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Search Results (1,229)

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23 pages, 438 KiB  
Review
Molecular and Cellular Mechanisms of Immunosenescence: Modulation Through Interventions and Lifestyle Changes
by Luca Pangrazzi and Andreas Meryk
Biology 2025, 14(1), 17; https://doi.org/10.3390/biology14010017 (registering DOI) - 27 Dec 2024
Viewed by 150
Abstract
Immunosenescence, the age-related decline in immune function, is a complex biological process with profound implications for health and longevity. This phenomenon, characterized by alterations in both innate and adaptive immunity, increases susceptibility to infections, reduces vaccine efficacy, and contributes to the development of [...] Read more.
Immunosenescence, the age-related decline in immune function, is a complex biological process with profound implications for health and longevity. This phenomenon, characterized by alterations in both innate and adaptive immunity, increases susceptibility to infections, reduces vaccine efficacy, and contributes to the development of age-related diseases. At the cellular level, immunosenescence manifests as decreased production of naive T and B cells, accumulation of memory and senescent cells, thymic involution, and dysregulated cytokine production. Recent advances in molecular biology have shed light on the underlying mechanisms of immunosenescence, including telomere attrition, epigenetic alterations, mitochondrial dysfunction, and changes in key signaling pathways such as NF-κB and mTOR. These molecular changes lead to functional impairments in various immune cell types, altering their proliferative capacity, differentiation, and effector functions. Emerging research suggests that lifestyle factors may modulate the rate and extent of immunosenescence at both cellular and molecular levels. Physical activity, nutrition, stress management, and sleep patterns have been shown to influence immune cell function, inflammatory markers, and oxidative stress in older adults. This review provides a comprehensive analysis of the molecular and cellular mechanisms underlying immunosenescence and explores how lifestyle interventions may impact these processes. We will examine the current understanding of immunosenescence at the genomic, epigenomic, and proteomic levels, and discuss how various lifestyle factors can potentially mitigate or partially reverse aspects of immune aging. By integrating recent findings from immunology, gerontology, and molecular biology, we aim to elucidate the intricate interplay between lifestyle and immune aging at the molecular level, potentially informing future strategies for maintaining immune competence in aging populations. Full article
(This article belongs to the Special Issue Immunosenescence and Its Modification by Interventions)
17 pages, 1006 KiB  
Article
Genome-Wide Patterns of Homozygosity and Heterozygosity and Candidate Genes in Greek Insular and Mainland Native Goats
by Valentina Tsartsianidou, Antonis Otapasidis, Spiros Papakostas, Nikoleta Karaiskou, Sotiria Vouraki and Alexandros Triantafyllidis
Genes 2025, 16(1), 27; https://doi.org/10.3390/genes16010027 - 27 Dec 2024
Viewed by 171
Abstract
Background: Runs of homozygosity (ROHs) and heterozygosity (ROHets) serve for the identification of genomic regions as candidates of selection, local adaptation, and population history. Methods: The present study aimed to comprehensively explore the ROH and ROHet patterns and hotspots in Greek native dairy [...] Read more.
Background: Runs of homozygosity (ROHs) and heterozygosity (ROHets) serve for the identification of genomic regions as candidates of selection, local adaptation, and population history. Methods: The present study aimed to comprehensively explore the ROH and ROHet patterns and hotspots in Greek native dairy goats, Eghoria and Skopelos, genotyped with the Illumina Goat SNP50 BeadChip. SNP and functional enrichment analyses were conducted to further characterize hotspots and the candidate genes located within these genomic regions. Genetic relationships between and within breeds and inbreeding coefficients were also evaluated. Results: Clear genetic differentiation and diversified management practices were depicted between the two native populations. The ROH and ROHet average genome coverage for Skopelos (65.35 and 35 Mb) and Eghoria (47.64 and 43 Mb) indicated differences in mainland and insular goats, with Skopelos showing more long ROH fragments, reflecting its geographic isolation and small population size. An ROH hotspot (CHR12: 43.59–44.61 Mb) detected in the Skopelos population has been also reported across European goats and co-localizes with a selection signal detected in the Egyptian Barki goats and sheep adapted to hot–arid conditions. A novel ROH hotspot (CHR18: 60.12–61.81 Mb), shared among the Greek breeds, harbors candidate genes enriched in biosynthesis, metabolism, and immune response. Two well-conserved ROHet islands were detected in Greek goats on chromosomes 1 and 18, with genes participating in development and embryogenesis. The Eghoria population showed the highest number of ROHet islands, potentially reflecting its adaptability to diverse environments. Conclusions: These findings offer new insights into the environmental adaptation and artificial selection in Greek goats and could be utilized in future breeding strategies for sustainable goat farming. Full article
(This article belongs to the Special Issue Genetics and Genomics of Sheep and Goat)
12 pages, 1487 KiB  
Review
Expanding Upon Genomics in Rare Diseases: Epigenomic Insights
by Jia W. Tan, Emily J. Blake, Joseph D. Farris and Eric W. Klee
Int. J. Mol. Sci. 2025, 26(1), 135; https://doi.org/10.3390/ijms26010135 - 27 Dec 2024
Viewed by 201
Abstract
DNA methylation is an essential epigenetic modification that plays a crucial role in regulating gene expression and maintaining genomic stability. With the advancement in sequencing technology, methylation studies have provided valuable insights into the diagnosis of rare diseases through the various identification of [...] Read more.
