The <i>ABCB1</i> 1199A variant differentially affects Tac and CsA efflux.

<p>Intracellular accumulation of tacrolimus after 120 min of incubation (N = 3) (<b>A</b>) at six different concentrations (0.0015–0.5 μM) in CTL HEK293, CTL HEKpcDNA3.1, HEK_1199G and HEK_1199A and (<b>B</b>) at 0.05 μM in CTL K562, CTL K562 pcDNA3.1, K562_1199G and K562_1199A. Intracellular accumulation of CsA after 120 min of incubation (N = 3) (<b>C</b>) at six different concentrations (0.015–5 μM) in CTL HEK, CTL HEKpcDNA3.1, HEK_1199G and HEK_1199A and (<b>D</b>) at 0.5 μM in CTL K562, CTL K562pcDNA3.1, K562_1199G and K562_1199A. The intracellular accumulation of Tac or CsA in each cell line was normalized by reporting the absolute amounts of Tac or CsA (in ng) on the total amount of proteins in cell extracts, expressed in mg. * compared to 1199G/WT *p<0.05 **p<0.01 ***p<0.001.</p

Influence of <i>ABCB1</i> 1199G>A polymorphism on drug transport and/or efficacy.

<p>*Compared to 1199G wild-type; n.a.: not available.</p><p>See text for details.</p

ABCB1 expression analysis by fluorescence microscopy.

<p>(<b>A</b>) Untransfected (CTL) HEK293, (<b>B</b>) transfected with empty plasmid (CTL pcDNA3.1) HEK pcDNA3.1 (<b>C</b>) HEK_1199G and (<b>D</b>) HEK_1199A cells were stained with anti-ABCB1 antibodies (green fluorescence) as described in materials and methods. DAPI was used to stain nuclei (blue).</p

Tacrolimus intracellular kinetics.

<p>Intracellular accumulation of tacrolimus (0.05 μM) after 15, 30 sec, 1, 5, 10, 30 or 60 min of efflux (N = 6) in (<b>A</b>) CTL HEK293, CTL HEKpcDNA3.1, HEK_1199G and HEK_1199A and (<b>B</b>) CTL K562, CTL K562pcDNA3.1, K562_1199G and K562_1199A. Cells were pre-loaded with tac for 120 min before efflux. The intracellular accumulation of Tac in each cell line was normalized by reporting the absolute amounts of Tac (in ng) on the total amount of proteins in cell extracts, expressed in mg. * compared to CTL pcDNA3.1 *p<0.05 **p<0.01 ***p<0.001, # compared to 1199G/WT #p<0.05 ##p<0.01 ###p<0.001.</p

Intracellular accumulation of Rhodamine123 is not influenced by <i>ABCB1</i> 1199A variant.

<p>Intracellular accumulation of Rhodamine123 (5 μM) in presence (0.1 and 0.2 μM) or absence of ABCB1 inhibitor (LY335979) (N = 6) in (<b>A</b>) CTL HEK293, CTL HEKpcDNA3.1, HEK_1199G and HEK_1199A and (<b>B</b>) CTL K562, CTL K562pcDNA3.1, K562_1199G and K562_1199A. * compared without inhibitor *p<0.05 **p<0.01 ***p<0.001, # compared to CTL pcDNA3.1 #p<0.05 ##p<0.01 ###p<0.001.</p

sanger_7690067

Fasta aligment of Amplicon1:Chr9:7690067 with all P. tremuloides clones included used for generating phylogenetic tree on Figure S2 panel

chr19_tree

Fasta aligment of concatenated Amplicon1:Chr19:40024, Amplicon2:Chr19:41515 and Amplicon3:Chr19:44107, used for generating phylogenetic tree on Figure 3b

44107_sanger_tree

Fasta alignment for Figure S2 panel e (Chr19 Amplicon3:Chr19:44107 , all P. tremuloides clones included

Impact of psychological profile on drug adherence and drug resistance in patients with apparently treatment-resistant hypertension

<p><b>Purpose:</b> Patients with apparent treatment-resistant hypertension (a-TRH) are often poorly adherent to drug treatment and have an unusual personal history and psychological profile. The aim of this study was to identify predictors of drug adherence and drug resistance in a cohort of patients with aTRH, with emphasis on psychological characteristics.</p> <p><b>Methods:</b> All patients with confirmed aTRH on standardized antihypertensive treatment were eligible. Drug adherence was assessed by drug dosages in urine using Liquid Chromatography coupled with tandem Mass Spectrometry (LC-MS/MS). Drug resistance was assessed by 24-hour ambulatory blood pressure adjusted for the number of antihypertensive drugs and for drug adherence. Psychological profile was assessed using a broad array of validated questionnaires.</p> <p><b>Results:</b> The analysis included 35 consecutive patients. The proportion of adherent, partly adherent and totally non-adherent patients was 29, 40 and 31%, respectively. In regression analysis, independent predictors of poor drug adherence were recent hospital admission for hypertension, a lower ability to put things into perspective when facing negative events and a higher tendency to somatize, accounting for 51% of variability in drug adherence. Independent predictors of treatment resistance were a higher recourse to the strategies of blaming others and oneself, accounting for 37% of variability in drug treatment resistance.</p> <p><b>Conclusion:</b> In patients with aTRH, poor adherence is frequent but does not entirely account for treatment resistance. Psychological characteristics appear as strong predictors of both drug adherence and drug resistance. Our results suggest that therapeutic drug monitoring and psychological evaluation should be an integral part of assessment of patients with aTRH.</p

44107_sanger_tree_ML

Newick tree file for Figure S2 panel e (Chr19 Amplicon3:Chr19:44107 , all P. tremuloides clones included