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Summary: Post-COVID-19 conditions (long COVID) has impacted many individuals, yet risk factors for this condition are poorly understood. This retrospective analysis of 88,943 COVID-19 patients at a multi-state US health system compares phenotypes, laboratory tests, medication orders, and outcomes for 1,086 long-COVID patients and their matched controls. We found that history of chronic pulmonary disease (CPD) (odds ratio: 1.9, 95% CI: [1.5, 2.6]), migraine (OR: 2.2, [1.6, 3.1]), and fibromyalgia (OR: 2.3, [1.3, 3.8]) were more common for long-COVID patients. During the acute infection phase long COVID patients exhibited high triglycerides, low HDL cholesterol, and a high neutrophil-lymphocyte ratio; and were more likely hospitalized (5% vs. 1%). Our findings suggest severity of acute infection and history of CPD, migraine, chronic fatigue syndrome (CFS), or fibromyalgia as risk factors for long COVID. These results suggest that suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

Abstract Introduction Sotrovimab, a recombinant human monoclonal antibody (mAb) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had US Food and Drug Administration Emergency Use Authorization for the treatment of high-risk outpatients with mild-to-moderate coronavirus disease 2019 (COVID-19) from 26 May 2021 to 5 April 2022. Real-world clinical effectiveness of sotrovimab in reducing the risk of 30-day all-cause hospitalization and/or mortality was evaluated for the period when the prevalence of circulating SARS-CoV-2 variants changed between Delta and Omicron in the USA. Methods A retrospective analysis was conducted of de-identified patients diagnosed with COVID-19 between 1 September 2021 to 30 April 2022 in the FAIR Health National Private Insurance Claims database. Patients meeting high-risk criteria were divided into two cohorts: sotrovimab and not treated with a mAb (“no mAb”). All-cause hospitalizations and facility-reported mortality ≤ 30 days of diagnosis (“30-day hospitalization or mortality”) were identified. Multivariable and propensity score-matched Poisson and logistic regressions were conducted to estimate the adjusted relative risk (RR) and odds of 30-day hospitalization or mortality in each cohort. Results Compared with the no mAb cohort (n = 1,514,868), the sotrovimab cohort (n = 15,633) was older and had a higher proportion of patients with high-risk conditions. In the no mAb cohort, 84,307 (5.57%) patients were hospitalized and 8167 (0.54%) deaths were identified, while in the sotrovimab cohort, 418 (2.67%) patients were hospitalized and 13 (0.08%) deaths were identified. After adjusting for potential confounders, the sotrovimab cohort had a 55% lower risk of 30-day hospitalization or mortality (RR 0.45, 95% CI 0.41–0.49) and an 85% lower risk of 30-day mortality (RR 0.15, 95% CI 0.08–0.29). Monthly, from September 2021 to April 2022, the RR reduction for 30-day hospitalization or mortality in the sotrovimab cohort was maintained, ranging from 46% to 71% compared with the no mAb cohort; the RR estimate in April 2022 was uncertain, with wide confidence intervals due to the small sample size. Conclusion Sotrovimab was associated with reduced risk of 30-day all-cause hospitalization and mortality versus no mAb treatment. Clinical effectiveness persisted during Delta and early Omicron variant waves and among all high-risk subgroups assessed.

Summary: Humoral immunity is sensitive to evasion by SARS-CoV-2 mutants, but CD8 T cells seem to be more resistant to mutational inactivation. By a systematic analysis of 30 spike variant peptides containing the most relevant VOC and VOI mutations that have accumulated overtime, we show that in vaccinated and convalescent subjects, mutated epitopes can have not only a neutral or inhibitory effect on CD8 T cell recognition but can also enhance or generate de novo CD8 T cell responses. The emergence of these mutated T cell function enhancing epitopes likely reflects an epiphenomenon of SARS-CoV-2 evolution driven by antibody evasion and increased virus transmissibility. In a subset of individuals with weak and narrowly focused CD8 T cell responses selection of these heteroclitic-like epitopes may bear clinical relevance by improving antiviral protection. The functional enhancing effect of these peptides is also worth of consideration for the future development of new generation, more potent COVID-19 vaccines.

Abstract Introduction: With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist. Methods: HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions? Results: This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected. Conclusion: This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic.

Summary: Memory B cells (MBCs) generate rapid antibody responses upon secondary encounter with a pathogen. Here, we investigated the kinetics, avidity, and cross-reactivity of serum antibodies and MBCs in 155 SARS-CoV-2 infected and vaccinated individuals over a 16-month time frame. SARS-CoV-2-specific MBCs and serum antibodies reached steady-state titers with comparable kinetics in infected and vaccinated individuals. Whereas MBCs of infected individuals targeted both prefusion and postfusion Spike (S), most vaccine-elicited MBCs were specific for prefusion S, consistent with the use of prefusion-stabilized S in mRNA vaccines. Furthermore, a large fraction of MBCs recognizing postfusion S cross-reacted with human betacoronaviruses. The avidity of MBC-derived and serum antibodies increased over time resulting in enhanced resilience to viral escape by SARS-CoV-2 variants, including Omicron BA.1 and BA.2 sublineages, albeit only partially for BA.4 and BA.5 sublineages. Overall, the maturation of high-affinity and broadly reactive MBCs provides the basis for effective recall responses to future SARS-CoV-2 variants.