DNA methylation is an essential epigenetic modification that plays a crucial role in regulating gene expression and maintaining genomic stability. With the advancement in sequencing technology, methylation studies have provided valuable insights into the diagnosis of rare diseases through the various identification of episignatures, epivariation, epioutliers, and allele-specific methylation. However, current methylation studies are not without limitations. This mini-review explores the current understanding of DNA methylation in rare diseases, highlighting the key mechanisms and diagnostic potential, and emphasizing the need for advanced methodologies and integrative approaches to enhance the understanding of disease progression and design more personable treatment for patients, given the nature of rare diseases. Full article
(This article belongs to the Special Issue Genomic Research of Rare Diseases)
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<p>Schematic of DNA methylation modulated gene transcription and associated episignatures and epivariations. (<b>A</b>) General representation of the association between DNA methylation state and gene transcription. Hypomethyaltion in promoter generally leads to transcription activation, where the establishment and maintenance of DNA methylation through DNMT family proteins leads to hypermethylation in the promoter, which represses transcription. The methylation state can be reversed in a process initiated by the TET family proteins. (<b>B</b>) General representation of disease-associated episignatures. Left most represents the reference methylation patterns, with methylated or unmethylated CpGs within a gene. Hypothetical syndromes are shown with red arrows to indicate DNA methylation patterns at specific genes that differ from the reference methylation patterns. (<b>C</b>) General representation of disease-associated epivariations. Aberrant DNA methylation can be either hyper- or hypo-methylation. Hypermethylation can be either germline or somatic, primary or secondary, and ultimately leads to the repression of haploinsufficient genes. Hypomethylation occurs globally (genome-wide) or locally, global hypomethylation leads to chromosomal instability, while local hypomethylation leads to the activation of disease-associated genes.</p>
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<p>Schematic representation of integrated N = 1 methylation studies for rare disease patients. Possible integrated approaches include SNP/haplotype-dependent Allele-Specific Methylation (ASM), aberrant DNA methylation, and DNA methylation outlier studies. The purpose of the integration is to capture the epigenetic landscape of the proband within a rare disease cohort, which could provide useful insight into rare disease pathology, leading to improved diagnosis and management.</p>
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20 pages, 2466 KiB  
Article
Silicon-Mitigated Effect on Zinc-Induced Stress Conditions: Epigenetic, Morphological, and Physiological Screening of Barley Plants
by Marzena Mazurek, Renata Tobiasz-Salach, Barbara Stadnik and Dagmara Migut
Int. J. Mol. Sci. 2025, 26(1), 104; https://doi.org/10.3390/ijms26010104 - 26 Dec 2024
Viewed by 189
Abstract
Plants are increasingly exposed to stress-induced factors, including heavy metals. Zinc, although it is a microelement, at high concentrations can be phytotoxic to plants by limiting their growth and development. The presented research confirmed the inhibition effect of Zn on morphological and physiological [...] Read more.
Plants are increasingly exposed to stress-induced factors, including heavy metals. Zinc, although it is a microelement, at high concentrations can be phytotoxic to plants by limiting their growth and development. The presented research confirmed the inhibition effect of Zn on morphological and physiological parameters in barley plants. However, the effect was Zn dose dependent (50 µM, 100 µM, and 200 µM), as well as part of the plants (above ground or roots). To mitigate the negative effects of Zn, plants were sprayed with 0.1% silicon. Silicon was proven to have a positive effect on mitigating the inhibitory effects of Zn-induced stress. In most cases, an increase in both morphological (length, elongation, fresh and dry weights, and weather content) and physiological (relative chlorophyll content and fluorescence) parameters was observed. This occurrence was dependent on the Zn dose. Epigenetic analyses confirmed differences in the DNA methylation level, both between plants subjected to stress at different strengths (50 µM, 100 µM, and 200 µM Zn) and between plants sprayed with Si or not. The differences indicate that silicon affects the epigenome of barley plants, thereby modifying the response of plants to stress factors. This modification may be the basis for plants to acquire resistance as “epigenetic memory”. Full article
(This article belongs to the Special Issue Plant Responses to Biotic and Abiotic Stresses)
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<p>Effects of the application of Zn and Si on the length (<b>A</b>) and growth (<b>B</b>) of the above-ground barley; data are expressed as mean ± SD values. * Different letters indicate significant differences between the variants of the experiment (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Effects of application of Zn and Si on the length (<b>A</b>) and growth (<b>B</b>) of the roots of barley; data are expressed as mean ± SD values. * Different letters indicate significant differences between the variants of the experiment (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Effects of the application of Zn and Si on the fresh (<b>A</b>) and dry (<b>B</b>) weights, and the water content (<b>C</b>) of the barley’s above-ground parts; data are expressed as mean ± SD values. * Different letters indicate significant differences between the variants of the experiment (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Effects of the application of Zn and Si on the fresh weight (<b>A</b>) and dry weight (<b>B</b>) and water content (<b>C</b>) of barley roots; data are expressed as mean ± SD values. * Different letters indicate significant differences between the variants of the experiment (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Effects of the application of Zn and Si on the relative chlorophyll content; data are expressed as mean ± SD values. * Different letters indicate significant differences between the variants of the experiment (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Effects of Zn and Si application on chlorophyll fluorescence parameters: maximum photochemical efficiency of PSII (F<sub>v</sub>/F<sub>m</sub>) (<b>A</b>), total number of active reaction centers for absorption (RC/ABS) (<b>B</b>), maximum quantum yield of primary photochemistry (F<sub>v</sub>/F<sub>0</sub>) (<b>C</b>), and performance index (PI) (<b>D</b>) in barley plants. Data are expressed as mean ± SD values. * Different letters indicate significant differences between the variants of the experiment (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Sample of 3 electropherograms photo-presented DNA products of selective amplification with the selected primers used. Red arrows indicate polymorphic bands (products of selective amplifications). H and M signatures indicate separate bands for combination restriction enzymes EcoRI × HpaII and EcoRI × MspI, respectively, used in the restriction step of MSAP techniques.</p>
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24 pages, 3714 KiB  
Article
Profiling Genome-Wide Methylation Patterns in Cattle Infected with Ostertagia ostertagi
by Clarissa Boschiero, Ethiopia Beshah, Xiaoping Zhu, Wenbin Tuo and George E. Liu
Int. J. Mol. Sci. 2025, 26(1), 89; https://doi.org/10.3390/ijms26010089 - 26 Dec 2024
Viewed by 242
Abstract
DNA methylation (DNAm) regulates gene expression and genomic imprinting. This study aimed to investigate the effect of gastrointestinal (GI) nematode infection on host DNAm. Helminth-free Holstein steers were either infected with Ostertagia ostertagi (the brown stomach worm) or given tap water only as [...] Read more.
