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Frosi, G.

Publications and source records attributed to Frosi, G..

5 recordsLinked to original sources

EpiATLAS - a reference for human epigenomic research

The sequence of the human genome provides a foundation for understanding cellular processes in health and disease1. The organisation of this primary genetic information into cell-specific structure and function is critical to understanding the cell type-specific interpretation and execution of the genome. Epigenetic processes are essential for packaging and higher-level functional organisation of the genome, and changes therein are increasingly recognised as contributors to human disease. Building on primary data generated by multinational consortia, the International Human Epigenome Consortium2 (IHEC) has uniformly processed a collection of more than 2000 comprehensive human reference epigenomes, collectively referred to as EpiATLAS. This effort involved the development of standardised molecular and bioinformatics protocols, metadata models, and analytical tools to manage, integrate, display, and share vast amounts of epigenomic data. This includes the creation of a publicly available Epigenome Reference Registry, which provides a system for accessing protected human subject datasets and facilitates open searching of de-identified samples and experimental data. The integrated EpiATLAS ecosystem and its comprehensive human reference epigenome maps provide an unprecedented resource for the biosciences, expanding the annotated epigenomic landscape while uncovering previously unappreciated relationships among regulatory layers and revealing how epigenetic inputs underpin fundamental cellular functions and disease associations.

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↗

A multimodal characterization of the human uncinate fasciculus

The uncinate fasciculus (UF) is a hook-shaped long-range association white matter tract that serves to bidirectionally transmit information between the anterior temporal lobe and the orbitofrontal cortex. Neuroimaging studies have suggested that changes in UF microstructure are involved in the neurobiological sequalae of childhood abuse (CA). Given that the UF is not present in rodents, it is vastly understudied with no cellular and molecular information available. To this end, we aimed to perform a multimodal characterization of the UF between individuals diagnosed with depression who died by suicide with (DS-CA) and without a history of severe CA (DS) and psychiatrically healthy individuals (CTRL). Fresh frozen UF tissue was obtained from the Douglas Bell-Canada Brain Bank, with phenotypic information collected via psychological autopsy. Immunohistochemistry with PDGFR and NogoA was used to label oligodendrocyte precursor cell (OPC) and oligodendrocyte (OL), respectively, and stereology was performed to ascertain cell density and soma volume. Single nucleus RNA sequencing (snRNAseq) was used to generate a transcriptomic survey of the cell types found in the UF. Finally, spectral focusing Coherent Anti-Stokes Raman Scattering (sf-CARS) microscopy was employed in tandem with a custom AxonDeepSeg segmentation model to measure axon diameter, myelin thickness, and g-ratio. No group differences were observed in histology or ultrastructure metrics, but nearly 50 differentially expressed genes (DEG) were identified between groups. Interestingly NECTIN3, the top DEG downregulated in OL1 and OL3 of DS-CA, is a computationally predicted target of the microRNA MIR646, the host gene of which was significantly downregulated in multiple cell types in DS-CA. Age-associated changes were pronounced and observed in all modalities, including an age-related increase in OL density, extensive changes in glial gene expression, as well as decreases in axon diameter and g-ratio. This study serves as a foundational resource on the molecular and cellular properties of the human UF. Our results suggest that observable myelin-related traces of depression or CA are limited in the UF and highlights the need for future research on the cellular and molecular properties of white matter tracts during aging.

neuroscience↗

A glucocorticoid-responsive polygenic signature in the anterior cingulate cortex moderates the association of early-life adversity and vulnerability for depression

Stress exposure is a major risk factor for psychopathology, yet how stress mediators shape long-term psychiatric vulnerability in humans remains unclear. Glucocorticoids, central effectors of the stress response, regulate gene expression through tissue-specific transcriptional programs, suggesting that glucocorticoid-responsive networks may shape sensitivity to adversity. Using RNA-sequencing following chronic glucocorticoid exposure in a non-human primate model, we identified a gene co-expression network specific to the anterior cingulate cortex (ACC) that was highly preserved across human post-mortem brain datasets relevant to depression. We derived an expression-based polygenic score (ePGS) reflecting genetic variation in network activity and tested its interaction with adversity in the UK Biobank. The ACC-specific glucocorticoid-responsive ePGS moderated the association between adversity and depressive symptoms in adult females, with the strongest effects for early-life adversity. Network genes were enriched for neurodevelopmental processes and showed stronger co-expression during childhood, highlighting a developmentally sensitive, region-specific mechanism linking stress exposure to depression risk.

neuroscience↗

Leveraging the largest harmonized epigenomic data collection for metadata prediction validated and augmented over 350,000 public epigenomic datasets

Epigenomic data found in public databases often suffer from issues of non-standardization and incompleteness in their associated metadata. There are currently no automated approaches to validate or correct missing or inaccurate information listed in databases. To tackle this challenge, we harnessed the extensive harmonized data and metadata provided by the EpiATLAS project of the International Human Epigenome Consortium (IHEC) to train EpiClass, a suite of machine learning classifiers that can predict key metadata ([~]98% accuracy), including experimental assay, donor sex, biospecimen and sample cancer status. The development of these classifiers enabled the identification of a few mislabeled and low-quality datasets in the EpiATLAS project, while also completing with high-confidence most of the missing metadata. These classifiers were also validated on ENCODE datasets absent from the initial training, then applied to assess more than 350,000 human ChIP-Seq and RNA-Seq datasets from public repositories. Overall, this effort not only validated the accuracy of the vast majority of assays reported by the original authors, but also unveiled [~]500 datasets with discrepancies, in particular through data swap within series of experiments. More importantly, EpiClass also supplied high-confidence predictions for over 320,000 metadata attributes of the biological sample such as the sex, cancer status and biomaterial type, which had been originally omitted in the majority of cases. Our work introduces the first systematic approach for metadata correction and augmentation, enhancing the quality and reliability of publicly available epigenomic data.

bioinformatics↗