Guidelines for releasing a variant effect predictor.

Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs. Emphasising open-source availability, transparent methodologies, clear variant effect score interpretations, standardised scales, accessible predictions, and rigorous training data disclosure, we aim to improve the usability and interpretability of VEPs, and promote their integration into analysis and evaluation pipelines. We also provide a large, categorised list of currently available VEPs, aiming to facilitate the discovery and encourage the usage of novel methods within the scientific community.

Expansion of the neurodevelopmental phenotype of individuals with EEF1A2 variants and genotype-phenotype study.

Translation elongation factor eEF1A2 constitutes the alpha subunit of the elongation factor-1 complex, responsible for the enzymatic binding of aminoacyl-tRNA to the ribosome. Since 2012, 21 pathogenic missense variants affecting EEF1A2 have been described in 42 individuals with a severe neurodevelopmental phenotype including epileptic encephalopathy and moderate to profound intellectual disability (ID), with neurological regression in some patients. Through international collaborative call, we collected 26 patients with EEF1A2 variants and compared them to the literature. Our cohort shows a significantly milder phenotype. 83% of the patients are walking (vs. 29% in the literature), and 84% of the patients have language skills (vs. 15%). Three of our patients do not have ID. Epilepsy is present in 63% (vs. 93%). Neurological examination shows a less severe phenotype with significantly less hypotonia (58% vs. 96%), and pyramidal signs (24% vs. 68%). Cognitive regression was noted in 4% (vs. 56% in the literature). Among individuals over 10 years, 56% disclosed neurocognitive regression, with a mean age of onset at 2 years. We describe 8 novel missense variants of EEF1A2. Modeling of the different amino-acid sites shows that the variants associated with a severe phenotype, and the majority of those associated with a moderate phenotype, cluster within the switch II region of the protein and thus may affect GTP exchange. In contrast, variants associated with milder phenotypes may impact secondary functions such as actin binding. We report the largest cohort of individuals with EEF1A2 variants thus far, allowing us to expand the phenotype spectrum and reveal genotype-phenotype correlations.

Interface Gain-of-Function Mutations in TLR7 Cause Systemic and Neuro-inflammatory Disease.

TLR7 recognizes pathogen-derived single-stranded RNA (ssRNA), a function integral to the innate immune response to viral infection. Notably, TLR7 can also recognize self-derived ssRNA, with gain-of-function mutations in human TLR7 recently identified to cause both early-onset systemic lupus erythematosus (SLE) and neuromyelitis optica. Here, we describe two novel mutations in TLR7, F507S and L528I. While the L528I substitution arose de novo, the F507S mutation was present in three individuals from the same family, including a severely affected male, notably given that the TLR7 gene is situated on the X chromosome and that all other cases so far described have been female. The observation of mutations at residues 507 and 528 of TLR7 indicates the importance of the TLR7 dimerization interface in maintaining immune homeostasis, where we predict that altered homo-dimerization enhances TLR7 signaling. Finally, while mutations in TLR7 can result in SLE-like disease, our data suggest a broader phenotypic spectrum associated with TLR7 gain-of-function, including significant neurological involvement.

CDK4/6 inhibitor-mediated cell overgrowth triggers osmotic and replication stress to promote senescence.

Abnormal increases in cell size are associated with senescence and cell cycle exit. The mechanisms by which overgrowth primes cells to withdraw from the cell cycle remain unknown. We address this question using CDK4/6 inhibitors, which arrest cells in G0/G1 and are licensed to treat advanced HR+/HER2- breast cancer. We demonstrate that CDK4/6-inhibited cells overgrow during G0/G1, causing p38/p53/p21-dependent cell cycle withdrawal. Cell cycle withdrawal is triggered by biphasic p21 induction. The first p21 wave is caused by osmotic stress, leading to p38- and size-dependent accumulation of p21. CDK4/6 inhibitor washout results in some cells entering S-phase. Overgrown cells experience replication stress, resulting in a second p21 wave that promotes cell cycle withdrawal from G2 or the subsequent G1. We propose that the levels of p21 integrate signals from overgrowth-triggered stresses to determine cell fate. This model explains how hypertrophy can drive senescence and why CDK4/6 inhibitors have long-lasting effects in patients.

Predicting pathogenic protein variants.

Machine-learning algorithm uses structure prediction to spot disease-causing mutations.

Updated benchmarking of variant effect predictors using deep mutational scanning.

