Early diagnosis of bloodstream infection (BSI) is crucial for informed antibiotic use. This study developed a machine learning approach for early BSI detection using a comprehensive dataset from Rigshospitalet, Denmark (2010-2020). The dataset included 144,398 samples from adult patients, containing blood culture results, demographics, and up to 36 biochemical variables. Positive blood culture was observed in 6.4% of samples, mostly caused by Staphylococcus aureus, Escherichia coli, and Enterococcus faecium. 80% of the samples (N = 43,351 patients) were used for ML model development and five-fold cross-validation, with 20% for independent testing (N = 10,837). Among seven models, LightGBM performed best, achieving an AUC of 0.69 on the test set. It was more accurate in detecting negatives, with a negative predictive value (NPV) of 0.96 and specificity of 0.74, compared to a positive predictive value (PPV) of 0.13 and sensitivity of 0.54. SHapley Additive exPlanations (SHAP) identified platelets, leukocytes, and neutrophils-to-lymphocytes as the top-3 predictive features. The model showed higher sensitivity (average 0.66) for common pathogens, e.g., 0.71 for E. coli. Results highlight the potential of biochemical variables as diagnostic factors for BSI, indicating clinical use to focus on identifying patients at low risks and can be further enhanced in future investigations.

Alba domain-containing proteins are ubiquitously found in archaea and eukaryotes. By binding to either DNA, RNA, or DNA:RNA hybrids, these proteins function in genome stabilization, chromatin organization, gene regulation, and/or translational modulation. In the malaria parasite Plasmodium falciparum, six Alba domain proteins PfAlba1-6 have been described, of which PfAlba1 has emerged as a "master regulator" of translation during parasite intra-erythrocytic development (IED). Given that a tight control of gene expression is especially important during IED, when malaria pathogenesis manifests, in this study, we focus on three other P. falciparum Albas, PfAlba2-4. Because genetic manipulation of the genomic loci of PfAlba2-4 was unsuccessful, we overexpressed each of these proteins from an episome under a strong constitutive promoter. We observed that PfAlba2 or PfAlba3 overexpression strongly reduced parasite growth and impacted IED stage transitions. In contrast, elevated levels of PfAlba4 were well-tolerated by the parasite. In keeping with this, differential gene expression analysis using RNA-seq of PfAlba2 or PfAlba3 overexpressing strains revealed a significant misregulation of mRNAs encoding virulence factors, such as those related to erythrocyte invasion; a general repression of var gene expression was also apparent. PfAlba4 overexpression, on the other hand, did not significantly perturb the steady-state transcriptome of IED stages and appeared to enhance var mRNA levels. Moreover, distinct sets of genes were targeted by each PfAlba for regulation. Taken together, this study highlights the nonredundant roles of PfAlba proteins in the P. falciparum IED, emphasizing their importance in subtelomeric chromatin biology and RNA regulation. IMPORTANCE The malaria parasite Plasmodium falciparum tightly controls the expression of its genes at the epigenetic, transcriptional, post-transcriptional, and translational levels to synthesize essential proteins, including virulence factors, in a timely and spatially coordinated manner. A family of six proteins implicated in this process is called PfAlba, characterized by the presence of the DNA-, RNA- or DNA:RNA hybrid-binding Alba domain. To better understand the cellular pathways regulated by this protein family, we overexpressed three PfAlbas during P. falciparum intra-erythrocytic growth and found that high levels of PfAlba2 and PfAlba3 were detrimental to parasite development. This was accompanied by significant changes in the parasite's transcriptome, either with regards to mRNA steady-state levels or expression timing. PfAlba4 overexpression, on the other hand, was well-tolerated by the parasite. Overall, our results delineate specific pathways targeted by individual PfAlbas for regulation and link PfAlba2/PfAlba3 to mutually exclusive expression of the virulence-promoting surface antigen PfEMP1.

