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Epigenetics Dec 2023Most pregnancy complications originate with early placentation. MicroRNAs (miRNAs) may play an important role in placentation and function as biomarkers of future...
Most pregnancy complications originate with early placentation. MicroRNAs (miRNAs) may play an important role in placentation and function as biomarkers of future pregnancy complications. We summarized from the literature all first trimester circulating miRNAs associated with pregnancy complications of placental origin and further identified the miRNAs which have the most evidence as potential early biomarkers for pregnancy complications. We conducted a systematic review following PRISMA reporting guidelines (PROSPERO CRD42020183421). We identified all first trimester serum or plasma miRNAs associated with a pregnancy complication of placental origin (preeclampsia, intrauterine growth restriction (IUGR), gestational hypertension, preterm delivery) and the number of times those miRNAs were identified, as a measure of replication. Twenty-one studies examined 118 unique miRNAs, and 87 were associated with at least one pregnancy complication; preeclampsia was the most common. Seven miRNAs were significantly associated with a pregnancy complication in at least two studies: miR-125b, miR-518b, miR-628-3p, miR-365a-3p, miR-520h, miR-374a-5p, miR-191-5p. Few miRNAs were associated with more than one pregnancy complication: miR-518b and miR-520h with preeclampsia and gestational hypertension, miR-374a-5p and miR-191-5p with preterm birth and preeclampsia. Our systematic review suggests seven miRNAs as potential biomarkers of pregnancy complications. These complications are thought to originate with early placental defects and these miRNAs may also be biomarkers of placental pathology. First-trimester biomarkers of pregnancy complications can facilitate early detection and interventions.
Topics: Pregnancy; Humans; Infant, Newborn; Female; Pregnancy Trimester, First; Pre-Eclampsia; Hypertension, Pregnancy-Induced; Circulating MicroRNA; Placenta; Premature Birth; DNA Methylation; MicroRNAs; Pregnancy Complications; Placentation; Biomarkers
PubMed: 36503407
DOI: 10.1080/15592294.2022.2152615 -
Epigenetics Dec 2024Epigenetic modifications, including DNA methylation, are proposed mechanisms explaining the impact of parental exposures to foetal development and lifelong health.... (Review)
Review
Epigenetic modifications, including DNA methylation, are proposed mechanisms explaining the impact of parental exposures to foetal development and lifelong health. Micronutrients including folate, choline, and vitamin B provide methyl groups for the one-carbon metabolism and subsequent DNA methylation processes. Placental DNA methylation changes in response to one-carbon moieties hold potential targets to improve obstetrical care. We conducted a systematic review on the associations between one-carbon metabolism and human placental DNA methylation. We included 22 studies. Findings from clinical studies with minimal ErasmusAGE quality score 5/10 ( = 15) and studies ( = 3) are summarized for different one-carbon moieties. Next, results are discussed per study approach: (1) global DNA methylation ( = 9), (2) genome-wide analyses ( = 4), and (3) gene specific ( = 14). Generally, one-carbon moieties were not associated with global methylation, although conflicting outcomes were reported specifically for choline. Using genome-wide approaches, few differentially methylated sites associated with S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), or dietary patterns. Most studies taking a gene-specific approach indicated site-specific relationships depending on studied moiety and genomic region, specifically in genes involved in growth and development including , , and ; however, overlap between studies was low. Therefore, we recommend to further investigate the impact of an optimized one-carbon metabolism on DNA methylation and lifelong health.
Topics: Female; Humans; Pregnancy; DNA Methylation; Placenta; Genome-Wide Association Study; Folic Acid; S-Adenosylmethionine; Choline; Carbon
PubMed: 38484284
DOI: 10.1080/15592294.2024.2318516 -
Archives of Gynecology and Obstetrics Feb 2024Polycystic ovary syndrome (PCOS) is an endocrine metabolic disease that affects women of reproductive age and is one of the main causes of anovulatory infertility.... (Review)
Review
PURPOSE
Polycystic ovary syndrome (PCOS) is an endocrine metabolic disease that affects women of reproductive age and is one of the main causes of anovulatory infertility. However, the cause of PCOS is yet fully understood, and genetic factors play an important role in its etiology. In this study, we reviewed the main genes involved in the etiology of PCOS and the influence of DNA methylation, aiming to answer the study´s guiding question: 'What is the influence of DNA methylation on the main genes involved in PCOS?'.
