Genetically predicted high IGF-1 levels showed protective effects on COVID-19 susceptibility and hospitalization: a Mendelian randomisation study with data from 60 studies across 25 countries
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, China
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Sweden
- The Second School of Clinical Medicine, Southern Medical University, China
- School of Public Health and Women's Hospital, Zhejiang University School of Medicine, China
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Sweden
- Centre for Global Health, Usher Institute, University of Edinburgh, United Kingdom
- Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, United Kingdom
Figures
Figure 1
Overall study design.
Abbreviation: IGF-1, insulin-like growth factor-1; GWAS, genome-wide association study; SNP, single-nucleotide polymorphism; LD, linkage disequilibrium; IVW, inverse variance weighting; MR, Mendelian randomization.
Figure 2 with 2 supplements
IGF-1 and COVID-19 outcomes in Mendelian randomization (MR) analyses.
Abbreviation: IGF-1, insulin-like growth factor-1; SNP, single-nucleotide polymorphism; IVW, inverse variance weighting; OR, odds ratio; CI, confidence interval.
Figure 2—figure supplement 1
Leave-one-out plot for IGF-1 and COVID-19 susceptibility, hospitalization and severity in Mendelian randomization analysis.
Figure 2—figure supplement 2
Funnel plot for IGF-1 and COVID-19 susceptibility, hospitalization and severity in Mendelian randomization analysis.
Tables
Table 1
Sources of data for Mendelian randomization analysis in COVID-19 HGI.
| Phenotype | Participants |
|---|---|
| Susceptibility | Meta-analysis of 35 GWAS performed in individuals of European ancestry |
| Cases: 32,494 individuals with COVID-19 by laboratory confirmation, chart review, or self-report | |
| Controls: 1,316,207 individuals without confirmation or history of COVID-19 | |
| Hospitalization | Meta-analysis of 23 GWAS performed in individuals of European ancestry |
| Cases: 8316 hospitalized individuals with COVID-19 | |
| Controls: 1,549,095 individuals without confirmation or history of COVID-19 | |
| Severity | Meta-analysis of 14 GWAS performed in individuals of European ancestry |
| Cases: 4792 SARS-CoV-2 infected hospitalized individuals who died or required respiratory support (intubation, CPAP, BiPAP, continuous external negative pressure, high flow nasal cannula). | |
| Controls:1,054,664 individuals without confirmation or history of COVID-19 |
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Notes: COVID-19 outcomes are taken from the COVID-19 HGI.
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HGI, Host Genetics Initiative; GWAS, genome-wide association study; UKB, UK Biobank; CPAP, continuous positive airway pressure ventilation; BiPAP, bilevel positive airway pressure ventilation.
Table 2
Sex hormones, SHBG, IGF-1, and COVID-19 outcomes in Mendelian randomization (MR) analyses.
| Exposure | Method | Susceptibility | Hospitalization | Severity | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SNPs | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | SNPs | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | SNPs | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | ||
| Testosterone | IVW | 315 | 0.94 (0.83, 1.06) | 0.309 | 0.006 | – | 303 | 0.82 (0.64, 1.04) | 0.103 | 0.055 | – | 316 | 0.83 (0.60, 1.15) | 0.256 | 0.041 | – |
