Редактирование: FHL2

Four and a half LIM domains protein 2 (FHL-2) (LIM domain protein DRAL) (Skeletal muscle LIM-protein 3) (SLIM-3) [DRAL] [SLIM3]

==Publications==

{{medline-entry
|title=Age prediction in living: Forensic epigenetic age estimation based on blood samples.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/32721866
|abstract=DNA methylation analysis in a variety of genes has brought promising results in age estimation. The main aim of this study was to evaluate DNA methylation levels from four age-correlated genes, [[ELOVL2]], [[FHL2]], [[EDARADD]] and [[PDE4C]], in blood samples of healthy Portuguese individuals. Fifty-three samples were analyzed through the bisulfite polymerase chain reaction (PCR) sequencing method for CpG dinucleotide methylation status. Linear regression models were used to analyze relationships between methylation levels and chronological age. The highest age-associated CpG in each locus was chosen to build a multi-locus age prediction model (APM), allowing to obtain a Mean Absolute Deviation (MAD) between chronological and predicted ages of 5.35 years, explaining 94.1% of age variation. Validation approaches demonstrated the accuracy and reproducibility of the proposed multi-locus APM. Testing the APM in 51 blood samples from deceased individuals a MAD of 9.72 years was obtained. Potential differences in methylation status between samples from living and deceased individuals could exist since the highest age-correlated CpGs were different in some genes between both groups. In conclusion, our study using the bisulfite PCR sequencing method is in accordance with the high age prediction accuracy of DNA methylation levels in four previously reported age-associated genes. DNA methylation pattern differences between blood samples from living and deceased individuals should be taken into account in forensic contexts.
|mesh-terms=* Adolescent
* Adult
* Aged
* Aging
* Child
* Child, Preschool
* CpG Islands
* Cyclic Nucleotide Phosphodiesterases, Type 4
* DNA Methylation
* Edar-Associated Death Domain Protein
* Fatty Acid Elongases
* Female
* Forensic Genetics
* Humans
* Infant
* LIM-Homeodomain Proteins
* Male
* Middle Aged
* Muscle Proteins
* Polymerase Chain Reaction
* Transcription Factors
* Young Adult
|keywords=* Age the living
* CpGs
* DNA methylation age
* Forensic epigenetics
* Forensic sciences
|full-text-url=https://sci-hub.do/10.1016/j.legalmed.2020.101763
}}
{{medline-entry
|title=Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/31490551
|abstract=Age estimation using DNA methylation levels has been widely investigated in recent years because of its potential application in forensic genetics. The main aim of this study was to develop an age predictor model (APM) for blood samples of deceased individuals based in five age-correlated genes. Fifty-one samples were analyzed through the bisulfite polymerase chain reaction (PCR) sequencing method for DNA methylation evaluation in genes [[ELOVL2]], [[FHL2]], [[EDARADD]], [[PDE4C]], and C1orf132. Linear regression was used to analyze relationships between methylation levels and age. The model using the highest age-correlated CpG from each locus revealed a correlation coefficient of 0.888, explaining 76.3% of age variation, with a mean absolute deviation from the chronological age (MAD) of 6.08 years. The model was validated in an independent test set of 19 samples producing a MAD of 8.84 years. The developed APM seems to be informative and could have potential application in forensic analysis.
