toward modeling kinetics of biomolecular complexes

In order to advance the mission of in silico cell biology, modeling the interactions of large and complex biological systems becomes increasingly relevant. The combination of molecular dynamics (MD) and Markov state models (MSMs) have enabled the construction of simplified models of molecular kinetics on long timescales. Despite its success, this approach is inherently limited by the size of the molecular system. With increasing size of macromolecular complexes, the number of independent or weakly coupled subsystems increases, and the number of global system states increase exponentially, making the sampling of all distinct global states unfeasible. In this work, we present a technique called Independent Markov Decomposition (IMD) that leverages weak coupling between subsystems in order to compute a global kinetic model without requiring to sample all combinatorial states of subsystems. We give a theoretical basis for IMD and propose an approach for finding and validating such a decomposition. Using empirical few-state MSMs of ion channel models that are well established in electrophysiology, we demonstrate that IMD can reproduce experimental conductance measurements with a major reduction in sampling compared with a standard MSM approach. We further show how to find the optimal partition of all-atom protein simulations into weakly coupled subunits

Exposure to arsenic in drinking water is associated with increased prevalence of diabetes: a cross-sectional study in the Zimapán and Lagunera regions in Mexico

<p>Abstract</p> <p>Background</p> <p>Human exposures to inorganic arsenic (iAs) have been linked to an increased risk of diabetes mellitus. Recent laboratory studies showed that methylated trivalent metabolites of iAs may play key roles in the diabetogenic effects of iAs. Our study examined associations between chronic exposure to iAs in drinking water, metabolism of iAs, and prevalence of diabetes in arsenicosis-endemic areas of Mexico.</p> <p>Methods</p> <p>We used fasting blood glucose (FBG), fasting plasma insulin (FPI), oral glucose tolerance test (OGTT), glycated hemoglobin (HbA1c), and insulin resistance (HOMA-IR) to characterize diabetic individuals. Arsenic levels in drinking water and urine were determined to estimate exposure to iAs. Urinary concentrations of iAs and its trivalent and pentavalent methylated metabolites were measured to assess iAs metabolism. Associations between diabetes and iAs exposure or urinary metabolites of iAs were estimated by logistic regression with adjustment for age, sex, hypertension and obesity.</p> <p>Results</p> <p>The prevalence of diabetes was positively associated with iAs in drinking water (OR 1.13 per 10 ppb, p < 0.01) and with the concentration of dimethylarsinite (DMAs^III) in urine (OR 1.24 per inter-quartile range, p = 0.05). Notably, FPI and HOMA-IR were negatively associated with iAs exposure (β -2.08 and -1.64, respectively, p < 0.01), suggesting that the mechanisms of iAs-induced diabetes differ from those underlying type-2 diabetes, which is typically characterized by insulin resistance.</p> <p>Conclusions</p> <p>Our study confirms a previously reported, but frequently questioned, association between exposure to iAs and diabetes, and is the first to link the risk of diabetes to the production of one of the most toxic metabolites of iAs, DMAs^III.</p

Epigenetic Changes in Individuals with Arsenicosis

Inorganic arsenic (iAs) is an environmental toxicant currently poisoning millions of people worldwide, and chronically exposed individuals are susceptible to arsenicosis or arsenic poisoning. Using a state-of-the-art technique to map the methylomes of our study subjects, we identified a large interactome of hypermethylated genes that are enriched for their involvement in arsenic-associated diseases, such as cancer, heart disease, and diabetes. Notably, we have uncovered an arsenic-induced tumor suppressorome, a complex of 17 tumor suppressors known to be silenced in human cancers. This finding represents a pivotal clue in unraveling a possible epigenetic mode of arsenic-induced disease

Environmental exposure to arsenic, AS3MT polymorphism and prevalence of diabetes in Mexico

Exposure to arsenic in drinking water is associated with increased prevalence of diabetes. We previously reported an association of diabetes and urinary concentration of dimethylarsinite (DMAsIII), a toxic product of arsenic methylation by arsenic ( +3 oxidation state) methyltransferase (AS3MT). Here we examine associations between AS3MT polymorphism, arsenic metabolism and diabetes. Fasting blood glucose, oral glucose tolerance and self-reported diagnoses were used to identify diabetic individuals. Inorganic arsenic and its metabolites were measured in urine. Genotyping analysis focused on six polymorphic sites of AS3MT. Individuals with M287T and G4965C polymorphisms had higher levels of urinary DMAsIII and were more frequently diabetic than the respective wild-type carriers, although the excess was not statistically significant. Odds ratios were 11.4 (95% confidence interval (CI) 2.2–58.8) and 8.8 (95% CI 1.6–47.3) for the combined effects of arsenic exposure >75th percentile and 287T and 4965C genotypes, respectively. Carriers of 287T and 4965C may produce more DMAsIII and be more likely to develop diabetes when exposed to arsenic

