Comparison of shipping versus immediate freezer storage of vaginal samples for vaginal microbiota assessment.

ObjectivesWe evaluated how storing vaginal samples at room temperature in stabilising solutions versus immediate freezing affects 16S rRNA gene amplicon sequencing-based microbiota studies, aiming to simplify home and field collection. METHODS: Twenty participants self-collected six mid-vaginal swabs that were stored in two nucleic acid preservatives (three in modified Solution C2 (Qiagen) and three in Amies/RNALater (Sigma)) in January-February 2016. From each set, two were immediately frozen (-80°C) and one was shipped to the University of Idaho (Moscow, Idaho) with return shipping to the Institute for Genome Sciences (Baltimore, Maryland). Amplicon sequencing of the 16S rRNA gene was used to characterise the vaginal microbiota, VALENCIA was used to assign community state types (CSTs), and quantitative PCR (qPCR) of 16S rRNA genes was used to estimate bacterial abundance. Cohen's Kappa statistic was used to assess within-participant agreement. Bayesian difference of means models assessed within-participant comparisons between shipped and immediately frozen samples. RESULTS: There were 115 samples available for analysis. Average duration of transit for shipped samples was 8 days (SD: 1.60, range: 6-11). Within-participant comparisons of CSTs between shipped and immediately frozen samples revealed complete concordance (kappa: 1.0) for both preservative solutions. No significant differences comparing shipped and immediately frozen samples were found with taxon-level comparisons or bacterial abundances based on pan-bacterial qPCR. CONCLUSIONS: Short-term room temperature shipping of vaginal swabs placed in stabilising solutions did not affect vaginal microbiota composition. Home collection with mail-in of vaginal samples may be a reasonable approach for research and clinical purposes to assess the vaginal microbiota.

Oral Microbiota Alterations in Subjects with SARS-CoV-2 Displaying Prevalence of the Opportunistic Fungal Pathogen Candida albicans.

The oral cavity remains an underappreciated site for SARS-CoV-2 infection despite the myriad of oral conditions in COVID-19 patients. Recently, SARS-CoV-2 was shown to replicate in the salivary gland cells causing tissue inflammation. Given the established association between inflammation and microbiome disruption, we comparatively profiled oral microbial differences at a metagenomic level in a cohort of hospitalized COVID-19 patients and matched healthy controls. Specifically, we aimed to evaluate colonization by the opportunistic fungal pathogen Candida albicans, the etiologic agent of oral candidiasis. Comprehensive shotgun metagenomic analysis indicated that, overall, COVID-19 patients exhibited significantly reduced bacterial and viral diversity/richness; we identified 12 differentially abundant bacterial species to be negatively associated with COVID-19, and the functional pathways of certain bacteria to be highly associated with COVID-19 status. Strikingly, C. albicans was recovered from approximately half of the COVID-19 subjects but not from any of the healthy controls. The prevalence of Candida is likely linked to immune hypo-dysregulation caused by COVID-19 favoring Candida proliferation, warranting investigations into the interplay between Candida and SARS-CoV2 and potential therapeutic approaches directed toward oral candidiasis. Collectively, our findings prompt a reassessment of oral opportunistic infection risks during COVID-19 disease and their potential long-term impacts on oral health.

Use of drugs for hypertension or heart failure and the risk of death in COVID-19: association with loop-diuretics.

PURPOSE: To study the association between the use of drugs for hypertension or heart failure, particularly diuretics, and risk of death in COVID-19. METHODS: We conducted a cohort study, based on record linked individual-based data from national registers, of all Swedish inhabitants 50 years and older (n = 3,909,321) at the start of the first SARS-CoV-2 wave in Sweden. The association between use of angiotensin-converting enzyme inhibitors (ACEI), angiotensin II receptor blockers (ARB), thiazides, loop diuretics, aldosterone antagonists, beta blocking agents and calcium channel blockers at the index date 6 March 2020, and death in COVID-19 during 7 March to 31 July 2020, was analysed using Cox-proportional hazards regression, adjusted for a wide range of possible confounders. RESULTS: Use of loop diuretics was associated with higher risk [adjusted hazard ratio (HR) 1.26; 95% confidence interval (95% CI) 1.17-1.35] and thiazides with reduced risk (0.78; 0.69-0.88) of death in COVID-19. In addition, lower risk was observed for ACEI and higher risk for beta-blocking agents, although both associations were weak. For ARB, aldosterone antagonists and calcium channel blockers no significant associations were found. CONCLUSION: In this nationwide cohort of nearly 4 million persons 50 years and older, the use of loop diuretics was associated with increased risk of death in COVID-19 during the first SARS-CoV-2 wave in Sweden. This contrasted to the decreased risk observed for thiazides. As treatment with loop diuretics is common, particularly in the elderly, the group most affected by severe COVID-19, this finding merit further investigation.

