1
|
Wang SH, Huang YC, Cheng CW, Chang YW, Liao WL. Impact of the trans-ancestry polygenic risk score on type 2 diabetes risk, onset age and progression among population in Taiwan. Am J Physiol Endocrinol Metab 2024; 326:E547-E554. [PMID: 38363735 DOI: 10.1152/ajpendo.00252.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 02/18/2024]
Abstract
Type 2 diabetes (T2D) prevalence in adults at a younger age has increased but the disease status may go unnoticed. This study aimed to determine whether the onset age and subsequent diabetic complications can be attributed to the polygenic architecture of T2D in the Taiwan Han population. A total of 9,627 cases with T2D and 85,606 controls from the Taiwan Biobank were enrolled. Three diabetic polygenic risk scores (PRSs), PRS_EAS and PRS_EUR, and a trans-ancestry PRS (PRS_META), calculated using summary statistic from East Asian and European populations. The onset age was identified by linking to the National Taiwan Insurance Research Database, and the incidence of different diabetic complications during follow-up was recorded. PRS_META (7.4%) explained a higher variation for T2D status. And the higher percentile of PRS is also correlated with higher percentage of T2D family history and prediabetes status. More, the PRS was negatively associated with onset age (β = -0.91 yr), and this was more evident among males (β = -1.11 vs. -0.76 for males and females, respectively). The hazard ratio of diabetic retinopathy (DR) and diabetic foot were significantly associated with PRS_EAS and PRS_META, respectively. However, the PRS was not associated with other diabetic complications, including diabetic nephropathy, cardiovascular disease, and hypertension. Our findings indicated that diabetic PRS which combined susceptibility variants from cross-population could be used as a tool for early screening of T2D, especially for high-risk populations, such as individuals with high genetic risk, and may be associated with the risk of complications in subjects with T2D. NEW & NOTEWORTHY Our findings indicated that diabetic polygenic risk score (PRS) which combined susceptibility variants from Asian and European population affect the onset age of type 2 diabetes (T2D) and could be used as a tool for early screening of T2D, especially for individuals with high genetic risk, and may be associated with the risk of diabetic complications among people in Taiwan.
Collapse
Affiliation(s)
- Shi-Heng Wang
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, Zhunan, Taiwan
- Department of Public Health, China Medical University, Taichung, Taiwan
| | - Yu-Chuen Huang
- School of Chinese Medicine, China Medical University, Taichung, Taiwan
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chun-Wen Cheng
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
- Clinical Laboratory, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Ya-Wen Chang
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan
- Center for Personalized Medicine, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Wen-Ling Liao
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan
- Center for Personalized Medicine, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| |
Collapse
|
2
|
Ali AS, Pham C, Morahan G, Ekinci EI. Genetic Risk Scores Identify People at High Risk of Developing Diabetic Kidney Disease: A Systematic Review. J Clin Endocrinol Metab 2024; 109:1189-1197. [PMID: 38039081 PMCID: PMC11031242 DOI: 10.1210/clinem/dgad704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 11/20/2023] [Accepted: 11/29/2023] [Indexed: 12/03/2023]
Abstract
CONTEXT Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Measures to prevent and treat DKD require better identification of patients most at risk. In this systematic review, we summarize the existing evidence of genetic risk scores (GRSs) and their utility for predicting DKD in people with type 1 or type 2 diabetes. EVIDENCE ACQUISITION We searched MEDLINE, Embase, Web of Science, and Cochrane Reviews in June 2022 to identify all existing and relevant literature. Main data items sought were study design, sample size, population, single nucleotide polymorphisms of interest, DKD-related outcomes, and relevant summary measures of result. The Critical Appraisal Skills Programme checklist was used to evaluate the methodological quality of studies. EVIDENCE SYNTHESIS We identified 400 citations of which 15 are included in this review. Overall, 7 studies had positive results, 5 had mixed results, and 3 had negative results. Most studies with the strongest methodological quality (n = 9) reported statistically significant and favourable findings of a GRS's association with at least 1 measure of DKD. CONCLUSION This systematic review presents evidence of the utility of GRSs to identify people with diabetes that are at high risk of developing DKD. In practice, a robust GRS could be used at the first clinical encounter with a person living with diabetes in order to stratify their risk of complications. Further prospective research is needed.