Abstract Background Human genetic contribution to HIV progression remains inadequately explained. The type 1 interferon (IFN) pathway is important for host control of HIV and variation in type 1 IFN genes may contribute to disease progression. This study assessed the impact of variations at the gene and pathway level of type 1 IFN on HIV-1 viral load (VL). Methods Two cohorts of antiretroviral (ART) naïve participants living with HIV (PLWH) with either early (START) or advanced infection (FIRST) were analysed separately. Type 1 IFN genes (n = 17) and receptor subunits (IFNAR1, IFNAR2) were examined for both cumulated type 1 IFN pathway analysis and individual gene analysis. SKAT-O was applied to detect associations between the genotype and HIV-1 study entry viral load (log10 transformed) as a proxy for set point VL; P-values were corrected using Bonferroni (P < 0.0025). Results The analyses among those with early infection included 2429 individuals from five continents. The median study entry HIV VL was 14,623 (IQR 3460–45100) copies/mL. Across 673 SNPs within 19 type 1 IFN genes, no significant association with study entry VL was detected. Conversely, examining individual genes in START showed a borderline significant association between IFNW1, and study entry VL (P = 0.0025). This significance remained after separate adjustments for age, CD4+ T-cell count, CD4+/CD8+ T-cell ratio and recent infection. When controlling for population structure using linear mixed effects models (LME), in addition to principal components used in the main model, this was no longer significant (p = 0.0244). In subgroup analyses stratified by geographical region, the association between IFNW1 and study entry VL was only observed among African participants, although, the association was not significant when controlling for population structure using LME. Of the 17 SNPs within the IFNW1 region, only rs79876898 (A > G) was associated with study entry VL (p = 0.0020, beta = 0.32; G associated with higher study entry VL than A) in single SNP association analyses. The findings were not reproduced in FIRST participants. Conclusion Across 19 type 1 IFN genes, only IFNW1 was associated with HIV-1 study entry VL in a cohort of ART-naïve individuals in early stages of their infection, however, this was no longer significant in sensitivity analyses that controlled for population structures using LME.

Antibiotic-resistant bacterial infections are increasingly an issue in allogenic hematopoietic stem cell transplant patients. How antibiotic treatment impacts antibiotic resistance in the human gut microbiome remains poorly understood in vivo. Here, a total of 577 fecal samples from 233 heavily antibiotic-treated transplant patients were examined using high-resolution prescription data and shotgun metagenomics. The 13 most frequently used antibiotics were significantly associated with 154 (40% of tested associations) microbiome features. Use of broad-spectrum β-lactam antibiotics was most markedly associated with microbial disruption and increase in resistome features. The enterococcal vanA gene was positively associated with 8 of the 13 antibiotics, and in particular piperacillin/tazobactam and vancomycin. Here, we highlight the need for a high-resolution approach in understanding the development of antibiotic resistance in the gut microbiome. Our findings can be used to inform antibiotic stewardship and combat the increasing threat of antibiotic resistance.

Type 2 diabetes mellitus (T2DM) can be multifactorial where both genetics and environmental factors play a role. We aimed to investigate the use of polygenic risk scores (PRS) in the prediction of pre-transplant T2DM and post-transplant diabetes mellitus (PTDM) among solid organ transplant (SOT) patients. Using non-genetic risk scores alone; and the combination with PRS, separate logistic regression models were built and compared using receiver operator curves. Patients were assessed pre-transplant and in three post-transplant periods: 0-45, 46-365 and >365 days. A higher PRS was significantly associated with increased odds of pre-transplant T2DM. However, no improvement was observed for pre-transplant T2DM prediction when comparing PRS combined with non-genetic risk scores to using non-genetic risk scores alone. This was also true for predictions of PTDM in all three post-transplant periods. This study demonstrated that polygenic risk was only associated with the risk of T2DM among SOT recipients prior to transplant and not for PTDM. Combining PRS with a clinical model of non-genetic risk scores did not significantly improve the predictive ability, indicating its limited clinical utility in identifying patients at high risk for T2DM before transplantation, suggesting that non-genetic or different genetic factors may contribute to PTDM.

