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Liu WS, Wu BS, Yang L, Chen SD, Zhang YR, Deng YT, Wu XR, He XY, Yang J, Feng JF, Cheng W, Xu YM, Yu JT. Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications. GeroScience 2024; 46:5365-5385. [PMID: 38837026 PMCID: PMC11336033 DOI: 10.1007/s11357-024-01203-2] [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: 12/29/2023] [Accepted: 05/11/2024] [Indexed: 06/06/2024] Open
Abstract
Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (> 0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.
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Affiliation(s)
- Wei-Shi Liu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Xin-Rui Wu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Jing Yang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1St Eastern Jianshe Road, Zhengzhou, 450000, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Yu-Ming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1St Eastern Jianshe Road, Zhengzhou, 450000, China.
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12Th Wulumuqi Zhong Road, Shanghai, 200040, China.
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2
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Mao R, Li J, Xiao W. Identification of prospective aging drug targets via Mendelian randomization analysis. Aging Cell 2024; 23:e14171. [PMID: 38572516 PMCID: PMC11258487 DOI: 10.1111/acel.14171] [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: 10/17/2023] [Revised: 02/26/2024] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Aging represents a multifaceted process culminating in the deterioration of biological functions. Despite the introduction of numerous anti-aging strategies, their therapeutic outcomes have often been less than optimal. Consequently, discovering new targets to mitigate aging effects is of critical importance. We applied Mendelian randomization (MR) to identify potential pharmacological targets against aging, drawing upon summary statistics from both the Decode and FinnGen cohorts, with further validation in an additional cohort. To address potential reverse causality, bidirectional MR analysis with Steiger filtering was utilized. Additionally, Bayesian co-localization and phenotype scanning were implemented to investigate previous associations between genetic variants and traits. Summary-data-based Mendelian randomization (SMR) analysis was conducted to assess the impact of genetic variants on aging via their effects on protein expression. Additionally, mediation analysis was orchestrated to uncover potential intermediaries in these associations. Finally, we probed the systemic implications of drug-target protein expression across diverse indications by MR-PheWas analysis. Utilizing a Bonferroni-corrected threshold, our MR examination identified 10 protein-aging associations. Within this cohort of proteins, MST1, LCT, GMPR2, PSMB4, ECM1, EFEMP1, and ISLR2 appear to exacerbate aging risks, while MAX, B3GNT8, and USP8 may exert protective influences. None of these proteins displayed reverse causality except EFEMP1. Bayesian co-localization inferred shared variants between aging and proteins such as B3GNT8 (rs11670143), ECM1 (rs61819393), and others listed. Mediator analysis pinpointed 1,5-anhydroglucitol as a partial intermediary in the influence LCT exhibits on telomere length. Circulating proteins play a pivotal role in influencing the aging process, making them promising candidates for therapeutic intervention. The implications of these proteins in aging warrant further investigation in future clinical research.
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Affiliation(s)
- Rui Mao
- Department of Dermatology, Xiangya HospitalCentral South UniversityChangshaChina
- Hunan Key Laboratory of Aging Biology, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Ji Li
- Department of Dermatology, Xiangya HospitalCentral South UniversityChangshaChina
- Hunan Key Laboratory of Aging Biology, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Wenqin Xiao
- Department of Dermatology, Xiangya HospitalCentral South UniversityChangshaChina
- Hunan Key Laboratory of Aging Biology, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
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3
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Hill C, Duffy S, Kettyle LM, McGlynn L, Sandholm N, Salem RM, Thompson A, Swan EJ, Kilner J, Rossing P, Shiels PG, Lajer M, Groop PH, Maxwell AP, McKnight AJ. Differential Methylation of Telomere-Related Genes Is Associated with Kidney Disease in Individuals with Type 1 Diabetes. Genes (Basel) 2023; 14:genes14051029. [PMID: 37239390 DOI: 10.3390/genes14051029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/21/2023] [Accepted: 04/23/2023] [Indexed: 05/28/2023] Open
Abstract
Diabetic kidney disease (DKD) represents a major global health problem. Accelerated ageing is a key feature of DKD and, therefore, characteristics of accelerated ageing may provide useful biomarkers or therapeutic targets. Harnessing multi-omics, features affecting telomere biology and any associated methylome dysregulation in DKD were explored. Genotype data for nuclear genome polymorphisms in telomere-related genes were extracted from genome-wide case-control association data (n = 823 DKD/903 controls; n = 247 end-stage kidney disease (ESKD)/1479 controls). Telomere length was established using quantitative polymerase chain reaction. Quantitative methylation values for 1091 CpG sites in telomere-related genes were extracted from epigenome-wide case-control association data (n = 150 DKD/100 controls). Telomere length was significantly shorter in older age groups (p = 7.6 × 10-6). Telomere length was also significantly reduced (p = 6.6 × 10-5) in DKD versus control individuals, with significance remaining after covariate adjustment (p = 0.028). DKD and ESKD were nominally associated with telomere-related genetic variation, with Mendelian randomisation highlighting no significant association between genetically predicted telomere length and kidney disease. A total of 496 CpG sites in 212 genes reached epigenome-wide significance (p ≤ 10-8) for DKD association, and 412 CpG sites in 193 genes for ESKD. Functional prediction revealed differentially methylated genes were enriched for Wnt signalling involvement. Harnessing previously published RNA-sequencing datasets, potential targets where epigenetic dysregulation may result in altered gene expression were revealed, useful as potential diagnostic and therapeutic targets for intervention.
