Publications by authors named "Peter McGuffin"

245 Publications

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 Jun 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 Jun 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder.

Mol Psychiatry 2021 Jan 22. Epub 2021 Jan 22.

HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA.

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3-2.8, one-sided p = 6.0 × 10), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ.
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http://dx.doi.org/10.1038/s41380-020-01006-9DOI Listing
January 2021

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Addict Biol 2021 01 16;26(1):e12880. Epub 2020 Feb 16.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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http://dx.doi.org/10.1111/adb.12880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429266PMC
January 2021

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression.

Biol Psychiatry 2020 03 5;87(5):419-430. Epub 2019 Aug 5.

Max Planck Institute of Psychiatry, Munich, Germany.

Background: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression.

Methods: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10) and a candidate threshold (1.6 × 10).

Results: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99).

Conclusions: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
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http://dx.doi.org/10.1016/j.biopsych.2019.06.031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7001040PMC
March 2020

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression.

Biol Psychiatry 2020 03 5;87(5):419-430. Epub 2019 Aug 5.

Max Planck Institute of Psychiatry, Munich, Germany.

Background: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression.

Methods: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10) and a candidate threshold (1.6 × 10).

Results: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99).

Conclusions: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.
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http://dx.doi.org/10.1016/j.biopsych.2019.06.031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7001040PMC
March 2020

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Nat Genet 2019 08 15;51(8):1207-1214. Epub 2019 Jul 15.

Clinical Genetics Unit, Department of Woman and Child Health, University of Padova, Padova, Italy.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness, affecting 0.9-4% of women and 0.3% of men, with twin-based heritability estimates of 50-60%. Mortality rates are higher than those in other psychiatric disorders, and outcomes are unacceptably poor. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
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http://dx.doi.org/10.1038/s41588-019-0439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779477PMC
August 2019

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Nat Genet 2019 08 15;51(8):1207-1214. Epub 2019 Jul 15.

Clinical Genetics Unit, Department of Woman and Child Health, University of Padova, Padova, Italy.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness, affecting 0.9-4% of women and 0.3% of men, with twin-based heritability estimates of 50-60%. Mortality rates are higher than those in other psychiatric disorders, and outcomes are unacceptably poor. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
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http://dx.doi.org/10.1038/s41588-019-0439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779477PMC
August 2019

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Nat Genet 2019 05 1;51(5):793-803. Epub 2019 May 1.

Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
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http://dx.doi.org/10.1038/s41588-019-0397-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956732PMC
May 2019

Genome-wide Burden of Rare Short Deletions Is Enriched in Major Depressive Disorder in Four Cohorts.

Biol Psychiatry 2019 06 13;85(12):1065-1073. Epub 2019 Mar 13.

Department of Biological Psychology, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.

Background: Major depressive disorder (MDD) is moderately heritable, with a high prevalence and a presumed high heterogeneity. Copy number variants (CNVs) could contribute to the heritable component of risk, but the two previous genome-wide association studies of rare CNVs did not report significant findings.

Methods: In this meta-analysis of four cohorts (5780 patients and 6626 control subjects), we analyzed the association of MDD to 1) genome-wide burden of rare deletions and duplications, partitioned by length (<100 kb or >100 kb) and other characteristics, and 2) individual rare exonic CNVs and CNV regions.

Results: Patients with MDD carried significantly more short deletions than control subjects (p = .0059) but not long deletions or short or long duplications. The confidence interval for long deletions overlapped with that for short deletions, but long deletions were 70% less frequent genome-wide, reducing the power to detect increased burden. The increased burden of short deletions was primarily in intergenic regions. Short deletions in cases were also modestly enriched for high-confidence enhancer regions. No individual CNV achieved thresholds for suggestive or significant association after genome-wide correction. p values < .01 were observed for 15q11.2 duplications (TUBGCP5, CYFIP1, NIPA1, and NIPA2), deletions in or near PRKN or MSR1, and exonic duplications of ATG5.