Objective: Human leucocyte antigen (HLA) class I alleles are the main host genetic factors involved in controlling HIV-1 viral load (VL). Nevertheless, HLA diversity has proven a significant challenge in association studies. We assessed how accounting for binding affinities of HLA class I alleles to HIV-1 peptides facilitate association testing of HLA with HIV-1 VL in a heterogeneous cohort. Design: Cohort from the Strategic Timing of AntiRetroviral Treatment (START) study. Methods: We imputed HLA class I alleles from host genetic data (2546 HIV+ participants) and sampled immunopeptidomes from 2079 host-paired viral genomes (targeted amplicon sequencing). We predicted HLA class I binding affinities to HIV-1 and unspecific peptides, grouping alleles into functional clusters through consensus clustering. These functional HLA class I clusters were used to test associations with HIV VL. Results: We identified four clades totaling 30 HLA alleles accounting for 11.4% variability in VL. We highlight HLA-B∗57:01 and B∗57:03 as functionally similar but yet overrepresented in distinct ethnic groups, showing when combined a protective association with HIV+ VL (log, β −0.25; adj. P -value < 0.05). We further demonstrate only a slight power reduction when using unspecific immunopeptidomes, facilitating the use of the inferred functional HLA groups in other studies Conclusion: The outlined computational approach provides a robust and efficient way to incorporate HLA function and peptide diversity, aiding clinical association studies in heterogeneous cohorts. To facilitate access to the proposed methods and results we provide an interactive application for exploring data.

Background The immune pathogenesis underlying the diverse clinical course of COVID-19 is poorly understood. Currently, there is an unmet need in daily clinical practice for early biomarkers and improved risk stratification tools to help identify and monitor COVID-19 patients at risk of severe disease. Methods We performed longitudinal assessment of stimulated immune responses in 30 patients hospitalized with COVID-19. We used the TruCulture whole-blood ligand-stimulation assay applying standardized stimuli to activate distinct immune pathways, allowing quantification of cytokine responses. We further characterized immune cell subsets by flow cytometry and used this deep immunophenotyping data to map the course of clinical disease within and between patients. Results Here we demonstrate impairments in innate immune response pathways at time of COVID-19 hospitalization that are associated with the development of severe disease. We show that these impairments are transient in those discharged from hospital, as illustrated by functional and cellular immune reconstitution. Specifically, we identify lower levels of LPS-stimulated IL-1β, and R848-stimulated IL-12 and IL-17A, at hospital admission to be significantly associated with increasing COVID-19 disease severity during hospitalization. Furthermore, we propose a stimulated immune response signature for predicting risk of developing severe or critical COVID-19 disease at time of hospitalization, to validate in larger cohorts. Conclusions We identify early impairments in innate immune responses that are associated with subsequent COVID-19 disease severity. Our findings provide basis for early identification of patients at risk of severe disease which may have significant implications for the early management of patients hospitalized with COVID-19.

BACKGROUND:Many interventional in-patient coronavirus disease 2019 (COVID-19) trials assess primary outcomes through day 28 post-randomization. Since a proportion of patients experience protracted disease or relapse, such follow-up period may not fully capture the course of the disease, even when randomization occurs a few days after hospitalization. METHODS:Among adults hospitalized with COVID-19 in eastern Denmark from 18 March 2020-12 January 2021 we assessed all-cause mortality, recovery, and sustained recovery 90 days after admission, and readmission and all-cause mortality 90 days after discharge. Recovery was defined as hospital discharge and sustained recovery as recovery and alive without readmissions for 14 consecutive days. RESULTS:Among 3386 patients included in the study, 2796 (82.6%) reached recovery and 2600 (77.0%) achieved sustained recovery. Of those discharged from hospital, 556 (19.9%) were readmitted and 289 (10.3%) died. Overall, the median time to recovery was 6 days (interquartile range [IQR]: 3-10), and 19 days (IQR: 11-33) among patients in intensive care in the first 2 days of admission. CONCLUSIONS:Postdischarge readmission and mortality rates were substantial. Therefore, sustained recovery should be favored to recovery outcomes in clinical COVID-19 trials. A 28-day follow-up period may be too short for the critically ill.

