scores composed of variants at the extreme of a statistical distribution, most usually those that pass the genome-wide significant threshold for the trait concerned. 2. Global extended Polygenic Scores (gePS): scores generated from a deeper set of variants generated from genome-wide analyses, typically involving large numbers of sub-threshold significant variants. 3. Partitioned or Process-specific Polygenic Scores (pPS): scores composed of variants grouped according to some common biological process (e.g. association with a related endophenotype, tissue expression of related genes, chromatin state) ACKNOWLEDGEMENTS We acknowledge the timely assistance from Amit Khera (Cambridge, MA) and Michael Multhaup and colleagues at 23andMe (Mountain View, CA) who provided additional details concerning the basis of the T2D polygenic scores that allowed us to complete the comparisons reported in this paper. GRANTS and FELLOWSHIPS MMcC is a Wellcome Investigator and an NIHR Senior Investigator. Relevant funding support for this work comes from Wellcome (090532, 106130, 098381, 203141, 212259), NIDDK (U01-DK105535), and NIHR (NF-SI-0617-10090). JCF is supported by NIH grants U01 DK105554, R01 GM117163, R01 DK105154, K24 DK110550 and U54 DK118612. MSU is supported by NIH/NIDDK K23 1K23DK114551. ADVANCE ARTICLE: Endocrine Reviews Downloaded from https://academic.oup.com/edrv/advance-article-abstract/doi/10.1210/er.2019-00088/5535575 by 81225740 user on 24 July 2019 ADVANCE ARTICLE Endocrine Reviews; Copyright 2019 DOI: 10.1210/er.2019-00088 19 Wellcome Trust, 090532, Mark I McCarthy; Wellcome, 106130, Mark I McCarthy; Wellcome, 098381, Mark I McCarthy; Wellcome, 203141, Mark I McCarthy; Wellcome, 212259, Mark I McCarthy; NIDDK, u01-DK105535, Mark I McCarthy; NIHR, NF-SI-0617-10090, Mark I McCarthy; NIDDK, U01 DK105554, Jose C. Florez; NIH, R01 GM117163, Jose C. Florez; NIDDK, R01 DK105154, Jose C. Florez; NIDDK, K24 DK110550, Jose C. Florez; NIDDK, U54 DK118612, Jose C. Florez; NIDDK, K23 1K23DK114551, Miriam S. Udler CURRENT ADDRESS AND ADDRESS FOR CONTACT: Mark McCarthy Genentech, 1 DNA Way, South San Francisco, CA 94080, Tel: (1) 650 467 3970; Email: mccarthy.mark@gene.com, Requests for reprints should be made to the above address DISCLOSURE SUMMARY MMcC: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. He has served on advisory panels for Pfizer, NovoNordisk, Zoe Global; has received honoraria from Merck, Pfizer, NovoNordisk and Eli Lilly; has stock options in Zoe Global and has received research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier & Takeda. As of June 2019, MMcC is an employee of Genentech, and holds stock in Roche. JCF has received a consulting honorarium from Janssen. DATA AVAILABILITY All data generated or analyzed during this study are included in this published article or in the data repositories listed in References. REFERENCES 1. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, Malanda B. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018;138:271-281. PMID: 29496507. 2. Haffner SM, Stern MP, Hazuda HP, Mitchell BD, Patterson JK. Cardiovascular risk factors in confirmed prediabetic individuals. Does the clock for coronary heart disease start ticking before the onset of clinical diabetes? JAMA. 1990;263(21):2893-8. 3. McCarthy MI. Painting a new picture of personalised medicine for diabetes. Diabetologia. 2017;60(5):793-799. PMID: 28175964. 4. Schwartz SS, Epstein S, Corkey BE, Grant SF, Gavin JR 3rd, Aguilar RB. The Time Is Right for a New Classification System for Diabetes: Rationale Genetic variants of the human host influencing the coronavirus-associated phenotypes (SARS, MERS and COVID-19): rapid systematic review and field synopsis Emilio Di Maria1,2* , Andrea Latini3 , Paola Borgiani3 and Giuseppe Novelli3,4,5 Abstract The COVID-19 pandemic has strengthened the interest in the biological mechanisms underlying the complex interplay between infectious agents and the human host. The spectrum of phenotypes associated with the SARSCoV-2 infection, ranging from the absence of symptoms to severe systemic complications, raised the question as to what extent the variable response to coronaviruses (CoVs) is influenced by the variability of the hosts’ genetic background. To explore the current knowledge about this question, we designed a systematic review encompassing the scientific literature published from Jan. 2003 to June 2020, to include studies on the contemporary outbreaks caused by SARS-CoV-1, MERS-CoV and SARS-CoV-2 (namely SARS, MERS and COVID-19 diseases). Studies were eligible if human genetic variants were tested as predictors of clinical phenotypes. An ad hoc protocol for the rapid review process was designed according to the PRISMA paradigm and registered at the PROSPERO database (ID: CRD42020180860). The systematic workflow provided 32 articles eligible for data abstraction (28 on SARS, 1 on MERS, 3 on COVID-19) reporting