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Schmidt TT, Tyer C, Rughani P, Haggblom C, Jones JR, Dai X, Frazer KA, Gage FH, Juul S, Hickey S, Karlseder J. High resolution long-read telomere sequencing reveals dynamic mechanisms in aging and cancer. Nat Commun 2024; 15:5149. [PMID: 38890299 PMCID: PMC11189484 DOI: 10.1038/s41467-024-48917-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 05/15/2024] [Indexed: 06/20/2024] Open
Abstract
Telomeres are the protective nucleoprotein structures at the end of linear eukaryotic chromosomes. Telomeres' repetitive nature and length have traditionally challenged the precise assessment of the composition and length of individual human telomeres. Here, we present Telo-seq to resolve bulk, chromosome arm-specific and allele-specific human telomere lengths using Oxford Nanopore Technologies' native long-read sequencing. Telo-seq resolves telomere shortening in five population doubling increments and reveals intrasample, chromosome arm-specific, allele-specific telomere length heterogeneity. Telo-seq can reliably discriminate between telomerase- and ALT-positive cancer cell lines. Thus, Telo-seq is a tool to study telomere biology during development, aging, and cancer at unprecedented resolution.
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Affiliation(s)
| | - Carly Tyer
- Oxford Nanopore Technologies, Inc., New York, NY, USA
| | | | - Candy Haggblom
- Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Jeffrey R Jones
- Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Xiaoguang Dai
- Oxford Nanopore Technologies, Inc., New York, NY, USA
| | - Kelly A Frazer
- Institute of Genomic Medicine, University of California, San Diego, La Jolla, CA, 92093-0761, USA
| | - Fred H Gage
- Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Sissel Juul
- Oxford Nanopore Technologies, Inc., New York, NY, USA
| | - Scott Hickey
- Oxford Nanopore Technologies, Inc., New York, NY, USA.
| | - Jan Karlseder
- Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.
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2
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Savage SA. Telomere length and cancer risk: finding Goldilocks. Biogerontology 2024; 25:265-278. [PMID: 38109000 DOI: 10.1007/s10522-023-10080-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023]
Abstract
Telomeres are the nucleoprotein complex at chromosome ends essential in genomic stability. Baseline telomere length (TL) is determined by rare and common germline genetic variants but shortens with age and is susceptible to certain environmental exposures. Cellular senescence or apoptosis are normally triggered when telomeres reach a critically short length, but cancer cells overcome these protective mechanisms and continue to divide despite chromosomal instability. Rare germline variants in telomere maintenance genes cause exceedingly short telomeres for age (< 1st percentile) and the telomere biology disorders, which are associated with elevated risks of bone marrow failure, myelodysplastic syndrome, acute myeloid leukemia, and squamous cell carcinoma of the head/neck and anogenital regions. Long telomeres due to rare germline variants in the same or different telomere maintenance genes are associated with elevated risks of other cancers, such as chronic lymphocytic leukemia or sarcoma. Early epidemiology studies of TL in the general population lacked reproducibility but new methods, including creation of a TL polygenic score using common variants, have found longer telomeres associated with excess risks of renal cell carcinoma, glioma, lung cancer, and others. It has become clear that when it comes to TL and cancer etiology, not too short, not too long, but "just right" telomeres are important in minimizing cancer risk.
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Affiliation(s)
- Sharon A Savage
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, 6E456, Bethesda, MD, 20892-6772, USA.
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3
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Jaksik R, Szumała K, Dinh KN, Śmieja J. Multiomics-Based Feature Extraction and Selection for the Prediction of Lung Cancer Survival. Int J Mol Sci 2024; 25:3661. [PMID: 38612473 PMCID: PMC11011391 DOI: 10.3390/ijms25073661] [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: 02/15/2024] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024] Open
Abstract
Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features.
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Affiliation(s)
- Roman Jaksik
- Department of Systems Biology and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland;
| | - Kamila Szumała
- Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland;
| | - Khanh Ngoc Dinh
- Irving Institute for Cancer Dynamics and Department of Statistics, Columbia University, New York, NY 10027, USA;
| | - Jarosław Śmieja
- Department of Systems Biology and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland;
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Chien CW, Tang YA, Jeng SL, Pan HA, Sun HS. Blastocyst telomere length predicts successful implantation after frozen-thawed embryo transfer. Hum Reprod Open 2024; 2024:hoae012. [PMID: 38515829 PMCID: PMC10955253 DOI: 10.1093/hropen/hoae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 02/04/2024] [Indexed: 03/23/2024] Open
Abstract
STUDY QUESTION Do embryos with longer telomere length (TL) at the blastocyst stage have a higher capacity to survive after frozen-thawed embryo transfer (FET)? SUMMARY ANSWER Digitally estimated TL using low-pass whole genome sequencing (WGS) data from the preimplantation genetic testing for aneuploidy (PGT-A) process demonstrates that blastocyst TL is the most essential factor associated with likelihood of implantation. WHAT IS KNOWN ALREADY The lifetime TL is established in the early cleavage cycles following fertilization through a recombination-based lengthening mechanism and starts erosion beyond the blastocyst stage. In addition, a telomerase-mediated slow erosion of TL in human fetuses has been observed from a gestational age of 6-11 weeks. Finally, an abnormal shortening of telomeres is likely involved in embryo loss during early development. STUDY DESIGN SIZE DURATION Blastocyst samples were obtained from patients who underwent PGT-A and FET in an IVF center from March 2015 to May 2018. Digitally estimated mitochondrial copy number (mtCN) and TL were used to study associations with the implantation potential of each embryo. PARTICIPANTS/MATERIALS SETTING AND METHODS In total, 965 blastocysts from 232 cycles (164 patients) were available to investigate the biological and clinical relevance of TL. A WGS-based workflow was applied to determine the ploidy of each embryo. Data from low-pass WGS-PGT-A were used to estimate the mtCN and TL for each embryo. Single-variant and multi-variant logistic regression, decision tree, and random forest models were applied to study various factors in association with the implantation potential of each embryo. MAIN RESULTS AND THE ROLE OF CHANCE Of the 965 blastocysts originally available, only 216 underwent FET. While mtCN from the transferred embryos is significantly associated with the ploidy call of each embryo, mtCN has no role in impacting IVF outcomes after an embryo transfer in these women. The results indicate that mtCN is a marker of embryo aneuploidy. On the other hand, digitally estimated TL is the most prominent univariant factor and showed a significant positive association with pregnancy outcomes (P < 0.01, odds ratio 79.1). We combined several maternal and embryo parameters to study the joint effects on successful implantation. The machine learning models, namely decision tree and random forest, were trained and yielded classification accuracy of 0.82 and 0.91, respectively. Taken together, these results support the vital role of TL in governing implantation potential, perhaps through the ability to control embryo survival after transfer. LIMITATIONS REASONS FOR CAUTION The small sample size limits our study as only 216 blastocysts were transferred. The number was further reduced to 153 blastocysts, where pregnancy outcomes could be accurately traced. The other limitation of this study is that all data were collected from a single IVF center. The uniform and controlled operation of IVF cycles in a single center may cause selection bias. WIDER IMPLICATIONS OF THE FINDINGS We present novel findings to show that digitally estimated TL at the blastocyst stage is a predictor of pregnancy capacity after a FET cycle. As elective single-embryo transfer has become the mainstream direction in reproductive medicine, prioritizing embryos based on their implantation potential is crucial for clinical infertility treatment in order to reduce twin pregnancy rate and the time to pregnancy in an IVF center. The AI-powered, random forest prediction model established in this study thus provides a way to improve clinical practice and optimize the chances for people with fertility problems to achieve parenthood. STUDY FUNDING/COMPETING INTERESTS This study was supported by a grant from the National Science and Technology Council, Taiwan (MOST 108-2321-B-006-013 -). There were no competing interests. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Chun-Wei Chien
- Center for Genomic Medicine, Innovation Headquarters, National Cheng Kung University, Tainan, Taiwan
| | - Yen-An Tang
- Center for Genomic Medicine, Innovation Headquarters, National Cheng Kung University, Tainan, Taiwan
- Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Shuen-Lin Jeng
- Department of Statistics, Institute of Data Science, National Cheng Kung University, Tainan, Taiwan
- Center for Innovative FinTech Business Models, National Cheng Kung University, Tainan, Taiwan
| | - Hsien-An Pan
- IVF center, An-An Women and Children Clinic, Tainan, Taiwan
- Department of Obstetrics and Gynecology, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - H Sunny Sun
- Center for Genomic Medicine, Innovation Headquarters, National Cheng Kung University, Tainan, Taiwan
- Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
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Zavala-Paez M, Holliday J, Hamilton JA. Leveraging whole-genome sequencing to estimate telomere length in plants. Mol Ecol Resour 2024; 24:e13899. [PMID: 37966130 DOI: 10.1111/1755-0998.13899] [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: 06/01/2023] [Revised: 10/02/2023] [Accepted: 11/02/2023] [Indexed: 11/16/2023]
Abstract
Changes in telomere length are increasingly used to indicate species' response to environmental stress across diverse taxa. Despite this broad use, few studies have explored telomere length in plants. Thus, evaluation of new approaches for measuring telomeres in plants is needed. Rapid advances in sequencing approaches and bioinformatic tools now allow estimation of telomere content from whole-genome sequencing (WGS) data, a proxy for telomere length. While telomere content has been quantified extensively using quantitative polymerase chain reaction (qPCR) and WGS in humans, no study to date has compared the effectiveness of WGS in estimating telomere length in plants relative to qPCR approaches. In this study, we use 100 Populus clones re-sequenced using short-read Illumina sequencing to quantify telomere length comparing three different bioinformatic approaches (Computel, K-seek and TRIP) in addition to qPCR. Overall, telomere length estimates varied across different bioinformatic approaches, but were highly correlated across methods for individual genotypes. A positive correlation was observed between WGS estimates and qPCR, however, Computel estimates exhibited the greatest correlation. Computel incorporates genome coverage into telomere length calculations, suggesting that genome coverage is likely important to telomere length quantification when using WGS data. Overall, telomere estimates from WGS provided greater precision and accuracy of telomere length estimates relative to qPCR. The findings suggest WGS is a promising approach for assessing telomere length and, as the field of telomere ecology evolves, may provide added value to assaying response to biotic and abiotic environments for plants needed to accelerate plant breeding and conservation management.
