Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study

BACKGROUND

Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches.

METHODS

In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD.

RESULTS

In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01).

CONCLUSIONS

This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.

Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI

INTRODUCTION

The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI).

METHODS

We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian-mixture-modelling-derived cutpoints for Aβ PET positivity were converted.

RESULTS

The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM-based Centiloids. Linear adjustment produced a WM-based cutpoint of 18.1.

DISCUSSION

Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed.

HIGHLIGHTS

Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results.Centiloid values can be influenced by differences in acquisition.We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort.Whole cerebellum referenced values could be reliably transformed to Centiloids.White matter referenced values may be less generalizable between datasets.

Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative (GENFI) cohort

Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative.

387 mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). W-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as “normal” or “abnormal” based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the “normal” and “abnormal” groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score.

Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers.

Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials.

Methodological approaches to optimize multiplex oral fluid SARS-CoV-2 IgG assay performance and correlation with serologic and neutralizing antibody responses

BACKGROUND

Oral fluid (hereafter, saliva) is a non-invasive and attractive alternative to blood for SARS-CoV-2 IgG testing; however, the heterogeneity of saliva as a matrix poses challenges for immunoassay performance.

OBJECTIVES

To optimize performance of a magnetic microparticle-based multiplex immunoassay (MIA) for SARS-CoV-2 IgG measurement in saliva, with consideration of: i) threshold setting and validation across different MIA bead batches; ii) sample qualification based on salivary total IgG concentration; iii) calibration to U.S. SARS-CoV-2 serological standard binding antibody units (BAU); and iv) correlations with blood-based SARS-CoV-2 serological and neutralizing antibody (nAb) assays.

METHODS

The salivary SARS-CoV-2 IgG MIA included 2 nucleocapsid (N), 3 receptor-binding domain (RBD), and 2 spike protein (S) antigens. Gingival crevicular fluid (GCF) swab saliva samples were collected before December 2019 (n = 555) and after molecular test-confirmed SARS-CoV-2 infection from 113 individuals (providing up to 5 repeated-measures; n = 398) and used to optimize and validate MIA performance (total n = 953). Combinations of IgG responses to N, RBD and S and total salivary IgG concentration (μg/mL) as a qualifier of nonreactive samples were optimized and validated, calibrated to the U.S. SARS-CoV-2 serological standard, and correlated with blood-based SARS-CoV-2 IgG ELISA and nAb assays.

RESULTS

The sum of signal to cutoff (S/Co) to all seven MIA SARS-CoV-2 antigens and disqualification of nonreactive saliva samples with ≤15 μg/mL total IgG led to correct classification of 62/62 positives (sensitivity [Se] = 100.0%; 95% confidence interval [CI] = 94.8%, 100.0%) and 108/109 negatives (specificity [Sp] = 99.1%; 95% CI = 97.3%, 100.0%) at 8-million beads coupling scale and 80/81 positives (Se = 98.8%; 95% CI = 93.3%, 100.0%] and 127/127 negatives (Sp = 100%; 95% CI = 97.1%, 100.0%) at 20-million beads coupling scale. Salivary SARS-CoV-2 IgG crossed the MIA cutoff of 0.1 BAU/mL on average 9 days post-COVID-19 symptom onset and peaked around day 30. Among n = 30 matched saliva and plasma samples, salivary SARS-CoV-2 MIA IgG levels correlated with corresponding-antigen plasma ELISA IgG (N: ρ = 0.76, RBD: ρ = 0.83, S: ρ = 0.82; all p < 0.001). Correlations of plasma SARS-CoV-2 nAb assay area under the curve (AUC) with salivary MIA IgG (N: ρ = 0.68, RBD: ρ = 0.78, S: ρ = 0.79; all p < 0.001) and with plasma ELISA IgG (N: ρ = 0.76, RBD: ρ = 0.79, S: ρ = 0.76; p < 0.001) were similar.

