A second update on mapping the human genetic architecture of COVID-19

Ganna, Andrea

doi:10.1101/2022.12.24.22283874

Cited by 7 publications

(7 citation statements)

References 20 publications

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“…We refer to this analysis as the SC-HGI ALL meta-analysis. Out of the 40 genome-wide significant loci associated with COVID-19 hospitalization in the last HGI release 1 , this study replicated 39 and the association was stronger than in the original study in 29 of those (supplementary Table 11). However, the variant rs13003835 located in BAZ2B did not replicate (OR=1.00, 95%CI=0.98- 1.03, p=0.644).…”

Section: Resultssupporting

confidence: 51%

“…This association was not previously reported in any GWAS of COVID-19 published to date. Interestingly, rs13003835 did not reach significance (p=0.972) in the COVID-19 HGI trans-ancestry meta-analysis including the five population groups 1 . Based on our mapping strategy (see Methods), we also prioritized PLA2R1 , LY75 , WDSUB1 , and CD302 in this locus.…”

Section: Resultsmentioning

confidence: 91%

“…A polygenic risk score (PGS) for critical COVID-19 was derived combining the variants associated with hospitalization or disease severity that have been discovered to date. We curated a list of lead variants that were: 1) associated to either severe disease or hospitalization in the latest HGIv7 release 1 (using the hospitalization weights); or 2) associated to severe disease in the latest GenOMICC meta-analysis 2 that were not reported in the latest HGI release. A total of 49 markers were used in the PGS model (see supplementary Table 13) since two variants were absent from our study.…”

Section: Methodsmentioning

confidence: 99%

“…To date, more than 50 loci associated to COVID-19 susceptibility, hospitalization, and severity have been identified using genome-wide association studies (GWAS) 1,2 . The COVID-19 Host Genetics Initiative (HGI) has made significant efforts 3 to augment the power to identify disease loci by recruiting individuals from diverse populations and conducting a trans-ancestry meta-analysis.…”

Section: Introductionmentioning

confidence: 99%

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Novel risk loci for COVID-19 hospitalization among admixed American populations

Carracedo

2023

Preprint

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The genetic basis of severe COVID-19 has been thoroughly studied and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we have conducted the largest GWAS meta-analysis for COVID-19 hospitalization in admixed Americans, comprising a total of 4,702 hospitalized cases recruited by SCOURGE and other seven participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and first discovered in Latin-American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort.

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Section: Resultssupporting

confidence: 51%

Section: Resultsmentioning

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Novel risk loci for COVID-19 hospitalization among admixed American populations

Carracedo

2023

Preprint

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“…To explore whether signals of selection overlapped with recently published GWAS associations for COVID susceptibility (27), we selected all 51 lead SNPs which reached genome-wide significance (i.e. 5 x 10 -8 ) for "Critical illness", "Hospitalized" and "Reported infection" and counted the overlap between these loci (defined by the region within 200Kbp of the lead variant) and either the LRLD or the saltiLASSi regions identified in CKB and UKB, again using permutation across the genome to provide an empirical null.…”

Section: Overlap With Sars-cov2 Susceptibility Gwas Associationsmentioning

confidence: 99%

Natural selection exerted by historical coronavirus epidemic(s): comparative genetic analysis in China Kadoorie Biobank and UK Biobank

Morris,

Lin,

Millwood

et al. 2024

Preprint

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BackgroundPathogens have been one of the primary sources of natural selection affecting modern humans. The footprints of historical selection events – “selective sweeps” – can be detected in the genomes of present-day individuals. Previous analyses of 629 samples from the 1000 Genomes Project suggested that an ancient coronavirus epidemic ∼20,000 years ago drove multiple selective sweeps in the ancestors of present-day East Asians, but not in other worldwide populations.ResultsUsing a much larger genetic dataset of 76,719 unrelated individuals from each of the China Kadoorie Biobank (CKB) and UK Biobank (UKB) to identify regions of long-range linkage disequilibrium, we further investigated signatures of past selective sweeps and how they reflect previous viral epidemics. Using independently-curated lists of human host proteins which interact physically or functionally with viruses (virus-interacting proteins; VIPs), we found enrichment in CKB for regions of long-range linkage disequilibrium at genes encoding VIPs for coronaviruses, but not DNA viruses. By contrast, we found no clear evidence for any VIP enrichment in UKB. These findings were supported by additional analyses using saltiLASSi, a selection-scan method robust to false positives caused by demographic events. By contrast, for GWAS signals for SARS-Cov2 susceptibility (critical illness, hospitalisation, and reported infection), there was no difference between UKB and CKB in the number located at or near signals of selection, as expected for a novel virus which has had no opportunity to impact the CKB/UKB study populations.ConclusionsTogether, these results provide evidence of selection events consistent with historical coronavirus epidemic(s) originating in East Asia. These results show how biobank-scale datasets and evolutionary genomics theory can provide insight into the study of past epidemics. The results also highlights how historic infectious diseases epidemics can shape the genetic architecture of present-day human populations.

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