Conclusions: The increased burden of short deletions in patients with MDD suggests that rare CNVs increase the risk of MDD by disrupting regulatory regions. Results for longer deletions were less clear, but no large effects were observed for long multigenic CNVs (as seen in schizophrenia and autism). Further studies with larger sample sizes are warranted.
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http://dx.doi.org/10.1016/j.biopsych.2019.02.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6750266PMC
June 2019

Effect of antidepressant switching between nortriptyline and escitalopram after a failed first antidepressant treatment among patients with major depressive disorder.

Br J Psychiatry 2019 08 30;215(2):494-501. Epub 2019 Jan 30.

Professor,Psychosis Research Unit,Aarhus University Hospital - Psychiatry;Department of Clinical Medicine,Aarhus University;and iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research,Denmark.

Background: For patients with major depressive disorder (MDD) experiencing side-effects or non-response to their first antidepressant, little is known regarding the effect of switching between a tricyclic antidepressant (TCA) and a selective serotonin reuptake inhibitor (SSRI).AimsTo compare the switch between the TCA nortriptyline and the SSRI escitalopram.

Method: Among 811 adults with MDD treated with nortriptyline or escitalopram for up to 12 weeks, 108 individuals switched from nortriptyline to escitalopram or vice versa because of side-effects or non-response (trial registration: EudraCT No.2004-001723-38 (https://eudract.ema.europa.eu/) and ISRCTN No.03693000 (http://www.controlled-trials.com)). Patients were followed for up to 26 weeks after switching and response was measured with the Montgomery-Åsberg Depression Rating scale (MADRS). We performed adjusted mixed-effects linear regression models with full information maximum likelihood estimation reporting β-coefficients with 95% CIs.

Results: Switching antidepressants resulted in a significant decrease in MADRS scores. This was present for switchers from escitalopram to nortriptyline (n = 36, β = -0.38, 95% CI -0.51 to -0.25, P<0.001) and from nortriptyline to escitalopram (n = 72, β = -0.34, 95% CI -0.41 to -0.26, P<0.001). Both switching options resulted in significant improvement among individuals who switched because of non-response or side-effects. The results were supported by analyses on other rating scales and symptom dimensions.

Conclusions: These results suggest that switching from a TCA to an SSRI or vice versa after non-response or side-effects to the first antidepressant may be a viable approach to achieve response among patients with MDD.Declarations of interestK.J.A. holds an Alberta Centennial Addiction and Mental Health Research Chair, funded by the Government of Alberta. K.J.A. has been a member of various advisory boards, received consultancy fees and honoraria, and has received research grants from various companies including Johnson and Johnson Pharmaceuticals Research and Development and Bristol-Myers Squibb Pharmaceuticals Limited. D.S. has served on advisory boards for, and received unrestricted grants from, Lundbeck and AstraZeneca. A.F. and P.M. have received honoraria for participating in expert panels for Lundbeck and GlaxoSmithKline.
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http://dx.doi.org/10.1192/bjp.2018.302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624130PMC
August 2019

Family functioning, trauma exposure and PTSD: A cross sectional study.

J Affect Disord 2019 02 5;245:645-652. Epub 2018 Nov 5.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, UK. Electronic address:

Objective: Only a minority of trauma-exposed individuals go on to develop post traumatic stress disorder (PTSD). Previous studies in high income countries suggest that maladaptive family functioning adversities (MFFA) in childhood may partially explain individual variation in vulnerability to PTSD following trauma. We test in a lower middle-income setting (Sri Lanka) whether: (1) MFFA is associated with trauma exposure; (2) MFFA moderates the association between exposure to trauma and later (a) PTSD (b) other psychiatric diagnoses; and (3) any association between MFFA and PTSD is explained by experiences of interpersonal violence, cumulative trauma exposure or comorbid psychopathology.

Methods: We conducted a population study of 3995 twins and 2019 singletons residing in Colombo, Sri Lanka. Participants completed the Composite International Diagnostic Interview, including nine traumatic exposures and a questionnaire on MFFA.

