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2019, Número 5

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Rev Invest Clin 2019; 71 (5)


Exploratory Analysis of Polygenic Risk Scores for Psychiatric Disorders: Applied to Dual Diagnosis

Martínez-Magaña JJ, Gonzalez-Castro TB, Genís-Mendoza AD, Tovilla-Zárate CA, Juárez-Rojop IE, Saucedo-Uribe E, Rodríguez-Mayoral O, Lanzagorta N, Escamilla M, Macías-Kauffer L, Nicolini H

Idioma: Ingles.
Referencias bibliográficas: 57
Paginas: 321-329
Archivo PDF: 198.01 Kb.


RESUMEN

Sin resumen.


REFERENCIAS (EN ESTE ARTÍCULO)

  1. Mitchell KJ. What is complex about complex disorders? Genome Biol. 2012;13:237.

  2. Avramopoulos D. Genetics of psychiatric disorders methods: molecular approaches. Psychiatr Clin North Am. 2010;33:1-3.

  3. Psychiatric GWAS Consortium Bipolar Disorder Working Group. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet 2011;43:977-83.

  4. Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51:793-803.

  5. Ritter ML, Guo W, Samuels JF, Wang Y, Nestadt PS, Krasnow J, et al. Genome wide association study (GWAS) between attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD). Front Mol Neurosci. 2017;10:83.

  6. Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat Genet. 2013;45:1452-8.

  7. Schork AJ, Brown TT, Hagler DJ, Thompson WK, Chen CH, Dale AM, et al. Polygenic risk for psychiatric disorders correlates with executive function in typical development. Genes Brain Behav. 2019;18:e12480.

  8. Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013; 381:1371-9.

  9. Euesden J, Lewis CM, O’Reilly PF. PRSice: polygenic risk score software. Bioinformatics. 2015;31:1466-8.

  10. Lewis CM, Vassos E. Prospects for using risk scores in polygenic medicine. Genome Med. 2017;9:96.

  11. Vassos E, Di Forti M, Coleman J, Iyegbe C, Prata D, Euesden J, et al. An examination of polygenic score risk prediction in individuals with first-episode psychosis. Biol Psychiatry. 2017;81:470-7.

  12. Torkamani A, Wineinger NE, Topol EJ. The personal and clinical utility of polygenic risk scores. Nat Rev Genet. 2018;19:581-90.

  13. Wong CC, Schumann G. Review. Genetics of addictions: strategies for addressing heterogeneity and polygenicity of substance use disorders. Philos Trans R Soc Lond B Biol Sci. 2008;363:3213-22.

  14. Maher BS, Marazita ML, Zubenko WN, Kaplan BB, Zubenko GS. Genetic segregation analysis of alcohol and other substanceuse disorders in families with recurrent, early-onset major depression. Am J Drug Alcohol Abuse. 2002;28:711-31.

  15. Kessler RC. The epidemiology of dual diagnosis. Biol Psychiatry. 2004;56:730-7.

  16. Buckley PF, Brown ES. Prevalence and consequences of dual diagnosis. J Clin Psychiatry. 2006;67:e01.

  17. Breslau N. Psychiatric comorbidity of smoking and nicotine dependence. Behav Genet. 1995;25:95-101.

  18. Gattamorta KA, Mena MP, Ainsley JB, Santisteban DA. The comorbidity of psychiatric and substance use disorders among Hispanic adolescents. J Dual Diagn. 2017;13:254-63.

  19. Taukoor B, Paruk S, Karim E, Burns JK. Substance use in adolescents with mental illness in Durban, South Africa. J Child Adolesc Ment Health. 2017;29:51-61.

  20. Wilton G, Stewart LA. Outcomes of offenders with co-occurring substance use disorders and mental disorders. Psychiatr Serv. 2017;68:704-9.

  21. Di Lorenzo R, Galliani A, Guicciardi A, Landi G, Ferri P. A retrospective analysis focusing on a group of patients with dual diagnosis treated by both mental health and substance use services. Neuropsychiatr Dis Treat. 2014;10:1479-88.

  22. Levran O, Randesi M, da Rosa JC, Ott J, Rotrosen J, Adelson M, et al. Overlapping dopaminergic pathway genetic susceptibility to heroin and cocaine addictions in African Americans. Ann Hum Genet. 2015;79:188-98.

  23. Kendler KS, Karkowski LM, Neale MC, Prescott CA. Illicit psychoactive substance use, heavy use, abuse, and dependence in a US population-based sample of male twins. Arch Gen Psychiatry. 2000;57:261-9.

  24. Hartz SM, Horton AC, Oehlert M, Carey CE, Agrawal A, Bogdan R, et al. Association between substance use disorder and polygenic liability to schizophrenia. Biol Psychiatry. 2017;82:709-15.

  25. Carey CE, Agrawal A, Bucholz KK, Hartz SM, Lynskey MT, Nelson EC, et al. Associations between polygenic risk for psychiatric disorders and substance involvement. Front Genet. 2016;7:149.

  26. Palmer RH, Brick L, Nugent NR, Bidwell LC, McGeary JE, Knopik VS, et al. Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: genetics of vulnerability to drug dependence. Addiction. 2015;110:530-7.

  27. Maher BS. Polygenic scores in epidemiology: risk prediction, etiology, and clinical utility. Curr Epidemiol Rep. 2015;2:239-44.