Rabies virus (RABV) infection of unvaccinated individuals can be treated with post exposure prophylaxis. Here, Hellert et al. analyze the structure of a broadly neutralizing human antibody in complex with its target domain in the RABV glycoprotein and demonstrate that it blocks the acid-induced conformational change required for membrane fusion.

Whole genome sequencing (WGS) holds promise to solve a subset of Mendelian disease cases for which exome sequencing did not provide a genetic diagnosis. Here, Wells et al. report a supervised machine learning model trained on functional, mutational and structural features for rank-scoring and interpreting variants in non-coding regions from WGS.

Summary: Genome-wide association studies (GWASs) are instrumental in identifying loci harboring common single-nucleotide variants (SNVs) that affect human traits and diseases. GWAS hits emerge in clusters, but the focus is often on the most significant hit in each trait- or disease-associated locus. The remaining hits represent SNVs in linkage disequilibrium (LD) and are considered redundant and thus frequently marginally reported or exploited. Here, we interrogate the value of integrating the full set of GWAS hits in a locus repeatedly associated with cardiac conduction traits and arrhythmia, SCN5A-SCN10A. Our analysis reveals 5 common 7-SNV haplotypes (Hap1–5) with 2 combinations associated with life-threatening arrhythmia—Brugada syndrome (the risk Hap1/1 and protective Hap2/3 genotypes). Hap1 and Hap2 share 3 SNVs; thus, this analysis suggests that assuming redundancy among clustered GWAS hits can lead to confounding disease-risk associations and supports the need to deconstruct GWAS data in the context of haplotype composition.

Abstract The identification of individuals with null alleles enables studying how the loss of gene function affects infection. We previously described a non‐functional variant in SIGLEC1, which encodes the myeloid‐cell receptor Siglec‐1/CD169 implicated in HIV‐1 cell‐to‐cell transmission. Here we report a significant association between the SIGLEC1 null variant and extrapulmonary dissemination of Mycobacterium tuberculosis (Mtb) in two clinical cohorts comprising 6,256 individuals. Local spread of bacteria within the lung is apparent in Mtb‐infected Siglec‐1 knockout mice which, despite having similar bacterial load, developed more extensive lesions compared to wild type mice. We find that Siglec‐1 is necessary to induce antigen presentation through extracellular vesicle uptake. We postulate that lack of Siglec‐1 delays the onset of protective immunity against Mtb by limiting antigen exchange via extracellular vesicles, allowing for an early local spread of mycobacteria that increases the risk for extrapulmonary dissemination.

Background: Acetaminophen (paracetamol) is one of the most common medications used for management of pain in the world. There is lack of consensus about the mechanism of action, and concern about the possibility of adverse effects on reproductive health. Methods: We first established the metabolome profile that characterizes use of acetaminophen, and we subsequently trained and tested a model that identified metabolomic differences across samples from 455 individuals with and without acetaminophen use. We validated the findings in a European ancestry adult twin cohort of 1880 individuals (TwinsUK), and in a study of 1235 individuals of African American and Hispanic ancestry. We used genomics to elucidate the mechanisms targeted by acetaminophen. Findings: We identified a distinctive pattern of depletion of sulfated sex hormones with use of acetaminophen across all populations. We used a Mendelian randomization approach to characterize the role of Sulfotransferase Family 2A Member 1 (SULT2A1) as the site of the interaction. Although CYP3A7-CYP3A51P variants also modified levels of some sulfated sex hormones, only acetaminophen use phenocopied the effect of genetic variants of SULT2A1. Overall, acetaminophen use, age, gender and SULT2A1 and CYP3A7-CYP3A51P genetic variants are key determinants of variation in levels of sulfated sex hormones in blood. The effect of taking acetaminophen on sulfated sex hormones was roughly equivalent to the effect of 35 years of aging. Interpretation: These findings raise concerns of the impact of acetaminophen use on hormonal homeostasis. In addition, it modifies views on the mechanism of action of acetaminophen in pain management as sulfated sex hormones can function as neurosteroids and modify nociceptive thresholds.

Abstract Fine population structure can be examined through the clustering of individuals into subpopulations. The clustering of individuals in large sequence datasets into subpopulations makes the calculation of subpopulation specific allele frequency possible, which may shed light on selection of candidate variants for rare diseases. However, as the magnitude of the data increases, computational burden becomes a challenge in fine population structure analysis. To address this issue, we propose fine population structure analysis (FIPSA), which is an individual-based non-parametric method for dissecting fine population structure. FIPSA maximizes the likelihood ratio of the contingency table of the allele counts multiplied by the group. We demonstrated that its speed and accuracy were superior to existing non-parametric methods when the simulated sample size was up to 5,000 individuals. When applied to real data, the method showed high resolution on the Human Genome Diversity Project (HGDP) East Asian dataset. FIPSA was independently validated on 11,257 human genomes. The group assignment given by FIPSA was 99.1% similar to those assigned based on supervised learning. Thus, FIPSA provides high resolution and is compatible with a real dataset of more than ten thousand individuals.

