Identification of immune complement function as a determinant of adverse SARS-CoV-2 infection outcome
coagulation functional genomics
Authors: Vijendra Ramlall al.
Journal/ Pre-Print: Medrxiv
Tags: risk factors, Functional genomics, Complement and coagulation, SNP and eQTL
1. A prior history of macular degeneration (a possible indication of dysregulated complement activation) or of coagulation disorders are associated with poor COVID19 outcomes.
2. Candidate variants lying within complement and coagulation genes show evidence of associations with a positive SARS-Cov-2 test result
A retrospective observational study of health electronic records of 11,116 patients (6,398 positive for SARS-Cov-2) shows that patients with history of macular degeneration (considered an indication of dysregulated complement activation) are more prone to severe symptoms and deaths. Correction for age and sex reduced effect sizes, but they remained nominally significant, though further corrections for comorbidities were not carried out. The authors perform a candidate gene study in the UK BioBank to find genetic association between complement/coagulation and COVID-19, analysing 4.248 genetic variations lying within complement/coagulation pathway genes in individuals positive for SARS-Cov2 (957 vs >300,000 non-tested controls). 10 loci were identified to be significant at FDR < 0.05 (including CD55, C4BPD, F3 and C3), though none were genome-wide significant.
Impact for SARS-CoV2/COVID19 research efforts
Understand the risk factors for SARS-Cov-2 infection, propensity for severe infections may have factors beyond “usual demographic information”. Consideration for other epidemiological studies.
The authors give a rationale to investigate complement and coagulation pathways as a possible treatment target
· Retrospective observational study
· Prospective cohort - genetic association study
Strengths and limitations of the paper
Novelty: Describe a new risk factor for COVID-19 severity (over-active complement and coagulation pathways). It provides a possible genetic explanation for individual susceptibility to COVID-19.
Standing in the field: Supports the reported enhanced coagulation and D-dimers levels observed in severe COVID-19 cases while providing a genetic explanation for them. Agrees with prior work that an immunomodulatory approach maybe useful in the management.
Appropriate statistics: Mostly, standard analyses and corrections are carried out. There is little attempt to demonstrate that medical history associations are robust to confounding by comorbidity or other residual confounding (e.g. age is only analaysed as a linear confounder or a binary over-65 indicator variable). Use of reduced significant thresholds for candidate genes, and the use of FDR correction, is non-standard in genetic association studies and can generate false positives. Overall, these results should be considered provisional until they can be replicated at genome-wide significance.
Viral model used: NA
Translatability: medium- it helps identifying new risk factors and a direct therapy development. Given rapid deterioration of Covid patients, may limit applicability.
· Retrospective observational study, causality cannot be claimed
· Macular degeneration is only a proxy for complement dysregulation, no direct measurements of it in the study
· Small number of patients with defect in the coagulation pathway (acknowledged)
· The genomic study only focuses on very specific pathways (understandably due to small number and hypothesis driven study)
· No genome-wide significant associations and no replication in an external sample.
· Standard problems with the UK biobank samples: homogeneous genomic background, different hospital care for patients, no data on socio-economic background (acknowledged)
· Patients with hypercoagulability, or MAD may also have other conditions (hypertension, obesity, etc). The authors note a moderate correlation between AMD and other comorbidities but do not demonstrate that this is insufficient to account for the effect. Would have been better to use propensity matching with charlson comorbidity index to make more direct comparisons.