Results: 23.4% of participants reported exposure to MFFA. We found that (1) MFFA was strongly associated with trauma exposure (2) MFFA moderates the association between trauma exposure and both (a) PTSD and (b) other DSM psychiatric diagnosis. (3) This was not explained by interpersonal violence, cumulative trauma exposure or other psychopathology.

Conclusions: MFFA moderates the association between trauma and PTSD, and the association between trauma and non-PTSD psychopathology.
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http://dx.doi.org/10.1016/j.jad.2018.11.056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362264PMC
February 2019

Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies.

Eur Neuropsychopharmacol 2018 08 28;28(8):945-954. Epub 2018 Jun 28.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO80, De De Crespigny Park, Denmark Hill United Kingdom. Electronic address:

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 metabolic phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was assessed by standardized percentage symptom improvement and by remission. Side effect data were available at weeks 2-4, 6 and 9 in three samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD = 0.43, CI = 0.19-0.66) and higher remission rates (OR = 1.55, CI = 1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR = 1.26, CI = 1.08-1.47), neurological (OR = 1.28, CI = 1.07-1.53) and sexual side effects (OR = 1.52, CI = 1.23-1.87; week 6 values were similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs being relatively rare among Caucasians (∼2%).
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http://dx.doi.org/10.1016/j.euroneuro.2018.05.009DOI Listing
August 2018

Genetic disposition to inflammation and response to antidepressants in major depressive disorder.

J Psychiatr Res 2018 10 7;105:17-22. Epub 2018 Aug 7.

Department of Pathology, Dalhousie University, Halifax, NS, Canada; Department of Psychiatry, Dalhousie University, Halifax, NS, Canada; Nova Scotia Health Authority, Halifax, NS, Canada; King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, UK. Electronic address:

Background: Inflammation may play an important role in depression and its treatment. A previous study found that increased C-reactive protein (CRP), a marker of systemic inflammation, is associated with worse response to the serotonergic antidepressant escitalopram and better response to the noradrenergic antidepressant nortriptyline. It is unclear whether this reflects genetic disposition to inflammation.

Methods: We analyzed genotype data and weekly Montgomery-Åsberg Depression Rating Scale scores (MADRS) from 755 unrelated individuals obtained over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study. We calculated a polygenic risk score for CRP level based on genome-wide meta-analysis results from the CHARGE Consortium.

Results: A higher polygenic risk score for CRP was associated with slightly better response to escitalopram and slightly worse response to nortriptyline, reflected in a statistically significant interaction between polygenic risk score and drug (beta = 1.07, 95% CI = 0.26-1.87, p = 0.0093).

Discussion: A differential association between CRP-PRS and antidepressant drug that is in a direction opposite to that found with serum CRP measurement suggests that previously observed effect of inflammation on antidepressant efficacy may be driven by state factors distinct from genetic influences on systemic inflammation.
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http://dx.doi.org/10.1016/j.jpsychires.2018.08.011DOI Listing
October 2018

Genes associated with anhedonia: a new analysis in a large clinical trial (GENDEP).

Transl Psychiatry 2018 08 13;8(1):150. Epub 2018 Aug 13.

Psychiatry and Medical Genetics, University of Alberta, Edmonton, AB, Canada.

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson's Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies.
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http://dx.doi.org/10.1038/s41398-018-0198-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6089928PMC
August 2018

Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

Psychiatr Genet 2018 10;28(5):77-84

Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine.

Objective: Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD.

Participants And Methods: We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models.

Results: The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer's combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications.

Conclusion: Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression.
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http://dx.doi.org/10.1097/YPG.0000000000000203DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6531290PMC
October 2018

Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder.

Psychiatr Genet 2018 10;28(5):77-84

Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine.

Objective: Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD.

Participants And Methods: We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models.

Results: The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer's combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications.

Conclusion: Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression.
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http://dx.doi.org/10.1097/YPG.0000000000000203DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6531290PMC
October 2018

Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables.

Sci Rep 2018 04 3;8(1):5530. Epub 2018 Apr 3.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.

