Hidradenitis suppurativa associated telomere-methylome dysregulations in blood.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic debilitating disease with a significant burden of both organic and psychological comorbidities. It has been shown that certain telomere-related genes (TRGs) affect a wide range of diseases, including HS and its associated comorbidities, but their exact role in HS pathogenesis is still unknown. OBJECTIVES: To determine whether TRG methylomes can be used as biomarkers in HS. METHODS: Using the Illumina HumanMethylation450 BeadChip array, we examined methylation variations associated with TRGs in HS cases and age-, sex- and ethnicity-matched healthy controls. The study utilized integrated bioinformatics statistical methods, such as a false discovery rate (FDR), the area under the receiver operating characteristic curve (AUC) and principal component analysis. RESULTS: There were a total of 585 different differentially methylated CpG sites identified in 585 TRGs associated with HS (474 hypomethylated and 111 hypermethylated) (FDR p-value < 0.05). A number of these CpGs have been identified as being involved in increased pain sensitivity including EPAS1, AHR, CSNK1D, DNMT1, IKBKAP, NOS3, PLCB1 and PRDM16 genes; GABRB3 as a potential alcohol addiction marker; DDB1, NSMCE2 and HNRNPA2B1 associated with cancers. Pathway analysis identified 67 statistically significant pathways, including DNA repair, telomere maintenance, mismatch repair and cell cycle control (p < 0.001). CONCLUSION: The disruption of TRGs leads to the shortening of telomeres, which is associated with HS progression, ageing, cellular senescence and an increased risk of various diseases, including cancer and associated comorbidities, such as metabolic syndrome, cardiovascular disease and inflammatory disorders. Further research is necessary to better understand the underlying mechanisms and establish causal links between TRGs and HS. The present study is the first effort to comprehend potential pathomechanisms of sporadic HS cases concentrating on PBMC methylome since ours.

Cell-free DNA in maternal blood and artificial intelligence: accurate prenatal detection of fetal congenital heart defects.

BACKGROUND: DNA cytosine nucleotide methylation (epigenomics and epigenetics) is an important mechanism for controlling gene expression in cardiac development. Combined artificial intelligence and whole-genome epigenomic analysis of circulating cell-free DNA in maternal blood has the potential for the detection of fetal congenital heart defects. OBJECTIVE: This study aimed to use genome-wide DNA cytosine methylation and artificial intelligence analyses of circulating cell-free DNA for the minimally invasive detection of fetal congenital heart defects. STUDY DESIGN: In this prospective study, whole-genome cytosine nucleotide methylation analysis was performed on circulating cell-free DNA using the Illumina Infinium MethylationEPIC BeadChip array. Multiple artificial intelligence approaches were evaluated for the detection of congenital hearts. The Ingenuity Pathway Analysis program was used to identify gene pathways that were epigenetically altered and important in congenital heart defect pathogenesis to further elucidate the pathogenesis of isolated congenital heart defects. RESULTS: There were 12 cases of isolated nonsyndromic congenital heart defects and 26 matched controls. A total of 5918 cytosine nucleotides involving 4976 genes had significantly altered methylation, that is, a P value of <.05 along with ≥5% whole-genome cytosine nucleotide methylation difference, in congenital heart defect cases vs controls. Artificial intelligence analysis of the methylation data achieved excellent congenital heart defect predictive accuracy (areas under the receiver operating characteristic curve, ≥0.92). For example, an artificial intelligence model using a combination of 5 whole-genome cytosine nucleotide markers achieved an area under the receiver operating characteristic curve of 0.97 (95% confidence interval, 0.87-1.0) with 98% sensitivity and 94% specificity. We found epigenetic changes in genes and gene pathways involved in the following important cardiac developmental processes: "cardiovascular system development and function," "cardiac hypertrophy," "congenital heart anomaly," and "cardiovascular disease." This lends biologic plausibility to our findings. CONCLUSION: This study reported the feasibility of minimally invasive detection of fetal congenital heart defect using artificial intelligence and DNA methylation analysis of circulating cell-free DNA for the prediction of fetal congenital heart defect. Furthermore, the findings supported an important role of epigenetic changes in congenital heart defect development.

