ulf Gyllensten, Grant W. Montgomery, Veronique Vitart, Jai Rup Singh, Saima Afaq, Alan R. Shuldiner, Miao-Li Chee, Adebowale Adeyemo, Jennifer A. Smith, David A. van Heel, Jaspal S. Kooner, Daniela Toniolo, Cristian Pattaro, Jerome I. Rotter, John Whitfield, Melissa C. Smart, Kari E. North, Salman M. Tajuddin, Tallapragada Divya Sri Priyanka, Christopher A. Haiman, Diane M. Becker, Bernhard K. Krämer, Paul Elliott, Lihua Wang, He Gao, Patrick Sulem, Jinyan Huang, Chiea Chuen Khor, Ruifang Li-Gao, Åsa Johansson, Winfried März, Shai Carmi, Ilaria Gandin, Eric Boerwinkle, Gardar Sveinbjornsson, Saskia P. Hagenaars, Sander W. van der Laan, Gerard Pasterkamp, E-Shyong Tai, Hagit Hochner, Yih Chung Tham, Kent D. Taylor, Kari Stefansson, Matt J. Neville, Craig E. Pennell, Yanchun Bao, Annelot M. Dekker, Helena Schmidt, Mehdi Hedayati, Joshua Elliott, Ian J. Deary, Iris E. Jansen, Judith B. Borja, Edith Hofer, Martin Gögele, Igor Rudan, Lude Franke, Matthias Munz, Folkert W. Asselbergs, Bengt Sennblad, Imo Hofer, John D. Rioux, Pim van der Harst, Bahareh Sedaghati-khayat, Giovanni Cugliari, Morris A. Swertz, Francine Grodstein, Erwin P. Bottinger, Carol A. Wang, Andre Franke, Brian F. Meyer, Adele M. Taylor, Klodian Dhana, Jian'an Luan, Constance Turman, Robert A. Scott, May E. Montasser, Alison Pattie, Marco Brumat, Liming Li, Heiner Boeing, Karen L. Mohlke, Clemens Baumbach, Bishwa Raj Sapkota, Unnur Thorsteinsdottir, Naveed Sattar, Amy R. Bentley, Matthias B. Schulze, Ivana Kolcic, Stella Trompet, Sarah E. Harris, Ayo P. Doumatey, Charumathi Sabanayagam, David Eccles, Mary F. Feitosa, Jost B. Jonas, Massimo Mezzavilla, Mark O. Goodarzi, David Ellinghaus, Heribert Schunkert, Christian Gieger, Heikki V. Huikuri, Lingyao Zeng, Johan G. Eriksson, Woon-Puay Koh, Yucheng Jia, Gurpreet Singh Wander, James F. Wilson, Torgny Karlsson, Steven C. Hunt, Weihua Zhang, Maria Pina Concas, Zoltán Kutalik, Rebecca Rohde, Chittaranjan S. Yajnik, Yasaman Saba, Dabeeru C. Rao, Robin G. Walters, Reedik Mägi, Marie Loh, Eero Vuoksimaa, Josyf C. Mychaleckyj, Katri Räikkönen, Philippe Goyette, M. Arfan Ikram, Alicia Huerta-Chagoya, David J. Porteous, Teresa Nutile, J. Wouter Jukema, Noha A. Yousri, Yoichiro Kamatani, Maryam S. Daneshpour, Babette S. Zemel, Rona J. Strawbridge, Tien Yin Wong, Claudia Langenberg, Amy Moore, Marcus E. Kleber, Fereidoun Azizi, Avner Halevy, Erika Salvi, Francis S. Collins, Markku Laakso, Tim Kacprowski, S. Sunna Ebenesersdóttir, William R. Scott, Michael Boehnke, Jin-Fang Chai, Markus Perola, Nicola Pirastu, Wayne Huey-Herng Sheu, Robert Karlsson, Lenore J. Launer, Lili Milani, Renée de Mutsert, Fernando Rivadeneira, David A. Bennett, Nicola D. Kerrison, Paolo Manunta, Graciela E. Delgado, Magnus Johannesson, Carolina Medina-Gomez, Alanna C. Morrison, Kay-Tee Khaw, Jian-Min Yuan, Jaakko Kaprio, Melanie Waldenberger, Ralf Ewert, Hugoline G. de Haan, Andrew A. Hicks, Yukinori Okada, Maria Sabater-Lleal, Marilyn C. Cornelis, Stephanie J. London, Federica Rizzi, Jeanette Erdmann, Marina Ciullo, Michiaki Kubo, University of Edinburgh, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Osaka University Graduate School of Medicine, Laboratory for Cardiovascular Genomics and Informatics [Yokohama] (RIKEN IMS), RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN)-RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), deCODE genetics [Reykjavik], Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK (BIHR), Area Science Park, Università degli studi di Trieste = University of Trieste, MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, Harbor UCLA Medical Center [Torrance, Ca.], Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, Department of Electrical and Computer Engineering [Waterloo] (ECE), University of Waterloo [Waterloo], Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], Institute of Pop. Genetics, CNR, Sassari, Shardna life science Pula Cagliari, Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne = University of Lausanne (UNIL), Medstar Research Institute, Florida State University [Tallahassee] (FSU), University Medical Center [Utrecht], Centre for Population Health Sciences, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), California State University [Sacramento], Department of Thrombosis and Haemostasis, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Medical University Graz, Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Heidelberg, Frederick National Laboratory for Cancer Research (FNLCR), Wellcome Trust Centre of Human Genetics, University of Oxford, Department of Epidemiology, German Institute of Human Nutrition, University Medical Center Groningen [Groningen] (UMCG), Institute of Genetics and Biophysics, National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Department of Medicine, Surgery, and Dentistry, University of Milano, Icelandic Heart Association, Kopavogur, Iceland., Department of Epidemiology [Rotterdam], Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Glasgow, Department of Cardiology, Leiden University Medical Center, Leiden, Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, Queen Mary University of London (QMUL), General Internal Medicine, Johns Hopkins School of Medicine, Johns Hopkins University School of Medicine [Baltimore], Institut de biologie moléculaire des plantes (IBMP), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Immunobiologie des Cellules dendritiques, Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Institut Pasteur [Paris] (IP), Genentech, Inc., Genentech, Inc. [San Francisco], University of Tartu, Duke-NUS Medical School [Singapore], Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke (DifE), Leibniz Association, Human Genome Sequencing Center, Baylor College of Medicine, Baylor College of Medicine (BCM), Baylor University-Baylor University, University of San Carlos, Office of Population Studies Foundation, Icahn School of Medicine at Mount Sinai [New York] (MSSM), King‘s College London, Division of Cancer Epidemiology and Genetics, National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH)-National Institutes of Health [Bethesda] (NIH), University of Oxford, Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Department of Internal Medicine B, University Medicine Greifswald, Greifswald, University of Chicago, University