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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. The UK Biobank Exome Sequencing Consortium aims to sequence all the exomes of approximately 500,000 UK Biobank participants. This Perspective describes the results from approximately 200,000 exomes and discusses the lessons learned from this UK Biobank–biopharmaceutical company collaboration.

Infants and young children born prematurely are at high risk of severe acute lower respiratory infection (ALRI) caused by respiratory syncytial virus (RSV). In this study, we aimed to assess the global disease burden of and risk factors for RSV-associated ALRI in infants and young children born before 37 weeks of gestation. We conducted a systematic review and meta-analysis of aggregated data from studies published between Jan 1, 1995, and Dec 31, 2021, identified from MEDLINE, Embase, and Global Health, and individual participant data shared by the Respiratory Virus Global Epidemiology Network on respiratory infectious diseases. We estimated RSV-associated ALRI incidence in community, hospital admission, in-hospital mortality, and overall mortality among children younger than 2 years born prematurely. We conducted two-stage random-effects meta-regression analyses accounting for chronological age groups, gestational age bands (early preterm, <32 weeks gestational age [wGA], and late preterm, 32 to <37 wGA), and changes over 5-year intervals from 2000 to 2019. Using individual participant data, we assessed perinatal, sociodemographic, and household factors, and underlying medical conditions for RSV-associated ALRI incidence, hospital admission, and three severity outcome groups (longer hospital stay [>4 days], use of supplemental oxygen and mechanical ventilation, or intensive care unit admission) by estimating pooled odds ratios (ORs) through a two-stage meta-analysis (multivariate logistic regression and random-effects meta-analysis). This study is registered with PROSPERO, CRD42021269742. We included 47 studies from the literature and 17 studies with individual participant-level data contributed by the participating investigators. We estimated that, in 2019, 1 650 000 (95% uncertainty range [UR] 1 350 000–1 990 000) RSV-associated ALRI episodes, 533 000 (385 000–730 000) RSV-associated hospital admissions, 3050 (1080–8620) RSV-associated in-hospital deaths, and 26 760 (11 190–46 240) RSV-attributable deaths occurred in preterm infants worldwide. Among early preterm infants, the RSV-associated ALRI incidence rate and hospitalisation rate were significantly higher (rate ratio [RR] ranging from 1·69 to 3·87 across different age groups and outcomes) than for all infants born at any gestational age. In the second year of life, early preterm infants and young children had a similar incidence rate but still a significantly higher hospitalisation rate (RR 2·26 [95% UR 1·27–3·98]) compared with all infants and young children. Although late preterm infants had RSV-associated ALRI incidence rates similar to that of all infants younger than 1 year, they had higher RSV-associated ALRI hospitalisation rate in the first 6 months (RR 1·93 [1·11–3·26]). Overall, preterm infants accounted for 25% (95% UR 16–37) of RSV-associated ALRI hospitalisations in all infants of any gestational age. RSV-associated ALRI in-hospital case fatality ratio in preterm infants was similar to all infants. The factors identified to be associated with RSV-associated ALRI incidence were mainly perinatal and sociodemographic characteristics, and factors associated with severe outcomes from infection were mainly underlying medical conditions including congenital heart disease, tracheostomy, bronchopulmonary dysplasia, chronic lung disease, or Down syndrome (with ORs ranging from 1·40 to 4·23). Preterm infants face a disproportionately high burden of RSV-associated disease, accounting for 25% of RSV hospitalisation burden. Early preterm infants have a substantial RSV hospitalisation burden persisting into the second year of life. Preventive products for RSV can have a substantial public health impact by preventing RSV-associated ALRI and severe outcomes from infection in preterm infants. EU Innovative Medicines Initiative Respiratory Syncytial Virus Consortium in Europe.

A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing 1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study 2 . We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P  ≤ 2.18 × 10 −11 . Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension ( SLC9A3R2 ), diabetes ( MAP3K15 , FAM234A ) and asthma ( SLC27A3 ). Six genes were associated with brain imaging phenotypes, including two involved in neural development ( GBE1 , PLD1 ). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene–trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale. Whole-exome sequencing analysis of 454,787 individuals in the UK Biobank is used to examine the association of protein-coding variants with nearly 4,000 health-related traits, identifying 564 distinct genes with significant trait associations.

Observations from human microbiome studies are often conflicting or inconclusive. Many factors likely contribute to these issues including small cohort sizes, sample collection, and handling and processing differences. The field of microbiome research is moving from 16S rDNA gene sequencing to a more comprehensive genomic and functional representation through whole-genome sequencing (WGS) of complete communities. Here we performed quantitative and qualitative analyses comparingWGS metagenomic data from human stool specimens using the Illumina Nextera XT and Illumina TruSeq DNA PCR-free kits, and the KAPA Biosystems Hyper Prep PCR and PCR-free systems. Significant differences in taxonomy are observed among the four different next-generation sequencing library preparations using a DNA mock community and a cell control of known concentration. We also revealed biases in error profiles, duplication rates, and loss of reads representing organisms that have a high %G+C content that can significantly impact results. As with all methods, the use of benchmarking controls has revealed critical differences among methods that impact sequencing results and later would impact study interpretation. We recommend that the community adopt PCR-free–based approaches to reduce PCR bias that affects calculations of abundance and to improve assemblies for accurate taxonomic assignment. Furthermore, the inclusion of a known-input cell spike-in control provides accurate quantitation of organisms in clinical samples.

Enlargement of the aorta is an important risk factor for aortic aneurysm and dissection, a leading cause of morbidity in the developed world. Here we performed automated extraction of ascending aortic diameter from cardiac magnetic resonance images of 36,021 individuals from the UK Biobank, followed by genome-wide association. We identified lead variants across 41 loci, including genes related to cardiovascular development ( HAND2 , TBX20 ) and Mendelian forms of thoracic aortic disease ( ELN , FBN1 ). A polygenic score significantly predicted prevalent risk of thoracic aortic aneurysm and the need for surgical intervention for patients with thoracic aneurysm across multiple ancestries within the UK Biobank, FinnGen, the Penn Medicine Biobank and the Million Veterans Program (MVP). Additionally, we highlight the primary causal role of blood pressure in reducing aortic dilation using Mendelian randomization. Overall, our findings provide a roadmap for using genetic determinants of human anatomy to understand cardiovascular development while improving prediction of diseases of the thoracic aorta. Trans-ancestry genome-wide analyses identify multiple loci associated with ascending aortic diameter. A polygenic score constructed from these loci predicted prevalent risk of thoracic aortic aneurysm in independent populations.

Charge carrier trapping is an important phenomenon in nanocrystal (NC) decay dynamics because it reduces photoluminescence (PL) quantum efficiencies and obscures efforts to understand the interaction of NC excitons with their surroundings. Particularly crucial to our understanding of excitation dynamics in, e.g., multiNC assemblies, would be a way of differentiating between processes involving trap states and those that do not. Direct optical measurement of NC trap state processes is not usually possible because they have negligible transition dipole moments; however, they are known to indirectly affect exciton photoluminescence. Here, we develop a framework, based on Marcus electron transfer theory, to determine NC trap state dynamics from time-resolved NC exciton PL measurements. Our results demonstrate the sensitivity of PL to interfacial dynamics, indicating that the technique can be used as an indirect but effective probe of trap distribution changes. We anticipate that this study represents a step toward understanding how excitons in nanocrystals interact with their surroundings: a quality that must be optimized for their efficient application in photovoltaics, photodetectors, or chemical sensors.

Bacillus thuringiensis (Bt) is a soil-dwelling bacteria that forms small crystalline inclusions within the confines of its cell wall as a response to starvation. These inclusions are composed exclusively of proteins with highly specific insecticidal activity, leading them to become the most widespread bio-pesticide worldwide. Unpicking the activity of these proteins requires a detailed understanding of both their structure and their arrangement within the crystal lattice. The small size of these inclusions makes them challenging for conventional structural biology as they are difficult to locate and their small number of unit cells produces much weaker Bragg scattering for a given flux. Electron microscopy can readily image nanocrystals and the larger scattering cross section of electrons relative to X-rays allows meaningful diffraction signals to be measured from far fewer crystalline repeats. In this work, we explore electron diffraction (specifically microED and serialED) as a tool for structure determination of Bt toxins in their native state. We demonstrate that electron diffraction methods are comparable and in some cases surpass other cutting-edge crystallographic methods such as serial femtosecond crystallography at Free electron lasers. The workflow presented should also apply to other sub-micron crystals that are highly beam-sensitive and difficult to study by other means.