Collapse
Affiliation(s)
- Aleena Shujaat Ali
- Department of Medicine, The University of Melbourne, Melbourne 3084, Australia
- Australian Centre for Accelerating Diabetes Innovations, The University of Melbourne, Melbourne 3000, Australia
| | - Cecilia Pham
- Department of Medicine, The University of Melbourne, Melbourne 3084, Australia
- Australian Centre for Accelerating Diabetes Innovations, The University of Melbourne, Melbourne 3000, Australia
| | - Grant Morahan
- Australian Centre for Accelerating Diabetes Innovations, The University of Melbourne, Melbourne 3000, Australia
- Diabetes Research Foundation, The University of Western Australia, Perth 6009, Australia
| | - Elif Ilhan Ekinci
- Department of Medicine, The University of Melbourne, Melbourne 3084, Australia
- Australian Centre for Accelerating Diabetes Innovations, The University of Melbourne, Melbourne 3000, Australia
- Department of Endocrinology, Austin Health, Melbourne 3084, Australia
| |
Collapse
|
3
|
Kim NY, Lee H, Kim S, Kim YJ, Lee H, Lee J, Kwak SH, Lee S. The clinical relevance of a polygenic risk score for type 2 diabetes mellitus in the Korean population. Sci Rep 2024; 14:5749. [PMID: 38459065 PMCID: PMC10923897 DOI: 10.1038/s41598-024-55313-0] [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: 05/30/2023] [Accepted: 02/22/2024] [Indexed: 03/10/2024] Open
Abstract
The clinical utility of a type 2 diabetes mellitus (T2DM) polygenic risk score (PRS) in the East Asian population remains underexplored. We aimed to examine the potential prognostic value of a T2DM PRS and assess its viability as a clinical instrument. We first established a T2DM PRS for 5490 Korean individuals using East Asian Biobank data (269,487 samples). Subsequently, we assessed the predictive capability of this T2DM PRS in a prospective longitudinal study with baseline data and data from seven additional follow-ups. Our analysis showed that the T2DM PRS could predict the transition of glucose tolerance stages from normal glucose tolerance to prediabetes and from prediabetes to T2DM. Moreover, T2DM patients in the top-decile PRS group were more likely to be treated with insulin (hazard ratio = 1.69, p value = 2.31E-02) than were those in the remaining PRS groups. T2DM PRS values were significantly high in the severe diabetes subgroup, characterized by insulin resistance and β -cell dysfunction (p value = 0.0012). The prediction models with the T2DM PRS had significantly greater Harrel's C-indices than did corresponding models without it. By utilizing prospective longitudinal study data and extensive clinical risk factor information, our analysis provides valuable insights into the multifaceted clinical utility of the T2DM PRS.
Collapse
Affiliation(s)
- Na Yeon Kim
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Haekyung Lee
- Division of Nephrology, Department of Internal Medicine, Soonchunhyang University Seoul Hospital, Seoul, South Korea
| | - Sehee Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, Seoul, South Korea
| | - Ye-Jee Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, Seoul, South Korea
| | - Hyunsuk Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Translational Medicine, Seoul National University College of Medicine, Seoul, Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University College of Medicine, Seoul, South Korea
| | - Junhyeong Lee
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul, South Korea.
| |
Collapse
|
4
|
Yu G, Tam HCH, Huang C, Shi M, Lim CKP, Chan JCN, Ma RCW. Lessons and Applications of Omics Research in Diabetes Epidemiology. Curr Diab Rep 2024; 24:27-44. [PMID: 38294727 PMCID: PMC10874344 DOI: 10.1007/s11892-024-01533-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/04/2024] [Indexed: 02/01/2024]
Abstract
PURPOSE OF REVIEW Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies. RECENT FINDINGS We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.
