Biology subjects

Uddin, M.

Publications and source records attributed to Uddin, M..

27 records · Page 2Linked to original sources

bioRxiv2020

Associations between childhood family emotional health, fronto-limbic grey matter volume, and saliva 5mC in young adulthood

BackgroundPoor family emotional health (FEH) during childhood is prevalent and impactful, and likely confers similar neurodevelopmental risks as other adverse social environments. Pointed FEH study efforts are underdeveloped, and the mechanisms by which poor FEH are biologically embedded are unclear. The current exploratory study examined whether variability in DNA methylation (DNAm) and fronto-limbic grey matter volume may represent pathways through which FEH may become biologically embedded. ResultsSelf-reported childhood FEH was nominally associated with right hemisphere hippocampus (b=10.4, p=0.005), left hemisphere amygdala (b=5.3, p=0.009), and right hemisphere amygdala (b=5.8, p=0.016) volumes. Childhood FEH was also nominally associated with 49 DNAm MEs (prange=3x10-6 to 0.047). After limiting analyses to probes correlated between saliva and brain, saliva-derived DNAm MEs partially mediated the association between FEH and right hippocampal volume (Burlywood ME indirect effect b=-111, p=0.014), and fully mediated the FEH and right amygdala volume relationship (Pink4 ME indirect effect b=-48, p=0.026). Modules were enriched with probes falling in genes with immune, CNS, and metabolic functions. ConclusionsFindings extend work highlighting neurodevelopmental variability associated with adverse social environment exposure during childhood by specifically implicating poor FEH, while informing a mechanism of biological embedding. FEH-associated epigenetic signatures could function as proxies of altered fronto-limbic grey matter volume associated with poor childhood FEH and inform further investigation into primarily affected tissues such as endocrine, immune, and CNS cell types.

genomics↗

bioRxiv2020

Neighborhood environment, social cohesion, and epigenetic aging

Living in adverse neighborhood environments have been linked to increased risk of aging-related diseases and mortality; however, the biological mechanisms explaining this observation remain poorly understood. DNA methylation (DNAm), a proposed biomarker of biological aging responsive to environmental stressors, offers promising insight into molecular pathways. We examined associations of three measures of neighborhood conditions (poverty, quality, and social cohesion) with three different epigenetic clocks (Horvath, Hannum, and Levine) using data from the Detroit Neighborhood Health Study (n=158). Using linear regression models, we evaluated associations in the total sample and stratified by gender and social cohesion. Differential effects by gender were found between men and women. Neighborhood poverty was associated with PhenoAge acceleration among women, but not among men (women: {beta} = 1.4; 95% CI: -0.4, 3.3 vs. men: {beta} = -0.3; 95% CI: -2.2, 1.5) in fully adjusted models. In models stratified on social cohesion, association of neighborhood poverty and quality with accelerated DNAm aging remained elevated for residents living in neighborhoods with lower social cohesion, but were null for those living in neighborhoods with higher social cohesion. Our study suggests that living in adverse neighborhood conditions can speed up epigenetic aging, while positive neighborhood characteristics may buffer effects.

genomics↗

bioRxiv2020

Heterogeneous Mediation Analysis for Causal Inference

DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mechanism of PTSD for African Americans still remains unknown. To fill this gap, in this paper, we investigate how DNAm mediates the effects of traumatic experiences on PTSD symptoms in the Detroit Neighborhood Health Study (DNHS) (2008-2013) which involves primarily African Americans adults. To achieve this, we develop a new mediation analysis approach for high-dimensional potential DNAm mediators. A key novelty of our method is that we consider heterogeneity in mediation effects across sub-populations. Specifically, mediators in different sub-populations could have opposite effects on the outcome, and thus could be difficult to identify under a traditional homogeneous model framework. In contrast, the proposed method can estimate heterogeneous mediation effects and identifies sub-populations in which individuals share similar effects. Simulation studies demonstrate that the proposed method outperforms existing methods for both homogeneous and heterogeneous data. We also present our mediation analysis results of a dataset with 125 participants and more than 450, 000 CpG sites from the DNHS study. The proposed method finds three sub-groups of subjects and identifies DNAm mediators corresponding to genes such as HSP90AA1 and NFATC1 which have been linked to PTSD symptoms in literature. Our finding could be useful in future finer-grained investigation of PTSD mechanism and in the development of new treatments for PTSD.

