Showing papers by "Nancy L. Saccone published in 2018"
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Stanford University1, Columbia University2, University of North Carolina at Chapel Hill3, Emory University4, Virginia Commonwealth University5, Duke University6, Veterans Health Administration7, Washington University in St. Louis8, Cardiff University9, Harvard University10, University of Cape Town11, Boston University12, Yale University13, Research Triangle Park14, University of Michigan15, Groote Schuur Hospital16, University of Pennsylvania17, VA Boston Healthcare System18, University of California, San Diego19, Broad Institute20, Rhode Island Hospital21, Charité22, Columbia University Medical Center23, University of Illinois at Urbana–Champaign24, Uniformed Services University of the Health Sciences25, Icahn School of Medicine at Mount Sinai26, McLean Hospital27
TL;DR: The results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples.
Abstract: The Psychiatric Genomics Consortium-Posttraumatic Stress Disorder group (PGC-PTSD) combined genome-wide case–control molecular genetic data across 11 multiethnic studies to quantify PTSD heritability, to examine potential shared genetic risk with schizophrenia, bipolar disorder, and major depressive disorder and to identify risk loci for PTSD. Examining 20 730 individuals, we report a molecular genetics-based heritability estimate (h2SNP) for European-American females of 29% that is similar to h2SNP for schizophrenia and is substantially higher than h2SNP in European-American males (estimate not distinguishable from zero). We found strong evidence of overlapping genetic risk between PTSD and schizophrenia along with more modest evidence of overlap with bipolar and major depressive disorder. No single-nucleotide polymorphisms (SNPs) exceeded genome-wide significance in the transethnic (overall) meta-analysis and we do not replicate previously reported associations. Still, SNP-level summary statistics made available here afford the best-available molecular genetic index of PTSD—for both European- and African-American individuals—and can be used in polygenic risk prediction and genetic correlation studies of diverse phenotypes. Publication of summary statistics for ∼10 000 African Americans contributes to the broader goal of increased ancestral diversity in genomic data resources. In sum, the results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples. As has been the case with schizophrenia and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.
363 citations
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Washington University in St. Louis1, Australian National University2, Heidelberg University3, University of Michigan4, Flinders University5, Paris Diderot University6, King's College London7, Office of Population Research8, French Institute of Health and Medical Research9, University of Montpellier10, University of Otago11, Hungarian Academy of Sciences12, University of Sussex13, University of Bologna14, VU University Amsterdam15, University of Adelaide16, University of London17, University of Oxford18, University of Queensland19, University of New England (Australia)20, University of Pennsylvania21, Georgetown University22, National and Kapodistrian University of Athens23, Roy J. and Lucille A. Carver College of Medicine24, University of Basel25, Greifswald University Hospital26, University Medical Center Groningen27, Semmelweis University28, VU University Medical Center29, Michigan State University30, University of Cambridge31, Icahn School of Medicine at Mount Sinai32, University of Manchester33, University of Münster34, Uppsala University35, Research Triangle Park36, QIMR Berghofer Medical Research Institute37, University of Bristol38, Deakin University39, Charité40, University of Melbourne41, University of Molise42, University of California, San Francisco43, Indiana University44
TL;DR: If an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.
Abstract: The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.
258 citations
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Research Triangle Park1, deCODE genetics2, Anschutz Medical Campus3, Boston University4, University of Helsinki5, VU University Amsterdam6, Dartmouth College7, University of Iceland8, National Institutes of Health9, West Virginia University10, Washington University in St. Louis11, Radboud University Nijmegen12, Virginia Commonwealth University13, University of Pennsylvania14, Veterans Health Administration15, International Agency for Research on Cancer16, Lunenfeld-Tanenbaum Research Institute17, University of Pittsburgh18, University of Wisconsin-Madison19
TL;DR: The well-known CHRNA5-CHRNA3-CHRNB4 genes were reconfirmed and a novel association in the DNA methyltransferase gene DNMT3B yielded, which highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.