CONCLUSIONS

A salivary SARS-CoV-2 IgG MIA produced consistently high Se (> 98.8%) and Sp (> 99.1%) across two bead coupling scales and correlations with nAb responses that were similar to blood-based SARS-CoV-2 IgG ELISA data. This non-invasive salivary SARS-CoV-2 IgG MIA could increase engagement of vulnerable populations and improve broad understanding of humoral immunity (kinetics and gaps) within the evolving context of booster vaccination, viral variants and waning immunity.

Detecting Liver Cancer Using Cell-Free DNA Fragmentomes

Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

SIGNIFICANCE

There is a great need for accessible and sensitive screening approaches for HCC worldwide. We have developed an approach for examining genome-wide cfDNA fragmentation features to provide a high-performing and cost-effective approach for liver cancer detection. See related commentary Rolfo and Russo, p. 532. This article is highlighted in the In This Issue feature, p. 517.

Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease

BACKGROUND

Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD).

METHODS

Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (p_FDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (p_FDR < 0.05) with an imaging outcome (N = 1638).

RESULTS

In the fully adjusted model, three lipid modules were associated with a brain volume measure (p_FDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß =  - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß =  - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (p_FDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction.

CONCLUSIONS

Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.

Transfusing Convalescent Plasma as Post-Exposure Prophylaxis Against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Double-Blinded, Phase 2 Randomized, Controlled Trial

BACKGROUND

The efficacy of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) convalescent plasma (CCP) for preventing infection in exposed, uninfected individuals is unknown. CCP might prevent infection when administered before symptoms or laboratory evidence of infection.

METHODS

This double-blinded, phase 2 randomized, controlled trial (RCT) compared the efficacy and safety of prophylactic high titer (≥1:320 by Euroimmun ELISA) CCP with standard plasma. Asymptomatic participants aged ≥18 years with close contact exposure to a person with confirmed coronavirus disease 2019 (COVID-19) in the previous 120 hours and negative SARS-CoV-2 test within 24 hours before transfusion were eligible. The primary outcome was new SARS-CoV-2 infection.

RESULTS

In total, 180 participants were enrolled; 87 were assigned to CCP and 93 to control plasma, and 170 transfused at 19 sites across the United States from June 2020 to March 2021. Two were excluded for screening SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) positivity. Of the remaining 168 participants, 12/81 (14.8%) CCP and 13/87 (14.9%) control recipients developed SARS-CoV-2 infection; 6 (7.4%) CCP and 7 (8%) control recipients developed COVID-19 (infection with symptoms). There were no COVID-19-related hospitalizations in CCP and 2 in control recipients. Efficacy by restricted mean infection free time (RMIFT) by 28 days for all SARS-CoV-2 infections (25.3 vs 25.2 days; P = .49) and COVID-19 (26.3 vs 25.9 days; P = .35) was similar for both groups.

CONCLUSIONS

Administration of high-titer CCP as post-exposure prophylaxis, although appearing safe, did not prevent SARS-CoV-2 infection.

CLINICAL TRIALS REGISTRATION

NCT04323800.

Pathogen exposure misclassification can bias association signals in GWAS of infectious diseases when using population-based common control subjects

Genome-wide association studies (GWASs) have been performed to identify host genetic factors for a range of phenotypes, including for infectious diseases. The use of population-based common control subjects from biobanks and extensive consortia is a valuable resource to increase sample sizes in the identification of associated loci with minimal additional expense. Non-differential misclassification of the outcome has been reported when the control subjects are not well characterized, which often attenuates the true effect size. However, for infectious diseases the comparison of affected subjects to population-based common control subjects regardless of pathogen exposure can also result in selection bias. Through simulated comparisons of pathogen-exposed cases and population-based common control subjects, we demonstrate that not accounting for pathogen exposure can result in biased effect estimates and spurious genome-wide significant signals. Further, the observed association can be distorted depending upon strength of the association between a locus and pathogen exposure and the prevalence of pathogen exposure. We also used a real data example from the hepatitis C virus (HCV) genetic consortium comparing HCV spontaneous clearance to persistent infection with both well-characterized control subjects and population-based common control subjects from the UK Biobank. We find biased effect estimates for known HCV clearance-associated loci and potentially spurious HCV clearance associations. These findings suggest that the choice of control subjects is especially important for infectious diseases or outcomes that are conditional upon environmental exposures.

