Table 1.
COVID-19 Genetic Correlations When Accounting for Potential Confounding Variables
| Substance Use Phenotype | CUD | β Substance Use Phenotypea | EA | TDI | BMI | FEV1 | Fast Gluc | β Risk | β ADHD |
|---|---|---|---|---|---|---|---|---|---|
| Cannabis Use | 0.539b | −0.300 | 0.015 | 0.057 | 0.312b | 0.025 | −0.024 | −0.007 | −0.058 |
| CPD | 0.381b | 0.042 | −0.193b | −0.052 | 0.327b | 0.011 | 0.006 | −0.026 | −0.092 |
| Age Smoke | 0.398b | 0.067 | −0.215b | −0.037 | 0.336b | 0.009 | 0.010 | −0.025 | −0.064 |
| Smoking Cessation | 0.402b | −0.205 | −0.114 | −0.122 | 0.329b | 0.014 | −0.0003 | −0.054 | −0.069 |
| Ever Smoke | 0.439b | −0.123 | −0.191b | −0.021 | 0.344b | 0.011 | −0.003 | −0.029 | −0.052 |
| PAU | 0.315 | 0.162 | −0.211b | −0.082 | 0.345b | 0.004 | 0.009 | −0.036 | −0.088 |
Standardized beta estimates for CUD and substance use phenotypes were taken from a multiple regression parameterized in gSEM. When all of the above covariates were included in the model simultaneously with PAU and CUD, the partial rG between CUD and COVID-19 was no longer significant (rG = 0.315, p = .08). This was largely due to the number of covariates; when only PAU was included in the model, the partial r effect size for CUD was similar in magnitude and significant (r = 0.364, p = .004).
ADHD, attention-deficit/hyperactivity disorder; Age Smoke, age of smoking initiation; BMI, body mass index; Cannabis Use, any lifetime cannabis use; CPD, cigarettes/day; CUD, cannabis use disorder; EA, education attainment; Ever Smoke, ever smoking tobacco; Fast Gluc, fasting glucose; FEV1, forced expiratory volume for 1 second; gSEM, genomic structural equation modeling; GWAS, genome-wide association study; PAU, problematic alcohol use; Risk, risk taking; TDI, Townsend deprivation index.
Substance use phenotypes were entered and tested separately to avoid multicollinearity among them. Each row represents genetic correlations with COVID-19 hospitalization from one model. The multiple rows indicate the separate models run substituting each substance use phenotype (listed in the first column). The model was COVID-19 hospitalization = CUD + substance use phenotype + BMI + TDI + EA + FEV1 + Fasting Gluc + ADHD + Risk taking + error. The original GWASs accounted for standard GWAS covariates (age, sex, genetic principal components, etc.).
p < .05.