RESEARCH ARTICLE Neuropsychiatric Genetics
Genetic Susceptibility for Bipolar Disorder and Response to Antidepressants in Major Depressive Disorder Katherine E. Tansey,1* Michel Guipponi,2 Enrico Domenici,3 Glyn Lewis,4 Alain Malafosse,2,5 Michael O’Donovan,6 Jens R. Wendland,7 Cathryn M. Lewis,1 Peter McGuffin,1 and Rudolf Uher1,8 1
Institute of Psychiatry, King’s College London, London, United Kingdom Department of Genetic Medicine and Laboratories, University Hospitals of Geneva, Geneva, Switzerland
2 3
F. Hoffmann-La Roche, Pharma Research and Early Development, Basel, Switzerland
4
School of Social and Community Medicine, University of Bristol, Bristol, UK Department of Psychiatry, University of Geneva, Geneva, Switzerland
5 6
Department of Psychological Medicine and Neurology, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom 7
Worldwide R&D, Pfizer, Inc., Cambridge, Massachusetts Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
8
Manuscript Received: 16 April 2013; Manuscript Accepted: 15 October 2013
The high heterogeneity of response to antidepressant treatment in major depressive disorder (MDD) makes individual treatment outcomes currently unpredictable. It has been suggested that resistance to antidepressant treatment might be due to undiagnosed bipolar disorder or bipolar spectrum features. Here, we investigate the relationship between genetic susceptibility for bipolar disorder and response to treatment with antidepressants in MDD. Polygenic scores indexing risk for bipolar disorder were derived from the Psychiatric Genomics Consortium Bipolar Disorder whole genome association study. Linear regressions tested the effect of polygenic risk scores for bipolar disorder on proportional reduction in depression severity in two large samples of individuals with MDD, treated with antidepressants, NEWMEDS (n ¼ 1,791) and STAR D (n ¼ 1,107). There was no significant association between polygenic scores for bipolar disorder and response to treatment with antidepressants. Our data indicate that molecular measure of genetic susceptibility to bipolar disorder does not aid in understanding non-response to antidepressants. Ó 2013 Wiley Periodicals, Inc.
Key words: antidepressant; polygenic scoring; bipolarity; major depressive disorder
INTRODUCTION Response to antidepressants is heterogeneous with high levels of inter-individual variation in treatment outcome. There is the need to identify specific sub-groups of patients who may respond better or worse to currently available treatments in order to personalise treatment and reduce the time to remission of the disorder. Among factors to be involved in the lack of response to treatment with
Ó 2013 Wiley Periodicals, Inc.
How to Cite this Article: Tansey KE, Guipponi M, Domenici E, Lewis G, Malafosse A, O’Donovan M, Wendland JR, Lewis CM, McGuffin P, Uher R. 2014. Genetic Susceptibility for Bipolar Disorder and Response to Antidepressants in Major Depressive Disorder. Am J Med Genet Part B 165B:77–83.
Conflict of Interest: J.R.W. is a full-time employee of Pfizer, and was a full-time employee of F. Hoffmann La-Roche in the initial stages of NEWMEDS. E.D. is a full time employee of F. Hoffmann La-Roche and was a full-time employee of Glaxo-Smith-Kline in the initial stages of NEWMEDS. Grant sponsor: The work was sponsored by the Innovative Medicine Initiative Joint Undertaking (IMI-JU) under grant agreement number 115008, of which resources are composed of European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013). Correspondence to: Katherine Tansey, Box Number P081, De Crespigny Park, Denmark Hill, London SE5 8AF, UK. E-mail: [email protected] Article first published online in Wiley Online Library (wileyonlinelibrary.com): 8 November 2013 DOI 10.1002/ajmg.b.32210
77
78 antidepressants, undiagnosed bipolar disposition has received the most attention [Ghaemi et al., 2002; Ghaemi, 2008; Smith et al., 2009; Perlis et al., 2011; Smith et al., 2011]. The distinction between major depressive disorder (MDD) and bipolar disorder can be difficult in individuals who present during a depressive episode and impossible in those who have not yet developed their first episode of mania but may have a latent bipolar disposition [Ghaemi et al., 2002]. Studies have suggested that individuals with bipolar disorder may not benefit from antidepressants more than from placebo [Sachs and Gardner-Schuster, 2007; McElroy et al., 2010]. Previous research has shown individuals who fail to respond to treatment with antidepressant are more likely to change diagnosis from MDD to bipolar disorder in the