Regional Cortical Thickness in Children and Adolescents with Obesity

(1)

INTRODUCTION

Inrecentdecades^,theprevalenceofobesityhasincreaseddramatically worldwidetoepidemicproportions.¹⁾Ithasbeenreportedthatone-third oftheadultpopulationinmostdevelopedcountriesisobese^,²⁾whichhas resulted inanincreasing number of peoplewith type2 diabetes^, cardiovasculardisease^,stroke^,cancer^,metabolicsyndrome^,liverdisease^,

andotherconditions^.³⁾Inparticular^,childhoodobesityisaglobalhealth problem^,⁴⁾andincreasingratesofobesity^,beginninginchildhood^,are expectedtocauseasignificantdecreaseinlifeexpectancy^.^5,6)Indeed^, obesityinthisagegroupisassociatedwithadverseoutcomessuchas diabetes^,highblood pressure^,coronary arterydisease^,depressive symptoms^,lowerlifesatisfaction^,andproblematicpatternsofalcohol use^.⁷⁾ Moreover^,longitudinalstudies haveshown that obesity in

Received August 21, 2020 Accepted November 15, 2020 Corresponding author Se-Hong Kim

Tel: +82-31-249-8316, Fax: +82-31-249-8006 E-mail: [email protected]

ORCID: https://orcid.org/0000-0001-6465-8993

This is an open-access article distributed under the terms of the Creative Commons At- tribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Original Article

https://doi.org/10.21215/kjfp.2021.11.1.61 eISSN 2233-9116

Korean J Fam Pract. 2021;11(1):61-66

Korean Journal of Family Practice

KJFP

비만 소아에서 대뇌피질 두께 변화

김영균¹, 김세홍^2,*, 김태홍², 정주혜³, 은영미³

1의정부성모병원 가정의학과, ²성빈센트병원 가정의학과, ³여의도성모병원 가정의학과

Regional Cortical Thickness in Children and Adolescents with Obesity

Young Kyun Kim¹, Se-Hong Kim^2,*, Tae-Hong Kim², Ju-Hye Chung³, Young-Mi Eun³

1Department of Family Medicine, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu; ²Department of Family Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Suwon; ³Department of Family Medicine, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea

Background: Previous studies have demonstrated obesity-associated changes in the brain in adults; however, no study has evaluated the cortical thickness or subcortical volumes in obese children and adolescents. The purpose of our study was to investigate changes in cortical thickness in asymptomatic children and adolescents with obesity.

Methods: A total of 21 participants (10 patients with obesity and 11 subjects without obesity), aged 6–18 years, underwent 3T brain magnetic resonance imaging (MRI) scanning, and cortical thickness was compared between the obese group and the control group across multiple locations.

The subcortical volumes were also compared on a structure-by-structure basis.

Results: No significant differences between the obese and non-obese control group were observed with respect to the mean volumes of the total white matter in each hemisphere. However, the obese group showed a significant reduction in the mean cortical thickness of both hemispheres compared to the control group. Group comparison analysis of the regional cortical thicknesses between the two groups also revealed a significant reduction in the cortical thickness of the left supramarginal, inferior parietal, pars orbitalis, and pars opercularis cortices in the obese group compared with that in the control group (P<0.05, false discovery rate corrected).

Conclusion: We demonstrated a significant reduction in the thickness of the cortical areas of obese patients, especially in areas involved in body weight control. Our results suggest the existence of structural brain abnormalities in obese children and adolescents, and further prospective studies are required to evaluate this relationship.

