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Vol. 75, No. 2-4, 2013
Issue release date: September 2013
Section title:  
Free Access
Hum Hered 2013;75:136-143
(DOI:10.1159/000353953)

Identification of Pleiotropic Genetic Effects on Obesity and Brain Anatomy

Curran J.E.a · McKay D.R.e, f · Winkler A.M.e,f,h · Olvera R.L.b · Carless M.A.a · Dyer T.D.a · Kent Jr. J.W.a · Kochunov P.g · Sprooten E.e, f · Knowles E.E.e, f · Comuzzie A.G.a · Fox P.T.c, d · Almasy L.a · Duggirala R.a · Blangero J.a · Glahn D.C.e, f
aDepartment of Genetics, Texas Biomedical Research Institute, bDepartment of Psychiatry, and cResearch Imaging Institute, University of Texas Health Science Center San Antonio, and dSouth Texas Veterans Health System, San Antonio, Tex., eOlin Neuropsychiatry Research Center, Institute of Living, Hartford, Conn., fDepartment of Psychiatry, Yale University School of Medicine, New Haven, Conn., and gDepartment of Psychiatry and Maryland Psychiatric Research Center, University of Maryland, Catonsville, Md., USA; hCentre for Functional MRI of the Brain, University of Oxford, Oxford, UK
email Corresponding Author

Abstract

Background/Aims: Obesity is a major contributor to the global burden of chronic disease and disability, though current knowledge of causal biologic underpinnings is lacking. Through the regulation of energy homeostasis and interactions with adiposity and gut signals, the brain is thought to play a significant role in the development of this disorder. While neuroanatomical variation has been associated with obesity, it is unclear if this relationship is influenced by common genetic mechanisms. In this study, we sought genetic components that influence both brain anatomy and body mass index (BMI) to provide further insight into the role of the brain in energy homeostasis and obesity. Methods: MRI images of brain anatomy were acquired in 839 Mexican American individuals from large extended pedigrees. Bivariate linkage and quantitative analyses were performed in SOLAR. Results: Genetic factors associated with an increased BMI were also associated with a reduced cortical surface area and subcortical volume. We identified two genome-wide quantitative trait loci that influenced BMI and the ventral diencephalon volume, and BMI and the supramarginal gyrus surface area, respectively. Conclusions: This study represents the first genetic analysis seeking evidence of pleiotropic effects acting on both brain anatomy and BMI. Our results suggest that a region on chromosome 17 contributes to the development of obesity, potentially through leptin-induced signaling in the hypothalamus, and that a region on chromosome 3 appears to jointly influence the food-related reward circuitry and the supramarginal gyrus.

© 2013 S. Karger AG, Basel


  

Key Words


  • Body mass index
  • Obesity
  • Imaging
  • Brain
  • Pleiotropy


References

  1. Centers for Disease Control and Prevention (CDC): Vital signs: state-specific obesity prevalence among adults - United States, 2009. MMWR Morb Mortal Wkly Rep 2010;59:951-955.

