Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses

Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.

Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters; A Retrospective Cohort Analysis and Pilot Study

Background

Two years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited.

Objectives

To measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively.

Findings

1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests.

Conclusions

Laboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible.

Indirect determination of biochemistry reference intervals using outpatient data

The aim of this study was to determine reference intervals in an outpatient population from Vall d'Hebron laboratory using an indirect approach previously described in a Dutch population (NUMBER project). We used anonymized test results from individuals visiting general practitioners and analysed during 2018. Analytical quality was assured by EQA performance, daily average monitoring and by assessing longitudinal accuracy between 2018 and 2020 (using trueness verifiers from Dutch EQA). Per test, outliers by biochemically related tests were excluded, data were transformed to a normal distribution (if necessary) and means and standard deviations were calculated, stratified by age and sex. In addition, the reference limit estimator method was also used to calculate reference intervals using the same dataset. Finally, for standardized tests reference intervals obtained were compared with the published NUMBER results. Reference intervals were calculated using data from 509,408 clinical requests. For biochemical tests following a normal distribution, similar reference intervals were found between Vall d'Hebron and the Dutch study. For creatinine and urea, reference intervals increased with age in both populations. The upper limits of Gamma-glutamyl transferase were markedly higher in the Dutch study compared to Vall d'Hebron results. Creatine kinase and uric acid reference intervals were higher in both populations compared to conventional reference intervals. Medical test results following a normal distribution showed comparable and consistent reference intervals between studies. Therefore a simple indirect method is a feasible and cost-efficient approach for calculating reference intervals. Yet, for generating standardized calculated reference intervals that are traceable to higher order materials and methods, efforts should also focus on test standardization and bias assessment using commutable trueness verifiers.

Recovery of serum testosterone levels is an accurate predictor of survival from COVID-19 in male patients

BACKGROUND

SARS-CoV-2 infection portends a broad range of outcomes, from a majority of asymptomatic cases to a lethal disease. Robust correlates of severe COVID-19 include old age, male sex, poverty, and co-morbidities such as obesity, diabetes, and cardiovascular disease. A precise knowledge of the molecular and biological mechanisms that may explain the association of severe disease with male sex is still lacking. Here, we analyzed the relationship of serum testosterone levels and the immune cell skewing with disease severity in male COVID-19 patients.

METHODS

Biochemical and hematological parameters of admission samples in 497 hospitalized male and female COVID-19 patients, analyzed for associations with outcome and sex. Longitudinal (in-hospital course) analyses of a subcohort of 114 male patients were analyzed for associations with outcome. Longitudinal analyses of immune populations by flow cytometry in 24 male patients were studied for associations with outcome.

RESULTS

We have found quantitative differences in biochemical predictors of disease outcome in male vs. female patients. Longitudinal analyses in a subcohort of male COVID-19 patients identified serum testosterone trajectories as the strongest predictor of survival (AUC of ROC = 92.8%, p < 0.0001) in these patients among all biochemical parameters studied, including single-point admission serum testosterone values. In lethal cases, longitudinal determinations of serum luteinizing hormone (LH) and androstenedione levels did not follow physiological feedback patterns. Failure to reinstate physiological testosterone levels was associated with evidence of impaired T helper differentiation and augmented circulating classical monocytes.

CONCLUSIONS

Recovery or failure to reinstate testosterone levels is strongly associated with survival or death, respectively, from COVID-19 in male patients. Our data suggest an early inhibition of the central LH-androgen biosynthesis axis in a majority of patients, followed by full recovery in survivors or a peripheral failure in lethal cases. These observations are suggestive of a significant role of testosterone status in the immune responses to COVID-19 and warrant future experimental explorations of mechanistic relationships between testosterone status and SARS-CoV-2 infection outcomes, with potential prophylactic or therapeutic implications.

A descriptive and validation study of a predictive model of severity of SARS-COV-2 infection

Objectives

The strain the SARS-COV-2 pandemic is putting on hospitals requires that predictive values are identified for a rapid triage and management of patients at a higher risk of developing severe COVID-19. We developed and validated a prognostic model of COVID-19 severity.

