Investigating the potential of single-cell DNA methylation data to detect allele-specific methylation and imprinting.

Allele-specific methylation (ASM) is an epigenetic modification whereby one parental allele becomes methylated and the other unmethylated at a specific locus. ASM is most often driven by the presence of nearby heterozygous variants that influence methylation, but also occurs somatically in the context of genomic imprinting. In this study, we investigate ASM using publicly available single-cell reduced representation bisulfite sequencing (scRRBS) data on 608 B cells sampled from six healthy B cell samples and 1,230 cells from 11 chronic lymphocytic leukemia (CLL) samples. We developed a likelihood-based criterion to test whether a CpG exhibited ASM, based on the distributions of methylated and unmethylated reads both within and across cells. Applying our likelihood ratio test, 65,998 CpG sites exhibited ASM in healthy B cell samples according to a Bonferroni criterion (p < 8.4 × 10-9), and 32,862 CpG sites exhibited ASM in CLL samples (p < 8.5 × 10-9). We also called ASM at the sample level. To evaluate the accuracy of our method, we called heterozygous variants from the scRRBS data, which enabled variant-based calls of ASM within each cell. Comparing sample-level ASM calls to the variant-based measures of ASM, we observed a positive predictive value of 76%-100% across samples. We observed high concordance of ASM across samples and an overrepresentation of ASM in previously reported imprinted genes and genes with imprinting binding motifs. Our study demonstrates that single-cell bisulfite sequencing is a potentially powerful tool to investigate ASM, especially as studies expand to increase the number of samples and cells sequenced.

Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI.

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E-7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

DNA methylation profiles of cancer-related fatigue associated with markers of inflammation and immunometabolism.

Cancer patients are commonly affected by fatigue. Herein, we sought to examine epigenetic modifications (i.e., DNA methylation) related to fatigue in peripheral blood among patients during and after treatment for head and neck cancer (HNC). Further, we determined whether these modifications were associated with gene expression and inflammatory protein markers, which we have previously linked to fatigue in HNC. This prospective, longitudinal study enrolled eligible patients with data collected at pre-radiotherapy, end of radiotherapy, and six months and one-year post-radiotherapy. Fatigue data were reported by patients using the Multidimensional Fatigue Inventory (MFI)-20. DNA methylation (Illumina MethylationEPIC) and gene expression (Applied Biosystems Clariom S) arrays and assays for seven inflammatory markers (R&D Systems multiplex) were performed. Mixed models and enrichment analyses were applied to establish the associations. A total of 386 methylation loci were associated with fatigue among 145 patients (False Discovery Rate [FDR] < 0.05). Enrichment analyses showed the involvement of genes related to immune and inflammatory responses, insulin and lipid metabolism, neuropsychological disorders, and tumors. We further identified 16 methylation-gene expression pairs (FDR < 0.05), which were linked to immune and inflammatory responses and lipid metabolism. Ninety-one percent (351) of the 386 methylation loci were also significantly associated with inflammatory markers (e.g., interleukin 6, c-reactive protein; FDR < 0.05), which further mediated the association between methylation and fatigue (FDR < 0.05). These data suggest that epigenetic modifications associated with inflammation and immunometabolism, in conjunction with relevant gene expression and protein markers, are potential targets for treating fatigue in HNC patients. The findings also merit future prospective studies in other cancer populations as well as interventional investigations.

Gaseous air pollutants and DNA methylation in a methylome-wide association study of an ethnically and environmentally diverse population of U.S. adults.

Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO2; NOx), ozone (O3), and sulfur dioxide (SO2) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation- and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (PCochran's Q > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a -0.3 (95% CI: -0.4, -0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a -0.3 (95% CI: -0.4, -0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression.

Critical evaluation of copy number variant calling methods using DNA methylation.

Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data.

Epigenetic age acceleration, fatigue, and inflammation in patients undergoing radiation therapy for head and neck cancer: A longitudinal study.