DNA methylation (DNAm) regulates gene expression and genomic imprinting. This study aimed to investigate the effect of gastrointestinal (GI) nematode infection on host DNAm. Helminth-free Holstein steers were either infected with Ostertagia ostertagi (the brown stomach worm) or given tap water only as a control. Animals were euthanized 30 days post-infection, and tissues were collected at necropsy. We conducted epigenome-wide profiling using a mammalian methylation array to explore the impact of infection on methylation patterns in the mucosa from abomasal fundus (FUN), pylorus (PYL), draining lymph nodes (dLNs), and the duodenum (DUO). The analysis covered 31,107 cattle CpGs of 5082 genes and revealed infection-driven, tissue-specific, differential methylation patterns. A total of 389 shared and 2770 tissue-specific, differentially methylated positions (DMPs) were identified in dLN and FUN, particularly in genes associated with immune responses. The shared DMPs were found in 263 genes, many of which are involved in immune responses. Furthermore, 282, 244, 52, and 24 differentially methylated regions (DMRs) were observed in dLN, FUN, PYL, and DUO, respectively. More hypomethylated DMRs were detected in dLN and FUN, while more hypermethylated DMRs were found in PYL and DUO. Genes carrying DMPs and DMRs and enriched pathways relating to immune functions/responses were detected in infected animals, indicating a link between DNA methylation and the infection. The data may implicate a crucial role of DNAm in regulating the nature/strength of host immunity to infection and contribute to a deeper understanding of the epigenetic regulatory landscape in cattle infected by GI nematodes. Full article
(This article belongs to the Special Issue Molecular Genetics and Genomics of Ruminants)
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<p>Overview of the cattle CpGs probes mapped to the cattle genome. (<b>A</b>) Number of cattle probes from the mammalian methylation array, along with respective genome annotation. (<b>B</b>) PCA of the 37 samples analyzed in this study based on the β-values. (<b>C</b>) The β-value distribution of 37 individual samples from infected and uninfected groups. (<b>D</b>) The M-value distribution of 37 samples from infected and uninfected animals, where infected samples are depicted in green, and uninfected samples are shown in orange.</p>
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<p>Overview of the dLN DMPs showing the counts of hypomethylated (yellow) and hypermethylated (purple) DMPs. (<b>A</b>) Number of hypomethylated and hypermethylated DMPs (FDR &lt; 0.05 and |Δβ| &gt; 5%). (<b>B</b>) DMP annotation (−10 kb to +1 kb from the nearest TSS) for both hypomethylated and hypermethylated DMPs. (<b>C</b>) Volcano plots of the DMPs, where black dots represent the DMPs that are not significantly differentially methylated, while the yellow or purple dots indicate the DMPs that are significantly hypermethylated or hypomethylated (FDR &lt; 0.05 and |Δβ| ≥ 5%). The red line represents FDR &lt; 0.05. (<b>D</b>) Circular plots of the genome distribution of the hypomethylated and hypermethylated DMPs. (<b>E</b>) Heatmaps of the hypomethylated and hypermethylated DMPs for each animal in either the control or the infected group. The legend indicates the beta coefficient values.</p>
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<p>Overview of the FUN DMPs showing the counts of hypomethylated (yellow) and hypermethylated (purple) DMPs. (<b>A</b>) Number of hypomethylated and hypermethylated DMPs (FDR &lt; 0.05 and |Δβ| &gt; 5%). (<b>B</b>) DMP annotation (−10 kb to +1 kb from the nearest TSS) for both the hypomethylated and hypermethylated DMPs. (<b>C</b>) Volcano plots of the DMPs where black dots represent the DMPs that are not significantly differentially methylated, while the yellow or purple dots indicate the DMPs that are significantly hypermethylated or hypomethylated (FDR &lt; 0.05 and |Δβ| ≥ 5%). The red line represents FDR &lt; 0.05. (<b>D</b>) Circular plots of the genome distribution of the hypomethylated and hypermethylated DMPs. (<b>E</b>) Heatmaps of the hypomethylated and hypermethylated DMPs for each animal in either a control or an infected group. The legend indicates the beta coefficient values.</p>
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<p>Overview of the fundic DMRs showing the hypomethylated (yellow) and hypermethylated (purple) regions. (<b>A</b>) Number of hypomethylated and hypermethylated DMRs (<span class="html-italic">p</span>-value ≤ 0.001 and |Δβ| ≤ 10%) identified across four cattle tissues. (<b>B</b>) DMR annotation (−10 kb to +1 kb from the nearest TSS) showing the hypomethylated and hypermethylated DMRs in each tissue (LN: lymph nodes; FUN: fundic; PYL: pyloric; DUO: duodenum). (<b>C</b>) Circular genome distribution plots of the hypomethylated and hypermethylated DMRs in each tissue.</p>
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<p>STRING network analysis of DMR genes from (<b>A</b>) dLN, (<b>B</b>) FUN, and (<b>C</b>) PYL tissues. Each node represents a gene, and the lines represent predicted interactions (with a minimum confidence score of 0.7). The line thickness indicates the strength of the supporting data for the predicted interactions.</p>
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<p>STRING network analysis of DMR and DPMG genes from (<b>A</b>) dLN, (<b>B</b>) FUN, and (<b>C</b>) PYL tissues. Each node represents a gene, and the lines represent predicted interactions (with a minimum confidence score of 0.7). The line thickness indicates the strength of the supporting data for the predicted interactions.</p>
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18 pages, 688 KiB  
Review
Biological Aging and Venous Thromboembolism: A Review of Telomeres and Beyond
by Rafaela Vostatek and Cihan Ay
Biomedicines 2025, 13(1), 15; https://doi.org/10.3390/biomedicines13010015 - 25 Dec 2024
Viewed by 358
Abstract
Although venous thromboembolism (VTE) is the third most common cardiovascular disease, and the risk of VTE increases sharply with advancing age, approximately 40% of VTE cases are currently classified as unprovoked, highlighting the importance of risk factor research. While chronological aging is associated [...] Read more.
