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Saxena, R.

Publications and source records attributed to Saxena, R..

At least 37 records · Page 2Linked to original sources

CIRCUST: a novel methodology for reconstruction of temporal order of molecular rhythms; validation and application towards a human circadian gene expression atlas

AO_SCPLOWBSTRACTC_SCPLOWThe circadian system drives near-24-h oscillations in behaviors and biological processes. The underlying core molecular clock regulates the expression of other genes, and it has been shown that the expression of more than 50 percent of genes in mammals displays 24-h rhythmic patterns, with the specific genes that cycle varying from one tissue to another. Determining rhythmic gene expression patterns in human tissues sampled as single timepoints has several challenges, including the reconstruction of temporal order of highly noisy data. Previous methodologies have attempted to address these challenges in one or a small number of tissues for which clock gene evolutionary conservation is assumed to be preserved. Here we introduce CIRCUST, a novel CIRCular-robUST methodology for analyzing molecular rhythms, that relies on circular statistics, is robust against noise, and requires fewer assumptions than existing methodologies. Next, we validated the method against two controlled experiments in which sampling times were known, and finally, CIRCUST was applied to 34 tissues from the Genotype-Tissue Expression (GTEx) dataset with the aim towards building a comprehensive daily rhythm gene expression atlas in humans. The validation and application shown here indicate that CIRCUST provides a flexible framework to formulate and solve the issues related to the analysis of molecular rhythms in human tissues. CIRCUST methodology is publicly available at https://github.com/yolandalago/CIRCUST/.

bioinformatics↗

Genome sequencing and de novo and reference-based genome assemblies of Bos indicus breeds

Bos indicus is a domestic cattle species with many indigenous breeds found in India and is important for dairy, draught work, and other household activities. Distinct phenotypic differences are observed among the breeds of this species; however, their whole genome sequences were not available. Therefore, in this study, we performed the whole genome sequencing using Illumina short-read technology to construct draft genome assemblies of four B. indicus breeds; Ongole, Kasargod Dwarf, Kasargod Kapila, and Vechur, of which Vechur is known as the smallest cow of the world. We also report the first de novo genome assemblies of these native B. indicus breeds. Further, we constructed the 18S rRNA marker gene sequences of these B. indicus breeds, which were not yet known. Genomic analysis helped to identify the distinct bovine phenotypic characteristics-related and other biological process-related genes in this species compared to B. taurus, and to gain comparative genomic insights between the dwarf and non-dwarf breeds of this species.

genomics↗

A transformer model for predicting cognitive impairment from sleep

Sleep disturbances are known to be aggravated with normal aging. Additionally, sleep disruptions have a potentially bidirectional causal relationship with dementia due to neurodegenerative diseases like Alzheimers disease. Predictive techniques that can automatically detect cognitive impairment from an individuals sleep data have broad clinical and biological significance. Here, we present a deep learning approach based on a transformer architecture to predict cognitive status from sleep electroencephalography (EEG) data. This work uses data from N = 1, 502 subjects from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Our transformer model achieves 70.22% accuracy at the binary classification task for distinguishing cognitively normal and impaired subjects based on their sleep EEG. Our method outperforms traditional feature handcrafting, which has an overall accuracy of 57.61% for the same task. We use a sparse regression model to understand and interpret the information captured by each learned feature from our transformer model. To our knowledge, this is the first effort to use deep learning to predict cognitive impairment from sleep metrics.

neuroscience↗

Updated Variant Curation Expert Panel Criteria and Pathogenicity Classifications for 251 Variants for RYR1-related Malignant Hyperthermia Susceptibility