Immune dysfunction resulting from allogeneic haematopoietic stem cell transplantation (aHSCT) predisposes one to an elevated risk of cytomegalovirus (CMV) infection. Changes in metabolism have been associated with adverse outcomes, and in this study, we explored the associations between metabolic profiles and post-transplantation CMV infection using plasma samples collected 7–33 days after aHSCT. We included 68 aHSCT recipients from Rigshospitalet, Denmark, 50% of whom experienced CMV infection between days 34–100 post-transplantation. First, we investigated whether 12 metabolites selected based on the literature were associated with an increased risk of post-transplantation CMV infection. Second, we conducted an exploratory network-based analysis of the complete metabolic and lipidomic profiles in relation to clinical phenotypes and biological pathways. Lower levels of trimethylamine N-oxide were associated with subsequent CMV infection (multivariable logistic regression: OR = 0.63; 95% CI = [0.41; 0.87]; p = 0.01). Explorative analysis revealed 12 clusters of metabolites or lipids, among which one was predictive of CMV infection, and the others were associated with conditioning regimens, age upon aHSCT, CMV serostatus, and/or sex. Our results provide evidence for an association between the metabolome and CMV infection post-aHSCT that is independent of known risk factors.

Abstract Background Dengue could cause complications with an estimated 10,000 deaths per annum. It mostly affects low- and middle-income countries such as Sri Lanka with limited healthcare resources to handle seasonal outbreaks. A third of dengue patients usually have a critical phase characterized by plasma leakage with increased risk of life-threatening complications. A data-driven approach was required to find early predictors of plasma leakage that are usually available in routine care from a resource limited setting, as means of triaging patients for hospital admission. Methods We utilized a prospective cohort (The Colombo dengue study in Sri Lanka) that recruits patients meeting the clinical case definition of dengue fever. The cohort includes 4,781 instances of clinical signs, symptoms, and in-hospital laboratory tests from N=877 patients (60.3% patients infected by Dengue) recorded in first four days of fever. By excluding incomplete patient instances, the data was randomly split to a development set (N=378) and a test set (N=144). From the development set, five most informative features were identified using the minimum description length (MDL) algorithm. Logistic regression was used to create a prediction model using the development set. Shapley analysis was used to explain the model on the test set extracting the extent by which each predictor contributed to the predictions. Results The MDL algorithm revealed that hemoglobin (HGB), hematocrit (HCT), aspartate aminotransferase (AST), age, and gender to be the most informative predictors of plasma leakage. The logistic regression model predicted plasma leakage with (AUC = 0.76) on the test set (Fig 1). The HGB appeared to contribute the most to the predictions with the higher values associated with higher predicted risk of plasma leakage and vice versa (Fig 2). Figure 2 SHAP decision plot for the logistic regression model on the test set. The features are sorted from top to bottom by their mean absolute SHAP values (higher interpreted as more contributing). Feature values are normalised to [0 1] by the min-max normalisation method and colour-coded (grey points are missing values), outliers were squished to the range using Hampel filter. For gender, male is indicated by red and female by blue. The colour of each line is the same as the value of the feature connected to in downwards direction. Conclusion Our results give support to the predictability of plasma leakage in patients suspected of Dengue fever in their first four days of fever onset. The study also underlines the relevance of the machine learning approach to identify the predictors and the practicality of the prediction model as reflected by the prediction performance to triage patients for hospital admission in resource limited settings. Disclosures All Authors: No reported disclosures.

