Brain networks modeling for studying the mechanism underlying the development of Alzheimer's disease
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摘要
Alzheimer's disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer's disease patients have been established,the mechanisms that drive these alterations remain incompletely understood.This study,which was conducted in 2018 at Northeastern University in China,included data from 97 participants of the Alzheimer's Disease Neuroimaging Initiative(ADNI)dataset covering genetics,imaging,and clinical data.All participants were divided into two groups:normal control(n=52;20 males and 32 females;mean age 73.90±4.72 years)and Alzheimer's disease(n=45,23 males and 22 females;mean age 74.85±5.66).To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer's disease patients,we proposed a local naive Bayes brain network model based on graph theory.Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined,including clustering coefficient,modularity,characteristic path length,network efficiency,betweenness,and degree distribution compared with empirical methods.This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer's disease patients.Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions.The ADNI was performed in accordance with the Good Clinical Practice guidelines,US 21 CFR Part 50-Protection of Human Subjects,and Part 56-Institutional Review Boards(IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards(IRBs)/Research Ethics Boards(REBs).
Alzheimer's disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer's disease patients have been established,the mechanisms that drive these alterations remain incompletely understood.This study,which was conducted in 2018 at Northeastern University in China,included data from 97 participants of the Alzheimer's Disease Neuroimaging Initiative(ADNI)dataset covering genetics,imaging,and clinical data.All participants were divided into two groups:normal control(n=52;20 males and 32 females;mean age 73.90±4.72 years)and Alzheimer's disease(n=45,23 males and 22 females;mean age 74.85±5.66).To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer's disease patients,we proposed a local naive Bayes brain network model based on graph theory.Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined,including clustering coefficient,modularity,characteristic path length,network efficiency,betweenness,and degree distribution compared with empirical methods.This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer's disease patients.Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions.The ADNI was performed in accordance with the Good Clinical Practice guidelines,US 21 CFR Part 50-Protection of Human Subjects,and Part 56-Institutional Review Boards(IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards(IRBs)/Research Ethics Boards(REBs).
Alzheimer's disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer's disease patients have been established,the mechanisms that drive these alterations remain incompletely understood.This study,which was conducted in 2018 at Northeastern University in China,included data from 97 participants of the Alzheimer's Disease Neuroimaging Initiative(ADNI)dataset covering genetics,imaging,and clinical data.All participants were divided into two groups:normal control(n=52;20 males and 32 females;mean age 73.90±4.72 years)and Alzheimer's disease(n=45,23 males and 22 females;mean age 74.85±5.66).To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer's disease patients,we proposed a local naive Bayes brain network model based on graph theory.Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined,including clustering coefficient,modularity,characteristic path length,network efficiency,betweenness,and degree distribution compared with empirical methods.This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer's disease patients.Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions.The ADNI was performed in accordance with the Good Clinical Practice guidelines,US 21 CFR Part 50-Protection of Human Subjects,and Part 56-Institutional Review Boards(IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards(IRBs)/Research Ethics Boards(REBs).
引文
Alexander-Bloch AF,Vertes PE,Stidd R,Lalonde F,Clasen L,Rapoport J,Giedd J,Bullmore ET,Gogtay N(2013)The anatomical distance of functional connections predicts brain network topology in health and schizophrenia.Cereb Cortex23:127-138.
Alzheimer’s Association(2018)2018 Alzheimer’s disease facts and figures.Alzheimers Dement 14:367-429.
Avena-Koenigsberger A,Misic B,Sporns O(2017)Communication dynamics in complex brain networks.Nat Rev Neurosci 19:17-33.
Barabasi AL,Albert R(1999)Emergence of scaling in random networks.Science286:509-512.
Bassett DS,Sporns O(2017)Network neuroscience.Nat Neurosci 20:353-364.
Bassett DS,Zurn P,Gold JI(2018)On the nature and use of models in network neuroscience.Nat Rev Neurosci 19:566-578.
Betzel RF,Avena-Koenigsberger A,Go?i J,He Y,de Reus MA,Griffa A,Vértes PE,Mi?ic B,Thiran JP,Hagmann P,van den Heuvel M,Zuo XN,Bullmore ET,Sporns O(2016)Generative models of the human connectome.Neuroimage 124:1054-1064.
Brier MR,Thomas JB,Fagan AM,Hassenstab J,Holtzman DM,Benzinger TL,Morris JC,Ances BM(2014)Functional connectivity and graph theory in preclinical Alzheimer’s disease.Neurobiol Aging 35:757-768.
