Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging.

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

Introduction of a multiplex amplicon sequencing assay to quantify DNA methylation in target cytosine markers underlying four selected epigenetic clocks.

BACKGROUND: DNA methylation analysis has proven to be a powerful tool for age assessment. However, the implementation of epigenetic age prediction in diagnostics or routine forensic casework requires appropriate laboratory methods. In this study, we aimed to compare the performance of large-scale DNA methylation analysis protocols that show promise in terms of accuracy, throughput, multiplexing capacity, and high sensitivity. RESULTS: The protocols were designed to target a predefined panel of 161 genomic CG/CA sites from four known estimators of epigenetic age-related parameters, optimized and validated using artificially methylated controls or blood samples. We successfully targeted 96% of these loci using two enrichment protocols: Ion AmpliSeq™, an amplicon-based method integrated with Ion Torrent S5, and SureSelectXT Methyl-Seq, a hybridization-based method followed by MiSeq FGx sequencing. Both protocols demonstrated high accuracy and robustness. Although hybridization assays have greater multiplexing capabilities, the best overall performance was observed for the amplicon-based protocol with the lowest variability in DNA methylation at 25 ng of starting DNA, mean observed marker coverage of ~ 6.7 k reads, and accuracy of methylation quantification with a mean absolute difference between observed and expected methylation beta value of 0.054. The Ion AmpliSeq method correlated strongly with genome-scale EPIC microarray data (R = 0.91) and showed superiority in terms of methylation measurement accuracy. Method-to-method bias was accounted for by the use of linear transformation, which provided a highly accurate prediction of calendar age with a mean absolute error of less than 5 years for the VISAGE and Hannum age clocks used. The pace of aging (PoAm) and the mortality risk score (MRS) estimators included in our panel represent next-generation clocks, were found to have low to moderate correlations with the VISAGE and Hannum models (R < 0.75), and thus may capture different aspects of epigenetic aging. CONCLUSIONS: We propose a laboratory tool that allows the quantification of DNA methylation in cytosines underlying four different clocks, thus providing broad information on epigenetic aging while maintaining a reasonable number of CpG markers, opening the way to a wide range of applications in forensics, medicine, and healthcare.

Overlapping association signals in the genetics of hair-related phenotypes in humans and their relevance to predictive DNA analysis.

Genetic prediction of different hair phenotypes can help reconstruct the physical appearance of an individual whose biological sample is analyzed in criminal and identification cases. Up to date, forensic prediction models for hair colour, hair shape, hair loss and hair greying have been developed, but studies investigating predictability of hair thickness and density traits are missing. First data suggesting overlapping associations in various hair features have emerged in recent years, suggesting partially common genetic basis and molecular mechanisms, and this knowledge can be used for predictive purposes. Here we aim to broaden our understanding of the genetics underlying head, facial and body hair thickness and density traits and examine the association for a set of literature SNPs. We characterize the overlap in SNP association for various hair phenotypes, the extent of genetic interactions and the potential for genetic prediction. The study involved 999 samples from Poland, genotyped for 240 SNPs with targeted next-generation sequencing. Logistic regression methods were applied for association and prediction analyses while entropy-based approach was used for interaction testing. As a result, we refined known associations for monobrow and hairiness (PAX3, 5q13.2, TBX) and identified two novel association signals in IGFBP5 and VDR. Both genes were among top significant loci, showed broad association with different hair-related traits and were implicated in multiple interaction effects. Overall, for 14.7% of SNPs previously associated with head hair loss and/or hair shape, a positive signal of association was revealed with at least one hair feature studied in the current research. Overlap in association with at least two hair-related traits was demonstrated for 24 distinct loci. We showed that the associated SNPs explain ∼5-30% of the variation observed in particular hair traits and allow moderate accuracy of prediction. The highest accuracy was achieved for hairiness level prediction in females (AUC = 0.69 for the "none", 0.69 for the "low" and 0.76 for the "excessive" hairiness category) and monobrow (AUC = 0.69 for the "none", 0.62 for the "slight" and 0.70 for the "significant" monobrow category) with 33% of the variation in hairiness level in females explained by 7 SNPs and age, and 20% of the variation in monobrow captured by 7 SNPs and sex. Our study presents clear evidence of pleiotropy and epistasis in the genetics of hair traits. The acquired knowledge may have practical application in forensics, as well as in the cosmetic industry and anthropological research.

Searching for improvements in predicting human eye colour from DNA.

Increasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting pigmentation characteristics, but the inference of some phenotypes is still challenging. In search of further improvements in predicting human eye colour, we conducted whole-exome (enriched in regulome) sequencing of 150 Polish samples to discover new markers. For this, we adopted quantitative characterization of eye colour phenotypes using high-resolution photographic images of the iris in combination with DIAT software analysis. An independent set of 849 samples was used for subsequent predictive modelling. Newly identified candidates and 114 additional literature-based selected SNPs, previously associated with pigmentation, and advanced machine learning algorithms were used. Whole-exome sequencing analysis found 27 previously unreported candidate SNP markers for eye colour. The highest overall prediction accuracies were achieved with LASSO-regularized and BIC-based selected regression models. A new candidate variant, rs2253104, located in the ARFIP2 gene and identified with the HyperLasso method, revealed predictive potential and was included in the best-performing regression models. Advanced machine learning approaches showed a significant increase in sensitivity of intermediate eye colour prediction (up to 39%) compared to 0% obtained for the original IrisPlex model. We identified a new potential predictor of eye colour and evaluated several widely used advanced machine learning algorithms in predictive analysis of this trait. Our results provide useful hints for developing future predictive models for eye colour in forensic and anthropological studies.

Development of the VISAGE enhanced tool and statistical models for epigenetic age estimation in blood, buccal cells and bones.

DNA methylation is known as a biomarker for age with applications in forensics. Here we describe the VISAGE (VISible Attributes through GEnomics) Consortium's enhanced tool for epigenetic age estimation in somatic tissues. The tool is based on eight DNA methylation markers (44 CpGs), bisulfite multiplex PCR followed by sequencing on the MiSeq FGx platform, and three statistical prediction models for blood, buccal cells and bones. The model for blood is based on six CpGs from ELOVL2, MIR29B2CHG, KLF14, FHL2, TRIM59 and PDE4C, and predicts age with a mean absolute error (MAE) of 3.2 years, while the model for buccal cells includes five CpGs from PDE4C, MIR29B2CHG, ELOVL2, KLF14 and EDARADD and predicts age with MAE of 3.7 years, and the model for bones has six CpGs from ELOVL2, KLF14, PDE4C and ASPA and predicts age with MAE of 3.4 years. The VISAGE enhanced tool for age estimation in somatic tissues enables reliable collection of DNA methylation data from small amounts of DNA using a sensitive multiplex MPS assay that provides accurate estimation of age in blood, buccal swabs, and bones using the statistical model tailored to each tissue.

Relationship between Fatigue and Physical Activity in a Polish Cohort of Multiple Sclerosis Patients.

Background and objectives: Fatigue is one of the most common and disabling symptoms of multiple sclerosis (MS). It can be defined as a subjective lack of physical and mental energy. The aim of this study was to evaluate the frequency and severity of fatigue in patients with MS and its relationship with overall physical activity and disease-related disability. Materials and Methods: The study included 100 patients with a clinical relapsing-remitting form of MS. Patients with severe depression were excluded. Neurological impairment was rated using the Expanded Disability Status Scale (EDSS). Fatigue was assessed using the Modified Fatigue Impact Scale (MFIS) and the Fatigue Severity Scale (FSS), with FSS scores greater than 36 indicating patients with fatigue. Physical activity was evaluated with the International Physical Activity Questionnaire (IPAQ) and categorized on three levels: low, moderate, and high, using standard metabolic equivalents (MET). Results: The average FSS and MFIS scores were (mean ± SD) 31.3 ± 15.2 and 30.1 ± 17.0, respectively. The mean EDSS score was 2.5 ± 1.5. 42%. Patients were classified as fatigued based on FSS. Fatigued patients had higher mean EDSS scores than non-fatigued (3.0 ± 1.6 vs. 2.2 ± 1.4, respectively, p = 0.002). Low, moderate, and high levels of physical activity were reported in 35%, 20%, and 45% of patients, respectively. Higher scores of fatigue in FSS and MFIS were inversely correlated with the intensity of physical activity (r = -0.38, p < 0.001 and r = -0.33, p < 0.001, respectively). Conclusions: In patients with MS, fatigue is a common symptom. Patients with lower physical activity and greater MS-related disability have a higher severity of fatigue, which negatively affects cognitive, psychosocial, and physical functioning.

Recommendations of the Polish Speaking Working Group of the International Society for Forensic Genetics on forensic Y chromosome typing.

Y chromosome typing has been performed in forensic genetic practice for more than 20 years. The latest recommendations of the DNA Commission of the International Society of Forensic Genetics (ISFG) concerning the application of Y-chromosomal markers in forensic genetics were published in 2006. The aim of this report is to recapitulate, systematise and supplement existing recommendations on the forensic analysis of polymorphism of the Y chromosome with standards already implemented in practice, new capabilities linked to the development of research techniques as well as current solutions used in statistical analysis. The recommendations have been adapted specifically to aspects related to the preparation of expert opinions in the field of forensic genetics in Poland. The Polish Speaking Working Group of the ISFG believes that the presented guidelines should become a standard implemented by all Polish laboratories performing Y chromosome typing for forensic purposes.

Exploring the possibility of predicting human head hair greying from DNA using whole-exome and targeted NGS data.