Evaluation of a pilot emergency department linkage to care program for patients previously diagnosed with Hepatitis C

There is a significant number of Emergency Department (ED) patients with known chronic hepatitis C virus (HCV) infection who have not been treated with directly acting antivirals. We implemented a pilot ED-based linkage-to-care program to address this need and evaluated the impact of the program using the HCV Care Continuum metrics. Between March 2015 and May 2016, dedicated patient care navigators identified HCV RNA-positive patients in an urban ED and offered expedited appointments with the on-site viral hepatitis clinic. Patient demographics and care continuum outcomes were abstracted from the EMR and analysed to determine significant factors influencing linkage-to-care (LTC) and treatment initiation rates. The ED linkage-to-care program achieved a 43% linkage-to-care rate (165/384), 22% treatment rate (84/384) and 16% sustained virologic response rate (63/384). Significant associations were found between linkage-to-care and increasing age (OR = 1.03), Medicare insurance (OR = 2.21) and having a primary care physician (PCP) (OR = 4.03). For patients who were linked, the odds of initiating treatment were also positively significantly associated with increasing age (OR = 1.04) and having a PCP (OR = 2.77). For patients who initiated treatment, the odds of sustained virologic response were marginally associated with having a PCP (OR = 4.92).Our ED linkage-to-care program utilized care coordination to successfully link nearly half of approached HCV RNA-positive patients to care. This design can be feasibly replicated by other EDs given limited non-clinical training required for linkage-to-care staff. Adoption of similar programs in other EDs may improve the rates of LTC and treatment initiation for previously diagnosed HCV patients.

Long COVID brain fog and muscle pain are associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute infection

The incidence of long COVID is substantial, even in people who did not require hospitalization for acute COVID-19. The pathobiological mechanisms of long COVID and the role of early viral kinetics in its development are largely unknown. Seventy-three non-hospitalized adult participants were enrolled within approximately 48 hours of their first positive SARS-CoV-2 RT-PCR test, and mid-turbinate nasal and saliva samples were collected up to 9 times within the first 45 days after enrollment. Samples were assayed for SARS-CoV-2 using RT-PCR and additional test results were abstracted from the clinical record. Each participant indicated the presence and severity of 49 long- COVID symptoms at 1-, 3-, 6-, 12-, and 18-months post-COVID-19 diagnosis. Time from acute COVID-19 illness onset to SARS-CoV-2 RNA clearance greater or less than 28 days was tested for association with the presence or absence of each of 49 long COVID symptoms at 90+ days from acute COVID-19 symptom onset. Brain fog and muscle pain at 90+ days after acute COVID-19 onset were negatively associated with viral RNA clearance within 28 days of acute COVID-19 onset with adjustment for age, sex, BMI ≥ 25, and COVID vaccination status prior to COVID-19 (brain fog: aRR 0.46, 95% CI 0.22-0.95; muscle pain: aRR 0.28, 95% CI 0.08-0.94). This work indicates that at least two long COVID symptoms - brain fog and muscle pain - at 90+ days from acute COVID-19 onset are specifically associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract.

A hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence construction for genetic analysis of HBV

Hepatitis B virus (HBV) remains a global public health concern, with over 250 million individuals living with chronic HBV infection (CHB) and no curative therapy currently available. Viral diversity is associated with CHB pathogenesis and immunological control of infection. Improved methods to characterize the viral genome at both the population and intra-host level could aid drug development efforts. Conventionally, HBV sequencing data are aligned to a linear reference genome and only sequences capable of aligning to the reference are captured for analysis. Reference selection has additional consequences, including sample-specific 'consensus' sequence construction. It remains unclear how to select a reference from available sequences and whether a single reference is sufficient for genetic analyses. Using simulated short-read sequencing data generated from full-length publicly available HBV genome sequences and HBV sequencing data from a longitudinally sampled individual with CHB, we investigate alternative graph-based alignment approaches. We demonstrate that using a phylogenetically representative 'genome graph' for alignment, rather than linear reference sequences, avoids issues of reference ambiguity, improves alignment, and facilitates the construction of sample-specific consensus sequences genetically similar to an individual's infection. Graph-based methods can therefore improve efforts to characterize the genetics of viral pathogens, including HBV, and may have broad implications in host pathogen research.

Modeling in higher dimensions to improve diagnostic testing accuracy: Theory and examples for multiplex saliva-based SARS-CoV-2 antibody assays

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the importance and challenges of correctly interpreting antibody test results. Identification of positive and negative samples requires a classification strategy with low error rates, which is hard to achieve when the corresponding measurement values overlap. Additional uncertainty arises when classification schemes fail to account for complicated structure in data. We address these problems through a mathematical framework that combines high dimensional data modeling and optimal decision theory. Specifically, we show that appropriately increasing the dimension of data better separates positive and negative populations and reveals nuanced structure that can be described in terms of mathematical models. We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics. We validate the usefulness of this approach in the context of a multiplex salivary SARS-CoV-2 immunoglobulin G assay dataset. This example illustrates how our analysis: (i) improves the assay accuracy, (e.g. lowers classification errors by up to 42% compared to CI methods); (ii) reduces the number of indeterminate samples when an inconclusive class is permissible, (e.g. by 40% compared to the original analysis of the example multiplex dataset) and (iii) decreases the number of antigens needed to classify samples. Our work showcases the power of mathematical modeling in diagnostic classification and highlights a method that can be adopted broadly in public health and clinical settings.

Incarceration, Inequality, and Hepatitis C Treatment: The Story of Two Southern States

Hepatitis C virus (HCV) infection causes liver-related morbidity/mortality and disproportionately affects people who are incarcerated and non-Hispanic Black populations, largely due to social and policy issues that contribute to poor health. With the advent of highly efficacious treatment, HCV is now curable. However, most states' departments of corrections do not offer universal HCV testing or treatment. Two southern states-Tennessee and Louisiana-provide examples of divergent approaches to addressing HCV infection. While Tennessee has offered treatment on a limited basis, resulting in a class action lawsuit, the state of Louisiana recently adopted a new approach. In establishing the 2019 Hepatitis Elimination Plan, the state created a standard of care for HCV infection that included robust testing and treatment in state prison facilities while capping costs. Louisiana has demonstrated the feasibility of HCV testing and treatment programs within state prisons, an important step towards achieving health equity.

The value of arterial spin labelling (ASL) perfusion MRI in the assessment of post-treatment progression in adult glioma: A systematic review and meta-analysis

Background

The distinction between viable tumor and therapy-induced changes is crucial for the clinical management of patients with gliomas. This study aims to quantitatively assess the efficacy of arterial spin labeling (ASL) biomarkers, including relative cerebral blood flow (rCBF) and absolute cerebral blood flow (CBF), for the discrimination of progressive disease (PD) and treatment-related effects.

Methods

Eight articles were included in the synthesis after searching the literature systematically. Data have been extracted and a meta-analysis using the random-effect model was subsequently carried out. Diagnostic accuracy assessment was also performed.

