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Sandholm N, Dahlström EH, Groop PH. Genetic and epigenetic background of diabetic kidney disease. Front Endocrinol (Lausanne) 2023; 14:1163001. [PMID: 37324271 PMCID: PMC10262849 DOI: 10.3389/fendo.2023.1163001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/10/2023] [Indexed: 06/17/2023] Open
Abstract
Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.
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Affiliation(s)
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Emma H. Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia
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2
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Zhao Q, Xu Q, Serafino MA, Zhang Q, Wang C, Yu Y. Comprehensive analysis of circular RNAs in porcine small intestine epithelial cells associated with susceptibility to Escherichia coli F4ac diarrhea. BMC Genomics 2023; 24:211. [PMID: 37085748 PMCID: PMC10122348 DOI: 10.1186/s12864-022-08994-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 11/06/2022] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Diarrhea is one of the most common diseases in pig industry, which seriously threatens the health of piglets and causes huge economic losses. Enterotoxigenic Escherichia coli (ETEC) F4 is regarded as the most important cause of diarrhea in piglets. Some pigs are naturally resistant to those diarrheas caused by ETEC-F4, because they have no F4 receptors (F4R) on their small intestine epithelial cells that allow F4 fimbriae adhesion. Circular RNA (circRNA) has been shown to play an important regulatory role in the pathogenesis of disease. We hypothesized that circRNAs may also regulate the adhesion of piglet small intestinal epithelial cells to ETEC F4 fimbriae. However, the circRNA expression profiles of piglets with different Enterotoxigenic Escherichia coli F4 fimbriae (ETEC-F4ac) adhesion phenotypes are still unclear, and the intermediate regulatory mechanisms need to be explored. Hence, the present study assessed the circRNA expression profiling in small intestine epithelial cells of eight male piglets with different ETEC-F4 adhesion phenotypes and ITGB5 genotypes to unravel their regulatory function in susceptibility to ETEC-F4ac diarrhea. Piglets were divided into two groups: non-adhesive group (n = 4) with CC genotype and adhesive group (n = 4) with TT genotype. RESULTS The RNA-seq data analysis identified 13,199 circRNAs from eight samples, most of which were exon-derived. In the small intestine epithelial cells, 305 were differentially expressed (DE) circRNAs between the adhesive and non-adhesive groups; of which 46 circRNAs were upregulated, and 259 were downregulated. Gene ontology and KEGG enrichment analysis revealed that most significantly enriched DE circRNAs' host genes were linked to cytoskeletal components, protein phosphorylation, cell adhesion, ion transport and pathways (such as adherens junction, gap junction) associated with ETEC diarrhea. The circRNA-miRNA-mRNA interaction network was also constructed to elucidate their underlying regulatory relationships. Our results identified several candidate circRNAs that affects susceptibility to ETEC diarrhea. Among them, circ-SORBS1 can adsorb ssc-miR-345-3p to regulate the expression of its host gene SORBS1, thus improving cell adhesion. CONCLUSION Our results provided insights into the regulation function of circRNAs in susceptibility to ETEC diarrhea of piglets, and enhanced our understanding of the role of circRNAs in regulating ETEC diarrhea, and reveal the great potential of circRNA as a diagnostic marker for susceptibility of ETEC diarrhea in piglets.
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Affiliation(s)
- Qingyao Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Qinglei Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, People's Republic of China
| | - M A Serafino
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, People's Republic of China
- School of Natural Resources and Environmental Studies, University of Juba, B. O. Pox 82, Juba, South Sudan
| | - Qin Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, People's Republic of China
- College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Shandong, 271018, China
| | - Chuduan Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, People's Republic of China.
| | - Ying Yu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, People's Republic of China.
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Jin H, Kim YA, Lee Y, Kwon SH, Do AR, Seo S, Won S, Seo JH. Identification of genetic variants associated with diabetic kidney disease in multiple Korean cohorts via a genome-wide association study mega-analysis. BMC Med 2023; 21:16. [PMID: 36627639 PMCID: PMC9832630 DOI: 10.1186/s12916-022-02723-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/28/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND The pathogenesis of diabetic kidney disease (DKD) is complex, involving metabolic and hemodynamic factors. Although DKD has been established as a heritable disorder and several genetic studies have been conducted, the identification of unique genetic variants for DKD is limited by its multiplex classification based on the phenotypes of diabetes mellitus (DM) and chronic kidney disease (CKD). Thus, we aimed to identify the genetic variants related to DKD that differentiate it from type 2 DM and CKD. METHODS We conducted a large-scale genome-wide association study mega-analysis, combining Korean multi-cohorts using multinomial logistic regression. A total of 33,879 patients were classified into four groups-normal, DM without CKD, CKD without DM, and DKD-and were further analyzed to identify novel single-nucleotide polymorphisms (SNPs) associated with DKD. Additionally, fine-mapping analysis was conducted to investigate whether the variants of interest contribute to a trait. Conditional analyses adjusting for the effect of type 1 DM (T1D)-associated HLA variants were also performed to remove confounding factors of genetic association with T1D. Moreover, analysis of expression quantitative trait loci (eQTL) was performed using the Genotype-Tissue Expression project. Differentially expressed genes (DEGs) were analyzed using the Gene Expression Omnibus database (GSE30529). The significant eQTL DEGs were used to explore the predicted interaction networks using search tools for the retrieval of interacting genes and proteins. RESULTS We identified three novel SNPs [rs3128852 (P = 8.21×10-25), rs117744700 (P = 8.28×10-10), and rs28366355 (P = 2.04×10-8)] associated with DKD. Moreover, the fine-mapping study validated the causal relationship between rs3128852 and DKD. rs3128852 is an eQTL for TRIM27 in whole blood tissues and HLA-A in adipose-subcutaneous tissues. rs28366355 is an eQTL for HLA-group genes present in most tissues. CONCLUSIONS We successfully identified SNPs (rs3128852, rs117744700, and rs28366355) associated with DKD and verified the causal association between rs3128852 and DKD. According to the in silico analysis, TRIM27 and HLA-A can define DKD pathophysiology and are associated with immune response and autophagy. However, further research is necessary to understand the mechanism of immunity and autophagy in the pathophysiology of DKD and to prevent and treat DKD.
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Affiliation(s)
- Heejin Jin
- Institute of Health and Environment, Seoul National University, Seoul, Korea
| | - Ye An Kim
- Division of Endocrinology, Department of Internal Medicine, Veterans Health Service Medical Center, Seoul, Korea
| | - Young Lee
- Veterans Medical Research Institute, Veterans Health Service Medical Center, Jinhwangdo-ro 61-gil 53, Gangdong-gu, Seoul, Korea
| | - Seung-Hyun Kwon
- Veterans Medical Research Institute, Veterans Health Service Medical Center, Jinhwangdo-ro 61-gil 53, Gangdong-gu, Seoul, Korea
| | - Ah Ra Do
- Interdisciplinary Program of Bioinformatics, College of National Sciences, Seoul National University, Seoul, South Korea
| | - Sujin Seo
- Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, Korea
| | - Sungho Won
- Institute of Health and Environment, Seoul National University, Seoul, Korea.,Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, Korea.,RexSoft Corps, Seoul, Korea
| | - Je Hyun Seo
- Veterans Medical Research Institute, Veterans Health Service Medical Center, Jinhwangdo-ro 61-gil 53, Gangdong-gu, Seoul, Korea.