Collapse
Affiliation(s)
- Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Henry C H Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Mai Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
| |
Collapse
|
5
|
Lanktree MB, Kline T, Pei Y. Assessing the Risk of Progression to Kidney Failure in Patients With Autosomal Dominant Polycystic Kidney Disease. ADVANCES IN KIDNEY DISEASE AND HEALTH 2023; 30:407-416. [PMID: 38097331 DOI: 10.1053/j.akdh.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 06/07/2023] [Accepted: 06/09/2023] [Indexed: 12/18/2023]
Abstract
While autosomal dominant polycystic kidney disease (ADPKD) is a dichotomous diagnosis, substantial variability in disease severity exists. Identification of inherited risk through family history, genetic testing, and environmental risk factors through clinical assessment are important components of risk assessment for optimal management of patients with ADPKD. Genetic testing is especially helpful in cases with diagnostic uncertainty, particularly in cases with no apparent family history, in young cases (age less than 25 years) where a definitive diagnosis is sought, or in atypical presentations with early, severe, or discordant findings. Currently, risk assessment in ADPKD may be performed with the use of age-adjusted estimated glomerular filtration rate thresholds, evidence of rapid estimated glomerular filtration rate decline on serial measurements, age- and height-adjusted total kidney volume by Mayo Clinic Imaging Classification, or evidence of early hypertension and urological complications combined with PKD1 or PKD2 mutation class; however, caveats exist with each of these approaches. Fine-tuning of risk stratification with advanced imaging features and biomarkers is the subject of research but is not yet ready for general clinical practice. While conservative treatment strategies will be advised for all patients, those with the greatest rate of disease progression will have the most benefit from aggressive disease-modifying therapy. In this narrative review, we will summarize the evidence behind the clinical assessment and risk stratification of patients with ADPKD.
Collapse
Affiliation(s)
- Matthew B Lanktree
- Division of Nephrology, Department of Medicine, St Joseph's Healthcare Hamilton, McMaster University, Hamilton, Ontario, Canada; Population Health Research Institute, Hamilton, Ontario, Canada
| | - Timothy Kline
- Mayo Clinic, Department of Radiology and Division of Nephrology and Hypertension, Rochester, MN
| | - York Pei
- Division of Nephrology, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada.
| |
Collapse
|
6
|
Klen J, Dolžan V. SGLT2 Inhibitors in the Treatment of Diabetic Kidney Disease: More than Just Glucose Regulation. Pharmaceutics 2023; 15:1995. [PMID: 37514181 PMCID: PMC10386344 DOI: 10.3390/pharmaceutics15071995] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 06/30/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Diabetic kidney disease (DKD) is a severe and common complication and affects a quarter of patients with type 2 diabetes mellitus (T2DM). Oxidative stress and inflammation related to hyperglycemia are interlinked and contribute to the occurrence of DKD. It was shown that sodium-glucose cotransporter-2 (SGLT2) inhibitors, a novel yet already widely used therapy, may prevent the development of DKD and alter its natural progression. SGLT2 inhibitors induce systemic and glomerular hemodynamic changes, provide metabolic advantages, and reduce inflammatory and oxidative stress pathways. In T2DM patients, regardless of cardiovascular diseases, SGLT2 inhibitors may reduce albuminuria, progression of DKD, and doubling of serum creatinine levels, thus lowering the need for kidney replacement therapy by over 40%. The molecular mechanisms behind these beneficial effects of SGLT2 inhibitors extend beyond their glucose-lowering effects. The emerging studies are trying to explain these mechanisms at the genetic, epigenetic, transcriptomic, and proteomic levels.
Collapse
Affiliation(s)
- Jasna Klen
- Division of Surgery, Department of Abdominal Surgery, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia
- Department of Internal Medicine, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Vita Dolžan
- Pharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| |
Collapse
|
7
|
Cañadas-Garre M, Kunzmann AT, Anderson K, Brennan EP, Doyle R, Patterson CC, Godson C, Maxwell AP, McKnight AJ. Albuminuria-Related Genetic Biomarkers: Replication and Predictive Evaluation in Individuals with and without Diabetes from the UK Biobank. Int J Mol Sci 2023; 24:11209. [PMID: 37446387 PMCID: PMC10342310 DOI: 10.3390/ijms241311209] [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: 05/31/2023] [Revised: 06/26/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
Increased albuminuria indicates underlying glomerular pathology and is associated with worse renal disease outcomes, especially in diabetic kidney disease. Many single nucleotide polymorphisms (SNPs), associated with albuminuria, could be potentially useful to construct polygenic risk scores (PRSs) for kidney disease. We investigated the diagnostic accuracy of SNPs, previously associated with albuminuria-related traits, on albuminuria and renal injury in the UK Biobank population, with a particular interest in diabetes. Multivariable logistic regression was used to evaluate the influence of 91 SNPs on urine albumin-to-creatinine ratio (UACR)-related traits and kidney damage (any pathology indicating renal injury), stratifying by diabetes. Weighted PRSs for microalbuminuria and UACR from previous studies were used to calculate the area under the receiver operating characteristic curve (AUROC). CUBN-rs1801239 and DDR1-rs116772905 were associated with all the UACR-derived phenotypes, in both the overall and non-diabetic cohorts, but not with kidney damage. Several SNPs demonstrated different effects in individuals with diabetes compared to those without. SNPs did not improve the AUROC over currently used clinical variables. Many SNPs are associated with UACR or renal injury, suggesting a role in kidney dysfunction, dependent on the presence of diabetes in some cases. However, individual SNPs or PRSs did not improve the diagnostic accuracy for albuminuria or renal injury compared to standard clinical variables.