ABSTRACT The latent HIV reservoir is generated following HIV infection of activated effector CD4 T cells, which then transition to a memory phenotype. Here, we describe an ex vivo method, called QUECEL (quiescent effector cell latency), that mimics this process efficiently and allows production of large numbers of latently infected CD4+ T cells. Naïve CD4+ T cells were polarized into the four major T cell subsets (Th1, Th2, Th17, and Treg) and subsequently infected with a single-round reporter virus which expressed GFP/CD8a. The infected cells were purified and coerced into quiescence using a defined cocktail of cytokines, including tumor growth factor beta, interleukin-10 (IL-10), and IL-8, producing a homogeneous population of latently infected cells. Flow cytometry and transcriptome sequencing (RNA-Seq) demonstrated that the cells maintained the correct polarization phenotypes and had withdrawn from the cell cycle. Key pathways and gene sets enriched during transition from quiescence to reactivation include E2F targets, G2M checkpoint, estrogen response late gene expression, and c-myc targets. Reactivation of HIV by latency-reversing agents (LRAs) closely mimics RNA induction profiles seen in cells from well-suppressed HIV patient samples using the envelope detection of in vitro transcription sequencing (EDITS) assay. Since homogeneous populations of latently infected cells can be recovered, the QUECEL model has an excellent signal-to-noise ratio and has been extremely consistent and reproducible in numerous experiments performed during the last 4 years. The ease, efficiency, and accuracy of the mimicking of physiological conditions make the QUECEL model a robust and reproducible tool to study the molecular mechanisms underlying HIV latency. IMPORTANCE Current primary cell models for HIV latency correlate poorly with the reactivation behavior of patient cells. We have developed a new model, called QUECEL, which generates a large and homogenous population of latently infected CD4+ memory cells. By purifying HIV-infected cells and inducing cell quiescence with a defined cocktail of cytokines, we have eliminated the largest problems with previous primary cell models of HIV latency: variable infection levels, ill-defined polarization states, and inefficient shutdown of cellular transcription. Latency reversal in the QUECEL model by a wide range of agents correlates strongly with RNA induction in patient samples. This scalable and highly reproducible model of HIV latency will permit detailed analysis of cellular mechanisms controlling HIV latency and reactivation.

Abstract The outsourcing of genomic data into public cloud computing settings raises concerns over privacy and security. Significant advancements in secure computation methods have emerged over the past several years, but such techniques need to be rigorously evaluated for their ability to support the analysis of human genomic data in an efficient and cost-effective manner. With respect to public cloud environments, there are concerns about the inadvertent exposure of human genomic data to unauthorized users. In analyses involving multiple institutions, there is additional concern about data being used beyond agreed research scope and being prcoessed in untrused computational environments, which may not satisfy institutional policies. To systematically investigate these issues, the NIH-funded National Center for Biomedical Computing iDASH (integrating Data for Analysis, ‘anonymization’ and SHaring) hosted the second Critical Assessment of Data Privacy and Protection competition to assess the capacity of cryptographic technologies for protecting computation over human genomes in the cloud and promoting cross-institutional collaboration. Data scientists were challenged to design and engineer practical algorithms for secure outsourcing of genome computation tasks in working software, whereby analyses are performed only on encrypted data. They were also challenged to develop approaches to enable secure collaboration on data from genomic studies generated by multiple organizations (e.g., medical centers) to jointly compute aggregate statistics without sharing individual-level records. The results of the competition indicated that secure computation techniques can enable comparative analysis of human genomes, but greater efficiency (in terms of compute time and memory utilization) are needed before they are sufficiently practical for real world environments.

Binding of virus, HIV-1, to cellular protein Siglec-1 is important for infection of immune cells. Here the authors show that a natural mutation leading to production of truncated Siglec-1 reduces HIV binding and infectivity transfer in vitro, but does not substantially affect infection or AIDS outcome in patients.

Ease of worldwide travel provides increased opportunities for organisms not only to colonize new environments but also to encounter related but diverged populations. Such events of reconnection and secondary contact of previously isolated populations are widely observed at different time scales. For example, during the quaternary glaciation, sea water level fluctuations caused temporal isolation of populations, often to be followed by secondary contact. At shorter time scales, population isolation and reconnection of viruses are commonly observed, and such events are often associated with epidemics and pandemics. Here, using coalescent theory and simulations, we describe the temporal impact of population reconnection after isolation on nucleotide differences and the site frequency spectrum, as well as common summary statistics of DNA variation. We identify robust genomic signatures of population reconnection after isolation. We utilize our development to infer the recent evolutionary history of human immunodeficiency virus 1 (HIV-1) in Asia and South America, successfully retrieving the successive HIV subtype colonization events in these regions. Our analysis reveals that divergent HIV-1 subtype populations are currently admixing in these regions, suggesting that HIV-1 may be undergoing a process of homogenization, contrary to popular belief.

Drug development (target identification, advancing drug leads to candidates for preclinical and clinical studies) can be facilitated by genetic and genomic knowledge. Here, we review the contribution of population genomics to target identification, the value of bulk and single cell gene expression analysis for understanding the biological relevance of a drug target, and genome-wide CRISPR editing for the prioritization of drug targets. In genomics, we discuss the different scope of genome-wide association studies using genotyping arrays, versus exome and whole genome sequencing. In transcriptomics, we discuss the information from drug perturbation and the selection of biomarkers. For CRISPR screens, we discuss target discovery, mechanism of action and the concept of gene to drug mapping. Harnessing genetic support increases the probability of drug developability and approval.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not 'phase' the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available 'Genome-In-A-Bottle' (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density.

