Recent advances in neuroimaging technology have shown that rich club organization in human brain networks plays a crucial role in global communication and cognitive functionality. In this study, we investigated rich club organization within white matter structural brain networks in two common types of dementia, Alzheimer’s disease (AD) and subcortical vascular dementia (SVaD). We recruited 30 AD patients ([11C] Pittsburgh compound-B (PiB) PET positive), 39 SVaD patients (PiB negative), and 72 age-, gender-, and education-matched cognitively normal (CN) subjects. Rich club organization was significantly disrupted in both dementia patient groups, which exhibited higher rich club coefficients than the CN group. Rich club organization in the patient groups was primarily disrupted over the left frontal and left middle temporal areas when compared to the CN group. The number of rich club nodes was significantly reduced in the dementia groups, which was more severe in SVaD (p = 0.0107, permutation-based t-test). Although rich club organization was disrupted both in the patient groups, its disruption pattern is different between them. The rich-club connections normalized by degree-and-strength preserved random networks were significantly increased in the dementia groups with SVaD more severely, and feeder connections were reduced more significantly than in AD. Furthermore, SVaD patients exhibited more sporadic disruption in white matter connectivity than AD patients, with local connections showing a more significant degree of deterioration. Combined with the distinct disruption in rich club nodes, these findings may imply a differing role for rich club organization in AD and SVaD, due to different pathological mechanisms.
van den HeuvelMP, SpornsO (2011) Rich-club organization of the human connectome. J Neurosci31, 15775–15786.
12.
RayS, MillerM, KaralunasS, RobertsonC, GraysonDS, CaryRP, HawkeyE, PainterJG, KrizD, FombonneE, NiggJT, FairDA (2014) Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: A rich club-organization study. Hum Brain Mapp35, 6032–6048.
13.
van den HeuvelMP, SpornsO, CollinG, ScheeweT, MandlRC, CahnW, GoniJ, Hulshoff PolHE, KahnRS (2013) Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry70, 783–792.
14.
DaianuM, DennisEL, JahanshadN, NirTM, TogaAW, Jack CRJr, WeinerMW, ThompsonPM, the Alzheimer’s Disease Neuroimaging Initiative (2013) Alzheimer’s disease disrupts rich club organization in brain connectivity networks. Proc IEEE Int Symp Biomed Imaging2013, 266–269.
15.
DaianuM, JahanshadN, NirTM, JackCRJr, WeinerMW, BernsteinMA, ThompsonPM, Alzheimer’s Disease Neuroimaging Initiative (2015) Rich club analysis in the Alzheimer’s disease connectome reveals a relatively undisturbed structural core network. Hum Brain Mapp36, 3087–3103.
16.
DaianuM, JahanshadN, Villalon-ReinaJE, MendezMF, BartzokisG, JimenezEE, JoshiA, BarsugliaJ, ThompsonPM (2014) Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer’s disease. Math Vis2014, 13–22.
17.
DaianuM, MezherA, MendezMF, JahanshadN, JimenezEE, ThompsonPM (2016) Disrupted rich club network in behavioral variant frontotemporal dementia and early-onset Alzheimer’s disease. Hum Brain Mapp37, 868–883.
18.
TuladharAM, LawrenceA, NorrisDG, BarrickTR, MarkusHS, de LeeuwFE (2017) Disruption of rich club organisation in cerebral small vessel disease. Hum Brain Mapp38, 1751–1766.
19.
BullmoreE, SpornsO (2009) Complex brain networks: Graph theoretical analysis of structural and functional systems. Nat Rev Neurosci10, 186–198.
20.
LawrenceAJ, ChungAW, MorrisRG, MarkusHS, BarrickTR (2014) Structural network efficiency is associated with cognitive impairment in small-vessel disease. Neurology83, 304–311.
21.
ReijmerYD, LeemansA, CaeyenberghsK, HeringaSM, KoekHL, BiesselsGJ, Utrecht Vascular Cognitive Impairment Study Group (2013) Disruption of cerebral networks and cognitive impairment in Alzheimer disease. Neurology80, 1370–1377.
22.
JungNY, HanCE, KimHJ, YooSW, KimHJ, KimEJ, NaDL, LockhartSN, JagustWJ, SeongJK, SeoSW (2016) Tract-specific correlates of neuropsychological deficits in patients with subcortical vascular cognitive impairment. J Alzheimers Dis50, 1125–1135.
23.
FazekasF, KleinertR, OffenbacherH, SchmidtR, KleinertG, PayerF, RadnerH, LechnerH (1993) Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology43, 1683–1689.
24.
KimSH, SeoSW, GoSM, ChinJ, LeeBH, LeeJH, HanSH, NaDL (2011) Pyramidal and extrapyramidal scale (PEPS): A new scale for the assessment of motor impairment in vascular cognitive impairment associated with small vessel disease. Clin Neurol Neurosurg113, 181–187.
25.