Although venous thromboembolism (VTE) is the third most common cardiovascular disease, and the risk of VTE increases sharply with advancing age, approximately 40% of VTE cases are currently classified as unprovoked, highlighting the importance of risk factor research. While chronological aging is associated with the risk of VTE, the association with biological aging remains unclear. Biological aging is highly complex, influenced by several dysregulated cellular and biochemical mechanisms. In the last decade, advancements in omics methodologies provided insights into the molecular complexity of biological aging. Techniques such as high-throughput genomics, epigenomics, transcriptomics, proteomics, and metabolomics analyses identified and quantified numerous epigenetic markers, transcripts, proteins, and metabolites. These methods have also revealed the molecular alterations organisms undergo as they age. Despite the progress, there is still a lack of consensus regarding the methods for assessing and validating these biomarkers, and their application lacks standardization. This review gives an overview of biomarkers of biological aging, including telomere length, and their potential role for VTE. Furthermore, we critically examine the advantages and disadvantages of the proposed methods and discuss possible future directions for investigating biological aging in VTE. Full article
(This article belongs to the Special Issue The Role of Telomere and Telomerase in Human Disease)
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<p>Biological aging biomarkers can be grouped into three categories: physiological, molecular, and digital biomarkers. Molecular biomarkers include genomics, epigenomics, transcriptomics, proteomics, and metabolomics studies. Figure was created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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40 pages, 5235 KiB  
Review
Unlocking the Heterogeneity in Acute Leukaemia: Dissection of Clonal Architecture and Metabolic Properties for Clinical Interventions
by Martina Maria Capelletti, Orsola Montini, Emilio Ruini, Sarah Tettamanti, Angela Maria Savino and Jolanda Sarno
Int. J. Mol. Sci. 2025, 26(1), 45; https://doi.org/10.3390/ijms26010045 - 24 Dec 2024
Viewed by 344
Abstract
Genetic studies of haematological cancers have pointed out the heterogeneity of leukaemia in its different subpopulations, with distinct mutations and characteristics, impacting the treatment response. Next-generation sequencing (NGS) and genome-wide analyses, as well as single-cell technologies, have offered unprecedented insights into the clonal [...] Read more.
Genetic studies of haematological cancers have pointed out the heterogeneity of leukaemia in its different subpopulations, with distinct mutations and characteristics, impacting the treatment response. Next-generation sequencing (NGS) and genome-wide analyses, as well as single-cell technologies, have offered unprecedented insights into the clonal heterogeneity within the same tumour. A key component of this heterogeneity that remains unexplored is the intracellular metabolome, a dynamic network that determines cell functions, signalling, epigenome regulation, immunity and inflammation. Understanding the metabolic diversities among cancer cells and their surrounding environments is therefore essential in unravelling the complexities of leukaemia and improving therapeutic strategies. Here, we describe the currently available methodologies and approaches to addressing the dynamic heterogeneity of leukaemia progression. In the second section, we focus on metabolic leukaemic vulnerabilities in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL). Lastly, we provide a comprehensive overview of the most interesting clinical trials designed to target these metabolic dependencies, highlighting their potential to advance therapeutic strategies in leukaemia treatment. The integration of multi-omics data for cancer identification with the metabolic states of tumour cells will enable a comprehensive “micro-to-macro” approach for the refinement of clinical practices and delivery of personalised therapies. Full article
(This article belongs to the Special Issue Acute Leukemia: From Basic Research to Clinical Application)
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<p>Amino acid pathways dysregulated in acute leukaemia and potentially addressable with targeted molecules. 5,10-Methylenetetrahydrofolate (5,10-mTHF); Alpha-Ketoglutarate (α-KG); Arginine (Arg); Asparagine (Asn); Asparagine-Synthase (ASNS); Aspartic Acid (Asp); Branched-Chain Amino Acids (BCAAS), Mitochondrial BCAA-Transaminases (BCATs); Cysteine (Cys); Glutamine (Gln); Glutaminase (GLS); Glutamate (Glu); Glutamate Dehydrogenase (GLUD); Glycine (Gly); Glutathione Synthase (GS); Indoleamine 2,3 Dioxygenase (IDO); Leucine (Leu); Isoleucine (IsoLeu); Kynurenine (KYN); Methionine-Adenosyl-Transferase (MAT); Methionine (Met); Methionine Synthase (MS); Ornithine-Decarboxylase (ODC); Phosphoglycerate Dehydrogenase (PHGDH); Phosphoserine Aminotransferase (PSAT); S-Adenosyl-Homocysteine (SAH); S-Adenosyl-Methionine (SAM); Serine Hydroxymethyltransferase (SHMT); Tricarboxylic Acid (TCA); Tryptophan-2,3-Dioxygenase (TDO); Tetrahydrofolate (THF); Tryptophan (Trp); Valine (Val). Created in BioRender. Tettamanti, S. (2025) <a href="https://BioRender.com/d64v911" target="_blank">https://BioRender.com/d64v911</a> (accessed on 18 December 2024).</p>
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<p>Action sites of clinically targeted molecules. Panel (<b>A</b>) shows targets in acute myeloid leukaemia (AML) and panel (<b>B</b>) in acute lymphoblastic leukaemia (ALL). 2-Deoxy glucose (2-DG); electron transport chain (ETC); glucose transporter 1 (GLUT1); isocitrate dehydrogenase (IDH); outer mitochondrial membrane (OMM); tricarboxylic acid cycle (TCA); Tet methyl cytosine dioxygenase 2 (TET2). Created in BioRender. Tettamanti, S. (2025) <a href="https://BioRender.com/l59b367" target="_blank">https://BioRender.com/l59b367</a> (accessed on 18 December 2024).</p>
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<p>Impact of nutritional, behavioural and physical approaches on gut microbiota diversity, mediating immune responses and improving the metabolic response to anti-leukaemic treatment. Created in BioRender. Tettamanti, S. (2025) <a href="https://BioRender.com/p91b288" target="_blank">https://BioRender.com/p91b288</a> (accessed on 18 December 2024).</p>
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30 pages, 7117 KiB  
Review
Epigenetic Mechanisms of Endocrine-Disrupting Chemicals in Breast Cancer and Their Impact on Dietary Intake
by Desh Deepak Singh
J. Xenobiot. 2025, 15(1), 1; https://doi.org/10.3390/jox15010001 - 24 Dec 2024
Viewed by 208
Abstract
Addressing the consequences of exposure to endocrine-disrupting chemicals (EDCs) demands thorough research and elucidation of the mechanism by which EDCs negatively impact women and lead to breast cancer (BC). Endocrine disruptors can affect major pathways through various means, including histone modifications, the erroneous [...] Read more.