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Mohammedi K, Marre M, Hadjadj S, Potier L, Velho G. Redox Genetic Risk Score and the Incidence of End-Stage Kidney Disease in People with Type 1 Diabetes. Cells 2022; 11:cells11244131. [PMID: 36552894 PMCID: PMC9777489 DOI: 10.3390/cells11244131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 11/23/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
End-stage kidney disease (ESKD) is a multifactorial condition influenced by genetic background, but the extent to which a genetic risk score (GRS) improves ESKD prediction is unknown. We built a redox GRS on the base of previous association studies (six polymorphisms from six redox genes) and tested its relationship with ESKD in three cohorts of people with type 1 diabetes. Among 1012 participants, ESKD (hemodialysis requirement, kidney transplantation, eGFR < 15 mL/min/1.73 m2) occurred in 105 (10.4%) during a 14-year follow-up. High redox GRS was associated with increased ESKD risk (adjusted HR for the upper versus the lowest GRS tertile: 2.60 (95% CI, 1.51-4.48), p = 0.001). Each additional risk-allele was associated with a 20% increased risk of ESKD (95% CI, 8-33, p < 0.0001). High GRS yielded a relevant population attributable fraction (30%), but only a marginal enhancement in c-statistics index (0.928 [0.903-0.954]) over clinical factors 0.921 (0.892-0.950), p = 0.04). This is the first report of an independent association between redox GRS and increased risk of ESKD in type 1 diabetes. Our results do not support the use of this GRS in clinical practice but provide new insights into the involvement of oxidative stress genetic factors in ESKD risk in type 1 diabetes.
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Affiliation(s)
- Kamel Mohammedi
- Centre Hospitalier de Bordeaux, Department of Endocrinology, Diabetes and Nutrition, University Hospital of Bordeaux, 33604 Pessac, France
- Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, ON L8S 4L8, Canada
- Correspondence:
| | - Michel Marre
- Institut Necker-Enfants Malades, INSERM, Université de Paris, 75013 Paris, France
- Clinique Ambroise Paré, 92200 Neuilly-sur-Seine, France
| | - Samy Hadjadj
- Institut du Thorax, INSERM, CNRS, UNIV Nantes, CHU Nantes, 44109 Nantes, France
| | - Louis Potier
- Institut Necker-Enfants Malades, INSERM, Université de Paris, 75013 Paris, France
- Clinique Ambroise Paré, 92200 Neuilly-sur-Seine, France
- Service d’Endocrinologie Diabétologie Nutrition, Hôpital Bichat, AP-HP, 75013 Paris, France
| | - Gilberto Velho
- Institut Necker-Enfants Malades, INSERM, Université de Paris, 75013 Paris, France
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Key Genetic Components of Fibrosis in Diabetic Nephropathy: An Updated Systematic Review and Meta-Analysis. Int J Mol Sci 2022; 23:ijms232315331. [PMID: 36499658 PMCID: PMC9736240 DOI: 10.3390/ijms232315331] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/27/2022] [Accepted: 11/29/2022] [Indexed: 12/09/2022] Open
Abstract
Renal fibrosis (RF) constitutes the common end-point of all kinds of chronic kidney disease (CKD), regardless of the initial cause of disease. The aim of the present study was to identify the key players of fibrosis in the context of diabetic nephropathy (DN). A systematic review and meta-analysis of all available genetic association studies regarding the genes that are included in signaling pathways related to RF were performed. The evaluated studies were published in English and they were included in PubMed and the GWAS Catalog. After an extensive literature review and search of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, eight signaling pathways related to RF were selected and all available genetic association studies of these genes were meta-analyzed. ACE, AGT, EDN1, EPO, FLT4, GREM1, IL1B, IL6, IL10, IL12RB1, NOS3, TGFB1, IGF2/INS/TH cluster, and VEGFA were highlighted as the key genetic components driving the fibrosis process in DN. The present systematic review and meta-analysis indicate, as key players of fibrosis in DN, sixteen genes. However, the results should be interpreted with caution because the number of studies was relatively small.
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Advances in the previous two decades in our understanding of the post-translational modifications, functions, and drug perspectives of ArgBP2 and its family members. Biomed Pharmacother 2022; 155:113853. [DOI: 10.1016/j.biopha.2022.113853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 09/28/2022] [Accepted: 10/06/2022] [Indexed: 11/20/2022] Open
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7
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Gong S, Huo S, Luo Y, Li Y, Ma Y, Huang X, Hu M, Liu W, Zhang R, Cai X, Zhou L, Chen L, Ren Q, Zhang S, Zhu Y, Zhang X, Chen J, Wu J, Zhou X, Lin X, Han X, Ji L. A variation in SORBS1 is associated with type 2 diabetes and high-density lipoprotein cholesterol in Chinese population. Diabetes Metab Res Rev 2022; 38:e3524. [PMID: 35107206 DOI: 10.1002/dmrr.3524] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 12/05/2021] [Accepted: 12/25/2021] [Indexed: 11/09/2022]
Abstract
AIM Sorbin and SH3-domain-containing-1 (SORBS1) play important roles in insulin signalling and cytoskeleton regulation. Variants of the SORBS1 gene have been inconsistently reported to be associated with type 2 diabetes or diabetic kidney disease (DKD). METHODS Two independent case-control studies based on two randomized sampling cohorts (cohort 1, n = 3345; cohort 2, n = 2282) were used to confirm the association between rs2281939 of SORBS1 and impaired glucose regulation (IGR). An additional hospital-based cohort (cohort 3, n = 2135) and cohort 1 were used to investigate the association between rs2281939 and DKD. The phenotype of rare variants of SORBS1 was explored in 453 patients with early onset type 2 diabetes (diagnosed before 40 years of age, EOD). RESULTS The G allele was associated with type 2 diabetes (additive model: OR = 1.25, 95% CI [1.03-1.52], p = 0.022) in cohort 1, and IGR in cohort 2 (additive model: OR = 1.22, 95% CI [1.05-1.43], p = 0.01). We found that the G allele was also associated with HDL-c levels in women in both cohort 1 (p = 0.03) and 2 (p = 0.029) in the dominant model. The rare variant carriers also had lower HDL-c and LDL-c levels than non-carriers in patients with EOD. No association between rs2281939 or rare variants and DKD was observed. CONCLUSIONS The variants in the SORBS1 gene were associated with IGR and HDL-c levels but not with DKD in the Chinese Han population.
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Affiliation(s)
- Siqian Gong
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Shaofeng Huo
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China
| | - Yingying Luo
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Yufeng Li
- Beijing Pinggu Hospital, Beijing, China
| | - Yumin Ma
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Xiuting Huang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Mengdie Hu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Wei Liu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Rui Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Xiaoling Cai
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Lingli Zhou
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Ling Chen
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Qian Ren
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Simin Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Yu Zhu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Xiuying Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Jing Chen
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Jing Wu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Xianghai Zhou
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Xu Lin
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, China
| | - Xueyao Han
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
| | - Linong Ji
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Center, Beijing, China
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Childebayeva A, Rohrlach AB, Barquera R, Rivollat M, Aron F, Szolek A, Kohlbacher O, Nicklisch N, Alt KW, Gronenborn D, Meller H, Friederich S, Prüfer K, Deguilloux MF, Krause J, Haak W. Population Genetics and Signatures of Selection in Early Neolithic European Farmers. Mol Biol Evol 2022; 39:6586604. [PMID: 35578825 PMCID: PMC9171004 DOI: 10.1093/molbev/msac108] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Human expansion in the course of the Neolithic transition in western Eurasia has been one of the major topics in ancient DNA research in the last 10 years. Multiple studies have shown that the spread of agriculture and animal husbandry from the Near East across Europe was accompanied by large-scale human expansions. Moreover, changes in subsistence and migration associated with the Neolithic transition have been hypothesized to involve genetic adaptation. Here, we present high quality genome-wide data from the Linear Pottery Culture site Derenburg-Meerenstieg II (DER) (N = 32 individuals) in Central Germany. Population genetic analyses show that the DER individuals carried predominantly Anatolian Neolithic-like ancestry and a very limited degree of local hunter-gatherer admixture, similar to other early European farmers. Increasing the Linear Pottery culture cohort size to ∼100 individuals allowed us to perform various frequency- and haplotype-based analyses to investigate signatures of selection associated with changes following the adoption of the Neolithic lifestyle. In addition, we developed a new method called Admixture-informed Maximum-likelihood Estimation for Selection Scans that allowed us test for selection signatures in an admixture-aware fashion. Focusing on the intersection of results from these selection scans, we identified various loci associated with immune function (JAK1, HLA-DQB1) and metabolism (LMF1, LEPR, SORBS1), as well as skin color (SLC24A5, CD82) and folate synthesis (MTHFR, NBPF3). Our findings shed light on the evolutionary pressures, such as infectious disease and changing diet, that were faced by the early farmers of Western Eurasia.
