The study made by  Onuchic et al.  was aimed to construct the maps of allelic imbalances in DNA methylation, gene transcription, and also of histone modifications. 36 cell and tissue types from 13 participant donors were used to examine 71 epigenomes. The results of WGBS tested on 49 methylomes revealed CpG methylation imbalances exceeding 30% differences in 5% of the loci. The stochastic switching occurred at thousands of heterozygous regulatory loci that were bound to transcription factors. The intermediate methylation state is referred to the relative frequencies between methylated and unmethylated epialleles. The epiallele frequency variations are correlated with the allele affinity for transcription factors.


The analysis of the study suggests that human epigenome in average covers approximately 200 adverse SD-ASM variants. The sensitivity of the genes with tissue-specific expression patterns gives the opportunity for the evolutionary innovation in gene regulation. [ 9 ]


Haplotype reconstruction strategy is used to trace chromatin chemical modifications (using ChIP-seq) in a variety of human tissues. Haplotype-resolved epigenomic maps can trace allelic biases in chromatin configuration. A substantial variation among different tissues and individuals is observed. This allows the deeper understanding of cis-regulatory relationships between genes and control sequences. [ 10 ]


Post-translational modifications of histone proteins, which include methylation,  acetylation ,  phosphorylation ,  ubiquitination , and  sumoylation . These modifications can either activate or repress gene expression by altering chromatin structure and accessibility of the DNA to transcriptional machinery.


The epigenetic profiles of human tissues reveals the following distinct histone modifications in different functional areas: [ 10 ]


Histone acetylation neutralizes the positive charge on histones. This weakens the electrostatic attraction to negatively charged DNA and causes unwinding of DNA from histones, making the DNA more accessible to the transcriptional machinery and hence resulting in transcriptional activation. [ 11 ]


Can lead to activation or repression of gene expression depending on the specific amino acids that are methylated.


Non-coding RNA  (ncRNA) gene silencing involves various types of non-coding RNAs, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and small interfering RNAs (siRNAs).  These RNA molecules can modulate gene expression by various mechanisms, including mRNA degradation, inhibition of translation, and chromatin remodeling. [ 3 ]


During the last few years, several methods have been developed to study the structural and consequently the functional modifications of chromatin. The first project that used epigenomic profiling to identify regulatory elements in the human genome was  ENCODE  (Encyclopedia of DNA Elements) that focused on profiling histone modifications on cell lines. A few years later ENCODE was included in the  International Human Epigenome Consortium  (IHEC), which aims to coordinate international epigenome studies. [ 12 ]


The structural modifications that these projects aim to study can be divided into five main groups:


Topological associated domains  are a degree of structural organization of the  genome  of the cell. They are formed by regions of chromatin, sized from 100 kilobases up to megabases, which highly self-interact. The domains are linked by other genomic regions, which, based on their size, are either called “topological boundary regions” or “unorganized chromatin”. These boundary regions separate the topological domains from heterochromatin, and prevent the amplification of the latter. Topological domains are diffused in mammalian, although similar genome partitions were identified also in  Drosophila . [ 13 ]


Topological domains in humans, like in other mammalians, have many functions regarding gene expression and  transcriptional control  process. Inside these domains, the chromatin shows to be well tangled, while in the boundary regions chromatin interactions are far less present. [ 14 ]  These boundary areas in particular show some peculiarity that determine the functions of all the topological domains.


Firstly, they contain  insulator  regions and barrier elements, both of which function as inhibitors of further transcription from the  RNA polymerase  enzyme. [ 15 ]  Such elements are characterized by the massive presence of insulator binding proteins  CTCF .


Secondly, boundary regions block heterochromatin spreading, thus preventing the loss of useful genetic informations. This information derives from the observation that the heterochromatin mark  H3K9me3  sequences clearly interrupts near boundary sequences. [ 16 ]


Thirdly, transcription start sites (TSS),  housekeeping genes  and  tRNA  genes are particularly abundant in boundary regions, denoting that those areas have a prolific transcriptional activity, thanks to their structural characteristics, different from other topological regions. [ 17 ] [ 18 ]


Finally, in the border areas of the topological domains and their surroundings there is an enrichment of  Alu /B1 and B2  SINE   retrotransposons . In the recent years, those sequences were referred to alter binding site of CTCF, thus interfering with expression of some genomic areas. [ 19 ]


Further proofs towards a role in genetic modulation and transcription regulation refers to the great conservation of the boundary pattern across mammalian evolution, with a dynamic range of small diversities inside different cell types, suggesting that these topological domains take part in cell-type specific regulatory events. [ 14 ]


The 4D Nucleome project aims to realize a 3D maps of mammalian genomes in order to develop predictive models to correlate epigenomic modifications with genetic variation. In particular the goal is to link genetic and epigenomic modifications with the enhancers and promoters which they interact with in three-dimensional space, thus discovering gene-set  interactomes  and pathways as new candidates for functional analysis and therapeutic targeting.


Hi-C  [ 20 ]  is an experimental method used to map the connections between DNA fragments in three-dimensional space on a genome-wide scale. This technique combines  chemical crosslinking  of chromatin with  restriction enzyme  digestion and next-generation DNA sequencing. [ 21 ]


This kind of studies are currently limited by the lack or unavailability of raw data. [ 12 ]


Epigenetics  is a currently active topic in  cancer  research. Human  tumors  undergo a major disruption of  DNA methylation  and  histone  modification patterns. The aberrant epigenetic landscape of the cancer cell is characterized by a global genomic hypomethylation,  CpG island  promoter hypermethylation of tumor suppressor  genes , an altered  histone  code for critical genes and a global loss of monoacetylated and trimethylated histone H4.


The idea that  DNA damage  drives aging by compromising  transcription  and  DNA replication  has been widely supported since it was initially developed the 1980s. [ 22 ]   In recent decades, evidence has accumulated supporting the additional idea that DNA damage and repair elicit widespread epigenome alterations that also contribute to aging (e.g. [ 23 ] [ 24 ] ).  Such epigenome changes include age-related changes in the patterns of DNA methylation and histone modification. [ 23 ]


As a prelude to a potential  Human Epigenome Project , the  Human Epigenome Pilot Project  aims to identify and catalogue Methylation Variable Positions (MVPs) in the human  genome . [ 25 ]  Advances in sequencing technology now allow for assaying genome-wide epigenomic states by multiple molecular methodologies. [ 26 ]   Micro- and nanoscale devices have been constructed or proposed to investigate the epigenome. [ 27 ]


An international effort to assay reference epigenomes commenced in 2010 in the form of the  International Human Epigenome Consortium  (IHEC). [ 28 ] [ 29 ] [ 30 ] [ 31 ]  IHEC members aim to generate at least 1,000 reference (baseline) human epigenomes from different types of normal and disease-related human  cell types . [ 32 ] [ 33 ] [ 34 ]


One goal of the  NIH Roadmap Epigenomics Project   Archived  2021-04-08 at the  Wayback Machine  is to generate human reference epigenomes from normal, healthy individuals across a large variety of cell lines, primary cells, and primary tissues. Data produced by the project, which can be browsed and downloaded from the  Human Epigenome Atlas , fall into five types that assay different aspects of the epigenome and outcomes of epigenomic states (such as gene expression):


Reference epigenomes for healthy individuals will enable the second goal of the Roadmap Epigenomics Project, which is to examine epigenomic differences that occur in disease states such as  Alzheimer's disease .


An  epigenome-wide association study  ( EWAS ) is an examination of a genome-wide set of quantifiable  epigenetic  marks, such as  DNA methylation , in different individuals to derive associations between epigenetic variation and a particular identifiable  phenotype /trait. When patterns change such as DNA methylation at specific  loci , discriminating the phenotypically affected cases from control individuals, this is considered an indication that epigenetic perturbation has taken place that is associated, causally or consequentially, with the phenotype. [ 1 ]


The  epigenome  is governed by both genetic and environmental factors, causing it to be highly dynamic and complex. Epigenetic information exists in the cell as DNA and  histone  marks, as well as  non-coding RNAs . DNA methylation (DNAm) patterns change over time, and vary between developmental stage and tissue type. The main type of DNAm is at  cytosines  within  CpG  dinucleotides which is known to be involved in  gene expression regulation . DNAm pattern changes have been extensively studied in complex diseases such as cancer and diabetes. [ 1 ]  In a normal cell, the bulk  genome  is highly methylated at CpGs, whereas  CpG islands  (CPI) at  gene promoter  regions remain highly unmethylated. Aberrant DNAm is the most common type of molecular abnormality in cancer cells, where the bulk genome becomes globally ‘hypomethylated’ and CPIs in promoter regions become ‘hypermethylated’, usually leading to silencing of tumour suppressor genes. [ 2 ]  More recently, studies on diabetes have uncovered further evidence to support an epigenetic component of diseases, including differences in disease-associated epigenetic marks between  monozygotic twins , the rising incidence of  type 1 diabetes  in the general population, and developmental reprogramming events in which  in utero  or childhood environments can influence disease outcome in adulthood. [ 1 ]


Post-translational histone modifications include, but are not limited to, methylation, acetylation and phosphorylation on the core histone tails. These post-translational modifications are read by proteins that can then modify the  chromatin  state at that locus. [ 1 ]
Epigenetic variation arises in three distinct ways; it can be inherited and be therefore present in all cells of the adult including the  germline  (a process known as  transgenerational epigenetic inheritance ; a controversial phenomenon that has not yet been observed in humans); it can occur randomly and be present in a subset of cells in the adult, the amount of which depending on how early in development the variation occurs; or it can be induced as a result of behavioural or environmental factors. [ 1 ]   EWAS has previously associated changes in methylation with several diseases and complex conditions which do not have a known epidemiology and therefore are crucial for the identification of epigenetic factors that contribute to or are a consequence of pathogenesis of these diseases. [ 3 ]


Retrospective studies compare unrelated individuals who fall into two categories, controls without the disease or phenotype of interest, and cases who have the phenotype of interest. An advantage of such studies is that many cohorts of case-control samples already exist with available genotype and expression data that can be integrated with epigenome data. A downside, however, is that they cannot determine whether epigenetic differences are a result of disease-associated genetic differences, post-disease processes or disease-associated drug interventions. [ 1 ]