Collapse
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, GENYO, Centre for Genomics and Oncological Research, Pfizer-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), Avenida de Madrid, 15, 18012 Granada, Spain
| | - Andrew T. Kunzmann
- Cancer Epidemiology Research Group, Centre for Public Health, Queen’s University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast BT12 6BA, UK
| | - Kerry Anderson
- 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, D04 V1W8 Dublin, Ireland
| | - Ross Doyle
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, D04 V1W8 Dublin, Ireland
- School of Medicine, University College Dublin, Health Sciences Centre, Belfield, D04 V1W8 Dublin, Ireland
- Mater Misericordiae University Hospital, Eccles St., D07 R2WY Dublin, Ireland
| | - Christopher C. Patterson
- 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
| | - Catherine Godson
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, D04 V1W8 Dublin, Ireland
- School of Medicine, University College Dublin, Health Sciences Centre, Belfield, D04 V1W8 Dublin, 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, Level 11, Belfast City Hospital, Lisburn 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
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
Shojima N, Yamauchi T. Progress in genetics of type 2 diabetes and diabetic complications. J Diabetes Investig 2023; 14:503-515. [PMID: 36639962 PMCID: PMC10034958 DOI: 10.1111/jdi.13970] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/12/2022] [Accepted: 12/15/2022] [Indexed: 01/15/2023] Open
Abstract
Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
Collapse
Affiliation(s)
- Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| |
Collapse
|
10
|
Liao LN, Li TC, Yeh CC, Li CI, Liu CS, Yang CW, Yang YF, Lin CH, Tsai FJ, Lin CC. Risk prediction of nephropathy by integrating clinical and genetic information among adult patients with type 2 diabetes. Acta Diabetol 2023; 60:413-424. [PMID: 36576562 DOI: 10.1007/s00592-022-02017-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 12/10/2022] [Indexed: 12/29/2022]
Abstract
AIMS Diabetic nephropathy (DN) is a major healthcare challenge. We developed and internally and externally validated a risk prediction model of DN by integrating clinical factors and SNPs from genes of multiple CKD-related pathways in the Han Chinese population. MATERIALS AND METHODS A total of 1526 patients with type 2 diabetes were randomly allocated into derivation (n = 1019) or validation (n = 507) sets. External validation was performed with 3899 participants from the Taiwan Biobank. We selected 66 SNPs identified from literature review for building our weighted genetic risk score (wGRS). The steps for prediction model development integrating clinical and genetic information were based on the Framingham Heart Study. RESULTS The AUROC (95% CI) for this DN prediction model with combined clinical factors and wGRS was 0.81 (0.78, 0.84) in the derivation set. Furthermore, by directly using the information of these 66 SNPs, our final prediction model had AUROC values of 0.85 (0.82, 0.87), 0.89 (0.86, 0.91), and 0.77 (0.74, 0.80) in the derivation, internal validation, and external validation sets, respectively. Under the combined model, the results with a cutoff point of 30% showed 70.91% sensitivity, 67.84% specificity, 51.54% positive predictive value, and 82.86% negative predictive value. CONCLUSIONS We developed and internally and externally validated a model with clinical factors and SNPs from genes of multiple CKD-related pathways to predict DN in Taiwan. This model can be used in clinical risk management practice as a screening tool to identify persons who are genetically predisposed to DN for early intervention and prevention.
