Deep generative modeling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders

Abstract

Identifying causal mutations accelerates genetic disease diagnosis, and therapeutic development. Missense variants present a bottleneck in genetic diagnoses as their effects are less straightforward than truncations or nonsense mutations. While computational prediction methods are increasingly successful at prediction for variants inknowndisease genes, they do not generalize well to other genes as the scores are not calibrated across the proteome. To address this, we developed a deep generative model, popEVE, that combines evolutionary information with population sequence data and achieves state-of-the-art performance at ranking variants by severity to distinguish patients with severe developmental disorders from potentially healthy individuals. popEVE identifies 442 genes in a cohort of developmental disorder cases, including evidence of 119 novel genetic disorders without the need for gene-level enrichment and without overestimating the prevalence of pathogenic variants in the population. By placing variants on a unified scale, our model offers a comprehensive perspective on the distribution of fitness effects across the entire proteome and the broader human population. popEVE provides compelling evidence for genetic diagnoses even in exceptionally rare single-patient disorders where conventional techniques relying on repeated observations may not be applicable. Interactive web viewer and downloads available atpop.evemodel.org.

Variant effect predictor correlation with functional assays is reflective of clinical classification performance

“…TranceptEVE (Notin et al , 2022b) ranks 6 th overall, and is a hybrid of Tranception (Notin et al , 2022a) and EVE (a hybrid of Tranception (Notin et al , 2022a). popEVE (Orenbuch et al , 2023) ranks 7 th and is a hybrid of ESM-1v and EVE that also performs gene-level calibration on variants from UK Biobank, with the goal of making scores from different genes directly comparable. Because of its utilisation of population data, we have classified popEVE as a population-based VEP, although it is not necessarily subject to the same type 1 circularity concerns as many other VEPs, as discussed later.…”

“…In addition, given the radically different performance of VEPs across different genes, we think that gene-specific thresholds and interpretation, as well as consideration of inheritance, will be necessary to advance the clinical utility of VEPs. To an extent, this is what the popEVE is attempting, combining population-free gene-level scoring with calibration across genes based upon the distributions of observed population variants (Orenbuch et al , 2023). Closely related to this, it is important to emphasise that both of our benchmarking strategies here have been based on gene-level approaches.…”

Site saturation mutagenesis of 500 human protein domains reveals the contribution of protein destabilization to genetic disease

“…For each domain, we used the predictions corresponding to the window in which the domain is most centered. We obtained EVE 11 , popEVE 59 and Tranception 13 scores from https://pop.evemodel.org/. We used precomputed RaSP scores 60 , and generated DDMut 61 and thermoMPNN 28 predictions with the aid of AlphaFold2 structure predictions.…”

Pervasive ancestry bias in variant effect predictors

“…It is also important to note that not all variant effect prediction strategies that incorporate population data are necessarily susceptible to this bias. For example, popEVE uses patterns of population variation to calibrate variant effect scores from gene to gene, but knowledge of specific population variants is not used in scoring 20 ; it is consistent with the population-free VEPs in terms of its differences between populations. We also note the great potential of high-throughput experimental approaches involving multiplexed assays of variant effect (MAVEs) for scoring population variants in an unbiased manner 21 , although the number of genes for which these measurements are available is still very limited.…”