The RUSH2A Study: Best-Corrected Visual Acuity, Full-Field Electroretinography Amplitudes, and Full-Field Stimulus Thresholds at Baseline

Purpose: The purpose of this study was to evaluate baseline best corrected visual acuity (BCVA), full-field electroretinography (ERG), full-field stimulus thresholds (FST), and their relationship with baseline demographic and clinical characteristics in the Rate of Progression in Usher syndrome type 2 (USH2A)-related Retinal Degeneration (RUSH2A) multicenter study. Methods: Participants had Usher syndrome type 2 (USH2, N = 80) or autosomal recessive nonsyndromic retinitis pigmentosa (ARRP, N = 47) associated with biallelic variants in the USH2A gene. Associations of demographic and clinical characteristics with BCVA, ERG, and FST were assessed with regression models. Results: In comparison to ARRP, USH2 had worse BCVA (median 79 vs. 82 letters; P < 0.001 adjusted for age), lower rod-mediated ERG b-wave amplitudes (median 0.0 vs. 6.6 µV; P < 0.001) and 30 Hz flicker cone-mediated ERG amplitudes (median 1.5 vs. 3.1 µV; P = 0.001), and higher (white, blue, and red) FST thresholds (means [-26, -31, -23 dB] vs. [-39, -45, -28 dB]; P < 0.001 for all stimuli). After adjusting for age, gender, and duration of vision loss, the difference in BCVA between diagnosis groups was attenuated (P = 0.09). Only diagnosis was associated with rod- and cone-mediated ERG parameters, whereas both genders (P = 0.04) and duration of visual loss (P < 0.001) also were associated with FST white stimulus. Conclusions: USH2 participants had worse BCVA, ERG, and FST than ARRP participants. FST was strongly associated with duration of disease; it remains to be determined whether it will be a sensitive measure of progression. Translational Relevance: Using standardized research protocols in RUSH2A, measures have been identified to monitor disease progression and treatment response and differentiate features of prognostic relevance between USH2 and ARRP participants with USH2A mutations

