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Browsing by Author "Francis, Meredith W."
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Item Changes over time in endorsement of 11 DSM-IV alcohol use disorder (AUD) criteria in young adults with persistent or recurrent AUD in The Collaborative Study on the Genetics of Alcoholism(Wiley, 2023) Schuckit, Marc A.; Smith, Tom L.; Danko, George; Tear, Jake; Hennies, Jessica; Mendoza, Lee Anne; Hesselbrock, Victor; Edenberg, Howard J.; Hesselbrock, Michie; Bucholz, Kathleen; Chan, Grace; Kuperman, Samuel; Francis, Meredith W.; Plawecki, Martin H.; Biochemistry and Molecular Biology, School of MedicineBackground: Endorsement of specific Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) alcohol use disorder (AUD) criteria have been shown to change significantly over time in men in their thirties who have persistent or recurrent AUD. However, few studies have documented whether the endorsement of AUD items changes over time in younger individuals or in women. We evaluated changes in the endorsement of AUD criteria in 377 men and women with persistent or recurrent AUD during their twenties. Methods: Information on AUD-item endorsement over time was available for 223 men and 154 women aged 20-25 with persistent or recurrent AUD in at least three interviews in the Collaborative Study on the Genetics of Alcoholism. The statistical significance of endorsement changes over time was evaluated using the related-sample Cochran's Q test for the full sample and for men and women separately. Additional analyses evaluated sex differences in the patterns of change. Results: In the full sample, the predominant pattern was for a significant increase in the rates of endorsement for six of the seven alcohol dependence criteria but not in the four abuse criteria. A similar pattern was seen within men, but women had significant changes in only three of the seven dependence criteria. Conclusions: Endorsement of the seven alcohol dependence criteria among individuals with persistent or recurrent AUD in their twenties generally increased, but few changes were observed in the rates of endorsement of the four abuse criteria. These results are discussed in terms of how they reflect on the nature of AUD and the DSM criteria.Item Characterization of Service Use for Alcohol Problems Across Generations and Sex in Adults With Alcohol Use Disorder(Wiley, 2020-03) Bourdon, Jessica L.; Tillman, Rebecca; Francis, Meredith W.; Dick, Danielle M.; Stephenson, Mallory; Kamarajan, Chella; Edenberg, Howard J.; Kramer, John; Kuperman, Samuel; Bucholz, Kathleen K.; McCutcheon, Vivia V.; Biochemistry and Molecular Biology, School of MedicineBackground: There are gaps in the literature on service use (help-seeking and treatment utilization) for alcohol problems among those with alcohol use disorder (AUD). First, policy changes and cultural shifts (e.g., insurance) related to AUD have occurred over the last few decades, making it important to study generational differences. Second, multiple studies have found that females receive fewer services than males, and exploring whether these sex differences persist across generations can inform public health and research endeavors. The current study examined service use for alcohol problems among individuals with AUD. The aims were as follows: (i) to describe service use for alcohol problems; (ii) to assess generational differences (silent [b. 1928 to 1945], boomer [b. 1946 to 1964], generation X [b. 1965 to 1980], millennial [b. 1981 to 1996]) in help-seeking and treatment utilization; and (iii) to examine sex differences across generations. Methods: Data were from affected family members of probands who participated in the Collaborative Study on the Genetics of Alcoholism (N = 4,405). First, frequencies for service use variables were calculated across generations. Pearson chi-square and ANOVA were used to test for differences in rates and types of service use across generations, taking familial clustering into account. Next, Cox survival modeling was used to assess associations of generation and sex with time to first help-seeking and first treatment for AUD, and time from first onset of AUD to first help-seeking and