BACKGROUND: The authors measured epigenetic age acceleration (EAA) during and after cancer treatment and its association with inflammation and fatigue, which is a debilitating symptom in patients with cancer. METHODS: Patients who had head and neck cancer without distant metastases were assessed before, immediately after, and at 6 months and 12 months postradiotherapy. Blood DNA methylation was assessed using a proprietary bead chip (the Illumina MethylationEPIC BeadChip). EAA was calculated using the Levine epigenetic clock (DNAmPhenoAge), adjusted for chronological age. Fatigue was assessed using the Multidimensional Fatigue Inventory-20. Inflammatory markers were measured using standard techniques. RESULTS: Most patients (N = 133) were men, White, had advanced disease, and received concurrent chemoradiation. EAA changes over time were significant, with the largest increase (4.9 years) observed immediately after radiotherapy (P < .001). Increased EAA was associated with elevated fatigue (P = .003) over time, and patients who had severe fatigue experienced 3.1 years higher EAA than those who had low fatigue (P < .001), which was more prominent (5.6 years; P = .018) for patients who had human papillomavirus-unrelated disease at 12 months posttreatment. EAA was also positively associated with inflammatory markers, including C-reactive protein (CRP) and interleukin-6 (IL-6), over time (P < .001), and patients who had high CRP and IL-6 levels exhibited increases of 4.6 and 5.9 years, respectively, in EAA compared with those who had low CRP and IL-6 levels (P < .001). CRP and IL-6 mediated the association between EAA and fatigue (CRP: 95% CI, 0.060-0.279; IL-6: 95% CI, 0.024-0.220). CONCLUSIONS: Patients with head and neck cancer experienced increased EAA, especially immediately after treatment completion. EAA was associated with greater fatigue and inflammation, including 1 year after treatment. Inflammation may be a target to reduce the impact of age acceleration on poor functional outcomes.

The role of the gut microbiome in cancer-related fatigue: pilot study on epigenetic mechanisms.

PURPOSE: Recent evidence supports a key role of gut microbiome in brain health. We conducted a pilot study to assess associations of gut microbiome with cancer-related fatigue and explore the associations with DNA methylation changes. METHODS: Self-reported Multidimensional Fatigue Inventory and stool samples were collected at pre-radiotherapy and one-month post-radiotherapy in patients with head and neck cancer. Gut microbiome data were obtained by sequencing the 16S ribosomal ribonucleic acid gene. DNA methylation changes in the blood were assessed using Illumina Methylation EPIC BeadChip. RESULTS: We observed significantly different gut microbiota patterns among patients with high vs. low fatigue across time. This pattern was characterized by low relative abundance in short-chain fatty acid-producing taxa (family Ruminococcaceae, genera Subdoligranulum and Faecalibacterium; all p < 0.05), with high abundance in taxa associated with inflammation (genera Family XIII AD3011 and Erysipelatoclostridium; all p < 0.05) for high-fatigue group. We identified nine KEGG Orthology pathways significantly different between high- vs. low-fatigue groups over time (all p < 0.001), including pathways related to fatty acid synthesis and oxidation, inflammation, and brain function. Gene set enrichment analysis (GSEA) was performed on the top differentially methylated CpG sites that were associated with the taxa and fatigue. All biological processes from the GSEA were related to immune responses and inflammation (FDR < 0.05). CONCLUSIONS: Our results suggest different patterns of the gut microbiota in cancer patients with high vs. low fatigue. Results from functional pathways and DNA methylation analyses indicate that inflammation is likely to be the major driver in the gut-brain axis for cancer-related fatigue.

Epigenetically mediated electrocardiographic manifestations of sub-chronic exposures to ambient particulate matter air pollution in the Women's Health Initiative and Atherosclerosis Risk in Communities Study.

BACKGROUND: Short-duration exposure to ambient particulate matter (PM) air pollution is associated with cardiac autonomic dysfunction and prolonged ventricular repolarization. However, associations with sub-chronic exposures to coarser particulates are relatively poorly characterized as are molecular mechanisms underlying their potential relationships with cardiovascular disease. MATERIALS AND METHODS: We estimated associations between monthly mean concentrations of PM < 10 µm and 2.5-10 µm in diameter (PM10; PM2.5-10) with time-domain measures of heart rate variability (HRV) and QT interval duration (QT) among U.S. women and men in the Women's Health Initiative and Atherosclerosis Risk in Communities Study (nHRV = 82,107; nQT = 76,711). Then we examined mediation of the PM-HRV and PM-QT associations by DNA methylation (DNAm) at three Cytosine-phosphate-Guanine (CpG) sites (cg19004594, cg24102420, cg12124767) with known sensitivity to monthly mean PM concentrations in a subset of the participants (nHRV = 7,169; nQT = 6,895). After multiply imputing missing PM, electrocardiographic and covariable data, we estimated associations using attrition-weighted, linear, mixed, longitudinal models adjusting for sociodemographic, behavioral, meteorological, and clinical characteristics. We assessed mediation by estimating the proportions of PM-HRV and PM-QT associations mediated by DNAm. RESULTS: We found little evidence of PM-HRV association, PM-QT association, or mediation by DNAm. CONCLUSIONS: The findings suggest that among racially/ethnically and environmentally diverse U.S. populations, sub-chronic exposures to coarser particulates may not exert appreciable, epigenetically mediated effects on cardiac autonomic function or ventricular repolarization. Further investigation in better-powered studies is warranted, with additional focus on shorter duration exposures to finer particulates and non-electrocardiographic outcomes among relatively susceptible populations.

