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Cañadas-Garre M, Baños-Jaime B, Maqueda JJ, Smyth LJ, Cappa R, Skelly R, Hill C, Brennan EP, Doyle R, Godson C, Maxwell AP, McKnight AJ. Genetic variants affecting mitochondrial function provide further insights for kidney disease. BMC Genomics 2024; 25:576. [PMID: 38858654 PMCID: PMC11163707 DOI: 10.1186/s12864-024-10449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 05/24/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. METHODS We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. RESULTS Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440-21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR. CONCLUSIONS We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.
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Affiliation(s)
- Marisa Cañadas-Garre
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK.
- Genomic Oncology Area, Centre for Genomics and Oncological Research: Pfizer, GENYO, University of Granada-Andalusian Regional Government, PTS Granada. Avenida de La Ilustración 114, 18016, Granada, Spain.
- Hematology Department, Hospital Universitario Virgen de Las Nieves, Avenida de Las Fuerzas Armadas 2, 18014, Granada, Spain.
- Instituto de Investigación Biosanitaria de Granada (Ibs.GRANADA), Avda. de Madrid, 15, 18012, Granada, Spain.
| | - Blanca Baños-Jaime
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Instituto de Investigaciones Químicas (IIQ), Centro de Investigaciones Científicas Isla de La Cartuja (cicCartuja), Consejo Superior de Investigaciones Científicas (CSIC), Universidad de Sevilla, Avda. Américo Vespucio 49, 41092, Seville, Spain
| | - Joaquín J Maqueda
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Experimental Oncology Laboratory, IRCCS Rizzoli Orthopaedic Institute, 40136, Bologna, Italy
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, 40126, Bologna, Italy
| | - Laura J Smyth
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Ruaidhri Cappa
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Ryan Skelly
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Claire Hill
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Eoin P Brennan
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Ross Doyle
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
- Mater Misericordiae University Hospital, Eccles St, Dublin, D07 R2WY, Ireland
| | - Catherine Godson
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Alexander P Maxwell
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Regional Nephrology Unit, Belfast City Hospital, Level 11Lisburn Road, Belfast, BT9 7AB, UK
| | - Amy Jayne McKnight
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
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Wang J, Li D, Sun Y, Tian Y. Air pollutants, genetic factors, and risk of chronic kidney disease: Findings from the UK Biobank. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 247:114219. [PMID: 36306611 DOI: 10.1016/j.ecoenv.2022.114219] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/10/2022] [Accepted: 10/19/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Experiment studies have suggested the emerging role of air pollutants in chronic kidney disease (CKD). However, only a few population studies conducted in Asia and North America have assessed their association, and the conclusions remained controversial. This study aims to investigate the effect of air pollutants exposure on CKD in the European population and first explores the modification effect of genetic risk on this association. METHODS 458,968 participants from the UK Biobank were included in this study. Cox proportional hazards model was used to assess the associations of air pollutants (PM2.5, PM10, NO2, and NOx) with incident CKD. A genetic risk score of 53 single nucleotide polymorphisms was constructed to represent the genetic susceptibility to CKD. To assess the interaction effect between air pollutants and the genetic risk, we added a multiplicative interaction term and did a stratified analysis. RESULTS During a median follow-up of 11.7 years, 16,637 incidents of CKD were identified. We observed positive associations between air pollutants exposure and CKD risk with the HRs for CKD were 1.09 (1.07, 1.11), 1.08 (1.06, 1.10), 1.05 (1.03, 1.07), 1.06 (1.04, 1.08) with per IQR (interquartile range) increment in PM2.5, PM10, NO2, and NOx, respectively. Stratified analysis showed that the associations between air pollutants and CKD were modest and marginal in the high genetic risk population (P > 0.05), while the associations were statistically significant in the low and intermediate genetic risk groups. CONCLUSIONS Our study indicated that exposure to various air pollutants, including PM2.5, PM10, NO2, and NOx, was associated with an elevated risk of CKD. This finding provide evidence that formulating strategies to improve air quality can be helpful to reduce the burden of CKD.
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Affiliation(s)
- Jianing Wang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dankang Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yu Sun
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yaohua Tian
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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3
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Koraishy FM, Mann FD, Waszczuk MA, Kuan PF, Jonas K, Yang X, Docherty A, Shabalin A, Clouston S, Kotov R, Luft B. Polygenic association of glomerular filtration rate decline in world trade center responders. BMC Nephrol 2022; 23:347. [PMID: 36307804 PMCID: PMC9615399 DOI: 10.1186/s12882-022-02967-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/26/2022] [Accepted: 10/06/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The factors associated with estimated glomerular filtrate rate (eGFR) decline in low risk adults remain relatively unknown. We hypothesized that a polygenic risk score (PRS) will be associated with eGFR decline. METHODS We analyzed genetic data from 1,601 adult participants with European ancestry in the World Trade Center Health Program (baseline age 49.68 ± 8.79 years, 93% male, 23% hypertensive, 7% diabetic and 1% with cardiovascular disease) with ≥ three serial measures of serum creatinine. PRSs were calculated from an aggregation of single nucleotide polymorphisms (SNPs) from a recent, large-scale genome-wide association study (GWAS) of rapid eGFR decline. Generalized linear models were used to evaluate the association of PRS with renal outcomes: baseline eGFR and CKD stage, rate of change in eGFR, stable versus declining eGFR over a 3-5-year observation period. eGFR decline was defined in separate analyses as "clinical" (> -1.0 ml/min/1.73 m2/year) or "empirical" (lower most quartile of eGFR slopes). RESULTS The mean baseline eGFR was ~ 86 ml/min/1.73 m2. Subjects with decline in eGFR were more likely to be diabetic. PRS was significantly associated with lower baseline eGFR (B = -0.96, p = 0.002), higher CKD stage (OR = 1.17, p = 0.010), decline in eGFR (OR = 1.14, p = 0.036) relative to stable eGFR, and the lower quartile of eGFR slopes (OR = 1.21, p = 0.008), after adjusting for established risk factors for CKD. CONCLUSION Common genetic variants are associated with eGFR decline in middle-aged adults with relatively low comorbidity burdens.
