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Featured researches published by Phil H. Lee.


The Lancet | 2013

Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis

Jordan W. Smoller; Kenneth S. Kendler; Nicholas John Craddock; Phil H. Lee; Benjamin M. Neale; John I. Nurnberger; Stephan Ripke; Susan L. Santangelo; Patrick F. Sullivan; Shaun Purcell; Richard Anney; Jan K. Buitelaar; Ayman H. Fanous; Stephen V. Faraone; Witte J. G. Hoogendijk; Klaus-Peter Lesch; Douglas F. Levinson; Roy H. Perlis; Marcella Rietschel; Brien P. Riley; Edmund Sonuga-Barke; Russell Schachar; Thomas G. Schulze; Anita Thapar; Michael C. Neale; Patrick Bender; Sven Cichon; Mark J. Daly; John R. Kelsoe; Thomas Lehner

BACKGROUND: Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia. METHODS: We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples. FINDINGS: SNPs at four loci surpassed the cutoff for genome-wide significance (p<5x10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers. INTERPRETATION: Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause. FUNDING: National Institute of Mental Health.BACKGROUND Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia. METHODS We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples. FINDINGS SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers. INTERPRETATION Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause. FUNDING National Institute of Mental Health.


Nature Genetics | 2012

Identification of common variants associated with human hippocampal and intracranial volumes

Jason L. Stein; Sarah E. Medland; A A Vasquez; Derrek P. Hibar; R. E. Senstad; Anderson M. Winkler; Roberto Toro; K Appel; R. Bartecek; Ørjan Bergmann; Manon Bernard; Andrew Anand Brown; Dara M. Cannon; M. Mallar Chakravarty; Andrea Christoforou; M. Domin; Oliver Grimm; Marisa Hollinshead; Avram J. Holmes; Georg Homuth; J.J. Hottenga; Camilla Langan; Lorna M. Lopez; Narelle K. Hansell; Kristy Hwang; Sungeun Kim; Gonzalo Laje; Phil H. Lee; Xinmin Liu; Eva Loth

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimers disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10−16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10−12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10−7).


Nature Reviews Genetics | 2013

Pleiotropy in complex traits: challenges and strategies

Nadia Solovieff; Chris Cotsapas; Phil H. Lee; Shaun Purcell; Jordan W. Smoller

Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.


Human Molecular Genetics | 2011

Common Variants near FRK/COL10A1 and VEGFA are Associated with Advanced Age-related Macular Degeneration

Yi Yu; Tushar Bhangale; Jesen Fagerness; Stephan Ripke; Gudmar Thorleifsson; Perciliz L. Tan; E. Souied; Andrea J. Richardson; Joanna E. Merriam; Gabriëlle H.S. Buitendijk; Robyn Reynolds; Soumya Raychaudhuri; Kimberly A. Chin; Lucia Sobrin; Evangelos Evangelou; Phil H. Lee; Aaron Y. Lee; Nicolas Leveziel; Donald J. Zack; Betsy Campochiaro; Peter A. Campochiaro; R. Theodore Smith; Gaetano R. Barile; Robyn H. Guymer; Ruth E. Hogg; Usha Chakravarthy; Luba Robman; Omar Gustafsson; Haraldur Sigurdsson; Ward Ortmann

Despite significant progress in the identification of genetic loci for age-related macular degeneration (AMD), not all of the heritability has been explained. To identify variants which contribute to the remaining genetic susceptibility, we performed the largest meta-analysis of genome-wide association studies to date for advanced AMD. We imputed 6 036 699 single-nucleotide polymorphisms with the 1000 Genomes Project reference genotypes on 2594 cases and 4134 controls with follow-up replication of top signals in 5640 cases and 52 174 controls. We identified two new common susceptibility alleles, rs1999930 on 6q21-q22.3 near FRK/COL10A1 [odds ratio (OR) 0.87; P = 1.1 × 10−8] and rs4711751 on 6p12 near VEGFA (OR 1.15; P = 8.7 × 10−9). In addition to the two novel loci, 10 previously reported loci in ARMS2/HTRA1 (rs10490924), CFH (rs1061170, and rs1410996), CFB (rs641153), C3 (rs2230199), C2 (rs9332739), CFI (rs10033900), LIPC (rs10468017), TIMP3 (rs9621532) and CETP (rs3764261) were confirmed with genome-wide significant signals in this large study. Loci in the recently reported genes ABCA1 and COL8A1 were also detected with suggestive evidence of association with advanced AMD. The novel variants identified in this study suggest that angiogenesis (VEGFA) and extracellular collagen matrix (FRK/COL10A1) pathways contribute to the development of advanced AMD.


