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Charge fluctuations along stacked nucleobases in the DNA double helix play a key role in processes such as DNA repair and replication. While classical charge transfer mechanisms between adjacent bases due to energetic excitations are well established, quantum effects can also contribute significantly. Specifically, the overlap of -orbitals in well-stacked nucleobases can enable charge delocalization along the DNA double-strand. However, the cellular environment, including water, surrounding molecules, and thermal noise, is thought to induce rapid decoherence, limiting quantum-enhanced charge transport under physiological conditions. To explore charge mobility in such noisy environments, we model quantum diffusion in DNA-inspired two-dimensional tight-binding lattices, considering intrinsic and environmental fluctuations and revealing, via atomistic parametrization, a complex network of charge transport pathways. Our results show that long-range quantum phenomena depend on the carrier type (electrons or holes), base sequence, and noise/disorder characteristics. Notably, spatially correlated low-frequency fluctuations can sustain coherent charge transfer across several bases, whereas moderate vibrational noise can enhance rather than suppress quantum coherence by facilitating tunneling effects. These findings suggest that even under physiological conditions, the DNA structure can support non-classical charge dynamics, offering insights into its potential role in bioelectronic processes and inspiring future models of quantum transport in biological systems.

Significance Because obese people are at an increased risk of many age-related diseases, it is a plausible hypothesis that obesity increases the biological age of some tissues and cell types. However, it has been difficult to detect such an accelerated aging effect because it is unclear how to measure tissue age. Here we use a recently developed biomarker of aging (known as “epigenetic clock”) to study the relationship between epigenetic age and obesity in several human tissues. We report an unexpectedly strong correlation between high body mass index and the epigenetic age of liver tissue. This finding may explain why obese people suffer from the early onset of many age-related pathologies, including liver cancer. Because of the dearth of biomarkers of aging, it has been difficult to test the hypothesis that obesity increases tissue age. Here we use a novel epigenetic biomarker of aging (referred to as an “epigenetic clock”) to study the relationship between high body mass index (BMI) and the DNA methylation ages of human blood, liver, muscle, and adipose tissue. A significant correlation between BMI and epigenetic age acceleration could only be observed for liver ( r = 0.42, P = 6.8 × 10 ⁻⁴ in dataset 1 and r = 0.42, P = 1.2 × 10 ⁻⁴ in dataset 2). On average, epigenetic age increased by 3.3 y for each 10 BMI units. The detected age acceleration in liver is not associated with the Nonalcoholic Fatty Liver Disease Activity Score or any of its component traits after adjustment for BMI. The 279 genes that are underexpressed in older liver samples are highly enriched (1.2 × 10 ⁻⁹) with nuclear mitochondrial genes that play a role in oxidative phosphorylation and electron transport. The epigenetic age acceleration, which is not reversible in the short term after rapid weight loss induced by bariatric surgery, may play a role in liver-related comorbidities of obesity, such as insulin resistance and liver cancer.

The only potentially curative treatment for lung adenocarcinoma patients remains complete resection of early-stage tumors. However, many patients develop recurrence and die of their disease despite curative surgery. Underlying mechanisms leading to establishment of systemic disease after complete resection are mostly unknown. We therefore aimed at identifying molecular signatures of resected lung adenocarcinomas associated with the risk of an early relapse. The study comprised 89 patients with totally resected stage IA–IIIA lung adenocarcinomas. Patients suffering from an early relapse within two years after surgery were compared to patients without a relapse in two years. Patients were clinically and molecular pathologically characterized. Tumor tissues were immunohistochemically analyzed for the expression of Ki67, CD45, CD4, CD8, PD1, PD-L1, PD-L2 and CD34, by Nanostring nCounter PanCancer Immune Profiling Panel as well as a comprehensive methylome profiling using the Infinium MethylationEPIC BeadChip. We detected differential DNA methylation patterns as well as significantly differentially expressed genes associated with an early relapse after complete resection. Especially, CD1A was identified as a potential biomarker, whose reduced expression is associated with an early relapse. These findings might help to develop biomarkers improving risk assessment and patient selection for adjuvant therapy as well as establish novel targeted therapeutic strategies.

Head and neck squamous cell carcinoma (HNSCC) affects about 700.000 individuals per year worldwide with oral squamous cell carcinoma (OSCC) as a major subcategory. Despite a comprehensive treatment concept including surgery, radiation, and chemotherapy the 5-year survival rate is still only about 50 percent. Chronic inflammation is one of the hallmarks of carcinogenesis. Until now, little is known about the premalignant status of oral lichen planus (OLP) and molecular alterations in OLP are still poorly characterized. Our study aims to delineate differential DNA methylation patterns in OLP, OSCC, and normal oral mucosa. By applying a bead chip approach, we identified altered chromosomal patterns characteristic for OSCC while finding no recurrent alterations in OLP. In contrast, we identified numerous alterations in the DNA methylation pattern in OLP, as compared to normal controls, that were also present in OSCC. Our data support the hypothesis that OLP is a precursor lesion of OSCC sharing multiple epigenetic alterations with OSCC.