Hidradenitis suppurativa presents a methylome dysregulation capable to explain the pro-inflammatory microenvironment: Are these DNA methylations potential therapeutic targets?

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, systemic, inflammatory skin condition with elusive pathogenesis that affects therapeutic intervention directly. OBJECTIVE: To characterize epigenetic variations in cytokines genes contributing to HS. METHODS: Epigenome-wide DNA methylation profiling with the Illumina Epic array was performed on blood DNA samples from 24 HS patients and 24 age- and sex-matched controls to explore DNA methylation changes in cytokine genes. RESULTS: We identified 170 cytokine genes including 27 hypermethylated CpG sites and 143 genes with hypomethylated sites respectively. Hypermethylated genes, including LIF, HLA-DRB1, HLA-G, MTOR, FADD, TGFB3, MALAT1 and CCL28; hypomethylated genes, including NCSTN, SMAD3, IGF1R, IL1F9, NOD2, NOD1, YY1, DLL1 and BCL2 may contribute to the pathogenesis of HS. These genes were enriched in the 117 different pathways (FDR p-values ≤ 0.05), including IL-4/IL-13 pathways and Wnt/ß-catenin signalling. CONCLUSIONS: The lack of wound healing, microbiome dysbiosis and increased tumour susceptibility are all sustained by these dysfunctional methylomes, hopefully, capable to be targeted in the next future. Since methylome describes and summarizes genetic and environmental contributions, these data may represent a further step towards a feasible precision medicine also for HS patients.

Alzheimer's Precision Neurology: Epigenetics of Cytochrome P450 Genes in Circulating Cell-Free DNA for Disease Prediction and Mechanism.

Precision neurology combines high-throughput technologies and statistical modeling to identify novel disease pathways and predictive biomarkers in Alzheimer's disease (AD). Brain cytochrome P450 (CYP) genes are major regulators of cholesterol, sex hormone, and xenobiotic metabolism, and they could play important roles in neurodegenerative disorders. Increasing evidence suggests that epigenetic factors contribute to AD development. We evaluated cytosine ('CpG')-based DNA methylation changes in AD using circulating cell-free DNA (cfDNA), to which neuronal cells are known to contribute. We investigated CYP-based mechanisms for AD pathogenesis and epigenetic biomarkers for disease detection. We performed a case-control study using 25 patients with AD and 23 cognitively healthy controls using the cfDNA of CYP genes. We performed a logistic regression analysis using the MetaboAnalyst software computer program and a molecular pathway analysis based on epigenetically altered CYP genes using the Cytoscape program. We identified 130 significantly (false discovery rate correction q-value < 0.05) differentially methylated CpG sites within the CYP genes. The top two differentially methylated genes identified were CYP51A1 and CYP2S1. The significant molecular pathways that were perturbed in AD cfDNA were (i) androgen and estrogen biosynthesis and metabolism, (ii) C21 steroid hormone biosynthesis and metabolism, and (iii) arachidonic acid metabolism. Existing evidence suggests a potential role of each of these biochemical pathways in AD pathogenesis. Next, we randomly divided the study group into discovery and validation sub-sets, each consisting of patients with AD and control patients. Regression models for AD prediction based on CYP CpG methylation markers were developed in the discovery or training group and tested in the independent validation group. The CYP biomarkers achieved a high predictive accuracy. After a 10-fold cross-validation, the combination of cg17852385/cg23101118 + cg14355428/cg22536554 achieved an AUC (95% CI) of 0.928 (0.787~1.00), with 100% sensitivity and 92.3% specificity for AD detection in the discovery group. The performance remained high in the independent validation or test group, achieving an AUC (95% CI) of 0.942 (0.905~0.979) with a 90% sensitivity and specificity. Our findings suggest that the epigenetic modification of CYP genes may play an important role in AD pathogenesis and that circulating CYP-based cfDNA biomarkers have the potential to accurately and non-invasively detect AD.

