Table_1_Cardiac copper content and its relationship with heart physiology: Insights based on quantitative genetic and functional analyses using BXD family mice.xlsx

BackgroundCopper (Cu) is essential for the functioning of various enzymes involved in important cellular and physiological processes. Although critical for normal cardiac function, excessive accumulation, or deficiency of Cu in the myocardium is detrimental to the heart. Fluctuations in cardiac Cu content have been shown to cause cardiac pathologies and imbalance in systemic Cu metabolism. However, the genetic basis underlying cardiac Cu levels and their effects on heart traits remain to be understood. Representing the largest murine genetic reference population, BXD strains have been widely used to explore genotype-phenotype associations and identify quantitative trait loci (QTL) and candidate genes.MethodsCardiac Cu concentration and heart function in BXD strains were measured, followed by QTL mapping. The candidate genes modulating Cu homeostasis in mice hearts were identified using a multi-criteria scoring/filtering approach.ResultsSignificant correlations were identified between cardiac Cu concentration and left ventricular (LV) internal diameter and volumes at end-diastole and end-systole, demonstrating that the BXDs with higher cardiac Cu levels have larger LV chamber. Conversely, cardiac Cu levels negatively correlated with LV posterior wall thickness, suggesting that lower Cu concentration in the heart is associated with LV hypertrophy. Genetic mapping identified six QTLs containing a total of 217 genes, which were further narrowed down to 21 genes that showed a significant association with cardiac Cu content in mice. Among those, Prex1 and Irx3 are the strongest candidates involved in cardiac Cu modulation.ConclusionCardiac Cu level is significantly correlated with heart chamber size and hypertrophy phenotypes in BXD mice, while being regulated by multiple genes in several QTLs. Prex1 and Irx3 may be involved in modulating Cu metabolism and its downstream effects and warrant further experimental and functional validations.</p

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

SummaryBackground The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the fi rst of a series ofannual updates of the GBD. Risk factor quantifi cation, particularly of modifi able risk factors, can help to identifyemerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunityto update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriatecounterfactual risk distribution.Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs)have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meetingexplicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs:risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into ahierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the fi rst level of thehierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with moredetail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added:handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafesex, and low glomerular fi ltration rate. For most risks, data for exposure were synthesised with a Bayesian metaregressionmethod, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based onmeta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all riskscombined took into account evidence on the mediation of some risks such as high body-mass index (BMI) throughother risks such as high systolic blood pressure and high cholesterol.Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6%(40·1–43·0) of DALYs. Risks quantifi ed account for 87·9% (86·5?89·3) of cardiovascular disease DALYs, rangingto a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 milliondeaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs,child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 milliondeaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time.In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water,sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the MiddleEast, and in many other high-income countries, high BMI is the leading risk factor, with high systolic bloodpressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolicblood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and theMiddle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya toSouth Africa.Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortalityand more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, theattributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural riskfactors, behavioural and social science research on interventions for these risks should be strengthened. Manyprevention and primary care policy options are available now to act on key risks.</p