Collapse
Affiliation(s)
- Li-Na Liao
- Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan, R.O.C
| | - Tsai-Chung Li
- Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan, R.O.C
- Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung, Taiwan, R.O.C
| | - Chih-Ching Yeh
- Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan, R.O.C
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan, R.O.C
- Master Program in Applied Epidemiology, College of Public Health, Taipei Medical University, Taipei, Taiwan, R.O.C
| | - Chia-Ing Li
- Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, R.O.C
- School of Medicine, College of Medicine, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung, 406040, Taiwan, R.O.C
| | - Chiu-Shong Liu
- School of Medicine, College of Medicine, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung, 406040, Taiwan, R.O.C
- Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan, R.O.C
| | - Chuan-Wei Yang
- Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, R.O.C
| | - Ya-Fei Yang
- Department of Nephrology, Everan Hospital, Taichung, Taiwan, R.O.C
| | - Chih-Hsueh Lin
- School of Medicine, College of Medicine, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung, 406040, Taiwan, R.O.C
- Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan, R.O.C
| | - Fuu-Jen Tsai
- School of Chinese Medicine, College of Chinese Medicine, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung, 406040, Taiwan, R.O.C..
- Human Genetic Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, R.O.C..
| | - Cheng-Chieh Lin
- Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, R.O.C..
- School of Medicine, College of Medicine, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung, 406040, Taiwan, R.O.C..
- Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan, R.O.C..
| |
Collapse
|
11
|
Cook TW, Wilstermann AM, Mitchell JT, Arnold NE, Rajasekaran S, Bupp CP, Prokop JW. Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics. Biomolecules 2023; 13:257. [PMID: 36830626 PMCID: PMC9953665 DOI: 10.3390/biom13020257] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 01/31/2023] Open
Abstract
Insulin is amongst the human genome's most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (INS) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The INS gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the INS transcripts that might influence the readthrough fusion transcript INS-IGF2. This INS-IGF2 transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS-IGF2 results in a loss of the stop codon. INS transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3'UTR alternatively spliced INS transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.
Collapse
Affiliation(s)
- Taylor W. Cook
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | | | - Jackson T. Mitchell
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | - Nicholas E. Arnold
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | - Surender Rajasekaran
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Office of Research, Corewell Health, Grand Rapids, MI 49503, USA
| | - Caleb P. Bupp
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Division of Medical Genetics, Corewell Health, Grand Rapids, MI 49503, USA
| | - Jeremy W. Prokop
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
- Office of Research, Corewell Health, Grand Rapids, MI 49503, USA
| |
Collapse
|
12
|
Testing the Utility of Polygenic Risk Scores for Type 2 Diabetes and Obesity in Predicting Metabolic Changes in a Prediabetic Population: An Observational Study. Int J Mol Sci 2022; 23:ijms232416081. [PMID: 36555722 PMCID: PMC9787993 DOI: 10.3390/ijms232416081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/03/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
Prediabetes is an intermediate state of hyperglycemia during which glycemic parameters are above normal levels but below the T2D threshold. T2D and its precursor prediabetes affect 6.28% and 7.3% of the world’s population, respectively. The main objective of this paper was to create and compare two polygenic risk scores (PRSs) versus changes over time (Δ) in metabolic parameters related to prediabetes and metabolic complications. The genetics of 446 prediabetic patients from the Polish Registry of Diabetes cohort were investigated. Seventeen metabolic parameters were measured and compared at baseline and after five years using statistical analysis. Subsequently, genetic polymorphisms present in patients were determined to build a T2D PRS (68 SNPs) and an obesity PRS (21 SNPs). Finally, the association among the two PRSs and the Δ of the metabolic traits was assessed. After a multiple linear regression with adjustment for age, sex, and BMI at a nominal significance of (p < 0.05) and adjustment for multiple testing, the T2D PRS was found to be positively associated with Δ fat mass (FM) (p = 0.025). The obesity PRS was positively associated with Δ FM (p = 0.023) and Δ 2 h glucose (p = 0.034). The comparison of genotype frequencies showed that AA genotype carriers of rs10838738 were significantly higher in Δ 2 h glucose and in Δ 2 h insulin. Our findings suggest that prediabetic individuals with a higher risk of developing T2D experience increased Δ FM, and those with a higher risk of obesity experience increased Δ FM and Δ two-hour postprandial glucose. The associations found in this research could be a powerful tool for identifying prediabetic individuals with an increased risk of developing T2D and obesity.
