Biology subjects

Flowers, E.

Publications and source records attributed to Flowers, E..

6 recordsLinked to original sources

bioRxiv2026

Co-Expressed MicroRNAs Identify Potential Mechanisms Underlying Risk for Multimorbid Depression and Type 2 Diabetes in Midlife Women

BackgroundWomen are disproportionately affected by multimorbid depression and type 2 diabetes (T2D), with prevalence peaking during midlife (40-64 years), a biologically dynamic timeframe due to changes associated with reproductive aging. Yet, phenotypic and mechanistic factors contributing to midlife womens disproportionate risk for co-occurrence remain poorly defined. We previously identified co-expressed microRNAs (miRs) in midlife women with prediabetes that increased odds of assignment to a high psychometabolic risk phenotype. Here, we extend these findings by characterizing putative mRNA targets of these co-expressed miRs and pathways overrepresented among mRNAs, providing insights into potential mechanisms underlying psychometabolic risk in midlife women. MethodsThis study included baseline data from midlife women (ages 40-64 years) with prediabetes who participated in the Diabetes Prevention Program (DPP) (n = 603). In silico analyses were performed using miRTarBase to identify mRNAs regulated by 3 or more of the miRs that most prominently loaded a principal component previously identified to increase odds of assignment to a high psychometabolic risk phenotype defined in this sample. Pathway enrichment analysis was conducted to assess for overrepresentation of KEGG pathways among predicted mRNA targets. To enhance interpretability, pathways were thematically clustered based on their evidenced role in human physiology. ResultsWe identified a total of 13 mRNAs targeted by co-expressed miRs associated with increased odds of assignment to a high psychometabolic risk phenotype in midlife women with prediabetes. Pathway enrichment analysis revealed a total of 71 KEGG pathways with overrepresentation of identified mRNA targets. Four overarching biological themes emerged, reflecting involvement of metabolic, inflammatory, endocrine, and stress/biological weathering-related processes. ConclusionsExperimentally validated mRNA targets related biological pathways were identified, providing multisystem insights into potential mechanisms underlying risk for multimorbid depression and T2D in midlife women. Findings offer mechanistic targets for experimental validation and future precision health research focused on this high-risk population. Overall, this work positions the utility of miRs as context-sensitive biomarkers in the characterization of risk for complex, multimorbid conditions in women during biologically dynamic timeframes.

genomics↗

bioRxiv2025

Perinatal Shifts in Fecal-Derived Metabolites and Associations with Postpartum Depression

IntroductionResearch on maternal depression is largely limited to static, blood-derived biomarkers in the postpartum period and mechanistic targets derived from populations outside the physiological contexts of pregnancy and postpartum, resulting in critical gaps in understanding context-specific mechanisms underlying this debilitating condition. ObjectivesTo examine temporal shifts in the maternal gut metabolome and associations between pregnancy-specific shifts and postpartum depression (PPD). MethodsWe applied untargeted metabolomics (UPLC-MS/MS) to fecal samples collected from participants (N= 25) enrolled in the Maternal and Infant NutriTion (MINT) study. Random forest analysis was used to identify key pathways and metabolites contributing to temporal shifts. Fold change analysis and paired t-tests were used to quantify the magnitude and significance of metabolite changes. Associations between pregnancy-specific changes and PPD (Edinburgh Postnatal Depression Scale at 6 weeks) were identified using Pearsons correlation. ResultsLipid, amino acid, and xenobiotic metabolism emerged as core pathways driving temporal changes in the maternal gut metabolome. The most pronounced shifts occurred from 35 weeks gestation to postpartum, with 55 metabolites significantly altered compared to 24 from 24-to 35 weeks gestation and 26 from 24 weeks gestation to postpartum. Of the 29 metabolites associated with PPD; 68.9% were metabolic intermediates, primarily involved in lipid and amino acid metabolism (58.6%). ConclusionsThis study provides some of the first evidence of temporal shifts in the maternal gut metabolome and associations with PPD, highlighting the importance of lipid and amino acid metabolism and laying the groundwork for future multi-omics research.

systems biology↗

bioRxiv2024

Prediabetes Phenotype Clusters in the Diabetes Prevention Program Study

ObjectiveThe purpose of this study was to apply clustering methods to identify and characterize prediabetes phenotypes and their relationships with treatment arm and type 2 diabetes (T2D) outcomes in the Diabetes Prevention Program (DPP), and to compare the utility of additional clustering measures in phenotype characterization and T2D risk stratification. Research Design and MethodsThis was a secondary analysis of data from a subset of participants (n=994) from the previously completed Diabetes Prevention Program trial. Unsupervised k-means clustering analysis was applied to derive the optimal number of clusters of participants based on common clinical risk factors alone or common risk factors plus more comprehensive measures of glucose tolerance and body composition. ResultsFive clusters were derived from common clinical characteristics and the addition of comprehensive measures of glucose tolerance and body composition. Within each modeling approach, participants show significantly different levels of risk factors. The clinical only model showed higher accuracy for time to T2D, however the more comprehensive models further differentiated a metabolically health overweight phenotype. For both models, the greatest differentiation in determining time to T2D was in the metformin arm of the trial. ConclusionsData driven clustering of patients with prediabetes allows for identification of prediabetes phenotypes at greater risk for disease progression and responses to risk reduction interventions. Further investigation into phenotypic differences in treatment response could enable better personalization of prediabetes and T2D prevention and treatment choices.

genomics↗

bioRxiv2024

Longitudinal Associations Between MicroRNAs and Weight in the Diabetes Prevention Program

OBJECTIVECirculating microRNAs show cross-sectional associations with overweight and obesity. Few studies provided data to differentiate between a snapshot perspective on these associations versus how microRNAs characterize prodromal risk from disease pathology and complications. This study assessed longitudinal relationships between circulating microRNAs and weight at multiple time-points in the Diabetes Prevention Program trial. RESEARCH DESIGN AND METHODSA subset of participants (n=150) from the Diabetes Prevention Program were included. MicroRNAs were measured from banked plasma using a Fireplex Assay. We used generalized linear mixed models to evaluate relationships between microRNAs and changes in weight at baseline, year-1, and year-2. Logistic regression was used to evaluate whether microRNAs at baseline were associated with weight change after 2 years. RESULTSIn fully adjusted models that included relevant covariates, seven miRs (i.e., miR-126, miR-15a, miR-192, miR-23a, and miR-27a) were statistically associated with weight over 2 years. MiR-197 and miR-320a remained significant after adjustment for multiple comparisons. Baseline levels of let-7f, miR-17, and miR-320c were significantly associated with 3% weight loss after 2 years in fully adjusted models. DISCUSSIONThis study provided evidence for longitudinal relationships between circulating microRNAs and weight. Because microRNAs characterize the combined effects of genetic determinants and responses to behavioral determinants, they may provide insights about the etiology of overweight and obesity in the context or risk for common, complex diseases. Additional studies are needed to validate the potential genes and biological pathways that might be targeted by these microRNA biomarkers and have mechanistic implications for weight loss and disease prevention.

genomics↗

bioRxiv2019

The cohesin loader NIPBL interacts with pre-ribosomal RNA and treacle to regulate ribosomal RNA synthesis

NIPBL is an essential loader of cohesin to mediate sister chromatid cohesion and chromatin loop organization. NIPBL mutations cause Cornelia de Lange Syndrome. How NIPBLs genomic localization is specified is not fully understood. We found that NIPBL localizes to the nucleolus in an RNA-dependent manner and binds directly to ribosomal RNA (rRNA). We identified two RNA binding domains in NIPBL in vitro, both of which are required for efficient rRNA binding in vivo. NIPBL binds to ribosomal DNA (rDNA) in an RNA-stimulated manner, recruits PAF1 and promotes pre-rRNA transcription. Stress that inhibits rRNA synthesis displaces NIPBL from the nucleolus and rDNA. Interestingly, treacle, mutated in Treacher Collins syndrome, tightly binds to and recruits NIPBL to the nucleolus, nucleolar organizer regions, and the stress-induced nucleolar cap. The results reveal that a subpopulation of NIPBL is recruited to the nucleolus through its interaction with RNA and treacle and regulates pre-rRNA transcription.

molecular biology↗

bioRxiv2017

The Effect Of Nipped-B-Like (Nipbl) Haploinsufficiency On Genome-Wide Cohesin Binding And Target Gene Expression: Modeling Cornelia de Lange Syndrome

Cornelia de Lange Syndrome (CdLS) is a multisystem developmental disorder frequently associated with heterozygous loss-of-function mutations of Nipped-B-like (NIPBL), the human homolog of Drosophila Nipped-B. NIPBL loads cohesin onto chromatin. Cohesin mediates sister chromatid cohesion important for mitosis, but is also increasingly recognized as a regulator of gene expression. In CdLS patient cells and animal models, the presence of multiple gene expression changes with little or no sister chromatid cohesion defect suggests that disruption of gene regulation underlies this disorder. However, the effect of NIPBL haploinsufficiency on cohesin binding, and how this relates to the clinical presentation of CdLS, has not been fully investigated. Nipbl haploinsufficiency causes CdLS-like phenotype in mice. We examined genome-wide cohesin binding and its relationship to gene expression using mouse embryonic fibroblasts (MEFs) from Nipbl +/- mice that recapitulate the CdLS phenotype. We found a global decrease in cohesin binding, including at CCCTC-binding factor (CTCF) binding sites and repeat regions. Cohesin-bound genes were found to be enriched for histone H3 lysine 4 trimethylation (H3K4me3) at their promoters; were disproportionately downregulated in Nipbl mutant MEFs; and displayed evidence of reduced promoter-enhancer interaction. The results suggest that gene activation is the primary cohesin function sensitive to Nipbl reduction. Over 50% of significantly dysregulated transcripts in mutant MEFs come from cohesin target genes, including genes involved in adipogenesis that have been implicated in contributing to the CdLS phenotype. Thus, decreased cohesin binding at the gene regions directly contributes to disease-specific expression changes. Taken together, our Nipbl haploinsufficiency model allows us to analyze the dosage effect of cohesin loading on CdLS development.

developmental biology↗