Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank.

The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a private-public partnership between the UK Biobank (UKB) and eight biopharmaceutical companies that will complete the sequencing of exomes for all ~500,000 UKB participants. Here, we describe the early results from ~200,000 UKB participants and the features of this project that enabled its success. The biopharmaceutical industry has increasingly used human genetics to improve success in drug discovery. Recognizing the need for large-scale human genetics data, as well as the unique value of the data access and contribution terms of the UKB, the UKB-ESC was formed. As a result, exome data from 200,643 UKB enrollees are now available. These data include ~10 million exonic variants-a rich resource of rare coding variation that is particularly valuable for drug discovery. The UKB-ESC precompetitive collaboration has further strengthened academic and industry ties and has provided teams with an opportunity to interact with and learn from the wider research community.

SOMAscan Proteomics Identifies Serum Biomarkers Associated With Liver Fibrosis in Patients With NASH.

Nonalcoholic steatohepatitis (NASH) is a major cause of liver-related morbidity and mortality worldwide. Liver fibrosis stage, a key component of NASH, has been linked to the risk of mortality and liver-related clinical outcomes. Currently there are no validated noninvasive diagnostics that can differentiate between fibrosis stages in patients with NASH; many existing tests do not reflect underlying disease pathophysiology. Noninvasive biomarkers are needed to identify patients at high-risk of NASH with advanced fibrosis. This was a retrospective study of patients with histologically proven NASH with fibrosis stages 0-4. The SOMAscan proteomics platform was used to quantify 1,305 serum proteins in a discovery cohort (n = 113). In patients with advanced (stages 3-4) versus early fibrosis (stages 0-2), 97 proteins with diverse biological functions were differentially expressed. Next, fibrosis-stage classification models were explored using a machine learning-based approach to prioritize the biomarkers for further evaluation. A four-protein model differentiated patients with stage 0-1 versus stage 2-4 fibrosis (area under the receiver operating characteristic curve [AUROC] = 0.74), while a 12-protein classifier differentiated advanced versus early fibrosis (AUROC = 0.83). Subsequently, the model's performance was validated in two independent cohorts (n = 71 and n = 32) with similar results (AUROC = 0.74-0.78). Our advanced fibrosis model performed similarly to or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and nonalcoholic fatty liver disease (NAFLD) fibrosis score-based models for all three cohorts. Conclusion: A SOMAscan proteomics-based exploratory classifier for advanced fibrosis, consisting of biomarkers that reflect the complexity of NASH pathophysiology, demonstrated similar performance in independent validation cohorts and performed similarly or better than Fibrosis-4 index, aspartate aminotransferase-to-platelet ratio index, and NAFLD fibrosis score. Further studies are warranted to evaluate the clinical utility of these biomarker panels in patients with NAFLD.

Association of inflammatory biomarkers with clinical outcomes in nivolumab-treated patients with advanced hepatocellular carcinoma.

BACKGROUND & AIMS: Nivolumab, a programmed death (PD)-1 (PD-1) inhibitor, led to durable responses, manageable safety, and increased survival in patients with advanced hepatocellular carcinoma (HCC). In our retrospective analysis, we studied the immunobiology and potential associations between biomarkers and outcomes with nivolumab in HCC. METHODS: Fresh and archival tumour samples from dose-escalation and dose-expansion phases of the CheckMate 040 trial were analysed by immunohistochemistry and RNA sequencing to assess several inflammatory gene expression signatures, including CD274 (PD-ligand 1 [PD-L1]), CD8A, LAG3, and STAT1. Biomarkers were assessed for association with clinical outcomes (best overall response by blinded independent central review per RECIST v1.1 and overall survival [OS]). RESULTS: Complete or partial tumour responses were observed in PD-L1-positive and PD-L1-negative patients treated with nivolumab monotherapy. Median OS was 28.1 (95% CI 18.2-n.a.) vs. 16.6 months (95% CI 14.2-20.2) for patients with tumour PD-L1 ≥1% vs. <1% (p = 0.03). Increased CD3 and CD8 showed a non-significant trend towards improved OS (both p = 0.08), and macrophage markers were not associated with OS. Tumour PD-1 and PD-L1 expression were associated with improved OS (p = 0.05 and p = 0.03, respectively). An inflammatory gene signature consisting of 4 genes was associated with improved objective response rate (p = 0.05) and OS (p = 0.01). CONCLUSIONS: PD-1 and PD-L1 expression, biomarkers of inflammation, and inflammatory gene signatures trended with improved survival and response. While further confirmation within a larger phase III trial is needed to evaluate predictive value of these biomarkers, these exploratory analyses suggest that anti-tumour immune response may play a role in the treatment benefit of nivolumab in HCC. LAY SUMMARY: Certain tests may be used to provide a picture of how a tumour is escaping the immune system, allowing it to continue to grow and create more tumours. Therapies such as nivolumab are designed to help the immune system fight the tumour. These tests may be used to determine how effective such therapies will be in the treatment of advanced liver cancer. NCT NUMBER: NCT01658878.

NaV channel variants in patients with painful and nonpainful peripheral neuropathy.

OBJECTIVE: To examine the incidence of nonsynonymous missense variants in SCN9A (NaV1.7), SCN10A (NaV1.8), and SCN11A (NaV1.9) in patients with painful and nonpainful peripheral neuropathy. METHODS: Next-generation sequencing was performed on 457 patient DNA samples provided by the Peripheral Neuropathy Research Registry (PNRR). The patient diagnosis was as follows: 278 idiopathic peripheral neuropathy (67% painful and 33% nonpainful) and 179 diabetic distal polyneuropathy (77% painful and 23% nonpainful). RESULTS: We identified 36 (SCN9A), 31 (SCN10A), and 15 (SCN11A) nonsynonymous missense variants, with 47.7% of patients carrying a low-frequency (minor allele frequency <5%) missense variant in at least 1 gene. The incidence of previously reported gain-of-function missense variants was low (≤3%), and these were detected in patients with and without pain. There were no significant differences in missense variant allele frequencies of any gene, or SCN9A haplotype frequencies, between PNRR patients with painful or nonpainful peripheral neuropathy. PNRR patient SCN9A and SCN11A missense variant allele frequencies were not significantly different from the Exome Variant Server, European American (EVS-EA) reference population. For SCN10A, there was a significant increase in the alternate allele frequency of the common variant p.V1073A and low-frequency variant pS509P in PNRR patients compared with EVS-EA and the 1000 Genomes European reference populations. CONCLUSIONS: These results suggest that identification of a genetically defined subpopulation for testing of NaV1.7 inhibitors in patients with peripheral neuropathy is unlikely and that additional factors, beyond expression of previously reported disease "mutations," are more important for the development of painful neuropathy than previously discussed.

The genome as pharmacopeia: association of genetic dose with phenotypic response.

The majority of compounds that enter clinical trials fail to meet regulatory standards for marketed therapeutics. Success in clinical trials is increased when therapies are directed against targets for which genetic variants have been linked to disease risk or progression in humans. Here we review how genome-wide association studies (GWAS) have furthered our understanding of the genetic basis of common disease, and how GWAS findings could stimulate development of novel drugs. Genetic screens that associate variants with clinical phenotypes of interest, like pharmacological screens that associate compounds with in vitro responses of interest, establish an intervention-response relationship on which a therapeutic hypothesis can be based. We highlight the similarities between the GWAS approach and well-established principles in early drug discovery, from primary screen through lead identification. We believe that integration of genetic and pharmacological screens will considerably enhance the development of therapeutic interventions with clear benefit to patients.

Windshield splatter analysis with the Galaxy metagenomic pipeline.