future [Sharma et al., 2005; Li et al., 2012]. Among individuals with MDD, sub-threshold manic symptoms predicted poor outcome of treatment with antidepressants [Smith et al., 2009], suggesting bipolar features in MDD result in resistance to treatment with antidepressants. However, there have been contradictory findings. A large study of MDD individuals treated with antidepressants found no association between unrecognised bipolar spectrum disorder and treatment resistance [Perlis et al., 2011]. The lack of consistency in this area warrants further investigations. Previous studies have relied on clinical features to define bipolar disposition in individuals diagnosed with MDD. This method relies on the manifestation and reporting of signs of a disorder and may not detect latent disposition to developing bipolar disorder. With advancements in psychiatric genetics, we can for the first time attempt to answer this question using specific genetic susceptibility for bipolar disorder, indexed by a score summing a large number of risk variants across the human genome, based on results of the largest genetic association study under taken to date, the Psychiatric Genomics Consortium Bipolar Disorder [PGC-BP; 7,481 individuals with bipolar disorder and 9,250 controls; Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011]. Polygenic scores based on these results have been shown to significantly predict bipolar disorder and other phenotypes of interest (endophenotypes and clinical dimensions) in independent samples [Hamshere et al., 2011; Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011; Whalley et al., 2012]. Furthermore, polygenic score derived from bipolar disorder have been able to discriminate between cases and controls in MDD [Schulze et al., 2012; Cross-Disorder Group of the Psychiatric Genomics Consortium et al., 2013]. We hypothesize that increased genetic susceptibility for bipolar disorder would be associated with poor response to antidepressant treatment. We investigate the effect of increased genetic loading for bipolar disorder on antidepressant treatment response in two large pharmacogenetic studies of individuals with MDD treated with antidepressants.
MATERIALS AND METHODS Samples We analyzed two large cohorts of adults with major depressive disorder (MDD), with prospectively recorded outcome of antidepressant treatment and genome-wide genotyping, the Novel Meth-
AMERICAN JOURNAL OF MEDICAL GENETICS PART B ods leading to New Medications in Depression and Schizophrenia (NEWMEDS) and the Sequenced Treatment Alternatives to Relieve Depression (STAR D). NEWMEDS (http://www.newmeds-europe.com) included 2,146 treatment seeking adults (age range 18–74 years) treated for up to 12 weeks with serotonin-reuptake inhibiting (SSRI: escitalopram, citalopram, paroxetine, sertraline, fluoxetine) or norepinephrine reuptake inhibiting (NRI: nortriptyline, reboxetine) antidepressants as part of several academic (GENDEP n ¼ 868; GENPOD n ¼ 601; GODS n ¼ 131) and industry-led clinical trials [Pfizer n ¼ 355, GSK n ¼ 191; Tansey et al., 2012]. Individuals with self-reported white European ancestry, available high-quality blood DNA samples and valid information on treatment outcome with either SSRI or NRI were genotyped (n ¼ 1,893). Gender and age did not differ substantially between drug groups (any antidepressant mean age 42.19 (SD 11.60) 62.91% female; serotonergic antidepressants mean age 42.18 (SD 11.54) 62.15% female; noradrenergic antidepressants mean age 42.20 (SD 11.70) 63.96% female). Each study included in NEWMEDS was approved by institutional review boards and all participants signed informed consent. Further information about individual samples can be found in Supplementary Materials. STAR D (http://www.nimh.nih.gov/trials/practical/stard/index.shtml) included 4,041 treatment-seeking adult outpatients (age range 18–75 years) with a diagnosis of non-psychotic MDD recruited across the United States [Rush et al., 2004]. Individuals were included if they had a minimal depression severity of 14 on Hamilton Rating Scale for Depression [HRSD-17; Hamilton, 1960]. This analysis focuses on the first treatment step, when all individuals were treated with protocol-guided citalopram 20– 60 mg daily [Trivedi et al., 2006] in the 1,948 individuals with available DNA samples. Mean age of individuals included in this study was 43.17 (SD 13.72) and 57.54% were females. STAR D was approved by institutional ethics review boards in all centers. All participants provided a written consent after the procedures and associated risks were explained.
