bioRxivCell BiologyPreprint
Abnormal nuclear organization impairs adipogenic lineage commitment and terminal maturation in Hutchinson-Gilford progeria syndrome (HGPS)
Nishita GogiaiD, Alvaro Rodriguez Gonzalez, Lily Eisenklam, Rebeca San MartiniD, Rachel Patton McCordiD
Abstract
Hutchinson-Gilford progeria syndrome (HGPS) is a fatal premature aging disorder driven by progerin, a truncated Lamin A protein that destabilizes nuclear architecture and disproportionately affects mesenchymal-lineage tissues. One notable mesenchymal lineage defect in Progeria patients is early and severe subcutaneous lipodystrophy. We hypothesized that disorganized chromatin architecture underlies the failure of mesenchymal stem cell (MSC) lineage commitment and adipogenesis in HGPS. To test this while preserving donor age, epigenetic history, and tissue context, we induced adipogenesis in age-matched healthy and HGPS patient-derived dermal fibroblasts and profiled cells using imaging, bulk RNA-seq, and Hi-C across the differentiation time course. We found that HGPS fibroblasts commit to the adipogenic lineage at rates comparable to healthy controls but diverge downstream: induced cells display aberrant lipid-droplet morphology, mount a disorganized and delayed transcriptional response, and retain priming for alternative mesenchymal lineages (osteochondrogenic, vascular) alongside stalled adipogenic maturation. Hi-C revealed that HGPS fibroblasts exhibit some baseline spatial compartment differences from healthy cells, but more notably show differences in how they reorganize compartments during adipogenic induction. Compartment-transcription coupling was strong during adipogenesis for lipid-metabolic genes in healthy cells but was more dysregulated in HGPS. These results indicate that HGPS disrupts lineage consolidation rather than initiation, associated with disease-specific failures in chromatin reorganization during differentiation.
- organism: human
- assay: bulk RNA-seq
- assay: Hi-C
- assay: imaging
- research focus: cell-cell communication
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: spatial domain detection
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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