Addressing the consequences of exposure to endocrine-disrupting chemicals (EDCs) demands thorough research and elucidation of the mechanism by which EDCs negatively impact women and lead to breast cancer (BC). Endocrine disruptors can affect major pathways through various means, including histone modifications, the erroneous expression of microRNA (miRNA), DNA methylation, and epigenetic modifications. However, it is still uncertain if the epigenetic modifications triggered by EDCs can help predict negative outcomes. Consequently, it is important to understand how different endocrine disrupters or signals interact with epigenetic modifications and regulate signalling mechanisms. This study proposes that the epigenome may be negatively impacted by several EDCs, such as cadmium, arsenic, lead, bisphenol A, phthalates, polychlorinated biphenyls and parabens, organochlorine, and dioxins. Further, this study also examines the impact of EDCs on lifestyle variables. In breast cancer research, it is essential to consider the potential impacts of EDC exposure and comprehend how EDCs function in tissues. Full article
(This article belongs to the Special Issue The Role of Endocrine-Disrupting Chemicals in the Human Health)
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<p>The effects of endocrine-disrupting chemicals (EDCs) and the mechanism(s) by which epigenetic modification, including DNA methylation, expression of aberrant microRNA (miRNA), and histone modification, is one mechanism assumed to be a primary pathway leading to the untoward effects of endocrine disruptors (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 28 July 2024).</p>
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<p>Endocrine disruptors and risk factors mediate epigenome modifications that increase the risk of breast cancer. EDC may prolong puberty and increase mammary epithelial cell proliferation, allowing for a longer duration or faster rate of epigenetic remodelling of the developing mammary gland, resulting in chromatin destabilisation, mispackaging of genes in active/inactive domains, and aberrant expression of genes in key regulatory pathways. Mutations in HMTs (histone methyltransferases), HDMs (histone methyltransferases), and H3.3 (Histone variant H3.3) increase Histone deacetylase 1 (HDAC1) but reduce HATs (histone acetyltransferases) (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 28 July 2024).</p>
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<p>Epigenetic control is crucial in mitigating the toxic effects of cadmium (Cd<sup>2+</sup>), a heavy metal that causes serious health and environmental problems. Cadmium can alter cellular homeostasis and cause cancer, often through non-genetic mechanisms such as DNA methylation, histone changes, and microRNA (miRNA) control. The disrupting effects of cadmium on MAPK pathways on cellular signalling and health. Figure highlights the direct and indirect effects of Cd<sup>2+</sup> interference on cellular function, which lead to aberrant cell responses and elevated breast cancer. These disruptions can result in altered gene expression and impaired cell proliferation, ultimately contributing to tumourigenesis (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 8 August 2024).</p>
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<p>Growth factor receptors activated by arsenic stimulate the PI3K/AKT pathway, which promotes angiogenesis, cell cycle progression, and cellular proliferation. Through the TRAIL receptor and reactive oxygen species, arsenic triggered apoptosis by upregulating pro-apoptotic markers and down-regulating anti-apoptotic signs. These mechanisms illustrate how arsenic can exert both pro-survival and pro-death signals within cells, leading to complex interplay in tumour standing these pathways is crucial for developing targeted therapies that could mitigate the adverse effects of arsenic exposure while potentially harnessing its apoptotic capabilities against cancer cell biology. Understanding these pathways is crucial for developing targeted therapies that could mitigate the adverse effects of arsenic exposure while potentially harnessing its apoptotic capabilities against cancer cells (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 9 August 2024).</p>
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<p>Lead inhibits delta-aminolevulinic acid dehydratase (ALAD) and enhances the δ-aminolevulinic acid substrate, which is known to increase ROS production and oxidative stress within cells. Epigenetic alterations can modify gene expression without changing the underlying DNA sequence, making them an important role in breast cancer growth and progression (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 10 August 2024).</p>
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<p>Potential pathways underlying BPA-induced breast cancer formation and progression. Bisphenol A (BPA), oestrogen receptor alpha (ERA), G-protein-coupled receptor 30 (GPR30), ten-eleven translocation 2 (TET2), Snail family zinc finger protein (SNAIL), and extracellular signal-regulated kinase 1/2 (ERK1/2). These elements interact in intricate ways to alter biological pathways, eventually leading to cancer linked with BPA exposure. Understanding these pathways is critical for developing tailored treatments and prevention methods for BPA-induced breast cancer (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 12 August 2024).</p>
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<p>All the way through the Plyc, Mekk, IRAK, and PLC-β signalling pathways, phthalates altered the gene expression in breast cancer. These changes in gene expression could potentially influence tumour growth and metastasis, highlighting the need for further research into the mechanisms by which phthalates affect cellular processes. Understanding these pathways may lead to new therapeutic strategies for breast cancer treatment (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 13 August 2024).</p>
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<p>PCB activates relevant upstream signalling cascades, including p38, extracellular regulated protein kinases (ERK), and mitogen-activated protein kinase (MAPK). This includes phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)/Akt. Reactive oxygen species (ROS) were produced following a PCB challenge and antioxidant therapy, which significantly reduced the activation of these axis signalling pathways by PCBs and caused breast cancer metastasis and progression. This interaction underscores the potential for targeted therapies that could disrupt these pathways, offering new avenues for treatment in patients affected by PCB-related breast cancer (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 14 August 2024).</p>
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<p>Epigenetic changes can influence the expression of genes involved in paraben metabolism, detoxification, and response. Parabens, including methyl paraben and propylparaben, are weak estrogen mimics that attach to estrogen receptors. Aberrant hypermethylation of CpG islands in promoter regions can mute genes that metabolise or detoxify paraben, including UDP-glucuronosyl transferees (UGTs) and sulfotransferases. Their estrogenic action may impact breast cancer cell proliferation, especially in ER-positive tumours. Parabens may affect the expression of microRNA (miR-155, miR-21), which regulate genes involved in cell cycle control, apoptosis, and estrogen response (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 16 August 2024).</p>
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<p>Epigenetic inactivation of organochlorine-responsive pathways in breast cancer entails suppressing cellular activity and imitating or interfering with estrogen signalling, which is crucial in hormone receptor-positive breast cancers. Aberrant methylation of gene promoters can silence detoxifying enzymes such as CYP1A1 and glutathione S-transferases (GSTs), which metabolise OCs. Epigenetically silencing genes that encode hormone receptors, such as ESR1 for ERα, can influence tumour responsiveness to estrogen (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 16 August 2024).</p>
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<p>The AhR is a ligand-activated transcription factor that regulates gene expression by translocating to the nucleus after binding to dioxins or similar ligands. Aberrant methylation of CpG islands in promoter regions has the potential to silence critical AhR pathway genes such as CYP1A1 and CYP1B1, which are involved in the detoxification of hazardous drugs. Loss of AhR function may disrupt cell proliferation and apoptosis, contributing to carcinogenesis in breast cancer (the figure was designed using BioRender graphics: <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 19 August 2024).</p>
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21 pages, 742 KiB  
Review
Defining the Differential Corticosteroid Response Basis from Multiple Omics Approaches
by Melody Ramirez-Falcon, Eva Suarez-Pajes and Carlos Flores
Int. J. Mol. Sci. 2024, 25(24), 13611; https://doi.org/10.3390/ijms252413611 - 19 Dec 2024
Viewed by 274
Abstract
Since their discovery, corticosteroids have been widely used in the treatment of several diseases, including asthma, acute lymphoblastic leukemia, chronic obstructive pulmonary disease, and many other conditions. However, it has been noted that some patients develop undesired side effects or even fail to [...] Read more.