|mesh-terms=* Adult
* Aged
* Aged, 80 and over
* Aging
* CpG Islands
* Cyclic Nucleotide Phosphodiesterases, Type 4
* DNA Methylation
* Edar-Associated Death Domain Protein
* Fatty Acid Elongases
* Female
* Forensic Genetics
* Genetic Markers
* Humans
* LIM-Homeodomain Proteins
* Linear Models
* Male
* Middle Aged
* Muscle Proteins
* Polymerase Chain Reaction
* Sequence Analysis, DNA
* Sulfites
* Transcription Factors
* Young Adult
|keywords=* DNA methylation age
* bisulfite PCR sequencing
* deceased individuals
* forensic epigenetics
* forensic science
|full-text-url=https://sci-hub.do/10.1111/1556-4029.14185
}}
{{medline-entry
|title=Genetic associations with age of menopause in familial longevity.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/31188284
|abstract=We hypothesize that mechanisms associated with extended reproductive age may overlap with mechanisms for the selection of genetic variants that slow aging and decrease risk for age-related diseases. Therefore, the goal of this analysis is to search for genetic variants associated with delayed age of menopause (AOM) among women in a study of familial longevity. We performed a meta-analysis of genome-wide association studies for AOM in 1,286 women in the Long Life Family Study (LLFS) and 3,151 women in the Health and Retirement Study, and then sought replication in the Framingham Heart Study (FHS). We used Cox proportional hazard regression of AOM to account for censoring, with a robust variance estimator to adjust for within familial relations. In the meta-analysis, a single nucleotide polymorphism (SNP) previously associated with AOM reached genome-wide significance (rs16991615; HR = 0.74, P = 6.99 × 10). A total of 35 variants reached >10 level of significance and replicated in the FHS and in a 2015 large meta-analysis (ReproGen Consortium). We also identified several novel SNPs associated with AOM including rs3094005: [[MICB]], rs13196892: [[TXNDC5]] | MUTED, rs72774935: [[SSBP2]] | [[ATG10]], rs9447453: [[COL12A1]], rs114298934: [[FHL2]] | [[NCK2]], rs6467223: [[TNPO3]], rs9666274 and rs10766593: [[NAV2]], and rs7281846: [[HSPA13]]. This work indicates novel associations and replicates known associations between genetic variants and AOM. A number of these associations make sense for their roles in aging. Supplemental Digital Content 1, http://links.lww.com/MENO/A420.
|mesh-terms=* Adult
* Age Factors
* Aged
* Aging
* Cohort Studies
* Family
* Female
* Genome, Human
* Genome-Wide Association Study
* Genotype
* Humans
* Longevity
* Male
* Menopause
* Middle Aged
* Polymorphism, Single Nucleotide
* Reproduction
* Young Adult

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7008937
}}
{{medline-entry
|title=DNA methylation of the [[ELOVL2]], [[FHL2]], [[KLF14]], C1orf132/MIR29B2C, and [[TRIM59]] genes for age prediction from blood, saliva, and buccal swab samples.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/30300865
|abstract=Many studies have reported age-associated DNA methylation changes and age-predictive models in various tissues and body fluids. Although age-associated DNA methylation changes can be tissue-specific, a multi-tissue age predictor that is applicable to various tissues and body fluids with considerable prediction accuracy might be valuable. In this study, DNA methylation at 5 CpG sites from the [[ELOVL2]], [[FHL2]], [[KLF14]], C1orf132/MIR29B2C, and [[TRIM59]] genes were investigated in 448 samples from blood, saliva, and buccal swabs. A multiplex methylation SNaPshot assay was developed to measure DNA methylation simultaneously at the 5 CpG sites. Among the 5 CpG sites, 3 CpG sites in the [[ELOVL2]], [[KLF14]] and [[TRIM59]] genes demonstrated strong correlation between DNA methylation and age in all 3 sample types. Age prediction models built separately for each sample type using the DNA methylation values at the 5 CpG sites showed high prediction accuracy with a Mean Absolute Deviation from the chronological age (MAD) of 3.478 years in blood, 3.552 years in saliva and 4.293 years in buccal swab samples. A tissue-combined model constructed with 300 training samples including 100 samples from each blood, saliva and buccal swab samples demonstrated a very strong correlation between predicted and chronological ages (r = 0.937) and a high prediction accuracy with a MAD of 3.844 years in the 148 independent test set samples of 50 blood, 50 saliva and 48 buccal swab samples. Although more validation might be needed, the tissue-combined model's prediction accuracies in each sample type were very much similar to those obtained from each tissue-specific model. The multiplex methylation SNaPshot assay and the age prediction models in our study would be useful in forensic analysis, which frequently involves DNA from blood, saliva, and buccal swab samples.