The assessment of variant effect predictor (VEP) performance is fraught with biases introduced by benchmarking against clinical observations. In this study, building on our previous work, we use independently generated measurements of protein function from deep mutational scanning (DMS) experiments for 26 human proteins to benchmark 55 different VEPs, while introducing minimal data circularity. Many top-performing VEPs are unsupervised methods including EVE, DeepSequence and ESM-1v, a protein language model that ranked first overall. However, the strong performance of recent supervised VEPs, in particular VARITY, shows that developers are taking data circularity and bias issues seriously. We also assess the performance of DMS and unsupervised VEPs for discriminating between known pathogenic and putatively benign missense variants. Our findings are mixed, demonstrating that some DMS datasets perform exceptionally at variant classification, while others are poor. Notably, we observe a striking correlation between VEP agreement with DMS data and performance in identifying clinically relevant variants, strongly supporting the validity of our rankings and the utility of DMS for independent benchmarking.

Correspondence between functional scores from deep mutational scans and predicted effects on protein stability.

Many methodologically diverse computational methods have been applied to the growing challenge of predicting and interpreting the effects of protein variants. As many pathogenic mutations have a perturbing effect on protein stability or intermolecular interactions, one highly interpretable approach is to use protein structural information to model the physical impacts of variants and predict their likely effects on protein stability and interactions. Previous efforts have assessed the accuracy of stability predictors in reproducing thermodynamically accurate values and evaluated their ability to distinguish between known pathogenic and benign mutations. Here, we take an alternate approach, and explore how well stability predictor scores correlate with functional impacts derived from deep mutational scanning (DMS) experiments. In this work, we compare the predictions of 9 protein stability-based tools against mutant protein fitness values from 49 independent DMS datasets, covering 170,940 unique single amino acid variants. We find that FoldX and Rosetta show the strongest correlations with DMS-based functional scores, similar to their previous top performance in distinguishing between pathogenic and benign variants. For both methods, performance is considerably improved when considering intermolecular interactions from protein complex structures, when available. Furthermore, using these two predictors, we derive a "Foldetta" consensus score, which improves upon the performance of both, and manages to match dedicated variant effect predictors in reflecting variant functional impacts. Finally, we also highlight that predicted stability effects show consistently higher correlations with certain DMS experimental phenotypes, particularly those based upon protein abundance, and, in certain cases, can significantly outcompete sequence-based variant effect prediction methodologies for predicting functional scores from DMS experiments.

Hallmarks and evolutionary drivers of cotranslational protein complex assembly.

Recent discoveries have highlighted the prevalence of cotranslational assembly in proteomes, revealing a range of mechanisms that enables the assembly of protein complex subunits on the ribosome. Structural analyses have uncovered emergent properties that may inherently control whether a subunit undergoes cotranslational assembly. However, the evolutionary paths that have yielded such complexes over an extended timescale remain largely unclear. In this review, we reflect on historical experiments that contributed to the field, including breakthroughs that have made possible the proteome-wide detection of cotranslational assembly, and the technical challenges yet to be overcome. We introduce a simple framework that encapsulates the hallmarks of cotranslational assembly and discuss how results from new experiments are shaping our view of the mechanistic, structural and evolutionary factors driving the phenomenon.

Buffering of genetic dominance by allele-specific protein complex assembly.

Protein complex assembly often occurs while subunits are being translated, resulting in complexes whose subunits were translated from the same mRNA in an allele-specific manner. It has thus been hypothesized that such cotranslational assembly may counter the assembly-mediated dominant-negative effect, whereby co-assembly of mutant and wild-type subunits "poisons" complex activity. Here, we show that cotranslationally assembling subunits are much less likely to be associated with autosomal dominant relative to recessive disorders, and that subunits with dominant-negative disease mutations are significantly depleted in cotranslational assembly compared to those associated with loss-of-function mutations. We also find that complexes with known dominant-negative effects tend to expose their interfaces late during translation, lessening the likelihood of cotranslational assembly. Finally, by combining complex properties with other features, we trained a computational model for predicting proteins likely to be associated with non-loss-of-function disease mechanisms, which we believe will be of considerable utility for protein variant interpretation.

Type I Interferonopathy due to a Homozygous Loss-of-Inhibitory Function Mutation in STAT2.

