The Experts below are selected from a list of 3612 Experts worldwide ranked by ideXlab platform
Jana Naue - One of the best experts on this subject based on the ideXlab platform.
-
analysis of age dependent dna methylation changes in plucked hair samples using Massive Parallel Sequencing
Rechtsmedizin, 2021Co-Authors: Jana Naue, Ulrike Schmidt, Julia Winkelmann, Sabine LutzbonengelAbstract:The analysis of age-dependent DNA methylation changes is a valuable tool in epigenetic research and forensic genetics. With some exceptions, most studies in the past concentrated on the analysis of blood, buccal, and saliva samples. Another important sample type in forensic investigations is hair, where age-dependent DNA methylation has not been investigated so far. In this pilot study a deeper look was taken at the possibilities and challenges of DNA methylation analysis in hair. The DNA methylation of selected age-dependent 5’-C-phosphate-G‑3’ (CpG) sites were characterized for their potential use as a biomarker for age prediction using plucked hair samples and Massive Parallel Sequencing. Plucked hair roots of 49 individuals were included in the study. The DNA methylation of 31 hairs was successfully analyzed. The DNA methylation pattern of 10 loci, including ELOVL2, F5, KLF14, and TRIM59, was determined by amplicon-based Massive Parallel Sequencing. Age-dependent changes were found for several markers. The results demonstrate the possible use of already established age-dependent markers but at the same time they have tissue/cell type-specific characteristics. Special challenges such as low amounts of DNA and degraded DNA as well as the possible heterogeneous cellular composition of plucked hair samples, have to be considered.
-
proof of concept study of age dependent dna methylation markers across different tissues by Massive Parallel Sequencing
Forensic Science International-genetics, 2018Co-Authors: Huub C J Hoefsloot, Ate D Kloosterman, Pernette J Verschure, Timo Sanger, Sabine Lutzbonengel, Jana NaueAbstract:The use of DNA methylation (DNAm) for chronological age determination has been widely investigated within the last few years for its application within the field of forensic genetics. The majority of forensic studies are based on blood, saliva, and buccal cell samples, respectively. Although these types of samples represent an extensive amount of traces found at a crime scene or are readily available from individuals, samples from other tissues can be relevant for forensic investigations. Age determination could be important for cases involving unidentifiable bodies and based on remaining soft tissue e.g. brain and muscle, or completely depend on hard tissue such as bone. However, due to the cell type specificity of DNAm, it is not evident whether cell type specific age-dependent CpG positions are also applicable for age determination in other cell types. Within this pilot study, we investigated whether 13 previously selected age-dependent loci based on whole blood analysis including amongst others ELOVL2, TRIM59, F5, and KLF14 also have predictive value in other forensically relevant tissues. Samples of brain, bone, muscle, buccal swabs, and whole blood of 29 deceased individuals (age range 0-87 years) were analyzed for these 13 age-dependent markers using Massive Parallel Sequencing. Seven of these loci did show age-dependency in all five tissues. The change of DNAm during lifetime was different in the set of tissues analyzed, and sometimes other CpG sites within the loci showed a higher age-dependency. This pilot study shows the potential of existing blood DNAm markers for age-determination to analyze other tissues than blood. We identified seven known blood-based DNAm markers for use in muscle, brain, bone, buccal swabs, and blood. Nevertheless, a different reference set for each tissue is needed to adapt for tissue-specific changes of the DNAm over time.
