Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk / Huckins, L.M., Dobbyn, A., Ruderfer, D.M., Hoffman, G., Wang, W., Pardinas, A.F., Rajagopal, V.M., Als, T.D., T. Nguyen, H., Girdhar, K., Boocock, J., Roussos, P., Fromer, M., Kramer, R., Domenici, E., Gamazon, E.R., Purcell, S., Commonmind, C., Schizophrenia Working Group of the Psychiatric Genomics, C., iPSYCH-GEMS Schizophrenia Working, G., et al.. - In: NATURE GENETICS. - ISSN 1546-1718. - 51:4(2019), pp. 659-674. [10.1038/s41588-019-0364-4]

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Wang W.;Kramer R.;Domenici E.;
2019-01-01

Abstract

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.
2019
4
Huckins, L. M.; Dobbyn, A.; Ruderfer, D. M.; Hoffman, G.; Wang, W.; Pardinas, A. F.; Rajagopal, V. M.; Als, T. D.; T. Nguyen, H.; Girdhar, K.; Boocock...espandi
Gene expression imputation across multiple brain regions provides insights into schizophrenia risk / Huckins, L.M., Dobbyn, A., Ruderfer, D.M., Hoffman, G., Wang, W., Pardinas, A.F., Rajagopal, V.M., Als, T.D., T. Nguyen, H., Girdhar, K., Boocock, J., Roussos, P., Fromer, M., Kramer, R., Domenici, E., Gamazon, E.R., Purcell, S., Commonmind, C., Schizophrenia Working Group of the Psychiatric Genomics, C., iPSYCH-GEMS Schizophrenia Working, G., et al.. - In: NATURE GENETICS. - ISSN 1546-1718. - 51:4(2019), pp. 659-674. [10.1038/s41588-019-0364-4]
File in questo prodotto:
File Dimensione Formato  
Huckins et al 2019.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.78 MB
Formato Adobe PDF
2.78 MB Adobe PDF   Visualizza/Apri
nihms-1067544.pdf

accesso aperto

Tipologia: Post-print referato (Refereed author’s manuscript)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.35 MB
Formato Adobe PDF
1.35 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/240708
Citazioni
  • ???jsp.display-item.citation.pmc??? 111
  • Scopus 147
  • ???jsp.display-item.citation.isi??? 145
  • OpenAlex 204
social impact