bioinformatics↗

bioRxiv2020

The Impact of Psychopathology, Social Adversity and Stress-relevant DNAm on Prospective Risk for Post-traumatic Stress: A Machine Learning Approach

BackgroundA range of factors have been identified that contribute to greater incidence, severity, and prolonged course of post-traumatic stress disorder (PTSD), including: comorbid and/or prior psychopathology; social adversity such as low socioeconomic position, perceived discrimination, and isolation; and biological factors such as genomic variation at glucocorticoid receptor regulatory network (GRRN) genes. This complex etiology and clinical course make identification of people at higher risk of PTSD challenging. Here we leverage machine learning (ML) approaches to identify a core set of factors that may together predispose persons to PTSD. MethodsWe used multiple ML approaches to assess the relationship among DNA methylation (DNAm) at GRRN genes, prior psychopathology, social adversity, and prospective risk for PTS severity (PTSS). ResultsML models predicted prospective risk of PTSS with high accuracy. The Gradient Boost approach was the top-performing model with mean absolute error of 0.135, mean square error of 0.047, root mean square error of 0.217, and R2 of 95.29%. Prior PTSS ranked highest in predicting the prospective risk of PTSS, accounting for >88% of the prediction. The top ranked GRRN CpG site was cg05616442, in AKT1, and the top ranked social adversity feature was loneliness. ConclusionMultiple factors including prior PTSS, social adversity, and DNAm play a role in predicting prospective risk of PTSS. ML models identified factors accounting for increased PTSS risk with high accuracy, which may help to target risk factors that reduce the likelihood or course of PTSD, potentially pointing to approaches that can lead to early intervention.

bioinformatics↗

bioRxiv2020

Host transcriptomic profiling of COVID-19 patients with mild, moderate, and severe clinical outcomes

Characterizing key molecular and cellular pathways involved in COVID-19 is essential for disease prognosis and management. We perform shotgun transcriptome sequencing of human RNA obtained from nasopharyngeal swabs of patients with COVID-19, and identify a molecular signature associated with disease severity. Specifically, we identify globally dysregulated immune related pathways, such as cytokine-cytokine receptor signaling, complement and coagulation cascades, JAK-STAT, and TGF-{beta} signaling pathways in all, though to a higher extent in patients with severe symptoms. The excessive release of cytokines and chemokines such as CCL2, CCL22, CXCL9 and CXCL12 and certain interferons and interleukins related genes like IFIH1, IFI44, IFIT1 and IL10 were significantly higher in patients with severe clinical presentation compared to mild and moderate presentations. Moreover, early induction of the TGF-{beta} signaling pathway might be the primary cause of pulmonary fibrosis in patients with severe disease. Differential gene expression analysis identified a small set of regulatory genes that might act as strong predictors of patient outcome. Our data suggest that rapid transcriptome analysis of nasopharyngeal swabs can be a powerful approach to quantify host molecular response and may provide valuable insights into COVID-19 pathophysiology.

genomics↗

bioRxiv2020

Whole genome and phylogenetic analysis of SARS-CoV-2 strains from the index and early patients with COVID-19 in Dubai, United Arab Emirates, 29 January to 18 March 2020

International travel played a significant role in the early global spread of SARS-CoV-2. Understanding transmission patterns from different regions of the world will further inform global dynamics of the pandemic. Using data from Dubai in the United Arab Emirates (UAE), a major international travel hub in the Middle East, we establish SARS-CoV-2 full genome sequences from the index and early COVID-19 patients in the UAE. The genome sequences are analysed in the context of virus introductions, chain of transmissions, and possible links to earlier strains from other regions of the world. Phylogenetic analysis showed multiple spatiotemporal introductions of SARS-CoV-2 into the UAE from Asia, Europe, and the Middle East during the early phase of the pandemic. We also provide evidence for early community-based transmission and catalogue new mutations in SARS-CoV-2 strains in the UAE. Our findings contribute to the understanding of the global transmission network of SARS-CoV-2.

