Search bioRxiv⌕ Search

Biology subjects

Suderman, M.

Publications and source records attributed to Suderman, M..

At least 19 recordsLinked to original sources

The prenatal exposome and genome in predictive modelling of DNA methylation

IntroductionFetal development represents a critical window during which genetic and environmental influences shape lifelong health. DNA methylation (DNAm) is a candidate underlying mechanism. While individual prenatal exposures have been related to DNAm, no studies have investigated the broader prenatal exposome, nor incorporated genetics with the exposome. Here, we integrated the prenatal exposome and genetics as predictors of DNAm at birth. MethodsWe used data from the Dutch Generation R (n=2282) and English Avon Longitudinal Study of Parents and Children (ALSPAC; n=809) cohorts. We performed epigenome-wide elastic net regression, using Generation R for model development/internal validation and ALSPAC for external validation, to predict DNAm at each CpG site. We used three models: Model 1 included 42 prenatal exposures, Model 2 additionally included child sex, gestational age and birth weight, and Model 3 further included meQTLs. ResultsIn Model 1, the prenatal exposome explained on average 0.7% of DNAm variation across 347 validated CpGs (0.1% of tested CpGs). This increased to 40,044 CpGs (10.2%) with 1.3% of variation explained in Model 2, and 91,305 CpGs (23.2%) with 3.0% of variation explained in Model 3. In Model 1, prenatal smoking was the largest predictor, followed by delivery characteristics, among which meconium-stained amniotic fluid was a novel finding. In Model 3, typically both SNPs and multiple prenatal exposures were selected. DiscussionWe find that genomic associations with cord blood DNAm are stronger and more widespread than prenatal exposures, although typically, the prenatal exposome explains additional variation in DNAm beyond genetic influences.

genomics↗

Sex-specific hormone-sensitive regulatory architecture in adolescence as a scaffold for depression vulnerability

Adolescence is a critical developmental period during which sex differences in depression risk emerge, yet the underlying molecular mechanisms remain unclear. Here, we integrated longitudinal transcriptomic, epigenomic, and gene regulatory network analyses to characterize sex-specific regulatory dynamics of the brain across adolescence under normative conditions and elucidate how baseline molecular differences may shape later vulnerability. We observed that immediate early genes exhibited the strongest sex-biased signals, with males and females showing opposing developmental trajectories, suggesting a role in sex-specific stress-responsive programs. Across analyses, a consistent pattern emerged: males showed stronger activity-dependent neuronal signatures, whereas females showed stronger stress- and immune-related signatures. Extending these findings to a disease context using single-nucleus chromatin accessibility data, we identified hormone-responsive regulatory elements enriched in depression-associated regions, with sex- and cell type-specific links to genetic risk. Grounded in established models of sex-specific stress responses, these findings offer a developmental regulatory framework for understanding the differential presentation of, and vulnerability to, depression.

genomics↗

Epigenome-wide association study meta-analysis of wellbeing

Wellbeing is associated with both behavioral phenotypes as well as several key life outcomes, such as health, employment, and coping with stressful events. These phenotypes associated with wellbeing could be potential indicators of differential epigenetic patterns between individuals that differ in their levels of wellbeing. We performed the largest epigenome-wide (EWAS) meta-analysis of wellbeing to date by combining whole blood DNA methylation data (Illumina 450k array) from 13 cohorts from Europe, Australia, and the USA (N = 10,757 participants). After correcting for smoking and BMI, no epigenome-wide significant methylation sites were identified. We tested whether a weighted methylation score (MS) based on leave-one-cohort-out EWAS meta-analysis summary statistics predicted wellbeing in an independent cohort, and whether prediction was significant over and above the polygenic score (PGS) for wellbeing. The MS was associated with wellbeing (variance explained=0.22%, p=0.03) and was no longer significant after adding the polygenic score (PGS; variance explained=0.43%, p=0.0046, MS; variance explained=0.07%, p=0.2842). We further compared DNA methylation levels in 16 pairs of monozygotic twins discordant for wellbeing. These analyses revealed no significant within-pair DNA methylation differences at the top-sites from the meta-analysis or in MS. Our results suggest that larger EWAS meta-analyses with uniform phenotype assessment are required to identify methylation sites associated with wellbeing.

genomics↗

Epigenetic investigation of multifocal small intestinal neuroendocrine tumours reveals accelerated ageing of tumours and epigenetic alteration of metabolic genes

