Modification of the association between paroxetine serum concentration and SERT-occupancy by ABCB1 (P-glycoprotein) polymorphisms in major depressive disorder.

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) exert substantial variability in effectiveness in patients with major depressive disorder (MDD), with up to 50-60% not achieving adequate response. Elucidating pharmacokinetic factors that explain this variability is important to increase treatment effectiveness. OBJECTIVES: To examine potential modification of the relationship between paroxetine serum concentration (PSC) and serotonin transporter (SERT)-occupancy by single nucleotide polymorphisms (SNPs) of the ABCB1 gene, coding for the P-glycoprotein (P-gp) pump, in MDD patients. To investigate the relationship between ABCB1 SNPs and clinical response. METHODS: Patients had MDD and received paroxetine 20 mg/day. We measured PSC after 6 weeks. We quantified SERT-occupancy with SPECT imaging (n = 38) and measured 17-item Hamilton Depression Rating Scale (HDRS17)-scores at baseline and after 6 weeks (n = 81). We genotyped ABCB1 at rs1045642 [3435C>T], rs1128503 [1236C>T], rs2032582 [2677G>T/A] and rs2235040 [2505G>A]. For our primary aim, we modeled mean SERT-occupancy in an Emax nonlinear regression model with PSC and assessed whether the model improved by genetic subgrouping. For our secondary aim, we used multivariate linear regression analysis. RESULTS: The rs1128503 and rs2032582 SNPs modified the relationship between PSC and SERT-occupancy in both our intention-to-treat and sensitivity analyses at the carriership level. However, we could not detect significant differences in clinical response between any of the genetic subgroups. CONCLUSION: Pharmacokinetic influences of the ABCB1 rs1128503 and rs2032582 represent a potentially relevant pharmacogenetic mechanism to consider when evaluating paroxetine efficacy. Future studies are needed to support the role of ABCB1 genotyping for individualizing SSRI pharmacotherapy.

Biomarker approaches in major depressive disorder evaluated in the context of current hypotheses.

Major depressive disorder is a heterogeneous disorder, mostly diagnosed on the basis of symptomatic criteria alone. It would be of great help when specific biomarkers for various subtypes and symptom clusters of depression become available to assist in diagnosis and subtyping of depression, and to enable monitoring and prognosis of treatment response. However, currently known biomarkers do not reach sufficient sensitivity and specificity, and often the relation to underlying pathophysiology is unclear. In this review, we evaluate various biomarker approaches in terms of scientific merit and clinical applicability. Finally, we discuss how combined biomarker approaches in both preclinical and clinical studies can help to make the connection between the clinical manifestations of depression and the underlying pathophysiology.

Striatal dopamine D2/3 receptor availability in treatment resistant depression.

Several studies demonstrated improvement of depressive symptoms in treatment resistant depression (TRD) after administering dopamine agonists which suggest abnormal dopaminergic neurotransmission in TRD. However, the role of dopaminergic signaling through measurement of striatal dopamine D(2/3) receptor (D2/3R) binding has not been investigated in TRD subjects. We used [(123)I]IBZM single photon emission computed tomography (SPECT) to investigate striatal D2/3R binding in TRD. We included 6 severe TRD patients, 11 severe TRD patients on antipsychotics (TRD AP group) and 15 matched healthy controls. Results showed no significant difference (p = 0.75) in striatal D2/3R availability was found between TRD patients and healthy controls. In the TRD AP group D2/3R availability was significantly decreased (reflecting occupancy of D2/3Rs by antipsychotics) relative to TRD patients and healthy controls (p<0.001) but there were no differences in clinical symptoms between TRD AP and TRD patients. This preliminary study therefore does not provide evidence for large differences in D2/3 availability in severe TRD patients and suggests this TRD subgroup is not characterized by altered dopaminergic transmission. Atypical antipsychotics appear to have no clinical benefit in severe TRD patients who remain depressed, despite their strong occupancy of D2/3Rs.

Relation between structural and functional connectivity in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is characterized by abnormalities in both brain structure and function within a frontolimbic network. However, little is known about the relation between structural and functional abnormalities in MDD. Here, we used a multimodal neuroimaging approach to investigate the relation between structural connectivity and functional connectivity within the frontolimbic network. METHODS: Eighteen MDD and 24 healthy control subjects were included, of which the integrity of the uncinate fasciculus was assessed that connects the subgenual anterior cingulate cortex (ACC) to the medial temporal lobe (MTL) with diffusion tensor imaging. Furthermore, we assessed the functional connectivity between these brain regions with functional magnetic resonance imaging. RESULTS: The results showed that white matter integrity of the uncinate fasciculus was reduced and that functional connectivity between the subgenual ACC and MTL was enhanced in MDD. Importantly, we identified a negative correlation between uncinate fasciculus integrity and subgenual ACC functional connectivity with the bilateral hippocampus in MDD but not in healthy control subjects. Moreover, this negative structure-function relation in MDD was positively associated with depression severity. CONCLUSIONS: These findings suggest that structural abnormalities in MDD are associated with increased functional connectivity between subgenual ACC and MTL and that these changes are concomitant with severity of depressive symptoms. This association indicates that structural abnormalities in MDD contribute to increased functional connectivity within the frontolimbic network.