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GWAS Study

Nationwide health, socio-economic and genetic predictors of COVID-19 vaccination status in Finland.

Hartonen T, Jermy B, Sõnajalg H et al.

37081098 PubMed ID
GWAS Study Type
419380 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

HT
Hartonen T
JB
Jermy B
SH
Sõnajalg H
VP
Vartiainen P
KK
Krebs K
VA
Vabalas A
LT
Leino T
NH
Nohynek H
SJ
Sivelä J
MR
Mägi R
DM
Daly M
OH
Ollila HM
ML
Milani L
PM
Perola M
RS
Ripatti S
GA
Ganna A
Chapter II

Abstract

Summary of the research findings

Understanding factors associated with COVID-19 vaccination can highlight issues in public health systems. Using machine learning, we considered the effects of 2,890 health, socio-economic and demographic factors in the entire Finnish population aged 30-80 and genome-wide information from 273,765 individuals. The strongest predictors of vaccination status were labour income and medication purchase history. Mental health conditions and having unvaccinated first-degree relatives were associated with reduced vaccination. A prediction model combining all predictors achieved good discrimination (area under the receiver operating characteristic curve, 0.801; 95% confidence interval, 0.799-0.803). The 1% of individuals with the highest predicted risk of not vaccinating had an observed vaccination rate of 18.8%, compared with 90.3% in the study population. We identified eight genetic loci associated with vaccination uptake and derived a polygenic score, which was a weak predictor in an independent subset. Our results suggest that individuals at higher risk of suffering the worst consequences of COVID-19 are also less likely to vaccinate.

45,202 European ancestry cases, 374,178 European ancestry controls

Chapter III

Study Statistics

Key metrics and study information

419380
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Finland, Estonia
Recruitment Country
Chapter IV

AI-Generated Summary

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