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Affiliation(s)
- Michelle Zavala-Paez
- Department of Ecosystem Science and Management, Pennsylvania State University, State College, Pennsylvania, USA
| | - Jason Holliday
- Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, Virginia, USA
| | - Jill A Hamilton
- Department of Ecosystem Science and Management, Pennsylvania State University, State College, Pennsylvania, USA
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Guo M, Songyang Z, Xiong Y. ChArmTelo Enables Large-Scale Chromosome Arm-Level Telomere Analysis across Human Populations and in Cancer Patients. SMALL METHODS 2023; 7:e2300385. [PMID: 37526331 DOI: 10.1002/smtd.202300385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 06/29/2023] [Indexed: 08/02/2023]
Abstract
Telomeres are structures protecting chromosome ends. However, a scalable and cost-effective method to investigate chromosome arm-level (ChArm) telomeres (Telos) in large-scale projects is still lacking, hindering intensive investigation of high-resolution telomeres across cancers and other diseases. Here, ChArmTelo, the first computational toolbox to analyze telomeres at chromosome arm level in human and other animal species, using 10X linked-read and similar technologies, is presented. ChArmTelo currently consists of two algorithms, TeloEM and TeloKnow, for arm-level telomere length (TL) analysis. The algorithms are demonstrated by comprehensive analysis of chromosome arm-level telomere lengths (chArmTLs) in nearly 400 whole genome sequencing samples (WGS) from human populations and animals, including healthy and cancer samples. Notably, considerable performance improvement contributed by using the latest complete telomere-to-telomere reference genome (CHM13v2), compared to hg38, is shown. ChArmTelo reveals population-specific chArmTL differences and liver cancer signatures of chArmTLs and that DNA replication origin disruption may contribute to cancer by affecting TLs. Importantly, ChArmTelo can be readily applied to tens of thousands of cancer and healthy samples with published WGS data.
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Affiliation(s)
- Mengbiao Guo
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510006, China
| | - Zhou Songyang
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510006, China
| | - Yuanyan Xiong
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510006, China
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7
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Igoshin AV, Yudin NS, Romashov GA, Larkin DM. A Multibreed Genome-Wide Association Study for Cattle Leukocyte Telomere Length. Genes (Basel) 2023; 14:1596. [PMID: 37628647 PMCID: PMC10454124 DOI: 10.3390/genes14081596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 07/26/2023] [Accepted: 08/02/2023] [Indexed: 08/27/2023] Open
Abstract
Telomeres are terminal DNA regions of chromosomes that prevent chromosomal fusion and degradation during cell division. In cattle, leukocyte telomere length (LTL) is associated with longevity, productive lifespan, and disease susceptibility. However, the genetic basis of LTL in this species is less studied than in humans. In this study, we utilized the whole-genome resequencing data of 239 animals from 17 cattle breeds for computational leukocyte telomere length estimation and subsequent genome-wide association study of LTL. As a result, we identified 42 significant SNPs, of which eight were found in seven genes (EXOC6B, PTPRD, RPS6KC1, NSL1, AGBL1, ENSBTAG00000052188, and GPC1) when using covariates for two major breed groups (Turano-Mongolian and European). Association analysis with covariates for breed effect detected 63 SNPs, including 13 in five genes (EXOC6B, PTPRD, RPS6KC1, ENSBTAG00000040318, and NELL1). The PTPRD gene, demonstrating the top signal in analysis with breed effect, was previously associated with leukocyte telomere length in cattle and likely is involved in the mechanism of alternative lengthening of telomeres. The single nucleotide variants found could be tested for marker-assisted selection to improve telomere-length-associated traits.
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Affiliation(s)
- Alexander V. Igoshin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090 Novosibirsk, Russia
| | - Nikolay S. Yudin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090 Novosibirsk, Russia
| | - Grigorii A. Romashov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090 Novosibirsk, Russia
| | - Denis M. Larkin
- Royal Veterinary College, University of London, London NW1 0TU, UK
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D’Angiolo M, Yue JX, De Chiara M, Barré BP, Giraud Panis MJ, Gilson E, Liti G. Telomeres are shorter in wild Saccharomyces cerevisiae isolates than in domesticated ones. Genetics 2023; 223:iyac186. [PMID: 36563016 PMCID: PMC9991508 DOI: 10.1093/genetics/iyac186] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 11/02/2022] [Accepted: 12/03/2022] [Indexed: 12/24/2022] Open
Abstract
Telomeres are ribonucleoproteins that cap chromosome-ends and their DNA length is controlled by counteracting elongation and shortening processes. The budding yeast Saccharomyces cerevisiae has been a leading model to study telomere DNA length control and dynamics. Its telomeric DNA is maintained at a length that slightly varies between laboratory strains, but little is known about its variation at the species level. The recent publication of the genomes of over 1,000 S. cerevisiae strains enabled us to explore telomere DNA length variation at an unprecedented scale. Here, we developed a bioinformatic pipeline (YeaISTY) to estimate telomere DNA length from whole-genome sequences and applied it to the sequenced S. cerevisiae collection. Our results revealed broad natural telomere DNA length variation among the isolates. Notably, telomere DNA length is shorter in those derived from wild rather than domesticated environments. Moreover, telomere DNA length variation is associated with mitochondrial metabolism, and this association is driven by wild strains. Overall, these findings reveal broad variation in budding yeast's telomere DNA length regulation, which might be shaped by its different ecological life-styles.
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Affiliation(s)
- Melania D’Angiolo
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
| | - Jia-Xing Yue
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center (SYSUCC), 651 Dongfeng Road East, China
| | - Matteo De Chiara
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
| | - Benjamin P Barré
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
| | - Marie-Josèphe Giraud Panis
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
| | - Eric Gilson
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
- Department of Genetics, CHU, 06107 Nice, France
| | - Gianni Liti
- Institute for Research on Cancer and Aging (IRCAN), Université Côte d’Azur, 28 Avenue de Valombrose, 06107 Nice, France
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Zhang X, Cheng S, Li Z, Gu H, Jiang Y, Li H, Meng X, Wang Y. Telomere length and stroke recurrence after ischemic stroke and TIA. Int J Stroke 2023; 18:208-214. [PMID: 35422196 DOI: 10.1177/17474930221096552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND AND OBJECTIVE Shortening telomere length (TL), as an indicator of aging, has been associated with increased risk of cardiovascular disease and incident stroke. However, there are limited data relating to the association between TL and recurrent stroke. METHODS Patients from the Third China National Stroke Registry who had whole genome sequencing (WGS) were selected. TL was estimated using TelSeq based on binary sequence alignment/map files derived from WGS data. Cox proportional hazards regression models were performed to assess the association of TL with recurrent stroke. RESULTS A total of 8041 patients with ischemic stroke (IS) or transient ischemic attack (TIA) were included. Mean TL was 2.14 ± 0.82 kb. Patients in the lowest tertile of TL had higher incidence of stroke recurrence compared to those in the middle and highest tertile (6.4% vs 5.9% vs 5.2%), but the difference was not longer significant after adjusting for age, sex, cardiovascular risk factors and stroke severity. Similarly, when analyzing TL as a continuous variable, the HR per 1000 bp increase in TL was significant 0.88 (0.79-0.98), but after adjusting for co-variates, was no longer significant (0.91; 95% confidence interval (CI), 0.81-1.02). In patients aged > 65 years, but not in younger patients, after adjusting for co-variates, TL was significantly associated with stroke recurrence. Compared to the lowest tertile, HRs (95% CI) after adjustment for all co-variates for the middle and highest tertiles were 0.78 (0.55-1.10) and 0.67 (0.46-0.98), respectively, with p for trend of 0.03. In analyses using TL as a continuous variable, adjusted HR (95% CI) per 1000 bp increase in TL was 0.80 (0.66-0.96). However, there was no significant interaction between TL and age on risk of stroke recurrence (p for interaction = 0.09). CONCLUSIONS In Chinese IS or TIA patients, no independent association was found between TL and risk of stroke recurrence after adjusting for co-variates. We found a possible association in older patients but this needs replicating.
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Affiliation(s)
- Xing Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Si Cheng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zixiao Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Hongqiu Gu
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yingyu Jiang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Hao Li
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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10
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Germline TP53 mutations undergo copy number gain years prior to tumor diagnosis. Nat Commun 2023; 14:77. [PMID: 36604421 PMCID: PMC9816166 DOI: 10.1038/s41467-022-35727-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 12/08/2022] [Indexed: 01/06/2023] Open
Abstract
Li-Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome associated with germline TP53 pathogenic variants. Here, we perform whole-genome sequence (WGS) analysis of tumors from 22 patients with TP53 germline pathogenic variants. We observe somatic mutations affecting Wnt, PI3K/AKT signaling, epigenetic modifiers and homologous recombination genes as well as mutational signatures associated with prior chemotherapy. We identify near-ubiquitous early loss of heterozygosity of TP53, with gain of the mutant allele. This occurs earlier in these tumors compared to tumors with somatic TP53 mutations, suggesting the timing of this mark may distinguish germline from somatic TP53 mutations. Phylogenetic trees of tumor evolution, reconstructed from bulk and multi-region WGS, reveal that LFS tumors exhibit comparatively limited heterogeneity. Overall, our study delineates early copy number gains of mutant TP53 as a characteristic mutational process in LFS tumorigenesis, likely arising years prior to tumor diagnosis.
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11
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Lyčka M, Fajkus P, Jenner LP, Sýkorová E, Fojtová M, Peska V. Identification of the Sequence and the Length of Telomere DNA. Methods Mol Biol 2023; 2672:285-302. [PMID: 37335484 DOI: 10.1007/978-1-0716-3226-0_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Telomeres are essential nucleoprotein structures at the very ends of linear eukaryote chromosomes. They shelter the terminal genome territories against degradation and prevent the natural chromosome ends from being recognized by repair mechanisms as double-strand DNA breaks.There are two basic characteristics of telomeric DNA, its sequence and its length. The telomere sequence is important as a "landing area" for specific telomere-binding proteins, which function as signals and moderate the interactions required for correct telomere function. While the sequence forms the proper "landing surface" of telomeric DNA, its length is similarly important. Too short or exceptionally long telomere DNA cannot perform its function properly. In this chapter, methods for the investigation of these two basic telomere DNA characteristics are described, namely, telomere motif identification and telomere length measurement.
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Affiliation(s)
- Martin Lyčka
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Petr Fajkus
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic
- Department of Cell Biology and Radiobiology, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
| | - Leon P Jenner
- Department of Cell Biology and Radiobiology, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
| | - Eva Sýkorová
- Department of Cell Biology and Radiobiology, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
| | - Miloslava Fojtová
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic.
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Brno, Czech Republic.
| | - Vratislav Peska
- Department of Cell Biology and Radiobiology, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic.