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Affiliation(s)
- Claire Hill
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Seamus Duffy
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Laura M Kettyle
- Centre for Cancer Research and Cell Biology, Queen's University of Belfast, Belfast BT9 7AE, UK
| | - Liane McGlynn
- College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, 00290 Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, 00290 Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290 Helsinki, Finland
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Alex Thompson
- School of Medicine, The Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, UK
| | - Elizabeth J Swan
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Jill Kilner
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
| | - Peter Rossing
- Nordsjaellands Hospital, Hilleroed, Denmark and Health, Aarhus University, 8000 Aarhus, Denmark
- Steno Diabetes Center, 2730 Gentofte, Denmark
- Department of Clinical Medicine, University of Copenhagen, 1165 Copenhagen, Denmark
| | - Paul G Shiels
- School of Molecular Biosciences, Davidson Building, University of Glasgow, Glasgow G12 8QQ, UK
| | - Maria Lajer
- Steno Diabetes Center, 2730 Gentofte, Denmark
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, 00290 Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, 00290 Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290 Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC 3800, Australia
| | - Alexander Peter Maxwell
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast BT9 7AB, UK
| | - Amy Jayne McKnight
- Centre for Public Health, Queen's University of Belfast, Belfast BT12 6BA, UK
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4
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Hill C, Duffy S, Coulter T, Maxwell AP, McKnight AJ. Harnessing Genomic Analysis to Explore the Role of Telomeres in the Pathogenesis and Progression of Diabetic Kidney Disease. Genes (Basel) 2023; 14:609. [PMID: 36980881 PMCID: PMC10048490 DOI: 10.3390/genes14030609] [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: 02/09/2023] [Revised: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
The prevalence of diabetes is increasing globally, and this trend is predicted to continue for future decades. Research is needed to uncover new ways to manage diabetes and its co-morbidities. A significant secondary complication of diabetes is kidney disease, which can ultimately result in the need for renal replacement therapy, via dialysis or transplantation. Diabetic kidney disease presents a substantial burden to patients, their families and global healthcare services. This review highlights studies that have harnessed genomic, epigenomic and functional prediction tools to uncover novel genes and pathways associated with DKD that are useful for the identification of therapeutic targets or novel biomarkers for risk stratification. Telomere length regulation is a specific pathway gaining attention recently because of its association with DKD. Researchers are employing both observational and genetics-based studies to identify telomere-related genes associated with kidney function decline in diabetes. Studies have also uncovered novel functions for telomere-related genes beyond the immediate regulation of telomere length, such as transcriptional regulation and inflammation. This review summarises studies that have revealed the potential to harness therapeutics that modulate telomere length, or the associated epigenetic modifications, for the treatment of DKD, to potentially slow renal function decline and reduce the global burden of this disease.
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Affiliation(s)
- Claire Hill
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
| | - Seamus Duffy
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
| | - Tiernan Coulter
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
| | - Alexander Peter Maxwell
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast BT9 7AB, UK
| | - Amy Jayne McKnight
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
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5
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van der Spek A, Karamujić-Čomić H, Pool R, Bot M, Beekman M, Garmaeva S, Arp PP, Henkelman S, Liu J, Alves AC, Willemsen G, van Grootheest G, Aubert G, Ikram MA, Jarvelin MR, Lansdorp P, Uitterlinden AG, Zhernakova A, Slagboom PE, Penninx BWJH, Boomsma DI, Amin N, van Duijn CM. Fat metabolism is associated with telomere length in six population-based studies. Hum Mol Genet 2021; 31:1159-1170. [PMID: 34875050 DOI: 10.1093/hmg/ddab281] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 08/13/2021] [Accepted: 09/07/2021] [Indexed: 11/13/2022] Open
Abstract
Telomeres are repetitive DNA sequences located at the end of chromosomes, which are associated to biological aging, cardiovascular disease, cancer, and mortality. Lipid and fatty acid metabolism have been associated with telomere shortening. We have conducted an in-depth study investigating the association of metabolic biomarkers with telomere length (LTL). We performed an association analysis of 226 metabolic biomarkers with LTL using data from 11 775 individuals from six independent population-based cohorts (BBMRI-NL consortium). Metabolic biomarkers include lipoprotein lipids and subclasses, fatty acids, amino acids, glycolysis measures and ketone bodies. LTL was measured by quantitative polymerase chain reaction or FlowFISH. Linear regression analysis was performed adjusting for age, sex, lipid-lowering medication and cohort-specific covariates (model 1) and additionally for body mass index (BMI) and smoking (model 2), followed by inverse variance-weighted meta-analyses (significance threshold pmeta = 6.5x10-4). We identified four metabolic biomarkers positively associated with LTL, including two cholesterol to lipid ratios in small VLDL (S-VLDL-C % and S-VLDL-ce %) and two omega-6 fatty acid ratios (FAw6/FA and LA/FA). After additionally adjusting for BMI and smoking, these metabolic biomarkers remained associated with LTL with similar effect estimates. In addition, cholesterol esters in very small VLDL (XS-VLDL-ce) became significantly associated with LTL (p = 3.6x10-4). We replicated the association of FAw6/FA with LTL in an independent dataset of 7845 individuals (p = 1.9x10-4). To conclude, we identified multiple metabolic biomarkers involved in lipid and fatty acid metabolism that may be involved in LTL biology. Longitudinal studies are needed to exclude reversed causation.
