Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 65,016 bioRxiv papers from 288,163 authors.
Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders
Hoang T. Nguyen,
Laura M. Huckins,
Ana B Munoz-Manchado,
Douglas M Ruderfer,
August B. Smit,
Joseph D. Buxbaum,
Shaun M. Purcell,
Patrick F Sullivan,
Eli Ayumi Stahl
Posted 08 May 2017
bioRxiv DOI: 10.1101/135293 (published DOI: 10.1186/s13073-017-0497-y)
Posted 08 May 2017
Background. Integrating rare variation from trio family and case/control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DD), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through study of rare variation, only two risk genes have been identified. Methods. We used hierarchical Bayesian modeling of rare variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence (WES) data for schizophrenia (1,077 trios, 6,699 cases and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls). Results. For SCZ, we estimate 1,551 risk genes, more risk genes and weaker effects than for NDDs. We provide power analyses to predict the number of risk gene discoveries as more data become available, demonstrating greater value of case-control over trio samples. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ > 0.55), but low between SCZ and the NDDs (ρ < 0.3). In depth analysis of 288 NDD genes shows highly significant protein-protein interaction (PPI) network connectivity, and functionally distinct PPI subnetworks based on pathway enrichments, single-cell RNA-seq (scRNAseq) cell types and multi-region developmental brain RNA-seq. Conclusions. We have extended a pipeline used in ASD studies and applied it to infer rare genetic parameters for SCZ and four NDDs. We find many new DD risk genes, supported by gene set enrichment and PPI network connectivity analyses. We find greater similarity among NDDs than between NDDs and SCZ. NDD gene subnetworks are implicated in postnatally expressed presynaptic and postsynaptic genes, and for transcriptional and post-transcriptional gene regulation in prenatal neural progenitor and stem cells.
- Downloaded 1,215 times
- Download rankings, all-time:
- Site-wide: 5,377 out of 65,016
- In genomics: 919 out of 4,446
- Year to date:
- Site-wide: 15,580 out of 65,016
- Since beginning of last month:
- Site-wide: 10,971 out of 65,016
Downloads over time
Distribution of downloads per paper, site-wide
- Top preprints of 2018
- Paper search
- Author leaderboards
- Overall metrics
- The API
- Email newsletter
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!