Methods

A descriptive, comparative study of patients with positive vs. negative PCR-RT for SARS-COV-2 and of patients who developed moderate vs. severe COVID-19 was conducted. The model was built based on analytical and demographic data and comorbidities of patients seen in an Emergency Department with symptoms consistent with COVID-19. A logistic regression model was designed from data of the COVID-19-positive cohort.

Results

The sample was composed of 410 COVID-positive patients (303 with moderate disease and 107 with severe disease) and 81 COVID-negative patients. The predictive variables identified included lactate dehydrogenase, C-reactive protein, total proteins, urea, and platelets. Internal calibration showed an area under the ROC curve (AUC) of 0.88 (CI 95%: 0.85-0.92), with a rate of correct classifications of 85.2% for a cut-off value of 0.5. External validation (100 patients) yielded an AUC of 0.79 (95% CI: 0.71-0.89), with a rate of correct classifications of 73%.

Conclusions

The predictive model identifies patients at a higher risk of developing severe COVID-19 at Emergency Department, with a first blood test and common parameters used in a clinical laboratory. This model may be a valuable tool for clinical planning and decision-making.

GEHEP 010 study: Prevalence and distribution of hepatitis B virus genotypes in Spain (2000-2016)

OBJECTIVE

To study the prevalence and distribution of HBV genotypes in Spain for the period 2000-2016.

METHODS

Retrospective study recruiting 2559 patients from 17 hospitals. Distribution of HBV genotypes, as well as sex, age, geographical origin, mode of transmission, HDV-, HIV- and/or HCV-coinfection, and treatment were recorded.

RESULTS

1924 chronically HBV native Spanish patients have been recruited. Median age was 54 years (IQR: 41-62), 69.6% male, 6.3% HIV-coinfected, 3.1% were HCV-coinfected, 1.7% HDV-co/superinfected. Genotype distribution was: 55.9% D, 33.5% A, 5.6% F, 0.8% G, and 1.9% other genotypes (E, B, H and C). HBV genotype A was closely associated with male sex, sexual transmission, and HIV-coinfection. In contrast, HBV genotype D was associated with female sex and vertical transmission. Different patterns of genotype distribution and diversity were found between different geographical regions. In addition, HBV epidemiological patterns are evolving in Spain, mainly because of immigration. Finally, similar overall rates of treatment success across all HBV genotypes were found.

CONCLUSIONS

We present here the most recent data on molecular epidemiology of HBV in Spain (GEHEP010 Study). This study confirms that the HBV genotype distribution in Spain varies based on age, sex, origin, HIV-coinfection, geographical regions and epidemiological groups.

Real world evaluation of a novel lateral flow assay (AlphaKit® QuickScreen) for the detection of alpha-1-antitrypsin deficiency

BACKGROUND

Alpha-1-Antitrypsin (AAT) deficiency (AATD) is a hereditary disorder that manifests primarily as pulmonary emphysema and liver cirrhosis. The clinically most relevant mutation causing AATD is a single nucleotide polymorphism Glu342Lys (Z-mutation). Despite the recommendation to test every COPD patient, the condition remains severely underdiagnosed with a delay of several years between first symptoms and diagnosis. The Grifols' AlphaKit® QuickScreen is a novel qualitative point-of-care (POC) in vitro screening test developed for the detection of the Z AAT protein in capillary whole blood. The objective of this prospective, international, multi-center, diagnostic, interventional real-world study was to assess the performance of this device for the detection of AATD in test-naïve COPD patients.

METHODS

1044 test-naïve COPD patients were recruited from 9 centers in Spain and 10 centers in Germany, ranging from primary to tertiary care. To evaluate the performance of the test, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated compared with the gold standard (genotyping).

RESULTS

Genotyping and phenotyping of all 1019 evaluable samples revealed 4.12% of patients as carriers of at least one Z-allele, while 0.29% carried the homozygous genotype Pi*ZZ. The evaluation of the test's ability to detect the PiZ protein yielded the following results: specificity 97.8%, sensitivity 73.8%, negative predictive value 98.9%, and positive predictive value 58.5%. All false negatives (n = 11) were heterozygote Pi*MZ samples.

CONCLUSIONS

The tested device can be used as an appropriate tool to exclude AATD in primary care and in the overall COPD population, except in patients with a high a-priori- probability of AATD.