Arsenic and the Epigenome: Inter-individual differences in arsenic metabolism related to distinct patterns of DNA methylation

Biotransformation of inorganic arsenic (iAs) is one of the factors that determines the character and magnitude of the diverse detrimental health effects associated with chronic iAs exposure, but it is unknown how iAs biotransformation may impact the epigenome. Here, we integrated analyses of genome-wide, gene-specific promoter DNA methylation levels of peripheral blood leukocytes (PBLs) with urinary arsenical concentrations of subjects from a region of Mexico with high levels of iAs in drinking water. These analyses revealed dramatic differences in DNA methylation profiles associated with concentrations of specific urinary metabolites of arsenic. The majority of individuals in this study had positive indicators of arsenic-related disease, namely pre-diabetes mellitus or diabetes mellitus. Methylation patterns of genes with known associations to diabetes mellitus were associated with urinary concentrations of specific iAs metabolites. Future studies will determine whether these DNA methylation profiles provide mechanistic insight into the development of iAs-associated disease, predict disease risk, and/or serve as biomarkers of iAs exposure in humans

Exposure to arsenic in drinking water is associated with increased prevalence of diabetes: a cross-sectional study in the Zimapan and Lagunera Regions in Mexico

Abstract Background Human exposures to inorganic arsenic (iAs) have been linked to an increased risk of diabetes mellitus. Recent laboratory studies showed that methylated trivalent metabolites of iAs may play key roles in the diabetogenic effects of iAs. Our study examined associations between chronic exposure to iAs in drinking water, metabolism of iAs, and prevalence of diabetes in arsenicosis-endemic areas of Mexico. Methods We used fasting blood glucose (FBG), fasting plasma insulin (FPI), oral glucose tolerance test (OGTT), glycated hemoglobin (HbA1c), and insulin resistance (HOMA-IR) to characterize diabetic individuals. Arsenic levels in drinking water and urine were determined to estimate exposure to iAs. Urinary concentrations of iAs and its trivalent and pentavalent methylated metabolites were measured to assess iAs metabolism. Associations between diabetes and iAs exposure or urinary metabolites of iAs were estimated by logistic regression with adjustment for age, sex, hypertension and obesity. Results The prevalence of diabetes was positively associated with iAs in drinking water (OR 1.13 per 10 ppb, p < 0.01) and with the concentration of dimethylarsinite (DMAsIII) in urine (OR 1.24 per inter-quartile range, p = 0.05). Notably, FPI and HOMA-IR were negatively associated with iAs exposure (β -2.08 and -1.64, respectively, p < 0.01), suggesting that the mechanisms of iAs-induced diabetes differ from those underlying type-2 diabetes, which is typically characterized by insulin resistance. Conclusions Our study confirms a previously reported, but frequently questioned, association between exposure to iAs and diabetes, and is the first to link the risk of diabetes to the production of one of the most toxic metabolites of iAs, DMAsIII

Association of AS3MT polymorphisms and the risk of premalignant arsenic skin lesions

Exposure to naturally occurring inorganic arsenic (iAs), primarily from contaminated drinking water, is considered one of the top environmental health threats worldwide. Arsenic (+3 oxidation state) methyltransferase (AS3MT) is the key enzyme in the biotransformation pathway of iAs. AS3MT catalyzes the transfer of a methyl group from S-adenosyl-L-methionine to trivalent arsenicals, resulting in the production of methylated (MAs) and dimethylated arsenicals (DMAs). MAs is a susceptibility factor for iAs-induced toxicity. In this study, we evaluated the association of the polymorphism in AS3MT gene with iAs metabolism and with the presence of arsenic (As) premalignant skin lesions. This is a case-control study of 71 cases with skin lesions and 51 controls without skin lesions recruited from a iAs endemic area in Mexico. We measured urinary As metabolites, differentiating the trivalent and pentavalent arsenical species, using the hydride generation atomic absorption spectrometry. In addition, the study subjects were genotyped to analyze three single nucleotide polymorphisms (SNPs), A-477G, T14458C (nonsynonymus SNP; Met287Thr), and T35587C, in the AS3MT gene. We compared the frequencies of the AS3MT alleles, genotypes, and haplotypes in individuals with and without skin lesions. Marginal differences in the frequencies of the Met287Thr genotype were identified between individuals with and without premalignant skin lesions (p=0.055): individuals carrying the C (TC+CC) allele (Thr) were at risk [odds ratio=4.28; 95% confidence interval (1.0–18.5)]. Also, individuals with C allele of Met287Thr displayed greater percentage of MAs in urine and decrease in the percentage of DMAs. These findings indicate that Met287Thr influences the susceptibility to premalignant As skin lesions and might be at increased risk for other adverse health effects of iAs exposure

