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Hand hygiene is at the core of effective infection prevention and control (IPC) programmes. 10 years after the development of the WHO Multimodal Hand Hygiene Improvement Strategy, we aimed to ascertain the level of hand hygiene implementation and its drivers in health-care facilities through a global WHO survey.From Jan 16 to Dec 31, 2019, IPC professionals were invited through email and campaigns to complete the online Hand Hygiene Self-Assessment Framework (HHSAF). A geospatial clustering algorithm selected unique health-care facilities responses and post-stratification weighting was applied to improve representativeness. Weighted median HHSAF scores and IQR were reported. Drivers of the HHSAF score were determined through a generalised estimation equation.3206 unique responses from 90 countries (46% WHO Member States) were included. The HHSAF score indicated an intermediate hand hygiene implementation level (350 points, IQR 248-430), which was positively associated with country income level and health-care facility funding structure. System Change had the highest score (85 points, IQR 55-100), whereby alcohol-based hand rub at the point of care has become standard practice in many health-care facilities, especially in high-income countries. Institutional Safety Climate had the lowest score (55 points, IQR 35-75). From 2015 to 2019, the median HHSAF score in health-care facilities participating in both HHSAF surveys (n=190) stagnated.Most health-care facilities had an intermediate level of hand hygiene implementation or higher, for which health-care facility funding and country income level were important drivers. Availability of resources, leadership, and organisational support are key elements to further improve quality of care and provide access to safe care for all.WHO, Geneva University Hospitals and Faculty of Medicine, and WHO Collaborating Center on Patient Safety, Geneva, Switzerland.

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health–supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes

Hearing impairment (HI) is characterized by extensive genetic heterogeneity. To determine the population-specific contribution of known autosomal recessive nonsyndromic (ARNS)HI genes and variants to HI etiology; pathogenic and likely pathogenic (PLP) ARNSHI variants were selected from ClinVar and the Deafness Variation Database and their frequencies were obtained from gnomAD for seven populations. ARNSHI prevalence due to PLP variants varies greatly by population ranging from 96.9 affected per 100,000 individuals for Ashkenazi Jews to 5.2 affected per 100,000 individuals for Africans/African Americans. For Europeans, Finns have the lowest prevalence due to ARNSHI PLP variants with 9.5 affected per 100,000 individuals. For East Asians, Latinos, non-Finish Europeans, and South Asians, ARNSHI prevalence due to PLP variants ranges from 17.1 to 33.7 affected per 100,000 individuals. ARNSHI variants that were previously reported in a single ancestry or family were observed in additional populations, e.g., USH1C p.(Q723*) reported in a Chinese family was the most prevalent pathogenic variant observed in gnomAD for African/African Americans. Variability between populations is due to how extensively ARNSHI has been studied, ARNSHI prevalence and ancestry specific ARNSHI variant architecture which is impacted by population history. Our study demonstrates that additional gene and variant discovery studies are necessary for all populations and particularly for individuals of African ancestry.

Analysis of large genomic datasets, including gnomAD, reveals that partial LRRK2 loss of function is not strongly associated with diseases, serving as an example of how human genetics can be leveraged for target validation in drug discovery. Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes(1,2). Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson's disease(3,4), suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns(5-8), the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)(9), 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work(10), confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.

Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening., A large empirical assessment of sequence-resolved structural variants from 14,891 genomes across diverse global populations in the Genome Aggregation Database (gnomAD) provides a reference map for disease-association studies, population genetics, and diagnostic screening.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03176-6.

SummaryGenetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organism’s function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.

Motivation The correct classification of missense variants as benign or pathogenic remains challenging. Pathogenic variants are expected to have higher deleterious prediction scores than benign variants in the same gene. However, most of the existing variant annotation tools do not reference the score range of benign population variants on gene level. Results We present a web-application, Variant Score Ranker, which enables users to rapidly annotate variants and perform gene-specific variant score ranking on the population level. We also provide an intuitive example of how gene- and population-calibrated variant ranking scores can improve epilepsy variant prioritization. Availability and implementation http://vsranker.broadinstitute.org Supplementary information Supplementary data are available at Bioinformatics online.