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12
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Telomere Length: Implications for Atherogenesis. Curr Atheroscler Rep 2023; 25:95-103. [PMID: 36689071 PMCID: PMC9947063 DOI: 10.1007/s11883-023-01082-6] [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] [Accepted: 12/11/2022] [Indexed: 01/24/2023]
Abstract
PURPOSE OF REVIEW The purpose of the study is to explore the evidence linking telomere length with atherosclerotic ischemic disease. RECENT FINDINGS There has been a recent expansion in strategies for measuring telomere length, including analyzing genome sequence data and capitalizing on genomic loci that associate with telomere length. These, together with more established approaches, have been used to generate a more complete picture of telomere length relationships with ischemic disease. Whereas earlier meta-analyses suggested an association between short leukocyte telomeres and ischemic disease, several recent large population studies now provide particularly compelling data, including an association with cardiovascular mortality. In addition, whether short leukocyte telomeres might be causally related to ischemic disease has been interrogated using Mendelian randomization strategies, which point to shorter leukocyte telomeres as a determining risk factor. Importantly however, the wide, interindividual variability in telomere length still means that a single assessment of leukocyte telomere length in an individual does not reliably report on a biological aging process. In this regard, recent multi-tissue analyses of telomere length dynamics are providing both new mechanistic insights into how telomere length and shortening rates may participate in atherogenesis and risk prediction opportunities. The balance of evidence indicates that short leukocyte telomeres confer a risk for atherosclerotic cardiovascular disease. Moreover, an integrated analysis of telomere lengths in leukocytes and other tissues may provide a window into individualized telomere dynamics, raising new prospects for risk management.
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13
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Power ML, Foley NM, Jones G, Teeling EC. Taking flight: An ecological, evolutionary and genomic perspective on bat telomeres. Mol Ecol 2022; 31:6053-6068. [PMID: 34387012 DOI: 10.1111/mec.16117] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/21/2021] [Accepted: 08/03/2021] [Indexed: 01/31/2023]
Abstract
Over 20% of all living mammals are bats (order Chiroptera). Bats possess extraordinary adaptations including powered flight, laryngeal echolocation and a unique immune system that enables them to tolerate a diversity of viral infections without presenting clinical disease symptoms. They occupy multiple trophic niches and environments globally. Significant physiological and ecological diversity occurs across the order. Bats also exhibit extreme longevity given their body size with many species showing few signs of ageing. The molecular basis of this extended longevity has recently attracted attention. Telomere maintenance potentially underpins bats' extended healthspan, although functional studies are still required to validate the causative mechanisms. In this review, we detail the current knowledge on bat telomeres, telomerase expression, and how these relate to ecology, longevity and life-history strategies. Patterns of telomere shortening and telomerase expression vary across species, and comparative genomic analyses suggest that alternative telomere maintenance mechanisms evolved in the longest-lived bats. We discuss the unique challenges faced when working with populations of wild bats and highlight ways to advance the field including expanding long-term monitoring across species that display contrasting life-histories and occupy different environmental niches. We further review how new high quality, chromosome-level genome assemblies can enable us to uncover the molecular mechanisms governing telomere dynamics and how phylogenomic analyses can reveal the adaptive significance of telomere maintenance and variation in bats.
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Affiliation(s)
- Megan L Power
- School of Biology and Environmental Science, Science Centre West, University College Dublin, Belfield, Ireland
| | - Nicole M Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, USA
| | - Gareth Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Emma C Teeling
- School of Biology and Environmental Science, Science Centre West, University College Dublin, Belfield, Ireland
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14
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Wang C, Gu Y, Zhou J, Zang J, Ling X, Li H, Hu L, Xu B, Zhang B, Qin N, Lv H, Duan W, Jiang Y, He Y, Jiang T, Chen C, Han X, Zhou K, Xu B, Liu X, Tao S, Jiang Y, Du J, Dai J, Diao F, Lu C, Guo X, Huo R, Liu J, Lin Y, Xia Y, Jin G, Ma H, Shen H, Hu Z. Leukocyte telomere length in children born following blastocyst-stage embryo transfer. Nat Med 2022; 28:2646-2653. [PMID: 36522605 DOI: 10.1038/s41591-022-02108-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/25/2022] [Indexed: 12/23/2022]
Abstract
Perinatal and childhood adverse outcomes associated with assisted reproductive technology (ART) has been reported, but it remains unknown whether the initial leukocyte telomere length (LTL), which is an indicator of age-related phenotypes in later life, is affected. Here, we estimated the LTLs of 1,137 individuals from 365 families, including 202 children conceived by ART and 205 children conceived spontaneously from two centers of the China National Birth Cohort, using whole-genome sequencing (WGS) data. One-year-old children conceived by ART had shorter LTLs than those conceived spontaneously (beta, -0.36; P = 1.29 × 10-3) after adjusting for plurality, sex and other potential confounding factors. In particular, blastocyst-stage embryo transfer was associated with shorter LTL (beta, -0.54, P = 2.69 × 10-3) in children conceived by ART. The association was validated in 586 children conceived by ART from five centers using different LTL quantification methods (that is, WGS or qPCR). Blastocyst-stage embryo transfer resulted in shorter telomere lengths in mice at postnatal day 1 (P = 2.10 × 10-4) and mice at 6 months (P = 0.042). In vitro culturing of mice embryos did not result in shorter telomere lengths in the late cleavage stage, but it did suppress telomerase activity in the early blastocyst stage. Our findings demonstrate the need to evaluate the long-term consequences of ART, particularly for aging-related phenotypes, in children conceived by ART.
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Affiliation(s)
- Cheng Wang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yayun Gu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jun Zhou
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jie Zang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiufeng Ling
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Reproduction, The Affiliated Obstetrics and Gynecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, China
| | - Hong Li
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Reproductive Genetic Center, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Lingmin Hu
- Department of Reproduction, Changzhou Maternity and Child Health Care Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China
| | - Bei Xu
- Reproductive Medicine Center, Tongji Hospital, Tongji Medicine College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bo Zhang
- Center for Reproductive Medicine, The Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Na Qin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hong Lv
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Weiwei Duan
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yue Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuanlin He
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Tao Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Congcong Chen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiumei Han
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Kun Zhou
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Bo Xu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaoyu Liu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Shiyao Tao
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yangqian Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiangbo Du
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Juncheng Dai
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Feiyang Diao
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Clinical Center of Reproductive Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chuncheng Lu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xuejiang Guo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ran Huo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiayin Liu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China.,Clinical Center of Reproductive Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuan Lin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China.,Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Hongbing Shen
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China.,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, China. .,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China. .,State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China.
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15
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Meeser A, Bartenhagen C, Werr L, Hellmann AM, Kahlert Y, Hemstedt N, Nürnberg P, Altmüller J, Ackermann S, Hero B, Simon T, Peifer M, Fischer M, Rosswog C. Reliable assessment of telomere maintenance mechanisms in neuroblastoma. Cell Biosci 2022; 12:160. [PMID: 36153564 PMCID: PMC9508734 DOI: 10.1186/s13578-022-00896-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 09/03/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Telomere maintenance mechanisms (TMM) are a hallmark of high-risk neuroblastoma, and are conferred by activation of telomerase or alternative lengthening of telomeres (ALT). However, detection of TMM is not yet part of the clinical routine, and consensus on TMM detection, especially on ALT assessment, remains to be achieved. METHODS Whole genome sequencing (WGS) data of 68 primary neuroblastoma samples were analyzed. Telomere length was calculated from WGS data or by telomere restriction fragment analysis (n = 39). ALT was assessed by C-circle assay (CCA, n = 67) and detection of ALT-associated PML nuclear bodies (APB) by combined fluorescence in situ hybridization and immunofluorescence staining (n = 68). RNA sequencing was performed (n = 64) to determine expression of TERT and telomeric long non-coding RNA (TERRA). Telomerase activity was examined by telomerase repeat amplification protocol (TRAP, n = 15). RESULTS Tumors were considered as telomerase-positive if they harbored a TERT rearrangement, MYCN amplification or high TERT expression (45.6%, 31/68), and ALT-positive if they were positive for APB and CCA (19.1%, 13/68). If all these markers were absent, tumors were considered TMM-negative (25.0%, 17/68). According to these criteria, the majority of samples were classified unambiguously (89.7%, 61/68). Assessment of additional ALT-associated parameters clarified the TMM status of the remaining seven cases with high likelihood: ALT-positive tumors had higher TERRA expression, longer telomeres, more telomere insertions, a characteristic pattern of telomere variant repeats, and were associated with ATRX mutations. CONCLUSIONS We here propose a workflow to reliably detect TMM in neuroblastoma. We show that unambiguous classification is feasible following a stepwise approach that determines both, activation of telomerase and ALT. The workflow proposed in this study can be used in clinical routine and provides a framework to systematically and reliably determine telomere maintenance mechanisms for risk stratification and treatment allocation of neuroblastoma patients.
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Affiliation(s)
- Alina Meeser
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Christoph Bartenhagen
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Lisa Werr
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Anna-Maria Hellmann
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Yvonne Kahlert
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Nadine Hemstedt
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Peter Nürnberg
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
- Cologne Center for Genomics (CCG), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Janine Altmüller
- Cologne Center for Genomics (CCG), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
- Core Facility Genomics, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Sandra Ackermann
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
| | - Barbara Hero
- Department of Pediatric Oncology and Hematology, University of Cologne, Cologne, Germany
| | - Thorsten Simon
- Department of Pediatric Oncology and Hematology, University of Cologne, Cologne, Germany
| | - Martin Peifer
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Translational Genomics, Center of Integrated Oncology Cologne-Bonn, Medical Faculty, University of Cologne, Cologne, Germany
| | - Matthias Fischer
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany.
| | - Carolina Rosswog
- Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
- Center for Molecular Medicine Cologne, Medical Faculty, University of Cologne, Cologne, Germany.