METHODS
We used the MEDLINE database, and inclusion criteria (primary and original articles, written in English, found through our entry terms) and exclusion criteria (literature reviews and articles that used animals to perform the experiments and that focused in other epigenetics mechanism without being DNA methylation) were applied.
RESULTS
Twenty-three scientific articles, from a total of 43 articles read in full, were chosen for this study. Eighteen studies confirmed DNA methylation associated with PCOS.
CONCLUSION
The most relevant genes related to PCOS were INSR, LHCGR, and RAB5B, which may be epigenetically altered in DNA, with the first two genes hypomethylated and the last hypermethylated. The epigenetic changes presented in the genes related to PCOS or their promoters were only at the CpG sites.
Topics: Animals; Female; Humans; DNA Methylation; Polycystic Ovary Syndrome; Epigenesis, Genetic; Reproduction
PubMed: 37119419
DOI: 10.1007/s00404-023-07025-5 -
Talanta Jun 2024Gene methylation-related enzymes (GMREs) are disfunction and aberrantly expressed in a variety of cancers, such as lung, gastric, and pancreatic cancers and have... (Review)
Review
Gene methylation-related enzymes (GMREs) are disfunction and aberrantly expressed in a variety of cancers, such as lung, gastric, and pancreatic cancers and have important implications for human health. Therefore,it is critical for early diagnosis and therapy of tumor to develop strategies that allow rapid and sensitive quantitative and qualitative detection of GMREs. With the development of modern analytical techniques and the application of various biosensors, there are numerous methods have been developed for analysis of GMREs. Therefore, this paper provides a systematic review of the strategies for level and activity assay of various GMREs including methyltransferases and demethylase. The detection methods mainly involve immunohistochemistry, colorimetry, fluorescence, chemiluminescence, electrochemistry, etc. Then, this review also addresses the coordinated role of various detection probes, novel nanomaterials, and signal amplification methods. The aim is to highlight potential challenges in the present field, to expand the analytical application of GMREs detection strategies, and to meet the urgent need for future disease diagnosis and intervention.
Topics: Humans; DNA Methylation; RNA Methylation; DNA; Biosensing Techniques; Neoplasms
PubMed: 38471421
DOI: 10.1016/j.talanta.2024.125872 -
Critical Reviews in Oncology/hematology Jan 2024The research aimed to identify previously published CpG-methylation-based prognostic biomarkers and prediction models for colorectal cancer (CRC) prognosis and validate... (Review)
Review
The research aimed to identify previously published CpG-methylation-based prognostic biomarkers and prediction models for colorectal cancer (CRC) prognosis and validate them in a large external cohort. A systematic search was conducted, analyzing 298 unique CpGs and 12 CpG-based prognostic models from 28 studies. After adjustment for clinical variables, 48 CpGs and five prognostic models were confirmed to be associated with survival. However, the discrimination ability of the models was insufficient, with area under the receiver operating characteristic curves ranging from 0.53 to 0.62. Calibration accuracy was mostly poor, and no significant added prognostic value beyond traditional clinical variables was observed. All prognostic models were rated at high risk of bias. While a fraction of CpGs showed potential clinical utility and generalizability, the CpG-based prognostic models performed poorly and lacked clinical relevance.
Topics: Humans; DNA Methylation; Prognosis; Biomarkers, Tumor; Colorectal Neoplasms
PubMed: 37952858
DOI: 10.1016/j.critrevonc.2023.104199 -
Environmental and Molecular Mutagenesis Aug 2023Individual differences in drug response have always existed in clinical treatment. Many non-genetic factors show non-negligible impacts on personalized medicine.... (Review)
Review
Individual differences in drug response have always existed in clinical treatment. Many non-genetic factors show non-negligible impacts on personalized medicine. Emerging studies have demonstrated epigenetic could connect non-genetic factors and individual treatment differences. We used systematic retrieval methods and reviewed studies that showed individual factors' impact on DNA methylation of drug metabolism genes. In total, 68 studies were included, and half (n = 36) were cohort studies. Six aspects of individual factors were summarized from the perspective of personalized medicine: parental exposure, environmental pollutants exposure, obesity and diet, drugs, gender and others. The most research (n = 11) focused on ABCG1 methylation. The majority of studies showed non-genetic factors could result in a significant DNA methylation alteration in drug metabolism genes, which subsequently affects the pharmacokinetic processes. However, the underlying mechanism remained unknown. Finally, some viewpoints were presented for future research.