Significance CRISPR-Cas9 holds enormous potential for therapeutic genome editing. Effective therapy requires treatment to be efficient and safe with minimal toxicity. The sequence-based targeting for CRISPR systems necessitates consideration of the unique genomes for each patient targeted for therapy. We show using 7,444 whole-genome sequences that SNPs and indels can reduce on-target CRISPR activity and increase off-target potential when targeting therapeutically implicated loci; however, these occurrences are relatively rare. We further identify that differential allele frequencies among populations may result in population-specific alterations in CRISPR targeting specificity. Our findings suggest that human genetic variation should be considered in the design and evaluation of CRISPR-based therapy to minimize risk of treatment failure and/or adverse outcomes., The CRISPR-Cas9 nuclease system holds enormous potential for therapeutic genome editing of a wide spectrum of diseases. Large efforts have been made to further understanding of on- and off-target activity to assist the design of CRISPR-based therapies with optimized efficacy and safety. However, current efforts have largely focused on the reference genome or the genome of cell lines to evaluate guide RNA (gRNA) efficiency, safety, and toxicity. Here, we examine the effect of human genetic variation on both on- and off-target specificity. Specifically, we utilize 7,444 whole-genome sequences to examine the effect of variants on the targeting specificity of ∼3,000 gRNAs across 30 therapeutically implicated loci. We demonstrate that human genetic variation can alter the off-target landscape genome-wide including creating and destroying protospacer adjacent motifs (PAMs). Furthermore, single-nucleotide polymorphisms (SNPs) and insertions/deletions (indels) can result in altered on-target sites and novel potent off-target sites, which can predispose patients to treatment failure and adverse effects, respectively; however, these events are rare. Taken together, these data highlight the importance of considering individual genomes for therapeutic genome-editing applications for the design and evaluation of CRISPR-based therapies to minimize risk of treatment failure and/or adverse outcomes.

The genetic basis combined with the sporadic occurrence of amyotrophic lateral sclerosis (ALS) suggests a role of de novo mutations in disease pathogenesis. Previous studies provided some evidence for this hypothesis; however, results were conflicting: no genes with recurrent occurring de novo mutations were identified and different pathways were postulated. In this study, we analyzed whole-exome data from 82 new patient-parents trios and combined it with the datasets of all previously published ALS trios (173 trios in total). The per patient de novo rate was not higher than expected based on the general population (P = 0.40). We showed that these mutations are not part of the previously postulated pathways, and gene-gene interaction analysis found no enrichment of interacting genes in this group (P = 0.57). Also, we were able to show that the de novo mutations in ALS patients are located in genes already prone for de novo mutations (P < 1 × 10(−15)). Although the individual effect of rare de novo mutations in specific genes could not be assessed, our results indicate that, in contrast to previous hypothesis, de novo mutations in general do not impose a major burden on ALS risk.

Negative selection against deleterious alleles produced by mutation is the most common form of natural selection, which strongly influences within-population variation and interspecific divergence. However, some fundamental properties of negative selection remain obscure. In particular, it is still not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis must produce negative linkage disequilibrium between deleterious alleles, and therefore, underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function (LoF) alleles in eight independent datasets from modern human andDrosophila melanogasterpopulations. Thus, ongoing selection against deleterious alleles is characterized by synergistic epistasis, which can explain how human and fly populations persist despite very high genomic deleterious mutation rates.

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project. © 2014 Macmillan Publishers Limited All rights reserved.

Germline mutation detection from human DNA sequence data is challenging due to the rarity of such events relative to the intrinsic error rates of sequencing technologies and the uneven coverage across the genome. We developed PhaseByTransmission (PBT) to identify de novo single nucleotide variants and short insertions and deletions (indels) from sequence data collected in parent-offspring trios. We compute the joint probability of the data given the genotype likelihoods in the individual family members, the known familial relationships and a prior probability for the mutation rate. Candidate de novo mutations (DNMs) are reported along with their posterior probability, providing a systematic way to prioritize them for validation. Our tool is integrated in the Genome Analysis Toolkit and can be used together with the ReadBackedPhasing module to infer the parental origin of DNMs based on phase-informative reads. Using simulated data, we show that PBT outperforms existing tools, especially in low coverage data and on the X chromosome. We further show that PBT displays high validation rates on empirical parent-offspring sequencing data for whole-exome data from 104 trios and X-chromosome data from 249 parent-offspring families. Finally, we demonstrate an association between father’s age at conception and the number of DNMs in female offspring’s X chromosome, consistent with previous literature reports.European Journal of Human Genetics advance online publication, 23 November 2016; doi:10.1038/ejhg.2016.147.

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, current studies on SVs have failed to provide a global view of the full spectrum of SVs and to integrate them into reference panels of genetic variation. Here, we analyzed 769 individuals from 250 Dutch families, whole genome sequenced at an average coverage of 14.5x, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion of the structural variants (36%) were discovered in the size range of 21 to 100bp, a size range which remains under reported in many studies. Furthermore, we detected 4 megabases of novel sequence, extending the human pangenome with 11 new active transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with a structural variant and demonstrate that our panel facilitates accurate imputation of SVs into unrelated individuals, which is essential for future genome-wide association studies.