A new HDV mouse model identifies mitochondrial antiviral signaling protein (MAVS) as a key player in IFN-β induction

BACKGROUND & AIMS

Studying hepatitis delta virus (HDV) and developing new treatments is hampered by the limited availability of small animal models. Herein, a description of a robust mouse model of HDV infection that mimics several important characteristics of the human disease is presented.

METHODS

HDV and hepatitis B virus (HBV) replication competent genomes were delivered to the mouse liver using adeno-associated viruses (AAV; AAV-HDV and AAV-HBV). Viral load, antigen expression and genomes were quantified at different time points after AAV injection. Furthermore, liver pathology, genome editing, and the activation of the innate immune response were evaluated.

RESULTS

AAV-HDV infection initiated HDV replication in mouse hepatocytes. Genome editing was confirmed by the presence of small and large HDV antigens and sequencing. Viral replication was detected for 45days, even after the AAV-HDV vector had almost disappeared. In the presence of HBV, HDV infectious particles were detected in serum. Furthermore, as observed in patients, co-infection was associated with the reduction of HBV antigen expression and the onset of liver damage that included the alteration of genes involved in the development of liver pathologies. HDV replication induced a sustained type I interferon response, which was significantly reduced in immunodeficient mice and almost absent in mitochondrial antiviral signaling protein (MAVS)-deficient mice.

CONCLUSION

The animal model described here reproduces important characteristics of human HDV infection and provides a valuable tool for characterizing the viral infection and for developing new treatments. Furthermore, MAVS was identified as a main player in HDV detection and adaptive immunity was found to be involved in the amplification of the innate immune response. Lay summary: Co-infection with hepatitis B and D virus (HBV and HDV, respectively) often causes a more severe disease condition than HBV alone. Gaining more insight into HDV and developing new treatments is hampered by limited availability of adequate immune competent small animal models and new ones are needed. Here, a mouse model of HDV infection is described, which mimics several important characteristics of the human disease, such as the initiation and maintenance of replication in murine hepatocytes, genome editing and, in the presence of HBV, generation of infectious particles. Lastly, the involvement of an adaptive immunity and the intracellular signaling molecule MAVS in mounting a strong and lasting innate response was shown. Thus, our model serves as a useful tool for the investigation of HDV biology and new treatments.

Prevalence and distribution of hepatitis C virus genotypes in Spain during the 2000-2015 period (the GEHEP 005 study)

We report the largest study on the prevalence and distribution of HCV genotypes in Spain (2000-2015), and we relate them with clinical, epidemiological and virological factors. Patients from 29 hospitals in 10 autonomous communities (Andalusia, Aragon, Castilla-Leon, Catalonia, Galicia, Canary Islands, Madrid Community, Valencian Community, Murcia Region and Basque Country) have been studied. Annual distribution of HCV genotypes and subtypes, as well as gender, age, transmission route, HIV and/or HBV coinfection, and treatment details were recorded. We included 48595 chronically HCV-infected patients with the following characteristics: median age 51 years (IQR, 44-58), 67.9% male, 19.1% HIV-coinfected, 23.5% HBV-coinfected. Parenteral transmission route was the most frequent (58.7%). Genotype distribution was 66.9% GT1 (24.9% subtype 1a and 37.9% subtype 1b), 2.8% GT2, 17.3% GT3, 11.4% GT4 and 0.1% GT5 and 0.02% GT6. LiPA was the most widely HCV genotyping test used (52.4%). HCV subtype 1a and genotypes 3 and 4 were closely associated with male gender, parenteral route of infection and HIV and HBV coinfection; in contrast, subtype 1b and genotype 2 were associated with female gender, nonparenteral route and mono-infection. Age was related to genotype distribution, and different patterns of distribution and biodiversity index were observed between different geographical areas. Finally, we describe how treatment and changes in transmission routes may have affected HCV genotype prevalence and distribution patterns. We present the most recent data on molecular epidemiology of hepatitis C virus in Spain. This study confirms that genotype distributions vary with age, sex, HIV and HBV coinfection and within geographical areas and epidemiological groups.