Individuals with depression differ substantially in their response to treatment with antidepressants. Specific predictors explain only a small proportion of these differences. To meaningfully predict who will respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. Using statistical learning on common genetic variants and clinical information in a training sample of 280 individuals randomly allocated to 12-week treatment with antidepressants escitalopram or nortriptyline, we derived models to predict remission with each antidepressant drug. We tested the reproducibility of each prediction in a validation set of 150 participants not used in model derivation. An elastic net logistic model based on eleven genetic and six clinical variables predicted remission with escitalopram in the validation dataset with area under the curve 0.77 (95%CI; 0.66-0.88; p = 0.004), explaining approximately 30% of variance in who achieves remission. A model derived from 20 genetic variables predicted remission with nortriptyline in the validation dataset with an area under the curve 0.77 (95%CI; 0.65-0.90; p < 0.001), explaining approximately 36% of variance in who achieves remission. The predictive models were antidepressant drug-specific. Validated drug-specific predictions suggest that a relatively small number of genetic and clinical variables can help select treatment between escitalopram and nortriptyline.
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http://dx.doi.org/10.1038/s41598-018-23584-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882876PMC
April 2018

One year double blind study of high vs low frequency subcallosal cingulate stimulation for depression.

J Psychiatr Res 2018 01 3;96:124-134. Epub 2017 Oct 3.

The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel; Biological Psychiatry Laboratory, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.

Subcallosal Brodmann's Area 25 (Cg25) Deep Brain Stimulation (DBS) is a new promising therapy for treatment resistant major depressive disorder (TR-MDD). While different DBS stimulating parameters may have an impact on the efficacy and safety of the therapy, there is no data to support a protocol for optimal stimulation parameters for depression. Here we present a prospective multi-center double-blind randomized crossed-over 13-month study that evaluated the effects of High (130 Hz) vs Low (20 Hz) frequency Cg25 stimulation for nine patients with TR-MDD. Four out of nine patients achieved response criteria (≥40% reduction of symptom score) compared to mean baseline values at the end of the study. The mean percent change of MADRS score showed a similar improvement in the high and low frequency stimulation groups after 6 months of stimulation (-15.4 ± 21.1 and -14.7 ± 21.1 respectively). The mean effect at the end of the second period (6 months after cross-over) was higher than the first period (first 6 months of stimulation) in all patients (-23.4 ± 19.9 (n = 6 periods) and -13.0 ± 22 (n = 9 periods) respectively). At the end of the second period, the mean percent change of the MADRS scores improved more in the high than low frequency groups (-31.3 ± 19.3 (n = 4 patients) and -7.7 ± 10.9 (n = 2 patients) respectively). Given the small numbers, detailed statistical analysis is challenging. Nonetheless the results of this study suggest that long term high frequency stimulation might confer the best results. Larger scale, randomized double blind trials are needed in order to evaluate the most effective stimulation parameters.
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http://dx.doi.org/10.1016/j.jpsychires.2017.09.026DOI Listing
January 2018

Advancing psychiatric genetics through dissecting heterogeneity.

Hum Mol Genet 2017 10;26(R2):R160-R165

MRC Centre for Social, Genetic and Developmental Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.

There has been substantial progress in psychiatric genetics in recent years, through collaborative efforts to build large samples sizes for case/control analyses for a number of psychiatric disorders. The identification of replicated trait-associated genomic loci represents a large stride forward in a field where little is known about the biological processes involved in disorder. As researchers build on this early foundation, they are beginning to advance the field towards more fine-grained approaches that interrogate the many sources of heterogeneity within psychiatric genetics that can obscure the identification of genotypic influences on disorder. In this review, we provide a brief overview, across a range of psychiatric diagnoses, of recent approaches that have been employed to dissect heterogeneity to give a flavour of the current direction of the field. We group these into three main categories; tackling the heterogeneity in phenotype that is found within the diagnostic categories used within psychiatry, the many different forms of genetic variation that might influence psychiatric traits and then finally, the heterogeneity that is seen across individuals of different ancestries.
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http://dx.doi.org/10.1093/hmg/ddx241DOI Listing
October 2017

Childhood maltreatment and the medical morbidity in bipolar disorder: a case-control study.