Results

This study revealed that there is a significant difference in perfusion measurements between groups with PD and therapy-induced changes. The rCBF yielded a standardized mean difference (SMD) of 1.25 [95% CI 0.75, 1.75] (p < .00001). The maximum perfusion indices (rCBFmax and CBFmax) both showed equivalent discriminatory ability, with SMD of 1.35 [95% CI 0.78, 1.91] (p < .00001) and 1.56 [95% CI 0.79, 2.33] (p < .0001), respectively. Similarly, accuracy estimates were comparable among ASL-derived metrices. Pooled sensitivities [95% CI] were 0.85 [0.67, 0.94], 0.88 [0.71, 0.96], and 0.93 [0.73, 0.98], and pooled specificities [95% CI] were 0.83 [0.71, 0.91], 0.83 [0.67, 0.92], 0.84 [0.67, 0.93], for rCBF, rCBFmax and CBFmax, respectively. Corresponding HSROC area under curve (AUC) [95% CI] were 0.90 [0.87, 0.92], 0.92 [0.89, 0.94], and 0.93 [0.90, 0.95].

Conclusion

These results suggest that ASL quantitative biomarkers, particularly rCBFmax and CBFmax, have the potential to discriminate between glioma progression and therapy-induced changes.

Long COVID brain fog and muscle pain are associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute infection

Introduction

The incidence of long COVID is substantial, even in people with mild to moderate acute COVID-19. The role of early viral kinetics in the subsequent development of long COVID is largely unknown, especially in individuals who were not hospitalized for acute COVID-19.

Methods

Seventy-three non-hospitalized adult participants were enrolled within approximately 48 hours of their first positive SARS-CoV-2 RT-PCR test, and mid-turbinate nasal and saliva samples were collected up to 9 times within the first 45 days after enrollment. Samples were assayed for SARS-CoV-2 using RT-PCR and additional SARS-CoV-2 test results were abstracted from the clinical record. Each participant indicated the presence and severity of 49 long COVID symptoms at 1-, 3-, 6-, 12-, and 18-months post-COVID-19 diagnosis. Time from acute COVID-19 illness onset to SARS-CoV-2 RNA clearance greater or less than 28 days was tested for association with the presence or absence of each of 49 long COVID symptoms at 90+ days from acute COVID-19 symptom onset.

Results

Self-reported brain fog and muscle pain at 90+ days after acute COVID-19 onset were negatively associated with viral RNA clearance within 28 days of acute COVID-19 onset with adjustment for age, sex, BMI ≥ 25, and COVID vaccination status prior to COVID-19 (brain fog: aRR 0.46, 95% CI 0.22-0.95; muscle pain: aRR 0.28, 95% CI 0.08-0.94). Participants reporting higher severity brain fog or muscle pain at 90+ days after acute COVID-19 onset were less likely to have cleared SARS-CoV-2 RNA within 28 days. The acute viral RNA decay trajectories of participants who did and did not later go on to experience brain fog 90+ days after acute COVID-19 onset were distinct.

Discussion

This work indicates that at least two long COVID symptoms - brain fog and muscle pain - at 90+ days from acute COVID-19 onset are specifically associated with prolonged time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute COVID-19. This finding provides evidence that delayed immune clearance of SARS-CoV-2 antigen or greater amount or duration of viral antigen burden in the upper respiratory tract during acute COVID-19 are directly linked to long COVID. This work suggests that host-pathogen interactions during the first few weeks after acute COVID-19 onset have an impact on long COVID risk months later.

Methodological approaches to optimize multiplex oral fluid SARS-CoV-2 IgG assay performance and correlation with serologic and neutralizing antibody responses

Background

Oral fluid (hereafter, saliva) is a non-invasive and attractive alternative to blood for SARS-CoV-2 IgG testing; however, the heterogeneity of saliva as a matrix poses challenges for immunoassay performance.

Objectives

To optimize performance of a magnetic microparticle-based multiplex immunoassay (MIA) for SARS-CoV-2 IgG measurement in saliva, with consideration of: i) threshold setting and validation across different MIA bead batches; ii) sample qualification based on salivary total IgG concentration; iii) calibration to U.S. SARS-CoV-2 serological standard binding antibody units (BAU); and iv) correlations with blood-based SARS-CoV-2 serological and neutralizing antibody (nAb) assays.

