A rapid and flexible microneutralization assay for serological assessment of influenza viruses.

BACKGROUND: Serological responses from influenza vaccination or infection are typically measured by hemagglutinin inhibition (HAI) or microneutralization (MN). Both methods are limited in feasibility, standardization, and generalizability to recent strains. We developed a luciferase MN (LMN) assay that combines the advantages of the conventional MN assay with the ease of the HAI assay. METHODS: Sera were obtained from the HIVE study, a Michigan household cohort. Reverse genetics was used to generate recombinant influenza viruses expressing the hemagglutinin and neuraminidase of test strains, all other viral proteins from an A/WSN/1933 backbone, and a NanoLuc reporter. Serum neutralization of luciferase-expressing targets was quantified as a reduction in light emission from infected cells. Neutralization titers were measured for cell- and egg-adapted versions of A/Hong Kong/4801/2014 and A/Singapore/INFIMH-16-0019/2016 and compared to HAI titers against egg-grown antigens. RESULTS: Three hundred thirty-three sera were collected from 259 participants between May 2016 and July 2018. Sampled participants were 7-68 years of age, and >80% were vaccinated against influenza. HAI and LMN titers were correlated for A/Hong Kong/4801/2014 (ρ = 0.52, p ≤ 0.01) and A/Singapore/INFIMH-16-0019/2016 (ρ = 0.79, p ≤ 0.01). LMN titers were lower for cell strains compared to egg strains (A/Hong Kong/4801/2014 mean log2 fold change = -2.66, p ≤ 0.01 and A/Singapore/INFIMH-16-0019/2016 mean log2 fold change = -3.15, p ≤ 0.01). CONCLUSIONS: The LMN assay was feasible using limited sample volumes and able to differentiate small antigenic differences between egg-adapted and cell-derived strains. The correspondence of these results with the commonly used HAI confirms the utility of this assay for high-throughput studies of correlates of protection and vaccine response.

Trans-Ethnic Meta-Analysis of Interactions Between Genetics and Early-Life Socioeconomic Context on Memory Performance and Decline in Older Americans.

BACKGROUND: Later-life cognitive function is influenced by genetics as well as early- and later-life socioeconomic context. However, few studies have examined the interaction between genetics and early childhood factors. METHODS: Using gene-based tests (interaction sequence kernel association test [iSKAT]/iSKAT optimal unified test), we examined whether common and/or rare exonic variants in 39 gene regions previously associated with cognitive performance, dementia, and related traits had an interaction with childhood socioeconomic context (parental education and financial strain) on memory performance or decline in European ancestry (EA, N = 10 468) and African ancestry (AA, N = 2 252) participants from the Health and Retirement Study. RESULTS: Of the 39 genes, 22 in EA and 19 in AA had nominally significant interactions with at least one childhood socioeconomic measure on memory performance and/or decline; however, all but one (father's education by solute carrier family 24 member 4 [SLC24A4] in AA) were not significant after multiple testing correction (false discovery rate [FDR] < .05). In trans-ethnic meta-analysis, 2 genes interacted with childhood socioeconomic context (FDR < .05): mother's education by membrane-spanning 4-domains A4A (MS4A4A) on memory performance, and father's education by SLC24A4 on memory decline. Both interactions remained significant (p < .05) after adjusting for respondent's own educational attainment, apolipoprotein-ε4 allele (APOE ε4) status, lifestyle factors, body mass index, and comorbidities. For both interactions in EA and AA, the genetic effect was stronger in participants with low parental education. CONCLUSIONS: Examination of common and rare variants in genes discovered through genome-wide association studies shows that childhood context may interact with key gene regions to jointly impact later-life memory function and decline. Genetic effects may be more salient for those with lower childhood socioeconomic status.

Severe Acute Respiratory Syndrome Coronavirus 2 Total and Subgenomic RNA Viral Load in Hospitalized Patients.