genomics↗

bioRxiv2020

RANDOMIZE: A Web Server for Data Randomization

SummaryDNA methylation microarray data may suffer from batch effects due to improper handling of the samples during the plating process. RANDOMIZE is a web-based application designed to perform randomization of relevant metadata to evenly distribute samples across the factors typically responsible for batch effects in DNA methylation microarrays, such as row, chips and plates. Randomization helps to reduce the likelihood of bias and impact of difference among groups. AvailabilityThe tool is freely available online at https://coph-usf.shinyapps.io/RANDOMIZE/ and can be accessed using any web browser. Sample data and tutorial is also available with the tool. Contactahwani@usf.edu

bioinformatics↗

bioRxiv2019

Meta-analysis of longitudinal epigenome-wide association studies of military cohorts reveals multiple CpG sites associated with post-traumatic stress disorder

BackgroundEpigenetic mechanisms have been suggested to play a role in the development of post-traumatic stress disorder (PTSD). Here, blood-derived DNA methylation data (HumanMethylation450 BeadChip) collected prior to and following combat exposure in three cohorts composed of male military members were combined to assess whether DNA methylation profiles are associated with the development of PTSD.\n\nMethodsA total of 123 cases and 143 trauma-exposed controls were included. The Psychiatric Genomics Consortium (PGC) PTSD EWAS QC pipeline was used on all cohorts, and results were combined using a sample size weighted meta-analysis. We first combined two cohorts in a discovery stage (N=126 and 78), sought targeted replication in the third cohort (N=62) and then performed a meta-analysis of all three datasets.\n\nResultsThe discovery stage identified four CpG sites in which, conditional on pre-deployment DNA methylation, post-deployment DNA methylation was associated with PTSD status after adjustment for multiple comparisons. The most significant CpG (p = 1.0 x 10-08) was located on 5q31 and replicated in the third cohort. When combining all cohorts, this intergenic site remained most significant along with two CpGs located in MAD1L1 and HEXDC. Interestingly, the CpG site of MAD1L1 had an underlying single nucleotide polymorphism (SNP) which was located within the same LD block as a recently identified PTSD-associated SNP. Twelve differential methylated regions (DMRs) were also identified, one of which was located in MAD1L1 and four were situated in the human leukocyte antigen (HLA) region.\n\nConclusionThis study suggests that the development of PTSD is associated with distinct methylation patterns in several genomic positions and regions. Our most prominent finding points to the involvement of MAD1L1 which was previously associated with PTSD.

genetics↗

bioRxiv2019

Methylomic profiles reveal sex-specific shifts in leukocyte composition associated with post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is a debilitating mental disorder precipitated by trauma exposure. However, only some persons exposed to trauma develop PTSD. There are sex differences in risk; twice as many women as men, develop a lifetime diagnosis of PTSD. Methylomic profiles derived from peripheral blood are well-suited for investigating PTSD because DNA methylation (DNAm) encodes individual response to trauma and may play a key role in the immune dysregulation characteristic of PTSD pathophysiology. In the current study, we leveraged recent methodological advances to investigate sex-specific shifts in DNAm-based leukocyte composition that are associated with lifetime PTSD. We estimated leukocyte composition on a combined methylation array dataset (483 participants, [~]450k CpG sites) consisting of two civilian cohorts, the Detroit Neighborhood Health Study and Grady Trauma Project. Sex-stratified Mann-Whitney U test and two-way ANCOVA revealed that lifetime PTSD was associated with a small but significant elevation in monocyte proportions in males, but not in females (Holm-adjusted p-val < 0.05). No difference in monocyte proportions was observed between current and remitted PTSD cases in males, suggesting that this sex-specific peak shift reflects a long-standing trait of lifetime history of PTSD, rather than current state of PTSD. Associations with lifetime PTSD or PTSD status were not observed in any other leukocyte subtype and our finding in monocytes was confirmed using cell estimates based on a different deconvolution algorithm, suggesting that our sex-specific findings are robust across cell estimation approaches. Overall, our main finding of elevated monocyte proportions in males, but not in females with lifetime history of PTSD provides evidence for a sex-specific shift in peripheral blood leukocyte composition that is detectable in methylomic profiles and that reflects long-standing changes associated with PTSD diagnosis.

genomics↗