Myeloid cells initiate immune responses and are crucial to control infections. In the case of retroviruses, however, myeloid cells also promote pathogenesis by enabling viral dissemination; a process extensively studied in vitro using human immunodeficiency virus type 1 (HIV-1). This viral hijacking mechanism does not rely on productive myeloid cell infection but requires HIV-1 capture via Siglec-1/CD169, a receptor expressed on myeloid cells that facilitates the infection of bystander target cells. Murine retroviruses are also recognized by Siglec-1, and this interaction is required for robust retroviral infection in vivo. Yet, the relative contribution of Siglec-1-mediated viral dissemination to HIV-1 disease progression remains unclear. The identification of human null individuals lacking working copies of a particular gene enables studying how this loss affects disease progression. Moreover, it can reveal novel antiviral targets whose blockade might be therapeutically effective and safe, since finding null individuals in natura uncovers dispensable functions. We previously described a loss-of-function variant in SIGLEC-1. Analysis of a large cohort of HIV-1-infected individuals identified homozygous and heterozygous subjects, whose cells were functionally null or partially defective for Siglec-1 activity in HIV-1 capture and transmission ex vivo. Nonetheless, analysis of the effect of Siglec-1 truncation on progression to AIDS was not conclusive due to the limited cohort size, the lack of complete clinical records, and the restriction to study only off-therapy periods. Here, we review how the study of loss-of-function variants might serve to illuminate the role of myeloid cells in viral pathogenesis in vivo and the challenges ahead.

Background: Efavirenz (EFV) based antiretroviral therapy is expanding worldwide. However discontinuation of EFV containing regimens is common in some patients, particularly black patients, due most often to neuropsychiatric side effects. These adverse drug effects often result in premature drug discontinuation, as well as considerable morbidity. Methods: We genotyped CYP2A6, CYP2B6 and CYP3A4, which encode enzymes principally involved in EFV metabolism, from patients enrolled in the multinational SMART, FIRST and ESPRIT studies, for whom outcome data of treatment adherence was available. Patients with loss or decrease of function single nucleotide polymorphisms (SNPs) in the above genes were assigned a risk score based upon the number of SNPs present weighted relative to whether CYP2B6 (main metabolism pathway) and/or CYP2A6 and CYP3A4 (accessory pathways) were involved. Cox regression models were used to study the association between high genetic risk and time from initiation to EFV discontinuation. Failure was defined as discontinuation of an antiretroviral regimen other than for virologic failure or protocol determined discontinuation. Findings: Patients with highest pharmacogenetic risk, as defined by cumulative SNPs in CYP2A6, CYP2B6 and CYP3A4, have an increased risk of discontinuation of EFV containing therapy compared to patients with lower genetic risk scores (adjusted HR 1.9, 95% CI 1.2, 3.1, P = 0.009). High genetic risk score was not associated with an increased risk of discontinuing atazanavir or nevirapine. High genetic risk was present more often in blacks compared to non-blacks (Adjusted OR 4.5, 95% CI: 1.9,10.5), and treatment discontinuation was also increased in blacks overall (Adjusted HR 1.4, 95% CI 1.0, 1.9). However, high genetic risk was more associated with treatment discontinuation than race alone for both blacks (Adjusted OR 1.9, 95% CI 0.8, 4.8) and non-blacks (Adjusted OR 5.3, 95% CI 1.5, 18.0). Interpretation: Premature discontinuation of ART delays the time to effective long term viral suppression, and is associated with significant morbidity. Pharmacogenetic testing may predict those with a high risk of EFV discontinuation, and therefore should be considered in patients in whom initiation of EFV based ART is being considered. Funding: Funded by NIH.

CXCL12-CXCR4 signaling controls multiple physiological processes and its dysregulation is associated with cancers and inflammatory diseases. To discover as-yet-unknown endogenous ligands of CXCR4, we screened a blood-derived peptide library for inhibitors of CXCR4-tropic HIV-1 strains. This approach identified a 16 amino acid fragment of serum albumin as an effective and highly specific CXCR4 antagonist. The endogenous peptide, termed EPI-X4, is evolutionarily conserved and generated from the highly abundant albumin precursor by pH-regulated proteases. EPI-X4 forms an unusual lasso-like structure and antagonizes CXCL12-induced tumor cell migration, mobilizes stem cells, and suppresses inflammatory responses in mice. Furthermore, the peptide is abundant in the urine of patients with inflammatory kidney diseases and may serve as a biomarker. Our results identify EPI-X4 as a key regulator of CXCR4 signaling and introduce proteolysis of an abundant precursor protein as an alternative concept for chemokine receptor regulation.

Cellular permissiveness to HIV infection is highly heterogeneous across individuals. Heterogeneity is also found across CD4+ T cells from the same individual, where only a fraction of cells gets infected. To explore the basis of permissiveness, we performed single-cell RNA-seq analysis of non-infected CD4+ T cells from high and low permissive individuals. Transcriptional heterogeneity translated in a continuum of cell states, driven by T-cell receptor-mediated cell activation and was strongly linked to permissiveness. Proteins expressed at the cell surface and displaying the highest correlation with T cell activation were tested as biomarkers of cellular permissiveness to HIV. FACS sorting using antibodies against several biomarkers of permissiveness led to an increase of HIV cellular infection rates. Top candidate biomarkers included CD25, a canonical activation marker. The combination of CD25 high expression with other candidate biomarkers led to the identification of CD298, CD63 and CD317 as the best biomarkers for permissiveness. CD25highCD298highCD63highCD317high cell population showed an enrichment of HIV-infection of up to 28 fold as compared to the unsorted cell population. The purified hyper-permissive cell subpopulation was characterized by a downregulation of interferon-induced genes and several known restriction factors. Single-cell RNA-seq analysis coupled with functional characterization of cell biomarkers provides signatures of the "HIV-permissive cell".