The ClinGen malignant hyperthermia susceptibility (MHS) variant curation expert panel specified the ACMG/AMP criteria for RYR1-related MHS and a pilot analysis of 84 variants was published. We have now classified an additional 251 variants for RYR1-related MHS according to current ClinGen standards and updated the criteria where necessary. Criterion PS4 was modified such that individuals with multiple RYR1 variants classified as pathogenic (P), likely pathogenic (LP) or variant of uncertain significance (VUS) were not considered as providing evidence for pathogenicity. Critera PS1 and PM5 were revised to consider LP variants at the same amino acid residue as providing evidence for pathogenicity at reduced strength. Finally, PM1 was revised such that if PS1 or PM5 are used PM1, if applicable, should be downgraded to supporting. Of the 251 RYR1 variants, 42 were classified as P/LP, 16 as B/LB, and 193 as VUS. The primary driver of 176 VUS classifications was insufficient evidence supporting pathogenicity, rather than evidence against pathogenicity. Functional data supporting PS3/BS3 was identified for only 13 variants. Based on the posterior probabilities of pathogenicity and variant frequencies in gnomAD, we estimated the prevalence of individuals with RYR1-related MHS pathogenic variants to be between 1/300 and 1/1,075, considerably higher than current estimates. We have updated ACMG/AMP criteria for RYR1-related MHS and classified 251 variants. We suggest that prioritization of functional studies is needed to resolve the large number of VUS classifications and allow for appropriate risk assessment. RYR1-related MHS pathogenic variants are likely to be more common than currently appreciated.

genetics↗

Multi-ancestry genome-wide analysis identifies common genetic variants for self-reported sleep duration and shared genetic effects

Both short and long sleep duration are associated with increased risk of chronic diseases, but the genetic determinants of sleep duration are largely unknown outside of European populations. Here we report transferability of a polygenic score of 78 European ancestry sleep duration SNPs to an African (n=7,288; p=0.003), a South Asian (n=7,485; p=0.025), and a Japanese (n=13,618; p=6x10-4) cohort, but not to a cohort of Hispanic/Latino (n- XXX; p=0.71) participants. Furthermore, in a pan-ancestry (N = 483,235) meta-analysis of genome-wide association studies (GWAS) for habitual sleep duration, 5 novel and 68 known loci are associated with genome-wide significance. For the novel loci, sleep duration signals colocalize with expression-QTLs for PRR12 and COG5 in brain tissues, and pleiotropic associations are observed with cardiovascular and neuropsychiatric traits. Overall, our results suggest that the genetic basis of sleep duration is at least partially shared across diverse ancestry groups.

genomics↗

Draft genome assembly data of Anoxybacillus sp. strain MB8 isolated from Tattapani hot springs, India

Discovery of novel thermophiles has shown promising applications in the field of biotechnology. Due to their thermal stability, they can survive the harsh processes in the industries, which make them important to be characterized and studied. Members of Anoxybacillus are alkaline tolerant thermophiles and have been extensively isolated from manure, dairy-processed plants, and geothermal hot springs. This article reports the assembled data of an aerobic bacterium Anoxybacillus sp. strain MB8, isolated from the Tattapani hot springs in Central India, where the 16S rRNA gene shares an identity of 97% (99% coverage) with Anoxybacillus kamchatkensis strain G10. The de novo assembly and annotation performed on the genome of Anoxybacillus sp. strain MB8 comprises of 2,898,780 bp (in 190 contigs) with a GC content of 41.8% and includes 2,976 protein-coding genes,1 rRNA operon, 73 tRNAs, 1 tm-RNA and 10 CRISPR arrays. The predicted protein-coding genes have been classified into 21 eggNOG categories. The KEGG Automated Annotation Server (KAAS) analysis indicated the presence of assimilatory sulfate reduction pathway, nitrate reducing pathway, and genes for glycoside hydrolases (GHs) and glycoside transferase (GTs). GHs and GTs hold widespread applications, in the baking and food industry for bread manufacturing, and in the paper, detergent and cosmetic industry. Hence, Anoxybacillus sp. strain MB8 holds the potential to be screened and characterized for such commercially relevant enzymes. Specifications Table O_TBL View this table: org.highwire.dtl.DTLVardef@46be2org.highwire.dtl.DTLVardef@46fbe2org.highwire.dtl.DTLVardef@42cc37org.highwire.dtl.DTLVardef@16d5912org.highwire.dtl.DTLVardef@1f2bcdc_HPS_FORMAT_FIGEXP M_TBL C_TBL Values of DataO_LIThe Anoxybacillus sp. strain MB8 genome assembly data provides insights into functional potential of thermophilic enzymes of this thermotolerant microbe. C_LIO_LIThe presence of genes for Glycoside Hydrolase (GHs) like alpha-amylase, pullulanase, neopullulanase, alpha-glucosidase, beta-fructofuranosidase etc. and genes for Glycosyl Transferase (GTs) like sucrose synthase, maltodextrin phosphorylase, starch synthase, and glycogen phosphorylase were identified, which hold strong industrial values. C_LIO_LIThe taxonomic annotation of Anoxybacillus sp. strain MB8 using different approaches indicates that the closest relatives were Anoxybacillus gonensis NZ CP012152T (96.86% ANI) and Anoxybacillus kamchatkensis G10 NZ CP025535 (96.83% ANI) obtained from. The strain MB8 most likely belongs to the same subspecies of Anoxybacillus gonensis NZ CP012152T. C_LI

genomics↗

Single cell transcriptomic analysis reveals cellular diversity of murine esophageal epithelium and age-associated mitochondrial dysfunction

