Arsenic metabolism and creatine synthesis.

<p>(A) Guanadinoacetate methyltransferase (GAMT) and phosphatidyl ethanolamine methyltransferase (PEMT), which catalyze the synthesis of creatine (Cr) and phosphatidylcholine, are the major consumers of S-adenosylmethionine (SAM). Arsenic methyltransferase (AS3MT) uses quantitatively much less SAM. (B) In the first, and rate-limiting, step of Cr biosynthesis, guanadinoacetate (GAA) is formed in the kidney by arginine:glycine amidinotransferase (AGAT). Dietary creatine (e.g. primarily from meat) leads to pre-translational inhibition of AGAT, thereby inhibiting endogenous creatine biosynthesis. GAA is transported to the liver, where it is methylated by GAMT to generate Cr, with SAM as the methyl donor. SAM also serves as the methyl donor for the methylation of trivalent inorganic arsenic (InAs^III) to monomethylarsonic acid (MMA^V), and for the methylation of monomethylaronous acid (MMA^III) to dimethylarsinic acid (DMA^V). The by-product of these methylation reactions is S-adenosylhomocysteine (SAH). Creatine, whether derived from endogenous biosynthesis or dietary sources, is transported to tissues with high energy requirements such as skeletal muscle, heart, and brain, where it is phosphorylated to phosphoryl-creatine (PCr). PCr is used for the regeneration of ATP during intensive exercise. Creatine and PCr are converted non-enzymatically at a constant rate to creatinine (Crn), which is then excreted in the urine. Image credit: Brandilyn A. Peters.</p

Characteristics of the study samples.

a<p>Chi-square and Wilcoxon's rank-sum tests were used to test for between sample differences in categorical and continuous variables, respectively.</p>b<p>2001 sample N = 366, 2003 sample N = 109.</p>c<p>%DMA, %MMA, and %InAs, the proportion of total urinary arsenic excreted as dimethylarsinic acid, monomethylarsonic acid, and inorganic arsenic, respectively.</p>d<p>2003 sample N = 109.</p>e<p>tHcys, total homocysteine.</p>f<p>Defined as trace protein or greater in urine by dipstick test.</p>g<p>2001 sample N = 365.</p>h<p>2001 sample N = 344.</p><p>Characteristics of the study samples.</p

Partial Spearman correlation coefficients for associations between % urinary As metabolites and urinary creatinine, cystatin C, and eGFR, adjusting for sex and age (and recruitment year in the total sample only).

a<p>r (p-value), all such values.</p><p>Partial Spearman correlation coefficients for associations between % urinary As metabolites and urinary creatinine, cystatin C, and eGFR, adjusting for sex and age (and recruitment year in the total sample only).</p

Logistic and linear regression models using uCrn and eGFR to predict %uAs metabolites.

a<p>We examined confounding or mediation of associations between uCrn and %As metabolites by using nested models, with and without control for eGFR; Model 1 parameters are log(age), sex, current smoking, log(total uAs), log(uCrn), and recruitment year (in total sample only); Model 2 parameters are log(age), sex, current smoking, log(total uAs), log(uCrn), eGFR, and recruitment year (in total sample only).</p>b<p>Generalized R².</p>c<p>Probability modeled is %uInAs >12.2 (total sample: %uInAs ≤12.2 N = 168, %uInAs >12.2 N = 310; 2001 sample: %uInAs ≤12.2 N = 123, %uInAs >12.2 N = 245; 2003 sample: %uInAs ≤12.2 N = 45, %uInAs >12.2 N = 65).</p><p>Logistic and linear regression models using uCrn and eGFR to predict %uAs metabolites.</p

Prevalence of chronic kidney disease (CKD) stages by gender.

<p>Prevalence of chronic kidney disease (CKD) stages by gender.</p

Linear regression models using log(total urinary As in µg/L), log(uAs metabolites in µg/L), or log(water As in µg/L) to predict eGFR.

a<p>Adjusted for log(age), sex, current smoking, log(urinary creatinine), and recruitment year (total sample only).</p>b<p>Adjusted for log(age), sex, current smoking, and recruitment year (total sample only).</p><p>Linear regression models using log(total urinary As in µg/L), log(uAs metabolites in µg/L), or log(water As in µg/L) to predict eGFR.</p