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Affiliation(s)
- Ainash Childebayeva
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | - Adam Benjamin Rohrlach
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, The University of Adelaide, Adelaide, Australia
| | - Rodrigo Barquera
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | - Maïté Rivollat
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Université de Bordeaux, CNRS, PACEA-UMR 5199, 33615 Pessac, France
| | - Franziska Aron
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany
| | - András Szolek
- Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany.,Department of Immunology, Interfaculty Institute for Cell Biology, University of Tübingen, Tübingen, Germany
| | - Oliver Kohlbacher
- Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany.,Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.,Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany.,Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Nicole Nicklisch
- Center of Natural and Cultural Human History, Danube Private University, Krems-Stein, Austria.,State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Kurt W Alt
- Center of Natural and Cultural Human History, Danube Private University, Krems-Stein, Austria.,State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Detlef Gronenborn
- Römisch-Germanisches Zentralmuseum, Leibniz Research Institute for Archaeology, Ernst-Ludwig-Platz 2, 55116 Mainz, Germany
| | - Harald Meller
- State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Susanne Friederich
- State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Kay Prüfer
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | | | - Johannes Krause
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | - Wolfgang Haak
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
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Yang L, Min X, Zhu Y, Hu Y, Yang M, Yu H, Li J, Xiong X. Polymorphisms of SORBS1 Gene and Their Correlation with Milk Fat Traits of Cattleyak. Animals (Basel) 2021; 11:ani11123461. [PMID: 34944239 PMCID: PMC8697865 DOI: 10.3390/ani11123461] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 11/29/2021] [Accepted: 12/03/2021] [Indexed: 12/28/2022] Open
Abstract
Simple Summary Increasing milk fat rate has a good effect on the milk quality of cattleyak. SNPs can help us find potential molecular markers for the milk fat traits of cattleyak, and they can be screened according to molecular markers when they are young. It provides a reference for cultivating high milk fat cattle population in the future. The results of this study suggest that the SORBS1 gene polymorphism is closely related to the milk fat traits of cattleyak, which could be used as a candidate genetic marker for milk fat trait selection in cattleyak. This study provides a new molecular marker and theoretical basis for screening the milk fat traits of cattleyak. It has a certain reference value for the research and improvement of milk quality. Abstract This study aimed to find the SNPs in the SORBS1 gene of cattleyak, analyze the relationship between its polymorphisms and the milk fat traits, and find potential molecular markers for the milk fat traits of cattleyak. The polymorphism of the SORBS1 gene in 350 cattleyak from Hongyuan County (Sichuan, China) were detected by PCR and DNA sequencing, and the correlation between these SNPs and the milk production traits of cattleyak was analyzed. The results showed that there were nine SNPs in the CDS and their adjacent non-coding regions of the SORBS1 gene, and all SNPs have three genotypes. The correlation analysis found that the genotypes with superior milk fat traits in the other eight alleles were homozygous genotypes with a high genotype frequency except the g.96284 G > A (c.3090 G > A) (p < 0.05). However, at locus g.96284 G > A, the milk fat percentage, monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs) and saturated fatty acids (SFAs) of the GA genotype were significantly higher than that of GG and AA genotypes (p < 0.05). Among these SNPs, three SNPs (g.6256 C > T (c.298 C > T), g.24791 A > G (c.706 A > G) and g.29121 A > G (c.979 A > G)) caused the amino acids change. The genotypes of the three SNPs consist of three haplotypes and four diplotypes. The amino acid mutation degree of diplotype H1–H1 (CCAAAA) was the highest, and its milk fat percentage, MUFAs, PUFAs and SFAs were also the highest (p < 0.05). Taken together, we found nine SNPs in the SORBS1 gene that are closely related to the milk fat traits of cattleyak. Moreover, the mutation of amino acids caused by SNPs had positive effects on the milk fat traits of cattleyak. H1-H1 is the dominant diplotype which significantly related to the milk fat traits of cattleyak. This study provides a new molecular marker and theoretical basis for screening the milk fat traits of cattleyak.
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Affiliation(s)
- Luyu Yang
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Reservation and Exploitation of Ministry of Education, Southwest Minzu University, Chengdu 610041, China; (L.Y.); (X.M.); (Y.Z.); (Y.H.); (J.L.)
- Key Laboratory of Animal Science of National Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610041, China; (M.Y.); (H.Y.)
| | - Xingyu Min
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Reservation and Exploitation of Ministry of Education, Southwest Minzu University, Chengdu 610041, China; (L.Y.); (X.M.); (Y.Z.); (Y.H.); (J.L.)
| | - Yanjin Zhu
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Reservation and Exploitation of Ministry of Education, Southwest Minzu University, Chengdu 610041, China; (L.Y.); (X.M.); (Y.Z.); (Y.H.); (J.L.)
| | - Yulei Hu
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Reservation and Exploitation of Ministry of Education, Southwest Minzu University, Chengdu 610041, China; (L.Y.); (X.M.); (Y.Z.); (Y.H.); (J.L.)
| | - Manzhen Yang
- Key Laboratory of Animal Science of National Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610041, China; (M.Y.); (H.Y.)
| | - Hailing Yu
- Key Laboratory of Animal Science of National Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610041, China; (M.Y.); (H.Y.)
| | - Jian Li
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Reservation and Exploitation of Ministry of Education, Southwest Minzu University, Chengdu 610041, China; (L.Y.); (X.M.); (Y.Z.); (Y.H.); (J.L.)
- Key Laboratory of Animal Science of National Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610041, China; (M.Y.); (H.Y.)
| | - Xianrong Xiong
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Reservation and Exploitation of Ministry of Education, Southwest Minzu University, Chengdu 610041, China; (L.Y.); (X.M.); (Y.Z.); (Y.H.); (J.L.)
- Key Laboratory of Animal Science of National Ethnic Affairs Commission, Southwest Minzu University, Chengdu 610041, China; (M.Y.); (H.Y.)
- Correspondence:
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10
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Tziastoudi M, Dardiotis E, Pissas G, Filippidis G, Golfinopoulos S, Siokas V, Tachmitzi SV, Eleftheriadis T, Hadjigeorgiou GM, Tsironi E, Stefanidis I. Serpin Family E Member 1 Tag Single-Nucleotide Polymorphisms in Patients with Diabetic Nephropathy: An Association Study and Meta-Analysis Using a Genetic Model-Free Approach. Genes (Basel) 2021; 12:1887. [PMID: 34946835 PMCID: PMC8701119 DOI: 10.3390/genes12121887] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/18/2021] [Accepted: 11/23/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Many lines of evidence highlight the genetic contribution on the development of diabetic nephropathy (DN). One of the studied genes is SERPINE1 whose the role in the risk of developing DN remains questionable. In order to elucidate the contribution of SERPINE1 in DN progression in the context of type 2 diabetes mellitus (T2DM), we conducted an association study and meta-analysis of SERPINE1 genetic variants. MATERIALS AND METHODS A total of 190 patients with DN, 150 T2DM (type 2 diabetes mellitus) patients without DN and 238 healthy controls were recruited. We selected five tag single-nucleotide polymorphisms (SNPs) from the HapMap. The generalized odds ratio (ORG) was calculated to estimate the risk on DN development. Subgroup analyses based on ethnicity and type of diabetes were also performed. RESULTS Both the present association study regarding SERPINE1 SNPs (rs2227667, rs2070682, rs1050813, rs2227690, rs2227692) did not found any significant association between SERPINE1 variants and DN and the meta-analysis of variant 4G>5G (rs1799889) did not also reveal a significant association between 4G>5G variant and DN in main and subgroup analyses. DISCUSSION In conclusion, the present association study and meta-analysis provides strong evidence that SERPINE1 genetic variant 4G>5G is not implicated in the risk or development of DN in Caucasians. Further studies in other populations remain to further investigate the role of this variant in the course of DN.