Stratified squamous epithelium of the esophagus is comprised of basal keratinocytes that execute a terminal differentiation program in overlying suprabasal and superficial cell layers. Although morphologic progression coupled with expression of specific molecular markers has been characterized along the esophageal epithelial differentiation gradient, the molecular heterogeneity within the cell types along this trajectory has yet to be classified at the level of single cell resolution. To explore the molecular characteristics of esophageal keratinocytes along the squamous differentiation continuum, we performed single cell RNA-Sequencing transcriptomic profiling of 7,972 cells from murine esophageal epithelial sheets. We identified 8 distinct cell clusters in esophageal epithelium, unveiling an unexpected level of diversity, particularly among basal cells. We further mapped the cellular pathways and lineage trajectories within basal, suprabasal, and superficial clusters as well as within the heterogeneous basal cell populations, providing a comprehensive molecular view of esophageal epithelial cells in the context of squamous differentiation. Finally, we explored the impact of tissue aging upon esophageal epithelial cell clusters and demonstrated that mitochondrial dysfunction is a feature of aging in normal esophageal epithelium. These studies provide an unparalleled molecular perspective on murine esophageal keratinocytes that will serve as a valuable resource for dissecting cell type-specific roles in esophageal biology under conditions of homeostasis, aging, and tissue pathology.

molecular biology↗

Variant Curation Expert Panel Recommendations for RYR1 Pathogenicity Assertions in Malignant Hyperthermia Susceptibility

PurposePrevention of malignant hyperthermia (MH) requires an understanding of RYR1 variant pathogenicity to assess the risk of exposure to triggering agents. Personalized medicine, especially secondary findings and eventually genomic screening, will contribute toward this goal. MethodsWe specified ACMG/AMP criteria for variant interpretation for RYR1 and MH. Proposed rules were piloted on 84 variants. We applied quantitative evidence calibration for several criteria using likelihood ratios based on the Bayesian framework. ResultsSeven ACMG/AMP criteria were adopted without changes, ten were adopted with RYR1-specific modifications, and nine were dropped. The in silico (PP3 and BP4) and hot spot criteria (PM1) were evaluated quantitatively. REVEL gave an OR of 23:1 for PP3 and 16:1 for BP4 using trichotomized cut-offs of >0.85 (pathogenic) and <0.5 (benign). The PM1 hotspot criterion had an OR of 24:1. PP3 and PM1 were implemented at moderate strength. Applying the revised ACMG criteria to 44 recognized MH variants, 30 were assessed as pathogenic, 12 as likely pathogenic, and two as VUS. ConclusionCuration of these variants will facilitate interpretation of RYR1/MH genomic testing results, which is especially important for secondary findings analyses. Our approach to quantitatively calibrating criteria are generalizable to other variant curation expert panels.

genetics↗

Risk of preeclampsia in patients with genetic predisposition to common medical conditions: a case-control study