    External Resources

  2. Walley AJ, Blakemore AIF, Froguel P: Genetics of obesity and the prediction of risk of health. Hum Mol Genet 2006;15:R124-R130.
  3. Comuzzie AG, Higgins PB, Voruganti S, Cole S: Cutting the fat: the genetic dissection of body weight; in: Bouchard C (ed): Genes and Obesity. Prog Mol Biol Transl Sci., Elsevier Academic Press, 2010, vol 94, pp 197-212.
  4. Loos RF: Recent progress in the genetics of common obesity. Br J Clin Pharmacol 2009;68:811-829.
  5. Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B, Perusse L, Bouchard L: The human obesity gene map: the 2005 update. Obesity 2006;14:529-644.
  6. Cheung WW, Mao P: Recent advances in obesity: genetics and beyond. ISRN Endocrinol 2012;2012:536905.
  7. Raji CA, Ho AJ, Parikshak N, Becker JT, Lopez OL, Kuller LH, Hua X, Leow AD, Toga AW, Thompson PM: Brain structure and obesity. Hum Brain Mapp 2010;31:353-364.
  8. Gazdzinski S, Kornak J, Weiner MW, Meyerhoff DJ: Body mass index and magnetic resonance markers of brain integrity in adults. Ann Neurol 2008;63:652-657.
  9. Ho AJ, Stein JL, Hua X, Lee S, Hibar DP, Leow AD, Dinov ID, Toga AW, Saykin AJ, Shen L, Foroud T, Pankratz N, Huentelman MJ, Craig DW, Gerber JD, Allen AN, Corneveaux JJ, Stephan DA, DeCarli CS, DeChairo BM, Potkin SG, Jack CR Jr, Weiner MW, Raji CA, Lopez OL, Becker JT, Carmichael OT, Thompson PM, Alzheimer's Disease Neuroimaging Initiative. A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly. Proc Natl Acad Sci USA 2010;107:8404-8409.
  10. Mitchell BD, Kammerer CM, Blangero J, Mahaney MC, Rainwater DL, Dyke B, Hixson JE, Henkel RD, Sharp RM, Comuzzie AG, VandeBerg JL, Stern MP, MacCluer JW: Genetic and environmental contributions to cardiovascular risk factors in Mexican Americans. The San Antonio Family Heart Study. Circulation 1996;94:2159-2170.
  11. Puppala S, Dodd GD, Fowler S, Arya R, Schneider J, Farook VS, Granato R, Dyer TD, Almasy L, Jenkinson CP, Diehl AK, Stern MP, Blangero J, Duggirala R: A genomewide search finds major susceptibility loci for gallbladder disease on chromosome 1 in Mexican Americans. Am J Hum Genet 2006;78:377-392.
  12. Duggirala R, Blangero J, Almasy L, Dyer TD, Williams KL, Leach RJ, O'Connell P, Stern MP: Linkage of type 2 diabetes mellitus and of age at onset to a genetic location on chromosome 10q in Mexican Americans. Am J Hum Genet 1999;64:1127-1140.
  13. Olvera RL, Bearden CE, Velligan DI, Almasy L, Carless MA, Curran JE, Williamson DE, Duggirala R, Blangero J, Glahn DC: Common genetic influences on depression, alcohol, and substance use disorders in Mexican-American families. Am J Genet B Neuropsychiatr Genet 2011;156:561-568.
  14. Kochunov P, Lancaster JL, Glahn DC, Purdy D, Laird AR, Gao F, Fox P: Retrospective motion correction protocol for high-resolution anatomical MRI. Hum Brain Mapp 2006;27:957-962.
  15. Dale AM, Fischl B, Sereno MI: Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 1999;9:179-194.
  16. Fischl B, Sereno MI, Dale AM: Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 1999;9:195-207.
  17. Winkler A, Kochunov P, Blangero J, Almasy L, Zilles K, Fox P, Duggirala R, Glahn D: Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. Neuroimage 2010;53:1135-1146.
  18. Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Hyman BT, Albert MS, Killiany RJ: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968-980.
  19. Rosas HD, Liu AK, Hersch S, Glessner M, Ferrante RJ, Salat DH, van der Kouwe A, Jenkins BG, Dale AM, Fischl B: Regional and progressive thinning of the cortical ribbon in Huntington's disease. Neurology 2002;58:695-701.
  20. Kuperberg GR, Broome MR, McGuire PK, David AS, Eddy M, Ozawa F, Goff D, West WC, Williams SC, van der Kouwe AJ, Salat DH, Dale AM, Fischl B: Regionally localized thinning of the cerebral cortex in schizophrenia. Arch Gen Psychiatry 2003;60:878-888.
  21. Salat DH, Buckner RL, Snyder AZ, Greve DN, Desikan RS, Busa E, Morris JC, Dale AM, Fischl B: Thinning of the cerebral cortex in aging. Cereb Cortex 2004;14:721-730.
  22. Burdick JT, Chen WM, Abecasis GR, Cheung VG: In silico method for inferring genotypes in pedigrees. Nat Genet 2006;38:1002-1004.
  23. Abecasis GR, Cherny SS, Cookson WO, Cardon LR: Merlin - rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 2002;30:97-101.
  24. Almasy L, Blangero J: Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 1998;62:1198-1211.
  25. Almasy L, Dyer TD, Blangero J: Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages. Genet Epidemiol 1997;14:953-958.
  26. Williams JT, Begleiter H, Porjesz B, Edenberg HJ, Foroud T, Reich T, Goate A, Van Eerdewegh P, Almasy L, Blangero J: Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. II. Alcoholism and event-related potentials. Am J Hum Genet 1999;65:1148-1160.
  27. Glahn DC, Curran JE, Winkler AM, Carless MA, Kent JW Jr, Charlesworth JC, Johnson MP, Göring HH, Cole SA, Dyer TD, Moses EK, Olvera RL, Kochunov P, Duggirala R, Fox PT, Almasy L, Blangero J: High dimensional endophenotype ranking in search for major depression risk genes. Biol Psychiatry 2012;71:6-14.
  28. Sobel E, Papp JC, Lange K: Detection and integration of genotyping errors in statistical genetics. Am J Hum Genet 2002;70:496-508.
  29. Heath S: Markov chain Monte Carlo methods for radiation hybrid mapping. J Comput Biol 1997;4:505-515.
  30. Kong A, Gudbjartsson DF, Sainz J, Jonsdottir GM, Gudjonsson SA, Richardsson B, Sigurdardottir S, Barnard J, Hallbeck B, Masson G, Shlien A, Palsson ST, Frigge ML, Thorgeirsson TE, Gulcher JR, Stefansson K: A high-resolution recombination map of the human genome. Nat Genet 2002;31:241-247.
  31. Feingold E, Brown PO, Siegmund D: Gaussian models for genetic linkage analysis using complete high-resolution maps of identity by descent. Am J Hum Genet 1993;53:234-251.

