Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are ...selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we investigated how well the current archive of genetic evidence predicts drug mechanisms. We found that, among well-studied indications, the proportion of drug mechanisms with direct genetic support increases significantly across the drug development pipeline, from 2.0% at the preclinical stage to 8.2% among mechanisms for approved drugs, and varies dramatically among disease areas. We estimate that selecting genetically supported targets could double the success rate in clinical development. Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs.
Mitochondria undergo architectural/functional changes in response to metabolic inputs. How this process is regulated in physiological feeding/fasting states remains unclear. Here we show that ...mitochondrial dynamics (notably fission and mitophagy) and biogenesis are transcriptional targets of the circadian regulator Bmal1 in mouse liver and exhibit a metabolic rhythm in sync with diurnal bioenergetic demands. Bmal1 loss-of-function causes swollen mitochondria incapable of adapting to different nutrient conditions accompanied by diminished respiration and elevated oxidative stress. Consequently, liver-specific Bmal1 knockout (LBmal1KO) mice accumulate oxidative damage and develop hepatic insulin resistance. Restoration of hepatic Bmal1 activities in high-fat-fed mice improves metabolic outcomes, whereas expression of Fis1, a fission protein that promotes quality control, rescues morphological/metabolic defects of LBmal1KO mitochondria. Interestingly, Bmal1 homolog AHA-1 in C. elegans retains the ability to modulate oxidative metabolism and lifespan despite lacking circadian regulation. These results suggest clock genes are evolutionarily conserved energetics regulators.
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•Bmal1 controls rhythmic mitochondrial dynamics gene expression in the liver•The dynamic mitochondrial activity manages metabolic flexibility and oxidative stress•Bmal1 depletion causes enlarged, dysfunctional mitochondria and hepatic pathologies•C. elegans Bmal1 homolog AHA-1 regulates oxidative metabolism and extends lifespan
Mitochondrial dynamics plays an important role in metabolic adaptation to nutrient influx. Jacobi et al. reveal that the circadian regulator Bmal1 controls rhythmic mitochondrial dynamics gene expression in the liver. Hepatic Bmal1 gene deletion causes abnormal mitochondrial morphology, elevated oxidative damage, and metabolic inflexibility.
The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma ...protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.
Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes ...encoding drug targets in 14,002 individuals. We find rare variants are abundant (1 every 17 bases) and geographically localized, so that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. We conclude that because of rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.
Although much is known about human genetic variation, such information is typically ignored in assembling new genomes. Instead, reads are mapped to a single reference, which can lead to poor ...characterization of regions of high sequence or structural diversity. We introduce a population reference graph, which combines multiple reference sequences and catalogs of variation. The genomes of new samples are reconstructed as paths through the graph using an efficient hidden Markov model, allowing for recombination between different haplotypes and additional variants. By applying the method to the 4.5-Mb extended MHC region on human chromosome 6, combining 8 assembled haplotypes, the sequences of known classical HLA alleles and 87,640 SNP variants from the 1000 Genomes Project, we demonstrate using simulations, SNP genotyping, and short-read and long-read data how the method improves the accuracy of genome inference and identified regions where the current set of reference sequences is substantially incomplete.
Statistical imputation of classical HLA alleles in case-control studies has become established as a valuable tool for identifying and fine-mapping signals of disease association in the MHC. ...Imputation into diverse populations has, however, remained challenging, mainly because of the additional haplotypic heterogeneity introduced by combining reference panels of different sources. We present an HLA type imputation model, HLA*IMP:02, designed to operate on a multi-population reference panel. HLA*IMP:02 is based on a graphical representation of haplotype structure. We present a probabilistic algorithm to build such models for the HLA region, accommodating genotyping error, haplotypic heterogeneity and the need for maximum accuracy at the HLA loci, generalizing the work of Browning and Browning (2007) and Ron et al. (1998). HLA*IMP:02 achieves an average 4-digit imputation accuracy on diverse European panels of 97% (call rate 97%). On non-European samples, 2-digit performance is over 90% for most loci and ethnicities where data available. HLA*IMP:02 supports imputation of HLA-DPB1 and HLA-DRB3-5, is highly tolerant of missing data in the imputation panel and works on standard genotype data from popular genotyping chips. It is publicly available in source code and as a user-friendly web service framework.
