Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Scoping Review on the Use of Drugs Targeting JAK/STAT Pathway in Atopic Dermatitis, Vitiligo, and Alopecia Areata.

The JAK/STAT signaling pathway is involved in the immune-mediated inflammatory skin diseases atopic dermatitis (AD), vitiligo, and alopecia areata (AA), and represents a potential target when developing treatments. So far, no drugs targeting this pathway have been approved for the treatment of dermatological diseases. We reviewed the use of drugs blocking the JAK/STAT pathway in the aforementioned diseases. An a priori protocol was published. We used Joanna Briggs Institute Reviewer's Manual methodology to conduct the review and PRISMA Extension for Scoping Review (PRISMA-ScR) to report results. MEDLINE, EMBASE, CINAHL, Scopus, and Web of Science databases were searched in a three-step approach on April 2019 by two researchers. Ninety-six mainly multicenter observational studies were included (66, 10, and 20 studies on AA, vitiligo, and AD, respectively). Tofacitinib and ruxolitinib were mainly used for the three diseases, and also upadacitinib, abrocitinib, baricitinib, cerdulatinib, delgocitinib, gusacitinib for AD, and baricitinib, PF-06700841, and PF-06651600 for AA. All patients with AD improved, whereas patients with vitiligo and patients with AA showed varied responses, including unresponsive cases. The safety profiles were similar for all drugs and diseases, mainly comprising mild or no adverse events. Evidence on the efficacy and safety of drugs targeting the JAK/STAT pathway for the treatment of patients with AD, vitiligo, or AA is increasing but is still of low quality

Frontal fibrosing alopecia shows robust T helper 1 and Janus kinase 3 skewing

Frontal fibrosing alopecia (FFA) is a scarring alopecia with unclear pathogenesis and a progressive course. The disease has a major impact on patients' quality of life and there is a lack of effective treatment to halt disease progression. We profiled lesional and nonlesional scalp biopsies collected in 2017 from patients with FFA (n = 12) compared with scalp biopsies from patients with alopecia areata (AA) (n = 8) and controls (n = 8) to evaluate gene and protein expression, including the primary outcome (CXCL9). We determined significant differences between biomarkers using a two-sided Student's t-test adjusting P-values by false discovery rate. Significant increases were seen in CD8+ cytotoxic T cells, CD11c+ dendritic cells, CD103+ and CD69+ tissue-resident memory T cells in FFA and AA vs. control scalp (P < 0·05), with corresponding significantly upregulated granzyme B mRNA, particularly in FFA (P < 0·01). In AA, cellular infiltrates were primarily concentrated at the bulb, while in FFA these were mainly localized at the bulge. FFA demonstrated significant upregulation of T helper 1/intereferon (IFN) (IFN-γ, CXCL9/CXCL10), the Janus kinase/signal transducers and activators of transcription (JAK-STAT) pathway (STAT1, JAK3) and fibrosis-related products (vimentin, fibronectin; P < 0·05), with no concomitant downregulation of hair keratins and the T-regulatory marker, forkhead box P3, which were decreased in AA. The stem cell markers CD200 and K15 demonstrated significantly reduced expression only in FFA (P < 0·05). These data suggest that follicular damage and loss of stem cells in FFA may be mediated through immune attack in the bulge region, with secondary fibrosis and reduced but still detectable stem cells. JAK/STAT-targeting treatments may be able to prevent permanent follicular destruction and fibrosis in early disease stages

Author-paper affiliation network architecture influences the methodological quality of systematic reviews and meta-analyses of psoriasis

<div><p>Moderate-to-severe psoriasis is associated with significant comorbidity, an impaired quality of life, and increased medical costs, including those associated with treatments. Systematic reviews (SRs) and meta-analyses (MAs) of randomized clinical trials are considered two of the best approaches to the summarization of high-quality evidence. However, methodological bias can reduce the validity of conclusions from these types of studies and subsequently impair the quality of decision making. As co-authorship is among the most well-documented forms of research collaboration, the present study aimed to explore whether authors’ collaboration methods might influence the methodological quality of SRs and MAs of psoriasis. Methodological quality was assessed by two raters who extracted information from full articles. After calculating total and per-item Assessment of Multiple Systematic Reviews (AMSTAR) scores, reviews were classified as low (0-4), medium (5-8), or high (9-11) quality. Article metadata and journal-related bibliometric indices were also obtained. A total of 741 authors from 520 different institutions and 32 countries published 220 reviews that were classified as high (17.2%), moderate (55%), or low (27.7%) methodological quality. The high methodological quality subnetwork was larger but had a lower connection density than the low and moderate methodological quality subnetworks; specifically, the former contained relatively fewer nodes (authors and reviews), reviews by authors, and collaborators per author. Furthermore, the high methodological quality subnetwork was highly compartmentalized, with several modules representing few poorly interconnected communities. In conclusion, structural differences in author-paper affiliation network may influence the methodological quality of SRs and MAs on psoriasis. As the author-paper affiliation network structure affects study quality in this research field, authors who maintain an appropriate balance between scientific quality and productivity are more likely to develop higher quality reviews.</p></div

Summary statistics for the co-authorship networks based on methodology quality.

<p>Summary statistics for the co-authorship networks based on methodology quality.</p

The differential impact of scientific quality, bibliometric factors, and social media activity on the influence of systematic reviews and meta-analyses about psoriasis

<div><p>Researchers are increasingly using on line social networks to promote their work. Some authors have suggested that measuring social media activity can predict the impact of a primary study (i.e., whether or not an article will be highly cited). However, the influence of variables such as scientific quality, research disclosures, and journal characteristics on systematic reviews and meta-analyses has not yet been assessed. The present study aims to describe the effect of complex interactions between bibliometric factors and social media activity on the impact of systematic reviews and meta-analyses about psoriasis (PROSPERO 2016: CRD42016053181). Methodological quality was assessed using the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool. Altmetrics, which consider Twitter, Facebook, and Google+ mention counts as well as Mendeley and SCOPUS readers, and corresponding article citation counts from Google Scholar were obtained for each article. Metadata and journal-related bibliometric indices were also obtained. One-hundred and sixty-four reviews with available altmetrics information were included in the final multifactorial analysis, which showed that social media and impact factor have less effect than Mendeley and SCOPUS readers on the number of cites that appear in Google Scholar. Although a journal’s impact factor predicted the number of tweets (OR, 1.202; 95% CI, 1.087–1.049), the years of publication and the number of Mendeley readers predicted the number of citations in Google Scholar (OR, 1.033; 95% CI, 1.018–1.329). Finally, methodological quality was related neither with bibliometric influence nor social media activity for systematic reviews. In conclusion, there seems to be a lack of connectivity between scientific quality, social media activity, and article usage, thus predicting scientific success based on these variables may be inappropriate in the particular case of systematic reviews.</p></div

Cumulative frequency of node degree distributions.

<p>The cumulative node degree distribution shows the cumulative number of nodes of each degree class. The distribution of degree values over all nodes characterizes the network as a whole.</p