    External Resources

  32. Belligni EF, Di Gregorio E, Biamino E, Calcia A, Molinatto C, Talarico F, Ferrero GB, Brusco A, Silengo MC: 790 Kb microduplication in chromosome band 17p13.1 associated with intellectual disability, afebrile seizures, dysmorphic features, diabetes, and hypothyroidism. Eur J Med Genet 2012;55:222-224.
  33. Kissebah AH, Sonnenberg GE, Myklebust J, Goldstein M, Broman K, James RG, Marks JA, Krakower GR, Jacob HJ, Weber J, Martin L, Blangero J, Comuzzie AG: Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc Natl Acad Sci USA 2000;97:14478-14483.
  34. Wu X, Cooper RS, Borecki I, Hanis C, Bray M, Lewis CE, Zhu X, Kan D, Luke A, Curb D: A combined analysis of genomewide linkage scans for body mass index from the National Heart, Lung, and Blood Institute Family Blood Pressure Program. Am J Hum Genet 2002;70:1247-1256.
  35. Frankort A, Roefs A, Siep N, Roebroeck A, Havermans R, Jansen A: Reward activity in satiated overweight women is decreased during unbiased viewing but increased when imagining taste: an event-related fMRI study. Int J Obes (Lond) 2012;36:627-637.
  36. Meyre D, Lecoeur C, Delplanque J, Francke S, Vatin V, Durand E, Weill J, Dina C, Froguel P: A genome-wide scan for childhood obesity-associated traits in French families shows significant linkage on chromosome 6q22.31-q23.2. Diabetes 2004;53:803-811.
  37. Rothemund Y, Preuschhof C, Bohner G, Bauknecht HC, Klingebiel R, Flor H, Klapp BF: Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage 2007;37:410-421.

