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Donghong Cui 崔东红 Shanghai Mental Health Center 上海市精神卫生中心 Yale Unversity 耶鲁大学 12-04-2008

low-density gene chip candidate genes association study of primary vs. substance-comobid affective disorders in two distinct American populations. Donghong Cui 崔东红 Shanghai Mental Health Center 上海市精神卫生中心 Yale Unversity 耶鲁大学 12-04-2008. Outline . Background Materials and Methods

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Donghong Cui 崔东红 Shanghai Mental Health Center 上海市精神卫生中心 Yale Unversity 耶鲁大学 12-04-2008

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  1. low-density gene chip candidate genes association study of primary vs. substance-comobid affective disorders in two distinct American populations Donghong Cui 崔东红 Shanghai Mental Health Center 上海市精神卫生中心 Yale Unversity 耶鲁大学 12-04-2008

  2. Outline • Background • Materials and Methods • Design of study • Subjects • Genotype • Quality control • Statistics • Results • Stage one • Stage two • Conclusions

  3. Background Affective disorders (AFDs) are kind of mental disorder characterized by dramatic changes or extremes of mood (including major depression, MDD and bipolar disorder, BPD). Prevalence16-20% Substance use disorders, SUDs include substance abuse and dependence World population age 15-64，4,177 million people (100%*) Problem drug use:age 15-64:25 million people (0.6%*) Annual prevalence of drug use:200 million people (4.8%*)

  4. Background The rate of BPD in SUDs subjects: 2 - 31% (Salloum and Thase, 2000). The rate of SUDs in BPD patients: 14% - 65% (Regier DA, 1990; Brown ES et al. 2001). The prevalence of SUDs in MDD: 8.5%- 21.4%, lifetime prevalence of comorbid SUDs: 27%- 40% (Davis L. et al 2008). The lifetime prevalence of SUDs is higher in bipolar disorder than in any other psychiatric disorders, including MDD (Goldberg JF. 2001). The comorbidity in magnitude is stronger for drug dependence compared with abuse and for BPD compared with MDD (Grant BF et al.2004; Merikangas KR et al. 1998).

  5. Background AFDs with concurrent SUDs was usually characterized with: earlier age of onset greater severity of symptoms poor prognosis less response to treatment greater functional impairment. more hypersomnia, anxious mood and suicidal ideation (Davis L. et al 2008).

  6. Background • Statistical studies have suggested a hereditary predisposition to AFDs. • Bipolar is more genetic than schizophrenia and major depression. Heritability——90% • First-degree relative ---likelihood is10-15% • Second-degree relative--- likelihood is 5-10% • In twin studies, likelihood is 60% The International Society for Affective Disorders (ISAD)

  7. Design of Study Multi-marker Association Stage One Susceptibility Genes Candidate Gene Confirmation Stage Two

  8. Subjects Table 1 Characteristic of samples

  9. Genotype Custom Illumina GoldenGate Assay (Illumina Inc., San Diego, CA, USA) (Hodgkinson et al, 2008). 1350 SNPs in/near 130 candidate genes 186 SNP markers as AIMs 1216 samples totally

  10. Markers were excluded: Hardy-Weinberg disequilibrium (P<0.001) low minor allele frequency (MAF<0.025 ) Call rate<95% in all samples X-chromosomal SNPs 1263 SNPs (including 113 AIMs) Quality Control

  11. Statistics • Single marker association analysis.software JMP Genetics & Helixtree • Haplotype association analysis. LD values between SNP pairs were determined separately by population (EAs and AAs) using LD statistics (D’) with the Haploview version 4.0. • Diplotype association analysis. • Multiple tests.1,000,000 times of permutations for both single-marker and haplotype association For diplotype analysis, we used Bonferroni to correct the multiple testing. • Population structure analysis.Structure 2.2

  12. Stage One ResultsMulti-gene Association

  13. Positive genes in each group ADRA2A AHI1 CNR1 DBH DDC FOSL1 GABRB3 GRIN2B HTR1B HTR3B NTSR1 OPRD1 PPP1R1B PSMD11 TPLB RAB11FIP2 SLC6A12 TXNRD2 18 ADCY7 AVP CSNK1E TTNBP2 DBI GRIK1 PRKCE SLC18A2 TPH2 9 5 ABCG2 ADH6 ADRA1A CDX1 CHRM3 CHRNB2 CLOCK COMT CRHR1 CRHR2 8 11 32 GRIN2A MGC4171 NTRK2 PELP1 SLC6A3 ADH7 CCKBR CRHBP CYP2E1 DRD2 GLRA1 2 GLRB GRM1

  14. Positive markers in each group 38 3 rs10249419 rs10877970 rs1229967 rs1424386 rs2129575 rs2171363 rs2350780 rs2740210 rs2856813 rs36017 rs3753127 rs4570625 rs4953321 rs6001093 rs6330 23 rs3784079 1 3 rs1402851 rs1869237 rs2880774 67 28

  15. Stage Two ResultsNGFB and affective disorder

  16. Nerve Growth Factor (NGF) • Nerve Growth Factor (NGF) is one of the Neurotrophins • Rita Levi-Montalcini and Stanley Cohen won the 1986 Nobel Prize in Physiology or Medicine for their discovery of NGF and other growth factors • Neurotrophins have five factors • nerve growth factor (NGF) • brain-derived neurotrophic factor (BDNF) • neurotrophin-3 (NT-3) • neurotrophin-4 (NT-4) • novel neurotrophin-1 (NNT1)

