Showing papers by "Kaya Bilguvar published in 2022"

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

Abstract: Significance There is growing evidence that preexisting autoantibodies neutralizing type I interferons (IFNs) are strong determinants of life-threatening COVID-19 pneumonia. It is important to estimate their quantitative impact on COVID-19 mortality upon SARS-CoV-2 infection, by age and sex, as both the prevalence of these autoantibodies and the risk of COVID-19 death increase with age and are higher in men. Using an unvaccinated sample of 1,261 deceased patients and 34,159 individuals from the general population, we found that autoantibodies against type I IFNs strongly increased the SARS-CoV-2 infection fatality rate at all ages, in both men and women. Autoantibodies against type I IFNs are strong and common predictors of life-threatening COVID-19. Testing for these autoantibodies should be considered in the general population.

Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA

Abstract: •SARS-CoV-2 Delta variant emerges 1.37–2.63 times faster than Alpha (state range)•Delta is on average 63%–167% more transmissible than Alpha (state range)•Delta infections average 6.2 times more viral RNA copies per milliliter than Alpha•Variant transmissibility estimates depend on innate, population, and data factors The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%–80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant’s respective emergence period, finding that Delta emerged 1.37–2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%–167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1–10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta’s enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability. The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%–80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant’s respective emergence period, finding that Delta emerged 1.37–2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%–167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1–10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta’s enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability. The evolution and emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants associated with increased transmissibility, more severe disease, and/or decreased vaccine effectiveness continue to exacerbate the coronavirus disease 2019 (COVID-19) pandemic.1CDCSARS-CoV-2 variant classifications and definitions.https://www.cdc.gov/coronavirus/2019-ncov/variants/variant-info.htmlDate: 2021Google Scholar A SARS-CoV-2 variant is a virus with a defining set of mutations that distinguishes it from viruses belonging to other lineages.2Lauring A.S. Hodcroft E.B. Genetic variants of SARS-CoV-2—what do they mean?.JAMA. 2021; 325: 529-531Google Scholar In particular, two SARS-CoV-2 variants with enhanced transmissibility substantially altered the pandemic’s trajectory: Alpha (B.1.1.7 lineage) and Delta (B.1.617.2 and AY.x sub-lineages). Alpha, defined in part by a N501Y amino acid substitution in the spike gene receptor binding domain that may affect ACE2 binding, was first detected in the United Kingdom in late 2020 and became the dominant global variant by early 2021.3Rambaut A. Loman N. Pybus O. Barclay W. Barrett J. Carabelli A. Connor T. Peacock T. Robertson D.L. Volz E. et al.Preliminary genomic characterisation of an emergent SARS-CoV-2 lineage in the UK defined by a novel set of spike mutations.https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563Date: 2020Google Scholar, 4Alpert T. Brito A.F. Lasek-Nesselquist E. Rothman J. Valesano A.L. MacKay M.J. Petrone M.E. Breban M.I. Watkins A.E. Vogels C.B.F. et al.Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States.Cell. 2021; 184: 2595-2604.e13Google Scholar, 5Tao K. Tzou P.L. Nouhin J. Gupta R.K. de Oliveira T. Kosakovsky Pond S.L. Fera D. Shafer R.W. The biological and clinical significance of emerging SARS-CoV-2 variants.Nat. Rev. Genet. 2021; 22: 757-773Google Scholar Delta, containing the spike L452R and P681H mutations (in the receptor binding domain and near the furin cleavage site, respectively) that may affect antibody recognition, was first recognized in India in early 2021 and displaced Alpha as the dominant variant by mid-2021.5Tao K. Tzou P.L. Nouhin J. Gupta R.K. de Oliveira T. Kosakovsky Pond S.L. Fera D. Shafer R.W. The biological and clinical significance of emerging SARS-CoV-2 variants.Nat. Rev. Genet. 2021; 22: 757-773Google Scholar This shift led to a significant resurgence in COVID-19 cases in many countries.6CDCDelta variant: what we know about the science.https://www.cdc.gov/coronavirus/2019-ncov/variants/delta-variant.htmlDate: 2021Google Scholar, 7WHOWeekly Epidemiological Update on COVID-19 - 20 July 2021. WHO, 2021Google Scholar, 8Bolze A. Cirulli E.T. Luo S. White S. Cassens T. Jacobs S. Ngyuyen J. Ramirez J.M. Sandoval E. Wang X. et al.Rapid displacement of SARS-CoV-2 variant B.1.1.7 by B.1.617.2 and P.1 in the United States [Internet].medRxiv. 2021; (Preprint at bioRxiv)http://medrxiv.org/lookup/doi/10.1101/2021.06.20.21259195Google Scholar, 9Challen R. Dyson L. Overton C.E. Guzman-Rincon L.M. Hill E.M. Stage H.B. Brooks-Pollok E. Pellis L. Scarabel F. Pascall D.J. et al.Early epidemiological signatures of novel SARS-CoV-2 variants: establishment of B.1.617.2 in England [Internet].medRxiv. 