No evidence that ACE2 or TMPRSS2 drive population disparity in COVID risks.

Early in the SARS-CoV2 pandemic, in this journal, Hou et al. (BMC Med 18:216, 2020) interpreted public genotype data, run through functional prediction tools, as suggesting that members of particular human populations carry potentially COVID-risk-increasing variants in genes ACE2 and TMPRSS2 far more often than do members of other populations. Beyond resting on predictions rather than clinical outcomes, and focusing on variants too rare to typify population members even jointly, their claim mistook a well known artifact (that large samples reveal more of a population's variants than do small samples) as if showing real and congruent population differences for the two genes, rather than lopsided population sampling in their shared source data. We explain that artifact, and contrast it with empirical findings, now ample, that other loci shape personal COVID risks far more significantly than do ACE2 and TMPRSS2-and that variation in ACE2 and TMPRSS2 per se unlikely exacerbates any net population disparity in the effects of such more risk-informative loci.

GenomeDiver: a platform for phenotype-guided medical genomic diagnosis.

PURPOSE: Making a diagnosis from clinical genomic sequencing requires well-structured phenotypic data to guide genotype interpretation. A patient's phenotypic features can be documented using the Human Phenotype Ontology (HPO), generating terms used to prioritize genes potentially causing the patient's disease. We have developed GenomeDiver to provide a user interface for clinicians that allows more effective collaboration with the clinical diagnostic laboratory, with the goal of improving the success of the diagnostic process. METHODS: GenomeDiver uses genomic data to prompt reverse phenotyping of patients undergoing genetic testing, enriching the amount and quality of structured phenotype data for the diagnostic laboratory, and helping clinicians to explore and flag diseases potentially causing their patient's presentation. RESULTS: We show how GenomeDiver communicates the clinician's informed insights to the diagnostic lab in the form of HPO terms for interpretation of genomic sequencing data. We describe our user-driven design process, the engineering of the software for efficiency, security and portability, and examples of the performance of GenomeDiver using genomic testing data. CONCLUSION: GenomeDiver is a first step in a new approach to genomic diagnostics that enhances laboratory-clinician interactions, with the goal of directly engaging clinicians to improve the outcome of genomic diagnostic testing.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

GUÍA: a digital platform to facilitate result disclosure in genetic counseling.

PURPOSE: Use of genomic sequencing is increasing at a pace that requires technological solutions to effectively meet the needs of a growing patient population. We developed GUÍA, a web-based application, to enhance the delivery of genomic results and related clinical information to patients and families. METHODS: GUÍA development occurred in five overlapping phases: formative research, content development, stakeholder/community member input, user interface design, and web application development. Development was informed by formative qualitative research involving parents (N = 22) whose children underwent genomic testing. Participants enrolled in the NYCKidSeq pilot study (N = 18) completed structured feedback interviews post-result disclosure using GUÍA. Genetic specialists, researchers, patients, and community stakeholders provided their perspectives on GUÍA's design to ensure technical, cultural, and literacy appropriateness. RESULTS: NYCKidSeq participants responded positively to the use of GUÍA to deliver their children's results. All participants (N = 10) with previous experience with genetic testing felt GUÍA improved result disclosure, and 17 (94%) participants said the content was clear. CONCLUSION: GUÍA communicates complex genomic information in an understandable and personalized manner. Initial piloting demonstrated GUÍA's utility for families enrolled in the NYCKidSeq pilot study. Findings from the NYCKidSeq clinical trial will provide insight into GUÍA's effectiveness in communicating results among diverse, multilingual populations.

Chromosome Y-encoded antigens associate with acute graft-versus-host disease in sex-mismatched stem cell transplant.

Allogeneic hematopoietic stem cell transplantation (allo-HCT) is a curative option for blood cancers, but the coupled effects of graft-versus-tumor and graft-versus-host disease (GVHD) limit its broader application. Outcomes improve with matching at HLAs, but other factors are required to explain residual risk of GVHD. In an effort to identify genetic associations outside the major histocompatibility complex, we conducted a genome-wide clinical outcomes study on 205 acute myeloid leukemia patients and their fully HLA-A-, HLA-B-, HLA-C-, HLA-DRB1-, and HLA-DQB1-matched (10/10) unrelated donors. HLA-DPB1 T-cell epitope permissibility mismatches were observed in less than half (45%) of acute GVHD cases, motivating a broader search for genetic factors affecting clinical outcomes. A novel bioinformatics workflow adapted from neoantigen discovery found no associations between acute GVHD and known, HLA-restricted minor histocompatibility antigens (MiHAs). These results were confirmed with microarray data from an additional 988 samples. On the other hand, Y-chromosome-encoded single-nucleotide polymorphisms in 4 genes (PCDH11Y, USP9Y, UTY, and NLGN4Y) did associate with acute GVHD in male patients with female donors. Males in this category with acute GVHD had more Y-encoded variant peptides per patient with higher predicted HLA-binding affinity than males without GVHD who matched X-paralogous alleles in their female donors. Methods and results described here have an immediate impact for allo-HCT, warranting further development and larger genomic studies where MiHAs are clinically relevant, including cancer immunotherapy, solid organ transplant, and pregnancy.