Background: Recent studies have shown extensive crosstalk between our immune system and gut microbiome (GM). The host immune system plays a vital role in the maintenance of GM homeostasis by 1) establishing a balance between eliminating invading pathogens and promoting the growth of beneficial microbes, 2) producing short-chain fatty acids (SCFA), the main source of nutrition for the colon cells, and 3) modulating the immune system by cytokine production. Mounting evidence shows that the GM of patients with high rates of infection are characterized by an imbalance of bacteria, inducing proinflammatory states and reduced capacity for SCFA synthesis. As chronic lymphocytic leukemia (CLL) is, among others, also characterized by high rate of infectious complications and an altered immune system, it is warranted to explore composition of the CLL microbiome. Aims: We aim to investigate the hypothesis that deviation of the GM from homeostasis, i.e. loss of ‘health promoting’ gut microbes and/or overgrowth of pathogenic bacteria, distinguishes patients with CLL from the background population. Methods: Feces samples of patients with CLL were collected, immediately fixated and frozen within 72 h; total genomic DNA was sequenced. Feces samples of healthy controls were chosen to match the CLL population with respect to age, demographic data, sample collection method, and sequencing platform. Taxonomical profiling was done using an in-house bioinformatics pipeline. Results: A total of 61 CLL patients and 30 healthy individuals were included in the study. We observed reduced GM alpha diversity, and depletion of bacterial members of Lachnospiraceae and Ruminococcaceae families among the CLL patients when compared to healthy individuals. Our data show that members of the Lachnospiraceae family (Anaerostipes hadrus, Coprococcus comes, Blautia spp., Dorea spp.), and 3 members of Ruminococcaeae family (Ruminococcus torques, Ruminococcus bromii, Faecalibacterium prausnitzii) were among the most differentially abundant bacterial species between the microbiomes of healthy individuals and CLL. Their mean proportions were shown to be significantly higher in healthy microbiome samples. As further differentially abundant species we observed Bacteroides sp. and Alistipes finegoldii, which both demonstrated significantly higher mean proportions in CLL microbiomes (Fig 1). Image:Summary/Conclusion: To sum up, the CLL microbiomes in comparison to healthy controls demonstrated lower enrichment of Lachnospiraceae and Ruminococcaceae families, the major SCFAs-producing bacterial taxa reported to have a protective effect against inflammation. This supports the notion that proinflammatory risk factors identified in other cohorts with GM dysbiosis are also present within CLL patients. As CLL represents an antigen driven malignancy with immune dysfunction, we hypothesize that GM dysbiosis could both be implicated in the pathogenesis of CLL, through antigenic drive, and contribute to the distortion of the immune system in CLL. Notably, both immune dysfunction and treatment (e.g. antimicrobials) may influence the CLL microbiome itself and therefore confound cross-sectional clinical studies. We therefore plan to investigate the interaction between microbiome and CLL development in the TCL1 mouse model of CLL. Also, identification of potential mechanistic links between the GM and the microenvironment in CLL should be investigated, e.g. extravesicular vesicles or cytokines released from or impacted by the GM. In addition, modulation of the microbiome in animal models may help to establish causal connections between the GM and CLL development.

Interpretable risk assessment of SARS-CoV-2 positive patients can aid clinicians to implement precision medicine. Here we trained a machine learning model to predict mortality within 12 weeks of a first positive SARS-CoV-2 test. By leveraging data on 33,938 confirmed SARS-CoV-2 cases in eastern Denmark, we considered 2723 variables extracted from electronic health records (EHR) including demographics, diagnoses, medications, laboratory test results and vital parameters. A discrete-time framework for survival modelling enabled us to predict personalized survival curves and explain individual risk factors. Performance on the test set was measured with a weighted concordance index of 0.95 and an area under the curve for precision-recall of 0.71. Age, sex, number of medications, previous hospitalizations and lymphocyte counts were identified as top mortality risk factors. Our explainable survival model developed on EHR data also revealed temporal dynamics of the 22 selected risk factors. Upon further validation, this model may allow direct reporting of personalized survival probabilities in routine care.