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16
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Daios S, Anogeianaki A, Kaiafa G, Kontana A, Veneti S, Gogou C, Karlafti E, Pilalas D, Kanellos I, Savopoulos C. Telomere Length as a marker of biological aging: A critical review of recent literature. Curr Med Chem 2022; 29:5478-5495. [PMID: 35838223 DOI: 10.2174/0929867329666220713123750] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 02/10/2022] [Accepted: 04/01/2022] [Indexed: 11/22/2022]
Abstract
INTRODUCTION Aging is characterized as a syndrome of deleterious, progressive, universal, and irreversible function changes affecting every structural and functional aspect of the organism and accompanied by a generalized increase in mortality. Although a substantial number of candidates for biomarkers of aging have been proposed, none has been validated or universally accepted. Human telomeres constitute hexameric repetitive DNA sequence nucleoprotein complexes that cap chromosome ends, regulating gene expression and modulating stress-related pathways. Telomere length (TL) shortening is observed both in cellular senescence and advanced age, leading to the investigation of TL as a biomarker for aging and a risk factor indicator for the development and progression of the most common age-related diseases. OBJECTIVE The present review underlines the connection between TL and the pathophysiology of the diseases associated with telomere attrition. METHODS We performed a structured search of the PubMed database for peer-reviewed research of the literature regarding leukocyte TL and cardiovascular diseases (CVD), more specifically stroke and heart disease, and focused on the relevant articles published during the last 5 years. We also applied Hill's criteria of causation to strengthen this association. RESULTS We analyzed the recent literature regarding TL length, stroke, and CVD. Although approximately one-third of the available studies support the connection, the results of different studies seem to be rather conflicting as a result of different study designs, divergent methods of TL determination, small study samples, and patient population heterogeneity. After applying Hill's criteria, we can observe that the literature conforms to them weakly, with chronology being the only Hill criterion of causality that probably cannot be contested. CONCLUSION The present review attempted to examine the purported relation between leukocyte TL and age-related diseases such as CVD and more specific stroke and heart disease in view of the best established, comprehensive, medical and epidemiological criteria that have characterized the focused recent relevant research. Although several recommendations have been made that may contribute significantly to the field, a call for novel technical approaches and studies is mandatory to further elucidate the possible association.
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Affiliation(s)
- Stylianos Daios
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Antonia Anogeianaki
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Georgia Kaiafa
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Anastasia Kontana
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Stavroula Veneti
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Christiana Gogou
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Eleni Karlafti
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Dimitrios Pilalas
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Ilias Kanellos
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
| | - Christos Savopoulos
- First Propedeutic Department of Internal Medicine, AHEPA University Hospital, Thessaloniki, Greece
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17
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Gampawar P, Schmidt R, Schmidt H. Telomere length and brain aging: A systematic review and meta-analysis. Ageing Res Rev 2022; 80:101679. [PMID: 35777725 DOI: 10.1016/j.arr.2022.101679] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 02/06/2023]
Abstract
The current evidence on the association of leukocyte telomere length (LTL) with age-related structural and cognitive changes in the brain is mixed. Herein conforming to PRISMA 2020 guidelines, we performed a systematic review and meta-analysis using data from 27 observational studies in non-demented individuals. We used effect size and p-value based meta-analysis methods considering marked heterogeneity among studies. We found that the longer LTL was associated with higher brain volume (β = 0.43, 95%CI: 0.36-0.50%, p = 0.008, N = 1102) and with higher global cognition (β = 0.01; 95%CI: 0.00-0.02, p = 0.03, N = 19609) by effect size based meta-analysis and with brain volume, hippocampal volume, global cognition, cognitive domains of attention/speed as well as executive functions by p-value based meta-analysis. No significant association of LTL with brain white matter hyperintensities was detected. Furthermore, the evidence strongly suggests a subgroup-specific canonical effect of telomeres, notably in older individuals and females. In conclusion, we provide meta-analytic evidence on the beneficial effect of telomeres on brain structure as well as cognition and advocate for a beneficial subgroup-specific effect that warrants further attention.
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Affiliation(s)
- Piyush Gampawar
- Research Unit-Genetic Epidemiology, Gottfried Schatz Research Centre for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Helena Schmidt
- Research Unit-Genetic Epidemiology, Gottfried Schatz Research Centre for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria.
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18
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Holmes O, Nones K, Tang YH, Loffler KA, Lee M, Patch AM, Dagg RA, Lau LMS, Leonard C, Wood S, Xu Q, Pickett HA, Reddel RR, Barbour AP, Grimmond SM, Waddell N, Pearson JV. qmotif: determination of telomere content from whole-genome sequence data. BIOINFORMATICS ADVANCES 2022; 2:vbac005. [PMID: 36699384 PMCID: PMC9710677 DOI: 10.1093/bioadv/vbac005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 12/15/2021] [Indexed: 01/28/2023]
Abstract
Motivation Changes in telomere length have been observed in cancer and can be indicative of mechanisms involved in carcinogenesis. Most methods used to estimate telomere length require laboratory analysis of DNA samples. Here, we present qmotif, a fast and easy tool that determines telomeric repeat sequences content as an estimate of telomere length directly from whole-genome sequencing. Results qmotif shows similar results to quantitative PCR, the standard method for high-throughput clinical telomere length quantification. qmotif output correlates strongly with the output of other tools for determining telomere sequence content, TelSeq and TelomereHunter, but can run in a fraction of the time-usually under a minute. Availability and implementation qmotif is implemented in Java and source code is available at https://github.com/AdamaJava/adamajava, with instructions on how to build and use the application available from https://adamajava.readthedocs.io/en/latest/. Supplementary information Supplementary data are available at Bioinformatics Advances online.
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Affiliation(s)
- Oliver Holmes
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia
| | - Katia Nones
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia
| | - Yue Hang Tang
- Surgical Oncology Group, Diamantina Institute, The University of Queensland, Translational Research Institute at the Princess Alexandra Hospital, Woolloongabba, Brisbane 4102, QLD, Australia
| | - Kelly A Loffler
- Surgical Oncology Group, Diamantina Institute, The University of Queensland, Translational Research Institute at the Princess Alexandra Hospital, Woolloongabba, Brisbane 4102, QLD, Australia,Flinders Health and Medical Research Institute, Flinders University, Bedford Park, SA 5042, Australia
| | - Michael Lee
- Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Ann-Marie Patch
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia
| | - Rebecca A Dagg
- Children’s Hospital at Westmead, University of Sydney, Westmead, NSW 2145, Australia
| | - Loretta M S Lau
- Children’s Hospital at Westmead, University of Sydney, Westmead, NSW 2145, Australia
| | - Conrad Leonard
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia
| | - Scott Wood
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia
| | - Qinying Xu
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia
| | - Hilda A Pickett
- Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Roger R Reddel
- Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Andrew P Barbour
- Surgical Oncology Group, Diamantina Institute, The University of Queensland, Translational Research Institute at the Princess Alexandra Hospital, Woolloongabba, Brisbane 4102, QLD, Australia
| | - Sean M Grimmond
- Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia,University of Melbourne, Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, VIC 3000, Australia
| | - Nicola Waddell
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia,To whom correspondence should be addressed. or
| | - John V Pearson
- QIMR Berghofer Medical Research Institute, Herston, Brisbane 4006, QLD, Australia,Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane 4072, QLD, Australia,To whom correspondence should be addressed. or
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Taub MA, Conomos MP, Keener R, Iyer KR, Weinstock JS, Yanek LR, Lane J, Miller-Fleming TW, Brody JA, Raffield LM, McHugh CP, Jain D, Gogarten SM, Laurie CA, Keramati A, Arvanitis M, Smith AV, Heavner B, Barwick L, Becker LC, Bis JC, Blangero J, Bleecker ER, Burchard EG, Celedón JC, Chang YPC, Custer B, Darbar D, de las Fuentes L, DeMeo DL, Freedman BI, Garrett ME, Gladwin MT, Heckbert SR, Hidalgo BA, Irvin MR, Islam T, Johnson WC, Kaab S, Launer L, Lee J, Liu S, Moscati A, North KE, Peyser PA, Rafaels N, Seidman C, Weeks DE, Wen F, Wheeler MM, Williams LK, Yang IV, Zhao W, Aslibekyan S, Auer PL, Bowden DW, Cade BE, Chen Z, Cho MH, Cupples LA, Curran JE, Daya M, Deka R, Eng C, Fingerlin TE, Guo X, Hou L, Hwang SJ, Johnsen JM, Kenny EE, Levin AM, Liu C, Minster RL, Naseri T, Nouraie M, Reupena MS, Sabino EC, Smith JA, Smith NL, Lasky-Su J, Taylor JG, Telen MJ, Tiwari HK, Tracy RP, White MJ, Zhang Y, Wiggins KL, Weiss ST, Vasan RS, Taylor KD, Sinner MF, Silverman EK, Shoemaker MB, Sheu WHH, Sciurba F, Schwartz DA, Rotter JI, Roden D, Redline S, Raby BA, Psaty BM, Peralta JM, Palmer ND, Nekhai S, Montgomery CG, Mitchell BD, Meyers DA, McGarvey ST, Mak AC, Loos RJ, Kumar R, Kooperberg C, Konkle BA, Kelly S, Kardia SL, Kaplan R, He J, Gui H, Gilliland FD, Gelb BD, Fornage M, Ellinor PT, de Andrade M, Correa A, Chen YDI, Boerwinkle E, Barnes KC, Ashley-Koch AE, Arnett DK, Albert C, Laurie CC, Abecasis G, Nickerson DA, Wilson JG, Rich SS, Levy D, Ruczinski I, Aviv A, Blackwell TW, Thornton T, O’Connell J, Cox NJ, Perry JA, Armanios M, Battle A, Pankratz N, Reiner AP, Mathias RA. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed. CELL GENOMICS 2022; 2:S2666-979X(21)00105-1. [PMID: 35530816 PMCID: PMC9075703 DOI: 10.1016/j.xgen.2021.100084] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 09/03/2021] [Accepted: 12/10/2021] [Indexed: 01/16/2023]
Abstract
Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value <5×10-9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes.
