bioRxivNeurosciencePreprint
Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders
Jakob SeidlitziD, Ajay NadigiD, Siyuan LiuiD, Richard A. I. BethlehemiD, Petra E. VértesiD, Sarah Elizabeth MorganiD, František VášaiD, Rafael Romero-GarcíaiD, François M. LalondeiD, LIV S. CLASEN, Jonathan D. Blumenthal, Casey PaquolaiD, Boris C. BernhardtiD, Konrad WagstyliD, Damon Polioudakis, Luis de la Torre-UbietaiD, Daniel H. GeschwindiD, Joan C. HaniD, Nancy LeeiD, Declan MurphyiD, Edward Thomas BullmoreiD, Armin RaznahaniD
Abstract
Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i) in vivo neuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorders anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this "transcriptional vulnerability model" by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and blood-derived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.
- organism: human
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: matrix factorization
- Citations
- 24
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