  17. NGF, beta polypeptide monomer A monomer B NGF homodimer: monomer A ,orange monomer B, red

  18. Receptor binding mechanism • NGF can bind with two classes of receptors, p75 and the "TrkA “ • p75, a low affinity neurotrophin receptor, can bind with all neurotrophins. • The Trk , a family of Tyrosine kinase receptors, include TrkA, TrkB, and TrkC, and will only bind with specific neurotrophins, but with a much higher affinity. • NGF bind to TrkA, • BDNF and NT-4 bind to TrkB • NT-3 binds to TrkC, TrkA and TrkB 12/5/2008

  19. Model of NGF-receptor interactions Xiao-lin He and K. Christopher Garcia SCIENCE 2004 304 (7 ) :871 The NGFdimer binds to a monomeric form of p75 but to a dimeric form of the TrkA receptor. Heterodimers of p75 and Trk are possible, but the receptors would need to be in opposite orientations to accommodate the NGF dimer. Niccoló Zampieri and Moses V. Chao SCIENC 2004 304 (7):833 Model of NGF-receptor interactions 12/5/2008

  20. NGF/TrkA Signaling Pathway NGF Activation p+ intrinsic TrkA tyrosine residues p+ PLC-g and Shc Activation Activation the PI3K/Akt pathway Ras/raf/ERK pathway development, patterning, and maintenance of the mammalian nervous system 12/5/2008

  21. NGFB Function • NGFB is involved in the neurogenesis, differentiation, growth and maintenance of • Peripheral (sympathetic and sensory) • Central neurons (such as forebrain cholinergic neurons, which are involved in learning and cognitive processes) during development and at adulthood.

  22. Nerve Growth Factor (NGF) Evidence derived from animal models has shown that NGFB plays a role in etiology of AFDs, however, little clinical evidence support these findings, moreover, few studies focused on the differences in genetic background between PAFD and CAFD. The present study was designed to investigate different genetic contributions of NGFB gene to PAFDs and CAFDs by association analysis. 12/5/2008

  23. Marker checking for 15 markers in NGFB gene * MAF < 0.025 12/5/2008

  24. Fig. 1 LD structures of 15 SNPs spanning the NGFB gene in EA and AA sample sets 1A Haplotypes in EAs 1B Haplotypes in AAs

  25. Fig. 2 Single-marker, Haplotye, and Diplotye Association in EAs population 2a. Total AFD: All (N=868), F (N=497), M (N=371) 2A. AFD (N=868), PAFD (N=654), CAFD (N=686)

  26. Fig. 2 Single-marker, Haplotye, and Diplotye Association in EAs population 2B. PAFD: All (N=654), Female (N=384), Male (N=270) 2b. CAFD: All (N=686), Female (N=388), Male (N=304)

  27. Fig. 2 Single-marker, Haplotye, and Diplotye Association in EAs population 2C. Female: AFD (N=497), PAFD (N=384), CAFD (N=388) 2c. Male: AFD (N=371), PAFD (N=270), CAFD (N=298)

  28. Table. 1. Single-Marker association analysis in EAs

  29. Table. 2. Haplotype association analysis in EAs

  30. Table. 3. Diplotype association analysis (Global p values) in EAs Diplotype GG-CT from SNP 9-10 genotype pattern showed strong significance to female PAFD (P=0.00004)

  31. Fig. 3 Probability estimations for the number of clusters Fig. 4 Ancestry structure of individuals 4A a b 4B

  32. Association of SNPs with NGFB expression levels To assess a possible functional role of NGFB SNPs, which significantly associated with AFD, on the expression of NGFB [StrangerBE,2007; Mercader JM,2008], whole genome Illumina lymphoblastoid cell line gene expression data from 210 unrelated HapMap individuals were extracted from the GSE6536 series data set in Gene Expression Omnibus (GEO) site (http://www.ncbi.nlm.nih.gov/geo). The probe GI_4505390-S of NGFB was selected for the analysis. Genotype data of SNPs of NGFB from 210 unrelated individuals from CEPH (from European, African and Asian Ancestry) were downloaded from HapMap browser (http://www.hapmap.org/cgi-perl/gbrowse/hapmap_B36). The association analysis between these SNPs and the levels of expression for probe GI_4505390-S was tested using one-way ANOVA for genotypic model.

  33. Fig. 5 The expression of NGFB gene in lymphoblast cell ling in CUE, YRI Female subjects among different diplotypes Association of diplotypes from SNP 9-10 genotype pattern in the female PAFD subgroup

  34. Conclusion • NGFB is a risk gene for PAFD， but not in CAFD • NGFB is a risk gene for female with PAFD, but not for male with PAFD • PAFD and CAFD have different genetic background; • female and male PAFD have different gene-contributions in their pathology. • PAFD and CAFD might represent common manifestations of a different underlying predisposition, due to distinct genetic backgrounds, pathologic procedures and pathways.

  35. Acknowledgements 1) Dept Psychiatry, Yale Univ Sch Med, New Haven, CT, 06520, USA; Joel Gelernter Yang BZ Zhang H, Li D Wei F Ann Marie 2) Dept Psychiatry, Univ of Connecticut, Sch Med, Farmington, CT Kranzler HR 3) Dept Psychiatry & Hum Beh, Brown Univ, Providence, RI; Price L Tyrka A Carpenter L, 4) Dept of Anthropology, New York Univ., NY, USA; Jennifer Listman Grants: This work was supported by the VA CT REAP Center, and NIH grants AA11330, DA12849, and DA12690.

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