SummaryBackgroundHuman genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount.MethodsThe Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team.FindingsAround 80 000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation.InterpretationImplementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene–phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial.FundingHealth Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health.

Exome sequencing of parent-offspring trios is a popular strategy for identifying causative genetic variants in children with rare diseases. This method owes its strength to the leveraging of inheritance information, which facilitates de novo variant calling, inference of compound heterozygosity, and the identification of inheritance anomalies. Uniparental disomy describes the inheritance of a homologous chromosome pair from only one parent. This aberration is important to detect in genetic disease studies because it can result in imprinting disorders and recessive diseases. We have developed a software tool to detect uniparental disomy from child–mother–father genotype data that uses a binomial test to identify chromosomes with a significant burden of uniparentally inherited genotypes. This tool is the first to read VCF-formatted genotypes, to perform integrated copy number filtering, and to use a statistical test inherently robust for use in platforms of varying genotyping density and noise characteristics. Simulations demonstrated superior accuracy compared with previously developed approaches. We implemented the method on 1057 trios from the Deciphering Developmental Disorders project, a trio-based rare disease study, and detected six validated events, a significant enrichment compared with the population prevalence of UPD (1 in 3500), suggesting that most of these events are pathogenic. One of these events represents a known imprinting disorder, and exome analyses have identified rare homozygous candidate variants, mainly in the isodisomic regions of UPD chromosomes, which, among other variants, provide targets for further genetic and functional evaluation.

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We assess the potential impact of rural health insurance and pension reforms on macroeconomic outcomes and social welfare in a dynamic general equilibrium model calibrated to the Chinese economy. We analyze transition paths as well as steady state responses to the new policies. The current reforms in China provide modest rural pensions and reimbursement of a portion of healthcare costs, but at rates that are substantially lower than are already in place in the urban sector. We investigate the potential effect of raising the rural benefit rates to those enjoyed in the urban sector. While both reforms reduce income per capita, we show that the health insurance reforms are potentially welfare improving if they are implemented in a way that leads to reduced out-of-pocket health spending. The welfare gains are driven by rural health insurance providing relief from the risk of catastrophic medical expenditures that can wipe out household savings and force long working hours. A pay-as-you-go rural pension results in a welfare gain in the short-run but welfare loss in the long-run due to the distorting effects of taxes. Despite an increase in required financing due to an aging population, the welfare impact of rural health insurance remains positive when incorporating the projected old-age dependency ratio for the year 2050. However, a pay-as-you-go rural pension creates large income and welfare losses with 2050 demographics.

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