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Affiliation(s)
- Farrukh M Koraishy
- Division of Nephrology, Department of Medicine, Stony Brook University, 100 Nicolls Road, HSCT16-080E, Stony Brook, NY, USA.
| | - Frank D Mann
- Department of Family, Population, and Preventative Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, USA
| | - Pei-Fen Kuan
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA
| | - Katherine Jonas
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Xiaohua Yang
- Department of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anna Docherty
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Andrey Shabalin
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Sean Clouston
- Department of Family, Population, and Preventative Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Benjamin Luft
- Department of Medicine, Stony Brook University, Stony Brook, NY, USA
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Alaamery M, Alghamdi J, Massadeh S, Alsawaji M, Aljawini N, Albesher N, Alghamdi B, Almutairi M, Hejaili F, Alfadhel M, Baz B, Almuzzaini B, Almutairi AF, Abdullah M, Quintana FJ, Sayyari A. Analysis of chronic kidney disease patients by targeted next-generation sequencing identifies novel variants in kidney-related genes. Front Genet 2022; 13:886038. [PMID: 36035137 PMCID: PMC9407681 DOI: 10.3389/fgene.2022.886038] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 06/29/2022] [Indexed: 11/13/2022] Open
Abstract
Despite the enormous economic and societal burden of chronic kidney disease (CKD), its pathogenesis remains elusive, impeding specific diagnosis and targeted therapy. Herein, we sought to elucidate the genetic causes of end-stage renal disease (ESRD) and identify genetic variants associated with CKD and related traits in Saudi kidney disease patients. We applied a genetic testing approach using a targeted next-generation sequencing gene panel including 102 genes causative or associated with CKD. A total of 1,098 Saudi participants were recruited for the study, including 534 patients with ESRD and 564 healthy controls. The pre-validated NGS panel was utilized to screen for genetic variants, and then, statistical analysis was conducted to test for associations. The NGS panel revealed 7,225 variants in 102 sequenced genes. Cases had a significantly higher number of confirmed pathogenic variants as classified by the ClinVar database than controls (i.e., individuals with at least one allele of a confirmed pathogenic variant that is associated with CKD; 279 (0.52) vs. 258 (0.45); p-value = 0.03). A total of 13 genetic variants were found to be significantly associated with ESRD in PLCE1, CLCN5, ATP6V1B1, LAMB2, INVS, FRAS1, C5orf42, SLC12A3, COL4A6, SLC3A1, RET, WNK1, and BICC1, including four novel variants that were not previously reported in any other population. Furthermore, studies are necessary to validate these associations in a larger sample size and among individuals of different ethnic groups.
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Affiliation(s)
- Manal Alaamery
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
- Saudi Human Genome Program, National Center for Genomic Technologies and Bioinformatics, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- KACST-BWH Centre of Excellence for Biomedicine, Joint Centres of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- *Correspondence: Manal Alaamery, ; Abdullah Sayyari,
| | | | - Salam Massadeh
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
- Saudi Human Genome Program, National Center for Genomic Technologies and Bioinformatics, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- KACST-BWH Centre of Excellence for Biomedicine, Joint Centres of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | - Mona Alsawaji
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
| | - Nora Aljawini
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
- Saudi Human Genome Program, National Center for Genomic Technologies and Bioinformatics, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- KACST-BWH Centre of Excellence for Biomedicine, Joint Centres of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | - Nour Albesher
- KACST-BWH Centre of Excellence for Biomedicine, Joint Centres of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- Department of Biological Sciences, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Bader Alghamdi
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
| | - Mansour Almutairi
- Developmental Medicine Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
| | - Fayez Hejaili
- Department of Internal Medicine, Division of Nephrology, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
- King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Majid Alfadhel
- Medical Genomics Research Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
| | - Batoul Baz
- Saudi Human Genome Program, National Center for Genomic Technologies and Bioinformatics, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | - Bader Almuzzaini
- Medical Genomics Research Department, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
| | - Adel F. Almutairi
- Science and Technology Unit, King Abdullah International Medical Research Center, King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard- Health Affairs, Riyadh, Saudi Arabia
| | - Mubarak Abdullah
- Department of Medicine, Ministry of the National Guard–Health Affairs, Riyadh, Saudi Arabia
| | - Francisco J. Quintana
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Broad Institute of MIT and Harvard, Boston, MA, United States
| | - Abdullah Sayyari
- King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
- Department of Medicine, Ministry of the National Guard–Health Affairs, Riyadh, Saudi Arabia
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia
- *Correspondence: Manal Alaamery, ; Abdullah Sayyari,
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Khan A, Turchin MC, Patki A, Srinivasasainagendra V, Shang N, Nadukuru R, Jones AC, Malolepsza E, Dikilitas O, Kullo IJ, Schaid DJ, Karlson E, Ge T, Meigs JB, Smoller JW, Lange C, Crosslin DR, Jarvik GP, Bhatraju PK, Hellwege JN, Chandler P, Torvik LR, Fedotov A, Liu C, Kachulis C, Lennon N, Abul-Husn NS, Cho JH, Ionita-Laza I, Gharavi AG, Chung WK, Hripcsak G, Weng C, Nadkarni G, Irvin MR, Tiwari HK, Kenny EE, Limdi NA, Kiryluk K. Genome-wide polygenic score to predict chronic kidney disease across ancestries. Nat Med 2022; 28:1412-1420. [PMID: 35710995 PMCID: PMC9329233 DOI: 10.1038/s41591-022-01869-1] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 05/11/2022] [Indexed: 01/03/2023]
Abstract
Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.