Since their discovery, corticosteroids have been widely used in the treatment of several diseases, including asthma, acute lymphoblastic leukemia, chronic obstructive pulmonary disease, and many other conditions. However, it has been noted that some patients develop undesired side effects or even fail to respond to treatment. The reasons behind this have not yet been fully elucidated. This poses a significant challenge to effective treatment that needs to be addressed urgently. Recent genomic, transcriptomic, and other omics-based approximations have begun to shed light into the genetic factors influencing interindividual variability in corticosteroid efficacy and its side effects. Here, we comprehensively revise the recent literature on corticosteroid response in various critical and chronic diseases, with a focus on omics approaches, and highlight existing knowledge gaps where further investigation is urgently needed. Full article
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<p>Schematic diagram of the genomic and non-genomic mediated glucocorticoid effects. GR: glucocorticoid receptor; GRE: glucocorticoid response element; and TF: transcription factor.</p>
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19 pages, 329 KiB  
Review
Decoding Kidney Pathophysiology: Omics-Driven Approaches in Precision Medicine
by Charlotte Delrue and Marijn M. Speeckaert
J. Pers. Med. 2024, 14(12), 1157; https://doi.org/10.3390/jpm14121157 - 19 Dec 2024
Viewed by 489
Abstract
Chronic kidney disease (CKD) is a major worldwide health concern because of its progressive nature and complex biology. Traditional diagnostic and therapeutic approaches usually fail to account for disease heterogeneity, resulting in low efficacy. Precision medicine offers a novel approach to studying kidney [...] Read more.
Chronic kidney disease (CKD) is a major worldwide health concern because of its progressive nature and complex biology. Traditional diagnostic and therapeutic approaches usually fail to account for disease heterogeneity, resulting in low efficacy. Precision medicine offers a novel approach to studying kidney disease by combining omics technologies such as genomics, transcriptomics, proteomics, metabolomics, and epigenomics. By identifying discrete disease subtypes, molecular biomarkers, and therapeutic targets, these technologies pave the way for personalized treatment approaches. Multi-omics integration has enhanced our understanding of CKD by revealing intricate molecular linkages and pathways that contribute to treatment resistance and disease progression. While pharmacogenomics offers insights into expected responses to personalized treatments, single-cell and spatial transcriptomics can be utilized to investigate biological heterogeneity. Despite significant development, challenges persist, including data integration concerns, high costs, and ethical quandaries. Standardized data protocols, collaborative data-sharing frameworks, and advanced computational tools such as machine learning and causal inference models are required to address these challenges. With the advancement of omics technology, nephrology may benefit from improved diagnostic accuracy, risk assessment, and personalized care. By overcoming these barriers, precision medicine has the potential to develop novel techniques for improving patient outcomes in kidney disease treatment. Full article
10 pages, 1067 KiB  
Article
Evaluation of Circulating MicroRNAs in Schizophrenia: From Epigenomic Dysregulation to Potential Biomarkers
by André Luiz de Souza Rodrigues, Carla de Castro Sant’Anna, Diego Di Felipe Ávila Alcantara, Amanda Cohen-Paes, Margareth Maria Braun Guimarães Imbiriba and Rommel Mario Rodriguez Burbano
Psychiatry Int. 2024, 5(4), 1026-1035; https://doi.org/10.3390/psychiatryint5040070 - 18 Dec 2024
Viewed by 311
Abstract
To evaluate the expression profile of circulating miRNAs in patients with schizophrenia (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572, and miR-652) in relation to individual negative controls for the disease. This was an analytical, case-controlled, cross-sectional study, using samples previously collected from patients diagnosed [...] Read more.
To evaluate the expression profile of circulating miRNAs in patients with schizophrenia (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572, and miR-652) in relation to individual negative controls for the disease. This was an analytical, case-controlled, cross-sectional study, using samples previously collected from patients diagnosed with schizophrenia (N = 650) and a control group (N = 924). Samples were analyzed after RNA extraction and quantification. After making a general comparison between the case and control groups, regardless of gender and other variables, all seven miRNAs showed statistically significant differences (p-value < 0.05). This also occurred in the variables gender, smoking, and alcoholism. Thus, the results indicated that depending on the clinical characteristics in the face of suspected schizophrenia, the miRNAs explored here seem to work as possible biomarkers, as they demonstrated, at various times, important differences between the studied groups. Full article
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<p>General graph of the case group and control group in relation to the “<span class="html-italic">p</span>-value” and miRNA. Confrontation of data from case and control groups. Statistical analysis performed by IBM SPSS22 software and graph by OriginPro 9.1 software. Data parameters were checked for normality using the Kolmogorov–Smirnov normality test and the method of statistical analysis for miRNAs was performed using Student’s <span class="html-italic">t</span>-test with two samples at different variances, with Welch correction. Statistical differences shown are between case and control groups, with <span class="html-italic">p</span>-value &lt; 0.05 for all miRNAs.</p>
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<p>Graph of the case group and control group of male and female individuals, respectively, in relation to miRNA. Data parameters were checked for normality using the Kolmogorov–Smirnov normality test and the method of statistical analysis for miRNAs was performed using Student’s <span class="html-italic">t</span>-test with two samples at different variances, with Welch correction. Statistical differences shown are between case and control groups, with <span class="html-italic">p</span>-value &lt; 0.05 for all miRNAs.</p>
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<p>Graph of individuals in the case group regarding family history of schizophrenia in relation to “log(<span class="html-italic">p</span>-value)” and miRNA confrontation of individuals in the case group regarding family history of schizophrenia. Statistical analysis performed by IBM SPSS22 software and graph by OriginPro 9.1 software. Data parameters were checked for normality using the Kolmogorov–Smirnov normality test and the method of statistical analysis for miRNAs was performed using Student’s <span class="html-italic">t</span>-test with two samples at different variances, with Welch correction. Statistical differences shown are between individuals in the case group, with <span class="html-italic">p</span>-value &lt; 0.05 for miRNAs 449a, 564, 432-5p, 548d, and 572.</p>
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14 pages, 1197 KiB  
Review
Maternal Gut Microbiome-Mediated Epigenetic Modifications in Cognitive Development and Impairments: A New Frontier for Therapeutic Innovation
by Shabnam Nohesara, Hamid Mostafavi Abdolmaleky, Faith Dickerson, Adrián A. Pinto-Tomás, Dilip V. Jeste and Sam Thiagalingam
Nutrients 2024, 16(24), 4355; https://doi.org/10.3390/nu16244355 - 17 Dec 2024
Viewed by 465
Abstract
Cognitive impairment in various mental illnesses, particularly neuropsychiatric disorders, has adverse functional and clinical consequences. While genetic mutations and epigenetic dysregulations of several genes during embryonic and adult periods are linked to cognitive impairment in mental disorders, the composition and diversity of resident [...] Read more.