The characterization of the blood virome is important for the safety of blood-derived transfusion products, and for the identification of emerging pathogens. We explored non-human sequence data from whole-genome sequencing of blood from 8,240 individuals, none of whom were ascertained for any infectious disease. Viral sequences were extracted from the pool of sequence reads that did not map to the human reference genome. Analyses sifted through close to 1 Petabyte of sequence data and performed 0.5 trillion similarity searches. With a lower bound for identification of 2 viral genomes/100,000 cells, we mapped sequences to 94 different viruses, including sequences from 19 human DNA viruses, proviruses and RNA viruses (herpesviruses, anelloviruses, papillomaviruses, three polyomaviruses, adenovirus, HIV, HTLV, hepatitis B, hepatitis C, parvovirus B19, and influenza virus) in 42% of the study participants. Of possible relevance to transfusion medicine, we identified Merkel cell polyomavirus in 49 individuals, papillomavirus in blood of 13 individuals, parvovirus B19 in 6 individuals, and the presence of herpesvirus 8 in 3 individuals. The presence of DNA sequences from two RNA viruses was unexpected: Hepatitis C virus is revealing of an integration event, while the influenza virus sequence resulted from immunization with a DNA vaccine. Age, sex and ancestry contributed significantly to the prevalence of infection. The remaining 75 viruses mostly reflect extensive contamination of commercial reagents and from the environment. These technical problems represent a major challenge for the identification of novel human pathogens. Increasing availability of human whole-genome sequences will contribute substantial amounts of data on the composition of the normal and pathogenic human blood virome. Distinguishing contaminants from real human viruses is challenging.

We evaluated the fraction of variation in HIV-1 set point viral load attributable to viral or human genetic factors by using joint host/pathogen genetic data from 541 HIV infected individuals. We show that viral genetic diversity explains 29% of the variation in viral load while host factors explain 8.4%. Using a joint model including both host and viral effects, we estimate a total of 30% heritability, indicating that most of the host effects are reflected in viral sequence variation.

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene's tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p

[This corrects the article DOI: 10.1371/journal.ppat.1003161.].

Following publication of our article [1], we identified discrepancies between the pedigree shown in Figure 1 and the rest of the text.[...]

Retinitis pigmentosa (RP) causes progressive photoreceptor loss resulting from mutations in over 80 genes. This study identified the genetic cause of RP in three members of a non-consanguineous pedigree. Detailed ophthalmic evaluation was performed in the three affected family members. Whole exome sequencing (WES) and whole genome sequencing (WGS) were performed in the three affected and the two unaffected family members and variants were filtered to detect rare, potentially deleterious variants segregating with disease. WES and WGS did not identify potentially pathogenic variants shared by all three affected members. However, WES identified a previously reported homozygous nonsense mutation in KIZ (c.226C>T, p.Arg76*) in two affected sisters, but not in their affected second cousin. WGS revealed a novel 1.135 kb homozygous deletion in a retina transcript of C21orf2 and a novel 30.651 kb heterozygous deletion in CACNA2D4 in the affected second cousin. The sisters with the KIZ mutation carried no copies of the C21orf2 or CACNA2D4 deletions, while the second cousin with the C21orf2 and CACNA2D4 deletions carried no copies of the KIZ mutation. This study identified two independent, homozygous mutations in genes previously reported in autosomal recessive RP in a non-consanguineous family, and demonstrated the value of WGS when WES fails to identify likely disease-causing mutations.

In ecology, "disease tolerance" is defined as an evolutionary strategy of hosts against pathogens, characterized by reduced or absent pathogenesis despite high pathogen load. To our knowledge, tolerance has to date not been quantified and disentangled from host resistance to disease in any clinically relevant human infection. Using data from the Swiss HIV Cohort Study, we investigated if there is variation in tolerance to HIV in humans and if this variation is associated with polymorphisms in the human genome. In particular, we tested for associations between tolerance and alleles of the Human Leukocyte Antigen (HLA) genes, the CC chemokine receptor 5 (CCR5), the age at which individuals were infected, and their sex. We found that HLA-B alleles associated with better HIV control do not confer tolerance. The slower disease progression associated with these alleles can be fully attributed to the extent of viral load reduction in carriers. However, we observed that tolerance significantly varies across HLA-B genotypes with a relative standard deviation of 34%. Furthermore, we found that HLA-B homozygotes are less tolerant than heterozygotes. Lastly, tolerance was observed to decrease with age, resulting in a 1.7-fold difference in disease progression between 20 and 60-y-old individuals with the same viral load. Thus, disease tolerance is a feature of infection with HIV, and the identification of the mechanisms involved may pave the way to a better understanding of pathogenesis.

Loss-of-function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies. Recent resequencing projects report that stop-gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter-individual variability in innate immune response. Current computational approaches evaluating loss-of-function in genes carrying these variants rely on gene-level characteristics such as evolutionary conservation and functional redundancy across the genome. However, innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated. To create a ranking of severity that would be applicable to innate immunity genes we evaluated 17,764 stop-gain and 13,915 frameshift variants from the NHLBI Exome Sequencing Project and 1,000 Genomes Project. Sequence-based features such as loss of functional domains, isoform-specific truncation and nonsense-mediated decay were found to correlate with variant allele frequency and validated with gene expression data. We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against Online Mendelian Inheritance in Man (OMIM) disease stop-gains and frameshifts. The classification scheme was applied in the assessment of 335 stop-gains and 236 frameshifts affecting 227 interferon-stimulated genes. The sequence-based score ranks variants in innate immunity genes according to their potential to cause disease, and complements existing gene-based pathogenicity scores. Specifically, the sequence-based score improves measurement of functional gene impairment, discriminates across different variants in a given gene and appears particularly useful for analysis of less conserved genes.

