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Daneshpour MS, Akbarzadeh M, Lanjanian H, Sedaghati-Khayat B, Guity K, Masjoudi S, Zahedi AS, Moazzam-Jazi M, Bonab LNH, Shalbafan B, Asgarian S, Farhood GK, Javanrooh N, Zarkesh M, Riahi P, Moghaddas MR, Dehkordi PA, Ahmadi AD, Hosseini F, Farahani SJ, Hadaegh F, Mirmiran P, Tehrani FR, Ghanbarian A, Pasand MSFM, Amiri P, Valizadeh M, Hosseipanah F, Tohidi M, Ghasemi A, Zadeh-Vakili A, Piryaei M, Alamdari S, Khalili D, Momenan A, Barzin M, Zeinali S, Hedayati M, Azizi F. Cohort profile update: Tehran cardiometabolic genetic study. Eur J Epidemiol 2023:10.1007/s10654-023-01008-1. [PMID: 37169991 PMCID: PMC10175059 DOI: 10.1007/s10654-023-01008-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 04/13/2023] [Indexed: 05/13/2023]
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.
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Affiliation(s)
- Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran.
| | - Mahdi Akbarzadeh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Hossein Lanjanian
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Bahar Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
- Faculty of Medicine, University of Iceland, School of Health Sciences, Reykjavik, Iceland
| | - Sajedeh Masjoudi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Asiyeh Sadat Zahedi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Maryam Moazzam-Jazi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Leila Najd Hassan Bonab
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Bita Shalbafan
- Clinical Research Development Center of Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sara Asgarian
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Goodarz Koli Farhood
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Niloofar Javanrooh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Maryam Zarkesh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Parisa Riahi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Mohammad Reza Moghaddas
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Parvaneh Arbab Dehkordi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Azar Delbarpour Ahmadi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Firoozeh Hosseini
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sara Jalali Farahani
- Research Center for Social Determinants of Health, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farzad Hadaegh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parvin Mirmiran
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fahimeh Ramezani Tehrani
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Arash Ghanbarian
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Parisa Amiri
- Research Center for Social Determinants of Health, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Majid Valizadeh
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farhad Hosseipanah
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Tohidi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Asghar Ghasemi
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Azita Zadeh-Vakili
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Piryaei
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Shahram Alamdari
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amirabbas Momenan
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Barzin
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sirous Zeinali
- Dr. Zeinali's Medical Genetics Lab, Kawsar Human Genetics Research Center (KHGRC), Tehran, Iran
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19195-4763, Tehran, Iran.
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Wan JY, Goodman DL, Willems EL, Freedland AR, Norden-Krichmar TM, Santorico SA, Edwards KL. Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study. Diabetol Metab Syndr 2021; 13:59. [PMID: 34074324 PMCID: PMC8170963 DOI: 10.1186/s13098-021-00670-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/28/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. METHODS Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina's Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping. RESULTS Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects. CONCLUSIONS This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.
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Affiliation(s)
- Jia Y Wan
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Deborah L Goodman
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Emileigh L Willems
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA
| | - Alexis R Freedland
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Trina M Norden-Krichmar
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Stephanie A Santorico
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA
- Human Medical Genetics and Genomics Program, University of Colorado, Denver, CO, USA
- Department of Biostatistics & Informatics, University of Colorado, Denver, CO, USA
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Karen L Edwards
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA.
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Jovanovic VM, Sarfert M, Reyna-Blanco CS, Indrischek H, Valdivia DI, Shelest E, Nowick K. Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution. Front Genet 2021; 12:662239. [PMID: 34079582 PMCID: PMC8166252 DOI: 10.3389/fgene.2021.662239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 04/19/2021] [Indexed: 01/09/2023] Open
Abstract
Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.