SpeciateIT and vSpeciateDB: Novel, fast and accurate per sequence 16S rRNA gene taxonomic classification of vaginal microbiota.

Clustering of sequences into operational taxonomic units (OTUs) and denoising methods are a mainstream stopgap to taxonomically classifying large numbers of 16S rRNA gene sequences. We developed speciateIT, a novel taxonomic classification tool which rapidly and accurately classifies individual amplicon sequences (https://github.com/Ravel-Laboratory/speciateIT). Environment-specific reference databases generally yield optimal taxonomic assignment. To this end, we also present vSpeciateDB, a custom reference database for the taxonomic classification of 16S rRNA gene amplicon sequences from vaginal microbiota. We show that speciateIT requires minimal computational resources relative to other algorithms and, when combined with vSpeciateDB, affords accurate species level classification in an environment-specific manner.

Integrating compositional and functional content to describe vaginal microbiomes in health and disease.

BACKGROUND: A Lactobacillus-dominated vaginal microbiome provides the first line of defense against adverse genital tract health outcomes. However, there is limited understanding of the mechanisms by which the vaginal microbiome modulates protection, as prior work mostly described its composition through morphologic assessment and marker gene sequencing methods that do not capture functional information. To address this gap, we developed metagenomic community state types (mgCSTs) which use metagenomic sequences to describe and define vaginal microbiomes based on both composition and functional potential. RESULTS: MgCSTs are categories of microbiomes classified using taxonomy and the functional potential encoded in their metagenomes. MgCSTs reflect unique combinations of metagenomic subspecies (mgSs), which are assemblages of bacterial strains of the same species, within a microbiome. We demonstrate that mgCSTs are associated with demographics such as age and race, as well as vaginal pH and Gram stain assessment of vaginal smears. Importantly, these associations varied between mgCSTs predominated by the same bacterial species. A subset of mgCSTs, including three of the six predominated by Gardnerella vaginalis mgSs, as well as mgSs of L. iners, were associated with a greater likelihood of bacterial vaginosis diagnosed by Amsel clinical criteria. This L. iners mgSs, among other functional features, encoded enhanced genetic capabilities for epithelial cell attachment that could facilitate cytotoxin-mediated cell lysis. Finally, we report a mgSs and mgCST classifier for which source code is provided and may be adapted for use by the microbiome research community. CONCLUSIONS: MgCSTs are a novel and easily implemented approach to reduce the dimension of complex metagenomic datasets while maintaining their functional uniqueness. MgCSTs enable the investigation of multiple strains of the same species and the functional diversity in that species. Future investigations of functional diversity may be key to unraveling the pathways by which the vaginal microbiome modulates the protection of the genital tract. Importantly, our findings support the hypothesis that functional differences between vaginal microbiomes, including those that may look compositionally similar, are critical considerations in vaginal health. Ultimately, mgCSTs may lead to novel hypotheses concerning the role of the vaginal microbiome in promoting health and disease, and identify targets for novel prognostic, diagnostic, and therapeutic strategies to improve women's genital health. Video Abstract.

Association of Pregnancy and HIV Status With Molecular-Bacterial Vaginosis in Indian Women.