of Huddersfield, Infectious diseases division, Department of internal medicine, Washington University in Saint Louis (WUSTL), Section on Nephrology [Winston-Salem, NC, USA] (Department of Internal Medicine), Wake Forest School of Medicine [Winston-Salem], Wake Forest Baptist Medical Center-Wake Forest Baptist Medical Center, Radcliffe Department of Medicine [Oxford], Harvard School of Public Health, Kunming University of Science and Technology (KMUST), Sans affiliation, University of Southern California (USC), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), MRC Centrer for Nutritional Epidemiology and Cancer Prevention and Survival, University of Cambridge [UK] (CAM), National University of Singapore (NUS), Experimental Cardiology Laboratory (ECL), Unirversity Medical Center, Department of Medical Statistics, Epidemiology and Medical Informatics, University of Zagreb, Department of Medical Genetics, Department of Medicine, University of Eastern Finland-Kuopio University Hospital, MRC Epidemiology Unit, University of Cambridge [UK] (CAM)-Institute of Metabolic Science, Capital Normal University [Beijing], Saw Swee Hock School of Public Health, National Institute for Environmental Health Sciences Research Triangle Park, Brown University, MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, Toyota Research Institute, Helmholtz Zentrum München = German Research Center for Environmental Health, Department of Chemistry and Biochemistry [Boulder], University of Colorado [Boulder], Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Hôpital de la Timone [CHU - APHM] (TIMONE), Metacohorts Consortium, Universiteit Leiden, Institute of Clinical Chemistry and Laboratory Medicine, University of Groningen [Groningen], Medical Research Concil Epidemiology Unit, Institute of Medical Science, Faculty of Medicine, Genetics and Pathology, Imperial College London, Génétique Evolutive Humaine - Human Evolutionary Genetics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Brigham and Women's Hospital [Boston], Erasmus University Rotterdam, Department of Chronic Disease Prevention, National Institute for Health and Welfare [Helsinki], Department of Biostatistics and Center for Statistical Genetics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU), Stockholm Bioinformatics Center (SBC), Stockholm University, Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, INRH, Department of Genetics, Los Angeles Biomedical Research Institute (LA BioMed), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán - National Institute of Medical Science and Nutrition Salvador Zubiran [Mexico], Western General Hospital, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Medical Research Council, Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute-University of Pittsburgh Graduate School of Public Health, Zhengzhou University of Light Industry, Department of Electrical and Electronic Engineering [Niigata Univ.], Niigata University, Genetic Epidemiology Unit, University College of London [London] (UCL), Aston Business School, Aston University [Birmingham], Division of Cancer Epidemiology and Genetics [Bethesda, MD, États-Unis], Centre Hospitalier Universitaire Vaudois (CHUV), Pennington Biomedical Research Center, University of Washington [Seattle], Guy's and St Thomas' Hospitals, Northwestern Polytechnical University [Xi'an] (NPU), Department of Social Medicine, University of Bristol [Bristol], Department of Genomics of Common Disease [London, UK], Imperial College London-Hammersmith Hospital NHS Imperial College Healthcare, Department of Internal Medicine, Institute of Clinical Molecular Biology, Kiel University, Medizinische Klinik II, Universität zu Lübeck = University of Lübeck [Lübeck], Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina, Institute for Social Research, University of Michigan System-University of Michigan System, Division of Statistical Genomics, Washington University School of Medicine, Institute for Clinical Molecular Biology, Christian-Albrechts-Universität zu Kiel (CAU), Department of Physics, RISSC-Lab-University of Naples Federico II = Università degli studi di Napoli Federico II, Lund University [Lund], Icelandic Heart Association, Heart Preventive Clinic and Research Institute, The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Génétique moléculaire de la neurotransmission et des processus neurodégénératifs (LGMNPN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Medical Research Center Oulu, University of Oulu, University of Utah School of Medicine [Salt Lake City], The Generation R Study, Pediatrics, Epidemiology, Center for Translational and Computational Neuroimmunology [New York, NY, États-Unis] (CTCN), Department of Neurology [New York, NY, États-Unis], Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York]-Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York], Universität Heidelberg [Heidelberg] = Heidelberg University, Interuniversity Cardiology Institute Netherlands, School of Public Health, University of Michigan [Dearborn], Department of Epidemiology and Public Health, University of Kuopio, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Institute of Epidemiology and Biobank PopGen, Department of Biostatistics, University of Washington, Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Clinical Institute of Medical and Chemical Laboratory Diagnostics, Karl-Franzens-Universität Graz, Department of Genetics, Biology and Biochemistry, Università degli studi di Torino = University of Turin (UNITO), Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), QIMR Berghofer Medical Research Institute, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC)-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, University of Illinois [Chicago] (UIC), University of Illinois System, Experimental Cardiology Laboratory, Genetic Epidemiology and Clinical Research Group, Umea University Hospital, Functional Genomics, Erasmus Medical Centre, National Human Genome Research Institute (NHGRI), School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), Department of Pathological Biochemistry, Royal Infirmary, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Institute of Metabolic Science, MRC, University of Maryland School of Medicine [Baltimore, MD, USA], Centre for Molecular Epidemiology, Centre