Here, we used a modified layer-by-layer (LBL) fabrication protocol to generate thick human cardiac muscle patches (hCMPs) with thicknesses of ~3.75 mm. The LBL-hCMPs were composed of a layer of endothelial cells (ECs) sandwiched between two layers of cardiomyocytes (CMs): both cell populations were differentiated from the same human induced pluripotent stem cell line (hiPSCs) and suspended in a fibrin matrix, and the individual layers were sutured together, leaving channels that allowed the culture medium to access the internal cell layer. The LBL-hCMPs were cultured on a dynamic culture platform with electrical stimulation, and when compared to Control-hCMPs consisting of the same total number of hiPSC-ECs and -CMs suspended in a single layer of fibrin, hiPSC-CMs in the LBL-hCMPs were qualitatively more mature with significantly longer sarcomeres and expressed significantly higher levels of mRNA transcripts for proteins that participate in cardiomyocyte contractile activity and calcium handing. Apoptotic cells were also less common in LBL- than in Control-hCMPs. The thickness of fabricated LBL-hCMP gradually decreased to 0.8 mm by day 28 in dynamic culture. When the hCMP constructs were compared in a mouse model of myocardial infarction, the LBL-hCMPs were associated with significantly better measurements of engraftment, cardiac function, infarct size, hypertrophy, and vascularity. Collectively these observations indicate that our modified LBL fabrication protocol produced thicker hCMPs with no decline in cell viability, and that LBL-hCMPs were more potent than Control-hCMPs for promoting myocardial repair in mice.The engineered myocardial tissues produced  Layers of hiPSC-CMs and hiPSC-derived endothelial cells (hiPSC-ECs) were generated separately and then sutured together, leaving gaps between the layers that allowed the medium to access the internal cell layer. LBL-hCMPs were also cultured on a rocking platform with electrical stimulation to promote hiPSC-CM maturation and connectivity, and the effectiveness of LBL-hCMP transplantation for promoting recovery from myocardial injury was evaluated in a mouse MI model.All procedures and protocols involving animals were approved by the Institutional Animal Care and Use Committee of the University of Alabama at Birmingham and performed in accordance with the National Research Council's Guide for the Care and Use of Laboratory Animals (NIH publication No 85–23).Cardiac fibroblasts were isolated from the left atrium of an adult male patient and transfected with Sendai virus coding for OCT4, SOX2, KLF4, and C-MYC as described previously  to genervia metabolic selection (TM Cat: 11879020) supplemented with 4 mM lactate and 2% B27+ for 6 days.The hiPSC-CM differentiation protocol was performed as described previously . Brieflyelection  in glucovia flow-cytometry selection for the expression of both CD31 and vascular endothelial cadherin (CD144).hiPSCs were differentiated into endothelial cells (hiPSC-ECs) as described previously . BrieflyThe hiPSC-derived cardiac cells were characterized by immunofluorescence staining as described previously . Brieflyvia flow cytometry analysis as described previously  compound, frozen, and cut into 10-μm sections; then, the sections were permeabilized with 0.25% Triton-X-100 for 15 mins, blocked with UltraV block  for 7 mins, and sequentially stained with primary antibodies  overnight at 4°C and with fluorescently conjugated secondary antibodies for 1 h at 37°C. Images were obtained with a fluorescent microscope.2+ transients were measured as described previously .Cardiomyocytes were dissociated from control hCMPs and LBL hCMPs with 0.2% collagenase type I (Fisher Scientific LS004194) in 20% FBS/DMEM (Gibco) at 37°C for 1 h, followed by gentle shaking with 0.25% trypsin/EDTA for 10 mins. Cavia the 2−ΔΔCt method and normalized to the abundance of glyceraldehyde phosphate dehydrogenase (GAPDH) RNA.Total RNA was extracted with RNeasy mini kits  as directed by the manufacturer's instructions; then, the RNA was quantified by Nanodrop and reverse transcribed with SuperScriptTM II Reverse Transcriptase . qRT-PCR was performed with Power Up SYBR Green PCR Mix (Thermo Fisher Scientific) and appropriate primers  on a Quavia TEM in the the UAB High-Resolution Imaging Facility. Briefly, the hCMPs were fixed in 2.5% glutaraldehyde solution for 1 h at 4°C, embedded, and cut into ~70-nm sections with a diamond knife. Samples were mounted and photographed with a Tecnai Spirit T12 TEM.hCMPs were imaged Cardiomyocyte orientation and alignment was quantified as described previously . Brieflyvia a left thoracotomy, and the left anterior descending coronary artery was permanently ligated with an 8–0 non-absorbable suture. Animals in the MI+LBL-hCMP group were treated with LBL-hCMPs, animals in the MI+Control-hCMP group were treated with Control-hCMPs, and animals in the MI group recovered without hCMP implantation. Animals in the sham group underwent all surgical procedures for MI induction except arterial ligation and recovered without hCMP implantation. A quarter of the LBL- or Control-hCMPs (due to the large size) were positioned over the infarcted region of the left ventricular (LV) anterior wall and sutured to the visceral layer of pericardium with two stitches; then, the chest was closed in layers, and mice were administered buprenorphine (0.1 mg/kg every 12 h for 3 consecutive days) and carprofen (5 mg/kg every 12 h for 1 day) for pain control during recovery.MI was surgically induced in male and female NOD/SCID Gamma mice  as described previously . Brieflyvia the following equations:Echocardiographic measurements were performed as described previously . BrieflyBecause the hiPSCs were of human origin , engraft6) and expressed as a percentage.The engraftment rate was determined as described previously . Cells t+ cell density of Control hCMP and LBL hCMP in vitro were assessed by counting the number of cells that expressed CD31. Assessments were conducted every 20th serial section from peripheral to middle, 5 fields per section. Arteriole density was evaluated by counting the number of structures that expressed αSMA, and hypertrophy was evaluated by calculating the cross-sectional surface area of cardiomyocytes as defined by the WGA stain  from animal hearts were stained in hematoxylin  and eosin Y (30 secs) solution, dehydrated, mounted in Permount, and imaged with a bright field microscope (Olympus IX83 epifluorescent microscope).In-situ Cell Death Detection Kit  as described previously  containing a nylon frame. The mixture solidified within a few minutes and was cultured for 24 h on a dynamic platform; then, individual cell layers were removed from the mold, and the hiPSC-EC layer  was sandAnalysis of LBL-hCMP cross-sections that had been immunofluorescently stained for cTnI and CD31  indicatevia transmission electron microscopy, the sarcomeres of LBL-hCMPs appeared well-ordered with visible A-bands, M-lines, and Z-lines, as well as primitive intercalated disc-like structures that contained fascia adherens junctions and desmosomes , and hiPSC-ECs were identified by the expression of human-specific CD31 (hCD31)  . Observa (hCD31) , and tha (hCD31) .via echocardiographic assessments (Cardiac function was evaluated one and 4 weeks after MI induction or sham surgery essments  of left-essments  and fracessments : both paessments , cardiomessments , heart-wessments , the denessments , and theessments  were allThe goal of cardiac tissue engineering is to develop hCMPs that fully replicate the structural and functional properties of the native myocardium . HoweverhCMPs with thicknesses exceeding 2 mm have also been produced by depositing 2–3 layers of cell-containing fibrin solution into a single mold, and allowing each layer to polymerize before adding the subsequent layer . HoweverhiPSC-CMs are phenotypically more similar to fetal than adult cardiomyocytes and, consequently, engineered cardiac tissues tend to be less mature than the myocardium of adult animals . A varieIn conclusion, our modified LBL protocol enabled us to generate thicker hCMPs with no loss of cell viability. hiPSC-CMs were also more mature in LBL-hCMPs than in Control-hCMPs, and measures of cardiac function, infarct size, hypertrophy, vascularity, and apoptosis were significantly better in mice treated with LBL-hCMPs after surgically induced MI than in the Control-hCMP treatment group. Collectively, these observations indicate that future investigations in large-animal models of myocardial injury are warranted to evaluate the potential benefit of LBL-hCMP implantation for promoting myocardial repair, and to more thoroughly characterize potential safety concerns, such as the risk of arrhythmogenic complications.The original contributions presented in the study are included in the article/The animal study was reviewed and approved by Institutional Animal Care and Use Committee of the University of Alabama at Birmingham.LW and JZ: designed the project, wrote the manuscript, and revised the manuscript. LW: conducted all the experiments. JZ; supervised the whole project. Both the authors approved the submission and publication of the manuscript.This work was supported in part by the following funding sources: NIH RO1s, HL114120, HL 131017, HL 149137, NIH UO1 HL134764, and AHA 20PRE35210006.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


