Development and validation of a clinical and genetic model for predicting risk of severe COVID-19

Abstract

Clinical and genetic risk factors for severe coronavirus disease 2019 (COVID-19) are often considered independently and without knowledge of the magnitudes of their effects on risk. Using severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) positive participants from the UK Biobank, we developed and validated a clinical and genetic model to predict risk of severe COVID-19. We used multivariable logistic regression on a 70% training dataset and used the remaining 30% for validation. We also validated a previously published prototype model. In the validation dataset, our new model was associated with severe COVID-19 (odds ratio per quintile of risk = 1.77, 95% confidence interval (CI) 1.64–1.90) and had acceptable discrimination (area under the receiver operating characteristic curve = 0.732, 95% CI 0.708–0.756). We assessed calibration using logistic regression of the log odds of the risk score, and the new model showed no evidence of over- or under-estimation of risk (α = −0.08; 95% CI −0.21−0.05) and no evidence or over-or under-dispersion of risk (β = 0.90, 95% CI 0.80–1.00). Accurate prediction of individual risk is possible and will be important in regions where vaccines are not widely available or where people refuse or are disqualified from vaccination, especially given uncertainty about the extent of infection transmission among vaccinated people and the emergence of SARS-CoV-2 variants of concern.

Host genetic factors determining COVID-19 susceptibility and severity

“…Genetic data has enabled the development of polygenic risk scores (PRSs) for complex diseases ( www.pgscatalog.org/ ), including COVID-19 [ 70 , [82] , [83] , [84] ]. A PRS is a calculated estimate of traits or disease susceptibility according to individual genetic profiles based on GWAS summary statistics.…”

“…It is known that the effects of individual GWAS variants are small; a combination of many genetic variants in a polygenic risk score, however, explains a larger portion of the risk. Some studies have now generated risk scores to predict COVID-19 severity using GWAS data generated by international collaborations [ 70 , [82] , [83] , [84] ]. Some risk scores apparently predict severe COVID-19 reliably, allowing for identification of high-risk individuals who should be prioritized for vaccination, preventive measures and behavioral changes.…”

The Existence of At Least Three Genomic Signature Patterns and At Least Seven Subtypes of COVID-19 and the End of the Disease

“…Scientists have put tremendous effort into trying to find genomic clues linked to COVID-19. However, knowledge of COVID-19 is still limited, and many problems have remained unanswered 1;2;3;4;5;6;7;8;9;10;11;12 . Many published results cannot guarantee 100% accuracy.…”

Update on human genetic susceptibility to COVID-19: susceptibility to virus and response

“…The estimate of predictive models deserves a separate discussion. Due to the availability of international biobanks, it has been possible to identify and confirm novel susceptibility loci for COVID-19 [60][61][62][63][64][65][66]. Thirteen novel susceptibility loci have been linked to several aspects of SARS-CoV-2 infection as a result of a recent meta-analysis performed by COVID-19 Host Genetics Initiative (COVID-19 H.G.I.)…”