ObjectiveTo assess whether women with a genetic predisposition to medical conditions known to increase preeclampsia risk have an increased risk of preeclampsia in pregnancy. DesignCase-control study. Setting and populationPreeclampsia cases (n=498) and controls (n=1864) of European ancestry from 5 US sites genotyped on a cardiovascular gene-centric array. MethodsSignificant single nucleotide polymorphisms (SNPs) from 21 traits in 7 disease categories (cardiovascular, inflammatory/autoimmune, insulin resistance, liver, obesity, renal, thrombophilia) with published genome-wide association studies (GWAS) were used to create a genetic instrument for each trait. Multivariable logistic regression was used to test the association of each continuous, scaled genetic instrument with preeclampsia. Odds of preeclampsia were compared across quartiles of the genetic instrument and evaluated for significance using a test for trend. Main Outcome Measurespreeclampsia. ResultsAn increasing burden of risk alleles for elevated diastolic blood pressure (DBP) and increased body mass index (BMI) were associated with an increased risk of preeclampsia (DBP: overall OR 1.11 (1.01-1.21), p=0.025; BMI: OR 1.10 (1.00-1.20), p=0.042), while risk alleles associated with elevated alkaline phosphatase (ALP) were protective (OR 0.89 (0.82-0.97), p=0.008), driven primarily by pleiotropic effects of variants in the FADS gene region. The effect of DBP genetic loci was even greater in early-onset (<34 weeks) preeclampsia cases (OR 1.30 (1.08-1.56), p=0.005). For all other traits, the genetic instrument was not robustly associated with preeclampsia risk. ConclusionsThese results suggest that the underlying genetic architecture of preeclampsia is shared with other disorders, specifically hypertension and obesity. TWEETABLE ABSTRACTGenetic predisposition to increased diastolic blood pressure and obesity increases the risk of preeclampsia.

genetics↗

Nightmares share strong genetic risk with sleep and psychiatric disorders

Nightmares are vivid, extended and extremely dysphoric dreams that awaken the dreamer. Twin studies indicate that nightmare frequency has a heritability between 36 and 51% providing evidence for genetic factors underlying predisposition to nightmares. Furthermore, while cross-sectional epidemiological findings suggest that heavy alcohol usage, traumatic experiences and psychiatric diseases associate with nightmares, the causal relationships between these conditions and nightmares have remained unknown. To examine the biological mechanisms behind nightmares, we performed a genome-wide association study in 28,596 individuals from Finland and the United States. We identified individual genetic variants that predispose to nightmares near MYOF (rs701873, p=2.18e-8) and PTPRJ (rs11039471,p=3.7e-8), a gene previously associated with sleep duration. We found a strong genetic correlation between the frequency of nightmares and traits related to personality and psychiatric disorders; neuroticism (rg=0.59, p=8e-7), post-traumatic stress disorder (PTSD) (rg=0.58, p=0.004) as well as major depressive disorder (rg=0.68, p=7e-4), and sleep traits; and daytime sleepiness (rg=0.62, p=1e-6) and insomnia (rg=0.50, p=1.87e-5). Analysis of directionality using mendelian randomization showed a significant effect from feelings of fed-up (p=0.001), nervous (p=0.004) and miserableness (p=0.0045) to nightmares with no evidence of pleiotropy and no evidence of nightmares predisposing to psychiatric or psychological problems. Our findings suggest that nightmares are caused by unique genetic risk factors, and here we identify the first individual genetic associations. In addition, a substantial effect on nightmares is conveyed through underlying psychological and sleep problems, with psychological problems being causal for nightmares.

genetics↗

Whole-Genome Association Analyses of Sleep-disordered Breathing Phenotypes in the NHLBI TOPMed Program

Sleep-disordered breathing (SDB) is a common disorder associated with significant morbidity. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program we report the first whole-genome sequence analysis of SDB. We identified 4 rare gene-based associations with SDB traits in 7,988 individuals of diverse ancestry and 4 replicated common variant associations with inclusion of additional samples (n=13,257). We identified a multi-ethnic set-based rare-variant association (p = 3.48 x 10-8) on chromosome X with ARMCX3. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Results highlighted associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis and HIF1A-mediated hypoxic response.

genetics↗

Omnibus Inverse Normal Transformation Based Association Test Improves Power in Genome-Wide Association Studies of Quantitative Traits

SO_SCPLOWUMMARYC_SCPLOWQuantitative traits analyzed in Genome-Wide Association Studies (GWAS) are often non-normally distributed. For such traits, association tests based on standard linear regression are subject to reduced power and inflated type I error in finite samples. Applying the rank-based Inverse Normal Transformation (INT) to non-normally distributed traits has become common practice in GWAS. However, the different variations on INT-based association testing have not been formally defined, and guidance is lacking on when to use which approach. In this paper, we formally define and systematically compare the direct (D-INT) and indirect (I-INT) INT-based association tests. We discuss their assumptions, underlying generative models, and connections. We demonstrate that the relative powers of D-INT and I-INT depend on the underlying data generating process. Since neither approach is uniformly most powerful, we combine them into an adaptive omnibus test (O-INT). O-INT is robust to model misspecification, protects the type I error, and is well powered against a wide range of non-normally distributed traits. Extensive simulations were conducted to examine the finite sample operating characteristics of these tests. Our results demonstrate that, for non-normally distributed traits, INT-based tests outperform the standard untransformed association test (UAT), both in terms of power and type I error rate control. We apply the proposed methods to GWAS of spirometry traits in the UK Biobank. O-INT has been implemented in the R package RNOmni, which is available on CRAN.

