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Schwaninger G, Forer L, Ebenbichler C, Dieplinger H, Kronenberg F, Zschocke J, Witsch-Baumgartner M. Filling the gap: Genetic risk assessment in hypercholesterolemia using LDL-C and LPA genetic scores. Clin Genet 2023. [PMID: 37417318 DOI: 10.1111/cge.14387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/11/2023] [Accepted: 05/29/2023] [Indexed: 07/08/2023]
Abstract
Routine genetic testing in hypercholesterolemia patients reveals a causative monogenic variant in less than 50% of affected individuals. Incomplete genetic characterization is partly due to polygenic factors influencing low-density-lipoprotein-cholesterol (LDL-C). Additionally, functional variants in the LPA gene affect lipoprotein(a)-associated cholesterol concentrations but are difficult to determine due to the complex structure of the LPA gene. In this study we examined whether complementing standard sequencing with the analysis of genetic scores associated with LDL-C and Lp(a) concentrations improves the diagnostic output in hypercholesterolemia patients. 1.020 individuals including 252 clinically diagnosed hypercholesterolemia patients from the FH Register Austria were analyzed by massive-parallel-sequencing of candidate genes combined with array genotyping, identifying nine novel variants in LDLR. For each individual, validated genetic scores associated with elevated LDL-C and Lp(a) were calculated based on imputed genotypes. Integrating these scores especially the score for Lp(a) increased the proportion of individuals with a clearly defined disease etiology to 68.8% compared to 46.6% in standard genetic testing. The study highlights the major role of Lp(a) in disease etiology in clinically diagnosed hypercholesterolemia patients, of which parts are misclassified. Screening for monogenic causes of hypercholesterolemia and genetic scores for LDL-C and Lp(a) permits more precise diagnosis, allowing individualized treatment.
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Affiliation(s)
- Gunda Schwaninger
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Christoph Ebenbichler
- University Clinic for Internal Medicine I, Medical University of Innsbruck, Innsbruck, Austria
| | - Hans Dieplinger
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Johannes Zschocke
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
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Antoine D, Guéant-Rodriguez RM, Chèvre JC, Hergalant S, Sharma T, Li Z, Rouyer P, Chery C, Halvick S, Bui C, Oussalah A, Ziegler O, Quilliot D, Brunaud L, Guéant JL, Meyre D. Low-frequency Coding Variants Associated With Body Mass Index Affect the Success of Bariatric Surgery. J Clin Endocrinol Metab 2022; 107:e1074-e1084. [PMID: 34718599 DOI: 10.1210/clinem/dgab774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT A recent study identified 14 low-frequency coding variants associated with body mass index (BMI) in 718 734 individuals predominantly of European ancestry. OBJECTIVE We investigated the association of 2 genetic scores (GS) with i) the risk of severe/morbid obesity, ii) BMI variation before weight-loss intervention, iii) BMI change in response to an 18-month lifestyle/behavioral intervention program, and iv) BMI change up to 24 months after bariatric surgery. METHODS The 14 low-frequency coding variants were genotyped or sequenced in 342 French adults with severe/morbid obesity and 574 French adult controls from the general population. We built risk and protective GS based on 6 BMI-increasing and 5 BMI-decreasing low-frequency coding variants that were polymorphic in our study. RESULTS While the risk GS was not associated with severe/morbid obesity status, BMI-decreasing low-frequency coding variants were significantly less frequent in patients with severe/morbid obesity than in French adults from the general population. Neither the risk nor the protective GS was associated with BMI before intervention in patients with severe/morbid obesity, nor did they affect BMI change in response to a lifestyle/behavioral modification program. The protective GS was associated with a greater BMI decrease following bariatric surgery. The risk and protective GS were associated with a higher and lower risk of BMI regain after bariatric surgery. CONCLUSION Our data indicate that in populations of European descent, low-frequency coding variants associated with BMI in the general population also affect the outcomes of bariatric surgery in patients with severe/morbid obesity.
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Affiliation(s)
- Darlène Antoine
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Rosa-Maria Guéant-Rodriguez
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Jean-Claude Chèvre
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Sébastien Hergalant
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Tanmay Sharma
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario L8S 4L8, Canada
| | - Zhen Li
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
- Specialized Obesity Center and Endocrinology, Diabetology, department of Nutrition, Brabois Hospital, CHRU of Nancy, 54500 Vandoeuvre-Les-Nancy, France
| | - Pierre Rouyer
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Céline Chery
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Sarah Halvick
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Catherine Bui
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Abderrahim Oussalah
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - Olivier Ziegler
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
- Specialized Obesity Center and Endocrinology, Diabetology, department of Nutrition, Brabois Hospital, CHRU of Nancy, 54500 Vandoeuvre-Les-Nancy, France
- Department of Surgery, Endocrine and metabolic surgery, Multidisciplinary unit for obesity surgery (CVMC), University Hospital Centre of Nancy, Brabois Hospital, 54500 Nancy, France
| | - Didier Quilliot
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
- Specialized Obesity Center and Endocrinology, Diabetology, department of Nutrition, Brabois Hospital, CHRU of Nancy, 54500 Vandoeuvre-Les-Nancy, France
- Department of Surgery, Endocrine and metabolic surgery, Multidisciplinary unit for obesity surgery (CVMC), University Hospital Centre of Nancy, Brabois Hospital, 54500 Nancy, France
| | - Laurent Brunaud
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
- Department of Surgery, Endocrine and metabolic surgery, Multidisciplinary unit for obesity surgery (CVMC), University Hospital Centre of Nancy, Brabois Hospital, 54500 Nancy, France
| | - Jean-Louis Guéant
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
| | - David Meyre
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, 54500 Nancy, France
- FHU ARRIMAGE, department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, 54500 Nancy, France
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario L8S 4L8, Canada
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Hughes AE, Hayes MG, Egan AM, Patel KA, Scholtens DM, Lowe LP, Lowe WL, Dunne FP, Hattersley AT, Freathy RM. All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes. Wellcome Open Res 2021; 5:175. [PMID: 33869792 PMCID: PMC8030121 DOI: 10.12688/wellcomeopenres.16097.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2021] [Indexed: 11/20/2022] Open
Abstract
Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.