BackgroundSmall intestinal neuroendocrine tumours (SI-NETs) are the most common malignancy of the small intestine and around 50% of patients present in clinic with multifocal disease. Recent investigations into the genomic architecture of multifocal SI-NETs have found evidence that these synchronous primary tumours evolve independently of each other. They also have extremely low mutational burden and few known driver genes, suggesting that epigenetic dysregulation may be driving tumorigenesis. Very little is known about epigenetic gene regulation, metabolism and ageing in these tumours, and how these traits differ across multiple tumours within individual patients. MethodsIn this study, we performed the first investigation of genome-wide DNA methylation in multifocal SI-NETs, assessing multiple primary tumours within each patient (n=79 primary tumours from 14 patients) alongside matched metastatic tumours (n=12) and normal intestinal epithelial tissue (n=9). We assessed multifocal SI-NET differential methylation using a novel method, comparing primary tumours with matched normal epithelial tissue and an enterochromaffin-enriched cell line to enrich for tumour-specific effects. This method reduced the identification of false positive methylation differences driven by cell composition differences between tumour and normal epithelial tissue. We also assessed tumour ageing using epigenetic clocks and applied metabolic predictors in the dataset to assess methylation variation across key metabolic genes. ResultsWe have identified 12,392 tumour-specific differentially methylated positions (Bonferroni corrected p<0.05) which were enriched for neural pathways. The expression levels of the genes associated with top sites were also found to be significantly altered in SI-NETs. Age acceleration was observed across SI-NETs and a variability in epigenetic age of tumours within each patient, which we believe is reflecting the order in which tumours have developed. This is supported by the correlation of age acceleration with somatic mutational count in the tumours. We have identified SI-NET associated alterations to the methylation patterns in key metabolic genes compared to matched normal tissue, which is more pronounced in metastatic tumours and tumours harbouring chromosome 18 loss of heterozygosity, indicating metabolic differences in these tumour subtypes. ConclusionsWe have identified accelerated ageing and changes to regulation of metabolic genes, alongside an epigenetic signature of multifocal SI-NETs. These findings add to our understanding of multifocal SI-NET biology and their molecular differences which may be instrumental in the development of these elusive tumours.

cancer biology↗

What makes clocks tick? Characterizing developmental dynamics of adult epigenetic clock sites

DNA methylation (DNAm) at specific sites can be used to calculate epigenetic clocks, which in adulthood are used as indicators of age(ing). However, little is known about how these clock sites behave during development and what factors influence their variability in early life. This knowledge could be used to optimize healthy aging well before the onset of age-related conditions. Here, we leveraged results from two longitudinal population-based cohorts (N=5,019 samples from 2,348 individuals) to characterize trajectories of adult clock sites from birth to early adulthood. We find that clock sites (i) diverge widely in their developmental trajectories, often showing non-linear change over time; (ii) are substantially more likely than non-clock sites to vary between individuals already from birth, differences that are predictive of DNAm variation at later ages; and (iii) show enrichment for genetic and prenatal environmental exposures, supporting an early-origins perspective to epigenetic aging.

developmental biology↗

An epigenome-wide analysis of DNA methylation, racialized and economic inequities, and air pollution

ImportanceDNA methylation (DNAm) provides a plausible mechanism by which adverse exposures become embodied and contribute to health inequities, due to its role in genome regulation and responsiveness to social and biophysical exposures tied to societal context. However, scant epigenome-wide association studies (EWAS) have included structural and lifecourse measures of exposure, especially in relation to structural discrimination. ObjectiveOur study tests the hypothesis that DNAm is a mechanism by which racial discrimination, economic adversity, and air pollution become biologically embodied. DesignA series of cross-sectional EWAS, conducted in My Body My Story (MBMS, biological specimens collected 2008-2010, DNAm assayed in 2021); and the Multi Ethnic Study of Atherosclerosis (MESA; biological specimens collected 2010-2012, DNAm assayed in 2012-2013); using new georeferenced social exposure data for both studies (generated in 2022). SettingMBMS was recruited from four community health centers in Boston; MESA was recruited from four field sites in: Baltimore, MD; Forsyth County, NC; New York City, NY; and St. Paul, MN. ParticipantsTwo population-based samples of US-born Black non-Hispanic (Black NH), white non-Hispanic (white NH), and Hispanic individuals (MBMS; n=224 Black NH and 69 white NH) and (MESA; n=229 Black NH, n=555 white NH and n=191 Hispanic). ExposuresEight social exposures encompassing racial discrimination, economic adversity, and air pollution. Main outcomeGenome-wide changes in DNAm, as measured using the Illumina EPIC BeadChip (MBMS; using frozen blood spots) and Illumina 450k BeadChip (MESA; using purified monocytes). Our hypothesis was formulated after data collection. ResultsWe observed the strongest associations with traffic-related air pollution (measured via black carbon and nitrogen oxides exposure), with evidence from both studies suggesting that air pollution exposure may induce epigenetic changes related to inflammatory processes. We also found suggestive associations of DNAm variation with measures of structural racial discrimination (e.g., for Black NH participants, born in a Jim Crow state; adult exposure to racialized economic residential segregation) situated in genes with plausible links to effects on health. Conclusions and RelevanceOverall, this work suggests that DNAm is a biological mechanism through which structural racism and air pollution become embodied and may lead to health inequities. Key pointsO_ST_ABSQuestionC_ST_ABSCould DNAm be a mechanism by which adversity becomes embodied? FindingsTraffic-related air pollution exposure may induce epigenetic changes related to inflammatory processes and there are suggestive associations with measures of structural racism MeaningDNAm may be a biological mechanism through which structural racism and air pollution become biologically embodied