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Affiliation(s)
- Vladimir M Jovanovic
- Human Biology and Primate Evolution, Freie Universität Berlin, Berlin, Germany.,Bioinformatics Solution Center, Freie Universität Berlin, Berlin, Germany
| | - Melanie Sarfert
- Human Biology and Primate Evolution, Freie Universität Berlin, Berlin, Germany
| | - Carlos S Reyna-Blanco
- Department of Biology, University of Fribourg, Fribourg, Switzerland.,Swiss Institute of Bioinformatics, Fribourg, Switzerland
| | - Henrike Indrischek
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.,Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.,Center for Systems Biology Dresden, Dresden, Germany
| | - Dulce I Valdivia
- Evolutionary Genomics Laboratory and Genome Topology and Regulation Laboratory, Genetic Engineering Department, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-Irapuato), Irapuato, Mexico
| | - Ekaterina Shelest
- Centre for Enzyme Innovation, University of Portsmouth, Portsmouth, United Kingdom
| | - Katja Nowick
- Human Biology and Primate Evolution, Freie Universität Berlin, Berlin, Germany
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Teng F, Qin R, Liu X, Geng H, Xu W, Wu T, Li Y, Lai P, Liang J. Interaction between the rs9356744 polymorphism and metabolic risk factors in relation to type 2 diabetes mellitus: The Cardiometabolic Risk in Chinese (CRC) Study. J Diabetes Complications 2021; 35:107855. [PMID: 33558148 DOI: 10.1016/j.jdiacomp.2021.107855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 12/25/2020] [Accepted: 01/04/2021] [Indexed: 10/22/2022]
Abstract
The understanding of the genetic basis of type 2 diabetes mellitus (T2DM) has progressed rapidly, but the interactions among common genetic variants and metabolic risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and metabolic environments on the risk of T2DM. Obesity is emerging as an independent risk factor for T2DM and arterial stiffness. Here, we examined the effect of the rs9356744 polymorphism in the body mass index (BMI) gene CDKAL1 on the risk of T2DM in East Asians and particularly assessed the interactions between this polymorphism and other metabolic risk factors. A total of 1975 subjects in whom the rs9356744 polymorphism had been detected in the CDKAL1 gene were enrolled in this study. The height, weight, blood pressure and relevant markers, including glucose, lipids, liver and renal function, of the participants were successfully measured. Pulse wave velocity (PWV) was measured using an automatic wave form analyzer. At baseline, we found a significant association between BMI and rs9356744 genotypes (CC, CT, TT) (P = 0.048). After adjusting for confounding factors, including sex, age and BMI, participants carrying the T allele of rs9356744 showed a lower incidence of T2DM. Further adjustment for blood pressure and lipids did not appreciably change the results (P = 0.019, 0.009, 0.015, respectively). We found significant interactions between the rs9356744 polymorphism and high-density lipoprotein (HDL), serum uric acid (SUA) and carotid-femoral pulse wave velocity (cf-PWV) in relation to T2DM incidence (P for interaction = 0.007, 0.002, 0.004, respectively), especially in the group with the lowest SUA level and the group with the highest HDL and cf-PWV levels (P for trend = 0.006, 0.008, 0.018, respectively). Furthermore, we found a significant interaction between the rs9356744 polymorphism and cf-PWV in relation to the level of 2-h plasma glucose in the oral glucose tolerance test (OGTT) (P for interaction = 0.0341). In summary, the T allele of rs9356744 was an independent protective factor for T2DM. There were significant interactions between rs9356744 and HDL, SUA, and cf-PWV in relation to T2DM risk.
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Affiliation(s)
- Fei Teng
- Department of Endocrinology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, The Affiliated XuZhou Hospital of Medical College of Southeast University, Jiangsu 221009, China; Xuzhou Institute of Medical Sciences, Xuzhou Institute of Diabetes, Xuzhou, Jiangsu 221000, China
| | - Ruihao Qin
- Department of Vascular and Thyroid Surgeon, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, The Affiliated XuZhou Hospital of Medical College of Southeast University, Jiangsu 221009, China
| | - Xuekui Liu
- Department of Endocrinology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, The Affiliated XuZhou Hospital of Medical College of Southeast University, Jiangsu 221009, China
| | - Houfa Geng
- Department of Endocrinology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, The Affiliated XuZhou Hospital of Medical College of Southeast University, Jiangsu 221009, China
| | - Wei Xu
- Department of Endocrinology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, The Affiliated XuZhou Hospital of Medical College of Southeast University, Jiangsu 221009, China
| | - Tingting Wu
- Xuzhou Medical University, Xuzhou, Jiangsu 221000, China
| | - Yinxia Li
- Bengbu Medical College, Bengbu, Anhui 233030, China
| | - Peng Lai
- Xuzhou Medical University, Xuzhou, Jiangsu 221000, China
| | - Jun Liang
- Department of Endocrinology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, The Affiliated XuZhou Hospital of Medical College of Southeast University, Jiangsu 221009, China; Xuzhou Institute of Medical Sciences, Xuzhou Institute of Diabetes, Xuzhou, Jiangsu 221000, China.
