Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variation to common disease remains relatively unexplored. The UK Biobank (UKB) contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the impact of rare variation on a broad collection of traits1,2. Here, we studied the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UKB participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UKB participants of African, East Asian, or South Asian ancestry. Together, our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal (http://azphewas.com/).

Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and mediating genes for more than half such disorders remain to be discovered. We implemented whole-genome sequencing (WGS) in a national healthcare system to streamline diagnosis and to discover unknown aetiological variants, in the coding and non-coding regions of the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed aetiological. Using WGS of UK Biobank 1 , we showed that rare alleles can explain the presence of some individuals in the tails of a quantitative red blood cell (RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare. 3. Ferreira CR. The burden of rare diseases.

PurposeUsing exome sequencing, the underlying variants in many persons with autosomal recessive diseases remain undetected. We explored autosomal recessive Stargardt disease (STGD1) as a model to identify the missing heritability.MethodsSequencing of ABCA4 was performed in 8 STGD1 cases with one variant and p.Asn1868Ile in trans, 25 cases with one variant, and 3 cases with no ABCA4 variant. The effect of intronic variants was analyzed using in vitro splice assays in HEK293T cells and patient-derived fibroblasts. Antisense oligonucleotides were used to correct splice defects.ResultsIn 24 of the probands (67%), one known and five novel deep-intronic variants were found. The five novel variants resulted in messenger RNA pseudoexon inclusions, due to strengthening of cryptic splice sites or by disrupting a splicing silencer motif. Variant c.769-784C>T showed partial insertion of a pseudoexon and was found in cis with c.5603A>T (p.Asn1868Ile), so its causal role could not be fully established. Variant c.4253+43G>A resulted in partial skipping of exon 28. Remarkably, antisense oligonucleotides targeting the aberrant splice processes resulted in (partial) correction of all splicing defects.ConclusionOur data demonstrate the importance of assessing noncoding variants in genetic diseases, and show the great potential of splice modulation therapy for deep-intronic variants.

BackgroundThe genetic cause of primary immunodeficiency disease (PID) carries prognostic information.ObjectiveWe conducted a whole-genome sequencing study assessing a large proportion of the NIHR BioResource–Rare Diseases cohort.MethodsIn the predominantly European study population of principally sporadic unrelated PID cases (n = 846), a novel Bayesian method identified nuclear factor κB subunit 1 (NFKB1) as one of the genes most strongly associated with PID, and the association was explained by 16 novel heterozygous truncating, missense, and gene deletion variants. This accounted for 4% of common variable immunodeficiency (CVID) cases (n = 390) in the cohort. Amino acid substitutions predicted to be pathogenic were assessed by means of analysis of structural protein data. Immunophenotyping, immunoblotting, and ex vivo stimulation of lymphocytes determined the functional effects of these variants. Detailed clinical and pedigree information was collected for genotype-phenotype cosegregation analyses.ResultsBoth sporadic and familial cases demonstrated evidence of the noninfective complications of CVID, including massive lymphadenopathy (24%), unexplained splenomegaly (48%), and autoimmune disease (48%), features prior studies correlated with worse clinical prognosis. Although partial penetrance of clinical symptoms was noted in certain pedigrees, all carriers have a deficiency in B-lymphocyte differentiation. Detailed assessment of B-lymphocyte numbers, phenotype, and function identifies the presence of an increased CD21low B-cell population. Combined with identification of the disease-causing variant, this distinguishes between healthy subjects, asymptomatic carriers, and clinically affected cases.ConclusionWe show that heterozygous loss-of-function variants in NFKB1 are the most common known monogenic cause of CVID, which results in a temporally progressive defect in the formation of immunoglobulin-producing B cells.