bioinformatics↗

Differential Chromatin Architecture and Risk Variants in Deep Layer Excitatory Neurons and Grey Matter Microglia Contribute to Major Depressive Disorder

Major depressive disorder (MDD) associated genetic variants reside primarily in the non-coding, regulatory genome. Here we investigate genome-wide regulatory differences and putative gene-regulatory effects of disease risk-variants by examining chromatin accessibility combined with single-cell gene-expression profiles in over 200,000 cells from the dorsolateral prefrontal cortex (DLPFC) of 84 individuals with MDD and neurotypical controls. MDD-associated accessibility alterations were prominent in deep-layer excitatory neurons characterized by transcription factor (TF) motif accessibility and binding of nuclear receptor (NR)4A2, an activity-dependent TF responsive to pathological stress. The same neurons were significantly enriched for MDD-associated genetic variation disrupting cis-regulatory sites and TF binding associated with genes involved in synaptic communication. Furthermore, a grey matter microglial cluster exhibited differentially closed chromatin in MDD affecting binding sites bound by TFs known to regulate immune homeostasis. In summary, our study points to specific cell types and regulatory mechanisms whereby genetic variation may increase predisposition to MDD.

genomics↗

Genetic impacts on DNA methylation help elucidate regulatory genomic processes

Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2,358 blood samples from three UK cohorts, with replication. Methylation levels at 34.2% of CpGs were affected by SNPs, and 98% of effects were cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both meQTL SNPs and CpGs with meQTLs were overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identified 1,520 co-localisations across 1,325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such ICOSLG (inflammatory bowel disease), and USP1 and DOCK7 (total cholesterol levels). Enrichment analysis of meQTLs and integration with expression QTLs gave insights into mechanisms underlying cis-meQTLs, for example through disruption of transcription factor binding sites for CTCF and SMC3, and trans-meQTLs, for example through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites. Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. A results database and viewer are available online.

genomics↗

Fathers' preconception smoking and offspring DNA methylation: A two generation study

RationaleExperimental studies suggest that exposures may impact respiratory health across generations via epigenetic changes transmitted specifically through male germ cells. Studies in humans are however limited. We aim to identify epigenetic marks in offspring associated with fathers preconception smoking. MethodsWe conducted epigenome-wide association studies (EWAS) in the RHINESSA cohort on fathers any preconception smoking (N=875 offspring) and fathers pubertal onset smoking <15 years (N=304), using Infinium MethylationEPIC Beadchip arrays, adjusting for offspring age, maternal smoking and personal smoking. EWAS of maternal and offspring personal smoking were performed for replication. ResultsFathers smoking commencing preconception was associated with methylation of blood DNA in offspring at two Cytosine-phosphate-Guanine sites (CpGs) (False Discovery Rate (FDR) <0.05) in PRR5 and CENPP. Fathers pubertal onset smoking was associated with 19 CpGs (FDR <0.05) mapped to 14 genes (TLR9, DNTT, FAM53B, NCAPG2, PSTPIP2, MBIP, C2orf39, NTRK2, DNAJC14, CDO1, PRAP1, TPCN1, IRS1 and CSF1R). These differentially methylated sites were hypermethylated and associated with promoter regions capable of gene silencing. Some of these sites were associated with offspring outcomes in this cohort including ever-asthma (NTRK2), ever-wheezing (DNAJC14, TPCN1), weight (FAM53B, NTRK2) and BMI (FAM53B, NTRK2) (P< 0.05). Pathway analysis showed enrichment for gene ontology pathways including regulation of gene expression, inflammation and innate immune responses. ConclusionFathers preconception smoking, particularly in puberty, is associated with offspring DNA methylation, providing evidence that epigenetic mechanisms may underly epidemiological observations that pubertal paternal smoking increases risk of offspring asthma, low lung function and obesity.