Genotyping and Quality Control Quality control was implemented in PLINK [Purcell et al., 2007]. NEWMEDS samples were genotyped on Illumina Human610Quad BeadChip (n ¼ 727) or Illumina Human 660W-Quad BeadChip (n ¼ 1,166; Illumina, Inc., San Diego, CA). We included markers with a minor allele frequency of 0.01 or more and at least 97% complete genotyping. We excluded markers that differed significantly (P < 1 103) by genotyping center. We excluded individuals for ambiguous sex (n ¼ 22), abnormal heterozygosity (n ¼ 16), cryptic relatedness up to third-degree relatives by identity by descent (n ¼ 20), genotyping completeness 0.0001 0.0002 0.0001 0.0001 >0.0001 0.0002 >0.0001 >0.0001 >0.0001 >0.0001 0.0027 0.0029 0.0015 0.0010 >0.0001 0.0001 >0.0001 0.0001 >0.0001
P-Value 0.837 0.837 0.590 0.606 0.621 0.829 0.638 0.911 0.934 0.865 0.960 0.214 0.202 0.355 0.463 0.918 0.774 0.956 0.686 0.815
With population covariates R2 >0.0001 >0.0001 0.0001 0.0001 0.0001 >0.0001 0.0002 >0.0001 >0.0001 >0.0001 >0.0001 0.0031 0.0034 0.0024 0.0017 >0.0001 >0.0001 0.0001 0.0001 >0.0001
P-Value 0.834 0.880 0.624 0.623 0.633 0.782 0.613 0.878 0.999 0.931 0.999 0.184 0.168 0.252 0.338 0.982 0.876 0.828 0.826 0.942
TANSEY ET AL.
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FIG. 1. Scatter plots of the relationship between polygenic score for bipolar disorder and response to antidepressants. Top left is NEWMEDS ALL, top right NEWMEDS SSRI, bottom left NEWMEDS NRI and bottom right STAR D.
noradrenergic (nortriptyline and reboxentine) antidepressants. The interpretation of the present results are therefore limited to these types of antidepressants and to White Caucasian population. Our results may not generalize to other types of antidepressants or
to individuals from ethnic backgrounds other than white European. Future studies of other types of antidepressants and different populations may offer important insights. Polygenic risk scores created from the PGC-BP dataset are not being suggested as tools
82 for personalizing treatment for individuals with MDD, but were used to decipher potential reasons about non-response to antidepressant treatment. The present negative findings, taking together with previous positive findings with other phenotypes using the same methodology and bipolar polygenic risk scores, constitute evidence against the hypothesis that latent bipolarity is responsible for substantial amount of treatment resistance among individuals diagnosed with MDD.
CONCLUSIONS Differentiating between bipolar disorder and major depressive disorder remains an important element of clinical practice. However, we found no evidence that testing for latent genetic disposition to bipolar disorder could contribute to response to antidepressant treatment among individuals with apparent MDD. It may be time to rethink the hypothesis about the causes of treatment resistance in MDD, and open new investigations into the reasons for treatment failure at both the clinical and biological level.
ACKNOWLEDGEMENTS The research leading to these results has received support from the Innovative Medicine Initiative Joint Undertaking (IMI-JU) under grant agreement no. 115008 of which resources are composed of European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013). EFPIA members Pfizer, Glaxo Smith Kline, and F. Hoffmann La-Roche have contributed work and samples to the project presented here. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. GENDEP was funded by the European Commission Framework 6 grant, EC Contract Ref.: LSHB-CT-2003-503428. Lundbeck provided nortriptyline and escitalopram for the GENDEP study. GlaxoSmithKline and the UK National Institute for Health Research of the Department of Health contributed to the funding of the sample collection at the Institute of Psychiatry, London. GENDEP genotyping was funded by a joint grant from the U.K. Medical Research Council (MRC, UK) and GlaxoSmithKline (G0701420). GenPod was funded by the Medical Research Council (MRC, UK) and supported by the Mental Health Research Network. GODS study was partly supported by external funding provided by the Swiss branches of the following pharmaceutical companies: GlaxoSmithKline, Wyeth-Lederle, Bristol-MyersSquibb, and Sanofi Aventis. R.U. is supported by the Canada Research Chairs program (http://www.chairs-chaires.gc.ca/). K.E. T. and R.U. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The authors thank the National Institute of Mental Health (NIMH) for providing access to the STAR D genetic dataset. STAR D was funded by NIMH via contract (N01MH90003) to the University of Texas Southwestern Medical Center at Dallas (A. John Rush, principal investigator). STAR D genotyping was supported by the National Institute of Mental Health (NIMH) grant to SPH (Grant No. MH072802).