Abstract: Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency=44–77%) was associated with increased risk of nicotine dependence at P=3.7 × 10−8 (odds ratio (OR)=1.06 and 95% confidence interval (CI)=1.04–1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N=48,931) using heavy vs never smoking as a proxy phenotype (P=3.6 × 10−4, OR=1.05, and 95% CI=1.02–1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N=60,586, meta-analysis P=0.0095, OR=1.05, and 95% CI=1.01–1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N=166, P=2.3 × 10−26) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N=103, P=3.0 × 10−6) and the independent Brain eQTL Almanac (N=134, P=0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.
127 citations
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Caroline M. Nievergelt1, Caroline M. Nievergelt2, Adam X. Maihofer2, Adam X. Maihofer1 +215 more•Institutions (53)
TL;DR: This largest GWAS meta-analysis of PTSD to date identifies a total of 6 genome-wide significant loci, 4 in European and 2 in African-ancestry analyses, and shows evidence that some of these loci may be specific to PTSD.
Abstract: Post-traumatic stress disorder (PTSD) is a common and debilitating disorder. The risk of PTSD following trauma is heritable, but robust common variants have yet to be identified by genome-wide association studies (GWAS). We have collected a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls. We first demonstrate significant genetic correlations across 60 PTSD cohorts to evaluate the comparability of these phenotypically heterogeneous studies. In this largest GWAS meta-analysis of PTSD to date we identify a total of 6 genome-wide significant loci, 4 in European and 2 in African-ancestry analyses. Follow-up analyses incorporated local ancestry and sex-specific effects, and functional studies. Along with other novel genes, a non-coding RNA (ncRNA) and a Parkinson’s Disease gene, PARK2, were associated with PTSD. Consistent with previous reports, SNP-based heritability estimates for PTSD range between 10-20%. Despite a significant shared liability between PTSD and major depressive disorder, we show evidence that some of our loci may be specific to PTSD. These results demonstrate the role of genetic variation contributing to the biology of differential risk for PTSD and the necessity of expanding GWAS beyond European ancestry.
26 citations
01 Jan 2018
TL;DR: In this paper, the authors performed new analyses on 31 data sets containing 38,802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results.
Abstract: The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.
18 citations
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TL;DR: The goal is to encourage and provide support for treatment researchers to consider biosample collection and genotyping their existing samples as well as integrating genetic analyses into their study design in order to realize precision medicine in treatment of nicotine dependence.
Abstract: Implications This article outlines a framework for the consistent integration of biological data/samples into smoking cessation pharmacotherapy trials, aligned with the objectives of the recently unveiled Precision Medicine Initiative. Our goal is to encourage and provide support for treatment researchers to consider biosample collection and genotyping their existing samples as well as integrating genetic analyses into their study design in order to realize precision medicine in treatment of nicotine dependence.
16 citations
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TL;DR: In this paper, the authors reviewed several compelling genetic and biomarker findings related to smoking cessation and treatment and provided practical guidance on how to incorporate biosample collection into a planned clinical trial and discussed avenues for harmonizing data and fostering consortium-based collaborative research on the pharmacogenomics of smoking cessation.
