Progress in genetic association studies of plasma lipids.

This review summarizes recently published large-scale efforts elucidating the genetic architecture of lipid levels. A supplemental file with all genetic loci is provided for research purposes and we performed bioinformatic analyses of the genetic variants to give an oversight of involved pathways

Systems epidemiology of metabolomics measures reveals new relationships between lipoproteins and other small molecules

Supplementary information included online at https://link.springer.com/article/10.1007/s11306-021-01856-6.Copyright © 2022 The Author. Introduction The study of lipoprotein metabolism at the population level can provide valuable information for the organisation of lipoprotein related processes in the body. To use this information towards interventional hypotheses generation and testing, we need to be able to identify the mechanistic connections among the large number of observed correlations between the measured components of the system. Objectives To use population level metabolomics information to gain insight on their biochemical networks and metabolism. Methods Genetic and metabolomics information for 230 metabolic measures, predominately lipoprotein related, from a targeted nuclear magnetic resonance approach, in two samples of an established European cohort, totalling more than 9400 individuals analysed using phenotypic and genetic correlations, as well as Mendelian Randomisation. Results More than 20,500 phenotypic correlations were identified in the data, with almost 2000 also showing evidence of strong genetic correlation. Mendelian randomisation, provided evidence for a causal effect between 9496 pairs of metabolic measures, mainly between lipoprotein traits. The results provide insights on the organisation of lipoproteins in three distinct classes, the heterogeneity between HDL particles, and the association, or lack of, between CLA, glycolysis markers, such as glucose and citrate, and glycoproteins with lipids subfractions. Two examples for the use of the approach in systems biology of lipoproteins are presented. Conclusions Genetic variation can be used to infer the underlying mechanisms for the associations between lipoproteins for hypothesis generation and confirmation, and, together with biological information, to map complex biological processes.BHF-Turing Cardiovascular Data Science Award (BHF-Turing-19/2/1008)

Assessment of the clinical utility of adding common single nucleotide polymorphism genetic scores to classical risk factor algorithms in coronary heart disease risk prediction in UK men

Background: Risk prediction algorithms for coronary heart disease (CHD) are recommended for clinical use. However, their predictive ability remains modest and the inclusion of genetic risk may improve their performance. Methods: QRISK2 was used to assess CHD risk using conventional risk factors (CRFs). The performance of a 19 single nucleotide polymorphism (SNP) gene score (GS) for CHD including variants identified by genome-wide association study and candidate gene studies (weighted using the results from the CARDIoGRAMplusC4D meta-analysis) was assessed using the second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases). To improve the GS, five SNPs with weak evidence of an association with CHD were removed and replaced with seven robustly associated SNPs – giving a 21-SNP GS. Results: The weighted 19 SNP GS was associated with lipid traits (p<0.05) and CHD after adjustment for CRFs, (OR=1.31 per standard deviation, p=0.03). Addition of the 19 SNP GS to QRISK2 showed improved discrimination (area under the receiver operator characteristic curve 0.68 vs. 0.70 p=0.02), a positive net reclassification index (0.07, p=0.04) compared to QRISK2 alone and maintained good calibration (p=0.17). The 21-SNP GS was also associated with CHD after adjustment for CRFs (OR=1.39 per standard deviation, 1.42×10−3), but the combined QRISK2 plus GS score was poorly calibrated (p=0.03) and showed no improvement in discrimination (p=0.55) or reclassification (p=0.10) compared to QRISK2 alone. Conclusions: The 19-SNP GS is robustly associated with CHD and showed potential clinical utility in the UK population

How close are we to implementing a genetic risk score for coronary heart disease?

Introduction: Genome-wide association meta-analysis have now identified more than 150 loci where common variants (SNPs) are significantly associated with coronary heart disease (CHD) and CHD end points. Areas covered: The authors review publications from their own laboratory and published recently where identified CHD risk SNPs are used in combination, and ‘scaled’ by their effect size, to create a ‘weighted’ Genetic risk Score (GRS), which, in combination with an individual’s classical CHD risk factors, can be used to identify those at overall low, intermediate and high future risk. Those at highest risk can be offered life-style and therapeutic options to reduce their risk and those at intermediate levels can be monitored. Expert commentary: The authors discuss the selection of the best variants to be included in the GRS, and the potential utility of such scores in different clinical settings. The limitations of the current data sets and the way forward in the next 5 years is discussed

Alcohol causes an increased risk of head and neck but not breast cancer in individuals from the UK Biobank study: A Mendelian randomisation analysis