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
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Genetic Susceptibility for Bipolar Disorder and Response to Antidepressants in Major Depressive Disorder Katherine E. Tansey,1* Michel Guipponi,2 Enrico Domenici,3 Glyn Lewis,4 Alain Malafosse,2,5 Michael O’Donovan,6 Jens R. Wendland,7 Cathryn M. Lewis,1 Peter McGuffin,1 and Rudolf Uher1,8 1
Institute of Psychiatry, King’s College London, London, United Kingdom Department of Genetic Medicine and Laboratories, University Hospitals of Geneva, Geneva, Switzerland
2 3
F. Hoffmann-La Roche, Pharma Research and Early Development, Basel, Switzerland
4
School of Social and Community Medicine, University of Bristol, Bristol, UK Department of Psychiatry, University of Geneva, Geneva, Switzerland
5 6
Department of Psychological Medicine and Neurology, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom 7
Worldwide R&D, Pfizer, Inc., Cambridge, Massachusetts Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
8
Manuscript Received: 16 April 2013; Manuscript Accepted: 15 October 2013
The high heterogeneity of response to antidepressant treatment in major depressive disorder (MDD) makes individual treatment outcomes currently unpredictable. It has been suggested that resistance to antidepressant treatment might be due to undiagnosed bipolar disorder or bipolar spectrum features. Here, we investigate the relationship between genetic susceptibility for bipolar disorder and response to treatment with antidepressants in MDD. Polygenic scores indexing risk for bipolar disorder were derived from the Psychiatric Genomics Consortium Bipolar Disorder whole genome association study. Linear regressions tested the effect of polygenic risk scores for bipolar disorder on proportional reduction in depression severity in two large samples of individuals with MDD, treated with antidepressants, NEWMEDS (n ¼ 1,791) and STAR D (n ¼ 1,107). There was no significant association between polygenic scores for bipolar disorder and response to treatment with antidepressants. Our data indicate that molecular measure of genetic susceptibility to bipolar disorder does not aid in understanding non-response to antidepressants. Ó 2013 Wiley Periodicals, Inc.
Key words: antidepressant; polygenic scoring; bipolarity; major depressive disorder
INTRODUCTION Response to antidepressants is heterogeneous with high levels of inter-individual variation in treatment outcome. There is the need to identify specific sub-groups of patients who may respond better or worse to currently available treatments in order to personalise treatment and reduce the time to remission of the disorder. Among factors to be involved in the lack of response to treatment with
Ó 2013 Wiley Periodicals, Inc.
How to Cite this Article: Tansey KE, Guipponi M, Domenici E, Lewis G, Malafosse A, O’Donovan M, Wendland JR, Lewis CM, McGuffin P, Uher R. 2014. Genetic Susceptibility for Bipolar Disorder and Response to Antidepressants in Major Depressive Disorder. Am J Med Genet Part B 165B:77–83.
Conflict of Interest: J.R.W. is a full-time employee of Pfizer, and was a full-time employee of F. Hoffmann La-Roche in the initial stages of NEWMEDS. E.D. is a full time employee of F. Hoffmann La-Roche and was a full-time employee of Glaxo-Smith-Kline in the initial stages of NEWMEDS. Grant sponsor: The work was sponsored by the Innovative Medicine Initiative Joint Undertaking (IMI-JU) under grant agreement number 115008, of which resources are composed of European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013). Correspondence to: Katherine Tansey, Box Number P081, De Crespigny Park, Denmark Hill, London SE5 8AF, UK. E-mail: [email protected] Article first published online in Wiley Online Library (wileyonlinelibrary.com): 8 November 2013 DOI 10.1002/ajmg.b.32210
77
78 antidepressants, undiagnosed bipolar disposition has received the most attention [Ghaemi et al., 2002; Ghaemi, 2008; Smith et al., 2009; Perlis et al., 2011; Smith et al., 2011]. The distinction between major depressive disorder (MDD) and bipolar disorder can be difficult in individuals who present during a depressive episode and impossible in those who have not yet developed their first episode of mania but may have a latent bipolar disposition [Ghaemi et al., 2002]. Studies have suggested that individuals with bipolar disorder may not benefit from antidepressants more than from placebo [Sachs and Gardner-Schuster, 2007; McElroy et al., 2010]. Previous research has shown individuals who fail to respond to treatment with antidepressant are more likely to change diagnosis from