Keywords: Obesity; Cortical Thickness; Children; Adolescent; Magnetic Resonance Imaging

(2)

Young Kyun Kim, et al. Cortical Thickness in Adolescent Obesity

KJFP

childhood independently predictsfutureadverse health outcomes^, includingincreasedriskofmortality^.⁸⁾

Interestingly^,obesityisknowntocausechangesinbrainstructure^. Brainimagingstudieshavedemonstratedthatobesitymaybeassociated withbothgeneralizedandregionalbrainatrophy, aswellasstructural changesinwhitematter.^9,10)However, onlyafewstudiesontheregional distributionofbrain atrophyinchildrenand adolescentshavebeen reportedsofar^.Thesestudiesofsmall^,selectedsampleshavereported associationsofobesitywithchangesin brainstructureandbehavior^, whileneuroimagingstudieshaveindicateddecreasedcorticalthickness andsubcorticalvolume^.¹¹⁾Anotherstudyonthemechanismsleadingto childhoodobesityhasshownthatobeseadolescentshavelowervolumes ofgraymatter⁽GM⁾thanleanindividuals^.¹²⁾

Althoughpreviousstudieshavedemonstratedanassociationbetween adultobesityandchangesincerebralwhitematterintegrity^,¹³⁾nostudy todatehasevaluatedeithercorticalthicknessorsubcorticalvolumesin adolescents usingmagneticresonanceimaging⁽MRI^).Therefore^,it remains unclear whetherearly structural brain changesoccur in asymptomaticchildren andadolescents. Since brainstructureand functional changes during development in adults may not be generalizabletoyoungerpeople^,itisessentialtoconductseparatestudies inchildrenandadolescents^.However^,theeffectsofobesityonthebrain in children and adolescents are poorly understood^.This study investigatedthebrainstructureinleanandobeseadolescentsusingMRI andevaluatedtheassociationsbetweenBMIandcorticalthickness. METHODS

1. Subjects

Inthisstudy^,21right-handedasymptomaticparticipants^,aged6–18 years^,wererecruitedfromtheoutpatientclinicatSt^.Vincent^’sHospital inSouthKorea. Allsubjectsunderwentcomprehensivehealthscreening andabrainMRIscanbetweenMarch2014andSeptember2016^.The participantsincluded10patientswithobesityand11withoutobesity^.

Theexclusioncriteriawereasfollows^:1⁾psychologicalconditions^,2⁾ historyofendocrinedisorders⁽includingabnormalthyroidfunctionand type 2diabetes^),3⁾activeneurologicalorpsychiatric conditions^,4⁾ alcoholordrugabuse (and/orhistoryofsubstanceabuseoraddiction), and 5) mentalretardation. Aclinicalneuroradiologistexaminedthe brainMRIsofallsubjects^;nogrossabnormalitieswerereportedinany

oftheparticipants^,andallshowedapparentlynormalwhitematter^.This studywasapprovedbytheResearchEthicalCommiteeofSt^.Vincent^’s Hospital andwasconducted inaccordancewith theDeclarationof Helsinki^.Writteninformedconsentwasobtainedfromallparticipants priortoinclusion.

2. Risk factor assessment

Anthropometric^,clinical^,andlaboratoryinvestigationswereperformed for allsubjects^.Theheightofeachparticipantwasmeasuredto the nearest0^.1cmusingafixedwall-scalemeasuringdevice^.Bodyweight was measured tothe nearest 0^.1 kg usingadigitalscale thatwas calibratedpriortoeachmeasurement. Bodymassindex (BMI; kg/m²) wascalculatedastheweightinkilograms⁽kg⁾dividedbythesquareof heightin meters⁽m^).Waistcircumferencewasmeasuredtwiceatthe endofanormalexpirationonahorizontalplaneimmediatelysuperior totheleftiliaccrest^.Twobloodpressuremeasurementsweretakenfrom allsubjectsata5-minintervalandthenaveragedforanalysis^.Fasting plasma glucose, total cholesterol, triglycerides, and high-density lipoprotein (HDL)-cholesterollevelsweremeasuredaftera12-hfastusing anauto-analyzer⁽Hitachi 747auto-analyzer^;Hitachi^,Tokyo^,Japan^).

Smokingstatusandalcoholusewerealsoinvestigated^.