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Affiliation(s)
- Maria Tziastoudi
- Department of Nephrology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (G.P.); (G.F.); (S.G.); (T.E.); (I.S.)
| | - Efthimios Dardiotis
- Laboratory of Neurogenetics, Department of Neurology, University Hospital of Larissa, University of Thessaly, 41110 Larissa, Greece; (E.D.); (V.S.); (G.M.H.)
| | - Georgios Pissas
- Department of Nephrology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (G.P.); (G.F.); (S.G.); (T.E.); (I.S.)
| | - Georgios Filippidis
- Department of Nephrology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (G.P.); (G.F.); (S.G.); (T.E.); (I.S.)
| | - Spyridon Golfinopoulos
- Department of Nephrology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (G.P.); (G.F.); (S.G.); (T.E.); (I.S.)
| | - Vasileios Siokas
- Laboratory of Neurogenetics, Department of Neurology, University Hospital of Larissa, University of Thessaly, 41110 Larissa, Greece; (E.D.); (V.S.); (G.M.H.)
| | - Sophia V. Tachmitzi
- Department of Ophthalmology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (S.V.T.); (E.T.)
| | - Theodoros Eleftheriadis
- Department of Nephrology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (G.P.); (G.F.); (S.G.); (T.E.); (I.S.)
| | - Georgios M. Hadjigeorgiou
- Laboratory of Neurogenetics, Department of Neurology, University Hospital of Larissa, University of Thessaly, 41110 Larissa, Greece; (E.D.); (V.S.); (G.M.H.)
- Department of Neurology, Medical School, University of Cyprus, Nicosia 22006, Cyprus
| | - Evangelia Tsironi
- Department of Ophthalmology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (S.V.T.); (E.T.)
| | - Ioannis Stefanidis
- Department of Nephrology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (G.P.); (G.F.); (S.G.); (T.E.); (I.S.)
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Yi X, Cheng X. Understanding Competitive Endogenous RNA Network Mechanism in Type 1 Diabetes Mellitus Using Computational and Bioinformatics Approaches. Diabetes Metab Syndr Obes 2021; 14:3865-3945. [PMID: 34526791 PMCID: PMC8436179 DOI: 10.2147/dmso.s315488] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 07/24/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Type 1 diabetes mellitus (T1DM), an autoimmune disease with a genetic tendency, has an increasing prevalence. Long non-coding RNA (lncRNA) and circular RNA (circRNA) are receiving increasing attention in disease pathogenesis. However, their roles in T1DM are poorly understood. The present study aimed at identifying signature lncRNAs and circRNAs and investigating their roles in T1DM using the competing endogenous RNA (ceRNA) network analysis. METHODS The T1DM expression profile was downloaded from Gene Expression Omnibus (GEO) database to identify the differentially expressed circRNAs, lncRNAs, and mRNAs. The biological functions of these differentially expressed circRNAs, lncRNAs, and mRNAs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Targeting relationships of circRNA-miRNA, lncRNA-miRNA, and miRNA-mRNA were predicted, and the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. Finally, qRT-PCR was applied to identify the effect of hsa_circ_0002202 inhibition on the IFN-I induced macrophage inflammation. RESULTS A total of 178 circRNAs, 404 lncRNAs, and 73 mRNAs were identified to be abnormally expressed in T1DM samples. Functional enrichment analysis results indicated that the differentially expressed genes were mainly enriched in extracellular matrix components and macrophage activation. CeRNA regulatory network showed that circRNAs and lncRNAs regulate mRNAs through integrate multiple miRNAs. In addition, in vitro experiments showed that hsa_circ_0002202 inhibition suppressed the type I interferon (IFN-I)-induced macrophage inflammation. CONCLUSION In the present study, the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network in T1DM was established for the first time. We also found that hsa_circ_0002202 inhibition suppressed the IFN-I-induced macrophage inflammation. Our study may lay a foundation for future studies on the ceRNA regulatory network in T1DM.
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Affiliation(s)
- Xuanzi Yi
- Department of Medicine II, Division of Endocrinology and Diabetology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, 79106, Germany
- Correspondence: Xuanzi Yi Department of Medicine II, Division of Endocrinology and Diabetology, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, Freiburg, 79106, GermanyTel/Fax +49 761 270-73270 Email
| | - Xu Cheng
- Department of Urology, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, 79106, Germany
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12
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Tziastoudi M, Stefanidis I, Zintzaras E. The genetic map of diabetic nephropathy: evidence from a systematic review and meta-analysis of genetic association studies. Clin Kidney J 2020; 13:768-781. [PMID: 33123356 PMCID: PMC7577775 DOI: 10.1093/ckj/sfaa077] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Indexed: 12/20/2022] Open
Abstract
Despite the extensive efforts of scientists, the genetic background of diabetic nephropathy (DN) has not yet been clarified. To elucidate the genetic variants that predispose to the development of DN, we conducted a systematic review and meta-analysis of all available genetic association studies (GAS) of DN. We searched in the Human Genome Epidemiology Navigator (HuGE Navigator) and PubMed for available GAS of DN. The threshold for meta-analysis was three studies per genetic variant. The association between genotype distribution and DN was examined using the generalized linear odds ratio (ORG). For variants with available allele frequencies, the examined model was the allele contrast. The pooled OR was estimated using the DerSimonian and Laird random effects model. The publication bias was assessed with Egger’s test. We performed pathway analysis of significant genes with DAVID 6.7. Genetic data of 606 variants located in 228 genes were retrieved from 360 GASs and were synthesized with meta-analytic methods. ACACB, angiotensin I-converting enzyme (ACE), ADIPOQ, AGT, AGTR1, AKR1B1, APOC1, APOE, ATP1B2, ATP2A3, CARS, CCR5, CGNL1, Carnosine dipeptidase 1 (CNDP1), CYGB-PRCD, EDN1, Engulfment and cell motility 1 (ELMO1), ENPP1, EPO, FLT4, FTO, GLO1, HMGA2, IGF2/INS/TH cluster, interleukin 1B (IL1B), IL8, IL10, KCNQ1, KNG, LOC101927627, Methylenetetrahydrofolate reductase, nitric oxide synthase 3 (NOS3), SET domain containing seven, histone lysine methyltransferase (SETD7), Sirtuin 1 (SIRT1), SLC2A1, SLC2A2, SLC12A3, SLC19A3, TCF7L2, TGFB1, TIMP1, TTC39C, UNC13B, VEGFA, WTAPP1, WWC1 as well as XYLT1 and three intergenic polymorphisms showed significant association with DN. Pathway analysis revealed the overrepresentation of six signalling pathways. The significant findings provide further evidence for genetic factors implication in DN offering new perspectives in discovery of new therapies.
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Affiliation(s)
- Maria Tziastoudi
- Department of Biomathematics, University of Thessaly, School of Medicine, Larissa, Greece
| | - Ioannis Stefanidis
- Department of Nephrology, University of Thessaly, School of Medicine, Larissa, Greece
| | - Elias Zintzaras
- Department of Biomathematics, University of Thessaly, School of Medicine, Larissa, Greece.,The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, USA
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13
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Canadas-Garre M, Smyth LJ, Anderson K, Kerr K, McKnight AJ. Genetic Strategies to Understand Human Diabetic Nephropathy: In Silico Strategies for Molecular Data-Association Studies. Methods Mol Biol 2020; 2067:241-275. [PMID: 31701456 DOI: 10.1007/978-1-4939-9841-8_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Multiple genetic strategies are available to help improve understanding of diabetic nephropathy. This chapter provides detailed methodology for a single-nucleotide polymorphism association study and meta-analysis, using a protocol suitable for targeted SNP or genome-wide association studies, to identify genetic risk factors for diabetic nephropathy.
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Affiliation(s)
| | - Laura J Smyth
- Centre for Public Health, Queen's University Belfast, Northern Ireland, UK
| | - Kerry Anderson
- Centre for Public Health, Queen's University Belfast, Northern Ireland, UK
| | - Katie Kerr
- Centre for Public Health, Queen's University Belfast, Northern Ireland, UK
| | - Amy Jayne McKnight
- Centre for Public Health, Queen's University Belfast, Northern Ireland, UK.