Blood-Derived DNA Methylation Signatures of Crohn's Disease and Severity of Intestinal Inflammation.

BACKGROUND & AIMS: Crohn's disease is a relapsing and remitting inflammatory disorder with a variable clinical course. Although most patients present with an inflammatory phenotype (B1), approximately 20% of patients rapidly progress to complicated disease, which includes stricturing (B2), within 5 years. We analyzed DNA methylation patterns in blood samples of pediatric patients with Crohn's disease at diagnosis and later time points to identify changes that associate with and might contribute to disease development and progression. METHODS: We obtained blood samples from 164 pediatric patients (1-17 years old) with Crohn's disease (B1 or B2) who participated in a North American study and were followed for 5 years. Participants without intestinal inflammation or symptoms served as controls (n = 74). DNA methylation patterns were analyzed in samples collected at time of diagnosis and 1-3 years later at approximately 850,000 sites. We used genetic association and the concept of Mendelian randomization to identify changes in DNA methylation patterns that might contribute to the development of or result from Crohn's disease. RESULTS: We identified 1189 5'-cytosine-phosphate-guanosine-3' (CpG) sites that were differentially methylated between patients with Crohn's disease (at diagnosis) and controls. Methylation changes at these sites correlated with plasma levels of C-reactive protein. A comparison of methylation profiles of DNA collected at diagnosis of Crohn's disease vs during the follow-up period showed that, during treatment, alterations identified in methylation profiles at the time of diagnosis of Crohn's disease more closely resembled patterns observed in controls, irrespective of disease progression to B2. We identified methylation changes at 3 CpG sites that might contribute to the development of Crohn's disease. Most CpG methylation changes associated with Crohn's disease disappeared with treatment of inflammation and might be a result of Crohn's disease. CONCLUSIONS: Methylation patterns observed in blood samples from patients with Crohn's disease accompany acute inflammation; with treatment, these change to resemble methylation patterns observed in patients without intestinal inflammation. These findings indicate that Crohn's disease-associated patterns of DNA methylation observed in blood samples are a result of the inflammatory features of the disease and are less likely to contribute to disease development or progression.

Endometriosis, endocrine disrupters, and epigenetics: an investigation into the complex interplay in women with polybrominated biphenyl exposure and endometriosis.

PURPOSE: Endocrine disrupting compounds (EDCs) have been shown to affect multiple biologic processes especially steroid-hormone processes. We sought to determine differences in DNA methylation exists between women with and without endometriosis following exposure to polybrominated biphenyl (PBB). METHODS: Cross-sectional study of 305 females in the Michigan PBB Registry. DNA was extracted, and DNA methylation was interrogated using the MethylationEPIC BeadChip (Illumina, San Diego, California). Demographic data was analyzed using Chi-squared and T tests. Linear regressions were performed for each cytosine-guanine dinucleotide (CpG) site, modeling the logit transformation of the ß value as a linear function of the presence of endometriosis. Sensitivity analyses were conducted controlling for estradiol levels and menopausal status. Replication study performed evaluating for any association between CpGs reported in the literature and our findings. RESULTS: In total, 39,877 CpGs nominally associated with endometriosis (p < 0.05) after adjusting for age and cellular heterogeneity, although none remained significant after correction for multiple comparisons (FDR < 0.05). Pathway analysis of these CpGs showed enrichment in 68 biologic pathways involved in various endocrine, immunologic, oncologic, and cell regulation processes as well as embryologic reproductive tract development and function (FoxO, Wnt, and Hedgehog signaling). We identified 42,261 CpG sites in the literature reported to be associated with endometriosis; 2012 of these CpG sites were also significant in our cohort. CONCLUSION: We found 39,877 CpG sites that nominally associated with endometriosis (p < 0.05) after adjusting for age and cellular heterogeneity; however, none remained significant after correction for multiple comparisons (FDR < 0.05).