genomics↗

Cell type specific transcriptomic differences in depression show similar patterns between males and females but implicate distinct cell types and genes

Major depressive disorder (MDD) is a common, heterogenous, and potentially serious psychiatric illness. Diverse brain cell types have been implicated in MDD etiology. Significant sexual differences exist in MDD clinical presentation and outcome, and recent evidence suggests different molecular bases for male and female MDD. We evaluated over 160,000 nuclei from 71 female and male donors, leveraging new and pre-existing single-nucleus RNA-sequencing data from the dorsolateral prefrontal cortex. Cell type specific transcriptome-wide threshold-free MDD-associated gene expression patterns were similar between the sexes, but significant differentially expressed genes (DEGs) diverged. Among 7 broad cell types and 41 clusters evaluated, microglia and parvalbumin interneurons contributed the most DEGs in females, while deep layer excitatory neurons, astrocytes, and oligodendrocyte precursors were the major contributors in males. Further, the Mic1 cluster with 38% of female DEGs and the ExN10_L46 cluster with 53% of male DEGs, stood out in the meta-analysis of both sexes.

neuroscience↗

DNA co-methylation has a stable structure and is related to specific aspects of genome regulation

DNA methylation (DNAm) is influenced by genetic and environmental factors, and can be used to understand interindividual variability in genomic regulation. Co-methylation between DNAm sites is a known phenomenon, but the architecture of relationships between the approximately 450,000 (450k) sites commonly measured in epidemiological studies has not been described. We investigate whether interindividual co-methylation structure amongst the 450k sites changes with age, whether it differs between UK-born White (n=849, 910, 921 and 424) and Pakistani ancestry (n=439) individuals, and how it relates to genome regulation. We find stability between birth and adolescence, across cohorts, and between two ethnic groups. Highly correlated DNAm sites in close proximity are heritable, but these relationships are weakly influenced by nearby genetic variants, and are enriched for transcription factor (TF) binding sites related to regulation of short RNAs transcribed by RNA polymerase III. Highly correlated sites that are distant, or on different chromosomes (in trans), are driven by common and unique environmental factors, with methylation at these sites less likely to be driven by genotype. Trans co-methylated DNAm sites are enriched for multiple TF binding sites and for inter-chromosomal chromatin contact sites, suggesting DNA co-methylation of distant sites may relate to long-range cooperative TF interactions. We conclude that DNA co-methylation has a stable structure from birth to adolescence, and between UK-born White and Pakistani individuals. This stable structure might have implications for future design and interpretation of epigenetic studies. We hypothesise that co-methylation may have roles in genome regulation in humans, including 3D chromatin architecture.

bioinformatics↗

Highly divergent white-tailed deer SARS-CoV-2 with potential deer-to-human transmission

Wildlife reservoirs of SARS-CoV-2 may enable viral adaptation and spillback from animals to humans. In North America, there is evidence of unsustained spillover of SARS-CoV-2 from humans to white-tailed deer (Odocoileus virginianus), but no evidence of transmission from deer to humans. Through a biosurveillance program in Ontario, Canada we identified a new and highly divergent lineage of SARS-CoV-2 in white-tailed deer. This lineage is the most divergent SARS-CoV-2 lineage identified to date, with 76 consensus mutations (including 37 previously associated with non-human animal hosts) and signatures of considerable evolution and transmission within wildlife. Phylogenetic analysis also revealed an epidemiologically linked human case. Together, our findings represent the first clear evidence of sustained evolution of SARS-CoV-2 in white-tailed deer and of deer-to-human transmission.

microbiology↗

The impact of low input DNA on the reliability of DNA methylation as measured by the Illumina Infinium MethylationEPIC BeadChip

BackgroundDNA methylation (DNAm) is commonly assayed using the Illumina Infinium MethylationEPIC BeadChip, but there is currently little published evidence to define the lower limits of the amount of DNA that can be used whilst preserving data quality. Such evidence is valuable for analyses utilising precious or limited DNA sources. Materials and methodsWe use a single pooled sample of DNA in quadruplicate at three dilutions to define replicability and noise, and an independent population dataset of 328 individuals (from a community-based study including US-born non-Hispanic Black and white persons) to assess the impact of total DNA input on the quality of data generated using the Illumina Infinium MethylationEPIC BeadChip. ResultsData are less reliable and more noisy as DNA input decreases to 40ng, with clear reductions in data quality; however samples with a total input as low as 40ng pass standard quality control tests, and we observe little evidence that low input DNA obscures the associations between DNAm and two phenotypes, age and smoking status. ConclusionsDNA input as low as 40ng can be used with the Illumina Infinium MethylationEPIC BeadChip, provided quality checks and sensitivity analyses are undertaken.