BACKGROUND: Bacterial vaginosis (BV) is a highly prevalent disorder of the cervicovaginal microbiota. Molecular-BV may put women at increased risk for adverse reproductive and obstetric outcomes. We investigated the association of HIV and pregnancy on the vaginal microbiota and associations with molecular-BV in women of reproductive age from Pune, India. SETTING: We studied vaginal samples from N = 170 women, including N = 44 nonpregnant HIV seronegative, N = 56 pregnant seronegative, N = 47 nonpregnant women with HIV (WWH), and N = 23 pregnant WWH, and collected data on clinical, behavioral, and demographic factors. METHODS: We used 16S rRNA gene amplicon sequencing to characterize the composition of the vaginal microbiota. We classified the vaginal microbiota of these women into community state types based on bacterial composition and relative abundance and further categorized them into molecular-BV versus Lactobacillus -dominated states. To determine associations between pregnancy and HIV status with outcome of molecular-BV, logistic regression models were used. RESULTS: There was a high prevalence of molecular-BV (30%) in this cohort. We found that pregnancy was associated with decreased odds of molecular-BV (adjusted OR = 0.35, 95% CI: 0.14 to 0.87), while HIV was associated with increased odds of molecular-BV (adjusted OR = 2.76, 95% CI: 1.33 to 5.73), even when controlling for multiple relevant factors such as age, number of sexual partners, condom use, and douching. CONCLUSION: Larger and longitudinal studies are needed to further characterize molecular-BV and the vaginal microbiota in pregnant women and WWH and relate these factors to infectious, reproductive, and obstetric outcomes. In the long term, these studies may lead to novel microbiota-based therapeutics to improve women's reproductive and obstetric health.

Lactobacillus iners and genital health: molecular clues to an enigmatic vaginal species.

Purpose of review: Vaginal lactobacilli are recognized as important drivers of genital health including protection against bacterial vaginosis and sexually transmitted infections. Lactobacillus iners is distinct from L. crispatus, L. gasseri, and L. jensenii by its high global prevalence in vaginal microbiomes, relatively small genome, production of only L-lactic acid, and inconsistent associations with genital health outcomes. In this review, we summarize our current understanding of the role of L. iners in the vaginal microbiome, highlight the importance of strain-level consideration for this species, and explain that while marker gene-based characterization of the composition of the vaginal microbiota does not capture strain-level resolution, whole metagenome sequencing can aid in expanding our understanding of this species in genital health. Recent findings: L. iners exists in the vaginal microbiome as a unique combination of strains. The functional repertoires of these strain combinations are likely wide and contribute to the survival of this species in a variety of vaginal microenvironments. In published studies to date, strain-specific effects are aggregated and may yield imprecise estimates of risk associated with this species. Summary: The worldwide high prevalence of Lactobacillus iners warrants more research into its functional roles in the vaginal microbiome and how it may directly impact susceptibility to infections. By incorporating strain-level resolution into future research endeavors, we may begin to appreciate L. iners more thoroughly and identify novel therapeutic targets for a variety of genital health challenges.

Investigating the impact of condomless vaginal intercourse and lubricant use on the vaginal metabolome: a pre-post observational study.

OBJECTIVE: The vaginal metabolome is a significant factor in the vaginal microenvironment, and data are emerging on its independent role in urogenital health. Condomless vaginal intercourse and personal lubricant use are common practices that may affect the vaginal metabolome. The aim of the present study is to describe the associations between condomless intercourse and lubricant use on the vaginal metabolome. METHODS: This study used archived mid-vaginal swabs from a 10-week observational cohort of reproductive age women who self-collected samples and recorded behavioural diaries daily. Cases and controls were defined as participants who self-reported condomless vaginal intercourse with or without lubricant use, respectively. Samples were drawn prior to and following condomless vaginal intercourse. Twenty-two case participants were race/ethnicity matched to 22 control participants. Mid-vaginal swabs were subjected to 16S rRNA gene amplicon sequencing and untargeted ultrahigh performance liquid chromatography tandem mass spectroscopy metabolomics. Bayesian mixed-effects regression (unadjusted and adjusted for the vaginal microbiota) was used to evaluate differences in metabolite concentration associated with vaginal intercourse and lubricant use. RESULTS: Both condomless penile-vaginal intercourse and lubricant use were independently associated with higher (up to 8.3-fold) concentrations of metabolites indicative of epithelial damage (eg, sarcosine) and many host-produced antioxidants. Lubricant use was significantly associated with increases in lipids related to cellular damage, host-produced sphingolipids (antimicrobials), antioxidants and salicylate, a cooling agent common to lubricants, in a study design which controls for the independent effect of intercourse. Metabolites involved in oxidative stress and salicylate were strongly correlated with several molecular bacterial vaginosis-associated bacteria. CONCLUSIONS: This study provides important foundational data on how condomless vaginal-penile intercourse and lubricant use affect the vaginal metabolome and may affect the protective mechanisms in the vaginal microenvironment.