2021; (Preprint at bioRxiv)http://medrxiv.org/lookup/doi/10.1101/2021.06.05.21258365Google Scholar Transmission rates can be affected by two main factors: innate attributes of the variant itself and the specific population in which it spreads. Variant-associated attributes may lead to innately increased transmissibility (e.g., increased viral loads, longer infection duration, decreased infectious doses).10Grubaugh N.D. Hodcroft E.B. Fauver J.R. Phelan A.L. Cevik M. Public health actions to control new SARS-CoV-2 variants.Cell. 2021; https://www.cell.com/cell/fulltext/S0092-8674(21)00087-8?dgcid=raven_jbs_aip_emailGoogle Scholar The rapid spread of Delta in many locations around the world suggests that it is innately more transmissible than Alpha and other SARS-CoV-2 variants. However, estimates of Delta’s transmissibility may also vary among populations because of differences in underlying immunity, control measures, behaviors, and demographics. For example, a variant that is more likely to cause vaccine breakthroughs may have a larger observed transmissibility advantage in populations with higher vaccination rates because it can spread to more individuals. In addition, the quality and volume of data generated by sequencing programs in different locations can influence estimates. Studies conducted in the United Kingdom estimated that Delta is 40%–80% more transmissible than Alpha, which itself was more transmissible than the SARS-CoV-2 lineages previously in circulation.11SAGESPI-M-O: Summary of Further Modelling of Easing Restrictions – Roadmap Step 4 on 19 July 2021, 7 July. GOV.UK, 2021Google Scholar The World Health Organization similarly estimated a 55% increase in Delta transmissibility on the basis of data from India and the United Kingdom.12Campbell F. Archer B. Laurenson-Schafer H. Jinnai Y. Konings F. Batra N. Pavlin B. Vandemaele K. Van Kerkhove M.D. Jombart T. et al.Increased transmissibility and global spread of SARS-CoV-2 variants of concern as at June 2021.Euro Surveill. 2021; https://doi.org/10.2807/1560-7917.ES.2021.26.24.2100509Google Scholar To understand whether these estimates are applicable elsewhere, it is critical to compare the relative transmissibility of SARS-CoV-2 variants in different locations to test the sensitivity of estimates to population-specific conditions. Accurate variant transmissibility estimates enable us to begin exploring drivers of transmissibility differences between populations. In this study, we posed several important questions that arose with Delta: (1) how much more transmissible was Delta than Alpha, (2) what was the range in relative transmissibility estimates across states, and (3) was Delta more transmissible because it caused higher viral loads during infection? To investigate each, we partnered with SARS-CoV-2 genomic surveillance programs from all six New England states: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont. Using logistic growth rates and estimated effective reproductive numbers,4Alpert T. Brito A.F. Lasek-Nesselquist E. Rothman J. Valesano A.L. MacKay M.J. Petrone M.E. Breban M.I. Watkins A.E. Vogels C.B.F. et al.Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States.Cell. 2021; 184: 2595-2604.e13Google Scholar,13Petrone M.E. Rothman J.E. Breban M.I. Ott I.M. Russell A. Lasek-Nesselquist E. Kelly K. Omerza G. Renzette N. Watkins A.E. et al.Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 lineages.medRxiv. 2021; (Preprint at)https://doi.org/10.1101/2021.07.01.21259859Google Scholar,14Davies N.G. Abbott S. Barnard R.C. Jarvis C.I. Kucharski A.J. Munday J.D. Pearson C.A.B. Russell T.W. Tully D.C. Washburne A.D. et al.Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England.Science. 2021; : 372https://doi.org/10.1126/science.abg3055Google Scholar we found that Delta was consistently more transmissible than Alpha, but the relative difference varied across states. Furthermore, we found on average 6.2 (95% confidence interval [CI] 3.1–10.9) times more viral RNA copies per milliliter from samples collected from Delta infections compared with Alpha infections during their respective emergence periods, supporting the hypothesis that Delta may be more transmissible because it generates higher viral loads. Overall, we estimated that Delta is 63%–167% more transmissible than Alpha (range across states). Our data indicated that the overall transmission advantage of Delta may in part be attributed to its innate ability to enhance infections and that the range in estimates between populations may be driven by differences in underlying characteristics and sequencing data availability. In response to emerging SARS-CoV-2 variants, all states within the New England region of the United States (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont) increased their virus sequencing capacity through local and regional partnerships (Figure 1A ). From early April to mid-July 2021, at least 5% of the weekly reported COVID-19 cases were being sequenced from each state (with the exception of 7 days in June for New Hampshire and 10 days for Vermont when daily mean coverage dropped to 4% and 2%, respectively). The maximum daily sequencing coverage ranged from 16% (New Hampshire) to 46% (Maine). From these state-level sequencing data, we tracked the frequencies of the SARS-CoV-2 Alpha variant (B.1.1.7 lineage), the Delta variant (B.1.617.2 and AY.x sub-lineages), and all other lineages (Figure 1B). We observed similar trajectories in variant frequencies, with other lineages declining as Alpha increased in March and April 2021. Beginning in June 2021, Delta rapidly displaced the Alpha and other lineages. We also observed that the emergence of Delta resulted in a “selective sweep” and more fully dominated the variant landscape compared with Alpha. By the final week in July 2021, Delta constituted the vast majority of sequenced samples in all states (range 94%–100%). In contrast, although Alpha was the main variant in early 2021, we still observed other lineages maintained in the population. Although Delta rose to dominance within several months of its emergence (Figure 1), it was unknown how quickly it emerged relative to Alpha in different populations. We addressed this knowledge gap by comparing the initial growth rates