Objective To compare differences in risk factors and 90-day mortality prediction from 2 machine learning (ML) models with a previously published non-ML model and investigate their validity in an external cohort.Materials and methods Prospectively collected data from 2 separate randomized controlled trial (RCT) cohorts from 2020 to 2021, the Therapeutics for Inpatients with COVID-19 (TICO/ACTIV-3) Trial (derivation and internal validation cohort) and the Inpatient Treatment with Anti-Coronavirus Immunoglobulin (ITAC) Trial (external validation cohort) were used. Data were collected from 114 sites in 10 countries (TICO/ACTIV-3) and 63 sites in 11 countries (ITAC). A ML pipeline including 5 classification models, and 1 survival model was used for risk factor identification and clinical outcome prediction. Risk factors were compared between a ML-based classification model, a ML-based survival model and a previously published Cox model. Performance of the ML-based classification model was compared across TICO/ACTIV-3 and ITAC.Results A total of 2625 (TICO/ACTIV-3) and 579 (ITAC) adults hospitalized for COVID-19 were included. Some overlap of risk factors was identified across models. Five were identified in all models, 3 only in ML models, and 4 only in the non-ML model. The ML model showed good predictive performance in TICO/ACTIV-3. Internal validation showed no overfitting. Lower model performance was observed in ITAC (-15.8%), but performance remained above chance level.Discussion Differences in methods for risk factor identification using ML and non-ML complicates the comparison of results derived from each approach, but using multiple approaches may unveil overlooked risk factors.Conclusion Risk factor identification may benefit from integrating both ML and non-ML methods, but external validation is necessary, even in RCTs.

ABSTRACT Background Knowledge of the human genetic contribution to the risk of complications from influenza is limited. This study assessed the association between human single‐nucleotide polymorphisms (SNPs) and disease progression in individuals with influenza. Methods A targeted analysis of 10 SNPs with prior evidence in COVID‐19 and a genome‐wide association study (GWAS) were used to assess associations between SNPs and disease progression in two multinational cohorts with suspected or laboratory‐confirmed influenza: a hospitalized cohort (n = 1634) and a pooled cohort of hospitalized and outpatients (n = 3469). Disease progression was defined as prolonged hospitalization (> 28 days), progression to mechanical ventilation, admittance to intensive care unit, or death (for hospitalized individuals) or progression to hospitalization or death (for outpatients). Results Disease progression was observed in 9.1% of hospitalized patients and 2.2% of outpatients. Age was a significant risk factor for disease progression, with 20% increased odds of disease progression per 10‐year increase in age (OR: 1.20, 95%CI: 1.08–1.33, p < 0.001). Disease progression rates also differed by continent (p < 0.0001). Targeted SNP analyses did not identify significant associations with disease progression; however, the strength of associations was most pronounced in sensitivity analyses for the pooled cohort in individuals < 65 years old. GWAS analyses did not identify significant common SNP associations in either the hospitalized or pooled cohorts, nor in sensitivity analysis of (1) individuals with laboratory‐confirmed influenza and (2) those aged < 65 years. Conclusion In a geographically diverse cohort of individuals with influenza, the genetic links to disease progression only started to become evident in the sensitivity analyses, mainly when looking at younger individuals. The power to detect associations was limited by the rate of disease progression and heterogeneity in phenotypes of the individuals studied, and therefore, additional studies focused on the role of genetics in influenza disease progression are needed.

DAVID is a widely used bioinformatics resource that provides functional annotation and functional enrichment analysis for gene and protein lists derived from high-throughput studies. It integrates a comprehensive gene-centered knowledgebase with a suite of web-accessible analytical tools. Since its initial release in 2003, DAVID developments have been published in 12 papers and cited >80 000 times. Here, we report updates made since the previous NAR Web Server Issue publication in 2022. This update introduces two new tools: DAVID Ortholog for cross-species functional analysis and DAVID Gene Search for identifier-agnostic gene exploration, modernizes the web interface, and implements a new backend architecture that decouples the frontend from the legacy Java processing engine. A new Servlet layer and REST APIs enable asynchronous processing and support integration of a Neo4j graph database for relationship-based queries. Major existing tools have been redesigned with modern, interactive interfaces, and multiformat result export. The pathway viewer has been redesigned with interactive drag-and-zoom navigation, animated user gene highlighting, and publication-quality downloads. Collectively, these updates enhance performance and usability, and the new backend architecture enables independent evolution of frontend and backend components while maintaining continuity with legacy analyses. DAVID remains freely available at https://davidbioinformatics.nih.gov without login.