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Affiliation(s)
- Margaret A. Taub
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Matthew P. Conomos
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Rebecca Keener
- Department of Biomedical Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA
| | - Kruthika R. Iyer
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Joshua S. Weinstock
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Lisa R. Yanek
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - John Lane
- Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Tyne W. Miller-Fleming
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Caitlin P. McHugh
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Deepti Jain
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Stephanie M. Gogarten
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Cecelia A. Laurie
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Ali Keramati
- Department of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Marios Arvanitis
- Department of Medicine, Division of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Albert V. Smith
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Benjamin Heavner
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Lucas Barwick
- LTRC Data Coordinating Center, The Emmes Company, LLC, Rockville, MD, USA
| | - Lewis C. Becker
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eugene R. Bleecker
- Department of Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona, Tucson, AZ, USA
- Division of Pharmacogenomics, University of Arizona, Tucson, AZ, USA
| | - Esteban G. Burchard
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Juan C. Celedón
- Division of Pediatric Pulmonary Medicine, UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yen Pei C. Chang
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Brian Custer
- Vitalant Research Institute, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Dawood Darbar
- Division of Cardiology, University of Illinois at Chicago, Chicago, IL, USA
| | - Lisa de las Fuentes
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Melanie E. Garrett
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Mark T. Gladwin
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Bertha A. Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Talat Islam
- Division of Environmental Health, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - W. Craig Johnson
- Department of Biostatistics, Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA
| | - Stefan Kaab
- Department of Medicine I, University Hospital Munich, Ludwig-Maximilian’s University, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Lenore Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jiwon Lee
- Department of Medicine, Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Simin Liu
- Department of Epidemiology and Brown Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E. North
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Patricia A. Peyser
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Nicholas Rafaels
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | | | - Daniel E. Weeks
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fayun Wen
- Center for Sickle Cell Disease and Department of Medicine, College of Medicine, Howard University, Washington, DC 20059, USA
| | - Marsha M. Wheeler
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - L. Keoki Williams
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Ivana V. Yang
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Paul L. Auer
- Zilber School of Public Health, University of Wisconsin, Milwaukee, Milwaukee, WI, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Brian E. Cade
- Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Zhanghua Chen
- Division of Environmental Health, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Michael H. Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Michelle Daya
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Ranjan Deka
- Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Tasha E. Fingerlin
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
- Department of Biostatistics and Informatics, University of Colorado, Denver, Aurora, CO, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jill M. Johnsen
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- University of Washington, Department of Medicine, Seattle, WA, USA
| | - Eimear E. Kenny
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Albert M. Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Chunyu Liu
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Ryan L. Minster
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
- Department of Epidemiology & International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | - Mehdi Nouraie
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Ester C. Sabino
- Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Nicholas L. Smith
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - James G. Taylor
- Center for Sickle Cell Disease and Department of Medicine, College of Medicine, Howard University, Washington, DC 20059, USA
| | - Marilyn J. Telen
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
- Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Russell P. Tracy
- Departments of Pathology & Laboratory Medicine and Biochemistry, Larrner College of Medicine, University of Vermont, Colchester, VT, USA
| | - Marquitta J. White
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Yingze Zhang
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Ramachandran S. Vasan
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Moritz F. Sinner
- Department of Medicine I, University Hospital Munich, Ludwig-Maximilian’s University, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - M. Benjamin Shoemaker
- Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wayne H.-H. Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Frank Sciurba
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - David A. Schwartz
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Daniel Roden
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Susan Redline
- Division of Sleep Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Benjamin A. Raby
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary Medicine, Boston Children’s Hospital, Boston, MA, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA
| | - Juan M. Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Sergei Nekhai
- Center for Sickle Cell Disease and Department of Medicine, College of Medicine, Howard University, Washington, DC 20059, USA
| | - Courtney G. Montgomery
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Deborah A. Meyers
- Department of Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona, Tucson, AZ, USA
- Division of Pharmacogenomics, University of Arizona, Tucson, AZ, USA
| | - Stephen T. McGarvey
- Department of Epidemiology & International Health Institute, School of Public Health, Brown University, Providence, RI, USA
| | | | - Angel C.Y. Mak
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rajesh Kumar
- Division of Allergy and Clinical Immunology, The Ann and Robert H. Lurie Children’s Hospital of Chicago, and Department of Pediatrics, Northwestern University, Chicago, IL, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Barbara A. Konkle
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- University of Washington, Department of Medicine, Seattle, WA, USA
| | - Shannon Kelly
- Vitalant Research Institute, San Francisco, CA, USA
- UCSF Benioff Children’s Hospital, Oakland, CA, USA
| | - Sharon L.R. Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jiang He
- Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Hongsheng Gui
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Frank D. Gilliland
- Division of Environmental Health, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Bruce D. Gelb
- Mindich Child Health and Development Institute, Departments of Pediatrics and Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Patrick T. Ellinor
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mariza de Andrade
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Adolfo Correa
- Jackson Heart Study and Departments of Medicine and Population Health Science, Jackson, MS, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kathleen C. Barnes
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Allison E. Ashley-Koch
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Christine Albert
- Harvard Medical School, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | | | | | | | - Cathy C. Laurie
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Goncalo Abecasis
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MI, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Daniel Levy
- The National Heart, Lung, and Blood Institute, Boston University’s Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Abraham Aviv
- Center of Human Development and Aging, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Thomas W. Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Timothy Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jeff O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nancy J. Cox
- Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - James A. Perry
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mary Armanios
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA
- Departments of Computer Science and Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Rasika A. Mathias
- GeneSTAR Research Program, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
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20
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Lyčka M, Peska V, Demko M, Spyroglou I, Kilar A, Fajkus J, Fojtová M. WALTER: an easy way to online evaluate telomere lengths from terminal restriction fragment analysis. BMC Bioinformatics 2021; 22:145. [PMID: 33752601 PMCID: PMC7986547 DOI: 10.1186/s12859-021-04064-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 03/07/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Telomeres, nucleoprotein structures comprising short tandem repeats and delimiting the ends of linear eukaryotic chromosomes, play an important role in the maintenance of genome stability. Therefore, the determination of the length of telomeres is of high importance for many studies. Over the last years, new methods for the analysis of the length of telomeres have been developed, including those based on PCR or analysis of NGS data. Despite that, terminal restriction fragment (TRF) method remains the gold standard to this day. However, this method lacks universally accepted and precise tool capable to analyse and statistically evaluate TRF results. RESULTS To standardize the processing of TRF results, we have developed WALTER, an online toolset allowing rapid, reproducible, and user-friendly analysis including statistical evaluation of the data. Given its web-based nature, it provides an easily accessible way to analyse TRF data without any need to install additional software. CONCLUSIONS WALTER represents a major upgrade from currently available tools for the image processing of TRF scans. This toolset enables a rapid, highly reproducible, and user-friendly evaluation of almost any TRF scan including in-house statistical evaluation of the data. WALTER platform together with user manual describing the evaluation of TRF scans in detail and presenting tips and troubleshooting, as well as test data to demo the software are available at https://www.ceitec.eu/chromatin-molecular-complexes-jiri-fajkus/rg51/tab?tabId=125#WALTER and the source code at https://github.com/mlyc93/WALTER .
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Affiliation(s)
- Martin Lyčka
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00, Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic
| | - Vratislav Peska
- Institute of Biophysics, Academy of Sciences of the Czech Republic, v.v.i., 612 00, Brno, Czech Republic.
| | - Martin Demko
- Core Facility Bioinformatics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00, Brno, Czech Republic
- Faculty of Informatics, Masaryk University, 602 00, Brno, Czech Republic
| | - Ioannis Spyroglou
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00, Brno, Czech Republic
| | - Agata Kilar
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00, Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic
| | - Jiří Fajkus
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00, Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic
- Institute of Biophysics, Academy of Sciences of the Czech Republic, v.v.i., 612 00, Brno, Czech Republic
| | - Miloslava Fojtová
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00, Brno, Czech Republic.
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00, Brno, Czech Republic.
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21
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Lindrose AR, McLester-Davis LWY, Tristano RI, Kataria L, Gadalla SM, Eisenberg DTA, Verhulst S, Drury S. Method comparison studies of telomere length measurement using qPCR approaches: A critical appraisal of the literature. PLoS One 2021; 16:e0245582. [PMID: 33471860 PMCID: PMC7817045 DOI: 10.1371/journal.pone.0245582] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 01/05/2021] [Indexed: 12/16/2022] Open
Abstract
Use of telomere length (TL) as a biomarker for various environmental exposures and diseases has increased in recent years. Various methods have been developed to measure telomere length. Polymerase chain reaction (PCR)-based methods remain wide-spread for population-based studies due to the high-throughput capability. While several studies have evaluated the repeatability and reproducibility of different TL measurement methods, the results have been variable. We conducted a literature review of TL measurement cross-method comparison studies that included a PCR-based method published between January 1, 2002 and May 25, 2020. A total of 25 articles were found that matched the inclusion criteria. Papers were reviewed for quality of methodologic reporting of sample and DNA quality, PCR assay characteristics, sample blinding, and analytic approaches to determine final TL. Overall, methodologic reporting was low as assessed by two different reporting guidelines for qPCR-based TL measurement. There was a wide range in the reported correlation between methods (as assessed by Pearson’s r) and few studies utilized the recommended intra-class correlation coefficient (ICC) for assessment of assay repeatability and methodologic comparisons. The sample size for nearly all studies was less than 100, raising concerns about statistical power. Overall, this review found that the current literature on the relation between TL measurement methods is lacking in validity and scientific rigor. In light of these findings, we present reporting guidelines for PCR-based TL measurement methods and results of analyses of the effect of assay repeatability (ICC) on statistical power of cross-sectional and longitudinal studies. Additional cross-laboratory studies with rigorous methodologic and statistical reporting, adequate sample size, and blinding are essential to accurately determine assay repeatability and replicability as well as the relation between TL measurement methods.
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Affiliation(s)
- Alyssa R. Lindrose
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Tulane University, New Orleans, Louisiana, United States of America
- * E-mail: (ARL); (SD)
| | | | - Renee I. Tristano
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, United States of America
| | - Leila Kataria
- School of Science and Engineering, Tulane University, New Orleans, Louisiana, United States of America
| | - Shahinaz M. Gadalla
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Dan T. A. Eisenberg
- Department of Anthropology, Department of Biology, Center for Studies in Demography and Ecology, University of Washington, Seattle, Washington, United States of America
| | - Simon Verhulst
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands
| | - Stacy Drury
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Tulane University, New Orleans, Louisiana, United States of America
- Tulane Brain Institute, Tulane University, New Orleans, Louisiana, United States of America
- Department of Pediatrics, School of Medicine, Tulane University, New Orleans, Louisiana, United States of America
- * E-mail: (ARL); (SD)
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22
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Luxton JJ, McKenna MJ, Taylor LE, George KA, Zwart SR, Crucian BE, Drel VR, Garrett-Bakelman FE, Mackay MJ, Butler D, Foox J, Grigorev K, Bezdan D, Meydan C, Smith SM, Sharma K, Mason CE, Bailey SM. Temporal Telomere and DNA Damage Responses in the Space Radiation Environment. Cell Rep 2020; 33:108435. [PMID: 33242411 DOI: 10.1016/j.celrep.2020.108435] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/15/2020] [Accepted: 11/04/2020] [Indexed: 02/08/2023] Open
Abstract
Telomeres, repetitive terminal features of chromosomes essential for maintaining genome integrity, shorten with cell division, lifestyle factors and stresses, and environmental exposures, and so they provide a robust biomarker of health, aging, and age-related diseases. We assessed telomere length dynamics (changes over time) in three unrelated astronauts before, during, and after 1-year or 6-month missions aboard the International Space Station (ISS). Similar to our results for National Aeronautics and Space Administration's (NASA's) One-Year Mission twin astronaut (Garrett-Bakelman et al., 2019), significantly longer telomeres were observed during spaceflight for two 6-month mission astronauts. Furthermore, telomere length shortened rapidly after return to Earth for all three crewmembers and, overall, telomere length tended to be shorter after spaceflight than before spaceflight. Consistent with chronic exposure to the space radiation environment, signatures of persistent DNA damage responses were also detected, including mitochondrial and oxidative stress, inflammation, and telomeric and chromosomal aberrations, which together provide potential mechanistic insight into spaceflight-specific telomere elongation.