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Affiliation(s)
- Ashley van der Spek
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,SkylineDx B.V., Rotterdam, The Netherlands
| | - Hata Karamujić-Čomić
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit University Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health research institute, Amsterdam University Medical Centers, The Netherlands.,BBMRI-NL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), The Netherlands
| | - Mariska Bot
- Department of Psychiatry and GGZ in Geest, Amsterdam Public Health research institute and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Sanzhima Garmaeva
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Pascal P Arp
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Sandra Henkelman
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jun Liu
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit University Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health research institute, Amsterdam University Medical Centers, The Netherlands
| | - Gerard van Grootheest
- Department of Psychiatry and GGZ in Geest, Amsterdam Public Health research institute and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Geraldine Aubert
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, V5Z 1L3 British Columbia, Canada
| | | | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,Center for Life Course Epidemiology, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Peter Lansdorp
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, V5Z 1L3 British Columbia, Canada.,Departments of Medical Genetics and Hematology, University of British Columbia, Vancouver, V6T 1Z4 British Columbia, Canada
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry and GGZ in Geest, Amsterdam Public Health research institute and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit University Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health research institute, Amsterdam University Medical Centers, The Netherlands.,BBMRI-NL: Infrastructure for the Application of Metabolomics Technology in Epidemiology (RP4), The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
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6
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Chang X, Gurung RL, Wang L, Jin A, Li Z, Wang R, Beckman KB, Adams-Haduch J, Meah WY, Sim KS, Lim WK, Davila S, Tan P, Teo JX, Yeo KK, M Y, Liu S, Lim SC, Liu J, van Dam RM, Friedlander Y, Koh WP, Yuan JM, Khor CC, Heng CK, Dorajoo R. Low frequency variants associated with leukocyte telomere length in the Singapore Chinese population. Commun Biol 2021; 4:519. [PMID: 33941849 PMCID: PMC8093266 DOI: 10.1038/s42003-021-02056-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 03/26/2021] [Indexed: 02/02/2023] Open
Abstract
The role of low frequency variants associated with telomere length homeostasis in chronic diseases and mortalities is relatively understudied in the East-Asian population. Here we evaluated low frequency variants, including 1,915,154 Asian specific variants, for leukocyte telomere length (LTL) associations among 25,533 Singapore Chinese samples. Three East Asian specific variants in/near POT1, TERF1 and STN1 genes are associated with LTL (Meta-analysis P 2.49×10-14-6.94×10-10). Rs79314063, a missense variant (p.Asp410His) at POT1, shows effect 5.3 fold higher and independent of a previous common index SNP. TERF1 (rs79617270) and STN1 (rs139620151) are linked to LTL-associated common index SNPs at these loci. Rs79617270 is associated with cancer mortality [HR95%CI = 1.544 (1.173, 2.032), PAdj = 0.018] and 4.76% of the association between the rs79617270 and colon cancer is mediated through LTL. Overall, genetically determined LTL is particularly associated with lung adenocarcinoma [HR95%CI = 1.123 (1.051, 1.201), Padj = 0.007]. Ethnicity-specific low frequency variants may affect LTL homeostasis and associate with certain cancers.
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Affiliation(s)
- Xuling Chang
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Resham L Gurung
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Ling Wang
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Aizhen Jin
- Health Services and Systems Research, Duke-NUS Medical School Singapore, Singapore, Singapore
| | - Zheng Li
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kenneth B Beckman
- University of Minnesota Genomics Center, University of Minnesota, Minneapolis, MN, USA
| | - Jennifer Adams-Haduch
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wee Yang Meah
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Kar Seng Sim
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Weng Khong Lim
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
- Cancer & Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Singapore
| | - Sonia Davila
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
- Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Singapore
| | - Patrick Tan
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
- Cancer & Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Jing Xian Teo
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
| | - Khung Keong Yeo
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Singapore
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore
| | - Yiamunaa M
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Sylvia Liu
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Su Chi Lim
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
- Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yechiel Friedlander
- School of Public Health and Community Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Woon-Puay Koh
- Health Services and Systems Research, Duke-NUS Medical School Singapore, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore.
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore.
- Health Services and Systems Research, Duke-NUS Medical School Singapore, Singapore, Singapore.
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