{"id":{"repo_id":"vu-aus","oai_identifier":"oai:eprints.vu.edu.au:15226"},"canonical_url":"https://search.dev.ndltd.org/etd/vu-aus/oai:eprints.vu.edu.au:15226","repository":{"repo_id":"vu-aus","name":"Victoria University (Australia)","base_url":"https://vuir.vu.edu.au/cgi/oai2"},"display":{"title":"Prediction of age from DNA","abstract":"Currently DNA profiling methods only compare a suspect’s DNA with DNA left at the crime scene. When there is no suspect, it would be useful for the police to be able to predict what the person of interest looks like by analysing the DNA left behind in a crime scene. Determination of the age of the suspect is an important factor in creating an “identikit” (set of drawings of different features that can be put together to form the face of a person). This study investigated if one could use a correlation between telomere length and age, to predict the age of an individual from their DNA. Telomere length, in buccal cells, of 167 individuals aged between 1 and 96 years old was measured using quantitative real time PCR. The causes for the presence of large variation in telomere lengths in the population were further investigated. The age prediction accuracies were low even after dividing samples into non-related Europeans, males and females (5%, 9% and 1% respectively). Mean telomere lengths of eight age groups representing each decade of life showed a non-linear decrease in telomere length with age. There were variations in telomere lengths even among similarly aged individuals aged 26 years old (n = 10) and age 54 years old (n = 9). One of the factors that causes large inter individual variation could be the inheritance of telomere length. If there is a strong paternal or maternal influence, this could be incorporated into the age prediction formula. Parents’ telomere lengths were compared with children’s telomere lengths.","abstract_html":"Currently DNA profiling methods only compare a suspect’s DNA with DNA left at the crime scene. When there is no suspect, it would be useful for the police to be able to predict what the person of interest looks like by analysing the DNA left behind in a crime scene. Determination of the age of the suspect is an important factor in creating an “identikit” (set of drawings of different features that can be put together to form the face of a person). This study investigated if one could use a correlation between telomere length and age, to predict the age of an individual from their DNA. Telomere length, in buccal cells, of 167 individuals aged between 1 and 96 years old was measured using quantitative real time PCR. The causes for the presence of large variation in telomere lengths in the population were further investigated. The age prediction accuracies were low even after dividing samples into non-related Europeans, males and females (5%, 9% and 1% respectively). Mean telomere lengths of eight age groups representing each decade of life showed a non-linear decrease in telomere length with age. There were variations in telomere lengths even among similarly aged individuals aged 26 years old (n = 10) and age 54 years old (n = 9). One of the factors that causes large inter individual variation could be the inheritance of telomere length. If there is a strong paternal or maternal influence, this could be incorporated into the age prediction formula. Parents’ telomere lengths were compared with children’s telomere lengths.","abstract_has_math":false,"creators":["Hewakapuge, Sudinna Kulangana"],"institution":"Victoria University","degree_name":"phd","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009","date_published":"2009","updated_at":"2026-07-24T06:33:07Z","subjects":["0601 Biochemistry and Cell Biology","0604 Genetics","School of Biomedical and Health Sciences"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Hewakapuge, Sudinna Kulangana"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009"]},{"key":"dc:date.issued","label":"Date","values":["2009"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Biomedical Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Victoria University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://vuir.vu.edu.au/15226/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["phd"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["0601 Biochemistry and Cell Biology","0604 Genetics","School of Biomedical and Health Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://vuir.vu.edu.au/15226/1/hewakapuge.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Currently DNA profiling methods only compare a suspect’s DNA with DNA left at the crime scene. When there is no suspect, it would be useful for the police to be able to predict what the person of interest looks like by analysing the DNA left behind in a crime scene. Determination of the age of the suspect is an important factor in creating an “identikit” (set of drawings of different features that can be put together to form the face of a person). This study investigated if one could use a correlation between telomere length and age, to predict the age of an individual from their DNA. Telomere length, in buccal cells, of 167 individuals aged between 1 and 96 years old was measured using quantitative real time PCR. The causes for the presence of large variation in telomere lengths in the population were further investigated. The age prediction accuracies were low even after dividing samples into non-related Europeans, males and females (5%, 9% and 1% respectively). Mean telomere lengths of eight age groups representing each decade of life showed a non-linear decrease in telomere length with age. There were variations in telomere lengths even among similarly aged individuals aged 26 years old (n = 10) and age 54 years old (n = 9). One of the factors that causes large inter individual variation could be the inheritance of telomere length. If there is a strong paternal or maternal influence, this could be incorporated into the age prediction formula. Parents’ telomere lengths were compared with children’s telomere lengths."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Prediction of age from DNA"]}]}],"canonical_facts":{"dc:creator":["Hewakapuge, Sudinna Kulangana"],"dc:date":["2009"],"dc:date.issued":["2009"],"dc:description.abstract":["Currently DNA profiling methods only compare a suspect’s DNA with DNA left at the crime scene. When there is no suspect, it would be useful for the police to be able to predict what the person of interest looks like by analysing the DNA left behind in a crime scene. Determination of the age of the suspect is an important factor in creating an “identikit” (set of drawings of different features that can be put together to form the face of a person). This study investigated if one could use a correlation between telomere length and age, to predict the age of an individual from their DNA. Telomere length, in buccal cells, of 167 individuals aged between 1 and 96 years old was measured using quantitative real time PCR. The causes for the presence of large variation in telomere lengths in the population were further investigated. The age prediction accuracies were low even after dividing samples into non-related Europeans, males and females (5%, 9% and 1% respectively). Mean telomere lengths of eight age groups representing each decade of life showed a non-linear decrease in telomere length with age. There were variations in telomere lengths even among similarly aged individuals aged 26 years old (n = 10) and age 54 years old (n = 9). One of the factors that causes large inter individual variation could be the inheritance of telomere length. If there is a strong paternal or maternal influence, this could be incorporated into the age prediction formula. Parents’ telomere lengths were compared with children’s telomere lengths."],"dc:format":["text"],"dc:identifier.uri":["https://vuir.vu.edu.au/15226/1/hewakapuge.pdf"],"dc:language":["en"],"dc:publisher.department":["School of Biomedical Sciences"],"dc:publisher.institution":["Victoria University"],"dc:relation.isreferencedby":["https://vuir.vu.edu.au/15226/"],"dc:subject":["0601 Biochemistry and Cell Biology","0604 Genetics","School of Biomedical and Health Sciences"],"dc:title":["Prediction of age from DNA"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["phd"]},"updated_at":"2026-07-24T06:33:07Z"}