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Affiliation(s)
- Jared J Luxton
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA; Cell and Molecular Biology Program, Colorado State University, Fort Collins, CO, USA
| | - Miles J McKenna
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA; Cell and Molecular Biology Program, Colorado State University, Fort Collins, CO, USA
| | - Lynn E Taylor
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
| | | | - Sara R Zwart
- University of Texas Medical Branch, Galveston, TX, USA
| | | | - Viktor R Drel
- Center for Renal Precision Medicine, UT Health, San Antonio, TX, USA
| | - Francine E Garrett-Bakelman
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA; Department of Medicine, University of Virginia, Charlottesville, VA, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Matthew J Mackay
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Daniel Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Kirill Grigorev
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Daniela Bezdan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | | | - Kumar Sharma
- Center for Renal Precision Medicine, UT Health, San Antonio, TX, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
| | - Susan M Bailey
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA; Cell and Molecular Biology Program, Colorado State University, Fort Collins, CO, USA.
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23
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Sieverling L, Hong C, Koser SD, Ginsbach P, Kleinheinz K, Hutter B, Braun DM, Cortés-Ciriano I, Xi R, Kabbe R, Park PJ, Eils R, Schlesner M, Brors B, Rippe K, Jones DTW, Feuerbach L. Genomic footprints of activated telomere maintenance mechanisms in cancer. Nat Commun 2020; 11:733. [PMID: 32024817 PMCID: PMC7002710 DOI: 10.1038/s41467-019-13824-9] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 11/26/2019] [Indexed: 12/14/2022] Open
Abstract
Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.
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Affiliation(s)
- Lina Sieverling
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120, Heidelberg, Germany
| | - Chen Hong
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120, Heidelberg, Germany
| | - Sandra D Koser
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120, Heidelberg, Germany
| | - Philip Ginsbach
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Kortine Kleinheinz
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, 69120, Heidelberg, Germany
| | - Barbara Hutter
- German Cancer Consortium (DKTK), Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
- Heidelberg Center for Personalized Oncology (DKFZ-HIPO), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Delia M Braun
- Faculty of Biosciences, Heidelberg University, 69120, Heidelberg, Germany
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and BioQuant, 69120, Heidelberg, Germany
| | - Isidro Cortés-Ciriano
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, 02115, USA
- Department of Chemistry, Centre for Molecular Science Informatics, University of Cambridge, Cambridge, CB2 1EW, UK
- Ludwig Center at Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Ruibin Xi
- School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing, 100871, China
| | - Rolf Kabbe
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Peter J Park
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, 02115, USA
- Ludwig Center at Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Roland Eils
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, 69120, Heidelberg, Germany
| | - Matthias Schlesner
- Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Benedikt Brors
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and BioQuant, 69120, Heidelberg, Germany
| | - David T W Jones
- Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany
- Pediatric Glioma Research Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lars Feuerbach
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
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24
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Nersisyan L, Hopp L, Loeffler-Wirth H, Galle J, Loeffler M, Arakelyan A, Binder H. Telomere Length Maintenance and Its Transcriptional Regulation in Lynch Syndrome and Sporadic Colorectal Carcinoma. Front Oncol 2019; 9:1172. [PMID: 31750255 PMCID: PMC6848383 DOI: 10.3389/fonc.2019.01172] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Accepted: 10/18/2019] [Indexed: 12/14/2022] Open
Abstract
Background: Activation of telomere maintenance mechanisms (TMMs) is a hallmark of most cancers, and is required to prevent genome instability and to establish cellular immortality through reconstitution of capping of chromosome ends. TMM depends on the cancer type. Comparative studies linking tumor biology and TMM have potential impact for evaluating cancer onset and development. Methods: We have studied alterations of telomere length, their sequence composition and transcriptional regulation in mismatch repair deficient colorectal cancers arising in Lynch syndrome (LS-CRC) and microsatellite instable (MSI) sporadic CRC (MSI s-CRC), and for comparison, in microsatellite stable (MSS) s-CRC and in benign colon mucosa. Our study applied bioinformatics analysis of whole genome DNA and RNA sequencing data and a pathway model to study telomere length alterations and the potential effect of the "classical" telomerase (TEL-) and alternative (ALT-) TMM using transcriptomic signatures. Results: We have found progressive decrease of mean telomere length in all cancer subtypes compared with reference systems. Our results support the view that telomere attrition is an early event in tumorigenesis. TMM gets activated in all tumors studied due to concerted overexpression of a large fraction of genes with direct relation to telomere function, where only a very small fraction of them showed recurrent mutations. TEL-related transcriptional state was dominating in all CRC subtypes, showing, however, subtype-specific activation patterns; while contribution of the ALT-TMM was slightly more prominent in the hypermutated MSI s-CRC and LS-CRC. TEL-TMM is mainly activated by over-expression of DKC1 and/or TERT genes and their interaction partners, where DKC1 is more prominent in MSS than in MSI s-CRC and can serve as a transcriptomic marker of TMM activity. Conclusions: Our results suggest that transcriptional patterns are indicative for TMM pathway activation with subtle differences between TEL and ALT mechanisms in a CRC subtype-specific fashion. Sequencing data potentially provide a suited measure to study alterations of telomere length and of underlying transcriptional regulation. Further studies are needed to improve this method.
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Affiliation(s)
- Lilit Nersisyan
- Group of Bioinformatics, Institute of Molecular Biology, National Academy of Sciences, Yerevan, Armenia
| | - Lydia Hopp
- Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Henry Loeffler-Wirth
- Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Jörg Galle
- Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Markus Loeffler
- Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany.,Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany
| | - Arsen Arakelyan
- Group of Bioinformatics, Institute of Molecular Biology, National Academy of Sciences, Yerevan, Armenia
| | - Hans Binder
- Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
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25
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Abstract
Conventional approaches to identify a telomere motif in a new genome are laborious and time-intensive. An efficient new methodology based on next-generation sequencing (NGS), de novo sequence repeat finder (SERF) and fluorescence in situ hybridization (FISH) is presented. Unlike existing heuristic approaches, SERF utilizes an exhaustive analysis of raw NGS reads or assembled contigs for rapid de novo detection of conserved tandem repeats representing telomere motifs. SERF was validated using the NGS data from Ipheion uniflorum and Allium cepa with known telomere motifs. The analysis program was then used on NGS data to investigate the telomere motifs in several additional plant species and together with FISH proved to be an efficient approach to identify as yet unknown telomere motifs.
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26
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Lee M, Teber ET, Holmes O, Nones K, Patch AM, Dagg RA, Lau LMS, Lee JH, Napier CE, Arthur JW, Grimmond SM, Hayward NK, Johansson PA, Mann GJ, Scolyer RA, Wilmott JS, Reddel RR, Pearson JV, Waddell N, Pickett HA. Telomere sequence content can be used to determine ALT activity in tumours. Nucleic Acids Res 2019; 46:4903-4918. [PMID: 29718321 PMCID: PMC6007693 DOI: 10.1093/nar/gky297] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 04/10/2018] [Indexed: 01/16/2023] Open
Abstract
The replicative immortality of human cancer cells is achieved by activation of a telomere maintenance mechanism (TMM). To achieve this, cancer cells utilise either the enzyme telomerase, or the Alternative Lengthening of Telomeres (ALT) pathway. These distinct molecular pathways are incompletely understood with respect to activation and propagation, as well as their associations with clinical outcomes. We have identified significant differences in the telomere repeat composition of tumours that use ALT compared to tumours that do not. We then employed a machine learning approach to stratify tumours according to telomere repeat content with an accuracy of 91.6%. Importantly, this classification approach is applicable across all tumour types. Analysis of pathway mutations that were under-represented in ALT tumours, across 1,075 tumour samples, revealed that the autophagy, cell cycle control of chromosomal replication, and transcriptional regulatory network in embryonic stem cells pathways are involved in the survival of ALT tumours. Overall, our approach demonstrates that telomere sequence content can be used to stratify ALT activity in cancers, and begin to define the molecular pathways involved in ALT activation.
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Affiliation(s)
- Michael Lee
- Telomere Length Regulation Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Erdahl T Teber
- Bioinformatics Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Oliver Holmes
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Katia Nones
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Ann-Marie Patch
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Rebecca A Dagg
- Cancer Research Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Loretta M S Lau
- Cancer Research Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Joyce H Lee
- Cancer Research Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Christine E Napier
- Cancer Research Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Jonathan W Arthur
- Bioinformatics Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - Sean M Grimmond
- University of Melbourne Centre for Cancer Research, University of Melbourne, Melbourne, Victoria, Australia
| | - Nicholas K Hayward
- Melanoma Institute Australia, University of Sydney, North Sydney, New South Wales, Australia.,Oncogenomics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Peter A Johansson
- Oncogenomics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Graham J Mann
- Melanoma Institute Australia, University of Sydney, North Sydney, New South Wales, Australia.,Centre for Cancer Research, Westmead Institute for Medical Research, University of Sydney, Westmead, New South Wales, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, University of Sydney, North Sydney, New South Wales, Australia.,Discipline of Pathology, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia.,Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, New South Wales, Australia
| | - James S Wilmott
- Melanoma Institute Australia, University of Sydney, North Sydney, New South Wales, Australia.,Discipline of Pathology, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Roger R Reddel
- Cancer Research Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
| | - John V Pearson
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Nicola Waddell
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Hilda A Pickett
- Telomere Length Regulation Unit, Children's Medical Research Institute, University of Sydney, Westmead, New South Wales, Australia
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27
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Feuerbach L, Sieverling L, Deeg KI, Ginsbach P, Hutter B, Buchhalter I, Northcott PA, Mughal SS, Chudasama P, Glimm H, Scholl C, Lichter P, Fröhling S, Pfister SM, Jones DTW, Rippe K, Brors B. TelomereHunter - in silico estimation of telomere content and composition from cancer genomes. BMC Bioinformatics 2019; 20:272. [PMID: 31138115 PMCID: PMC6540518 DOI: 10.1186/s12859-019-2851-0] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 04/26/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Establishment of telomere maintenance mechanisms is a universal step in tumor development to achieve replicative immortality. These processes leave molecular footprints in cancer genomes in the form of altered telomere content and aberrations in telomere composition. To retrieve these telomere characteristics from high-throughput sequencing data the available computational approaches need to be extended and optimized to fully exploit the information provided by large scale cancer genome data sets. RESULTS We here present TelomereHunter, a software for the detailed characterization of telomere maintenance mechanism footprints in the genome. The tool is implemented for the analysis of large cancer genome cohorts and provides a variety of diagnostic diagrams as well as machine-readable output for subsequent analysis. A novel key feature is the extraction of singleton telomere variant repeats, which improves the identification and subclassification of the alternative lengthening of telomeres phenotype. We find that whole genome sequencing-derived telomere content estimates strongly correlate with telomere qPCR measurements (r = 0.94). For the first time, we determine the correlation of in silico telomere content quantification from whole genome sequencing and whole genome bisulfite sequencing data derived from the same tumor sample (r = 0.78). An analogous comparison of whole exome sequencing data and whole genome sequencing data measured slightly lower correlation (r = 0.79). However, this is considerably improved by normalization with matched controls (r = 0.91). CONCLUSIONS TelomereHunter provides new functionality for the analysis of the footprints of telomere maintenance mechanisms in cancer genomes. Besides whole genome sequencing, whole exome sequencing and whole genome bisulfite sequencing are suited for in silico telomere content quantification, especially if matched control samples are available. The software runs under a GPL license and is available at https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html .
