Fabiola Del Greco M, Luisa Foco1, Alexander Teumer2, Niek Verweij3, Giuseppe Paglia1, Viviana Meraviglia4, Roberto Melotti1, Vladimir Vukovic1, Werner Rauhe5, Peter K Joshi6, Ayse Demirkan7,8, Stephan B Felix2, Maik Pietzner9,10, M Abdullah Said3, Yordi J van de Vegte3, Pim van der Harst3, Alan F Wright11, Andrew A Hicks1, Harry Campbell6, Marcus Dörr12,10, Harold Snieder13, James F Wilson6,11, Peter P Pramstaller1, Alessandra Rossini1, Cristian Pattaro1. 1. Institute for Biomedicine, Eurac Research, Affiliated to the University of Lübeck, Bolzano, Italy (G.P., L.F., R.M., V.V., A.A.H., P.P.P., A.R., C.P.). 2. Institute for Community Medicine (A.T., S.B.F.), University Medicine Greifswald, Germany. 3. Department of Cardiology (N.V., M.A.S., Y.J.v.d.V., P.v.d.H.), University of Groningen, University Medical Center Groningen, The Netherlands. 4. Leiden University Medical Center, The Netherlands (V.M.). 5. Department of Cardiology, San Maurizio Hospital, Bolzano, Italy (W.R.). 6. Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics (J.F.W., H.C., P.K.J.), University of Edinburgh, Scotland, United Kingdom. 7. Department of Anatomy and Embryology and Department of Human Genetics (A.D.). 8. Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands (A.D.). 9. Institute of Clinical Chemistry and Laboratory Medicine (M.P.), University Medicine Greifswald, Germany. 10. German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Germany (M.P., M.D.). 11. MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine (A.F.W., J.F.W.), University of Edinburgh, Scotland, United Kingdom. 12. Department of Internal Medicine B (M.D.), University Medicine Greifswald, Germany. 13. Department of Epidemiology (H.S.), University of Groningen, University Medical Center Groningen, The Netherlands.
Abstract
BACKGROUND: Lipids are increasingly involved in cardiovascular risk prediction as potential proarrhythmic influencers. However, knowledge is limited about the specific mechanisms connecting lipid alterations with atrial conduction. METHODS: To shed light on this issue, we conducted a broad assessment of 151 sphingo- and phospholipids, measured using mass spectrometry, for association with atrial conduction, measured by P wave duration (PWD) from standard electrocardiograms, in the MICROS study (Microisolates in South Tyrol) (n=839). Causal pathways involving lipidomics, body mass index (BMI), and PWD were assessed using 2-sample Mendelian randomization analyses based on published genome-wide association studies of lipidomics (n=4034) and BMI (n=734 481), and genetic association analysis of PWD in 5 population-based studies (n=24 236). RESULTS: We identified an association with relative phosphatidylcholine 38:3 (%PC 38:3) concentration, which was replicated in the ORCADES (Orkney Complex Disease Study; n=951), with a pooled association across studies of 2.59 (95% CI, 1.3-3.9; P=1.1×10-4) ms PWD per mol% increase. While being independent of cholesterol, triglycerides, and glucose levels, the %PC 38:3-PWD association was mediated by BMI. Results supported a causal effect of BMI on both PWD ( P=8.3×10-5) and %PC 38:3 ( P=0.014). CONCLUSIONS: Increased %PC 38:3 levels are consistently associated with longer PWD, partly because of the confounding effect of BMI. The causal effect of BMI on PWD reinforces evidence of BMI's involvement into atrial electrical activity.
BACKGROUND:Lipids are increasingly involved in cardiovascular risk prediction as potential proarrhythmic influencers. However, knowledge is limited about the specific mechanisms connecting lipid alterations with atrial conduction. METHODS: To shed light on this issue, we conducted a broad assessment of 151 sphingo- and phospholipids, measured using mass spectrometry, for association with atrial conduction, measured by P wave duration (PWD) from standard electrocardiograms, in the MICROS study (Microisolates in South Tyrol) (n=839). Causal pathways involving lipidomics, body mass index (BMI), and PWD were assessed using 2-sample Mendelian randomization analyses based on published genome-wide association studies of lipidomics (n=4034) and BMI (n=734 481), and genetic association analysis of PWD in 5 population-based studies (n=24 236). RESULTS: We identified an association with relative phosphatidylcholine 38:3 (%PC 38:3) concentration, which was replicated in the ORCADES (Orkney Complex Disease Study; n=951), with a pooled association across studies of 2.59 (95% CI, 1.3-3.9; P=1.1×10-4) ms PWD per mol% increase. While being independent of cholesterol, triglycerides, and glucose levels, the %PC 38:3-PWD association was mediated by BMI. Results supported a causal effect of BMI on both PWD ( P=8.3×10-5) and %PC 38:3 ( P=0.014). CONCLUSIONS: Increased %PC 38:3 levels are consistently associated with longer PWD, partly because of the confounding effect of BMI. The causal effect of BMI on PWD reinforces evidence of BMI's involvement into atrial electrical activity.
Entities:
Keywords:
Mendelian randomization analysis; body mass index; genome-wide association study; mass spectrometry; phosphatidylcholine 38:3
Authors: David B Emmert; Vladimir Vukovic; Nikola Dordevic; Christian X Weichenberger; Chiara Losi; Yuri D'Elia; Claudia Volpato; Vinicius V Hernandes; Martin Gögele; Luisa Foco; Giulia Pontali; Deborah Mascalzoni; Francisco S Domingues; Rupert Paulmichl; Peter P Pramstaller; Cristian Pattaro; Alessandra Rossini; Johannes Rainer; Christian Fuchsberger; Marzia De Bortoli Journal: Biomolecules Date: 2021-11-09
Authors: Chiara Volani; Johannes Rainer; Vinicius Veri Hernandes; Viviana Meraviglia; Peter Paul Pramstaller; Sigurður Vidir Smárason; Giulio Pompilio; Michela Casella; Elena Sommariva; Giuseppe Paglia; Alessandra Rossini Journal: Metabolites Date: 2021-03-25