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Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Michael C Turchin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Rajiv Nadukuru
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alana C Jones
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Ozan Dikilitas
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Daniel J Schaid
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Elizabeth Karlson
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tian Ge
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - James B Meigs
- Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Jordan W Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David R Crosslin
- Division of Biomedical Informatics and Genomics, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Pavan K Bhatraju
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jacklyn N Hellwege
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paulette Chandler
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Laura Rasmussen Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Alex Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University, New York, NY, USA
| | - Cong Liu
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | | | - Niall Lennon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Noura S Abul-Husn
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy H Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Girish Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nita A Limdi
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
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6
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Lieberman KV, Chang AR, Block GA, Robinson K, Bristow SL, Morales A, Mitchell A, McCalley S, McKay J, Pollak MR, Aradhya S, Warady BA, Pollak MR, Aradhya S, Warady BA. The KIDNEYCODE Program: Diagnostic Yield and Clinical Features of Individuals with CKD. KIDNEY360 2022; 3:900-909. [PMID: 36128480 PMCID: PMC9438426 DOI: 10.34067/kid.0004162021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 02/14/2022] [Indexed: 01/10/2023]
Abstract
Background Despite increasing recognition that CKD may have underlyi ng genetic causes, genetic testing remains limited. This study evaluated the diagnostic yield and phenotypic spectrum of CKD in individuals tested through the KIDNEYCODE sponsored genetic testing program. Methods Unrelated individuals who received panel testing (17 genes) through the KIDNEYCODE sponsored genetic testing program were included. Individuals had to meet at least one of the following eligibility criteria: eGFR ≤90 ml/min per 1.73m2 and hematuria or a family history of kidney disease; or suspected/biopsy-confirmed Alport syndrome or FSGS in tested individuals or relatives. Results Among 859 individuals, 234 (27%) had molecular diagnoses in genes associated with Alport syndrome (n=209), FSGS (n=12), polycystic kidney disease (n=6), and other disorders (n=8). Among those with positive findings in a COL4A gene, the majority were in COL4A5 (n=157, 72 hemizygous male and 85 heterozygous female individuals). A positive family history of CKD, regardless of whether clinical features were reported, was more predictive of a positive finding than was the presence of clinical features alone. For the 248 individuals who had kidney biopsies, a molecular diagnosis was returned for 49 individuals (20%). Most (n=41) individuals had a molecular diagnosis in a COL4A gene, 25 of whom had a previous Alport syndrome clinical diagnosis, and the remaining 16 had previous clinical diagnoses including FSGS (n=2), thin basement membrane disease (n=9), and hematuria (n=1). In total, 491 individuals had a previous clinical diagnosis, 148 (30%) of whom received a molecular diagnosis, the majority (89%, n=131) of which were concordant. Conclusions Although skewed to identify individuals with Alport syndrome, these findings support the need to improve access to genetic testing for patients with CKD-particularly in the context of family history of kidney disease, hematuria, and hearing loss.
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Affiliation(s)
- Kenneth V. Lieberman
- Division of Pediatric Nephrology, Joseph M. Sanzari Children's Hospital of the Hackensack Meridian Health Network, Hackensack, New Jersey
| | - Alexander R. Chang
- Division of Nephrology, Geisinger Medical Center, Danville, Pennsylvania
| | - Geoffrey A. Block
- Division of Clinical Research, Reata Pharmaceuticals, Inc., Plano, Texas
| | | | - Sara L. Bristow
- Department of Clinical Genomics, Invitae, San Francisco, California,Department of Medical Affairs, Invitae, San Francisco, California
| | - Ana Morales
- Department of Clinical Genomics, Invitae, San Francisco, California,Department of Medical Affairs, Invitae, San Francisco, California
| | - Asia Mitchell
- Department of Clinical Genomics, Invitae, San Francisco, California,Department of Medical Affairs, Invitae, San Francisco, California
| | - Stephen McCalley
- Division of Medical Affairs, Reata Pharmaceuticals, Inc., Plano, Texas
| | - Jim McKay
- Division of Medical Affairs, Reata Pharmaceuticals, Inc., Plano, Texas
| | - Martin R. Pollak
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Swaroop Aradhya
- Department of Clinical Genomics, Invitae, San Francisco, California,Department of Medical Affairs, Invitae, San Francisco, California
| | - Bradley A. Warady
- Division of Pediatric Nephrology, Children’s Mercy Kansas City, Kansas City, Missouri
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7
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Yu Z, Jin J, Tin A, Köttgen A, Yu B, Chen J, Surapaneni A, Zhou L, Ballantyne CM, Hoogeveen RC, Arking DE, Chatterjee N, Grams ME, Coresh J. Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases. J Am Soc Nephrol 2021; 32:3161-3173. [PMID: 34548389 PMCID: PMC8638405 DOI: 10.1681/asn.2020111599] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 08/29/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (eGFR). The relationship between polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. METHODS We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS ( n =765,348) and UK Biobank GWAS (90% of the cohort; n =451,508), followed by best-parameter selection using the remaining 10% of UK Biobank data ( n =45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study ( n =8866) with incident CKD, ESKD, kidney failure, and AKI. We also examined associations between the PRS and 4877 plasma proteins measured at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. RESULTS The developed PRS showed a significant association with all outcomes. Hazard ratios per 1 SD lower PRS ranged from 1.06 (95% CI, 1.01 to 1.11) to 1.33 (95% CI, 1.28 to 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin C, collagen α -1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for five proteins, including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. CONCLUSIONS A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.
