Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age

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Abstract

Introduction: Telomere length (TL) is causally related to aging and several age-related diseases. Specifically, the abundance of short telomeres and the rate of telomere shortening are strong determinants of cell homeostasis. Thus, tools for analyzing and manipulating TL data can vastly improve research focused on aging. Aim: In this study, we developed a semi-automated worksheet, BIOTEL, to generate individual and group TL statistics and provide a crude estimation of biological age.

Results: Data from the Telomere Length Database Project (TLDP) were implemented to the spreadsheet to produce TL statistics. 150 participants were included, and their age was from 21 to 82 years, and the sex distribution ratio was 52.3%: 47.7% (male: female). Initially, we analyzed the fluorescence intensities of telomeres that were measured on metaphase spread leukocytes using three-dimensional (3D) quantitative-fluorescent in situ hybridization (Q-FISH) procedures (3D DNA FISH) with a (C3TA2)3 peptide nucleic acid (PNA) probe. Raw data of fluorescence intensities, demographic data and medical records from the participants were imported into the worksheet. Basic statistical analyses of TL data were provided through BIOTEL, including TL percentiles, specialized charts for TL distribution including the percentage of critically short telomeres (< 3,000 kilobases), individual telomere profiles, and graphs of biological age vs. chronological age.

Conclusion: BIOTEL ver. 2.4 is a functional semi-automated worksheet that calculates a wide range of TL statistics, thus a useful tool with applications in research of telomeres and biological age estimation.

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Biological Age Predictors

Juulia Jylhävä, Nancy Pedersen, Sara Hägg (2017)

The search for reliable indicators of biological age, rather than chronological age, has been ongoing for over three decades, and until recently, largely without success. Advances in the fields of molecular biology have increased the variety of potential candidate biomarkers that may be considered as biological age predictors. In this review, we summarize current state-of-the-art findings considering six potential types of biological age predictors: epigenetic clocks, telomere length, transcriptomic predictors, proteomic predictors, metabolomics-based predictors, and composite biomarker predictors. Promising developments consider multiple combinations of these various types of predictors, which may shed light on the aging process and provide further understanding of what contributes to healthy aging. Thus far, the most promising, new biological age predictor is the epigenetic clock; however its true value as a biomarker of aging requires longitudinal confirmation.

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The epigenetic clock and telomere length are independently associated with chronological age and mortality

Riccardo E Marioni, Sarah E. Harris, Sonia Shah … (2016)

Background: Telomere length and DNA methylation have been proposed as biological clock measures that track chronological age. Whether they change in tandem, or contribute independently to the prediction of chronological age, is not known. Methods: We address these points using data from two Scottish cohorts: the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936). Telomere length and epigenetic clock estimates from DNA methylation were measured in 920 LBC1936 participants (ages 70, 73 and 76 years) and in 414 LBC1921 participants (ages 79, 87 and 90 years). Results: The epigenetic clock changed over time at roughly the same rate as chronological age in both cohorts. Telomere length decreased at 48–67 base pairs per year on average. Weak, non-significant correlations were found between epigenetic clock estimates and telomere length. Telomere length explained 6.6% of the variance in age in LBC1921, the epigenetic clock explained 10.0%, and combined they explained 17.3% (all P < 1 × 10−7). Corresponding figures for the LBC1936 cohort were 14.3%, 11.7% and 19.5% (all P < 1 × 10−12). In a combined cohorts analysis, the respective estimates were 2.8%, 28.5% and 29.5%. Also in a combined cohorts analysis, a one standard deviation increase in baseline epigenetic age was linked to a 22% increased mortality risk (P = 2.6 × 10−4) whereas, in the same model, a one standard deviation increase in baseline telomere length was independently linked to an 11% decreased mortality risk (P = 0.06). Conclusions: These results suggest that telomere length and epigenetic clock estimates are independent predictors of chronological age and mortality risk.