The emergence of HIV drug resistance is a challenge in controlling the acquired immunodeficiency syndrome (AIDS) pandemic caused by human immunodeficiency virus-1 (HIV-1) infection. Detection of drug resistance variants at minor frequencies can help to formulate successful antiretroviral therapy (ART) regimens for people living with HIV (PLWH) and reduce the emergence of drug resistance. Therefore, a pipeline which can accurately produce consensus nucleotide sequences and identify drug resistance mutations (DRMs) at defined frequency thresholds will be helpful in the treatment of PLWH, analysis of virus evolution, and the control of the pandemic. We have developed a pipeline, HIVGenoPipe, to determine HIV drug resistance variants within the gag-pol region above user-defined frequencies for HIV-1 samples sequenced using Illumina technology. The pipeline has been validated by comparing its results with the results generated by a widely used pipeline, HyDRA, which is limited to the pol region, and with the results generated by Sanger sequencing technology using the same set of 30 samples. The variant frequency used to generate ambiguous consensus sequences in HIVGenoPipe is more accurate than other pipelines because a sample-specific reference, which is generated in real-time with a novel hybrid strategy of de novo and reference-based assembly, is used for the frequency calculation, leading to more accurate drug resistance calls for use by clinicians. In addition, since Nextflow is used as the pipeline platform, HIVGenoPipe inherently has great portability, scalability and reproducibility; and the components can be updated or replaced independently if required. We developed HIVGenoPipe for the detection of HIV-1 drug resistance. It constructs more accurate gag-pol consensus sequences, leading to improved detection of DRMs. HIVGenoPipe is open source and freely available under the MIT license at https://github.com/LHRI-Bioinformatics/HIVGenoPipe . The current release (v1.0.1) is archived and available at https://doi.org/ https://doi.org/10.5281/zenodo.15528502 .

BACKGROUND:Increasingly, persons with HIV in Liberia are receiving antiretroviral therapy containing the integrase strand-transfer inhibitor (InSTI) dolutegravir (DTG), but the prevalence of and factors associated with virologic failure and HIV drug resistance (HIVDR) remain unknown. METHODS:Cross-sectional analysis of 2019-2022 enrolment data from 1276 persons with HIV in the HONOR cohort included sociodemographic information, plasma viral loads (pVL), CD4 counts, and HIVDR testing by next generation sequencing in participants with virologic failure (pVL≥1000 copies/mL). RESULTS:Of the 1201 participants with pVL results, 72% are female and median age is 42 (interquartile range [IQR] 35-50) years. All are on ART (median 6.1 [2.1-11] years): 74% on DTG-based and 23% on non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens. Ninety (7.5%) had virologic failure; 970 (81%) are suppressed (<40 copies/mL). Virologic failure is less prevalent with DTG- versus NNRTI-based regimens (5.3% vs. 14%, adjusted prevalence ratio [aPR]=0.3, 95% confidence interval [CI] 0.2-0.5) and is associated with age <50 years, CD4 count <200 cells/µL, and hemoglobin <11 g/dL. In 70 participants with virologic failure and successful sequencing, HIVDR prevalence is 81% for any ARV, 5.7% for InSTIs, 79% for NNRTIs, and 61% for nucleos(t)ide reverse transcriptase inhibitors (NRTIs). Intermediate-to-high resistance to ≥1 NRTI in current ART is less prevalent with DTG+2NRTIs than NNRTI+2NRTIs regimens (aPR = 0.5, 95%CI 0.3-0.8). CONCLUSIONS:Most participants in the cohort are virologically-suppressed. Among those with virologic failure, HIVDR prevalence is high to NRTIs and NNRTIs, but low to InSTIs. Ongoing evaluation is necessary to determine the durability of DTG-based ART.

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.