Maternal opioid use disorder: Placental transcriptome analysis for neonatal opioid withdrawal syndrome.

Excessive prenatal opioid exposure may lead to the development of Neonatal Opioid Withdrawal Syndrome (NOWS). RNA-seq was done on 64 formalin-fixed paraffin-embedded placental tissue samples from 32 mothers with opioid use disorder, with newborns with NOWS that required treatment, and 32 prenatally unexposed controls. We identified 93 differentially expressed genes in the placentas of infants with NOWS compared to unexposed controls. There were 4 up- and 89 downregulated genes. Among these, 7 genes CYP1A1, APOB, RPH3A, NRXN1, LINC01206, AL157396.1, UNC80 achieved an FDR p-value of <0.01. The remaining 87 genes were significant with FDR p-value <0.05. The 4 upregulated, CYP1A1, FP671120.3, RAD1, RN7SL856P, and the 10 most significantly downregulated genes were RNA5SP364, GRIN2A, UNC5D, DMBT1P1, MIR3976HG, LINC02199, LINC02822, PANTR1, AC012178.1, CTNNA2. Ingenuity Pathway Analysis identified the 7 most likely to play an important role in the etiology of NOWS. Our study expands insights into the genetic mechanisms of NOWS development.

Placental DNA methylation profiles in opioid-exposed pregnancies and associations with the neonatal opioid withdrawal syndrome.

Opioid abuse during pregnancy can result in Neonatal Opioid Withdrawal Syndrome (NOWS). We investigated genome-wide methylation analyses of 96 placental tissue samples, including 32 prenatally opioid-exposed infants with NOWS who needed therapy (+Opioids/+NOWS), 32 prenatally opioid-exposed infants with NOWS who did not require treatment (+Opioids/-NOWS), and 32 prenatally unexposed controls (-Opioids/-NOWS, control). Statistics, bioinformatics, Artificial Intelligence (AI), including Deep Learning (DL), and Ingenuity Pathway Analyses (IPA) were performed. We identified 17 dysregulated pathways thought to be important in the pathophysiology of NOWS and reported accurate AI prediction of NOWS diagnoses. The DL had an AUC (95% CI) =0.98 (0.95-1.0) with a sensitivity and specificity of 100% for distinguishing NOWS from the +Opioids/-NOWS group and AUCs (95% CI) =1.00 (1.0-1.0) with a sensitivity and specificity of 100% for distinguishing NOWS versus control and + Opioids/-NOWS group versus controls. This study provides strong evidence of methylation dysregulation of placental tissue in NOWS development.

Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy.

The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic predictors of CP in newborns and to investigate disease pathogenesis. Methylation analysis of newborn blood DNA using an Illumina HumanMethylation450K array was performed in 23 CP cases and 21 unaffected controls. There were 230 significantly differentially-methylated CpG loci in 258 genes. Each locus had at least 2.0-fold change in methylation in CP versus controls with a FDR p-value ≤ 0.05. Methylation level for each CpG locus had an area under the receiver operating curve (AUC) ≥ 0.75 for CP detection. Using Artificial Intelligence (AI) platforms/Machine Learning (ML) analysis, CpG methylation levels in a combination of 230 significantly differentially-methylated CpG loci in 258 genes had a 95% sensitivity and 94.4% specificity for newborn prediction of CP. Using pathway analysis, multiple canonical pathways plausibly linked to neuronal function were over-represented. Altered biological processes and functions included: neuromotor damage, malformation of major brain structures, brain growth, neuroprotection, neuronal development and de-differentiation, and cranial sensory neuron development. In conclusion, blood leucocyte epigenetic changes analyzed using AI/ML techniques appeared to accurately predict CP and provided plausible mechanistic information on CP pathogenesis.

Deregulated Long Non-Coding RNAs (lncRNA) as Promising Biomarkers in Hidradenitis Suppurativa.