Useful to study transgenerational inheritance patterns of epigenetic marks. A main limitation of EWAS is deciphering if a phenotype is associated with epigenetic changes as a result of a variable in question or a result of previous genomic variants leading to epigenetic alterations. Comparisons between parent and offspring genomic and epigenomic data allows one to rule out the possibility that a disease or phenotype is due to genomic variation. A limitation of this study design is that very few cohorts which are large enough exist. [ 1 ]


Monozygotic twins carry identical genomic information. Therefore, if they are discordant for a particular disease or phenotype it is likely a result of epigenetic differences. However, unless the twins are studied longitudinally it is impossible to determine if epigenetic variation is the cause of or consequence of disease. Another limitation is recruiting a large enough cohort of discordant monozygotic twins with the disease of interest. [ 1 ]


Longitudinal studies follow a cohort of individuals over an extended period of time, usually from birth or before disease onset. Samples are taken and records are kept over many years, making these studies extremely useful to determine causality of particular phenotypes. Since the same individuals are followed at time points before and after disease onset, it removes the confounding effects of differences between cases and controls. Longitudinal studies are not only useful for risk studies (using DNA samples prior to disease onset), but also in intervention studies using pre- and posttreatment with specific exposures to investigate environmental impacts on the epigenome. [ 4 ]  A major disadvantage is the long timeline of the studies as well as the expense. Longitudinal studies using disease-discordant monozygotic twins gives the added benefit of ruling out genetic influences on epigenetic variation. [ 1 ]


The tissue specificity of epigenomic marks create another challenge when designing an EWAS. Tissue choice is limited by both accessibility and stability of epigenetic patterning. It is crucial to choose a tissue in which epigenetic marks are variable in the population yet stable over time. If this isn't possible, it would be required to use multiple serially collected samples from the same individuals to report robust associations with a particular phenotype. EWAS for diseases are often measured using DNA methylation in blood samples because disease-relevant tissues are difficult to obtain. In some cases, the pattern of methylation is not necessarily biologically relevant to the proposed phenotype. The choice of blood also requires stringent analysis and careful interpretation due to variable cell type composition. Choosing a surrogate tissue therefore requires that the interindividual differences correlate between the tissue of interest and the surrogate, but also for the exposure to induce similar changes in both tissues. To date, an underlying issue is that there is no clear evidence that, in general, epigenetic marks respond to environmental exposures in a similar way across tissues. [ 5 ]


The platform for epigenome-wide DNAm quantification utilizes the high throughput technology  Illumina Methylation Assay . In the past, the 27k Illumina array covered on average two CpG sites in the promoter regions of approximately 14,000 genes and represented less than 0.1% of the 28 million CpG sites in the human genome. This falls short of being representative of the entire human epigenome. None of the early EWAS using this array  [ 6 ] [ 7 ]  used independent validation to verify the associated probes. An interesting observation was a bias in the differences between cases and controls towards non-CpG island probes (which were significantly underrepresented in this array design), arguing strongly for the use of the latterly designed 450k array which does cover non-CpG islands with a higher density of probes. Presently, the Illumina 450k array is the most widely used platform in the last two years for studies reporting EWAS. The array still only covers less than 2% of the CpG sites in the genome, but does attempt to cover all known genes with a high density of probes in the promoters (including CpG islands and surrounding sequences), but also covers with a lower density across the gene bodies,  3′ untranslated regions , and other  intergenic sequences . [ 8 ]


DNA methylation is typically quantified on a scale of 0–1, as the methylation array measures the proportion of DNA molecules that are methylated at a particular CpG site. The initial analyses performed are univariate tests of association to identify sites where DNA methylation varies with exposure and/or phenotype. This is followed by multiple testing corrections and utilizing an analytical strategy to reduce  batch effects  and other technical confounding effects in the quantification of DNA methylation. The potential confounding effects arising from alterations in tissue composition is also taken into account. Additionally, adjusting for confounding factors such as age, gender and behaviours that may influence the methylation status as covariates is conducted. The association results are also corrected for the genomic control inflation factor in order to account for the population stratification.


Generally, mean levels of CpG methylation are compared across categories using linear regression [ 9 ]  which allows for the adjustment of confounders and batch effects. [ 10 ]  A P-value threshold of P < 1e-7 [ 11 ]  is generally used to identify CpGs associated with the tested phenotype/stimulus. These CpGs are considered to reach epigenome-wide significance. An effect size is also calculated at this significance level, indicating the difference in methylation when comparing two qualitative groups, or different quantitative values depending on your phenotype. CpG sites significantly associated with the phenotype and/or treatment/environmental stimulus are typically represented in a manhattan plot. [ 12 ]


Single CpG sites are prone to single site natural variation effects and technical variation such as bad microarray probes and outliers. To make more robust associations and take into account such variation, using adjacent measurements can help increase power. [ 13 ] [ 14 ]  In previous studies, functionally relevant findings have been associated with genomic regions as opposed to single CpGs. Therefore, looking at the regional level can help identify associated regions with more confidence, guiding downstream functional studies.


Another method of analysis is using unsupervised clustering to create classes of CpG sites based on similarity of methylation variation across samples. The average methylation values within each class is used to construct data sets of reduced dimensionality, facilitating efficient tests of association between DNA methylation and phenotypes of interest. [ 15 ]  This is used to reduce the dimensionality of large data sets and take advantage of substantial biologically induced correlation. This method is useful for identifying gross patterns of methylation associated with the tested variable, but may miss specific CpG sites of interest. Besides differences in mean methylation levels, differences in variation of DNA methylation across samples may also be biologically meaningful, motivating scans for differential variability between groups. [ 12 ]


The location of the associated CpG sites or islands/regions can then be analyzed  in silico  to imply possible functional relevance. For example, considering whether the associated CpGs are within a promoter region or determining distance from the transcription start site that may be relevant, especially when we assume that DNA methylation associated with a phenotype acts by regulating gene transcription. Many other inferences based on past biological knowledge can be inferred if that particular region of CpGs have been studied and associated with changes in transcription. This can be used as an additional filter for identifying regions to pursue for functional validation. Several bioinformatic tools that have been developed for functional enrichment analysis can be applied to differentially methylated regions by first mapping these regions to genes. This is done by mapping the distance between the CpGs and a gene promoter that is potentially regulated by this region. Enrichment analysis based on the genomic region has thus been suggested as a complementary approach and confers substantial interpretive potential. [ 12 ]  Differentially methylated regions can then be compared to a catalog of genomic regions including, for example, sites enriched for specific chromatin modifications or transcription factor binding sites.


A methylation odds ratio can be calculated if we consider the mean methylation rate at a site in cases (or controls) to represent the methylation probability for a randomly chosen DNA strand in the case (or control) tissue samples. The methylation odds ratio is the odds for a random DNA strand in the tissue sample from a random case to be methylated, divided by the same odds for controls. This provides a measure of effect size that incorporates relative magnitudes, but also does not allow for the difference between cases and controls of features of the methylation spectrum, such as variance. The methylation odds ratio is also comparable across prospective and retrospective studies and its value only measures association and does not imply causation. Methylation risk scores have also been calculated which can integrate information across CpG sites by calculating a weighted methylation risk score as the sum of methylation values at each of the markers associated with the phenotype, weighted by marker-specific effect size [ 16 ]


Replication using an independent cohort is required to rule out false positives identified in the initial study. This can be done in a human cohort or in a more focused manner in animal models. It is important that, when selecting the replication cohort, the individuals are reflective of the initial cohort and that the same confounding variables are taken into account. Replication, however, can be limited due to the availability of individuals and samples.


Variations in the epigenome can cause disease but can also arise as a consequence of disease, and distinguishing between the two is a major limitation in EWAS. A way to circumvent this is to determine whether the epigenetic variation is present before any symptoms of disease, preferably via longitudinal studies following the same cohort of people over many years (this in itself has its own setbacks of expense and study time frame). Also needed to be taken into consideration is the possibility that epigenetic variation which arises before disease onset does not necessarily constitute causation for disease.


The most commonly used tissue in EWAS is blood. However, blood samples contain multiple different cell types each of which have a unique epigenetic signature. In this way, it is extremely difficult to determine if the sample you have taken is homogeneous and is therefore difficult to determine if the variation in epigenetic marks are due to the differences in phenotype/stimulus or due to the sample heterogeneity.


Currently many EWAS use blood as a surrogate tissue due to its availability and ease of collection. However, epigenetic changes in the blood may not be associated with the changes in the particular tissue associated with the disease. Many intriguing disorders that could have epigenetic causative factors affect tissues such as brain, lung, heart, etc. However, when studying human patients it is not an option to take these tissues for sampling, and they are therefore left unstudied.


EWASdb [ 17 ] ( http://www.bioapp.org/ewasdb/ ) is the first epigenome-wide association database (first online at 2015, and first published on Nucleic Acids Res. 2018 Oct 13) which stores the results of 1319 EWAS studies associated with 302 diseases/phenotypes (p<1e-7). Three types of EWAS results were stored in EWASdb: EWAS for single epi-marker; EWAS for KEGG pathway and EWAS for GO ( Gene Ontology ) categories.


EWAS Atlas [ 18 ]  ( http://bigd.big.ac.cn/ewas ) is a curated knowledgebase of EWAS that provides a comprehensive collection of EWAS knowledge. Unlike extant data-oriented epigenetic resources, EWAS Atlas features manual curation of EWAS knowledge from extensive publications. In the current implementation, EWAS Atlas focuses on DNA methylation—one of the key epigenetic marks; it integrates a large number of 388,851 high-quality EWAS associations, involving 126 tissues/cell lines and covering 351 traits, 2,230 cohorts and 390 ontology entities, which are completely based on manual curation from 649 studies reported in 495 publications. In addition, it is equipped with a powerful trait enrichment analysis tool, which is capable of profiling trait-trait and trait-epigenome relationships. Future developments include regular curation of recent EWAS publications, incorporation of more epigenetic marks and possible integration of EWAS with  GWAS . Collectively, EWAS Atlas is dedicated to the curation, integration and standardization of EWAS knowledge and has the great potential to help researchers dissect molecular mechanisms of epigenetic modifications associated with biological traits.


EWAS Data Hub [ 19 ]  ( https://bigd.big.ac.cn/ewas/datahub ) is a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.


