Arsenic exposure, diabetes-related genes and diabetes prevalence in a general population from Spain

Inorganic arsenic exposure may be associated with diabetes, but the evidence at low-moderate levels is not sufficient. Polymorphisms in diabetes-related genes have been involved in diabetes risk. We evaluated the association of inorganic arsenic exposure on diabetes in the Hortega Study, a representative sample of a general population from Valladolid, Spain. Total urine arsenic was measured in 1451 adults. Urine arsenic speciation was available in 295 randomly selected participants. To account for the confounding introduced by non-toxic seafood arsenicals, we designed a multiple imputation model to predict the missing arsenobetaine levels. The prevalence of diabetes was 8.3%. The geometric mean of total arsenic was 66.0 µg/g. The adjusted odds ratios (95% confidence interval) for diabetes comparing the highest with the lowest tertile of total arsenic were 1.76 (1.01, 3.09) and 2.14 (1.47, 3.11) before and after arsenobetaine adjustment, respectively. Polymorphisms in several genes including IL8RA, TXN, NR3C2, COX5A and GCLC showed suggestive differential associations of urine total arsenic with diabetes. The findings support the role of arsenic on diabetes and the importance of controlling for seafood arsenicals in populations with high seafood intake. Suggestive arsenic-gene interactions require confirmation in larger studies

Genomic and metabolomic profile associated to microalbuminuria

To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE) were analyzed. Serum metabolomic profile was assessed by H-1 NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54 +/- 19, 50.6% men, ACR>30 mg/g in 81 subjects) with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of RPH3A gene and the rs4359_CC of ACE gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors.

Background To identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population. Methods and Findings One thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by H-1 NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54 +/- 19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine. Conclusions The results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors

GENOMIC AND METABOLOMIC PROFILE ASSOCIATED TO CLUSTERING OF CARDIO-METABOLIC RISK FACTORS

the sample included individuals older than 18 years in the absence of serious concomitantdisease or psychiatric disorder, which could interfere with the study. All the subjectsincluded were white, living in an area with a low immigration rate.<br>The study included the assessment of anthropometric measurements, blood pressure,  glycaemia, lipid profile and smoking status as well as personal and familial information<br>about cardiovascular risk factors and disease. Cardiometabolic risk factors were iidentified, according to the ATPIII criteria used for MS ], and MS was defined by the presence of three or more of the following components: 1) high waist circumference(men ≥ 102cm; women ≥88 cm); 2) high triglycerides (≥150mg/dL); 3) low HDL<br>cholesterol (men ≥ 40mg/dL; women ≥50mg/dL); 4) high blood pressure (systolic blood<br>pressure ≥130 mmHg and/or diastolic blood pressure ≥ 85 mmHg or being on<br>antihypertensive medications) and 5) high fasting glucose (≥ 110 mg/dL or being on drug treatment for elevated glucose). The subjects were divided into three groups:<br>Group 1 comprised of 617 subjects with less than two risk criteria of the ATPIIguideline; Group 2 comprised of 295 subjects with 2 risk factors and Group 3 comprised of 283 subjects with 3 or more of the criteria, which is considered to be MS.Weight was assessed with precise scales while the individuals were without shoes and<br>wearing light clothing. Height was determined in a similar way. Body mass index (BMI) was calculated using the following formula "weight (kg)/height2 (m)". Glucose<br>and lipid profile was measured in blood samples obtained with a mean of 3 hoursfasting (range 0-17). Basic serum biochemistry and lipid profile.Differences in the 28 metabolite values for each SNP in patients from Group 1 and Group 3 of each genotype were calculated. Finally, the metabolic profile and the most relevant metabolites of 5<br>genotype and allele were compared between patients from Group 1 and Group 3. The data were co-variated with respect to age, sex  and smoking status. Bonferroni correctionwas applied in all the analysis<br><br

The why behind the high: determinants of neurocognition during acute cannabis exposure

Acute cannabis intoxication may induce neurocognitive impairment and is a possible cause of human error, injury and psychological distress. One of the major concerns raised about increasing cannabis legalization and the therapeutic use of cannabis is that it will increase cannabis-related harm. However, the impairing effect of cannabis during intoxication varies among individuals and may not occur in all users. There is evidence that the neurocognitive response to acute cannabis exposure is driven by changes in the activity of the mesocorticolimbic and salience networks, can be exacerbated or mitigated by biological and pharmacological factors, varies with product formulations and frequency of use and can differ between recreational and therapeutic use. It is argued that these determinants of the cannabis-induced neurocognitive state should be taken into account when defining and evaluating levels of cannabis impairment in the legal arena, when prescribing cannabis in therapeutic settings and when informing society about the safe and responsible use of cannabis. Acute cannabis exposure modulates numerous aspects of neurocognitive function; however, the effects experienced by individuals are highly variable. Ramaekers and colleagues here review the neural basis of cannabis-induced neurocognitive changes and response variability, and consider the legal, therapeutic and societal implications