Background/Objectives: In recent times, epigenetics alterations in Hidradenitis suppurativa (HS) have been explored and exploited translationally to guide investigation of new therapeutic approaches. On the other hand, long noncoding RNAs (LncRNAs), main regulators of the epigenetic status of the human genome, have been scarcely investigated, notwithstanding their potential relevance in broad pathogenesis comprehension. Here, we aim to explore the methylation pattern of lncRNAs in HS. Methods: In this case-control study, 24 HS patients and age-, sex- and BMI-matched controls were analyzed to characterize the methylome of lncRNA genes in peripheral blood cells. Gene ontology analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) network, and MCODE analysis were performed. Results: A set of fifteen lncRNA genes exhibited significantly differential methylation patterns, with ten of them showing hypomethylation and five displaying hypermethylation at specific CpG sites. The hypomethylated lncRNA genes were DLEU2, MESTIT1, CASC2, TUG1, KCNQ1DN, PSORS1C3, PCA3, DSCR8, RFPL1S, and PVT1, while the hypermethylated ones were HAR1A, FAM66B, SNHG9, HCG9, and HCP5. These lncRNA genes have been linked to various important biological processes, including cell proliferation, apoptosis, inflammation, chronic inflammatory skin diseases, and wound healing. Their altered methylation status suggests potential roles in regulating these processes, and may contribute to HS pathogenesis and healing mechanisms. Conclusions: This study revealed an interesting dysregulation pattern of definite lncRNAs in the methylome which is linked to both the development of HS and its comorbidities. Epigenetically altered lncRNAs genes could represent useful biomarkers, and could help in guiding innovative treatment strategies.

Human male infertility associated with mutations in NR5A1 encoding steroidogenic factor 1.

One in seven couples worldwide are infertile, and male factor infertility accounts for approximately 30%-50% of these cases. Although many genes are known to be essential for gametogenesis, there are surprisingly few monogenic mutations that have been conclusively demonstrated to cause human spermatogenic failure. A nuclear receptor, NR5A1 (also called steroidogenic factor 1), is a key transcriptional regulator of genes involved in the hypothalamic-pituitary-steroidogenic axis, and it is expressed in the steroidogenic tissue of the developing and adult human gonad. Mutations of NR5A1 have been reported in 46,XY disorders of sex development and in 46,XX primary ovarian insufficiency. To test the hypothesis that mutations in NR5A1 cause male infertility, we sequenced NR5A1 in 315 men with idiopathic spermatogenic failure. We identified seven men with severe spermatogenic failure who carried missense mutations in NR5A1. Functional studies indicated that these mutations impaired NR5A1 transactivational activity. We did not observe these mutations in more than 4000 control alleles, including the entire coding sequence of 359 normospermic men and 370 fertile male controls. NR5A1 mutations are found in approximately 4% of men with otherwise unexplained severe spermatogenic failure.

Genome-wide linkage and copy number variation analysis reveals 710 kb duplication on chromosome 1p31.3 responsible for autosomal dominant omphalocele.

BACKGROUND: Omphalocele is a congenital birth defect characterised by the presence of internal organs located outside of the ventral abdominal wall. The purpose of this study was to identify the underlying genetic mechanisms of a large autosomal dominant Caucasian family with omphalocele. METHODS AND FINDINGS: A genetic linkage study was conducted in a large family with an autosomal dominant transmission of an omphalocele using a genome-wide single nucleotide polymorphism (SNP) array. The analysis revealed significant evidence of linkage (non-parametric NPL = 6.93, p=0.0001; parametric logarithm of odds (LOD) = 2.70 under a fully penetrant dominant model) at chromosome band 1p31.3. Haplotype analysis narrowed the locus to a 2.74 Mb region between markers rs2886770 (63014807 bp) and rs1343981 (65757349 bp). Molecular characterisation of this interval using array comparative genomic hybridisation followed by quantitative microsphere hybridisation analysis revealed a 710 kb duplication located at 63.5-64.2 Mb. All affected individuals who had an omphalocele and shared the haplotype were positive for this duplicated region, while the duplication was absent from all normal individuals of this family. Multipoint linkage analysis using the duplication as a marker yielded a maximum LOD score of 3.2 at 1p31.3 under a dominant model. The 710 kb duplication at 1p31.3 band contains seven known genes including FOXD3, ALG6, ITGB3BP, KIAA1799, DLEU2L, PGM1, and the proximal portion of ROR1. Importantly, this duplication is absent from the database of genomic variants. CONCLUSIONS: The present study suggests that development of an omphalocele in this family is controlled by overexpression of one or more genes in the duplicated region. To the authors' knowledge, this is the first reported association of an inherited omphalocele condition with a chromosomal rearrangement.