Epigenomics  is a  peer-reviewed   medical journal  established in 2009 and published by Future Medicine. The  editors-in-chief  are James G. Herman ( University of Pittsburgh Cancer Institute ) and Jörg Tost ( Centre national de génotypage  [ fr ] ). The journal covers all aspects of research on  epigenomics  and  epigenetics  and their implications for diagnosis, prognosis and therapeutics.


The journal is abstracted and indexed in  EMBASE / Excerpta Medica ,  Index Medicus / MEDLINE / PubMed ,  Chemical Abstracts ,  BIOSIS Previews ,  Science Citation Index Expanded , and  Scopus . According to the  Journal Citation Reports , the journal has a 2017  impact factor  of 4.979, ranking it 31st out of 166 journals in the category "Genetics & Heredity". [ 1 ]


Epiphenotyping  involves studying the relationship between DNA methylation patterns and  phenotypic traits  in individuals and populations to be able to predict a phenotype from a DNA methylation profile. In the following sections, the background of epiphenotyping, an overview of a general methodology, its applications, advantages, and limitations are covered.


Epigenetics  refers to heritable changes in gene expression that are not changes in the underlying DNA sequence... [ 1 ]   DNA methylation  is a key epigenetic mechanism, involving the addition of methyl (-CH 3 ) groups to specific DNA regions, almost always at cytosine-guanine dinucleotides (CpG sites). CpG sites are DNA sequences where a cytosine nucleotide is followed by a guanine nucleotide connected by a phosphate group. [ 2 ]


The term  epiphenotyping  comes from integrating the two words "epigenetics" and "phenotyping". Epiphenotyping is the process of using genome-wide DNA methylation patterns to predict phenotypes. [ 3 ] [ 4 ]  Through computational methods, epiphenotyping utilizes DNA methylation data to infer information about phenotypic traits such as gestational age, sex, cell composition, and genetic ancestry. [ 3 ] [ 4 ] [ 5 ] [ 6 ]


Importantly, epiphenotyping and  epigenome-wide association studies (EWAS)  are both approaches used in epigenetics research, however they focus on distinct aspects of epigenetic data analysis. Epiphenotyping is focused on inferring phenotypic information from epigenetic data and understanding the biological implications of epigenetic patterns. [ 3 ]  Whereas EWAS is a hypothesis-driven approach that is centered around identifying specific epigenetic markers associated with a particular disease status, environmental factor, and/or phenotype. [ 7 ] [ 8 ]


The term "epiphenotyping" was first introduced in a paper in 2023 that evaluated the use of epiphenotyping in DNA methylation array studies of the human placenta. [ 3 ]  It is worth noting that although this specific term may be recent, the method itself of using DNA methylation data to predict phenotypes has been utilized since 2011. [ 9 ]


The following section goes through the general methodology employed by studies that generate epiphenotyping models.


Firstly, researchers extract and purify DNA from samples of interest (e.g., blood or placental tissues). The DNA samples are then assayed on high-throughput technologies such as DNA methylation arrays (e.g., Illumina Infinium MethylationEPIC (850K) array) or with  whole genome bisulfite sequencing  (WGBS) to collect DNA methylation data. In addition to collecting biological samples, key biological variables (e.g., gestational age at birth, sex, and self-reported ethnicity) and technical variables (e.g., processing time and temperature at which samples are stored) are also collected. [ 3 ]


The raw DNA methylation data undergoes preprocessing steps to address technical variation and filter out noise or low-quality methylation probes.  Normalization  and batch correction also happen at this stage. R packages such as minfi, wateRmelon, and ewastools facilitate data quality control checks. [ 10 ] [ 11 ] [ 12 ]  For example, bisulfite conversion efficiency, array run quality, and average total fluorescence intensity are crucial measures to assess between samples. [ 3 ] [ 13 ]  The use of data normalization algorithms (e.g., functional or quantile) and probe filtering have been shown to reduce variability in biological and technical variables between sets of DNA methylation data. [ 14 ] [ 15 ] [ 16 ]   Principal component analysis  (PCA) is often applied to reduce the dimensionality of the data before proceeding to analyze it further. [ 17 ]


In this stage a model is developed that tries to predict epiphenotypes from the DNA methylation data. The model predictions are compared with known phenotypic information for validation. From the preprocessed and normalized data, a portion of the dataset is used for training the model known as the training dataset. Epiphenotyping models have been developed that use linear regression to identify CpGs that are predictors of the phenotype of interest, while newer models have used machine learning techniques. [ 4 ] [ 5 ]   Machine learning  algorithms such as  random forests  or  support vector machines  are used to train models on the preprocessed DNA methylation data. [ 18 ]


Once the models have been tested and shown to have high predictive power, they can be applied to new DNA methylation data to infer epiphenotypes. Sometimes generating the epiphenotypes is the final step of a study, but other times the epiphenotypes are generated to be used for further analysis and association studies. Epiphenotypes can be included as covariates in other models that look for associations between phenotypes and DNA methylation patterns. [ 3 ] [ 19 ]


Further analysis can also be done on the estimated epiphenotypes to look for potential associations between epiphenotypes and specific biological functions or disease processes. For instance, there may be CpGs that are highly predictive of a phenotype which could indicate which genes are important for the development of that phenotype. An example of this is examining how blood or placental cell composition relates to preeclampsia, or how certain CpGs predictive of epigenetic age correlate with gestational age discrepancies. [ 3 ]


The most common use of epiphenotyping are  epigenetic clocks  that predict the age of a biological sample based on DNA methylation. [ 20 ] [ 21 ]  Epigenetic changes, including changes in DNA methylation (overall global hypomethylation), are associated with cellular aging. [ 22 ]


Epigenetic predicted chronological age generally increases with actual chronological age but the rate of epigenetic aging can vary across tissues and between individuals. [ 20 ]  Deviation of the predicted age and actual age is known as epigenetic age acceleration. [ 23 ]  Epigenetic age acceleration has been associated with several phenotypes including obesity, [ 24 ]  lung cancer incidence, [ 25 ]  and traumatic stress [ 26 ]  among others.


The first published epigenetic clock that used DNA methylation to predict chronological age came from the Bocklandt group in 2011. [ 9 ]  This clock was generated with saliva samples and was based on 3 CpGs found in 3 gene promoters ( EDARADD, TOM1L1 , and  NPTX2 ). Two years later, Steve Horvath generated epigenetic clocks for 51 different tissues and cell-types using 353 CpGs. [ 4 ]


Since 2013 there has been an explosion of new epigenetic clocks with newer clocks including more CpG sites in their models and having higher predictive accuracy. [ 20 ] [ 21 ]  Additionally, there have been both intrinsic and extrinsic epigenetic clocks developed. [ 27 ]


Newer epigenetic clocks known as the "second generation" were developed that used additional clinical biomarkers (e.g. White blood cell count) to more accurately predict phenotypic age rather than chronological age of a sample from DNA methylation. [ 21 ] [ 28 ]  The PhenoAge model trained on whole blood samples predicted phenotypic age using 513 CpGs, with improved prediction of mortality compared to "first generation" clocks like Horvath's. [ 28 ]  GrimAge is another model trained to use DNA methylation to predict the levels of 7 plasma proteins and lifespan/time-to-death. [ 29 ]  GrimAge has also been shown to be predictive of other phenotypes such as an individual's time-to-coronary heart disease, time-to-cancer, time-to-menopause, and cognitive performance. [ 5 ] [ 29 ]  Both PhenoAge and GrimAge were developed for whole blood, whereas other clocks have been developed for other tissues such as the brain [ 30 ]  and skeletal muscle. [ 31 ]


Epigenetic clocks have also been developed to predict the gestational age based on DNA methylation from the cord blood or placenta. [ 32 ] [ 33 ] [ 34 ]  Epigenetic age acceleration measured from placental samples has been associated with preeclampsia and maternal dislipidemia. [ 35 ] [ 36 ]


Epigenetic clocks have the potential to be used in forensic science applications for estimating the chronological age of a biological sample. [ 38 ] [ 39 ] [ 40 ]  Epigenetic clocks could be used to estimate the age of an unidentified body, a perpetrators biological sample, or settle a legal dispute about an individual's age. Aside from age estimates, there are a number of other potential phenotypes that could be useful in a forensic setting that could be elucidated from DNA methylation: genetic ancestry, smoking, alcohol consumption, body size, socioeconomic status, and more. [ 40 ]


Some limitations in the application of the technology to forensic science is that generating comprehensive methylome profiles is technically difficult for most forensic laboratories, individuals of young and old ages are poorly represented in most model datasets, ethical and legal issues, and low-quantity/quality DNA samples. [ 39 ] [ 40 ] [ 41 ]


It is known that cancer cells have altered DNA methylation patterns compared to normal cells. [ 21 ]  One application of epiphenotyping is to use models to predict an individual's risk of cancer, as well as in some cases DNA methylation patterns are used to diagnose certain cancer types. [ 42 ]  A variety of epiphenotyping models for oncology use have been developed for various cancers including breast, prostate, neurological, and lung among others. [ 21 ]  Another oncological application of epiphenotyping is for predicting the tissue-of-origin of a cancer from DNA methylation. [ 43 ] [ 44 ]


Aside from cancer, epiphenotyping has been done to predict an individual's risk for other diseases including Alzheimer's disease and cardiovascular disease. [ 45 ] [ 46 ]


Another application of epiphenotyping includes predicting cell-type compositions within bulk tissue samples. [ 47 ] [ 48 ]  There have also been some epiphenotyping models that predict genetic ancestry or sex from global DNA methylation patterns  [ 49 ] [ 50 ] [ 51 ]


Epiphenotyping models are only as good as the data they used to train their models. Cohort age range, genetic ancestry make-up, and sex ratio can all affect how predictive the model will be on other data, their external validity. [ 21 ]  Sometimes the epiphenotyping models only work, or work better on certain age ranges, or for certain genetic ancestries, [ 52 ]  this is generally a result of the epiphenotyping model being  overfit .