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Affiliation(s)
- Lars Feuerbach
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Lina Sieverling
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120 Heidelberg, Germany
| | - Katharina I. Deeg
- Research Group Genome Organization & Function/Division of Chromatin Networks, German Cancer Research Center (DKFZ) and BioQuant Center, 69120 Heidelberg, Germany
| | - Philip Ginsbach
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Barbara Hutter
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Ivo Buchhalter
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Paul A. Northcott
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Sadaf S. Mughal
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120 Heidelberg, Germany
| | - Priya Chudasama
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Hanno Glimm
- Translational Functional Cancer Genomics, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Dresden, University Hospital Carl Gustav Carus, Dresden and DKFZ, Heidelberg, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
| | - Claudia Scholl
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Division of Applied Functional Genomics, DKFZ, 69120 Heidelberg, Germany
| | - Peter Lichter
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Division of Molecular Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Stefan Fröhling
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
| | - Stefan M. Pfister
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Hopp Children’s Cancer Center at the NCT Heidelberg (KiTZ), 69120 Heidelberg, Germany
- Department of Pediatric Oncology, Hematology and Immunology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - David T. W. Jones
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Hopp Children’s Cancer Center at the NCT Heidelberg (KiTZ), 69120 Heidelberg, Germany
- Pediatric Glioma Research Group, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Karsten Rippe
- Research Group Genome Organization & Function/Division of Chromatin Networks, German Cancer Research Center (DKFZ) and BioQuant Center, 69120 Heidelberg, Germany
| | - Benedikt Brors
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
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28
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Mensà E, Latini S, Ramini D, Storci G, Bonafè M, Olivieri F. The telomere world and aging: Analytical challenges and future perspectives. Ageing Res Rev 2019; 50:27-42. [PMID: 30615937 DOI: 10.1016/j.arr.2019.01.004] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 11/15/2018] [Accepted: 01/03/2019] [Indexed: 12/12/2022]
Abstract
Telomeres, the terminal nucleoprotein structures of eukaryotic chromosomes, play pleiotropic functions in cellular and organismal aging. Telomere length (TL) varies throughout life due to the influence of genetic factors and to a complex balancing between "shortening" and "elongation" signals. Telomerase, the only enzyme that can elongate a telomeric DNA chain, and telomeric repeat-containing RNA (TERRA), a long non-coding RNA involved in looping maintenance, play key roles in TL during life. Despite recent advances in the knowledge of TL, TERRA and telomerase activity (TA) biology and their measurement techniques, the experimental and theoretical issues involved raise a number of problems that should carefully be considered by researchers approaching the "telomere world". The increasing use of such parameters - hailed as promising clinically relevant biomarkers - has failed to be paralleled by the development of automated and standardized measurement technology. Consequently, associating given TL values to specific pathological conditions involves on the one hand technological issues and on the other clinical-biological issues related to the planning of clinically relevant association studies. Addressing these issues would help avoid major biases in association studies involving TL and a number of outcomes, especially those focusing on psychological and bio-behavioral variables. The main challenge in telomere research is the development of accurate and reliable measurement methods to achieve simple and sensitive TL, TERRA, and TA detection. The discovery of the localization of telomeres and TERRA in cellular and extracellular compartments had added an additional layer of complexity to the measurement of these age-related biomarkers. Since combined analysis of TL, TERRA and TA may well provide more exhaustive clinical information than a single parameter, we feel it is important for researchers in the various fields to become familiar with their most common measurement techniques and to be aware of the respective merits and drawbacks of these approaches.
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Affiliation(s)
- Emanuela Mensà
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
| | - Silvia Latini
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
| | - Deborah Ramini
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
| | - Gianluca Storci
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy; Interdepartmental Centre "L. Galvani" (CIG), University of Bologna, Bologna, Italy
| | - Massimiliano Bonafè
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy; Interdepartmental Centre "L. Galvani" (CIG), University of Bologna, Bologna, Italy; Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST), IRCCS, Biosciences Laboratory, Meldola, Italy
| | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy; Center of Clinical Pathology and Innovative Therapy, IRCCS INRCA, Ancona, Italy.
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29
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Lopez-Doriga A, Valle L, Alonso MH, Aussó S, Closa A, Sanjuan X, Barquero D, Rodríguez-Moranta F, Sanz-Pamplona R, Moreno V. Telomere length alterations in microsatellite stable colorectal cancer and association with the immune response. Biochim Biophys Acta Mol Basis Dis 2018; 1864:2992-3000. [DOI: 10.1016/j.bbadis.2018.06.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 06/12/2018] [Accepted: 06/12/2018] [Indexed: 02/07/2023]
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30
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Macintyre G, Goranova TE, De Silva D, Ennis D, Piskorz AM, Eldridge M, Sie D, Lewsley LA, Hanif A, Wilson C, Dowson S, Glasspool RM, Lockley M, Brockbank E, Montes A, Walther A, Sundar S, Edmondson R, Hall GD, Clamp A, Gourley C, Hall M, Fotopoulou C, Gabra H, Paul J, Supernat A, Millan D, Hoyle A, Bryson G, Nourse C, Mincarelli L, Sanchez LN, Ylstra B, Jimenez-Linan M, Moore L, Hofmann O, Markowetz F, McNeish IA, Brenton JD. Copy number signatures and mutational processes in ovarian carcinoma. Nat Genet 2018; 50:1262-1270. [PMID: 30104763 PMCID: PMC6130818 DOI: 10.1038/s41588-018-0179-8] [Citation(s) in RCA: 253] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 06/19/2018] [Indexed: 01/22/2023]
Abstract
The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.
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Affiliation(s)
| | | | | | - Darren Ennis
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | | | - Daoud Sie
- VU University Medical Center, Amsterdam, the Netherlands
| | - Liz-Anne Lewsley
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Aishah Hanif
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Cheryl Wilson
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Suzanne Dowson
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | - Michelle Lockley
- Barts Cancer Institute, Queen Mary University of London, London, UK
- University College London Hospital, London, UK
| | | | | | | | | | - Richard Edmondson
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, UK
- Department of Obstetrics and Gynaecology, Manchester Academic Health Science Centre, St Mary's Hospital, Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | | | | | - Charlie Gourley
- Nicola Murray Centre for Ovarian Cancer Research, MRC IGMM, University of Edinburgh, Edinburgh, UK
| | | | - Christina Fotopoulou
- Division of Cancer and Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College, London, UK
| | - Hani Gabra
- Division of Cancer and Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College, London, UK
- Early Clinical Development, IMED Biotech Unit, AstraZeneca, Cambridge, UK
| | - James Paul
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Anna Supernat
- Cancer Research UK Cambridge Institute, Cambridge, UK
| | - David Millan
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Aoisha Hoyle
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Gareth Bryson
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Craig Nourse
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Laura Mincarelli
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | - Bauke Ylstra
- VU University Medical Center, Amsterdam, the Netherlands
| | | | | | - Oliver Hofmann
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
- Centre for Cancer Research, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Iain A McNeish
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK.
- Beatson West of Scotland Cancer Centre, Glasgow, UK.
- Division of Cancer and Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College, London, UK.
| | - James D Brenton
- Cancer Research UK Cambridge Institute, Cambridge, UK.
- Addenbrooke's Hospital, Cambridge, UK.
- Department of Oncology, University of Cambridge, Cambridge, UK.
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31
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Abstract
The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.
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32
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Macintyre G, Goranova TE, De Silva D, Ennis D, Piskorz AM, Eldridge M, Sie D, Lewsley LA, Hanif A, Wilson C, Dowson S, Glasspool RM, Lockley M, Brockbank E, Montes A, Walther A, Sundar S, Edmondson R, Hall GD, Clamp A, Gourley C, Hall M, Fotopoulou C, Gabra H, Paul J, Supernat A, Millan D, Hoyle A, Bryson G, Nourse C, Mincarelli L, Sanchez LN, Ylstra B, Jimenez-Linan M, Moore L, Hofmann O, Markowetz F, McNeish IA, Brenton JD. Copy number signatures and mutational processes in ovarian carcinoma. Nat Genet 2018. [PMID: 30104763 DOI: 10.1038/s41588-018-0179-8]+[] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.