Motivation: The Database for Annotation, Visualization, and Integrated Discovery (DAVID) is a web-based bioinformatics system for the functional interpretation of large lists of genes/proteins generated from high-throughput assays. It has been cited in 72 287 papers since its debut in 2003 as of 23 July 2024. The analysis is usually limited to the species of study. However, the knowledge of genes may be incomplete or unavailable for some species. Model organisms have been studied more extensively and analyzing gene lists in the context of these species can offer valuable insights, helping users better understand the genes and biological themes in their species of interest. Results: We developed DAVID Ortholog for the conversion of gene lists between species. We utilized the ortholog data downloaded from Orthologous MAtrix (OMA) and Ensembl Compara as the base for the conversion. The OMA ortholog IDs and Ensembl gene IDs were converted to DAVID gene IDs and the pairing information of these IDs from these two sources was integrated into the DAVID Knowledgebase. DAVID Ortholog can convert the user's source gene list to an ortholog list of a desired species and the downstream DAVID analysis, in the context of that species, can be continued seamlessly, allowing users to further understand the biological meaning of their gene list based on the functional annotation found for the orthologs.

Herpes Simplex Virus type 1 (HSV-1) infects humans and causes a variety of clinical manifestations. Many HSV-1 genomes have been sequenced with high-throughput sequencing technologies and the annotation of these genome sequences heavily relies on the known genes in reference strains. Consequently, the accuracy of reference strain annotation is critical for future research and treatment of HSV-1 infection. In this study, we analyzed RNA-Seq data of HSV-1 from NCBI databases and discovered a novel intron in the overlapping coding sequence (CDS) of US10 and US11, and the 3′ UTR of US12 in strain 17, a commonly used HSV-1 reference strain. To comprehensively understand the shared US10/US11/US12 intron structure, we used US11 as a representative and surveyed all US11 gene sequences from the NCBI nt/nr database. A total of 193 high-quality US11 sequences were obtained, of which 186 sequences have a domain of uninterrupted tandemly repeated RXP (Arg-X-Pro) in the C-terminus half of the protein. In total, 97 of the 186 sequences encode US11 protein with the same length of the mature US11 in strain 17:26 of them have the same structure of US11 and can be spliced as in strain 17; 71 of them have transcripts that are the same as mature US11 mRNA in strain 17. In total, 76 US11 gene sequences have either canonical or known noncanonical intron border sequences and may be spliced like strain 17 and obtain mature US11 CDS with the same length. If not spliced, they will have extra RXP repeats. A tandemly repeated RXP domain was proposed to be essential for US11 to bind with RNA and other host factors. US10 protein sequences from the same strains have also been studied. The results of this study show that even a frequently used reference organism may have errors in widely used databases. This study provides accurate annotation of the US10, US11, and US12 gene structure, which will build a more solid foundation to study expression regulation of the function of these genes.

Reservoirs of HIV maintained in anatomic compartments during antiretroviral therapy prevent HIV eradication. However, mechanisms driving their persistence and interventions to control them remain elusive. Here we report the presence of an inducible HIV reservoir within antigen-specific CD4+T cells in the central nervous system of a 59-year-old male with progressive multifocal leukoencephalopathy immune reconstitution inflammatory syndrome (PML-IRIS). HIV production during PML-IRIS was suppressed by modulating inflammation with corticosteroids; selection of HIV drug resistance caused subsequent breakthrough viremia. Therefore, inflammation can influence the composition, distribution and induction of HIV reservoirs, warranting it as a key consideration for developing effective HIV remission strategies.

Background There is an incompletely understood increased risk for cardiovascular disease (CVD) among people with HIV (PWH). We investigated if a collection of biomarkers were associated with CVD among PWH. Mendelian randomization (MR) was used to identify potentially causal associations. Methods Data from follow-up in 4 large trials among PWH were used to identify 131 incident CVD cases and they were matched to 259 participants without incident CVD (controls). Tests of associations between 460 baseline protein levels and case status were conducted. Results Univariate analysis found CLEC6A, HGF, IL-6, IL-10RB, and IGFBP7 as being associated with case status and a multivariate model identified 3 of these: CLEC6A (odds ratio [OR] = 1.48, P = .037), HGF (OR = 1.83, P = .012), and IL-6 (OR = 1.45, P = .016). MR methods identified 5 significantly associated proteins: AXL, CHI3L1, GAS6, IL-6RA, and SCGB3A2. Conclusions These results implicate inflammatory and fibrotic processes as contributing to CVD. While some of these biomarkers are well established in the general population and in PWH (IL-6 and its receptor), some are novel to PWH (HGF, AXL, and GAS6) and some are novel overall (CLEC6A). Further investigation into the uniqueness of these biomarkers in PWH and the role of these biomarkers as targets among PWH is warranted.