While  polygenic risk scores (PRS)  represent an estimate of an individual's phenotype based on many genetic variants, methylation risk scores (MRS) similarly provide an estimate of an individual's phenotype based on the methylation at many CpGs. [ 53 ]  PRS are generated through  Genome Wide Association Studies  (GWAS) and analogously MRS are generated by EWAS. Some use the term MRS in a similar way to the term epiphenotyping, to predict a phenotype from DNA methylation data  [ 53 ]


Machine learning classification models like random forests identify discriminatory features in a dataset to generate MRS. For example, MRS have been developed to identify smokers versus non-smokers. [ 54 ]  Alternatively, MRS can be used as a covariate in other analyses to adjust for that phenotype and reduce confounding effects. For example, the predicted smoking status based on DNA methylation was used as a covariate in an EWAS study that identified associations between DNA methylation and schizophrenia  [ 55 ]


The  fetal origins hypothesis  (differentiated from the  Developmental Origins of Health and Disease  hypothesis, which emphasizes environmental conditions both before and immediately after birth) proposes that the period of gestation has significant impacts on the developmental health and wellbeing outcomes for an individual ranging from infancy to adulthood. The effects of fetal origin are marked by three characteristics: latency, wherein effects may not be apparent until much later in life; persistency, whereby conditions resulting from a fetal effect continue to exist for a given individual; and genetic programming, which describes the 'switching on' of a specific gene due to prenatal environment. [ 1 ]  Research in the areas of economics, epidemiology, and epigenetics offer support for the hypothesis. [ 2 ]


The fetus was once believed to be immune to harmful environmental toxins passed from the mother via the placenta. Stemming from this belief, some pregnant women of the early to mid 20th century consumed in drinking of alcohol, ingesting of medications, and  smoked cigarettes.  This easy going attitude about pregnancy was challenged, however, by findings relating substances ingested by a mother to tragic outcomes for a fetus. The birth defects crisis due to the medication thalidomide in the 1960s, where thousands of children were born with defects ranging from brain damage to truncated and missing arms and legs is an example of how a seemingly miracle medication supposed to prevent morning sickness instead had disastrous consequences. [ 3 ]  Similarly, in 1971, a drug known as DES,  diethylstilbestrol , when taken by pregnant women, was found to be causing an incredibly rare cancer,  clear-cell adenocarcinoma of the vagina  in young girls when the cancer was traditionally only found to affect those of post-menopausal age. [ 2 ]  This finding, in particular, demonstrates that events occurring during gestation are capable of impacting future health into adulthood. As perhaps the most well-known fetal risk, It wasn't until 1973 that fetal alcohol syndrome was first formally diagnosed, and not until 1989 that the United States government began requiring warning labels directed at pregnant women to be in place on all alcoholic beverages for sale. [ 2 ]  While the risks associated with certain substances have been well documented during pregnancy, the fetal origins hypothesis goes beyond medical substances to expand upon the effects of maternal stress, obesity, influenza, nutrition, and pollution on a developing fetus. [ 2 ]


Epidemiologist  David Barker  was the earliest proponent of the theory of fetal origins of adult disease, prompting the theory to be denoted as "Barker's hypothesis". In 1986, Barker published findings proposing a direct link between prenatal nutrition and late-onset coronary heart disease. [ 4 ]  He had noticed that the poorest areas of England were the same areas with the highest rates of heart disease, unearthing the predictive relationship between low birth weight and adult disease. His findings were met with criticism, mainly because at the time heart disease was considered to be predominantly determined by lifestyle and genetic factors. Since Barker's initial findings, the results have been replicated in diverse populations of Europe, Asia, North American, Africa, and Australia. [ 2 ]  In explanation of such findings, Barker suggests that fetuses learn to adapt to the environment they expect to enter into once outside of the womb. Essentially, all transmissions entering the placenta act as "postcards" giving the fetus clues as to the outside world, preparing its physiology appropriately. [ 2 ]  This can be an adaptive mechanism, when fetal conditions accurately represent the world of birth; alternatively, it can be a harmful mechanism, when fetal conditions of plenitude or scarcity do not match the world of birth and the child has been physiologically predisposed to inhabit an environment where expected resources are drastically different from reality. [ citation needed ]


The  thrifty phenotype  hypothesis proposes that a low availability of nutrients during the prenatal stage followed by an improvement in nutritional availability in early childhood causes an increase risk of metabolic disorders, including Type II diabetes, as a result of permanent changes in the metabolic processing of glucose-insulin determined in utero. [ 5 ]  This predominantly affects poor communities, where maternal malnutrition may be rampant, in turn causing fetuses to be biologically programmed to expect sparse nutritional environments. But, once in the world, the readily accessible processed foods consumed are unable to be processed efficiently by individuals who had their metabolic systems pre-set to expect scarcity. This difference between expected nutritional deficits and actual food surplus results in obesity and eventually Type II Diabetes. [ 6 ]  Janet Rich-Edwards, an epidemiologist at Harvard Medical School, initially set out to disprove the fetal origins theory with her database of over 100,000 nurses. Instead, she found that the results hold: a strong relationship exists between low birth weight and later coronary heart disease and stroke. [ 7 ]


Pregnancy outcomes can impact the well-being of a society. Comparisons between the children who were in gestation during the  1918 flu pandemic  and those in gestation immediately before or after the health crisis show marked differences between the two groups on census data. Across all socioeconomic measures, those who were fetuses during the crisis attained lower educational achievement, income, and socioeconomic status. Specifically, individuals affected were 15% less likely to graduate high school, 15% more likely to be poor, and 20% more likely to be disabled as adults. Even federal welfare payments were higher for the gestational cohort than those born before or after the flu hit. [ 2 ]  The same economic researcher, Douglas Almond, has investigated other historical situations affecting particular cohorts of fetuses: children born during or immediately following the  Chernobyl nuclear disaster  explosion, and China's  Great Leap Forward  (which resulted in a deadly famine). Both prenatally exposed groups suffered lower cognitive abilities and reduced employment levels. [ 2 ]  Such outcomes can have lasting impacts on the productivity and economic security of a society for an entire generation of individuals, and perhaps even continue to affect future descendants through changes in gene expression. [ citation needed ]


Epigenetics refers to the study of the behavior of genes, and how gene expression can be altered by the environment without changes made in DNA. This is believed to be particularly possible during prenatal development, and both stress and diet have been known to cause changes to a fetus. [ 8 ]  Findings linking maternal exposure to pollution with poor health outcomes for children are possibly linked to the altering of gene expression. [ 2 ]  Additionally, studies focusing on maternal weight show gene altering may be occurring. Women who are overweight at the time of pregnancy have children that are more likely to be overweight themselves. This could be due to the genetic heritability of genes related to obesity. But, siblings born to these same women after they had weight reduction surgery were no more likely to be overweight than the rest of the general population. The metabolic nature of the children was completely different, despite being born to the same mother, supporting the idea that the gestational environment strongly influences future outcomes. [ 2 ]  In discussing the epigenetics findings of fetal origins, Princeton University's Janet Currie says, "The long-vaunted distinction between nature and nurture is therefore outdated and unhelpful. Poor nurture during pregnancy can worsen the hand that nature has dealt." [ 9 ]


Epidemiological research, or the study of the health and disease patterns of certain populations, allow for controls not possible in other research avenues. When a significant situation, disaster, or event occurs across a given population, it can be assumed that the entire population is affected, thus generalizing findings across all demographics in a given group. Certain historical events provide epidemiological support for the  Developmental Origins of Health and Disease , including the Dutch Hunger Winter and the Holocaust. [ citation needed ]


During the 1918 flu pandemic, an estimated 20% of the world's population became infected and 50 million of those infections proved to be fatal. In the United States, the average lifespan dropped by 12 years per person. [ 10 ]  The disease struck indiscriminately by class but was often fatal for those that were in their 20s and 30s while having a particularly strong effect on pregnant women, infecting one third of all American women that were pregnant between 1918 and 1919. [ 1 ]  Children who were born in 1919 and had mothers who were infected during gestation experienced many handicaps later in life. Those born in 1919 experienced a 5% or more wage drop and were often found to have lower educational achievement overall. These children were also 20% more likely to be disabled than other comparable cohorts (early 1918 and late 1919) who did not experience in utero exposure. [ 1 ]  In a study conducted in 2008 it was found that in utero exposure to the pandemic led to higher chances of developing coronary heart disease and kidney disease later in life. The study concluded an 11.8% increased chance of coronary heart disease for those born in the first quarter of 1919. and a 51% increased chance of developing kidney disease for those born in the fourth quarter in 1918 as compared to those born in early 1918 and late 1919. It is also notable that those who were already born but young (between the ages of 1 and 5) during exposure did not have a noticeable increase in coronary heart disease or kidney disease. [ 11 ]  In Italy, one of the countries most affected by the pandemic, there was a drop in educational attainment for those in utero during exposure to the pandemic. Being exposed to the pandemic while in utero would lead to an average loss of 0.3–0.4 years of schooling. These effects were much higher or lower depending on the district of Italy. [ 12 ]  The possibility that maternal exposure to influenza during gestation may be linked to increased rates of schizophrenia later in life for the child. In a recent [ when? ]  study conducted in California they were able to predict schizophrenia in adult offspring by analyzing the influenza antibodies of pregnant women in 1959–1966. It has been hypothesized that a definite link exists between influenza-induced stress on the fetus and schizophrenia. [ 13 ]


During World War II, a Nazi barricade resulted in a severe famine in the Western Netherlands. Where food was previously plentiful, supplies immediately were cut off in November 1944, resulting in a period of starvation that lasted until spring of 1945. The Dutch people survived on as little as 30% of their daily needed caloric intake, and tens of thousands of people died. Analyses of the orderly health records from this time period allow for a systematic comparison of the effects of fetal starvation. Individuals who were in utero during the  Hunger Winter  were subject to different outcomes depending on the period of time in which they were conceived. Those who were in the first trimester during the three-month siege were likely to be born normal size, having caught up with typical development. However, these normal size babies developed high blood pressure, diabetes, and obesity. Contrary to this group, those who were in the third trimester during the siege, who presumably had been well nourished up until the last few months of gestation, were born small. But, these small babies stayed small their entire lives, and did not develop higher rates of obesity or disease. Surprisingly, effects continued to be seen in the offspring of the individuals who were fetuses at the time of the famine. [ 14 ]