3. Brain imaging and data processing

T1-weightedoptimizedhigh-resolution3D magnetization-prepared rapidacquisitionofgradientecho (3D-MPRAGE) imagesofthebrain were acquiredusing a 3T whole-body scannerequipped with a 32-channelheadcoil⁽Verio^;Siemens^,Erlangen^,Germany^).Therewere 208contiguouscoronalsliceswiththefollowingscanningparameters^: TR^/TI^/TE=1^,900^/900^/2^.5ms^,FOV=250^×250mm^,flipangle⁽FA⁾=9^°, 256^×256matrix^;isotropicvoxeldimensionsof1^.0mm^,thicknessof0^.8 mm^,andacquisitiontimeof7^.34min^.FreeSurfer5^.1^.0⁽http^://surfer^. nmr.mgh.harvard.edu) wasusedtoperformcorticalreconstructionand volumetricsegmentationofthebrain^.Thissoftwareprovidesoneofthe bestvalidated automatedbrainsegmentationmethods^,thetechnical detailsofwhichhavebeendescribedpreviously^.^14,15)

Briefly^,theprocessingstreamincludesaTalairachtransformofeach subject^’snativebrain^,removalofthenon-braintissue^,andsegmentation ofthegraymatter–whitematter tissue. Thecorticalsurfaceofeach hemispherewasinflatedtoanaveragesphericalsurfacetolocateboththe pialsurfaceandthegray–whitematterboundary^.Blindedtotheidentity

(3)

김영균 외. 비만 소아에서 대뇌피질 두께 Korean Journal of Family Practice

KJFP

oftheparticipant^,wevisuallyinspectedtheentirecortexofeachsubject andmanuallycorrectedanytopologicdefects^.Thecorticalthicknesswas computedastheshortestdistancebetweenthepialsurfaceandthegray–

whitematterboundaryateach pointthroughoutthecorticalmantle^. Theglobalmeancorticalthicknessforeach subjectwascomputed by averagingthecorticalthicknessateachvertex, andthecorticalthick- nessesoftherightandlefthemisphereswerealsoaveragedseparately^; thesevalueswereusedinthestatisticalanalyses^.Theregionalthickness value ateachvertexforeachsubjectwasmappedtothesurfaceofan averagebraintemplate^,allowingvisualizationofdataacrosstheentire corticalsurface⁽describedathttp^://surfer^.nmr^.mgh^.harvard^.edu^/fswiki^/ FsAverage). Inaddition, theentirecerebralcortexwasparcellatedinto34 regions^,¹⁶⁾andvarioussurface-baseddata^,includingmapsofthecortical volume^,surfacearea^,curvature^,andsulcaldepth^,werecreated^.Data wereresampledforallsubjectsusingacommonsphericalcoordinate system^.ThecorticalmapofeachsubjectwassmoothedusingaGaussian kernelof10mmfullwidthathalf-maximumfortheanalysesofthe entirecortex. Thesubcorticalvolumeswereobtainedfromtheautomated procedure for the volumetric measurement ofbrain structures implemented inFreeSurfer^.Atotalof40volumetricmeasureswere investigated^,andeightsubcorticalstructures⁽whitematter^,caudate^, thalamus^,pallidum^,putamen^,hippocampus^,accumbens^,andamygdala⁾ were extractedfromeach hemisphere^.Allof thesemeasures were corrected fortheirestimatedtotalintracranialvolume⁽eTIV⁾before statistical analysis. Reliabilitystudies onmeasurementsof cortical

thickness and subcortical volumes reported that within-scanner variabilitiesincorticalthicknessandsubcorticalvolumemeasurements using FreeSurfer were estimated to be <0^.03 mm and 4^.3^%, respectively^.¹⁷⁾