bioinformatics↗

Characterizing the human methylome across the life course: findings from eight UK-based studies

Variation in DNA methylation (DNAm) is associated with multiple biological processes that track growth and development, ageing and age-related diseases. However, there is little understanding of what constitutes typical patterns of DNAm variation and how these patterns change across the life course. In this study, we synthesised a map of the human methylome across the life course, focussing on changes in variability and mean DNAm. Harmonizing DNAm datasets across eight longitudinal and cross-sectional UK-based studies, we meta-analysed n=13,215 blood samples from n=7,037 unique individuals from birth to 98 years of age. Changes in CpG-specific variability and means were described across the life course using a meta-regression framework. CpG-specific associations of variability or mean DNAm in relation to the likelihood of association with 100 traits linked to environmental exposures, health and disease were tested within and across ten developmental age bins across the life course. Age was linked to DNAm variability at 29,212 CpG sites. On average, we observed a 1.26 fold increase in DNAm variability per year across the life course. 33,730 CpGs displayed changes in mean DNAm, with 64% of these loci showing decreases in DNAm over time. CpG sites linked to traits were in general more variable across the life course. Our study provides, for the first time, a map of the human methylome across the life course, which is publicly accessible through a searchable online database. This resource allows researchers to query CpG-specific trajectories from birth to old age and link these to health and disease.

genetics↗

Grandmaternal smoking during pregnancy is associated with differential DNA methylation in their grandchildren

The idea that information can be transmitted to subsequent generation(s) by epigenetic means has been studied for decades but remains controversial in humans. Epidemiological studies have established that grandparental exposures are associated with health outcomes in their grandchildren, often with sex-specific effects; however the mechanism of transmission is still unclear. We conducted Epigenome Wide Association Studies (EWAS) to test whether grandmaternal smoking during pregnancy is associated with altered DNA methylation (DNAm) in their adolescent grandchildren. We used data from a birth cohort, with discovery and replication datasets of 1225 and 708 individuals (respectively), aged 15-17 years, and tested replication in the same individuals at birth and 7 years. We show for the first time that DNAm at a small number of loci is associated with grandmaternal smoking in humans, and their locations in the genome suggest hypotheses of transmission. We observe and replicate sex-specific associations at two sites on the X chromosome, one located in an imprinting control region and both within transcription factor binding sites (TFBSs). In fact, we observe enrichment for TFBSs among the CpG sites with the strongest associations, suggesting that TFBSs may be a mechanism by which grandmaternal exposures influence offspring DNA methylation. There is limited evidence that these associations appear at earlier timepoints, so effects are not static throughout development. The implication of this work is that effects of smoking during pregnancy may induce DNAm changes in later generations and that these changes are often sex-specific, in line with observational associations.

genomics↗

DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N=15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha=1.2x10-7; Bonferroni correction). In cord blood samples of 2,425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r=0.74, p=0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripherl blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range=3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

genetics↗

Epigenome-wide change and variation in DNA methylation from birth to late adolescence

DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5,019 blood samples collected at multiple time-points from birth to late adolescence from 2,348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for nonlinear change and inter-individual variation in nonlinear trajectories was somewhat less common (11% and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. By contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often nonlinear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.

genomics↗

A robust mean and variance test with application to epigenome-wide association studies

Most studies of high-dimensional phenotypes focus on assessing differences in mean levels (location) of the phenotype by exposure, e.g. epigenome-wide association studies of DNA methylation at CpG sites. However, identifying effects on the variability (scale) of these outcomes, and combining tests of mean and variability (location-and-scale), could provide additional insights into biological mechanisms. Here, we review variability tests, specifically an extended (for continuous exposures) version of the Brown-Forsythe test, and develop a novel joint location-and-scale score test for both categorical and continuous exposures (JLSsc). The Brown-Forsythe test and JLSsc performed well in comparison to alternative approaches in simulations. These approaches identified >7500 CpG sites that were associated with either mean or variability with gender or gestational age in cord blood methylation in ARIES (Accessible Resource for Integrated Studies). The Brown-Forsythe test and JLSsc are robust tests that can be used to detect associations not solely driven by a mean effect.

bioinformatics↗