During the COVID-19 pandemic within the United States, much of the responsibility for diagnostic testing and epidemiologic response has relied on the action of county-level departments of public health. Here we describe the integration of genomic surveillance into epidemiologic response within Humboldt County, a rural county in northwest California.Through a collaborative effort, 853 whole SARS-CoV-2 genomes were generated, representing ~58% of the 1,449 SARS-CoV-2-positive cases detected in Humboldt County as of March 12, 2021. Phylogenetic analysis of these data was used to develop a comprehensive understanding of SARS-CoV-2 introductions to the county and to support contact tracing and epidemiologic investigations of all large outbreaks in the county.In the case of an outbreak on a commercial farm, viral genomic data were used to validate reported epidemiologic links and link additional cases within the community who did not report a farm exposure to the outbreak. During a separate outbreak within a skilled nursing facility, genomic surveillance data were used to rule out the putative index case, detect the emergence of an independent Spike:N501Y substitution, and verify that the outbreak had been brought under control.These use cases demonstrate how developing genomic surveillance capacity within local public health departments can support timely and responsive deployment of genomic epidemiology for surveillance and outbreak response based on local needs and priorities.The online version contains supplementary material available at 10.1186/s12889-022-12790-0. In early December 2019 a novel human coronavirus, now known as SARS-CoV-2, emerged in Wuhan, China. During January and February 2020, travel-associated cases of COVID-19, the disease caused by SARS-CoV-2, surfaced within the United States. By the end of February 2020 the United States reported instances of community transmission [Within the United States, frontline public health activities typically fall under the jurisdictional authority of states, counties, or smaller administrative units. County-level public health departments are routinely responsible for performing diagnostic testing, mounting epidemiologic responses, and reporting notifiable illnesses or conditions to higher level jurisdictional authorities. Thus, much of the responsibility for detecting and preventing COVID-19 transmission has relied on the action of county-level departments of public health. Despite a remit to conduct similar public health activities, the capacities and resources available to departments of public health vary greatly across the United States, which has resulted in an uneven response to the pandemic.When compared to other counties in California, the unique features of Humboldt County present particular challenges with respect to pandemic response, especially for COVID-19. Humboldt County is a rural county in northwest California encompassing 2.3 million acres, 80% of which is forestland, protected redwoods and recreation areas, serviced by a single small regional airport. The county is a healthcare and behavioral healthcare provider shortage area, meaning that many of the county’s 135,727 residents must travel long distances for access to healthcare services, and the largest population center (Eureka-Arcata) may be isolated due to landslides or other natural disasters. Many Humboldt residents are uninsured and more than one in five individuals live at or below the federal poverty line. The largest minority populations are Native American and Latino, both at high risk for serious COVID-19 disease, and the area experiences notable health disparities and overall poorer health outcomes when compared to state and national data [Despite these challenges, Humboldt County has used genomic sequencing of SARS-CoV-2 as a key component in the arsenal of epidemiological tools used to monitor, track, and control spread of the virus. Epidemiological analyses of viral sequence data have played critical roles in our understanding of SARS-CoV-2 epidemiology, and have been used to detect cryptic transmission of SARS-CoV-2 , 4, idenSamples were collected from a variety of submitters throughout Humboldt County including local hospitals, clinics, skilled nursing facilities (SNFs), assisted living facilities (ALFs), other congregate living facilities such as behavioral health centers, the county jail, local college dormitories and local health centers. Samples were typically collected upon clinical suspicion of SARS-CoV-2 infection or as part of case investigations conducted by the Humboldt County Department of Health and Human Services - Public Health (DHHS-PH), which performed targeted prospective surveillance in populations of concern such as SNFs and ALFs. While some SNFs were subject to routine surveillance testing to identify possible outbreaks early on, most samples were collected from symptomatic individuals and thus represent a skewed sample of all infections that likely occurred within Humboldt County.Throughout the pandemic the sample type evolved. Initially, samples were collected using dual or combined nasopharyngeal/oropharyngeal swabs. More recently, nasopharyngeal swabs and observed self-collected nasal swabs were the primary sample types that were received and tested. Additionally, swabs in both viral transport media (VTM) and saline transport media were validated for testing. Samples were collected and transported to the lab as soon as possible and held at 4 degrees Celsius for up to 72 h, or frozen for up to 7 days if sample processing was delayed.Early in the pandemic the majority of specimens collected by health care providers within Humboldt County requiring SARS-CoV-2 testing were handled by the HCPHL. A prioritization system was established to ensure that symptomatic samples and high risk populations were tested locally, which improved result turnaround times. Low priority samples, such as those collected to provide travel clearance, pre-operative screening, and general population surveillance, were deferred to commercial laboratories such as Quest and LabCorp. SARS-CoV-2 testing of hospital in-patients was mostly conducted by the hospital. Additionally, some specimens were collected and tested by OptumServe through a partnership with the Californian government to increase testing capacity.The OptumServe testing site served as a community surveillance site and began operating in April 2020. The site was initially a walk-in sample collection service that operated 5 days per week, collecting approximately 120 samples per day. Optum sample collection capacity increased over time, expanding to two collection teams which increased capacity up to 319 samples per day. Additionally, an Optum mobile team provided capacity to collect up to 561 samples per week. All samples collected by Optum were tested at the California Department of Public Health’s Valencia Branch Laboratory. None of these samples were sequenced as part of this project. Finally, Humboldt County, Del Norte County and United Indian Health Services formed a regional COVID testing task force to coordinate testing strategy and resources for the region. Analysis by the task force led to the establishment of the North Coast Testing Partnership (NCTP) which began performing diagnostic testing in December 2020. The NCTP lab tested between 100 and 200 samples 5 days a week.Throughout the pandemic the HCPHL used a variety of extraction platforms. RNA extractions were initially performed manually using the QIAamp Viral RNA mini kit (Qiagen) following manufacturer instructions. To improve throughput, automated RNA extraction was implemented on the MagNAPure Compact (Roche), eluting the extracted sample in 100 µls of elution buffer. Additionally, some extractions were either performed on the Qiagen EZ1 Advanced, eluting samples in 120 µls of elution buffer, or on the KingFisher™ Flex Purification System and the MagMAX™ Viral/Pathogen II Nucleic Acid Isolation Kit (ThermoFisher), which eluted the sample in 100 µls of elution buffer.At the beginning of the pandemic, HCPHL used the CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel. This assay is a singleplex assay which only allows processing of 10 samples at a time. In August of 2020 we began using the TaqPath COVID-19 Combo Kit (ThermoFisher), which allowed multiplexing of 93 samples per run. In preparation for Influenza season, HCPHL transitioned to the CDC Influenza SARS-CoV-2 (Flu SC2) Multiplex Assay that identifies SARS-CoV-2, Influenza A, and Influenza B simultaneously and tests 93 samples per run. Recent diagnostic testing primarily used the CDC Flu SC2 Multiplex Assay. To accommodate rapid turnaround of high-priority specimens, the HCPHL also validated the Xpert Xpress SARS-CoV-2 assay using the GeneXpert testing system (CEPHEID). The lab upgraded the GeneXpert testing system from 4 modules to 16 modules to increase capacity and reduce turn-around time. Additionally, the Xpert SARS-CoV-2/Flu/RSV 4-plex assay (CEPHEID) was validated and used during the influenza season. All PCR assays were used according to manufacturer instructions and instructions for use (IFU) without deviation.Convenience samples of diagnostic specimens were sent periodically for whole genome sequencing at the Chan Zuckerberg Biohub in San Francisco. Viral load was used as the primary criteria for choosing samples to sequence given that samples with higher viral loads are more likely to yield high quality whole genome sequences. All samples tested by HCPHL with RT-PCR cycle threshold (Ct) values of less than 31 were sent for sequencing. Additional samples of epidemiologic interest, such as specimens associated with specific case investigations, were also included. Eluted RNA was aliquoted into 96-well plates and sent to the Biohub in batches ranging from 40 to 96 samples. Metadata were compiled by communicable disease investigators to assist in post-sequencing analysis and case investigations.https://protocols.io/view/artic-neb-tagmentation-protocol-high-throughput-wh-bt66nrhe). Briefly, 3 µl of total nucleic acid was used as input for a randomly primed cDNA synthesis reaction. This cDNA served as input for 30 cycles of amplification with ARTIC V3 primers (primer sequences available at https://github.com/artic-network/artic-ncov2019), and was then diluted 1:100 before tagmentation. Adaptor tagmentation was performed using homebrew Tn5, and 8 cycles of index PCR was performed using unique dual barcode Nextera indices. Final libraries were pooled at equal volumes and cleaned at 0.7x (SPRI: Sample) using SPRIselect beads. The library was sequenced on the Illumina Novaseq SP platform in a paired-end 2 × 150 cycle run.Extracted total nucleic acid was diluted based on average SARS-CoV-2 N and E gene cycle threshold (Ct) values; samples with a Ct range 12-15 were diluted 1:100, 15-18 1:10 and >18 no dilution. For high throughput scaling, library preparation reaction volumes and dilutions were miniaturized utilizing acoustic liquid handling , Europe, Asia, and Oceania). The workflow describing the subsampling scheme can be found at The geographic migration history between locations was inferred across the tree using the discrete trait analysis method within TreeTime . Under tBeginning in February 2020, the HCPHL sent COVID-19 testing requests to the