for Causal Analyses in Translational Epidemiology, University of Bristol [Bristol]-Medical Research Council, IRCCS San Raffaele Scientific Institute [Milan, Italie], U937, Génomique cardiovasculaire, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), University of Michigan System, HMNC Brain Health, Singapore Eye Research Institute, Partenaires INRAE, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Department of Psychiatry and Psychotherapy, Rheinische Friedrich-Wilhelms-Universität Bonn, University of Groningen, Department of Genomics of Common Disease, Department of Microbiology, The Freeman Hospital, Department Biostatistics University of North Carolina, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Clark, D. W., Okada, Y., Moore, K. H. S., Mason, D., Pirastu, N., Gandin, I., Mattsson, H., Barnes, C. L. K., Lin, K., Zhao, J. H., Deelen, P., Rohde, R., Schurmann, C., Guo, X., Giulianini, F., Zhang, W., Medina-Gomez, C., Karlsson, R., Bao, Y., Bartz, T. M., Baumbach, C., Biino, G., Bixley, M. J., Brumat, M., Chai, J. -F., Corre, T., Cousminer, D. L., Dekker, A. M., Eccles, D. A., van Eijk, K. R., Fuchsberger, C., Gao, H., Germain, M., Gordon, S. D., de Haan, H. G., Harris, S. E., Hofer, E., Huerta-Chagoya, A., Igartua, C., Jansen, I. E., Jia, Y., Kacprowski, T., Karlsson, T., Kleber, M. E., Li, S. A., Li-Gao, R., Mahajan, A., Matsuda, K., Meidtner, K., Meng, W., Montasser, M. E., van der Most, P. J., Munz, M., Nutile, T., Palviainen, T., Prasad, G., Prasad, R. B., Priyanka, T. D. S., Rizzi, F., Salvi, E., Sapkota, B. R., Shriner, D., Skotte, L., Smart, M. C., Smith, A. V., van der Spek, A., Spracklen, C. N., Strawbridge, R. J., Tajuddin, S. M., Trompet, S., Turman, C., Verweij, N., Viberti, C., Wang, L., Warren, H. R., Wootton, R. E., Yanek, L. R., Yao, J., Yousri, N. A., Zhao, W., Adeyemo, A. A., Afaq, S., Aguilar-Salinas, C. A., Akiyama, M., Albert, M. L., Allison, M. A., Alver, M., Aung, T., Azizi, F., Bentley, A. R., Boeing, H., Boerwinkle, E., Borja, J. B., de Borst, G. J., Bottinger, E. P., Broer, L., Campbell, H., Chanock, S., Chee, M. -L., Chen, G., Chen, Y. -D. I., Chen, Z., Chiu, Y. -F., Cocca, M., Collins, F. S., Concas, M. P., Corley, J., Cugliari, G., van Dam, R. M., Damulina, A., Daneshpour, M. S., Day, F. R., Delgado, G. E., Dhana, K., Doney, A. S. F., Dorr, M., Doumatey, A. P., Dzimiri, N., Ebenesersdottir, S. S., Elliott, J., Elliott, P., Ewert, R., Felix, J. F., Fischer, K., Freedman, B. I., Girotto, G., Goel, A., Gogele, M., Goodarzi, M. O., Graff, M., Granot-Hershkovitz, E., Grodstein, F., Guarrera, S., Gudbjartsson, D. F., Guity, K., Gunnarsson, B., Guo, Y., Hagenaars, S. P., Haiman, C. A., Halevy, A., Harris, T. B., Hedayati, M., van Heel, D. A., Hirata, M., Hofer, I., Hsiung, C. A., Huang, J., Hung, Y. -J., Ikram, M. A., Jagadeesan, A., Jousilahti, P., Kamatani, Y., Kanai, M., Kerrison, N. D., Kessler, T., Khaw, K. -T., Khor, C. C., de Kleijn, D. P. V., Koh, W. -P., Kolcic, I., Kraft, P., Kramer, B. K., Kutalik, Z., Kuusisto, J., Langenberg, C., Launer, L. J., Lawlor, D. A., Lee, I. -T., Lee, W. -J., Lerch, M. M., Li, L., Liu, J., Loh, M., London, S. J., Loomis, S., Lu, Y., Luan, J., Magi, R., Manichaikul, A. W., Manunta, P., Masson, G., Matoba, N., Mei, X. W., Meisinger, C., Meitinger, T., Mezzavilla, M., Milani, L., Millwood, I. Y., Momozawa, Y., Moore, A., Morange, P. -E., Moreno-Macias, H., Mori, T. A., Morrison, A. C., Muka, T., Murakami, Y., Murray, A. D., de Mutsert, R., Mychaleckyj, J. C., Nalls, M. A., Nauck, M., Neville, M. J., Nolte, I. M., Ong, K. K., Orozco, L., Padmanabhan, S., Palsson, G., Pankow, J. S., Pattaro, C., Pattie, A., Polasek, O., Poulter, N., Pramstaller, P. P., Quintana-Murci, L., Raikkonen, K., Ralhan, S., Rao, D. C., van Rheenen, W., Rich, S. S., Ridker, P. M., Rietveld, C. A., Robino, A., van Rooij, F. J. A., Ruggiero, D., Saba, Y., Sabanayagam, C., Sabater-Lleal, M., Sala, C. F., Salomaa, V., Sandow, K., Schmidt, H., Scott, L. J., Scott, W. R., Sedaghati-Khayat, B., Sennblad, B., van Setten, J., Sever, P. J., Sheu, W. H. -H., Shi, Y., Shrestha, S., Shukla, S. R., Sigurdsson, J. K., Sikka, T. T., Singh, J. R., Smith, B. H., Stancakova, A., Stanton, A., Starr, J. M., Stefansdottir, L., Straker, L., Sulem, P., Sveinbjornsson, G., Swertz, M. A., Taylor, A. M., Taylor, K. D., Terzikhan, N., Tham, Y. -C., Thorleifsson, G., Thorsteinsdottir, U., Tillander, A., Tracy, R. P., Tusie-Luna, T., Tzoulaki, I., Vaccargiu, S., Vangipurapu, J., Veldink, J. H., Vitart, V., Volker, U., Vuoksimaa, E., Wakil, S. M., Waldenberger, M., Wander, G. S., Wang, Y. X., Wareham, N. J., Wild, S., Yajnik, C. S., Yuan, J. -M., Zeng, L., Zhang, L., Zhou, J., Amin, N., Asselbergs, F. W., Bakker, S. J. L., Becker, D. M., Lehne, B., Bennett, D. A., van den Berg, L. H., Berndt, S. I., Bharadwaj, D., Bielak, L. F., Bochud, M., Boehnke, M., Bouchard, C., Bradfield, J. P., Brody, J. A., Campbell, A., Carmi, S., Caulfield, M. J., Cesarini, D., Chambers, J. C., Chandak, G. R., Cheng, C. -Y., Ciullo, M., Cornelis, M., Cusi, D., Smith, G. D., Deary, I. J., Dorajoo, R., van Duijn, C. M., Ellinghaus, D., Erdmann, J., Eriksson, J. G., Evangelou, E., Evans, M. K., Faul, J. D., Feenstra, B., Feitosa, M., Foisy, S., Franke, A., Friedlander, Y., Gasparini, P., Gieger, C., Gonzalez, C., Goyette, P., Grant, S. F. A., Griffiths, L. R., Groop, L., Gudnason, V., Gyllensten, U., Hakonarson, H., Hamsten, A., van der Harst, P., Heng, C. -K., Hicks, A. A., Hochner, H., Huikuri, H., Hunt, S. C., Jaddoe, V. W. V., De Jager, P. L., Johannesson, M., Johansson, A., Jonas, J. B., Jukema, J. W., Junttila, J., Kaprio, J., Kardia, S. L. R., Karpe, F., Kumari, M., Laakso, M., van der Laan, S. W., Lahti, J., Laudes, M., Lea, R. A., Lieb, W., Lumley, T., Martin, N. G., Marz, W., Matullo, G., Mccarthy, M. I., Medland, S. E., Merriman, T. R., Metspalu, A., Meyer, B. F., Mohlke, K. L., Montgomery, G. W., Mook-Kanamori, D., Munroe, P. B., North, K. E., Nyholt, D. R., O'Connell, J. R., Ober, C., Oldehinkel, A. J., Palmas, W., Palmer, C., Pasterkamp, G. G., Patin, E., Pennell, C. E., Perusse, L., Peyser, P. A., Pirastu, M., Polderman, T. J. C., Porteous, D. J., Posthuma, D., Psaty, B. M., Rioux, J. D., Rivadeneira, F., Rotimi, C., Rotter, J. I., Rudan, I., Den