BACKGROUND: Previous studies demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be detected for weeks after infection. The significance of this finding is unclear and, in most patients, does not represent active infection. Detection of subgenomic RNA has been proposed to represent productive infection and may be a useful marker for monitoring infectivity. METHODS: We used quantitative reverse-transcription polymerase chain reaction (RT-qPCR) to quantify total and subgenomic nucleocapsid (sgN) and envelope (sgE) transcripts in 185 SARS-CoV-2-positive nasopharyngeal swab samples collected on hospital admission and to relate to symptom duration. RESULTS: We find that all transcripts decline at the same rate; however, sgE becomes undetectable before other transcripts. The median duration of symptoms to a negative test is 14 days for sgE and 25 days for sgN. There is a linear decline in subgenomic compared to total RNA, suggesting that subgenomic transcript copy number is dependent on copy number of total transcripts. The mean difference between total and sgN is 16-fold and the mean difference between total and sgE is 137-fold. This relationship is constant over duration of symptoms, allowing prediction of subgenomic copy number from total copy number. CONCLUSIONS: Subgenomic RNA may be no more useful in determining infectivity than a copy number threshold determined for total RNA.

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts.

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

SARS-CoV-2 Total and Subgenomic RNA Viral Load in Hospitalized Patients.

Understanding viral load in patients infected with SARS-CoV-2 is critical to epidemiology and infection control. Previous studies have demonstrated that SARS-CoV-2 RNA can be detected for many weeks after symptom onset. The clinical significance of this finding is unclear and, in most patients, likely does not represent active infection. There are, however, patients who shed infectious virus for weeks. Detection of subgenomic RNA transcripts expressed by SARS-CoV-2 has been proposed to represent productive infection and may be a tractable marker for monitoring infectivity. Here, we use RT-PCR to quantify total and subgenomic nucleocapsid (N) and envelope (E) transcripts in 190 SARS-CoV-2 positive samples collected on hospital admission. We relate these findings to duration of symptoms. We find that all transcripts decline at the same rate; however, subgenomic E becomes undetectable before other transcripts. In Kaplan-Meier analysis the median duration of symptoms to a negative test is 14 days for sgE and 25 days for sgN. There is a linear decline in subgenomic RNA compared to total RNA suggesting subgenomic transcript copy number is highly dependent on copy number of total transcripts. The mean difference between total N and subgenomic N is 16-fold (4.0 cycles) and the mean difference between total E and sub-genomic E is 137-fold (7.1 cycles). This relationship is constant over duration of symptoms allowing prediction of subgenomic copy number from total copy number. Although Subgenomic E is undetectable at a time that may more closely reflect the duration of infectivity, its utility in determining active infection may be no more useful than a copy number threshold determined for total transcripts.

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts.

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

Association Between Episodic Memory and Genetic Risk Factors for Alzheimer's Disease in South Asians from the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD).

BACKGROUND/OBJECTIVES: Genetic factors play an important role in Alzheimer's disease (AD) and cognitive aging. However, it is unclear whether risk loci identified in European ancestry (EA) populations have similar effects in other groups, such as South Asians. DESIGN: We investigated the allelic distribution and cognitive associations of 56 known AD risk single-nucleotide polymorphisms (SNPs) identified from three EA genome-wide association studies (EA-GWASs) in a South Asian population. Single SNP and genetic risk score (GRS) associations with measures of episodic memory were assessed. SETTING: The Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD). PARTICIPANTS: A total of 906 LASI-DAD participants from diverse states in India. MEASUREMENTS: Participants were genotyped using the Illumina Global Screening Array and imputed with 1000G Phase 3v5. Cognitive measures included total learning and delayed word recall. RESULTS: Although only a few SNPs were significantly associated with memory scores (P < .05), effect estimates from the EA-GWAS and the LASI-DAD showed moderate correlation (0.35-0.88) in the expected direction. GRSs were also associated with memory scores, although percentage variation explained was small (0.1%-0.6%). CONCLUSIONS: Discrepancies in allele frequencies and cognitive association results suggest that genetic factors found predominantly through EA-GWASs may play a limited role in South Asians. However, the extent of differences in the genetic architecture of AD and cognition in EA and South Asians remains uncertain. There is also a critical need to perform a more comprehensive assessment of the mutational spectrum of South Asia to identify novel genetic variants associated with AD and cognition in this population. J Am Geriatr Soc 68:S45-S53, 2020.