Targeting checkpoint inhibitors using monoclonal antibodies results in significantly better outcome of cancer patients compared to conventional chemotherapy. However, the current companion diagnostics to predict response is so far suboptimal, since they base on more or less reliable immunohistochemical approaches. In order to overcome these limitations, we analyzed epigenetic modifications of PDCD1 (PD1), CD274 (PD-L1), and CTLA4 in NSCLC tissues from 39 patients. Results were correlated with transcriptome data. Significant differences in the CpG-methylation patterns between tumor tissues and matched controls were observed for CTLA4 and PDCD1 (PD1) showing a decreased methylation of these genes compared to matched tumor-free tissues from the same patients. Results were confirmed by bisulfide sequencing in an independent validation cohort. Hypomethylation also resulted in increased expression of these genes as shown by transcriptome data. These epigenetic pathways as a hallmark of NSCLC might be useful to generate more precise diagnostic approaches in the future.

DNA methylation of the elongation of very long chain fatty acids protein 2 (ELOVL2) was suggested as a biomarker of biological aging, while childhood maltreatment (CM) has been associated with accelerated biological aging. We investigated the association of age and CM experiences with ELOVL2 methylation in peripheral blood mononuclear cells (PBMC). Furthermore, we investigated ELOVL2 methylation in the umbilical cord blood mononuclear cells (UBMC) of newborns of mothers with and without CM. PBMC and UBMC were isolated from 113 mother–newborn dyads and genomic DNA was extracted. Mothers with and without CM experiences were recruited directly postpartum. Mass array spectrometry and pyrosequencing were used for methylation analyses of ELOVL2 intron 1, and exon 1 and 5′ end, respectively. ELOVL2 5′ end and intron 1 methylation increased with higher age but were not associated with CM experiences. On the contrary, overall ELOVL2 exon 1 methylation increased with higher CM, but these changes were minimal and did not increase with age. Maternal CM experiences and neonatal methylation of ELOVL2 intron 1 or exon 1 were not significantly correlated. Our study suggests region-specific effects of chronological age and experienced CM on ELOVL2 methylation and shows that the epigenetic biomarker for age within the ELOVL2 gene does not show accelerated biological aging years after CM exposure.

Background The newly released 450k DNA methylation array from Illumina, Inc. offers the possibility to analyze more than 480,000 individual CpG sites in a user friendly standardized format. In this study the relationship between the β-values provided by the Illumina, Inc. array for each individual CpG dinucleotide and the quantitative methylation levels obtained by pyrosequencing were analyzed. In addition, the representation of microRNA genes and imprinted loci on the Illumina, Inc. array was assessed in detail. Genomic DNA from 4 human breast cancer cell lines (IPH-926, HCC1937, MDA-MB-134, PMC42) and 18 human breast cancer specimens as well as 4 normal mammary epithelial fractions was analyzed on 450k DNA methylation arrays. The β-values for 692 individual CpG sites from 62 different genes were cross-validated using conventional quantitative pyrosequencing. Findings The newly released 450k methylation array from Illumina, Inc. shows a high concordance with quantitative pyrosequencing if identical CpG sites are analyzed in cell lines (Spearman r = 0.88, p ≪ 0.0001), which is somewhat reduced in primary tumor specimens (Spearman r = 0.86, p ≪ 0.0001). 80.7% of the CpG sites show an absolute difference in methylation level of less than 15 percentage points. If different CpG sites in the same CpG islands are targeted the concordance is lower (r = 0.83 in cell lines and r = 0.7 in primary tumors). The number of CpG sites representing microRNA genes and imprinted loci is very heterogeneous (range: 1 – 70 CpG sites for microRNAs and 1 – 288 for imprinted loci). Conclusions The newly released 450k methylation array from Illumina, Inc. provides a genome-wide quantitative representation of DNA methylation aberrations in a convenient format. Overall, the congruence with pyrosequencing data is very good. However, for individual loci one should be careful to translate the β-values directly into percent methylation levels.