Whole-genome sequencing and the clinician: a tale of two cities.

BACKGROUND: Clinicians are faced with unprecedented opportunities to identify the genetic aetiologies of hitherto molecularly uncharacterised conditions via the use of high-throughput sequencing. Access to genomic technology and resultant data is no longer limited to clinicians, geneticists and bioinformaticians, however; ongoing commercialisation gives patients themselves ever greater access to sequencing services. We report an increasingly common medical scenario by describing two neuromuscular patients--a mother and adult son--whose consumer access to whole-genome sequencing affected their diagnostic journey. RESULTS: Whole-genome sequencing initiated by the patients--to predict their risk of common diseases--revealed that they share several variants potentially relevant to neuromuscular diseases, which initially sidetracked diagnostic efforts. Since eventual clinical reassessment, including muscle imaging, pointed towards Bethlem myopathy, a collagen VI-related myopathy, we pursued Sanger sequencing of COL6A1, COL6A2 and COL6A3. This targeted approach revealed a heterozygous causative variant in COL6A3 (c.6365G>T (p.Gly2122Val)), shared by both individuals, that was not flagged by the interpretation of the whole-genome sequencing data. CONCLUSIONS: This report highlights the essential interplay of clinical and genomic expertise in realising the potential of high-throughput sequencing. In an era when patients themselves may bring their own data to the table, definitively identifying clinically significant genomic variants will require close collaboration among clinicians, geneticists and bioinformaticians.

Balanced codon usage optimizes eukaryotic translational efficiency.

Cellular efficiency in protein translation is an important fitness determinant in rapidly growing organisms. It is widely believed that synonymous codons are translated with unequal speeds and that translational efficiency is maximized by the exclusive use of rapidly translated codons. Here we estimate the in vivo translational speeds of all sense codons from the budding yeast Saccharomyces cerevisiae. Surprisingly, preferentially used codons are not translated faster than unpreferred ones. We hypothesize that this phenomenon is a result of codon usage in proportion to cognate tRNA concentrations, the optimal strategy in enhancing translational efficiency under tRNA shortage. Our predicted codon-tRNA balance is indeed observed from all model eukaryotes examined, and its impact on translational efficiency is further validated experimentally. Our study reveals a previously unsuspected mechanism by which unequal codon usage increases translational efficiency, demonstrates widespread natural selection for translational efficiency, and offers new strategies to improve synthetic biology.

Human polymorphism and human-chimpanzee divergence in pseudoautosomal region correlate with local recombination rate.

Previous studies have shown widespread correlation between nucleotide polymorphism and recombination rate, but the cause of this correlation is unresolved. One explanation is that recombination is associated with point mutations, potentially through mutagenic effects of meiotic crossover. This hypothesis predicts that regions of frequent recombination should show both elevated nucleotide diversity within a species and increased nucleotide divergence between species. Here we tested this hypothesis by studying the human short-arm pseudoautosomal region (PAR1), which recombines between X and Y chromosomes in men at a rate approximately 20 times the genome average. We sequenced dispersed intronic loci within PAR1 in a panel of humans and in the chimpanzee and directly measured sequence variation and recombination rate from these data. In line with previous reports, we saw a correlation between human polymorphism level and local recombination rate. Moreover, we also found a highly significant correlation between human-chimpanzee divergence and recombination rate. These results are consistent with the hypothesis that recombination is associated with point mutations, possibly because recombination is mutagenic.

Recombination has little effect on the rate of sequence divergence in pseudoautosomal boundary 1 among humans and great apes.

Recent studies indicated that recombination is strongly mutagenic. In particular, data from the mouse pseudoautosomal boundary (PAB) suggested that locally intensive recombination increased the nucleotide substitution rate by more than 100-fold and greatly increased the GC content. Here we study the rates of nucleotide substitution in eight introns of the human and great ape XG gene, which spans the boundary between the pseudoautosomal region 1 (PAR1) and the X-specific region. Contrary to what is expected under the above hypothesis, our sequence data from humans and great apes reveal that the PAR1 introns of XG have actually evolved slightly slower than X-specific introns. Only when a New World monkey was compared with hominoids were the rates slightly increased in the PAR1 introns. In terms of base composition, although the intergenic regions of the human PAR1 show a significant increase of G and C nucleotides, the base composition of the surveyed PAR1 introns is similar to that of the X-specific introns. Direct and indirect evidence indicates that the recombination rate is, indeed, much higher in PAR1 introns than in X-specific introns, and that the present PAB has persisted since the common ancestor of hominoids. Therefore, the mutagenic effect of recombination is far weaker than previously proposed, at least in hominoid PABs.