Powerful and robust cross-phenotype association test for case-parent trios.

There has been increasing interest in identifying genes within the human genome that influence multiple diverse phenotypes. In the presence of pleiotropy, joint testing of these phenotypes is not only biologically meaningful but also statistically more powerful than univariate analysis of each separate phenotype accounting for multiple testing. Although many cross-phenotype association tests exist, the majority of such methods assume samples composed of unrelated subjects and therefore are not applicable to family-based designs, including the valuable case-parent trio design. In this paper, we describe a robust gene-based association test of multiple phenotypes collected in a case-parent trio study. Our method is based on the kernel distance covariance (KDC) method, where we first construct a similarity matrix for multiple phenotypes and a similarity matrix for genetic variants in a gene; we then test the dependency between the two similarity matrices. The method is applicable to either common variants or rare variants in a gene, and resulting tests from the method are by design robust to confounding due to population stratification. We evaluated our method through simulation studies and observed that the method is substantially more powerful than standard univariate testing of each separate phenotype. We also applied our method to phenotypic and genotypic data collected in case-parent trios as part of the Genetics of Kidneys in Diabetes (GoKinD) study and identified a genome-wide significant gene demonstrating cross-phenotype effects that was not identified using standard univariate approaches.

Thyroid hormone levels associate with exposure to polychlorinated biphenyls and polybrominated biphenyls in adults exposed as children.

BACKGROUND: Michigan residents were directly exposed to endocrine-disrupting compounds, polybrominated biphenyl (PBB) and polychlorinated biphenyl (PCB). A growing body of evidence suggests that exposure to certain endocrine-disrupting compounds may affect thyroid function, especially in people exposed as children, but there are conflicting observations. In this study, we extend previous work by examining age of exposure's effect on the relationship between PBB exposure and thyroid function in a large group of individuals exposed to PBB. METHODS: Linear regression models were used to test the association between serum measures of thyroid function (total thyroxine (T4), total triiodothyronine (T3), free T4, free T3, thyroid stimulating hormone (TSH), and free T3: free T4 ratio) and serum PBB and PCB levels in a cross-sectional analysis of 715 participants in the Michigan PBB Registry. RESULTS: Higher PBB levels were associated with many thyroid hormones measures, including higher free T3 (p = 0.002), lower free T4 (p = 0.01), and higher free T3: free T4 ratio (p = 0.0001). Higher PCB levels were associated with higher free T4 (p = 0.0002), and higher free T3: free T4 ratio (p = 0.002). Importantly, the association between PBB and thyroid hormones was dependent on age at exposure. Among people exposed before age 16 (N = 446), higher PBB exposure was associated with higher total T3 (p = 0.01) and free T3 (p = 0.0003), lower free T4 (p = 0.04), and higher free T3: free T4 ratio (p = 0.0001). No significant associations were found among participants who were exposed after age 16. No significant associations were found between TSH and PBB or PCB in any of the analyses conducted. CONCLUSIONS: This suggests that both PBB and PCB are associated with thyroid function, particularly among those who were exposed as children or prenatally.

An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells.

