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Toward a generalized developmental model of psychopathological liabilities and psychiatric disorders

Published online by Cambridge University Press:  07 February 2022

Carlos Blanco*
Affiliation:
Division of Epidemiology, Services and Prevention Research, National Institute on Drug Abuse, 6001 Executive Boulevard, Bethesda, MD 20852, USA
Melanie M. Wall
Affiliation:
Department of Psychiatry, Columbia University/New York State Psychiatric Institute, 1051 Riverside Drive, Unit 69, New York, NY, 10032, USA
Nicolas Hoertel
Affiliation:
Department of Psychiatry, Assistance Publique-Hôpitaux de Paris, Hôpital Corentin-Celton, Issy-les-Moulineaux, France INSERM UMR 894, Psychiatry and Neurosciences Center, Paris, France Paris Descartes University, Pôles de recherche et d'enseignement supérieur Sorbonne Paris Cité, Paris, France
Robert F. Krueger
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, USA
Mark Olfson
Affiliation:
Department of Psychiatry, Columbia University/New York State Psychiatric Institute, 1051 Riverside Drive, Unit 69, New York, NY, 10032, USA
*
Author for correspondence: Carlos Blanco, E-mail: carlos.blanco2@nih.gov

Abstract

Background

Most psychiatric disorders are associated with several risk factors, but a few underlying psychopathological dimensions account for the common co-occurrence of disorders. If these underlying psychopathological dimensions mediate associations of the risk factors with psychiatric disorders, it would support a trans-diagnostic orientation to etiological research and treatment development.

Method

An analysis was performed of the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions III (NESARC-III), a US nationally representative sample of non-institutionalized civilian adults, focusing on respondents who were aged ⩾21 (n = 34 712). Structural equation modeling was used to identify the psychopathological dimensions underlying psychiatric disorders; to examine associations between risk factors, psychopathological dimensions and individual disorders; and to test whether associations of risk factors occurring earlier in life were mediated by risk factors occurring later in life.

Results

A bifactor model of 13 axis I disorders provided a good fit (CFI = 0.987, TLI = 0.982, and RMSEA = 0.011) including an overall psychopathology factor as measured by all 13 disorders and 2 specific factors, one for externalizing disorders and one for fear-related disorders. A substantial proportion of the total effects of the risk factors occurring early in life were indirectly mediated through factors occurring later in life. All risk factors showed a significant total effect on the general psychopathology, externalizing and fear-related factors. Only 23 of 325 direct associations of risk factors with psychiatric disorders achieved statistical significance.

Conclusion

Most risk factors for psychiatric disorders are mediated through broad psychopathological dimensions. The central role of these dimensions supports trans-diagnostic etiological and intervention research.

Type
Original Article
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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Footnotes

*

Drs. Blanco and Wall are co-first authors of the manuscript.