Deep sequencing in the management of hepatitis virus infections

The hepatitis viruses represent a major public health problem worldwide. Procedures for characterization of the genomic composition of their populations, accurate diagnosis, identification of multiple infections, and information on inhibitor-escape mutants for treatment decisions are needed. Deep sequencing methodologies are extremely useful for these viruses since they replicate as complex and dynamic quasispecies swarms whose complexity and mutant composition are biologically relevant traits. Population complexity is a major challenge for disease prevention and control, but also an opportunity to distinguish among related but phenotypically distinct variants that might anticipate disease progression and treatment outcome. Detailed characterization of mutant spectra should permit choosing better treatment options, given the increasing number of new antiviral inhibitors available. In the present review we briefly summarize our experience on the use of deep sequencing for the management of hepatitis virus infections, particularly for hepatitis B and C viruses, and outline some possible new applications of deep sequencing for these important human pathogens.

High-resolution hepatitis C virus subtyping using NS5B deep sequencing and phylogeny, an alternative to current methods

Hepatitis C virus (HCV) is classified into seven major genotypes and 67 subtypes. Recent studies have shown that in HCV genotype 1-infected patients, response rates to regimens containing direct-acting antivirals (DAAs) are subtype dependent. Currently available genotyping methods have limited subtyping accuracy. We have evaluated the performance of a deep-sequencing-based HCV subtyping assay, developed for the 454/GS-Junior platform, in comparison with those of two commercial assays (Versant HCV genotype 2.0 and Abbott Real-time HCV Genotype II) and using direct NS5B sequencing as a gold standard (direct sequencing), in 114 clinical specimens previously tested by first-generation hybridization assay (82 genotype 1 and 32 with uninterpretable results). Phylogenetic analysis of deep-sequencing reads matched subtype 1 calling by population Sanger sequencing (69% 1b, 31% 1a) in 81 specimens and identified a mixed-subtype infection (1b/3a/1a) in one sample. Similarly, among the 32 previously indeterminate specimens, identical genotype and subtype results were obtained by direct and deep sequencing in all but four samples with dual infection. In contrast, both Versant HCV Genotype 2.0 and Abbott Real-time HCV Genotype II failed subtype 1 calling in 13 (16%) samples each and were unable to identify the HCV genotype and/or subtype in more than half of the non-genotype 1 samples. We concluded that deep sequencing is more efficient for HCV subtyping than currently available methods and allows qualitative identification of mixed infections and may be more helpful with respect to informing treatment strategies with new DAA-containing regimens across all HCV subtypes.

[Hepatitis E: molecular virology, epidemiology and pathogenesis]

Hepatitis E represents a significant proportion of enteric transmitted liver diseases and poses a major public health problem, mainly associated with epidemics due to contamination of water supplies, especially in developing countries. Hepatitis E virus (HEV) is responsible for self-limiting acute liver oral-faecal infections. In industrialised countries, acute hepatitis E is sporadic, detected in travellers from endemic areas but also in sporadic cases with no risk factors. HEV is a non-enveloped virus with a single-stranded RNA genome classified into 4 genotypes and a single serotype. Genotypes 1 and 2 only infect humans, and are predominant in the developing countries, while 3 and 4 are predominant in industrialised countries, and also infect other species of mammals, especially pigs, and multiple evidence classifies HEV as a zoonotic agent. Some HEV chronic infections have recently been reported in kidney and liver transplant patients. The mortality rate of HEV infection is greater than hepatitis A. In addition to faecal-oral transmission, parenteral transmission of HEV has also been reported. Several vaccines are currently in development. The severity of this infection in some groups of patients, especially pregnant women, and the occurrence of chronic hepatitis, even with progression to cirrhosis, have raised interest in the application of interferon and/or ribavirin therapy.

α1-Antitrypsin in fibromyalgia: results of a randomized, placebo-controlled, double-blind and crossover pilot trial

OBJECTIVE

To assess clinical effect of a human plasma-derived alpha-1 antitrypsin (AAT) concentrate in reducing pain severity of patients with fibromyalgia (FM).

METHODS

Thirteen subjects with FM completed a randomized, double-blind, placebo-controlled, crossover study which consisted of 9 weeks trial of AAT or placebo with a washout period of 6 weeks. Primary efficacy endpoint was change on pain severity score, assessed by a daily visual analogue scale (VAS) for pain. Other outcome measures included a tender point score, the Fibromyalgia Impact Questionnaire, (FIQ), the Medical Outcomes Study Short Form 36 (SF-36), the Health Assessment Questionnaire Disability Index (HAQ-DI), the Hospital Anxiety and Depression Scale (HADS) and tiredness score evaluated by VAS.