-
chronological age prediction based on dna methylation Massive Parallel Sequencing and random forest regression
Forensic Science International-genetics, 2017Co-Authors: Huub C J Hoefsloot, Olaf R F Mook, Laura Rijlaarsdamhoekstra, Marloes C H Van Der Zwalm, Peter Henneman, Ate D Kloosterman, Pernette J Verschure, Jana NaueAbstract:The use of DNA methylation (DNAm) to obtain additional information in forensic investigations showed to be a promising and increasing field of interest. Prediction of the chronological age based on age-dependent changes in the DNAm of specific CpG sites within the genome is one such potential application. Here we present an age-prediction tool for whole blood based on Massive Parallel Sequencing (MPS) and a random forest machine learning algorithm. MPS allows accurate DNAm determination of pre-selected markers and neighboring CpG-sites to identify the best age-predictive markers for the age-prediction tool. 15 age-dependent markers of different loci were initially chosen based on publicly available 450K microarray data, and 13 finally selected for the age tool based on MPS (DDO, ELOVL2, F5, GRM2, HOXC4, KLF14, LDB2, MEIS1-AS3, NKIRAS2, RPA2, SAMD10, TRIM59, ZYG11A). Whole blood samples of 208 individuals were used for training of the algorithm and a further 104 individuals were used for model evaluation (age 18-69). In the case of KLF14, LDB2, SAMD10, and GRM2, neighboring CpG sites and not the initial 450K sites were chosen for the final model. Cross-validation of the training set leads to a mean absolute deviation (MAD) of 3.21 years and a root-mean square error (RMSE) of 3.97 years. Evaluation of model performance using the test set showed a comparable result (MAD 3.16 years, RMSE 3.93 years). A reduced model based on only the top 4 markers (ELOVL2, F5, KLF14, and TRIM59) resulted in a RMSE of 4.19 years and MAD of 3.24 years for the test set (cross validation training set: RMSE 4.63 years, MAD 3.64 years). The amplified region was additionally investigated for occurrence of SNPs in case of an aberrant DNAm result, which in some cases can be an indication for a deviation in DNAm. Our approach uncovered well-known DNAm age-dependent markers, as well as additional new age-dependent sites for improvement of the model, and allowed the creation of a reliable and accurate epigenetic tool for age-prediction without restriction to a linear change in DNAm with age.
Vladimir Zachar - One of the best experts on this subject based on the ideXlab platform.
-
correction transcriptional dissection of human limbal niche compartments by Massive Parallel Sequencing
PLOS ONE, 2013Co-Authors: Danson V Muttuvelu, Jeppe Emmersen, Chris Bath, Henrik Vorum, Jesper Hjortdal, Vladimir ZacharAbstract:The Supporting Information Tables S1-S4 were erroneously omitted. Please see the missing Tables below. Table S1: Click here for additional data file.(15K, docx) Table S2: Click here for additional data file.(27K, docx) Table S3: Click here for additional data file.(61K, docx) Table S4: Click here for additional data file.(45K, docx)
-
transcriptional dissection of human limbal niche compartments by Massive Parallel Sequencing
PLOS ONE, 2013Co-Authors: Danson V Muttuvelu, Jeppe Emmersen, Chris Bath, Henrik Vorum, Jesper Hjortdal, Vladimir ZacharAbstract:Corneal epithelium is maintained throughout life by well-orchestrated proliferation of limbal epithelial stem cells (LESCs), followed by migration and maturation centripetally towards the ocular surface. Disturbance of LESCs can potentially lead to a blinding condition, which can be reversed by reconstitution of a functional LESC pool. The current clinical procedures are effective to some degree, however, deeper knowledge of the molecular interplay within the limbal niche is necessary to achieve a fully satisfactory patient outcome. The present study was thus undertaken to carry out a comprehensive transcriptome analysis of four distinct human limbal compartments, including basal limbal crypts (BLCs), superficial limbal crypts (SLCs), cornea, and the supporting stroma, with the aid of laser capture microdissection and deep RNA Sequencing. The tissue harvest pipeline was rigorously optimized so that the exposure to cold ischemia would be less than five minutes. The global gene ontology analysis confirmed existence of primitive cells in BLCs, migratory and activated cells in SLCs, and differentiated cells in cornea. Interestingly, many significantly upregulated genes in SLCs mapped to processes involved in regulation of vasculature, such as sFLT1. In contrast, BLCs exhibited many genes mapping to neurogenic processes and processes related to cell development. The primitive nature of BLCs was, furthermore, confirmed by the KEGG pathway analysis, and some potential regulators of LESCs were revealed, such as Lrig1 and SOX9. The analysis also yielded comprehensive lists of uniquely expressed genes in both BLCs and cornea, which may be useful to identify possible biomarkers. In conclusion, the current investigation provides new insight into the relationship between distinct cell populations within the limbal niche, identifies candidates to be verified for novel biological functions, and yields a wealth of information for prospective data mining.
