Genetic association analysis of 77,539 genomes reveals rare disease etiologies

Abstract

The genetic etiologies of more than half of rare diseases remain unknown. Standardized genome sequencing and phenotyping of large patient cohorts provide an opportunity for discovering the unknown etiologies, but this depends on efficient and powerful analytical methods. We built a compact database, the ‘Rareservoir’, containing the rare variant genotypes and phenotypes of 77,539 participants sequenced by the 100,000 Genomes Project. We then used the Bayesian genetic association method BeviMed to infer associations between genes and each of 269 rare disease classes assigned by clinicians to the participants. We identified 241 known and 19 previously unidentified associations. We validated associations with ERG, PMEPA1 and GPR156 by searching for pedigrees in other cohorts and using bioinformatic and experimental approaches. We provide evidence that (1) loss-of-function variants in the Erythroblast Transformation Specific (ETS)-family transcription factor encoding gene ERG lead to primary lymphoedema, (2) truncating variants in the last exon of transforming growth factor-β regulator PMEPA1 result in Loeys–Dietz syndrome and (3) loss-of-function variants in GPR156 give rise to recessive congenital hearing impairment. The Rareservoir provides a lightweight, flexible and portable system for synthesizing the genetic and phenotypic data required to study rare disease cohorts with tens of thousands of participants.

Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection.

“…This result is consistent with the pattern observed in the previous study (Domazet-Lošo and Tautz 2008). By utilizing DNVs and rare variants from large-scale datasets of exomic and genomic sequencing aggregated in recent years (Wang et al 2022;Greene et al 2023), we found that evolutionary older genes tend to have higher gene-wise DNVs burden. Logistic regression modeling indicates that protein length, gene age, and DNVs burden are positively correlated with the probability of genes as being disease genes.…”

“…We retrieved the burden of de novo germline variants from multiple studies, including the Gene4Denovo database (68,404 individuals) (Zhao et al 2020), UK Biobank exomes (394,783 individuals), and gnomAD database (V4.0, 76,215 individuals) (Wang et al 2022;Greene et al 2023). The genotypes and allele frequencies were downloaded from gno-mAD (https://gnomad.broadinstitute.org/downloads).…”

“…In recent years, increasing availability of large-scale sequencing of whole exomes and whole genomes have greatly promoted the identification of deleterious variants underlying rare disorders (Richards et al 2015). Statistical and medical studies have demonstrated that rare diseases are often caused by rare variants, which have more significant effects on disease phenotypes than common variants (Richards et al 2015;Wang et al 2021;Chen et al 2022;Greene et al 2023;Jia et al 2023;Weiner et al 2023;Chen et al 2024a). The effect of genebased rare variant burden-the aggregate impact of rare (including de novo germline) protein-altering variants-has been confirmed in many genetic disorders (Purcell et al 2014;Zuk et al 2014;Guo et al 2018;Halvorsen et al 2020;Jiang et al 2021).…”

Inhibitory G proteins play multiple roles to polarize sensory hair cell morphogenesis

“…While both GPR156 (Greene et al, 2023; Ramzan et al, 2023) and GPSM2 (Doherty et al, 2012; Walsh et al, 2010) have been identified as human deafness genes, there is currently no evidence implicating a GNAI/O protein. This is most likely because all GNAI/O proteins, including GNAI3 which is more specifically required in HC for hair bundle morphogenesis (Figure 9), play ubiquitous and critical signaling roles in the context of heterotrimeric protein signaling across many cell types.…”

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

“…These are not rare occurrences: recently, a research group described matching immediately upon submission to MME to an existing cohort with phenotypic and genetic similarities for almost ~10% of their novel candidate genes 51 Finally, many large-scale clinical and hybrid clinical-research genomic testing efforts are already identifying, sharing, and reporting results in novel candidate genes and have described substantial benefits in identifying a genetic diagnosis for their patients. 28,[31][32][33]51,56 Thus we strongly encourage clinical laboratories and research programs to proactively identify, share, and report variants in novel candidate genes.…”