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Browsing by Author "Tindle, Hilary A."
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Item 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 ScienceIMPORTANCE 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.Item Contribution of Behavioral Health Factors to Non-AIDS-Related Comorbidities: an Updated Review(SpringerLink, 2020-08) Chichetto, Natalie E.; Polanka, Brittanny M.; So-Armah, Kaku A.; Sung, Minhee; Stewart, Jesse C.; Koethe, John R.; Edelman, E. Jennifer; Tindle, Hilary A.; Freiberg, Matthew S.; Psychology, School of SciencePurpose of review: We summarize recent literature on the contribution of substance use and depression to non-AIDS-related comorbidities. Discussion of recent randomized clinical trials and implementation research to curtail risk attributed to each behavioral health issue is provided. Recent findings: Smoking, unhealthy alcohol use, opioid use, and depression are common among PWH and individually contribute to increased risk for non-AIDS-related comorbidities. The concurrence of these conditions is notable, yet understudied, and provides opportunity for linked-screening and potential treatment of more than one behavioral health factor. Current results from randomized clinical trials are inconsistent. Investigating interventions to reduce the impact of these behavioral health conditions with a focus on implementation into clinical care is important. Non-AIDS-defining cancers, cardiovascular disease, liver disease, and diabetes are leading causes of morbidity in people with HIV. Behavioral health factors including substance use and mental health issues, often co-occurring, likely contribute to the excess risk of non-AIDS-related comorbidities.Item Depression as a Risk Factor for Incident Ischemic Stroke Among HIV‐Positive Veterans in the Veterans Aging Cohort Study(American Heart Association, 2021-07-06) Sico, Jason J.; Kundu, Suman; So-Armah, Kaku; Gupta, Samir K.; Chang, Chung-Chou H.; Butt, Adeel A.; Gibert, Cynthia L.; Marconi, Vincent C.; Crystal, Stephen; Tindle, Hilary A.; Freiberg, Matthew S.; Stewart, Jesse C.; Medicine, School of MedicineBackground: HIV infection and depression are each associated with increased ischemic stroke risk. Whether depression is a risk factor for stroke within the HIV population is unknown. Methods and Results: We analyzed data on 106 333 (33 528 HIV-positive; 72 805 HIV-negative) people who were free of baseline cardiovascular disease from an observational cohort of HIV-positive people and matched uninfected veterans in care from April 1, 2003 through December 31, 2014. International Classification of Diseases, Ninth Revision (ICD-9) codes from medical records were used to determine baseline depression and incident stroke. Depression occurred in 19.5% of HIV-positive people. After a median of 9.2 years of follow-up, stroke rates were highest among people with both HIV and depression and lowest among those with neither condition. In Cox proportional hazard models, depression was associated with an increased risk of stroke for HIV-positive people after adjusting for sociodemographic characteristics and cerebrovascular risk factors (hazard ratio [HR], 1.18; 95% CI: 1.03-1.34; 0.014). The depression-stroke relationship was attenuated by alcohol use disorders, cocaine use, and baseline antidepressant use, and unaffected by combined antiretroviral therapy use or individual antiretroviral agents. A numerically higher HR of depression on stroke was found among those younger than 60 years. Conclusions: Depression is associated with an increased risk of stroke among HIV-positive people after adjusting for sociodemographic characteristics, traditional cerebrovascular risk factors, and HIV-specific factors. Alcohol use disorders, cocaine use, and baseline antidepressant use accounted for some of the observed stroke risk. Depression may be a novel, independent risk factor for ischemic stroke in HIV, particularly among younger people.Item Exome chip meta-analysis fine maps causal variants and elucidates the genetic architecture of rare coding variants in smoking and alcohol use(Elsevier, 2018) Brazel, David M.; Jiang, Yu; Hughey, Jordan M.; Turcot, Valérie; Zhan, Xiaowei; Gong, Jian; Batini, Chiara; Weissenkampen, J. Dylan; Liu, MengZhen; Barnes, Daniel R.; Bertelsen, Sarah; Chou, Yi-Ling; Erzurumluoglu, A. Mesut; Faul, Jessica D.; Haessler, Jeff; Hammerschlag, Anke R.; Hsu, Chris; Kapoor, Manav; Lai, Dongbing; Le, Nhung; de Leeuw, Christiaan A.; Loukola, Anu; Mangino, Massimo; Melbourne, Carl A.; Pistis, Giorgio; Qaiser, Beenish; Rohde, Rebecca; Shao, Yaming; Stringham, Heather; Wetherill, Leah; Zhao, Wei; Agrawal, Arpana; Bierut, Laura; Chen, Chu; Eaton, Charles B.; Goate, Alison; Haiman, Christopher; Heath, Andrew; Iacono, William G.; Martin, Nicholas G.; Polderman, Tinca