of Delta and Alpha across New England. As Alpha and Delta emerged at different times, we defined their emergence periods as the 90 days following their initial detection in each state (Figure 2A ). We then estimated the logistic growth rate of Alpha and Delta during their respective state-specific emergence periods (Figure 2B). We found that Delta emerged faster than Alpha despite higher vaccination rates during mid-2021. Although Alpha appeared to initially outpace Delta, as indicated by its steeper growth curve during the early emergence period (Figure 2B), we hypothesized that this was due to gaps in surveillance programs that impeded detection of Alpha but were addressed before Delta emerged. In some states, the predicted probability of a given sequence belonging to Alpha is non-zero at the time of first phylogenetic detection, providing further support for this hypothesis. As noted previously (Figure 1A), sequencing coverage improved over time in all states as incident cases declined. The probability of a given sequenced sample belonging to Alpha at the start of its emergence period was 11% in Vermont, 8% in Connecticut, and between 1% and 2% in the remaining states, indicating that Alpha likely was circulating for some time before its first detection (Figure 2B). In contrast, the probability of a given sequenced sample belonging to Delta was 0% at the start of the emergence period in all states. We estimated that the logistic growth rate for Delta was 2.63 times greater than Alpha in Vermont, 2.51 times greater in Connecticut, 1.98 times greater in Rhode Island, 1.95 times greater in Maine, 1.75 times greater in New Hampshire, and 1.37 times greater in Massachusetts (Figure 2C). From the first sequenced detection, it took Delta on average 71 days (range across states 54–92 days) to become dominant (to surpass 50% predicted frequency; Figure 2B). Given that the Alpha and Delta variants circulating across New England were intermixed, the differences in the growth rates between states are likely due in part to population-specific factors. As an initial exploration, we compared the increase in the logistic growth rate for Delta versus Alpha with the vaccination rates or estimated infections (Figure 2A) per state at the start of the Delta emergence period. We noted an association between the relative emergence speed of Delta with state vaccination rates; however, states with earlier Delta detection dates, such as Massachusetts, necessarily have lower vaccination rates during the Delta emergence period. We did not note an association between the relative emergence speed of Delta and estimated infections per 100,000 population in each state. Finally, we performed a sensitivity analysis varying the emergence period by ±30 days from the selected 90 day emergence period (Figure S1; Table S4). Using a 60 day emergence period, Delta emerged 1.30–1.57 times faster (range across states) in all states except Maine and New Hampshire, where Alpha emerged 2.33 and 4.55 times faster than Delta, respectively. Using a 120 day emergence period, Delta emerged 1.97–3.30 times faster (range across states). We showed that Delta emerged faster in New England than Alpha had previously (Figure 2) and rose to higher levels of dominance, almost completely displacing Alpha and other lineages (Figure 1). However, we still do not know how much more transmissible Delta was than Alpha when they were co-circulating and the extent to which our estimates varied across. To answer this question, we adapted our previously developed framework to estimate the variant-specific effective reproductive number (Rt) from inferred SARS-CoV-2 infections.13Petrone M.E. Rothman J.E. Breban M.I. Ott I.M. Russell A. Lasek-Nesselquist E. Kelly K. Omerza G. Renzette N. Watkins A.E. et al.Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 lineages.medRxiv. 2021; (Preprint at)https://doi.org/10.1101/2021.07.01.21259859Google Scholar,15Chitwood M.H. Russi M. Gunasekera K. Havumaki J. Klaassen F. Pitzer V.E. Salomon J.A. Smartwood N.A. Warren J.L. Weinberger D.M. et al.Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: results of a Bayesian evidence synthesis model.medRxiv. 2021; (Preprint at)https://doi.org/10.1101/2020.06.17.20133983Google Scholar Our Rt estimates for each variant approximate the time-varying average number of secondary cases from a primary infection within a population. Rt estimates greater than 1 imply that COVID-19 cases associated with variants will increase in the future. We report the length of the Alpha/Delta co-circulation period (STAR Methods) and estimated mean Alpha and Delta infections per 100,000 population during the co-circulation period for each state (Figure S2A). We computed Rt for each variant category during January to August 2021 (Figure 3A ) by combining the frequency estimates from our genomic surveillance data (Figure 1B) with daily estimated SARS-CoV-2 infections (Figure 2A). Specifically, we used a multi-step bootstrapped sampling approach to generate 1,000 samples containing the estimated number of variant-specific infections. Our approach is further detailed in STAR Methods. Delta had Rt > 1 for the majority of the time period following its emergence, which exceeded the Rt estimates for Alpha and other lineages (Figure 3). Our mean Rt estimates for other lineages was <1 for all states, ranging from 0.87 to 0.91. Prior to the emergence of Delta, our mean Rt for Alpha was 1.20 across states, dropping to a mean of 0.78 as vaccination increased during the period following Delta’s emergence. Our mean Rt estimate for Delta was 1.40, ranging from 1.27 (New Hampshire) to 1.65 (Vermont). We found that the Rt for Delta exceeded that of Alpha in all states for the majority of the time following its initial detection (Figure 3B). We then estimated that the mean Rt ratio of Delta to Alpha during their co-circulation period was 2.67 in Vermont, 2.04 in Maine, 1.92 in New Hampshire, 1.83 in Rhode Island, 1.78 in Connecticut, and 1.63 in Massachusetts, suggesting that Delta was 63%–167% more transmissible on average than Alpha (range across states). In addition, separately for Delta and Alpha, we calculated the multiplicative increase in Rt, another measure of relative transmissibility (Figure S3).14Davies N.G. Abbott S. Barnard R.C. Jarvis C.I. Kucharski A.J. Munday J.D. Pearson C.A.B. Russell T.W. Tully D.C. Washburne A.D. et al.Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England.Science. 2021; : 372https://doi.org/10.1126/science.abg3055Google Scholar For this estimate, we exponentiated the coefficients from the binomial logistic regression and multiplied them by the mean generation interval to estimate the change in the probability of a given sequence belonging to a lineage over a generation interval. The multiplicative increase in Rt for Delta was greater than that for Alpha in all states. Across states, we observed a mean 1.30 increase in the probability of a sample belonging to Alpha over a generation interval, compared with 1.69 for Delta. Our multiplicative increase in Rt estimates suggests that Delta had the greatest advantage in Maine (1.99-fold increase) and the lowest advantage in Massachusetts (1.45-fold) (Figure 3C). Differences in transmissibility estimates between states may be due to a combination of viral, underlying population, and data factors that are further described in the Discussion. One potential mechanism for Delta’s increased transmissibility relative to Alpha (Figures 2 and 3) is that infections with the Delta variant could lead to higher virus titers than those with Alpha. To test this hypothesis, we compared the qRT-PCR cycle threshold (CT) values of sequence-confirmed Alpha and Delta infections (anterior nares or nasopharyngeal swabs) available from four institutes in New England: Yale University (Connecticut), Jackson Laboratory (Connecticut), Mass General Brigham (Massachusetts), and the Health and Environmental Testing Laboratory (Maine) (Figure 4). PCR CT values are a metric of virus RNA copies, and lower CT values indicate that there are more copies. We consistently found lower CT values for Delta infections across all institutes, but some comparisons did not yield significant differences. Importantly, PCR CT values from cross-sectional tests can be biased by the epidemic period because viral loads are dynamic and tend to decrease with time.18Hay J.A. Kennedy-Shaffer L. Kanjilal S. Lennon N.J. Gabriel S.B. Lipsitch M. Mina M.J. Estimating epidemiologic dynamics from cross-sectional viral load distributions.Science. 2021; 373: eabh0635Google Scholar During the emergence phase of an epidemic, most PCR tests come from recent infections, whereas the opposite is true when the epidemic is declining. The result is that PCR CT values could be higher (meaning less virus detected) during the declining phase even though the infection dynamics are the same throughout the epidemic. We first investigated if variant-specific PCR CT values change during different epidemic phases by running a one-way ANOVA for Alpha and Delta samples (separately) generated by one of the institutes (Yale University) to test for significant differences between monthly mean CT values (Figures S4A and S4B). We found a significant difference for only the Alpha samples. Using a post hoc Tukey’s honestly significant difference (HSD) test to investigate pairwise differences in monthly CT values while controlling for the experiment-wise error rate, we found that for the Alpha samples, there was a significant difference only for March versus April. If the epidemic phase were affecting our mean monthly CT values, we would expect higher CT values (corresponding to lower viral loads) for April versus March, as April is further in the declining phase of Alpha. We observe the opposite, providing further support for our previous finding that we did not observe evidence of an epidemic phase effect on our monthly CT values. Still, to account for any effects that the epidemic period may have on our comparisons, we limited our analysis to the approximate emergence phase of each variant: January to March 2021 for Alpha and June to August for Delta. Furthermore, the PCR CT data that we used from the four institutes are from different assays and some target different genes (though most target the nucleocapsid [N] gene). The Yale University data are from the N1 primer/probe set (originally from the “Centers for Disease Control and Prevention [CDC] assay”) of a “research use only” assay17Vogels C.B.F. Breban M.I. Ott I.M. Alpert T. Petrone M.E. Watkins A.E. Kalinich C.C. Earnest R. Rothman J.E. deJesus J.G. et al.Multiplex qPCR discriminates variants of concern to enhance global surveillance of SARS-CoV-2.PLoS Biol. 2021; 19: e3001236Google Scholar; the Health and Environmental Testing Laboratory data are from the same N1 primer/probe set at Yale but from the OPTI SARS-CoV-2 RT-PCR Test; the Jackson Laboratory data are from the N gene primer/probe set of the TaqPath COVID-19 Combo Kit; and the Mass General Brigham data are from the envelope (E) and open reading frame 1a (ORF1a) gene primer/probe set of the Roche Cobas SARS-CoV-2 test. Therefore, we analyzed the PCR CT values independently for each institute and gene target. Assessing cross-sectional PCR data from the four institutes, we consistently found lower mean CT values (more viral RNA copies) from Delta compared with Alpha nasal swab samples (Figure 4). The differences were significant from the Yale University (p ≤ 0.0001) and Jackson Laboratory (p ≤ 0.001) data, but not from Mass General Brigham and the Health and Environmental Testing Laboratory (p > 0.05 for each). In addition, for the Yale University samples, we used a standardized PCR curve to translate the CT values into viral RNA copies per milliliter.19Vogels C.B.F. Brito A.F. Wyllie A.L. Fauver J.R. Ott I.M. Kalinich C.C. Petrone M.E. Casanovas-Massana A. Catherine Muenker M. Moore A.J. et al.Analytical sensitivity and efficiency comparisons of SARS-CoV-2 RT-qPCR primer-probe sets.Nat. Microbiol. 