Biology subjects

Suderman, M.

Publications and source records attributed to Suderman, M..

7 recordsLinked to original sources

bioRxiv2018

Single-nucleus RNA sequencing shows convergent evidence from different cell types for altered synaptic plasticity in major depressive disorder.

Major depressive disorder (MDD) is a complex illness that involves the interaction of different brain systems, pathways, and cell types. Past molecular studies of MDD relied on cellular homogenates of post-mortem brain tissue, making it impossible to determine gene expression changes within individual cells. Using single-cell transcriptomics, we examined almost 80,000 nuclei from the dorsolateral prefrontal cortex of individuals with MDD and healthy controls. Our analyses identified 26 distinct cellular clusters, and over 60% of these showed transcriptional differences between groups. Specifically, 96 genes were differentially expressed, the majority of which were downregulated. Convergent evidence from our analyses, including gene expression, differential correlation, and gene ontology implicated dysregulation of synaptic plasticity in the etiopathogenesis of MDD. Our results show that this high-resolution approach can reveal previously undetectable changes in specific cell types in the context of complex phenotypes and heterogeneous tissues.

neuroscience↗

bioRxiv2018

Candidate SNP analyses integrated with mRNA expression and hormone levels reveal influence on mammographic density and breast cancer risk

Introduction Introduction Materials and methods Results Discussion Globaltest Conclusion Competing interests Authors contributions Reference List Mammographic density (MD) is a well-documented risk factor for breast cancer[1-9], and thus a promising target for early detection of the disease. Based on mammographic results, the breast is given a percent density (PDEN) score ranging from 0-100% with 0 being the least dense (primarily adipose tissue). It is estimated that the risk of developing breast cancer is four to six times higher in women with an MD score of at least 75% [2,9] and that one-third of breast cancers occur in patients with PDEN scores of at least 50% [2]. MD is ...

genomics↗

bioRxiv2018

Identification of loci where DNA methylation potentially mediate genetic risk of type 1 diabetes

The risk of Type 1 Diabetes (T1D) comprises both genetic and environmental components. We investigated whether genetic susceptibility to T1D could be mediated by changes in DNA methylation, an epigenetic mechanism that potentially plays a role in autoimmune diabetes. Using data from a non-diabetic population comprising blood samples taken at birth (n=844), childhood (n=911) and adolescence (n=907), we evaluated the associations between 65 top GWAS single nucleotide polymorphisms (SNPs) and genome-wide DNA methylation levels. We identified 159 proximal SNP-cytosine phosphate guanine (CpG) pairs (cis), and 7 distal SNP-CpG associations (trans) at birth, childhood, and adolescence. There was also a systematic enrichment for methylation related SNPs to be associated with T1D across the genome, after controlling for genomic characteristics of the SNPs, implying that methylation could either be on the causal pathway to T1D or a non-causal biomarker. Combining the principles of Mendelian Randomization and genetic colocalization analysis, we provided evidence that at 5 loci, ITGB3BP, AFF3, PTPN2, CTSH and CTLA4, DNA methylation is potentially on the causal pathway to T1D.

genomics↗

bioRxiv2017

Epigenome-Wide Association Study Of Asthma And Wheeze In Childhood And Adolescence

Asthma heritability has only been partially explained by genetic variants and is known to be sensitive to environmental factors, implicating epigenetic modifications such as DNA methylation in its pathogenesis.\n\nUsing data collected in the Avon Longitudinal Study of Parents and Children (ALSPAC), we assessed associations of asthma and wheeze with DNA methylation at 7.5 years and 16.5 years, at over 450,000 CpG sites in DNA from the peripheral blood of approx. 1000 participants. We used Mendelian randomization (MR), a method of causal inference that uses genetic variants as instrumental variables, to infer the direction of association between DNA methylation and asthma.\n\nWe identified 302 CpGs associated with current asthma status (FDR-adjusted P-value <0.05) and 445 with current wheeze status at 7.5 years, with substantial overlap between the two. Genes annotated to the 302 associated CpGs were enriched for pathways related to movement of cellular/subcellular components, locomotion, interleukin-4 production and eosinophil migration. All associations attenuated when adjusted for eosinophil and neutrophil cell count estimates. At 16.5 years, two sites were associated with current asthma after adjustment for cell counts. The CpGs mapped to the AP2A2 and IL5RA genes, with a -2.32 [95% CI -1.47,-3.18] and -2.49 [95% CI -1.56,-3.43] change in percentage methylation in asthma cases respectively. Two-sample bi-directional MR indicated a causal effect of asthma on DNA methylation at several CpG sites at 7.5 years. However, associations did not persist after adjustment for multiple testing. There was no evidence of a causal effect of asthma on DNA methylation at either of the two CpG sites at 16.5 years.\n\nThe majority of observed associations are driven by higher eosinophil cell counts in asthma cases, acting as an intermediate phenotype, with important implications for future studies of DNA methylation in atopic diseases.

epidemiology↗

bioRxiv2017

Meffil: efficient normalisation and analysis of very large DNA methylation samples

