Duke University’s COVID-19 Genetics And Phenotype Study Discovers Alternate Associations With SARS-CoV-2 Risk Loci.

COVID-19-Genetics: Researchers from Duke Molecular Physiology Institute-North Carolina, USA, Duke University Department of Medicine-North Carolina, USA and Duke Clinical Research Institute-North Carolina, USA have in a new study discovered alternate associations with SARS-CoV-2 risk loci.


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Genetic loci associated with risk of severe COVID-19 infection were identified and it was found that individuals with complicated COVID-19 infections often have multiple comorbidities.
 
The study team wanted to identify known and unidentified comorbidities associated with genetic loci linked to risk of severe COVID-19 infection.
 
A detailed Phenome Wide Association Study (PheWAS) was conducted in 247,448 unrelated, white individuals from the UK Biobank to test the association of 1,402 unique phenotypes with ten genome-wide significant severe-COVID risk single nucleotide polymorphisms (SNP) identified from prior studies. A validation PheWAS was conducted in 2,247 white individuals from the CATHGEN.
 
The study findings showed that four of the ten tested genetic loci showed significant phenotypic associations in UK Biobank after FDR adjustment.
 
Vascular dementia significantly associated with rs7271165 near TMEM65 on 8q24.13 in individuals with the C risk allele (OR 5.66 [95% CI 2.21-11.85], q=0.049).
 
The study findings also identified 40 novel phenotype associations with rs657152 on 9q34.2 coinciding with the ABO gene with individuals with the A COVID risk allele having higher odds of heart failure (OR 1.09 [95% CI 1.03-1.14], q=0.004), diabetes mellitus (OR 1.05 [95% CI 1.02-1.07], q=0.004) and hypercholesterolemia (OR 1.04 [95% CI 1.02-1.06], q=6.3x10-5).
 
Eight phenotypes associated with rs1819040 near KANSL1 on 17q21.31 in individuals with the A risk allele including atrial fibrillation and flutter (OR 1.07 [95% CI 1.04-1.10], q=0.0084) and pulmonary fibrosis (OR 0.80 [95% CI 0.71-0.89], q=0.035).
 
Ten novel phenotypic associations were identified in association with rs74956615 on 19p13.2 near the TYK2 gene including individuals with the A COVID risk allele having lower odds of psoriatic arthropathy (OR 0.31 [95% CI 0.20-0.47], q=4.5x10-5), rheumatoid arthritis (OR 0.83 [95% CI 0.64-0.83], p=1.4x10-6) and thyrotoxicosis with or without goiter (OR 0.77 [95% CI 0.68-0.87], p-6.9x10-5).
 
Two associations for rs1819040 (KANSL1) and seven associations for rs74956615 (TYK2) validated in CATHGEN.
 
The study findings identified novel phenotypic associations with risk alleles for severe COVID-19 infection. Interestingly, the ABO locus was associated with comorbidities that are also risk factors for sever e COVID-19 infection, suggesting that this locus has pleiotropic effects and provides a potential mechanism for this association.
 
Interestingly the 19p13 locus was associated with lower risk of autoimmune disease.
 
The stud findings may have broad implications for the importance of multiple comorbidities across both infectious and non-infectious diseases and may provide insight in the molecular function of the genes near these genetic risk loci.
 
The study findings were published on a preprint server and are currently being peer reviewed. https://www.medrxiv.org/content/10.1101/2021.12.08.21267433v1
 
The COVID-19 disease displays a broad array of symptoms and can vary widely and alarmingly in severity. Many report only mild symptoms such as coughing or temporary loss of taste (anosmia), while others end up in intensive care with respiratory failure and multiple organ failure.
 
To date, there have been numerous studies that have examined clinical comorbidities, such as age, gender, and ethnicity, as well as a variety of medical conditions, but there are significantly fewer studies on the genetic factors associated with severe COVID-19.
 
The study team from Duke University have been investigating genetic associations with more severe disease and examining the associations that certain genetic features have with other diseases.
 
The study team used data from the UK Biobank, a population-based cohort with genetic and phenotypic data on 500,000 individuals between 40 and 69 years old.
 
The team examined data for ~247,000 of these individuals. In addition, a validation cohort was also created, using data from ~2,300 individuals from the CATHGEN study, examining cardiac catheterization.
 
The study team selected ten single nucleotide polymorphisms (SNPs) that had been previously identified as COVID-19 genetic risk variants.
 
These included: rs11385942, rs1886814, rs72711165, rs657152, rs10735079, rs1819040, rs77534576, rs210969 and rs2236757 and four SNPs more recently identified.

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Detailed logistic regression was performed to analyze for disease outcome, and results were adjusted for age, genotyping array, gender, and five principal genetic components. Significant associations were considered at an FDR adjusted value.
 
The COVID-19-Genetics study team found that four of the tested genetic loci associated with severe COVID-19 risk showed significant phenotypic associations in the UK Biobank after FDR adjustment. Vascular dementia is significantly associated with rs72711165.
 
Interestingly there were 40 phenotype associations for rs657152 after FDR adjustment, 26 of which were novel and had not previously been described. These included heart failure, hypercholesterolemia, diabetes, and lower odds of certain gastrointestinal disorders.
 
However, none of these findings were validated in CATHGEN.
 
rs1819040 was associated with eight phenotypes, including flutter, pulmonary fibrosis, and glaucoma. However only glaucoma was validated in CATHGEN.
 
It was found that seven out of ten phenotypes were associated with rs74956615, including psoriasis, arthritis, and hypothyroidism.
 
Interestingly no phenotypes were associated with rs11385942 at the 3p21.31 locus, but 68 phenotypes were nominally associated, all of which were novel findings. These included obstructive chronic bronchitis, hypertensive heart disease, and atrial fibrillation, as well as lower odds of eosinophilia. The association between memory loss and another neurological disorder was validated in CATHGEN.
 
rs1886814 also showed only nominal associations, including for nephrotic syndrome, chronic lymphocytic thyroiditis and lower odds of empyema, none of which were validated in CATHGEN.
 
The study found no phenotypes were significant for rs10735709, but 85 phenotypes were nominally associated, generally showing lower odds of circulatory disorders. One of these nominal associations was validated in CATHGEN, for lower odds of benign neoplasm of the colon.
 
Also, no phenotypes were also associated with rs77534576 or rs2236757, but both showed ~80 nominal associations, rs 10735709 with greater odds of renal failure, Hodgkin’s disease, hypertensive complications and post-inflammatory pulmonary fibrosis, and rs 2236757 with viral pneumonia, thyroiditis and lower odds of bacterial infection. Only the pulmonary fibrosis and bacterial infection associations were validated in CATHGEN.
 
The study team highlight that their research has identified novel phenotypic associations with the risk alleles from four of the ten loci that they chose to identify.
 
Although these loci are associated with more severe COVID-19 risk, they also show connections to many other diseases. The study team suggest that the increased risk these genetic markers carry for diseases such as autoimmune/inflammatory disorders, or cardiovascular disease, could in turn, increase the risk of severe COVID-19, either through comorbidities, increased complications, or simply increased burdens on the body and the immune system.
 
The study findings could be valuable for other geneticists, healthcare workers, and potentially even drug manufacturers. They could allow for more directed treatment, as well as indicating targets that might make it easier for tests for hospitals and clinics to identify those most at-risk.
 
The study findings also reassert Thailand Medical News’ view that COVID-19 treatments should adopt a personalized medicine approach.
 
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