Increased VLCFA-lipids and ELOVL4 underlie neurodegeneration in frontotemporal dementia

Rare, yet biologically critical, lipids that contain very long chain fatty acids (VLCFA-lipids) are synthesized in the brain by the enzyme ELOVL4. High levels of VLCFA-lipids are toxic to cells and excess VLCFA-lipids are actively removed by ABCD1 in an ATP-dependent manner. Virtually nothing is known about the impact of VLCFA-lipids in neurodegenerative diseases. Here, we investigated the possible role of VLCFA-lipids in frontotemporal dementia (FTD), which is a leading cause of younger-onset dementia. Using quantitative discovery lipidomics, we identified three VLCFA-lipid species that were significantly increased in FTD brain compared to controls, with strong correlations with ELOVL4. Increases in ELOVL4 expression correlated with significant decreases in the membrane-bound synaptophysin in FTD brain. Furthermore, increases in ABCD1 expression correlated with increases in VLCFA-lipids. We uncovered a new pathomechanism that is pertinent to understanding the pathogenesis of FTD.

Identifying cell type specific driver genes in autism-associated copy number loci from cerebral organoids

ABSTRACTNeuropsychiatric and neurodevelopmental disorders have been particularly challenging to study using animal models, and recently, human-derived cerebral organoids demonstrate great promise for discovering molecular processes that are important in these disorders. However, several challenges remain in achieving robust phenotyping to discover cell type specific genes. We perform RNA sequencing on 71 samples comprising of 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to identify cell type specific driver genes, for 16p11.2 deletions and 15q11-13 duplications. We identify neuroepithelial cells as critical cell types for 16p11.2 deletions, and discover novel and previously reported cell type specific driver genes. Finally, we validated our results that mutations in KCTD13 in the 16p11.2 locus lead to imbalances in the proportion of neuroepithelial cells, using CRISPR/Cas9-edited mosaic organoids. Our work presents a quantitative discovery and validation framework for identifying cell type specific driver genes associated with complex diseases using cerebral organoids.