Browsing by Author "Justice, Amy C."

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    Association Between Depressive Disorders and Incident Acute Myocardial Infarction in Human Immunodeficiency Virus–Infected Adults
    (American Medical Association, 2016-11-01) Khambaty, Tasneem; Stewart, Jesse C.; Gupta, Samir K.; Chang, Chung-Chou H.; Bedimo, Roger J.; Budoff, Matthew J.; Butt, Adeel A.; Crane, Heidi; Gibert, Cynthia L.; Leaf, David A.; Rimland, David; Tindle, Hilary A.; So-Armah, Kaku A.; Justice, Amy C.; Freiberg, Matthew S.; Psychology, School of Science
    IMPORTANCE With the advent of highly effective antiretroviral therapy and improved survival, human immunodeficiency virus (HIV)–infected people are living longer and are now at an increased risk for cardiovascular disease (CVD). There is an urgent need to identify novel risk factors and primary prevention approaches for CVD in HIV. Although depression is prevalent in HIV-infected adults and is associated with future CVD in the general population, its association with CVD events has not been examined in the HIV-infected population. OBJECTIVE To examine whether depressive disorders are prospectively associated with incident acute myocardial infarction (AMI) in a large cohort of adults with HIV. DESIGN, SETTING, AND PARTICIPANTS Included in this cohort study were 26 144 HIV-infected veterans without CVD at baseline (1998–2003) participating in the US Department of Veterans Affairs Veterans Aging Cohort Study from April 1, 2003, through December 31, 2009. At baseline, 4853 veterans (19%) with major depressive disorder (MDD; International Classification of Diseases, Ninth Revision [ICD-9] codes 296.2 and 296.3) and 2296 (9%) with dysthymic disorder (ICD-9 code 300.4) were identified. The current analysis was conducted from January 2015 to November 2015. MAIN OUTCOMES AND MEASURES Incident AMI (defined by discharge summary documentation, enzyme/electrocardiography evidence of AMI, inpatient ICD-9 code for AMI (410), or AMI as underlying cause of death [International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code 121]) between the enrollment date and December 31, 2009. RESULTS The mean (SD) age of those with MDD was 47.3 (7.9) years and for those without MDD was 48.2 (9.7) years. During 5.8 years of follow-up, 490 AMI events (1.9%) occurred. Baseline MDD was associated with incident AMI after adjusting for demographics (hazard ratio [HR], 1.31; 95% CI, 1.05–1.62), CVD risk factors (HR, 1.29; 95% CI, 1.04–1.60), and HIV-specific factors (HR, 1.30; 95% CI, 1.05–1.62). Further adjustment for hepatitis C, renal disease, substance abuse, and hemoglobin level (HR, 1.25; 95% CI, 1.00–1.56) and antidepressant use (HR, 1.12; 95% CI, 0.87–1.42) attenuated associations. Baseline dysthymic disorder was not associated with incident AMI. CONCLUSIONS AND RELEVANCE We report novel evidence that HIV-infected adults with MDD have a 30% increased risk for AMI than HIV-infected adults without MDD after adjustment for many potential confounders. Our findings raise the possibility that MDD may be independently associated with incident atherosclerotic CVD in the HIV-infected population.
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    Candidate Genes from an FDA-Approved Algorithm Fail to Predict Opioid Use Disorder Risk in Over 450,000 Veterans
    (medRxiv, 2024-05-16) Davis, Christal N.; Jinwala, Zeal; Hatoum, Alexander S.; Toikumo, Sylvanus; Agrawal, Arpana; Rentsch, Christopher T.; Edenberg, Howard J.; Baurley, James W.; Hartwell, Emily E.; Crist, Richard C.; Gray, Joshua C.; Justice, Amy C.; Gelernter, Joel; Kember, Rachel L.; Kranzler, Henry R.; Biochemistry and Molecular Biology, School of Medicine
    Importance: Recently, the Food and Drug Administration gave pre-marketing approval to algorithm based on its purported ability to identify genetic risk for opioid use disorder. However, the clinical utility of the candidate genes comprising the algorithm has not been independently demonstrated. Objective: To assess the utility of 15 variants in candidate genes from an algorithm intended to predict opioid use disorder risk. Design: This case-control study examined the association of 15 candidate genetic variants with risk of opioid use disorder using available electronic health record data from December 20, 1992 to September 30, 2022. Setting: Electronic health record data, including pharmacy records, from Million Veteran Program participants across the United States. Participants: Participants were opioid-exposed individuals enrolled in the Million Veteran Program (n = 452,664). Opioid use disorder cases were identified using International Classification of Disease diagnostic codes, and controls were individuals with no opioid use disorder diagnosis. Exposures: Number of risk alleles present across 15 candidate genetic variants. Main outcome and measures: Predictive performance of 15 genetic variants for opioid use disorder risk assessed via logistic regression and machine learning models. Results: Opioid exposed individuals (n=33,669 cases) were on average 61.15 (SD = 13.37) years old, 90.46% male, and had varied genetic similarity to global reference panels. Collectively, the 15 candidate genetic variants accounted for 0.4% of variation in opioid use disorder risk. The accuracy of the ensemble machine learning model using the 15 genes as predictors was 52.8% (95% CI = 52.1 - 53.6%) in an independent testing sample. Conclusions and relevance: Candidate genes that comprise the approved algorithm do not meet reasonable standards of efficacy in predicting opioid use disorder risk. Given the algorithm's limited predictive accuracy, its use in clinical care would lead to high rates of false positive and negative findings. More clinically useful models are needed to identify individuals at risk of developing opioid use disorder.