Gut microbiota is thought to influence host responses to allogeneic hematopoietic stem cell transplantation (aHSCT). Recent evidence points to this post-transplant for acute graft-versus-host disease (aGvHD). We asked whether any such association might be found pre-transplant and conducted a metagenome-wide association study (MWAS) to explore. Microbial abundance profiles were estimated using ensembles of Kaiju, Kraken2, and DeepMicrobes calls followed by dimensionality reduction. The area under the curve (AUC) was used to evaluate classification of the samples (aGvHD vs. none) using an elastic net to test the relevance of metagenomic data. Clinical data included the underlying disease (leukemia vs. other hematological malignancies), recipient age, and sex. Among 172 aHSCT patients of whom 42 developed aGVHD post transplantation, a total of 181 pre-transplant tool samples were analyzed. The top performing model predicting risk of aGVHD included a reduced species profile (AUC = 0.672). Beta diversity (37% in Jaccard’s Nestedness by mean fold change, p < 0.05) was lower in those developing aGvHD. Ten bacterial species including Prevotella and Eggerthella genera were consistently found to associate with aGvHD in indicator species analysis, as well as relief and impurity-based algorithms. The findings support the hypothesis on potential associations between gut microbiota and aGvHD based on a data-driven approach to MWAS. This highlights the need and relevance of routine stool collection for the discovery of novel biomarkers.

Human Leucocyte Antigen (HLA) class I alleles are the main host genetic factors involved in controlling HIV-1 viral load (VL). Nevertheless, HLA diversity has proven a significant challenge in association studies. We assessed how accounting for binding affinities of HLA class I alleles to HIV-1 peptides facilitate association testing of HLA with HIV-1 VL in a heterogeneous cohort from the Strategic Timing of AntiRetroviral Treatment (START) study. We imputed HLA class I alleles from host genetic data (2,546 HIV+ participants) and sampled immunopeptidomes from 2,079 host-paired viral genomes (targeted amplicon sequencing). We predicted HLA class I binding affinities to HIV-1 and unspecific peptides, grouping alleles into functional clusters through consensus clustering. These functional HLA class I clusters were used to test associations with HIV VL. We identified four clades totalling 30 HLA alleles accounting for 11.4% variability in VL. We highlight HLA-B*57:01 and B*57:03 as functionally similar but yet overrepresented in distinct ethnic groups, showing when combined a protective association with HIV+ VL (log, β −0.25; adj. p-value < 0.05). We further demonstrate only a slight power reduction when using unspecific immunopeptidomes, facilitating the use of the inferred functional HLA groups in other studies. The outlined computational approach provides a robust and efficient way to incorporate HLA function and peptide diversity, aiding clinical association studies in heterogeneous cohorts. To facilitate access to the proposed methods and results we provide an interactive application for exploring data. ![Figure][1] ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by the Danish National Research Foundation (DNRF126) and the National Institute of Allergy and Infectious Diseases, Division of Clinical Research and Division of AIDS (National Institutes of Health grants UM1-AI068641, UM1-AI120197 and U01-AI136780). The START trial was supported by the National Institute of Allergy and Infectious Diseases, National Institutes of Health Clinical Center, National Cancer Institute, National Heart, Lung, and Blood Institute, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Agence Nationale de Recherches sur le SIDA et les Hepatites Virales (France), National Health and Medical Research Council (Australia), National Research Foundation (Denmark), Bundes Ministerium fur Bildung und Forschung (Germany), European AIDS Treatment Network, Medical Research Council (United Kingdom), National Institute for Health Research, National Health Service (United Kingdom), and the University of Minnesota. Antiretroviral drugs were donated to the central drug repository by AbbVie, Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline/ViiV Healthcare, Janssen Scientific Affairs, and Merck. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The International Network for Strategic Initiatives in Global HIV Trials (INSIGHT) gave approval for accessing the data to conduct this work. Written consent for the study and genetic analyses were obtained from the participants and ethical approval was given by site ethics review committees represented in the INSIGHT network International Coordinating Centers: The University of Minnesota -- Minneapolis, Minnesota, USA. Copenhagen HIV Programme (CHIP) -- Copenhagen, Denmark. Medical Research Council (MRC) Clinical Trials Unit -- London, United Kingdom. National Centre in HIV Epidemiology and Clinical Research (NCHECR), University of New South Wales -- Sydney, Australia. The Institute for Clinical Research at the Veterans Affairs Medical Center -- Washington, D.C., USA. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT) [https://persimune-health-informatics.shinyapps.io/PAW2022Zucco_\_HLA\_HIV_INSIGHT/][2] [1]: pending:yes [2]: https://persimune-health-informatics.shinyapps.io/PAW2022Zucco__HLA_HIV_INSIGHT/