Collapse
|
13
|
Schiborn C, Schulze MB. Precision prognostics for the development of complications in diabetes. Diabetologia 2022; 65:1867-1882. [PMID: 35727346 PMCID: PMC9522742 DOI: 10.1007/s00125-022-05731-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 01/17/2022] [Indexed: 11/24/2022]
Abstract
Individuals with diabetes face higher risks for macro- and microvascular complications than their non-diabetic counterparts. The concept of precision medicine in diabetes aims to optimise treatment decisions for individual patients to reduce the risk of major diabetic complications, including cardiovascular outcomes, retinopathy, nephropathy, neuropathy and overall mortality. In this context, prognostic models can be used to estimate an individual's risk for relevant complications based on individual risk profiles. This review aims to place the concept of prediction modelling into the context of precision prognostics. As opposed to identification of diabetes subsets, the development of prediction models, including the selection of predictors based on their longitudinal association with the outcome of interest and their discriminatory ability, allows estimation of an individual's absolute risk of complications. As a consequence, such models provide information about potential patient subgroups and their treatment needs. This review provides insight into the methodological issues specifically related to the development and validation of prediction models for diabetes complications. We summarise existing prediction models for macro- and microvascular complications, commonly included predictors, and examples of available validation studies. The review also discusses the potential of non-classical risk markers and omics-based predictors. Finally, it gives insight into the requirements and challenges related to the clinical applications and implementation of developed predictions models to optimise medical decision making.
Collapse
Affiliation(s)
- Catarina Schiborn
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
- German Center for Diabetes Research (DZD), Neuherberg, Germany.
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany.
| |
Collapse
|
14
|
Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets. J Pers Med 2022; 12:jpm12091402. [PMID: 36143187 PMCID: PMC9504677 DOI: 10.3390/jpm12091402] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 01/02/2023] Open
Abstract
Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.
Collapse
|
15
|
Brunet F, Malas K, Pomey MP. Reconnecting health through innovation. Healthc Manage Forum 2022; 35:344-348. [PMID: 35960988 DOI: 10.1177/08404704221114249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Learning health systems identify appropriate data to improve their performance and population health. The pandemic has shown that a proper response depends on using data from patients' needs, scientific research, hospital capacity, digital innovations, and stakeholder knowledge. Academic health centres play a role in data collection, information synthesis, and decision making supported by digital innovations. The results obtained by an academic centre and network in Quebec have demonstrated the value of integrating these elements during the pandemic and beyond.
Collapse
Affiliation(s)
- Fabrice Brunet
- 25443Centre hospitalier de l'Université de Montréal, Montreal, Quebec, Canada.,HEC Montréal, Montreal, Quebec, Canada
| | - Kathy Malas
- 25443Centre hospitalier de l'Université de Montréal, Montreal, Quebec, Canada.,HEC Montréal, Montreal, Quebec, Canada
| | - Marie-Pascale Pomey
- 25443Centre hospitalier de l'Université de Montréal, Montreal, Quebec, Canada.,5622Université de Montréal, Montreal, Quebec, Canada
| |
Collapse
|
16
|
Polygenic risk scores: improving the prediction of future disease or added complexity? Br J Gen Pract 2022; 72:396-398. [PMID: 35902257 PMCID: PMC9343049 DOI: 10.3399/bjgp22x720437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
|
17
|
Ashenhurst JR, Sazonova OV, Svrchek O, Detweiler S, Kita R, Babalola L, McIntyre M, Aslibekyan S, Fontanillas P, Shringarpure S, Pollard JD, Koelsch BL. A Polygenic Score for Type 2 Diabetes Improves Risk Stratification Beyond Current Clinical Screening Factors in an Ancestrally Diverse Sample. Front Genet 2022; 13:871260. [PMID: 35559025 PMCID: PMC9086969 DOI: 10.3389/fgene.2022.871260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
A substantial proportion of the adult United States population with type 2 diabetes (T2D) are undiagnosed, calling into question the comprehensiveness of current screening practices, which primarily rely on age, family history, and body mass index (BMI). We hypothesized that a polygenic score (PGS) may serve as a complementary tool to identify high-risk individuals. The T2D polygenic score maintained predictive utility after adjusting for family history and combining genetics with family history led to even more improved disease risk prediction. We observed that the PGS was meaningfully related to age of onset with implications for screening practices: there was a linear and statistically significant relationship between the PGS and T2D onset (-1.3 years per standard deviation of the PGS). Evaluation of U.S. Preventive Task Force and a simplified version of American Diabetes Association screening guidelines showed that addition of a screening criterion for those above the 90th percentile of the PGS provided a small increase the sensitivity of the screening algorithm. Among T2D-negative individuals, the T2D PGS was associated with prediabetes, where each standard deviation increase of the PGS was associated with a 23% increase in the odds of prediabetes diagnosis. Additionally, each standard deviation increase in the PGS corresponded to a 43% increase in the odds of incident T2D at one-year follow-up. Using complications and forms of clinical intervention (i.e., lifestyle modification, metformin treatment, or insulin treatment) as proxies for advanced illness we also found statistically significant associations between the T2D PGS and insulin treatment and diabetic neuropathy. Importantly, we were able to replicate many findings in a Hispanic/Latino cohort from our database, highlighting the value of the T2D PGS as a clinical tool for individuals with ancestry other than European. In this group, the T2D PGS provided additional disease risk information beyond that offered by traditional screening methodologies. The T2D PGS also had predictive value for the age of onset and for prediabetes among T2D-negative Hispanic/Latino participants. These findings strengthen the notion that a T2D PGS could play a role in the clinical setting across multiple ancestries, potentially improving T2D screening practices, risk stratification, and disease management.