4. Statistical analysis

ThedatawereanalyzedusingtheStatisticalPackagefortheSocial Sciencesversion21⁽IBMCo^.,Armonk^,NY^,USA⁾andarepresentedas means^±standarddeviation^.Assumptionsofnormalitywere assessed usingtheKolmogorov–Smirnovtestfor allcontinuousvariables^.All variableswerenormallydistributed^.Anindependentt-testora χ²test wasusedtotestbaselinecomparisonsbetweentheobeseandcontrol groupsfor alldemographicvariables^.Themultivariategenerallinear modelwasimplementedateachvertexinthewholebraintoidentifythe regionsinwhichobesepatientsshowedsignificantdifferencesincortical thickness relativetothecontrols^.Theeffectsofage^,education^,total intracranialvolume⁽TIV^),andsexwereregressedoutinthesemodels^. Allanalyseswereperformedseparatelyfortherightandlefthemispheres. Only regions withclusters of 10or more contiguousvoxelswere reported^,andthethresholdwassetatP<0^.05^,withafalsediscoveryrate (FDR⁾correctionformultiplecomparisons^.Atwo-tailedP-value<0^.05 wasconsideredstatisticallysignificant^.

Table 1. General characteristics of the study participants (n=21) Variable Obese (n=10) Control (n=11) P-value

Age (y) 15.40±4.06 12.82±5.78 0.255

BMI (kg/m²) 25.14±2.75 21.21±2.08 0.001

Total cholesterol (mg/dL) 136.67±16.56 183.50±64.35 0.285 HDL cholesterol (mg/dL) 49.50±10.61 50.33±17.21 0.956 Triglyceride (mg/dL) 64.50±27.58 135.67±90.15 0.377 LDL cholesterol (mg/dL) 69.50±33.23 110.00±35.54 0.292

SBP (mmHg) 118.25±11.29 107.00±9.75 0.094

DBP (mmHg) 72.63±8.67 66.60±6.15 0.205

Glucose (mg/dL) 95.56±15.70 92.67±5.05 0.673

AST (IU) 21.78±12.18 18.57±3.64 0.515

ALT (IU) 30.78±35.35 16.29±6.40 0.306

Education (y) 8.60±3.50 6.18±5.29 0.237

Sex (male/female) 6/4 6/5 0.801

Values are mean±standard deviation or number.

BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate transaminase; ALT, alanine aminotransferase.

Statistical significance was tested using independent t-tests or χ² test.

Table 2. Cortical thickness between two groups

Region Obese group

(n=10)

Control group

(n=11) P-value Right

Inferior parietal 2.573±0.223 2.787±0.155 0.018

Lingual 1.918±0.212 2.177±0.231 0.015

Middle temporal 2.937±0.500 3.284±0.168 0.042 Pars orbitalis 2.815±0.311 3.090±0.198 0.025 Pars triangularis 2.503±0.268 2.807±0.289 0.022 Rostral middlefrontal 2.460±0.138 2.692±0.297 0.036 Mean thickness 2.561±0.208 2.735±0.143 0.036 Left

Inferior parietal 2.662±0.179 2.760±0.176 0.026 Inferior temporal 2.751±0.496 3.105±0.164 0.037 Literal orbitofrontal 2.640±0.291 2.961±0.298 0.022 Medial orbitofrontal 2.546±0.142 2.862±0.256 0.003 Pars opercularis 2.600±0.263 2.793±0.155 0.012 Pars orbitalis 2.697±0.270 3.135±0.280 0.002 Pars triangularis 2.556±0.178 2.824±0.256 0.013

Supramarginal 2.674±0.199 2.837±0.164 0.011

Mean thickness 2.570±0.142 2.737±0.151 0.017 Values are mean±standard deviation.

Statistical significance was tested using analysis of covariance adjusted for age, education, total intracranial volume, and gender.

