Genomics of lipid metabolism: Identifying novel causal pathways and new therapeutic targets for reducing risk of coronary heart disease

Coronary heart disease (CHD) is one of the leading causes of death worldwide; mortality rates are expected to continue to rise over the coming decades. Circulating lipids have been shown to be strongly and linearly associated with risk of CHD; however, despite considerable efforts to demonstrate causality, available evidence is conflicting and insufficient. Study of the underlying metabolic pathways implicated in the association between lipids and CHD would help to disentangle and elucidate these complex relationships. Direct infusion high-resolution mass spectrometry was performed on 5,551 participants from the Pakistan Risk of Myocardial Infarction Study; raw data were then processed, cleaned, and normalized to extract signals corresponding to 444 known lipid metabolites. Cross-correlations of lipid metabolites and their correlations with circulating lipids were examined, and the association of principal components of lipid metabolites with CHD risk factors was assessed. Genome-wide analyses were conducted to analyze the association of each lipid metabolite with 7.2 million genotyped and imputed single nucleotide polymorphisms (SNPs). Following conditional analyses on the lead SNP within each loci, we identified genome-wide significant associations at 148 independent metabolic loci and 54 novel loci. We then used functional annotation to link the variants associated with each metabolite to the most probable causal genes, and two-sample Mendelian randomization to examine the causal effect of lipid metabolites on risk of CHD. Analyses of circulating lipid metabolites in large epidemiological studies could lead to enhanced understanding of mechanisms for CHD development and identification of novel causal pathways and new therapeutic targets

Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado

Air pollution sensors are quickly proliferating for use in a wide variety of applications, with a low price point that supports use in high-density networks, citizen science, and individual consumer use. This emerging technology motivates the assessment under real-world conditions, including varying pollution levels and environmental conditions. A seven-month, systematic field evaluation of low-cost air pollution sensors was performed in Denver, Colorado, over 2015–2016; the location was chosen to evaluate the sensors in a high-altitude, cool, and dry climate. A suite of particulate matter (PM), ozone (O3), and nitrogen dioxide (NO2) sensors were deployed in triplicate and were collocated with federal equivalent method (FEM) monitors at an urban regulatory site. Sensors were evaluated for their data completeness, correlation with reference monitors, and ability to reproduce trends in pollution data, such as daily concentration values and wind-direction patterns. Most sensors showed high data completeness when data loggers were functioning properly. The sensors displayed a range of correlations with reference instruments, from poor to very high (e.g., hourly-average PM Pearson correlations with reference measurements varied from 0.01 to 0.86). Some sensors showed a change in response to laboratory audits/testing from before the sampling campaign to afterwards, such as Aeroqual, where the O3 response slope changed from about 1.2 to 0.6. Some PM sensors measured wind-direction and time-of-day trends similar to those measured by reference monitors, while others did not. This study showed different results for sensor performance than previous studies performed by the U.S. EPA and others, which could be due to different geographic location, meteorology, and aerosol properties. These results imply that continued field testing is necessary to understand emerging air sensing technology.</p

Non-emphysematous chronic obstructive pulmonary disease is associated with diabetes mellitus

Abstract Background Chronic obstructive pulmonary disease (COPD) has been classically divided into blue bloaters and pink puffers. The utility of these clinical subtypes is unclear. However, the broader distinction between airway-predominant and emphysema-predominant COPD may be clinically relevant. The objective was to define clinical features of emphysema-predominant and non-emphysematous COPD patients. Methods Current and former smokers from the Genetic Epidemiology of COPD Study (COPDGene) had chest computed tomography (CT) scans with quantitative image analysis. Emphysema-predominant COPD was defined by low attenuation area at -950 Hounsfield Units (LAA-950) ≥10%. Non-emphysematous COPD was defined by airflow obstruction with minimal to no emphysema (LAA-950 < 5%). Results Out of 4197 COPD subjects, 1687 were classified as emphysema-predominant and 1817 as non-emphysematous; 693 had LAA-950 between 5–10% and were not categorized. Subjects with emphysema-predominant COPD were older (65.6 vs 60.6 years, p < 0.0001) with more severe COPD based on airflow obstruction (FEV1 44.5 vs 68.4%, p < 0.0001), greater exercise limitation (6-minute walk distance 1138 vs 1331 ft, p < 0.0001) and reduced quality of life (St. George’s Respiratory Questionnaire score 43 vs 31, p < 0.0001). Self-reported diabetes was more frequent in non-emphysematous COPD (OR 2.13, p < 0.001), which was also confirmed using a strict definition of diabetes based on medication use. The association between diabetes and non-emphysematous COPD was replicated in the ECLIPSE study. Conclusions Non-emphysematous COPD, defined by airflow obstruction with a paucity of emphysema on chest CT scan, is associated with an increased risk of diabetes. COPD patients without emphysema may warrant closer monitoring for diabetes, hypertension, and hyperlipidemia and vice versa. Trial registration Clinicaltrials.gov identifiers: COPDGene NCT00608764 , ECLIPSE NCT00292552 .http://deepblue.lib.umich.edu/bitstream/2027.42/109496/1/12890_2014_Article_599.pd