2020; 5: 1299-1305Google Scholar We found 6.2 (95% CI 3.1–10.9) times more RNA copies per milliliter (non-log scale) on average in Delta anterior nares swab samples compared with Alpha samples (Figure S4C). Thus, during their respective emergence periods, upper respiratory tract samples collected from individuals infected with Delta on average had higher viral copies than from Alpha infections, possibly contributing to enhanced transmissibility. An important limitation of this analysis is that viral load differences may change later in each variant’s epidemic trajectory as PCR tests increasingly come from less recent infections, and thus our findings are restricted to the respective emergence periods. We discuss our CT analysis limitations further in the Discussion. The SARS-CoV-2 variant Delta emerged across the United States in mid-2021, displacing previous variants, including Alpha. Assessing the variability in relative emergence growth rates and transmissibility estimates of Delta versus Alpha across different settings remains an important public health question. With more than 3 million SARS-CoV-2 genomes available in public repositories, large-scale and globally diverse assessments can be conducted. However, there is always a risk when analyzing diverse sources of data without input from the data submitters on possible sampling biases (e.g., targeted sequencing in certain settings or sub-state locations) that may not be apparent in the repositories. We directly partnered with SARS-CoV-2 genomic surveillance programs from all six states in the New England region of the United States (Figure 1) to confidently assess emergence growth rates and relative transmissibility at the state level. We found that the logistic growth rates (Figure 2) and effective reproductive numbers (Figure 3) of Delta were consistently greater than Alpha across all New England states, although there was variation among states. The estimated initial growth rates for Alpha and Delta could have been influenced by population factors that differed between each variant’s respective emergence period. At the time of Alpha’s emergence in January and February 2021, 0% of the population across New England was reported as being fully vaccinated (Figure 2A). In comparison, when Delta first emerged in March and April 2021, 18%–37% of the population was fully vaccinated. Estimated infections per 100,000 population were also substantially lower during Delta’s emergence period (Figure 2A). However, with rising vaccination rates, all of the states began relaxing capacity constraints from late February to late March 2021. States continued rolling back COVID-19 mitigation measures with the majority lifted by the end of May 2021, although some states maintained indoor masking for unvaccinated individuals.20BallotpediaDocumenting America’s path to recovery.https://ballotpedia.org/Documenting_America%27s_Path_to_RecoveryDate: 2021Google Scholar The emergence of Delta also occurred within the background of other variants, including Alpha (Figure 1B). Thus, the fitness landscape for SARS-CoV-2 variants may have changed dramatically during 2021, potentially playing out differently across the states and explaining the large range in relative growth rates between Delta and Alpha (Figure 2C). Finally, the initial growth rates are sensitive to the length of the emergence period (Figure S1). We found consistently faster relative growth rates for Delta versus Alpha when using a longer emergence period (120 days instead of 90 days) but had mixed findings when using a shorter emergence period (60 days instead of 90 days) (Table S4). Shorter emergence periods may exacerbate the potential aforementioned biases in surveillance between Alpha and Delta, leading to more variable results. This underscores the importance of understanding the sequencing context in the early days of a variant’s emergence when making these estimates. Our estimates of the transmission advantage (measured as the mean Rt ratio of Delta to Alpha) for Massachusetts (63%) and Connecticut (78%) were within the 40%–80% estimate range provided by the United Kingdom.11SAGESPI-M-O: Summary of Further Modelling of Easing Restrictions – Roadmap Step 4 on 19 July 2021, 7 July. GOV.UK, 2021Google Scholar We estimated a greater transmission advantage for Delta in Rhode Island (83%), New Hampshire (92%), Maine (104%), and Vermont (167%). This variation may be driven by differences in the underlying state populations, such as population density, vaccination rates, travel patterns, control measures, behaviors, and competing variants in circulation. In addition, the differences could reflect the noisier Delta Rt estimates we observed for states with fewer infections and, as a result, fewer genomic sequences. In particular, we noted wide confidence intervals around the Delta Rt estimates for Maine, New Hampshire, and Vermont, the states with the greatest Delta to Alpha transmission advantage (Figures S2B and S2C). It is possible that additional sequencing data from these states would bring their estimates of relative transmissibility more in line with those from other locations. Our study adds to the growing evidence that Delta may be more transmissible in part by causing higher viral loads during acute infections.21Teyssou E. Delagrèverie H. Visseaux B. Lambert-Niclot S. Brichler S. Ferre V. Marot S. Jary A. Todesco E. Schnurigere A. et al.The Delta SARS