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    Delayed presentation of HIV among older individuals: a growing problem
    (Elsevier, 2022) Justice, Amy C.; Goetz, Matthew B.; Stewart, Cameron N.; Hogan, Brenna C.; Humes, Elizabeth; Luz, Paula M.; Castilho, Jessica L.; Nash, Denis; Brazier, Ellen; Musick, Beverly; Yiannoutsos, Constantin; Malateste, Karen; Jaquet, Antoine; Cornell, Morna; Shamu, Tinei; Rajasuriar, Reena; Jiamsakul, Awachana; Althoff, Keri N.; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Late presentation for care is a major impediment to the prevention and effective treatment of HIV infection. Older individuals are at increased risk of late presentation, represent a growing proportion of people with late presentation, and might require interventions tailored to their age group. We provide a summary of the literature published globally between 2016-21 (reporting data from 1984-2018) and quantify the association of age with delayed presentation. Using the most common definitions of late presentation and older age from these earlier studies, we update this work with data from the International Epidemiology Databases to Evaluate AIDS (IeDEA) consortium, focusing on data from 2000-19, encompassing four continents. Finally, we consider how late presentation among older individuals might be more effectively addressed as electronic medical records become widely adopted.
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    Depression and HIV Infection are Risk Factors for Incident Heart Failure Among Veterans: Veterans Aging Cohort Study.
    (AHA, 2015-10-27) White, Jessica R.; Chang, Chung-Chou H.; So-Armah, Kaku A.; Stewart, Jesse C.; Gupta, Samir Kumar; Butt, Adeel A.; Gibert, Cynthia L.; Rimland, David; Rodriguez-Barradas, Maria C.; Leaf, David A.; Bedimo, Roger J.; Gottdiener, John S.; Kop, Willem J.; Gottlieb, Stephen S.; Budoff, Matthew J.; Khambaty, Tasneem; Tindle, Hilary; Justice, Amy C.; Freiberg, Matthew S.; Department of Psychology, School of Science
    Background: Both HIV and depression are associated with increased heart failure (HF) risk. Depression, a common comorbidity, may further increase the risk of HF among HIV+ adults. We assessed the association between HIV, depression and incident HF. Methods and Results: Veterans Aging Cohort Study (VACS) participants free from cardiovascular disease at baseline (N = 81,427; 26,908 HIV+, 54,519
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    Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci
    (Springer, 2022-10) Deak, Joseph D.; Zhou, Hang; Galimberti, Marco; Levey, Daniel F.; Wendt, Frank R.; Sanchez-Roige, Sandra; Hatoum, Alexander S.; Johnson, Emma C.; Nunez, Yaira Z.; Demontis, Ditte; Børglum, Anders D.; Rajagopal, Veera M.; Jennings, Mariela V.; Kember, Rachel L.; Justice, Amy C.; Edenberg, Howard J.; Agrawal, Arpana; Polimanti, Renato; Kranzler, Henry R.; Gelernter, Joel; Biochemistry and Molecular Biology, School of Medicine
    Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10−8) lead SNPs—one at FURIN (rs11372849; p = 9.54 × 10−10) and two OPRM1 variants (rs1799971, p = 4.92 × 10−09; rs79704991, p = 1.11 × 10−08; r2 = 0.02). Rs1799971 (p = 4.91 × 10−08) and another OPRM1 variant (rs9478500; p = 1.95 × 10−08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10−47) and AUD (rg = 0.77; p = 6.36 × 10−78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10−16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10−13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.
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    Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
    (Nature, 2020-07) Zhou, Hang; Sealock, Julia M.; Sanchez-Roige, Sandra; Clarke, Toni-Kim; Levey, Daniel F.; Cheng, Zhongshan; Li, Boyang; Polimanti, Renato; Kember, Rachel L.; Smith, Rachel Vickers; Thygesen, Johan H.; Morgan, Marsha Y.; Atkinson, Stephen R.; Thursz, Mark R.; Nyegaard, Mette; Mattheisen, Manuel; Børglum, Anders D.; Johnson, Emma C.; Justice, Amy C.; Palmer, Abraham A.; McQuillin, Andrew; Davis, Lea K.; Edenberg, Howard J.; Agrawal, Arpana; Kranzler, Henry R.; Gelernter, Joel; Medical and Molecular Genetics, School of Medicine
    Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.
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    Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals
    (Springer Nature, 2023) Zhou, Hang; Kember, Rachel L.; Deak, Joseph D.; Xu, Heng; Toikumo, Sylvanus; Yuan, Kai; Lind, Penelope A.; Farajzadeh, Leila; Wang, Lu; Hatoum, Alexander S.; Johnson, Jessica; Lee, Hyunjoon; Mallard, Travis T.; Xu, Jiayi; Johnston, Keira J. A.; Johnson, Emma C.; Galimberti, Marco; Dao, Cecilia; Levey, Daniel F.; Overstreet, Cassie; Byrne, Enda M.; Gillespie, Nathan A.; Gordon, Scott; Hickie, Ian B.; Whitfield, John B.; Xu, Ke; Zhao, Hongyu; Huckins, Laura M.; Davis, Lea K.; Sanchez-Roige, Sandra; Madden, Pamela A. F.; Heath, Andrew C.; Medland, Sarah E.; Martin, Nicholas G.; Ge, Tian; Smoller, Jordan W.; Hougaard, David M.; Børglum, Anders D.; Demontis, Ditte; Krystal, John H.; Gaziano, J. Michael; Edenberg, Howard J.; Agrawal, Arpana; Million Veteran Program; Justice, Amy C.; Stein, Murray B.; Kranzler, Henry R.; Gelernter, Joel; Biochemistry and Molecular Biology, School of Medicine
    Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.