  

Author Contacts

Dr. Joanne E. Curran
Department of Genetics, Texas Biomedical Research Institute
PO Box 760549
San Antonio, TX 78245-0549 (USA)
E-Mail jcurran@txbiomedgenetics.org

  

Article Information

Published online: September 27, 2013
Number of Print Pages : 8
Number of Figures : 1, Number of Tables : 3, Number of References : 37

  

Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 75, No. 2-4, Year 2013 (Cover Date: September 2013)

Journal Editor: Clerget-Darpoux F. (Paris)
ISSN: 0001-5652 (Print), eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

Abstract

Background/Aims: Obesity is a major contributor to the global burden of chronic disease and disability, though current knowledge of causal biologic underpinnings is lacking. Through the regulation of energy homeostasis and interactions with adiposity and gut signals, the brain is thought to play a significant role in the development of this disorder. While neuroanatomical variation has been associated with obesity, it is unclear if this relationship is influenced by common genetic mechanisms. In this study, we sought genetic components that influence both brain anatomy and body mass index (BMI) to provide further insight into the role of the brain in energy homeostasis and obesity. Methods: MRI images of brain anatomy were acquired in 839 Mexican American individuals from large extended pedigrees. Bivariate linkage and quantitative analyses were performed in SOLAR. Results: Genetic factors associated with an increased BMI were also associated with a reduced cortical surface area and subcortical volume. We identified two genome-wide quantitative trait loci that influenced BMI and the ventral diencephalon volume, and BMI and the supramarginal gyrus surface area, respectively. Conclusions: This study represents the first genetic analysis seeking evidence of pleiotropic effects acting on both brain anatomy and BMI. Our results suggest that a region on chromosome 17 contributes to the development of obesity, potentially through leptin-induced signaling in the hypothalamus, and that a region on chromosome 3 appears to jointly influence the food-related reward circuitry and the supramarginal gyrus.

© 2013 S. Karger AG, Basel


  

Author Contacts

Dr. Joanne E. Curran
Department of Genetics, Texas Biomedical Research Institute
PO Box 760549
San Antonio, TX 78245-0549 (USA)
E-Mail jcurran@txbiomedgenetics.org

  

Article Information

Published online: September 27, 2013
Number of Print Pages : 8
Number of Figures : 1, Number of Tables : 3, Number of References : 37

  

Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 75, No. 2-4, Year 2013 (Cover Date: September 2013)

Journal Editor: Clerget-Darpoux F. (Paris)
ISSN: 0001-5652 (Print), eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


Article / Publication Details

First-Page Preview
Abstract of  

Published online: 9/27/2013
Issue release date: September 2013

Number of Print Pages: 8
Number of Figures: 1
Number of Tables: 3

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE


Copyright / Drug Dosage

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in goverment regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

References

  1. Centers for Disease Control and Prevention (CDC): Vital signs: state-specific obesity prevalence among adults - United States, 2009. MMWR Morb Mortal Wkly Rep 2010;59:951-955.