Bullmore E,Sporns O(2009)Complex brain networks:graph theoretical analysis of structural and functional systems.Nat Rev Neurosci 10:186-198.
Bullmore E,Sporns O(2012)The economy of brain network organization.Nat Rev Neurosci 13:336-349.
Cheng C,Chen J,Cao X,Guo H(2016)Comparison of local information indices applied in resting state functional brain network connectivity prediction.Front Neurosci 10:585.
Dimitriadis SI,Liparas D,Alzheimer’s Disease Neuroimaging Initiative(2018)How random is the random forest?Random forest algorithm on the service of structural imaging biomarkers for Alzheimer’s disease:from Alzheimer’s disease neuroimaging initiative(ADNI)database.Neural Regen Res 13:962-970.
Frere S,Slutsky I(2018)Alzheimer’s disease:from firing instability to homeostasis network collapse.Neuron 97:32-58.
GuimeràR,Sales-Pardo M(2009)Missing and spurious interactions and the reconstruction of complex networks.Proc Natl Acad Sci U S A 106:22073-22078.
Guo H,Cheng C,Cao X,Xiang J,Chen J,Zhang K(2014)Resting-state functional connectivity abnormalities in first-onset unmedicated depression.Neural Regen Res 9:153-163.
Harrison TM,Burggren AC,Small GW,Bookheimer SY(2016)Altered memory-related functional connectivity of the anterior and posterior hippocampus in older adults at increased genetic risk for Alzheimer’s disease.Hum Brain Mapp 37:366-380.
Jalili M(2017)Graph theoretical analysis of Alzheimer’s disease:Discrimination of AD patients from healthy subjects.Inform Sci 384:145-156.
Kaiser M,Hilgetag CC(2004)Modelling the development of cortical systems networks.Neurocomputing 58-60:297-302.
Liben-Nowell D,Kleinberg J(2007)The link-prediction problem for social networks.J Am Soc Inf Sci 58:1019-1031.
Liu Z,Zhang QM,LüL,Zhou T(2011)Link prediction in complex networks:Alocal na?ve Bayes model.Europhys Lett 96:48007.
Meunier D,Lambiotte R,Bullmore ET(2010)Modular and hierarchically modular organization of brain networks.Front Neurosci 4:200.
Morris JC(1993)The Clinical Dementia Rating(CDR):current version and scoring rules.Neurology 43:2412-2414.
Muldoon SF(2018)Multilayer network modeling creates opportunities for novel network statistics:Comment on“Network science of biological systems at different scales:A review”by Gosak et al.Phys Life Rev 24:143-145.
Roberts JA,Perry A,Lord AR,Roberts G,Mitchell PB,Smith RE,Calamante F,Breakspear M(2016)The contribution of geometry to the human connectome.Neuroimage 124:379-393.
Samu D,Seth AK,Nowotny T(2014)Influence of wiring cost on the large-scale architecture of human cortical connectivity.PLoS Comput Biol 10:e1003557.
Sperling R,Mormino E,Johnson K(2014)The evolution of preclinical Alzheimer’s disease:implications for prevention trials.Neuron 84:608-622.
Sporns O(2011)Networks of the Brain.Cambridge,USA:The MIT Press.
Stam CJ(2014)Modern network science of neurological disorders.Nat Rev Neurosci 15:683-695.
Tan TT,Wang D,Huang JK,Zhou XM,Yuan X,Liang JP,Yin L,Xie HL,Jia XY,Shi J,Wang F,Yang HB,Chen SJ(2017)Modulatory effects of acupuncture on brain networks in mild cognitive impairment patients.Neural Regen Res 12:250-258.
Tijms BM,Wink AM,de Haan W,van der Flier WM,Stam CJ,Scheltens P,Barkhof F(2013)Alzheimer’s disease:connecting findings from graph theoretical studies of brain networks.Neurobiol Aging 34:2023-2036.
Tombaugh TN,McIntyre NJ(1992)The mini-mental state examination:a comprehensive review.J Am Geriatr Soc 40:922-935.
Toussaint PJ,Maiz S,Coynel D,Doyon J,Messe A,de Souza LC,Sarazin M,Perlbarg V,Habert MO,Benali H(2014)Characteristics of the default mode functional connectivity in normal ageing and Alzheimer’s disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements.Neuroimage 101:778-786.