High-resolution functional description of vaginal microbiomes in health and disease.

Background: A Lactobacillus-dominated vaginal microbiome provides the first line of defense against numerous adverse genital tract health outcomes. However, there is limited understanding of the mechanisms by which the vaginal microbiome modulates protection, as prior work mostly described its composition through morphologic assessment and marker gene sequencing methods that do not capture functional information. To address this limitation, we developed metagenomic community state types (mgCSTs) which uses metagenomic sequences to describe and define vaginal microbiomes based on both composition and function. Results: MgCSTs are categories of microbiomes classified using taxonomy and the functional potential encoded in their metagenomes. MgCSTs reflect unique combinations of metagenomic subspecies (mgSs), which are assemblages of bacterial strains of the same species, within a microbiome. We demonstrate that mgCSTs are associated with demographics such as age and race, as well as vaginal pH and Gram stain assessment of vaginal smears. Importantly, these associations varied between mgCSTs predominated by the same bacterial species. A subset of mgCSTs, including three of the six predominated by Gardnerella mgSs, as well as a mgSs of L. iners, were associated with a greater likelihood of Amsel bacterial vaginosis diagnosis. This L. iners mgSs, among other functional features, encoded enhanced genetic capabilities for epithelial cell attachment that could facilitate cytotoxin-mediated cell lysis. Finally, we report a mgSs and mgCST classifier as an easily applied, standardized method for use by the microbiome research community. Conclusions: MgCSTs are a novel and easily implemented approach to reducing the dimension of complex metagenomic datasets, while maintaining their functional uniqueness. MgCSTs enable investigation of multiple strains of the same species and the functional diversity in that species. Future investigations of functional diversity may be key to unraveling the pathways by which the vaginal microbiome modulates protection to the genital tract. Importantly, our findings support the hypothesis that functional differences between vaginal microbiomes, including those that may look compositionally similar, are critical considerations in vaginal health. Ultimately, mgCSTs may lead to novel hypotheses concerning the role of the vaginal microbiome in promoting health and disease, and identify targets for novel prognostic, diagnostic, and therapeutic strategies to improve women's genital health.

A prognostic model for predicting the duration of 20,049 sickness absence spells due to shoulder lesions in a population-based cohort in Sweden.

MAIN OBJECTIVE: Sickness absence duration for shoulder lesion patients is difficult to prognosticate, and scientific evidence for the sick-listing practice is lacking. Our objective was to develop a clinically implementable prediction model for the duration of a sickness absence spell due to shoulder lesions. METHODS: All new sickness absence spells due to shoulder lesions (ICD-10-code: M75) issued in the period January 2010-June 2012 that were longer than 14 days were identified through the nationwide sickness absence insurance register. Information on predictors was linked from four other nationwide registers. Piecewise-constant hazards regression models were fitted to predict duration of sickness absence. The model was developed and validated using split sample validation. Variable selection was based on log-likelihood loss ranking when excluding a variable from the model. The model was evaluated using calibration plots and the c-statistic. RESULTS: 20 049 sickness absence spells were identified, of which 34% lasted >90 days. Predictors included in the model were age, sex, geographical region, occupational status, educational level, birth country, specialized healthcare at start of the spell, number of sickness absence days in the last 12 months, and specialized healthcare the last 12 months, before start date of the index sickness absence spell. The model was satisfactorily specified and calibrated. Overall c-statistic was 0.54 (95% CI 0.53-0.55). C-statistic for predicting durations >90, >180, and >365 days was 0.61, 0.66, and 0.74, respectively. SIGNIFICANCE: The model can be used to predict the duration of sickness absence due to shoulder lesions. Covariates had limited predictive power but could discriminate the very long sickness absence spells from the rest.

Dynamics of the Gut Microbiome in Shigella-Infected Children during the First Two Years of Life.

