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Podéus H, Simonsson C, Nasr P, Ekstedt M, Kechagias S, Lundberg P, Lövfors W, Cedersund G. A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth. NPJ Digit Med 2024; 7:112. [PMID: 38702474 PMCID: PMC11068902 DOI: 10.1038/s41746-024-01089-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/29/2024] [Indexed: 05/06/2024] Open
Abstract
Alcohol consumption is associated with a wide variety of preventable health complications and is a major risk factor for all-cause mortality in the age group 15-47 years. To reduce dangerous drinking behavior, eHealth applications have shown promise. A particularly interesting potential lies in the combination of eHealth apps with mathematical models. However, existing mathematical models do not consider real-life situations, such as combined intake of meals and beverages, and do not connect drinking to clinical markers, such as phosphatidylethanol (PEth). Herein, we present such a model which can simulate real-life situations and connect drinking to long-term markers. The new model can accurately describe both estimation data according to a χ2 -test (187.0 < Tχ2 = 226.4) and independent validation data (70.8 < Tχ2 = 93.5). The model can also be personalized using anthropometric data from a specific individual and can thus be used as a physiologically-based digital twin. This twin is also able to connect short-term consumption of alcohol to the long-term dynamics of PEth levels in the blood, a clinical biomarker of alcohol consumption. Here we illustrate how connecting short-term consumption to long-term markers allows for a new way to determine patient alcohol consumption from measured PEth levels. An additional use case of the twin could include the combined evaluation of patient-reported AUDIT forms and measured PEth levels. Finally, we integrated the new model into an eHealth application, which could help guide individual users or clinicians to help reduce dangerous drinking.
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Affiliation(s)
- Henrik Podéus
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Christian Simonsson
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
- Center for Medicine Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden
| | - Patrik Nasr
- Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
- Wallenberg Center for Molecular Medicine, Linköping University, Linköping, Sweden
| | - Mattias Ekstedt
- Center for Medicine Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden
- Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
| | - Stergios Kechagias
- Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
| | - Peter Lundberg
- Center for Medicine Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden
- Department of Radiation Physics, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - William Lövfors
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
- School of Medical Sciences and Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Gunnar Cedersund
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden.
- Center for Medicine Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden.
- School of Medical Sciences and Inflammatory Response and Infection Susceptibility Centre (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
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Baker EJ, Moore S, Gonzales SW, Grant KA. Long-term drinking stability in the open-access self-administration monkey model. Alcohol 2023; 113:41-48. [PMID: 37516372 PMCID: PMC10818025 DOI: 10.1016/j.alcohol.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/14/2023] [Accepted: 07/05/2023] [Indexed: 07/31/2023]
Abstract
The Non-Human Primate (NHP) model for the study of Alcohol Use Disorders (AUD) as developed in our laboratories is critical to our understanding of the pathophysiology of voluntary, chronic, ethanol consumption. Previous work in this model established categories of ethanol consumption that parallel reported categories of human consumption across a spectrum spanning low drinking, binge drinking, heavy drinking, and very heavy drinking, albeit at generally higher daily intakes across categories than documented in people. Original categories assigned to ethanol consumption patterns were established using a limited cohort of rhesus macaques. This study revisits the validity of categorical drinking using an additional 28 monkeys. In addition to finding categorical representations consistent with the original 2014 report, our findings demonstrate that drinking categories remain stable across the observed 12 months of nearly consistent access to ethanol (22 h/day), termed "open access". Animals occupying the two ends of the spectrum, "low" and "very heavy" drinkers, exhibit the largest stability. The findings also indicate a slight escalatory drift over time, with very heavy drinking animals experiencing fatigue near the end of open access.
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Affiliation(s)
- Erich J Baker
- Department of Computer Science, Baylor University, Waco, TX, USA.
| | - Sharon Moore
- Department of Computer Science, Baylor University, Waco, TX, USA
| | - Steven W Gonzales
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Kathleen A Grant
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Portland, OR, USA
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Grant KA, Newman NN, Gonzales SW, Cuzon Carlson VC. Impact of putamen inhibition by DREADDs on schedule-induced drinking in rhesus monkeys. J Exp Anal Behav 2022; 117:493-504. [PMID: 35411949 PMCID: PMC9090979 DOI: 10.1002/jeab.761] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 03/30/2022] [Accepted: 03/30/2022] [Indexed: 11/11/2022]
Abstract
The putamen is a nucleus within the sensory-motor striatal network that is involved in automatic, habitual actions. Schedule-induced polydipsia (SIP) is highly automated behavior, reliably occurring under intermediate interval schedules of reinforcement. The effect of putamen inhibition in mediating SIP of water and ethanol (4% w/v) under a Fixed Time 5-min (FT-5 min) schedule for food delivery was tested in 12 rhesus monkeys (6 male, 6 female). Water and ethanol SIP sessions ended after set volumes were consumed. Baseline patterns of SIP intake differed between water and ethanol SIP in volume but not in pattern of drinking. Activation of the designer receptor exclusively activated by designer drug (DREADD: hM4Di) with deschloroclozapine (DCZ; 300 μg/kg, i.m.) administered 30 min prior to the onset of the SIP session, for four consecutive sessions. DCZ administration increased the postpellet drink volume and reduced the time to drink both water and ethanol. Although the effect of DCZ treatment was similar for increasing SIP with either water or ethanol, post-DCZ return to baseline SIP rates of differed, perhaps highlighting the effect of a state dependency with ethanol SIP. Overall, the study shows that targeting the putamen with the inhibitory DREADD produces a reversible, reproducible and reliable increase in adjunctive drinking.
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Affiliation(s)
- Kathleen A Grant
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland
| | - Natali N Newman
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton
| | - Steven W Gonzales
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton
| | - Verginia C Cuzon Carlson
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland
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