Obesity related methylation changes in DNA of peripheral blood leukocytes

<p>Abstract</p> <p>Background</p> <p>Despite evidence linking obesity to impaired immune function, little is known about the specific mechanisms. Because of emerging evidence that immune responses are epigenetically regulated, we hypothesized that DNA methylation changes are involved in obesity induced immune dysfunction and aimed to identify these changes.</p> <p>Method</p> <p>We conducted a genome wide methylation analysis on seven obese cases and seven lean controls aged 14 to 18 years from extreme ends of the obesity distribution and performed further validation of six CpG sites from six genes in 46 obese cases and 46 lean controls aged 14 to 30 years.</p> <p>Results</p> <p>In comparison with the lean controls, we observed one CpG site in the UBASH3A gene showing higher methylation levels and one CpG site in the TRIM3 gene showing lower methylation levels in the obese cases in both the genome wide step (<it>P </it>= 5 × 10^-6and <it>P </it>= 2 × 10^-5for the UBASH3A and the TRIM3 gene respectively) and the validation step (<it>P </it>= 0.008 and <it>P </it>= 0.001 for the UBASH3A and the TRIM3 gene respectively).</p> <p>Conclusions</p> <p>Our results provide evidence that obesity is associated with methylation changes in blood leukocyte DNA. Further studies are warranted to determine the causal direction of this relationship as well as whether such methylation changes can lead to immune dysfunction.</p> <p>See commentary: <url>http://www.biomedcentral.com/1741-7015/8/88/abstract</url></p

The Bangladesh Risk of Acute Vascular Events (BRAVE) Study: objectives and design.

During recent decades, Bangladesh has experienced a rapid epidemiological transition from communicable to non-communicable diseases. Coronary heart disease (CHD), with myocardial infarction (MI) as its main manifestation, is a major cause of death in the country. However, there is limited reliable evidence about its determinants in this population. The Bangladesh Risk of Acute Vascular Events (BRAVE) study is an epidemiological bioresource established to examine environmental, genetic, lifestyle and biochemical determinants of CHD among the Bangladeshi population. By early 2015, the ongoing BRAVE study had recruited over 5000 confirmed first-ever MI cases, and over 5000 controls "frequency-matched" by age and sex. For each participant, information has been recorded on demographic factors, lifestyle, socioeconomic, clinical, and anthropometric characteristics. A 12-lead electrocardiogram has been recorded. Biological samples have been collected and stored, including extracted DNA, plasma, serum and whole blood. Additionally, for the 3000 cases and 3000 controls initially recruited, genotyping has been done using the CardioMetabochip+ and the Exome+ arrays. The mean age (standard deviation) of MI cases is 53 (10) years, with 88 % of cases being male and 46 % aged 50 years or younger. The median interval between reported onset of symptoms and hospital admission is 5 h. Initial analyses indicate that Bangladeshis are genetically distinct from major non-South Asian ethnicities, as well as distinct from other South Asian ethnicities. The BRAVE study is well-placed to serve as a powerful resource to investigate current and future hypotheses relating to environmental, biochemical and genetic causes of CHD in an important but under-studied South Asian population.The Gates Cambridge Trust has supported Dr Chowdhury. Epidemiological fieldwork in BRAVE has been supported by grants to investigators at the Cardiovascular Epidemiology Unit, University of Cambridge. The Cardiovascular Epidemiology Unit is underpinned by programme grants from the British Heart Foundation (RG/13/13/30194), the UK Medical Research Council (MR/L003120/1), and the UK National Institute of Health Research Cambridge Biomedical Research Centre. BRAVE has received support for genetic assays from the European Research Council (ERC-2010-AdG-20100317), European Commission Framework 7 (Grant Agreement number: 279233), and the Cambridge British Heart Foundation Centre for Excellence in Cardiovascular Science; We would like to acknowledge the contributions of the following individuals: Cardiology Research Group in Bangladesh Mohammad Afzalur Rahman, Mohammad Abdul Kader Akanda, M Atahar Ali, Mir Jamal Uddin, SM Siddiqur Rahman, Amal Kumar Choudhury, Md. Mamunur Rashid, Nazir Ahmed Chowdhury, Mohammad Abdullahel Baqui, Kajal Kumar Karmoker, Mohammad Golam Azam; Setting up/implementation of fieldwork in Bangladesh Abbas Bhuiya, Susmita Chowdhury, Kamrun Nahar, Neelima Das, Proshon Roy, Sumona Ferdous, Taposh Kumar Biswas, Abu Sadat Mohammad Sayed Sharif, Ranjit Shingha, Rose Jinnath Tomas, Babulal Parshei, Mabubur Rahman, Mohammad Emon Hossain, Akhirunnesa Mily, AK Mottashir Ahmed, Sati Chowdhury, Sushila Roy, Dipak Kanti Chowdhury, Swapan Kumar Roy; Epidemiological/statistical support in Cambridge Stephen Kaptoge, Simon Thompson, Angela Wood, Narinder Bansal, Anna Ramond, Clare Oliver-Williams, Marinka Steur, Linda O’Keeffe, Eleni Sofianopoulou, Setor Kunutsor, Donal Gorman, Oscar H Franco, Malcolm Legget, Pinal Patel, Marc Suhrcke, Sylvaine Bruggraber, Jonathan Powell; Data management Matthew Walker, Steve Ellis, Shawkat Jahangir, Habibur Rahman, Rifat Hasan Shammi, Shafqat Ullah, Mohammad Abdul Matin and Administration Beth Collins, Hannah Lombardi, Binder Kaur, Rachel Henry, Marilena Papanikolaou, Robert Smith, Abdul Wazed, Robert Williams, Julie Jenkins, Keith Hoddy.This is the final published version of the article. It was originally published in the European Journal of Epidemiology (Chowdhury R, et al., European Journal of Epidemiology, 2015, doi:10.1007/s10654-015-0037-2). The final version is available at http://dx.doi.org/10.1007/s10654-015-0037-