Methods

The salivary SARS-CoV-2 IgG MIA included 2 nucleocapsid (N), 3 receptor-binding domain (RBD), and 2 spike protein (S) antigens. Gingival crevicular fluid (GCF) swab saliva samples were collected before December, 2019 (n=555) and after molecular test-confirmed SARS-CoV-2 infection from 113 individuals (providing up to 5 repeated-measures; n=398) and used to optimize and validate MIA performance (total n=953). Combinations of IgG responses to N, RBD and S and total salivary IgG concentration (μg/mL) as a qualifier of nonreactive samples were optimized and validated, calibrated to the U.S. SARS-CoV-2 serological standard, and correlated with blood-based SARS-CoV-2 IgG ELISA and nAb assays.

Results

The sum of signal to cutoff (S/Co) to all seven MIA SARS-CoV-2 antigens and disqualification of nonreactive saliva samples with ≤15 μg/mL total IgG led to correct classification of 62/62 positives (sensitivity [Se]=100.0%; 95% confidence interval [CI]=94.8%, 100.0%) and 108/109 negatives (specificity [Sp]=99.1%; 95% CI=97.3%, 100.0%) at 8-million beads coupling scale and 80/81 positives (Se=98.8%; 95% CI=93.3%, 100.0%] and 127/127 negatives (Sp=100%; 95% CI=97.1%, 100.0%) at 20-million beads coupling scale. Salivary SARS-CoV-2 IgG crossed the MIA cutoff of 0.1 BAU/mL on average 9 days post-COVID-19 symptom onset and peaked around day 30. Among n=30 matched saliva and plasma samples, salivary SARS-CoV-2 MIA IgG levels correlated with corresponding-antigen plasma ELISA IgG (N: ρ=0.67, RBD: ρ=0.76, S: ρ=0.82; all p <0.0001). Correlations of plasma SARS-CoV-2 nAb assay area under the curve (AUC) with salivary MIA IgG (N: ρ=0.68, RBD: ρ=0.78, S: ρ=0.79; all p <0.0001) and with plasma ELISA IgG (N: ρ=0.76, RBD: ρ=0.79, S: ρ=0.76; p <0.0001) were similar.

Conclusions

A salivary SARS-CoV-2 IgG MIA produced consistently high Se (>98.8%) and Sp (>99.1%) across two bead coupling scales and correlations with nAb responses that were similar to blood-based SARS-CoV-2 IgG ELISA data. This non-invasive salivary SARS-CoV-2 IgG MIA could increase engagement of vulnerable populations and improve broad understanding of humoral immunity (kinetics and gaps) within the evolving context of booster vaccination, viral variants and waning immunity.

Prospects for Long-Acting Treatments for Hepatitis C

In 2019, more than 4 years after the widespread availability of safe, oral, curative treatments, an estimated 58 million people were living with hepatitis C virus infections (PLWHC). Additional tools may enable those not yet reached to be treated. One such tool could be long-acting parenteral formulations of HCV treatments, which may allow PLWHC to be diagnosed and cured in a single encounter. Although existing highly effective oral medications might be formulated as long-acting parenteral treatments, pharmacological, regulatory, patent, and medical challenges have to be overcome; this requires the concerted efforts of PLWHC, researchers, funding agencies, industry, the World Health Organization, and other stakeholders.

Long-Acting Treatments for Hepatitis B

There are an estimated 257 million persons living with chronic hepatitis B for whom there are multiple potential applications of long-acting antiviral compounds. Current efforts include both injection and implant approaches to formulating derivates of existing anti-HBV compounds such as tenofovir or entecavir. Substantial progress has already occurred especially as aligned with the development of long-acting tenofovir-based medications with dual activity against human immunodeficiency virus (HIV) and hepatitis B virus (HBV). Nonetheless, substantial challenges will need to be overcome before these agents are available.