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14
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Akbar T, McGurnaghan S, Palmer CNA, Livingstone SJ, Petrie J, Chalmers J, Lindsay RS, McKnight JA, Pearson DWM, Patrick AW, Walker J, Looker HC, Colhoun HM. Cohort Profile: Scottish Diabetes Research Network Type 1 Bioresource Study (SDRNT1BIO). Int J Epidemiol 2018; 46:796-796i. [PMID: 28338705 DOI: 10.1093/ije/dyw152] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/11/2016] [Indexed: 02/06/2023] Open
Affiliation(s)
- Tahira Akbar
- Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh, UK
| | - Stuart McGurnaghan
- Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh, UK
| | - Colin N A Palmer
- Cardiovascular and Diabetes Medicine, University of Dundee, Dundee, UK
| | | | - John Petrie
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK
| | - John Chalmers
- Cameron Hospital, National Health Service (NHS) Fife, Kirkcaldy, UK
| | - Robert S Lindsay
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | | | - Donald W M Pearson
- JJR Macleod Centre for Diabetes, Endocrinology and Metabolism, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Alan W Patrick
- Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK
| | | | - Helen C Looker
- Diabetes Epidemiology Unit, University of Dundee, Dundee, UK
| | - Helen M Colhoun
- Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh, UK.,Department of Public Health, NHS Fife, Kirkcaldy, UK
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15
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Nyaga DM, Vickers MH, Jefferies C, Perry JK, O’Sullivan JM. Type 1 Diabetes Mellitus-Associated Genetic Variants Contribute to Overlapping Immune Regulatory Networks. Front Genet 2018; 9:535. [PMID: 30524468 PMCID: PMC6258722 DOI: 10.3389/fgene.2018.00535] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 10/22/2018] [Indexed: 01/01/2023] Open
Abstract
Type 1 diabetes (T1D) is a chronic metabolic disorder characterized by the autoimmune destruction of insulin-producing pancreatic islet beta cells in genetically predisposed individuals. Genome-wide association studies (GWAS) have identified over 60 risk regions across the human genome, marked by single nucleotide polymorphisms (SNPs), which confer genetic predisposition to T1D. There is increasing evidence that disease-associated SNPs can alter gene expression through spatial interactions that involve distal loci, in a tissue- and development-specific manner. Here, we used three-dimensional (3D) genome organization data to identify genes that physically co-localized with DNA regions that contained T1D-associated SNPs in the nucleus. Analysis of these SNP-gene pairs using the Genotype-Tissue Expression database identified a subset of SNPs that significantly affected gene expression. We identified 246 spatially regulated genes including HLA-DRB1, LAT, MICA, BTN3A2, CTLA4, CD226, NOTCH1, TRIM26, PTEN, TYK2, CTSH, and FLRT3, which exhibit tissue-specific effects in multiple tissues. We observed that the T1D-associated variants interconnect through networks that form part of the immune regulatory pathways, including immune-cell activation, cytokine signaling, and programmed cell death protein-1 (PD-1). Our results implicate T1D-associated variants in tissue and cell-type specific regulatory networks that contribute to pancreatic beta cell inflammation and destruction, adaptive immune signaling, and immune-cell proliferation and activation. A number of other regulatory changes we identified are not typically considered to be central to the pathology of T1D. Collectively, our data represent a novel resource for the hypothesis-driven development of diagnostic, prognostic, and therapeutic interventions in T1D.
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Affiliation(s)
- Denis M. Nyaga
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Mark H. Vickers
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Craig Jefferies
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
- Starship Children’s Health, Auckland, New Zealand
| | - Jo K. Perry
- The Liggins Institute, The University of Auckland, Auckland, New Zealand
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Li M, Pezzolesi MG. Advances in understanding the genetic basis of diabetic kidney disease. Acta Diabetol 2018; 55:1093-1104. [PMID: 30083980 DOI: 10.1007/s00592-018-1193-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 07/16/2018] [Indexed: 02/08/2023]
Abstract
Diabetic kidney disease (DKD) is a devastating complication of Type 1 and Type 2 diabetes and leads to increased morbidity and mortality. Earlier work in families has provided strong evidence that heredity is a major determinant of DKD. Previous linkage analyses and candidate gene studies have identified potential DKD genes; however, such approaches have largely been unsuccessful. Genome-wide association studies (GWAS) have made significant contribution in identifying SNPs associated with common complex diseases. Thanks to advanced technology, new analytical approaches, and international research collaborations, many DKD GWASs have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms. This review summarizes the current state of GWAS technology; findings from GWASs of DKD and its related traits conducted over the past 15 years and discuss the future of this field.
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Affiliation(s)
- Man Li
- Division of Nephrology and Hypertension, Department of Internal Medicine,, University of Utah School of Medicine, Salt Lake City, UT, 84105, USA
- VA Boston Healthcare System, VA Cooperative Studies Program, Boston, MA, USA
| | - Marcus G Pezzolesi
- Division of Nephrology and Hypertension, Department of Internal Medicine,, University of Utah School of Medicine, Salt Lake City, UT, 84105, USA.
- Diabetes and Metabolism Center, University of Utah School of Medicine, Salt Lake City, UT, USA.
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA.
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17
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Limou S, Vince N, Parsa A. Lessons from CKD-Related Genetic Association Studies-Moving Forward. Clin J Am Soc Nephrol 2018; 13:140-152. [PMID: 29242368 PMCID: PMC5753320 DOI: 10.2215/cjn.09030817] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Over the past decade, genetic association studies have uncovered numerous determinants of kidney function in the general, diabetic, hypertensive, CKD, ESRD, and GN-based study populations (e.g., IgA nephropathy, membranous nephropathy, FSGS). These studies have led to numerous novel and unanticipated findings, which are helping improve our understanding of factors and pathways affecting both normal and pathologic kidney function. In this review, we report on major discoveries and advances resulting from this rapidly progressing research domain. We also predict some of the next steps the nephrology community should embrace to accelerate the identification of genetic and molecular processes leading to kidney dysfunction, pathophysiologically based disease subgroups, and specific therapeutic targets, as we attempt to transition toward a more precision-based medicine approach.
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Affiliation(s)
- Sophie Limou
- Centre de Recherche en Transplantation et Immunologie Unité Mixte de Recherche 1064, Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Nantes, Nantes, France
- Institut de Transplantation Urologie et Néphrologie, Centre Hospitalier Universitaire Nantes, Nantes, France
- Ecole Centrale de Nantes, Nantes, France
- Basic Science Program, Basic Research Laboratory, National Cancer Institute/National Institutes of Health, Leidos Biomedical Research Inc., Frederick National Laboratory, Frederick, Maryland
| | - Nicolas Vince
- Centre de Recherche en Transplantation et Immunologie Unité Mixte de Recherche 1064, Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Nantes, Nantes, France
- Institut de Transplantation Urologie et Néphrologie, Centre Hospitalier Universitaire Nantes, Nantes, France
| | - Afshin Parsa
- Division of Nephrology, University of Maryland School of Medicine, Baltimore, Maryland; and
- Department of Medicine, Baltimore VA Medical Center, Baltimore, Maryland
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18
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Abstract
Approximately 20% to 40% of patients with type 1 or type 2 diabetes mellitus develop diabetic kidney disease. This is a clinical syndrome characterized by persistent albuminuria (> 300 mg/24 h, or > 300 mg/g creatinine), a relentless decline in glomerular filtration rate (GFR), raised arterial blood pressure, and enhanced cardiovascular morbidity and mortality. There is a characteristic histopathology. In classical diabetic nephropathy, the first clinical sign is moderately increased urine albumin excretion (microalbuminuria: 30-300 mg/24 h, or 30-300 mg/g creatinine; albuminuria grade A2). Untreated microalbuminuria will gradually worsen, reaching clinical proteinuria or severely increased albuminuria (albuminuria grade A3) over 5 to 15 years. The GFR then begins to decline, and without treatment, end-stage renal failure is likely to result in 5 to 7 years. Although albuminuria is the first sign of diabetic nephropathy, the first symptom is usually peripheral edema, which occurs at a very late stage. Regular, systematic screening for diabetic kidney disease is needed in order to identify patients at risk of or with presymptomatic diabetic kidney disease. Annual monitoring of urinary albumin-to-creatinine ratio, estimated GFR, and blood pressure is recommended. Several new biomarkers or profiles of biomarkers have been investigated to improve prognostic and diagnostic precision, but none have yet been implemented in routine clinical care. In the future such techniques may pave the way for personalized treatment.