Shigella continues to be a major contributor to diarrheal illness and dysentery in children younger than 5 years of age in low- and middle-income countries. Strategies for the prevention of shigellosis have focused on enhancing adaptive immunity. The interaction between Shigella and intrinsic host factors, such as the microbiome, remains unknown. We hypothesized that Shigella infection would impact the developing microbial community in infancy and, conversely, that changes in the gastrointestinal microbiome may predispose infections. To test this hypothesis, we characterized the gastrointestinal microbiota in a longitudinal birth cohort from Malawi that was monitored for Shigella infection using 16S rRNA amplicon sequencing. Children with at least one Shigella quantitative polymerase chain reaction (qPCR) positive sample during the first 2 years of life (cases) were compared to uninfected controls that were matched for sex and age. Overall, the microbial species diversity, as measured by the Shannon diversity index, increased over time, regardless of case status. At early time points, the microbial community was dominated by Bifidobacterium longum and Escherichia/Shigella. A greater abundance of Prevotella 9 and Bifidobacterium kashiwanohense was observed at 2 years of age. While no single species was associated with susceptibility to Shigella infection, significant increases in Lachnospiraceae NK4A136 and Fusicatenibacter saccharivorans were observed following Shigella infection. Both taxa are in the family Lachnospiraceae, which are known short-chain fatty acid producers that may improve gut health. Our findings identified temporal changes in the gastrointestinal microbiota associated with Shigella infection in Malawian children and highlight the need to further elucidate the microbial communities associated with disease susceptibility and resolution. IMPORTANCE Shigella causes more than 180 million cases of diarrhea globally, mostly in children living in poor regions. Infection can lead to severe health impairments that reduce quality of life. There is increasing evidence that disruptions in the gut microbiome early in life can influence susceptibility to illnesses. A delayed or impaired reconstitution of the microbiota following infection can further impact overall health. Aiming to improve our understanding of the interaction between Shigella and the developing infant microbiome, we investigated changes in the gut microbiome of Shigella-infected and uninfected children over the course of their first 2 years of life. We identified species that may be involved in recovery from Shigella infection and in driving the microbiota back to homeostasis. These findings support future studies into the elucidation of the interaction between the microbiota and enteric pathogens in young children and into the identification of potential targets for prevention or treatment.

Wellbeing and mental health amongst medical students in Canada.

RESEARCH: There is abundant data revealing that there is significant rate of rates of Psychiatric morbidity, psychological stress, and burnout in the medical student population. A core study group in the UK collaborated with 12 countries around the world to review medical student wellness. In this context we surveyed 101 medical students at the Cummings medical school, Calgary, Canada during the height of the COVID pandemic regarding their wellbeing and mental health. RESULTS/MAIN FINDINGS: Prior to medical school 27% reported a diagnosis with a mental disorder. Whilst at medical school 21% reported a mental health condition, most commonly an anxiety disorder and or depressive disorder. The most commonly reported source of stress was study at 81%, the second being relationships at 62%, money stress was a significant source of stress for 35%, and finally 10% reported accommodation or housing as stressful. Interestingly only 14% tested CAGE positive but 20% of students reported having taken a non-prescription substance to feel better or regulate their mood. Seventy-five percent of medical students met specific case criteria for exhaustion on the Oldenburg Burnout inventory 74% met criteria for the GHQ questionnaire. CONCLUSIONS: These findings confirm that medical students are facing significant stressors during their training. These stressors include, in order of frequency, study, relational, financial, and accommodation issues. Nonprescription Substance use was a common finding as well as exhaustion and psychiatric morbidity. Future interventions pursued will have to address cultural issues as well as the organizational and individual determinates of stress.

Mortality in hospitalized COVID-19 patients was associated with the COVID-19 admission rate during the first year of the pandemic in Sweden.