Duplications of BHLHA9 are associated with ectrodactyly and tibia hemimelia inherited in non-Mendelian fashion.

BACKGROUND: Split-hand/foot malformation (SHFM)-also known as ectrodactyly-is a congenital disorder characterised by severe malformations of the distal limbs affecting the central rays of hands and/or feet. A distinct entity termed SHFLD presents with SHFM and long bone deficiency. Mouse models suggest that a defect of the central apical ectodermal ridge leads to the phenotype. Although six different loci/mutations (SHFM1-6) have been associated with SHFM, the underlying cause in a large number of cases is still unresolved. METHODS: High resolution array comparative genomic hybridisation (CGH) was performed in patients with SHFLD to detect copy number changes. Candidate genes were further evaluated for expression and function during limb development by whole mount in situ hybridisation and morpholino knock-down experiments. RESULTS: Array CGH showed microduplications on chromosome 17p13.3, a locus previously associated with SHFLD. Detailed analysis of 17 families revealed that this copy number variation serves as a susceptibility factor for a highly variable phenotype with reduced penetrance, particularly in females. Compared to other known causes for SHFLD 17p duplications appear to be the most frequent cause of SHFLD. A ~11.8 kb minimal critical region was identified encompassing a single gene, BHLHA9, a putative basic loop helix transcription factor. Whole mount in situ hybridisation showed expression restricted to the limb bud mesenchyme underlying the apical ectodermal ridge in mouse and zebrafish embryos. Knock down of bhlha9 in zebrafish resulted in shortening of the pectoral fins. CONCLUSIONS: Genomic duplications encompassing BHLHA9 are associated with SHFLD and non-Mendelian inheritance characterised by a high degree of non-penetrance with sex bias. Knock-down of bhlha9 in zebrafish causes severe reduction defects of the pectoral fin, indicating a role for this gene in limb development.

An Updated Mutation Spectrum of the γ-Secretase Complex: Novel NCSTN Gene Mutation in an Indian Family with Hidradenitis Suppurativa and Acne Conglobata.

Background: Hidradenitis suppurativa (HS) is a complex, chronic inflammatory skin disorder whose pathophysiology is poorly understood. Genetic studies have shown that HS is predisposed by mutations in the γ-secretase gene, but only a proportion of familial and partial sporadic cases have been shown to possess such mutations. HS has high genetic heterogeneity and is thought to be triggered by a combination of genetics and environmental factors. Aims: The study aimed to investigate the genetic causes of HS in a large cohort of patients and to update the mutation spectrum of γ-secretase complex genes. Methods: We conducted mutational screening of 95 sporadic HS cases and one large family with both HS and acne conglobata (AC) to identify mutations in the coding and splice junction region of γ-secretase complex genes (nicastrin (NCSTN), presenilin 1 (PSEN1), presenilin enhancer 2 (PSENEN), and aph-1 homolog B, gamma-secretase subunit (APH1B)). Results: Our study identified a nucleotide substitution of 1876C>T in the NCSTN gene, which caused a stop codon (p.Arg626X) in the affected members of a large family with HS and AC. No pathogenic variants were detected in 95 sporadic cases of HS, indicating there is possible genetic heterogeneity. Conclusion: We report a new family with a nonsense mutation in the NCSTN gene that supports the role of the γ-secretase complex genes in HS with AC. The updated γ-secretase mutation spectrum for HS now includes 78 mutations.