Int J Bipolar Disord 2017 Sep 7;5(1):30. Epub 2017 Sep 7.

MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK.

Background: Childhood maltreatment (abuse and neglect) can have long-term deleterious consequences, including increased risk for medical and psychiatric illnesses, such as bipolar disorder in adulthood. Emerging evidence suggests that a history of childhood maltreatment is linked to the comorbidity between medical illnesses and mood disorders. However, existing studies on bipolar disorder have not yet explored the specific influence of child neglect and have not included comparisons with individuals without mood disorders (controls). This study aimed to extend the existing literature by examining the differential influence of child abuse and child neglect on medical morbidity in a sample of bipolar cases and controls.

Methods: The study included 72 participants with bipolar disorder and 354 psychiatrically healthy controls (average age of both groups was 48 years), who completed the Childhood Trauma Questionnaire, and were interviewed regarding various medical disorders.

Results: A history of any type of childhood maltreatment was significantly associated with a diagnosis of any medical illness (adjusted OR = 6.28, 95% confidence intervals 1.70-23.12, p = 0.006) and an increased number of medical illnesses (adjusted OR = 3.77, 95% confidence intervals 1.34-10.57, p = 0.012) among adults with bipolar disorder. Exposure to child abuse was more strongly associated with medical disorders than child neglect. No association between childhood maltreatment and medical morbidity was detected among controls.

Conclusions: To summarise, individuals with bipolar disorder who reported experiencing maltreatment during childhood, especially abuse, were at increased risk of suffering from medical illnesses and warrant greater clinical attention.
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http://dx.doi.org/10.1186/s40345-017-0099-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5587525PMC
September 2017

Interaction between the gene, body mass index and depression: meta-analysis of 13701 individuals.

Br J Psychiatry 2017 08 22;211(2):70-76. Epub 2017 Jun 22.

Margarita Rivera, PhD, Department of Biochemistry and Molecular Biology II and Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, Spain, and MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kinǵs College London, UK; Adam E. Locke, PhD, Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Tanguy Corre, PhD, Department of Medical Genetics, University of Lausanne, Lausanne, and Swiss Institute of Bioinformatics, Lausanne, Switzerland; Darina Czamara, PhD, Christiane Wolf, PhD, Max Planck Institute of Psychiatry, Munich, Germany; Ana Ching-Lopez, Department of Psychiatry, School of Medicine, University of Granada, and Institute of Neurosciences Federico Olóriz, Centra de Investigación Biomédica, University of Granada, Spain; Yuri Milaneschi, PhD, Department of Psychiatry and EMGO Institute for Health and Care Research, VU University Medical Center/GGZ in Geest, Amsterdam, The Netherlands; Stefan Kloiber, MD, Max Planck Institute of Psychiatry, Munich, Germany; Sara Cohen-Woods, PhD, School of Psychology, Flinders University, Adelaide, South Australia, Australia; James Rucker, MD, PhD, MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Katherine J. Aitchison, MD, PhD, Department of Psychiatry, University of Alberta, Alberta, Canada; Sven Bergmann, PhD, Department of Medical Genetics, University of Lausanne, Lausanne, and Swiss Institute of Bioinformatics, Lausanne, Switzerland; Dorret I. Boomsma, PhD, Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands; Nick Craddock, MB, PhD, FMedSci, Department of Psychological Medicine and Neurology, Cardiff University School of Medicine, Henry Wellcome Building, Cardiff, UK; Michael Gill, MD, Department of Psychiatry, Trinity Centre for Health Sciences, Dublin 8, Ireland; Florian Holsboer, MD, PhD, Max Planck Institute of Psychiatry, Munich, Germany; Jouke-Jan Hottenga, PhD, Department of Psychiatry, University of Alberta, Alberta, Canada; Ania Korszun, PhD, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; Zoltan Kutalik, PhD, Department of Medical Genetics, University of Lausanne, Lausanne, and Swiss Institute of Bioinformatics, Lausanne, Switzerland; Susanne Lucae, MD, PhD, Max Planck Institute of Psychiatry, Munich, Germany; Wolfgang Maier, MD, Department of Psychiatry, University of Bonn, Bonn, Germany; Ole Mors, MD, PhD, Research Department P, Aarhus University Hospital, Risskov, Denmark; Bertram Müller-Myhsok MD, Max Planck Institute of Psychiatry, Munich, Germany; Michael J. Owen, MB, PhD, FMedSci, MRC Centre for Neuropsychiatry Genetics and Genomics, Department of Psychological Medicine and Neurology, School of Medicine, Cardiff University, Cardiff, UK; Brenda W. J. H. Penninx, PhD, Department of Psychiatry and EMGO Institute for Health and Care Research, VU University Medical Center/GGZ in Geest, Amsterdam, The Netherlands; Martin Preisig, MD, Department of Psychiatry, Lausanne University Hospital, 1008 Prilly-Lausanne, Switzerland; John Rice, PhD, Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri, USA; Marcella Rietschel, MD, Central Institute of Mental Health, Mannheim, Germany; Federica Tozzi, MD, Genetics Division, Drug Discovery, GlaxoSmithKline Research and Development, Verona, Italy; Rudolf Uher, MD, PhD, MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK, and Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada; Peter Vollenweider, MD, PhD, Gerard Waeber, MD, PhD, Division of Internal Medicine, CHUV, Lausanne, Switzerland; Gonneke Willemsen, PhD, Department of Psychiatry, University of Alberta, Alberta, Canada; Ian W. Craig, PhD, Anne E. Farmer, MD, MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Cathryn M. Lewis, PhD, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, and Department of Medical and Molecular Genetics, School of Medicine, King's College London, UK; Gerome Breen, PhD, Peter McGuffin, MB, PhD, FMedSci, MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK.