INTRODUCTION: Studies from the first pandemic wave found associations between COVID-19 hospital load and mortality. Here, we aimed to study if mortality of hospitalized COVID-19 patients was associated with the COVID-19 admission rate during a full year of the pandemic in Sweden. METHOD: Observational review of all patients admitted to hospital with COVID-19 in Sweden between March 2020 and February 2021 (n = 42,017). Primary outcome was 60-day all-cause mortality related to number of COVID-19 hospital admissions per month/100,000 inhabitants. Poisson regression was used to estimate the relative risk for death by month of admission, adjusting for pre-existing factors. RESULTS: The overall mortality was 17.4%. Excluding March 2020, mortality was clearly correlated to the number of COVID-19 admissions per month (coefficient of correlation ρ=.96; p<.0001). After adjustment for pre-existing factors, the correlation remained significant (ρ=.75, p=.02). Patients admitted in December (high admission rate and high mortality) had more comorbidities and longer hospital stays, and patients treated in intensive care units (ICU) had longer pre-ICU hospital stays and worse respiratory status on ICU admission than those admitted in July to September (low admission rate and low mortality). CONCLUSION: Mortality in hospitalized COVID-19 patients was clearly associated with the COVID-19 admission rate. Admission of healthier patients between pandemic waves and delayed ICU care during wave peaks could contribute to this pattern. The study supports measures to flatten-the-curve to reduce the number of COVID-19 patients admitted to hospital.

Assessing the Concordance Between Urogenital and Vaginal Microbiota: Can Urine Specimens Be Used as a Proxy for Vaginal Samples?

Background: The vaginal microbiota play a key role in defense against reproductive tract infections; however, many population-based women's health studies do not collect vaginal samples. Molecular examinations of urine samples have revealed common vaginal bacteria. We sought to assess the extent that community state type assignments of archived random-catch and clean-catch urine samples agreed with the paired vaginal samples in both reproductive-age and peri/post-menopausal women. Results: Using archived samples, we evaluated the microbiota concordance among women in three studies: two with paired mid-vaginal/random-catch urine (N=91 reproductive-age participants and N=13 peri/post-menopausal participants), and one with paired mid-vaginal/clean-catch urine (N=99 reproductive-age participants). Microbiota composition was characterized by sequencing amplicons of the 16S rRNA gene V3-V4 regions and assigned to community state types. Similarity of paired samples was gauged using agreement of community state types and Yue-Clayton θ indices. Analysis of Composition of Microbiomes II indicated which taxa were differently relatively abundant in paired vaginal and urine samples. In reproductive-age women, random-catch and clean-catch urines were 89.0% and 86.9% concordant on five community state types with paired mid-vaginal swabs, and Kappa statistics indicated almost perfect agreement (κrandom-catch=.85, κclean-catch=.81, p<0.0001). A small number of pairs of samples were discordant (23/190, 12%), and discordant pairs tended to be between samples classified to L. iners-dominated and/or low-Lactobacillus states. Concordance and agreement remained similar when dichotomizing the microbiota to Lactobacillus-dominated versus low-Lactobacillus microbiota, as well as when evaluating separately the three subtypes of the low-Lactobacillus community state type IV. Median similarity of paired urine/vaginal samples was high (θrandom-catch=.85, θclean-catch=.88), and a comparison of the random-catch and clean-catch similarity scores showed no significant difference (p=.80). Concordance and similarity were lower for peri/post-menopausal women, but agreement remained substantial (76.9% concordant, κrandom-catch= 0.64, θrandom-catch=.62). Taxonomic-level analysis confirmed these findings. Conclusions: Random-catch and clean-catch urine samples showed substantial agreement on bacterial composition to paired mid-vaginal samples, indicating that the genitourinary microbiota may be a reliable proxy for assessing the overall composition of the vaginal microbiota via community state types. This data suggests that urine samples can, with proper interpretation, be utilized as a surrogate for developing preliminary data and hypothesis-generating studies.

Predicting the duration of sickness absence due to knee osteoarthritis: a prognostic model developed in a population-based cohort in Sweden.

BACKGROUND: Predicting the duration of sickness absence (SA) among sickness absent patients is a task many sickness certifying physicians as well as social insurance officers struggle with. Our aim was to develop a prediction model for prognosticating the duration of SA due to knee osteoarthritis. METHODS: A population-based prospective study of SA spells was conducted using comprehensive microdata linked from five Swedish nationwide registers. All 12,098 new SA spells > 14 days due to knee osteoarthritis in 1/1 2010 through 30/6 2012 were included for individuals 18-64 years. The data was split into a development dataset (70 %, nspells =8468) and a validation data set (nspells =3690) for internal validation. Piecewise-constant hazards regression was performed to prognosticate the duration of SA (overall duration and duration > 90, >180, or > 365 days). Possible predictors were selected based on the log-likelihood loss when excluding them from the model. RESULTS: Of all SA spells, 53 % were > 90 days and 3 % >365 days. Factors included in the final model were age, sex, geographical region, extent of sickness absence, previous sickness absence, history of specialized outpatient healthcare and/or inpatient healthcare, employment status, and educational level. The model was well calibrated. Overall, discrimination was poor (c = 0.53, 95 % confidence interval (CI) 0.52-0.54). For predicting SA > 90 days, discrimination as measured by AUC was 0.63 (95 % CI 0.61-0.65), for > 180 days, 0.69 (95 % CI 0.65-0.71), and for SA > 365 days, AUC was 0.75 (95 % CI 0.72-0.78). CONCLUSION: It was possible to predict patients at risk of long-term SA (> 180 days) with acceptable precision. However, the prediction of duration of SA spells due to knee osteoarthritis has room for improvement.

