Baseline CRP levels seem to be a biomarker of chronic inflammation preceding lung cancer, even after subtracting a 5-year latent period. Furthermore, CRP gene variation associated with low CRP blood levels was relatively common in patients with lung cancer. Both chronic inflammation and impaired defense mechanisms resulting in chronic inflammation might explain these results.

This review provides information on the overall incidence of D-DIs as a cause of adverse patient outcomes, although there is still uncertainty about the impact of D-DIs on adverse patient outcomes. Our results suggest that a limited number of drugs are involved in the majority of cases and that the number of reasons for admission as a consequence of D-DIs seems to be modest.

OBJECTIVENumerous studies have suggested a decreased risk of cancer in patients with diabetes on metformin. Because different comparison groups were used, the effect magnitude is difficult to estimate. Therefore, the objective of this study was to further analyze whether, and to what extent, use of metformin is associated with a decreased risk of cancer in a cohort of incident users of metformin compared with users of sulfonylurea derivatives.RESEARCH DESIGN AND METHODSData for this study were obtained from dispensing records from community pharmacies individually linked to hospital discharge records from 2.5 million individuals in the Netherlands. The association between the risk of cancer in those using metformin compared with those using sulfonylurea derivatives was analyzed using Cox proportional hazard models with cumulative duration of drug use as a time-varying determinant.RESULTSUse of metformin was associated with a lower risk of cancer in general (hazard ratio 0.90 [95% CI 0.88–0.91]) compared with use of sulfonylurea derivatives. When specific cancers were used as end points, similar estimates were found. Dosage-response relations were identified for users of metformin but not for users of sulfonylurea derivatives.CONCLUSIONSIn our study, cumulative exposure to metformin was associated with a lower risk of specific cancers and cancer in general, compared with cumulative exposure to sulfonylurea derivatives. However, whether this should indeed be seen as a decreased risk of cancer for the use of metformin or as an increased risk of cancer for the use sulfonylurea derivatives remains to be elucidated.

1,5,6,7 OBJECTIVE-Metformin, an oral glucose-lowering drug, is taken up in hepatocytes by the organic cation transporter (OCT) 1 and in renal epithelium by OCT2. In these cells, the multidrug and toxin extrusion (MATE) 1 protein, encoded by the SLC47A1 gene, is responsible for the excretion of metformin into the bile and urine, respectively. We studied the effect of single nucleotide polymorphisms (SNPs) in the SLC47A1 gene on the A1C-lowering effect of metformin. RESEARCH DESIGN AND METHODS-We identified all incident metformin users in the Rotterdam Study, a populationbased cohort study. Associations between 12 tagging SNPs in the SLC47A1 gene and change in A1C level were analyzed. RESULTS-One hundred and sixteen incident metformin users were included in the study sample. The rs2289669 GϾA SNP was significantly associated with metformin response. For the other SNPs, no associations were found. For each minor A allele at rs2289669, the A1C reduction was 0.30% (95% CI Ϫ0.51 to Ϫ0.10; P ϭ 0.005) larger. After Bonferroni correction for multiple testing, the P value was 0.045. M etformin is an oral glucose-lowering drug, widely used for the treatment of type 2 diabetes (1). The molecular mechanism of the glucose-lowering effect is not fully understood, although it is known that inhibition of the hepatic gluconeogenesis has an important role (2). Metformin is mainly eliminated by tubular secretion, and hepatic metabolism has a minor role. CONCLUSIONS-TheSeveral drug transporters are involved in the distribution and excretion of metformin (3). The role of two organic cation transporters (OCTs), OCT1 and OCT2, is assumed. OCT1 and OCT2 are members of the solute carrier (SLC) 22 family and encoded by the SLC22A1 and SLC22A2 genes, respectively, with gene location 6q25.3. OCT1 is expressed in the basolateral membrane of hepatocytes, and the uptake of metformin in the hepatocytes by OCT1 is an essential step for the glucose-lowering effect (4 -6). In OCT1 gene knockout mice, the metformin liver concentrations were lower and the glucose-lowering effect impaired (4,7). Genetic variations in the SLC22A1 gene (R61C, G401S, M420del, and G465R) are associated with differences in metformin plasma levels and glucose concentrations after an oral glucose tolerance test in healthy volunteers (4,7). OCT2 is expressed in the basolateral membrane of the renal epithelium, and transportation of metformin over this membrane may be the first step to tubular secretion (8,9). Genetic variations in SLC22A2 (T199I, T201M, and A270S) are associated with decreased renal excretion and increased plasma concentrations of metformin (10,11).Recently, a multidrug and toxin extrusion (MATE) transporter protein family was identified, assigned as the SLC 47 family (12,13). The SLC47A1 gene, with gene location 17p11.2, encodes the MATE1 transporter. Metformin is one of the substrates of this transporter (14). MATE1 is located in the bile canalicular membrane in the hepatocyte and in the brush border of the renal epithelium and is responsible for the final...