Cognitive impairment in various mental illnesses, particularly neuropsychiatric disorders, has adverse functional and clinical consequences. While genetic mutations and epigenetic dysregulations of several genes during embryonic and adult periods are linked to cognitive impairment in mental disorders, the composition and diversity of resident bacteria in the gastrointestinal tract—shaped by environmental factors—also influence the brain epigenome, affecting behavior and cognitive functions. Accordingly, many recent studies have provided evidence that human gut microbiota may offer a potential avenue for improving cognitive deficits. In this review, we provide an overview of the relationship between cognitive impairment, alterations in the gut microbiome, and epigenetic alterations during embryonic and adult periods. We examine how various factors beyond genetics—such as lifestyle, age, and maternal diet—impact the composition, diversity, and epigenetic functionality of the gut microbiome, consequently influencing cognitive performance. Additionally, we explore the potential of maternal gut microbiome signatures and epigenetic biomarkers for predicting cognitive impairment risk in older adults. This article also explores the potential roles of nutritional deficiencies in programming cognitive disorders during the perinatal period in offspring, as well as the promise of gut microbiome-targeted therapeutics with epigenetic effects to prevent or alleviate cognitive dysfunctions in infants, middle-aged adults, and older adults. Unsolved challenges of gut microbiome-targeted therapeutics in mitigating cognitive dysfunctions for translation into clinical practice are discussed, lastly. Full article
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<p>Association between various factors (nutritional interventions, age, antibiotics, and environmental factors such as chemicals), changes in the composition of the gut microbiome, and cognitive performance.</p>
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<p>Gut microbiome-targeted therapeutics for improving cognitive impairments.</p>
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17 pages, 2053 KiB  
Data Descriptor
Genome-Scale DNA Methylome and Transcriptome Profiles of Prostate Cancer Recurrence After Prostatectomy
by Jim Smith, Priyadarshana Ajithkumar, Emma J. Wilkinson, Atreyi Dutta, Sai Shyam Vasantharajan, Angela Yee, Gregory Gimenez, Rathan M. Subramaniam, Michael Lau, Amir D. Zarrabi, Euan J. Rodger and Aniruddha Chatterjee
Data 2024, 9(12), 150; https://doi.org/10.3390/data9120150 - 16 Dec 2024
Viewed by 559
Abstract
Prostate cancer (PCa) is a major health burden worldwide, and despite early treatment, many patients present with biochemical recurrence (BCR) post-treatment, reflected by a rise in prostate-specific antigen (PSA) over a clinical threshold. Novel transcriptomic and epigenomic biomarkers can provide a powerful tools [...] Read more.
Prostate cancer (PCa) is a major health burden worldwide, and despite early treatment, many patients present with biochemical recurrence (BCR) post-treatment, reflected by a rise in prostate-specific antigen (PSA) over a clinical threshold. Novel transcriptomic and epigenomic biomarkers can provide a powerful tools for the clinical management of PCa. Here, we provide matched RNA sequencing and array-based genome-wide DNA methylome data of PCa patients (n = 17) with or without evidence of BCR following radical prostatectomy. Formalin-fixed paraffin-embedded (FFPE) tissues were used to generate these data, which included technical replicates to provide further validity of the data. We describe the sample features, experimental design, methods and bioinformatic pipelines for processing these multi-omic data. Importantly, comprehensive clinical, histopathological, and follow-up data for each patient were provided to enable the correlation of transcriptome and methylome features with clinical features. Our data will contribute towards the efforts of developing epigenomic and transcriptomic markers for BCR and also facilitate a deeper understanding of the molecular basis of PCa recurrence. Full article
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<p>Schematic representation of the experiment workflow. The figure describes an overview of the patient recruitment (the status of biochemical recurrence of the patients was retrieved later for grouping the patients), analysis strategy and platforms used to generate the data described in this work. Created using BioRender.com. <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a> (accessed on 8 August 2024).</p>
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<p>Quality assessment of the MethylationEPIC v2.0 and RNA-Seq data. (<b>A</b>) A bar plot illustrating the mean detection <span class="html-italic">p</span>-values for the 11 high-quality methylation array samples. Sample IDs are displayed on the Y-axis, and the mean detection <span class="html-italic">p</span>-value of each sample is depicted on the X-axis. (<b>B</b>) Beta value distribution plot showing methylation distribution on a global scale across the 11 high-quality samples. (<b>C</b>) Mean quality scores for RNA-Seq samples after trimming (plotted with Phred scores on the Y-axis vs. read position on the X-axis). The Y-axis is colour-coded into three sections, with green indicating high-quality base calls, yellow for moderate, and red for poor-quality calls. (<b>D</b>) Sequence length distribution plot for RNA samples following trimming, showing the length of sequences in base pairs on the X-axis and the corresponding read counts on the Y-axis.</p>
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<p>Gene biotype analysis from RNA-Seq data of PCa FFPE samples. Data showing the distribution of the percentage of genes mapped to protein-coding and non-coding regions of the genome. The protein-coding genes include those that code for immunoglobulins (IG gene) and T-cell receptors (TR gene). The protein non-coding genes encompass pseudogenes, long non-coding RNA (lncRNA), processed transcripts, and other non-coding RNA (ncRNA). The ‘other ncRNAs’ category encompassed consisting of microRNA (miRNA), small nucleolar RNA (snoRNA), miscellaneous RNA (misc_RNA), ribosomal RNA (rRNA), small nuclear RNA (snRNA), mitochondrial rRNA (mt_rRNA) and mitochondrial transfer RNA (mt_tRNA).</p>
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<p>Analysis of technical reproducibility and features of EPIC v2.0 Array and RNA-Seq platforms for FFPE tissues in prostate cancer. (<b>A</b>) <span class="html-italic">p</span>-value detection distribution for methylation analysis. (<b>B</b>) The beta values of each sample were assessed for normality using the Shapiro-Wilk test, and Spearman’s correlation was conducted to illustrate the technical reproducibility of DNA methylation levels. (<b>C</b>,<b>D</b>) Technical replicate plots for coding and non-coding RNA and correlation measurements.</p>
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10 pages, 1001 KiB  
Article
An Epigenetic Locus Associated with Loss of Smell in COVID-19
by Elif Sibel Aslan, Kenneth White, Gulsen Meral, Zeyneb Nur Akcay, Aytug Altundag, Savas Gur, Mehmet Dokur, Mehmet Akif Baktir and Lutfiye Karcioglu Batur
Diagnostics 2024, 14(24), 2823; https://doi.org/10.3390/diagnostics14242823 - 15 Dec 2024
Viewed by 526
Abstract
Background/Aim: Loss of smell, also known as anosmia, is a prevalent and often prolonged symptom following infection with SARS-CoV-2. While many patients regain olfactory function within weeks, a significant portion experience persistent anosmia lasting over a year post-infection. The underlying mechanisms responsible for [...] Read more.