Refinement of 16S rRNA gene analysis for low biomass biospecimens.

High-throughput phylogenetic 16S rRNA gene analysis has permitted to thoroughly delve into microbial community complexity and to understand host-microbiota interactions in health and disease. The analysis comprises sample collection and storage, genomic DNA extraction, 16S rRNA gene amplification, high-throughput amplicon sequencing and bioinformatic analysis. Low biomass microbiota samples (e.g. biopsies, tissue swabs and lavages) are receiving increasing attention, but optimal standardization for analysis of low biomass samples has yet to be developed. Here we tested the lower bacterial concentration required to perform 16S rRNA gene analysis using three different DNA extraction protocols, three different mechanical lysing series and two different PCR protocols. A mock microbiota community standard and low biomass samples (108, 107, 106, 105 and 104 microbes) from two healthy donor stools were employed to assess optimal sample processing for 16S rRNA gene analysis using paired-end Illumina MiSeq technology. Three DNA extraction protocols tested in our study performed similar with regards to representing microbiota composition, but extraction yield was better for silica columns compared to bead absorption and chemical precipitation. Furthermore, increasing mechanical lysing time and repetition did ameliorate the representation of bacterial composition. The most influential factor enabling appropriate representation of microbiota composition remains sample biomass. Indeed, bacterial densities below 106 cells resulted in loss of sample identity based on cluster analysis for all tested protocols. Finally, we excluded DNA extraction bias using a genomic DNA standard, which revealed that a semi-nested PCR protocol represented microbiota composition better than classical PCR. Based on our results, starting material concentration is an important limiting factor, highlighting the need to adapt protocols for dealing with low biomass samples. Our study suggests that the use of prolonged mechanical lysing, silica membrane DNA isolation and a semi-nested PCR protocol improve the analysis of low biomass samples. Using the improved protocol we report a lower limit of 106 bacteria per sample for robust and reproducible microbiota analysis.

Mortality trends among hospitalised COVID-19 patients in Sweden: A nationwide observational cohort study.

BACKGROUND: It is important to know if mortality among hospitalised COVID-19 patients has changed as the pandemic has progressed. The aim of this study was to describe the dynamics over time of mortality among patients hospitalised for COVID-19 in Sweden, using nationwide data compiled by the Swedish National Board of Health and Welfare. METHODS: Observational cohort study where all patients hospitalised in Sweden between March 1 and September 30, 2020, with SARS-CoV-2 RNA positivity 14 days before to 5 days after admission and a discharge code for COVID-19 were included. Outcome was 60-day all-cause mortality. Patients were categorised according to month of hospital admission. Poisson regression was used to estimate the relative risk of death by month of admission, adjusting for, age, sex, comorbidities, care dependency, country of birth, healthcare region, and Simplified Acute Physiology, version 3 (patients in intensive care units; ICU). FINDINGS: A total of 17,140 patients were included, of which 2943 died within 60 days of admission. The overall 60-day mortality was thus 17·2% (95% CI, 16·6%-17·7%), and it decreased from 24·7% (95% CI, 23·0%-26·5%) in March to 10·4% (95% CI, 8·9%-12·1%) post-wave (July-September). Adjusted relative risk (RR) of death was 0·46 (95% CI, 0·39-0·54) post-wave, using March as reference. Corresponding RR for patients not admitted to ICU and those admitted to ICU were 0·49 (95% CI, 0·42-0·59) and 0·49 (95% CI, 0·33-0·72), respectively. The proportion of patients admitted to ICU decreased from 19·4% (95% CI, 17·9%-21·1%) in the March cohort to 8·9% (95% CI, 7·5%-10·6%) post-wave. INTERPRETATION: There was a gradual decline in mortality during the spring of 2020 in Swedish hospitalised COVID-19 patients, independent of baseline patient characteristics. Future research is needed to explain the reasons for this decline. The changing COVID-19 mortality should be taken into account when management and results of studies from the first pandemic wave are evaluated. FUNDING: This study was funded by Sweden's National Board of Health and Welfare.

