DOI: 10.18742/22179655
title: Integrating human endogenous retroviruses into transcriptome-wide association studies highlights novel risk factors for major psychiatric conditions

description: <b>Integrating human endogenous retroviruses into transcriptome-wide association studies highlights novel risk factors for major psychiatric conditions</b>Duarte et al., 2024.<b>Content: </b>This repository contains the following files:<br>- This readme file (readme.txt).<br>- SNP weights for the TWAS pipeline FUSION (FUSION_weights_AFR_all_1.tar.gz, FUSION_weights_EUR_all_1.tar.gz) and for the TWAS fine-mapping pipeline FOCUS (FOCUS_weights_AFR_all_1.tar.gz, FOCUS_weights_EUR_all_1.tar.gz), which can be used to impute the expression of human endogenous retroviruses (HERVs) and protein coding genes. Instructions for perfoming an rTWAS are available at https://rodrigoduarte88.github.io/neuro_rTWAS/. SNP weights are provided for Europeans (N = 563) and African Americans (N = 229), as detailed in the manuscript.<br>- Linkage disequilibrium reference panel for the rTWAS analysis, created using the European (1000G_EUR_LDREF_3.per_chr.tar.gz) or African (1000G_AFR_LDREF_3.per_chr.tar.gz) subset of the 1,000 Genomes. N.B.: The analyses described in Duarte et al., 2024 were performed using the European or African subset of the CommonMind Consortium as linkage disequilibrium reference panel. However, access to those files is controlled by the NIMH Repository and Genomics Resources (NRGR). Thus, we provide here an equivalent dataset for use as the linkage disequilibrium reference panel for your own rTWAS, based on 1,000 Genomes data.<br>- All code used in the manuscript, including filtering criteria used to generate the reference panels and SNP weights (Duarte et al. 2024 - all code.zip).<b>Related content:</b><br>- How to perform an rTWAS: https://rodrigoduarte88.github.io/neuro_rTWAS/.<br>- CommonMind Consortium: https://www.synapse.org//#!Synapse:syn2759792/wiki/69613<br>Reference: Hoffman, G.E., Bendl, J., Voloudakis, G. et al. CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder. Sci Data 6, 180 (2019). https://doi.org/10.1038/s41597-019-0183-6<br>- 1000 Genomes Project: https://www.internationalgenome.org/<br>Reference: The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015). https://doi.org/10.1038/nature15393<br>- FUSION software: https://github.com/gusevlab/fusion_twas<br>Reference: Gusev, A., Ko, A., Shi, H. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet 48, 245–252 (2016). https://doi.org/10.1038/ng.3506<br>- FOCUS software: https://github.com/bogdanlab/focus<br>Reference: Mancuso, N., Freund, M.K., Johnson, R. et al. Probabilistic fine-mapping of transcriptome-wide association studies. Nat Genet 51, 675–682 (2019). https://doi.org/10.1038/s41588-019-0367-1<b>Disclaimers:</b> If you choose to download and use these scripts and data, you acknowledge that:<br>- These are provided on an “as is” basis, and no warranty is provided as to their performance or fitness for any purpose.<br>- You will cite Duarte et al. 2024 in any communications or publications arising directly or indirectly from these scripts.<br>- SNPs are annotated using dbsnp 151/hg19.<b>Acknowledgements: </b>Research reported in this publication was supported by the National Institutes of Health (NIH) under award number R21 HG011513. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. TRP is supported by an MRC (UKRI) New Investigator Research Grant (MR/W028018/1). Analyses were performed using King’s College London’s High Performance Computing Cluster CREATE (King's College London, 2023). Data for this publication were obtained from the National Institute of Mental Health (NIMH) Repository & Genomics Resource, a centralized national biorepository for genetic studies of psychiatric disorders. The data were generated as part of the CommonMind Consortium, supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffman-La Roche Ltd and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, AG02219, AG05138, MH06692, R01MH110921, R01MH109677, R01MH109897, U01MH103392, and contract HHSN271201300031C through IRP NIMH. Brain tissue for the study was obtained from the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the NIMH Human Brain Collection Core. Thanks to CMC Leadership, including Panos Roussos, Joseph Buxbaum, Andrew Chess, Schahram Akbarian, Vahram Haroutunian (Icahn School of Medicine at Mount Sinai), Bernie Devlin, David Lewis (University of Pittsburgh), Raquel Gur, Chang-Gyu Hahn (University of Pennsylvania), Enrico Domenici (University of Trento), Mette A. Peters, Solveig Sieberts (Sage Bionetworks), Thomas Lehner, Stefano Marenco, Barbara K. Lipska (NIMH).