first treatment. Interactions between generation and sex were tested within each Cox regression. Results: Significant hazards were found in all 4 transitions. Overall, younger generations used services earlier than older generations, which translated into higher likelihoods of these behaviors. Regardless of generation, younger females were less likely to use services than males. Conclusions: There are generational and sex differences in service use for alcohol problems among individuals with AUD. Policy and clinical implications are discussed.Item Clinical, environmental, and genetic risk factors for substance use disorders: characterizing combined effects across multiple cohorts(Springer, 2022-10-04) Barr, Peter B.; Driver, Morgan N.; Kuo, Sally I-Chun; Stephenson, Mallory; Aliev, Fazil; Linnér, Richard Karlsson; Marks, Jesse; Anokhin, Andrey P.; Bucholz, Kathleen; Chan, Grace; Edenberg, Howard J.; Edwards, Alexis C.; Francis, Meredith W.; Hancock, Dana B.; Harden, K. Paige; Kamarajan, Chella; Kaprio, Jaakko; Kinreich, Sivan; Kramer, John R.; Kuperman, Samuel; Latvala, Antti; Meyers, Jacquelyn L.; Palmer, Abraham A.; Plawecki, Martin H.; Porjesz, Bernice; Rose, Richard J.; Schuckit, Marc A.; Salvatore, Jessica E.; Dick , Danielle M.; Medical and Molecular Genetics, School of MedicineSubstance use disorders (SUDs) incur serious social and personal costs. The risk for SUDs is complex, with risk factors ranging from social conditions to individual genetic variation. We examined whether models that include a clinical/environmental risk index (CERI) and polygenic scores (PGS) are able to identify individuals at increased risk of SUD in young adulthood across four longitudinal cohorts for a combined sample of N = 15,134. Our analyses included participants of European (NEUR = 12,659) and African (NAFR = 2475) ancestries. SUD outcomes included: (1) alcohol dependence, (2) nicotine dependence; (3) drug dependence, and (4) any substance dependence. In the models containing the PGS and CERI, the CERI was associated with all three outcomes (ORs = 01.37-1.67). PGS for problematic alcohol use, externalizing, and smoking quantity were associated with alcohol dependence, drug dependence, and nicotine dependence, respectively (OR = 1.11-1.33). PGS for problematic alcohol use and externalizing were also associated with any substance dependence (ORs = 1.09-1.18). The full model explained 6-13% of the variance in SUDs. Those in the top 10% of CERI and PGS had relative risk ratios of 3.86-8.04 for each SUD relative to the bottom 90%. Overall, the combined measures of clinical, environmental, and genetic risk demonstrated modest ability to distinguish between affected and unaffected individuals in young adulthood. PGS were significant but added little in addition to the clinical/environmental risk index. Results from our analysis demonstrate there is still considerable work to be done before tools such as these are ready for clinical applications.Item Deriving a Measure of Social Recovery Capital From the Important People and Activities Instrument: Construction and Psychometric Properties(Oxford University Press, 2022) Francis, Meredith W.; Bourdon, Jessica L.; Chan, Grace; Dick, Danielle M.; Edenberg, Howard J.; Kamarajan, Chella; Kinreich, Sivan; Kramer, John; Kuo, Sally I-Chun; Pandey, Ashwini K.; Pandey, Gayathri; Smith, Rebecca L.; Bucholz, Kathleen K.; McCutcheon, Vivia V.; Psychiatry, School of MedicineAim: This study presents a measure of Social Recovery Capital (SRC) derived from the Important People and Activities instrument (IPA). Methods: The sample comprised young adults who participated in the Collaborative Study on the Genetics of Alcoholism, a high-risk family study of alcohol use disorder (N = 2472). Exploratory and confirmatory factor analysis identified influential items and factor structure, adjusting for family relatedness. The final scale was tested for reliability and validity. Results: Factor analysis retained 10 items loading on three factors (Network Abstinence Behaviors, Basic Network Structure and Network Importance) that together explained 42% of the variance in SRC. The total model showed adequate fit (Comparative Fit Index = 0.95; Tucker Lewis Index = 0.93; Root