A precision medicine approach to pharmacological adjuncts to extinction: A call to broaden research
Open accessAbstract
There is a pressing need to improve treatments for anxiety. Although exposure-based therapy is currently the gold-standard treatment, many people either do not respond to this therapy or experience a relapse of symptoms after treatment has ceased. In recent years, there have been many novel pharmacological agents identified in preclinical research that have potential as adjuncts for exposure therapy, yet very few of these are regularly integrated into clinical practice. Unfortunately, the robust effects observed in the laboratory animal often do not translate to a clinical population. In this review, we discuss how age, sex, genetics, stress, medications, diet, alcohol, and the microbiome can vary across a clinical population and yet are rarely considered in drug development. While not an exhaustive list, we have focused on these factors because they have been shown to influence an individual's vulnerability to anxiety and alter the neurotransmitter systems often targeted by pharmacological adjuncts to therapy. We argue that for potential adjuncts to be successfully translated from the lab to the clinic empirical research must be broadened to consider how individual difference factors will influence drug efficacy.
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The benefit of DCS-augmented EBT seems to be reduced in patients receiving antidepressants.
“Furthermore, the benefit of DCS-augmented EBT seems to be reduced in patients receiving antidepressants (King et al., 2018;Otto et al., 2016).”
From Novel pharmacological targets in drug development for the treatment of anxiety and anxiety-related disorders (2019) · cites this paper as King et al., 2018
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Cowan, C. S. M., Callaghan, B. L., & Richardson, R. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.94 · Cited by 83 · see citing works
Self-citationCohen, M. M., Tottenham, N., & Casey, B. J. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.01.023 · Cited by 81 · see citing works
Kanellopoulos, D., Gunning, F. M., Morimoto, S. S., Hoptman, M. J., Murphy, C. F., Kelly, R. E., Glatt, C. E., Lim, K. O., & Alexopoulos, G. S. (2010) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e3181f61d62 · Cited by 81 · see citing works
Martire, S. I., Maniam, J., South, T., Holmes, N. M., Westbrook, R. F., & Morris, M. J. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.02.027 · Cited by 80 · see citing works
No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression
Cole, J. H., Weinberger, D. R., Mattay, V. S., Cheng, X., Toga, A. W., Thompson, P. M., Powell‐Smith, G., Cohen‐Woods, S., Simmons, A., McGuffin, P., et al. (2011) · Genes Brain & Behavior · doi:10.1111/j.1601-183x.2011.00714.x · Cited by 80 · see citing works
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Prevalence of anxiety disorders in elderly adults: A critical analysis
Fuentes, K., & Cox, B. J. (1997) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/s0005-7916(97)00025-6 · Cited by 78 · see citing works
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Sartori, S. B., & Singewald, N. (2019) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2019.107402 · Cited by 236 · see citing works
Mayo, L. M., Asratian, A., Lindé, J., Morena, M., Haataja, R., Hammar, V., Augier, G., Hill, M. N., & Heilig, M. A. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.07.034 · Cited by 207 · see citing works
Developmental differences in the effects of CB1/2R agonist WIN55212-2 on extinction of learned fear
Bisby, M. A., Richardson, R., & Baker, K. (2019) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2019.109834 · Cited by 15 · see citing works
Self-citationEditorial: the psychopharmacology of extinction—from theory to therapy
Milton, A. L., & Holmes, A. (2019) · Psychopharmacology · doi:10.1007/s00213-018-5152-9 · Cited by 14 · see citing works
Harmon‐Jones, S. K., Cowan, C. S. M., Shnier, N. L., & Richardson, R. (2020) · Behaviour Research and Therapy · doi:10.1016/j.brat.2020.103763 · Cited by 6 · see citing works
Self-citationAnti-Depression a Systematic Review of Analytical methods in PharmaceuticalsPreprint
Perumal, D., Krishnan, M., & K.S, L. (2022) · doi:10.22541/au.165658161.19930674/v1
- Authors
- King, G., Baker, K. D., Bisby, M. A., Chan, D., Cowan, C. S. M., Stylianakis, A. A., Zimmermann, K. S., & Richardson, R.
- Affiliations
- UNSW Sydney (AU)
- University College Cork (IE)
- Corresponding author
- King, Gabrielle
- ORCID
- Venue
- Psychopharmacology
- Published
- 2018-08-16
- Volume
- 236
- Issue
- 1
- Pages
- 143-161
- ISSN
- 0033-3158 (ISSN-L)
- 1432-2072
- OpenAlex
- W2886849746
- Cited by
- 6
- References
- 258
- Citations by year
- 2022: 1 · 2020: 1 · 2019: 4
- FWCI
- 0.20
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Psychopharmacology (publishedVersion)
- PubMed (publishedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- precision medicine, extinction, anxiety disorders, exposure therapy, individual differences, sex differences, age effects, genetic factors, stress, diet, alcohol, gut microbiota, translational research, drug development, neurotransmitter systems
- MeSH terms
- Drug Development, Animals, Anxiety, Brain, Extinction, Psychological, Humans, Anti-Anxiety Agents, Neurotransmitter Agents, Precision Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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