genetics↗

Multi-trait genome-wide association meta-analysis of dietary intake identifies new loci and genetic and functional links with metabolic traits

Dietary intake, a major contributor to the global obesity epidemic1-5, is a complex phenotype partially affected by innate physiological processes.6-11 However, previous genome-wide association studies (GWAS) have only implicated a few loci in variability of dietary composition.12-14 Here, we present a multi-trait genome-wide association meta-analysis of inter-individual variation in dietary intake in 283,119 European-ancestry participants from UK Biobank and CHARGE consortium, and identify 96 genome-wide significant loci. Dietary intake signals map to different brain tissues and are enriched for genes expressed in {beta}1-tanycytes and serotonergic and GABAergic neurons. We also find enrichment of biological pathways related to neurogenesis. Integration of cell-line and brain-specific epigenomic annotations identify 15 additional loci. Clustering of genome-wide significant variants yields three main genetic clusters with distinct associations with obesity and type 2 diabetes (T2D). Overall, these results enhance biological understanding of dietary composition, highlight neural mechanisms, and support functional follow-up experiments.

genetics↗

Is disrupted sleep a risk factor for Alzheimers disease? Evidence from a two-sample Mendelian randomization analysis

INTRODUCTIONIt is established that Alzheimers disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.\n\nMETHODSMendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness) on AD risk.\n\nRESULTSOverall, there was little evidence that sleep traits affect the risk of AD. There was some evidence to suggest that self-reported daytime napping was associated with lower AD risk (odds ratio [OR]: 0.70, 95% confidence interval [CI]: 0.50 to 0.99). Some other sleep traits (accelerometer-measured eveningness and sleep duration, and self-reported daytime sleepiness) had ORs for AD risk of a similar magnitude to daytime napping, but were less precisely estimated.\n\nDISCUSSONOur findings provide tentative evidence that daytime napping may reduce AD risk. However, findings should be replicated using independent samples.

epidemiology↗

Comparative analysis of corrected tiger genome provides clues to their neuronal evolution

The availability of completed and draft genome assemblies of tiger, leopard, and other felids provides an opportunity to gain comparative insights on their unique evolutionary adaptations. However, genome-wide comparative analyses are very sensitive to errors in genome sequences and thus require accurate genomic assemblies for reliable evolutionary insights. In this study, while analyzing the tiger genome, we found almost one million erroneous substitutions in the coding and non-coding region of the genome affecting 4,472 genes, hence, biasing the current understanding of tiger evolution. Moreover, these errors produced several misleading observations in previous studies. Thus, to gain insights into the tiger evolution, we corrected the erroneous bases in the genome assembly and gene set of tiger, which was also validated by resequencing of a Bengal tiger genome and transcriptome. A comprehensive evolutionary analysis was performed using 10,920 orthologs from nine mammalian species including the corrected gene sets of tiger and leopard, and using five different methods at three hierarchical levels i.e. felids, Panthera, and tiger. The unique genetic changes in tiger revealed that the genes showing the signatures of adaptation in tiger were enriched in development and neuronal functioning. Specifically, the genes belonging to Notch signalling pathway, which is among the most conserved pathways involved in embryonic and neuronal development, were found to be significantly diverged in tiger in comparison to the other mammals. Our findings suggest the role of adaptive evolution in neuronal functions and development processes, which correlates well with the presence of exceptional traits such as sensory perception, strong neuro-muscular coordination, and hypercarnivorous behavior in tiger.

genomics↗

Investigating causal relationships between sleep traits and risk of breast cancer: a Mendelian randomization study