| MR-Egger | 0.93 (0.76, 1.12) | 0.430 | 0.005 | 0.860 | 0.79 (0.55, 1.15) | 0.217 | 0.051 | 0.819 | 0.78 (0.48, 1.27) | 0.313 | 0.038 | 0.732 | ||||
| Weighted median | 0.89 (0.71, 1.12) | 0.329 | – | – | 0.81 (0.52, 1.28) | 0.370 | – | – | 0.71 (0.40, 1.26) | 0.246 | – | – | ||||
| Simple mode | 1.13 (0.73, 1.77) | 0.584 | – | – | 0.77 (0.27, 2.20) | 0.623 | – | – | 0.44 (0.09, 2.18) | 0.316 | – | – | ||||
| Weighted mode | 0.91 (0.77, 1.08) | 0.300 | – | – | 0.77 (0.52, 1.13) | 0.180 | – | – | 0.65 (0.40, 1.05) | 0.081 | – | – | ||||
| MR-PRESSO | 0.94 (1.06, 0.84) | – | – | – | 0.82 (1.04, 0.65) | – | – | – | 0.83 (1.15, 0.59) | – | – | – | ||||
| SHBG | IVW | 319 | 0.91 (0.80, 1.04) | 0.182 | 0.002 | – | 309 | 0.86 (0.66, 1.11) | 0.255 | 0.087 | – | 320 | 0.92 (0.65, 1.29) | 0.618 | 0.096 | – |
| MR-Egger | 0.96 (0.78, 1.18) | 0.708 | 0.002 | 0.494 | 0.83 (0.57, 1.22) | 0.352 | 0.081 | 0.818 | 0.92 (0.56, 1.51) | 0.730 | 0.090 | 0.994 | ||||
| Weighted median | 0.90 (0.72, 1.13) | 0.360 | – | – | 0.82 (0.52, 1.29) | 0.391 | – | – | 0.72 (0.41, 1.27) | 0.255 | – | – | ||||
| Simple mode | 1.09 (0.66, 1.81) | 0.735 | – | – | 1.18 (0.40, 3.44) | 0.767 | – | – | 1.16 (0.25, 5.41) | 0.850 | – | – | ||||
| Weighted mode | 0.94 (0.78, 1.14) | 0.547 | – | – | 0.81 (0.56, 1.18) | 0.279 | – | – | 0.79 (0.47, 1.33) | 0.376 | – | – | ||||
| MR-PRESSO | 0.91 (1.05, 0.80) | – | – | – | 0.86 (1.11, 0.67) | – | – | – | 0.91 (1.28, 0.65) | – | – | – | ||||
| Estradiol | IVW | 7 | 0.54 (0.15, 1.94) | 0.346 | 0.188 | – | 7 | 0.87 (0.11, 6.70) | 0.895 | 0.769 | – | 7 | 0.50 (0.03, 7.64) | 0.620 | 0.987 | – |
| MR-Egger | 0.73 (0.04, 14.11) | 0.845 | 0.123 | 0.830 | 0.34 (0.00, 29.54) | 0.657 | 0.685 | 0.662 | 0.04 (0.00, 17.04) | 0.345 | 1.000 | 0.401 | ||||
| Weighted median | 0.36 (0.10, 1.35) | 0.130 | – | – | 0.35 (0.03, 4.21) | 0.407 | – | – | 0.30 (0.01, 7.26) | 0.458 | – | – | ||||
| Simple mode | 0.29 (0.03, 2.60) | 0.313 | – | – | 0.71 (0.01, 44.94) | 0.875 | – | – | 0.33 (0.00, 43.56) | 0.673 | - | - | ||||
| Weighted mode | 0.34 (0.07, 1.73) | 0.241 | – | – | 0.38 (0.03, 4.81) | 0.482 | – | – | 0.29 (0.01, 9.43) | 0.511 | - | - | ||||
| MR-PRESSO | 0.54 (1.94, 0.15) | – | – | – | 0.87 (3.93, 0.19) | – | – | – | 0.51 (1.52, 0.17) | - | - | - | ||||
| IGF-1 | IVW | 16 | 0.77 (0.61, 0.97) | 0.027 | 0.175 | – | 16 | 0.62 (0.25, 0.51) | 0.018 | 0.715 | – | 18 | 0.85 (0.52, 1.38) | 0.513 | 0.601 | - |
| MR-Egger | 0.84 (0.56, 1.26) | 0.408 | 0.145 | 0.614 | 0.72 (0.37, 1.38) | 0.336 | 0.668 | 0.595 | 1.45 (0.67, 3.10) | 0.358 | 0.758 | 0.096 | ||||
| Weighted median | 0.76 (0.57, 1.02) | 0.071 | – | – | 0.75 (0.44, 1.28) | 0.294 | – | – | 0.76 (0.38, 1.53) | 0.446 | - | - | ||||
| Simple mode | 0.64 (0.39, 1.05) | 0.097 | – | – | 0.66 (0.30, 1.45) | 0.318 | – | – | 0.82 (0.27, 2.47) | 0.730 | - | - | ||||
| Weighted mode | 0.77 (0.58, 1.02) | 0.084 | – | – | 0.71 (0.44, 1.17) | 0.199 | – | – | 0.70 (0.35, 1.38) | 0.319 | - | - | ||||
| MR-PRESSO | 0.77 (0.98, 0.61) | – | – | – | 0.62 (0.88, 0.43) | – | – | – | 0.85 (1.34, 0.54) | - | - | - | ||||
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SNP, single-nucleotide polymorphism; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighting; SHBG, sex hormones-binding globulin; IGF-1, insulin-like growth factor-1.