Ruijter, H. M., Sanghera, D. K., Sattar, N., Schmidt, R., Schulze, M. B., Schunkert, H., Scott, R. A., Shuldiner, A. R., Sim, X., Small, N., Smith, J. A., Sotoodehnia, N., Tai, E. -S., Teumer, A., Timpson, N. J., Toniolo, D., Tregouet, D. -A., Tuomi, T., Vollenweider, P., Wang, C. A., Weir, D. R., Whitfield, J. B., Wijmenga, C., Wong, T. -Y., Wright, J., Yang, J., Yu, L., Zemel, B. S., Zonderman, A. B., Perola, M., Magnusson, P. K. E., Uitterlinden, A. G., Kooner, J. S., Chasman, D. I., Loos, R. J. F., Franceschini, N., Franke, L., Haley, C. S., Hayward, C., Walters, R. G., Perry, J. R. B., Esko, T., Helgason, A., Stefansson, K., Joshi, P. K., Kubo, M., Wilson, J. F., Læknadeild (HÍ), Faculty of Medicine (UI), Félagsfræði-, mannfræði- og þjóðfræðideild (HÍ), Faculty of Sociology, Anthropology and Folkloristics (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), School of Engineering and Natural Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), Félagsvísindasvið (HÍ), School of Social Sciences (UI), Háskóli Íslands, University of Iceland, Clark, David W [0000-0002-1025-9185], Okada, Yukinori [0000-0002-0311-8472], Moore, Kristjan H S [0000-0002-9579-4362], Mason, Dan [0000-0002-0026-9216], Pirastu, Nicola [0000-0002-5363-3886], Gandin, Ilaria [0000-0003-3196-2491], Deelen, Patrick [0000-0002-5654-3966], Schurmann, Claudia [0000-0003-4158-9192], Medina-Gomez, Carolina [0000-0001-7999-5538], Karlsson, Robert [0000-0002-8949-2587], Bao, Yanchun [0000-0002-6102-5098], Biino, Ginevra [0000-0002-9936-946X], Brumat, Marco [0000-0003-3268-039X], Chai, Jin-Fang [0000-0003-3770-1137], Eccles, David A [0000-0003-4634-4995], Gordon, Scott D [0000-0001-7623-328X], Harris, Sarah E [0000-0002-4941-5106], Kacprowski, Tim [0000-0002-5393-2413], Karlsson, Torgny [0000-0001-8095-6149], Kleber, Marcus E [0000-0003-0663-7275], Mahajan, Anubha [0000-0001-5585-3420], Matsuda, Koichi [0000-0001-7292-2686], Meng, Weihua [0000-0001-5388-8494], van der Most, Peter J [0000-0001-8450-3518], Munz, Matthias [0000-0002-4728-3357], Palviainen, Teemu [0000-0002-7847-8384], Prasad, Rashmi B [0000-0002-4400-6741], Salvi, Erika [0000-0002-2724-2291], Skotte, Line [0000-0002-7398-1271], van der Spek, Ashley [0000-0001-7136-0159], Spracklen, Cassandra N [0000-0003-3590-7182], Strawbridge, Rona J [0000-0001-8506-3585], Tajuddin, Salman M [0000-0002-7919-8528], Verweij, Niek [0000-0002-4303-7685], Yanek, Lisa R [0000-0001-7117-1075], Zhao, Wei [0000-0001-7388-0692], Albert, Matthew L [0000-0001-7285-6973], Bentley, Amy R [0000-0002-0827-9101], Chanock, Stephen [0000-0002-2324-3393], Chen, Zhengming [0000-0001-6423-105X], Chiu, Yen-Feng [0000-0002-3352-4500], Cocca, Massimiliano [0000-0002-1127-7596], Collins, Francis S [0000-0002-1023-7410], Cugliari, Giovanni [0000-0002-6080-0718], Damulina, Anna [0000-0001-8241-2727], Day, Felix R [0000-0003-3789-7651], Dhana, Klodian [0000-0002-6397-7009], Dzimiri, Nduna [0000-0003-3395-5754], Elliott, Paul [0000-0002-7511-5684], Felix, Janine F [0000-0002-9801-5774], Freedman, Barry I [0000-0003-0275-5530], Girotto, Giorgia [0000-0003-4507-6589], Goel, Anuj [0000-0003-2307-4021], Goodarzi, Mark O [0000-0001-6364-5103], Gudbjartsson, Daniel F [0000-0002-5222-9857], Guity, Kamran [0000-0002-8379-9668], van Heel, David A [0000-0002-0637-2265], Hirata, Makoto [0000-0002-9994-9958], Ikram, M Arfan [0000-0003-0372-8585], Kamatani, Yoichiro [0000-0001-8748-5597], Kanai, Masahiro [0000-0001-5165-4408], Khor, Chiea Chuen [0000-0002-1128-4729], Kolcic, Ivana [0000-0001-7918-6052], Langenberg, Claudia [0000-0002-5017-7344], Lawlor, Deborah A [0000-0002-6793-2262], Liu, Jianjun [0000-0002-3255-3019], London, Stephanie J [0000-0003-4911-5290], Luan, Jian’an [0000-0003-3137-6337], Matoba, Nana [0000-0001-5329-0134], Mei, Xue W [0000-0002-6279-4884], Mezzavilla, Massimo [0000-0002-9000-4595], Milani, Lili [0000-0002-5323-3102], Mori, Trevor A [0000-0002-5264-9229], Murakami, Yoshinori [0000-0002-2826-4396], Murray, Alison D [0000-0003-4915-4847], Mychaleckyj, Josyf C [0000-0003-2595-0005], Neville, Matt J [0000-0002-6004-5433], Nolte, Ilja M [0000-0001-5047-4077], Ong, Ken K [0000-0003-4689-7530], Pálsson, Gunnar [0000-0002-8231-3961], Pankow, James S [0000-0001-7076-483X], Pattaro, Cristian [0000-0002-4119-0109], Quintana-Murci, Lluis [0000-0003-2429-6320], van Rheenen, Wouter [0000-0002-5860-1533], Rich, Stephen S [0000-0003-3872-7793], Rietveld, Cornelius A [0000-0003-4053-1861], Ruggiero, Daniela [0000-0003-3898-7827], Sabanayagam, Charumathi [0000-0002-4042-4719], Sabater-Lleal, Maria [0000-0002-0128-379X], Sala, Cinzia Felicita [0000-0003-2514-2075], Salomaa, Veikko [0000-0001-7563-5324], Scott, Laura J [0000-0002-4886-5084], Sedaghati-Khayat, Bahareh [0000-0002-7665-8648], Sennblad, Bengt [0000-0002-4360-8003], van Setten, Jessica [0000-0002-4934-7510], Smith, Blair H [0000-0002-5362-9430], Stančáková, Alena [0000-0002-1375-0252], Stanton, Alice [0000-0002-4961-165X], Straker, Leon [0000-0002-7786-4128], Sulem, Patrick [0000-0001-7123-6123], Swertz, Morris A [0000-0002-0979-3401], Taylor, Kent D [0000-0002-2756-4370], Tzoulaki, Ioanna [0000-0002-4275-9328], Veldink, Jan H [0000-0001-5572-9657], Vitart, Veronique [0000-0002-4991-3797], Völker, Uwe [0000-0002-5689-3448], Wander, Gurpreet S [0000-0002-4596-4247], Wang, Ya Xing [0000-0003-2749-7793], Wild, Sarah [0000-0001-7824-2569], Yuan, Jian-Min [0000-0002-4620-3108], Asselbergs, Folkert W [0000-0002-1692-8669], Boehnke, Mike [0000-0002-6442-7754], Bouchard, Claude [0000-0002-0048-491X], Brody, Jennifer A [0000-0001-8509-148X], Campbell, Archie [0000-0003-0198-5078], Caulfield, Mark J [0000-0001-9295-3594], Smith, George Davey [0000-0002-1407-8314], Dorajoo, Rajkumar [0000-0001-6608-2051], Ellinghaus, David [0000-0002-4332-6110], Erdmann, Jeanette [0000-0002-4486-6231], Evangelou, Evangelos [0000-0002-5488-2999], Feenstra, Bjarke [0000-0003-1478-649X], Feitosa, Mary [0000-0002-0933-2410], Franke, Andre [0000-0003-1530-5811], Grant, Struan F A [0000-0003-2025-5302], Griffiths, Lyn R [0000-0002-6774-5475], Groop, Leif [0000-0002-0187-3263], Gudnason, Vilmundur [0000-0001-5696-0084], van der Harst, Pim [0000-0002-2713-686X], Heng, Chew-Kiat [0000-0002-7309-9473], Hicks, Andrew A [0000-0001-6320-0411], Jaddoe, Vincent W V [0000-0003-2939-0041], De Jager, Philip L [0000-0002-8057-2505], Johannesson, Magnus [0000-0001-8759-6393], Johansson, Åsa [0000-0002-2915-4498], Jonas, Jost B [0000-0003-2972-5227], Jukema, J Wouter [0000-0002-3246-8359], Kaprio, Jaakko [0000-0002-3716-2455], Laakso, Markku [0000-0002-3394-7749], van der Laan, Sander W [0000-0001-6888-1404], Lahti, Jari [0000-0002-4310-5297], Martin, Nicholas G [0000-0003-4069-8020], Medland, Sarah E [0000-0003-1382-380X], Merriman, Tony R [0000-0003-0844-8726], Metspalu, Andres [0000-0002-3718-796X], Mohlke, Karen L [0000-0001-6721-153X], Montgomery, Grant W [0000-0002-4140-8139], Munroe, Patricia B [0000-0002-4176-2947], Nyholt, Dale R [0000-0001-7159-3040], Ober, Carole [0000-0003-4626-9809], Oldehinkel, Albertine J [0000-0003-3925-3913], Palmer, Colin [0000-0002-6415-6560], Perusse, Louis [0000-0001-6440-9698], Polderman, Tinca J. C. [0000-0001-5564-301X], Porteous, David J [0000-0003-1249-6106], Rioux, John D [0000-0001-7560-8326], Rivadeneira, Fernando [0000-0001-9435-9441], Rotimi, Charles [0000-0001-5759-053X], Rotter, Jerome I [0000-0001-7191-1723], Rudan, Igor [0000-0001-6993-6884], Sattar, Naveed [0000-0002-1604-2593], Sim, Xueling [0000-0002-1233-7642], Smith, Jennifer A [0000-0002-3575-5468], Teumer, Alexander [0000-0002-8309-094X], Timpson, Nicholas J [0000-0002-7141-9189], Tuomi, Tiinamaija [0000-0002-8306-6202], Wang, Carol A [0000-0002-4301-3974], Weir, David R [0000-0002-1661-2402], Whitfield, John B [0000-0002-1103-0876], Magnusson, Patrik K. E. [0000-0002-7315-7899], Uitterlinden, André G [0000-0002-7276-3387], Loos, Ruth J. F. [0000-0002-8532-5087], Franke, Lude [0000-0002-5159-8802], Haley, Chris S [0000-0002-9811-0210], Hayward, Caroline [0000-0002-9405-9550], Walters, Robin G [0000-0002-9179-0321], Joshi, Peter K [0000-0002-6361-5059], Wilson, James F [0000-0001-5751-9178], Apollo - University of Cambridge Repository, Moore, Kristjan HS [0000-0002-9579-4362], Luan, Jian'an [0000-0003-3137-6337], Grant, Struan FA [0000-0003-2025-5302], Jaddoe, Vincent WV [0000-0003-2939-0041], Polderman, Tinca JC [0000-0001-5564-301X], Magnusson, Patrik KE [0000-0002-7315-7899], Loos, Ruth JF [0000-0002-8532-5087], Neurology, Human genetics, Amsterdam Reproduction & Development (AR&D), Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Stem Cell Aging Leukemia and Lymphoma (SALL), Institute for Molecular Medicine Finland, Department of Psychology and Logopedics, University Management, Developmental Psychology Research Group, Staff Services, Cognitive and Brain Aging, Research Programs Unit, Diabetes and Obesity Research Program, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Clinicum, University of Helsinki, Centre of Excellence in Complex Disease Genetics, Department of Public Health, Genetic Epidemiology, Helsinki Collegium for Advanced Studies, HUS Abdominal Center, Endokrinologian yksikkö, Bradford Teaching Hospitals NHS Foundation Trust [Bradford, UK] (BTHFT), University of Trieste, Université de Lausanne (UNIL), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Consiglio Nazionale delle Ricerche (CNR), Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur [Paris], Institut Pasteur [Paris], University of Oxford [Oxford], Medical Genetics, Dept. RSD and Public Health, IRCCS-Burlo Garofolo/University of Trieste, sans affiliation, Helmholtz-Zentrum München (HZM), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institute of Cardiovascular Science, University College London, Hammersmith Hospital NHS Imperial College Healthcare-Imperial College London, Universität zu Lübeck [Lübeck], University of Ioannina Medical School, Università degli studi di Napoli Federico II-RISSC-Lab, Universität Heidelberg [Heidelberg], University of Turin, University of California-University of California, Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), University of Helsinki-University of Helsinki, Université de Nantes (UN)-Université de Rennes 1 (UR1), Erasmus MC other, Internal Medicine, and Applied Economics
Subjects: 0301 basic medicine, 631/208/1397, Chemistry(all), Health Status, [SDV]Life Sciences [q-bio], LOCI, General Physics and Astronomy, MESH: Haplotype, MESH: Cognition, 030105 genetics & heredity, Runs of Homozygosity, Biochemistry, Consanguinity, Cognition, Inbreeding depression, 2.1 Biological and endogenous factors, Body Size, Inbreeding, Skyldleikarækt, Aetiology, Human phenotypes, lcsh:Science, MESH: Health Status, Genetics, Multidisciplinary, Inbreeding Depression, Confounding, Homozygote, RUNS, 631/208/205, 631/208/721, 3. Good health, genomic inbreeding coefficients, MESH: Risk-Taking, 631/208/730, Autozygosit, homozygosity, Erfðarannsóknir, Medical Genetics, genomic inbreeding coefficient, MESH: Homozygote, Offspring, Science, Autozygosity, Blóðsifjar, 610 Medicine & health, Biology, INBREEDING DEPRESSION, HOMOZYGOSITY, FERTILITY, QUANTIFICATION, Physics and Astronomy(all), General Biochemistry, Genetics and Molecular Biology, Article, Association, 03 medical and health sciences, Risk-Taking, 360 Social problems & social services, Journal Article, Humans, ddc:610, Allele, Alleles, Medicinsk genetik, Genetic association study, MESH: Consanguinity, MESH: Body Size, MESH: Humans, Biochemistry, Genetics and Molecular Biology(all), MESH: Alleles, Haplotype, MESH: Fertility, General Chemistry, Brain Disorders, MESH: Inbreeding Depression, 030104 developmental biology, Fertility, Haplotypes, Genetic markers, lcsh:Q, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 3111 Biomedicine, Genetics and Molecular Biology(all)
Abstract: Publisher's version (útgefin grein)., In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding., This paper is the work of the ROHgen consortium. We thank the Sigma T2D Consortium, whose members are detailed in Supplementary Note 3. We thank the UK Biobank Resource, approved under application 19655; we acknowledge funding from the UK Medical Research Council Human Genetics Unit and MRC Doctoral Training Programme in Precision Medicine. We also thank Neil Robertson, Wellcome Trust Centre for Human Genetics, Oxford, for use of his author details management software, Authorial. Finally, we thank all the participants, researchers and funders of ROHgen cohorts. Cohort-specific acknowledgements are in Supplementary Data 2; personal acknowledgements and disclosures are in Supplementary Note 2. We thank Rachel Edwards for administrative assistance.
Published: 2019

