Aims/hypothesis: Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions.
Methods: Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software.
Results: All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction.
Conclusions/interpretation: Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.
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http://dx.doi.org/10.1007/s00125-016-4184-0 | DOI Listing |
Background: Although Amyloid-beta and Tau are the hallmarks of Alzheimer's Disease (AD), other protein pathways such as endothelial dysfunction may be involved and may precede cognitive symptoms. Our objective was to characterize the cerebrospinal fluid (CSF) proteomic profiles focusing on cardiometabolic-related protein pathways in individuals on the AD spectrum.
Methods: We performed CSF and plasma-targeted proteomics (276 proteins) from 354 participants of the Brain Stress Hypertension and Aging Program (BSHARP), of which 8% had preclinical AD, and 24% had MCI due to AD.
J Am Heart Assoc
January 2025
Center for Non-Communicable Disease Management Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.
Background: The differential impact of serum lipids and their targets for lipid modification on cardiometabolic disease risk is debated. This study used Mendelian randomization to investigate the causal relationships and underlying mechanisms.
Methods: Genetic variants related to lipid profiles and targets for lipid modification were sourced from the Global Lipids Genetics Consortium.
Background: Clonal hematopoiesis of indeterminate potential (CHIP) is the age-related presence of expanded somatic clones secondary to leukemogenic driver mutations and is associated with cardiovascular (CV) disease and mortality. We sought to evaluate relationships between CHIP with cardiometabolic diseases and incident outcomes in high-risk individuals.
Methods: CHIP genotyping was performed in 8469 individuals referred for cardiac catheterization at Duke University (CATHGEN study) to identify variants present at a variant allele fraction (VAF) ≥2%.
Healthcare (Basel)
January 2025
Faculty of Physical Education and Sports, Wroclaw University of Health and Sport Sciences, 51-612 Wrocław, Poland.
To date, the health effects of karate have not been identified. Therefore, the aim of this article is to learn more about the health effects of karate training based on a review of current research. The Scopus database was searched from 2000 onwards for available articles related only to karate.
View Article and Find Full Text PDFCommun Biol
January 2025
Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, so together may provide a more complete picture of sleep health, while illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches.
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