LeeJH, KimSH, KimGH, SeoSW, ParkHK, OhSJ, KimJS, CheongHK, NaDL (2011) Identification of pure subcortical vascular dementia using 11C-Pittsburgh compound B. Neurology77, 18–25.
McKhannG, DrachmanD, FolsteinM, KatzmanR, PriceD, StadlanEM (1984) Clinical diagnosis of Alzheimer’sdisease: Report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology34, 939–944.
28.
KimTH, JhooJH, ParkJH, KimJL, RyuSH, MoonSW, ChooIH, LeeDW, YoonJC, DoYJ, LeeSB, KimMD, KimKW (2010) Korean version of mini mental status examination for dementia screening and its’ short form. Psychiatry Investig7, 102–108.
29.
ParkJ, KwonY (1989) Standardization of Korean version of the Mini-Mental State Examination (MMSE-K) for use in the elderly. Part II: Diagnostic validity. Journal of Korean Neuropsychiatry Association, pp. 508–513.
30.
KimSH, SeoSW, GoSM, ChinJ, LeeBH, LeeJ-H, HanS-H, NaDL (2011) Pyramidal and extrapyramidal scale (PEPS): A new scale for the assessment of motor impairment in vascular cognitive impairment associated with small vessel disease. Clin Neurol Neurosurg113, 181–187.
31.
HanCE, YooSW, SeoSW, NaDL, SeongJK (2013) Cluster-based statistics for brain connectivity in correlation with behavioral measures. PLoS One8, e72332.
32.
MyungW, HanCE, FavaM, MischoulonD, PapakostasGI, HeoJY, KimKW, KimST, KimDJ, KimDK, SeoSW, SeongJK, JeonHJ (2016) Reduced frontal-subcortical white matter connectivity in association with suicidal ideation in major depressive disorder. Transl Psychiatry6, e835.
33.
Tzourio-MazoyerN, LandeauB, PapathanassiouD, CrivelloF, EtardO, DelcroixN, MazoyerB, JoliotM (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage15, 273–289.
34.
MoriS, BarkerPB (1999) Diffusion magnetic resonance imaging: Its principle and applications. Anat Rec257, 102–109.
35.
JenkinsonM, SmithS (2001) A global optimisation method for robust affine registration of brain images. Med Image Anal5, 143–156.
36.
JenkinsonM, BannisterP, BradyM, SmithS (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage17, 825–841.
37.
AnderssonJLR, JenkinsonM, SmithS (2007) Non-linear optimisation. In FMRIB Technial Report, FMRIB Centre, Oxford, United Kingdom.
WangR, BennerT, SorensenAG, WedeenVJ (2007) Diffusion Toolkit: A software package for diffusion imaging data processing and tractography. Proc Intl Soc Mag Reson Med15, 3720.
40.
MoriS, KaufmannWE, DavatzikosC, StieltjesB, AmodeiL, FredericksenK, PearlsonGD, MelhemER, SolaiyappanM, RaymondGV, MoserHW, van ZijlPC (2002) Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking. Magn Reson Med47, 215–223
.
41.
GraysonDS, RayS, CarpenterS, IyerS, DiasTG, StevensC, NiggJT, FairDA (2014) Structural and functional rich club organization of the brain in children and adults. PLoS One9, e88297.
42.
TaylorPA, ChoKH, LinCP, BiswalBB (2012) Improving DTI tractography by including diagonal tract propagation. PLoS One7, e43415.
JacobsHI, Van BoxtelMP, JollesJ, VerheyFR, UylingsHB (2012) Parietal cortex matters in Alzheimer’s disease: An overview of structural, functional and metabolic findings. Neurosci Biobehav Rev36, 297–309.
47.
MurrayME, Graff-RadfordNR, RossOA, PetersenRC, DuaraR, DicksonDW (2011) Neuropathologically defined subtypes of Alzheimer’s disease with distinct clinical characteristics: A retrospective study. Lancet Neurol10, 785–796.
48.
NohY, JeonS, LeeJM, SeoSW, KimGH, ChoH, YeBS, YoonCW, KimHJ, ChinJ, ParkKH, HeilmanKM, NaDL (2014) Anatomical heterogeneity of Alzheimer disease: Based on cortical thickness on MRIs. Neurology83, 1936–1944.
49.
ParkJ-Y, NaHK, KimS, KimH, KimHJ, SeoSW, NaDL, HanCE, SeongJ-K (2017) Robust identification of Alzheimer’s disease subtypes based on cortical atrophy patterns. Sci Rep7, 43270.
BoccardiM, SabattoliF, LaaksoMP, TestaC, RossiR, BeltramelloA, SoininenH, FrisoniGB (2005) Frontotemporal dementia as a neural system disease. Neurobiol Aging26, 37–44.
56.
van den HeuvelMP, KahnRS, Goñ iJ, SpornsO (2012) High-cost, high-capacity backbone for global brain communication. Proc Natl Acad Sci U S A109, 11372–11377.