How many species inhabit our immediate surroundings? A straightforward collection technique suitable for answering this question is known to anyone who has ever driven a car at highway speeds. The windshield of a moving vehicle is subjected to numerous insect strikes and can be used as a collection device for representative sampling. Unfortunately the analysis of biological material collected in that manner, as with most metagenomic studies, proves to be rather demanding due to the large number of required tools and considerable computational infrastructure. In this study, we use organic matter collected by a moving vehicle to design and test a comprehensive pipeline for phylogenetic profiling of metagenomic samples that includes all steps from processing and quality control of data generated by next-generation sequencing technologies to statistical analyses and data visualization. To the best of our knowledge, this is also the first publication that features a live online supplement providing access to exact analyses and workflows used in the article.

Wheels within wheels: clues to the evolution of the Gnas and Gnal loci.

The Gnas and Gnal loci, which encode the alpha subunits of stimulatory G-proteins, are among the most complex eukaryotic genes. They combine elaborate patterns of imprinting, alternative splicing, and antisense transcription with tissue- and developmental stage-specific expression. Different regions of these genes evolve at drastically different rates such that some show complete conservation, whereas others are virtually unalignable. Yet, the most unusual feature of the Gnas/Gnal complex is the presence of the longest known overlap between coding regions resulting in the production of two unrelated proteins: XLalphas and its putative regulator ALEX. Here we elucidate the evolutionary history of both loci and uncover new complexities. First, alternatively spliced regions of both loci evolve under varying selective regimes echoing their distinct biological roles. Second, an enigmatic alternative transcript of the Gnas locus, known as Nesp, is likely bicistronic. Third, rodent XLalphas and ALEX follow an evolutionary trajectory distinct from that of other mammals and show extensive sequence variation in the internal repeat region, a fact that might be explained by variation in the robustness of imprinting. Fourth, we show that the overlap between the XLalphas and ALEX frames is restricted to eutherian mammals. Finally, we reconcile our findings with extensive physiological data derived from animal models.

A first look at ARFome: dual-coding genes in mammalian genomes.

Coding of multiple proteins by overlapping reading frames is not a feature one would associate with eukaryotic genes. Indeed, codependency between codons of overlapping protein-coding regions imposes a unique set of evolutionary constraints, making it a costly arrangement. Yet in cases of tightly coexpressed interacting proteins, dual coding may be advantageous. Here we show that although dual coding is nearly impossible by chance, a number of human transcripts contain overlapping coding regions. Using newly developed statistical techniques, we identified 40 candidate genes with evolutionarily conserved overlapping coding regions. Because our approach is conservative, we expect mammals to possess more dual-coding genes. Our results emphasize that the skepticism surrounding eukaryotic dual coding is unwarranted: rather than being artifacts, overlapping reading frames are often hallmarks of fascinating biology.

Oscillating evolution of a mammalian locus with overlapping reading frames: an XLalphas/ALEX relay.

XLalphas and ALEX are structurally unrelated mammalian proteins translated from alternative overlapping reading frames of a single transcript. Not only are they encoded by the same locus, but a specific XLalphas/ALEX interaction is essential for G-protein signaling in neuroendocrine cells. A disruption of this interaction leads to abnormal human phenotypes, including mental retardation and growth deficiency. The region of overlap between the two reading frames evolves at a remarkable speed: the divergence between human and mouse ALEX polypeptides makes them virtually unalignable. To trace the evolution of this puzzling locus, we sequenced it in apes, Old World monkeys, and a New World monkey. We show that the overlap between the two reading frames and the physical interaction between the two proteins force the locus to evolve in an unprecedented way. Namely, to maintain two overlapping protein-coding regions the locus is forced to have high GC content, which significantly elevates its intrinsic evolutionary rate. However, the two encoded proteins cannot afford to change too quickly relative to each other as this may impair their interaction and lead to severe physiological consequences. As a result XLalphas and ALEX evolve in an oscillating fashion constantly balancing the rates of amino acid replacements. This is the first example of a rapidly evolving locus encoding interacting proteins via overlapping reading frames, with a possible link to the origin of species-specific neurological differences.