Gene-level integrated metric of negative selection (GIMS) prioritizes candidate genes for nephrotic syndrome

Essential genes from genome-wide screenings as a resource for neuropsychiatric disorders gene discovery

Genome-wide screenings of "essential genes", i.e., genes required for an organism or cell survival, have been traditionally conducted in vitro in cancer cell lines, limiting the translation of results to other tissues and non-cancerous cells. Recently, an in vivo screening was conducted in adult mouse striatum tissue, providing the first genome-wide dataset of essential genes in neuronal cells. Here, we aim to investigate the role of essential genes in brain development and disease risk with a comprehensive set of bioinformatics tools, including integration with transcriptomic data from developing human brain, publicly available data from genome-wide association studies, de novo mutation datasets for different neuropsychiatric disorders, and case-control transcriptomic data from postmortem brain tissues. For the first time, we found that the expression of neuronal essential genes (NEGs) increases before birth during the early development of human brain and maintains a relatively high expression after birth. On the contrary, common essential genes from cancer cell line screenings (ACEGs) tend to be expressed at high levels during development but quickly drop after birth. Both gene sets were enriched in neurodevelopmental disorders, but only NEGs were robustly associated with neuropsychiatric disorders risk genes. Finally, NEGs were more likely to show differential expression in the brains of neuropsychiatric disorders patients than ACEGs. Overall, genome-wide central nervous system screening of essential genes can provide new insights into neuropsychiatric diseases.

Essentiality-specific pathogenicity prioritization gene score to improve filtering of disease sequence data

The causal genetic variants underlying more than 50% of single gene (monogenic) disorders are yet to be discovered. Many patients with conditions likely to have a monogenic basis do not receive a confirmed molecular diagnosis which has potential impacts on clinical management. We have developed a gene-specific score, essentiality-specific pathogenicity prioritization (ESPP), to guide the recognition of genes likely to underlie monogenic disease variation to assist in filtering of genome sequence data. When a patient genome is sequenced, there are frequently several plausibly pathogenic variants identified in different genes. Recognition of the single gene most likely to include pathogenic variation can guide the identification of a causal variant. The ESPP score integrates gene-level scores which are broadly related to gene essentiality. Previous work towards the recognition of monogenic disease genes proposed a model with increasing gene essentiality from 'non-essential' to 'essential' genes (for which pathogenic variation may be incompatible with survival) with genes liable to contain disease variation positioned between these two extremes. We demonstrate that the ESPP score is useful for recognizing genes with high potential for pathogenic disease-related variation. Genes classed as essential have particularly high scores, as do genes recently recognized as strong candidates for developmental disorders. Through the integration of individual gene-specific scores, which have different properties and assumptions, we demonstrate the utility of an essentiality-based gene score to improve sequence genome filtering.

Human and mouse essentiality screens as a resource for disease gene discovery

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery.

Exome-wide Association Study Identifies GREB1L Mutations in Congenital Kidney Malformations

Renal agenesis and hypodysplasia (RHD) are major causes of pediatric chronic kidney disease and are highly genetically heterogeneous. We conducted whole-exome sequencing in 202 case subjects with RHD and identified diagnostic mutations in genes known to be associated with RHD in 7/202 case subjects. In an additional affected individual with RHD and a congenital heart defect, we found a homozygous loss-of-function (LOF) variant in SLIT3, recapitulating phenotypes reported with Slit3 inactivation in the mouse. To identify genes associated with RHD, we performed an exome-wide association study with 195 unresolved case subjects and 6,905 control subjects. The top signal resided in GREB1L, a gene implicated previously in Hoxb1 and Shha signaling in zebrafish. The significance of the association, which was p = 2.0 × 10^-5 for novel LOF, increased to p = 4.1 × 10^-6 for LOF and deleterious missense variants combined, and augmented further after accounting for segregation and de novo inheritance of rare variants (joint p = 2.3 × 10^-7). Finally, CRISPR/Cas9 disruption or knockdown of greb1l in zebrafish caused specific pronephric defects, which were rescued by wild-type human GREB1L mRNA, but not mRNA containing alleles identified in case subjects. Together, our study provides insight into the genetic landscape of kidney malformations in humans, presents multiple candidates, and identifies SLIT3 and GREB1L as genes implicated in the pathogenesis of RHD.

