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Institute
The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Most systematic discussion of dyad morphemes has focussed on Australian languages, owing to a combination of their relative prevalence there, and the development of a descriptive tradition that investigates them in some depth. In the course of researching this paper, however, I became aware of functionally and semantically similar morphemes in many other parts of the world, almost invariably described in isolation from any typological reference point. I have incorporated such data as far as I am aware of it, in the hope that a systematic study will encourage other investigators to identify, and investigate in detail, similar constructions in a range of languages. The current state of our research, however, as well as some interesting geographical skewings that I discuss below, such that outside Australia dyad constructions almost exclusively employ reciprocal morphology, means that most of this paper will focus on Australian languages.
In this paper we test previous claims concerning the universality of patterns of polysemy and semantic change in perception verbs. Implicit in such claims are two elements: firstly, that the sharing of two related senses A and B by a given form is cross-linguistically widespread, and matched by a complementary lack of some rival polysemy, and secondly that the explanation for the ubiquity of a given pattern of polysemy is ultimately rooted in our shared human cognitive make-up. However, in comparison to the vigorous testing of claimed universals that has occurred in phonology, syntax and even basic lexical meaning, there has been little attempt to test proposed universals of semantic extension against a detailed areal study of non-European languages. To address this problem we examine a broad range of Australian languages to evaluate two hypothesized universals: one by Viberg (1984), concerning patterns of semantic extension across sensory modalities within the domain of perception verbs (i .e. intra-field extensions), and the other by Sweetser (1990), concerning the mapping of perception to cognition (i.e. trans-field extensions). Testing against the Australian data allows one claimed universal to survive, but demolishes the other, even though both assign primacy to vision among the senses.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