During  Ramadan  (of the lunar cycle) many Muslims around the world participate in a fast during the daylight hours of the lunar month. This fasting usually entails abstaining from food or drink for the daylight hours of the month. There are groups that are automatically exempt from having to participate such as the young, sick and old but the list of exemption does not officially include pregnant women (though they are most often allowed exemption). The majority of pregnant women however, choose to participate despite the hardship due to cultural and personal pressure. [ 15 ]  In several recent studies on the effects of fasting during Ramadan and Fetal Origins Hypothesis they have found many negative outcomes on children who were in utero during the fast. These outcomes were as numerous as a change in birth weight to the long term health of the affected. The studies were conducted primarily in Uganda and Iraq but had some smaller sections in Michigan and other places for control groups or specific studies. The effects on birth weight are negatively correlated with Ramadan fasting. Arab Muslim pregnancies that overlap with the Ramadan fast experienced a lower birth weight of 18 grams per child. The effect was slightly larger at a lower birth weight of 20-25 grams if Ramadan fell somewhere in the first or second trimester of the pregnancy. [ 15 ]  In utero exposure to Ramadan fasting has a negative effect on male birth rate causing a skewed sex ratio for total births. When exposure to the Ramadan fast takes place a month after conception it is correlated with a 13% decline in total births. The effects on exposed males and females is drastically different where the male birth rate drops by 26% the female birth rate only drops by 2.5% leading to the assumption that "male vulnerability" may be to blame. [ 15 ]  In a study conducted in Uganda and Iraq on the levels of disability among those exposed to the fast while in utero they concluded that disability rates were much higher for those exposed when controlling for outside factors. Though the measure for disability differs by country the effect is still noticeable. For those born 9 months after Ramadan the likelihood of disability is higher than the surrounding population. The mean rate of disability in Uganda is 3.8% for the country but for those exposed the number is drastically higher at 22% mean disability rate. A similar effect can be observed in Iraq where the mean rate of disability is 1.5% but the disability rate of those exposed is 23%. [ 15 ]  In Uganda the recorded number of blind and deaf can be specifically recorded allowing one to see the effect on this specific disability to expose. Those born 9 months after Ramadan were 33% more likely to be blind and 64% more likely to be deaf than those not exposed in utero. The effects of exposure to the Ramadan fast can even be observed in mental disorders. In a study conducted in Uganda it was concluded that exposure to the fast, early in a pregnancy effectively doubles the likelihood of a person having a cognitive disorder of some kind. A similar discovery was made in Iraq where 63% higher likelihood of a cognitive disorder relative to the mean was discovered for all those exposed. [ 15 ]  Certain specific health effects have been observed for those exposed to in utero fasting. The reported signs of Anemia among the old were higher for those exposed during mid gestation, all other points in the gestation period were found to be insignificant. Anemia is caused by damage to the kidneys so the findings are consistent that the effect is noticeable during mid-gestation when the kidneys are developing. [ 16 ]


The offspring of  Holocaust  survivors have been found to have an epigenetic 'tag' change in their DNA similar to those of their parents, individuals affected directly by the Holocaust. This finding shows that gene expressions can be altered via stressful experiences and then passed down to children through prenatal conditions. While the children of the Holocaust survivors had not themselves experienced Nazi inflicted trauma, they experienced the physiological and emotional trauma as if they had. When compared to Jewish families who were living outside of affected areas of Europe, the findings continued to stand: "The gene changes in the children could only be attributed to Holocaust exposure in the parents." [ 17 ]


Pollution may affect the health of the mother, or cross over the placenta and enter the developing fetus. Beate Ritz, a professor at UCLA, found significantly higher rates of heart malformations and valve defects in the children born to women living in highly polluted areas of Los Angeles. [ 18 ]


Maternal stress has been linked to a number of negative outcomes for the developing fetus. Pregnant women who firsthand experienced the devastation of the World Trade Center attack on  September 11, 2001  were studied to observe the effects of PTSD (post-traumatic stress disorder) on their child's future health. Of the women studied, those who developed PTSD following the attacks had lower basal cortisol levels than a control group. Their children, also, had lower basal cortisol levels than those not exposed to extreme prenatal stressors. The finding was strongest for the women who were in their third trimester during 9/11. Based on the findings that there was a trimester distinction in strength, conclusions can be drawn that the development of a vulnerability to stress was due at least in part to environment in utero. [ 2 ]  9/11 is also correlated with lower birth weights of children born to women with Arabic sounding names following the attacks; this could possibly be due to fear of retaliation or stereotyping associations with the attackers. [ 19 ]  Stress has also been linked to preterm birth, as shown by research studies conducted following the  Tarapaca, Chile earthquake  in 2005, as well as the  Northridge, California earthquake  in 1994. [ 20 ]  Similar findings have been replicated for stressful life experiences and fetal outcomes in the  Hurricane Katrina  population of 2005. Women in New Orleans at the time who reported enduring multiple severe disaster experiences also had a significantly higher chance of delivering early or low birth weight children. [ 21 ]  Experiencing loss during pregnancy also influences postnatal outcomes. Women who experienced the death of a close family member, friend, or spouse, or were pregnant during a wartime conflict, were more likely to have children prematurely, and the children of these women were significantly more likely than the general population to suffer from schizophrenia in adulthood. [ 19 ] [ 22 ]  Besides birth weight, mental health, and reduced cortisol levels, effects of stress during pregnancy have also been linked to impaired cognitive development in children as seen in the maternal population exposed to a severe snowstorm in Canada. [ 23 ]  Women who experienced the most stressful storm related events had children with detriments in cognitive, language, behavioral, and attention outcomes. [ 23 ]  Shockingly, the poorer performance by these children has persisted until the age of ten. [ 23 ]  Even job-related stress has been found to be associated with low birth weight and preterm birth. Working long hours, having temporarily employment, or reporting physically demanding job tasks showed "significant and strong" associations with poorer later birth outcomes. [ 24 ]  Findings for the job stress-birth association have been replicated by obstetricians at Cedars-Sinai Medical Center in Los Angeles. [ 2 ]  However, some research has found that moderate amounts of stress and cortisol passed on to a developing fetus are actually beneficial, perhaps acting to give organs a "workout" prior to birth. [ 2 ]  Further cementing the theory that maternal emotional state can impact child development are the sound research findings that women who are clinically or slightly depressed during pregnancy are more likely to have children with low birth weight, putting them at risk for future health concerns of their own. [ 25 ]  On May 12, 2008, a raid took place in Postville, Iowa, where 389 workers at a meat processing factory were arrested and held for questioning. Out of the 389 workers detained, 270 served sentences and most were deported to primarily Mexico and Guatemala. [ 26 ]  Among those arrested 98% were Latino as they were suspected of being illegal immigrants. Latino families feared future deportations and future raids creating psychological stress on Latinos in the area. In relation to maternal stress a study was conducted which found that Latino babies born 37 weeks after the event experienced a 24% greater risk of lower birth (about 5.5 pounds) weight than babies born in other years. [ 27 ]  The risk for preterm births was also higher for Latina women when compared to non-Latina White women. [ citation needed ]


Criticism of the fetal origins hypothesis can be aimed at the limitations of the research. Confounds abound due to the intertwined nature of environment before and after birth, as well as the correlational factors associated with poverty outcomes. Additionally, the use of historical and longitudinal data raises the question of reliability. [ 28 ]  Also, some critics maintain that despite the compelling relationship documented between low birth weight and later disease, it is too soon to begin to mandate interventions aimed at increasing birth weight. Such interventions could instead have increased negative effects, [ 29 ]  until the specific mechanisms and processes are more deeply understood by which birth and early childhood weight determine development. As stated in "Killing Me Softly: The Fetal Origins Hypothesis", "Such pre-emptive targeting would constitute a radical departure from current policies that steer nearly all healthcare resources to the sick, i.e. the "pound of cure" approach. That said, the existing evidence is not sufficient to allow us to rank the cost-effectiveness of interventions targeted at women against more traditional interventions targeted at children, adolescents, or adults. For example, broadening the target population to women who might get pregnant would reduce the set of policies which are cost effective." [ 1 ]


The implications of the  Developmental Origins of Health and Disease  hypothesis are akin to changing the focus of public health intervention from childhood to in utero. Because the demonstrated effects range from dramatic to subtle in the wide spread areas of educational achievement, emotional stability, career trajectory, life expectancy, disease prognosis, and psychological disorders, interventions addressing the gestational period could potentially have significant impact on individual and societal levels. Proposed and in effect interventions include the following:


Fetal programming , also known as  prenatal programming , is the theory that environmental cues experienced during fetal development play a seminal role in determining health trajectories across the lifespan.


Three main forms of programming that occur due to changes in the maternal environment are:


These changes in the maternal environmental can be due to nutritional alteration, [ 1 ]  hormonal fluctuations [ 2 ]  or exposure to toxins.


In 1944–45, the German blockade of the Netherlands led to a lack of food supplies, causing the  Dutch famine of 1944–45 . The famine caused severe malnutrition among the population, including women in various stages of pregnancy. The Dutch Famine Birth Cohort Study examined the impact of lack of nutrition on children born during or after this famine. It showed that over the course of their life, these children were at greater risk of  diabetes ,  cardiovascular disease ,  obesity , and other  non-communicable diseases . [ citation needed ]


In the 1980s,  David Barker  began a research study on this topic. The Barker Hypothesis, or  Thrifty phenotype , forms the basis for much of the research conducted on fetal programming. This hypothesis states that if the fetus is exposed to low nutrition, it will adapt to that particular environment. Nutrients are diverted towards the development of the heart, brain, and other essential organs of the fetus. The body also undergoes metabolic alterations that ensure survival in spite of low nutrition but may cause problems in situations with normal or high nutrition. [ 3 ]  This leads to increased risk of  metabolic syndrome .


