Dna Methylation

Introduction

DNA methylation is a fundamental epigenetic mechanism that plays a crucial role in gene regulation without altering the underlying DNA sequence. It involves the addition of a methyl group to a cytosine base, most commonly occurring at CpG sites, which are regions where a cytosine nucleotide is followed by a guanine nucleotide. This modification can influence gene expression by affecting how readily genes are transcribed into proteins. DNA methylation patterns are dynamic, changing throughout an individual’s lifespan and can be influenced by a complex interplay of genetic and environmental factors.^[1]

Biological Basis

At its core, DNA methylation acts as a switch, typically silencing genes when present in a gene’s promoter region or contributing to genomic stability in other contexts. This process is essential for normal biological functions, including embryonic development, cellular differentiation, and the inactivation of one of the two X chromosomes in females. The precise patterns of methylation are established and maintained by specific enzymes, and their disruption can lead to altered gene function. Research indicates that DNA methylation levels change with age, with many CpG sites across the genome showing a correlation with an individual’s chronological age.^[2]Furthermore, studies have shown that the rate of change in DNA methylation over time can vary significantly between individuals.^[2]Genes near CpG sites that show significant variation in their rate of change are often enriched in pathways related to aging processes, such as Homeobox transcription factors and the Wnt signaling pathway.^[2]

Clinical Relevance

The widespread influence of DNA methylation on gene expression makes it highly relevant to human health and disease. Aberrant methylation patterns are frequently observed in various conditions, including different types of cancer, neurological disorders, cardiovascular diseases, and autoimmune conditions.^[3]For instance, abnormal methylation can lead to the silencing of tumor suppressor genes or the activation of oncogenes, contributing to cancer development and progression. Consequently, DNA methylation markers are being explored as potential biomarkers for disease diagnosis, prognosis, and monitoring treatment efficacy. Understanding these patterns can also inform the development of novel therapeutic strategies aimed at correcting methylation abnormalities.

Social Importance

The study of DNA methylation extends beyond clinical applications, holding significant social importance. It provides a molecular link between an individual’s genetic predisposition, lifestyle choices, and environmental exposures, offering insights into how these factors collectively shape health outcomes. For example, diet, stress, and exposure to toxins can alter methylation patterns, potentially contributing to the risk of various diseases over a lifetime. This understanding is crucial for public health initiatives focused on preventive medicine and personalized health interventions. By elucidating how epigenetic marks change differently between individuals and how this variation is associated with genetic factors and biological function, DNA methylation research contributes to a more comprehensive view of human health and disease.^[2]

Cohort Specificity and Generalizability

The findings regarding DNA methylation patterns and their genetic influences are primarily derived from the Lothian Birth Cohorts (LBC1921 and LBC1936), which comprise older individuals predominantly of European ancestry This indicates that an individual’s genetic makeup can predetermine how their epigenome evolves with age, potentially impacting various age-related biological processes and disease susceptibilities.^[2]Among the variants identified for their impact on the random slope of DNA methylation arers10948674 and rs190148485 . The SNP rs10948674 , located in a region involving PKHD1(Polycystic Kidney and Hepatic Disease 1) andMIR206(microRNA 206), has been found to significantly affect the rate of change of DNA methylation at cg21795255.^[2] PKHD1is a large gene primarily associated with autosomal recessive polycystic kidney disease, and its expression can be modulated by epigenetic mechanisms.MIR206is a microRNA known to regulate gene expression post-transcriptionally, often involved in muscle development and disease, suggesting that variations in this region could influence both disease susceptibility and broader developmental processes through altered epigenetic regulation. Similarly,rs190148485 , situated near the RASSF2gene (Ras Association Domain Family Member 2), demonstrates a significant association with the random slope of DNA methylation at cg26820259.^[2] RASSF2 is a known tumor suppressor gene involved in cell cycle arrest and apoptosis, with its epigenetic silencing often observed in various cancers. A variant like rs190148485 could influence the long-term stability of RASSF2 methylation, potentially affecting its protective role against uncontrolled cell growth over time.