AbstractO_ST_ABSBackgroundC_ST_ABSTechnological advances in high throughput DNA methylation microarrays have allowed dramatic growth of a new branch of epigenetic epidemiology. DNA methylation datasets are growing ever larger in terms of the number of samples profiled, the extent of genome coverage, and the number of studies being meta-analysed. Novel computational solutions are required to efficiently handle these data.\n\nMethodsWe have developed meffil, an R package designed to quality control, normalize and perform epigenome-wide association studies (EWAS) efficiently on large samples of Illumina Infinium HumanMethylation450 and MethylationEPIC BeadChip microarrays. We tested meffil by applying it to 6000 450k microarrays generated from blood collected for two different datasets, Accessible Resource for Integrative Epigenomic Studies (ARIES) and The Genetics of Overweight Young Adults (GOYA) study.\n\nResultsA complete reimplementation of functional normalization minimizes computational memory requirements to 5% of that required by other R packages, without increasing running time. Incorporating fixed and random effects alongside functional normalization, and automated estimation of functional normalisation parameters reduces technical variation in DNA methylation levels, thus reducing false positive associations and improving power. We also demonstrate that the ability to normalize datasets distributed across physically different locations without sharing any biologically-based individual-level data may reduce heterogeneity in meta-analyses of epigenome-wide association studies. However, we show that when batch is perfectly confounded with cases and controls functional normalization is unable to prevent spurious associations.\n\nConclusionsmeffil is available online (https://github.com/perishky/meffil/) along with tutorials covering typical use cases.

bioinformatics↗

bioRxiv2017

DNA Methylation As A Marker For Prenatal Smoke Exposure In Adults

Prenatal cigarette smoke is an environmental stressor that has a profound effect on DNA methylation in the exposed offspring. We have previously shown that some of these effects persist throughout childhood and into adolescence. Of interest is whether these signals persist into adulthood.\n\nWe conducted an analysis to investigate associations between reported maternal smoking in pregnancy and DNA methylation in peripheral blood of women in the Avon Longitudinal Study of Parents and Children (ALSPAC) (n=754; mean age 30 years). We observed associations at 15 CpG sites in 11 gene regions, MYO1G, FRMD4A, CYP1A1, CNTNAP2, ARL4C, AHRR, TIFAB, MDM4, AX748264, DRD1, FTO (FDR < 5%). All but two of these CpG sites have previously been identified in relation to prenatal smoke exposure in the offspring at birth and the majority showed persistent hypermethylation among the offspring of smokers.\n\nWe confirmed that most of these associations were not driven by own smoking and that they were still present 18 years later (N = 656; mean age 48 years). In addition, we replicated findings of a persistent methylation signal related to prenatal smoke exposure in peripheral blood among men in the ALSPAC cohort (N = 230; mean age 53 years). For both participant groups, there was a strong signal of association above that expected by chance at CpG sites previously associated with prenatal smoke exposure in newborns (Wilcoxon rank sum p-value < 2.2 x 10-4). Furthermore, we found that a prenatal smoking score, derived by combining methylation values at these CpG sites, could predict whether the mothers of the ALSPAC women smoked during pregnancy with an AUC 0.69 (95% 0.67, 0.73).

epidemiology↗

bioRxiv2017

Sex-associated autosomal DNA methylation differences are wide-spread and stablethroughout childhood

Almost all species show sexual discordance in many traits and diseases. DNA methylation is known to contribute to these differences through well-established mechanisms including X-inactivation in females, imprinting and parent-of-origin effects. Here we investigate sex discordance in DNA methylation throughout childhood in a sample of 700 individuals from the Avon Longitudinal Study of Parents and Children. We show that autosomal sex-discordant methylation is widespread, affecting approximately 12,000 CpG sites at any given age, and stable; at least 8,500 sites are consistently different across all time points and a large proportion discordant in both the fetal and adult brain cortices. Just over 1,000 methylation differences change from birth to late adolescence, 90% of these between birth and around age seven. Sexually discordant CpG sites are enriched in genomic loci containing androgen but not estrogen targets and in genes involved in tissue development but not housekeeping functions. A methylation-derived sex score capturing the variance was calculated at each time point and found to be highly correlated between time points. This score is nominally associated with sex hormone levels in childhood as well as some phenotypes previously linked to sex hormone levels. These findings suggest that sex-discordant autosomal DNA methylation is widespread throughout the genome, likely due to the first androgen exposures in utero. It is then stably maintained from birth to late adolescence. Methylation variation at sex-discordant sites within the sexes, as summarized by the methylation sex score, likely reflects in utero androgen exposure which is relevant to human health.\n\nSignificance StatementAlthough we know that sex hormones are critical for establishing sexual discordance, less is known about how this discordance is achieved and maintained. Here we present evidence for widespread differences in DNA methylation between male and female children. We show that most of these differences are established prenatally, likely due to the first androgen exposures in utero, and then stably maintained throughout childhood, despite extreme fluctuations in the levels of these very same hormones. Our results support a role for DNA methylation as a means for recording and maintaining the effects of exposure to sex hormones and thus to better understand sexual variation and how it is driven by the prenatal environment.

epidemiology↗