Collapse
|
18
|
Aka TD, Saha U, Shati SA, Aziz MA, Begum M, Hussain MS, Millat MS, Uddin MS, Islam MS. Risk of type 2 diabetes mellitus and cardiovascular complications in KCNJ11, HHEX and SLC30A8 genetic polymorphisms carriers: A case-control study. Heliyon 2021; 7:e08376. [PMID: 34849419 PMCID: PMC8608605 DOI: 10.1016/j.heliyon.2021.e08376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/15/2021] [Accepted: 11/10/2021] [Indexed: 01/10/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) are two deadly diseases caused by the complex interaction of multiple genetic loci, lifestyle and environmental factors. Genome-wide association studies described hundreds of susceptibility loci for T2DM and T2DM-related CVD, but it remains uncertain due to geographic and ethnic variations. The objective of this study was to evaluate the associations of KCNJ11 rs5219, SLC30A8 rs13266634 and HHEX rs1111875 polymorphisms with T2DM and related CVD. Methods Genotyping of all three polymorphisms was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method on 250 T2DM cases and 246 healthy controls. Both descriptive and inferential statistical methods were applied using MedCalc and IBM SPSS software programs for statistical analyses. Results A significantly increased association of KCNJ11 rs5219 (p<0.05) with T2DM was found in dominant, recessive, heterozygote, homozygote, and allele model (aOR = 2.23, 2.03, 1.90, 3.09, and 1.80, respectively). For SLC30A8 rs13266634, only dominant, heterozygote, and allele model (aOR = 3.37, 3.59, and 1.79, respectively) showed significantly increased association with T2DM. SNP rs1111875 (HHEX) also revealed 2.08, 4.18, 5.93, and 2.08-times significant association in dominant, recessive, homozygote, and allele models. Besides, a significantly reduced correlation of KCNJ11 rs5219 was found with T2DM-related CVD in the recessive and allele model (aOR = 0.40 and 0.65, respectively). Again, a significant difference was observed between T2DM-related CVD and non-CVD patients in terms of gender distribution, fasting blood glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), and triglycerides (TG). Conclusions Our investigation indicates that KCNJ11 rs5219, SLC30A8 rs13266634 and HHEX rs1111875 polymorphisms are associated with T2DM. Moreover, KCNJ11 rs5219 polymorphism is correlated with the risk of T2DM-related CVD.
Collapse
Affiliation(s)
- Tutun Das Aka
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Urmi Saha
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Sayara Akter Shati
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Md Abdul Aziz
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh.,Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Mobashera Begum
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Md Saddam Hussain
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Md Shalahuddin Millat
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh.,Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Mohammad Sarowar Uddin
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh.,Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| | - Mohammad Safiqul Islam
- Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh.,Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Sonapur, 3814, Noakhali, Bangladesh
| |
Collapse
|
19
|
Gagner M. Metabolic Surgery Needs Stronger Scientific and Genetic Endorsements in Asian T2DM Patients with Low BMI. Obes Surg 2021; 32:214-215. [PMID: 34357534 DOI: 10.1007/s11695-021-05637-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 07/24/2021] [Accepted: 07/27/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Michel Gagner
- Department of Surgery, Westmount Square Surgical Center, Westmount, Canada. .,Department of Surgery, Hopital du Sacre Coeur, Montreal, Canada.
| |
Collapse
|