Other variants, such as rs3796839 in the SLC2A9-AS1/SLC2A9 locus and rs80170476 in ABCA1, are pertinent to metabolic health and cellular transport. SLC2A9encodes a transporter primarily responsible for uric acid and glucose reabsorption in the kidneys, making variants in this region relevant to conditions like gout and type 2 diabetes. The antisense RNASLC2A9-AS1 can modulate SLC2A9 expression, and rs3796839 may alter this regulatory interaction, thereby influencing metabolic homeostasis through epigenetic mechanisms. ABCA1(ATP Binding Cassette Subfamily A Member 1) is a crucial cholesterol efflux transporter, and variants likers80170476 can impact lipid metabolism and cardiovascular disease risk. Alterations in DNA methylation nearABCA1 due to such SNPs could affect its expression, impacting cellular cholesterol handling and potentially contributing to age-related changes in metabolic health.^[2] The H19 gene, associated with rs4930103 , is a long non-coding RNA (lncRNA) that plays a critical role in fetal growth and development, acting as a tumor suppressor in some contexts and an oncogene in others, often regulated by imprinting and DNA methylation. Variants in this highly regulated region, likers4930103 , can influence H19expression or its interaction with other regulatory elements, thereby affecting cell proliferation, differentiation, and disease susceptibility through epigenetic means. Similarly,rs183717966 is found in LRP1B(Low Density Lipoprotein Receptor Related Protein 1B), a large receptor gene frequently inactivated in various cancers and recognized for its role in cell signaling and as a tumor suppressor. SNPs withinLRP1B could modulate its expression or function, potentially impacting cell growth pathways and influencing the epigenetic landscape of genes involved in cellular regulation.^[2] Further extending the genetic influence on diverse biological functions, rs8015861 is located in TRAV8-5 (T Cell Receptor Alpha Variable 8-5), a gene crucial for the recognition of antigens by T cells, central to adaptive immunity. Variants here could impact immune response efficiency, potentially influencing the epigenetic regulation of immune cell development and function over time. The MYO3B gene (Myosin IIIB), with its associated antisense RNA MYO3B-AS1 and variant rs114758110 , encodes a motor protein involved in cellular motility and sensory functions, particularly in inner ear hair cells. Changes in its regulation due to this variant might affect cellular mechanics or sensory perception. The region involving SUCLG1(Succinate-CoA Ligase Alpha Subunit) andDNAH6 (Dynein Axonemal Heavy Chain 6), harboring rs146331657 , links mitochondrial metabolism (through SUCLG1, part of the Krebs cycle) with ciliary function (through DNAH6, a motor protein for cilia). A variant here could impact cellular energy production or motility, influencing the epigenetic state of genes involved in these fundamental processes. Lastly, rs138696382 in AP1G1 (Adaptor Related Protein Complex 1 Subunit Gamma 1) affects a gene involved in intracellular vesicle trafficking and protein sorting, crucial for maintaining cellular organization and function. Variations here could alter protein transport efficiency, potentially affecting the epigenetic machinery responsible for maintaining cellular homeostasis.^[2]

Core Definitions and Measurement Methodologies

DNA methylation is a fundamental epigenetic modification characterized by the addition of a methyl group to a cytosine base, typically occurring at cytosine-guanine dinucleotides, known as CpG sites.^[2] This biochemical process does not alter the underlying DNA sequence but profoundly influences gene expression and cellular function.^[2]The collective state of these methylation patterns across the genome defines an individual’s methylome. Conceptually, DNA methylation acts as a crucial interface between genetic predisposition and environmental influences, contributing to phenotypic variation and disease susceptibility.^[2]The operational definition and measurement of DNA methylation in research commonly involve genome-wide profiling technologies. In many studies, DNA is extracted from biological samples, such as whole blood, and subjected to bisulphite conversion, which differentiates methylated from unmethylated cytosines.^[2] The converted DNA is then analyzed using platforms like the Illumina HumanMethylation450K array, which quantifies methylation levels at hundreds of thousands of specific CpG sites.^[2] Raw intensity data from these arrays undergo background correction and normalization, yielding quantitative metrics such as M values, which are often regularized to a specific interval (e.g., -9.96 to 9.96, corresponding to beta-values of 0.001 to 0.999) to ensure robust analysis and outlier exclusion.^[2]

