Life-Time Covariation of Major Cardiovascular Diseases: A 40-Year Longitudinal Study and Genetic Studies.
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Lind L, Sundström J, Ärnlöv J, Ingelsson M, Henry A, Lumbers RT, Lampa E
Circ Genom Precis Med 14 (2) e002963 [2021-04-00; online 2021-02-26]
It is known that certain cardiovascular diseases (CVD) are associated, like atrial fibrillation and stroke. However, for other CVDs, the links and temporal trends are less studied. In this longitudinal study, we have investigated temporal epidemiological and genetic associations between different CVDs. The ULSAM (Uppsala Longitudinal Study of Adult Men; 2322 men aged 50 years) has been followed for 40 years regarding 4 major CVDs (incident myocardial infarction, ischemic stroke, heart failure, and atrial fibrillation). For the genetic analyses, publicly available data were used. Using multistate modeling, significant relationships were seen between pairs of all of the 4 investigated CVDs. However, the risk of obtaining one additional CVD differed substantially both between different CVDs and between their temporal order. The relationship between heart failure and atrial fibrillation showed a high risk ratio (risk ratios, 24-26) regardless of the temporal order. A consistent association was seen also for myocardial infarction and atrial fibrillation but with a lower relative risk (risk ratios, 4-5). In contrast, the risk of receiving a diagnosis of heart failure following a myocardial infarction was almost twice as high as for the reverse temporal order (risk ratios, 16 versus 9). Genetic loci linked to traditional risk factors could partly explain the observed associations between the CVDs, but pathway analyses disclosed also other pathophysiological links. During 40 years, all of the 4 investigated CVDs were pairwise associated with each other regardless of the temporal order of occurrence, but the risk magnitude differed between different CVDs and their temporal order. Genetic analyses disclosed new pathophysiological links between CVDs.
Bioinformatics Support for Computational Resources [Service]
NGI Uppsala (SNP&SEQ Technology Platform) [Service]
National Genomics Infrastructure [Service]
PubMed 33635119
DOI 10.1161/CIRCGEN.120.002963
Crossref 10.1161/CIRCGEN.120.002963