The developing fetus forms an impression of the world into which it will be born via its mother's nutritional status. Its development is thus modulated to create the best chance of survival. However, excessive or insufficient nutrition in the mother can provoke maladaptive developmental responses in the fetus, which in turn manifest in the form of post-natal diseases. It is possible that this has such a profound effect on the fetus’ adult life that it can even outweigh lifestyle factors. [ 1 ]


Body mass index  prior to pregnancy and weight gain during pregnancy are both linked to high blood pressure in the offspring during adulthood. Mouse models suggest that this is due to high levels of the fetal hormone  leptin , which is present in the blood of individuals that are overweight or obese. There is a theory that this hormone has a negative impact on the regulatory systems of the fetus, and renders it impossible to maintain normal blood pressure levels. [ 4 ]


Pre-eclampsia , involving oxygen deprivation and death of  trophoblastic cells  that make up most of the placenta, is a disease which is often associated with maladaptive long-term consequences of inappropriate fetal programming. Here, an inadequately developed and poorly functioning placenta fails to meet the fetus’ nutritional needs during gestation, either by altering its selection for nutrients which can cross into fetal blood or restricting total volume thereof. Consequences of this for the fetus in adult life include cardiovascular and metabolic conditions. [ 5 ]


A delicate balance of hormones during pregnancy is regarded as being highly relevant to fetal programming and may significantly influence the outcome on the offspring. [ 6 ]  Placental endocrine transfer from the mother to the developing fetus could be altered by the mental state of the mother, due to affected  glucocorticoid  transfer that takes place across the placenta. [ 6 ]


Thyroid hormones play an instrumental role during the early development of the fetus's brain. Therefore, mothers suffering from thyroid-related issues and altered thyroid hormone levels may inadvertently trigger structural and functional changes in the fetal brain. The fetus is able to produce its own thyroid hormones from the onset of the second trimester; however, maternal thyroid hormones are important for brain development before and after the baby is able to synthesize the hormones while still in the uterus. [ 7 ]  Due to this, the baby may experience an increased risk of neurological or psychiatric diseases later in life. [ 7 ]


Cortisol (and glucocorticoids more generally) is the most well studied hormonal mechanism that may have prenatal programming effects. [ 8 ]  Although cortisol has normative developmental effects during prenatal development, excess cortisol exposure has deleterious effects on fetal growth, [ 9 ]  the postnatal function of physiological systems such as the hypothalamic-pituitary-adrenal axis  [ 10 ]  and brain structure or connectivity (e.g., amygdala). [ 11 ] [ 12 ]


During gestation, cortisol concentrations in maternal circulation are up to ten times higher than cortisol concentrations in fetal circulation. [ 13 ]  The maternal-to-fetal cortisol gradient is maintained by the placenta, which forms a structural and enzymatic barrier to cortisol. [ 14 ] [ 15 ]  During the first two trimesters of gestation intrauterine cortisol is primarily produced by the maternal adrenal glands. [ 16 ]  However, during the third trimester the fetal adrenal glands begin to endogenously produce cortisol and become responsible for most intrauterine cortisol by the time the fetus reaches term. [ 16 ]


Mental state of the mother during pregnancy affects the fetus in the uterus, predominantly via hormones and genetics. [ 17 ]  The mother's mood, including maternal prenatal anxiety, depression and stress during pregnancy correlates with altered outcomes for the child. [ 17 ]  That being said, not every fetus exposed to these factors is affected in the same way and to the same degree, and genetic and environmental factors are believed to have a significant degree of influence. [ 17 ]


Maternal depression poses one of the greatest risks for increased vulnerability to adverse outcomes for a baby that is developing in the uterus, especially in terms of susceptibility to a variety of psychological conditions. [ 18 ]  Mechanisms that may explain the connection between maternal depression and the offspring's future health are mostly unclear and form a current area of active research. [ 18 ]  Genetic inheritance that may be rendering the child more susceptible may play a role, including the effect on the intrauterine environment for the baby whilst the mother suffers from depression. [ 18 ]


Maternally experienced psychological stress that occurs either prior to or during gestation can have intergenerational effects on offspring. Stress experienced during gestation has been linked with preterm delivery, low birth weight, and increased risk of psychopathology. [ 6 ]  The new mother may suffer from after-effects too, such as postpartum depression, and subsequently may find parenting more difficult as compared to those who did not experience as much stress during their pregnancies. [ 6 ]


Toxins such as alcohol, tobacco and certain drugs to which the baby is exposed to during its development are thought to contribute to fetal programming, especially via alterations to the HPA axis. [ 19 ]  If the exposure occurs during a critical phase of fetal development, it could have drastic and dire consequences for the fetus. [ 19 ]


Prenatal and/or early postnatal exposure to alcohol (ethanol) has been found to have a negative effect on child's neuroendocrine and behavioral factors. [ 20 ]  Alcohol passes through the placenta on being ingested by the mother during her pregnancy, and makes its way to the baby  in utero . [ 20 ]  Changes posed to the fetus through ethanol exposure may significantly effect growth and development; these are collectively known as fetal alcohol spectrum disorders (FASD). [ 20 ]  The exact interaction between ethanol and the developing fetus is complex and largely uncertain, however, several direct and indirect effects have been observed as the fetus matures. [ 20 ]  Predominant among these are irregularities in the fetus's endocrine, metabolic and physiological functions. [ 20 ]


The negative consequences of  smoking  are well-known, and these may be even more apparent during pregnancy. [ 17 ]  Exposure to tobacco smoke during pregnancy, commonly known as  in utero  maternal tobacco smoke exposure (MTSE), can contribute towards various problems in babies of smoking mothers. [ 17 ]  About 20% of mothers smoke whilst pregnant and this is associated with increased risk of complications, such as preterm birth, decreased fetal growth leading to lower birth weight, and impaired fetal lung development. [ 17 ]


There is evidence pointing towards pharmacological programming of the fetus during the first trimester. [ 21 ]  One type of drugs which is suspected of influencing the developing baby when used during pregnancy is anti-hypertensive drugs. [ 21 ]  Pre-eclampsia (a condition of hypertension during pregnancy), is a serious problem for the majority of pregnant mothers and can predispose the mother to a variety of complications, including increased risk of mortality and problems during parturition. [ 21 ]


Gene silencing  is the  regulation of gene expression  in a cell to prevent the expression of a certain  gene . [ 1 ] [ 2 ]  Gene silencing can occur during either  transcription  or  translation  and is often used in research. [ 1 ] [ 2 ]  In particular, methods used to silence genes are being increasingly used to produce  therapeutics  to combat cancer and other diseases, such as  infectious diseases  and  neurodegenerative disorders .


Gene silencing is often considered the same as  gene knockdown . [ 3 ] [ 4 ]  When genes are silenced, their expression is reduced. [ 3 ] [ 4 ]  In contrast, when genes are knocked out, they are completely erased from the organism's  genome  and, thus, have no expression. [ 3 ] [ 4 ]  Gene silencing is considered a gene knockdown mechanism since the methods used to silence genes, such as  RNAi ,  CRISPR , or  siRNA , generally reduce the expression of a gene by at least 70% but do not eliminate it [ citation needed ] . Methods using gene silencing are often considered better than gene knockouts [ citation needed ]  since they allow researchers to study essential genes that are required for the  animal models  to survive and cannot be removed. In addition, they provide a more complete view on the development of diseases since diseases are generally associated with genes that have a reduced expression. [ 3 ]


Antisense oligonucleotides  were discovered in 1978 by  Paul Zamecnik  and Mary Stephenson. [ 5 ]   Oligonucleotides , which are short  nucleic acid  fragments, bind to complementary target mRNA molecules when added to the cell. [ 5 ] [ 6 ]  These molecules can be composed of single-stranded DNA or RNA and are generally 13–25 nucleotides long. [ 6 ] [ 7 ]  The antisense oligonucleotides can affect gene expression in two ways: by using an  RNase H -dependent mechanism or by using a steric blocking mechanism. [ 6 ] [ 7 ]   RNase H-dependent oligonucleotides cause the target  mRNA  molecules to be degraded, while steric-blocker  oligonucleotides  prevent translation of the mRNA molecule. [ 6 ] [ 7 ]  The majority of antisense drugs function through the RNase H-dependent mechanism, in which RNase H hydrolyzes the RNA strand of the DNA/RNA  heteroduplex . [ 6 ] [ 7 ]  expression. [ 6 ]


Ribozymes  are catalytic RNA molecules used to inhibit  gene expression . These molecules work by cleaving  mRNA  molecules, essentially silencing the genes that produced them.  Sidney Altman  and  Thomas Cech  first discovered catalytic RNA molecules, RNase P and group II intron ribozymes, in 1989 and won the Nobel Prize for their discovery. [ 8 ] [ 9 ]  Several types of ribozyme motifs exist, including  hammerhead ,  hairpin ,  hepatitis delta virus ,  group I ,  group II , and  RNase P  ribozymes. Hammerhead, hairpin, and hepatitis delta virus (HDV) ribozyme motifs are generally found in  viruses  or viroid RNAs. [ 8 ]  These motifs are able to self-cleave a specific phosphodiester bond on an mRNA molecule. [ 8 ]  Lower  eukaryotes  and a few  bacteria  contain group I and group II ribozymes. [ 8 ]  These motifs can self-splice by cleaving and joining phosphodiester bonds. [ 8 ]   The last ribozyme motif, the RNase P ribozyme, is found in  Escherichia coli  and is known for its ability to cleave the phosphodiester bonds of several  tRNA  precursors when joined to a protein cofactor. [ 8 ]


The general  catalytic mechanism  used by ribozymes is similar to the mechanism used by protein  ribonucleases . [ 10 ]  These catalytic RNA molecules bind to a specific site and attack the neighboring phosphate in the RNA backbone with their 2' oxygen, which acts as a  nucleophile , resulting in the formation of cleaved products with a 2'3'-cyclic phosphate and a 5' hydroxyl terminal end. [ 10 ]  This catalytic mechanism has been increasingly used by scientists to perform sequence-specific cleavage of target mRNA molecules. In addition, attempts are being made to use ribozymes to produce gene silencing therapeutics, which would silence genes that are responsible for causing diseases. [ 11 ]


RNA interference ( RNAi ) is a natural process used by cells to regulate gene expression. It was discovered in 1998 by  Andrew Fire  and  Craig Mello , who won the Nobel Prize for their discovery in 2006. [ 12 ]  The process to silence genes first begins with the entrance of a  double-stranded RNA (dsRNA)  molecule into the cell, which triggers the RNAi pathway. [ 12 ]  The double-stranded molecule is then cut into small double-stranded fragments by an enzyme called  Dicer . [ 12 ]   These small fragments, which include  small interfering RNAs (siRNA)  and  microRNA (miRNA) , are approximately 21–23 nucleotides in length. [ 12 ] [ 13 ]  The fragments integrate into a multi-subunit protein called the  RNA-induced silencing complex , which contains  Argonaute  proteins that are essential components of the RNAi pathway. [ 12 ] [ 13 ]  One strand of the molecule, called the "guide" strand, binds to RISC, while the other strand, known as the "passenger" strand is degraded. [ 12 ] [ 13 ]  The guide or antisense strand of the fragment that remains bound to RISC directs the sequence-specific silencing of the target mRNA molecule. [ 13 ]  The genes can be silenced by siRNA molecules that cause the endonucleatic cleavage of the target mRNA molecules or by miRNA molecules that suppress translation of the mRNA molecule. [ 13 ]  With the cleavage or translational repression of the mRNA molecules, the genes that form them are rendered essentially inactive. [ 12 ]  RNAi is thought to have evolved as a cellular defense mechanism against invaders, such as  RNA viruses , or to combat the proliferation of  transposons  within a cell's DNA. [ 12 ]   Both RNA viruses and transposons can exist as double-stranded RNA and lead to the activation of RNAi. [ 12 ]  Currently,  siRNAs  are being widely used to suppress specific  gene expression  and to assess the function of  genes . Companies utilizing this approach include  Alnylam ,  Sanofi , [ 14 ]  Arrowhead, Discerna, [ 15 ]  and  Persomics , [ 16 ]  among others.