Classification of Methylation Dynamics and Site Subtypes

While many DNA methylation studies are cross-sectional, longitudinal analyses provide critical insights into the dynamic nature of methylation patterns over an individual’s lifespan.^[2] A key classification within this dynamic framework is the identification of CpG sites exhibiting a “random slope” in methylation, which signifies individual differences in the rate of change of methylation over time.^[2] This approach moves beyond the assumption of a constant rate of change across individuals, acknowledging that methylation trajectories can vary significantly between people. Sites showing a statistically significant non-zero variance in their random slope are classified as “random slope CpG sites” (rsCpGs), indicating that the rate of methylation change at these loci is not uniform across individuals.^[2] The identification of rsCpGs allows for a more nuanced understanding of how epigenetic marks evolve and how this variation might be linked to genetic factors and biological function.^[2] Such a classification is derived through statistical modeling, typically using mixed linear models where a random intercept represents the mean methylation level for an individual, and a random slope captures their specific rate of change.^[2] A likelihood ratio test (LRT) is then employed to determine if the variance of this random slope is significantly greater than zero, thereby categorizing the CpG site as an rsCpG.^[2]This classification system facilitates the study of genetic and environmental contributions to individual epigenetic aging processes.

Terminology, Nomenclature, and Research Criteria

The field of DNA methylation research employs a precise terminology to describe its various facets. Key terms include “CpG site” for the specific dinucleotide where methylation occurs, “methylome” for the entire set of methylation marks, and “epigenetic marks” as a broader category encompassing DNA methylation and other heritable modifications.^[2]Related concepts like “Single Nucleotide Polymorphism” (SNP) are crucial, as genetic variations can significantly influence methylation patterns (methyl-quantitative trait loci or mQTLs).^[2] “Genome-wide association studies” (GWAS) are frequently utilized to identify such genetic associations, often incorporating “linkage disequilibrium” (LD) clumping to refine SNP selection.^[2] Other terms like “Differently Methylated Region” (DMR) refer to genomic areas with significant methylation differences between groups or conditions.

Standardized research criteria and thresholds are critical for ensuring the quality and interpretability of DNA methylation data. For instance, quality control measures typically involve filtering out probes that are potentially cross-hybridizing or have inconsistent measurements.^[2] Outlier samples, defined by methylation values (M values) falling beyond three standard deviations from the mean for a given probe, are routinely removed.^[2] For classifying rsCpGs, a stringent statistical threshold, such as a Bonferroni-corrected P value (e.g., P < 1.5 × 10−7 for 344,000 probes), is applied to account for multiple testing.^[2] Similarly, genotyping data undergoes rigorous quality control, including filtering SNPs based on imputation quality (e.g., R2 < 0.8), minor allele frequency (MAF < 0.01), and Hardy-Weinberg equilibrium (HWE P < 1 × 10−6), to ensure robust genetic association analyses.^[2]

Fundamentals of DNA Methylation and Gene Regulation

DNA methylation is a critical epigenetic modification that plays a significant role in regulating gene expression, influencing which genes are turned on or off in a cell.^[3]This process involves the addition of a methyl group, typically to a cytosine base that is followed by a guanine base (CpG site), without altering the underlying DNA sequence.^[4]The patterns of DNA methylation are crucial for normal cellular functions, embryonic development, and maintaining genomic stability. These methylation patterns are not static; local levels of DNA methylation can vary both within an individual’s different cell types and between different individuals, reflecting a dynamic interplay of biological processes.^[2]The precise control of DNA methylation is maintained by a complex regulatory network involving specific enzymes and proteins. These key biomolecules, such as DNA methyltransferases (DNMTs) and ten-eleven translocation (TET) enzymes, are responsible for establishing, maintaining, and removing methyl marks, respectively. The balance of their activity ensures that gene expression is appropriately regulated, contributing to cellular differentiation and overall physiological homeostasis. Disruptions in these regulatory networks can lead to altered gene expression patterns, which are implicated in various biological processes and disease states.^[1]