(4)

KJFP

RESULTS

1. Baseline characteristics of the study participants Table1summarizesthebaselinecharacteristicsofthestudypartici- pants. Therewasnosignificantdifferenceinsex, age, education, and glucoseorlipidprofilebetweenthetwogroups. TheBMIwassignifi- cantlyhigherintheobesegroupthaninthecontrolgroup⁽25^.14^±2^.75 kg^/m²vs^.21^.21^±2^.08kg^/m²^,P<0^.05^).

2. Cortical thickness differences between the obese and control groups

Nosignificantdifferencesbetweentheobese groupandthecontrol groupwereobservedwithregardtothemeanvolumesofthetotalwhite matterineachhemisphere^.However^,comparedtothecontrolgroup^, theobesegroupshowedasignificantreductionin themeancortical thicknessinbothhemispheres⁽Table2^).TheANCOVA^,adjustedfor age^,education^,TIV^,andsex^,revealedasignificantcorticalthickness reductionoftherightinferiorparietallingual, middletemporal, pars orbitalis, parstriangularis, androstralmiddlefrontalcortices. Forthe lefthemisphere^,thethicknessesoftheleftinferiortemporal^,lateral orbitofrontal^,medialorbitofrontal^,parsorbitalis^,andparstriangularis cortices werehigherinthe controlgroup thanintheobesegroup (P<0^.05^).Groupcomparisonanalysisof regionalcorticalthickness betweentheobeseandcontrolgroupsrevealedasignificantreductionin thethicknessoftheleftsupramarginal, inferiorparietal, parsorbitalis, andparsoperculariscorticesintheobesegroupcomparedwiththatin thecontrolgroup⁽P<0^.05^;FDRcorrected^{) (}Figure1andTable3^).

DISCUSSION

Tothebestofourknowledge^,thisisthefirststudytoevaluatethe patternofcorticalatrophyinadolescentobesityusingMRI^.Ourresults demonstrated asignificant reductionin thethicknessof the left supramarginal, inferiorparietal, parsorbitalis, and parsopercularis corticesintheobesegroupcomparedwiththatin thecontrolgroup^. Thesefindingssuggestthatstructuraldifferencesincorticalareasmaybe relatedtoobesityinchildrenandadolescents^.

Wealsoshowedsignificantreductionsinthecorticalthicknessofthe leftsupramarginal^,inferiorparietal^,parsorbitalis^,andparsopercularis corticesofadolescentsintheobesegroupcomparedwiththat inthe control group^.This findinghas implicationsforthe nature ofthe relationshipbetweenbrainanatomyandweightgain^.Consistentwith ourresults^,asimilarpatternofcorticalchangewasdescribedinprevious

Table 3. Mean cortical thickness for clusters where a significant cortical atrophy was observed in obese patients compared to controls (FDR correct- ed, P<0.05)

Region Cortical thickness (mm) No. of vertexes

in cluster

Cluster size (mm²)

Talairach coordinates (X, Y, Z) Obese group (n=10) Control group (n=11)

Left

Supramarginal 2.674±0.199 2.837±0.164 377 180.97 -50.8 -52.8 20.2

Inferior parietal 2.751±0.496 3.105±0.164 128 78.73 -44.5 -70.5 23

Pars orbitalis 2.697±0.270 3.135±0.280 90 42.21 -44.2 40.2 -13.4

Pars opercularis 2.600±0.263 2.793±0.155 14 5.72 -42.2 13.1 4.9

Values are mean±standard deviation.

FDR, false discovery rate.

Statistical significance was tested using analysis of covariance adjusted for age, education, total intracranial volume, and gender.

Figure 1. Statistical maps, corrected for age, education, and sex, show- ing reduced cortical thickness in obese patients relative to that in controls (P<0.05; FDR corrected). The anatomical terms follow the Desi- kan template.¹⁶⁾ FDR, false discovery rate.