Depression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the gene, suggesting its implication in the association between depression and obesity.To confirm these findings by investigating the polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis.The sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT.In the replication cohorts, we observed a significant interaction between , BMI and depression with fixed effects meta-analysis (β = 0.12, = 2.7 × 10) and with the Han/Eskin random effects method ( = 1.4 × 10) but not with traditional random effects (β = 0.1, = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (β = 0.12, = 0.027) being highly significant based on the Han/Eskin model ( = 6.9 × 10). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of This meta-analysis provides additional support for a significant interaction between , depression and BMI, indicating that depression increases the effect of on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression.
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http://dx.doi.org/10.1192/bjp.bp.116.183475DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537566PMC
August 2017

The DAOA gene is associated with schizophrenia in the Taiwanese population.

Psychiatry Res 2017 06 7;252:201-207. Epub 2017 Mar 7.

MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.

The gene D-amino acid oxidase activator (DAOA), which has a former name of G72, and the D-amino acid oxidase (DAO) gene have been suggested as candidate genes of schizophrenia. However, association studies have so far yielded equivocal results. We analyzed one single nucleotide polymorphism (SNP) for DAO (rs3741775) and seven SNPs for G72 (rs3916956, rs2391191, rs9558562, rs947267, rs778292, rs3918342, and rs1421292) in this study enrolling 248 schizophrenia cases and 267 controls in the Taiwanese samples. In SNP-based single locus association analyses, the rs778292 in the DAOA gene showed significant association with schizophrenia. The rs3741775 in the DAO gene could not withstand statistically significant after multiple corrections. Additionally, a three-SNP haplotype (rs778292-rs3918342-rs1421292) in the DAOA gene were observed to be significantly associated with schizophrenia. Among them, the TCT haplotype presented higher prevalence in controls than in cases whereas the TTT and CTT haplotype were significantly more frequent in cases than in controls. The study also provides significant evidence for epistatic interactions among DAOA and DAO gene in the development of schizophrenia. These results provide additional evidence and indicate that the DAOA gene and DAOA-DAO gene-gene interactions might play a role for schizophrenia in a Taiwanese sample.
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http://dx.doi.org/10.1016/j.psychres.2017.03.013DOI Listing
June 2017

Association between C-reactive protein (CRP) with depression symptom severity and specific depressive symptoms in major depression.