Mean Square Error of Approximation = 0.06; Standardized Root Mean Squared Residual = 0.05) and acceptable reliability (α = 0.60; McDonald's ω = 0.73) and correlated with validation measures mostly in the weak to moderate range. Due to variable factor scores for reliability and validity, we only recommend using the total score. Conclusion: The SRC-IPA is a novel measure of SRC derived from the IPA that captures social network data and has applications in research and clinical work. Secondary data analyses using the SRC-IPA in studies that collected the IPA can further demonstrate the interaction of SRC with a wide variety of clinical indicators and demographic characteristics, making it a valuable addition to other measures of SRC.Item Evaluating risk for alcohol use disorder: Polygenic risk scores and family history(Wiley, 2022) Lai, Dongbing; Johnson, Emma C.; Colbert, Sarah; Pandey, Gayathri; Chan, Grace; Bauer, Lance; Francis, Meredith W.; Hesselbrock, Victor; Kamarajan, Chella; Kramer, John; Kuang, Weipeng; Kuo, Sally; Kuperman, Samuel; Liu, Yunlong; McCutcheon, Vivia; Pang, Zhiping; Plawecki, Martin H.; Schuckit, Marc; Tischfield, Jay; Wetherill, Leah; Zang, Yong; Edenberg, Howard J.; Porjesz, Bernice; Agrawal, Arpana; Foroud, Tatiana; Medical and Molecular Genetics, School of MedicineBackground: Early identification of individuals at high risk for alcohol use disorder (AUD) coupled with prompt interventions could reduce the incidence of AUD. In this study, we investigated whether Polygenic Risk Scores (PRS) can be used to evaluate the risk for AUD and AUD severity (as measured by the number of DSM-5 AUD diagnostic criteria met) and compared their performance with a measure of family history of AUD. Methods: We studied individuals of European ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM-5 diagnostic criteria were available for 7203 individuals, of whom 3451 met criteria for DSM-IV alcohol dependence or DSM-5 AUD and 1616 were alcohol-exposed controls aged ≥21 years with no history of AUD or drug dependence. Further, 4842 individuals had a positive first-degree family history of AUD (FH+), 2722 had an unknown family history (FH?), and 336 had a negative family history (FH-). PRS were derived from a meta-analysis of a genome-wide association study of AUD from the Million Veteran Program and scores from the problem subscale of the Alcohol Use Disorders Identification Test in the UK Biobank. We used mixed models to test the association between PRS and risk for AUD and AUD severity. Results: AUD cases had higher PRS than controls with PRS increasing as the number of DSM-5 diagnostic criteria increased (p-values ≤ 1.85E-05 ) in the full COGA sample, the FH+ subsample, and the FH? subsample. Individuals in the top decile of PRS had odds ratios (OR) for developing AUD of 1.96 (95% CI: 1.54 to 2.51, p-value = 7.57E-08 ) and 1.86 (95% CI: 1.35 to 2.56, p-value = 1.32E-04 ) in the full sample and the FH+ subsample, respectively. These values are comparable to previously reported ORs for a first-degree family history (1.91 to 2.38) estimated from national surveys. PRS were also significantly associated with the DSM-5 AUD diagnostic criterion count in the full sample, the FH+ subsample, and the FH? subsample (p-values ≤6.7E-11 ). PRS remained significantly associated with AUD and AUD severity after accounting for a family history of AUD (p-values ≤6.8E-10 ). Conclusions: Both PRS and family history were associated with AUD and AUD severity, indicating that these risk measures assess distinct aspects of liability to AUD traits.Item Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach(Springer Nature, 2021-03-15) Kinreich, Sivan; McCutcheon, Vivia V.; Aliev, Fazil; Meyers, Jacquelyn L.; Kamarajan, Chella; Pandey, Ashwini K.; Chorlian, David B.; Zhang, Jian; Kuang, Weipeng; Pandey, Gayathri; Subbie-Saenz de. Viteri, Stacey; Francis, Meredith W.; Chan, Grace; Bourdon, Jessica L.; Dick, Danielle M.; Anokhin, Andrey P.; Bauer, Lance; Hesselbrock, Victor; Schuckit, Marc A.; Nurnberger, John I., Jr.; Foroud, Tatiana M.; Salvatore, Jessica E.; Bucholz, Kathleen K.; Porjesz, Bernice; Psychiatry, School of MedicinePredictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.