Left hemisphere Pars opercularis

Pars orbitalis

Supramarginal Inferior parietal

-4.85 -2.43 0.00 2.43 4.85

(5)

김영균 외. 비만 소아에서 대뇌피질 두께 Korean Journal of Family Practice

KJFP

studiesonobesity^,whichreportedanassociationbetweenBMIand corticalthicknessinadults^.However^,therelationshipbetweenobesity andbrainvolumeinolderadolescentsislesswellestablished^.Inone study^,obeseadolescents⁽14–21yearsold⁾werefoundtohavereduced orbitofrontal cortexvolume, highscoresonalldomainsoftheThree FactorEatingQuestionnaire, andimpairedcognitivetaskperformance, notablyduringtestsoninhibitorycontrol^.Itwashypothesizedtoreflect arelationshipbetweenbodyweight^,orbitofrontalcortex⁽OFC⁾function^, andatendencytodisinhibiteating^.¹⁸⁾Anotherfunctionalimagingstudy inwomenwithameanageof18years^,foundaglobaldecreaseingray matter inobese individualscomparedtothatinleanoroverweight individuals.¹²⁾ Incontrast, no significantassociationbetweencortical thicknessandBMIwasfoundinchildren^.¹⁹⁾

Arecent structural MRIstudyof obesityindicatedthat BMIis negatively associated with thegray matter correspondingto the somatosensorymapsofthemouth^,lips^,andtongue^.²⁰⁾Inthat study^, obesesubjectspresentedwithlowerGMdensitiesthanleanindividuals inthefrontaloperculumandpostcentralgyrus, whichincludecortical areas representingtaste processing. Anotherpositron emission tomographyscan⁽PET⁾studyshowed higherincreasesin theneural activityofthefrontaloperculumandpostcentralgyrusinresponseto the administrationof aliquidmeal inobesewomen^.²¹⁾They also suggestedthatthishigherincreaseincerebralbloodflowoftheparietal cortexinresponsetofoodexposureinobesesubjectsmightbeduetoan initiallylowerneuralactivityofthisbrainareaatrest.²²⁾Consistentwith previousstudies, ourresultsshowedthattheobesegrouppresentedwith significantly lowercorticalthicknessoftheleftparsopercularisand parietalcortices^.Althoughtherewasareductioninthecorticalthickness oftheparietallobeintheobesegroup^,nochangeinthefrontalgray matterwasobservedinourstudy^.Asimilarpatternofcorticalatrophy hasbeendescribedinearlyAlzheimer^’sdiseaseinalongitudinalMRI study,²³⁾inwhichgraymatterlossbeganinthetemporal, entorhinal, andparietallobesbeforeprogressingtoorbitofrontalregionsandbeyond inthelefthemisphere^.Thesefindingssuggestearlyvulnerabilityofthe fronto-parietalexecutivesystemaccordingtoadolescentobesity^.

Interestingly^,ourstudyshowedastructuralchangeinbrainregions relatedtofeedingandbodyweightcontrolinchildrenandadolescents withobesity. Asignificantreductioninthecorticalthicknessoftheleft frontalandparietalcorticeswasobservedintheobesegroupcompared withthatinthecontrolgroup^.Moreover^,numerousfunctionalimaging

studieshavereportedthattheparietalcortexplaysanimportantrolein theresponsetofoodstimuliandthecontroloffoodintake^.Thefasted or^“hungry^”stateisassociatedwith increasedresting-stateregional cerebralbloodflowandincreasedactivityinresponsetovisualfoodcues in theinsularcortex.^24,25)Giventheimportance ofregulatingeating behavior, corticalatrophyinthisareamaydiminishitscapacityto receive information on changes in energy balance after food consumption^,whichmayleadtoexcessivefoodintake^.Increasedactivity intheparietal cortexinresponseto visualfood exposurewasalso reportedinapreviousstudyofobesewomen^,butasimilarresponsewas notobservedinnormal-weightwomen^.²²⁾Inaddition^,inalargestudyof 1,428individuals, higherBMIswereassociatedwithsmallervolumesin thefrontal^,temporal^,andparietalcortices^,aswellasthecerebellum^.²⁶⁾