Dendritic cells (DCs) are essential in order to combat invading viruses and trigger antiviral responses. Paradoxically, in the case of HIV-1, DCs might contribute to viral pathogenesis through trans-infection, a mechanism that promotes viral capture and transmission to target cells, especially after DC maturation. In this review, we highlight recent evidence identifying sialyllactose-containing gangliosides in the viral membrane and the cellular lectin Siglec-1 as critical determinants for HIV-1 capture and storage by mature DCs and for DC-mediated trans-infection of T cells. In contrast, DC-SIGN, long considered to be the main receptor for DC capture of HIV-1, plays a minor role in mature DC-mediated HIV-1 capture and trans-infection.

HIV latency is a major obstacle to curing infection. Current strategies to eradicate HIV aim at increasing transcription of the latent provirus. In the present study we observed that latently infected CD4+ T cells from HIV-infected individuals failed to produce viral particles upon ex vivo exposure to SAHA (vorinostat), despite effective inhibition of histone deacetylases. To identify steps that were not susceptible to the action of SAHA or other latency reverting agents, we used a primary CD4+ T cell model, joint host and viral RNA sequencing, and a viral-encoded reporter. This model served to investigate the characteristics of latently infected cells, the dynamics of HIV latency, and the process of reactivation induced by various stimuli. During latency, we observed persistence of viral transcripts but only limited viral translation. Similarly, the reactivating agents SAHA and disulfiram successfully increased viral transcription, but failed to effectively enhance viral translation, mirroring the ex vivo data. This study highlights the importance of post-transcriptional blocks as one mechanism leading to HIV latency that needs to be relieved in order to purge the viral reservoir.

Natural progression of HIV-1 infection depends on genetic variation in the human major histocompatibility complex (MHC) class I locus, and the CD8+ T cell response is thought to be a primary mechanism of this effect. However, polymorphism within the MHC may also alter innate immune activity against human immunodeficiency virus type 1 (HIV-1) by changing interactions of human leukocyte antigen (HLA) class I molecules with leukocyte immunoglobulin-like receptors (LILR), a group of immunoregulatory receptors mainly expressed on myelomonocytic cells including dendritic cells (DCs). We used previously characterized HLA allotype-specific binding capacities of LILRB1 and LILRB2 as well as data from a large cohort of HIV-1-infected individuals (N = 5126) to test whether LILR-HLA class I interactions influence viral load in HIV-1 infection. Our analyses in persons of European descent, the largest ethnic group examined, show that the effect of HLA-B alleles on HIV-1 control correlates with the binding strength between corresponding HLA-B allotypes and LILRB2 (p = 10(-2)). Moreover, overall binding strength of LILRB2 to classical HLA class I allotypes, defined by the HLA-A/B/C genotypes in each patient, positively associates with viral replication in the absence of therapy in patients of both European (p = 10(-11)-10(-9)) and African (p = 10(-5)-10(-3)) descent. This effect appears to be driven by variations in LILRB2 binding affinities to HLA-B and is independent of individual class I allelic effects that are not related to the LILRB2 function. Correspondingly, in vitro experiments suggest that strong LILRB2-HLA binding negatively affects antigen-presenting properties of DCs. Thus, we propose an impact of LILRB2 on HIV-1 disease outcomes through altered regulation of DCs by LILRB2-HLA engagement.

The storage of greater numbers of exomes or genomes raises the question of loss of privacy for the individual and for families if genomic data are not properly protected. Access to genome data may result from a personal decision to disclose, or from gaps in protection. In either case, revealing genome data has consequences beyond the individual, as it compromises the privacy of family members. Increasing availability of genome data linked or linkable to metadata through online social networks and services adds one additional layer of complexity to the protection of genome privacy. The field of computer science and information technology offers solutions to secure genomic data so that individuals, medical personnel or researchers can access only the subset of genomic information required for healthcare or dedicated studies.

HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p

HIV-1 infects CD4+ T cells and completes its replication cycle in approximately 24 hours. We employed repeated measurements in a standardized cell system and rigorous mathematical modeling to characterize the emergence of the viral replication intermediates and their impact on the cellular transcriptional response with high temporal resolution. We observed 7,991 (73%) of the 10,958 expressed genes to be modulated in concordance with key steps of viral replication. Fifty-two percent of the overall variability in the host transcriptome was explained by linear regression on the viral life cycle. This profound perturbation of cellular physiology was investigated in the light of several regulatory mechanisms, including transcription factors, miRNAs, host-pathogen interaction, and proviral integration. Key features were validated in primary CD4+ T cells, and with viral constructs using alternative entry strategies. We propose a model of early massive cellular shutdown and progressive upregulation of the cellular machinery to complete the viral life cycle.

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6 × 10⁻¹¹). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception of CCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size.

