Skip to main content Accessibility help
×
Home
Hostname: page-component-568f69f84b-jg9p7 Total loading time: 0.139 Render date: 2021-09-17T02:18:06.834Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

99164 Resting Functional Connectivity of Networks Associated with Preoccupation in Alcohol Use Disorder Predicts Time to Relapse

Published online by Cambridge University Press:  30 March 2021

Emily M. Koithan
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Kai Xuan Nyoi
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Timothy Hendrickson
Affiliation:
University of Minnesota Informatics Institute
Hannah Verdoorn
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Casey Gilmore
Affiliation:
Minneapolis VA Health Care System
Bryon Mueller
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Matt Kushner
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Kelvin Lim
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Jazmin Camchong
Affiliation:
University of Minnesota Department of Psychiatry and Behavioral Sciences
Rights & Permissions[Opens in a new window]

Abstract

HTML view is not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

ABSTRACT IMPACT: Our research has the potential to impact human health by identifying a neural network that can be used to predict time to relapse in individuals with alcohol use disorder. OBJECTIVES/GOALS: Preoccupation towards alcohol use (e.g. craving, rumination, and poor executive control) is a maladaptive behavior associated with relapse risk. We investigated whether alterations in resting state networks known to mediate preoccupation could predict time to relapse in alcohol use disorder (AUD). METHODS/STUDY POPULATION: 50 participants with alcohol use disorder (AUD) (Age: M=41.76, SD=10.22, 19 females) were recruited from an addiction treatment program at ˜2 weeks of abstinence. fMRI data were preprocessed with the Human Connectome Project pipeline. Strength of resting state functional connectivity (RSFC) within two networks known to mediate the ‘Preoccupation go’ (PG) and ‘Preoccupation stop’ (PS) stages of addiction were calculated. T-tests were conducted to compare RSFC between subsequent abstainers and relapsers (after 4 months). Linear regressions were conducted to determine whether RSFC (of PG and PS networks) can predict time to relapse. Craving measures were included in the model. RESULTS/ANTICIPATED RESULTS: 19 AUD relapsed during the 4-month follow-up period. There were no RSFC group effects (subsequent abstainers and relapsers) in the PG or PS networks. Number of days to relapse could be predicted by PG RSFC (F(1,17)=14.90, p=0.001, r 2=0.47). Time to relapse increased by 13.19 days for each PG RSFC unit increase. Number of days to relapse could be predicted by PS RSFC (F(1,17)=9.39, p=0.002, r ²=0.36). Time to relapse increased by 12.94 days for each PS RSFC unit increase. After adding a self-report craving measure (i.e. Penn Alcohol Craving Scale) in the prediction model, both PG and PS RSFC still significantly predicted time to relapse. Craving metric did not predict time to relapse. DISCUSSION/SIGNIFICANCE OF FINDINGS: RSFC in preoccupation networks during short-term abstinence predicted time to relapse. These preliminary findings highlight promising targets for AUD neuromodulation interventions aimed to reduce relapse. Future larger scale studies that examine the effects of covariates and mediators are needed.

Type
Clinical Trial
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Association for Clinical and Translational Science 2021
You have Access
Open access

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

99164 Resting Functional Connectivity of Networks Associated with Preoccupation in Alcohol Use Disorder Predicts Time to Relapse
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

99164 Resting Functional Connectivity of Networks Associated with Preoccupation in Alcohol Use Disorder Predicts Time to Relapse
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

99164 Resting Functional Connectivity of Networks Associated with Preoccupation in Alcohol Use Disorder Predicts Time to Relapse
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *