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Lussier, A. A.

Publications and source records attributed to Lussier, A. A..

3 recordsLinked to original sources

Acute Ethanol Exposure Induces Stage-Specific Bioenergetic, Mitochondrial and Neurodevelopmental Transcriptional Remodeling in Human Forebrain Progenitors

Prenatal alcohol exposure (PAE) is associated with long-term neurodevelopmental risk, yet how neuronal progenitor metabolism responds to alcohol across developmental stages remains unclear. Here, we integrated brain-isoform-focused analysis of public datasets with targeted transcriptional, translational, and functional mitochondrial assessments in human iPSC-derived cortical progenitor models representing distinct bioenergetic states. Re-analysis of prior PAE studies revealed broad metabolic gene downregulation in embryonic systems, whereas neurodevelopmental models showed limited and non-coherent transcriptional signatures. In vitro, acute ethanol exposure (AEE) induced stage-dependent transcriptional remodeling in iPSC-derived neuronal progenitor cells. Early progenitors exhibited selective upregulation of mitochondrial-associated transcripts alongside increased neuronal lineage markers. In contrast, late progenitors showed broader increases in glycolytic, lipid, and mitochondrial gene expression. Despite these transcriptional changes, mitochondrial ATP production and mitochondrial protein abundance remained unchanged in both models with altered dynamics being restricted to late progenitors. These findings indicate that ethanol exposure is associated with developmental stage-dependent neuronal remodeling of bioenergetic genes. Measurements of mitochondrial-neural frameworks after AEE showed no major alterations in either model. Overall, our results reveal a dissociation between transcriptional, translational, and functional bioenergetic outputs in models of early human neurodevelopment and highlight that transcriptional alterations of mitochondria and cellular bioenergetics under AEE should be interpreted in the context of developmental stage rather than in isolation as evidence of energetic dysfunction.

neuroscience↗

Identification of Dynamic Genetic Influences on DNA Methylation from Birth to Adulthood

Whether and how genetic regulation of DNA methylation (DNAm) change across the lifespan remains unclear. Here, we map age-dependent methylation quantitative trait loci (longitudinal mQTLs) using linear mixed models applied to repeated blood DNAm measures from birth, childhood, adolescence and adulthood in the Avon Longitudinal Study of Parents and Children. We identify 2,210 longitudinal mQTLs (2,393 SNP-CpG pairs; 7.3% trans) and observe consistent genotype-by-age effects in two independent cohorts of diverse ancestries (Pearsons r = 0.85 in the Generation R Study; r = 0.56 in the Drakenstein Child Health Study). Longitudinal mQTLs show increasing effects with age at half of loci and associations with multiple phenotypes. CpGs with longitudinal mQTLs are more heritable and enriched in regulatory elements and pathways related to multicellular organism development and cell adhesion. These results chart dynamic genetic influences on the human methylome and provide a novel perspective on epigenetic regulation.

genomics↗

Updates to data versions and analytic methods influence the reproducibility of results from epigenome-wide association studies

IntroductionBiomedical research has grown increasingly cooperative, with several large consortia compiling and sharing epigenomic data. Since data are typically preprocessed by consortia prior to distribution, the implementation of new pipelines can lead to different versions of the same dataset. Analytic frameworks also constantly evolve to incorporate cutting-edge methods and shifting best practices. However, it remains unknown how differences in data and analytic versions alter the results of epigenome-wide analyses, which has broad implications for the replicability of epigenetic associations. Thus, we assessed the impact of these changes using a subsample of the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. MethodsWe analyzed two versions of DNA methylation data, processed using separate preprocessing and analytic pipelines, to examine associations between childhood adversity and prenatal smoking exposure on DNA methylation at age 7. We performed two sets of analyses: (1) epigenome-wide association studies (EWAS); (2) Structured Life Course Modeling Approach (SLCMA), a two-stage method that models time-dependent effects. We also compared results from the SLCMA using more recent methodological recommendations. ResultsDifferences between ALSPAC data versions impacted both EWAS and SLCMA analyses, yielding different sets of associations at conventional p-value thresholds. However, the magnitude and direction of associations was generally consistent between data versions, regardless of significance thresholds. Updating the SLCMA analytic version similarly altered top associations, but time-dependent effects remained concordant. ConclusionsChanges to data and analytic versions influenced the results of epigenome-wide studies, particularly when using p-value thresholds as reference points for successful replication and stability.

genetics↗