Single-cell sequencing technologies, i.e., single cell analysis followed by deep sequencing investigate cellular heterogeneity in many biological settings. It was only in the past year that single-cell sequencing analyses has been applied in the field of virology, providing new ways to explore viral diversity and cell response to viral infection, which are summarized in the present review.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Dendritic cells (DCs) are essential antigen-presenting cells for the induction of immunity against pathogens. However, HIV-1 spread is strongly enhanced in clusters of DCs and CD4(+) T cells. Uninfected DCs capture HIV-1 and mediate viral transfer to bystander CD4(+) T cells through a process termed trans-infection. Initial studies identified the C-type lectin DC-SIGN as the HIV-1 binding factor on DCs, which interacts with the viral envelope glycoproteins. Upon DC maturation, however, DC-SIGN is down-regulated, while HIV-1 capture and trans-infection is strongly enhanced via a glycoprotein-independent capture pathway that recognizes sialyllactose-containing membrane gangliosides. Here we show that the sialic acid-binding Ig-like lectin 1 (Siglec-1, CD169), which is highly expressed on mature DCs, specifically binds HIV-1 and vesicles carrying sialyllactose. Furthermore, Siglec-1 is essential for trans-infection by mature DCs. These findings identify Siglec-1 as a key factor for HIV-1 spread via infectious DC/T-cell synapses, highlighting a novel mechanism that mediates HIV-1 dissemination in activated tissues.

BackgroundGood adherence to antiretroviral therapy (ART) is critical for successful HIV treatment. However, some patients remain virologically suppressed despite suboptimal adherence. We hypothesized that this could result from host genetic factors influencing drug levels.MethodsEligible individuals were Caucasians treated with efavirenz (EFV) and/or boosted lopinavir (LPV/r) with self-reported poor adherence, defined as missing doses of ART at least weekly for more than 6 months. Participants were genotyped for single nucleotide polymorphisms (SNPs) in candidate genes previously reported to decrease EFV (rs3745274, rs35303484, rs35979566 in CYP2B6) and LPV/r clearance (rs4149056 in SLCO1B1, rs6945984 in CYP3A, rs717620 in ABCC2). Viral suppression was defined as having HIV-1 RNA ResultsFrom January 2003 until May 2009, 37 individuals on EFV (28 suppressed and 9 not suppressed) and 69 on LPV/r (38 suppressed and 31 not suppressed) were eligible. The poor adherence period was a median of 32 weeks with 18.9% of EFV and 20.3% of LPV/r patients reporting missed doses on a daily basis. The tested SNPs were not determinant for viral suppression. Reporting missing >1 dose/week was associated with a lower probability of viral suppression compared to missing 1 dose/week (EFV: odds ratio (OR) 0.11, 95% confidence interval (CI): 0.01-0.99; LPV/r: OR 0.29, 95% CI: 0.09-0.94). In both groups, the probability of remaining suppressed increased with the duration of continuous suppression prior to the poor adherence period (EFV: OR 3.40, 95% CI: 0.62-18.75; LPV/r: OR 5.65, 95% CI: 1.82-17.56).ConclusionsThe investigated genetic variants did not play a significant role in the sustained viral suppression of individuals with suboptimal adherence. Risk of failure decreased with longer duration of viral suppression in this population.

To study the causes for the lack of clinical progression in a superinfected HIV-1 LTNP elite controller patient.We studied host genetic, virological and immunological factors associated with viral control in a SI long term non progressor elite controller (LTNP-EC). The individual contained both viruses and maintained undetectable viral loads for >20 years and he did not express any of the described host genetic polymorphisms associated with viral control. None of four full-length gp160 recombinants derived from the LTNP-EC replicated in heterologous peripheral blood mononuclear cells. CTL responses after SI were maintained in two samples separated by 9 years and they were higher in breadth and magnitude than responses seen in most of 250 treatment naïve patients and also 25 controller subjects. The LTNP-EC showed a neutralization response, against 4 of the 6 viruses analyzed, superior to other ECs.The study demonstrated that a strong and sustained cellular and humoral immune response and low replicating viruses are associated with viral control in the superinfected LTNP-EC.

Epstein-Barr virus (EBV) is associated with several types of cancers including Hodgkin's lymphoma (HL) and nasopharyngeal carcinoma (NPC). EBV-encoded latent membrane protein 1 (LMP1), a multifunctional oncoprotein, is a powerful activator of the transcription factor NF-κB, a property that is essential for EBV-transformed lymphoblastoid cell survival. Previous studies reported LMP1 sequence variations and induction of higher NF-κB activation levels compared to the prototype B95-8 LMP1 by some variants. Here we used biopsies of EBV-associated cancers and blood of individuals included in the Swiss HIV Cohort Study (SHCS) to analyze LMP1 genetic diversity and impact of sequence variations on LMP1-mediated NF-κB activation potential. We found that a number of variants mediate higher NF-κB activation levels when compared to B95-8 LMP1 and mapped three single polymorphisms responsible for this phenotype: F106Y, I124V and F144I. F106Y was present in all LMP1 isolated in this study and its effect was variant dependent, suggesting that it was modulated by other polymorphisms. The two polymorphisms I124V and F144I were present in distinct phylogenetic groups and were linked with other specific polymorphisms nearby, I152L and D150A/L151I, respectively. The two sets of polymorphisms, I124V/I152L and F144I/D150A/L151I, which were markers of increased NF-κB activation in vitro, were not associated with EBV-associated HL in the SHCS. Taken together these results highlighted the importance of single polymorphisms for the modulation of LMP1 signaling activity and demonstrated that several groups of LMP1 variants, through distinct mutational paths, mediated enhanced NF-κB activation levels compared to B95-8 LMP1.

