scholarly journals Epigenetic age prediction in semen – marker selection and model development

Aging ◽  
2021 ◽  
Author(s):  
Aleksandra Pisarek ◽  
Ewelina Pośpiech ◽  
Antonia Heidegger ◽  
Catarina Xavier ◽  
Anna Papież ◽  
...  

Aging Cell ◽  
2021 ◽  
Author(s):  
Daniel J. Simpson ◽  
Tamir Chandra


2020 ◽  
Vol 47 ◽  
pp. 101763
Author(s):  
Helena Correia Dias ◽  
Eugénia Cunha ◽  
Francisco Corte Real ◽  
Licínio Manco


2021 ◽  
Author(s):  
Patrick T Griffin ◽  
Alice E Kane ◽  
Alexandre Trapp ◽  
Jien Li ◽  
Maeve S McNamara ◽  
...  

Epigenetic "clocks" based on DNA methylation (DNAme) are the most robust and widely employed aging biomarker. They have been built for numerous species and reflect gold-standard interventions that extend lifespan. However, conventional methods for measuring epigenetic clocks are expensive and low-throughput. Here, we describe Tagmentation-based Indexing for Methylation Sequencing (TIME-Seq) for ultra-cheap and scalable targeted methylation sequencing of epigenetic clocks and other DNAme biomarkers. Using TIME-Seq, we built and validated inexpensive epigenetic clocks based on genomic and ribosomal DNAme in hundreds of mice and human samples. We also discover it is possible to accurately predict age from extremely low-cost shallow sequencing (e.g., 10,000 reads) of TIME-Seq libraries using scAge, a probabilistic age-prediction algorithm originally applied to single cells. Together, these methods reduce the cost of DNAme biomarker analysis by more than two orders of magnitude, thereby expanding and democratizing their use in aging research, clinical trials, and disease diagnosis.



Author(s):  
Danuta Piniewska-Róg ◽  
Antonia Heidegger ◽  
Ewelina Pośpiech ◽  
Catarina Xavier ◽  
Aleksandra Pisarek ◽  
...  

AbstractDNA methylation-based clocks provide the most accurate age estimates with practical implications for clinical and forensic genetics. However, the effects of external factors that may influence the estimates are poorly studied. Here, we evaluated the effect of alcohol consumption on epigenetic age prediction in a cohort of extreme alcohol abusers. Blood samples from deceased alcohol abusers and age- and sex-matched controls were analyzed using the VISAGE enhanced tool for age prediction from somatic tissues that enables examination of 44 CpGs within eight age markers. Significantly altered DNA methylation was recorded for alcohol abusers in MIR29B2CHG. This resulted in a mean predicted age of 1.4 years higher compared to the controls and this trend increased in older individuals. The association of alcohol abuse with epigenetic age acceleration, as determined by the prediction analysis performed based on MIR29B2CHG, was small but significant (β = 0.190; P-value = 0.007). However, the observed alteration in DNA methylation of MIR29B2CHG had a non-significant effect on age estimation with the VISAGE age prediction model. The mean absolute error in the alcohol-abusing cohort was 3.1 years, compared to 3.3 years in the control group. At the same time, upregulation of MIR29B2CHG expression may have a biological function, which merits further studies.



2022 ◽  
Vol 12 ◽  
Author(s):  
N. Kuzub ◽  
V. Smialkovska ◽  
V. Momot ◽  
V. Moseiko ◽  
O. Lushchak ◽  
...  

Epigenetic clocks are the models, which use CpG methylation levels for the age prediction of an organism. Although there were several epigenetic clocks developed there is a demand for development and evaluation of the relatively accurate and sensitive epigenetic clocks that can be used for routine research purposes. In this study, we evaluated two epigenetic clock models based on the 4 CpG sites and 2 CpG sites in the human genome using the pyrosequencing method for their methylation level estimation. The study sample included 153 people from the Ukrainian population with the age from 0 to 101. Both models showed a high correlation with the chronological age in our study sample (R2 = 0.85 for the 2 CpG model and R2 = 0.92 for the 4 CpG model). We also estimated the accuracy metrics of the age prediction in our study sample. For the age group from 18 to 80 MAD was 5.1 years for the 2 CpG model and 4.1 years for the 4 CpG model. In this regard, we can conclude, that the models evaluated in the study have good age predictive accuracy, and can be used for the epigenetic age evaluation due to the relative simplicity and time-effectiveness.