Placental microRNA methylome signatures may serve as biomarkers and therapeutic targets for prenatally opioid-exposed infants with neonatal opioid withdrawal syndrome.

Introduction: The neonate exposed to opioids in utero faces a constellation of withdrawal symptoms postpartum commonly called neonatal opioid withdrawal syndrome (NOWS). The incidence of NOWS has increased in recent years due to the opioid epidemic. MicroRNAs (miRNAs) are small non-coding RNA molecules that play a crucial role in gene regulation. Epigenetic variations in microRNAs (miRNAs) and their impact on addiction-related processes is a rapidly evolving area of research. Methods: The Illumina Infinium Methylation EPIC BeadChip was used to analyze DNA methylation levels of miRNA-encoding genes in 96 human placental tissues to identify miRNA gene methylation profiles as-sociated with NOWS: 32 from mothers whose prenatally opioid-exposed infants required pharmacologic management for NOWS, 32 from mothers whose prenatally opioid-exposed infants did not require treat-ment for NOWS, and 32 unexposed controls. Results: The study identified 46 significantly differentially methylated (FDR p-value ≤ 0.05) CpGs associated with 47 unique miRNAs, with a receiver operating characteristic (ROC) area under the curve (AUC) ≥0.75 including 28 hypomethylated and 18 hypermethylated CpGs as potentially associated with NOWS. These dysregulated microRNA methylation patterns may be a contributing factor to NOWS pathogenesis. Conclusion: This is the first study to analyze miRNA methylation profiles in NOWS infants and illustrates the unique role miRNAs might have in diagnosing and treating the disease. Furthermore, these data may provide a step toward feasible precision medicine for NOWS babies as well.

Integrative Analysis Unveils the Correlation of Aminoacyl-tRNA Biosynthesis Metabolites with the Methylation of the SEPSECS Gene in Huntington's Disease Brain Tissue.

The impact of environmental factors on epigenetic changes is well established, and cellular function is determined not only by the genome but also by interacting partners such as metabolites. Given the significant impact of metabolism on disease progression, exploring the interaction between the metabolome and epigenome may offer new insights into Huntington's disease (HD) diagnosis and treatment. Using fourteen post-mortem HD cases and fourteen control subjects, we performed metabolomic profiling of human postmortem brain tissue (striatum and frontal lobe), and we performed DNA methylome profiling using the same frontal lobe tissue. Along with finding several perturbed metabolites and differentially methylated loci, Aminoacyl-tRNA biosynthesis (adj p-value = 0.0098) was the most significantly perturbed metabolic pathway with which two CpGs of the SEPSECS gene were correlated. This study improves our understanding of molecular biomarker connections and, importantly, increases our knowledge of metabolic alterations driving HD progression.

Placental cytochrome P450 methylomes in infants exposed to prenatal opioids: exploring the effects of neonatal opioid withdrawal syndrome on health horizons.

Background: Neonatal opioid withdrawal syndrome (NOWS), arises due to increased opioid use during pregnancy. Cytochrome P450 (CYP) enzymes play a pivotal role in metabolizing a wide range of substances in the human body, including opioids, other drugs, toxins, and endogenous compounds. The association between CYP gene methylation and opioid effects is unexplored and it could offer promising insights. Objective: To investigate the impact of prenatal opioid exposure on disrupted CYPs in infants and their anticipated long-term clinical implications. Study Design: DNA methylation levels of CYP genes were analyzed in a cohort of 96 placental tissues using Illumina Infinium MethylationEPIC (850 k) BeadChips. This involved three groups of placental tissues: 32 from mothers with infants exposed to opioids prenatally requiring pharmacologic treatment for NOWS, 32 from mothers with prenatally opioid-exposed infants not needing NOWS treatment, and 32 from unexposed control mothers. Results: The study identified 20 significantly differentially methylated CpG sites associated with 17 distinct CYP genes, with 14 CpGs showing reduced methylation across 14 genes (CYP19A1, CYP1A2, CYP4V2, CYP1B1, CYP24A1, CYP26B1, CYP26C1, CYP2C18, CYP2C9, CYP2U1, CYP39A1, CYP2R1, CYP4Z1, CYP2D7P1 and), while 8 exhibited hypermethylation (CYP51A1, CYP26B1, CYP2R1, CYP2U1, CYP4X1, CYP1A2, CYP2W1, and CYP4V2). Genes such as CYP1A2, CYP26B1, CYP2R1, CYP2U1, and CYP4V2 exhibited both increased and decreased methylation. These genes are crucial for metabolizing eicosanoids, fatty acids, drugs, and diverse substances. Conclusion: The study identified profound methylation changes in multiple CYP genes in the placental tissues relevant to NOWS. This suggests that disruption of DNA methylation patterns in CYP transcripts might play a role in NOWS and may serve as valuable biomarkers, suggesting a future pathway for personalized treatment. Further research is needed to confirm these findings and explore their potential for diagnosis and treatment.

