RT Journal Article
SR Electronic
T1 Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 573279
DO 10.1101/573279
A1 Jakob Seidlitz
A1 Ajay Nadig
A1 Siyuan Liu
A1 Richard A.I. Bethlehem
A1 Petra E. Vértes
A1 Sarah E. Morgan
A1 František Váša
A1 Rafael Romero-Garcia
A1 François M. Lalonde
A1 Liv S. Clasen
A1 Jonathan D. Blumenthal
A1 Casey Paquola
A1 Boris Bernhardt
A1 Konrad Wagstyl
A1 Damon Polioudakis
A1 Luis de la Torre-Ubieta
A1 Daniel H. Geschwind
A1 Joan C. Han
A1 Nancy R. Lee
A1 Declan G. Murphy
A1 Edward T. Bullmore
A1 Armin Raznahan
YR 2019
UL http://biorxiv.org/content/early/2019/11/17/573279.abstract
AB 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 disorder’s 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.