Centers for Disease Control and Prevention in Atlanta, Georgia. The first positive case of SARS-CoV-2 in Humboldt County occurred on February 21, 2020. Subsequently, HCPHL started onsite diagnostic testing via quantitative Polymerase Chain Reaction (qPCR) on March 7, 2020. The first case detected onsite by HCPHL occurred on March 19, 2020. The HCPHL capacity and testing strategy evolved over the pandemic, scaling from 10 samples per day at the start of the pandemic to 350 samples per day. By March 12, 2021, the laboratory had screened 35,499 possible cases and detected 1,449 (4.1%) PCR-confirmed SARS-CoV-2 infections . We conducted a phylogeographic analysis of these 853 sequences alongside 1800 contextual SARS-CoV-2 whole genomes, primarily from other counties in California (n=1527), and including sequences from other global regions as well . Thirty sequences were generated from diagnostic specimens collected from positive employees at the farm, while eight sequences were sampled from individuals reporting either an indirect link to the farm, or no contact with the farm whatsoever . Alternatively, amplification of transmission during the farm outbreak could have contributed to spillover of transmission from the farm back into the broader Humboldt County community .We combined case interview data with the inferred tree to investigate these two plausible scenarios. Two cases, a parent and their child, reported no exposure to the farm or any employee of the farm Fig. . Six casWhole genome sequencing helped support contact tracing efforts during this outbreak in various ways. Firstly, pathogen genomic data clearly linked infections among staff of the farm Fig. , therebyThis outbreak was one of the first large, localized outbreaks that occurred in Humboldt County, and the experience shaped the public health response going forward. This outbreak demonstrated that rapid SARS-CoV-2 transmission could occur within congregate living facilities housing young and active individuals, and that such outbreaks could potentially seed transmission outside of the primary outbreak setting. In response, DHHS-PH implemented a specific testing protocol to monitor for and respond to outbreaks in congregate settings. Under this regime, individuals working or residing in congregate settings were tested for SARS-CoV-2 weekly as surveillance testing. If a positive test was confirmed, this triggered response testing. Contact tracing was initiated, and staff and residents were tested twice weekly (if possible) until a two week period of time with no additional positive tests had elapsed. Additionally, DHHS-PH devoted additional resources to working with congregate living facilities to reduce transmission risk, such as working with commercial agricultural settings to break apart housing into smaller pods and providing more rapid access to testing.Like many parts of the United States, Humboldt County experienced a surge in COVID-19 cases during the late-fall and early-winter of 2020. Levels of community transmission were higher, increasing the probability of an introduction into congregate living settings at high risk for outbreaks. As part of standard testing procedures for congregate settings, on November 22, 2020 a SARS-CoV-2-positive specimen was collected from a staff member working in a skilled nursing facility, referred to here as Facility A. An outbreak was declared on November 23, 2020, which led to increased testing and contact tracing as per the congregate setting testing protocols described above. Over the course of the outbreak, all 72 residents of the facility tested positive for SARS-CoV-2 (100% attack rate), and 28 of the 98 staff members tested positive (28.6% attack rate). Thirteen residents of the facility died. No mortality was observed amongst infected staff. By January 16, 2021, no additional positive cases from Facility A had been recorded for two weeks, and the outbreak was declared over.Routine genomic surveillance of SARS-CoV-2 infections occurring within Humboldt County throughout the fall provided crucial context for understanding this outbreak. In the lead-up to the outbreak in Facility A, a subset of community-associated SARS-CoV-2 cases had been sequenced as part of ongoing genomic surveillance Fig. B. Indeedde novo asparagine to tyrosine substitution in site 501 of the Spike protein (N501Y). This amino acid substitution is associated with increased binding affinity for the human ACE2 receptor [Genomic surveillance of the outbreak in Facility A also revealed the emergence and eradication of a lineage that had a receptor , which creceptor , B.1.351receptor , and P.1receptor . Of 89 sOngoing community genomic surveillance of positive cases verified eradication of this lineage from Humboldt County. Since December 29, 2020, 233 samples collected from SARS-CoV-2 cases in Humboldt County were sequenced, yet none of these samples grouped with, or were descended from, the 501 N or 501Y lineages that circulated in Facility A. Two cases sampled in January 2021 had viral genome sequences that were descended from the lineage that circulated in the community Fig.  A. TheseHere we have described the development of increased laboratory capacity and use of genomic surveillance to support the public health response to COVID-19 in a local health department. While genomic surveillance data have frequently been used to understand geographical patterns of infectious disease transmission, our work here demonstrates the utility of pathogen genomic sequence data for supporting actionable public health activities, such as contact tracing and outbreak response, within a rural county locale. Due to the rural nature of Humboldt County, there are generally longer turnaround times between sample collection and a test result because of the need to transport samples longer distances. Sample transport usually adds several days to the time necessary to receive a test result, and these delays can affect the ability to respond locally in a timely manner. To mitigate the impact of these issues, the HCPHL focused on modernizing their public health surveillance capabilities, including scaling up testing infrastructure and integrating viral genomic surveillance into response efforts.These laboratory investments likely contributed significantly to DHHS-PH’s epidemiologic response efforts, thereby limiting community spread for many months. Combining traditional contact tracing with phylogenetic analysis of viral sequence data facilitated rapid identification and response in three important ways. First, sustained community transmission within the county could be actively monitored, instead of relying solely on state-wide or national data. Had DHHS-PH been reliant on state-wide or national data, several key opportunities to control local transmission may have been missed. Second, the ability to combine findings from case-contact interviews with genomic data allowed determination of which exposure event had resulted in transmission given multiple possible exposures, providing direct feedback on the efficacy of the overall response efforts. Finally, these new capabilities allowed early identification of introductions or emergence of variants of concern for immediate monitoring, containment, and local elimination.The genomic surveillance findings in Humboldt County suggest that the majority of introductions into the county resulted in limited onward transmission and successful local control with only 11 (11%) of documented introduction events resulting in greater than 10 sequenced cases. Notably, this analysis is likely conservative due to the directionality of the bias in the phylogeographic reconstruction. If greater numbers of sequences from other geographic areas were added, they would likely interdigitate with, and potentially break apart, some of the clades inferred to circulate within Humboldt County. In this case, the number of discrete introductions into Humboldt County would be greater, and the amount of onward transmission observed post-introduction would decrease further. Thus, our estimate of at least 100 distinct introductions of SARS-CoV-2 to Humboldt County should be viewed as the minimal estimate of introduction frequency, and lineages may be even more self-limiting than observed in this study. Furthermore, we note that the tail of the clade size distribution may be skewed by testing policies. While outbreaks were not preferentially sequenced , public health policies prioritized testing in congregate settings, likely increasing the numbers of tests conducted compared to testing in the broader community. Thus, even with the same sequencing criteria applied to all samples, outbreaks in congregate settings may have greater numbers of sequences because they were tested more densely, inflating the introduction clade size compared to more limited introductions.de novo N501Y substitution in the Spike protein. While the phenotypic characteristics of this substitution within this specific genetic context are not known, DHHS-PH’s response to this emergence event appears to have resulted in eradication of this lineage. This was feasible because a large proportion of positive diagnostic specimens collected from the surrounding community was consistently being sequenced. Monitoring these community samples in addition to specimens collected from the SNF where the substitution arose demonstrated that the lineage had been successfully contained to the facility and did not spill over and transmit within the broader community. To our knowledge, this is the first instance of a local health department within the United States detecting an emergent mutation of interest and documenting its eradication with genomic surveillance.Using this genomic surveillance system, we detected the emergence of a viral strain with a Genomic surveillance is still considered an advanced technique in public health and is often more accessible at higher levels of jurisdictional authority or in higher resource urban settings. This issue has less to do with implementation of laboratory protocols for conducting sequencing, which are increasingly accessible to most public health microbiology labs with molecular capabilities. Rather, this issue arises due to the unique challenges associated with genomic data management, analysis, and interpretation , 22. HowAdditional file 1.Additional file 2.