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Affiliation(s)
- Zhi Yu
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts,Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Centre–University of Freiburg, Freiburg, Germany
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Jingsha Chen
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Aditya Surapaneni
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Linda Zhou
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | | | - Ron C. Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Dan E. Arking
- McKusick-Nathans Department of Genetic Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Morgan E. Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland,Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland,Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
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8
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Thio CHL, van Zon SKR, van der Most PJ, Snieder H, Bültmann U, Gansevoort RT. Associations of Genetic Factors, Educational Attainment, and Their Interaction With Kidney Function Outcomes. Am J Epidemiol 2021; 190:864-874. [PMID: 33089864 PMCID: PMC8096480 DOI: 10.1093/aje/kwaa237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 10/02/2020] [Accepted: 10/19/2020] [Indexed: 11/16/2022] Open
Abstract
Both genetic predisposition and low educational attainment (EA) are associated with higher risk of chronic kidney disease. We examined the interaction of EA and genetic risk in kidney function outcomes. We included 3,597 participants from the Prevention of Renal and Vascular End-Stage Disease Cohort Study, a longitudinal study in a community-based sample from Groningen, the Netherlands (median follow-up, 11 years; 1997–2012). Kidney function was approximated by obtaining estimated glomerular filtration rate (eGFR) from serum creatinine and cystatin C. Individual longitudinal linear eGFR trajectories were derived from linear mixed models. Genotype data on 63 single-nucleotide polymorphisms, with known associations with eGFR, were used to calculate an allele-weighted genetic score (WGS). EA was categorized into high, medium, and low. In ordinary least squares analysis, higher WGS and lower EA showed additive effects on reduced baseline eGFR; the interaction term was nonsignificant. In analysis of eGFR decline, the significant interaction term suggested amplification of genetic risk by low EA. Adjustment for known renal risk factors did not affect our results. This study presents the first evidence of gene-environment interaction between EA and a WGS for eGFR decline and provides population-level insights into the mechanisms underlying socioeconomic disparities in chronic kidney disease.
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Affiliation(s)
- Chris H L Thio
- Correspondence to Dr. Chris H. L. Thio, Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology (HPC FA40), University Medical Center Groningen, University of Groningen Hanzeplein 1, PO Box 30.001, 9700RB Groningen, the Netherlands (e-mail: )
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9
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Zhang J, Thio CHL, Gansevoort RT, Snieder H. Familial Aggregation of CKD and Heritability of Kidney Biomarkers in the General Population: The Lifelines Cohort Study. Am J Kidney Dis 2020; 77:869-878. [PMID: 33359149 DOI: 10.1053/j.ajkd.2020.11.012] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Accepted: 11/06/2020] [Indexed: 01/08/2023]
Abstract
RATIONALE & OBJECTIVE Chronic kidney disease (CKD) has a heritable component. We aimed to quantify familial aggregation of CKD in the general population and assess the extent to which kidney traits could be explained by genetic and environmental factors. STUDY DESIGN Cross-sectional 3-generation family study. SETTING & PARTICIPANTS Data were collected at entry into the Lifelines Cohort Study from a sample of the general population of the northern Netherlands, composed predominantly of individuals of European ancestry. EXPOSURE Family history of CKD. OUTCOMES The primary outcome was CKD, defined as estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2, where GFR was estimated using the CKD Epidemiology Collaboration creatinine equation. Among a subsample for which urinary albumin concentration was available (n=59,943), urinary albumin excretion was expressed as the rate of urinary albumin excretion (UAE) per 24 hours or urinary albumin-creatinine ratio (UACR). ANALYTICAL APPROACH Familial aggregation of CKD was assessed by calculating the recurrence risk ratio (RRR), using adapted Cox proportional hazards models. Heritability of continuous kidney-related traits was estimated using linear mixed models and defined as the ratio of the additive genetic variance to total phenotypic variance. All models were adjusted for age, sex, and known risk factors for kidney disease. RESULTS Among 155,911 participants with available eGFR data, the prevalence of CKD was 1.19% (1,862 cases per 155,911). The risk of CKD in those with an affected first-degree relative was 3 timeshigher than the risk in the total sample (RRR, 3.04 [95% CI, 2.26-4.09). In those with an affected spouse, risk of CKD was also higher (RRR, 1.56 [95% CI, 1.20-1.96]), indicative of shared environmental factors and/or assortative mating. Heritability estimates of eGFR, UAE, and UACR were 44%, 20%, and 18%, respectively. For serum urea, creatinine, and uric acid, estimates were 31%, 37%, and 48%, respectively, whereas estimates for serum electrolytes ranged from 22% to 28%. LIMITATIONS Use of estimated rather than measured GFR. UAE data only available in a subsample. CONCLUSIONS In this large population-based family study, a positive family history was strongly associated with increased risk of CKD. We observed moderate to high heritability of kidney traits and related biomarkers. These results indicate an important role of genetic factors in CKD risk.