MDD to bipolar disorder in the future [Sharma et al., 2005; Li et al., 2012]. Among individuals with MDD, sub-threshold manic symptoms predicted poor outcome of treatment with antidepressants [Smith et al., 2009], suggesting bipolar features in MDD result in resistance to treatment with antidepressants. However, there have been contradictory findings. A large study of MDD individuals treated with antidepressants found no association between unrecognised bipolar spectrum disorder and treatment resistance [Perlis et al., 2011]. The lack of consistency in this area warrants further investigations. Previous studies have relied on clinical features to define bipolar disposition in individuals diagnosed with MDD. This method relies on the manifestation and reporting of signs of a disorder and may not detect latent disposition to developing bipolar disorder. With advancements in psychiatric genetics, we can for the first time attempt to answer this question using specific genetic susceptibility for bipolar disorder, indexed by a score summing a large number of risk variants across the human genome, based on results of the largest genetic association study under taken to date, the Psychiatric Genomics Consortium Bipolar Disorder [PGC-BP; 7,481 individuals with bipolar disorder and 9,250 controls; Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011]. Polygenic scores based on these results have been shown to significantly predict bipolar disorder and other phenotypes of interest (endophenotypes and clinical dimensions) in independent samples [Hamshere et al., 2011; Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011; Whalley et al., 2012]. Furthermore, polygenic score derived from bipolar disorder have been able to discriminate between cases and controls in MDD [Schulze et al., 2012; Cross-Disorder Group of the Psychiatric Genomics Consortium et al., 2013]. We hypothesize that increased genetic susceptibility for bipolar disorder would be associated with poor response to antidepressant treatment. We investigate the effect of increased genetic loading for bipolar disorder on antidepressant treatment response in two large pharmacogenetic studies of individuals with MDD treated with antidepressants.
MATERIALS AND METHODS Samples We analyzed two large cohorts of adults with major depressive disorder (MDD), with prospectively recorded outcome of antidepressant treatment and genome-wide genotyping, the Novel Meth-
AMERICAN JOURNAL OF MEDICAL GENETICS PART B ods leading to New Medications in Depression and Schizophrenia (NEWMEDS) and the Sequenced Treatment Alternatives to Relieve Depression (STAR D). NEWMEDS (http://www.newmeds-europe.com) included 2,146 treatment seeking adults (age range 18–74 years) treated for up to 12 weeks with serotonin-reuptake inhibiting (SSRI: escitalopram, citalopram, paroxetine, sertraline, fluoxetine) or norepinephrine reuptake inhibiting (NRI: nortriptyline, reboxetine) antidepressants as part of several academic (GENDEP n ¼ 868; GENPOD n ¼ 601; GODS n ¼ 131) and industry-led clinical trials [Pfizer n ¼ 355, GSK n ¼ 191; Tansey et al., 2012]. Individuals with self-reported white European ancestry, available high-quality blood DNA samples and valid information on treatment outcome with either SSRI or NRI were genotyped (n ¼ 1,893). Gender and age did not differ substantially between drug groups (any antidepressant mean age 42.19 (SD 11.60) 62.91% female; serotonergic antidepressants mean age 42.18 (SD 11.54) 62.15% female; noradrenergic antidepressants mean age 42.20 (SD 11.70) 63.96% female). Each study included in NEWMEDS was approved by institutional review boards and all participants signed informed consent. Further information about individual samples can be found in Supplementary Materials. STAR D (http://www.nimh.nih.gov/trials/practical/stard/index.shtml) included 4,041 treatment-seeking adult outpatients (age range 18–75 years) with a diagnosis of non-psychotic MDD recruited across the United States [Rush et al., 2004]. Individuals were included if they had a minimal depression severity of 14 on Hamilton Rating Scale for Depression [HRSD-17; Hamilton, 1960]. This analysis focuses on the first treatment step, when all individuals were treated with protocol-guided citalopram 20– 60 mg daily [Trivedi et al., 2006] in the 1,948 individuals with available DNA samples. Mean age of individuals included in this study was 43.17 (SD 13.72) and 57.54% were females. STAR D was approved by institutional ethics review boards in all centers. All participants provided a written consent after the procedures and associated risks were explained.