28. Spousal metabolic risk factors and incident hypertension: A longitudinal cohort study in Iran

Author: Kamran Guity, Azra Ramezankhani, Farzad Hadaegh, and Fereidoun Azizi
Subjects: Male, Waist, Endocrinology, Diabetes and Metabolism, 030204 cardiovascular system & hematology, Iran, Environment, Body Mass Index, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal Medicine, Medicine, Humans, 030212 general & internal medicine, Longitudinal Studies, Spouses, Aged, business.industry, Hazard ratio, Absolute risk reduction, medicine.disease, Confidence interval, Physical activity level, Diabetes Mellitus, Type 2, Spouse, Hypertension, Female, Waist Circumference, Cardiology and Cardiovascular Medicine, business, Body mass index, Dyslipidemia, Demography
Abstract: We investigated the association between metabolic risk factors in one spouse with incident hypertension in the other. Study sample included 1528 men and 1649 women aged ≥20 years from the Tehran lipid and glucose study with information on body mass index (BMI), waist circumference (WC), hypertension, type 2 diabetes mellitus (DM), and dyslipidemia. The hazard ratio (HR) and 95% confidence interval (95% CI) were estimated for the association of spousal metabolic factors and incident hypertension among men and women separately. A total of 604 and 566 cases of incident hypertension were observed in men and women, respectively. Among men, spousal DM was associated with a 40% (CI: 1.07-1.83) excess risk of hypertension after adjusting for the men's own and their spouse's risk factors including BMI, DM, smoking, and physical activity level. Among women, spousal DM was associated with more than two times (2.11, 1.69-2.63) higher risk of hypertension. After further adjustment for the women's own and their spouse's risk factors, the association was attenuated and remained marginally significant (1.25, 0.99-1.58; P value = .053). Having a spouse with DM increases an individual's risk of hypertension, which raises the possibility of using preexisting information of one partner to guide the screening of the other partner.
Published: 2019

29. Spousal metabolic risk factors and future cardiovascular events: A prospective cohort study

Author: Kamran Guity, Azra Ramezankhani, Fereidoun Azizi, and Farzad Hadaegh
Subjects: 0301 basic medicine, Adult, Male, Waist, Blood Pressure, 030204 cardiovascular system & hematology, Overweight, Iran, Body Mass Index, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Medicine, Humans, Obesity, Prospective Studies, Prospective cohort study, Spouses, Proportional hazards model, business.industry, Incidence, Hazard ratio, Cholesterol, HDL, Middle Aged, medicine.disease, 030104 developmental biology, Spouse, Cardiovascular Diseases, Female, medicine.symptom, Waist Circumference, Cardiology and Cardiovascular Medicine, business, Body mass index, Demography
Abstract: Background and aims We investigated whether the presence of metabolic risk factors in one spouse is associated with increased risk of cardiovascular disease (CVD) in the other spouse. Methods A total of 4390 married participants (2152 men and 2238 women free of CVD at baseline) aged ≥20 years were included in this study. The association between spousal risk factors and incident CVD was estimated separately for men and women (as index individuals) using Cox regression models, with spousal risk factors as exposures and CVD event in the index individuals as the outcome. Exposures included spousal body mass index (BMI), waist circumference, systolic and diastolic blood pressure, total cholesterol, high density lipoprotein cholesterol, fasting plasma glucose (all in both continuous and categorical forms) and smoking. Models were adjusted for the three nested sets of covariates. Results During a median follow-up of 16.1 years, 588 (419 men) cases of CVD were recorded. Among men, those whose wives were overweight and obese had significantly increased risk of CVD, compared with men whose spouses had normal weight, after adjusting for men risk factors. Hazard ratios (HR) with 95% confidence intervals (95% CI) were 1.41 (1.07–1.87) and 1.38 (1.03–1.85), respectively. Among women, no significant associations were observed between spousal metabolic risk factors and incidence of CVD, after controlling for their own risk factors. Conclusion Findings from this study show that overweight and obesity in women increase their spouses' risk for CVD beyond the effect of the spouses’ own risk factors.
Published: 2019

30. Incidence and predictors of early adulthood pre-diabetes/type 2 diabetes, among Iranian adolescents: the Tehran Lipid and Glucose Study

Author: Fereidoun Azizi, Paniz Charkhchi, Mohammadhassan Mirbolouk, Kamran Guity, Farzad Hadaegh, and Arash Derakhshan
Subjects: Univariate analysis, medicine.medical_specialty, Pediatrics, endocrine system diseases, business.industry, Endocrinology, Diabetes and Metabolism, Incidence (epidemiology), Hazard ratio, nutritional and metabolic diseases, Type 2 Diabetes Mellitus, 030209 endocrinology & metabolism, Type 2 diabetes, medicine.disease, 03 medical and health sciences, 0302 clinical medicine, Diabetes mellitus, Internal medicine, Pediatrics, Perinatology and Child Health, Internal Medicine, medicine, 030212 general & internal medicine, Young adult, business, Body mass index
Abstract: Purpose To evaluate the incidence and predictors of early adulthood pre-diabetes/type 2 diabetes (T2D) among Iranian adolescents during a median follow-up of 9.2 yr. Method A total of 2563 subjects aged 10–19 yr, without pre-diabetes/T2D at baseline, were entered in the study. Pre-diabetes was defined as those with fasting plasma glucose (FPG) 5.6 to
Published: 2016

31. Generality of genomic findings on blood pressure traits and its usefulness in precision medicine in diverse populations: A systematic review

Author: Bahareh Sedaghati Khayat, Hossein Mozafar Saadati, Nasim Khosravi, Kamran Guity, Mahdi Akbarzadeh, Siamak Sabour, Goodarz Kolifarhood, and Maryam S. Daneshpour
Subjects: 0301 basic medicine, Linkage disequilibrium, DNA Copy Number Variations, Quantitative Trait Loci, Locus (genetics), Genome-wide association study, Single-nucleotide polymorphism, Blood Pressure, 030105 genetics & heredity, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, 03 medical and health sciences, Quantitative Trait, Heritable, Population Groups, Genetics, Humans, Genetic Predisposition to Disease, Precision Medicine, Genetics (clinical), Generality, Genetic variants, Reproducibility of Results, Genomics, Precision medicine, 030104 developmental biology, Blood pressure, Evolutionary biology, Hypertension, Publication Bias, Genome-Wide Association Study
Abstract: Remarkable findings from genome wide association studies (GWAS) on blood pressure (BP) traits have made new insights for developing precision medicine towards more effective screening measures. However, generality of GWAS findings in diverse populations is hampered by some technical limitations. There is no comprehensive study to evaluate source(s) of the non-generality of GWAS results on BP traits, so to fill the gap, this systematic review study was carried out. Using MeSH terms, 1545 records were detected through searching in 5 databases and 49 relevant full-text articles were included in our review. Overall, 749 unique variants were reported, of those, majority of variants have been detected in Europeans and were associated to systolic and diastolic blood pressure traits. Frequency of genetic variants with same position was low in European and Non-European populations (n=38). However, more than 200 (>25%) single nucleotide polymorphism were found on same loci or linkage disequilibrium blocks (r2 ≥80%). Investigating for locus position and linkage disequilibrium of infrequent unique variants showed modest to high reproducibility of findings in Europeans that in some extent was generalizable in other populations. Beyond theoretical limitations, our study addressed other possible sources of non-generality of GWAS findings for BP traits in same and different origins.
Published: 2018