BACKGROUND: Gene expression can be influenced by DNA methylation 1) distally, at regulatory elements such as enhancers, as well as 2) proximally, at promoters. Our current understanding of the influence of distal DNA methylation changes on gene expression patterns is incomplete. Here, we characterize genome-wide methylation and expression patterns for ~ 13 k genes to explore how DNA methylation interacts with gene expression, throughout the genome. RESULTS: We used a linear mixed model framework to assess the correlation of DNA methylation at ~ 400 k CpGs with gene expression changes at ~ 13 k transcripts in two independent datasets from human blood cells. Among CpGs at which methylation significantly associates with transcription (eCpGs), > 50% are distal (> 50 kb) or trans (different chromosome) to the correlated gene. Many eCpG-transcript pairs are consistent between studies and ~ 90% of neighboring eCpGs associate with the same gene, within studies. We find that enhancers (P < 5e-18) and microRNA genes (P = 9e-3) are overrepresented among trans eCpGs, and insulators and long intergenic non-coding RNAs are enriched among cis and distal eCpGs. Intragenic-eCpG-transcript correlations are negative in 60-70% of occurrences and are enriched for annotated gene promoters and enhancers (P < 0.002), highlighting the importance of intragenic regulation. Gene Ontology analysis indicates that trans eCpGs are enriched for transcription factor genes and chromatin modifiers, suggesting that some trans eCpGs represent the influence of gene networks and higher-order transcriptional control. CONCLUSIONS: This work sheds new light on the interplay between epigenetic changes and gene expression, and provides useful data for mining biologically-relevant results from epigenome-wide association studies.

Relationship between Epigenetic Maturity and Respiratory Morbidity in Preterm Infants.

OBJECTIVE: To assess associations between epigenetic maturity of extremely preterm babies (born at less than 28 weeks of gestation), neonatal interventions, and respiratory outcomes, including the administration of surfactant and postnatal corticosteroids, duration of assisted ventilation, and development of bronchopulmonary dysplasia (BPD). STUDY DESIGN: DNA was extracted from neonatal blood spots collected after birth from 143 extremely preterm infants born 1991-1992 in Victoria, Australia and used to determined DNA methylation (DNAm). A DNAm based gestational age was determined using our previously published method. The residual of DNAm gestational age and clinically estimated gestational age (referred to as "gestational age acceleration") was used as a measure to assess developmental maturity. Associations between gestational age acceleration and respiratory interventions and morbidities were determined. RESULTS: Infants with higher gestational age acceleration were less likely to receive surfactant (P = .009) or postnatal corticosteroids (P = .008), had fewer days of assisted ventilation (P = .01), and had less BPD (P = .02). Respiratory measures are known to correlate with gestational age; however, models comparing each with clinically estimated gestational age were improved by the addition of the gestational age acceleration measure in the model. CONCLUSIONS: Gestational age acceleration correlates with respiratory interventions and outcomes of extremely preterm babies. Surfactant and postnatal corticosteroid use, assisted ventilation days, and BPD rates were all lower in babies who were epigenetically more mature than their obstetrically estimated gestational age. This suggests that gestational age acceleration is a clinically relevant metric of developmental maturity.

Problematic alcohol use associates with sodium channel and clathrin linker 1 (SCLT1) in trauma-exposed populations.

Excessive alcohol use is extremely prevalent in the United States, particularly among trauma-exposed individuals. While several studies have examined genetic influences on alcohol use and related problems, this has not been studied in the context of trauma-exposed populations. We report results from a genome-wide association study of alcohol consumption and associated problems as measured by the alcohol use disorders identification test (AUDIT) in a trauma-exposed cohort. Results indicate a genome-wide significant association between total AUDIT score and rs1433375 [N = 1036, P = 2.61 × 10-8 (dominant model), P = 7.76 × 10-8 (additive model)], an intergenic single-nucleotide polymorphism located 323 kb upstream of the sodium channel and clathrin linker 1 (SCLT1) at 4q28. rs1433375 was also significant in a meta-analysis of two similar, but independent, cohorts (N = 1394, P = 0.0004), the Marine Resiliency Study and Systems Biology PTSD Biomarkers Consortium. Functional analysis indicated that rs1433375 was associated with SCLT1 gene expression and cortical-cerebellar functional connectivity measured via resting state functional magnetic resonance imaging. Together, findings suggest a role for sodium channel regulation and cerebellar functioning in alcohol use behavior. Identifying mechanisms underlying risk for problematic alcohol use in trauma-exposed populations is critical for future treatment and prevention efforts.

Across-Platform Imputation of DNA Methylation Levels Incorporating Nonlocal Information Using Penalized Functional Regression.