Chronic Exposure to Arsenic and Markers of Cardiometabolic Risk: A Cross-Sectional Study in Chihuahua, Mexico

BackgroundExposure to arsenic (As) concentrations in drinking water > 150 μg/L has been associated with risk of diabetes and cardiovascular disease, but little is known about the effects of lower exposures.ObjectiveThis study aimed to examine whether moderate As exposure, or indicators of individual As metabolism at these levels of exposure, are associated with cardiometabolic risk.MethodsWe analyzed cross-sectional associations between arsenic exposure and multiple markers of cardiometabolic risk using drinking-water As measurements and urinary As species data obtained from 1,160 adults in Chihuahua, Mexico, who were recruited in 2008–2013. Fasting blood glucose and lipid levels, the results of an oral glucose tolerance test, and blood pressure were used to characterize cardiometabolic risk. Multivariable logistic, multinomial, and linear regression were used to assess associations between cardiometabolic outcomes and water As or the sum of inorganic and methylated As species in urine.ResultsAfter multivariable adjustment, concentrations in the second quartile of water As (25.5 to < 47.9 μg/L) and concentrations of total speciated urinary As (< 55.8 μg/L) below the median were significantly associated with elevated triglycerides, high total cholesterol, and diabetes. However, moderate water and urinary As levels were also positively associated with HDL cholesterol. Associations between arsenic exposure and both dysglycemia and triglyceridemia were higher among individuals with higher proportions of dimethylarsenic in urine.ConclusionsModerate exposure to As may increase cardiometabolic risk, particularly in individuals with high proportions of urinary dimethylarsenic. In this cohort, As exposure was associated with several markers of increased cardiometabolic risk (diabetes, triglyceridemia, and cholesterolemia), but exposure was also associated with higher rather than lower HDL cholesterol.CitationMendez MA, González-Horta C, Sánchez-Ramírez B, Ballinas-Casarrubias L, Hernández Cerón R, Viniegra Morales D, Baeza Terrazas FA, Ishida MC, Gutiérrez-Torres DS, Saunders RJ, Drobná Z, Fry RC, Buse JB, Loomis D, García-Vargas GG, Del Razo LM, Stýblo M. 2016. Chronic exposure to arsenic and markers of cardiometabolic risk: a cross-sectional study in Chihuahua, Mexico. Environ Health Perspect 124:104–111; http://dx.doi.org/10.1289/ehp.140874

Association Between Variants in Arsenic (+3 Oxidation State) Methyltranserase ( AS3MT ) and Urinary Metabolites of Inorganic Arsenic: Role of Exposure Level

Variants in AS3MT, the gene encoding arsenic (+3 oxidation state) methyltranserase, have been shown to influence patterns of inorganic arsenic (iAs) metabolism. Several studies have suggested that capacity to metabolize iAs may vary depending on levels of iAs exposure. However, it is not known whether the influence of variants in AS3MT on iAs metabolism also vary by level of exposure. We investigated, in a population of Mexican adults exposed to drinking water As, whether associations between 7 candidate variants in AS3MT and urinary iAs metabolites were consistent with prior studies, and whether these associations varied depending on the level of exposure. Overall, associations between urinary iAs metabolites and AS3MT variants were consistent with the literature. Referent genotypes, defined as the genotype previously associated with a higher percentage of urinary dimethylated As (DMAs%), were associated with significant increases in the DMAs% and ratio of DMAs to monomethylated As (MAs), and significant reductions in MAs% and iAs%. For 3 variants, associations between genotypes and iAs metabolism were significantly stronger among subjects exposed to water As >50 versus ≤50 ppb (water As X genotype interaction P < .05). In contrast, for 1 variant (rs17881215), associations were significantly stronger at exposures ≤50 ppb. Results suggest that iAs exposure may influence the extent to which several AS3MT variants affect iAs metabolism. The variants most strongly associated with iAs metabolism—and perhaps with susceptibility to iAs-associated disease—may vary in settings with exposure level

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation