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

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 rese...

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Main Authors: Aristidis Tsatsakis, Dimitrios Tsoukalas, Persefoni Fragkiadaki, Elena Vakonaki, Manolis Tzatzarakis, Evangelia Sarandi, Dragana Nikitovic, Gerasimos Tsilimidos, Athanasios K. Alegakis
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-02-01
Series:Frontiers in Genetics
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2019.00084/full
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spelling doaj-d3dbf0f222184656970ff8f086d9370d2020-11-24T22:49:18ZengFrontiers Media S.A.Frontiers in Genetics1664-80212019-02-011010.3389/fgene.2019.00084432132Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological AgeAristidis Tsatsakis0Dimitrios Tsoukalas1Dimitrios Tsoukalas2Persefoni Fragkiadaki3Elena Vakonaki4Manolis Tzatzarakis5Evangelia Sarandi6Evangelia Sarandi7Dragana Nikitovic8Gerasimos Tsilimidos9Athanasios K. Alegakis10Laboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceLaboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceMetabolomic Medicine, Health Clinics for Autoimmune and Chronic Diseases, Athens, GreeceLaboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceLaboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceLaboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceLaboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceMetabolomic Medicine, Health Clinics for Autoimmune and Chronic Diseases, Athens, GreeceLaboratory of Anatomy-Histology-Embryology, Medical School, University of Crete, Heraklion, GreeceMetabolomic Medicine, Health Clinics for Autoimmune and Chronic Diseases, Athens, GreeceLaboratory of Toxicology, Medical School, University of Crete, Heraklion, GreeceIntroduction: 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.https://www.frontiersin.org/article/10.3389/fgene.2019.00084/fulltelomere lengthspreadsheetbiological ageBIOTELaging
collection DOAJ
language English
format Article
sources DOAJ
author Aristidis Tsatsakis
Dimitrios Tsoukalas
Dimitrios Tsoukalas
Persefoni Fragkiadaki
Elena Vakonaki
Manolis Tzatzarakis
Evangelia Sarandi
Evangelia Sarandi
Dragana Nikitovic
Gerasimos Tsilimidos
Athanasios K. Alegakis
spellingShingle Aristidis Tsatsakis
Dimitrios Tsoukalas
Dimitrios Tsoukalas
Persefoni Fragkiadaki
Elena Vakonaki
Manolis Tzatzarakis
Evangelia Sarandi
Evangelia Sarandi
Dragana Nikitovic
Gerasimos Tsilimidos
Athanasios K. Alegakis
Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age
Frontiers in Genetics
telomere length
spreadsheet
biological age
BIOTEL
aging
author_facet Aristidis Tsatsakis
Dimitrios Tsoukalas
Dimitrios Tsoukalas
Persefoni Fragkiadaki
Elena Vakonaki
Manolis Tzatzarakis
Evangelia Sarandi
Evangelia Sarandi
Dragana Nikitovic
Gerasimos Tsilimidos
Athanasios K. Alegakis
author_sort Aristidis Tsatsakis
title Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age
title_short Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age
title_full Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age
title_fullStr Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age
title_full_unstemmed Developing BIOTEL: A Semi-Automated Spreadsheet for Estimating Telomere Length and Biological Age
title_sort developing biotel: a semi-automated spreadsheet for estimating telomere length and biological age
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2019-02-01
description 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.
topic telomere length
spreadsheet
biological age
BIOTEL
aging
url https://www.frontiersin.org/article/10.3389/fgene.2019.00084/full
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