NCT00088699 Strong evidence from family and twin studies demonstrates that major depressive disorder (MDD) is heritable, yet there has been limited progress in identifying the actual genes involved. A separate, perhaps overlapping set of genes is expected to play a role in individual variation in treatment response in MDD. By use of a large set of markers in many genes, we seek to characterize patients who differ in their response to standard antidepressant treatments. In the first years of this project, candidate gene studies implicated a few genes in treatment outcome and other genes in adverse effects. Future studies are needed to determine whether individuals who carry such genetic markers may benefit from closer monitoring or alternative treatments. We also participated in a meta-analysis of three genome-wide association studies of antidepressant outcome. Despite greater power of this combined sample to uncover association with common genetic markers, no genome-wide significant associations were found. We concluded that no common alleles of large effect on antidepressant outcome exist in these samples. Last year we re-examined this question in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) sample using newer analysis methods that improve upon older genotyping techniques initially used in this sample. In collaboration with Dr. Yin Yao and colleagues at NIMH, we carried out a new genome wide association study of antidepressant response in the STAR*D sample. This identified several SNPs associated with outcome after 12 weeks of treatment. Heritability was greater for outcomes following longer treatment periods, an unexpected finding that suggests the shorter treatment durations typically used in pharmacogenomic studies may not be optimal. Ongoing work is aimed at replicating these findings in additional samples. An exploratory GWAS of response to the novel antidepressants, ketamine and scopolamine, found that a polygenic score comprising alleles potentially associated with response to ketamine was significantly associated with response in an independent sample of patients treated with scopolamine. This suggests that some of genes associated with response to ketamine also play a role in scopolamine response. Ongoing work is aimed at replicating these findings in additional samples. We are also using new, high-throughput sequencing methods to test for rarer genetic variants that may exert larger effects, at least in patients with treatment resistant depression. Such variants may show larger effects, especially among patients with unusual treatment outcomes. Sequencing of the coding regions of the genome (exome) has now been completed on over 175 treatment-resistant (TRD) or typically responsive patients drawn from the STAR*D, the Univ. Michigan Depression Center, and NIMH studies of novel antidepressants such as ketamine and scopolamine. Much of the exome sequencing was carried out at the NIH Intramural Sequencing Center with funds provided by the NIH Clinical Center Genomics Opportunity (CCGO) program, which also provided exome sequence from about 200 non-psychiatric patients for comparison. Of the 350,000 high-quality genetic variants identified, about 15,000 were found to be rare, potentially-damaging variants within the protein-coding regions of genes. Some of these variants appeared in up to 6 TRD cases, although they were not detected in other sequenced patients. Nevertheless, no variant, gene, or gene set was found to be significantly associated with TRD after correction for multiple testing. There remains considerable debate about the return of secondary genomic findings to research participants. To address this, we contributed exome sequence data to a CCGO-led collaborative project designed to evaluate the impact of returning secondary genomic findings in research settings. Nearly 1,200 individuals were sequenced and 14 secondary findings were identified in 18 participants. Secondary findings were returned following a standardized protocol, followed by interviews and surveys of study participants aimed at assessing distress, understanding, and use of recommended health care services, where indicated. The majority of participants reported low distress, good understanding, and increased use of appropriate services, although a minority expressed confusion regarding the distinction between primary and secondary findings. This pilot study demonstrated the feasibility of coupling secondary findings to research sequencing, with minimal harms. Additional work is needed to understand barriers to follow-up care and help participants distinguish between secondary and primary findings in genomic studies. We have now identified an additional sample of individuals with TRD whose DNA will be sequenced In the coming year. Additional work will be needed to evaluate any contribution of identify copy number variants or variants in non-coding regions. Taken together, these approaches may increase power and identify genes robustly associated with resistance to anti-depressant treatment. Such genes could provide important clues about how to develop more effective antidepressant therapies.

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16
Fiscal Year
2019
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U.S. National Institute of Mental Health
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Niciu, Mark J; Iadarola, Nicolas D; Banerjee, Dipavo et al. (2017) The antidepressant efficacy of subanesthetic-dose ketamine does not correlate with baseline subcortical volumes in a replication sample with major depressive disorder. J Psychopharmacol 31:1570-1577
McMahon, Francis J (2016) Genetic association studies in psychiatry: time for pay-off. Lancet Psychiatry 3:309-10
Xu, Meng Yuan; Umbach, David M; Murphy, Eleanor et al. (2015) A Novel Mixture Model to Estimate the Time to Drug Effect Onset and Its Association with Covariates. Hum Hered 80:90-9
McMahon, Francis J (2015) Clinically Useful Genetic Markers of Antidepressant Response: How Do We Get There From Here? Am J Psychiatry 172:697-9
McMahon, Francis J (2014) Prediction of treatment outcomes in psychiatry--where do we stand ? Dialogues Clin Neurosci 16:455-64
Lekman, Magnus; Hössjer, Ola; Andrews, Peter et al. (2014) The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study. BioData Min 7:19
Kreisl, William C; Jenko, Kimberly J; Hines, Christina S et al. (2013) A genetic polymorphism for translocator protein 18 kDa affects both in vitro and in vivo radioligand binding in human brain to this putative biomarker of neuroinflammation. J Cereb Blood Flow Metab 33:53-8
Murphy, Eleanor; McMahon, Francis J (2013) Pharmacogenetics of antidepressants, mood stabilizers, and antipsychotics in diverse human populations. Discov Med 16:113-22
Murphy, Eleanor J; Kassem, Layla; Chemerinski, Anat et al. (2013) Retention and attrition among African Americans in the STAR*D study: what causes research volunteers to stay or stray? Depress Anxiety 30:1137-44
Murphy, Eleanor; Hou, Liping; Maher, Brion S et al. (2013) Race, genetic ancestry and response to antidepressant treatment for major depression. Neuropsychopharmacology 38:2598-606

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