RESULTS

No statistically significant differences were observed in either pain severity or other secondary outcome measures in either of the treatment groups, or between treatment groups in either of the treatment periods. No carryover or order of intervention effect was observed from one treatment to the other. Both investigational interventions were generally well tolerated, and vital signs during the drug infusions were within the respective normal ranges.

CONCLUSION

Treatment with a human plasma-derived AAT concentrate did not demonstrate significant improvement over placebo on reducing pain severity and other symptoms of FM. Further research should examine other FM subpopulations and drug doses.

Response-guided therapy for chronic hepatitis C virus infection in patients coinfected with HIV: a pilot trial

BACKGROUND

To study the feasibility of a response-guided therapy for chronic hepatitis C virus (HCV) infection in patients coinfected with human immunodeficiency virus (HIV) in a tertiary care hospital.

METHODS

Treatment duration was individualized on the basis of week 4 and week 12 virologic response. Sixty patients were enrolled and received pegylated interferon alfa-2b (1.5 microg/kg per week) plus weight-based ribavirin (800-1400 mg/day). Patients who achieved a rapid virologic response, defined as viral load <50 IU/mL at treatment week 4, completed 24 weeks of therapy. Patients who did not achieve a rapid virologic response were reassessed at treatment week 12. Patients with a complete early virologic response, defined as an HCV RNA level <600 IU/mL, were treated for 48 weeks. Patients with a partial response, defined as a decrease in the viral load > or = 2 log10 and an HCV RNA level > or = 600 IU/mL, who attained an undetectable viral load at week 24 were treated for 60 weeks. The primary efficacy end point was sustained virologic response, defined as HCV RNA <50 IU/mL, 24 weeks after the end of treatment.

RESULTS

Overall, 33 (55%) of 60 patients achieved a sustained virologic response: 11 (44%) of 25 patients with HCV genotype 1, 3 (27%) of 11 patients with genotype 4, and 19 (79%) of 24 patients with genotype 3. One-third of patients showed a rapid virologic response. Of patients with genotype 1, there was a rapid virologic response in 4 (16%) of 25; with genotype 4, in 1 (9%) of 11; and with genotype 3, in 14 (58%) of 24. Of the 19 patients with a rapid virologic response, 17 (89.5%) eradicated the virus after 24 weeks of therapy. The rate of sustained virologic response was significantly higher among patients with genotype 3 and low pretreatment HCV RNA levels. A high relapse rate (46%) after 48 weeks of therapy occurred among patients infected with genotypes 1 or 4 who first achieved undetectable viral load at treatment week 12.

CONCLUSION

A response-guide therapy is feasible and may be useful to optimize the individual outcome of HCV treatment in patients coinfected with HIV.

[Molecular virology of the hepatitis B virus]

The hepatitis B virus (HBV) belongs to the hepadnavirus family. The genome of the virus, formed by a small DNA molecule with 3,200 base pairs, has 4 strongly overlapping protein coding regions: ORF preS/S, corresponding to the envelope proteins that constitute the HBV surface antigen (HBsAg); ORF preC/C, which encodes the viral capsid component (core antigen or HBcAg) and a non-structural protein that, after postranslation modification, is secreted and constitutes the "e" antigen (HBeAg); ORF P, which encodes the viral polymerase (polyprotein with DNA polymerase activity, reverse transcriptase and RNAase), and ORF X, which encodes a protein that acts as a multifunctional regulator for both the viral and cell cycles. HBV has a mutation rate of 1.4-3.2 x 105 substitutions/nucleotide/year. As a result of this variability, the virus circulates as a complex mixture of genetic variants, constituting a semi-species, that evolves throughout the infection depending on the evolutionary pressure of factors such as the immune response and antiviral treatments. Based on this variability, HBV has been classified into 8 genotypes (A-H) defined by a difference of more than 8% in the sequences of the complete viral genome. This variability is also responsible for HBV resistance to antiviral treatments with nucleotide and nucleoside analogs. Diagnosis of HBV infection includes determination of virological markers: viral antigens (HBsAg, HBeAg), specific antibodies (anti-HBc, anti-HBe, anti-HBs) and study of HBV-DNA for its detection and quantification and determination of genotypes and viral variants.