A genome-wide screen for large structural variants showed that a copy number variant (CNV) in the region encoding killer cell immunoglobulin-like receptors (KIR) associates with HIV-1 control as measured by plasma viral load at set point in individuals of European ancestry. This CNV encompasses the KIR3DL1-KIR3DS1 locus, encoding receptors that interact with specific HLA-Bw4 molecules to regulate the activation of lymphocyte subsets including natural killer (NK) cells. We quantified the number of copies of KIR3DS1 and KIR3DL1 in a large HIV-1 positive cohort, and showed that an increase in KIR3DS1 count associates with a lower viral set point if its putative ligand is present (p = 0.00028), as does an increase in KIR3DL1 count in the presence of KIR3DS1 and appropriate ligands for both receptors (p = 0.0015). We further provide functional data that demonstrate that NK cells from individuals with multiple copies of KIR3DL1, in the presence of KIR3DS1 and the appropriate ligands, inhibit HIV-1 replication more robustly, and associated with a significant expansion in the frequency of KIR3DS1+, but not KIR3DL1+, NK cells in their peripheral blood. Our results suggest that the relative amounts of these activating and inhibitory KIR play a role in regulating the peripheral expansion of highly antiviral KIR3DS1+ NK cells, which may determine differences in HIV-1 control following infection.

BACKGROUND: Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study. METHODOLOGY/PRINCIPAL FINDINGS: We built up two prediction rules ("Snap-shot rule" for a single sample and "Track-shot rule" for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior ≥5% or 650 for a threshold of 200, >900 for 350, or >1150 for 500×10(6)/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.

This is a crucial transition time for human genetics in general, and for HIV host genetics in particular. After years of equivocal results from candidate gene analyses, several genome-wide association studies have been published that looked at plasma viral load or disease progression. Results from other studies that used various large-scale approaches (siRNA screens, transcriptome or proteome analysis, comparative genomics) have also shed new light on retroviral pathogenesis. However, most of the inter-individual variability in response to HIV-1 infection remains to be explained: genome resequencing and systems biology approaches are now required to progress toward a better understanding of the complex interactions between HIV-1 and its human host.

HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.

There is great interindividual variability in HIV-1 viral setpoint after seroconversion, some of which is known to be due to genetic differences among infected individuals. Here, our focus is on determining, genome-wide, the contribution of variable gene expression to viral control, and to relate it to genomic DNA polymorphism. RNA was extracted from purified CD4+ T-cells from 137 HIV-1 seroconverters, 16 elite controllers, and 3 healthy blood donors. Expression levels of more than 48,000 mRNA transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina). Genome-wide SNP data was generated from genomic DNA using the HumanHap550 Genotyping BeadChip (Illumina). We observed two distinct profiles with 260 genes differentially expressed depending on HIV-1 viral load. There was significant upregulation of expression of interferon stimulated genes with increasing viral load, including genes of the intrinsic antiretroviral defense. Upon successful antiretroviral treatment, the transcriptome profile of previously viremic individuals reverted to a pattern comparable to that of elite controllers and of uninfected individuals. Genome-wide evaluation of cis-acting SNPs identified genetic variants modulating expression of 190 genes. Those were compared to the genes whose expression was found associated with viral load: expression of one interferon stimulated gene, OAS1, was found to be regulated by a SNP (rs3177979, p = 4.9E-12); however, we could not detect an independent association of the SNP with viral setpoint. Thus, this study represents an attempt to integrate genome-wide SNP signals with genome-wide expression profiles in the search for biological correlates of HIV-1 control. It underscores the paradox of the association between increasing levels of viral load and greater expression of antiviral defense pathways. It also shows that elite controllers do not have a fully distinctive mRNA expression pattern in CD4+ T cells. Overall, changes in global RNA expression reflect responses to viral replication rather than a mechanism that might explain viral control.

BACKGROUND: Various patterns of HIV-1 disease progression are described in clinical practice and in research. There is a need to assess the specificity of commonly used definitions of long term non-progressor (LTNP) elite controllers (LTNP-EC), viremic controllers (LTNP-VC), and viremic non controllers (LTNP-NC), as well as of chronic progressors (P) and rapid progressors (RP). METHODOLOGY AND PRINCIPAL FINDINGS: We re-evaluated the HIV-1 clinical definitions, summarized in Table 1, using the information provided by a selected number of host genetic markers and viral factors. There is a continuous decrease of protective factors and an accumulation of risk factors from LTNP-EC to RP. Statistical differences in frequency of protective HLA-B alleles (p-0.01), HLA-C rs9264942 (p-0.06), and protective CCR5/CCR2 haplotypes (p-0.02) across groups, and the presence of viruses with an ancestral genotype in the "viral dating" (i.e., nucleotide sequences with low viral divergence from the most recent common ancestor) support the differences among principal clinical groups of HIV-1 infected individuals. CONCLUSIONS: A combination of host genetic and viral factors supports current clinical definitions that discriminate among patterns of HIV-1 progression. The study also emphasizes the need to apply a standardized and accepted set of clinical definitions for the purpose of disease stratification and research.

To extend the understanding of host genetic determinants of HIV-1 control, we performed a genome-wide association study in a cohort of 2,554 infected Caucasian subjects. The study was powered to detect common genetic variants explaining down to 1.3% of the variability in viral load at set point. We provide overwhelming confirmation of three associations previously reported in a genome-wide study and show further independent effects of both common and rare variants in the Major Histocompatibility Complex region (MHC). We also examined the polymorphisms reported in previous candidate gene studies and fail to support a role for any variant outside of the MHC or the chemokine receptor cluster on chromosome 3. In addition, we evaluated functional variants, copy-number polymorphisms, epistatic interactions, and biological pathways. This study thus represents a comprehensive assessment of common human genetic variation in HIV-1 control in Caucasians.