Serosurveillance helps establish reopening guidelines and determine the immunity levels in different populations to reach herd immunity. Then, there is an urgent need to estimate seroprevalence population wide. In Mexico, information about COVID-19 cases and related deaths is scarce. Also, there is no official serosurveillance, limiting our knowledge of the impact of the SARS-CoV-2 pandemic. Here, we report the prevalence of anti-SARS-CoV-2 antibodies in 522,690 unvaccinated people from July 5th to December 31st, 2020. The overall seroprevalence was 32.8% and highest in adults aged 30–39 years (38.5%) than people under 20 years (33.0%) or older (28.9%). Moreover, in a cohort of 1655 individuals confirmed COVID-19 by PCR, we found that symptomatic people (HR = 2.56) increased seroconversion than presymptomatic. Also, we identified that the most discriminative symptoms for COVID-19 that could predict seroconversion were anosmia and ageusia (HR = 1.70), fever, myalgia/arthralgia, and cough (HR = 1.75). Finally, we found that obese people had lower seroconversion (HR = 0.53) than healthy people, but the opposite happens in diabetic people (HR = 1.39). These findings reveal that around one-third of Mexican outpatients had anti-SARS-CoV-2 antibodies before vaccination. Also, some symptoms improve empirically COVID-19 diagnosis and seroconversion. This information could help fine-tune vaccination schemes and the reopening and back-to-work algorithms. Thus, although these tests do not help recognize an acute infection, they could help detect asymptomatic people since antibody tests can detect the disease after 5–7 days3. Also, most reports come from hospitalized people4 and few from community settings, outpatients, asymptomatic or presymptomatic people6. Therefore, the study of the natural immunity acquired after SARS-CoV-2 infection and its related factors is of interest to estimate the effectiveness of immunity mediated through vaccination. That information could help policymakers refine the extent of the ongoing vaccination programs and make interventions to prevent outbreaks, design back-to-work algorithms, and control the pandemic7. More studies are needed to understand the immunity response against SARS-CoV-2 better.Epidemiological serosurveillance could be helpful to understand the exposure levels to the SARS-CoV-2 infection and make inferences on the burden of COVID-19 at the geographical level and specific population groups. Some studies have shown that immunological tests could also help detect positive cases in asymptomatic people8. Moreover, in its last analysis, the Mexican National Institute of Statistic and Geography (INEGI) pointed out that positive cases and deaths are underestimated, implying the lack of reliable data about the spread of SARS-CoV-2 in the country9.In Mexico, the first positive case of SARS-CoV-2 infection was reported on February 27th, 2020. To this date, 5,436,566 confirmed cases and 316,492 deaths associated with COVID-19 had been documented13. Therefore, this study aimed to analyze information collected during the first and second SARS-CoV-2 epidemic outbreak before vaccination to understand the pandemic impact in Mexico and identify clinical factors associated with natural seroconversion. To this, we analyze information belong people tested for antibodies against SARS-CoV-2 in outpatient diagnostic Salud Digna clinics  in 2020 during the first and second viral wave in the country before vaccination.Moreover, previous reports of serosurveillance were restricted to some states, public health institutions, or high-risk populations like healthcare workersWe retrospectively analyze anonymized electronic health records from 522,690 unvaccinated outpatients tested for SARS-CoV-2 antibodies at the Salud Digna Clinics throughout Mexico from July 5th to December 31st, 2020.According to the Mexican Federal Law on Personal Data Protection , consent for the use of information from health records was obtained from each individual included in this work as follows. People receiving diagnostic and health care services in the Salud Digna clinics accept our privacy policy, which includes using their anonymized information for scientific research purposes. Also, people can deny the use of their information at any time through the personal data protection department of Salud Digna in adherence to the Mexican federal law (LFPDPPP). By the above, we do not need specific, informed consent from each person included in this work because this study is a cross-sectional analysis of an electronic health registry.According to Federal Law on Personal Data Protection in Mexico (LFPDPPP), we handle data protection and privacy. We assign a unique ID code to each registry that is not linked to the identity of individuals and to prevent data duplication; also, information is aggregated to enhance the protection of the identity and privacy of individuals.14 using the national COVID-19 incidence (45%) reported for the same period of study by the Ministry of Health in Mexico15. We found that people tested in each state exceeded the threshold (381 people), so we included all country states  and demographic information, were included in the analysis. The general seroprevalence and by states was done with the entire dataset . For the prevalence by state, previously, we determined the minimum number of people tested to represent a state 381 people) according to sample size calculation for cross-sectional studies people a17.Seroconversion is defined as a positive serological test in individuals previously diagnosed with COVID-19 by a real-time RT-PCR test; to analyze factors associated with seropositivity and seroconversion dynamic, we made a cohort of seroconverted people. In these subsets of people, we defined cases as symptomatic or presymptomatic according to the presence or absence of symptoms at the PCR test. Due to lack of follow-up patients was not possible to determine if they were genuinely asymptomatic or then after laboratory diagnostic, they have symptomsIn the entire electronic registry, we identify 14,592 people with a positive PCR test (≤ 14 days) previous to antibodies test; from this we assess the association of clinical and socioeconomic factors with seropositivity in this group. Also, from this subset  we identify people  with serial serological tests 180 days after the positive PCR test. Distribution of number of tests over time for each characteristic analyzed is showed in Supplementary Figs. For seroconversion dynamic, presymptomatic individuals were excluded to assess the impact of symptoms, and symptomatic people who did not experience the symptom analyzed were the reference group.® Anti-SARS-CoV-2 probe , which detects IgM and IgG antibodies and reports a sensitivity of 99.5% and a specificity of 99.8%. Sample processing and interpretation results (positive: COI ≥ 1 or negative: COI < 1) were according to manufacturer instructions using the module Cobas e602® .Serological analyses were performed in peripheral blood samples collected from people attendant in Salud Digna Clinics and analyzed for anti-SARS-CoV-2 antibodies by electrochemiluminescence immunoassay (ECLIA) using qualitative ElecsysThis study was approved by the Salud Digna Ethical Research and Review Committee (SDI-2020-2); The methods in this work adhered to the Helsinki declaration and were carried out according to the Federal law of Personal Data Protection in Mexico. Also, the committee evaluated and approved data collection and privacy protection procedures used in this study.18.We did a descriptive analysis for all variables in the dataset. Age groups were defined by decades, except for underrepresented groups (< 20 and > 60 years). The seroprevalence was obtained across the country, standardized by age and sex for every 100 persons, and calculated by the direct method using the standard world population as a reference; the confidence interval was obtained considering a Poisson distribution for ASR according toAge and sex-adjusted or unadjusted multivariate logistic regressions were carried out as appropriate to evaluate the association between SARS-CoV-2 antibodies and demographic and clinical factors. A backward step-by-step analysis was used to select variables (p < 0.001) to adjust the final model. We assess the significance of demographic factors and symptoms for seropositivity with the Chi-square test.Time-to-event analyses are shown by Kaplan–Meier curves from the time in which people tested positive by PCR test to a positive antibodies test result. Hazard ratios (HR) were calculated by Cox proportional hazards models, adjusted for sex and age (in decades), and time (number of days since PCR positive test) to account for the time from SARS-CoV-2 detection to seroconversion (positive results of antibodies test). We used the log-rank test (Mantel–Cox) to assess the significance of variables analyzed in Cox models.We make analyses using SPSS23  and time-to-event models using R 4.02 (CRAN project) and the survival (v3.1) package. Some graphs were made with GraphPad Prism 8  and R 4.02 (CRAN project).This work includes information from all country states (32 states) from July 5th to December 31st, 2020. The total prevalence of anti-SARS-CoV-2 antibodies was 32.8% the lower prevalence was in Colima (18.1%), Aguascalientes (22.7%), Nayarit (23.7%), and Queretaro (23.9%), while in Tabasco (51.3%), Chihuahua (41.2%), Sinaloa (40.9%) and Nuevo León (40.7%) we found a higher prevalence. However, no specific geographic pattern was observed ; however, it increased again in December   had antibodies against SARS-CoV-2.Most of the screened patients had social security (81.0%) and did not receive the influenza vaccine in the last year (76.8%) Table . InteresRegarding clinical characteristics, comorbidities were present in 13.9% of people diagnosed with COVID-19 Table ; the mosWe analyzed the seroconversion by time to event analysis in people previously diagnosed with COVID-19  and obesity reduced it  than healthy people, respectively. However, hypertension was not significant . Further analyses revealed that symptomatic people have higher seroconversion than presymptomatic individuals   and myalgia/arthralgia  significantly increased the frequency of seroconversion in less time than people that do not experience those symptoms. In contrast, respiratory symptoms such as breath difficulty , throat pain , and runny nose  were not significantly related to increasing seroconversion frequency except the cough   and ageusia  significantly increased seroconversion frequency in less time than people that do not experience it. On the other hand, gastric symptoms such as diarrhea , abdominal pain , and vomit  were not significantly related to increasing seroconversion frequency ; this could be due to the age distribution of the population in the country, and the majority could be economically active, which might have high occupational exposure. For example, we found that jobs like delivery people, logistics, transporting, and informal traders had higher seropositivity similar to previous reports25 that could be related to more robust antibody response27; then, we analyzed the impact of chronic diseases in seroconversion.Recent works showed that people with previous comorbidities had more risk to develop severe COVID-19We found a significant increase in the seroconversion frequency in diabetic people than healthy people. Other factors not evaluated, such as glycemic levels at the moment test; if the patient has treatment or not, their adherence to it, and time elapsed since disease diagnosis, the above could confuse the effect observed.28, as observed against other respiratory viruses such as flu30 and recently SARS-CoV-231. However, due to obesity being self-reported, we could not accurately identify obese people or stratified, then these results should be taken with caution.Furthermore, we found that obese people significantly had less seroconversion frequency than healthy people; this could be due to impair immune function33 that could explain low seroconversion frequency in time observed in presymptomatic people.On the other hand, symptomatic people significantly increased their HR for seroconversion than presymptomatic. Recent works show that adaptive immunity is strongly activated in presymptomatic people; however, T cell and antibody response may differ34. While headache and sore throat do not significantly impact natural seroconversion; similarly, allergy-like and gastric-related symptoms  and also increased hazard ratio for seroconversion. Similarly, other group of symptoms, such as fever, myalgia/arthralgia, and cough  that also increased hazard ratio for seroconversion than single symptoms . Some of them, such as the southern region, have lower representation due to fewer cases with complete clinical and demographic information.Because we studied outpatients in a community setting, it was impossible to follow up with each to collect serial samples for antibodies testing. Instead, we made a cohort-based on a convenient sampling of people confirmed with COVID-19 by PCR test and serial antibodies tests till 180 days after PCR test for time to event analysis. Then, the number of people analyzed was reduced.Nevertheless, our study provides an overview of SARS-CoV-2 seroprevalence in the unvaccinated Mexican population that contributes to understanding the Americas' pandemic impact. Also, these findings allow us to identify significant characteristics and symptoms related to natural seroconversion, especially those that boost this response in less time; this could be considered for clinical management of infected people and vaccination.Together, these results contribute to characterizing the natural immunity induced by SARS-CoV-2 and comparing it with the antibody-mediated immunity induced by vaccination, helping us design effective vaccination schemes against SARS-CoV-2, prioritizing risk groups to fine-tune algorithms for back to work based on serological testing.Supplementary Information.


Objective: To estimate the cost-effectiveness of three surveillance imaging strategies using whole-body positron emission tomography (PET) with computed tomography (CT) (PET/CT) in a follow-up program for adults with resected stage III melanoma. Methods: An analytic decision model was constructed to estimate the costs and benefits of PET/CT surveillance imaging performed 3-monthly, 6-monthly, or 12-monthly compared with no surveillance imaging. Results: At 5 years, 3-monthly PET/CT surveillance imaging incurred a total cost of AUD 88,387 per patient, versus AUD 77,998 for 6-monthly, AUD 52,560 for 12-monthly imaging, and AUD 51,149 for no surveillance imaging. When compared with no surveillance imaging, 12-monthly PET/CT imaging was associated with a 4% increase in correctly diagnosed and treated distant disease; a 0.5% increase with 6-monthly imaging and 1% increase with 3-monthly imaging. The incremental cost-effectiveness ratio (ICER) of 12-monthly PET/CT surveillance imaging was AUD 34,362 for each additional distant recurrence correctly diagnosed and treated, compared with no surveillance imaging. For the outcome of cost per diagnostic error avoided, the no surveillance imaging strategy was the least costly and most effective. Conclusion: With the ICER for this strategy less than AUD 50,000 per unit of health benefit, the 12-monthly surveillance imaging strategy is considered good value for money. Melanoma patients with distant metastases in more than two organs and high tumour burden have a poor response to therapy and low survival rates ,2. EarlyInternational guidelines for follow-up after treatment of stage III melanoma vary by country and discipline, particularly in relation to the type of imaging test recommended, the timing of imaging, and the clinical stage in which they should be performed . The GerFurthermore, few research studies have investigated the cost-effectiveness of a surveillance imaging strategy in resected stage III melanoma patients ,13,14. MThe follow-up strategies in current practice were developed before potentially effective systemic therapies were available to treat advanced melanoma and also before patients with stage III melanoma received adjuvant therapy . These new therapies have significant benefits for patients and in the metastatic setting the potential to be most efficacious in patients with lower disease burden . TherefoSeveral studies have estimated the potential harms of frequent imaging, including ‘scanxiety’ , exposurCurrently, there are no high-level evidence-based follow up guidelines to assist clinicians in weighing up the costs and benefits of surveillance imaging . Robust A randomised controlled trial  is curreThis study aimed to investigate the cost-effectiveness of current surveillance imaging strategies compared with no surveillance imaging, for an accurate diagnosis of distant melanoma recurrence from a health system perspective, by modelling the relative costs and benefits over 5 years.We examined resected American Joint Cancer Committee (AJCC) stage IIIA-D  melanomaWe constructed an analytic decision model to estimate the costs and benefits of follow-up with PET/CT performed 3–4 monthly, 6-monthly, or 12-monthly compared with no surveillance imaging follow up to diagnose distant melanoma recurrence.  The two Surveillance imaging was primarily used to identify distant recurrence; therefore, loco-regional recurrences were excluded.A first distant recurrence only occurs once. Therefore, the model simulates the costs and benefits up to the first  distant recurrence.Based on Australian guidelines , patientAll patients with distant melanoma detected underwent treatment.The costs for unresectable stage III or stage IV melanoma treatment included diagnostic imaging, doctors’ visits, genetic testing, and pharmacotherapies where relevant, as well as costs for management of Grade 3 and 4 adverse events from treatment modalities  .Radiation-attributable malignancies from PET/CT imaging were not included because these generally take >5 years to develop.Costs of palliative and end of life care were excluded because patients were censored after the development of distant disease.The key assumptions for the decision model were:The direct unit costs associated with healthcare activities in the four surveillance strategies, including PET/CT imaging, invasive procedures , and clinical follow-up, were estimated from the Medical Benefits Schedule (MBS) for outpatient care and Australian-Refined Diagnosis Related Groups (AR-DRGs) for hospital admissions  30]. Th. Th30]. Total costs were adjusted to 2020 Australian dollars (AUD) based on the Consumer Price Index . For a wThe base case represented a patient with melanoma stage IIIA to IIID undergoing follow-up for distant disease recurrence with surveillance imaging at the MIA. Probabilities for each branch of the decision tree were taken from the hazard rates for distant recurrence in the MIA cohort and the reported sensitivity and specificity of PET/CT ,33. The economic results were presented as the cost per distant recurrence appropriately diagnosed and treated, assuming all patients are treatable. The costs were calculated as an aggregate of follow-up surveillance costs, the cost of confirmatory tests, and the cost of treatment . For each of the outcomes, the incremental cost-effectiveness ratios (ICER) were calculated using the no surveillance imaging strategy as the comparator over a 5-year follow-up period. The ICER was compared to a willingness-to-pay (WTP) threshold of AUD 50,000 per unit of health benefit, a commonly used threshold for the value of money.Two major sources of uncertainty were identified for this model, uncertainty in the clinical parameters and uncertainty in the modelled calculations. Deterministic sensitivity analyses were conducted to address uncertainty for all the input clinical parameters over the range shown in The decision model was built using TreeAge software . This software package automatically generates the algorithms required to evaluate the model and choose the optimal strategy by giving weight to each possible outcome based on its probability. The cost-effectiveness analyses and the sensitivity analyses were also carried out using TreeAge, see Ethics approval was not required for this cost-effectiveness study; however, ethical approval for the original cohort was obtained from the MIA research committee (MIA2016/182), the Australian Institute of Health and Welfare (EO2019-1-454), and the Royal Prince Alfred hospital X18-0144, LNR/18/RPAH/206. The economic evaluation was reported according to the CHEERS  checklist .The results of one-way sensitivity analyses are displayed in a tornado diagram in which each bar represents the impact of uncertainty for the individual parameter on the ICER . The modOverall, our probabilistic sensitivity analysis results were consistent with our base case model and provided evidence that surveillance imaging of resected stage IIIA-D melanoma patients was unlikely to be a cost-effective strategy. The probabilistic sensitivity analyses showed ICERs for imaging-based surveillance were not favourable compared with no imaging. For example, 12-monthly imaging compared with no routine imaging showed less than half (44%) of the simulations were cost-effective using a WTP threshold of AUD 50,000 per distant recurrence appropriately diagnosed and treated .Using commonly recommended surveillance imaging strategies and real-world data from a large melanoma treatment centre in Australia, our baseline model suggests 12-monthly PET/CT surveillance imaging for resected stage IIIA-D melanoma patients was slightly more expensive but more effective than a no imaging strategy with an ICER that represents good value for money. Twelve-monthly surveillance imaging was less expensive and more effective than 3 or 6-monthly surveillance imaging for the detection of distant disease. Extensive sensitivity analyses highlighted that these cost-effectiveness results were sensitive to the probability of distant recurrence at 5 years in the 12-monthly and no imaging strategies. When compared with no surveillance imaging, 12-monthly PET/CT surveillance imaging was associated with the largest increase in appropriately diagnosed distant disease versus smaller increases for 6-monthly imaging and 3–4 monthly imaging.Our model favours less frequent imaging, which we found less expensive primarily due to fewer additional tests related to false positives. From our previous work of a well-documented stage III melanoma cohort, 42% of patients had false-positive findings and incidental findings in 21% of patients . These fOur findings are consistent with other studies that have analysed surveillance imaging modalities for stage II–III melanoma patients, in that frequent follow-up imaging is not cost-effective even for intermediate to high-risk patients ,38. HoweThe results of the cost-effectiveness of surveillance imaging with respect to early diagnosis and treatment need to be taken together with recent research supporting survival benefits of new systemic immunotherapy ,41. ObseOur model generated an ICER of AUD 34,362 for each additional case of accurate diagnosis and treatment of distant recurrence with a 12-monthly surveillance imaging strategy. However, an ICER of AUD 34,362 is challenging to interpret, as there is currently no established willingness to pay (WTP) threshold associated with a recurrence appropriately diagnosed and treated . Based oPET/CT is approved and currently being reimbursed by the Medical Services Advisory Committee (MSAC), and systemic treatment has been approved by the Pharmaceutical Benefits Advisory Committee (PBAC), meaning that the government is willing to pay for these tests and drugs. We could assume that the Australian Government would be willing to pay for the cost of a whole-body PET/CT (AUD 1128.75) for each additional accurate diagnosis, and the cost of therapeutic regimens offered to a patient diagnosed with distant metastatic disease, estimated to be AUD 115,072 . Hence, Novel research around the standardised estimates for WTP for an appropriate diagnosis of distant recurrence is needed as immunotherapy is now given as adjuvant treatment in stage III disease to prevent distant recurrence, and that surveillance imaging is used to monitor the effectiveness of these drugs, as well as looking for the first signs of disease to treat. Future research is needed to examine the cost-effectiveness of surveillance imaging for patients with stage III melanoma undergoing adjuvant or neo-adjuvant systemic therapies.The more frequent imaging strategies (3 or 4-monthly and 6-monthly imaging) are more costly and less effective in appropriately diagnosing distant melanoma compared with 12-monthly imaging. Indeed, the more intensive imaging strategies led to a higher number of diagnostic tests, procedures, clinic visits, and referrals to other physicians as a result of frequent false-positive findings.The main strength of this study is that our model inputs for PET/CT test performance were taken from a recent longitudinal cohort study that assessed the performance of an imaging schedule over several years, rather than at a single  time point . Our stuOur modelling suggests that 12-monthly surveillance imaging could be the most cost-effective diagnostic strategy in resected stage III melanoma patients, given current data. This work was based on a large prospective cohort study of routine PET/CT imaging in patients with stage III melanoma and is the first to quantify the costs and benefits of different imaging schedules and contribute to much-needed cost-effectiveness evidence for melanoma guidelines and health policy.Given the changing context, there still is insufficient evidence to firmly exclude more frequent PET/CT or no routine imaging strategy as cost-effective diagnostic options for resected stage III melanoma patients. These findings must be taken together with recent research supporting that current systemic immunotherapy provides a survival benefit . Indeed,Adopting the approach of less frequent imaging in resected asymptomatic patients following treatment would reduce costs and is unlikely to adversely impact the clinical outcomes of melanoma patients. Although the influence of both clinical practice guidelines and cost-effectiveness analyses on changing physician practice is variable ,46, thisLarge, prospective trials with in-built cost-effectiveness and survival studies are further needed to help guideline bodies provide efficiency-based follow-up recommendations.Healthcare funding decisions are increasingly being assessed on the basis of cost-effectiveness as well as their impact on health outcomes. Among resected stage III melanoma patients, if surveillance imaging is to be performed at all, then 12 months is the most cost-effective strategy. Twelve-monthly surveillance imaging was less expensive and more effective than 3 or 6- monthly compared with no surveillance imaging, and at a WTP that is less than AUD 50,000 per patient, accurately diagnosed and treated.