Artificial intelligence and placental DNA methylation: newborn prediction and molecular mechanisms of autism in preterm children.

BACKGROUND: Autism Spectrum Disorder (ASD) represents a heterogeneous group of disorders with a complex genetic and epigenomic etiology. DNA methylation is the most extensively studied epigenomic mechanism and correlates with altered gene expression. Artificial intelligence (AI) is a powerful tool for group segregation and for handling the large volume of data generated in omics experiments. METHODS: We performed genome-wide methylation analysis for differential methylation of cytosine nucleotide (CpG) was performed in 20 postpartum placental tissue samples from preterm births. Ten newborns went on to develop autism (Autistic Disorder subtype) and there were 10 unaffected controls. AI including Deep Learning (AI-DL) platforms were used to identify and rank cytosine methylation markers for ASD detection. Ingenuity Pathway Analysis (IPA) to identify genes and molecular pathways that were dysregulated in autism. RESULTS: We identified 4870 CpG loci comprising 2868 genes that were significantly differentially methylated in ASD compared to controls. Of these 431 CpGs met the stringent EWAS threshold (p-value <5 × 10-8) along with ≥10% methylation difference between CpGs in cases and controls. DL accurately predicted autism with an AUC (95% CI) of 1.00 (1-1) and sensitivity and specificity of 100% using a combination of 5 CpGs [cg13858611 (NRN1), cg09228833 (ZNF217), cg06179765 (GPNMB), cg08814105 (NKX2-5), cg27092191 (ZNF267)] CpG markers. IPA identified five prenatally dysregulated molecular pathways linked to ASD. CONCLUSIONS: The present study provides substantial evidence that epigenetic differences in placental tissue are associated with autism development and raises the prospect of early and accurate detection of the disorder.

Differential methylation of microRNA encoding genes may contribute to high myopia.

Introduction: High myopia (HM), an eye disorder with a refractive error ≤-6.0 diopters, has multifactorial etiology with environmental and genetic factors involved. Recent studies confirm the impact of alterations in DNA methylation and microRNAs (miRNAs) on myopia. Here, we studied the combined aspects evaluating to the role of methylation of miRNA encoding genes in HM. Materials and Methods: From the genome-wide DNA methylation data of 18 Polish children with HM and 18 matched controls, we retrieved differentially methylated CG dinucleotides localized in miRNA encoding genes. Putative target genes of the highest-ranked miRNAs were obtained from the miRDB and included in overrepresentation analyses in the ConsensusPathDB. Expression of target genes was assessed using the RNA sequencing data of retinal ARPE-19 cell line. Results: We identified differential methylation of CG dinucleotides in promoter regions of MIR3621, MIR34C, MIR423 (increased methylation level), and MIR1178, MIRLET7A2, MIR885, MIR548I3, MIR6854, MIR675, MIRLET7C, MIR99A (decreased methylation level) genes. Several targets of these miRNAs, e.g. GNAS, TRAM1, CTNNB1, EIF4B, TENM3 and RUNX were previously associated with myopia/HM/refractive error in Europeans in genome-wide association studies. Overrepresentation analyses of miRNAs' targets revealed enrichment in pathways/processes related to eye structure/function, such as axon guidance, transcription, focal adhesion, and signaling pathways of TGF-ß, insulin, MAPK and EGF-EGFR. Conclusion: Differential methylation of indicated miRNA encoding genes might influence their expression and contribute to HM pathogenesis via disrupted regulation of transcription of miRNAs' target genes. Methylation of genes encoding miRNAs may be a new direction in research on both the mechanisms determining HM and non-invasive indicators in diagnostics.

