Cell type specific transcriptomic differences in depression show similar patterns between males and females but implicate distinct cell types and genes

Abstract

Major depressive disorder (MDD) is a common, heterogenous, and potentially serious psychiatric illness. Diverse brain cell types have been implicated in MDD etiology. Significant sexual differences exist in MDD clinical presentation and outcome, and recent evidence suggests different molecular bases for male and female MDD. We evaluated over 160,000 nuclei from 71 female and male donors, leveraging new and pre-existing single-nucleus RNA-sequencing data from the dorsolateral prefrontal cortex. Cell type specific transcriptome-wide threshold-free MDD-associated gene expression patterns were similar between the sexes, but significant differentially expressed genes (DEGs) diverged. Among 7 broad cell types and 41 clusters evaluated, microglia and parvalbumin interneurons contributed the most DEGs in females, while deep layer excitatory neurons, astrocytes, and oligodendrocyte precursors were the major contributors in males. Further, the Mic1 cluster with 38% of female DEGs and the ExN10_L46 cluster with 53% of male DEGs, stood out in the meta-analysis of both sexes.

Transcriptomic pathology of neocortical microcircuit cell types across psychiatric disorders

“…Our DE analysis indicates that interneurons, especially PVALB, followed by SST and VIP, appear most altered in psychiatric disorders. This is in contrast to the preponderance of DE genes among excitatory neurons (relative to inhibitory) reported by recent single-nucleus studies of psychiatric disorders (29)(30)(31)(32)(33)(34), which might be influenced by higher sampling of excitatory neurons (Supplementary Figure 7). In our study, few DE genes were found overall in PYR cells.…”

“…NPAS3 plays a broad role in neurogenesis, and mutations in this gene have been associated with SCZ and neurodevelopmental disorders (59,60). LCM-seq cell-specific disease signatures were also moderately consistent with those surveyed in recent human snRNA-seq datasets from MDD and SCZ (30,34), as assessed by rank-rank hypergeometric overlap analysis ( Supplemental Figure 4 , see Methods).…”

“…The potential contribution of sex and other biological (age, race), clinical (mode of death, medication), technical and other (tobacco use) covariates were assessed and presented in Supplemental Figure 2. Second, we cannot resolve sub-subtypes of our five neuronal populations, which may be selectively vulnerable in the context of brain disease (29)(30)(31)(32)(33)(34)81). Third, profiling only 130 cells per neuronal subtype limits power, compared to single-nucleus datasets with hundreds of thousands to millions of cells, albeit with strong bias towards common cell types (Supplementary Figure 7).…”

“…We further compared the concordance between LCM-seq gene signatures and recent snRNA-seq datasets of MDD and SCZ (30,34). We obtained snRNA-seq count matrices, filtered out low-quality cells and genes, and performed pseudobulk DE testing using limma-voom (43).…”

“…Cell type-specific molecular changes in psychiatric disorders have been most widely studied through gene expression, primarily using two technologies: single-nucleus RNA sequencing (snRNA-seq) and laser capture microdissection followed by RNA sequencing (LCM-seq). snRNA-seq, in which each RNA molecule is tagged with its cell of origin, has been performed on postmortem brain samples from patients with MDD (29,30), MDD and PTSD (31), and SCZ (32)(33)(34). snRNA-seq offers the highest throughput, but with the disadvantages of only capturing RNA from inside the nucleus and of lower transcript coverage.…”