ReviewThe Clinical biochemist. Reviews2014
Genetic insights into cardiometabolic risk factors.
Review in The Clinical biochemist. Reviews, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review and meta-analysis on the association between CD36 rs1761667 polymorphism and cardiometabolic risk factors in adults.Scientific reports · 2022Pooled it
- Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes.International journal of molecular sciences · 2020Pooled it
- Clinical staging to guide management of metabolic disorders and their sequelae: a European Atherosclerosis Society consensus statement.European heart journal · 2025Article
- Immune and Vascular Function in Cardiometabolic Disorders: Interplay With Sex Differences and Impact on Incretin Therapy.Acta physiologica (Oxford, England) · 2025Review
- Article
- Associations of nonoccupational sedentary behaviors with cardiometabolic outcomes: coronary artery risk development in young adults (CARDIA).Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2025Article
- Childhood cardiometabolic risk factors associated with the perinatal environment of the maternal-paternal-child triad.Pediatric obesity · 2024Article
- Dietary Sugar Research in Preschoolers: Methodological, Genetic, and Cardiometabolic Considerations.Reviews in cardiovascular medicine · 2023Review
- Genetic Markers of Insulin Resistance and Atherosclerosis in Type 2 Diabetes Mellitus Patients with Coronary Artery Disease.Metabolites · 2023Review
- Maternal hyperandrogenism is associated with a higher risk of type 2 diabetes mellitus and overweight in adolescent and adult female offspring: a long-term population-based follow-up study.Journal of endocrinological investigation · 2022Article
- Genome-wide analysis of DNA methylation and risk of cardiovascular disease in a Chinese population.BMC cardiovascular disorders · 2021Article
- Association of genetic and epigenetic variants in one-carbon metabolism gene with folate treatment response in hyperhomocysteinaemia.European journal of clinical nutrition · 2020Article
- Searching for parent-of-origin effects on cardiometabolic traits in imprinted genomic regions.European journal of human genetics : EJHG · 2020Article
- Recent Evidence on the Impact of Ramadan Diurnal Intermittent Fasting, Mealtime, and Circadian Rhythm on Cardiometabolic Risk: A Review.Frontiers in nutrition · 2020Review
- Mediators of insulin resistance & cardiometabolic risk: Newer insights.The Indian journal of medical research · 2018Article
- Taking Systems Medicine to Heart.Circulation research · 2018Review
- Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey.PLoS genetics · 2018Article
- Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis.Experimental and therapeutic medicine · 2018Article
- Genetic variants in microRNA genes and targets associated with cardiovascular disease risk factors in the African-American population.Human genetics · 2018Article
- Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study.Human genetics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as 'cardiometabolic' risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.
Identifiers
24659834PMC3961996What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.