Abstract: Introduction Human genetic research has succeeded in definitively identifying multiple genetic variants associated with risk for nicotine dependence and heavy smoking. To build on these advances, and to aid in reducing the prevalence of smoking and its consequent health harms, the next frontier is to identify genetic predictors of successful smoking cessation and also of the efficacy of smoking cessation treatments ("pharmacogenomics"). More broadly, additional biomarkers that can be quantified from biosamples also promise to aid "Precision Medicine" and the personalization of treatment, both pharmacological and behavioral. Aims and methods To motivate ongoing and future efforts, here we review several compelling genetic and biomarker findings related to smoking cessation and treatment. Results These Key results involve genetic variants in the nicotinic receptor subunit gene CHRNA5, variants in the nicotine metabolism gene CYP2A6, and the nicotine metabolite ratio. We also summarize reports of epigenetic changes related to smoking behavior. Conclusions The results to date demonstrate the value and utility of data generated from biosamples in clinical treatment trial settings. This article cross-references a companion paper in this issue that provides practical guidance on how to incorporate biosample collection into a planned clinical trial and discusses avenues for harmonizing data and fostering consortium-based, collaborative research on the pharmacogenomics of smoking cessation. Implications Evidence is emerging that certain genotypes and biomarkers are associated with smoking cessation success and efficacy of smoking cessation treatments. We review key findings that open potential avenues for personalizing smoking cessation treatment according to an individual's genetic or metabolic profile. These results provide important incentive for smoking cessation researchers to collect biosamples and perform genotyping in research studies and clinical trials.
16 citations
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TL;DR: Results suggest that nicotine metabolism PRSs based on GWAS meta-analyses predict an individual's nicotine metabolism, so does use of the top hit variant.
Abstract: Aim This study tests whether polygenic risk scores (PRSs) for nicotine metabolism predict smoking behaviors in independent data. Materials & methods Linear regression, logistic regression and survival analyses were used to analyze nicotine metabolism PRSs and nicotine metabolism, smoking quantity and smoking cessation. Results Nicotine metabolism PRSs based on two genome wide association studies (GWAS) meta-analyses significantly predicted nicotine metabolism biomarkers (R2 range: 9.2-16%; minimum p = 7.6 × 10-8). The GWAS top hit variant rs56113850 significantly predicted nicotine metabolism biomarkers (R2 range: 14-17%; minimum p = 4.4 × 10-8). There was insufficient evidence for these PRSs predicting smoking quantity and smoking cessation. Conclusion Results suggest that nicotine metabolism PRSs based on GWAS meta-analyses predict an individual's nicotine metabolism, so does use of the top hit variant. We anticipate that PRSs will enter clinical medicine, but additional research is needed to develop a more comprehensive genetic score to predict smoking behaviors.
15 citations
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15 citations
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TL;DR: The readiness to incorporate smoking-related genomic applications in real-world settings is informed and cross-disciplinary collaboration to accelerate the integration of evidence-based genomics in behavioral medicine is facilitated.
Abstract: The incorporation of genomic information into routine care settings is a burgeoning area for investigation in behavioral medicine. The past decade has witnessed rapid advancements in knowledge of genetic biomarkers associated with smoking behaviors and tobacco-related morbidity and mortality, providing the basis for promising genomic applications in clinical and community settings. We assessed the current state of readiness for implementing genomic applications involving variation in the α5 nicotinic cholinergic receptor subunit gene CHRNA5 and smoking outcomes (behaviors and related diseases) using a process that could be translatable to a wide range of genomic applications in behavioral medicine. We reviewed the scientific literature involving CHRNA5 genetic variation and smoking cessation, and then summarized and synthesized a chain of evidence according to analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications (ACCE), a well-established set of criteria used to evaluate genomic applications. Our review identified at least three specific genomic applications for which implementation may be considered, including the use of CHRNA5 genetic test results for informing disease risk, optimizing smoking cessation treatment, and motivating smoking behavior change. For these genomic applications, we rated analytic validity as convincing, clinical validity as adequate, and clinical utility and ethical, legal, and social implications as inadequate. For clinical genomic applications involving CHRNA5 variation and smoking outcomes, research efforts now need to focus on establishing clinical utility. This approach is compatible with pre-implementation research, which is also needed to accelerate translation, improve innovation design, and understand and refine system processes involved in implementation. This study informs the readiness to incorporate smoking-related genomic applications in real-world settings and facilitates cross-disciplinary collaboration to accelerate the integration of evidence-based genomics in behavioral medicine.
12 citations
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TL;DR: Findings suggest that possible FTND non-invariance that occurs across study samples of various birth years has a negligible impact on study results.