DAVID is a popular bioinformatics resource system including a web server and web service for functional annotation and enrichment analyses of gene lists. It consists of a comprehensive knowledgebase and a set of functional analysis tools. Here, we report all updates made in 2021. The DAVID Gene system was rebuilt to gain coverage of more organisms, which increased the taxonomy coverage from 17 399 to 55 464. All existing annotation types have been updated, if available, based on the new DAVID Gene system. Compared with the last version, the number of gene-term records for most annotation types within the updated Knowledgebase have significantly increased. Moreover, we have incorporated new annotations in the Knowledgebase including small molecule-gene interactions from PubChem, drug-gene interactions from DrugBank, tissue expression information from the Human Protein Atlas, disease information from DisGeNET, and pathways from WikiPathways and PathBank. Eight of ten subgroups split from Uniprot Keyword annotation were assigned to specific types. Finally, we added a species parameter for uploading a list of gene symbols to minimize the ambiguity between species, which increases the efficiency of the list upload and eliminates confusion for users. These current updates have significantly expanded the Knowledgebase and enhanced the discovery power of DAVID.

Background: Levels of plasma SARS-CoV-2 nucleocapsid (N) antigen may be an important biomarker in patients with COVID-19 and enhance our understanding of the pathogenesis of COVID-19. Objective: To evaluate whether levels of plasma antigen can predict short-term clinical outcomes and identify clinical and viral factors associated with plasma antigen levels in hospitalized patients with SARS-CoV-2. Design: Cross-sectional study of baseline plasma antigen level from 2540 participants enrolled in the TICO (Therapeutics for Inpatients With COVID-19) platform trial from August 2020 to November 2021, with additional data on day 5 outcome and time to discharge. Setting: 114 centers in 10 countries. Participants: Adults hospitalized for acute SARS-CoV-2 infection with 12 days or less of symptoms. Measurements: Baseline plasma viral N antigen level was measured at a central laboratory. Delta variant status was determined from baseline nasal swabs using reverse transcriptase polymerase chain reaction. Associations between baseline patient characteristics and viral factors and baseline plasma antigen levels were assessed using both unadjusted and multivariable modeling. Association between elevated baseline antigen level of 1000 ng/L or greater and outcomes, including worsening of ordinal pulmonary scale at day 5 and time to hospital discharge, were evaluated using logistic regression and Fine-Gray regression models, respectively. Results: Plasma antigen was below the level of quantification in 5% of participants at enrollment, and 1000 ng/L or greater in 57%. Baseline pulmonary severity of illness was strongly associated with plasma antigen level, with mean plasma antigen level 3.10-fold higher among those requiring noninvasive ventilation or high-flow nasal cannula compared with room air (95% CI, 2.22 to 4.34). Plasma antigen level was higher in those who lacked antispike antibodies (6.42 fold; CI, 5.37 to 7.66) and in those with the Delta variant (1.73 fold; CI, 1.41 to 2.13). Additional factors associated with higher baseline antigen level included male sex, shorter time since hospital admission, decreased days of remdesivir, and renal impairment. In contrast, race, ethnicity, body mass index, and immunocompromising conditions were not associated with plasma antigen levels. Plasma antigen level of 1000 ng/L or greater was associated with a markedly higher odds of worsened pulmonary status at day 5 (odds ratio, 5.06 [CI, 3.41 to 7.50]) and longer time to hospital discharge (median, 7 vs. 4 days; subhazard ratio, 0.51 [CI, 0.45 to 0.57]), with subhazard ratios similar across all levels of baseline pulmonary severity. Limitations: Plasma samples were drawn at enrollment, not hospital presentation. No point-of-care test to measure plasma antigen is currently available. Conclusion: Elevated plasma antigen is highly associated with both severity of pulmonary illness and clinically important patient outcomes. Multiple clinical and viral factors are associated with plasma antigen level at presentation. These data support a potential role of ongoing viral replication in the pathogenesis of SARS-CoV-2 in hospitalized patients.