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19
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Ainsworth HC, Langefeld CD, Freedman BI. Genetic epidemiology in kidney disease. Nephrol Dial Transplant 2017; 32:ii159-ii169. [PMID: 28201750 DOI: 10.1093/ndt/gfw270] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2016] [Accepted: 06/04/2016] [Indexed: 12/20/2022] Open
Abstract
Familial aggregation of chronic kidney disease and its component phenotypes-reduced glomerular filtration rate, proteinuria and renal histologic changes-has long been recognized. Rates of severe kidney disease are also known to differ markedly between populations based on ancestry. These epidemiologic observations support the existence of nephropathy susceptibility genes. Several molecular genetic technologies are now available to identify causative loci. The present article summarizes available strategies useful for identifying nephropathy susceptibility genes, including candidate gene association, family-based linkage, genome-wide association and admixture mapping (mapping by admixture linkage disequilibrium) approaches. Examples of loci detected using these techniques are provided. Epigenetic studies and future directions are also discussed. The identification of nephropathy susceptibility genes, coupled with modifiable environmental triggers impacting their function, is likely to improve risk prediction and transform care. Development of novel therapies to prevent progression of kidney disease will follow.
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Affiliation(s)
- Hannah C Ainsworth
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Barry I Freedman
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA
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Abstract
PURPOSE OF REVIEW Diabetic complications affecting the kidneys, retina, nerves, and the cardiovasculature are the major causes of morbidity and mortality in diabetes. This paper aims to review the current understanding of the genetic basis of these complications, based on recent findings especially from genome-wide association studies. RECENT FINDINGS Variants in or near AFF3, RGMA-MCTP2, SP3-CDCA7, GLRA3, CNKSR3, and UMOD have reached genome-wide significance (p value <5 × 10-8) for association with diabetic kidney disease, and recently, GRB2 was reported to be associated at genome-wide significance with diabetic retinopathy. While some loci affecting cardiovascular disease in the general population have been replicated in diabetes, GLUL affects the risk of cardiovascular disease specifically in diabetic subjects. Genetic findings are emerging for diabetic complications, although the studies remain relatively small compared to those for type 1 and type 2 diabetes. In addition to pinpointing specific loci, the studies also reveal biological information on correlated traits and pathways.
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Affiliation(s)
- Emma Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Haartmaninkatu 8, 00290, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Haartmaninkatu 8, 00290, Helsinki, Finland.
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.
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21
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Charmet R, van Hylckama Vlieg A, Germain M, Roussel R, Marre M, Debette S, Amouyel P, Deleuze JF, Hadjadj S, Rosendaal FR, Morange PE, Trégouët DA. Association of impaired renal function with venous thrombosis: A genetic risk score approach. Thromb Res 2017; 158:102-107. [PMID: 28866378 DOI: 10.1016/j.thromres.2017.08.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2017] [Revised: 08/14/2017] [Accepted: 08/22/2017] [Indexed: 12/21/2022]
Abstract
OBJECTIVE The association between impaired kidney function and venous thrombosis has been previously reported but supportive data are still sparse. We here wish to strengthen this association by investigating, by use of a genetic risk score approach, whether single nucleotide polymorphisms (SNPs) known to decrease the estimated glomerular filtration rate (eGFR), a surrogate marker for renal dysfunction, are associated with increased risk of venous thrombosis. APPROACH AND RESULTS Fifty-one polymorphisms selected from the literature to robustly associate with eGFR were first tested for association with venous thrombosis in a French case-control collection of 1953 patients and 2338 healthy individuals. This led to the identification of a genetic risk score based on 9 polymorphisms that strongly associated with increased risk (odds ratio (OR)=1.09 [1.06-1.15], p=1.44·10-7). This genetic score association replicated (OR=1.18 [1.11-1.26], p=8.86·10-8) in an independent sample of 1289 patients and 1049 healthy controls part of the Dutch MEGA study. We then categorized the genetic score distribution observed in the combined samples into quintiles. Compared with the lowest quintile, the OR for increased risk of disease associated with the second, third, fourth and fifth quintiles were 1.13 [0.94-1.16], 1.47 [1.22-1.77], 1.52 [1.26-1.82] and 1.70 [1.41-2.05], respectively. CONCLUSIONS Using a genetic risk score analysis, our study provides new elements supporting the association between impaired renal function and the risk of venous thrombosis.
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Affiliation(s)
- Romain Charmet
- Sorbonne Universités, UPMC Univ. Paris 06, Institut National pour la Santé et la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR_S) 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France; ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | | | - Marine Germain
- Sorbonne Universités, UPMC Univ. Paris 06, Institut National pour la Santé et la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR_S) 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France; ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - Ronan Roussel
- Assistance Publique Hôpitaux de Paris, Hôpital Bichat, DHU FIRE, Départment de Diabétologie, Endocrinologie et Nutrition, Paris, France.; Université Paris Diderot, Sorbonne Paris Cité, UFR de Médecine, Paris, France
| | - Michel Marre
- Assistance Publique Hôpitaux de Paris, Hôpital Bichat, DHU FIRE, Départment de Diabétologie, Endocrinologie et Nutrition, Paris, France.; Université Paris Diderot, Sorbonne Paris Cité, UFR de Médecine, Paris, France
| | - Stéphanie Debette
- INSERM UMR_S 1219, Bordeaux Population Health Research Center, University of Bordeaux, France; Department of Neurology, Bordeaux University Hospital, Bordeaux, France
| | - Philippe Amouyel
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE - Risk Factors and Molecular Determinants of Aging-related Diseases, F-59000 Lille, France
| | - Jean-François Deleuze
- Centre National Génotypage, Institut de Génomique, CEA, 91057 Evry, France; CEPH, Fondation Jean Dausset, Paris, France
| | - Samy Hadjadj
- Université de Poitiers, UFR de Médecine et Pharmacie, Poitiers, France; INSERM, CIC 1402 & U1082, Poitiers, France; CHU de Poitiers, Service d'Endocrinologie & CIC 1402, Poitiers, France
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pierre-Emmanuel Morange
- Laboratory of Haematology, La Timone Hospital, Marseille, France; INSERM UMR_S 1062, Nutrition Obesity and Risk of Thrombosis, Aix-Marseille University, Marseille, France
| | - David-Alexandre Trégouët
- Sorbonne Universités, UPMC Univ. Paris 06, Institut National pour la Santé et la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR_S) 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France; ICAN Institute for Cardiometabolism and Nutrition, Paris, France.
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22
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Wang Y, Zhao Y, Zhang J, Yang Y, Liu F. A case of a novel mutation in HNF1β-related maturity-onset diabetes of the young type 5 with diabetic kidney disease complication in a Chinese family. J Diabetes Complications 2017; 31:1243-1246. [PMID: 28502589 DOI: 10.1016/j.jdiacomp.2016.11.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Revised: 11/08/2016] [Accepted: 11/09/2016] [Indexed: 02/05/2023]
Abstract
AIMS Precise diagnosis of maturity-onset diabetes of the young (MODY) has proven valuable for understanding mechanism of diabetes and selecting optimal therapy. A proband and her mother with diabetic kidney disease (DKD) were studied to investigate potential genes responsible for diabetes and different severity of DKD between the parent and offspring. METHODS The family with suspected MODY underwent mutational analyses by the whole exome sequencing (WES). Candidate pathogenic variants were validated by Sanger sequencing and tested for co-segregation. The clinical parameters of subjects were collected from medical records. RESULTS A novel missense heterozygous mutation in exon 4 of the hepatocyte nuclear factor 1β (HNF1β), c.1007A > G (p.H336R), was identified in both the proband and her mother. Moreover, comparing the family's WES results, we found that the proband had acquired a KCNQ1 gene mutation from her father and acquired ACE and SORBS1 gene mutations from her mother. These three genes are known susceptibility genes of DKD and may impose additional effects contributing to DKD severity. CONCLUSIONS A novel mutation in HNF1β-MODY was identified in a Chinese family complicated with DKD, and the additional effect of pathogenic variants in susceptibility genes was speculated to contribute to DKD severity.