References

Adams, P. F., Kirzinger, W. K., & Martinez, M. (2013). Summary health statistics for the U.S. Population: National health interview survey, 2012. Vital and Health Statistics. Series 10, Data from the National Health Survey, 259, 195.Google Scholar
The Brainstorm Consortium, Anttila, V., Bulik-Sullivan, B., Finucane, H. K., Walters, R. K., Bras, J., … Neale, B. M. (2018). Analysis of shared heritability in common disorders of the brain. Science (New York, N.Y.), 360(6395), eaap8757. doi: doi.org/10.1126/science.aap8757Google ScholarPubMed
Arango, C., Díaz-Caneja, C. M., McGorry, P. D., Rapoport, J., Sommer, I. E., Vorstman, J. A., … Carpenter, W. (2018). Preventive strategies for mental health. The Lancet Psychiatry, 5(7), 591604. doi: doi.org/10.1016/S2215-0366(18)30057-9CrossRefGoogle ScholarPubMed
Bakk, Z., & Kuha, J. (2018). Two-step estimation of models between latent classes and external variables. Psychometrika, 83(4), 871892. doi: doi.org/10.1007/s11336-017-9592-7CrossRefGoogle ScholarPubMed
Barlow, D. H., Farchione, T. J., Bullis, J. R., Gallagher, M. W., Murray-Latin, H., Sauer-Zavala, , … Cassiello-Robbins, C. (2017). The unified protocol for transdiagnostic treatment of emotional disorders compared with diagnosis-specific protocols for anxiety disorders: A randomized clinical trial. JAMA Psychiatry, 74(9), 875884. doi: doi.org/10.1001/jamapsychiatry.2017.2164CrossRefGoogle ScholarPubMed
Blanco, C., Compton, W. M., & Grant, B. F. (2016). Toward precision epidemiology. JAMA Psychiatry, 73(10), 10081009. doi: doi.org/10.1001/jamapsychiatry.2016.1869CrossRefGoogle ScholarPubMed
Blanco, C., Hanania, J., Petry, N. M., Wall, M. M., Wang, S., Jin, C. J., & Kendler, K. S. (2015). Towards a comprehensive developmental model of pathological gambling: Developmental model of pathological gambling. Addiction, 110(8), 13401351. doi: doi.org/10.1111/add.12946CrossRefGoogle ScholarPubMed
Blanco, C., Krueger, R. F., Hasin, D. S., Liu, S.-M., Wang, S., Kerridge, B. T., … Olfson, M. (2013). Mapping common psychiatric disorders: Structure and predictive validity in the national epidemiologic survey on alcohol and related conditions. JAMA Psychiatry, 70(2), 1992008. doi: doi.org/10.1001/jamapsychiatry.2013.281CrossRefGoogle ScholarPubMed
Blanco, C., Rafful, C., Wall, M. M., Ridenour, T. A., Wang, S., & Kendler, K. S. (2014a). Towards a comprehensive developmental model of cannabis use disorders: Developmental model of cannabis use disorders. Addiction, 109(2), 284294. doi: doi.org/10.1111/add.12382CrossRefGoogle ScholarPubMed
Blanco, C., Rubio, J., Wall, M., Wang, S., Jiu, C. J., & Kendler, K. S. (2014b). Risk factors for anxiety disorders: Common and specific effects in a national sample. Depression and Anxiety, 31(9), 756764. doi: doi.org/10.1002/da.22247CrossRefGoogle Scholar
Blanco, C., Wall, M. M., Feng, T., & Olfson, M. (2021a). Evaluating the modified common liability hypothesis of psychiatric comorbidity. Journal of Psychiatric Research, 141, 915. hdoi.org/10.1016/j.jpsychires.2021.06.017.CrossRefGoogle ScholarPubMed
Blanco, C., Wall, M. M., Liu, S.-M., & Olfson, M. (2019). Toward a comprehensive developmental model of prescription opioid use disorder. The Journal of Clinical Psychiatry, 81(1), 19m12775. doi: doi.org/10.4088/JCP.19m12775CrossRefGoogle Scholar
Blanco, C., Wall, M. M., & Olfson, M. (2021b). A population-level approach to suicide prevention. JAMA, 325(23), 23392340. doi: doi.org/10.1001/jama.2021.6678CrossRefGoogle ScholarPubMed
Blanco, C., Wall, M. M., Wang, S., & Olfson, M. (2017). Examining heterotypic continuity of psychopathology: A prospective national study. Psychological Medicine, 47(12), 20972106. doi: doi.org/10.1017/S003329171700054XCrossRefGoogle ScholarPubMed