Pernette J Verschure - One of the best experts on this subject based on the ideXlab platform.
-
proof of concept study of age dependent dna methylation markers across different tissues by Massive Parallel Sequencing
Forensic Science International-genetics, 2018Co-Authors: Huub C J Hoefsloot, Ate D Kloosterman, Pernette J Verschure, Timo Sanger, Sabine Lutzbonengel, Jana NaueAbstract:The use of DNA methylation (DNAm) for chronological age determination has been widely investigated within the last few years for its application within the field of forensic genetics. The majority of forensic studies are based on blood, saliva, and buccal cell samples, respectively. Although these types of samples represent an extensive amount of traces found at a crime scene or are readily available from individuals, samples from other tissues can be relevant for forensic investigations. Age determination could be important for cases involving unidentifiable bodies and based on remaining soft tissue e.g. brain and muscle, or completely depend on hard tissue such as bone. However, due to the cell type specificity of DNAm, it is not evident whether cell type specific age-dependent CpG positions are also applicable for age determination in other cell types. Within this pilot study, we investigated whether 13 previously selected age-dependent loci based on whole blood analysis including amongst others ELOVL2, TRIM59, F5, and KLF14 also have predictive value in other forensically relevant tissues. Samples of brain, bone, muscle, buccal swabs, and whole blood of 29 deceased individuals (age range 0-87 years) were analyzed for these 13 age-dependent markers using Massive Parallel Sequencing. Seven of these loci did show age-dependency in all five tissues. The change of DNAm during lifetime was different in the set of tissues analyzed, and sometimes other CpG sites within the loci showed a higher age-dependency. This pilot study shows the potential of existing blood DNAm markers for age-determination to analyze other tissues than blood. We identified seven known blood-based DNAm markers for use in muscle, brain, bone, buccal swabs, and blood. Nevertheless, a different reference set for each tissue is needed to adapt for tissue-specific changes of the DNAm over time.
-
chronological age prediction based on dna methylation Massive Parallel Sequencing and random forest regression
Forensic Science International-genetics, 2017Co-Authors: Huub C J Hoefsloot, Olaf R F Mook, Laura Rijlaarsdamhoekstra, Marloes C H Van Der Zwalm, Peter Henneman, Ate D Kloosterman, Pernette J Verschure, Jana NaueAbstract:The use of DNA methylation (DNAm) to obtain additional information in forensic investigations showed to be a promising and increasing field of interest. Prediction of the chronological age based on age-dependent changes in the DNAm of specific CpG sites within the genome is one such potential application. Here we present an age-prediction tool for whole blood based on Massive Parallel Sequencing (MPS) and a random forest machine learning algorithm. MPS allows accurate DNAm determination of pre-selected markers and neighboring CpG-sites to identify the best age-predictive markers for the age-prediction tool. 15 age-dependent markers of different loci were initially chosen based on publicly available 450K microarray data, and 13 finally selected for the age tool based on MPS (DDO, ELOVL2, F5, GRM2, HOXC4, KLF14, LDB2, MEIS1-AS3, NKIRAS2, RPA2, SAMD10, TRIM59, ZYG11A). Whole blood samples of 208 individuals were used for training of the algorithm and a further 104 individuals were used for model evaluation (age 18-69). In the case of KLF14, LDB2, SAMD10, and GRM2, neighboring CpG sites and not the initial 450K sites were chosen for the final model. Cross-validation of the training set leads to a mean absolute deviation (MAD) of 3.21 years and a root-mean square error (RMSE) of 3.97 years. Evaluation of model performance using the test set showed a comparable result (MAD 3.16 years, RMSE 3.93 years). A reduced model based on only the top 4 markers (ELOVL2, F5, KLF14, and TRIM59) resulted in a RMSE of 4.19 years and MAD of 3.24 years for the test set (cross validation training set: RMSE 4.63 years, MAD 3.64 years). The amplified region was additionally investigated for occurrence of SNPs in case of an aberrant DNAm result, which in some cases can be an indication for a deviation in DNAm. Our approach uncovered well-known DNAm age-dependent markers, as well as additional new age-dependent sites for improvement of the model, and allowed the creation of a reliable and accurate epigenetic tool for age-prediction without restriction to a linear change in DNAm with age.