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Affiliation(s)
- Yiting Wang
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Yingwang Zhao
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Junlin Zhang
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Yuxiang Yang
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Fang Liu
- Division of Nephrology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China.
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23
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Abstract
PURPOSE OF REVIEW Precision medicine approaches, that tailor medications to specific individuals has made paradigm-shifting improvements for patients with certain cancer types. RECENT FINDINGS Such approaches, however, have not been implemented for patients with diabetic kidney disease. Precision medicine could offer new avenues for novel diagnostic, prognostic and targeted therapeutics development. Genetic studies associated with multiscalar omics datasets from tissue and cell types of interest of well-characterized cohorts are needed to change the current paradigm. In this review, we will discuss precision medicine approaches that the nephrology community can take to analyze tissue samples to develop new therapeutics for patients with diabetic kidney disease.
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Affiliation(s)
- Caroline Gluck
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, 415 Curie Blvd, 415 Clinical Research Building, Philadelphia, PA, 19104, USA
- Division of Nephrology, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Yi-An Ko
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, 415 Curie Blvd, 415 Clinical Research Building, Philadelphia, PA, 19104, USA
- Department of Genetics Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Katalin Susztak
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, 415 Curie Blvd, 415 Clinical Research Building, Philadelphia, PA, 19104, USA.
- Department of Genetics Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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24
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Buzzetti R, Prudente S, Copetti M, Dauriz M, Zampetti S, Garofolo M, Penno G, Trischitta V. Clinical worthlessness of genetic prediction of common forms of diabetes mellitus and related chronic complications: A position statement of the Italian Society of Diabetology. Nutr Metab Cardiovasc Dis 2017; 27:99-114. [PMID: 28063875 DOI: 10.1016/j.numecd.2016.08.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Revised: 08/01/2016] [Accepted: 08/13/2016] [Indexed: 02/08/2023]
Abstract
AIM We are currently facing several attempts aimed at marketing genetic data for predicting multifactorial diseases, among which diabetes mellitus is one of the more prevalent. The present document primarily aims at providing to practicing physicians a summary of available data regarding the role of genetic information in predicting diabetes and its chronic complications. DATA SYNTHESIS Firstly, general information about characteristics and performance of risk prediction tools will be presented in order to help clinicians to get acquainted with basic methodological information related to the subject at issue. Then, as far as type 1 diabetes is concerned, available data indicate that genetic information and counseling may be useful only in families with many affected individuals. However, since no disease prevention is possible, the utility of predicting this form of diabetes is at question. In the case of type 2 diabetes, available data really question the utility of adding genetic information on top of well performing, easy available and inexpensive non-genetic markers. Finally, the possibility of using the few available genetic data on diabetic complications for improving our ability to predict them will also be presented and discussed. For cardiovascular complication, the addition of genetic information to models based on clinical features does not translate in a substantial improvement in risk discrimination. For all other diabetic complications genetic information are currently very poor and cannot, therefore, be used for improving risk stratification. CONCLUSIONS In all, nowadays the use of genetic testing for predicting diabetes and its chronic complications is definitively of little value in clinical practice.
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Affiliation(s)
- R Buzzetti
- Department of Experimental Medicine, "Sapienza" University of Rome, Rome, Italy; UOC Diabetology, Polo Pontino, "Sapienza" University of Rome, Rome, Italy
| | - S Prudente
- Mendel Laboratory, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - M Copetti
- Unit of Biostatistics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - M Dauriz
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Verona School of Medicine and Hospital Trust of Verona, Verona, Italy
| | - S Zampetti
- Department of Experimental Medicine, "Sapienza" University of Rome, Rome, Italy; UOC Diabetology, Polo Pontino, "Sapienza" University of Rome, Rome, Italy
| | - M Garofolo
- Section of Diabetes and Metabolic Disease, Department of Clinical and Experimental Medicine, University of Pisa and Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - G Penno
- Section of Diabetes and Metabolic Disease, Department of Clinical and Experimental Medicine, University of Pisa and Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - V Trischitta
- Department of Experimental Medicine, "Sapienza" University of Rome, Rome, Italy; Mendel Laboratory, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy; Research Unit of Diabetes and Endocrine Diseases, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
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25
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Sandholm N, Van Zuydam N, Ahlqvist E, Juliusdottir T, Deshmukh HA, Rayner NW, Di Camillo B, Forsblom C, Fadista J, Ziemek D, Salem RM, Hiraki LT, Pezzolesi M, Trégouët D, Dahlström E, Valo E, Oskolkov N, Ladenvall C, Marcovecchio ML, Cooper J, Sambo F, Malovini A, Manfrini M, McKnight AJ, Lajer M, Harjutsalo V, Gordin D, Parkkonen M, Tuomilehto J, Lyssenko V, McKeigue PM, Rich SS, Brosnan MJ, Fauman E, Bellazzi R, Rossing P, Hadjadj S, Krolewski A, Paterson AD, Florez JC, Hirschhorn JN, Maxwell AP, Dunger D, Cobelli C, Colhoun HM, Groop L, McCarthy MI, Groop PH. The Genetic Landscape of Renal Complications in Type 1 Diabetes. J Am Soc Nephrol 2016; 28:557-574. [PMID: 27647854 DOI: 10.1681/asn.2016020231] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Accepted: 07/17/2016] [Indexed: 12/14/2022] Open
Abstract
Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4×10-3). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2×10-5) and the risk of type 2 diabetes (P=6.1×10-4) associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1×10-4). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0×10-6), and pentose and glucuronate interconversions (P=3.0×10-6) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.
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Affiliation(s)
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Natalie Van Zuydam
- Wellcome Trust Centre for Human Genetics,Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom.,Medical Research Institute
| | - Emma Ahlqvist
- Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | | | - Harshal A Deshmukh
- Division of Population Health Sciences, University of Dundee, Dundee, United Kingdom
| | - N William Rayner
- Wellcome Trust Centre for Human Genetics,Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom.,Human Genetics, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Barbara Di Camillo
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Joao Fadista
- Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Daniel Ziemek
- Computational Sciences, Pfizer Worldwide Research and Development, Berlin, Germany
| | - Rany M Salem
- Departments of Genetics,Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts.,Divisions of Endocrinology and Genetics, Boston Children's Hospital, Boston, Massachusetts
| | - Linda T Hiraki
- Genetics and Genome Biology Program, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Marcus Pezzolesi
- Section on Genetics and Epidemiology, Joslin Diabetes Center, Boston, Massachusetts
| | - David Trégouët
- Sorbonne Universities, Pierre et Marie Curie University (UPMC) and National Institute for Health and Medical Research, Mixed Research Unit in Health (UMR_S) 1166, Paris, France.,Institute for Cardiometabolism and Nutrition, Genomics and pathophysiology of Cardiovascular diseases, Paris, France
| | - Emma Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Erkka Valo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Nikolay Oskolkov
- Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Claes Ladenvall
- Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | | | - Jason Cooper
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom
| | - Francesco Sambo
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Alberto Malovini
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.,Laboratory of Informatics and Systems Engineering for Clinical Research, Scientific Institute for Research, Hospitalization and Health Care, IRCCS (Instituto di Ricovero e Cura a Carattere Scientifico); Salvatore Maugeri Foundation, Pavia, Italy
| | - Marco Manfrini
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Amy Jayne McKnight
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom
| | - Maria Lajer
- Diabetic Complications, Steno Diabetes Center, Gentofte, Denmark
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.,The Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Daniel Gordin
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Maija Parkkonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | | | - Jaakko Tuomilehto
- The Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland.,Centre for Vascular Prevention, Danube University Krems, Krems, Austria
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden.,Diabetic Complications, Steno Diabetes Center, Gentofte, Denmark
| | - Paul M McKeigue
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | | | - Eric Fauman
- Computational Sciences, Pfizer Worldwide Research and Development, Cambridge, Massachusetts
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Peter Rossing
- Diabetic Complications, Steno Diabetes Center, Gentofte, Denmark.,Department of Health, Aarhus University, Aarhus, Denmark.,Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Samy Hadjadj
- Functional Research Unit of Medicine and Pharmacy, University of Poitiers, Poitiers, France.,Department of Endocrinology-Diabetology and Center of Clinical Investigation, Poitiers University Hospital, Poitiers, France.,Institute National pour la Santé et la Recherche Médicale, National Institute for Health and Medical Research, Center of Clinical Investigation 1402 and Unit 1082, Poitiers, France