Inactivating mutations within the AR gene are present in only ~40% of individuals with clinically and hormonally diagnosed androgen insensitivity syndrome (AIS). Previous studies revealed the existence of an AR gene mutation-negative group of patients with AIS who have compromised androgen receptor (AR) function (AIS type II). To investigate whether AIS type II can be due to epigenetic repression of AR transcription. Quantification of AR mRNA and AR proximal promoter CpG methylation levels in genital skin-derived fibroblasts (GFs) derived from patients with AIS type II and control individuals. University hospital endocrine research laboratory. GFs from control individuals (n = 11) and patients with AIS type II (n = 14). Measurement of AR mRNA and AR promoter CpG methylation as well as activity of AR proximal promoter in vitro. Fifty-seven percent of individuals with AIS type II (n = 8) showed a reduced AR mRNA expression in their GFs. A significant inverse correlation was shown between AR mRNA abundance and methylation at two consecutive CpGs within the proximal AR promoter. Methylation of a 158-bp-long region containing these CpGs was sufficient to severely reduce reporter gene expression. This region was bound by the runt related transcription factor 1 (RUNX1). Ectopic expression of RUNX1 in HEK293T cells was able to inhibit reporter gene expression through this region. Aberrant CpGs methylation within the proximal AR promoter plays an important role in the control of AR gene expression and may result in AIS type II. We suggest that transcriptional modifiers, such as RUNX1, could play roles therein offering new perspectives for understanding androgen-mediated endocrine diseases.

Background Epigenetic mechanisms are informational cellular processes instructing normal and diseased phenotypes. They are associated with DNA but without altering the DNA sequence. Whereas chemical processes like DNA methylation or histone modifications are well-accepted epigenetic mechanisms, we herein propose the existence of an additional quantum physics layer of epigenetics. Results We base our hypothesis on theoretical and experimental studies showing quantum phenomena to be active in double-stranded DNA, even under ambient conditions. These phenomena include coherent charge transfer along overlapping pi-orbitals of DNA bases and chirality-induced spin selectivity. Charge transfer via quantum tunneling mediated by overlapping orbitals results in charge delocalization along several neighboring bases, which can even be extended by classical (non-quantum) electron hopping. Such charge transfer is interrupted by flipping base(s) out of the double-strand e.g., by DNA modifying enzymes. Charge delocalization can directly alter DNA recognition by proteins or indirectly by DNA structural changes e.g., kinking. Regarding sequence dependency, charge localization, shown to favor guanines, could influence or even direct epigenetic changes, e.g., modification of cytosines in CpG dinucleotides. Chirality-induced spin selectivity filters electrons for their spin along DNA and, thus, is not only an indicator for quantum coherence but can potentially affect DNA binding properties. Conclusions Quantum effects in DNA are prone to triggering and manipulation by external means. By the hypothesis put forward here, we would like to foster research on “Quantum Epigenetics” at the interface of medicine, biology, biochemistry, and physics to investigate the potential epigenetic impact of quantum physical principles on (human) life.

Background To date, most studies involving high-throughput analyses of sputum in asthma and COPD have focused on identifying transcriptomic signatures of disease. No whole-genome methylation analysis of sputum cells has been performed yet. In this context, the highly variable cellular composition of sputum has potential to confound the molecular analyses. Methods Whole-genome transcription (Agilent Human 4 × 44 k array) and methylation (Illumina 450 k BeadChip) analyses were performed on sputum samples of 9 asthmatics, 10 healthy and 10 COPD subjects. RNA integrity was checked by capillary electrophoresis and used to correct in silico for bias conferred by RNA degradation during biobank sample storage. Estimates of cell type-specific molecular profiles were derived via regression by quadratic programming based on sputum differential cell counts. All analyses were conducted using the open-source R/Bioconductor software framework. Results A linear regression step was found to perform well in removing RNA degradation-related bias among the main principal components of the gene expression data, increasing the number of genes detectable as differentially expressed in asthma and COPD sputa (compared to controls). We observed a strong influence of the cellular composition on the results of mixed-cell sputum analyses. Exemplarily, upregulated genes derived from mixed-cell data in asthma were dominated by genes predominantly expressed in eosinophils after deconvolution. The deconvolution, however, allowed to perform differential expression and methylation analyses on the level of individual cell types and, though we only analyzed a limited number of biological replicates, was found to provide good estimates compared to previously published data about gene expression in lung eosinophils in asthma. Analysis of the sputum methylome indicated presence of differential methylation in genomic regions of interest, e.g. mapping to a number of human leukocyte antigen (HLA) genes related to both major histocompatibility complex (MHC) class I and II molecules in asthma and COPD macrophages. Furthermore, we found the SMAD3 (SMAD family member 3) gene, among others, to lie within differentially methylated regions which has been previously reported in the context of asthma. Conclusions In this methodology-oriented study, we show that methylation profiling can be easily integrated into sputum analysis workflows and exhibits a strong potential to contribute to the profiling and understanding of pulmonary inflammation. Wherever RNA degradation is of concern, in silico correction can be effective in improving both sensitivity and specificity of downstream analyses. We suggest that deconvolution methods should be integrated in sputum omics analysis workflows whenever possible in order to facilitate the unbiased discovery and interpretation of molecular patterns of inflammation.