Evaluating Mendelian nephrotic syndrome genes for evidence for risk alleles or oligogenicity that explain heritability

BACKGROUND

More than 30 genes can harbor rare exonic variants sufficient to cause nephrotic syndrome (NS), and the number of genes implicated in monogenic NS continues to grow. However, outside the first year of life, the majority of affected patients, particularly in ancestrally mixed populations, do not have a known monogenic form of NS. Even in those children classified with a monogenic form of NS, there is phenotypic heterogeneity. Thus, we have only discovered a fraction of the heritability of NS-the underlying genetic factors contributing to phenotypic variation. Part of the "missing heritability" for NS has been posited to be explained by patients harboring coding variants across one or more previously implicated NS genes, insufficient to cause NS in a classical Mendelian manner, but that nonetheless have a sufficient impact on protein function to cause disease. However, systematic evaluation in patients with NS for rare or low-frequency risk alleles within single genes, or in combination across genes ("oligogenicity"), has not been reported. To determine whether, compared with a reference population, patients with NS have either a significantly increased burden of protein-altering variants ("risk-alleles"), or a unique combination of them ("oligogenicity"), in a set of 21 genes implicated in Mendelian forms of NS.

METHODS

In 303 patients with NS enrolled in the Nephrotic Syndrome Study Network (NEPTUNE), we performed targeted amplification paired with next-generation sequencing of 21 genes implicated in monogenic NS. We created a high-quality variant call set and compared it with a variant call set of the same genes in a reference population composed of 2,535 individuals from phase 3 of the 1000 Genomes Project. We created both a "stringent" and a "relaxed" pathogenicity-filtering pipeline, applied them to both cohorts, and computed the burden of variants in the entire gene set per cohort, the burden of variants in the entire gene set per individual, the burden of variants within a single gene per cohort, and unique combinations of variants across two or more genes per cohort.

RESULTS

With few exceptions when using the relaxed filter, and which are likely the result of confounding by population stratification, NS patients did not have a significantly increased burden of variants in Mendelian NS genes in comparison to a reference cohort, nor was there any evidence for oligogenicity. This was true when using both the relaxed and the stringent variant pathogenicity filter.

CONCLUSION

In our study, there were no significant differences in the burden or particular combinations of low-frequency or rare protein-altering variants in a previously implicated Mendelian NS genes cohort between North American patients with NS and a reference population. Studies in larger independent cohorts or meta-analyses are needed to assess the generalizability of our discoveries and also address whether there is in fact small but significant enrichment of risk alleles or oligogenicity in NS cases that was undetectable with this current sample size. It is still possible that rare protein-altering variants in these genes, insufficient to cause Mendelian disease, still contribute to NS as risk alleles and/or via oligogenicity. However, we suggest that more accurate bioinformatic analyses and the incorporation of functional assays would be necessary to identify bona fide instances of this form of genetic architecture as a contributor to the heritability of NS.

Using Population Genetics to Interrogate the Monogenic Nephrotic Syndrome Diagnosis in a Case Cohort

To maximize clinical benefits of genetic screening of patients with nephrotic syndrome (NS) to diagnose monogenic causes, reliably distinguishing NS-causing variants from the background of rare, noncausal variants prevalent in all genomes is vital. To determine the prevalence of monogenic NS in a North American case cohort while accounting for background prevalence of genetic variation, we sequenced 21 implicated monogenic NS genes in 312 participants from the Nephrotic Syndrome Study Network and 61 putative controls from the 1000 Genomes Project (1000G). These analyses were extended to available sequence data from approximately 2500 subjects from the 1000G. A typical pathogenicity filter identified causal variants for NS in 4.2% of patients and 5.8% of subjects from the 1000G. We devised a more stringent pathogenicity filtering strategy, reducing background prevalence of causal variants to 1.5%. When applying this stringent filter to patients, prevalence of monogenic NS was 2.9%; of these patients, 67% were pediatric, and 44% had FSGS on biopsy. The rate of complete remission did not associate with monogenic classification. Thus, we identified factors contributing to inaccurate monogenic classification of NS and developed a more accurate variant filtering strategy. The prevalence and clinical correlates of monogenic NS in this sporadically affected cohort differ substantially from those reported for patients referred for genetic analysis. Particularly in unselected, population-based cases, considering putative causal variants in known NS genes from a probabilistic rather than a deterministic perspective may be more precise. We also introduce GeneVetter, a web tool for monogenic assessment of rare disease.