Karen Snyder

The Influence of Age on the Response of Major Depression to Electroconvulsive Therapy A C.O.R.E. Report

As part of a C.O.R.E., multi-site longitudinal study comparing continuation electroconvulsive therapy (ECT) vs. continuation pharmacotherapy, the authors determined the response of 253 patients with major depression to acute-phase, bilateral ECT by use of the 24-item Hamilton Rating Scale for Depression. Remission rates for three age-groups, > or =65 years; 46-64 years; and < or =45 years, were 90 percent, 89.8 percent, and 70 percent, respectively. Age, as a continuous variable, positively influenced response to treatment. Bilateral, dose-titrated ECT is a highly effective acute treatment for major depression, and older age confers a greater likelihood of achieving remission.

SLC6A4 variation and citalopram response.

The influence of genetic variations in SLC6A4 (serotonin transporter gene) on citalopram treatment of depression using the Sequenced Treatment to Relieve Depression (STAR*D) sample was assessed. Of primary interest were three previously studied polymorphisms: 1) the VNTR variation of the second intron, 2) the indel promoter polymorphism (5HTTLPR or SERT), and 3) a single nucleotide polymorphism (SNP) rs25531. Additionally, SLC6A4 was resequenced to identify new SNPs for exploratory analyses. DNA from 1914 subjects in the STAR*D study were genotyped for the intron 2 VNTR region, the indel promoter polymorphism, and rs25531. Associations of these variants with remission of depressive symptoms were evaluated following citalopram treatment. In white non‐Hispanic subjects, variations in the intron 2 VNTR (point‐wise P = 0.041) and the indel promoter polymorphism (point‐wise P = 0.039) were associated with remission following treatment with citalopram. The haplotype composed of the three candidate loci was also associated with remission, with a global p‐value of 0.040 and a maximum statistic simulation p‐value of 0.0031 for the S‐a‐12 haplotype, under a dominant model. One SNP identified through re‐sequencing the SLC6A4 gene, Intron7‐83‐TC, showed point‐wise evidence of association, which did not remain significant after correction for the number of SNPs evaluated in this exploratory analysis. No associations between these SLC6A4 variations and remission were found in the white Hispanic or black subjects. These findings suggest that multiple variations in the SLC6A4 gene are associated with remission in white non‐Hispanic depressed adults treated with citalopram. The mechanism of action of these variants remains to be determined.

Glycine and a glycine dehydrogenase (GLDC) SNP as citalopram/escitalopram response biomarkers in depression: pharmacometabolomics-informed pharmacogenomics.

Major depressive disorder (MDD) is a common psychiatric disease. Selective serotonin reuptake inhibitors (SSRIs) are an important class of drugs used in the treatment of MDD. However, many patients do not respond adequately to SSRI therapy. We used a pharmacometabolomics‐informed pharmacogenomic research strategy to identify citalopram/escitalopram treatment outcome biomarkers. Metabolomic assay of plasma samples from 20 escitalopram remitters and 20 nonremitters showed that glycine was negatively associated with treatment outcome (P = 0.0054). This observation was pursued by genotyping tag single‐nucleotide polymorphisms (SNPs) for genes encoding glycine synthesis and degradation enzymes, using 529 DNA samples from SSRI‐treated MDD patients. The rs10975641 SNP in the glycine dehydrogenase (GLDC) gene was associated with treatment outcome phenotypes. Genotyping for rs10975641 was carried out in 1,245 MDD patients in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, and its presence was significant (P = 0.02) in DNA taken from these patients. These results highlight a possible role for glycine in SSRI response and illustrate the use of pharmacometabolomics to “inform” pharmacogenomics.

Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting

Objective The objective was to evaluate the potential benefit of an integrated, five-gene pharmacogenomic test and interpretive report (GeneSight) for the management of psychotropic medications used to treat major depression in an outpatient psychiatric practice. Methods The open-label study was divided into two groups. In the first (unguided) group (n=113), pharmacogenomic information was not shared until all participants completed the study. In the second (guided) group (n=114), the pharmacogenomic report was provided to physicians for clinical use. Three depression ratings, the 17-item Hamilton Rating Scale for Depression (HAMD-17), the Quick Inventory of Depressive Symptomatology – Clinician Rated (QIDS-C16), and the Patient Health Questionnaire (PHQ-9), were collected at baseline, and at 2, 4, and 8 weeks. Results The guided group experienced greater percent improvement in depression scores from baseline on all three depression instruments (HAMD-17, P<0.0001; QIDS-C16, P<0.0001; PHQ-9, P<0.0001) compared with the unguided group. Eight-week response rates were higher in the guided group than in the unguided group on all three measurements (HAMD-17, P=0.03; QIDS-C16, P=0.005; PHQ-9, P=0.01). Eight-week QIDS-C16 remission rates were higher in the guided group (P=0.03). Participants in the unguided group who at baseline were prescribed a medication that was most discordant with their genotype experienced the least improvement compared with other unguided participants (HAMD-17, P=0.007). Participants in the guided group and on a baseline medication most discordant with their genotype showed the greatest improvement compared with the unguided cohort participants (HAMD-17, P=0.01). Conclusion These findings replicate previous studies and demonstrate significantly improved depression outcomes with use of GeneSight, an integrated, multigenetic pharmacogenomic testing platform.

CYP2C19 Variation and Citalopram Response

Objective Variations in cytochrome P450 (CYP) genes have been shown to be associated with both accelerated and delayed pharmacokinetic clearance of many psychotropic medications. Citalopram is metabolized by three CYP enzymes. CYP2C19 and CYP3A4 play a primary role in citalopram metabolism, whereas CYP2D6 plays a secondary role. Methods The Sequenced Treatment Alternatives to Relieve Depression sample was used to examine the relationship between variations in the CYP2C19 and CYP2D6 genes and remission of depressive symptoms and tolerance to treatment with citalopram. The primary analyses were of the White non-Hispanic patients adherent to the study protocol (n=1074). Results Generally, patients who had CYP2C19 genotypes associated with decreased metabolism were less likely to tolerate citalopram than those with increased metabolism, although this difference was not statistically significant (P=0.06). However, patients with the inactive 2C19*2 allele had significantly lower odds of tolerance (P=0.02). Patients with the poor metabolism CYP2C19 genotype-based category who were classified as citalopram tolerant were more likely to experience remission (P=0.03). No relationship between CYP2D6 genotype-based categories and either remission or tolerance was identified, although exploratory analyses identified a potential interaction between CYP2C19 and CYP2D6 effects. Conclusion Despite several limitations including the lack of serum drug levels, this study showed that variations in CYP2C19 were associated with tolerance and remission in a large sample of White non-Hispanic patients treated with citalopram.

Merging pharmacometabolomics with pharmacogenomics using '1000 Genomes' single-nucleotide polymorphism imputation: Selective serotonin reuptake inhibitor response pharmacogenomics

Objective We set out to test the hypothesis that pharmacometabolomic data could be efficiently merged with pharmacogenomic data by single-nucleotide polymorphism (SNP) imputation of metabolomic-derived pathway data on a ‘scaffolding’ of genome-wide association (GWAS) SNP data to broaden and accelerate ‘pharmacometabolomics-informed pharmacogenomic’ studies by eliminating the need for initial genotyping and by making broader SNP association testing possible. Methods We previously genotyped 131 tag SNPs for six genes encoding enzymes in the glycine synthesis and degradation pathway using DNA from 529 depressed patients treated with citalopram/escitalopram to pursue a glycine metabolomics ‘signal’ associated with selective serotonine reuptake inhibitor response. We identified a significant SNP in the glycine dehydrogenase gene. Subsequently, GWAS SNP data were generated for the same patients. In this study, we compared SNP imputation within 200 kb of these same six genes with the results of the previous tag SNP strategy as a rapid strategy for merging pharmacometabolomic and pharmacogenomic data. Results Imputed genotype data provided greater coverage and higher resolution than did tag SNP genotyping, with a higher average genotype concordance between genotyped and imputed SNP data for ‘1000 Genomes’ (96.4%) than HapMap 2 (93.2%) imputation. Many low P-value SNPs with novel locations within genes were observed for imputed compared with tag SNPs, thus altering the focus for subsequent functional genomic studies. Conclusion These results indicate that the use of GWAS data to impute SNPs for genes in pathways identified by other ‘omics’ approaches makes it possible to rapidly and cost efficiently identify SNP markers to ‘broaden’ and accelerate pharmacogenomic studies.