American Journal of Psychiatry | 2010

Cross-Disorder Genomewide Analysis of Schizophrenia, Bipolar Disorder, and Depression

Jie Huang; Roy H. Perlis; Phil H. Lee; A. John Rush; Maurizio Fava; Gary S. Sachs; Jeffrey A. Lieberman; Steven P. Hamilton; Patrick F. Sullivan; Pamela Sklar; Shaun Purcell; Jordan W. Smoller

OBJECTIVE Family and twin studies indicate substantial overlap of genetic influences on psychotic and mood disorders. Linkage and candidate gene studies have also suggested overlap across schizophrenia, bipolar disorder, and major depressive disorder. The purpose of this study was to apply genomewide association study (GWAS) analysis to address the specificity of genetic effects on these disorders. METHOD The authors combined GWAS data from three large effectiveness studies of schizophrenia (CATIE, genotyped: N=741), bipolar disorder (STEP-BD, geno-typed: N=1,575), and major depressive disorder (STAR*D, genotyped: N=1,938) as well as from psychiatrically screened control subjects (NIMH-Genetics Repository: N=1,204). A two-stage analytic procedure involving an omnibus test of allele frequency differences among case and control groups was applied, followed by a model selection step to identify the best-fitting model of allelic effects across disorders. RESULTS The strongest result was seen for a single nucleotide polymorphism near the adrenomedullin (ADM) gene (rs6484218), with the best-fitting model indicating that the effect was specific to bipolar II disorder. Findings also revealed evidence suggesting that several genes may have effects that transcend clinical diagnostic boundaries, including variants in NPAS3 that showed pleiotropic effects across schizophrenia, bipolar disorder, and major depressive disorder. CONCLUSIONS This study provides the first genomewide significant evidence implicating variants near the ADM gene on chromosome 11p15 in psychopathology, with effects that appear to be specific to bipolar II disorder. Although genomewide significant evidence of cross-disorder effects was not detected, the results provide evidence that there are both pleiotropic and disorder-specific effects on major mental illness and illustrate an approach to dissecting the genetic basis of mood and psychotic disorders that can inform future large-scale cross-disorder GWAS analyses.


Molecular Psychiatry | 2012

Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder

Sarah E. Bergen; Colm O'Dushlaine; Stephan Ripke; Phil H. Lee; Douglas M. Ruderfer; Susanne Akterin; Jennifer L. Moran; Robert E. Handsaker; Lena Backlund; Urban Ösby; Steven A. McCarroll; Mikael Landén; Edward M. Scolnick; Patrik K. E. Magnusson; Paul Lichtenstein; Christina M. Hultman; Shaun Purcell; Pamela Sklar; Patrick F. Sullivan

Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders with overlapping susceptibility loci and symptomatology. We conducted a genome-wide association study (GWAS) of these disorders in a large Swedish sample. We report a new and independent case–control analysis of 1507 SCZ cases, 836 BD cases and 2093 controls. No single-nucleotide polymorphisms (SNPs) achieved significance in these new samples; however, combining new and previously reported SCZ samples (2111 SCZ and 2535 controls) revealed a genome-wide significant association in the major histocompatibility complex (MHC) region (rs886424, P=4.54 × 10−8). Imputation using multiple reference panels and meta-analysis with the Psychiatric Genomics Consortium SCZ results underscored the broad, significant association in the MHC region in the full SCZ sample. We evaluated the role of copy number variants (CNVs) in these subjects. As in prior reports, deletions were enriched in SCZ, but not BD cases compared with controls. Singleton deletions were more frequent in both case groups compared with controls (SCZ: P=0.003, BD: P=0.013), whereas the largest CNVs (>500 kb) were significantly enriched only in SCZ cases (P=0.0035). Two CNVs with previously reported SCZ associations were also overrepresented in this SCZ sample: 16p11.2 duplications (P=0.0035) and 22q11 deletions (P=0.03). These results reinforce prior reports of significant MHC and CNV associations in SCZ, but not BD.


The Journal of Neuroscience | 2012

Individual Differences in Amygdala-Medial Prefrontal Anatomy Link Negative Affect, Impaired Social Functioning, and Polygenic Depression Risk

Avram J. Holmes; Phil H. Lee; Marisa Hollinshead; Leah Bakst; Joshua L. Roffman; Jordan W. Smoller; Randy L. Buckner

Individual differences in affective and social processes may arise from variability in amygdala-medial prefrontal (mPFC) circuitry and related genetic heterogeneity. To explore this possibility in humans, we examined the structural correlates of trait negative affect in a sample of 1050 healthy young adults with no history of psychiatric illness. Analyses revealed that heightened negative affect was associated with increased amygdala volume and reduced thickness in a left mPFC region encompassing the subgenual and rostral anterior cingulate cortex. The most extreme individuals displayed an inverse correlation between amygdala volume and mPFC thickness, suggesting that imbalance between these structures is linked to negative affect in the general population. Subgroups of participants were further evaluated on social (n = 206) and emotional (n = 533) functions. Individuals with decreased mPFC thickness exhibited the poorest social cognition and were least able to correctly identify facial emotion. Given prior links between disrupted amygdala–mPFC circuitry and the presence of major depressive disorder (MDD), we explored whether the individual differences in anatomy observed here in healthy young adults were associated with polygenic risk for MDD (n = 438) using risk scores derived from a large genome-wide association analysis (n = 18,759). Analyses revealed associations between increasing polygenic burden for MDD and reduced cortical thickness in the left mPFC. These collective findings suggest that, within the healthy population, there is significant variability in amygdala–mPFC circuitry that is associated with poor functioning across affective and social domains. Individual differences in this circuitry may arise, in part, from common genetic variability that contributes to risk for MDD.