Concordance of Immunohistochemistry-Based and Gene Expression-Based Subtyping in Breast Cancer.

Background: Use of immunohistochemistry-based surrogates of molecular breast cancer subtypes is common in research and clinical practice, but information on their comparative validity and prognostic capacity is scarce. Methods: Data from 2 PAM50-subtyped Swedish breast cancer cohorts were used: Stockholm tamoxifen trial-3 with 561 patients diagnosed 1976-1990 and Clinseq with 237 patients diagnosed 2005-2012. We evaluated 3 surrogate classifications; the immunohistochemistry-3 surrogate classifier based on estrogen receptor, progesterone receptor, and HER2 and the St. Gallen and Prolif surrogate classifiers also including Ki-67. Accuracy, kappa, sensitivity, and specificity were computed as compared with PAM50. Alluvial diagrams of misclassification patterns were plotted. Distant recurrence-free survival was assessed using Kaplan-Meier plots, and tamoxifen treatment benefit for luminal subtypes was modeled using flexible parametric survival models. Results: The concordance with PAM50 ranged from poor to moderate (kappa = 0.36-0.57, accuracy = 0.54-0.75), with best performance for the Prolif surrogate classification in both cohorts. Good concordance was only achieved when luminal subgroups were collapsed (kappa = 0.71-0.69, accuracy = 0.90-0.91). The St. Gallen surrogate classification misclassified luminal A into luminal B; the reverse pattern was seen with the others. In distant recurrence-free survival, surrogates were more similar to each other than PAM50. The difference in tamoxifen treatment benefit between luminal A and B for PAM50 was not replicated with any surrogate classifier. Conclusions: All surrogate classifiers had limited ability to distinguish between PAM50 luminal A and B, but patterns of misclassifications differed. PAM50 subtyping appeared to yield larger separation of survival between luminal subtypes than any of the surrogate classifications.

Systemic anti-commensal response to fungi analyzed by flow cytometry is related to gut mycobiome ecology.

BACKGROUND: Interest for the study of gut mycobiota in relation with human health and immune homeostasis has increased in the last years. From this perspective, new tools to study the immune/fungal interface are warranted. Systemic humoral immune responses could reflect the dynamic relationships between gut mycobiota and immunity. Using a novel flow cytometry technology (Fungi-Flow) to determine immunoglobulin (Ig) responses to fungi, we studied the relationships between gut mycobiota and systemic humoral anti-commensal immunity. RESULTS: The Fungi-Flow method allows a sensitive and specific measurement of systemic IgG responses against 17 commensal and environmental fungi from the two main divisions; Ascomycota and Basidiomycota. IgG responses exhibited a high inter-individual variability. Anti-commensal IgG responses were contrasted with the relative abundance, alpha-diversity, and intra-genus richness of fungal species in gut mycobiota of twenty healthy donors. Categorization of gut mycobiota composition revealed two differentiated fungal ecosystems. Significant difference of anti-Saccharomyces systemic IgG responses were observed in healthy donors stratified according to the fungal ecosystem colonizing their gut. A positive and significant correlation was observed between the variety of IgG responses against fungal commensals and intestinal alpha-diversity. At the level of intra-genus species richness, intense IgG responses were associated with a low intra-genus richness for known pathobionts, but not commensals. CONCLUSIONS: Fungi-Flow allows an easy and reliable measure of personalized humoral responses against commensal fungi. Combining sequencing technology with our novel Fungi-Flow immunological method, we propose that there are at least two defined ecosystems in the human gut mycobiome associated with systemic humoral responses. Fungi-Flow opens new opportunities to improve our knowledge about the impact of mycobiota in humoral anti-commensal immunity and homeostasis. Video Abstract.