The  three prime untranslated regions  (3'UTRs) of  messenger RNAs  (mRNAs) often contain regulatory sequences that post-transcriptionally cause gene silencing. Such 3'-UTRs often contain both  binding sites  for microRNAs (miRNAs) as well as for  regulatory proteins . By binding to specific sites within the 3'-UTR, a large number of specific miRNAs decrease  gene expression  of their particular target mRNAs by either inhibiting  translation  or directly causing degradation of the transcript, using a mechanism similar to RNA interference (see  MicroRNA ). The 3'-UTR also may have silencer regions that bind repressor proteins that inhibit the expression of an mRNA. [ citation needed ]


The 3'-UTR often contains  microRNA response elements (MREs) . MREs are sequences to which miRNAs bind and cause gene silencing.  These are prevalent motifs within 3'-UTRs. Among all regulatory motifs within the 3'-UTRs (e.g. including silencer regions), MREs make up about half of the motifs. [ citation needed ]


As of 2014, the  miRBase  web site, [ 17 ]  an archive of miRNA  sequences  and annotations, listed 28,645 entries in 233 biologic species.  Of these, 1,881 miRNAs were in annotated human miRNA loci. miRNAs were predicted to each have an average of about four hundred target mRNAs (causing gene silencing of several hundred genes). [ 18 ]   Freidman et al. [ 18 ]  estimate that >45,000 miRNA  target sites  within human mRNA 3'UTRs are conserved above background levels, and >60% of human protein-coding  genes  have been under selective pressure to maintain pairing to miRNAs. [ citation needed ]


Direct experiments show that a single miRNA can reduce the stability of hundreds of unique mRNAs. [ 19 ]  Other experiments show that a single  miRNA  may repress the production of hundreds of proteins, but that this repression often is relatively mild (less than 2-fold). [ 20 ] [ 21 ]


The effects of miRNA dysregulation of gene expression seem to be important in cancer. [ 22 ]  For instance, in gastrointestinal cancers, nine miRNAs have been identified as  epigenetically  altered and effective in down regulating DNA repair enzymes. [ 23 ]


The effects of miRNA dysregulation of gene expression also seem to be important in  neuropsychiatric  disorders, such as schizophrenia, bipolar disorder, major depression, Parkinson's disease, Alzheimer's disease and autism spectrum disorders. [ 24 ] [ 25 ] [ 26 ]


Gene silencing techniques have been widely used by researchers to study genes associated with disorders. These disorders include  cancer ,  infectious diseases ,  respiratory diseases , and  neurodegenerative disorders . Gene silencing is also currently being used in drug discovery efforts, such as  synthetic lethality ,  high-throughput screening , and miniaturized RNAi screens. [ citation needed ]


RNA interference  has been used to silence genes associated with several cancers. In  in vitro  studies of  chronic myelogenous leukemia (CML) ,  siRNA  was used to cleave the fusion protein,  BCR-ABL , which prevents the drug  Gleevec  ( imatinib ) from binding to the cancer cells. [ 27 ]  Cleaving the fusion protein reduced the amount of transformed  hematopoietic  cells that spread throughout the body by increasing the sensitivity of the cells to the drug. [ 27 ]  RNA interference can also be used to target specific mutants. For instance, siRNAs were able to bind specifically to tumor suppressor  p53  molecules containing a single  point mutation  and destroy it, while leaving the wild-type suppressor intact. [ 28 ]


Receptors involved in  mitogenic  pathways that lead to the increased production of cancer cells there have also been targeted by siRNA molecules. The  chemokine receptor chemokine receptor 4 (CXCR4) , associated with the proliferation of breast cancer, was cleaved by siRNA molecules that reduced the number of divisions commonly observed by the cancer cells. [ 29 ]  Researchers have also used siRNAs to selectively regulate the expression of cancer-related genes. Antiapoptotic proteins, such as  clusterin  and  survivin , are often expressed in cancer cells. [ 30 ] [ 31 ]  Clusterin and survivin-targeting siRNAs were used to reduce the number of antiapoptotic proteins and, thus, increase the sensitivity of the cancer cells to chemotherapy treatments. [ 30 ] [ 31 ]   In vivo  studies are also being increasingly utilized to study the potential use of siRNA molecules in cancer therapeutics. For instance, mice implanted with  colon adenocarcinoma  cells were found to survive longer when the cells were pretreated with siRNAs that targeted  B-catenin  in the cancer cells. [ 32 ]


Viral genes and host genes that are required for viruses to replicate or enter the cell, or that play an important role in the life cycle of the virus are often targeted by antiviral therapies. RNAi has been used to target genes in several viral diseases, such as the  human immunodeficiency virus (HIV)  and  hepatitis . [ 33 ] [ 34 ]  In particular, siRNA was used to silence the primary HIV receptor chemokine receptor 5 (CCR5). [ 35 ]  This prevented the virus from entering the human peripheral blood lymphocytes and the primary hematopoietic stem cells. [ 35 ] [ 36 ]  A similar technique was used to decrease the amount of the detectable virus in  hepatitis B  and C infected cells. In hepatitis B, siRNA silencing was used to target the surface antigen on the hepatitis B virus and led to a decrease in the number of viral components. [ 37 ]  In addition, siRNA techniques used in hepatitis C were able to lower the amount of the virus in the cell by 98%. [ 38 ] [ 39 ]


RNA interference has been in commercial use to control virus diseases of plants for over 20 years (see  Plant disease resistance ). In 1986–1990, multiple examples of "coat protein-mediated resistance" against plant viruses were published, before RNAi had been discovered. [ 40 ]   In 1993, work with tobacco etch virus first demonstrated that host organisms can target specific virus or mRNA sequences for degradation, and that this activity is the mechanism behind some examples of virus resistance in transgenic plants. [ 41 ] [ 42 ]  The discovery of small interfering RNAs (the specificity determinant in RNA-mediated gene silencing) also utilized virus-induced post-transcriptional gene silencing in plants. [ 43 ]  By 1994, transgenic squash varieties had been generated expressing coat protein genes from three different viruses, providing squash hybrids with field-validated multiviral resistance that remain in commercial use at present. Potato lines expressing viral replicase sequences that confer resistance to potato leafroll virus were sold under the trade names NewLeaf Y and NewLeaf Plus, and were widely accepted in commercial production in 1999–2001, until McDonald's Corp. decided not to purchase  GM  potatoes and Monsanto decided to close their NatureMark potato business. [ 44 ]   Another frequently cited example of virus resistance mediated by gene silencing involves papaya, where the Hawaiian papaya industry was rescued by virus-resistant GM papayas produced and licensed by university researchers rather than a large corporation. [ 45 ]   These papayas also remain in use at present, although not without significant public protest, [ 46 ] [ 47 ]  which is notably less evident in medical uses of gene silencing.


Gene silencing techniques have also been used to target other viruses, such as the  human papilloma virus , the  West Nile virus , and the Tulane virus. The E6 gene in tumor samples retrieved from patients with the human papilloma virus was targeted and found to cause apoptosis in the infected cells. [ 48 ]  Plasmid siRNA expression vectors used to target the West Nile virus were also able to prevent the replication of viruses in cell lines. [ 49 ]  In addition, siRNA has been found to be successful in preventing the replication of the Tulane virus, part of the virus family  Caliciviridae , by targeting both its structural and non-structural genes. [ 50 ]  By targeting the NTPase gene, one dose of siRNA 4 hours pre-infection was shown to control Tulane virus replication for 48 hours post-infection, reducing the viral  titer  by up to 2.6 logarithms. [ 50 ]   Although the Tulane virus is species-specific and does not affect humans, it has been shown to be closely related to the human  norovirus , which is the most common cause of  acute gastroenteritis  and  food-borne disease  outbreaks in the United States. [ 51 ]  Human noroviruses are notorious for being difficult to study in the laboratory, but the Tulane virus offers a model through which to study this family of viruses for the clinical goal of developing therapies that can be used to treat illnesses caused by human norovirus. [ citation needed ]


Unlike viruses, bacteria are not as susceptible to silencing by siRNA. [ 52 ]  This is largely due to how bacteria replicate. Bacteria replicate outside of the host cell and do not contain the necessary machinery for RNAi to function. [ 52 ]  However, bacterial infections can still be suppressed by siRNA by targeting the host genes that are involved in the immune response caused by the infection or by targeting the host genes involved in mediating the entry of bacteria into cells. [ 52 ] [ 53 ]  For instance, siRNA was used to reduce the amount of pro-inflammatory  cytokines  expressed in the cells of mice treated with  lipopolysaccharide (LPS) . [ 52 ] [ 54 ]  The reduced expression of the inflammatory cytokine,  tumor necrosis factor α (TNFα) , in turn, caused a reduction in the septic shock felt by the LPS-treated mice. [ 54 ]  In addition, siRNA was used to prevent the bacteria,  Psueomonas aeruginosa , from invading murine lung epithelial cells by knocking down the caveolin-2 (CAV2) gene. [ 55 ]  Thus, though bacteria cannot be directly targeted by siRNA mechanisms, they can still be affected by siRNA when the components involved in the bacterial infection are targeted. [ citation needed ]