Fibrodyplasia ossificans progressiva (FOP) is a rare hereditary disease, which has a variable course characterized by occasional flare-ups of heterotopic ossification (HO) in soft tissues that are followed by swelling, stiffness, pain and warmth. Here, we report for the first time a case of a 45-year-old female patient with known FOP recovering from COVID-19 with disease progression potentially linked with the viral illness. In December 2020 the patient contracted a mild form of COVID-19 infection without need for hospital admission. Since January 2021, the patient felt unwell, with occasional abdominal pain which progressively intensified. In March 2021 she presented with new onset of HO, complaining of pain, swelling and thickening sensation in the lower abdomen and left part of the neck. Computerized tomography (CT) and cytokine analysis were performed. CT scan revealed new heterotopic bone formation in multiple soft tissue areas of the neck indicating clear radiological progression. Radiotherapy, which has proven to be an efficient tool to control HO in this patient, was not able to halt HO formation after COVID-19 infection. Cytokine analysis of a plasma sample obtained during a flare-up after COVID-19 infection showed a significantly elevated pro-inflammatory cytokines compared to a flare-up panel prior to infection. Of the 23 analyzed levels of cytokines, a staggering number of 21 were above normal levels. This case is the first confirmation of uncontrolled post-COVID-19 effects in a FOP patient, which manifested with flare-ups followed by progressive HO, possibly caused by a thus far, never described form of post-COVID syndrome. Fibrodysplasia ossificans progressiva (FOP) is a rare, but debilitating disease that affects 1:2,000,000 people worldwide. The disease causes bone formation in muscles and connective tissues, effectively entombing the patient in a “second skeleton”. The earliest skeletal malformations that are indicators of FOP can be present at birth, such as inward curving of the great toe. The disease progresses variably, and is characterized by episodes of exacerbation (flare-ups) with heterotopic ossification (HO) in soft tissues. HO appears spontaneously or after trauma to skeletal muscles and connective tissues and is characterized by swelling, stiffness, pain and warmth. Some lesions regress spontaneously, but most of them mature by an endochondral ossification pathway [ pathway . Studies pathway , 5. Prev pathway . Coronav pathway . It can  pathway .In this report, we describe the case of a 45-year-old female patient with FOP who suffered from a mild form of COVID-19 infection after which she experienced intense FOP exacerbation . This case report is complemented by patient’s plasma cytokine profile analysis and literature review on the association of FOP and HO with COVID-19. To the best of our knowledge, this is the first report of a FOP patient recovering from COVID-19 and the first time COVID-19 convalescence has been linked to FOP progression.A 45-year-old female patient with FOP presented to the Rheumatology Outpatient Clinic in March 2021, complaining of pain and swelling of the lower abdomen and left part of the neck. The patient was diagnosed with FOP at the age of four when a red, painful gristle appeared on her back, which later turned into bone  swab for SARS-CoV-2. Main symptoms were mild fever (max 37.5 °C), mild cough, fatigue and sweating. She was treated as an outpatient with azithromycin and paracetamol and over the next 2 weeks, she recovered completely without the need for hospital admission and with negative control NP swab test for SARS-CoV-2. FOP exacerbation had restarted approximately 4 weeks post-COVID-19 convalescence and has thus continued steadily  up to doses of 64 mg per day with rapid decrease in dosage. She also continuously takes several anti-inflammatory and analgesic medications: a selective COX-2 inhibitor, a combination of paracetamol and opioid analgesic, a leukotriene and a histamine receptor antagonist. However, after SARS-CoV-2 infection, FOP has progressed, and radiotherapy has been unable to halt HO formation. Pathophysiological mechanisms to explain these observations are lacking. No damage or dysfunction of other vital organs was found in the patient after COVID-19 infection. Among the usual laboratory blood tests performed before and after COVID-19 infection, the only difference observed was in the values of C-reactive protein (CRP). Slightly elevated levels of CRP were observed in April 2021  in comparison to September 2020 and March 2021, which were within the reference interval (5.1 mg/mL). Increased hair loss was observed 3 months after infection as part of post-COVID-19 syndrome; no other signs or symptoms were observed or reported by the patient.Being aware of the rarity of her disease, this patient frequently contributes towards understanding of FOP by providing plasma samples for scientific purposes which are obtained for the purposes of evaluation and treatment during flare-ups . A panel of 23 pro- and anti-inflammatory mediators was used to screen her plasma before and after COVID-19 infection. The results were compared to three control samples: two female FOP patients in remission that were not COVID-19 positive and a plasma pool of ten healthy women of the same age group with no bone disorders. This study was approved by the institutional ethics committee and all participants signed an informed consent form. Blood samples were drawn into standard vacuette citrate tubes with special care as not to induce HO by needle insertion. Participants’ plasma samples were screened for differences in cytokine levels using the human cytokine antibody array  and analyzed using the Chemi Doc imaging system (BioRad) according to manufacturer's recommendations. Quantification of chemiluminescent signals was performed with ImageJ 1.52a software (NIH) [We searched the PubMed and Scopus databases for original articles, reviews, letters, short communications and notes in English from 1971 for PubMed and from 2004 for Scopus to the latest date, which was May 2021 for both. Our search strategy included looking for titles, abstracts, and keywords, using the following terms: (“Fibrodysplasia ossificans progressiva” OR “FOP”) AND (“COVID-19” OR “SARS-CoV-2”), including a search of PubMed by the aforementioned MeSH terms . The seaOur search for FOP and COVID-19-related biomedical literature, conducted as previously described, did not yield any results. Upon furthering our search strategy, three articles were found  and non-canonical (Activin A) ligands . Howeverlocus minoris resistentiae). Prolonged ectopic ossification after COVID-19 infection, with marked changes in the cytokine profile of our patient, may point towards potential mechanisms contributing to the pathophysiology of post-acute COVID-19 syndrome, which in this case might be accompanied by aberrations of the innate and adaptive immune system. Understanding of these mechanisms is limited and further study is needed to improve FOP patient care during the COVID-19 pandemic and beyond.This case is the first case report of uncontrolled post-COVID-19 effects in a FOP patient, which manifested with consecutive disease flare-ups followed by progressive HO. The episode was possibly caused by a, thus far, never described form of post-COVID syndrome, which regularly affects the most sensitive and already disturbed parts of the body (


However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were significantly associated with FEV1. This study investigates the utility of assessing gene-by-smoking interactions and underscores their effects on potential pulmonary function.Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV Pulmonary function is used to diagnose chronic obstructive pulmonary disease and to monitor the severity and progression of many lung conditions. Furthermore, even within the normal range, pulmonary function is a risk factor for mortality and morbidity from various conditions5. Genome-wide association studies (GWASs) have identified many single nucleotide variants (SNVs) for pulmonary function after adjusting for cigarette smoking, a well-established risk factor for reduced pulmonary function, as a confounder and potential effect modifier14. The interplay between genetic and environmental factors likely plays a role in complex traits, including chronic lung diseases. A large GWAS meta-analysis has shown the existence of SNV-by-smoking interaction in relation to two measures of pulmonary function  by performing joint analyses of genetic main effects and interaction effects of single SNVs and their interaction with smoking14. However, there is a lack of gene-by-environment (GxE) interaction analysis involving low-frequency  or rare variants (MAF less than 1%)15, which are typically not well captured or imputed by previous GWAS meta-analyses of pulmonary function. The more recent use of genotyping platforms including lower frequency and rare variants enables better assessment of the role of rare genetic variation in disease.Measures of pulmonary function provide important clinical and research tools for evaluating lung disease and other morbidities16. While single-variant-based interaction tests for common variants are well-established18, methods for detecting rare variant GxE interactions are relatively new. Recently developed novel approaches for testing rare variant GxE interaction effects include a joint test that allows for simultaneous testing of the genetic main and interaction effects as well as the ability to assess gene-based GxE interactions only for both related and unrelated individuals22. The joint test and the test for the interaction terms only are both important for different scientific hypotheses. The joint test assesses genetic associations with pulmonary function, accounting for heterogeneity of genetic effects in individuals with different environmental exposures . The test of the interaction terms only can identify genes that modify the effect of smoking on pulmonary function. For single variant analysis, an interaction requires at least four fold larger sample size than a genetic main effect of comparable magnitude23. Similarly, for gene-based interaction tests, larger sample sizes are required for detection, especially for rare variants. This study is the first to incorporate GxE interactions in modeling rare and low-frequency genetic variants and