Boschloo, L., van Borkulo, C. D., Borsboom, D., & Schoevers, R. A. (2016). A prospective study on How symptoms in a network predict the onset of depression. Psychotherapy and Psychosomatics, 85(3), 183184. doi: doi.org/10.1159/000442001CrossRefGoogle Scholar
Bureau of the Census. (2012). American Community survey, 2012 (Rep.). Suitland, Suitland-Silver Hill, MD: Bureau of the Census. https://www.census.gov.Google Scholar
Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., … Moffitt, T. E. (2014). The p factor: One general psychopathology factor in the structure of psychiatric disorders? Clinical Psychological Science, 2(2), 119137. doi: doi.org/10.1177/2167702613497473CrossRefGoogle Scholar
Castellanos-Ryan, N., Brière, F. N., O'Leary-Barrett, M., Banaschewski, T., Bokde, A., & Bromberg, U., … The IMAGEN Consortium. (2016). The structure of psychopathology in adolescence and its common personality and cognitive correlates. Journal of Abnormal Psychology, 125(8), 10391052. doi: doi.org/10.1037/abn0000193CrossRefGoogle ScholarPubMed
Cross-Disorder Group of the Psychiatric Genomics Consortium (2013). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 45(9), 984994. doi: doi.org/10.1038/ng.2711CrossRefGoogle Scholar
Devlieger, I., Mayer, A., & Rosseel, Y. (2016). Hypothesis testing using factor score regression: A comparison of four methods. Educational and Psychological Measurement, 76(5), 741770. doi: doi.org/10.1177/0013164415607618CrossRefGoogle ScholarPubMed
Dueber, D. M. (2017). Bifactor Indices Calculator: A Microsoft Excel-based tool to calculate various indices relevant to bifactor CFA models. https://dx.doi.org/10.13023/edp.tool.01].CrossRefGoogle Scholar
Etz, K. E., Goldstein, A. B., Lopez, M. F., & Blanco, C. (2020). Increasing collaboration and translation in epidemiology and intervention research. Psychology of Addictive Behaviors, 34(8), 890893. doi: doi.org/10.1037/adb0000641CrossRefGoogle ScholarPubMed
Franco, S., Olfson, M., Wall, M. M., Wang, S., Hoertel, N., & Blanco, C. (2019). Shared and specific associations of substance use disorders on adverse outcomes: A national prospective study. Drug and Alcohol Dependence, 201, 212219. doi: doi.org/10.1016/j.drugalcdep.2019.03.003CrossRefGoogle ScholarPubMed
García-Rodríguez, O., Blanco, C., Wall, M. M., Wang, S., Jin, C. J., & Kendler, K. S. (2014). Toward a comprehensive developmental model of smoking initiation and nicotine dependence. Drug and Alcohol Dependence, 144, 160169. doi: doi.org/10.1016/j.drugalcdep.2014.09.002CrossRefGoogle Scholar
Goldberg, L. R. (2006). Doing it all bass-ackwards: The development of hierarchical factor structures from the top down. Journal of Research in Personality, 40(4), 347358. doi: doi.org/10.1016/j.jrp.2006.01.001CrossRefGoogle Scholar
Goodkind, M., Eickhoff, S. B., Oathes, D. J., Jiang, Y., Chang, A., Jones-Hagata, , … Etkin, A. (2015). Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry, 72(4), 305315. doi: doi.org/10.1001/jamapsychiatry.2014.2206CrossRefGoogle ScholarPubMed
Grant, B. F., Chu, A., Sigman, R., Amsbary, M., Kali, J., … Goldstein, R. (2015). National Institute on Alcohol Abuse and Alcoholism National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC- III) Source and Accuracy Statement. Retrieved 2021, from https://www.niaaa.nih.gov/sites/default/files/NESARC_Final_Report_FINAL_1_8_15.pd.Google Scholar
Greene, A. L., Eaton, N. R., Li, K., Forbes, M. K., Krueger, R. F., Markon, K. E., … Kotov, R. (2019). Are fit indices used to test psychopathology structure biased? A simulation study. Journal of Abnormal Psychology, 128(7), 740764. doi: doi.org/10.1037/abn0000434CrossRefGoogle ScholarPubMed