32. Cardio-Metabolic Disease Genetic Risk Factors in Iran: Twenty Years of Tehran Lipid and Glucose Study

Author: Maryam S. Daneshpour, Maryam Zarkesh, Kamran Guity, Fereidoun Azizi, Niloofar Javanrooh, Mehdi Hedayati, Mahdi Akbarzadeh, Azita Zadeh-Vakili, and Bahareh Sedaghati-khayat
Subjects: 0301 basic medicine, education.field_of_study, business.industry, Endocrinology, Diabetes and Metabolism, Population, 030209 endocrinology & metabolism, Genome-wide association study, Context (language use), Quantitative trait locus, Heritability, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Genetic marker, Environmental health, Medicine, business, education, Cohort study, Genetic association
Abstract: Context Tehran Lipid and Glucose Study (TLGS), a longitudinal family based cohort study, is the oldest and largest longitudinal family based study in Iran, aimed at investigating effects of environmental, social and biological factors on the health of Tehranians over time. Considering the importance of genetic studies in this aspect, here we present a summary of the important genetic findings, and the potentiality of their contributions to future related projects. Evidence acquisition For all related studies during the past 20 years the search sources were all prominent search engines such as PubMed, Scopus, and Google Scholar with the most proper Medical Subject Headings (MeSH). Results This review summarizes associations of 6 binary phenotypes and 17 quantitative traits with genetic markers in 26 genes. Of the 47 genetic markers, studied most were related to cardio metabolic risk factors. Results of heritability and linkage analysis were also collected and the highest heritability was found to be related to HDL-C (0.5). Conclusion Considering the opportunity provided by large-scale cohort studies to investigate molecular effects of genetic variants on causality and different omics' data, genetic studies conducted on TLGS population have had a remarkable success in identifying genetic variants that facilitating a unique genetic database on Iranian populations. The results of genome wide association studies in this population are currently facilitating investigations to define the Iranian genetic differences with other population.
Published: 2018

33. Households and Family Projections in Tehran Lipid and Glucose Study: 1999 to 2016

Author: Kamran Guity, Bahareh Sedaghati-Khayat, Amirabbas Momenan, Atefeh Seyedhamzehzadeh, Narges Sarbazi, Fereidoun Azizi, and Maryam Sadat Daneshpour
Published: 2018

34. Some dietary factors can modulate the effect of the zinc transporters 8 polymorphism on the risk of metabolic syndrome

Author: Parvin Mirmiran, Gelareh Koochakpoor, Kamran Guity, Maryam S. Daneshpour, Firoozeh Hosseini-Esfahani, and Fereidoun Azizi
Subjects: Adult, Blood Glucose, Male, 0301 basic medicine, medicine.medical_specialty, Science, 030209 endocrinology & metabolism, Zinc Transporter 8, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Polymorphism (computer science), Internal medicine, Genotype, Odds Ratio, medicine, Humans, Abdominal obesity, Metabolic Syndrome, chemistry.chemical_classification, 030109 nutrition & dietetics, Multidisciplinary, Case-control study, Fatty acid, Fasting, Odds ratio, medicine.disease, Lipids, Diet, Endocrinology, chemistry, Case-Control Studies, Obesity, Abdominal, Medicine, Female, Metabolic syndrome, medicine.symptom
Abstract: There are conflicting data on the impact of zinc transporter 8 (ZNT8) gene variations on the metabolic syndrome (MetS). Hence, the effects of the interaction between rs13266634 and dietary factors on the risk of MetS were investigated in this study. Subjects of this nested case-control study were selected from the participants in Tehran Lipid and Glucose Study. Each of the cases (n = 817) was individually matched with a control. Dietary patterns were determined using factor analysis. The ZNT8 rs13266634 were genotyped by the Tetra-refractory mutation system-polymerase chain reaction analysis. Two dietary patterns were extracted. There were no significant interactions between the ZNT8 SNP and the dietary patterns on the risk of MetS or its components. An interaction was observed between rs13266634 and the omega-3 fatty acid intakes on the risk of MetS in subjects with the CC genotype (P interaction
Published: 2017
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35. Heritability of the metabolic syndrome and its components in the Tehran Lipid and Glucose Study (TLGS)

Author: Farhad Hosseinpanah, Bita Faam, Kamran Guity, Nima Hosseinzadeh, Maryam S. Daneshpour, Maryam Zarkesh, Amir Abbas Momenan, Mohammad-Sadegh Fallah, and Fereidoun Azizi
Subjects: Adult, Blood Glucose, Male, medicine.medical_specialty, Waist, Adolescent, Offspring, Blood Pressure, Iran, Young Adult, Risk Factors, Internal medicine, Genetics, medicine, Humans, Child, Nuclear family, Triglycerides, Abdominal obesity, Aged, Aged, 80 and over, Metabolic Syndrome, business.industry, Cholesterol, HDL, General Medicine, Middle Aged, Heritability, medicine.disease, Obesity, Cross-Sectional Studies, Endocrinology, Blood pressure, Child, Preschool, Female, Waist Circumference, Metabolic syndrome, medicine.symptom, business
Abstract: SummaryGrowing evidence suggests that metabolic syndrome (MetS) has both genetic and environmental bases. We estimated the heritability of the MetS and its components in the families from the Tehran Lipid and Glucose Study (TLGS). We investigated 904 nuclear families in TLGS with two biological parents and at least one offspring (1565 parents and 2448 children), aged 3–90 years, for whom MetS information was available and had at least two members of family with MetS. Variance component methods were used to estimate age and sex adjusted heritability of metabolic syndrome score (MSS) and MetS components using SOLAR software. The heritability of waist circumference (WC), HDL-cholesterol (HDL-C), triglycerides (TGs), fasting blood sugar (FBS), systolic blood pressure (SBP) and diastolic blood pressure (DBP) as continuous traits after adjusting for age and gender were 27, 46, 36, 29, 25, 26 and 15%, respectively, and MSS had a heritability of 15%. When MetS components were analysed as discrete traits, the estimates of age and gender adjusted heritability for MetS, abdominal obesity, low HDL-C, high TG, high FBS and high blood pressure (BP) were 22, 40, 34, 38 and 23%, respectively (P P
Published: 2012

36. The Relation between Metabolic Syndrome Risk Factors and Genetic Variations of Apolipoprotein V in Relation with Serum Triglyceride and HDL-C Level

