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.

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

SpyCEP-cleaved CXCL8 is unable to bind and activate CXCL8 receptors.

Neutrophil glycosaminoglycans are required for migration along a CXCL8 gradient.

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.

Pouch excision: indications and outcomes

AIM

Restorative proctocolectomy with ileal-pouch anal anastomosis is the procedure of choice for ulcerative colitis. Unfortunately, up to 10% of pouches will fail, requiring either reconstruction or excision. While several series have reported on the aetiology of pouch failure, no study to date has focused on the postoperative complications associated with pouch excision.

METHODS

Patients who had excision of ileoanal reservoir with ileostomy (CPT code 45136) were included. Data abstracted included preoperative, operative and postoperative variables. A Kaplan-Meier curve of pouch survival was performed.

RESULTS

In all, 147 patients met the inclusion criteria for the study. The median age of patients was 47 years (73 women), and 132 had a diagnosis of ulcerative colitis at the time of colectomy. The most common indications for pouch excision were sepsis (n = 46; 31%) and Crohn's disease (n = 37; 25%). 84 (57%) patients experienced short-term (< 30 days) postoperative complications, the most common of which was a surgical site infection (n = 32; 21%); 55 (37%) patients had long-term complications (> 30 days) postoperatively, the most common of which was a return to the operating room (n = 19; 13%) largely for perineal wounds. Thirty-day mortality was zero. 4.8%, 47.6%, 65.3% and 84.4% of patients had undergone pouch excision by 1, 5, 10 and 20 years from the time of pouch construction, respectively.

CONCLUSIONS

Pouch excision has a high rate of both short- and long-term postoperative complications. Patients should be appropriately counselled to set expectations accordingly. In view of these findings we suggest that this operation should ideally be performed at a high volume centre with the availability of a multidisciplinary surgical team.