An unbiased lipid phenotyping approach to study the genetic determinants of lipids and their association with coronary heart disease risk factors

Direct infusion high-resolution mass spectrometry (DIHRMS) is a novel, high-throughput approach to rapidly and accurately profile hundreds of lipids in human serum without prior chromatography, facilitating in-depth lipid phenotyping for large epidemiological studies to reveal the detailed associations of individual lipids with coronary heart disease (CHD) risk factors. Intact lipid profiling by DIHRMS was performed on 5662 serum samples from healthy participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS). We developed a novel semi-targeted peak-picking algorithm to detect mass-to-charge ratios in positive and negative ionization modes. We analyzed lipid partial correlations, assessed the association of lipid principal components with established CHD risk factors and genetic variants, and examined differences between lipids for a common genetic polymorphism. The DIHRMS method provided information on 360 lipids (including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids), with a median coefficient of variation of 11.6% (range: 5.4–51.9). The lipids were highly correlated and exhibited a range of associations with clinical chemistry biomarkers and lifestyle factors. This platform can provide many novel insights into the effects of physiology and lifestyle on lipid metabolism, genetic determinants of lipids, and the relationship between individual lipids and CHD risk factors

Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis

Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1 alpha and IL-1 beta); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0.22 SD (95% CI 0.18-0.25; 12.5%; p=9.3 x 10(-33)), concentrations of interleukin 6 decreased by 0.02 SD (-0.04 to -0.01; -1,7%; p=3.5 x 10(-3)), and concentrations of C-reactive protein decreased by 0.03 SD (-0.04 to -0.02; -3.4%; p=7.7 x 10(-14)). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1.15 (1.08-1.22; p=1.8 x 10(-6)) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1.03 (1.02-1.04; p=3.9 x 10(-10)). Perallele odds ratios were 0.97 (0.95-0.99; p=9.9 x 10(-4)) for rheumatoid arthritis, 0.99 (0.97-1.01; p=0.47) for type 2 diabetes, 1.00 (0.98-1.02; p=0.92) for ischaemic stroke, and 1.08 (1.04-1.12; p=1.8 x 10(-5)) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1 alpha/beta inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Copyright (C) The Interleukin 1 Genetics Consortium. Open Access article distributed under the terms of CC-BY-NC-ND

Non-emphysematous chronic obstructive pulmonary disease is associated with diabetes mellitus

Background: Chronic obstructive pulmonary disease (COPD) has been classically divided into blue bloaters and pink puffers. The utility of these clinical subtypes is unclear. However, the broader distinction between airway-predominant and emphysema-predominant COPD may be clinically relevant. The objective was to define clinical features of emphysema-predominant and non-emphysematous COPD patients. Methods: Current and former smokers from the Genetic Epidemiology of COPD Study (COPDGene) had chest computed tomography (CT) scans with quantitative image analysis. Emphysema-predominant COPD was defined by low attenuation area at -950 Hounsfield Units (LAA-950) ≥10%. Non-emphysematous COPD was defined by airflow obstruction with minimal to no emphysema (LAA-950 < 5%). Results: Out of 4197 COPD subjects, 1687 were classified as emphysema-predominant and 1817 as non-emphysematous; 693 had LAA-950 between 5-10% and were not categorized. Subjects with emphysema-predominant COPD were older (65.6 vs 60.6 years, p < 0.0001) with more severe COPD based on airflow obstruction (FEV1 44.5 vs 68.4%, p < 0.0001), greater exercise limitation (6-minute walk distance 1138 vs 1331 ft, p < 0.0001) and reduced quality of life (St. George's Respiratory Questionnaire score 43 vs 31, p < 0.0001). Self-reported diabetes was more frequent in non-emphysematous COPD (OR 2.13, p < 0.001), which was also confirmed using a strict definition of diabetes based on medication use. The association between diabetes and non-emphysematous COPD was replicated in the ECLIPSE study. Conclusions: Non-emphysematous COPD, defined by airflow obstruction with a paucity of emphysema on chest CT scan, is associated with an increased risk of diabetes. COPD patients without emphysema may warrant closer monitoring for diabetes, hypertension, and hyperlipidemia and vice versa