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Affiliation(s)
- Jia Zhang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; Shenzhen Center for Chronic Disease Control, Shenzhen, Guangdong, China; Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, and School of Basic Medicine, Peking Union, Medical College, Beijing, China
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Ron T Gansevoort
- Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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10
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Vaisitti T, Sorbini M, Callegari M, Kalantari S, Bracciamà V, Arruga F, Vanzino SB, Rendine S, Togliatto G, Giachino D, Pelle A, Cocchi E, Benvenuta C, Baldovino S, Rollino C, Fenoglio R, Sciascia S, Tamagnone M, Vitale C, Calabrese G, Biancone L, Bussolino S, Savoldi S, Borzumati M, Cantaluppi V, Chiappero F, Ungari S, Peruzzi L, Roccatello D, Amoroso A, Deaglio S. Clinical exome sequencing is a powerful tool in the diagnostic flow of monogenic kidney diseases: an Italian experience. J Nephrol 2020; 34:1767-1781. [PMID: 33226606 PMCID: PMC8494711 DOI: 10.1007/s40620-020-00898-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 11/02/2020] [Indexed: 11/30/2022]
Abstract
Background A considerable minority of patients on waiting lists for kidney transplantation either have no diagnosis (and fall into the subset of undiagnosed cases) because kidney biopsy was not performed or histological findings were non-specific, or do not fall into any well-defined clinical category. Some of these patients might be affected by a previously unrecognised monogenic disease. Methods Through a multidisciplinary cooperative effort, we built an analytical pipeline to identify patients with chronic kidney disease (CKD) with a clinical suspicion of a monogenic condition or without a well-defined diagnosis. Following the stringent phenotypical and clinical characterization required by the flowchart, candidates meeting these criteria were further investigated by clinical exome sequencing followed by in silico analysis of 225 kidney-disease-related genes. Results By using an ad hoc web-based platform, we enrolled 160 patients from 13 different Nephrology and Genetics Units located across the Piedmont region over 15 months. A preliminary “remote” evaluation based on well-defined inclusion criteria allowed us to define eligibility for NGS analysis. Among the 138 recruited patients, 52 (37.7%) were children and 86 (62.3%) were adults. Up to 48% of them had a positive family history for kidney disease. Overall, applying this workflow led to the identification of genetic variants potentially explaining the phenotype in 78 (56.5%) cases. Conclusions These results underline the importance of clinical exome sequencing as a versatile and highly useful, non-invasive tool for genetic diagnosis of kidney diseases. Identifying patients who can benefit from targeted therapies, and improving the management of organ transplantation are further expected applications. Electronic supplementary material The online version of this article (10.1007/s40620-020-00898-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tiziana Vaisitti
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy
| | - Monica Sorbini
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy
| | - Martina Callegari
- Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Silvia Kalantari
- Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Valeria Bracciamà
- Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Francesca Arruga
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy
| | - Silvia Bruna Vanzino
- Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Sabina Rendine
- Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Gabriele Togliatto
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy
| | - Daniela Giachino
- Service of Genetic Counseling, San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy.,Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Alessandra Pelle
- Service of Genetic Counseling, San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy
| | - Enrico Cocchi
- Pediatric Nephrology Dialysis and Transplantation Unit, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Chiara Benvenuta
- Pediatric Nephrology Dialysis and Transplantation Unit, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Simone Baldovino
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.,Nephrology and Dialysis Unit (ERKnet Member)-CMID, Center of Research of Immunopathology and Rare Diseases, San Giovanni Bosco Hospital, Turin, Italy
| | - Cristiana Rollino
- Nephrology and Dialysis Unit (ERKnet Member)-CMID, Center of Research of Immunopathology and Rare Diseases, San Giovanni Bosco Hospital, Turin, Italy
| | - Roberta Fenoglio
- Nephrology and Dialysis Unit (ERKnet Member)-CMID, Center of Research of Immunopathology and Rare Diseases, San Giovanni Bosco Hospital, Turin, Italy
| | - Savino Sciascia
- Nephrology and Dialysis Unit (ERKnet Member)-CMID, Center of Research of Immunopathology and Rare Diseases, San Giovanni Bosco Hospital, Turin, Italy
| | | | - Corrado Vitale
- Nephrology and Dialysis Unit, Ordine Mauriziano di Torino, Turin, Italy
| | | | - Luigi Biancone
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy.,Renal Transplantation Unit 'A. Vercellone,' Division of Nephrology Dialysis and Transplantation, Città della Salute e della Scienza University Hospital, Turin, Italy
| | | | | | - Maurizio Borzumati
- Nephrology and Dialysis Unit of Verbania ASL VCO, Verbano Cusio Ossola, Verbania, Italy
| | - Vincenzo Cantaluppi
- Nephrology and Kidney Transplantation Unit, Maggiore Della Carità University Hospital, Novara, Italy
| | | | - Silvana Ungari
- Struttura Semplice Genetics and Molecular Biology, ASL CN1, Cuneo, Italy
| | - Licia Peruzzi
- Pediatric Nephrology Dialysis and Transplantation Unit, Città della Salute e della Scienza University Hospital, Turin, Italy
| | - Dario Roccatello
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.,Nephrology and Dialysis Unit (ERKnet Member)-CMID, Center of Research of Immunopathology and Rare Diseases, San Giovanni Bosco Hospital, Turin, Italy
| | - Antonio Amoroso
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy. .,Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy.
| | - Silvia Deaglio
- Department of Medical Sciences, University of Turin, via Santena 19, 10126, Turin, Italy.,Immunogenetics and Transplant Biology Service, Città della Salute e della Scienza University Hospital, Turin, Italy
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11
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Fazzini F, Lamina C, Raschenberger J, Schultheiss UT, Kotsis F, Schönherr S, Weissensteiner H, Forer L, Steinbrenner I, Meiselbach H, Bärthlein B, Wanner C, Eckardt KU, Köttgen A, Kronenberg F. Results from the German Chronic Kidney Disease (GCKD) study support association of relative telomere length with mortality in a large cohort of patients with moderate chronic kidney disease. Kidney Int 2020; 98:488-497. [PMID: 32641227 DOI: 10.1016/j.kint.2020.02.034] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 02/12/2020] [Accepted: 02/20/2020] [Indexed: 02/08/2023]
Abstract
Telomere length is known to be inversely associated with aging and has been proposed as a marker for aging-related diseases. Telomere attrition can be accelerated by oxidative stress and inflammation, both commonly present in patients with chronic kidney disease. Here, we investigated whether relative telomere length is associated with mortality in a large cohort of patients with chronic kidney disease stage G3 and A1-3 or G1-2 with overt proteinuria (A3) at enrollment. Relative telomere length was quantified in peripheral blood by a quantitative PCR method in 4,955 patients from the GCKD study, an ongoing prospective observational cohort. Complete four-year follow-up was available from 4,926 patients in whom we recorded 354 deaths. Relative telomere length was a strong and independent predictor of all-cause mortality. Each decrease of 0.1 relative telomere length unit was highly associated with a 14% increased risk of death (hazard ratio1.14 [95% confidence interval 1.06-1.22]) in a model adjusted for age, sex, baseline eGFR, urine albumin/creatinine ratio, diabetes mellitus, prevalent cardiovascular disease, LDL-cholesterol, HDL-cholesterol, smoking, body mass index, systolic and diastolic blood pressure, C-reactive protein and serum albumin. This translated to a 75% higher risk for those in the lowest compared to the highest quartile of relative telomere length. The association was mainly driven by 117 cardiovascular deaths (1.20 [1.05-1.35]) as well as 67 deaths due to infections (1.27 [1.07-1.50]). Thus, our findings support an association of shorter telomere length with all-cause mortality, cardiovascular mortality and death due to infections in patients with moderate chronic kidney disease.