|mesh-terms=* Acetyltransferases
* Adolescent
* Adult
* Aged
* Aging
* Blood Chemical Analysis
* CpG Islands
* DNA Methylation
* Fatty Acid Elongases
* Forensic Genetics
* Genetic Markers
* Genotyping Techniques
* Humans
* Intracellular Signaling Peptides and Proteins
* Kruppel-Like Transcription Factors
* LIM-Homeodomain Proteins
* Membrane Proteins
* Metalloproteins
* Middle Aged
* Mouth Mucosa
* Muscle Proteins
* Saliva
* Sequence Analysis, DNA
* Sp Transcription Factors
* Transcription Factors
* Tripartite Motif Proteins
* Young Adult
|keywords=* Age
* Blood
* Buccal swab
* DNA methylation
* Methylation SNaPshot
* Saliva
|full-text-url=https://sci-hub.do/10.1016/j.fsigen.2018.09.010
}}
{{medline-entry
|title=DNA methylation in [[ELOVL2]] and C1orf132 correctly predicted chronological age of individuals from three disease groups.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28725932
|abstract=Improving accuracy of the available predictive DNA methods is important for their wider use in routine forensic work. Information on age in the process of identification of an unknown individual may provide important hints that can speed up the process of investigation. DNA methylation markers have been demonstrated to provide accurate age estimation in forensics, but there is growing evidence that DNA methylation can be modified by various factors including diseases. We analyzed DNA methylation profile in five markers from five different genes ([[ELOVL2]], C1orf132, [[KLF14]], [[FHL2]], and [[TRIM59]]) used for forensic age prediction in three groups of individuals with diagnosed medical conditions. The obtained results showed that the selected age-related CpG sites have unchanged age prediction capacity in the group of late onset Alzheimer's disease patients. Aberrant hypermethylation and decreased prediction accuracy were found for [[TRIM59]] and [[KLF14]] markers in the group of early onset Alzheimer's disease suggesting accelerated aging of patients. In the Graves' disease patients, altered DNA methylation profile and modified age prediction accuracy were noted for [[TRIM59]] and [[FHL2]] with aberrant hypermethylation observed for the former and aberrant hypomethylation for the latter. Our work emphasizes high utility of the [[ELOVL2]] and C1orf132 markers for prediction of chronological age in forensics by showing unchanged prediction accuracy in individuals affected by three diseases. The study also demonstrates that artificial neural networks could be a convenient alternative for the forensic predictive DNA analyses.
|mesh-terms=* Acetyltransferases
* Adolescent
* Adult
* Aged
* Aging
* Alzheimer Disease
* Case-Control Studies
* Child
* Child, Preschool
* CpG Islands
* DNA Methylation
* Fatty Acid Elongases
* Female
* Forensic Genetics
* Genetic Markers
* Graves Disease
* Humans
* Intracellular Signaling Peptides and Proteins
* Kruppel-Like Transcription Factors
* LIM-Homeodomain Proteins
* Male
* Membrane Proteins
* Metalloproteins
* Middle Aged
* Multivariate Analysis
* Muscle Proteins
* Neural Networks, Computer
* Sp Transcription Factors
* Transcription Factors
* Tripartite Motif Proteins
* Young Adult
|keywords=* Alzheimer’s disease
* Chronological age
* DNA methylation
* Graves’ disease
* Neural networks
* Prediction accuracy
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5748441
}}
{{medline-entry
|title=Independent validation of DNA-based approaches for age prediction in blood.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28511095
|abstract=Numerous molecular biomarkers have been proposed as predictors of chronological age. Among them, T-cell specific DNA rearrangement and DNA methylation markers have been introduced as forensic age predictors in blood because of their high prediction accuracy. These markers appear highly promising, but for better application to forensic casework sample analysis the proposed markers and genotyping methods must be tested further. In the current study, signal-joint T-cell receptor excision circles (sjTRECs) and DNA methylation markers located in the [[ELOVL2]], C1orf132, [[TRIM59]], [[KLF14]], and [[FHL2]] genes were reanalyzed in 100 Korean blood samples to test their associations with chronological age, using the same analysis platform used in previous reports. Our study replicated the age association test for sjTREC and DNA methylation markers in the 5 genes in an independent validation set of 100 Koreans, and proved that the age predictive performance of the previous models is relatively consistent across different population groups. However, the extent of age association at certain CpG loci was not identical in the Korean and Polish populations; therefore, several age predictive models were retrained with the data obtained here. All of the 3 models retrained with DNA methylation and/or sjTREC data have a CpG site each from the [[ELOVL2]] and [[FHL2]] genes in common, and produced better prediction accuracy than previously reported models. This is attributable to the fact that the retrained model better fits the existing data and that the calculated prediction accuracy could be higher when the training data and the test data are the same. However, it is notable that the combination of different types of markers, i.e., sjTREC and DNA methylation, improved prediction accuracy in the eldest group. Our study demonstrates the usefulness of the proposed markers and the genotyping method in an independent dataset, and suggests the possibility of combining different types of DNA markers to improve prediction accuracy.