Table 3
Sensitive analysis between serum IGF-1 levels instrumented by 10 SNPs in the IGF-1 gene region and COVID-19 outcomes.
| Method | Susceptibility | Hospitalization | Severity | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | p Effect | p Heterogeneity | p Intercept | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | |
| IVW | 0.99 (0.91, 1.07) | 0.777 | 0.596 | – | 0.90 (0.74, 1.10) | 0.645 | 0.104 | – | 1.01 (0.82, 1.24) | 0.415 | 0.437 | – |
| MR-Egger | 0.99 (0.93, 1.05) | 0.732 | 0.541 | 0.527 | 0.97 (0.84, 1.11) | 0.338 | 0.108 | 0.375 | 1.09 (0.92, 1.30) | 0.953 | 0.372 | 0.590 |
| Weighted median | 1.01 (0.96, 1.06) | 0.739 | – | – | 0.97 (0.86, 1.10) | 0.620 | – | – | 1.05 (0.93, 1.20) | 0.310 | – | – |
| Simple mode | 0.98 (0.89, 1.08) | 0.685 | – | – | 1.12 (0.88, 1.43) | 0.395 | – | – | 1.16 (0.88, 1.51) | 0.316 | – | – |
| Weighted mode | 0.98 (0.92, 1.05) | 0.596 | – | – | 0.94 (0.82, 1.09) | 0.439 | – | – | 1.12 (0.92, 1.37) | 0.279 | – | – |
-
IGF-1, insulin-like growth factor-1; SNP, single-nucleotide polymorphism; IVW, inverse variance weighting; OR, odds ratio; CI, confidence interval.
Table 4
Sex-specific associations of genetically testosterone and estradiol levels with COVID-19 risk.
| Exposure | Method | Susceptibility | Hospitalization | Severity | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Male | Female | Male | Female | ||||||||
| OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | ||
| Testosterone | IVW | 0.96 (0.90, 1.05) | 0.463 | 1.06 (0.97, 1.15) | 0.214 | 0.96 (0.83, 1.10) | 0.547 | 1.03 (0.87, 1.22) | 0.731 | 1.07 (0.89, 1.27) | 0.479 | 0.88 (0.69, 1.11) | 0.269 |
| MR-Egger | 0.97 (0.86, 1.09) | 0.644 | 1.04 (0.85, 1.26) | 0.713 | 0.88 (0.71, 1.10) | 0.270 | 1.13 (0.76, 1.69) | 0.549 | 0.81 (0.62, 1.08) | 0.152 | 0.68 (0.39, 1.18) | 0.169 | |
| Weighted median | 0.93 (0.83, 1.04) | 0.184 | 1.06 (0.94, 1.19) | 0.370 | 0.89 (0.72, 1.10) | 0.277 | 1.08 (0.84, 1.39) | 0.523 | 0.89 (0.67, 1.19) | 0.438 | 0.81 (0.57, 1.14) | 0.227 | |