Thisstudyhassomelimitations^.First^,notallsubcorticalregionscan be examinedusing the presentmethods^;forinstance^,FreeSurfer softwaredoes notofferautomaticsegmentationforthehypothalamus^. Anotherlimitationofthepresentstudyisitscross-sectionalnature^;asa result, wewereunabletodeterminecausalitybetweenstructuralbrain changesandobesityorwhethertheyarereversible. Furthermore, dueto thesmallsamplesize^,wefounddifferencesinsubcorticalvolumeinthe subjectswithobesity^,whichfailedtoreachsignificanceaftercorrection formultiple comparisons^.However^,inotherstudieson childhood obesity^,BMIwascorrelatedwithsubcorticalreward-relatedregions^.^11,12,27) Furtherprospectivestudieswith largersamplesizesare requiredto evaluate therelationshipbetween changes in brainstructure and childhoodobesityovertime.

Inconclusion^,wedemonstratedasignificantreductioninthecortical thicknesses^,especiallyoftheareasinvolvedinbodyweightcontroland cognitivefunction^,suchastheleftsupramarginal^,inferiorparietal^,pars orbitalis^,andparsoperculariscortices^,ofobesepatients^.Basedonthese findings^,itislikelythatobesechildrenandadolescentsexhibitstructural brainabnormalities. Furtherprospectivestudiesarerequiredtoevaluate therelationship betweenearlystructuralbrainchangesand BMIin childrenandadolescentswithobesity^.

ACKNOWLEDGEMENTS

Thiswork wassupportedbytheNationalResearchFoundation of Korea (NRF) grantfundedbythe Koreagovernment (MSIT) (No. 2019R1F1A1062937⁾andSt^.Vincent^’sHospital^,ResearchInstitute of

(6)

KJFP

MedicalScienceFoundation⁽SVHR-2015-03^).

CONFLICT OF INTEREST

Nopotentialconflictofinterestrelevanttothisarticlewasreported^. ORCID

YoungKyunKim^,https^://orcid^.org^/0000-0002-1331-088X Se-HongKim^,https^://orcid^.org^/0000-0001-6465-8993 Tae-HongKim^,https^://orcid^.org^/0000-0003-4984-7563 Ju-HyeChung, https://orcid.org/0000-0001-9543-7181 Young-MiEun^,https^://orcid^.org^/0000-0002-4439-7826

REFERENCES

1. World Health Organization. Fact sheets. Obesity and overweight [Internet].

Geneva: World Health Organization; 2017 [cited 2018 May 29]. Available from: https://www.who.int/en/news-room/fact-sheets/detail/obesity-and- overweight.

2. NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 popu- lation-based measurement studies with 19·2 million participants. Lancet 2016; 387: 1377-96.

3. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Soci- ety. J Am Coll Cardiol 2014; 63(25 Pt B): 2985-3023.

4. Gupta N, Shah P, Nayyar S, Misra A. Childhood obesity and the metabolic syndrome in developing countries. Indian J Pediatr 2013; 80 Suppl 1: S28-37.

5. Olshansky SJ, Passaro DJ, Hershow RC, Layden J, Carnes BA, Brody J, et al. A potential decline in life expectancy in the United States in the 21st century.

N Engl J Med 2005; 352: 1138-45.

6. Körner A, Wiegand S, Hungele A, Tuschy S, Otto KP, l'Allemand-Jander D, et al. Longitudinal multicenter analysis on the course of glucose metabolism in obese children. Int J Obes (Lond) 2013; 37: 931-6.

7. Fonseca H, Matos MG, Guerra A, Pedro JG. Are overweight and obese adolescents different from their peers? Int J Pediatr Obes 2009; 4: 166-74.

8. Must A, Jacques PF, Dallal GE, Bajema CJ, Dietz WH. Long-term morbidity and mortality of overweight adolescents. A follow-up of the Harvard Growth Study of 1922 to 1935. N Engl J Med 1992; 327: 1350-5.