Introduction: Identifying genetic factors that influence HIV-pathogenesis is critical for understanding disease pathways. Previous studies have suggested a role for the human gene ten-eleven methylcytosine dioxygenase 2 (TET2) in modulating HIV-pathogenesis. Methods: We assessed whether genetic variation in TET2 was associated with markers of HIV-pathogenesis using both gene level and single nucleotide polymorphism (SNP) level association in 8512 HIV-positive persons across five clinical trial cohorts. Results: Variation at both the gene and SNP-level of TET2 was found to be associated with levels of HIV viral load (HIV-VL) consistently in the two cohorts that recruited antiretroviral-naïve participants. The SNPs occurred in two clusters of high linkage disequilibrium (LD), one associated with high HIV-VL and the other low HIV-VL, and were predominantly found in Black participants. Conclusion: Genetic variation in TET2 was associated with HIV-VL in two large antiretroviral therapy (ART)-naive clinical trial cohorts. The role of TET2 in HIV-pathogenesis warrants further investigation.

Allogeneic hematopoietic stem cell transplantation (aHSCT) is a putative curative treatment for malignant hematologic disorders. During transplantation, the immune system is suppressed/eradicated through a conditioning regimen (non-myeloablative or myeloablative) and replaced with a donor immune system. In our previous study, we showed changes in gut taxonomic profiles and a decrease in bacterial diversity post-transplant. In this study, we expand the cohort with 114 patients and focus on the impact of the conditioning regimens on taxonomic features and the metabolic functions of the gut bacteria. This is, to our knowledge, the first study to examine the metabolic potential of the gut microbiome in this patient group. Adult aHSCT recipients with shotgun sequenced stool samples collected day −30 to +28 relative to aHSCT were included. One sample was selected per patient per period: pre-aHSCT (day −30–0) and post-aHSCT (day 1–28). In total, 254 patients and 365 samples were included. Species richness, alpha diversity, gene richness and metabolic richness were all lower post-aHSCT than pre-aHSCT and the decline was more pronounced for the myeloablative group. The myeloablative group showed a decline in 36 genera and an increase in 15 genera. For the non-myeloablative group, 30 genera decreased and 16 increased with lower fold changes than observed in the myeloablative group. For the myeloablative group, 32 bacterial metabolic functions decreased, and one function increased. For the non-myeloablative group, three functions decreased, and two functions increased. Hence, the changes in taxonomy post-aHSCT caused a profound decline in bacterial metabolic functions especially in the myeloablative group, thus providing new evidence for associations of myeloablative conditioning and gut dysbiosis from a functional perspective.