Are moral norms rooted in instincts? The sibling incest taboo as a case study

1. Are Moral Norms Rooted in Instincts? The Sibling Incest Taboo as a Case Study According to Westermarck's widely accepted explanation of the incest taboo, cultural prohibitions on sibling sex are rooted in an evolved biological disposition to feel sexual aversion toward our childhood coresidents. Bernard Williams posed the "representation problem" for Westermarck's theory: the content of the hypothesized instinct (avoid sex with childhood coresidents) is different from the content of the incest taboo (avoid sex with siblings)—thus the former cannot be causally responsible for the latter. Arthur Wolf posed the related "moralization problem": the instinct concerns personal behavior whereas the prohibition concerns everyone. This paper reviews possible ways of defending Westermarck's theory from the representation and moralization problems, and concludes that the theory is untenable. A recent study purports to support Westermarck's account by showing that unrelated children raised in the same peer groups on kibbutzim feel sexual aversion toward each other and morally oppose third-party intra-peer-group sex, but this study has been misinterpreted. I argue that the representation and moralization problems are general problems that could potentially undermine many popular evolutionary explanations of social/moral norms. The cultural evolution of morality is not tightly constrained by our biological endowment in the way some philosophers and evolutionary psychologists believe. 2. Power in Cultural Evolution and the Spread of Prosocial Norms According to cultural evolutionary theory in the tradition of Boyd and Richerson, cultural evolution is driven by individuals' learning biases, natural selection, and random forces. Learning biases lead people to preferentially acquire cultural variants with certain contents or in certain contexts. Natural selection favors individuals or groups with fitness-promoting variants. Durham (1991) argued that Boyd and Richerson's approach is based on a "radical individualism" that fails to recognize that cultural variants are often "imposed" on people regardless of their individual decisions. Fracchia and Lewontin (2005) raised a similar challenge, suggesting that the success of a variant is often determined by the degree of power backing it. With power, a ruler can impose beliefs or practices on a whole population by diktat, rendering all of the forces represented in cultural evolutionary models irrelevant. It is argued here, based on work by Boehm (1999, 2012), that, from at least the time of the early Middle Paleolithic, human bands were controlled by powerful coalitions of the majority that deliberately guided the development of moral norms to promote the common good. Cultural evolutionary models of the evolution of morality have been based on false premises. However, Durham (1991) and Fracchia and Lewontin's (2005) challenge does not undermine cultural evolutionary modeling in nonmoral domains. 3. A Debunking Explanation for Moral Progress According to "debunking arguments," our moral beliefs are explained by evolutionary and cultural processes that do not track objective, mind-independent moral truth. Therefore (the debunkers say) we ought to be skeptics about moral realism. Huemer counters that "moral progress"—the cross-cultural convergence on liberalism—cannot be explained by debunking arguments. According to him, the best explanation for this phenomenon is that people have come to recognize the objective correctness of liberalism. Although Huemer may be the first philosopher to make this explicit empirical argument for moral realism, the idea that societies will eventually converge on the same moral beliefs is a notable theme in realist thinking. Antirealists, on the other hand, often point to seemingly intractable cross-cultural moral disagreement as evidence against realism (the "argument from disagreement"). This paper argues that the trend toward liberalism is susceptible to a debunking explanation, being driven by two related non-truth-tracking processes. First, large numbers of people gravitate to liberal values for reasons of self-interest. Second, as societies become more prosperous and advanced, they become more effective at suppressing violence, and they create conditions where people are more likely to empathize with others, which encourages liberalism. The latter process is not truth tracking (or so this paper argues) because empathy-based moral beliefs are themselves susceptible to an evolutionary debunking argument. Cross-cultural convergence on liberalism per se does not support either realism or antirealism. 4. Realist Social Selection: How Gene–Culture Coevolution Can (but Probably Did Not) Track Mind-Independent Moral Truth Standard evolutionary debunking arguments (EDAs) in metaethics target moral beliefs by attributing them to natural selection. According to the debunkers, natural selection does not track mind-independent moral truth, so the discovery that our moral beliefs (realistically construed) were caused by natural selection renders them unjustified. I argue that our innate moral faculty is likely not the product of natural selection, but rather social selection. Social selection is a kind of gene–culture coevolution driven by the enforcement of collectively agreed-upon rules. Unlike natural selection, social selection is teleological and could potentially track mind-independent moral truth by a process that I term realist social selection: early humans could have acquired moral knowledge via reason and enforced rules based on that knowledge, thereby creating selection pressures that drove the evolution of our innate moral faculty. Given anthropological evidence that early humans designed rules with the conscious aim of preserving individual autonomy and advancing their collective interests, realist social selection appears to be an attractive theory for moral realists. However, I propose a new EDA to show that realist social selection is unlikely to have occurred. 5. A Debunking How-Possibly Explanation for the Principle of Universal Benevolence According to Street's evolutionary debunking argument (EDA), evolutionary biology provides "powerful" explanations of our "basic evaluative judgements." The discovery that our moral beliefs (realistically construed) are "saturated with evolutionary influence" renders them unjustified, since natural selection does not track mind-independent moral truth. De Lazari-Radek and Singer agree that most of our commonsense moral beliefs are debunked in the way Street claims, but they argue that belief in Sidgwick's principle of universal benevolence cannot be explained by natural selection and is therefore immune from EDAs. I argue that Street oversold the power of her evolutionary explanations, thus leaving an opening for realists to claim that moral beliefs with less powerful evolutionary explanations can escape debunking. In fact, all naturalistic theories of morality—including those invoked by Street and de Lazari-Radek and Singer—are speculative "how-possibly" explanations. If how-possibly explanations are not debunking, then both Street's (global) and de Lazari-Radek and Singer's (selective) debunking arguments fail. If how-possibly explanations are debunking, then selective debunkers must show that there is no plausible way that naturalistic forces could have produced the beliefs they want to defend. I argue that naturalistic how-possibly explanations can debunk moral beliefs by appealing to ontological parsimony, and provide a debunking how-possibly explanation for belief in the principle of universal benevolence

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals. © 2022, The Author(s)

Tracking SARS-CoV-2 mutations and variants through the COG-UK-Mutation Explorer

COG-UK Mutation Explorer (COG-UK-ME, https://sars2.cvr.gla.ac.uk/cog-uk/—last accessed date 16 March 2022) is a web resource that displays knowledge and analyses on SARS-CoV-2 virus genome mutations and variants circulating in the UK, with a focus on the observed amino acid replacements that have an antigenic role in the context of the human humoral and cellular immune response. This analysis is based on more than 2 million genome sequences (as of March 2022) for UK SARS-CoV-2 data held in the CLIMB-COVID centralised data environment. COG-UK-ME curates these data and displays analyses that are cross-referenced to experimental data collated from the primary literature. The aim is to track mutations of immunological importance that are accumulating in current variants of concern and variants of interest that could alter the neutralising activity of monoclonal antibodies (mAbs), convalescent sera, and vaccines. Changes in epitopes recognised by T cells, including those where reduced T cell binding has been demonstrated, are reported. Mutations that have been shown to confer SARS-CoV-2 resistance to antiviral drugs are also included. Using visualisation tools, COG-UK-ME also allows users to identify the emergence of variants carrying mutations that could decrease the neutralising activity of both mAbs present in therapeutic cocktails, e.g. Ronapreve. COG-UK-ME tracks changes in the frequency of combinations of mutations and brings together the curated literature on the impact of those mutations on various functional aspects of the virus and therapeutics. Given the unpredictable nature of SARS-CoV-2 as exemplified by yet another variant of concern, Omicron, continued surveillance of SARS-CoV-2 remains imperative to monitor virus evolution linked to the efficacy of therapeutics

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Summary Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: A genomics-based retrospective cohort analysis

Objectives The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. Methods In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. Results Our cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus pre-Alpha variants). Conclusions The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021