Regional differences in reported Covid-19 cases show genetic correlations with higher socio-economic status and better health, potentially confounding studies on the genetics of disease susceptibility
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Abstract
Background
In March 2020, England showed a rapid increase in Covid-19 cases. Susceptibility for infectious diseases like Covid-19 is likely to be partly genetic. Mapping the genetic susceptibility for Covid-19 outcomes may reveal biological mechanisms that could potentially aid in drug or vaccine developments. However, as the disease spreads unevenly across the country, regional allele frequency differences could become spuriously associated with disease prevalence.
Methods
A regional genome-wide association study (RGWAS) was conducted in 396,042 individuals from England to investigate the association between 1.2 million genetic variants and regional differences in daily reported Covid-19 cases from March 1 st to April 18 th 2020.
Results
The polygenic signal increases during the first weeks of March, peaking at March 13 th with the measured genetic variants explaining ∼3% of the variance, including two genome-wide significant loci. The explained variance starts to drop at the end of March and reaches almost zero on April 18 th . The majority of this temporary polygenic signal is due to genes associated with higher educational attainment and better health.
Conclusions
The temporary positive relationship between Covid-19 cases and regional socio-economic status (SES) at the beginning of the Covid-19 outbreak may reflect 1) a higher degree of international travelers, 2) more social contacts, and/or 3) better testing capacities in higher SES regions. These signals are in the opposite direction of expected disease risk increasing effects, which has the potential to cancel out signals of interest. Genetic association studies should be aware of the timing and location of cases as this can introduce interfering polygenic signals that reflect regional differences in genes associated with behavior.
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SciScore for 10.1101/2020.04.24.20075333: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The UKB dataset was projected onto the first two principal components (PCs) from the 2,504 participants of the 1000 Genomes Project, using HM3 SNPs with minor allele frequency (MAF) > 0.01 in both datasets. 1000 Genomes Projectsuggested: (1000 Genomes Project and AWS, RRID:SCR_008801)Assignments for European, African, East-Asian, and South-Asian ancestries were based on > 0.9 posterior-probability of belonging to the 1000 Genomes reference cluster, with the remaining participants classified as Admixed. 1000 Genomessuggested: (1000 Genomes Project and AWS, RRID:SCR_008801)Genetic … SciScore for 10.1101/2020.04.24.20075333: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The UKB dataset was projected onto the first two principal components (PCs) from the 2,504 participants of the 1000 Genomes Project, using HM3 SNPs with minor allele frequency (MAF) > 0.01 in both datasets. 1000 Genomes Projectsuggested: (1000 Genomes Project and AWS, RRID:SCR_008801)Assignments for European, African, East-Asian, and South-Asian ancestries were based on > 0.9 posterior-probability of belonging to the 1000 Genomes reference cluster, with the remaining participants classified as Admixed. 1000 Genomessuggested: (1000 Genomes Project and AWS, RRID:SCR_008801)Genetic Relatedness Matrix: The genetic relatedness matrices (GRMs) contain genetic relationships between all individuals based on a slightly LD pruned HapMap 3 SNP set (LD-pruning parameters used in PLINK: window size = 1000 variant count, step size = 100, r2 = 0.9 and MAF > 0.01, resulting in 575,293 SNPs). HapMapsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The same limitations that were described in the last implementation of the RGWAS approach remain11, including the ascertainment bias in the UK Biobank towards a more healthy and higher educated population and the unknown bias in the regional data (in this case, the bias in the regional data may be related to testing capacity and/or hospital access), and gene-environment correlations inflating genetic signals. This study combines longitudinal regional-level data with individual-level genotype data and GWAS summary statistics from 10 traits related to SES and health to investigate the nature of the polygenic effects associated with reported regional differences in Covid-19 infections. As large individual-level GWASs of Covid-19 susceptibilty are on the way,8 it is important to be aware that polygenic signals of Covid-19 susceptibility can contain genome-wide significant signals that reflect social differences in disease prevalence and/or testing capacity, and that these signals can vary over time.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2020.04.24.20075333: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The UKB dataset was projected onto the first two principal components ( PCs ) from the 2,504 participants of the 1000 Genomes Project , using HM3 SNPs with minor allele frequency ( MAF ) > 0.01 in both datasets . 1000 Genomes Projectsuggested: (1000 Genomes Project and AWS, SCR_008801)Assignments for European , African , East-Asian , and South-Asian ancestries were based on > 0.9 posterior-probability of belonging to the 1000 Genomes reference cluster , with the remaining participants classified as Admixed. …SciScore for 10.1101/2020.04.24.20075333: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The UKB dataset was projected onto the first two principal components ( PCs ) from the 2,504 participants of the 1000 Genomes Project , using HM3 SNPs with minor allele frequency ( MAF ) > 0.01 in both datasets . 1000 Genomes Projectsuggested: (1000 Genomes Project and AWS, SCR_008801)Assignments for European , African , East-Asian , and South-Asian ancestries were based on > 0.9 posterior-probability of belonging to the 1000 Genomes reference cluster , with the remaining participants classified as Admixed. 1000 Genomessuggested: (1000 Genomes Project and AWS, SCR_008801)11 Genetic Relatedness Matrix The genetic relatedness matrices ( GRMs ) contain genetic relationships between all individuals based on a slightly LD pruned HapMap 3 SNP set ( LD-pruning parameters used in PLINK: window size = 1000 variant count , step size = 100 , r2 = 0.9 and MAF > 0.01 , resulting in 575,293 SNPs) . HapMapsuggested: NoneResults from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).
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