9. Jagust W. What can imaging reveal about obesity and the brain? Curr Al- zheimer Res 2007; 4: 135-9.

10. Raji CA, Ho AJ, Parikshak NN, Becker JT, Lopez OL, Kuller LH, et al. Brain structure and obesity. Hum Brain Mapp 2010; 31: 353-64.

11. Yau PL, Kang EH, Javier DC, Convit A. Preliminary evidence of cognitive and brain abnormalities in uncomplicated adolescent obesity. Obesity (Sil-

ver Spring) 2014; 22: 1865-71.

12. Yokum S, Ng J, Stice E. Relation of regional gray and white matter volumes to current BMI and future increases in BMI: a prospective MRI study. Int J Obes (Lond) 2012; 36: 656-64.

13. Segura B, Jurado MA, Freixenet N, Falcón C, Junqué C, Arboix A. Micro- structural white matter changes in metabolic syndrome: a diffusion tensor imaging study. Neurology 2009; 73: 438-44.

14. Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmenta- tion and surface reconstruction. Neuroimage 1999; 9: 179-94.

15. Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 2000; 97:

11050-5.

16. Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al.

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006; 31:

968-80.

17. Jovicich J, Czanner S, Han X, Salat D, van der Kouwe A, Quinn B, et al. MRI- derived measurements of human subcortical, ventricular and intracranial brain volumes: reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths. Neuroimage 2009; 46: 177-92.

18. Zhang JP, Weiss JJ, McCardle M, Klopchin H, Rosendahl E, Maayan L, et al.

Effectiveness of a cognitive behavioral weight management intervention in obese patients with psychotic disorders compared to patients with nonpsy- chotic disorders or no psychiatric disorders: results from a 12-month, real- world study. J Clin Psychopharmacol 2012; 32: 458-64.

19. Sharkey RJ, Karama S, Dagher A. Overweight is not associated with cortical thickness alterations in children. Front Neurosci 2015; 9: 24.

20. Pannacciulli N, Del Parigi A, Chen K, Le DS, Reiman EM, Tataranni PA.

Brain abnormalities in human obesity: a voxel-based morphometric study.

Neuroimage 2006; 31: 1419-25.

21. Wang GJ, Volkow ND, Felder C, Fowler JS, Levy AV, Pappas NR, et al. En- hanced resting activity of the oral somatosensory cortex in obese subjects.

Neuroreport 2002; 13: 1151-5.

22. Karhunen LJ, Lappalainen RI, Vanninen EJ, Kuikka JT, Uusitupa MI. Re- gional cerebral blood flow during food exposure in obese and normal- weight women. Brain 1997; 120 (Pt 9): 1675-84.

23. Thompson PM, Hayashi KM, de Zubicaray G, Janke AL, Rose SE, Semple J, et al. Dynamics of gray matter loss in Alzheimer's disease. J Neurosci 2003;

23: 994-1005.

24. Hinton EC, Parkinson JA, Holland AJ, Arana FS, Roberts AC, Owen AM.

Neural contributions to the motivational control of appetite in humans. Eur J Neurosci 2004; 20: 1411-8.

25. Chechlacz M, Rotshtein P, Klamer S, Porubská K, Higgs S, Booth D, et al. Di- abetes dietary management alters responses to food pictures in brain regions associated with motivation and emotion: a functional magnetic resonance imaging study. Diabetologia 2009; 52: 524-33.

26. Taki Y, Kinomura S, Sato K, Inoue K, Goto R, Okada K, et al. Relationship between body mass index and gray matter volume in 1,428 healthy individuals. Obesity (Silver Spring) 2008; 16: 119-24.

27. Alosco ML, Stanek KM, Galioto R, Korgaonkar MS, Grieve SM, Brickman AM, et al. Body mass index and brain structure in healthy children and adolescents. Int J Neurosci 2014; 124: 49-55.