Ribozymes, antisense oligonucleotides, and more recently RNAi have been used to target mRNA molecules involved in  asthma . [ 53 ] [ 56 ]  These experiments have suggested that siRNA may be used to combat other respiratory diseases, such as  chronic obstructive pulmonary disease (COPD)  and  cystic fibrosis . [ 53 ]  COPD is characterized by  goblet cell   hyperplasia  and  mucus   hypersecretion . [ 57 ]  Mucus secretion was found to be reduced when the  transforming growth factor (TGF)-α  was targeted by siRNA in NCI-H292 human airway  epithelial cells . [ 58 ]  In addition to mucus hypersecretion,  chronic inflammation  and damaged lung tissue are characteristic of COPD and asthma. The  transforming growth factor TGF-β  is thought to play a role in these manifestations. [ 59 ] [ 60 ]  As a result, when  interferon (IFN)-γ  was used to knock down TGF-β,  fibrosis  of the lungs, caused by damage and scarring to lung tissue, was improved. [ 61 ] [ 62 ]


Huntington's disease (HD)  results from a mutation in the  huntingtin gene  that causes an excess of CAG repeats. [ 63 ]  The gene then forms a mutated  huntingtin protein  with polyglutamine repeats near the  amino terminus . [ 64 ]  This disease is incurable and known to cause motor,  cognitive , and behavioral deficits. [ 65 ]  Researchers have been looking to gene silencing as a potential therapeutic for HD. [ citation needed ]


Gene silencing can be used to treat HD by targeting the mutant huntingtin protein. The mutant huntingtin protein has been targeted through gene silencing that is allele specific using  allele specific oligonucleotides . In this method, the antisense oligonucleotides are used to target  single nucleotide polymorphism (SNPs) , which are single nucleotide changes in the DNA sequence, since HD patients have been found to share common SNPs that are associated with the mutated huntingtin allele. It has been found that approximately 85% of patients with HD can be covered when three SNPs are targeted. In addition, when antisense oligonucleotides were used to target an HD-associated SNP in mice, there was a 50% decrease in the mutant huntingtin protein. [ 63 ]


Non-allele specific gene silencing using siRNA molecules has also been used to silence the mutant huntingtin proteins. Through this approach, instead of targeting SNPs on the mutated protein, all of the normal and mutated huntingtin proteins are targeted. When studied in mice, it was found that siRNA could reduce the normal and mutant huntingtin levels by 75%. At this level, they found that the mice developed improved  motor control  and a longer  survival rate  when compared to the controls. [ 63 ]  Thus, gene silencing methods may prove to be beneficial in treating HD.


Amyotrophic lateral sclerosis (ALS) , also called Lou Gehrig's disease, is a  motor neuron disease  that affects the  brain  and  spinal cord . The disease causes  motor neurons  to degenerate, which eventually leads to neuron death and muscular degeneration. [ 66 ]  Hundreds of mutations in the Cu/Zn  superoxide dismutase  (SOD1) gene have been found to cause ALS. [ 67 ]  Gene silencing has been used to knock down the SOD1 mutant that is characteristic of ALS. [ 67 ] [ 68 ]  In specific, siRNA molecules have been successfully used to target the SOD1 mutant gene and reduce its expression through allele-specific gene silencing. [ 67 ] [ 69 ]


There are several challenges associated with gene silencing therapies, including  delivery  and specificity for targeted cells. For instance, for treatment of neurodegenerative disorders, molecules for a prospective gene silencing therapy must be delivered to the brain. The  blood–brain barrier  makes it difficult to deliver molecules into the brain through the bloodstream by preventing the passage of the majority of molecules that are injected or absorbed into the blood. [ 63 ] [ 64 ]  Thus, researchers have found that they must directly inject the molecules or implant pumps that push them into the brain. [ 63 ]


Once inside the brain, however, the molecules must move inside of the targeted cells. In order to efficiently deliver siRNA molecules into the cells,  viral vectors  can be used. [ 63 ] [ 65 ]   Nevertheless, this method of delivery can also be problematic as it can elicit an immune response against the molecules. In addition to delivery, specificity has also been found to be an issue in gene silencing. Both antisense oligonucleotides and siRNA molecules can potentially bind to the wrong mRNA molecule. [ 63 ]  Thus, researchers are searching for more efficient methods to deliver and develop specific gene silencing therapeutics that are still safe and effective. [ citation needed ]


Arctic Apples are a suite of trademarked [ 70 ]  apples that contain a nonbrowning trait created by using gene silencing to reduce the expression of polyphenol oxidase (PPO). It is the first approved food product to use this technique. [ 71 ]


Genomic imprinting  is an  epigenetic  phenomenon that causes  genes  to be  expressed  or not, depending on whether they are inherited from the female or male parent. [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ]   Genes can also be partially imprinted. Partial imprinting occurs when  alleles  from both parents are differently expressed rather than complete expression and complete suppression of one parent's allele. [ 6 ]  Forms of genomic imprinting have been demonstrated in fungi, plants and animals. [ 7 ] [ 8 ]  In 2014, there were about 150 imprinted genes known in mice and about half that in humans. [ 9 ]  As of 2019, 260 imprinted genes have been reported in mice and 228 in humans. [ 10 ]


Genomic imprinting is an inheritance process independent of the classical  Mendelian inheritance . [ 11 ]  It is an epigenetic process that involves  DNA methylation  and  histone methylation  without altering the genetic sequence. These epigenetic marks are established ("imprinted") in the  germline  (sperm or egg cells) of the parents and are maintained through  mitotic  cell divisions in the  somatic cells  of an organism. [ 12 ]


Appropriate imprinting of certain genes is important for normal development. Human diseases involving genomic imprinting include  Angelman ,  Prader–Willi , and  Beckwith–Wiedemann  syndromes. [ 13 ]  Methylation defects have also been associated with male  infertility . [ 3 ]


In  diploid  organisms (like humans), the somatic cells possess two copies of the  genome , one inherited from the male and one from the female. Each  autosomal  gene is therefore represented by two copies, or alleles, with one copy inherited from each parent at  fertilization . The expressed allele is dependent upon its parental origin. For example, the gene encoding  insulin-like growth factor 2  (IGF2/Igf2) is only expressed from the allele inherited from the male. Although imprinting accounts for a small proportion of mammalian genes, they play an important role in embryogenesis particularly in the formation of visceral structures and the nervous system. [ 14 ]


The term "imprinting" was first used to describe events in the insect  Pseudococcus nipae . [ 15 ]  In  Pseudococcids  ( mealybugs ) ( Hemiptera ,  Coccoidea ) both the male and female develop from a fertilised egg. In females, all chromosomes remain  euchromatic  and functional. In embryos destined to become males, one  haploid  set of chromosomes becomes  heterochromatinised  after the sixth cleavage division and remains so in most tissues; males are thus functionally haploid. [ 16 ] [ 17 ] [ 18 ]


That imprinting might be a feature of mammalian development was suggested in breeding experiments in mice carrying reciprocal  chromosomal translocations . [ 19 ]  Nucleus transplantation experiments in  mouse  zygotes in the early 1980s confirmed that normal development requires the contribution of both the maternal and paternal genomes. The vast majority of mouse embryos derived from  parthenogenesis  (called parthenogenones, with two maternal or egg genomes) and  androgenesis  (called androgenones, with two paternal or sperm genomes) die at or before the blastocyst/implantation stage. In the rare instances that they develop to postimplantation stages, gynogenetic embryos show better embryonic development relative to placental development, while for androgenones, the reverse is true. Nevertheless, for the latter, only a few have been described (in a 1984 paper). [ 20 ] [ 21 ] [ 22 ]  Nevertheless, in 2018 genome editing allowed for  bipaternal and viable bimaternal [ 23 ] [ 24 ]  mouse and even (in 2022) parthenogenesis, still this is far from full reimprinting. [ 25 ]  Finally in March 2023 viable bipaternal embryos were created. [ 26 ]


No naturally occurring cases of parthenogenesis exist in mammals because of imprinted genes. However, in 2004, experimental manipulation by Japanese researchers of a paternal methylation imprint controlling the  Igf2  gene led to the birth of a mouse (named  Kaguya ) with two maternal sets of chromosomes, though it is not a true parthenogenone since cells from two different female mice were used. The researchers were able to succeed by using one egg from an immature parent, thus reducing maternal imprinting, and modifying it to express the gene Igf2, which is normally only expressed by the paternal copy of the gene.


Parthenogenetic/gynogenetic embryos have twice the normal expression level of maternally derived genes, and lack expression of paternally expressed genes, while the reverse is true for androgenetic embryos. It is now known that there are at least 80 imprinted genes in humans and mice, many of which are involved in embryonic and placental growth and development. [ 12 ] [ 27 ] [ 28 ] [ 29 ]   Hybrid  offspring of two species may exhibit unusual growth due to the novel combination of imprinted genes. [ 30 ]


Various methods have been used to identify imprinted genes. In swine, Bischoff  et al.  compared transcriptional profiles using  DNA microarrays  to survey differentially expressed genes between parthenotes (2 maternal genomes) and control fetuses (1 maternal, 1 paternal genome). [ 31 ]  An intriguing study surveying the  transcriptome  of  murine  brain tissues revealed over 1300 imprinted gene loci (approximately 10-fold more than previously reported) by RNA-sequencing from F1 hybrids resulting from reciprocal crosses. [ 32 ]  The result however has been challenged by others who claimed that this is an overestimation by an order of magnitude due to flawed statistical analysis. [ 33 ] [ 34 ]


In domesticated livestock,  single-nucleotide polymorphisms  in imprinted genes influencing  foetal  growth and development have been shown to be associated with economically important production traits in cattle, sheep and pigs. [ 35 ] [ 36 ]


At the same time as the generation of the gynogenetic and androgenetic embryos discussed above, mouse embryos were also being generated that contained only small regions that were derived from either a paternal or maternal source. [ 37 ] [ 38 ]  The generation of a series of such  uniparental disomies , which together span the entire genome, allowed the creation of an imprinting map. [ 39 ]  Those regions which when inherited from a single parent result in a discernible phenotype contain imprinted gene(s). Further research showed that within these regions there were often numerous imprinted genes. [ 40 ]  Around 80% of imprinted genes are found in clusters such as these, called imprinted domains, suggesting a level of co-ordinated control. [ 5 ]  More recently, genome-wide screens to identify imprinted genes have used differential expression of mRNAs from control fetuses and parthenogenetic or androgenetic fetuses hybridized to  gene expression profiling  microarrays, [ 41 ]  allele-specific gene expression using  SNP genotyping  microarrays, [ 42 ]  transcriptome sequencing, [ 43 ]  and in silico prediction pipelines. [ 44 ]