Background/Aim: Loss of smell, also known as anosmia, is a prevalent and often prolonged symptom following infection with SARS-CoV-2. While many patients regain olfactory function within weeks, a significant portion experience persistent anosmia lasting over a year post-infection. The underlying mechanisms responsible for this sensory deficit remain largely uncharacterized. Previous studies, including genome-wide association studies (GWAS), have identified genetic variants near the UGT2A1 and UGT2A2 genes that are linked to anosmia in COVID-19 patients. However, the role of epigenetic changes in the development and persistence of smell loss has not been well explored. In this study, we aimed to investigate epigenetic alterations in the form of DNA methylation in the UGT1A1 gene, which is a locus associated with olfactory dysfunction in COVID-19 patients. Methods: We analysed DNA methylation patterns in blood samples from two carefully matched cohorts of 20 COVID-19 patients each, which are differentiated by their olfactory function—those with normal smell (normosmia) and those suffering from smell loss (anosmia). The cohorts were matched for age and sex to minimize potential confounding factors. Results: Using quantitative analysis, we found significantly lower levels of DNA methylation in the UGT1A1 locus in the anosmia group compared to the normosmia group, with a 14% decrease in median methylation values in patients with smell loss (p < 0.0001). These findings highlight potential epigenomic alterations in the UGT1A1 gene that may contribute to the pathogenesis of anosmia following COVID-19 infection. Our results suggest that the methylation status at this locus could serve as a biomarker for olfactory dysfunction in affected individuals. Conclusion: This study is among the first to describe epigenetic changes associated with smell loss in COVID-19, providing a foundation for future research into targeted interventions and potential therapeutic strategies aimed at reversing persistent anosmia. Further investigations involving larger cohorts and additional loci may help elucidate the complex interaction between genetic, epigenetic, and environmental factors influencing long-term sensory impairment post-COVID-19. Full article
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<p>Locus of UGT1A1 analysed. Primers are written in upper case. Methylation sites are shaded in grey. Positions of SNPs are shown in upper case, bold, and underlined. The SNP rs4663334 is located in the second methylation site shown.</p>
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<p>Methylation profiles of mononuclear blood cells in the UGT1A1 locus. The top scale shows the position of the locus in chromosome 2 and the positions of SNPs rs4663334 and rs545959455. The methylation landscape for two analyses of blood mononuclear cells across the locus of UGT1A1 are shown in the second and third scales.</p>
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<p>Comparison of methylation in the UGT1A1 locus. Median, quartiles, and ranges are shown. The mean methylation was 35.3% and 21.0% for the normosmic and anosmic groups, respectively (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Correlation analysis between methylation in the UGT1A1 locus and age.</p>
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35 pages, 570 KiB  
Review
Epigenetic Mechanisms in Aging: Extrinsic Factors and Gut Microbiome
by Alejandro Borrego-Ruiz and Juan J. Borrego
Genes 2024, 15(12), 1599; https://doi.org/10.3390/genes15121599 - 14 Dec 2024
Viewed by 983
Abstract
Background/Objectives: Aging is a natural physiological process involving biological and genetic pathways. Growing evidence suggests that alterations in the epigenome during aging result in transcriptional changes, which play a significant role in the onset of age-related diseases, including cancer, cardiovascular disease, diabetes, and [...] Read more.
Background/Objectives: Aging is a natural physiological process involving biological and genetic pathways. Growing evidence suggests that alterations in the epigenome during aging result in transcriptional changes, which play a significant role in the onset of age-related diseases, including cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. For this reason, the epigenetic alterations in aging and age-related diseases have been reviewed, and the major extrinsic factors influencing these epigenetic alterations have been identified. In addition, the role of the gut microbiome and its metabolites as epigenetic modifiers has been addressed. Results: Long-term exposure to extrinsic factors such as air pollution, diet, drug use, environmental chemicals, microbial infections, physical activity, radiation, and stress provoke epigenetic changes in the host through several endocrine and immune pathways, potentially accelerating the aging process. Diverse studies have reported that the gut microbiome plays a critical role in regulating brain cell functions through DNA methylation and histone modifications. The interaction between genes and the gut microbiome serves as a source of adaptive variation, contributing to phenotypic plasticity. However, the molecular mechanisms and signaling pathways driving this process are still not fully understood. Conclusions: Extrinsic factors are potential inducers of epigenetic alterations, which may have important implications for longevity. The gut microbiome serves as an epigenetic effector influencing host gene expression through histone and DNA modifications, while bidirectional interactions with the host and the underexplored roles of microbial metabolites and non-bacterial microorganisms such as fungi and viruses highlight the need for further research. Full article
(This article belongs to the Section Epigenomics)
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