PURPOSE: STAT2 is both an effector and negative regulator of type I interferon (IFN-I) signalling. We describe the characterization of a novel homozygous missense STAT2 substitution in a patient with a type I interferonopathy. METHODS: Whole-genome sequencing (WGS) was used to identify the genetic basis of disease in a patient with features of enhanced IFN-I signalling. After stable lentiviral reconstitution of STAT2-null human fibrosarcoma U6A cells with STAT2 wild type or p.(A219V), we performed quantitative polymerase chain reaction, western blotting, immunofluorescence, and co-immunoprecipitation to functionally characterize the p.(A219V) variant. RESULTS: WGS identified a rare homozygous single nucleotide transition in STAT2 (c.656C > T), resulting in a p.(A219V) substitution, in a patient displaying developmental delay, intracranial calcification, and up-regulation of interferon-stimulated gene (ISG) expression in blood. In vitro studies revealed that the STAT2 p.(A219V) variant retained the ability to transduce an IFN-I stimulus. Notably, STAT2 p.(A219V) failed to support receptor desensitization, resulting in sustained STAT2 phosphorylation and ISG up-regulation. Mechanistically, STAT2 p.(A219V) showed defective binding to ubiquitin specific protease 18 (USP18), providing a possible explanation for the chronic IFN-I pathway activation seen in the patient. CONCLUSION: Our data indicate an impaired negative regulatory role of STAT2 p.(A219V) in IFN-I signalling and that mutations in STAT2 resulting in a type I interferonopathy state are not limited to the previously reported R148 residue. Indeed, structural modelling highlights at least 3 further residues critical to mediating a STAT2-USP18 interaction, in which mutations might be expected to result in defective negative feedback regulation of IFN-I signalling.

Expanding the neurodevelopmental phenotype associated with HK1 de novo heterozygous missense variants.

Neurodevelopmental disorder with visual defects and brain anomalies (NEDVIBA) is a recently described genetic condition caused by de novo missense HK1 variants. Phenotypic data is currently limited; only seven patients have been published to date. This descriptive case series of a further four patients with de novo missense HK1 variants, alongside integration of phenotypic data with the reported cases, aims to improve our understanding of the associated phenotype. We provide further evidence that de novo HK1 variants located within the regulatory-terminal domain and alpha helix are associated with neurological problems and visual problems. We highlight for the first time an association with a raised cerebrospinal fluid lactate and specific abnormalities to the basal ganglia on brain magnetic resonance imaging, as well as associated respiratory issues and swallowing/feeding difficulties. We propose that this distinctive neurodevelopmental phenotype could arise through disruption of the regulatory glucose-6-phosphate binding site and subsequent gain of function of HK1 within the brain.

Monoallelic variants resulting in substitutions of MAB21L1 Arg51 Cause Aniridia and microphthalmia.

Classical aniridia is a congenital and progressive panocular disorder almost exclusively caused by heterozygous loss-of-function variants at the PAX6 locus. We report nine individuals from five families with severe aniridia and/or microphthalmia (with no detectable PAX6 mutation) with ultrarare monoallelic missense variants altering the Arg51 codon of MAB21L1. These mutations occurred de novo in 3/5 families, with the remaining families being compatible with autosomal dominant inheritance. Mice engineered to carry the p.Arg51Leu change showed a highly-penetrant optic disc anomaly in heterozygous animals with severe microphthalmia in homozygotes. Substitutions of the same codon (Arg51) in MAB21L2, a close homolog of MAB21L1, cause severe ocular and skeletal malformations in humans and mice. The predicted nucleotidyltransferase function of MAB21L1 could not be demonstrated using purified protein with a variety of nucleotide substrates and oligonucleotide activators. Induced expression of GFP-tagged wildtype and mutant MAB21L1 in human cells caused only modest transcriptional changes. Mass spectrometry of immunoprecipitated protein revealed that both mutant and wildtype MAB21L1 associate with transcription factors that are known regulators of PAX6 (MEIS1, MEIS2 and PBX1) and with poly(A) RNA binding proteins. Arg51 substitutions reduce the association of wild-type MAB21L1 with TBL1XR1, a component of the NCoR complex. We found limited evidence for mutation-specific interactions with MSI2/Musashi-2, an RNA-binding proteins with effects on many different developmental pathways. Given that biallelic loss-of-function variants in MAB21L1 result in a milder eye phenotype we suggest that Arg51-altering monoallelic variants most plausibly perturb eye development via a gain-of-function mechanism.

Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations.