| | - Andrzej Krolewski
- Section on Genetics and Epidemiology, Joslin Diabetes Center, Boston, Massachusetts
| | - Andrew D Paterson
- Genetics and Genome Biology Program, Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Jose C Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts.,Diabetes Unit and Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
| | - Joel N Hirschhorn
- Departments of Genetics,Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts.,Divisions of Endocrinology and Genetics, Boston Children's Hospital, Boston, Massachusetts
| | - Alexander P Maxwell
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom.,Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom; and
| | | | - David Dunger
- Department of Paediatrics, Institute of Metabolic Science, and
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Helen M Colhoun
- Division of Population Health Sciences, University of Dundee, Dundee, United Kingdom
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics,Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom.,Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, United Kingdom
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland,Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.,Baker IDI (International Diabetes Institute) Heart and Diabetes Institute, Melbourne, Victoria, Australia
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26
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Davoudi S, Sobrin L. Novel Genetic Actors of Diabetes-Associated Microvascular Complications: Retinopathy, Kidney Disease and Neuropathy. Rev Diabet Stud 2016; 12:243-59. [PMID: 26859656 DOI: 10.1900/rds.2015.12.243] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Both type 1 and type 2 diabetes mellitus can lead to the common microvascular complications of diabetic retinopathy, kidney disease, and neuropathy. Diabetic patients do not universally develop these complications. Long duration of diabetes and poor glycemic control explain a lot of the variability in the development of microvascular complications, but not all. Genetic factors account for some of the remaining variability because of the heritability and familial clustering of these complications. There have been a large number of investigations, including linkage studies, candidate gene studies, and genome-wide association studies, all of which have sought to identify the specific variants that increase susceptibility. For retinopathy, several genome-wide association studies have been performed in small or midsize samples, but no reproducible loci across the studies have been identified. For diabetic kidney disease, genome-wide association studies in larger samples have been performed, and loci for this complication are beginning to emerge. However, validation of the existing discoveries, and further novel discoveries in larger samples is ongoing. The amount of genetic research into diabetic neuropathy has been very limited, and much is dedicated to the understanding of genetic risk factors only. Collaborations that pool samples and aim to detect phenotype classifications more precisely are promising avenues for a better explanation of the genetics of diabetic microvascular complications.
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Affiliation(s)
- Samaneh Davoudi
- Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA
| | - Lucia Sobrin
- Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA
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27
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Abstract
The global prevalence of diabetic nephropathy is rising in parallel with the increasing incidence of diabetes in most countries. Unfortunately, up to 40 % of persons diagnosed with diabetes may develop kidney complications. Diabetic nephropathy is associated with substantially increased risks of cardiovascular disease and premature mortality. An inherited susceptibility to diabetic nephropathy exists, and progress is being made unravelling the genetic basis for nephropathy thanks to international research collaborations, shared biological resources and new analytical approaches. Multiple epidemiological studies have highlighted the clinical heterogeneity of nephropathy and the need for better phenotyping to help define important subgroups for analysis and increase the power of genetic studies. Collaborative genome-wide association studies for nephropathy have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms, but progress towards clinically relevant risk prediction models for diabetic nephropathy has been slow. This review summarises the current status, recent developments and ongoing challenges elucidating the genetics of diabetic nephropathy.
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Affiliation(s)
- Amy Jayne McKnight
- Nephrology Research Group, Centre for Public Health, Queen's University Belfast, c/o Regional Genetics Centre, Level A, Tower Block, Belfast City Hospital, Lisburn Road, Belfast, BT9 7AB, UK,
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28
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Kwak SH, Park KS. Genetic Studies on Diabetic Microvascular Complications: Focusing on Genome-Wide Association Studies. Endocrinol Metab (Seoul) 2015; 30:147-58. [PMID: 26194074 PMCID: PMC4508258 DOI: 10.3803/enm.2015.30.2.147] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 05/26/2015] [Accepted: 05/26/2015] [Indexed: 01/13/2023] Open
Abstract
Diabetes is a common metabolic disorder with a worldwide prevalence of 8.3% and is the leading cause of visual loss, end-stage renal disease and amputation. Recently, genome-wide association studies (GWASs) have identified genetic risk factors for diabetic microvascular complications of retinopathy, nephropathy, and neuropathy. We summarized the recent findings of GWASs on diabetic microvascular complications and highlighted the challenges and our opinion on future directives. Five GWASs were conducted on diabetic retinopathy, nine on nephropathy, and one on neuropathic pain. The majority of recent GWASs were underpowered and heterogeneous in terms of study design, inclusion criteria and phenotype definition. Therefore, few reached the genome-wide significance threshold and the findings were inconsistent across the studies. Recent GWASs provided novel information on genetic risk factors and the possible pathophysiology of diabetic microvascular complications. However, further collaborative efforts to standardize phenotype definition and increase sample size are necessary for successful genetic studies on diabetic microvascular complications.
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Affiliation(s)
- Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University Hospital; Depatment of Internal Medicine, Seoul National University College of Medicine; Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea.
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Liu R, Lee K, He JC. Genetics and Epigenetics of Diabetic Nephropathy. KIDNEY DISEASES (BASEL, SWITZERLAND) 2015; 1:42-51. [PMID: 27536664 PMCID: PMC4934801 DOI: 10.1159/000381796] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2015] [Revised: 03/20/2015] [Indexed: 12/21/2022]
Abstract
BACKGROUND Diabetic nephropathy (DN) is the most common cause of end-stage renal disease (ESRD) in the USA and worldwide, contributing to significant morbidity and mortality in diabetic patients. A genetic factor for the development of DN is strongly implicated, as only one third of diabetic patients eventually develop kidney disease. Growing evidence also supports an important role of epigenetic modifications in DN. SUMMARY Multiple studies have been performed to identify risk genes and loci associated with DN. So far, only several genes and loci have been identified, none of which showed a strong association with DN. Therefore, a better study design with a larger sample size to identify rare variants and a clinically defined patient population to identify genes and loci associated with progressive DN are still needed. In addition to genetic factors, epigenetic modifications, such as DNA methylation, histone modifications and microRNAs, also play a major role in the pathogenesis of DN through a second layer of gene regulation. Although a major progress has been made in this field, epigenetic studies in DN are still in the early phase and have been limited mostly due to the heterogeneity of kidney tissue samples with multiple cells. However, rapid development of high-throughput genome-wide techniques will help us to better identify genetic variants and epigenetic changes in DN. KEY MESSAGE Understanding of genetic and epigenetic changes in DN is needed for the development of new biomarkers and better drug targets against DN. Summarized in this review are important recent findings on genetic and epigenetic studies in the field of DN.
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Affiliation(s)
- Ruijie Liu
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, N.Y., USA
- Renal Section, James J. Peters VAMC, New York, N.Y., USA
| | - Kyung Lee
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, N.Y., USA
| | - John Cijiang He
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, N.Y., USA
- Renal Section, James J. Peters VAMC, New York, N.Y., USA
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Abstract
The rising global prevalence of diabetes mellitus is accompanied by an increasing burden of morbidity and mortality that is attributable to the complications of chronic hyperglycaemia. These complications include blindness, renal failure and cardiovascular disease. Current therapeutic options for chronic hyperglycaemia reduce, but do not eradicate, the risk of these complications. Success in defining new preventative and therapeutic strategies hinges on an improved understanding of the molecular processes involved in the development of these complications. This Review explores the role of human genetics in delivering such insights, and describes progress in characterizing the sequence variants that influence individual predisposition to diabetic kidney disease, retinopathy, neuropathy and accelerated cardiovascular disease. Numerous risk variants for microvascular complications of diabetes have been reported, but very few have shown robust replication. Furthermore, only limited evidence exists of a difference in the repertoire of risk variants influencing macrovascular disease between those with and those without diabetes. Here, we outline the challenges associated with the genetic analysis of diabetic complications and highlight ongoing efforts to deliver biological insights that can drive translational benefits.
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