Tzourio-Mazoyer N,Landeau B,Papathanassiou D,Crivello F,Etard O,Delcroix N,Mazoyer B,Joliot M(2002)Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.Neuroimage 15:273-289.
Vértes PE,Alexander-Bloch AF,Gogtay N,Giedd JN,Rapoport JL,Bullmore ET(2012)Simple models of human brain functional networks.Proc Natl Acad Sci US A 109:5868-5873.
Wang WW,Lu YC,Tang WJ,Zhang JH,Sun HP,Feng XY,Liu HQ(2018)Small-worldness of brain networks after brachial plexus injury:A resting-state functional magnetic resonance imaging study.Neural Regen Res 13:1061-1065.
Watts DJ,Strogatz SH(1998)Collective dynamics of‘small-world’networks.Nature 393:440-442.
World Health Organization(2017)Dementia.http://www.who.int/en/news-room/fact-sheets/detail/dementia.
Yan CG,Zang YF(2010)DPARSF:A MATLAB toolbox for“Pipeline”data analysis of resting-state fMRI.Front Syst Neurosci 4:13.
Zhang X,Moore C,Newman MEJ(2017)Random graph models for dynamic networks.Eur Phys J B 90:200.
Zhao QB,Feng HB,Tang YY(2007)Modelling human cortical network in real brain space.Chin Phys Lett 24:3582-3585.
Zhao X,Liu Y,Wang X,Liu B,Xi Q,Guo Q,Jiang H,Jiang T,Wang P(2012)Disrupted small-world brain networks in moderate Alzheimer’s disease:a resting-state fMRI study.PLoS One 7:e33540.
Alzheimer’s Association(2018)2018 Alzheimer’s disease facts and figures.Alzheimers Dement 14:367-429.
Avena-Koenigsberger A,Misic B,Sporns O(2017)Communication dynamics in complex brain networks.Nat Rev Neurosci 19:17-33.
Barabasi AL,Albert R(1999)Emergence of scaling in random networks.Science286:509-512.
Bassett DS,Sporns O(2017)Network neuroscience.Nat Neurosci 20:353-364.
Bassett DS,Zurn P,Gold JI(2018)On the nature and use of models in network neuroscience.Nat Rev Neurosci 19:566-578.
Betzel RF,Avena-Koenigsberger A,Go?i J,He Y,de Reus MA,Griffa A,Vértes PE,Mi?ic B,Thiran JP,Hagmann P,van den Heuvel M,Zuo XN,Bullmore ET,Sporns O(2016)Generative models of the human connectome.Neuroimage 124:1054-1064.
Brier MR,Thomas JB,Fagan AM,Hassenstab J,Holtzman DM,Benzinger TL,Morris JC,Ances BM(2014)Functional connectivity and graph theory in preclinical Alzheimer’s disease.Neurobiol Aging 35:757-768.
Bullmore E,Sporns O(2009)Complex brain networks:graph theoretical analysis of structural and functional systems.Nat Rev Neurosci 10:186-198.
Bullmore E,Sporns O(2012)The economy of brain network organization.Nat Rev Neurosci 13:336-349.
Cheng C,Chen J,Cao X,Guo H(2016)Comparison of local information indices applied in resting state functional brain network connectivity prediction.Front Neurosci 10:585.
Dimitriadis SI,Liparas D,Alzheimer’s Disease Neuroimaging Initiative(2018)How random is the random forest?Random forest algorithm on the service of structural imaging biomarkers for Alzheimer’s disease:from Alzheimer’s disease neuroimaging initiative(ADNI)database.Neural Regen Res 13:962-970.
Frere S,Slutsky I(2018)Alzheimer’s disease:from firing instability to homeostasis network collapse.Neuron 97:32-58.
GuimeràR,Sales-Pardo M(2009)Missing and spurious interactions and the reconstruction of complex networks.Proc Natl Acad Sci U S A 106:22073-22078.
Guo H,Cheng C,Cao X,Xiang J,Chen J,Zhang K(2014)Resting-state functional connectivity abnormalities in first-onset unmedicated depression.Neural Regen Res 9:153-163.
Harrison TM,Burggren AC,Small GW,Bookheimer SY(2016)Altered memory-related functional connectivity of the anterior and posterior hippocampus in older adults at increased genetic risk for Alzheimer’s disease.Hum Brain Mapp 37:366-380.