This research has been conducted using the UK Biobank Resource under project 44566 (https://www.ukbiobank.ac.uk/2018/12/genetic-and-non-genetic-factors-able-to-predict-and-modify-the-risk-of-different-types-of-cancer/). All bona fide researchers can apply to use the UK Biobank resource for health related research that is in the public interest.Copyright © The Author(s)/Funder. Alcohol intake and the risk of various types of cancers have been previously correlated. Correlation though does not always mean that a causal relationship between the two is present. Excessive alcohol consumption is also correlated with other lifestyle factors and behaviours, such as smoking and increased adiposity, that also affect the risk of cancer and make the identification and estimation of the causal effect of alcohol on cancer difficult. Here, using individual level data for 322,193 individuals from the UK Biobank, we report the observational and causal effects of alcohol consumption on types of cancer previously suggested as correlated to alcohol. Alcohol was observationally associated with cancers of the lower digestive system, head and neck and breast cancer. No associations were observed when we considered those keeping alcohol consumption below the recommended threshold of 14 units/week. When Mendelian randomisation was used to assess the causal effect of alcohol on cancer, we found that increasing alcohol consumption, especially above the recommended level, was causal to head and neck cancers but not breast cancer. Our results where replicated using a two sample MR method and data from the much larger COGS genome wide analysis of breast cancer. We conclude that alcohol is causally related to head and neck cancers, especially cancer of larynx, but the observed association with breast cancer are likely due to confounding. The suggested threshold of 14 units/week appears suitable to manage the risk of cancer due to alcohol.PhD studentship from the College of Health and Life Sciences, Brunel University London

Variation at the Klotho gene locus does not affect cognitive function in up to 335,074 British Caucasians in the UK Biobank

Version 2 issued 19 November 2019.Copyright © The Author(s)/Funder. The proportion of older adults in Western populations is increasing and there is, therefore, a need to define factors affecting maintenance of physical and cognitive health in old age. Variations in the Klotho (KL) gene, and specifically the KL-VS haplotype, have been identified by several authors as potentially influencing cognitive function and decline. We have attempted to verify the reported associations between KL variants, including the KL-VS haplotype, and cognitive function in up to 335,074 British Caucasian participants aged 40-79 years from the UK Biobank. We do not find evidence that KL-VS affects cognitive function or its decline with increasing age. We examined a further 244 KL variants and found that rs117650866 was associated with Prospective Memory, but could not replicate this in follow-up samples. In conclusion, there is insufficient evidence in the UK Biobank to support the concept that KL variants affect cognitive function or its rate of decline.Calico LLC (South San Francisco, California, United States)

Body Composition Characteristics of Type 1 Diabetes Children and Adolescents: A Hospital-Based Case-Control Study in Uganda

Background: Changes in body composition have been suggested as an intractable effect of Type 1 Diabetes Mellitus and its management. This study aims to compare body composition characteristics in a sample of young children and adolescents with Type 1 Diabetes Mellitus with healthy controls. Methods: In this case–control study, body composition was assessed using bioelectrical impedance among 328 participants. Anthropometric measurements included weight, height, upper arm, hip, and waist, circumferences; biceps; triceps; and subscapular and suprailiac skinfolds. From raw Bioelectrical impedance data, we calculated the impedance, phase angle, and height normalised resistance and reactance to assess body composition. Analysis of variance accounting for paired blocks was used to compare the two matched groups, while an independent Student’s t-test was used for intragroup comparisons among cases. Results: Waist Hip Ratio, biceps, triceps, subscapular and suprailiac skinfolds were higher among cases than in controls. Cases showed a higher Fat Mass Index, higher fasting blood glucose and higher glycated haemoglobin. Cases also had a higher mean value of resistance (p = 0.0133), and a lower mean value of reactance (p = 0.0329). Phase angle was lower among cases than in controls (p < 0.001). Conclusion: Our diabetic children showed higher levels of adiposity than controls. The observed differences in body composition are explained by differences in the fat-mass index. Abdominal fat accumulation was associated with poor glycaemic control and a lower phase angle.Clinical and Public Health Early Career Fellowship (grant number IA/CPHE/17/1/503345) from the DBT India Alliance/Wellcome Trust-Department of Biotechnology India Alliance (2018–2023)

Assessment of the clinical utility of adding common single nucleotide polymorphism genetic scores to classical risk factor algorithms in coronary heart disease risk prediction in UK men

UK Medical Research Council; British Heart Foundation