| p for intercept | 1.00 (1.00, 1.00) | 0.998 | 1.00 (0.99, 1.01) | 0.854 | 1.00 (1.00, 1.01) | 0.348 | 1.00 (0.99, 1.01) | 0.615 | 1.01 (1.00, 1.02) | 0.017 | 1.01 (0.99, 1.03) | 0.314 | |
| MR-PRESSO | 0.97 (0.90, 1.05) | 0.464 | 1.06 (0.97, 1.15) | 0.216 | 0.96 (0.83, 1.10) | 0.549 | 1.03 (0.87, 1.22) | 0.732 | 1.07 (0.89, 1.27) | 0.478 | 0.88 (0.69, 1.11) | 0.270 | |
| Estradiol | IVW | 0.99 (0.89, 1.11) | 0.923 | 0.95 (0.71, 1.26) | 0.724 | 0.98 (0.81, 1.18) | 0.826 | 1.04 (0.63, 1.73) | 0.873 | 0.90 (0.71, 1.15) | 0.403 | 1.39 (0.74, 7.15) | 0.310 |
| MR-Egger | 1.00 (0.73, 1.36) | 0.993 | 0.89 (0.59, 1.34) | 0.598 | 0.93 (0.52, 1.67) | 0.812 | 1.15 (0.56, 2.34) | 0.719 | 0.61 (0.29, 6.15) | 0.233 | 1.76 (0.74, 3.15) | 0.234 | |
| Weighted median | 1.05 (0.92, 1.20) | 0.432 | 0.95 (0.68, 1.32) | 0.745 | 0.93 (0.74, 1.16) | 0.508 | 1.32 (0.67, 2.57) | 0.422 | 0.88 (0.65, 1.15) | 0.411 | 1.96 (0.81, 5.15) | 0.135 | |
| p for intercept | 1.00 (0.96, 1.04) | 0.980 | 1.00 (0.99, 1.02) | 0.669 | 1.01 (0.94, 1.08) | 0.856 | 0.99 (0.96, 1.02) | 0.707 | 1.05 (0.96, 0.15) | 0.312 | 0.99 (0.95, 0.15) | 0.441 | |
| MR-PRESSO | 0.99 (0.89, 1.11) | 0.925 | 0.95 (0.71, 1.26) | 0.732 | 0.98 (0.81, 1.18) | 0.831 | 1.04 (0.63, 1.73) | 0.877 | 0.90 (0.71, 1.15) | 0.425 | 1.39 (0.74, 2.63) | 0.335 | |
-
OR, odds ratio; CI, confidence interval; IVW, inverse variance weighting.
Table 5
Associations of serum E2 levels instrumented by rs7173595 in the CYP19A1 gene region with COVID-19 outcomes.
| Sex | Phenotype | beta | SE | OR (95% CI) | p Effect |
|---|---|---|---|---|---|
| Female | Susceptibility | –1.14 | 0.88 | 0.32 (0.06, 1.80) | 0.195 |
| Hospitalization | –1.27 | 1.60 | 0.28 (0.01, 6.46) | 0.426 | |
| Severity | –1.49 | 2.06 | 0.22 (0.00, 12.73) | 0.469 | |
| Male | Susceptibility | –1.00 | 0.77 | 0.37 (0.08, 1.67) | 0.195 |
| Hospitalization | –1.11 | 1.40 | 0.33 (0.02, 5.11) | 0.426 | |
| Severity | –1.31 | 1.80 | 0.27 (0.01, 9.26) | 0.469 |
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E2, estradiol; OR, odds ratio; CI, confidence interval.
Table 6
Testosterone, SHBG, IGF-1, and COVID-19 outcomes in Mendelian randomization (MR) analyses adjusting BMI.