Topics: Humans; DNA Methylation; Epigenesis, Genetic; Diet
PubMed: 37522536
DOI: 10.1002/em.22567 -
Neurosurgical Review Apr 2024Recent studies suggest that differential DNA methylation could play a role in the mechanism of cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI) after... (Review)
Review
Recent studies suggest that differential DNA methylation could play a role in the mechanism of cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH). Considering the significance of this matter and a lack of effective prophylaxis against DCI, we aim to summarize the current state of knowledge regarding their associations with DNA methylation and identify the gaps for a future trial. PubMed MEDLINE, Scopus, and Web of Science were searched by two authors in three waves for relevant DNA methylation association studies in DCI after aSAH. PRISMA checklist was followed for a systematic structure. STROBE statement was used to assess the quality and risk of bias within studies. This research was funded by the National Science Centre, Poland (grant number 2021/41/N/NZ2/00844). Of 70 records, 7 peer-reviewed articles met the eligibility criteria. Five studies used a candidate gene approach, three were epigenome-wide association studies (EWAS), one utilized bioinformatics of the previous EWAS, with two studies using more than one approach. Methylation status of four cytosine-guanine dinucleotides (CpGs) related to four distinct genes (ITPR3, HAMP, INSR, CDHR5) have been found significantly or suggestively associated with DCI after aSAH. Analysis of epigenetic clocks yielded significant association of lower age acceleration with radiological CVS but not with DCI. Hub genes for hypermethylation (VHL, KIF3A, KIFAP3, RACGAP1, OPRM1) and hypomethylation (ALB, IL5) in DCI have been indicated through bioinformatics analysis. As none of the CpGs overlapped across the studies, meta-analysis was not applicable. The identified methylation sites might potentially serve as a biomarker for early diagnosis of DCI after aSAH in future. However, a lack of overlapping results prompts the need for large-scale multicenter studies. Challenges and prospects are discussed.
Topics: Humans; Subarachnoid Hemorrhage; DNA Methylation; Cerebral Infarction; Brain Ischemia; Biomarkers; Vasospasm, Intracranial; Cadherin Related Proteins
PubMed: 38594575
DOI: 10.1007/s10143-024-02381-5 -
Biomedicine & Pharmacotherapy =... Jul 2024The intricate crosstalk between long noncoding RNAs (lncRNAs) and epigenetic modifications such as chromatin/histone methylation and acetylation offer new perspectives... (Review)
Review
The intricate crosstalk between long noncoding RNAs (lncRNAs) and epigenetic modifications such as chromatin/histone methylation and acetylation offer new perspectives on the pathogenesis and treatment of kidney diseases. lncRNAs, a class of transcripts longer than 200 nucleotides with no protein-coding potential, are now recognized as key regulatory molecules influencing gene expression through diverse mechanisms. They modulate the epigenetic modifications by recruiting or blocking enzymes responsible for adding or removing methyl or acetyl groups, such as DNA, N6-methyladenosine (m6A) and histone methylation and acetylation, subsequently altering chromatin structure and accessibility. In kidney diseases such as acute kidney injury (AKI), chronic kidney disease (CKD), diabetic nephropathy (DN), glomerulonephritis (GN), and renal cell carcinoma (RCC), aberrant patterns of DNA/RNA/histone methylation and acetylation have been associated with disease onset and progression, revealing a complex interplay with lncRNA dynamics. Recent studies have highlighted how lncRNAs can impact renal pathology by affecting the expression and function of key genes involved in cell cycle control, fibrosis, and inflammatory responses. This review will separately address the roles of lncRNAs and epigenetic modifications in renal diseases, with a particular emphasis on elucidating the bidirectional regulatory effects and underlying mechanisms of lncRNAs in conjunction with DNA/RNA/histone methylation and acetylation, in addition to the potential exacerbating or renoprotective effects in renal pathologies. Understanding the reciprocal relationships between lncRNAs and epigenetic modifications will not only shed light on the molecular underpinnings of renal pathologies but also present new avenues for therapeutic interventions and biomarker development, advancing precision medicine in nephrology.