Chris Bath - One of the best experts on this subject based on the ideXlab platform.
-
correction transcriptional dissection of human limbal niche compartments by Massive Parallel Sequencing
PLOS ONE, 2013Co-Authors: Danson V Muttuvelu, Jeppe Emmersen, Chris Bath, Henrik Vorum, Jesper Hjortdal, Vladimir ZacharAbstract:The Supporting Information Tables S1-S4 were erroneously omitted. Please see the missing Tables below. Table S1: Click here for additional data file.(15K, docx) Table S2: Click here for additional data file.(27K, docx) Table S3: Click here for additional data file.(61K, docx) Table S4: Click here for additional data file.(45K, docx)
-
transcriptional dissection of human limbal niche compartments by Massive Parallel Sequencing
PLOS ONE, 2013Co-Authors: Danson V Muttuvelu, Jeppe Emmersen, Chris Bath, Henrik Vorum, Jesper Hjortdal, Vladimir ZacharAbstract:Corneal epithelium is maintained throughout life by well-orchestrated proliferation of limbal epithelial stem cells (LESCs), followed by migration and maturation centripetally towards the ocular surface. Disturbance of LESCs can potentially lead to a blinding condition, which can be reversed by reconstitution of a functional LESC pool. The current clinical procedures are effective to some degree, however, deeper knowledge of the molecular interplay within the limbal niche is necessary to achieve a fully satisfactory patient outcome. The present study was thus undertaken to carry out a comprehensive transcriptome analysis of four distinct human limbal compartments, including basal limbal crypts (BLCs), superficial limbal crypts (SLCs), cornea, and the supporting stroma, with the aid of laser capture microdissection and deep RNA Sequencing. The tissue harvest pipeline was rigorously optimized so that the exposure to cold ischemia would be less than five minutes. The global gene ontology analysis confirmed existence of primitive cells in BLCs, migratory and activated cells in SLCs, and differentiated cells in cornea. Interestingly, many significantly upregulated genes in SLCs mapped to processes involved in regulation of vasculature, such as sFLT1. In contrast, BLCs exhibited many genes mapping to neurogenic processes and processes related to cell development. The primitive nature of BLCs was, furthermore, confirmed by the KEGG pathway analysis, and some potential regulators of LESCs were revealed, such as Lrig1 and SOX9. The analysis also yielded comprehensive lists of uniquely expressed genes in both BLCs and cornea, which may be useful to identify possible biomarkers. In conclusion, the current investigation provides new insight into the relationship between distinct cell populations within the limbal niche, identifies candidates to be verified for novel biological functions, and yields a wealth of information for prospective data mining.
Ate D Kloosterman - One of the best experts on this subject based on the ideXlab platform.