The risk of COVID-19 death is much greater and age-dependent with type I IFN autoantibodies

Abstract: SARS-CoV-2 infection fatality rate (IFR) doubles with every five years of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-β are found in ~20% of deceased patients across age groups. In the general population, they are found in ~1 % of individuals aged 20–70 years and in >4% of those >70 years old. With a sample of 1,261 deceased patients and 34,159 uninfected individuals, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to non-carriers. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRD was 17.0[95% CI:11.7–24.7] for individuals under 70 years old and 5.8[4.5–7.4] for individuals aged 70 and over, whereas, for autoantibodies neutralizing both molecules, the RRD was 188.3[44.8–774.4] and 7.2[5.0–10.3], respectively. IFRs increased with age, from 0.17%[0.12–0.31] for individuals <40 years old to 26.7%[20.3–35.2] for those ≥80 years old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84%[0.31–8.28] to 40.5%[27.82–61.20] for the same two age groups, for autoantibodies neutralizing both molecules. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, particularly those neutralizing both IFN-α2 and -ω. Remarkably, IFR increases with age, whereas RRD decreases with age. Autoimmunity to type I IFNs appears to be second only to age among common predictors of COVID-19 death.

Inborn errors of OAS–RNase L in SARS-CoV-2–related multisystem inflammatory syndrome in children