Precision Oncology: Artificial Intelligence and DNA Methylation Analysis of Circulating Cell-Free DNA for Lung Cancer Detection.

Background: Lung cancer (LC) is a leading cause of cancer-deaths globally. Its lethality is due in large part to the paucity of accurate screening markers. Precision Medicine includes the use of omics technology and novel analytic approaches for biomarker development. We combined Artificial Intelligence (AI) and DNA methylation analysis of circulating cell-free tumor DNA (ctDNA), to identify putative biomarkers for and to elucidate the pathogenesis of LC. Methods: Illumina Infinium MethylationEPIC BeadChip array analysis was used to measure cytosine (CpG) methylation changes across the genome in LC. Six different AI platforms including support vector machine (SVM) and Deep Learning (DL) were used to identify CpG biomarkers and for LC detection. Training set and validation sets were generated, and 10-fold cross validation performed. Gene enrichment analysis using g:profiler and GREAT enrichment was used to elucidate the LC pathogenesis. Results: Using a stringent GWAS significance threshold, p-value <5x10-8, we identified 4389 CpGs (cytosine methylation loci) in coding genes and 1812 CpGs in non-protein coding DNA regions that were differentially methylated in LC. SVM and three other AI platforms achieved an AUC=1.00; 95% CI (0.90-1.00) for LC detection. DL achieved an AUC=1.00; 95% CI (0.95-1.00) and 100% sensitivity and specificity. High diagnostic accuracies were achieved with only intragenic or only intergenic CpG loci. Gene enrichment analysis found dysregulation of molecular pathways involved in the development of small cell and non-small cell LC. Conclusion: Using AI and DNA methylation analysis of ctDNA, high LC detection rates were achieved. Further, many of the genes that were epigenetically altered are known to be involved in the biology of neoplasms in general and lung cancer in particular.

Decreased Levels of DNA Methylation in the PCDHA Gene Cluster as a Risk Factor for Early-Onset High Myopia in Young Children.

Purpose: High myopia (HM), an eye disorder with at least -6.0 diopters refractive error, has a complex etiology with environmental, genetic, and likely epigenetic factors involved. To complement the DNA methylation assessment in children with HM, we analyzed genes that had significantly lower DNA methylation levels. Methods: The DNA methylation pattern was studied based on the genome-wide methylation data of 18 Polish children with HM paired with 18 controls. Genes overlapping CG dinucleotides with decreased methylation level in HM cases were assessed by enrichment analyses. From those, genes with CG dinucleotides in promoter regions were further evaluated based on exome sequencing (ES) data of 16 patients with HM from unrelated Polish families, Sanger sequencing data of the studied children, and the RNA sequencing data of human retinal ARPE-19 cells. Results: The CG dinucleotide with the most decreased methylation level in cases was identified in a promoter region of PCDHA10 that overlaps intronic regions of PCDHA1-9 of the PCDHA gene cluster in myopia 5q31 locus. Also, two single nucleotide variants, rs200661444, detected in our ES, and rs246073, previously found as associated with a refractive error in a genome-wide association study, were revealed within this gene cluster. Additionally, genes previously linked to ocular phenotypes, myopia-related traits, or loci, including ADAM20, ZFAND6, ETS1, ABHD13, SBSPON, SORBS2, LMOD3, ATXN1, and FARP2, were found to have decreased methylation. Conclusions: Alterations in the methylation pattern of specific CG dinucleotides may be associated with early-onset HM, so this could be used to develop noninvasive biomarkers of HM in children and adolescents.