Abstract Background Several interventional Coronavirus Disease 2019 (COVID-19) studies assess outcomes at day 28, but this follow-up time can be too short, since COVID-19 often cause protracted disease. Further, data on mortality and readmissions after discharge are scarse. Methods Patients aged 18-100 years and hospitalized with COVID-19 in Eastern Denmark between March 18th, 2020 and January 12th, 2021, were followed for 91 days after admission. Patients were stratified in a first and second wave, by admissions before or after June 15th, 2020, app. when remdesivir and dexamethasone were introduced as standard of care. Sustained recovery was defined as the first date, achieving 14 consecutive days after hospital discharge without an event of readmission or death. Cumulative incidences of sustained recovery were estimated in both waves and in subgroups based on the patient’s maximum level of respiratory support in the first 14 days of admission as a proxy for disease severity. Risk factors for poor outcomes were assessed in a multivariable cox proportional hazards model. Results Overall 3,386 patients were included in the study; 1,137 and 2,249 patients were admitted in the first and second wave, respectively (Table 1). The cumulative incidence of sustained recovery at day 91 was higher in the second (0.79, 95% CI: 0.77,0.81) than in the first wave (0.72, 95% CI: 0.70, 0.75) (Fig. 1A). In both waves, those with more severe disease recovered at a slower rate (Fig. 2B). There were no differences in cumulative incidences of readmissions or deaths at day 91 after discharge between the two waves, cumulative incidence (0.20, 95% CI: 0.19,0.21) and (0.11, 95% CI: 0.09,0.12), respectively (Fig 1C, Fig 1D). Male sex, high age, cardiovascular disease, diabetes, chronic pulmonary disease, renal disease, malignancies and neurological disease were associated with lower rates of sustained recovery (Table 2). Conclusion A follow-up period of 28 days in clinical trials for COVID-19 treatments is too short, especially for patients with severe disease. Rates of adverse outcomes after hospital discharge are non-neglible. In-hospital mortality was reduced with improvements in treatment, but post discharge mortality and readmissions rates did not change significantly. Disclosures Carsten Utoft Niemann, PhD MD, Abbvie (Grant/Research Support, Advisor or Review Panel member)Astra Zeneca (Grant/Research Support, Advisor or Review Panel member, teaching)CSL Behring (Consultant)Genmab (Grant/Research Support)Gilead (Grant/Research Support)Janssen (Grant/Research Support, teaching)Novo Nordisk Foundation (Grant/Research Support)Roche (Grant/Research Support)Sunesis (Grant/Research Support)

Objectives: The Strategic Timing of AntiRetroviral Treatment (START) and Strategies for Management of Antiretroviral Therapy (SMART) trials demonstrated that ART can partly reverse clinically defined immune dysfunction induced by HIV replication. As control of HIV replication is influenced by the HLA region, we explored whether HLA alleles independently influence the risk of clinical events in HIV+ individuals. Design: Cohort study. Methods: In START and SMART participants, associations between imputed HLA alleles and AIDS, infection-related cancer, herpes virus-related AIDS events, chronic inflammation-related conditions, and bacterial pneumonia were assessed. Cox regression was used to estimate hazard ratios for the risk of events among allele carriers versus noncarriers. Models were adjusted for sex, age, geography, race, time-updated CD4 + T-cell counts and HIV viral load and stratified by treatment group within trials. HLA class I and II alleles were analyzed separately. The Benjamini--Hochberg procedure was used to limit the false discovery rate to less than 5% (i.e. q value <0.05). Results: Among 4829 participants, there were 132 AIDS events, 136 chronic inflammation-related conditions, 167 bacterial pneumonias, 45 infection-related cancers, and 49 herpes virus-related AIDS events. Several associations with q value less than 0.05 were found: HLA-DQB1∗06:04 and HLA-DRB1∗13:02 with AIDS (adjusted HR [95% CI] 2.63 [1.5–4.6] and 2.25 [1.4–3.7], respectively), HLA-B∗15:17 and HLA-DPB1∗15:01 with bacterial pneumonia (4.93 [2.3–10.7] and 4.33 [2.0–9.3], respectively), and HLA-A∗69:01 with infection-related cancer (15.26 [3.5–66.7]). The carriage frequencies of these alleles were 10% or less. Conclusion: This hypothesis-generating study suggests that certain HLA alleles may influence the risk of immune dysfunction-related events irrespective of viral load and CD4 + T-cell count.