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Affiliation(s)
| | | | | | - Darren Ennis
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | | | - Daoud Sie
- VU University Medical Center, Amsterdam, the Netherlands
| | - Liz-Anne Lewsley
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Aishah Hanif
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Cheryl Wilson
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Suzanne Dowson
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | - Michelle Lockley
- Barts Cancer Institute, Queen Mary University of London, London, UK.,University College London Hospital, London, UK
| | | | | | | | | | - Richard Edmondson
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, UK.,Department of Obstetrics and Gynaecology, Manchester Academic Health Science Centre, St Mary's Hospital, Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | | | | | - Charlie Gourley
- Nicola Murray Centre for Ovarian Cancer Research, MRC IGMM, University of Edinburgh, Edinburgh, UK
| | | | - Christina Fotopoulou
- Division of Cancer and Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College, London, UK
| | - Hani Gabra
- Division of Cancer and Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College, London, UK.,Early Clinical Development, IMED Biotech Unit, AstraZeneca, Cambridge, UK
| | - James Paul
- Cancer Research UK Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Anna Supernat
- Cancer Research UK Cambridge Institute, Cambridge, UK
| | - David Millan
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Aoisha Hoyle
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Gareth Bryson
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Craig Nourse
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Laura Mincarelli
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | - Bauke Ylstra
- VU University Medical Center, Amsterdam, the Netherlands
| | | | | | - Oliver Hofmann
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK.,Centre for Cancer Research, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Iain A McNeish
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK. .,Beatson West of Scotland Cancer Centre, Glasgow, UK. .,Division of Cancer and Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College, London, UK.
| | - James D Brenton
- Cancer Research UK Cambridge Institute, Cambridge, UK. .,Addenbrooke's Hospital, Cambridge, UK. .,Department of Oncology, University of Cambridge, Cambridge, UK.
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33
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Epel ES, Prather AA. Stress, Telomeres, and Psychopathology: Toward a Deeper Understanding of a Triad of Early Aging. Annu Rev Clin Psychol 2018; 14:371-397. [PMID: 29494257 DOI: 10.1146/annurev-clinpsy-032816-045054] [Citation(s) in RCA: 101] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Telomeres play an important part in aging and show relationships to lifetime adversity, particularly childhood adversity. Meta-analyses demonstrate reliable associations between psychopathology (primarily depression) and shorter telomere length, but the nature of this relationship has not been fully understood. Here, we review and evaluate the evidence for impaired telomere biology as a consequence of psychopathology or as a contributing factor, and the important mediating roles of chronic psychological stress and impaired allostasis. There is evidence for a triadic relationship among stress, telomere shortening, and psychiatric disorders that is positively reinforcing and unfolds across the life course and, possibly, across generations. We review the role of genetics and biobehavioral responses that may contribute to shorter telomere length, as well as the neurobiological impact of impaired levels of telomerase. These complex interrelationships are important to elucidate because they have implications for mental and physical comorbidity and, potentially, for the prevention and treatment of depression.
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Affiliation(s)
| | - Aric A Prather
- Department of Psychiatry; Center for Health and Community; Aging, Metabolism, and Emotions Center; University of California, San Francisco, California 94118, USA; ,
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34
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Verma P, Dilley RL, Gyparaki MT, Greenberg RA. Direct Quantitative Monitoring of Homology-Directed DNA Repair of Damaged Telomeres. Methods Enzymol 2018; 600:107-134. [PMID: 29458755 DOI: 10.1016/bs.mie.2017.11.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Homology-directed DNA repair (HDR) is an evolutionary conserved mechanism that is required for genome integrity and organismal fitness across species. While a myriad of different factors and mechanisms are able to execute HDR, all forms necessitate common steps of DNA damage recognition, homology search and capture, and assembly of a DNA polymerase complex to conduct templated DNA synthesis. The central question of what determines HDR mechanism utilization in mammalian cells has been limited by an inability to directly monitor the DNA damage response and products of repair as they arise from a defined genomic lesion. In this chapter, we describe several methodologies to delineate major steps of HDR during alternative lengthening of telomeres in human cells. This includes procedures to visualize interchromosomal telomere homology searches in real time and quantitatively detect HDR synthesis of nascent telomeres emanating from synchronous activation of telomere DNA double-strand breaks. We highlight the critical details of these methods and their applicability to monitoring HDR at telomeres in a broad variety of mammalian cell types.
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Affiliation(s)
- Priyanka Verma
- Basser Research Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Robert L Dilley
- Basser Research Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Melina T Gyparaki
- Basser Research Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Roger A Greenberg
- Basser Research Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
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35
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Farmery JHR, Smith ML, Lynch AG. Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data. Sci Rep 2018; 8:1300. [PMID: 29358629 PMCID: PMC5778012 DOI: 10.1038/s41598-017-14403-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 09/22/2017] [Indexed: 01/22/2023] Open
Abstract
Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype.
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Affiliation(s)
- James H R Farmery
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
| | - Mike L Smith
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117, Heidelberg, Germany
| | - Andy G Lynch
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- School of Mathematics and Statistics/School of Medicine, University of St Andrews, St Andrews, Fife, KY16 9SS, UK
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36
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Dwight T, Flynn A, Amarasinghe K, Benn DE, Lupat R, Li J, Cameron DL, Hogg A, Balachander S, Candiloro ILM, Wong SQ, Robinson BG, Papenfuss AT, Gill AJ, Dobrovic A, Hicks RJ, Clifton-Bligh RJ, Tothill RW. TERT structural rearrangements in metastatic pheochromocytomas. Endocr Relat Cancer 2018; 25:1-9. [PMID: 28974544 DOI: 10.1530/erc-17-0306] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Accepted: 10/03/2017] [Indexed: 12/21/2022]
Abstract
Pheochromocytomas (PC) and paragangliomas (PGL) are endocrine tumors for which the genetic and clinicopathological features of metastatic progression remain incompletely understood. As a result, the risk of metastasis from a primary tumor cannot be predicted. Early diagnosis of individuals at high risk of developing metastases is clinically important and the identification of new biomarkers that are predictive of metastatic potential is of high value. Activation of TERT has been associated with a number of malignant tumors, including PC/PGL. However, the mechanism of TERT activation in the majority of PC/PGL remains unclear. As TERT promoter mutations occur rarely in PC/PGL, we hypothesized that other mechanisms - such as structural variations - may underlie TERT activation in these tumors. From 35 PC and four PGL, we identified three primary PCs that developed metastases with elevated TERT expression, each of which lacked TERT promoter mutations and promoter DNA methylation. Using whole genome sequencing, we identified somatic structural alterations proximal to the TERT locus in two of these tumors. In both tumors, the genomic rearrangements led to the positioning of super-enhancers proximal to the TERT promoter, that are likely responsible for the activation of the normally tightly repressed TERT expression in chromaffin cells.
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Affiliation(s)
- Trisha Dwight
- Cancer GeneticsKolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia
- The University of SydneySydney, New South Wales, Australia
| | - Aidan Flynn
- The Finsen LaboratoryRigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
- Biotech Research and Innovation Centre (BRIC)University of Copenhagen, Copenhagen N, Denmark
| | | | - Diana E Benn
- Cancer GeneticsKolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia
- The University of SydneySydney, New South Wales, Australia
| | - Richard Lupat
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
| | - Jason Li
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
| | - Daniel L Cameron
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
- Bioinformatics DivisionThe Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical BiologyUniversity of Melbourne, Melbourne, Victoria, Australia
| | - Annette Hogg
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
| | - Shiva Balachander
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
| | - Ida L M Candiloro
- Olivia Newton-John Cancer Research InstituteHeidelberg, Victoria, Australia
- The Department of PathologyUniversity of Melbourne, Parkville, Victoria, Australia
| | - Stephen Q Wong
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
| | - Bruce G Robinson
- Cancer GeneticsKolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia
- The University of SydneySydney, New South Wales, Australia
| | - Anthony T Papenfuss
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
- Bioinformatics DivisionThe Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical BiologyUniversity of Melbourne, Melbourne, Victoria, Australia
- The Sir Peter MacCallum Department of OncologyThe University of Melbourne, Parkville, Victoria, Australia
- The Department of Mathematics and StatisticsUniversity of Melbourne, Parkville, Victoria, Australia
| | - Anthony J Gill
- The University of SydneySydney, New South Wales, Australia
- Cancer Diagnosis and Pathology GroupKolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Alexander Dobrovic
- Olivia Newton-John Cancer Research InstituteHeidelberg, Victoria, Australia
- The Department of PathologyUniversity of Melbourne, Parkville, Victoria, Australia
- School of Cancer MedicineLa Trobe University, Bundoora, Victoria, Australia
| | - Rodney J Hicks
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
- The Sir Peter MacCallum Department of OncologyThe University of Melbourne, Parkville, Victoria, Australia
| | - Roderick J Clifton-Bligh
- Cancer GeneticsKolling Institute, Royal North Shore Hospital, Sydney, New South Wales, Australia
- The University of SydneySydney, New South Wales, Australia
| | - Richard W Tothill
- The Peter MacCallum Cancer CentreEast Melbourne, Victoria, Australia
- The Department of PathologyUniversity of Melbourne, Parkville, Victoria, Australia
- The Sir Peter MacCallum Department of OncologyThe University of Melbourne, Parkville, Victoria, Australia
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37
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Lai TP, Zhang N, Noh J, Mender I, Tedone E, Huang E, Wright WE, Danuser G, Shay JW. A method for measuring the distribution of the shortest telomeres in cells and tissues. Nat Commun 2017; 8:1356. [PMID: 29116081 PMCID: PMC5676791 DOI: 10.1038/s41467-017-01291-z] [Citation(s) in RCA: 104] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 09/07/2017] [Indexed: 01/23/2023] Open
Abstract
Improved methods to measure the shortest (not just average) telomere lengths (TLs) are needed. We developed Telomere Shortest Length Assay (TeSLA), a technique that detects telomeres from all chromosome ends from <1 kb to 18 kb using small amounts of input DNA. TeSLA improves the specificity and efficiency of TL measurements that is facilitated by user friendly image-processing software to automatically detect and annotate band sizes, calculate average TL, as well as the percent of the shortest telomeres. Compared with other TL measurement methods, TeSLA provides more information about the shortest telomeres. The length of telomeres was measured longitudinally in peripheral blood mononuclear cells during human aging, in tissues during colon cancer progression, in telomere-related diseases such as idiopathic pulmonary fibrosis, as well as in mice and other organisms. The results indicate that TeSLA is a robust method that provides a better understanding of the shortest length of telomeres. Short telomeres are a hallmark of senescence and can result in genomic instability as well as cancer progression. Here, the authors present TeSLA, a technique to accurately detect telomeres under 1 kb in length.
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Affiliation(s)
- Tsung-Po Lai
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Ning Zhang
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.,Department of Bioinformatics, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Jungsik Noh
- Department of Bioinformatics, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Ilgen Mender
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Enzo Tedone
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Ejun Huang
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Woodring E Wright
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Gaudenz Danuser
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.,Department of Bioinformatics, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA
| | - Jerry W Shay
- Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.
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38
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Telomeres and telomerase. Methods 2017; 114:1-3. [PMID: 28107827 DOI: 10.1016/j.ymeth.2017.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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