| Exposure | Method | Susceptibility | Hospitalization | Severity | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SNPs | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | SNPs | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | SNPs | OR (95% CI) | p Effect | p Heterogeneity | p Intercept | ||
| Testosterone | IVW | 306 | 0.95 (0.83,1.07) | 0.386 | 0.006 | – | 294 | 0.83 (0.64,1.06) | 0.134 | 0.041 | – | 307 | 0.84 (0.60,1.17) | 0.304 | 0.030 | – |
| MR-Egger | 0.93 (0.77,1.13) | 0.484 | 0.006 | 0.855 | 0.83 (0.56,1.21) | 0.324 | 0.038 | 0.991 | 0.83 (0.50,1.37) | 0.466 | 0.027 | 0.949 | ||||
| Weighted median | 0.90 (0.72,1.12) | 0.331 | – | – | 0.82 (0.52,1.28) | 0.375 | – | – | 0.71 (0.42,1.21) | 0.214 | – | – | ||||
| Simple mode | 1.13 (0.70,1.82) | 0.610 | – | – | 0.68 (0.24,1.91) | 0.465 | – | – | 0.37 (0.07,1.88) | 0.229 | – | – | ||||
| Weighted mode | 0.95 (0.79,1.13) | 0.540 | – | – | 0.81 (0.56,1.17) | 0.273 | – | – | 0.65 (0.40,1.06) | 0.085 | – | – | ||||
| MR-PRESSO | 0.94 (0.83,1.07) | – | – | – | 0.83 (0.64,1.06) | – | – | – | 0.83 (0.64,1.06) | – | – | – | ||||
| SHBG | IVW | 308 | 0.90 (0.79,1.04) | 0.160 | 0.002 | – | 198 | 0.84 (0.64,1.10) | 0.209 | 0.047 | – | 309 | 0.89 (0.62,1.26) | 0.511 | 0.058 | – |
| MR-Egger | 0.94 (0.76,1.15) | 0.538 | 0.001 | 0.663 | 0.81 (0.54,1.21) | 0.299 | 0.043 | 0.794 | 0.89 (0.53,1.49) | 0.666 | 0.054 | 0.978 | ||||
| Weighted median | 0.90 (0.71,1.13) | 0.356 | – | – | 0.81 (0.52,1.28) | 0.377 | – | – | 0.72 (0.42,1.23) | 0.230 | – | – | ||||
| Simple mode | 1.05 (0.60,1.84) | 0.860 | – | – | 1.25 (0.42,3.78) | 0.689 | – | – | 0.97 (0.22,4.22) | 0.967 | – | – | ||||
| Weighted mode | 0.94 (0.77,1.15) | 0.570 | – | – | 0.81 (0.55,1.20) | 0.295 | – | – | 0.72 (0.43,1.22) | 0.224 | – | – | ||||
| MR-PRESSO | 0.90 (0.79,1.04) | – | – | – | 0.84 (0.64,1.10) | – | – | – | 0.89 (0.62,1.26) | – | – | – | ||||
| IGF-1 | IVW | 15 | 0.76 (0.60,0.96) | 0.021 | 0.172 | – | 15 | 0.61 (0.41,0.90) | 0.014 | 0.688 | – | 17 | 0.84 (0.52,1.38) | 0.497 | 0.534 | – |
| MR- Egger | 0.88 (0.58,1.33) | 0.554 | 0.168 | 0.390 | 0.77 (0.39,1.50) | 0.458 | 0.676 | 0.403 | 1.55 (0.71,3.39) | 0.284 | 0.757 | |||||
| Weighted median | 0.75 (0.57,0.99) | 0.046 | – | – | 0.75 (0.45,1.24) | 0.260 | – | – | 0.75 (0.38,1.48) | 0.410 | – | – | ||||
| Simple mode | 0.65 (0.38,1.11) | 0.135 | – | – | 0.64 (0.30,1.37) | 0.265 | – | – | 0.75 (0.25,2.31) | 0.629 | – | – | ||||
| Weighted mode | 0.76 (0.56,1.03) | 0.096 | – | – | 0.71 (0.44,1.15) | 0.185 | – | – | 0.72 (0.36,1.47) | 0.383 | – | – | ||||
| MR-PRESSO | 0.76 (0.60,0.96) | – | – | – | 0.61 (0.43,0.86) | – | – | – | 0.84 (0.53,1.35) | – | – | – | ||||
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SNP, single-nucleotide polymorphism; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighting; SHBG, sex hormones-binding globulin; IGF-1, insulin-like growth factor-1.
Additional files
-
MDAR checklist
- https://cdn.elifesciences.org/articles/79720/elife-79720-mdarchecklist1-v2.docx
-
Supplementary file 1
Genetic instruments for testosterone, estrogen, SHBG, and IGF-1.
- https://cdn.elifesciences.org/articles/79720/elife-79720-supp1-v2.docx
-
Reporting standard 1
Reporting checklist for case-control study.
- https://cdn.elifesciences.org/articles/79720/elife-79720-repstand1-v2.docx
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Genetically predicted high IGF-1 levels showed protective effects on COVID-19 susceptibility and hospitalization: a Mendelian randomisation study with data from 60 studies across 25 countries
eLife 11:e79720.
https://doi.org/10.7554/eLife.79720