Abstract: Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe condition that follows benign COVID-19. We report autosomal recessive deficiencies of OAS1, OAS2, or RNASEL in five unrelated children with MIS-C. The cytosolic double-stranded RNA (dsRNA)–sensing OAS1 and OAS2 generate 2′-5′-linked oligoadenylates (2-5A) that activate the single-stranded RNA–degrading ribonuclease L (RNase L). Monocytic cell lines and primary myeloid cells with OAS1, OAS2, or RNase L deficiencies produce excessive amounts of inflammatory cytokines upon dsRNA or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stimulation. Exogenous 2-5A suppresses cytokine production in OAS1-deficient but not RNase L–deficient cells. Cytokine production in RNase L–deficient cells is impaired by MDA5 or RIG-I deficiency and abolished by mitochondrial antiviral-signaling protein (MAVS) deficiency. Recessive OAS–RNase L deficiencies in these patients unleash the production of SARS-CoV-2–triggered, MAVS-mediated inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C. Description Is the OAS–RNase L pathway the “MIS-C”ing link? Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that affects one in 10,000 infected children. MIS-C is reminiscent of Kawasaki disease and its etiology remains unknown. Lee et al. performed whole-exome and whole-genome sequencing on a cohort of MIS-C patients and uncovered autosomal-recessive deficiencies of OAS1, OAS2, or RNASEL in around 1% of the cohort (see the Perspective by Brodin). These genes are components of a signaling pathway that suppresses inflammation in double-stranded RNA–stimulated mononuclear phagocytes. Thus, single-gene recessive inborn errors of the OAS–RNase L pathway can result in uncontrolled inflammatory cytokine production by mononuclear phagocytes after SARS-CoV-2 infection, potentially explaining the origins of MIS-C in some children. —STS Autosomal-recessive deficits in RNA sensing can result in SARS-CoV-2–triggered Kawasaki-like disease. INTRODUCTION Multisystem inflammatory syndrome in children (MIS-C) is a severe, unexplained complication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with an estimated prevalence of ~1 per 10,000 infected children. It typically occurs 4 weeks after infection, without hypoxemic pneumonia. Affected children present with fever, rash, abdominal pain, myocarditis, and other clinical features reminiscent of Kawasaki disease, including lymphadenopathy, coronary aneurysm, and high levels of biological markers of acute inflammation. Sustained monocyte activation is consistently reported as a key immunological feature of MIS-C. A more specific immunological abnormality is the polyclonal expansion of CD4+ and CD8+ T cells bearing the T cell receptor Vβ21.3. The root cause of MIS-C and its immunological and clinical features remains unknown. RATIONALE We hypothesized that monogenic inborn errors of immunity to SARS-CoV-2 may underlie MIS-C in some children. We further hypothesized that the identification of these inborn errors would provide insights into the molecular and cellular mechanisms underlying its immunological and clinical phenotypes. Finally, we hypothesized that a genetic and mechanistic understanding of a few patients would provide a proof of principle that would facilitate studies in other patients. We performed whole-exome or whole-genome sequencing on 558 internationally recruited patients with MIS-C (aged 3 months to 19 years). We searched for rare nonsynonymous biallelic variants of protein-coding genes, testing a hypothesis of genetic homogeneity. RESULTS We found autosomal recessive deficiencies of OAS1 (2′-5′-oligoadenylate synthetase 1), OAS2, or RNase L (ribonuclease L) in five unrelated children of four different ancestries with MIS-C (~1% of our cohort). There were no similar defects in a cohort of 1288 individuals (aged 6 months to 99 years) with asymptomatic or mild infection (P = 0.001) or 334 young patients (aged 0 to 21 years) with asymptomatic or mild infection or COVID-19 pneumonia (P = 0.046). The estimated cumulative frequency of these defects in the general population was ~0.00013. The type I interferon (IFN)–inducible double-stranded RNA (dsRNA)–sensing proteins OAS1 and OAS2 generate 2′-5′-linked oligoadenylates (2-5A), which activate the antiviral single-stranded RNA (ssRNA)–degrading RNase L, particularly in mononuclear phagocytes. Consistent with the absence of pneumonia in these patients, epithelial cells and fibroblasts defective for this pathway restricted SARS-CoV-2 normally. This contrasted with interferon alpha and beta receptor subunit 1 (IFNAR1)–deficient cells from patients prone to hypoxemic pneumonia without MIS-C. Monocytic cell lines with genetic deficiencies of OAS1, OAS2, or RNase L displayed excessive inflammatory cytokine production in response to intracellular dsRNA. Cytokine production by RNase L–deficient cells was impaired by melanoma differentiation-associated protein 5 (MDA5) or retinoic acid–inducible gene I (RIG-I) deficiency and abolished by mitochondrial antiviral-signaling protein (MAVS) deficiency. Exogenous 2-5A suppressed inflammatory responses to these stimuli in control and OAS1-deficient cells but not in RNase L–deficient cells. Finally, monocytic cell lines, primary monocytes, and monocyte-derived dendritic cells with genetic deficiencies of OAS1, OAS2, or RNase L displayed exaggerated inflammatory responses to SARS-CoV-2 as well as SARS-CoV-2–infected cells and their RNA. CONCLUSION We report autosomal recessive deficiencies of OAS1, OAS2, or RNase L in ∼1% of an international cohort of MIS-C patients. The cytosolic OAS–RNase L pathway suppresses RIG-I/MDA5–MAVS–mediated inflammation in dsRNA-stimulated mononuclear phagocytes. Single-gene recessive inborn errors of the OAS–RNase L pathway unleash the production of SARS-CoV-2–triggered inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C. OAS–RNase L deficiency in MIS-C. dsRNAs from SARS-CoV-2 or SARS-CoV-2–permissive cells engulfed by mononuclear phagocytes simultaneously activate the RIG-I/MDA5–MAVS pathway, inducing inflammatory cytokine production, and the OAS–RNase L pathway, exerting posttranscriptional control over inflammatory cytokine production. OAS–RNase L deficiency results in excessive inflammatory cytokine production by myeloid cells, triggering MIS-C, including lymphoid cell activation and multiple tissue lesions. NK, natural killer; IRF3, interferon regulatory factor 3; NF-κB, nuclear factor κB.

Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques

Abstract: Abstract Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.

Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota

Abstract: SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19.

Further delineation of familial polycystic ovary syndrome (PCOS) via whole‐exome sequencing: PCOS‐related rare FBN3 and FN1 gene variants are identified

Abstract: To identify pathogenic rare coding Mendelian/high‐effect size variant(s) by whole‐exome sequencing in familial polycystic ovary syndrome (PCOS) patients to elucidate PCOS‐related pathways.