Author: Mohammad-Sadegh, Fallah, Bahareh, Sedaghatikhayat, Kamran, Guity, Fereshteh, Akbari, Fereidoun, Azizi, and Maryam S, Daneshpour
Subjects: Adult, Male, Metabolic Syndrome, Cholesterol, HDL, Genetic Variation, Iran, Middle Aged, Polymorphism, Single Nucleotide, Young Adult, Apolipoprotein A-V, Risk Factors, Humans, Female, Genetic Predisposition to Disease, Alleles, Apolipoproteins A, Triglycerides, Aged
Abstract: Metabolic syndrome (MetS) is a multi-factorial disorder with five important components. A high triglyceride level combined with low HDL cholesterol has been reported to be associated with Apolipoprotein A5 (APOA5) gene variations. In this study, we aimed to determine the association of single nucleotide polymorphisms including: rs662799, rs3135506 and rs2075291 in the apolipoprotein A-V (APOA5) gene in relation to MetS component like triglyceride and HDL-C level in Tehran Lipid and Glucose Study (TLGS).Metabolic syndrome was defined according to ATPIII and phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS. Demographic, biochemical parameters and anthropometric variables were measured. Selected APOA5 gene polymorphisms were genotyped using PCR-RFLP method.From TLGS population, 947 adults, aged 19 - 70 years, were randomly selected and recruited into the study. Mean age, triglyceride and WC were higher and mean HDL was lower in MetS vs. non-MetS group. C allele in rs2075291 showed a significant association with MetS (OR: 2.38, 95% CI; 1.11 - 5.08, P = 1.5 ×10(-2)). The association was shown between higher serum triglyceride and the presence of T allele (P = 4.5 × 10(-4)) and also lower serum HDL-C and the presence of T allele (P = 1.6 × 10(-3)) in rs2075291. Also this association showed between raised waist circumference and C allele in rs3135506 (P = 3.5 × 10(-2) ) and raised systolic and diastolic blood pressure level and C allele of rs662799 (P = 4.5 × 10(-2)).According to the results, there is a relationship between lipid profile and studied polymorphism in the presence of metabolic syndrome. It seems that APOA5 rs2075291 could play an important role in triglyceride and HDL-C level in metabolic syndrome affected, while the association of APOA5 rs662799 polymorphism is still under debate.
Published: 2015

37. Incidence and predictors of early adulthood pre-diabetes/type 2 diabetes, among Iranian adolescents: the Tehran Lipid and Glucose Study

Author: Mohammadhassan, Mirbolouk, Arash, Derakhshan, Paniz, Charkhchi, Kamran, Guity, Fereidoun, Azizi, and Farzad, Hadaegh
Subjects: Adult, Blood Glucose, Male, Adolescent, Incidence, Iran, Lipids, Prediabetic State, Young Adult, Diabetes Mellitus, Type 2, Risk Factors, Humans, Female, Age of Onset, Child
Abstract: To evaluate the incidence and predictors of early adulthood pre-diabetes/type 2 diabetes (T2D) among Iranian adolescents during a median follow-up of 9.2 yr.A total of 2563 subjects aged 10-19 yr, without pre-diabetes/T2D at baseline, were entered in the study. Pre-diabetes was defined as those with fasting plasma glucose (FPG) 5.6 to7 mmol/L. T2D was defined as anti-T2D drug consumption or FPG ≥7 mmol/L. Multivariate Cox-proportional analysis was applied to examine the association between different risk factors that showed attained statistical significance0.2 in univariate analysis, with incident pre-diabetes/T2D. Same method was repeated on 1803 subjects with complete parental data to find the relation between parental risk factors and pre-diabetes/T2D.The mean age of participants was 14.45 ± 2.78 yr, and 53.6% were female. During follow-up 208 cases of pre-diabetes/T2D occurred, resulting in an incidence rate of 9.61 per 1000 person-years. Multivariate-adjusted hazard ratios (HRs) for incident pre-diabetes/T2D showed significant risk for 1 standard deviation increase in FPG and body mass index with corresponding HR of 1.89 (1.6-2.23) and 1.435 (1.080-1.905), respectively. Among parental potential risk factors, the paternal history of T2D was independently associated with increased risk for pre-diabetes/T2D in the adolescence (HR = 1.63(1.02-2.60)).About 1% of Iranian adolescents developed pre-diabetes/T2D each year. Among the non-modifiable risk factors paternal history of T2D and, among modifiable risk factors, the presence of general adiposity as well as the higher level of FPG should be considered among adolescents for development of pre-diabetes/T2D later in the young adulthood.
Published: 2015

38. Heritability of Obesity-Related Variables in Tehran Families: Tehran Lipid and Glucose Study

Author: Farhad Hosseinpanah, Kamran Guity, Bita Faam, Fereidoun Azizi, Nima Hosseinzadeh, Amir Abbas Momenan, Mohammad-Sadegh Fallah, Somayeh Hosseinpour-Niazi, Maryam Zarkesh, and Maryam S. Daneshpour
Subjects: Gerontology, Waist, Offspring, business.industry, Heritability, Overweight, Waist–hip ratio, medicine, Resting energy expenditure, medicine.symptom, business, Nuclear family, Body mass index, Demography
Abstract: Patients and Methods: This cross-sectional family-based study was conducted on 769 TLGS families in Iran. All families with two biological parents, at least one offspring (nuclear family) and at least two overweight or obese members were eligible for this study. Participants, who lacked the complete family and demographic variables were excluded. Consequently, 529 two-generation nuclear families (1066 parents and 1394 offspring) remained. Obesity-related variables, including waist circumference (WC), waist to hip ratio (WHR), body mass index (BMI), resting energy expenditure (REE), and body size (BS) were determined. Variance component method was used to estimate the age and sex adjusted heritability for obesity-related variables using SOLAR software. Results: Recruited families consisted of 2460 individuals (493 fathers, 573 mothers, 720 sons, and 674 daughters). Parents and offspring were aged 45.7 ± 10.2 and 18.4 ± 9.7 years respectively. The age and sex adjusted heritability for all obesity-related variables were significant (P < 0.0001) and varied from 0.21 (hip) to 0.51 (BS). The heritability for body size considerably surpasses the heritabilities, which were estimated in this study. Conclusions: This study indicates that Tehran families are genetically predisposed to obesity; although, inappropriate lifestyle may interfere with genetic patterns.
Published: 2014

39. Recurrence risk ratio of siblings and familial aggregation of the metabolic syndrome among Tehranian population

Author: Maryam, Zarkesh, Farhad, Hosseinpanah, Maryam, Barzin, Nima, Hosseinzadeh, Kamran, Guity, Maryam Sadat, Daneshpour, and Fereidoun, Azizi
Subjects: Adult, Male, Metabolic Syndrome, Cross-Sectional Studies, Recurrence, Siblings, Odds Ratio, Humans, Family, Female, Iran, Middle Aged, Aged
Abstract: In this study, we aimed to determine the extent of possible genetic influence on cardio-metabolic risk factors, evaluate the familial aggregation of MetS and estimate the siblings' recurrence risk ratios in a Tehrani population.In a cross-sectional observational study, we made anthropometric, blood pressure, and biochemical measurements in each member of 566 Tehrani nuclear families.Grandmothers had the highest incidence of atherosclerotic risk factors. Four factors were found which accounted for 77.7% of the overall variance. Recurrence risk ratio among siblings was 5.61 (95% conﬁdence interval [CI]: 3.15-9.97). The adjusted odds ratio (OR) of proband's MetS status was 1.33 (95% CI: 1.06-1.67). The adjusted OR for the four factors to predict MetS were all signiﬁcant, with obesity having the highest risk (OR: 7.50, CI: 5.91-9.52), followed by dyslipidemia/hyperglycemia (OR: 4.86, CI: 4.03-5.87), and blood pressure (OR: 4.20, CI: 3.51-5.02).A high risk of MetS (five-fold) was found in siblings with MetS proband. Moreover, findings confirm the importance of obesity for the aggregation of MetS by nearly seven-fold in the study population.
Published: 2014

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