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Affiliation(s)
- Federica Fazzini
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Julia Raschenberger
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Renal Division, Department of Medicine IV, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany; Renal Division, Department of Medicine IV, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Hansi Weissensteiner
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Heike Meiselbach
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Barbara Bärthlein
- Medical Centre for Information and Communication Technology (MIK), University Hospital Erlangen, Erlangen, Germany
| | - Christoph Wanner
- Division of Nephrology, Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria.
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12
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Cañadas-Garre M, Anderson K, Cappa R, Skelly R, Smyth LJ, McKnight AJ, Maxwell AP. Genetic Susceptibility to Chronic Kidney Disease - Some More Pieces for the Heritability Puzzle. Front Genet 2019; 10:453. [PMID: 31214239 PMCID: PMC6554557 DOI: 10.3389/fgene.2019.00453] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 04/30/2019] [Indexed: 12/12/2022] Open
Abstract
Chronic kidney disease (CKD) is a major global health problem with an increasing prevalence partly driven by aging population structure. Both genomic and environmental factors contribute to this complex heterogeneous disease. CKD heritability is estimated to be high (30-75%). Genome-wide association studies (GWAS) and GWAS meta-analyses have identified several genetic loci associated with CKD, including variants in UMOD, SHROOM3, solute carriers, and E3 ubiquitin ligases. However, these genetic markers do not account for all the susceptibility to CKD, and the causal pathways remain incompletely understood; other factors must be contributing to the missing heritability. Less investigated biological factors such as telomere length; mitochondrial proteins, encoded by nuclear genes or specific mitochondrial DNA (mtDNA) encoded genes; structural variants, such as copy number variants (CNVs), insertions, deletions, inversions and translocations are poorly covered and may explain some of the missing heritability. The sex chromosomes, often excluded from GWAS studies, may also help explain gender imbalances in CKD. In this review, we outline recent findings on molecular biomarkers for CKD (telomeres, CNVs, mtDNA variants, sex chromosomes) that typically have received less attention than gene polymorphisms. Shorter telomere length has been associated with renal dysfunction and CKD progression, however, most publications report small numbers of subjects with conflicting findings. CNVs have been linked to congenital anomalies of the kidney and urinary tract, posterior urethral valves, nephronophthisis and immunoglobulin A nephropathy. Information on mtDNA biomarkers for CKD comes primarily from case reports, therefore the data are scarce and diverse. The most consistent finding is the A3243G mutation in the MT-TL1 gene, mainly associated with focal segmental glomerulosclerosis. Only one GWAS has found associations between X-chromosome and renal function (rs12845465 and rs5987107). No loci in the Y-chromosome have reached genome-wide significance. In conclusion, despite the efforts to find the genetic basis of CKD, it remains challenging to explain all of the heritability with currently available methods and datasets. Although additional biomarkers have been investigated in less common suspects such as telomeres, CNVs, mtDNA and sex chromosomes, hidden heritability in CKD remains elusive, and more comprehensive approaches, particularly through the integration of multiple -"omics" data, are needed.
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Affiliation(s)
- Marisa Cañadas-Garre
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
| | - Kerry Anderson
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
| | - Ruaidhri Cappa
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
| | - Ryan Skelly
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
| | - Laura Jane Smyth
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
| | - Amy Jayne McKnight
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
| | - Alexander Peter Maxwell
- Epidemiology and Public Health Research Group, Centre for Public Health, Queen’s University of Belfast, Belfast, United Kingdom
- Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom
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13
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Cañadas-Garre M, Anderson K, McGoldrick J, Maxwell AP, McKnight AJ. Genomic approaches in the search for molecular biomarkers in chronic kidney disease. J Transl Med 2018; 16:292. [PMID: 30359254 PMCID: PMC6203198 DOI: 10.1186/s12967-018-1664-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 10/14/2018] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is recognised as a global public health problem, more prevalent in older persons and associated with multiple co-morbidities. Diabetes mellitus and hypertension are common aetiologies for CKD, but IgA glomerulonephritis, membranous glomerulonephritis, lupus nephritis and autosomal dominant polycystic kidney disease are also common causes of CKD. MAIN BODY Conventional biomarkers for CKD involving the use of estimated glomerular filtration rate (eGFR) derived from four variables (serum creatinine, age, gender and ethnicity) are recommended by clinical guidelines for the evaluation, classification, and stratification of CKD. However, these clinical biomarkers present some limitations, especially for early stages of CKD, elderly individuals, extreme body mass index values (serum creatinine), or are influenced by inflammation, steroid treatment and thyroid dysfunction (serum cystatin C). There is therefore a need to identify additional non-invasive biomarkers that are useful in clinical practice to help improve CKD diagnosis, inform prognosis and guide therapeutic management. CONCLUSION CKD is a multifactorial disease with associated genetic and environmental risk factors. Hence, many studies have employed genetic, epigenetic and transcriptomic approaches to identify biomarkers for kidney disease. In this review, we have summarised the most important studies in humans investigating genomic biomarkers for CKD in the last decade. Several genes, including UMOD, SHROOM3 and ELMO1 have been strongly associated with renal diseases, and some of their traits, such as eGFR and serum creatinine. The role of epigenetic and transcriptomic biomarkers in CKD and related diseases is still unclear. The combination of multiple biomarkers into classifiers, including genomic, and/or epigenomic, may give a more complete picture of kidney diseases.