|mesh-terms=* Acetyltransferases
* Aging
* Asian Continental Ancestry Group
* CpG Islands
* DNA Methylation
* Fatty Acid Elongases
* Genetic Markers
* Genotyping Techniques
* Humans
* Intracellular Signaling Peptides and Proteins
* Kruppel-Like Transcription Factors
* LIM-Homeodomain Proteins
* Membrane Proteins
* Metalloproteins
* Muscle Proteins
* Receptors, Antigen, T-Cell
* Republic of Korea
* Sp Transcription Factors
* Transcription Factors
* Tripartite Motif Proteins
|keywords=* Age prediction
* Blood
* DNA methylation
* Forensic science
* Korean
* sjTREC
|full-text-url=https://sci-hub.do/10.1016/j.fsigen.2017.04.020
}}
{{medline-entry
|title=Genome-wide DNA methylation analysis reveals hypomethylation in the low-CpG promoter regions in lymphoblastoid cell lines.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28499412
|abstract=Epidemiological studies of DNA methylation profiles may uncover the molecular mechanisms through which genetic and environmental factors contribute to the risk of multifactorial diseases. There are two types of commonly used DNA bioresources, peripheral blood cells (PBCs) and EBV-transformed lymphoblastoid cell lines (LCLs), which are available for genetic epidemiological studies. Therefore, to extend our knowledge of the difference in DNA methylation status between LCLs and PBCs is important in human population studies that use these DNA sources to elucidate the epigenetic risks for multifactorial diseases. We analyzed the methylation status of the autosomes for 192 and 92 DNA samples that were obtained from PBCs and LCLs, respectively, using a human methylation 450 K array. After excluding SNP-associated methylation sites and low-call sites, 400,240 sites were subjected to analysis using a generalized linear model with cell type, sex, and age as the independent variables. We found that the large proportion of sites showed lower methylation levels in LCLs compared with PBCs, which is consistent with previous reports. We also found that significantly different methylation sites tend to be located on the outside of the CpG island and in a region relatively far from the transcription start site. Additionally, we observed that the methylation change of the sites in the low-CpG promoter region was remarkable. Finally, it was shown that the correlation between the chronological age and ageing-associated methylation sites in [[ELOVL2]] and [[FHL2]] in the LCLs was weaker than that in the PBCs. The methylation levels of highly methylated sites of the low-CpG-density promoters in PBCs decreased in the LCLs, suggesting that the methylation sites located in low-CpG-density promoters could be sensitive to demethylation in LCLs. Despite being generated from a single cell type, LCLs may not always be a proxy for DNA from PBCs in studies of epigenome-wide analysis attempting to elucidate the role of epigenetic change in disease risks.
|mesh-terms=* Acetyltransferases
* Aging
* Blood Cells
* Cell Line, Transformed
* CpG Islands
* DNA Methylation
* Fatty Acid Elongases
* Genome-Wide Association Study
* Humans
* LIM-Homeodomain Proteins
* Lymphocyte Activation
* Muscle Proteins
* Transcription Factors
|keywords=* DNA methylation
* Epigenetic epidemiology
* Epigenome-wide analysis
* Human methylation array
* Lymphoblastoid cell lines
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5429538
}}
{{medline-entry
|title=Systemic Age-Associated DNA Hypermethylation of [[ELOVL2]] Gene: In Vivo and In Vitro Evidences of a Cell Replication Process.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27672102
|abstract=Epigenetic remodeling is one of the major features of the aging process. We recently demonstrated that DNA methylation of [[ELOVL2]] and [[FHL2]] CpG islands is highly correlated with age in whole blood. Here we investigated several aspects of age-associated hypermethylation of [[ELOVL2]] and [[FHL2]]. We showed that [[ELOVL2]] methylation is significantly different in primary dermal fibroblast cultures from donors of different ages. Using epigenomic data from public resources, we demonstrated that most of the tissues show [[ELOVL2]] and [[FHL2]] hypermethylation with age. Interestingly, [[ELOVL2]] hypermethylation was not found in tissues with very low replication rate. We demonstrated that [[ELOVL2]] hypermethylation is associated with in vitro cell replication rather than with senescence. We confirmed intra-individual hypermethylation of [[ELOVL2]] and [[FHL2]] in longitudinally assessed participants from the Doetinchem Cohort Study. Finally we showed that, although the methylation of the two loci is not associated with longevity/mortality in the Leiden Longevity Study, [[ELOVL2]] methylation is associated with cytomegalovirus status in nonagenarians, which could be informative of a higher number of replication events in a fraction of whole-blood cells. Collectively, these results indicate that [[ELOVL2]] methylation is a marker of cell divisions occurring during human aging.