Brain Behav Immun 2017 May 1;62:344-350. Epub 2017 Mar 1.

Aarhus University Hospital, Risskov, Psychosis Research Unit, Aarhus, Denmark; iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.

Introduction: Population-based studies have associated inflammation, particularly higher C-reactive protein (CRP), with depressive severity, but clinical trials in major depressive disorder were rather non-specific without examining the role of gender. We aimed to investigate the association between CRP and overall depression severity including specific depressive symptoms and to examine potential gender differences.

Methods: We included 231 individuals with major depressive disorder from the Genome-Based Therapeutics Drugs for Depression (GENDEP) study. At baseline, we assessed high-sensitivity CRP levels and psychopathology with the Montgomery Aasberg Depression Rating Scale (MADRS). We performed linear regression analyses to investigate the association between baseline CRP levels with overall MADRS severity and specific symptoms at baseline and adjusted for age, gender, anti-inflammatory and psychotropic drug treatment, body mass index, smoking, inflammatory diseases, and recruitment center.

Results: Higher CRP levels were significantly associated with greater overall MADRS symptom severity (p=0.02), which was significant among women (p=0.02) but not among men (p=0.68). Among women, higher CRP was associated with increased severity on observed mood, cognitive symptoms, interest-activity, and suicidality, but we found no significant associations among men. Interaction analyses showed no significant gender differences on the overall MADRS score or specific symptoms.

Discussion: Our results support the sickness syndrome theory suggesting that chronic low-grade inflammation may be associated with a subtype of depression. The potential gender differences in psychopathology may be explained by biological and/or psychosocial factors, e.g. differential modulation of immune responses by sex hormones. Clinical studies should investigate symptom-specific and/or gender-specific treatment guided by peripheral inflammatory markers.
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http://dx.doi.org/10.1016/j.bbi.2017.02.020DOI Listing
May 2017

An Erudite Encounter with: Peter McGuffin CBE.

Authors:
Peter McGuffin

Aust N Z J Psychiatry 2017 Mar;51(3):298

Department of Psychiatry, Royal North Shore Hospital, CADE Clinic, St Leonards, NSW, Australia.

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http://dx.doi.org/10.1177/0004867417692426DOI Listing
March 2017

Pharmacogenetics of antidepressant response: A polygenic approach.

Prog Neuropsychopharmacol Biol Psychiatry 2017 04 31;75:128-134. Epub 2017 Jan 31.

Department of Psychiatry, University of Münster, Münster, Germany.

Background: Major depressive disorder (MDD) has a high personal and socio-economic burden and >60% of patients fail to achieve remission with the first antidepressant. The biological mechanisms behind antidepressant response are only partially known but genetic factors play a relevant role. A combined predictor across genetic variants may be useful to investigate this complex trait.

Methods: Polygenic risk scores (PRS) were used to estimate multi-allelic contribution to: 1) antidepressant efficacy; 2) its overlap with MDD and schizophrenia. We constructed PRS and tested whether these predicted symptom improvement or remission from the GENDEP study (n=736) to the STAR*D study (n=1409) and vice-versa, including the whole sample or only patients treated with escitalopram or citalopram. Using summary statistics from Psychiatric Genomics Consortium for MDD and schizophrenia, we tested whether PRS from these disorders predicted symptom improvement in GENDEP, STAR*D, and five further studies (n=3756).

Results: No significant prediction of antidepressant efficacy was obtained from PRS in GENDEP/STAR*D but this analysis might have been underpowered. There was no evidence of overlap in the genetics of antidepressant response with either MDD or schizophrenia, either in individual studies or a meta-analysis. Stratifying by antidepressant did not alter the results.

Discussion: We identified no significant predictive effect using PRS between pharmacogenetic studies. The genetic liability to MDD or schizophrenia did not predict response to antidepressants, suggesting differences between the genetic component of depression and treatment response. Larger or more homogeneous studies will be necessary to obtain a polygenic predictor of antidepressant response.
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http://dx.doi.org/10.1016/j.pnpbp.2017.01.011DOI Listing
April 2017

Stressful life events and catechol-O-methyl-transferase (COMT) gene in bipolar disorder.