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Automated Assay of Telomere Length Measurement and Informatics for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

Kyle Lapham, Mark N. Kvale, Jue Lin … (2015)

The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort includes DNA specimens extracted from saliva samples of 110,266 individuals. Because of its relationship to aging, telomere length measurement was considered an important biomarker to develop on these subjects. To assay relative telomere length (TL) on this large cohort over a short time period, we created a novel high throughput robotic system for TL analysis and informatics. Samples were run in triplicate, along with control samples, in a randomized design. As part of quality control, we determined the within-sample variability and employed thresholds for the elimination of outlying measurements. Of 106,902 samples assayed, 105,539 (98.7%) passed all quality control (QC) measures. As expected, TL in general showed a decline with age and a sex difference. While telomeres showed a negative correlation with age up to 75 years, in those older than 75 years, age positively correlated with longer telomeres, indicative of an association of longer telomeres with more years of survival in those older than 75. Furthermore, while females in general had longer telomeres than males, this difference was significant only for those older than age 50. An additional novel finding was that the variance of TL between individuals increased with age. This study establishes reliable assay and analysis methodologies for measurement of TL in large, population-based human studies. The GERA cohort represents the largest currently available such resource, linked to comprehensive electronic health and genotype data for analysis.

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Author and article information

Contributors

Aristidis Tsatsakis: URI : http://loop.frontiersin.org/people/683343/overview

Dimitrios Tsoukalas: URI : http://loop.frontiersin.org/people/683529/overview

Persefoni Fragkiadaki: URI : http://loop.frontiersin.org/people/507574/overview

Elena Vakonaki: URI : http://loop.frontiersin.org/people/683408/overview

Manolis Tzatzarakis: URI : http://loop.frontiersin.org/people/683412/overview

Evangelia Sarandi: URI : http://loop.frontiersin.org/people/683482/overview

Dragana Nikitovic: URI : http://loop.frontiersin.org/people/227088/overview

Gerasimos Tsilimidos: URI : http://loop.frontiersin.org/people/683545/overview

Athanasios K. Alegakis: URI : http://loop.frontiersin.org/people/648089/overview

Journal

Journal ID (nlm-ta): Front Genet

Journal ID (iso-abbrev): Front Genet

Journal ID (publisher-id): Front. Genet.

Title: Frontiers in Genetics

Publisher: Frontiers Media S.A.

ISSN (Electronic): 1664-8021

Publication date (Electronic): 19 February 2019

Publication date Collection: 2019

Volume: 10

Electronic Location Identifier: 84

Affiliations

[1] ¹Laboratory of Toxicology, Medical School, University of Crete , Heraklion, Greece

[2] ²Metabolomic Medicine, Health Clinics for Autoimmune and Chronic Diseases , Athens, Greece

[3] ³Laboratory of Anatomy-Histology-Embryology, Medical School, University of Crete , Heraklion, Greece

Author notes

Edited by: Jennifer L. Freeman, Purdue University, United States

Reviewed by: Takamitsu A. Kato, Colorado State University, United States; Tomokazu Tomo Fukuda, Iwate University, Japan

*Correspondence: Aristidis Tsatsakis, toxlab.uoc@ 123456gmail.com

^†These authors have contributed equally to this work

This article was submitted to Toxicogenomics, a section of the journal Frontiers in Genetics

Article

DOI: 10.3389/fgene.2019.00084

PMC ID: 6389611

PubMed ID: 30838025

SO-VID: efeefbb6-6b8c-4f06-896c-9264d5912177

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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 22 October 2018

Date accepted : 28 January 2019

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Figures: 6, Tables: 0, Equations: 0, References: 27, Pages: 8, Words: 0

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Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age

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Genomic Prediction

Most cited references 23

Biological Age Predictors

The epigenetic clock and telomere length are independently associated with chronological age and mortality

Automated Assay of Telomere Length Measurement and Informatics for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

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