What Clinicians Need to Know About the Development of Long-Acting Formulations

We encourage readers of this Supplement to find articles that are relevant to the current and future practice of infectious diseases medicine. Access to long-acting products and formulations in low- and middle-income countries remains a key determinant of the impact of these advances on global health.

Recent Technical Developments in ASL: A Review of the State of the Art

This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple-timepoint ASL, body ASL, and clinical ASL recommendations.

HIV and liver disease: a comprehensive update

Despite substantial advances in the field, liver disease morbidity and mortality remain serious issues among people with HIV. The causes of liver disease are often multifactorial and include hepatitis viruses, hepatic steatosis and oxidative stress, bacterial translocation with activation of hepatic macrophages and stellate cells, and direct toxicities from alcohol and drugs of abuse. Biopsychosocial factors including a high prevalence of psychiatric disorders, food insecurity, insufficient access to care and medications, and social stigma all play roles in the persistence of liver injury and hepatic fibrosis development among people with HIV. Rising rates of hepatocellular carcinoma have been observed, suggesting that the epidemiology of liver disease is evolving.

ASL-BIDS, the brain imaging data structure extension for arterial spin labeling

Arterial spin labeling (ASL) is a non-invasive MRI technique that allows for quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. There is a strong need for standardization of ASL data storage, including acquisition metadata. Recently, ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. Discussed are the structure of the ASL data, focussing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. We anticipate that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Investigating changes in blood-cerebrospinal fluid barrier function in a rat model of chronic hypertension using non-invasive magnetic resonance imaging

Chronic hypertension is a major risk factor for the development of neurodegenerative disease, yet the etiology of hypertension-driven neurodegeneration remains poorly understood. Forming a unique interface between the systemic circulation and the brain, the blood-cerebrospinal fluid barrier (BCSFB) at the choroid plexus (CP) has been proposed as a key site of vulnerability to hypertension that may initiate downstream neurodegenerative processes. However, our ability to understand BCSFB's role in pathological processes has, to date, been restricted by a lack of non-invasive functional measurement techniques. In this work, we apply a novel Blood-Cerebrospinal Fluid Barrier Arterial Spin Labeling (BCSFB-ASL) Magnetic resonance imaging (MRI) approach with the aim of detecting possible derangement of BCSFB function in the Spontaneous Hypertensive Rat (SHR) model using a non-invasive, translational technique. SHRs displayed a 36% reduction in BCSFB-mediated labeled arterial water delivery into ventricular cerebrospinal fluid (CSF), relative to normotensive controls, indicative of down-regulated choroid plexus function. This was concomitant with additional changes in brain fluid biomarkers, namely ventriculomegaly and changes in CSF composition, as measured by T1 lengthening. However, cortical cerebral blood flow (CBF) measurements, an imaging biomarker of cerebrovascular health, revealed no measurable change between the groups. Here, we provide the first demonstration of BCSFB-ASL in the rat brain, enabling non-invasive assessment of BCSFB function in healthy and hypertensive rats. Our data highlights the potential for BCSFB-ASL to serve as a sensitive early biomarker for hypertension-driven neurodegeneration, in addition to investigating the mechanisms relating hypertension to neurodegenerative outcomes.

Optimal decision theory for diagnostic testing: Minimizing indeterminate classes with applications to saliva-based SARS-CoV-2 antibody assays

In diagnostic testing, establishing an indeterminate class is an effective way to identify samples that cannot be accurately classified. However, such approaches also make testing less efficient and must be balanced against overall assay performance. We address this problem by reformulating data classification in terms of a constrained optimization problem that (i) minimizes the probability of labeling samples as indeterminate while (ii) ensuring that the remaining ones are classified with an average target accuracy X. We show that the solution to this problem is expressed in terms of a bathtub-type principle that holds out those samples with the lowest local accuracy up to an X-dependent threshold. To illustrate the usefulness of this analysis, we apply it to a multiplex, saliva-based SARS-CoV-2 antibody assay and demonstrate up to a 30 % reduction in the number of indeterminate samples relative to more traditional approaches.