|mesh-terms=* Acetyltransferases
* Aged
* Aging
* Cell Proliferation
* Cells, Cultured
* Cellular Senescence
* CpG Islands
* DNA Methylation
* Epigenesis, Genetic
* Fatty Acid Elongases
* Female
* Humans
* LIM-Homeodomain Proteins
* Longevity
* Longitudinal Studies
* Male
* Middle Aged
* Muscle Proteins
* Transcription Factors
|keywords=* Biomarker
* Epigenetics
* FHL2
* Methylation
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861890
}}
{{medline-entry
|title=Donor age and C1orf132/MIR29B2C determine age-related methylation signature of blood after allogeneic hematopoietic stem cell transplantation.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27602173
|abstract=Our recent study demonstrated that DNA methylation status in a set of CpGs located in [[ELOVL2]], C1orf132, [[TRIM59]], [[KLF14]], and [[FHL2]] can accurately predict calendar age in blood. In the present work, we used these markers to evaluate the effect of allogeneic hematopoietic stem cell transplantation (HSCT) on the age-related methylation signature of human blood. DNA methylation in 32 CpGs was investigated in 16 donor-recipient pairs using pyrosequencing. DNA was isolated from the whole blood collected from recipients 27-360 days (mean 126) after HSCT and from the donors shortly before the HSCT. It was found that in the recipients, the predicted age did not correlate with their calendar age but was correlated with the calendar age (r = 0.94, p = 4 × 10(-8)) and predicted age (r = 0.97, p = 5 × 10(-10)) of a respective donor. Despite this strong correlation, the predicted age of a recipient was consistently lower than the predicted age of a donor by 3.7 years (p = 7.8 × 10(-4)). This shift was caused by hypermethylation of the C1orf132 CpGs, for C1orf132 CpG_1. Intriguingly, the recipient-donor methylation difference correlated with calendar age of the donor (r = 0.76, p = 6 × 10(-4)). This finding could not trivially be explained by shifts of the major cellular factions of blood. We confirm the single previous report that after HSCT, the age of the donor is the major determinant of age-specific methylation signature in recipient's blood. A novel finding is the unique methylation dynamics of C1orf132 which encodes MIR29B2C implicated in the self-renewing of hematopoietic stem cells. This observation suggests that C1orf132 could influence graft function after HSCT.
|mesh-terms=* DNA Methylation
* Hematopoietic Stem Cell Transplantation
* Humans
* Tissue Donors
|keywords=* Aging
* Allogeneic hematopoietic stem cell transplantation
* DNA methylation
* MIR29B2C
* Rejuvenation
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012039
}}
{{medline-entry
|title=Forensic age prediction for dead or living samples by use of methylation-sensitive high resolution melting.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27497326
|abstract=Age prediction with epigenetic information is now edging closer to practical use in forensic community. Many age-related CpG (AR-CpG) sites have proven useful in predicting age in pyrosequencing or DNA chip analyses. In this study, a wide range methylation status in the [[ELOVL2]] and [[FHL2]] promoter regions were detected with methylation-sensitive high resolution melting (MS-HRM) in a labor-, time-, and cost-effective manner. Non-linear-distributions of methylation status and chronological age were newly fitted to the logistic curve. Notably, these distributions were revealed to be similar in 22 living blood samples and 52 dead blood samples. Therefore, the difference of methylation status between living and dead samples suggested to be ignorable by MS-HRM. Additionally, the information from [[ELOVL2]] and [[FHL2]] were integrated into a logistic curve fitting model to develop a final predictive model through the multivariate linear regression of logit-linked methylation rates and chronological age with adjusted R(2)=0.83. Mean absolute deviation (MAD) was 7.44 for 74 training set and 7.71 for 30 additional independent test set, indicating that the final predicting model is accurate. This suggests that our MS-HRM-based method has great potential in predicting actual forensic age. 
