1,144 research outputs found
sj-docx-1-sjp-10.1177_14034948221119634 – Supplemental material for Marital status and genetic liability independently predict coronary heart disease incidence
No full textSupplemental material, sj-docx-1-sjp-10.1177_14034948221119634 for Marital status and genetic liability independently predict coronary heart disease incidence by Karri Silventoinen, Hannu Lahtinen, Kaarina Korhonen, George Davey Smith, Samuli Ripatti, Tim Morris and Pekka Martikainen in Scandinavian Journal of Public Health</p
KardioKompassi yhdistää perimän ja perinteiset riskitekijät sepelvaltimotaudin ehkäisyssä
No full textNon peer reviewe
Integrating lipidomics and genomics : emerging tools to understand cardiovascular diseases
No full textCardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.Peer reviewe
Genetic prediction of medication use patterns in cardiometabolic disease
No full textBy performing a large-scale biobank-based genome-wide association study, we identified a strong link between the underlying risk of cardiometabolic disease and patterns of lifelong medication use in hyperlipidemia, hypertension and type 2 diabetes. We discover hundreds of genetic predictors of medication use behavior and show medication-use-enhanced applications for polygenic prediction in cardiometabolic diseases.Non peer reviewe
sj-pdf-1-cep-10.1177_03331024211045651 - Supplemental material for Polygenic risk provides biological validity for the ICHD-3 criteria among Finnish migraine families
No full textSupplemental material, sj-pdf-1-cep-10.1177_03331024211045651 for Polygenic risk provides biological validity for the ICHD-3 criteria among Finnish migraine families by Paavo Häppölä, Padhraig Gormley, Marjo E Nuottamo, Ville Artto, Marja-Liisa Sumelahti, Markku Nissilä, Petra Keski-Säntti, Matti Ilmavirta, Mari A Kaunisto, Eija I Hämäläinen, Samuli Ripatti, Matti Pirinen, Maija Wessman, Aarno Palotie, Mikko Kallela and International Headache Genetics Consortium (IHGC) in Cephalalgia</p
Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation
No full textBackground: Atrial fibrillation (AF) risk estimation using clinical factors with or without genetic information may identify AF screening candidates more accurately than the guideline-based age threshold of >= 65 years. Methods: We analyzed 4 samples across the United States and Europe (derivation: UK Biobank; validation: FINRISK, Geisinger MyCode Initiative, and Framingham Heart Study). We estimated AF risk using the CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) score and a combination of CHARGE-AF and a 1168-variant polygenic score (Predict-AF). We compared the utility of age, CHARGE-AF, and Predict-AF for predicting 5-year AF by quantifying discrimination and calibration. Results: Among 543 093 individuals, 8940 developed AF within 5 years. In the validation sets, CHARGE-AF (C index range, 0.720-0.824) and Predict-AF (0.749-0.831) had largely comparable discrimination, both favorable to continuous age (0.675-0.801). Calibration was similar using CHARGE-AF (slope range, 0.67-0.87) and Predict-AF (0.65-0.83). Net reclassification improvement using Predict-AF versus CHARGE-AF was modest (net reclassification improvement range, 0.024-0.057) but more favorable among individuals aged = 65 years across each sample, 70 849 had AF risk = 5%, of whom 2264 (7.9%) developed AF. Of 11 379 individuals aged = 5%, 435 (3.8%) developed AF before age 65 years, with roughly half (46.9%) meeting anticoagulation criteria. Conclusions: AF risk estimation using clinical factors may prioritize individuals for AF screening more precisely than the age threshold endorsed in current guidelines. The additional value of genetic predisposition is modest but greatest among younger individuals.Peer reviewe
Large-Scale Functional Characterization of Low-Density Lipoprotein Receptor Gene Variants Improves Risk Assessment in Cardiovascular Disease
No full textLimited access to functional information of genetic variants reduces the applicability of genetic tools for precision medicine applications in cardiovascular disease. We established an automated analysis platform based on multiplexed high-content imaging and derived in-depth functional data for several hundred LDLR gene variants. Residual low-density lipoprotein receptor activity of genetic variants impacted the risk for cardiovascular disease and elevated low-density lipoprotein cholesterol as well as the utilization of lipid-lowering and combination therapy. This enables increased risk stratification for carriers of LDLR gene variants and opens up new opportunities for improved diagnosis, risk assessment, and treatment selection in familial hypercholesterolemia. (JACC Basic Transl Sci. 2025;10:170-183) (c) 2025 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer reviewe
Effect of biological sex on human circulating lipidome: An overview of the literature
No full textCardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids-low-density lipoprotein cholesterol (LDL-C), high-density lipo-protein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome-and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.Peer reviewe
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