    External Resources

  2. Walley AJ, Blakemore AIF, Froguel P: Genetics of obesity and the prediction of risk of health. Hum Mol Genet 2006;15:R124-R130.
  3. Comuzzie AG, Higgins PB, Voruganti S, Cole S: Cutting the fat: the genetic dissection of body weight; in: Bouchard C (ed): Genes and Obesity. Prog Mol Biol Transl Sci., Elsevier Academic Press, 2010, vol 94, pp 197-212.
  4. Loos RF: Recent progress in the genetics of common obesity. Br J Clin Pharmacol 2009;68:811-829.
  5. Rankinen T, Zuberi A, Chagnon YC, Weisnagel SJ, Argyropoulos G, Walts B, Perusse L, Bouchard L: The human obesity gene map: the 2005 update. Obesity 2006;14:529-644.
  6. Cheung WW, Mao P: Recent advances in obesity: genetics and beyond. ISRN Endocrinol 2012;2012:536905.
  7. Raji CA, Ho AJ, Parikshak N, Becker JT, Lopez OL, Kuller LH, Hua X, Leow AD, Toga AW, Thompson PM: Brain structure and obesity. Hum Brain Mapp 2010;31:353-364.
  8. Gazdzinski S, Kornak J, Weiner MW, Meyerhoff DJ: Body mass index and magnetic resonance markers of brain integrity in adults. Ann Neurol 2008;63:652-657.
  9. Ho AJ, Stein JL, Hua X, Lee S, Hibar DP, Leow AD, Dinov ID, Toga AW, Saykin AJ, Shen L, Foroud T, Pankratz N, Huentelman MJ, Craig DW, Gerber JD, Allen AN, Corneveaux JJ, Stephan DA, DeCarli CS, DeChairo BM, Potkin SG, Jack CR Jr, Weiner MW, Raji CA, Lopez OL, Becker JT, Carmichael OT, Thompson PM, Alzheimer's Disease Neuroimaging Initiative. A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly. Proc Natl Acad Sci USA 2010;107:8404-8409.
  10. Mitchell BD, Kammerer CM, Blangero J, Mahaney MC, Rainwater DL, Dyke B, Hixson JE, Henkel RD, Sharp RM, Comuzzie AG, VandeBerg JL, Stern MP, MacCluer JW: Genetic and environmental contributions to cardiovascular risk factors in Mexican Americans. The San Antonio Family Heart Study. Circulation 1996;94:2159-2170.
  11. Puppala S, Dodd GD, Fowler S, Arya R, Schneider J, Farook VS, Granato R, Dyer TD, Almasy L, Jenkinson CP, Diehl AK, Stern MP, Blangero J, Duggirala R: A genomewide search finds major susceptibility loci for gallbladder disease on chromosome 1 in Mexican Americans. Am J Hum Genet 2006;78:377-392.
  12. Duggirala R, Blangero J, Almasy L, Dyer TD, Williams KL, Leach RJ, O'Connell P, Stern MP: Linkage of type 2 diabetes mellitus and of age at onset to a genetic location on chromosome 10q in Mexican Americans. Am J Hum Genet 1999;64:1127-1140.
  13. Olvera RL, Bearden CE, Velligan DI, Almasy L, Carless MA, Curran JE, Williamson DE, Duggirala R, Blangero J, Glahn DC: Common genetic influences on depression, alcohol, and substance use disorders in Mexican-American families. Am J Genet B Neuropsychiatr Genet 2011;156:561-568.
  14. Kochunov P, Lancaster JL, Glahn DC, Purdy D, Laird AR, Gao F, Fox P: Retrospective motion correction protocol for high-resolution anatomical MRI. Hum Brain Mapp 2006;27:957-962.
  15. Dale AM, Fischl B, Sereno MI: Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 1999;9:179-194.
  16. Fischl B, Sereno MI, Dale AM: Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 1999;9:195-207.
  17. Winkler A, Kochunov P, Blangero J, Almasy L, Zilles K, Fox P, Duggirala R, Glahn D: Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. Neuroimage 2010;53:1135-1146.
  18. Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Hyman BT, Albert MS, Killiany RJ: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968-980.
  19. Rosas HD, Liu AK, Hersch S, Glessner M, Ferrante RJ, Salat DH, van der Kouwe A, Jenkins BG, Dale AM, Fischl B: Regional and progressive thinning of the cortical ribbon in Huntington's disease. Neurology 2002;58:695-701.
  20. Kuperberg GR, Broome MR, McGuire PK, David AS, Eddy M, Ozawa F, Goff D, West WC, Williams SC, van der Kouwe AJ, Salat DH, Dale AM, Fischl B: Regionally localized thinning of the cerebral cortex in schizophrenia. Arch Gen Psychiatry 2003;60:878-888.
  21. Salat DH, Buckner RL, Snyder AZ, Greve DN, Desikan RS, Busa E, Morris JC, Dale AM, Fischl B: Thinning of the cerebral cortex in aging. Cereb Cortex 2004;14:721-730.
  22. Burdick JT, Chen WM, Abecasis GR, Cheung VG: In silico method for inferring genotypes in pedigrees. Nat Genet 2006;38:1002-1004.
  23. Abecasis GR, Cherny SS, Cookson WO, Cardon LR: Merlin - rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 2002;30:97-101.
  24. Almasy L, Blangero J: Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 1998;62:1198-1211.
  25. Almasy L, Dyer TD, Blangero J: Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages. Genet Epidemiol 1997;14:953-958.
  26. Williams JT, Begleiter H, Porjesz B, Edenberg HJ, Foroud T, Reich T, Goate A, Van Eerdewegh P, Almasy L, Blangero J: Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. II. Alcoholism and event-related potentials. Am J Hum Genet 1999;65:1148-1160.
  27. Glahn DC, Curran JE, Winkler AM, Carless MA, Kent JW Jr, Charlesworth JC, Johnson MP, Göring HH, Cole SA, Dyer TD, Moses EK, Olvera RL, Kochunov P, Duggirala R, Fox PT, Almasy L, Blangero J: High dimensional endophenotype ranking in search for major depression risk genes. Biol Psychiatry 2012;71:6-14.
  28. Sobel E, Papp JC, Lange K: Detection and integration of genotyping errors in statistical genetics. Am J Hum Genet 2002;70:496-508.
  29. Heath S: Markov chain Monte Carlo methods for radiation hybrid mapping. J Comput Biol 1997;4:505-515.
  30. Kong A, Gudbjartsson DF, Sainz J, Jonsdottir GM, Gudjonsson SA, Richardsson B, Sigurdardottir S, Barnard J, Hallbeck B, Masson G, Shlien A, Palsson ST, Frigge ML, Thorgeirsson TE, Gulcher JR, Stefansson K: A high-resolution recombination map of the human genome. Nat Genet 2002;31:241-247.
  31. Feingold E, Brown PO, Siegmund D: Gaussian models for genetic linkage analysis using complete high-resolution maps of identity by descent. Am J Hum Genet 1993;53:234-251.