-
proof of concept study of age dependent dna methylation markers across different tissues by Massive Parallel Sequencing
Forensic Science International-genetics, 2018Co-Authors: Huub C J Hoefsloot, Ate D Kloosterman, Pernette J Verschure, Timo Sanger, Sabine Lutzbonengel, Jana NaueAbstract:The use of DNA methylation (DNAm) for chronological age determination has been widely investigated within the last few years for its application within the field of forensic genetics. The majority of forensic studies are based on blood, saliva, and buccal cell samples, respectively. Although these types of samples represent an extensive amount of traces found at a crime scene or are readily available from individuals, samples from other tissues can be relevant for forensic investigations. Age determination could be important for cases involving unidentifiable bodies and based on remaining soft tissue e.g. brain and muscle, or completely depend on hard tissue such as bone. However, due to the cell type specificity of DNAm, it is not evident whether cell type specific age-dependent CpG positions are also applicable for age determination in other cell types. Within this pilot study, we investigated whether 13 previously selected age-dependent loci based on whole blood analysis including amongst others ELOVL2, TRIM59, F5, and KLF14 also have predictive value in other forensically relevant tissues. Samples of brain, bone, muscle, buccal swabs, and whole blood of 29 deceased individuals (age range 0-87 years) were analyzed for these 13 age-dependent markers using Massive Parallel Sequencing. Seven of these loci did show age-dependency in all five tissues. The change of DNAm during lifetime was different in the set of tissues analyzed, and sometimes other CpG sites within the loci showed a higher age-dependency. This pilot study shows the potential of existing blood DNAm markers for age-determination to analyze other tissues than blood. We identified seven known blood-based DNAm markers for use in muscle, brain, bone, buccal swabs, and blood. Nevertheless, a different reference set for each tissue is needed to adapt for tissue-specific changes of the DNAm over time.
-
chronological age prediction based on dna methylation Massive Parallel Sequencing and random forest regression
Forensic Science International-genetics, 2017Co-Authors: Huub C J Hoefsloot, Olaf R F Mook, Laura Rijlaarsdamhoekstra, Marloes C H Van Der Zwalm, Peter Henneman, Ate D Kloosterman, Pernette J Verschure, Jana NaueAbstract:The use of DNA methylation (DNAm) to obtain additional information in forensic investigations showed to be a promising and increasing field of interest. Prediction of the chronological age based on age-dependent changes in the DNAm of specific CpG sites within the genome is one such potential application. Here we present an age-prediction tool for whole blood based on Massive Parallel Sequencing (MPS) and a random forest machine learning algorithm. MPS allows accurate DNAm determination of pre-selected markers and neighboring CpG-sites to identify the best age-predictive markers for the age-prediction tool. 15 age-dependent markers of different loci were initially chosen based on publicly available 450K microarray data, and 13 finally selected for the age tool based on MPS (DDO, ELOVL2, F5, GRM2, HOXC4, KLF14, LDB2, MEIS1-AS3, NKIRAS2, RPA2, SAMD10, TRIM59, ZYG11A). Whole blood samples of 208 individuals were used for training of the algorithm and a further 104 individuals were used for model evaluation (age 18-69). In the case of KLF14, LDB2, SAMD10, and GRM2, neighboring CpG sites and not the initial 450K sites were chosen for the final model. Cross-validation of the training set leads to a mean absolute deviation (MAD) of 3.21 years and a root-mean square error (RMSE) of 3.97 years. Evaluation of model performance using the test set showed a comparable result (MAD 3.16 years, RMSE 3.93 years). A reduced model based on only the top 4 markers (ELOVL2, F5, KLF14, and TRIM59) resulted in a RMSE of 4.19 years and MAD of 3.24 years for the test set (cross validation training set: RMSE 4.63 years, MAD 3.64 years). The amplified region was additionally investigated for occurrence of SNPs in case of an aberrant DNAm result, which in some cases can be an indication for a deviation in DNAm. Our approach uncovered well-known DNAm age-dependent markers, as well as additional new age-dependent sites for improvement of the model, and allowed the creation of a reliable and accurate epigenetic tool for age-prediction without restriction to a linear change in DNAm with age.