Evidence from human genetics supporting the therapeutic hypothesis increases the likelihood that a drug will succeed in clinical trials. Rare and common disease genetics yield a wide array of alleles ...with a range of effect sizes that can proxy for the effect of a drug in disease. Recent advances in large scale population collections and whole genome sequencing approaches have provided a rich resource of human genetic evidence to support drug target selection. As the range of phenotypes profiled increases and ever more alleles are discovered across world-wide populations, these approaches will increasingly influence multiple stages across the lifespan of a drug discovery programme.
•Over 90% of clinical trials fail due to lack of efficacy or safety.•Genetic evidence of gene-disease association favours drug success in trials.•Naturally occurring genetic variants anticipate the effect of drugs.•Population biobanks enable unprecedented opportunities to leverage genetic data.•We discuss how genetics can systematically inform therapeutic hypothesis building.
The well-known frameworks of the type M2(dobdc) (dobdc(4-) = 2,5-dioxido-1,4-benzenedicarboxylate) have numerous potential applications in gas storage and separations, owing to their exceptionally ...high concentration of coordinatively unsaturated metal surface sites, which can interact strongly with small gas molecules such as H2. Employing a related meta-functionalized linker that is readily obtained from resorcinol, we now report a family of structural isomers of this framework, M2(m-dobdc) (M = Mg, Mn, Fe, Co, Ni; m-dobdc(4-) = 4,6-dioxido-1,3-benzenedicarboxylate), featuring exposed M(2+) cation sites with a higher apparent charge density. The regioisomeric linker alters the symmetry of the ligand field at the metal sites, leading to increases of 0.4-1.5 kJ/mol in the H2 binding enthalpies relative to M2(dobdc). A variety of techniques, including powder X-ray and neutron diffraction, inelastic neutron scattering, infrared spectroscopy, and first-principles electronic structure calculations, are applied in elucidating how these subtle structural and electronic differences give rise to such increases. Importantly, similar enhancements can be anticipated for the gas storage and separation properties of this new family of robust and potentially inexpensive metal-organic frameworks.
Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from ...nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and nearly complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the United States or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside California, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.
Abstract
Background
A total of 10%–20% of patients develop long-term toxicity following radiotherapy for prostate cancer. Identification of common genetic variants associated with susceptibility to ...radiotoxicity might improve risk prediction and inform functional mechanistic studies.
Methods
We conducted an individual patient data meta-analysis of six genome-wide association studies (n = 3871) in men of European ancestry who underwent radiotherapy for prostate cancer. Radiotoxicities (increased urinary frequency, decreased urinary stream, hematuria, rectal bleeding) were graded prospectively. We used grouped relative risk models to test associations with approximately 6 million genotyped or imputed variants (time to first grade 2 or higher toxicity event). Variants with two-sided Pmeta less than 5 × 10−8 were considered statistically significant. Bayesian false discovery probability provided an additional measure of confidence. Statistically significant variants were evaluated in three Japanese cohorts (n = 962). All statistical tests were two-sided.
Results
Meta-analysis of the European ancestry cohorts identified three genomic signals: single nucleotide polymorphism rs17055178 with rectal bleeding (Pmeta = 6.2 × 10−10), rs10969913 with decreased urinary stream (Pmeta = 2.9 × 10−10), and rs11122573 with hematuria (Pmeta = 1.8 × 10−8). Fine-scale mapping of these three regions was used to identify another independent signal (rs147121532) associated with hematuria (Pconditional = 4.7 × 10−6). Credible causal variants at these four signals lie in gene-regulatory regions, some modulating expression of nearby genes. Previously identified variants showed consistent associations (rs17599026 with increased urinary frequency, rs7720298 with decreased urinary stream, rs1801516 with overall toxicity) in new cohorts. rs10969913 and rs17599026 had similar effects in the photon-treated Japanese cohorts.
Conclusions
This study increases the understanding of the architecture of common genetic variants affecting radiotoxicity, points to novel radio-pathogenic mechanisms, and develops risk models for testing in clinical studies. Further multinational radiogenomics studies in larger cohorts are worthwhile.
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