BACKGROUND: Greying of the hair is an obvious sign of human aging. In addition to age, sex- and ancestry-specific patterns of hair greying are also observed and the progression of greying may be affected by environmental factors. However, little is known about the genetic control of this process. This study aimed to assess the potential of genetic data to predict hair greying in a population of nearly 1000 individuals from Poland. RESULTS: The study involved whole-exome sequencing followed by targeted analysis of 378 exome-wide and literature-based selected SNPs. For the selection of predictors, the minimum redundancy maximum relevance (mRMRe) method was used, and then two prediction models were developed. The models included age, sex and 13 unique SNPs. Two SNPs of the highest mRMRe score included whole-exome identified KIF1A rs59733750 and previously linked with hair loss FGF5 rs7680591. The model for greying vs. no greying prediction achieved accuracy of cross-validated AUC = 0.873. In the 3-grade classification cross-validated AUC equalled 0.864 for no greying, 0.791 for mild greying and 0.875 for severe greying. Although these values present fairly accurate prediction, most of the prediction information was brought by age alone. Genetic variants explained < 10% of hair greying variation and the impact of particular SNPs on prediction accuracy was found to be small. CONCLUSIONS: The rate of changes in human progressive traits shows inter-individual variation, therefore they are perceived as biomarkers of the biological age of the organism. The knowledge on the mechanisms underlying phenotypic aging can be of special interest to the medicine, cosmetics industry and forensics. Our study improves the knowledge on the genetics underlying hair greying processes, presents prototype models for prediction and proves hair greying being genetically a very complex trait. Finally, we propose a four-step approach based on genetic and epigenetic data analysis allowing for i) sex determination; ii) genetic ancestry inference; iii) greying-associated SNPs assignment and iv) epigenetic age estimation, all needed for a final prediction of greying.

DNA-based predictive models for the presence of freckles.

Freckles or ephelides are hyperpigmented spots observed on skin surface mainly in European and Asian populations. Easy recognition and external visibility make prediction of ephelides, the potentially useful target in the field of forensic DNA phenotyping. Prediction of freckles would be a step forward in sketching the physical appearance of unknown perpetrators or decomposed cadavers for the forensic DNA intelligence purposes. Freckles are especially common in people with pale skin and red hair and therefore it is expected that predisposition to freckles may partially share the genetic background with other pigmentation traits. The first proposed freckle prediction model was developed based on investigation that involved variation of MC1R and 8 SNPs from 7 genes in a Spanish cohort [19]. In this study we examined 113 DNA variants from 46 genes previously associated with human pigmentation traits and assessed their impact on freckles presence in a group of 960 individuals from Poland. Nineteen DNA variants revealed associations with the freckle phenotype and the study also revealed that females have ∼1.8 higher odds of freckles presence comparing to males (p-value = 9.5 × 10-5). Two alternative prediction models were developed using regression methods. A simplified binomial 12-variable model predicts the presence of ephelides with cross-validated AUC = 0.752. A multinomial 14-variable model predicts one of three categories - non-freckled, medium freckled and heavily freckled. The two extreme categories, non-freckled and heavily freckled were predicted with moderately high accuracy of cross-validated AUC = 0.754 and 0.792, respectively. Prediction accuracy of the intermediate category was lower, AUC = 0.657. The study presents novel DNA models for prediction of freckles that can be used in forensic investigations and emphasizes significance of pigmentation genes and sex in predictive DNA analysis of freckles.

PRES in the course of hemato-oncological treatment in children.

INTRODUCTION: Posterior reversible leukoencephalopathy syndrome (PRES) is a clinical syndrome of varying aetiologies, characterised by acute neurological symptoms of brain dysfunction with MRI abnormalities in posterior cerebral white and grey matter. In most cases, symptoms resolve without neurological consequences. AIM: The aim of this paper is the analysis of predisposing factors, clinical outcomes and radiological features of PRES in eight children with hemato-oncological disease. MATERIAL AND METHODS: We analysed the medical records of eight hemato-oncological patients aged from 3.0 to 16.1 years. The mean of age at primary diagnosis was 8.5 years. RESULTS: All patients had both clinical and radiological PRES features. Seven out of eight underwent intensive chemotherapy regimens. Time elapsed from start of treatment to the occurrence of PRES ranged from 6 to 556 days. In one case, PRES occurred before chemotherapy and was the first symptom of cancer. Most (six of eight) patients had history of hypertension (> 95pc) and some (two of eight) occurred electrolyte imbalance-mainly hypomagnesaemia. Patients presented headache (seven of eight), disturbances of consciousness (six of eight), seizures (six of eight), visual changes (four of eight) and vomiting (three of eight). MRI demonstrated abnormalities in seven children: typical cerebral oedema in the white matter of the occipital to the parietal lobes. Most patient lesions in the MRI shrunk after 4 weeks, and clinical symptoms of PRES disappeared completely within a few hours to few days. CONCLUSION: PRES may complicate oncological treatment in children. Hypertension is the most important risk factor of PRES. PRES should be included in differential diagnosis in all patients with acute neurological symptoms.