GenePy - a score for estimating gene pathogenicity in individuals using next-generation sequencing data.

BACKGROUND: Next-generation sequencing is revolutionising diagnosis and treatment of rare diseases, however its application to understanding common disease aetiology is limited. Rare disease applications binarily attribute genetic change(s) at a single locus to a specific phenotype. In common diseases, where multiple genetic variants within and across genes contribute to disease, binary modelling cannot capture the burden of pathogenicity harboured by an individual across a given gene/pathway. We present GenePy, a novel gene-level scoring system for integration and analysis of next-generation sequencing data on a per-individual basis that transforms NGS data interpretation from variant-level to gene-level. This simple and flexible scoring system is intuitive and amenable to integration for machine learning, network and topological approaches, facilitating the investigation of complex phenotypes. RESULTS: Whole-exome sequencing data from 508 individuals were used to generate GenePy scores. For each variant a score is calculated incorporating: i) population allele frequency estimates; ii) individual zygosity, determined through standard variant calling pipelines and; iii) any user defined deleteriousness metric to inform on functional impact. GenePy then combines scores generated for all variants observed into a single gene score for each individual. We generated a matrix of ~ 14,000 GenePy scores for all individuals for each of sixteen popular deleteriousness metrics. All per-gene scores are corrected for gene length. The majority of genes generate GenePy scores < 0.01 although individuals harbouring multiple rare highly deleterious mutations can accumulate extremely high GenePy scores. In the absence of a comparator metric, we examine GenePy performance in discriminating genes known to be associated with three common, complex diseases. A Mann-Whitney U test conducted on GenePy scores for this positive control gene in cases versus controls demonstrates markedly more significant results (p = 1.37 × 10- 4) compared to the most commonly applied association tool that combines common and rare variation (p = 0.003). CONCLUSIONS: Per-gene per-individual GenePy scores are intuitive when assessing genetic variation in individual patients or comparing scores between groups. GenePy outperforms the currently accepted best practice tools for combining common and rare variation. GenePy scores are suitable for downstream data integration with transcriptomic and proteomic data that also report at the gene level.

Clinical efficacy of a next-generation sequencing gene panel for primary immunodeficiency diagnostics.

Primary immunodeficiencies (PIDs) are rare monogenic inborn errors of immunity that result in impairment of functions of the human immune system. PIDs have a broad phenotype with increased morbidity and mortality, and treatment choices are often complex. With increased accessibility of next-generation sequencing (NGS), the rate of discovery of genetic causes for PID has increased exponentially. Identification of an underlying monogenic diagnosis provides important clinical benefits for patients with the potential to alter treatments, facilitate genetic counselling, and pre-implantation diagnostics. We investigated a NGS PID panel of 242 genes within clinical care across a range of PID phenotypes. We also evaluated Phenomizer to predict causal genes from human phenotype ontology (HPO) terms. Twenty-seven participants were recruited, and a total of 15 reportable variants were identified in 48% (13/27) of the participants. The panel results had implications for treatment in 37% (10/27) of participants. Phenomizer identified the genes harbouring variants from HPO terms in 33% (9/27) of participants. This study shows the clinical efficacy that genetic testing has in the care of PID. However, it also highlights some of the disadvantages of gene panels in the rapidly moving field of PID genomics and current challenges in HPO term assignment for PID.

Commercial chicken breeds exhibit highly divergent patterns of linkage disequilibrium.

The analysis of linkage disequilibrium (LD) underpins the development of effective genotyping technologies, trait mapping and understanding of biological mechanisms such as those driving recombination and the impact of selection. We apply the Malécot-Morton model of LD to create additive LD maps that describe the high-resolution LD landscape of commercial chickens. We investigated LD in chickens (Gallus gallus) at the highest resolution to date for broiler, white egg and brown egg layer commercial lines. There is minimal concordance between breeds of fine-scale LD patterns (correlation coefficient <0.21), and even between discrete broiler lines. Regions of LD breakdown, which may align with recombination hot spots, are enriched near CpG islands and transcription start sites (P<2.2 × 10-16), consistent with recent evidence described in finches, but concordance in hot spot locations between commercial breeds is only marginally greater than random. As in other birds, functional elements in the chicken genome are associated with recombination but, unlike evidence from other bird species, the LD landscape is not stable in the populations studied. The development of optimal genotyping panels for genome-led selection programmes will depend on careful analysis of the LD structure of each line of interest. Further study is required to fully elucidate the mechanisms underlying highly divergent LD patterns found in commercial chickens.

Operational Definition of Active and Healthy Ageing (AHA): A Conceptual Framework.

Health is a multi-dimensional concept, capturing how people feel and function. The broad concept of Active and Healthy Ageing was proposed by the World Health Organisation (WHO) as the process of optimizing opportunities for health to enhance quality of life as people age. It applies to both individuals and population groups. A universal Active and Healthy Ageing definition is not available and it may differ depending on the purpose of the definition and/or the questions raised. While the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) has had a major impact, a definition of Active and Healthy Ageing is urgently needed. A meeting was organised in Montpellier, France, October 20-21, 2014 as the annual conference of the EIP on AHA Reference Site MACVIA-LR (Contre les Maladies Chroniques pour un Vieillissement Actif en Languedoc Roussillon) to propose an operational definition of Active and Healthy Ageing including tools that may be used for this. The current paper describes the rationale and the process by which the aims of the meeting will be reached.

Resolving clinical diagnoses for syndromic cleft lip and/or palate phenotypes using whole-exome sequencing.

Individuals from three families ascertained in Bogota, Colombia, showing syndromic phenotypes, including cleft lip and/or palate, were exome-sequenced. In each case, sequencing revealed the underlying causal variation confirming or establishing diagnoses. The findings include very rare and novel variants providing insights into genotype and phenotype relationships. These include the molecular diagnosis of an individual with Nager syndrome and a family exhibiting an atypical incontinentia pigmenti phenotype with a missense mutation in IKBKG. IKBKG mutations are typically associated with preterm male death, but this variant is associated with survival for 8-15 days. The third family exhibits unusual phenotypic features and the proband received a provisional diagnosis of Pierre Robin sequence (PRS). Affected individuals share a novel deleterious mutation in IRF6. Mutations in IRF6 cause Van der Woude and popliteal pterygium syndrome and contribute to nonsyndromic cleft lip phenotypes but have not previously been associated with a PRS phenotype. Exome sequencing followed by in silico screening to identify candidate causal variant(s), and functional assay in some cases offers a powerful route to establishing molecular diagnoses. This approach is invaluable for conditions showing phenotypic and/or genetic heterogeneity including cleft lip and/or palate phenotypes where many underlying causal genes have not been identified.