|mesh-terms=* Age Determination by Skeleton
* Aging
* DNA Methylation
* Forensic Anthropology
* Forensic Genetics
* Polymerase Chain Reaction
|keywords=* Age prediction
* DNA methylation
* Forensic science
* MS-HRM
|full-text-url=https://sci-hub.do/10.1016/j.legalmed.2016.05.001
}}
{{medline-entry
|title=Identification of common and differential mechanisms of glomerulus and tubule senescence in 24-month-old rats by quantitative LC-MS/MS.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27452873
|abstract=Kidney aging together with related renal disease had become a major clinical problem. Understanding the mechanisms of aging was important for suspending senescence and decreasing the incidence of aging-related diseases. In the present work, 24-month-old F344 rats were used as aging rats and 3-month-old rats were used as young controls. Senescence-associated-β-galactosidase staining results showed that the degree of senescence in renal tubules was more severe than that in glomeruli. We performed quantitative LC-MS to assess the differential protein expression profiles of senescent glomeruli and tubules. Bioinformatics analysis showed that aging, response to oxidative stress, nucleotide metabolism, amine acid metabolism, and inflammatory response were common mechanisms of glomerulus and tubule senescence. Differentially expressed proteins network mediated Golgi vesicle transport, actin filament based process, and regulation of cell death were associated with tubule senescence. More importantly, we found that the changes of four and a half LIM protein 2 ([[FHL2]]) were opposite in senescent glomeruli and tubules, and [[FHL2]] could regulate p16 by suppressing T-box 3, which was involved in regulation of senescence in glomeruli and tubules. In conclusion, we assessed the mechanisms of senescence in aging glomeruli and tubules, and the results yielded new insight into kidney senescence.
|mesh-terms=* Actin Cytoskeleton
* Aging
* Animals
* Cell Line
* Cellular Senescence
* Chromatography, Liquid
* Cyclin-Dependent Kinase Inhibitor p16
* Kidney Glomerulus
* Kidney Tubules
* LIM-Homeodomain Proteins
* Muscle Proteins
* Oxidative Stress
* Proteome
* Proteomics
* Rats, Inbred F344
* T-Box Domain Proteins
* Tandem Mass Spectrometry
* Transcription Factors
|keywords=* Aging
* Animal proteomics
* FHL2
* Glomerular
* Tubule
|full-text-url=https://sci-hub.do/10.1002/pmic.201600121
}}
{{medline-entry
|title=Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27337627
|abstract=Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of [[ELOVL2]], [[ASPA]], [[PDE4C]], [[FHL2]], [[CCDC102B]], C1orf132 and chr16:85395429. The detected methylation levels in these loci provide a median absolute age prediction error of ±3.07years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website.
|mesh-terms=* Adolescent
* Adult
* Aged
* Aged, 80 and over
* Aging
* CpG Islands
* DNA Methylation
* Female
* Genetic Loci
* Genetic Markers
* Humans
* Male
* Mass Spectrometry
* Middle Aged
* Multivariate Analysis
* Polymerase Chain Reaction
* Software
* Twins, Monozygotic
* Young Adult
|keywords=* Agena Bioscience EpiTYPER
* CpG sites
* DNA methylation
* Forensic age estimation
* Illumina HumanMethylation 450K
* Multivariate quantile regression
|full-text-url=https://sci-hub.do/10.1016/j.fsigen.2016.06.005
}}
{{medline-entry
|title=Aging-associated DNA methylation changes in middle-aged individuals: the Young Finns study.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/26861258
|abstract=Chronological aging-associated changes in the human DNA methylome have been studied by multiple epigenome-wide association studies (EWASs). Certain CpG sites have been identified as aging-associated in multiple studies, and the majority of the sites identified in various studies show common features regarding location and direction of the methylation change. However, as a whole, the sets of aging-associated CpGs identified in different studies, even with similar tissues and age ranges, show only limited overlap. In this study, we further explore and characterize CpG sites that show close relationship between their DNA methylation level and chronological age during adulthood and which bear the relationship regardless of blood cell type heterogeneity. In this study, with a multivariable regression model adjusted for cell type heterogeneity, we identified 1202 aging-associated CpG sites (a-CpGs, FDR < 5%), in whole blood in a population with an especially narrow age range (40 - 49 years). Repeatedly reported a-CpGs located in genes [[ELOVL2]], [[FHL2]], [[PENK]] and [[KLF14]] were also identified. Regions with aging-associated hypermethylation were enriched regarding several gene ontology (GO) terms (especially in the cluster of developmental processes), whereas hypomethylated sites showed no enrichment. The genes with higher numbers of a-CpG hits were more often hypermethylated with advancing age. The comparison analysis revealed that of the 1202 a-CpGs identified in the present study, 987 were identified as differentially methylated also between nonagenarians and young adults in a previous study (The Vitality 90  study), and importantly, the directions of changes were identical in the previous and in the present study. Here we report that aging-associated DNA methylation features can be identified in a middle-aged population with an age range of only 9 years. A great majority of these sites have been previously reported as aging-associated in a population aged 19 to 90 years. Aging is associated with different types of changes in DNA methylation, clock-like as well as random. We speculate that the a-CpGs identified here in a population with a narrow age-range represent clock-like changes, as they showed concordant methylation behavior in population spanning whole adulthood as well.