Molecular Psychiatry | 2012

A genome-wide association study of attempted suicide

Virginia L. Willour; Fayaz Seifuddin; Pamela B. Mahon; Dubravka Jancic; Mehdi Pirooznia; Jo Steele; Barbara Schweizer; Fernando S. Goes; Francis M. Mondimore; Dean F. MacKinnon; Roy H. Perlis; Phil H. Lee; Jinyan Huang; John R. Kelsoe; Paul D. Shilling; Marcella Rietschel; Markus M. Nöthen; Sven Cichon; H M D Gurling; Shaun Purcell; Jordan W. Smoller; Nicholas John Craddock; J. R. DePaulo; Thomas G. Schulze; Francis J. McMahon; Peter P. Zandi; James B. Potash

The heritable component to attempted and completed suicide is partly related to psychiatric disorders and also partly independent of them. Although attempted suicide linkage regions have been identified on 2p11-12 and 6q25-26, there are likely many more such loci, the discovery of which will require a much higher resolution approach, such as the genome-wide association study (GWAS). With this in mind, we conducted an attempted suicide GWAS that compared the single-nucleotide polymorphism (SNP) genotypes of 1201 bipolar (BP) subjects with a history of suicide attempts to the genotypes of 1497 BP subjects without a history of suicide attempts. In all, 2507 SNPs with evidence for association at P<0.001 were identified. These associated SNPs were subsequently tested for association in a large and independent BP sample set. None of these SNPs were significantly associated in the replication sample after correcting for multiple testing, but the combined analysis of the two sample sets produced an association signal on 2p25 (rs300774) at the threshold of genome-wide significance (P=5.07 × 10−8). The associated SNPs on 2p25 fall in a large linkage disequilibrium block containing the ACP1 (acid phosphatase 1) gene, a gene whose expression is significantly elevated in BP subjects who have completed suicide. Furthermore, the ACP1 protein is a tyrosine phosphatase that influences Wnt signaling, a pathway regulated by lithium, making ACP1 a functional candidate for involvement in the phenotype. Larger GWAS sample sets will be required to confirm the signal on 2p25 and to identify additional genetic risk factors increasing susceptibility for attempted suicide.


Nature Neuroscience | 2016

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept.

Barbara Franke; Jason L. Stein; Stephan Ripke; Verneri Anttila; Derrek P. Hibar; van Hulzen Kje.; Alejandro Arias-Vasquez; Jordan W. Smoller; Thomas E. Nichols; Michael C. Neale; Andrew M. McIntosh; Phil H. Lee; Francis J. McMahon; Andreas Meyer-Lindenberg; Manuel Mattheisen; Ole A. Andreassen; Oliver Gruber; Perminder S. Sachdev; Roberto Roiz-Santiañez; Andrew J. Saykin; Stefan Ehrlich; Karen A. Mather; Jessica A. Turner; Emanuel Schwarz; Anbupalam Thalamuthu; Yin Yao Shugart; Yvonne Y.W. Ho; Nicholas G. Martin; Margaret J. Wright; Michael Conlon O'Donovan

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.


Cerebral Cortex | 2012

The Association between a Polygenic Alzheimer Score and Cortical Thickness in Clinically Normal Subjects

Mert R. Sabuncu; Randy L. Buckner; Jordan W. Smoller; Phil H. Lee; Bruce Fischl; Reisa A. Sperling

Late-onset Alzheimers disease (AD) is 50-70% heritable with complex genetic underpinnings. In addition to Apoliprotein E (APOE) ε4, the major genetic risk factor, recent genome-wide association studies (GWAS) have identified a growing list of sequence variations associated with the disease. Building on a prior large-scale AD GWAS, we used a recently developed analytic method to compute a polygenic score that involves up to 26 independent common sequence variants and is associated with AD dementia, above and beyond APOE. We then examined the associations between the polygenic score and the magnetic resonance imaging-derived thickness measurements across AD-vulnerable cortex in clinically normal (CN) human subjects (N = 104). AD-specific cortical thickness was correlated with the polygenic risk score, even after controlling for APOE genotype and cerebrospinal fluid (CSF) levels of β-amyloid (Aβ(1-42)). Furthermore, the association remained significant in CN subjects with levels of CSF Aβ(1-)(42) in the normal range and in APOE ε3 homozygotes. The observation that genetic risk variants are associated with thickness across AD-vulnerable regions of interest in CN older individuals, suggests that the combination of polygenic risk profile, neuroimaging, and CSF biomarkers may hold synergistic potential to aid in the prediction of future cognitive decline.

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Shaun Purcell

Icahn School of Medicine at Mount Sinai

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Patrick F. Sullivan

University of North Carolina at Chapel Hill

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Francis J. McMahon

National Institutes of Health

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