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Affiliation(s)
- M. Cañadas-Garre
- Epidemiology and Public Health Research Group, Centre for Public Health, Belfast City Hospital, Queen’s University of Belfast, c/o University Floor, Level A, Tower Block, Lisburn Road, Belfast, BT9 7AB Northern Ireland UK
| | - K. Anderson
- Epidemiology and Public Health Research Group, Centre for Public Health, Belfast City Hospital, Queen’s University of Belfast, c/o University Floor, Level A, Tower Block, Lisburn Road, Belfast, BT9 7AB Northern Ireland UK
| | - J. McGoldrick
- Epidemiology and Public Health Research Group, Centre for Public Health, Belfast City Hospital, Queen’s University of Belfast, c/o University Floor, Level A, Tower Block, Lisburn Road, Belfast, BT9 7AB Northern Ireland UK
| | - A. P. Maxwell
- Epidemiology and Public Health Research Group, Centre for Public Health, Belfast City Hospital, Queen’s University of Belfast, c/o University Floor, Level A, Tower Block, Lisburn Road, Belfast, BT9 7AB Northern Ireland UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast, UK
| | - A. J. McKnight
- Epidemiology and Public Health Research Group, Centre for Public Health, Belfast City Hospital, Queen’s University of Belfast, c/o University Floor, Level A, Tower Block, Lisburn Road, Belfast, BT9 7AB Northern Ireland UK
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14
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Wuttke M, Wong CS, Wühl E, Epting D, Luo L, Hoppmann A, Doyon A, Li Y, Sözeri B, Thurn D, Helmstädter M, Huber TB, Blydt-Hansen TD, Kramer-Zucker A, Mehls O, Melk A, Querfeld U, Furth SL, Warady BA, Schaefer F, Köttgen A. Genetic loci associated with renal function measures and chronic kidney disease in children: the Pediatric Investigation for Genetic Factors Linked with Renal Progression Consortium. Nephrol Dial Transplant 2016; 31:262-9. [PMID: 26420894 PMCID: PMC4829056 DOI: 10.1093/ndt/gfv342] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2015] [Accepted: 08/26/2015] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) in children is characterized by rapid progression and a high incidence of end-stage renal disease and therefore constitutes an important health problem. While unbiased genetic screens have identified common risk variants influencing renal function and CKD in adults, the presence and identity of such variants in pediatric CKD are unknown. METHODS The international Pediatric Investigation for Genetic Factors Linked with Renal Progression (PediGFR) Consortium comprises three pediatric CKD cohorts: Chronic Kidney Disease in Children (CKiD), Effect of Strict Blood Pressure Control and ACE Inhibition on the Progression of CRF in Pediatric Patients (ESCAPE) and Cardiovascular Comorbidity in Children with CKD (4C). Clean genotype data from > 10 million genotyped or imputed single-nucleotide polymorphisms (SNPs) were available for 1136 patients with measurements of serum creatinine at study enrollment. Genome-wide association studies were conducted to relate the SNPs to creatinine-based estimated glomerular filtration rate (eGFR crea) and proteinuria (urinary albumin- or protein-to-creatinine ratio ≥ 300 and ≥ 500 mg/g, respectively). In addition, European-ancestry PediGFR patients (cases) were compared with 1347 European-ancestry children without kidney disease (controls) to identify genetic variants associated with the presence of CKD. RESULTS SNPs with suggestive association P-values < 1 × 10(-5) were identified in 10 regions for eGFR crea, four regions for proteinuria and six regions for CKD including some plausible biological candidates. No SNP was associated at genome-wide significance (P < 5 × 10(-8)). Investigation of the candidate genes for proteinuria in adults from the general population provided support for a region on chromosome 15 near RSL24D1/UNC13C/RAB27A. Conversely, targeted investigation of genes harboring GFR-associated variants in adults from the general population did not reveal significantly associated SNPs in children with CKD. CONCLUSIONS Our findings suggest that larger collaborative efforts will be needed to draw reliable conclusions about the presence and identity of common variants associated with eGFR, proteinuria and CKD in pediatric populations.
