Abstract
Coordinated programs of gene expression drive brain development. It is unclear which transcriptional programs, in which cell-types, are affected in neuropsychiatric disorders such as schizophrenia. Here we integrate human genetics with transcriptomic data from differentiation of human embryonic stem cells into cortical excitatory neurons. We identify transcriptional programs expressed during early neurogenesis in vitro and in human foetal cortex that are down-regulated in DLG2−/− lines. Down-regulation impacted neuronal differentiation and maturation, impairing migration, morphology and action potential generation. Genetic variation in these programs is associated with neuropsychiatric disorders and cognitive function, with associated variants predominantly concentrated in loss-of-function intolerant genes. Neurogenic programs also overlap schizophrenia GWAS enrichment previously identified in mature excitatory neurons, suggesting that pathways active during prenatal cortical development may also be associated with mature neuronal dysfunction. Our data from human embryonic stem cells, when combined with analysis of available foetal cortical gene expression data, de novo rare variants and GWAS statistics for neuropsychiatric disorders and cognition, reveal a convergence on transcriptional programs regulating excitatory cortical neurogenesis.
| Original language | English |
|---|---|
| Article number | 27 |
| Journal | Nature Communications |
| Volume | 13 |
| Issue number | 1 |
| Early online date | 14 Jan 2022 |
| DOIs | |
| Publication status | Published - 14 Jan 2022 |
Bibliographical note
Funding Information:This work was supported by Wellcome Trust Strategic Award (100202/Z/12/Z, A.H. & M.O.), MRC programme grant (G08005009, M.O.D., M.O. & A.P.), MRC Centre grant (MR/L010305/1, M.O.D., M.O. & A.P.), Waterloo Foundation ‘Changing Minds’ programme (506926, E.S.) and start-up funding (AH1132S012, AH1132S204, E.S.) from the Neuroscience and Mental Health Research Institute, Cardiff University. We acknowledge excellent technical support for RNA sequencing from Joanne Morgan (MRC Centre) and MS analysis from Lydia Kiesel (University of Sheffield) and assistance in morphology tracing from Sophie Pocklington. We appreciate excellent general lab support from Emma Dalton, Trudy Workman and Olena Petter. We thank Prof. Meng Li for her advice and Dr. Claudia Tamburini for technical support in the initial stages of the project and Profs. Yves Barde and Lesley Jones for helpful comments on the manuscript and Emily Adair for providing rat primary glial cells. We thank the International Genomics of Alzheimer’s Project (IGAP) for providing summary results data for AD common variant analysis. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i–Select chips was funded by the French National Foundation on Alzheimer’s disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant no. 503480), Alzheimer’s Research UK (Grant no. 503176), the Wellcome Trust (Grant no. 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant no. 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association grant ADGC–10–19672. We thank the research participants and employees of 23andMe for the sharing of summary statistics for MDD common variant analysis.
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© 2022, The Author(s).