|mesh-terms=* Adult
* Age Factors
* Aging
* CpG Islands
* DNA Methylation
* Epigenesis, Genetic
* Epigenomics
* Female
* Genome, Human
* Genome-Wide Association Study
* Humans
* Male
* Middle Aged
* Sex Factors

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746895
}}
{{medline-entry
|title=Development of a forensically useful age prediction method based on DNA methylation analysis.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/26026729
|abstract=Forensic DNA phenotyping needs to be supplemented with age prediction to become a relevant source of information on human appearance. Recent progress in analysis of the human methylome has enabled selection of multiple candidate loci showing linear correlation with chronological age. Practical application in forensic science depends on successful validation of these potential age predictors. In this study, eight DNA methylation candidate loci were analysed using convenient and reliable pyrosequencing technology. A total number of 41 CpG sites was investigated in 420 samples collected from men and women aged from 2 to 75 years. The study confirmed correlation of all the investigated markers with human age. The five most significantly correlated CpG sites in [[ELOVL2]] on 6p24.2, C1orf132 on 1q32.2, [[TRIM59]] on 3q25.33, [[KLF14]] on 7q32.3 and [[FHL2]] on 2q12.2 were chosen to build a prediction model. This restriction allowed the technical analysis to be simplified without lowering the prediction accuracy significantly. Model parameters for a discovery set of 300 samples were R(2)=0.94 and the standard error of the estimate=4.5 years. An independent set of 120 samples was used to test the model performance. Mean absolute deviation for this testing set was 3.9 years. The number of correct predictions ±5 years achieved a very high level of 86.7% in the age category 2-19 and gradually decreased to 50% in the age category 60-75. The prediction model was deterministic for individuals belonging to these two extreme age categories. The developed method was implemented in a freely available online age prediction calculator. 
|mesh-terms=* Adolescent
* Adult
* Aged
* Aging
* Child
* Child, Preschool
* CpG Islands
* DNA
* DNA Methylation
* Female
* Forensic Genetics
* Humans
* Male
* Middle Aged
* Predictive Value of Tests
|keywords=* DNA methylation
* DNA-based age prediction
* Forensic science
* Prediction modelling
|full-text-url=https://sci-hub.do/10.1016/j.fsigen.2015.05.001
}}
{{medline-entry
|title=Genome-wide age-related changes in DNA methylation and gene expression in human PBMCs.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/24789080
|abstract=Aging is a progressive process that results in the accumulation of intra- and extracellular alterations that in turn contribute to a reduction in health. Age-related changes in DNA methylation have been reported before and may be responsible for aging-induced changes in gene expression, although a causal relationship has yet to be shown. Using genome-wide assays, we analyzed age-induced changes in DNA methylation and their effect on gene expression with and without transient induction with the synthetic transcription modulating agent WY14,643. To demonstrate feasibility of the approach, we isolated peripheral blood mononucleated cells (PBMCs) from five young and five old healthy male volunteers and cultured them with or without WY14,643. Infinium 450K BeadChip and Affymetrix Human Gene 1.1 ST expression array analysis revealed significant differential methylation of at least 5 % (ΔYO > 5 %) at 10,625 CpG sites between young and old subjects, but only a subset of the associated genes were also differentially expressed. Age-related differential methylation of previously reported epigenetic biomarkers of aging including [[ELOVL2]], [[FHL2]], [[PENK]], and [[KLF14]] was confirmed in our study, but these genes did not display an age-related change in gene expression in PBMCs. Bioinformatic analysis revealed that differentially methylated genes that lack an age-related expression change predominantly represent genes involved in carcinogenesis and developmental processes, and expression of most of these genes were silenced in PBMCs. No changes in DNA methylation were found in genes displaying transiently induced changes in gene expression. In conclusion, aging-induced differential methylation often targets developmental genes and occurs mostly without change in gene expression.