J.; Reiner, Alex; Rice, John; Schlessinger, David; Scholte, H. Steven; Smith, Jennifer A.; Tardif, Jean-Claude; Tindle, Hilary A.; van der Leij, Andries R.; Boehnke, Michael; Chang-Claude, Jenny; Cucca, Francesco; David, Sean P.; Foroud, Tatiana; Howson, Joanna M. M.; Kardia, Sharon L. R.; Kooperberg, Charles; Laakso, Markku; Lettre, Guillaume; Madden, Pamela; McGue, Matt; North, Kari; Posthuma, Danielle; Spector, Timothy; Stram, Daniel; Tobin, Martin D.; Weir, David R.; Kaprio, Jaakko; Abecasis, Gonçalo R.; Liu, Dajiang J.; Vrieze, Scott; Medical and Molecular Genetics, School of MedicineBackground Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences, and contribute to disease risk. Methods We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss of function coding variants. We performed a novel fine mapping analysis to winnow the number of putative causal variants within associated loci. Results Meta-analytic sample sizes ranged from 152,348-433,216, depending on the phenotype. Rare coding variation explained 1.1-2.2% of phenotypic variance, reflecting 11%-18% of the total SNP heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between 3 and 10 variants for 65 loci. 20 loci contained rare coding variants in the 95% credible intervals. Conclusions Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine mapping GWAS loci identifies specific variants contributing to the biological etiology of substance use behavior.Item Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci(Springer Nature, 2019-01-07) Erzurumluoglu, A. Mesut; Liu, Mengzhen; Jackson, Victoria E.; Barnes, Daniel R.; Datta, Gargi; Melbourne, Carl A.; Young, Robin; Batini, Chiara; Surendran, Praveen; Jiang, Tao; Adnan, Sheikh Daud; Afaq, Saima; Agrawal, Arpana; Altmaier, Elisabeth; Antoniou, Antonis C.; Asselbergs, Folkert W.; Baumbach, Clemens; Bierut, Laura; Bertelsen, Sarah; Boehnke, Michael; Bots, Michiel L.; Brazel, David M.; Chambers, John C.; Chang-Claude, Jenny; Chen, Chu; Corley, Janie; Chou, Yi-Ling; David, Sean P.; Boer, Rudolf A. de; Leeuw, Christiaan A. de; Dennis, Joe G.; Dominiczak, Anna F.; Dunning, Alison M.; Easton, Douglas F.; Eaton, Charles; Elliott, Paul; Evangelou, Evangelos; Faul, Jessica D.; Foroud, Tatiana; Goate, Alison; Gong, Jian; Grabe, Hans J.; Haessler, Jeff; Haiman, Christopher; Hallmans, Göran; Hammerschlag, Anke R.; Harris, Sarah E.; Hattersley, Andrew; Heath, Andrew; Hsu, Chris; Iacono, William G.; Kanoni, Stavroula; Kapoor, Manav; Kaprio, Jaakko; Kardia, Sharon L.; Karpe, Fredrik; Kontto, Jukka; Kooner, Jaspal S.; Kooperberg, Charles; Kuulasmaa, Kari; Laakso, Markku; Lai, Dongbing; Langenberg, Claudia; Le, Nhung; Lettre, Guillaume; Loukola, Anu; Luan, Jian’an; Madden, Pamela A. F.; Mangino, Massimo; Marioni, Riccardo E.; Marouli, Eirini; Marten, Jonathan; Martin, Nicholas G.; McGue, Matt; Michailidou, Kyriaki; Mihailov, Evelin; Moayyeri, Alireza; Moitry, Marie; Müller-Nurasyid, Martina; Naheed, Aliya; Nauck, Matthias; Neville, Matthew J.; Nielsen, Sune Fallgaard; North, Kari; Perola, Markus; Pharoah, Paul D. P.; Pistis, Giorgio; Polderman, Tinca J.; Posthuma, Danielle; Poulter, Neil; Qaiser, Beenish; Rasheed, Asif; Reiner, Alex; Renström, Frida; Rice, John; Rohde, Rebecca; Rolandsson, Olov; Samani, Nilesh J.; Samuel, Maria; Schlessinger, David; Scholte, Steven H.; Scott, Robert A.; Sever, Peter; Shao, Yaming; Shrine, Nick; Smith, Jennifer A.; Starr, John M.; Stirrups, Kathleen; Stram, Danielle; Stringham, Heather M.; Tachmazidou, Ioanna; Tardif, Jean-Claude; Thompson, Deborah J.; Tindle, Hilary A.; Tragante, Vinicius; Trompet, Stella; Turcot, Valerie; Tyrrell, Jessica; Vaartjes, Ilonca; Leij, Andries R. van der; Meer, Peter van der; Varga, Tibor V.; Verweij, Niek; Völzke, Henry; Wareham, Nicholas J.; Warren, Helen R.; Weir, David R.; Weiss, Stefan; Wetherill, Leah; Yaghootkar, Hanieh; Yavas, Ersin; Jiang, Yu; Chen, Fang; Zhan, Xiaowei; Zhang, Weihua; Zhao, Wei; Zhao, Wei; Zhou, Kaixin; Amouyel, Philippe; Blankenberg, Stefan; Caulfield, Mark J.; Chowdhury, Rajiv; Cucca, Francesco; Deary, Ian J.; Deloukas, Panos; Angelantonio, Emanuele Di; Ferrario, Marco; Ferrières, Jean; Franks, Paul W.; Frayling, Tim M.; Frossard, Philippe; Hall, Ian P.; Hayward, Caroline; Jansson, Jan-Håkan; Jukema, J. Wouter; Kee, Frank; Männistö, Satu; Metspalu, Andres; Munroe, Patricia B.; Nordestgaard, Børge Grønne; Palmer, Colin N. A.; Salomaa, Veikko; Sattar, Naveed; Spector, Timothy; Strachan, David Peter; Harst, Pim van der; Zeggini, Eleftheria; Saleheen, Danish; Butterworth, Adam S.; Wain, Louise V.; Abecasis, Goncalo R.; Danesh, John; Tobin, Martin D.; Vrieze, Scott; Liu, Dajiang J.; Howson, Joanna M. M.; Medical and Molecular Genetics, School of MedicineSmoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10−8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10−8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10−3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.