The organic cation transporter 1, encoded by the SLC22A1 gene, is responsible for the uptake of the anti-hyperglycaemic drug, metformin, in the hepatocyte. We assessed whether a genetic variation in the SLC22A1 gene is associated with the glucose-lowering effect of metformin. Incident metformin users in the Rotterdam Study, whose HbA1c measurements were available, were identified. Associations between 11 tagging single nucleotide polymorphisms in the SLC22A1 gene and change in the HbA1c level were analyzed. A total of 102 incident metformin users were included in this study sample. Except for the rs622342 A>C polymorphism, no significant differences in metformin response were observed. For each minor C allele at rs622342, the reduction in HbA1c levels was 0.28% less (95% CI 0.09-0.47, P=0.005). After Bonferroni correction, the P-value was 0.050. To conclude, genetic variation at rs622342 in the SLC22A1 gene was associated with the glucose-lowering effect of metformin in patients with diabetes mellitus.

Aims/hypothesisSeveral publications suggest an association between certain types of insulin and cancer, but with conflicting results. We investigated whether insulin glargine (A21Gly,B31Arg,B32Arg human insulin) is associated with an increased risk of cancer in a large population-based cohort study.MethodsData for this study were obtained from dispensing records from community pharmacies individually linked to hospital discharge records from 2.5 million individuals in the Netherlands. In a cohort of incident users of insulin, the association between insulin glargine and other insulin analogues, respectively, and cancer was analysed in comparison with human insulin using Cox proportional hazard models with cumulative duration of drug use as a time-varying determinant. The first hospital admission with a primary diagnosis of cancer was considered as the main outcome; secondary analyses were performed with specific cancers as outcomes.ResultsOf the 19,337 incident insulin users enrolled, 878 developed cancer. Use of insulin glargine was associated with a lower risk of malignancies in general in comparison with human insulin (HR 0.75, 95% CI 0.71, 0.80). In contrast, an increased risk was found for breast cancer (HR 1.58, 95% CI 1.22, 2.05). Dose–response relationships could not be identified.Conclusion/interpretationUsers of insulin glargine and users of other insulin analogues had a lower risk of cancer in general than those using human insulin. Both associations might be a consequence of residual confounding, lack of adherence or competing risk. However, as in previous studies, we demonstrated an increased risk of breast cancer in users of insulin glargine in comparison with users of human insulin.Electronic supplementary materialThe online version of this article (doi:10.1007/s00125-011-2312-4) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

In Dutch primary care, prevalent prescription of antidepressants continued to increase, but incident prescription of particular SSRIs decreased from 2000 onward. In later years, antidepressants were less frequently prescribed for depression-related indications in incident users.

Several genome-wide association studies have been performed on warfarin. For acenocoumarol, the most frequently used coumarin in many countries worldwide, pharmacodynamic influences are expected to be comparable. Pharmacokinetics however might differ. We aimed to confirm known or identify new genetic variants contributing to interindividual variation on stabilized acenocoumarol dosage by a GWAS. The index population consisted of 1451 Caucasian subjects from the Rotterdam study and results were replicated in 287 subjects from the Rotterdam study extended cohort. Both cohorts were genotyped on the Illumina 550K Human Map SNP array. From polymorphisms tested for association with acenocoumarol dosage, 35 single nucleotide polymorphisms (SNPs) on chromosome 16 and 18 SNPs on chromosome 10 reached genome-wide significance. The SNP with the lowest P-value was rs10871454 on chromosome 16 linked to SNPs within the vitamin K epoxide reductase complex subunit 1 (VKORC1) (P = 2.0 x 10(-123)). The lowest P-value on chromosome 10 was obtained by rs4086116 within cytochrome P450 2C9 (CYP2C9) (P = 3.3 x 10(-24)). After adjustment for these SNPs, the rs2108622 polymorphism within cytochrome P450 4F2 (CYP4F2) gene on chromosome 19 reached genome-wide significance (P = 2.0 x 10(-8)). On chromosome 10, we further identified genetic variation in the cytochrome P450 2C18 (CYP2C18) gene contributing to variance of acenocoumarol dosage. Thus we confirmed earlier findings that acenocoumarol dosage mainly depends on polymorphisms in the VKORC1 and CYP2C9 genes. Besides age, gender, body mass index and target INR, one polymorphism within each of the VKORC1, CYP2C9, CYP4F2 and CYP2C18 genes could explain 48.8% of acenocoumarol dosage variation.