Genetic and Environmental Influences on Methylome Variation

The observed variations in DNA methylation across individuals are influenced by a combination of genetic and environmental factors.^[1]Genetic mechanisms, particularly single nucleotide polymorphisms (SNPs), can impact DNA methylation levels and their rates of change over time. Studies have identified specific genetic loci that are associated with differences in the longitudinal changes of DNA methylation, suggesting a genetic basis for the dynamic nature of the methylome.^[2]For instance, specific SNPs have been found to significantly influence the random slope of DNA methylation, indicating a “SNP by age” effect on how methylation changes over an individual’s lifespan.^[2]The heritability of DNA methylation is substantial at many CpG sites, with some showing a mean heritability of 0.40, signifying a considerable genetic contribution to their variability.^[2] This genetic influence is not always localized, as a large proportion of significant SNPs affecting methylation changes are located on different chromosomes from their corresponding CpG probes.^[2]Environmental factors, ranging from diet and lifestyle to exposure to toxins, also interact with an individual’s genetic predisposition to shape the methylome, further contributing to the unique methylation patterns observed in each person.^[5]

DNA Methylation in Aging and Development

DNA methylation patterns undergo significant changes throughout an individual’s lifespan, with methylation levels at many CpG sites correlating with age.^[6]While age is often treated as a covariate in methylation studies, research indicates that the rate of change in DNA methylation over time is not constant between individuals; rather, there is considerable individual variability in these trajectories.^[7]This variability suggests that each person ages epigenetically at a unique pace, which can be quantified through longitudinal analyses of DNA methylation.^[2]Genes located near CpG sites exhibiting significant variation in their rate of change (random slope) are often enriched in pathways known to be involved in the aging process. Notably, Homeobox transcription factors and the Wnt signaling pathway have been identified in this context.^[2] Homeobox genes, such as Hox genes, are crucial regulatory elements involved in animal body patterning and developmental processes.^[8]The Wnt signaling pathway is a complex molecular and cellular pathway that plays a dual role in aging, impacting various cellular functions and developmental processes.^[9]The involvement of these pathways highlights the deep connection between epigenetic regulation, developmental biology, and the complex process of biological aging.^[2]

Molecular Pathways and Health Implications

The dynamic nature of DNA methylation, particularly its variation in change rate between individuals, has significant implications for health and disease. These individual differences in epigenetic aging could serve as valuable markers for understanding differential aging processes and disease susceptibility.^[2]For instance, the “epigenetic clock,” a measure derived from DNA methylation patterns, has been correlated with physical and cognitive fitness, and even mortality, underscoring its relevance to health outcomes.^[10]Disruptions in normal DNA methylation patterns are implicated in various pathophysiological processes, contributing to disease mechanisms. For example, altered DNA methylation has been observed in specific tissues, such as human brain tissue in schizophrenia patients.^[11]Furthermore, genome-wide analyses have linked DNA methylation to metabolic processes and conditions like body-mass index.^[12]Understanding the molecular and cellular pathways, including signaling pathways like Wnt and the regulatory networks involving Homeobox genes, that are influenced by DNA methylation changes provides critical insights into the etiology of age-related diseases and offers potential avenues for therapeutic interventions.^[2]

Epigenetic Regulation of Gene Expression

DNA methylation is a fundamental epigenetic modification that critically regulates gene expression, serving as a crucial mechanism for cellular differentiation, development, and maintaining tissue-specific gene silencing.^[2] This process primarily involves the covalent addition of a methyl group to the fifth carbon of cytosine residues, predominantly within CpG dinucleotides, which can influence chromatin structure and accessibility to transcription factors.^[4] The precise patterns of DNA methylation are highly dynamic and exhibit variation both within and between individuals, with distinct CpG island shores playing a role in distinguishing specific cell types, such as human induced pluripotent stem cells, embryonic stem cells, and fibroblasts.^[13] These intricate regulatory mechanisms ensure the appropriate spatial and temporal control of gene activity, which is essential for cellular identity and overall biological function.

Signaling Pathways and Methylation Dynamics

Cellular signaling pathways act as critical conduits for integrating external and internal cues, thereby modulating DNA methylation patterns and influencing epigenetic responses. Research indicates that genes located near CpG sites exhibiting significant individual variation in their rate of DNA methylation change are notably enriched in Homeobox transcription factors and components of the Wnt signaling pathway.^[2]Both Homeobox genes, which are fundamental for orchestrating developmental patterning, and the Wnt pathway, known for its extensive roles in cell proliferation, differentiation, and tissue homeostasis, are intrinsically linked to aging processes.^[2] This suggests that receptor activation and subsequent intracellular signaling cascades can directly or indirectly regulate the activity of DNA methyltransferases or demethylases, thereby influencing gene-specific methylation states and contributing to the dynamic nature of the epigenome.

Life-Course Trajectories and Environmental Integration

The human methylome is not static but undergoes continuous and dynamic changes across the lifespan, with DNA methylation levels evolving significantly from early development through older age.^[14] The observed variability in DNA methylation trajectories among individuals is shaped by a complex interplay of both genetic predispositions and diverse environmental factors.^[2] Studies highlight that while genetic influences contribute substantially to DNA methylation variation and help constrain epigenetic drift, environmental exposures also profoundly influence these patterns, leading to altered methylation landscapes.^[15]This systems-level integration demonstrates how various stimuli are processed and embedded into the epigenome, resulting in emergent properties in health and disease progression, where pathway crosstalk can modify the rate and direction ofDNA methylation changes.

Methylation Dysregulation in Aging and Disease

Dysregulation of DNA methylationpatterns is a hallmark of the aging process and contributes significantly to the etiology and progression of various disease states, underscoring its potential as a diagnostic marker and therapeutic target.^[3] For example, DNA methylationage, often referred to as the “epigenetic clock,” serves as a robust biological marker that correlates strongly with chronological age, predicts mortality, and reflects an individual’s physical and cognitive fitness.^[16] Furthermore, aberrant DNA methylationprofiles have been observed in specific pathological conditions, such as schizophrenia, where distinct changes are evident in brain tissue.^[11] Genome-wide analyses have also identified significant associations between DNA methylationpatterns and complex traits like body-mass index, indicating that altered methylation can both reflect and contribute to metabolic dysregulation and an increased risk of disease.^[12]

Dynamic DNA Methylation in Aging and Disease

DNA methylation patterns are not static; they undergo significant changes throughout an individual’s lifespan, with levels at many CpG sites correlating with age.^[2] Crucially, the rate of these methylation changes varies considerably between individuals, challenging the assumption of a constant rate of change often used in cross-sectional studies.^[2]Longitudinal analyses, which track these dynamic shifts, are vital for understanding how epigenetic marks diverge among individuals and how this variation associates with biological functions and disease progression.^[2]For instance, the “epigenetic clock,” a measure derived from DNA methylation, has shown correlations with mortality and physical and cognitive fitness, highlighting its potential prognostic value for long-term health outcomes.^{[10], [16]}Recognizing these individual-specific trajectories could refine predictions of age-related disease onset and severity.

Epigenetic Biomarkers for Risk Assessment and Personalized Medicine

The identification of specific CpG sites exhibiting significant individual variation in their rate of methylation change offers a promising avenue for developing novel epigenetic biomarkers. By analyzing these dynamic markers, clinicians may gain improved diagnostic utility and tools for risk stratification, allowing for the identification of high-risk individuals before the overt manifestation of disease.^[2] For example, a study identified over 1,500 CpG sites with significant variation in their rate of change, with many of these being enriched in the Homeodomain (Homeobox) transcription factor protein class, suggesting their functional importance.^[2]Such insights could pave the way for personalized medicine approaches, where interventions are tailored based on an individual’s unique epigenetic profile and predicted disease trajectory, potentially informing treatment selection and monitoring strategies.

Genetic and Environmental Modulators of Methylation Patterns

DNA methylation is influenced by a complex interplay of both genetic and environmental factors, which together shape an individual’s methylome.^{[1], [2], [5], [17]} Research demonstrates that the heritability of CpG sites with variable rates of methylation change is significantly higher than the average, underscoring a strong genetic contribution to these dynamic epigenetic processes.^[2] Furthermore, specific genetic variants, such as rs10948674 and rs190148485 , have been identified as having significant effects on the rate of change of methylation at particular CpG sites.^[2] Understanding these gene-environment interactions and their impact on methylation trajectories can provide critical insights into the etiology of various conditions, potentially explaining comorbidities or overlapping phenotypes and guiding the development of targeted prevention strategies.

Key Variants

RS ID	Gene	Related Traits
rs3796839	SLC2A9-AS1, SLC2A9	dna methylation
rs10948674	PKHD1 - MIR206	dna methylation
rs8015861	TRAV8-5	dna methylation
rs4930103	H19	dna methylation breast cancer, lung cancer
rs190148485	RASSF2	dna methylation
rs183717966	LRP1B	dna methylation
rs114758110	MYO3B-AS1, MYO3B	dna methylation
rs146331657	SUCLG1 - DNAH6	dna methylation
rs138696382	AP1G1	dna methylation
rs80170476	ABCA1	dna methylation

Frequently Asked Questions About Dna Methylation

These questions address the most important and specific aspects of dna methylation based on current genetic research.

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1. Can my diet really affect how my genes work?

Yes, absolutely! Your diet is a major environmental factor that can influence DNA methylation patterns. These patterns act like switches on your genes, determining whether they are turned on or off. By altering these methylation marks, what you eat can affect your gene expression and ultimately your health over time.

2. Does stress actually change my DNA?

While stress doesn’t change your fundamental DNA sequence, it can definitely alter how your genes are expressed. Stress is an environmental factor known to influence DNA methylation patterns. These changes can affect how readily certain genes are turned on or off, potentially impacting your body’s functions and disease risk.

3. Why do some people seem to age slower than others?

This can be partly due to differences in how their DNA methylation patterns change over time. While methylation levels correlate with chronological age, therateof these changes varies significantly between individuals. These different rates of change are often linked to genes involved in aging processes, making some people appear to age more gracefully.

4. If my parents had a disease, can I still avoid it?

Not always, but your lifestyle plays a significant role. While you inherit genetic predispositions, DNA methylation provides a molecular link between your genes, lifestyle, and environment. Aberrant methylation contributes to many diseases, but factors like diet, stress, and exposures can alter these patterns, offering avenues for prevention and risk reduction.

5. Do everyday chemicals impact my health at a genetic level?

Yes, they can. Exposure to toxins from your environment, including certain chemicals, can influence your DNA methylation patterns. These changes can affect gene expression, potentially contributing to your risk of various diseases throughout your lifetime. Understanding this link is crucial for public health and personalized prevention.

6. Can I really “turn off” unwanted genes?

In a way, yes, through DNA methylation. This process acts like a switch, typically silencing genes when methyl groups are added to their promoter regions. While you can’t manually target specific genes, your lifestyle and environment can influence these methylation patterns, affecting which genes are actively expressed or kept quiet.

7. Why do my friends react differently to the same lifestyle?

Individual differences in DNA methylation patterns and how they change over time play a role. Your unique genetic makeup interacts with environmental factors to shape your specific methylation landscape. This means that even with similar lifestyles, the way your genes are expressed can vary significantly, leading to different health outcomes.