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Affiliation(s)
- Matthias Wuttke
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Craig S. Wong
- Division of Pediatric Nephrology, University of New Mexico Children's Hospital, Albuquerque, NM, USA
| | - Elke Wühl
- Division of Pediatric Nephrology, University Medical Center Heidelberg, Heidelberg, Germany
| | - Daniel Epting
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Li Luo
- Division of Epidemiology, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Anselm Hoppmann
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Anke Doyon
- Division of Pediatric Nephrology, University Medical Center Heidelberg, Heidelberg, Germany
| | - Yong Li
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - CKDGen Consortium
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
- Division of Pediatric Nephrology, University of New Mexico Children's Hospital, Albuquerque, NM, USA
- Division of Pediatric Nephrology, University Medical Center Heidelberg, Heidelberg, Germany
- Division of Epidemiology, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
- Faculty of Medicine, Ege University, Izmir, Turkey
- Department of Pediatric Nephrology, Hannover Medical School, Hannover, Germany
- University of Manitoba, Winnipeg, Manitoba, Canada
- Charite Universitätsmedizin Berlin, Berlin, Germany
- Departments of Pediatrics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Childrens Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Pediatric Nephrology, Children's Mercy Hospital, Kansas City, MO, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Betül Sözeri
- Faculty of Medicine, Ege University, Izmir, Turkey
| | - Daniela Thurn
- Department of Pediatric Nephrology, Hannover Medical School, Hannover, Germany
| | - Martin Helmstädter
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Tobias B. Huber
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | | | - Albrecht Kramer-Zucker
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Otto Mehls
- Division of Pediatric Nephrology, University Medical Center Heidelberg, Heidelberg, Germany
| | - Anette Melk
- Department of Pediatric Nephrology, Hannover Medical School, Hannover, Germany
| | - Uwe Querfeld
- Charite Universitätsmedizin Berlin, Berlin, Germany
| | - Susan L. Furth
- Departments of Pediatrics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Childrens Hospital of Philadelphia, Philadelphia, PA, USA
| | - Bradley A. Warady
- Division of Pediatric Nephrology, Children's Mercy Hospital, Kansas City, MO, USA
| | - Franz Schaefer
- Division of Pediatric Nephrology, University Medical Center Heidelberg, Heidelberg, Germany
| | - Anna Köttgen
- Renal Division, Department of Internal Medicine, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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15
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Moore DJ, Gregory JM, Kumah-Crystal YA, Simmons JH. Mitigating micro-and macro-vascular complications of diabetes beginning in adolescence. Vasc Health Risk Manag 2009; 5:1015-31. [PMID: 19997571 PMCID: PMC2788594 DOI: 10.2147/vhrm.s4891] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2009] [Indexed: 01/26/2023] Open
Abstract
Diabetes is a chronic disorder, which manifests when insulin levels or resistance to insulin action becomes insufficient to control systemic glucose levels. Although the number of available agents to manage diabetes continues to expand rapidly, the maintenance of euglycemia by individuals with diabetes remains a substantial challenge. Unfortunately, many patients with type 1 and type 2 diabetes will ultimately experience diabetes complications. These complications result from the toxic effects of chronic hyperglycemia combined with other metabolic derangements that afflict persons with diabetes. This review will present a comprehensive look at the complications of diabetes, the risk factors for their progression, the mechanistic basis for their development, and the clinical approach to screening for, preventing, and treating these sequelae. In addition, since diabetes is commonly diagnosed in childhood, we will provide a special focus on the care of the adolescent patient.
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Affiliation(s)
- Daniel J Moore
- Department of Pediatrics, Division of Endocrinology and Diabetes, Vanderbilt Children's Hospital, Nashville, TN 37232-9170, USA
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16
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McKnight AJ, O'Donoghue D, Peter Maxwell A. Annotated chromosome maps for renal disease. Hum Mutat 2009; 30:314-20. [PMID: 19085929 DOI: 10.1002/humu.20885] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
A combination of linkage analyses and association studies are currently employed to promote the identification of genetic factors contributing to inherited renal disease. We have standardized and merged complex genetic data from disparate sources, creating unique chromosomal maps to enhance genetic epidemiological investigations. This database and novel renal maps effectively summarize genomic regions of suggested linkage, association, or chromosomal abnormalities implicated in renal disease. Chromosomal regions associated with potential intermediate clinical phenotypes have been integrated, adding support for particular genomic intervals. More than 500 reports from medical databases, published scientific literature, and the World Wide Web were interrogated for relevant renal-related information. Chromosomal regions highlighted for prioritized investigation of renal complications include 3q13-26, 6q22-27, 10p11-15, 16p11-13, and 18q22. Combined genetic and physical maps are effective tools to organize genetic data for complex diseases. These renal chromosome maps provide insights into renal phenotype-genotype relationships and act as a template for future genetic investigations into complex renal diseases. New data from individual researchers and/or future publications can be readily incorporated to this resource via a user-friendly web-form accessed from the website: www.qub.ac.uk/neph-res/CORGI/index.php.
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Affiliation(s)
- Amy Jayne McKnight
- Nephrology Research Group, Queen's University of Belfast, United Kingdom.
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17
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Ommen ES, Winston JA, Murphy B. Medical Risks in Living Kidney Donors: Absence of Proof Is Not Proof of Absence. Clin J Am Soc Nephrol 2006; 1:885-95. [PMID: 17699301 DOI: 10.2215/cjn.00840306] [Citation(s) in RCA: 75] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Living-kidney donation has become increasingly widespread, yet there has been little critical analysis of existing studies of long-term medical outcomes in living donors. This review analyzes issues in study design that affect the quality of the evidence and summarizes possible risk factors in living donors. Virtually all studies of long-term outcomes in donors are retrospective, many with large losses to follow-up, and therefore are subject to selection bias. Most studies have small sample sizes and are underpowered to detect clinically meaningful differences between donors and comparison groups. Many studies compare donors with the general population, but donors are screened to be healthier than the general population and this may not be a valid comparison group. Difficulties in measurement of BP and renal function may underestimate the impact of donation on these outcomes. Several studies have identified possible risk factors for development of hypertension, proteinuria, and ESRD, but potential vulnerability factors in donors have not been well explored and there is a paucity of data on cardiovascular risk factors in donors. Prospective registration of living kidney donors and prospective studies of diverse populations of donors are essential to protect living donors and preserve living-kidney donation.
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Affiliation(s)
- Elizabeth S Ommen
- Mount Sinai Medical Center, Division of Nephrology, 1 Gustave Levy Place, Box 1243, New York, NY 10029, USA.
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