Pharmacogenomics of selective serotonin reuptake inhibitor treatment for major depressive disorder: genome-wide associations and functional genomics

A genome-wide association (GWA) study of treatment outcomes (response and remission) of selective serotonin reuptake inhibitors (SSRIs) was conducted using 529 subjects with major depressive disorder. While no SNP associations reached the genome-wide level of significance, 14 SNPs of interest were identified for functional analysis. The rs11144870 SNP in the riboflavin kinase (RFK) gene on chromosome 9 was associated with 8-week treatment response (odds ratio (OR)=0.42, P=1.04 × 10−6). The rs915120 SNP in the G protein-coupled receptor kinase 5 (GRK5) gene on chromosome 10 was associated with 8-week remission (OR=0.50, P=1.15 × 10−5). Both SNPs were shown to influence transcription by a reporter gene assay and to alter nuclear protein binding using an electrophoretic mobility shift assay. This report represents an example of joining functional genomics with traditional GWA study results derived from a GWA analysis of SSRI treatment outcomes. The goal of this analytical strategy is to provide insights into the potential relevance of biologically plausible observed associations.

Catechol O-methyltransferase pharmacogenomics and selective serotonin reuptake inhibitor response

We applied a systematic pharmacogenetic approach to investigate the role of genetic variation in the gene encoding catechol O-methyltransferase (COMT) in individual variation in selective serotonin reuptake inhibitor (SSRI) response among depressed patients. In all, 23 single-nucleotide polymorphisms (SNPs) in COMT were genotyped using DNA from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (N=1914). One SNP, rs13306278, located in the distal promoter region of COMT, showed significant association with remission in White non-Hispanic (WNH) subjects (P=0.038). Electromobility shift assay for rs13306278 showed alternation in the ability of the variant sequence to bind nuclear proteins. A replication study was performed using samples from the Mayo Clinic Pharmacogenetics Research Network Citalopram/Escitalopram Pharmacogenomic study (N=422) that demonstrated a similar trend for association. Our findings suggest that novel genetic markers in the COMT distal promoter may influence SSRI response phenotypes.

Treatment outcomes of depression: the pharmacogenomic research network antidepressant medication pharmacogenomic study.

Background The effectiveness of selective serotonin reuptake inhibitors (SSRIs) in patients with major depressive disorder (MDD) is controversial. Aims The clinical outcomes of subjects with nonpsychotic MDD were reported and compared with the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study outcomes to provide guidance on the effectiveness of SSRIs. Methods Subjects were treated with citalopram/escitalopram for up to 8 weeks. Depression was measured using the Quick Inventory of Depressive Symptomatology—Clinician Rated (QIDS-C16) and the 17-item Hamilton Depression Rating Scale. Results The group of subjects with at least 1 follow-up visit had a remission (QIDS-C16 ⩽ 5) rate of 45.8% as well as a response (50% reduction in QIDS-C16) rate of 64.8%, and 79.9% achieved an improvement of 5 points or higher in QIDS-C16 score. The Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study subjects were more likely to achieve a response than STAR*D study subjects. After adjustment for demographic factors, the response rates were not significantly different. When reporting the adverse effect burden, 60.5% of the subjects reported no impairment, 31.7% reported a minimal-to-mild impairment, and 7.8% reported a moderate-to-severe burden at the 4-week visit. Conclusions Patients contemplating initiating an SSRI to treat their MDD can anticipate a high probability of symptom improvement (79.9%) with a low probability that their symptoms will become worse. Patients with lower baseline severity have a higher probability of achieving remission. The Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study replicates many findings of the first phase of the STAR*D study after controlling for the differences between the studies.

Relationship between somatization and remission with ECT

Patients treated with electroconvulsive therapy (ECT) were divided into those with less severe depression and those with more severe depression. In the less severely depressed group, high somatic anxiety and hypochondriasis predicted a low likelihood of sustained remission with ECT. In the more severely depressed group, these traits were not predictive of ECT outcome.