Background-Antidepressant response is likely influenced by genetic constitution, but the actual genes involved have yet to be determined. We have carried out a genome-wide association study to determine if common DNA variation influences antidepressant response.

We report a genome-wide association study (GWAS) of major depressive disorder (MDD) in 1,221 cases from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study and 1,636 screened controls. No genome-wide evidence for association was detected. We also carried out a meta-analysis of three European-ancestry MDD GWAS datasets: STAR*D, Genetics of Recurrent Early-Onset Depression (GenRED) and the publicly-available Genetic Association Information Network MDD dataset (GAIN-MDD). These datasets, totaling 3,957 cases and 3,428 controls, were genotyped using four different platforms (Affymetrix 6.0, 5.0 and 500K, and Perlegen). For each of 2.4 million HapMap II SNPs, using genotyped data where available and imputed data otherwise, single-SNP association tests were carried out in each sample with correction for ancestry-informative principal components. The strongest evidence for association in the meta-analysis was observed for intronic SNPs in ATP6V1B2 (P = 6.78 × 10−7), SP4 (P = 7.68 × 10−7) and GRM7 (P = 1.11 × 10−6). Additional exploratory analyses were carried out for a narrower phenotype (recurrent MDD with onset before age 31, N = 2,191 cases), and separately for males and females. Several of the best findings were supported primarily by evidence from narrow cases or from either males or females. Based on previous biological evidence, we consider GRM7 a strong MDD candidate gene. Larger samples will be required to determine whether any common SNPs are significantly associated with MDD.

In this study, we sought out to test the hypothesis that genetic factors may influence antidepressant response to fluoxetine. The investigation focused on seven candidate genes in the serotonergic pathway involved in the synthesis, transport, recognition, and degradation of serotonin. Our clinical sample consisted of 96 subjects with unipolar major depression treated with fluoxetine with response variables assessed after a 12-week trial. Patient data were also collected to investigate the pattern of drug response. Using a high-throughput singlenucleotide polymorphism (SNP) genotyping platform and capillary electrophoresis, we genotyped patients at 110 SNPs and four repeat polymorphisms located in seven candidate genes (HTR1A, HTR2A, HTR2C, MAOA, SLC6A4, TPH1, and TPH2). Statistical tests performed included single-locus and haplotype association tests, and linkage disequilibrium (LD) estimation. Little evidence of population stratification was observed in the sample with 20 random SNPs using a genomic control procedure. Our most intriguing result involved three SNPs in the TPH1 gene and one SNP in the SLC6A4 gene, which show significant single-locus association when response to fluoxetine is compared to nonresponse (P ¼ 0.02-0.04). All odds ratios indicated an increased risk of not responding to fluoxetine. In the specific response vs nonspecific and nonresponse comparison, three SNPs in the TPH2 gene (P ¼ 0.02-0.04) were positively associated and one SNP in the HTR2A gene (P ¼ 0.02) was negatively associated. When comparing specific response to nonspecific response, we found significant negative associations in three SNPs in the HTR2A gene (P ¼ 0.001-0.03) and two SNPs in the MAOA gene (P ¼ 0.03-0.05). We observed variable, although strong LD, in each gene and unexpectedly low numbers of estimated haplotypes, formed from tagged SNPs. Significant haplotype associations were found in all but the HTR1A and HTR2C genes. Although these data should be interpreted cautiously due to the small sample size, these results implicate TPH1 and SLC6A4 in general response, and HTR2A, TPH2, and MAOA in the specificity of response to fluoxetine. Intriguingly, we observe that a number of the less frequent alleles of many of the SNP markers were associated with the nonresponse and nonspecific phenotypes.

Genomic profiling of circulating tumor DNA derived from cell-free DNA (cfDNA) in blood can provide a noninvasive method for detecting genomic biomarkers to guide clinical decision making for cancer patients. We developed a hybrid capture-based next-generation sequencing assay for genomic profiling of circulating tumor DNA from blood (FoundationACT). High-sequencing coverage and molecular barcode-based error detection enabled accurate detection of genomic alterations, including short variants (base substitutions, short insertions/deletions) and genomic re-arrangements at low allele frequencies (AFs), and copy number amplifications. Analytical validation was performed on 2666 reference alterations. The assay achieved >99% overall sensitivity (95% CI, 99.1%-99.4%) for short variants at AF >0.5%, >95% sensitivity (95% CI, 94.2%-95.7%) for AF 0.25% to 0.5%, and 70% sensitivity (95% CI, 68.2%-71.5%) for AF 0.125% to 0.25%. No false positives were detected in 62 samples from healthy volunteers. Genomic alterations detected by FoundationACT demonstrated high concordance with orthogonal assays run on the same clinical cfDNA samples. In 860 routine clinical FoundationACT cases, genomic alterations were detected in cfDNA at comparable frequencies to tissue; for the subset of cases with temporally matched tissue and blood samples, 75% of genomic alterations and 83% of short variant mutations detected in tissue were also detected in cfDNA. On the basis of analytical validation results, FoundationACT has been approved for use in our Clinical Laboratory Improvement Amendments-certified/College of American Pathologists-accredited/New York State-approved laboratory.

We examined the impact of patient- and therapist-rated alliance developed during psychological assessment on the subsequent alliance measured early and late in formal psychotherapy. We hypothesized that a working alliance developed during psychological assessment conducted from a collaborative therapeutic model of assessment (TMA; Finn & Tonsager, 1992, 1997; Fischer, 1994) between the patient and therapist would carry into formal psychotherapy. We also hypothesized that alliance for those patients receiving a TMA would be significantly greater than patients receiving psychological testing as usual. To test this hypothesis, we administered the Combined Alliance Short Form-Patient Version (Hatcher & Barends, 1996) and the Combined Alliance Short Form-Therapist Version (Hatcher, 1999) to a sample of outpatients and their therapists at the end of the assessment feedback session, early, and late in psychotherapy. The hypotheses were supported as alliance scales rated at the assessment feedback session demonstrated positive and significant relationships with alliance throughout formal psychotherapy and in relation to a control group. The clinical utility and research implications of these findings are discussed.

BackgroundWe sought to determine whether clinical response or tolerance to the Selective Serotonin Reuptake Inhibitor (SSRI) citalopram is associated with genetic polymorphisms in potentially relevant pharmacokinetic enzymes.MethodologyWe used a two-stage case-control study design in which we split the sample of 1,953 subjects from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial into a discovery (n = 831) and validation set (n = 1,046). Fifteen polymorphisms from five (CYP2D6, ABCB1, CYP2C19, CYP3A4, and CYP3A5) pharmacokinetic genes were genotyped. We examined the associations between these polymorphisms and citalopram response and tolerance. Significant associations were validated in the second stage for those polymorphism found to be statistically significant in the first stage.ConclusionsNo genetic polymorphism in the pharmacokinetic genes examined was significantly associated with our response or tolerance phenotypes in both stages. For managing pharmacological treatment with citalopram, routine screening of the common pharmacokinetic DNA variants that we examined appears to be of limited clinical utility.

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Clinical applications of precision oncology require accurate tests that can distinguish true cancer specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.