Cells rely heavily on microtubules for several processes, including cell division and molecular trafficking. Mutations in the different tubulin-α and -ß proteins that comprise microtubules have been associated with various diseases and are often dominant, sporadic and congenital. While the earliest reported tubulin mutations affect neurodevelopment, mutations are also associated with other disorders such as bleeding disorders and infertility. We performed a systematic survey of tubulin mutations across all isotypes in order to improve our understanding of how they cause disease, and increase our ability to predict their phenotypic effects. Both protein structural analyses and computational variant effect predictors were very limited in their utility for differentiating between pathogenic and benign mutations. This was even worse for those genes associated with non-neurodevelopmental disorders. We selected tubulin-α and -ß disease mutations that were most poorly predicted for experimental characterisation. These mutants co-localise to the mitotic spindle in HeLa cells, suggesting they may exert dominant-negative effects by altering microtubule properties. Our results show that tubulin mutations represent a blind spot for current computational approaches, being much more poorly predicted than mutations in most human disease genes. We suggest that this is likely due to their strong association with dominant-negative and gain-of-function mechanisms.

Weighted Baseball Training Affects Arm Speed Without Increasing Elbow and Shoulder Joint Kinetics.

Long-term training effects of weighted ball throwing programs have been well documented. However, the mechanisms that facilitate these effects are poorly understood. The purpose of this study is to investigate within-session effects of throwing overload and underload baseballs to provide mechanistic evidence for weighted baseball training methods. Twenty-six collegiate- and professional-level baseball pitchers aged 20-30 years (mean age 23.5 [2.7] y) participated in a biomechanical evaluation while pitching a series of leather weighted baseballs. A 1-way repeated-measures analysis of variance was used to evaluate the intrasubject effect of ball weight on a total of 15 kinematic, kinetic, and performance parameters. Ball weight significantly affected pitch velocity, maximum elbow flexion, maximum pelvis rotation velocity, maximum shoulder internal rotation velocity, maximum elbow extension velocity, and anterior trunk tilt at ball release. None of the measured arm joint kinetics were significantly affected by ball weight. Training with 3- to 7-ounce (85- to 198-g) baseballs can be used to work on increasing pitching velocity without increasing throwing arm joint kinetics.

Large protein complex interfaces have evolved to promote cotranslational assembly.

Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromeric subunits in bacterial, yeast, and human complexes. When considering all together, we observe the N-terminal interface to be larger than the C-terminal interface 54% of the time, increasing to 64% when we exclude subunits with only small interfaces, which are unlikely to cotranslationally assemble. This strongly suggests that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding.

Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects.

Clonal hematopoiesis of indeterminate potential (CHIP) increases rapidly in prevalence beyond age 60 and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in hematopoietic stem and progenitor cells (HSPCs). Because mutations in HSPCs often drive leukemia, we hypothesized that HSPC fitness substantially contributes to transformation from CHIP to leukemia. HSPC fitness is defined as the proliferative advantage over cells carrying no or only neutral mutations. If mutations in different genes lead to distinct fitness advantages, this could enable patient stratification. We quantified the fitness effects of mutations over 12 years in older age using longitudinal sequencing and developed a filtering method that considers individual mutational context alongside mutation co-occurrence to quantify the growth potential of variants within individuals. We found that gene-specific fitness differences can outweigh inter-individual variation and, therefore, could form the basis for personalized clinical management.

Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure.

Most known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Taking protein structure into account has therefore provided great insight into the molecular mechanisms underlying human genetic disease. While there has been much focus on how mutations can disrupt protein structure and thus cause a loss of function (LOF), alternative mechanisms, specifically dominant-negative (DN) and gain-of-function (GOF) effects, are less understood. Here, we investigate the protein-level effects of pathogenic missense mutations associated with different molecular mechanisms. We observe striking differences between recessive vs dominant, and LOF vs non-LOF mutations, with dominant, non-LOF disease mutations having much milder effects on protein structure, and DN mutations being highly enriched at protein interfaces. We also find that nearly all computational variant effect predictors, even those based solely on sequence conservation, underperform on non-LOF mutations. However, we do show that non-LOF mutations could potentially be identified by their tendency to cluster in three-dimensional space. Overall, our work suggests that many pathogenic mutations that act via DN and GOF mechanisms are likely being missed by current variant prioritisation strategies, but that there is considerable scope to improve computational predictions through consideration of molecular disease mechanisms.