Topics: RNA, Long Noncoding; Humans; Epigenesis, Genetic; Histones; Acetylation; DNA Methylation; Kidney Diseases; Chromatin; Animals
PubMed: 38870627
DOI: 10.1016/j.biopha.2024.116922 -
Fertility and Sterility Jan 2024Because analytic technologies improve, increasing amounts of data on methylation differences between assisted reproductive technology (ART) and unassisted conceptions... (Review)
Review
IMPORTANCE
Because analytic technologies improve, increasing amounts of data on methylation differences between assisted reproductive technology (ART) and unassisted conceptions are available. However, various studies use different tissue types and different populations in their analyses, making data comparison and integration difficult.
OBJECTIVE
To compare and integrate data on genome-wide analyses of methylation differences due to ART, allowing exposure of overarching themes.
EVIDENCE REVIEW
All studies undertaking genome-wide analysis of human methylation differences due to ART or infertility in any tissue type across the lifespan were assessed for inclusion.
FINDINGS
Seventeen studies were identified that met the inclusion criteria. One study assessed trophectoderm biopsies, 2 first-trimester placenta, 1 first-trimester fetal tissue, 2 term placenta, 7 cord blood, 3 newborn dried blood spots, 1 childhood buccal smears, 1 childhood peripheral blood, and 2 adult peripheral blood. Eleven studies compared tissues from in vitro fertilization (IVF) conceptions with those of unassisted conceptions, 4 compared intracytoplasmic sperm injection with unassisted conceptions, 4 compared non-IVF fertility treatment (NIFT) with unassisted conceptions, 4 compared NIFT with IVF, and 5 compared an infertile population (conceiving via various methods) with an unassisted presumably fertile population. In studies assessing placental tissue, 1 gene with potential methylation changes due to IVF when compared with unassisted conceptions was identified by 2 studies. In blood, 11 potential genes with methylation changes due to IVF compared with unassisted conceptions were identified by 2 studies, 1 of which was identified by 3 studies. Three potentially affected genes were identified by 2 studies involving blood between intracytoplasmic sperm injection and unassisted populations. There were no overlapping genes identified in any tissue type between NIFT and unassisted populations, between NIFT and IVF, or the infertility combined population when compared with the unassisted fertile population.
CONCLUSIONS
Comparing studies is challenging due to differing variables between analyses. However, even in similar tissue types and populations, overlapping methylation changes are limited, suggesting that differences due to ART are minimal.
RELEVANCE
Information from this systematic review is significant for providers and patients who provide and use ART to understand methylation risks that may be associated with the technology.
Topics: Adult; Child; Female; Humans; Infant, Newborn; Male; Pregnancy; DNA Methylation; Fertilization in Vitro; Genome-Wide Association Study; Infertility; Placenta; Reproductive Techniques, Assisted; Semen
PubMed: 37827482
DOI: 10.1016/j.fertnstert.2023.10.007 -
Briefings in Bioinformatics Sep 2023DNA methylation is a fundamental epigenetic modification involved in various biological processes and diseases. Analysis of DNA methylation data at a genome-wide and...
DNA methylation is a fundamental epigenetic modification involved in various biological processes and diseases. Analysis of DNA methylation data at a genome-wide and high-throughput level can provide insights into diseases influenced by epigenetics, such as cancer. Recent technological advances have led to the development of high-throughput approaches, such as genome-scale profiling, that allow for computational analysis of epigenetics. Deep learning (DL) methods are essential in facilitating computational studies in epigenetics for DNA methylation analysis. In this systematic review, we assessed the various applications of DL applied to DNA methylation data or multi-omics data to discover cancer biomarkers, perform classification, imputation and survival analysis. The review first introduces state-of-the-art DL architectures and highlights their usefulness in addressing challenges related to cancer epigenetics. Finally, the review discusses potential limitations and future research directions in this field.
Topics: Humans; DNA Methylation; Deep Learning; Epigenesis, Genetic; Genome; Neoplasms
PubMed: 37985455
DOI: 10.1093/bib/bbad411