The rate at which human genomes mutate is a central biological parameter that has many implications for our ability to understand demographic and evolutionary phenomena. We present a method for inferring mutation and gene-conversion rates by using the number of sequence differences observed in identical-by-descent (IBD) segments together with a reconstructed model of recent population-size history. This approach is robust to, and can quantify, the presence of substantial genotyping error, as validated in coalescent simulations. We applied the method to 498 trio-phased sequenced Dutch individuals and inferred a point mutation rate of 1.66 × 10(-8) per base per generation and a rate of 1.26 × 10(-9) for

The rate at which human genomes mutate is a central biological parameter that has many implications for our ability to understand demographic and evolutionary phenomena. We present a method for inferring mutation and gene conversion rates using the number of sequence differences observed in identical-by-descent (IBD) segments together with a reconstructed model of recent population size history. This approach is robust to, and can quantify, the presence of substantial genotyping error, as validated in coalescent simulations. We applied the method to 498 trio-phased Dutch individuals from the Genome of the Netherlands (GoNL) project, sequenced at an average depth of 13×. We infer a point mutation rate of 1.66 ± 0.04 × 10-8per base per generation, and a rate of 1.26 ± 0.06 × 10-9for -6, consistent with recent reports. We find that recombination does not have observable mutagenic effects after gene conversion is accounted for, and that local gene conversion rates reflect recombination rates. We detect a strong enrichment for recent deleterious variation among mismatching variants found within IBD regions, and observe summary statistics of local IBD sharing to closely match previously proposed metrics of background selection, but find no significant effects of selection on our estimates of mutation rate. We detect no evidence for strong variation of mutation rates in a number of genomic annotations obtained from several recent studies.

Contains fulltext : 137213.pdf (Publisher’s version ) (Closed access) Whole-genome sequencing enables complete characterization of genetic variation, but geographic clustering of rare alleles demands many diverse populations be studied. Here we describe the Genome of the Netherlands (GoNL) Project, in which we sequenced the whole genomes of 250 Dutch parent-offspring families and constructed a haplotype map of 20.4 million single-nucleotide variants and 1.2 million insertions and deletions. The intermediate coverage ( approximately 13x) and trio design enabled extensive characterization of structural variation, including midsize events (30-500 bp) previously poorly catalogued and de novo mutations. We demonstrate that the quality of the haplotypes boosts imputation accuracy in independent samples, especially for lower frequency alleles. Population genetic analyses demonstrate fine-scale structure across the country and support multiple ancient migrations, consistent with historical changes in sea level and flooding. The GoNL Project illustrates how single-population whole-genome sequencing can provide detailed characterization of genetic variation and may guide the design of future population studies.

Item does not contain fulltext Birdshot chorioretinopathy (BSCR) is a rare form of autoimmune uveitis that can lead to severe visual impairment. Intriguingly, >95% of cases carry the HLA-A29 allele, which defines the strongest documented HLA association for a human disease. We have conducted a genome-wide association study in 96 Dutch and 27 Spanish cases, and 398 unrelated Dutch and 380 Spanish controls. Fine-mapping the primary MHC association through high-resolution imputation at classical HLA loci, identified HLA-A*29:02 as the principal MHC association (odds ratio (OR) = 157.5, 95% CI 91.6-272.6, P = 6.6 x 10(-74)). We also identified two novel susceptibility loci at 5q15 near ERAP2 (rs7705093; OR = 2.3, 95% CI 1.7-3.1, for the T allele, P = 8.6 x 10(-8)) and at 14q32.31 in the TECPR2 gene (rs150571175; OR = 6.1, 95% CI 3.2-11.7, for the A allele, P = 3.2 x 10(-8)). The association near ERAP2 was confirmed in an independent British case-control samples (combined meta-analysis P = 1.7 x 10(-9)). Functional analyses revealed that the risk allele of the polymorphism near ERAP2 is strongly associated with high mRNA and protein expression of ERAP2 in B cells. This study further defined an extremely strong MHC risk component in BSCR, and detected evidence for a novel disease mechanism that affects peptide processing in the endoplasmic reticulum.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License.-- et al., [Background]: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. [Results]: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. [Conclusions]: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups., This work was supported by funds provided through the Gene Partnership and the Manton Center for Orphan Disease Research at Boston Children’s Hospital and the Center for Biomedical Informatics at Harvard Medical School and by generous donations in-kind of genomic sequencing services by Life Technologies (Carlsbad, CA, USA) and Complete Genomics (Mountain View, CA, USA).