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Affiliation(s)
- Alice E Hughes
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | - M Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic School of Medicine, Rochester, MN, USA
| | - Kashyap A Patel
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | | | - Lynn P Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Fidelma P Dunne
- Galway Diabetes Research Centre and Saolta Hospital Group, National University of Ireland, Galway, Galway, Ireland
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
- National Institute for Health Research Exeter Clinical Research Facility, Exeter, UK
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
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Hughes AE, Hayes MG, Egan AM, Patel KA, Scholtens DM, Lowe LP, Lowe WL, Dunne FP, Hattersley AT, Freathy RM. All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes. Wellcome Open Res 2020; 5:175. [PMID: 33869792 PMCID: PMC8030121.2 DOI: 10.12688/wellcomeopenres.16097.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/13/2020] [Indexed: 04/02/2024] Open
Abstract
Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.
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Affiliation(s)
- Alice E Hughes
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | - M Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aoife M Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic School of Medicine, Rochester, MN, USA
| | - Kashyap A Patel
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | | | - Lynn P Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Fidelma P Dunne
- Galway Diabetes Research Centre and Saolta Hospital Group, National University of Ireland, Galway, Galway, Ireland
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
- National Institute for Health Research Exeter Clinical Research Facility, Exeter, UK
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
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5
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Hughes AE, Hayes MG, Egan AM, Patel KA, Scholtens DM, Lowe LP, Lowe Jr WL, Dunne FP, Hattersley AT, Freathy RM. All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes. Wellcome Open Res 2020; 5:175. [PMID: 33869792 PMCID: PMC8030121 DOI: 10.12688/wellcomeopenres.16097.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2020] [Indexed: 04/02/2024] Open
Abstract
Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.
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Affiliation(s)
- Alice E. Hughes
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | - M. Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Aoife M. Egan
- Division of Endocrinology, Diabetes and Metabolism, Mayo Clinic School of Medicine, Rochester, MN, USA
| | - Kashyap A. Patel
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
| | | | - Lynn P. Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Fidelma P. Dunne
- Galway Diabetes Research Centre and Saolta Hospital Group, National University of Ireland, Galway, Galway, Ireland
| | - Andrew T. Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
- Royal Devon and Exeter Hospitals NHS Foundation Trust, Exeter, UK
- National Institute for Health Research Exeter Clinical Research Facility, Exeter, UK
| | - Rachel M. Freathy
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, UK
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Uhl GR, Walther D, Musci R, Fisher C, Anthony JC, Storr CL, Behm FM, Eaton WW, Ialongo N, Rose JE. Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances. Mol Psychiatry 2014; 19:50-4. [PMID: 23128154 PMCID: PMC3922203 DOI: 10.1038/mp.2012.155] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2012] [Revised: 09/06/2012] [Accepted: 09/07/2012] [Indexed: 11/11/2022]
Abstract
Genotype scores that predict relevant clinical outcomes may detect other disease features and help direct prevention efforts. We report data that validate a previously established v1.0 smoking cessation quit success genotype score and describe striking differences in the score in individuals who display differing developmental trajectories of use of common addictive substances. In a cessation study, v1.0 genotype scores predicted ability to quit with P=0.00056 and area under receiver-operating characteristic curve 0.66. About 43% vs 13% quit in the upper vs lower genotype score terciles. Latent class growth analyses of a developmentally assessed sample identified three latent classes based on substance use. Higher v1.0 scores were associated with (a) higher probabilities of participant membership in a latent class that displayed low use of common addictive substances during adolescence (P=0.0004) and (b) lower probabilities of membership in a class that reported escalating use (P=0.001). These results indicate that: (a) we have identified genetic predictors of smoking cessation success, (b) genetic influences on quit success overlap with those that influence the rate at which addictive substance use is taken up during adolescence and (c) individuals at genetic risk for both escalating use of addictive substances and poor abilities to quit may provide especially urgent focus for prevention efforts.
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Affiliation(s)
- George R Uhl
- Molecular Neurobiology Branch, NIH-IRP, NIDA, Baltimore, Maryland 21224,Corresponding Author: George Uhl, Molecular Neurobiology, Box 5180, Baltimore, MD 21224, phone: (443) 740-2799, fax: (443) 740-2122, (GRU)
| | - Donna Walther
- Molecular Neurobiology Branch, NIH-IRP, NIDA, Baltimore, Maryland 21224
| | - Rashelle Musci
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21221
| | - Christian Fisher
- Molecular Neurobiology Branch, NIH-IRP, NIDA, Baltimore, Maryland 21224
| | - James C Anthony
- Dept of Epidemiology, Michigan State University, East Lansing, MI 48824
| | - Carla L Storr
- Department of Family and Community Health, University of Maryland School of Nursing, Baltimore, MD 21201,Dept of Psychiatry and Center for Nicotine and Smoking Cessation Research, Duke University, Durham NC 27705
| | - Frederique M. Behm
- Dept of Psychiatry and Center for Nicotine and Smoking Cessation Research, Duke University, Durham NC 27705
| | - William W Eaton
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21221
| | - Nicholas Ialongo
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21221
| | - Jed E. Rose
- Dept of Psychiatry and Center for Nicotine and Smoking Cessation Research, Duke University, Durham NC 27705
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