Herpes simplex virus type 2 (HSV-2) is a common causative agent of genital tract infections. Moreover, HSV-2 and HIV infection can mutually increase the risk of acquiring another virus infection. Due to the high GC content and highly repetitive regions in HSV-2 genomes, only the genomes of four strains have been completely sequenced (HG52, 333, SD90e, and MS). Strain G is commonly used for HSV-2 research, but only a partial genome sequence has been assembled with Illumina sequencing reads. In the current study, we de novo assembled and annotated the complete genome of strain G using PacBio long sequencing reads, which can span the repetitive regions, analyzed the 'α' sequence, which plays key roles in HSV-2 genome circulation, replication, cleavage, and packaging of progeny viral DNA, identified the packaging signals homologous to HSV-1 within the 'α' sequence, and determined both termini of the linear genome and cleavage site for the process of concatemeric HSV-2 DNA produced via rolling-circle replication. In addition, using Oxford Nanopore Technology sequencing reads, we visualized four HSV-2 genome isomers at the nucleotide level for the first time. Furthermore, the coding sequences of HSV-2 strain G have been compared with those of HG52, 333, and MS. Moreover, phylogenetic analysis of strain G and other diverse HSV-2 strains has been conducted to determine their evolutionary relationship. The results will aid clinical research and treatment development of HSV-2.

Motivation: The existence of quasispecies in the viral population causes difficulties for disease prevention and treatment. High-throughput sequencing provides opportunity to determine rare quasispecies and long sequencing reads covering full genomes reduce quasispecies determination to a clustering problem. The challenge is high similarity of quasispecies and high error rate of long sequencing reads. Results: We developed QuasiSeq using a novel signature-based self-tuning clustering method, SigClust, to profile viral mixtures with high accuracy and sensitivity. QuasiSeq can correctly identify quasispecies even using low-quality sequencing reads (accuracy <80%) and produce quasispecies sequences with high accuracy (>= 99.55%). Using high-quality circular consensus sequencing reads, QuasiSeq can produce quasispecies sequences with 100% accuracy. QuasiSeq has higher sensitivity and specificity than similar published software. Moreover, the requirement of the computational resource can be controlled by the size of the signature, which makes it possible to handle big sequencing data for rare quasispecies discovery. Furthermore, parallel computation is implemented to process the clusters and further reduce the runtime. Finally, we developed a web interface for the QuasiSeq workflow with simple parameter settings based on the quality of sequencing data, making it easy to use for users without advanced data science skills.

Interleukin-27 (IL-27) is a pleiotropic cytokine that influences the innate and adaptive immune systems. It inhibits viral infection and regulates the expression of microRNAs (miRNAs). We recently reported that macrophages differentiated from human primary monocytes in the presence of IL-27 and human AB serum resisted human immunodeficiency virus (HIV) infection and showed significant autophagy induction. In the current study, the miRNA profiles in these cells were investigated, especially focusing on the identification of novel miRNAs regulated by IL-27-treatment. The miRNA sequencing analysis detected 38 novel miRNAs. Real-time reverse transcription polymerase chain reaction (RT-PCR) analysis confirmed that IL-27 differentially regulated the expression of 16 of the 38 miRNAs. Overexpression of the synthesized miRNA mimics by transfection revealed that miRAB40 had potent HIV-inhibiting and autophagy-inducing properties. B18R, an interferon (IFN)-neutralization protein, partially suppressed both activities, indicating that the two functions were induced via IFN-dependent and -independent pathways. Although the target mRNA(s) of miRAB40 involving in the induction of both functions was unable to identify in this study, the discovery of miRAB40, a potential HIV-inhibiting and autophagy inducing miRNA, may provide novel insights into the miRNA (small none-coding RNA)-mediated regulation of HIV inhibition and autophagy induction as an innate immune response.