Hasin, D. S., Greenstein, E., Aivadyan, C., Stohl, M., Aharonovich, E., Saha, T., … Grant, B. F. (2015). The Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (AUDADIS-5): Procedural validity of substance use disorders modules through clinical re-appraisal in a general population sample. Drug and Alcohol Dependence, 148, 4046. doi: doi.org/10.1016/j.drugalcdep.2014.12.011CrossRefGoogle Scholar
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 155. doi: doi.org/10.1080/10705519909540118CrossRefGoogle Scholar
Jakubovski, E., Varigonda, A. L., Freemantle, N., Taylor, M. J., & Bloch, M. H. (2016). Systematic review and meta-analysis: Dose-response relationship of selective serotonin reuptake inhibitors in major depressive disorder. American Journal of Psychiatry, 173(2), 174183. doi: doi.org/10.1176/appi.ajp.2015.15030331CrossRefGoogle ScholarPubMed
Kendler, K. S., Gardner, C. O., & Prescott, C. A. (2002). Toward a comprehensive developmental model for major depression in women. American Journal of Psychiatry, 159(7), 11331145. doi: doi.org/10.1176/appi.ajp.159.7.1133CrossRefGoogle Scholar
Kendler, K. S., Gardner, C. O., & Prescott, C. A. (2006). Toward a comprehensive developmental model for major depression in men. American Journal of Psychiatry, 163(1), 115124. doi: doi.org/10.1176/appi.ajp.163.1.115CrossRefGoogle Scholar
Keyes, K. M., Eaton, N. R., Krueger, R. F., McLaughlin, K. A., Wall, M. M., Grant, B. F., & Hasin, D. S. (2012). Childhood maltreatment and the structure of common psychiatric disorders. British Journal of Psychiatry, 200(2), 107115. doi: doi.org/10.1192/bjp.bp.111.093062CrossRefGoogle ScholarPubMed
Kim, H., & Eaton, N. R. (2015). The hierarchical structure of common mental disorders: Connecting multiple levels of comorbidity, bifactor models, and predictive validity. Journal of Abnormal Psychology, 124(4), 10641078. doi: doi.org/10.1037/abn0000113CrossRefGoogle ScholarPubMed
Krueger, R. F. (1999). The structure of common mental disorders. Archives of General Psychiatry, 56(10), 921926. doi: doi.org/10.1001/archpsyc.56.10.921CrossRefGoogle ScholarPubMed
Lahey, B. B., Applegate, B., Hakes, J. K., Zald, D. H., Hariri, A. R., & Rathouz, P. J. (2012). Is there a general factor of prevalent psychopathology during adulthood? Journal of Abnormal Psychology, 121(4), 971977. doi: doi.org/10.1037/a0028355CrossRefGoogle Scholar
McTeague, L. M., Rosenberg, B. M., Lopez, J. W., Carreon, D. M., Huemer, J., Jiang, Y., … Etkin, A. (2020). Identification of common neural circuit disruptions in emotional processing across psychiatric disorders. American Journal of Psychiatry, 177(5), 411421. doi: doi.org/10.1176/appi.ajp.2019.18111271CrossRefGoogle ScholarPubMed
Muthén, L. K., & Muthén, B. O. (1998). Statistical Analysis With Latent Variables User's Guid. https://www.statmodel.com/download/usersguide/Mplus%20user%20guide%20Ver_7_r6 _web.pdf.Google Scholar
Pinto, J. V., Moulin, T. C., & Amaral, O. B. (2017). On the transdiagnostic nature of peripheral biomarkers in major psychiatric disorders: A systematic review. Neuroscience & Biobehavioral Reviews, 83, 97108. doi: doi.org/10.1016/j.neubiorev.2017.10.001CrossRefGoogle ScholarPubMed
Skrondal, A., & Laake, P. (2001). Regression among factor scores. Psychometrika, 66(4), 563575. https://doi.org/10.1007/BF02296196.CrossRefGoogle Scholar
VanderWeele, T., & Vansteelandt, S. (2014). Mediation analysis with multiple mediators. Epidemiologic Methods, 2(1), 95115. doi: doi.org/10.1515/em-2012-0010.CrossRefGoogle ScholarPubMed
Wall, M. M., & Li, R. (2003). Comparison of multiple regression to two latent variable techniques for estimation and prediction. Statistics in Medicine, 22(23), 36713685. doi: doi.org/10.1002/sim.1588CrossRefGoogle ScholarPubMed
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