smoking effects on pulmonary function based on large samples. In discovery, we used genetic and phenotypic information from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)24 and SpiroMeta Consortia, and we sought replication of findings in the UK BiLEVE and UK Biobank studies.Due to the low power to detect association with rare variants, a commonly adopted strategy in analyzing rare variant-phenotype associations is to group variants according to genes or genomic regions and test whether the grouped variants are associated with the phenotypeCharacteristics and sample sizes of the study cohorts are presented in Table 1, FVC, and FEV1/FVC ratio) of discovery stage are presented in Figure Quantile–quantile plots of the meta-analysis results for the interaction and joint tests from the six combinations of smoking variables status (ever smoking or current smoking) and pulmonary function measures  and gene-by-ever-smoking analyses  based on joint tests. In both replication studies, GPR126 was also statistically significant in the joint tests for gene-by-current-smoking  and gene-by-ever-smoking . The p-value of the interaction test was not significant for either smoking exposure evaluated , suggesting that these joint test results were largely due to the genetic main effects.In the discovery-stage meta-analyses, GPR126 was previously found to be significantly associated with FEV1/FVC among European ancestry25. Conditioning on this common variant rs3817928, the joint test of gene-by-current-smoking analysis for GPR126 remained nominally significant in the discovery  and genome-wide significant in the replication studies  in GPR126 and report the most significant SNV, rs17280293 (MAF = 3%), in Table GPR126. The significant joint test results for rs17280293 were replicated in the UK BiLEVE and UK Biobank studies , thus rs17280293 remained highly significant in the single-variant-based analysis when conditioning on rs3817928  with the previously reported common variant rs3817928 in PDE3B was significantly associated with FEV1 in the interaction-only test  and joint test  in the gene-by-current-smoking analyses  and joint tests . The other top variant rs61736639 (MAF = 0.7%) was not significant in the replication datasets. According to the Genotype-Tissue Expression (GTEx) project  both GPR126  and PDE3B (median TPM = 8.8) were expressed in lung tissue, relative to a minimal expression threshold of TPM > 0.130.31. However, the gene-level association could be missed if the signal is driven by rare variants or there is interaction with environmental exposures. Therefore, we focused on rare and low-frequency exonic genetic variants and their interaction with cigarette smoking, the major environmental risk factor for reduced lung function. Specifically, we performed gene-based tests of GxE interaction only and joint tests assessing genetic main effects and interaction effects. The joint analysis has been shown to be nearly optimal across a variety of models for common variants17. In some scenarios, the GxE interaction only tests could have higher statistical power than the joint tests21. To boost the statistical power for discovery, we combined data across thirteen studies with 44,429 European ancestry individuals through meta-analyses. Significant genes were examined in two replication studies with a total of 104,611 European ancestry individuals. This study is the first and the largest to incorporate GxE interactions in modeling rare and low-frequency variant genetic and smoking effects on pulmonary function. However, statistical power would continue to be improved with increased sample size. Table Most genome-wide analyses of pulmonary function have focused on common variants or genetic main effectsGPR126. We identified one low-frequency variant rs17280293 which was successfully replicated in our study and was previously reported by Jackson et al15 in a genetic main effect analysis. The SNV is in low LD with the known common variant, suggesting a distinct role of the rare variants. Neither gene-based nor single variant tests identified interaction with smoking for this SNV or this gene. Additionally, we found that PDE3B was significantly associated with FEV1 in the GxE interaction and joint association analysis in the discovery studies, however neither the interaction or joint effect gene-based tests replicated, although one leading rare variant rs142935352 reached nominal significance in UK BiLEVE for the interaction and joint tests. PDE3B had not been reported to be associated with lung function but is believed to be an important regulatory factor in modulating the inflammatory response and expressed in the lung32. One possible explanation is that smoking increases the inflammatory response in the lung, leading to the gene-by-smoking interaction. The signal of PDE3B in the discovery dataset was mainly driven by two SNVs (rs142935352 and rs61736639), both quite rare (MAF < 0.5% in EA), thus difficult to replicate even with large samples. We found that it was challenging to replicate rare signals in general, as rare variants varied across different studies. A variant present in one study was likely not included in the other study .Our results for the GxE joint analysis support the involvement of rare variants in a locus, 31. Second, a few quantile–quantile plots suggested inflation in the gene-by-current-smoking interaction and joint test statistics , there could still be some inflation. Third, we examined exonic rare variants, but we note that signals from rare variants in the regulatory regions are likely to interact with smoking. Inclusion of rare regulatory variants could improve our understanding of disease mechanisms and warrants further investigation. Fourth, our analysis did not take into account the type of cigarette smoking, which could increase the difficulty of replication due to the potential heterogeneity of GxE interaction effects. Fifth, rare and low-frequency variants in the two replication datasets UK BiLEVE and Biobank Study were imputed using the 1000 Genomes and UK10K haplotype reference panel36. Although the imputation quality had been examined through a pseudo-GWAS simulation36, it may still be suboptimal comparing with sequencing data, thus increasing the replication difficulty. In our case, SNVs included in GPR126 and PDE3B all had INFO score > 0.8 and the leading SNVs had INFO score > 0.95 38, Cardiovascular Health Study (CHS)39, Framingham Heart Study (FHS)41, Health, Aging, and Body Composition (HABC) study42, Northern Finland Birth Cohort of 1966 (NFBC1966)43, Multi-Ethnic Study of Atherosclerosis (MESA)44, Rotterdam Study (RS)45, Study of Health in Pomerania (SHIP)46, the Netherlands Epidemiology of Obesity Study (NEO)47, Lothian in Birth Cohort 1936 (LBC1936) study48, and Cooperative Health Research in the Region of Augsburg (KORA) study49. The discovery studies consisted of 44,429 individuals. Replication was conducted in two studies: UK BiLEVE Study  and UK Biobank 50. Study descriptions are provided in the Supplementary Note of Jackson et al., 201815 and Artigas et al., 201551.We combined data from 13 studies for the discovery stage, either from the CHARGE Consortium or the SpiroMeta Consortium: the Age, Environment, Susceptibility (AGES) study, Atherosclerosis Risk in Communities (ARIC) study1, FVC, and their ratio (FEV1/FVC). Details of the spirometry have been previously reported for the discovery15 and replication studies52. Because outlier phenotype values can be influential in rare variant analyses, pulmonary function values with residuals after regressing out covariates (listed below) on each lung function trait larger than four standard deviations from the mean were examined by investigators from each cohort expert in the collection of pulmonary function data. Data points were evaluated regarding whether they were biologically plausible for that individual as opposed to more consistent with data errors. To ensure the normality of the FEV1, FVC, and FEV1/FVC, a ranked-based inverse-normal transformation was performed on each pulmonary function trait by the individual participating studies. For FEV1/FVC, the ratio was first calculated prior to transformation.Spirometric measures included FEVCigarette smoking can have important adverse effects on pulmonary function. Smoking exposure was ascertained by questionnaire at the same time as the pulmonary function tests used in the analyses. Study participants were classified in two different ways: ever smokers vs never-smokers and current smokers vs never-smokers and past-smokers combined. Current smokers were defined as individuals who smoked at least one cigarette per day within the prior 12 months, past smokers were defined as smoking at least one cigarette per day but had stopped at least 12 months, and never smokers reported never having smoked. Ever smokers were a combination of current and past smokers.53. The remaining studies  called their genotypes in accordance to the UK exome chip consortium best practices36 using zCall54.Genotyping of the discovery stage studies was performed mainly using the Illumina HumanExome BeadChip Table . To impr53, we retained only nonsynonymous variants annotated by dbNSFP26 with MAF less than 5% among EAs and excluded monomorphic variants, variants with missing rates larger than 5%, and variants on the sex chromosomes. These low-frequency and rare variants were grouped by gene region in the aggregate variant tests26. Missing genotypes were imputed using a random draw from the binomial distribution with two trials and success probability equal to the estimated MAF. Genes with one or zero variants or overall cumulative minor allele count less than 20 were excluded.All studies performed comparable sample-level quality control steps and removed individuals according to the standard quality control metrics, i.e., sex mismatch, duplicate pairs, unexpected relatives, missing pulmonary function measurement, or missing covariate. Other than the standard variant-level quality control step55. Thorough sample and genotype quality control steps were undertaken before imputation to a combined 1000 Genomes56 and UK10K Project reference panel57. Following imputation, SNVs were excluded if they had imputation INFO score ≤ 0.5 or minor allele count < 3. Full details of the quality control and imputation procedure of the UK BiLEVE/UK Biobank genotype data were described elsewhere52.The replication