Best practices for government agencies to publish data: lessons from COVID-19.

Without data, knowing how to respond to the COVID-19 pandemic would have been impossible. Data were crucial to understanding how the disease spread and which efforts successfully protected people. Yet, national agencies often did not publish their data in an optimal way, which made responding to the pandemic challenging. Therefore, learning from what went well and what did not for the future is crucial. Drawing on our first-hand experience of republishing COVID-19 data, we identify seven best practices for how to publish data in an optimal way: collect the data that are relevant; make them comparable; clearly document the data; share them frequently and promptly; publish data at a stable location; choose a reusable format; and license others to reuse the data. These best practices are straightforward, inexpensive, and achievable, with some countries already having implemented most of them during the COVID-19 pandemic. More government agencies following these best practices will enable others to access their data and address the world's public health challenges-including the next pandemic.

Common and rare variant associations with latent traits underlying depression, bipolar disorder, and schizophrenia.

Genetic studies in psychiatry have primarily focused on the effects of common genetic variants, but few have investigated the role of rare genetic variants, particularly for major depression. In order to explore the role of rare variants in the gap between estimates of single nucleotide polymorphism (SNP) heritability and twin study heritability, we examined the contribution of common and rare genetic variants to latent traits underlying psychiatric disorders using high-quality imputed genotype data from the UK Biobank. Using a pre-registered analysis, we used items from the UK Biobank Mental Health Questionnaire relevant to three psychiatric disorders: major depression (N = 134,463), bipolar disorder (N = 117,376) and schizophrenia (N = 130,013) and identified a general hierarchical factor for each that described participants' responses. We calculated participants' scores on these latent traits and conducted single-variant genetic association testing (MAF > 0.05%), gene-based burden testing and pathway association testing associations with these latent traits. We tested for enrichment of rare variants (MAF 0.05-1%) in genes that had been previously identified by common variant genome-wide association studies, and genes previously associated with Mendelian disorders having relevant symptoms. We found moderate genetic correlations between the latent traits in our study and case-control phenotypes in previous genome-wide association studies, and identified one common genetic variant (rs72657988, minor allele frequency = 8.23%, p = 1.01 × 10-9) associated with the general factor of schizophrenia, but no other single variants, genes or pathways passed significance thresholds in this analysis, and we did not find enrichment in previously identified genes.

Whole genome sequencing reveals epistasis effects within RET for Hirschsprung disease.

Common variants in RET and NRG1 have been associated with Hirschsprung disease (HSCR), a congenital disorder characterised by incomplete innervation of distal gut, in East Asian (EA) populations. However, the allelic effects so far identified do not fully explain its heritability, suggesting the presence of epistasis, where effect of one genetic variant differs depending on other (modifier) variants. Few instances of epistasis have been documented in complex diseases due to modelling complexity and data challenges. We proposed four epistasis models to comprehensively capture epistasis for HSCR between and within RET and NRG1 loci using whole genome sequencing (WGS) data in EA samples. 65 variants within the Topologically Associating Domain (TAD) of RET demonstrated significant epistasis with the lead enhancer variant (RET+3; rs2435357). These epistatic variants formed two linkage disequilibrium (LD) clusters represented by rs2506026 and rs2506028 that differed in minor allele frequency and the best-supported epistatic model. Intriguingly, rs2506028 is in high LD with one cis-regulatory variant (rs2506030) highlighted previously, suggesting that detected epistasis might be mediated through synergistic effects on transcription regulation of RET. Our findings demonstrated the advantages of WGS data for detecting epistasis, and support the presence of interactive effects of regulatory variants in RET for HSCR.

Clarifying the causes of consistent and inconsistent findings in genetics.

As research in genetics has advanced, some findings have been unexpected or shown to be inconsistent between studies or datasets. The reasons these inconsistencies arise are complex. Results from genetic studies can be affected by various factors including statistical power, linkage disequilibrium, quality control, confounding and selection bias, as well as real differences from interactions and effect modifiers, which may be informative about the mechanisms of traits and disease. Statistical artefacts can manifest as differences between results but they can also conceal underlying differences, which implies that their critical examination is important for understanding the underpinnings of traits. In this review, we examine these factors and outline how they can be identified and conceptualised with structural causal models. We explain the consequences they have on genetic estimates, such as genetic associations, polygenic scores, family- and genome-wide heritability, and describe methods to address them to aid in the estimation of true effects of genetic variation. Clarifying these factors can help researchers anticipate when results are likely to diverge and aid researchers' understanding of causal relationships between genes and complex traits.

A Requirement for Neutrophil Glycosaminoglycans in Chemokine:Receptor Interactions Is Revealed by the Streptococcal Protease SpyCEP.

To evade the immune system, the lethal human pathogen Streptococcus pyogenes produces SpyCEP, an enzyme that cleaves the C-terminal α-helix of CXCL8, resulting in markedly impaired recruitment of neutrophils to sites of invasive infection. The basis for chemokine inactivation by SpyCEP is, however, poorly understood, as the core domain of CXCL8 known to interact with CXCL8 receptors is unaffected by enzymatic cleavage. We examined the in vitro migration of human neutrophils and observed that their ability to efficiently navigate a CXCL8 gradient was compromised following CXCL8 cleavage by SpyCEP. SpyCEP-mediated cleavage of CXCL8 also impaired CXCL8-induced migration of transfectants expressing the human chemokine receptors CXCR1 or CXCR2. Despite possessing an intact N terminus and preserved disulfide bonds, SpyCEP-cleaved CXCL8 had impaired binding to both CXCR1 and CXCR2, pointing to a requirement for the C-terminal α-helix. SpyCEP-cleaved CXCL8 had similarly impaired binding to the glycosaminoglycan heparin. Enzymatic removal of neutrophil glycosaminoglycans was observed to ablate neutrophil navigation of a CXCL8 gradient, whereas navigation of an fMLF gradient remained largely intact. We conclude, therefore, that SpyCEP cleavage of CXCL8 results in chemokine inactivation because of a requirement for glycosaminoglycan binding in productive chemokine:receptor interactions. This may inform strategies to inhibit the activity of SpyCEP, but may also influence future approaches to inhibit unwanted chemokine-induced inflammation.

Actionable secondary findings from whole-genome sequencing of 954 East Asians.

Recently, the American College of Medical Genetics (ACMG) recommended the return of actionable secondary findings detected from clinical sequencing. The reported frequency of secondary findings in Asian populations were highly variable and it is unclear whether the uniformity in coverage offered by whole-genome sequencing (WGS) may impact the estimate. In this analysis, we aimed to refine the rate of secondary findings on East Asians through a large-scale WGS study. We classified 1256 protein-altering or splicing variants of the 59 actionable genes detected from WGS of 954 East Asians in strict accordance with the ACMG and the Association for Molecular Pathology guidelines. A total of 21 pathogenic or likely pathogenic variants were detected in 24 of the 954 East Asian genomes with an estimate of 2.5% of East Asians carrying actionable variants. Although the overall estimate of secondary findings was consistent with those reported for non-East Asian ethnicities, genetic and allelic heterogeneity was observed. WGS offers a wider breadth of coverage over WES, which highlights the need to further investigate the variable sensitivity of WES and WGS in the detection of secondary findings. Identifying secondary findings in populations underrepresented in previous genetic literature might improve variant interpretation and has a profound impact on local decision-making with regard to the cost-effectiveness of returning the secondary findings from clinical sequencing.