2020 ◽  
Vol 35 (11) ◽  
pp. 2579-2588 ◽  
Author(s):  
Brent M Hanson ◽  
Xin Tao ◽  
Yiping Zhan ◽  
Timothy G Jenkins ◽  
Scott J Morin ◽  
...  

Abstract STUDY QUESTION Is poor ovarian response associated with a change in predicted age based on a DNA methylation-derived age prediction model (the Horvath algorithm) in white blood cells (WBCs) or cumulus cells (CCs)? SUMMARY ANSWER In young women, poor ovarian response is associated with epigenetic age acceleration within WBC samples but is not associated with age-related changes in CC. WHAT IS KNOWN ALREADY The majority of human tissues follow predictable patterns of methylation which can be assessed throughout a person’s lifetime. DNA methylation patterns may serve as informative biomarkers of aging within various tissues. Horvath’s ‘epigenetic clock’, which is a DNA methylation-derived age prediction model, accurately predicts a subject’s true chronologic age when applied to WBC but not to CC. STUDY DESIGN, SIZE, DURATION A prospective cohort study was carried out involving 175 women undergoing ovarian stimulation between February 2017 and December 2018. Women were grouped according to a poor (≤5 oocytes retrieved) or good (>5 oocytes) response to ovarian stimulation. Those with polycystic ovary syndrome (PCOS) (n = 35) were placed in the good responder group. PARTICIPANTS/MATERIALS, SETTING, METHODS DNA methylation patterns from WBC and CC were assessed for infertile patients undergoing ovarian stimulation at a university-affiliated private practice. DNA was isolated from peripheral blood samples and CC. Bisulfite conversion was then performed and a DNA methylation array was utilized to measure DNA methylation levels throughout the genome. Likelihood ratio tests were utilized to assess the relationship between predicted age, chronologic age and ovarian response. MAIN RESULTS AND THE ROLE OF CHANCE The Horvath-predicted age for WBC samples was consistent with patients’ chronologic age. However, predicted age from analysis of CC was younger than chronologic age. In subgroup analysis of women less than 38 years of age, poor ovarian response was associated with an accelerated predicted age in WBC (P = 0.017). Poor ovarian response did not affect the Horvath-predicted age based on CC samples (P = 0.502). No alternative methylation-based calculation was identified to be predictive of age for CC. LIMITATIONS, REASONS FOR CAUTION To date, analyses of CC have failed to identify epigenetic changes that are predictive of the aging process within the ovary. Despite the poor predictive nature of both the Horvath model and the novel methylation-based age prediction model described here, it is possible that our efforts failed to identify appropriate sites which would result in a successful age-prediction model derived from the CC epigenome. Additionally, lower DNA input for CC samples compared to WBC samples was a methodological limitation. We acknowledge that a universally accepted definition of poor ovarian response is lacking. Furthermore, women with PCOS were included and therefore the group of good responders in the current study may not represent a population with entirely normal methylation profiles. WIDER IMPLICATIONS OF THE FINDINGS The process of ovarian and CC aging continues to be poorly understood. Women who demonstrate poor ovarian response to stimulation represent a common clinical challenge, so clarifying the exact biological changes that occur within the ovary over time is a worthwhile endeavor. The data from CC support a view that hormonally responsive tissues may possess distinct epigenetic aging patterns when compared with other tissue types. Future studies may be able to determine whether alternative DNA methylation sites can accurately predict chronologic age or ovarian response to stimulation from CC samples. Going forward, associations between epigenetic age acceleration and reproductive and general health consequences must also be clearly defined. STUDY FUNDING/COMPETING INTEREST(S) No external funding was obtained for the study and there are no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.



2008 ◽  
Author(s):  
Nicole Kohari ◽  
Robert Lord ◽  
Joelle Elicker ◽  
Steven Ash ◽  
Bryce Hruska




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