samples were genotyped using the Affymetrix UK BiLEVE or UK Biobank arrays, which both include substantial overlap with the Illumina Human Exome BeadChip58 to conduct gene-based interaction and joint tests that simultaneously test the genetic main effects as well as GxE interaction effects. As a set-based variance component test, rareGE has been shown to be powerful across different underlying GxE association patterns19. For FHS, we used a modified rareGE joint test which incorporates correlation among family members by including a random intercept with covariance structure proportional to the kinship matrix59. The rareGE interaction, joint and modified joint tests are briefly described in the Supplementary Materials. Both smoking variables were included in the linear regression model as covariates, while one of them was modeled as the primary exposure variable of interest and was tested for interactions. This resulted in a total of six pairs of pulmonary function traits  and smoking status (ever vs never smoking or current vs past plus never smoking). Additional covariates included age, age-squared, sex, height, height-squared, recruitment sites, and the first 10 principal components accounting for any underlying population substructure. Principal components were constructed by each study using GWAS SNVs or exome-chip ancestry informative markers if GWAS not available55. Weight was only included as an adjustment variable for FVC as it is more strongly influenced by adiposity. Study-specific results were meta-analyzed by combining the p-values of the gene-based tests from each discovery study using Stouffer’s weighted Z-score method60: (1) transform p-values to z-values by the inverse CDF of a Gaussian distribution, i.e., ith study’s sample size. The final meta-analysis p-value was calculated as Since single-variant tests are usually underpowered for analyzing rare genetic variants, we used an aggregate variant test that analyzes multiple rare variants in a gene. For studies other than FHS, we utilized the R package rareGEGPR126 herein) with the previously reported leading common SNV, where the reported signal drivers were added in the gene-based test as covariates. For conditional analyses, p-values less than 0.05 were considered as nominally significant. We further investigated the tissue-specific gene expression of the significant genes on the GTEx Project portal .An a priori significance threshold was defined using the Bonferroni correction for the number of tests evaluated. Specifically, we used a significant threshold at 5.7E−07 based on 14,591 genes for 6 smoking status-lung outcome combinations. Significant genes were evaluated for replication in the UK BiLEVE and UK Biobank studies. To identify specific low-frequency or rare variants driving the signals from the aggregate variant tests, we conducted single variant analyses for the significant genes in both the discovery and replication datasets. Additionally, conditional analyses were performed for significant replicated genes (Supplementary Information.


Existing scores to identify children at risk of hospitalized pneumonia-related mortality lack broad external validation. Our objective was to externally validate three such risk scores.We applied the Respiratory Index of Severity in Children (RISC) for HIV-negative children, the RISC-Malawi, and the Pneumonia Etiology Research for Child Health (PERCH) scores to hospitalized children in the Pneumonia REsearch Partnerships to Assess WHO REcommendations (PREPARE) data set. The PREPARE data set includes pooled data from 41 studies on pediatric pneumonia from across the world. We calculated test characteristics and the area under the curve (AUC) for each of these clinical prediction rules.The RISC score for HIV-negative children was applied to 3574 children 0-24 months and demonstrated poor discriminatory ability  = 0.58-0.73) in the identification of children at risk of hospitalized pneumonia-related mortality. The RISC-Malawi score had fair discriminatory value  among 17 864 children 2-59 months. The PERCH score was applied to 732 children 1-59 months and also demonstrated poor discriminatory value .In a large external application of the RISC, RISC-Malawi, and PERCH scores, a substantial number of children were misclassified for their risk of hospitalized pneumonia-related mortality. Although pneumonia risk scores have performed well among the cohorts in which they were derived, their performance diminished when externally applied. A generalizable risk assessment tool with higher sensitivity and specificity to identify children at risk of hospitalized pneumonia-related mortality may be needed. Such a generalizable risk assessment tool would need context-specific validation prior to implementation in that setting. Worldwide, pneumonia is the most common cause of mortality among children 1-59 months old . DespiteTo date, four clinical prediction rules have been derived to identify children at risk of hospitalized pneumonia-related mortality -7. The RThese risk scores have not been widely validated using data from low- and middle-income settings outside sub-Saharan Africa ,9. The RGiven the lack of published reports of their implementation, the impact of existing clinical prediction rules on reducing hospitalized pneumonia-related mortality is unclear . Broad vWe applied the RISC, RISC-Malawi, and PERCH scores for hospitalized pneumonia-related mortality to all hospitalized children with all included parameters in the WHO PREPARE study group data set. The mRISC score includes several variables  which were not widely available in the WHO PREPARE study group data set. Thus, similar to prior work attempting to externally validate the mRISC score , we did This study used de-identified individual patient data from previously published studies in which ethical approval was obtained at each participating site. Additional ethical approval was obtained by the WHO ethics review committee for one study sponsored by the WHO.The WHO PREPARE data set has been described previously . BrieflyAlthough some data sets included older children, the cohort was restricted to children 0-59 months of age to be consistent with most other pneumonia investigations in children -15. We ePneumonia was defined in included studies included in the WHO PREPARE data set according to the WHO Pocket Book of Hospital Care for Children, based on the presence of age-adjusted tachypnea, lower chest indrawing, general danger signs , or signs of respiratory distress  in children with a cough or difficulty breathing .2≤90%. However, if a child’s SpO2 was >90%, chest indrawing became a part of the scoring system. If the SpO2 was ≤90%, chest indrawing was not included in the score assignment. Though originally derived among children 0-24 months old, we also applied the RISC score for HIV-negative children to children 0-59 months old who had all necessary parameters available as a supplement.Our outcome measure was hospitalized pneumonia-related mortality during the respective study periods. Variables included in the RISC, RISC-Malawi, and PERCH scores are found in The RISC-Malawi score had a range of -1 to 17 using weight-for-age z-score (WAZ) and a range of -2 to 23 points using mid-upper arm circumference (MUAC) . As MUACThe PERCH score had a range of -1 to 17 [We determined the accuracy of the RISC, RISC-Malawi, and PERCH scores on hospitalized children 0-59 months old in the WHO PREPARE data set. We calculated the case fatality ratio (CFR), as the number of deaths/number of patients, and the percentage of patients who were correctly classified as true positive and true negative cases among all children at each cut point for each score. We calculated the sensitivity, specificity, and positive and negative likelihood ratios (LR) of each score at ≥ each specified cut point as defined in the scores. We created receiver operating characteristic (ROC) curves for each risk score. Based on published standards, we used the following scale to qualify the discriminatory ability of each score: area under the curve (AUC)≥0.90 for “excellent discrimination”, AUC 0.80 to 0.89 for “good discrimination”, AUC = 0.70-0.79 for “fair discrimination”, and “poor discrimination” for AUC<0.70 ,20.We conducted a complete case analysis and excluded cases with missing data for any parameter. In order to accurately identify children at low-risk of hospitalized pneumonia-related mortality, we aimed to report maximum sensitivity without sacrificing specificity. We, therefore, report risk score cut points with the sensitivity of 60%-80% with concurrent specificity of at least 40%. We present risk predictiveness curves, to show the cumulative percentage of children at risk of hospitalized pneumonia-related mortality by their predicted risk. We report test characteristics and 95% confidence intervals (CI) for the +LRs and the -LRs. All analyses were conducted using Stata version 14.2 .Of the 41 separate data sets in the PREPARE study, there were 26 hospital-based studies and 15 community-based studies  of the deaths in the PERCH study. Lastly, we were unable to assess for collinearity of other variables that may have contributed to hospitalized pneumonia-related mortality, as children admitted to hospitals in resource-limited settings often carry more than one diagnosis concomitantly, which could have driven mortality.In a large external application of the RISC, RISC-Malawi, and PERCH scores, a substantial number of children were misclassified for their risk of hospitalized pneumonia-related mortality. The RISC score for HIV-negative children and the PERCH score had poor discriminatory value. The RISC-Malawi score had fair discriminatory value in identifying children at risk of hospitalized pneumonia-related mortality. Further development of a risk assessment tool with greater sensitivity and specificity to identify children at risk of hospitalized pneumonia-related mortality may be warranted. However, careful consideration is needed on whether clinical prediction rules for hospitalized pneumonia-related mortality should aim to be region-specific, considering local epidemiology and resources, or universal. Finally, risk assessment tools must be reassessed over time particularly with the advent of new interventions such as vaccines and medications, and as health systems strengthen and are more able to provide pulse oximetry measurement, supplemental oxygen, and antibiotics.