|mesh-terms=* Adult
* Aged
* Aging
* Cells, Cultured
* DNA Methylation
* Epigenesis, Genetic
* Gene Expression Regulation, Developmental
* Genome, Human
* Healthy Volunteers
* Humans
* Leukocytes, Mononuclear
* Male
* Middle Aged
* RNA

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4082572
}}
{{medline-entry
|title=Methylation of [[ELOVL2]] gene as a new epigenetic marker of age.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/23061750
|abstract=The discovery of biomarkers able to predict biological age of individuals is a crucial goal in aging research. Recently, researchers' attention has turn toward epigenetic markers of aging. Using the Illumina Infinium HumanMethylation450 BeadChip on whole blood DNA from a small cohort of 64 subjects of different ages, we identified 3 regions, the CpG islands of [[ELOVL2]], [[FHL2]], and [[PENK]] genes, whose methylation level strongly correlates with age. These results were confirmed by the Sequenom's EpiTYPER assay on a larger cohort of 501 subjects from 9 to 99 years, including 7 cord blood samples. Among the 3 genes, [[ELOVL2]] shows a progressive increase in methylation that begins since the very first stage of life (Spearman's correlation coefficient = 0.92) and appears to be a very promising biomarker of aging.
|mesh-terms=* Acetyltransferases
* Adolescent
* Adult
* Aged
* Aged, 80 and over
* Aging
* Child
* CpG Islands
* DNA Methylation
* Enkephalins
* Epigenesis, Genetic
* Fatty Acid Elongases
* Female
* Fetal Blood
* Genetic Markers
* Genome, Human
* Humans
* LIM-Homeodomain Proteins
* Male
* Middle Aged
* Muscle Proteins
* Oligonucleotide Array Sequence Analysis
* Protein Precursors
* Transcription Factors

|full-text-url=https://sci-hub.do/10.1111/acel.12005
}}
{{medline-entry
|title=Developmental evolution of the delayed rectifier current IKs in canine heart appears dependent on the beta subunit minK.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/15851242
|abstract=We tested the hypothesis that the developmental changes occurring in I(Kr) and I(Ks) can be explained by changes in the expression of [[ERG]] encoding I(Kr), and [[KCNQ1]], the beta subunit minK, and the recently reported subunit [[FHL2]] encoding I(Ks). The delayed rectifier current contributes importantly to the developmental evolution of the canine myocardial action potential. Specifically, in left ventricular epicardial myocytes, I(Ks) is absent and I(Kr) is the major repolarizing current until age 4 weeks. With subsequent development, I(Ks) density increases and I(Kr) decreases, resulting in an altered voltage-time course of repolarization. We used Western blotting and real-time polymerase chain reaction to compare the expression of [[ERG]], [[KCNQ1]], minK, and [[FHL2]] in 1-week-old pups and adult dogs. [[ERG]] levels are high at 1 week and decrease significantly with age, consistent with developmental decrease in I(Kr). Whereas expression of [[KCNQ1]] and [[FHL2]] is unchanged between the two age groups, minK is minimally expressed at 1 week and increases in adults, consistent with developmental increase in I(Ks). A reduction in [[ERG]] explains the developmental decrease in I(Kr), whereas the accessory subunit minK appears to be the critical determinant of developmental evolution of I(Ks).
|mesh-terms=* Aging
* Animals
* Blotting, Western
* Cation Transport Proteins
* Dogs
* Ether-A-Go-Go Potassium Channels
* Female
* Heart Ventricles
* Male
* Myocytes, Cardiac
* Pericardium
* Polymerase Chain Reaction
* Potassium Channels, Voltage-Gated
* RNA, Messenger

|full-text-url=https://sci-hub.do/10.1016/j.hrthm.2004.08.012
}}