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Piko P, Werissa NA, Fiatal S, Sandor J, Adany R. Impact of Genetic Factors on the Age of Onset for Type 2 Diabetes Mellitus in Addition to the Conventional Risk Factors. J Pers Med 2020; 11:jpm11010006. [PMID: 33375163 PMCID: PMC7822179 DOI: 10.3390/jpm11010006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/17/2020] [Accepted: 12/20/2020] [Indexed: 12/14/2022] Open
Abstract
It is generally accepted that the early detection of type 2 diabetes mellitus (T2DM) is important to prevent the development of complications and comorbidities, as well as premature death. The onset of type 2 diabetes mellitus results from a complex interplay between genetic, environmental, and lifestyle risk factors. Our study aims to evaluate the joint effect of T2DM associated single nucleotide polymorphisms (SNPs) on the age of onset for T2DM in combination with conventional risk factors (such as sex, body mass index (BMI), and TG/HDL-C ratio) in the Hungarian population. This study includes 881 T2DM patients (Case population) and 1415 samples from the Hungarian general population (HG). Twenty-three SNPs were tested on how they are associated with the age of onset for T2DM in the Case population and 12 of them with a certified effect on the age of T2DM onset were chosen for an optimized genetic risk score (GRS) analysis. Testing the validity of the GRS model developed was carried out on the HG population. The GRS showed a significant association with the age of onset for T2DM (β = -0.454, p = 0.001) in the Case population, as well as among T2DM patients in the HG one (β = -0.999, p = 0.003) in the replication study. The higher the GRS, the earlier was the T2DM onset. Individuals with more than eight risk alleles will presumably be diabetic six and a half years earlier than those with less than four risk alleles. Our results suggest that there is a considerable genetic predisposition for the early onset of T2DM; therefore, in addition to conventional risk factors, GRS can be used as a tool for estimating the risk of the earlier onset of T2DM and stratifying populations at risk in order to define preventive interventions.
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Affiliation(s)
- Peter Piko
- MTA-DE Public Health Research Group, University of Debrecen, 4028 Debrecen, Hungary; (P.P.); (N.A.W.)
| | - Nardos Abebe Werissa
- MTA-DE Public Health Research Group, University of Debrecen, 4028 Debrecen, Hungary; (P.P.); (N.A.W.)
- Doctoral School of Health Sciences, University of Debrecen, 4032 Debrecen, Hungary
| | - Szilvia Fiatal
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; (S.F.); (J.S.)
| | - Janos Sandor
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; (S.F.); (J.S.)
| | - Roza Adany
- MTA-DE Public Health Research Group, University of Debrecen, 4028 Debrecen, Hungary; (P.P.); (N.A.W.)
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; (S.F.); (J.S.)
- Correspondence: ; Tel.: +36-5251-2764
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Rapid Gout Detection Method and Kit. Diagnostics (Basel) 2019; 9:diagnostics9040157. [PMID: 31652657 PMCID: PMC6963814 DOI: 10.3390/diagnostics9040157] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 10/15/2019] [Accepted: 10/18/2019] [Indexed: 12/20/2022] Open
Abstract
Gout is a form of arthritis characterized by buildup of uric acid in synovial fluid, which causes severe swelling and can harm joints, tendons, and other tissues. It affects approximately 4% of the United States population, or approximately 8.3 million people nationwide and is therefore a topic of epidemiologic consideration due to its prevalence. Gout is typically diagnosed via polarized microscopy of arthroscopically-aspirated synovial fluid, which is a costly, time-consuming, labor-intensive, and technically complex procedure, warranting a simpler and less complex method for diagnosis. Here, we propose and validate a colorimetric method which is based on the ability of uric acid to reduce silver nitrate. We also assessed how the colorimetric change can be accelerated by changing the concentration of silver nitrate or adding different silver catalysts, as well as develop a matrix bed for improved handling and ease of use. When translated to the clinic, this diagnostic method for gout will have the potential to increase diagnostic efficiency and accelerate patient care at the bedside.
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