DNA methylation is a key epigenetic mark involved in both normal development and disease progression. Recent advances in high-throughput technologies have enabled genome-wide profiling of DNA methylation. However, DNA methylation profiling often employs different designs and platforms with varying resolution, which hinders joint analysis of methylation data from multiple platforms. In this study, we propose a penalized functional regression model to impute missing methylation data. By incorporating functional predictors, our model utilizes information from nonlocal probes to improve imputation quality. Here, we compared the performance of our functional model to linear regression and the best single probe surrogate in real data and via simulations. Specifically, we applied different imputation approaches to an acute myeloid leukemia dataset consisting of 194 samples and our method showed higher imputation accuracy, manifested, for example, by a 94% relative increase in information content and up to 86% more CpG sites passing post-imputation filtering. Our simulated association study further demonstrated that our method substantially improves the statistical power to identify trait-associated methylation loci. These findings indicate that the penalized functional regression model is a convenient and valuable imputation tool for methylation data, and it can boost statistical power in downstream epigenome-wide association study (EWAS).

Prioritizing individual genetic variants after kernel machine testing using variable selection.

Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach.

Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates.

DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Recent developments in whole genome bisulfite sequencing (WGBS) technology have enabled genome-wide measurements of DNA methylation at single base pair resolution. Many experiments have been conducted to compare DNA methylation profiles under different biological contexts, with the goal of identifying differentially methylated regions (DMRs). Due to the high cost of WGBS experiments, many studies are still conducted without biological replicates. Methods and tools available for analyzing such data are very limited.We develop a statistical method, DSS-single, for detecting DMRs from WGBS data without replicates. We characterize the count data using a rigorous model that accounts for the spatial correlation of methylation levels, sequence depth and biological variation. We demonstrate that using information from neighboring CG sites, biological variation can be estimated accurately even without replicates. DMR detection is then carried out via a Wald test procedure. Simulations demonstrate that DSS-single has greater sensitivity and accuracy than existing methods, and an analysis of H1 versus IMR90 cell lines suggests that it also yields the most biologically meaningful results. DSS-single is implemented in the Bioconductor package DSS.

Common polymorphism in the oxytocin receptor gene (OXTR) is associated with human social recognition skills.

The neuropeptides oxytocin and vasopressin are evolutionarily conserved regulators of social perception and behavior. Evidence is building that they are critically involved in the development of social recognition skills within rodent species, primates, and humans. We investigated whether common polymorphisms in the genes encoding the oxytocin and vasopressin 1a receptors influence social memory for faces. Our sample comprised 198 families, from the United Kingdom and Finland, in whom a single child had been diagnosed with high-functioning autism. Previous research has shown that impaired social perception, characteristic of autism, extends to the first-degree relatives of autistic individuals, implying heritable risk. Assessments of face recognition memory, discrimination of facial emotions, and direction of gaze detection were standardized for age (7-60 y) and sex. A common SNP in the oxytocin receptor (rs237887) was strongly associated with recognition memory in combined probands, parents, and siblings after correction for multiple comparisons. Homozygotes for the ancestral A allele had impairments in the range -0.6 to -1.15 SD scores, irrespective of their diagnostic status. Our findings imply that a critical role for the oxytocin system in social recognition has been conserved across perceptual boundaries through evolution, from olfaction in rodents to visual memory in humans.

Large inverted duplications in the human genome form via a fold-back mechanism.

Inverted duplications are a common type of copy number variation (CNV) in germline and somatic genomes. Large duplications that include many genes can lead to both neurodevelopmental phenotypes in children and gene amplifications in tumors. There are several models for inverted duplication formation, most of which include a dicentric chromosome intermediate followed by breakage-fusion-bridge (BFB) cycles, but the mechanisms that give rise to the inverted dicentric chromosome in most inverted duplications remain unknown. Here we have combined high-resolution array CGH, custom sequence capture, next-generation sequencing, and long-range PCR to analyze the breakpoints of 50 nonrecurrent inverted duplications in patients with intellectual disability, autism, and congenital anomalies. For half of the rearrangements in our study, we sequenced at least one breakpoint junction. Sequence analysis of breakpoint junctions reveals a normal-copy disomic spacer between inverted and non-inverted copies of the duplication. Further, short inverted sequences are present at the boundary of the disomic spacer and the inverted duplication. These data support a mechanism of inverted duplication formation whereby a chromosome with a double-strand break intrastrand pairs with itself to form a "fold-back" intermediate that, after DNA replication, produces a dicentric inverted chromosome with a disomic spacer corresponding to the site of the fold-back loop. This process can lead to inverted duplications adjacent to terminal deletions, inverted duplications juxtaposed to translocations, and inverted duplication ring chromosomes.