Genotyping and Quality Control Quality control was implemented in PLINK [Purcell et al., 2007]. NEWMEDS samples were genotyped on Illumina Human610Quad BeadChip (n ¼ 727) or Illumina Human 660W-Quad BeadChip (n ¼ 1,166; Illumina, Inc., San Diego, CA). We included markers with a minor allele frequency of 0.01 or more and at least 97% complete genotyping. We excluded markers that differed significantly (P < 1 103) by genotyping center. We excluded individuals for ambiguous sex (n ¼ 22), abnormal heterozygosity (n ¼ 16), cryptic relatedness up to third-degree relatives by identity by descent (n ¼ 20), genotyping completeness 0.0001 0.0002 0.0001 0.0001 >0.0001 0.0002 >0.0001 >0.0001 >0.0001 >0.0001 0.0027 0.0029 0.0015 0.0010 >0.0001 0.0001 >0.0001 0.0001 >0.0001
P-Value 0.837 0.837 0.590 0.606 0.621 0.829 0.638 0.911 0.934 0.865 0.960 0.214 0.202 0.355 0.463 0.918 0.774 0.956 0.686 0.815
With population covariates R2 >0.0001 >0.0001 0.0001 0.0001 0.0001 >0.0001 0.0002 >0.0001 >0.0001 >0.0001 >0.0001 0.0031 0.0034 0.0024 0.0017 >0.0001 >0.0001 0.0001 0.0001 >0.0001
P-Value 0.834 0.880 0.624 0.623 0.633 0.782 0.613 0.878 0.999 0.931 0.999 0.184 0.168 0.252 0.338 0.982 0.876 0.828 0.826 0.942
TANSEY ET AL.
81
FIG. 1. Scatter plots of the relationship between polygenic score for bipolar disorder and response to antidepressants. Top left is NEWMEDS ALL, top right NEWMEDS SSRI, bottom left NEWMEDS NRI and bottom right STAR D.
noradrenergic (nortriptyline and reboxentine) antidepressants. The interpretation of the present results are therefore limited to these types of antidepressants and to White Caucasian population. Our results may not generalize to other types of antidepressants or
to individuals from ethnic backgrounds other than white European. Future studies of other types of antidepressants and different populations may offer important insights. Polygenic risk scores created from the PGC-BP dataset are not being suggested as tools
82 for personalizing treatment for individuals with MDD, but were used to decipher potential reasons about non-response to antidepressant treatment. The present negative findings, taking together with previous positive findings with other phenotypes using the same methodology and bipolar polygenic risk scores, constitute evidence against the hypothesis that latent bipolarity is responsible for substantial amount of treatment resistance among individuals diagnosed with MDD.
CONCLUSIONS Differentiating between bipolar disorder and major depressive disorder remains an important element of clinical practice. However, we found no evidence that testing for latent genetic disposition to bipolar disorder could contribute to response to antidepressant treatment among individuals with apparent MDD. It may be time to rethink the hypothesis about the causes of treatment resistance in MDD, and open new investigations into the reasons for treatment failure at both the clinical and biological level.
ACKNOWLEDGEMENTS The research leading to these results has received support from the Innovative Medicine Initiative Joint Undertaking (IMI-JU) under grant agreement no. 115008 of which resources are composed of European Union and the European Federation of Pharmaceutical Industries and Associations (EFPIA) in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013). EFPIA members Pfizer, Glaxo Smith Kline, and F. Hoffmann La-Roche have contributed work and samples to the project presented here. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. GENDEP was funded by the European Commission Framework 6 grant, EC Contract Ref.: LSHB-CT-2003-503428. Lundbeck provided nortriptyline and escitalopram for the GENDEP study. GlaxoSmithKline and the UK National Institute for Health Research of the Department of Health contributed to the funding of the sample collection at the Institute of Psychiatry, London. GENDEP genotyping was funded by a joint grant from the U.K. Medical Research Council (MRC, UK) and GlaxoSmithKline (G0701420). GenPod was funded by the Medical Research Council (MRC, UK) and supported by the Mental Health Research Network. GODS study was partly supported by external funding provided by the Swiss branches of the following pharmaceutical companies: GlaxoSmithKline, Wyeth-Lederle, Bristol-MyersSquibb, and Sanofi Aventis. R.U. is supported by the Canada Research Chairs program (http://www.chairs-chaires.gc.ca/). K.E. T. and R.U. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The authors thank the National Institute of Mental Health (NIMH) for providing access to the STAR D genetic dataset. STAR D was funded by NIMH via contract (N01MH90003) to the University of Texas Southwestern Medical Center at Dallas (A. John Rush, principal investigator). STAR D genotyping was supported by the National Institute of Mental Health (NIMH) grant to SPH (Grant No. MH072802).
AMERICAN JOURNAL OF MEDICAL GENETICS PART B
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