Mutation spectrum of congenital heart disease in a consanguineous Turkish population

Abstract: While many studies agree that consanguinity increases the rate of congenital heart disease (CHD), few genome analyses have been conducted with consanguineous CHD cohorts.

Application of multiplex amplicon deep-sequencing (MAD-seq) to screen for putative drug resistance markers in the Necator americanus isotype-1 β-tubulin gene

Abstract: Global control of hookworm infections relies on periodic Mass Drug Administration of benzimidazole drugs to high-risk groups, regardless of infection status. Mutations in the isotype-1 β-tubulin gene have been identified in veterinary nematodes, resulting in structural changes and reduced drug-binding. In Ghana, previous studies have demonstrated significant variability in albendazole effectiveness among people infected with the hookworm Necator americanus, although the mechanisms underlying deworming response have not been defined. Using hookworm egg samples from a cross-sectional study in Ghana, we developed a multiplex amplicon deep sequencing (MAD-seq) method to screen genomic regions encapsulating putative drug-resistance markers in N. americanus isotype-1 β-tubulin gene. Three single nucleotide polymorphisms (SNPs) corresponding to resistance-associated mutations (F167Y, E198A, F200Y) within the coding region of the isotype-1 β-tubulin gene were characterized using MAD-seq in 30 matched pre- and post-treatment samples from individuals with persistent infection following therapy. Post-sequence analysis showed that the highest mean alternative nucleotide allele at each PCR amplicon was 0.034% (167amplicon) and 0.025% (198/200amplicon), suggesting minimal allelic variation. No samples contained the F167Y SNP, while one contained low-frequency reads associated with E198A (3.15%) and F200Y (3.13%). This MAD-seq method provides a highly sensitive tool to monitor the three putative benzimidazole resistance markers at individual and community levels. Further work is required to understand the association of these polymorphisms to treatment response.

Severe Phenotype in Patients with X-linked Hydrocephalus Caused by a Missense Mutation in L1CAM

Abstract: Objective: The study aimed to show the clinical characteristics and prognosis of the L1 syndrome in patients with L1CAM mutations in the extracellular region. Materials and Methods: Three affected boys and their siblings and parents from a large family were included in this study. Genetic etiology was investigated by whole-exome sequencing in the index patient. The pathogenic variant was detected by whole-exome sequencing and was validated by Sanger sequencing in 3 patients and other family members. Results: We present 2 brothers and their cousin with prenatal onset hydrocephalus, severe developmental and speech delay, corpus callosum agenesis/hypogenesis, epilepsia, and adducted thumbs. A hemizygous missense mutation NM_024003 (c.A2351G:p.Y784C) on exon 18 of L1CAM gene was found in the 3 patients and their carrier mother. This missense mutation in the conserved region of the second fibronectin type III-like repeats located in the extracellular region of L1CAM resulted in the severe phenotype of X-linked inherited L1 syndrome in the patients. Conclusion: L1 syndrome should be considered in the differential diagnosis of male children with intellectual disability, hydrocephalus, and adducted thumbs. While truncating mutations of L1CAM may cause a more severe phenotype, missense mutations cause milder forms. However, pathogenic missense mutations affecting key amino acid residues lead to severe phenotype likely.

Biallelic frameshift variants in PHLDB1 cause mild-type osteogenesis imperfecta with regressive spondylometaphyseal changes

Abstract: Background Osteogenesis imperfecta (OI) is a heterogeneous group of inherited disorders characterised by susceptibility to fractures, primarily due to defects in type 1 collagen. The aim of this study is to present a novel OI phenotype and its causative candidate gene. Methods Whole-exome sequencing and clinical evaluation were performed in five patients from two unrelated families. PHLDB1 mRNA expression in blood and fibroblasts was investigated by real-time PCR, and western blot analysis was further performed on skin fibroblasts. Results The common findings among the five affected children were recurrent fractures and/or osteopaenia, platyspondyly, short and bowed long bones, and widened metaphyses. Metaphyseal and vertebral changes regressed after early childhood, and no fractures occurred under bisphosphonate treatment. We identified biallelic NM_001144758.3:c.2392dup and NM_001144758.3:c.2690_2693del pathogenic variants in PHLDB1 in the affected patients, respectively, in the families; parents were heterozygous for these variants. PHLDB1 encodes pleckstrin homology-like domain family B member-1 (PHLDB1) protein, which has a role in insulin-dependent Akt phosphorylation. Compared with controls, a decrease in the expression levels of PHLDB1 in the blood and skin fibroblast samples was detected. Western blot analysis of cultured fibroblasts further confirmed the loss of PHLDB1. Conclusion Two biallelic frameshift variants in the candidate gene PHLDB1 were identified in independent families with a novel, mild-type, autosomal recessive OI. The demonstration of decreased PHLDB1 mRNA expression levels in blood and fibroblast samples supports the hypothesis that PHLDB1 pathogenic variants are causative for the observed phenotype.