Background The microbiome of the human gut serves a role in a number of physiological processes, but can be altered through effects of age, diet, and disturbances such as antibiotics. Several studies have demonstrated that commonly used antibiotics can have sustained impacts on the diversity and the composition of the gut microbiome. The impact of the two most overused antibiotics, azithromycin, and amoxicillin, in the human microbiome has not been thoroughly described. In this study, we recruited a group of individuals and unrelated controls to decipher the effects of the commonly used antibiotics amoxicillin and azithromycin on their gut microbiomes. Results We characterized the gut microbiomes by metagenomic sequencing followed by characterization of the resulting microbial communities. We found that there were clear and sustained effects of the antibiotics on the gut microbial community with significant alterations in the representations of Bifidobacterium species in response to azithromycin (macrolide antibiotic). These results were supported by significant increases identified in putative antibiotic resistance genes associated with macrolide resistance. Importantly, we did not identify these trends in the unrelated control individuals. There were no significant changes observed in other members of the microbial community. Conclusions As we continue to focus on the role that the gut microbiome plays and how disturbances induced by antibiotics might affect our overall health, elucidating members of the community most affected by their use is of critical importance to understanding the impacts of common antibiotics on those who take them. Clinical Trial Registration Number NCT05169255. This trial was retrospectively registered on 23–12-2021.

Oral health has substantial economic importance, with over $100 billion spent on dental care in the United States annually. The microbiome plays a critical role in oral health, yet remains poorly classified. To address the question of how microbial diversity and function in the oral cavities of children relate to caries diagnosis, we surveyed the supragingival plaque biofilm microbiome in 44 juvenile twin pairs. Using shotgun sequencing, we constructed a genome encyclopedia describing the core supragingival plaque microbiome. This unveiled several new previously uncharacterized but ubiquitous microbial lineages in the oral microbiome. Caries is a microbial community metabolic disorder that cannot be described by a single etiology, and our results provide the information needed for next-generation diagnostic tools and therapeutics for caries. To address the question of how microbial diversity and function in the oral cavities of children relates to caries diagnosis, we surveyed the supragingival plaque biofilm microbiome in 44 juvenile twin pairs. Using shotgun sequencing, we constructed a genome encyclopedia describing the core supragingival plaque microbiome. Caries phenotypes contained statistically significant enrichments in specific genome abundances and distinct community composition profiles, including strain-level changes. Metabolic pathways that are statistically associated with caries include several sugar-associated phosphotransferase systems, antimicrobial resistance, and metal transport. Numerous closely related previously uncharacterized microbes had substantial variation in central metabolism, including the loss of biosynthetic pathways resulting in auxotrophy, changing the ecological role. We also describe the first complete Gracilibacteria genomes from the human microbiome. Caries is a microbial community metabolic disorder that cannot be described by a single etiology, and our results provide the information needed for next-generation diagnostic tools and therapeutics for caries. IMPORTANCE Oral health has substantial economic importance, with over $100 billion spent on dental care in the United States annually. The microbiome plays a critical role in oral health, yet remains poorly classified. To address the question of how microbial diversity and function in the oral cavities of children relate to caries diagnosis, we surveyed the supragingival plaque biofilm microbiome in 44 juvenile twin pairs. Using shotgun sequencing, we constructed a genome encyclopedia describing the core supragingival plaque microbiome. This unveiled several new previously uncharacterized but ubiquitous microbial lineages in the oral microbiome. Caries is a microbial community metabolic disorder that cannot be described by a single etiology, and our results provide the information needed for next-generation diagnostic tools and therapeutics for caries.

The potential for commensal microorganisms indigenous to a host (the 'microbiome' or 'microbiota') to alter infection outcome by influencing host-pathogen interplay is largely unknown. We used a multi-omics \"systems\" approach, incorporating proteomics, metabolomics, glycomics, and metagenomics, to explore the molecular interplay between the murine host, the pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium), and commensal gut microorganisms during intestinal infection with S. Typhimurium. We find proteomic evidence that S. Typhimurium thrives within the infected 129/SvJ mouse gut without antibiotic pre-treatment, inducing inflammation and disrupting the intestinal microbiome (e.g., suppressing Bacteroidetes and Firmicutes while promoting growth of Salmonella and Enterococcus). Alteration of the host microbiome population structure was highly correlated with gut environmental changes, including the accumulation of metabolites normally consumed by commensal microbiota. Finally, the less characterized phase of S. Typhimurium's lifecycle was investigated, and both proteomic and glycomic evidence suggests S. Typhimurium may take advantage of increased fucose moieties to metabolize fucose while growing in the gut. The application of multiple omics measurements to Salmonella-induced intestinal inflammation provides insights into complex molecular strategies employed during pathogenesis between host, pathogen, and the microbiome.