  28. Vink JM, Hottenga JJ, de Geus EJ, Willemsen G, Neale MC, Furberg H, et al. Polygenic risk scores for smoking: predictors for alcohol and cannabis use? Addiction. 2014;109:1141-51.

  29. Reginsson GW, Ingason A, Euesden J, Bjornsdottir G, Olafsson S, Sigurdsson E, et al. Polygenic risk scores for schizophrenia and bipolar disorder associate with addiction. Addict Biol. 2018; 23:485-92.

  30. Gurriaran X, Rodriguez-Lopez J, Florez G, Pereiro C, Fernandez JM, Farinas E, et al. Relationships between substance abuse/ dependence and psychiatric disorders based on polygenic scores. Genes Brain Behav. 2019;18:e12504.

  31. Moreno-Estrada A, Gignoux CR, Fernandez-Lopez JC, Zakharia F, Sikora M, Contreras AV, et al. Human genetics. The genetics of Mexico recapitulates native American substructure and affects biomedical traits. Science. 2014;344:1280-5.

  32. Martin AR, Gignoux CR, Walters RK, Wojcik GL, Neale BM, Gravel S, et al. Human demographic history impacts genetic risk prediction across diverse populations. Am J Hum Genet. 2017; 100:635-49.

  33. Kim MS, Patel KP, Teng AK, Berens AJ, Lachance J. Genetic disease risks can be misestimated across global populations. Genome Biol. 2018;19:179.

  34. De La Vega FM, Bustamante CD. Polygenic risk scores: a biased prediction? Genome Med. 2018;10:100.

  35. Nurnberger JI Jr., Blehar MC, Kaufmann CA, York-Cooler C, Simpson SG, Harkavy-Friedman J, et al. Diagnostic interview for genetic studies. Rationale, unique features, and training. NIMH genetics initiative. Arch Gen Psychiatry. 1994;51:849-59.

  36. Volkow ND. Substance use disorders in schizophrenia clinical implications of comorbidity. Schizophr Bull. 2009;35:469-72.

  37. Sullivan PF, Daly MJ, O Donovan M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet. 2012;13:537-51.

  38. Autism Spectrum Disorders Working Group of the Psychiatric Genomics Consortium. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism. 2017;8:21.

  39. Neale BM, Medland SE, Ripke S, Asherson P, Franke B, Lesch KP, et al. Meta-analysis of genome-wide association studies of attention- deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2010;49:884-97.

  40. Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Ripke S, Wray NR, Lewis CM, Hamilton SP, Weissman MM, et al. A mega-analysis of genome-wide association studies for major depressive disorder. Mol Psychiatry. 2013;18:497-511.

  41. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421-7.

  42. Browning SR, Browning BL. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet. 2007;81:1084-97.

  43. Browning BL, Browning SR. Genotype imputation with millions of reference samples. Am J Hum Genet. 2016;98:116-26.

  44. 1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature. 2015;526:68-74.

  45. Verma SS, de Andrade M, Tromp G, Kuivaniemi H, Pugh E, Namjou-Khales B, et al. Imputation and quality control steps for combining multiple genome-wide datasets. Front Genet. 2014;5:370.

  46. International Schizophrenia Consortium, Purcell SM, Wray NR, Stone JL, Visscher PM, O Donovan MC, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460:748-52.

  47. Shi H, Medway C, Brown K, Kalsheker N, Morgan K. Using fisher’s method with PLINK ‘LD clumped’ output to compare SNP effects across genome-wide association study (GWAS) datasets. Int J Mol Epidemiol Genet. 2011;2:30-5.

  48. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011; 88:76-82.

  49. Galanter JM, Fernandez-Lopez JC, Gignoux CR, Barnholtz- Sloan J, Fernandez-Rozadilla C, Via M, et al. Development of a panel of genome-wide ancestry informative markers to study admixture throughout the Americas. PLoS Genet. 2012; 8:e1002554.

  50. Nagelkerke NJ. A note on a general definition of the coefficient of determination. Biometrika. 1991;78:691-2.

  51. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21:128-38.

  52. Team RDC. R: a Language and Environment for Statistical Computing. R Dev Core Team. R Foundation for Statistical Computing. Vienna, Austria: Team RDC; 2008.

  53. Dzafic I, Burianova H, Periyasamy S, Mowry B. Association between schizophrenia polygenic risk and neural correlates of emotion perception. Psychiatry Res Neuroimaging. 2018; 276:33-40.

  54. Poletti M, Raballo A. Polygenic risk score and the (neuro)developmental ontogenesis of the schizophrenia spectrum vulnerability phenotypes. Schizophr Res. 2018;202:389-90.

  55. Andersen AM, Pietrzak RH, Kranzler HR, Ma L, Zhou H, Liu X, et al. Polygenic scores for major depressive disorder and risk of alcohol dependence. JAMA Psychiatry. 2017;74:1153-60.

  56. Florez JC, Price AL, Campbell D, Riba L, Parra MV, Yu F, et al. Strong association of socioeconomic status with genetic ancestry in latinos: implications for admixture studies of Type 2 diabetes. Diabetologia. 2009;52:1528-36.

  57. Curtis D. Polygenic risk score for schizophrenia is more strongly associated with ancestry than with schizophrenia. Psychiatr Genet. 2018;28:85-9.




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