OBJECTIVES:Interleukin-27 (IL-27) is known as an anti-HIV cytokine. We have recently demonstrated that IL-27-pretreatment promotes phytohemagglutinin-stimulated CD4(+) T cells into HIV-1-resistant cells by inhibiting an uncoating step.PURPOSE:To further characterize the function of the HIV resistant T cells, we investigated profiles of microRNA in the cells using microRNA sequencing (miRNA-seq) and assessed anti-HIV effect of the microRNAs.METHODS:Phytohemagglutinin-stimulated CD4(+) T cells were treated with or without IL-27 for 3 days. MicroRNA profiles were analyzed using miRNA-seq. To assess anti-HIV effect, T cells or macrophages were transfected with synthesized microRNA mimics and then infected with HIVNL4.3 or HIVAD8. Anti-HIV effect was monitored by a p24 antigen enzyme-linked immunosorbent assay kit. interferon (IFN)-α, IFN-β, or IFN-λ production was quantified using each subtype-specific enzyme-linked immunosorbent assay kit.RESULTS:A comparative analysis of microRNA profiles indicated that expression of known miRNAs was not significantly changed in IL-27-treated cells compared with untreated T cells; however, a total of 15 novel microRNAs (miRTC1 ∼ miRTC15) were identified. Anti-HIV assay using overexpression of each novel microRNA revealed that 10 nM miRTC14 (GenBank accession number: MF281439) remarkably suppressed HIV infection by (99.3 ± 0.27%, n = 9) in macrophages but not in T cells. The inhibition was associated through induction of >1000 pg/mL of IFN-αs and IFN-λ1.CONCLUSION:We discovered a total of 15 novel microRNAs in T cells and characterized that miRTC14, one of the novel microRNAs, was a potent IFN-inducing anti-HIV miRNA, implicating that regulation of the expression of miRTC14 may be a potent therapeutic tool for not only HIV but also other virus infection.

We have recently reported that a recombinant HIV-1NL4.3 containing Met-to-Ile change at codon 50 of integrase (IN) (IN:M50I) exhibits suppression of the virus release below 0.5% of WT HIV, and the released viral particles are replication-incompetent due to defects in Gag/GagPol processing by inhibition of the initiation of autoprocessing of GagPol polyproteins in the virions and leads to replication-incompetent viruses. The coexisting Ser-to-Asn change at codon 17 of IN or Asn-to-Ser mutation at codon 79 of RNaseH (RH) compensated the defective IN:M50I phenotype, suggesting that both IN and RH regulate an HIV infectability. In the current study, to elucidate a distribution of the three mutations during anti-retroviral therapy among patients, we performed a population analysis using 529 plasma virus RNA sequences obtained through the MiSeq. The result demonstrated that 14 plasma HIVs contained IN:M50I without the compensatory mutations. Comparing the sequences of the 14 viruses with that of the defective virus illustrated that only Val-to-Ile change at codon 151 of IN (IN:V151I) existed in the recombinant virus. This IN:V151I is known as a polymorphic mutation and was derived from HIVNL4.3 backbone. A back-mutation at 151 from Ile-to-Val in the defective virus recovered HIV replication capability, and Western Blotting assay displayed that the back-mutation restored Gag/GagPol processing in viral particles. These results demonstrate that a combination of IN:M50I and IN:V151I mutations, but not IN:M50I alone, produces a defective virus.

Objectives: Elevated levels of interleukin-6 (IL-6), D-dimer, and C-reactive protein (hsCRP) are associated with increased incidence of comorbid disease and mortality among people living with HIV (PLWH). Prior studies suggest a genetic basis for these biomarker elevations in the general population. The study objectives are to identify the genetic basis for these biomarkers among PLWH. Methods: Baseline levels of hsCRP, D-dimer, and IL-6, and single nucleotide polymorphisms (SNPs) were determined for 7768 participants in three HIV treatment trials. Single variant analysis was performed for each biomarker on samples from each of three ethnic groups [African (AFR), Admixed American (AMR), European (EUR)] within each trial including covariates relevant to biomarker levels. For each ethnic group, the results were pooled across trials, then further pooled across ethnicities. Results: The transethnic analysis identified three, two, and one known loci associated with hsCRP, D-dimer, and IL-6 levels, respectively, and two novel loci, FGB and GCNT1, associated with D-dimer levels. Lead SNPs exhibited similar effects across ethnicities. Additionally, three novel, ethnic-specific loci were identified: CATSPERG associated with D-dimer in AFR and PROX1-AS1 and TRAPPC9 associated with IL-6 in AFR and AMR, respectively. Conclusion: Eleven loci associated with three biomarker levels were identified in PLWH from the three studies including six loci known in the general population and five novel loci associated with D-dimer and IL-6 levels. These findings support the hypothesis that host genetics may partially contribute to chronic inflammation in PLWH and help to identify potential targets for intervention of serious non-AIDS complications.

The authors wish to make the following corrections to this paper [...]