    External Resources

  32. Belligni EF, Di Gregorio E, Biamino E, Calcia A, Molinatto C, Talarico F, Ferrero GB, Brusco A, Silengo MC: 790 Kb microduplication in chromosome band 17p13.1 associated with intellectual disability, afebrile seizures, dysmorphic features, diabetes, and hypothyroidism. Eur J Med Genet 2012;55:222-224.
  33. Kissebah AH, Sonnenberg GE, Myklebust J, Goldstein M, Broman K, James RG, Marks JA, Krakower GR, Jacob HJ, Weber J, Martin L, Blangero J, Comuzzie AG: Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc Natl Acad Sci USA 2000;97:14478-14483.
  34. Wu X, Cooper RS, Borecki I, Hanis C, Bray M, Lewis CE, Zhu X, Kan D, Luke A, Curb D: A combined analysis of genomewide linkage scans for body mass index from the National Heart, Lung, and Blood Institute Family Blood Pressure Program. Am J Hum Genet 2002;70:1247-1256.
  35. Frankort A, Roefs A, Siep N, Roebroeck A, Havermans R, Jansen A: Reward activity in satiated overweight women is decreased during unbiased viewing but increased when imagining taste: an event-related fMRI study. Int J Obes (Lond) 2012;36:627-637.
  36. Meyre D, Lecoeur C, Delplanque J, Francke S, Vatin V, Durand E, Weill J, Dina C, Froguel P: A genome-wide scan for childhood obesity-associated traits in French families shows significant linkage on chromosome 6q22.31-q23.2. Diabetes 2004;53:803-811.
  37. Rothemund Y, Preuschhof C, Bohner G, Bauknecht HC, Klingebiel R, Flor H, Klapp BF: Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage 2007;37:410-421.