8. Can a test tell me my body’s “true” age?

Yes, there are tests that estimate “biological age” based on DNA methylation patterns. Since methylation levels across many CpG sites correlate with chronological age, these patterns can provide an epigenetic clock. This can give insights into how your body is aging at a molecular level, potentially differing from your actual birth age.

9. What can I do to keep my genes healthy long-term?

Focusing on a healthy lifestyle is key. Your diet, stress levels, and environmental exposures directly influence your DNA methylation patterns, which in turn regulate gene expression. By making positive lifestyle choices, you can support beneficial methylation patterns, contributing to better long-term gene health and disease prevention.

10. Does my early life environment affect my adult health?

Yes, it absolutely can. DNA methylation patterns are established early, even during embryonic development, and are crucial for cellular differentiation. These patterns are dynamic and influenced by environmental factors throughout your lifespan, meaning early life experiences and exposures can set foundational epigenetic marks that impact your health much later.

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This FAQ was automatically generated based on current genetic research and may be updated as new information becomes available.

Disclaimer: This information is for educational purposes only and should not be used as a substitute for professional medical advice. Always consult with a healthcare provider for personalized medical guidance.

References

[1] Feinberg, A. P., and M. D. Fallin. “Epigenetics at the crossroads of genes and the environment.” Jama, vol. 314, 2015, pp. 1129–30.

[2] Zhang, Q., et al. “Genotype effects contribute to variation in longitudinal methylome patterns in older people.” Genome Medicine, vol. 10, 2018, p. 75.

[3] Robertson, K. D. “DNA methylation and human disease.”Nat Rev Genet, vol. 6, 2005, pp. 597–610.

[4] Suzuki, M. M. and A. Bird. “DNA methylation landscapes: provocative insights from epigenomics.”Nat Rev Genet, vol. 9, 2008, pp. 465–76.

[5] Feil, R. and M. F. Fraga. “Epigenetics and the environment: emerging patterns and implications.” Nat Rev Genet, vol. 13, 2012, pp. 97–109.

[6] Richardson, B. “Impact of aging on DNA methylation.”Ageing Res Rev, vol. 2, 2003, pp. 245–61.

[7] Slieker, R. C., et al. “Age-related accrual of methylomic variability is linked to fundamental ageing mechanisms.” Genome Biol, vol. 17, 2016, p. 191.

[8] Pearson, J. C., et al. “Modulating Hox gene functions during animal body patterning.” Nat Rev Genet, vol. 6, 2005, pp. 893–904.

[9] Lezzerini, M., and Y. Budovskaya. “A dual role of the Wnt signaling pathway during aging in Caenorhabditis elegans.”Aging Cell, vol. 13, 2014, pp. 8–18.

[10] Marioni, R. E., et al. “The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936.”Int J Epidemiol, vol. 44, 2015, pp. 1388–96.

[11] Wockner, L., et al. “Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients.”Transl Psychiatry, vol. 4, 2014, e339.

[12] Dick, K. J., et al. “DNA methylation and body-mass index: a genome-wide analysis.”Lancet, vol. 383, 2014, pp. 1990–8.

[13] Aryee, M. J., et al. “Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.”Bioinformatics, vol. 30, no. 9, 2014, pp. 1363–69.

[14] Martino, D., et al. “Longitudinal, genome-scale analysis of DNA methylation in twins from birth to 18 months of age reveals rapid epigenetic change in early life and pair-specific effects of discordance.”Genome Biol, vol. 14, 2013, R42.

[15] Shah, S., et al. “Genetic and environmental exposures constrain epigenetic drift over the human life course.” Genome Res, vol. 24, 2014, pp. 1725–33.

[16] Christiansen, L., et al. “DNA methylation age is associated with mortality in a longitudinal Danish twin study.”Aging Cell, vol. 15, 2016, pp. 149–54.

[17] Jirtle, R. L., and M. K. Skinner. “Environmental epigenomics and disease susceptibility.”Nat Rev Genet, vol. 8, 2007, pp. 253–62.