Depress Anxiety 2017 05 19;34(5):419-426. Epub 2017 Jan 19.

MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Background: A small body of research suggests that gene-environment interactions play an important role in the development of bipolar disorder. The aim of the present study is to contribute to this work by exploring the relationship between stressful life events and the catechol-O-methyl-transferase (COMT) Val Met polymorphism in bipolar disorder.

Methods: Four hundred eighty-two bipolar cases and 205 psychiatrically healthy controls completed the List of Threatening Experiences Questionnaire. Bipolar cases reported the events experienced 6 months before their worst depressive and manic episodes; controls reported those events experienced 6 months prior to their interview. The genotypic information for the COMT Val Met variant (rs4680) was extracted from GWAS analysis of the sample.

Results: The impact of stressful life events was moderated by the COMT genotype for the worst depressive episode using a Val dominant model (adjusted risk difference = 0.09, 95% confidence intervals = 0.003-0.18, P = .04). For the worst manic episodes no significant interactions between COMT and stressful life events were detected.

Conclusions: This is the first study to explore the relationship between stressful life events and the COMT Val Met polymorphism focusing solely on bipolar disorder. The results of this study highlight the importance of the interplay between genetic and environmental factors for bipolar depression.
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http://dx.doi.org/10.1002/da.22606DOI Listing
May 2017

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression.

Am J Med Genet B Neuropsychiatr Genet 2017 Apr 1;174(3):235-250. Epub 2016 Oct 1.

Department of Computer Science, UCL, London, United Kingdom.

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/ajmg.b.32494DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5434854PMC
April 2017

Immune signatures and disorder-specific patterns in a cross-disorder gene expression analysis.

Br J Psychiatry 2016 09 5;209(3):202-8. Epub 2016 May 5.

Simone de Jong, PhD, Stephen J. Newhouse, PhD, Hamel Patel, Sanghyuck Lee, David Dempster, Charles Curtis, MSc, Jose Paya-Cano, PhD, MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London and NIHR Biomedical Research Centre for Mental Health, Maudsley Hospital and Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Declan Murphy, MD, The Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; C. Ellie Wilson, PhD, The Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London UK and Individual Differences, Language and Cognition Lab, Department of Developmental and Educational Psychology, University of Seville, Spain; Jamie Horder, PhD, M. Andreina Mendez, PhD, The Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London; Philip Asherson, PhD, MD, MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Margarita Rivera, PhD, MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK and CIBERSAM-University of Granada and Instituto de Investigación Biosanitaria ibs. GRANADA. Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain; Helen Costello, PhD, Wolfson Centre for Age Related Diseases, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Stefanos Maltezos, MSc, MD, Susannah Whitwell, MD, Mark Pitts, Adult ADHD Service, South London and Maudsley NHS Foundation Trust, London, UK; Charlotte T

Background: Recent studies point to overlap between neuropsychiatric disorders in symptomatology and genetic aetiology.

Aims: To systematically investigate genomics overlap between childhood and adult attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and major depressive disorder (MDD).

Method: Analysis of whole-genome blood gene expression and genetic risk scores of 318 individuals. Participants included individuals affected with adult ADHD (n = 93), childhood ADHD (n = 17), MDD (n = 63), ASD (n = 51), childhood dual diagnosis of ADHD-ASD (n = 16) and healthy controls (n = 78).

Results: Weighted gene co-expression analysis results reveal disorder-specific signatures for childhood ADHD and MDD, and also highlight two immune-related gene co-expression modules correlating inversely with MDD and adult ADHD disease status. We find no significant relationship between polygenic risk scores and gene expression signatures.

Conclusions: Our results reveal disorder overlap and specificity at the genetic and gene expression level. They suggest new pathways contributing to distinct pathophysiology in psychiatric disorders and shed light on potential shared genomic risk factors.
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http://dx.doi.org/10.1192/bjp.bp.115.175471DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5007452PMC
September 2016