Evidence of a genetic background predisposing to complex regional pain syndrome type 1.

BackgroundComplex regional pain syndrome type 1 (CRPS-1) is a rare, disabling and sometimes chronic disorder usually arising after a trauma. This exploratory study examined whether patients with chronic CRPS-1 have a different genetic profile compared with those who do not have the condition.MethodsExome sequencing was performed to seek altered non-synonymous SNP allele frequencies in a discovery cohort of well-characterised patients with chronic CRPS-1 (n=34) compared with population databases. Identified SNP alleles were confirmed by Sanger sequencing and sought in a replication cohort (n=50). Gene expression of peripheral blood macrophages was assessed.ResultsIn the discovery cohort, the rare allele frequencies of four non-synonymous SNPs were statistically increased. The replication cohort confirmed this finding. In a chronic pain cohort, these alleles were not overexpressed. In total, 25 out of 84 (29.8%) patients with CRPS-1 expressed a rare allele. The SNPs were rs41289586 in ANO10, rs28360457 in P2RX7, rs1126930 in PRKAG1 and rs80308281 in SLC12A9. Males were more likely than females to have a rare SNP allele, 8 out of 14 (57.1%) vs 17 out of 70 (24.3%) (Fisher's p=0.023). ANO10, P2RX7, PRKAG1 and SLC12A9 were all expressed in macrophages from healthy human controls.ConclusionA single SNP in each of the genes ANO10, P2RX7, PRKAG1 and SLC12A9 was associated with developing chronic CRPS-1, with more males than females expressing these rare alleles. Our work suggests the possibility that a permissive genetic background is an important factor in the development of CRPS-1

Evidence of a genetic background predisposing to complex regional pain syndrome type 1

Peer reviewed: TrueAcknowledgements: We thank the CRPS-UK Registry from which we obtained our study cohort and the study individuals for their enthusiastic participation. MCL, MSN and ID were supported by the Wellcome Trust (200183/Z/15/Z). AG was supported by the Pain Relief Foundation, Liverpool. YP was supported by the Indonesian Endowment Fund for Education (LPDP 201908222915477). SSS, NS, DKM, MCHC and CGW; this research was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. SSS, ID, AD and CGW are members of the UKRI Advanced Pain Discovery Platform.Funder: Pain Relief Foundation, LiverpoolBackgroundComplex regional pain syndrome type 1 (CRPS-1) is a rare, disabling and sometimes chronic disorder usually arising after a trauma. This exploratory study examined whether patients with chronic CRPS-1 have a different genetic profile compared with those who do not have the condition.MethodsExome sequencing was performed to seek altered non-synonymous SNP allele frequencies in a discovery cohort of well-characterised patients with chronic CRPS-1 (n=34) compared with population databases. Identified SNP alleles were confirmed by Sanger sequencing and sought in a replication cohort (n=50). Gene expression of peripheral blood macrophages was assessed.ResultsIn the discovery cohort, the rare allele frequencies of four non-synonymous SNPs were statistically increased. The replication cohort confirmed this finding. In a chronic pain cohort, these alleles were not overexpressed. In total, 25 out of 84 (29.8%) patients with CRPS-1 expressed a rare allele. The SNPs were rs41289586 inANO10, rs28360457 inP2RX7, rs1126930 inPRKAG1and rs80308281 inSLC12A9. Males were more likely than females to have a rare SNP allele, 8 out of 14 (57.1%) vs 17 out of 70 (24.3%) (Fisher’s p=0.023).ANO10,P2RX7,PRKAG1andSLC12A9were all expressed in macrophages from healthy human controls.ConclusionA single SNP in each of the genesANO10, P2RX7, PRKAG1andSLC12A9was associated with developing chronic CRPS-1, with more males than females expressing these rare alleles. Our work suggests the possibility that a permissive genetic background is an important factor in the development of CRPS-1.</jats:sec

Plasma Markers of Disrupted Gut Permeability in Severe COVID-19 Patients

A disruption of the crosstalk between the gut and the lung has been implicated as a driver of severity during respiratory-related diseases. Lung injury causes systemic inflammation, which disrupts gut barrier integrity, increasing the permeability to gut microbes and their products. This exacerbates inflammation, resulting in positive feedback. We aimed to test whether severe Coronavirus disease 2019 (COVID-19) is associated with markers of disrupted gut permeability. We applied a multi-omic systems biology approach to analyze plasma samples from COVID-19 patients with varying disease severity and SARS-CoV-2 negative controls. We investigated the potential links between plasma markers of gut barrier integrity, microbial translocation, systemic inflammation, metabolome, lipidome, and glycome, and COVID-19 severity. We found that severe COVID-19 is associated with high levels of markers of tight junction permeability and translocation of bacterial and fungal products into the blood. These markers of disrupted intestinal barrier integrity and microbial translocation correlate strongly with higher levels of markers of systemic inflammation and immune activation, lower levels of markers of intestinal function, disrupted plasma metabolome and glycome, and higher mortality rate. Our study highlights an underappreciated factor with significant clinical implications, disruption in gut functions, as a potential force that may contribute to COVID-19 severity

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.