Jalili M(2017)Graph theoretical analysis of Alzheimer’s disease:Discrimination of AD patients from healthy subjects.Inform Sci 384:145-156.
Kaiser M,Hilgetag CC(2004)Modelling the development of cortical systems networks.Neurocomputing 58-60:297-302.
Liben-Nowell D,Kleinberg J(2007)The link-prediction problem for social networks.J Am Soc Inf Sci 58:1019-1031.
Liu Z,Zhang QM,LüL,Zhou T(2011)Link prediction in complex networks:Alocal na?ve Bayes model.Europhys Lett 96:48007.
Meunier D,Lambiotte R,Bullmore ET(2010)Modular and hierarchically modular organization of brain networks.Front Neurosci 4:200.
Morris JC(1993)The Clinical Dementia Rating(CDR):current version and scoring rules.Neurology 43:2412-2414.
Muldoon SF(2018)Multilayer network modeling creates opportunities for novel network statistics:Comment on“Network science of biological systems at different scales:A review”by Gosak et al.Phys Life Rev 24:143-145.
Roberts JA,Perry A,Lord AR,Roberts G,Mitchell PB,Smith RE,Calamante F,Breakspear M(2016)The contribution of geometry to the human connectome.Neuroimage 124:379-393.
Samu D,Seth AK,Nowotny T(2014)Influence of wiring cost on the large-scale architecture of human cortical connectivity.PLoS Comput Biol 10:e1003557.
Sperling R,Mormino E,Johnson K(2014)The evolution of preclinical Alzheimer’s disease:implications for prevention trials.Neuron 84:608-622.
Sporns O(2011)Networks of the Brain.Cambridge,USA:The MIT Press.
Stam CJ(2014)Modern network science of neurological disorders.Nat Rev Neurosci 15:683-695.
Tan TT,Wang D,Huang JK,Zhou XM,Yuan X,Liang JP,Yin L,Xie HL,Jia XY,Shi J,Wang F,Yang HB,Chen SJ(2017)Modulatory effects of acupuncture on brain networks in mild cognitive impairment patients.Neural Regen Res 12:250-258.
Tijms BM,Wink AM,de Haan W,van der Flier WM,Stam CJ,Scheltens P,Barkhof F(2013)Alzheimer’s disease:connecting findings from graph theoretical studies of brain networks.Neurobiol Aging 34:2023-2036.
Tombaugh TN,McIntyre NJ(1992)The mini-mental state examination:a comprehensive review.J Am Geriatr Soc 40:922-935.
Toussaint PJ,Maiz S,Coynel D,Doyon J,Messe A,de Souza LC,Sarazin M,Perlbarg V,Habert MO,Benali H(2014)Characteristics of the default mode functional connectivity in normal ageing and Alzheimer’s disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements.Neuroimage 101:778-786.
Tzourio-Mazoyer N,Landeau B,Papathanassiou D,Crivello F,Etard O,Delcroix N,Mazoyer B,Joliot M(2002)Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.Neuroimage 15:273-289.
Vértes PE,Alexander-Bloch AF,Gogtay N,Giedd JN,Rapoport JL,Bullmore ET(2012)Simple models of human brain functional networks.Proc Natl Acad Sci US A 109:5868-5873.
Wang WW,Lu YC,Tang WJ,Zhang JH,Sun HP,Feng XY,Liu HQ(2018)Small-worldness of brain networks after brachial plexus injury:A resting-state functional magnetic resonance imaging study.Neural Regen Res 13:1061-1065.
Watts DJ,Strogatz SH(1998)Collective dynamics of‘small-world’networks.Nature 393:440-442.
World Health Organization(2017)Dementia.http://www.who.int/en/news-room/fact-sheets/detail/dementia.
Yan CG,Zang YF(2010)DPARSF:A MATLAB toolbox for“Pipeline”data analysis of resting-state fMRI.Front Syst Neurosci 4:13.
Zhang X,Moore C,Newman MEJ(2017)Random graph models for dynamic networks.Eur Phys J B 90:200.
Zhao QB,Feng HB,Tang YY(2007)Modelling human cortical network in real brain space.Chin Phys Lett 24:3582-3585.
Zhao X,Liu Y,Wang X,Liu B,Xi Q,Guo Q,Jiang H,Jiang T,Wang P(2012)Disrupted small-world brain networks in moderate Alzheimer’s disease:a resting-state fMRI study.PLoS One 7:e33540.