ObjectiveTo examine whether sleep traits have a causal effect on risk of breast cancer.\n\nDesignMultivariable regression, one- and two-sample Mendelian randomization.\n\nSettingThe UK Biobank prospective cohort study and the Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.\n\nParticipants156,848 women in the multivariable regression and one-sample Mendelian randomization analysis in UK Biobank (7,784 with a breast cancer diagnosis) and 122,977 breast cancer cases and 105,974 controls from BCAC in the two-sample Mendelian randomization analysis.\n\nExposuresSelf-reported chronotype (morning/evening preference), insomnia symptoms and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits.\n\nMain outcome measuresBreast cancer (prevalent and incident cases in UK Biobank, prevalent cases only in BCAC).\n\nResultsIn multivariable regression analysis using data on breast cancer incidence in UK Biobank, morning preference was inversely associated with breast cancer (HR 0.95, 95% CI 0.93, 0.98 per category increase) while there was little evidence for an association with sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated sleep duration and 57 SNPs associated with insomnia symptoms, one-sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (HR 0.85, 95% 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two-sample MR using data from BCAC supported findings for a protective effect of morning preference (OR 0.88, 95% CI 0.82, 0.93 per category increase) and adverse effect of increased sleep duration (OR 1.19, 95% CI 1.02, 1.39 per hour increase) on breast cancer (both estrogen receptor positive and negative), while there was inconsistent evidence for insomnia symptoms. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.\n\nConclusionsWe found consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of sleep duration on breast cancer risk.

epidemiology↗

Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups

Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with substantial functional deficits. We identified 42 loci for self-reported EDS in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirmed the aggregate effect of a genetic risk score of 42 SNPs on EDS in independent Scandinavian cohorts and on other sleep disorders (restless leg syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). Strong genetic correlations were also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing. EDS variants clustered into two predominant composite phenotypes - sleep propensity and sleep fragmentation - with the former showing stronger evidence for enriched expression in central nervous system tissues, suggesting two unique mechanistic pathways. Mendelian randomization analysis indicated that higher BMI is causally associated with EDS risk, but EDS does not appear to causally influence BMI.

genomics↗

Epigenome-wide association analysis of daytime sleepiness in the Multi-Ethnic Study of Atherosclerosis reveals African-American specific associations

Study ObjectivesExcessive daytime sleepiness (EDS) is a consequence of inadequate sleep, or of a primary disorder of sleep-wake control. Population variability in prevalence of EDS and susceptibility to EDS are likely due to genetic and biological factors as well as social and environmental influences. Epigenetic modifications (such as DNA methylation-DNAm) are potential influences on a range of health outcomes. Here, we explored the association between DNAm and daytime sleepiness quantified by the Epworth Sleepiness Scale (ESS).\n\nMethodsWe performed multi-ethnic and ethnic-specific epigenome-wide association studies for DNAm and ESS in 619 individuals from the Multi-Ethnic Study of Atherosclerosis. Replication was assessed in the Cardiovascular Health Study (CHS). Genetic variants in genes proximal to ESS-associated DNAm were analyzed to identify methylation quantitative trait loci and followed with replication of genotype-sleepiness associations in the UK Biobank.\n\nResults61 methylation sites were associated with ESS (FDR [&le;] 0.1) in African Americans only, including an association in KCTD5, a gene strongly implicated in sleep. One association (cg26130090) replicated in CHS African Americans (p-value 0.0004). We identified a sleepiness-associated methylation site in the gene RAI1, a gene associated with sleep and circadian phenotypes. In a follow-up analysis, a genetic variant within RAI1 associated with both DNAm and sleepiness score. The variants association with sleepiness was replicated in the UK Biobank.\n\nConclusionsOur analysis identified methylation sites in multiple genes that may be implicated in EDS. These sleepiness-methylation associations were specific to African Americans. Future work is needed to identify mechanisms driving ancestry-specific methylation effects.\n\nStatement of SignificanceExcessive daytime sleepiness is associated with negative health outcomes such as reduction in quality of life, increased workplace accidents, and cardiovascular mortality. There are race/ethnic disparities in excessive daytime sleepiness, however, the environmental and biological mechanisms for these differences are not yet understood. We performed an association analysis of DNA methylation, measured in monocytes, and daytime sleepiness within a racially diverse study population. We detected numerous DNA methylation markers associated with daytime sleepiness in African Americans, but not in European and Hispanic Americans. Future work is required to elucidate the pathways between DNA methylation, sleepiness, and related behavioral/environmental exposures.

genomics↗