Biology subjects

Butterworth, A. S.

Publications and source records attributed to Butterworth, A. S..

3 recordsLinked to original sources

bioRxiv2018

Interleukin-6 Receptor Signalling and Abdominal Aortic Aneurysm Growth Rates

BackgroundThe Asp358Ala variant (rs2228145; A>C) in the interleukin-6 receptor (IL6R) gene has been implicated in the development of abdominal aortic aneurysms (AAAs), but its effect on AAA growth over time is not known. We aimed to investigate the clinical association between the IL6R-Asp358Ala variant and AAA growth, and to assess the effect of blocking the IL-6 signalling pathway in mouse models of aneurysm rupture.\n\nMethodUsing data from 2,863 participants with AAA from nine prospective cohorts, age- and sex-adjusted mixed-effects linear regression models were used to estimate the association between the IL6R-Asp358Ala variant and annual change in AAA diameter (mm/year). In a series of complementary randomised trials in mice, the effect of blocking the IL-6 signalling pathways was assessed on plasma biomarkers, systolic blood pressure, aneurysm diameter and time to aortic rupture and death.\n\nResultsAfter adjusting for age and sex, baseline aneurysm size was 0.55mm (95% confidence interval [CI]: 0.13, 0.98mm) smaller per copy of the minor allele [C] of the Asp358Ala variant. There was no evidence of a reduction in AAA growth rate (change in growth=-0.06mm per year [-0.18, 0.06] per copy of the minor allele). In two mouse models of AAA, selective blockage of the IL-6 trans-signalling pathway, but not combined blockage of both, the classical and trans-signalling pathways, was associated with improved survival (p<0.05).\n\nConclusionsOur proof-of-principle data are compatible with the concept that IL-6 trans-signalling is relevant to AAA growth, encouraging larger-scale evaluation of this hypothesis.

genetics↗

bioRxiv2018

Genomic risk prediction of coronary artery disease in nearly 500,000 adults: implications for early screening and primary prevention

BackgroundCoronary artery disease (CAD) has substantial heritability and a polygenic architecture; however, genomic risk scores have not yet leveraged the totality of genetic information available nor been externally tested at population-scale to show potential utility in primary prevention.\n\nMethodsUsing a meta-analytic approach to combine large-scale genome-wide and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS), consisting of 1.7 million genetic variants. We externally tested metaGRS, individually and in combination with available conventional risk factors, in 22,242 CAD cases and 460,387 non-cases from UK Biobank.\n\nFindingsIn UK Biobank, a standard deviation increase in metaGRS had a hazard ratio (HR) of 1.71 (95% CI 1.68-1.73) for CAD, greater than any other externally tested genetic risk score. Individuals in the top 20% of the metaGRS distribution had a HR of 4.17 (95% CI 3.97-4.38) compared with those in the bottom 20%. The metaGRS had higher C-index (C=0.623, 95% CI 0.615-0.631) for incident CAD than any of four conventional factors (smoking, diabetes, hypertension, and body mass index), and addition of the metaGRS to a model of conventional risk factors increased C-index by 3.7%. In individuals on lipid-lowering or anti-hypertensive medications at recruitment, metaGRS hazard for incident CAD was significantly but only partially attenuated with HR of 2.83 (95% CI 2.61- 3.07) between the top and bottom 20% of the metaGRS distribution.\n\nInterpretationRecent genetic association studies have yielded enough information to meaningfully stratify individuals using the metaGRS for CAD risk in both early and later life, thus enabling targeted primary intervention in combination with conventional risk factors. The metaGRS effect was partially attenuated by lipid and blood pressure-lowering medication, however other prevention strategies will be required to fully benefit from earlier genomic risk stratification.\n\nFundingNational Health and Medical Research Council of Australia, British Heart Foundation, Australian Heart Foundation.

genetics↗

bioRxiv2017

Consequences Of Natural Perturbations In The Human Plasma Proteome

Proteins are the primary functional units of biology and the direct targets of most drugs, yet there is limited knowledge of the genetic factors determining inter-individual variation in protein levels. Here we reveal the genetic architecture of the human plasma proteome, testing 10.6 million DNA variants against levels of 2,994 proteins in 3,301 individuals. We identify 1,927 genetic associations with 1,478 proteins, a 4-fold increase on existing knowledge, including trans associations for 1,104 proteins. To understand consequences of perturbations in plasma protein levels, we introduce an approach that links naturally occurring genetic variation with biological, disease, and drug databases. We provide insights into pathogenesis by uncovering the molecular effects of disease-associated variants. We identify causal roles for protein biomarkers in disease through Mendelian randomization analysis. Our results reveal new drug targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

genomics↗