Body mass index (BMI) changes may be related to Alzheimer’s disease (AD) alterations, but it is unclear how the apolipoprotein E ɛ4 (APOE ɛ4) allele affects their association.
Objective:
To explore the association of BMI changes with AD pathologies in APOE ɛ4 carriers and non-carriers.
Methods:
In 862 non-demented ADNI participants with≥2 BMI measurements, we investigated the relationships between BMI slopes and longitudinal changes in amyloid-β (Aβ) accumulation, neurodegeneration and cognition, and follow-up tau deposition in different Aβ and APOE ɛ4 statuses.
Results:
In Aβ+ APOE ɛ4 non-carriers, faster BMI declines were associated with faster rates of Aβ accumulation (standardized β (βstd) = –0.29, p = 0.001), AD meta regions of interest (metaROI) hypometabolism (βstd = 0.23, p = 0.026), memory declines (βstd = 0.17, p = 0.029), executive function declines (βstd = 0.19, p = 0.011), and marginally faster Temporal-metaROI cortical thinning (βstd = 0.15, p = 0.067) and higher follow-up Temporal-metaROI tau deposition (βstd = –0.17, p = 0.059). Among Aβ- individuals, faster BMI decreases were related to faster Aβ accumulation (βstd = –0.25, p = 0.023) in APOE ɛ4 carriers, whereas predicted faster declines in memory and executive function in both APOE ɛ4 carriers (βstd = 0.25, p = 0.008; βstd = 0.32, p = 0.001) and APOE ɛ4 non-carriers (βstd = 0.11, p = 0.030; βstd = 0.12, p = 0.026).
Conclusions:
This study highlights the significance of tracking BMI data in older adults by providing novel insights into how body weight fluctuations and APOE ɛ4 interact with AD pathology and cognitive decline.
GuoT, KormanD, La JoieR, ShawLM, TrojanowskiJQ, JagustWJ, LandauSM (2020) Normalization of CSF pTau measurement by Aβ40 improves its performance as a biomarker of Alzheimer’s disease. Alzheimers Res Ther12, 97.
4.
GuoT, BrendelM, GrimmerT, RomingerA, YakushevI (2017) Predicting regional pattern of longitudinal β-amyloid accumulation by baseline PET. J Nucl Med58, 639–645.
5.
ProfennoLA, PorsteinssonAP, FaraoneS V. (2010) Meta-analysis of Alzheimer’s disease risk with obesity, diabetes, and related disorders. Biol Psychiatry67, 505–512.
6.
Zeki Al HazzouriA, VittinghoffE, HoangT, GoldenSH, FitzpatrickAL, ZhangA, GrassetL, YaffeK (2021) Body mass index in early adulthood and dementia in late life: Findings from a pooled cohort. Alzheimers Dement17, 1798–1807.
7.
FitzpatrickAL, KullerLH, LopezOL, DiehrP, O’MearaES, LongstrethWT, LuchsingerJA (2009) Midlife and late-life obesity and the risk of dementia: Cardiovascular health study. Arch Neurol66, 336–342.
HsuDC, MorminoEC, SchultzAP, AmariglioRE, DonovanNJ, RentzDM, JohnsonKA, SperlingRA, MarshallGA (2016) Lower late-life body-mass index is associated with higher cortical amyloid burden in clinically normal elderly. J Alzheimers Dis53, 1097–1105.
10.
ThirunavuV, McCulloughA, SuY, FloresS, DincerA, MorrisJC, CruchagaC, BenzingerTLS, GordonBA (2019) Higher body mass index is associated with lower cortical amyloid-β burden in cognitively normal individuals in late-life. J Alzheimers Dis69, 817–827.
11.
VidoniED, TownleyRA, HoneaRA, BurnsJM (2011) Alzheimer disease biomarkers are associated with body mass index. Neurology77, 1913.
12.
WidyaRL, De RoosA, TrompetS, De CraenAJM, WestendorpRGJ, Smit BuchemJWA, VanMA, Van Der GrondJ (2011) Increased amygdalar and hippocampal volumes in elderly obese individuals with or at risk of cardiovascular disease. Am J Clin Nutr93, 1190–1195.
13.
PeguerolesJ, PanéA, VilaplanaE, MontalV, BejaninA, VidelaL, Carmona-IraguiM, BarroetaI, IbarzabalA, CasajoanaA, AlcoleaD, ValldeneuS, AltunaM, de HollandaA, VidalJ, OrtegaE, OsorioR, ConvitA, BlesaR, LleóA, ForteaJ, JiménezA (2020) Obesity impacts brain metabolism and structure independently of amyloid and tau pathology in healthy elderly. Alzheimers Dement (Amst)12, e12052.
14.
SunZ, WangZT, SunFR, ShenXN, XuW, MaYH, DongQ, TanL, YuJTAlzheimer’s Disease Neuroimaging Initiative (2020) Late-life obesity is a protective factor for prodromal Alzheimer’s disease: A longitudinal study. Aging (Albany NY)12, 2005.
15.
LaneCA, BarnesJ, NicholasJM, BakerJW, SudreCH, CashDM, ParkerTD, MaloneIB, LuK, JamesSN, KeshavanA, BuchananS, KeussS, Murray-SmithH, WongA, GordonE, CoathW, ModatM, ThomasD, HardyR, RichardsM, FoxNC, SchottJM (2021) Investigating the relationship between BMI across adulthood and late life brain pathologies. Alzheimers Res Ther13, 91.
16.
XuW, SunFR, TanCC, TanL (2020) Weight loss is a preclinical signal of cerebral amyloid deposition and could predict cognitive impairment in elderly adults. J Alzheimers Dis77, 449–456.
17.
RabinJS, ShirzadiZ, SwardfagerW, MacIntoshBJ, SchultzA, YangHS, BuckleyRF, GatchelJR, KirnD, PruzinJJ, HeddenT, LipsmanN, RentzDM, BlackSE, JohnsonKA, SperlingRA, ChhatwalJP (2020) Amyloid-beta burden predicts prospective decline in body mass index in clinically normal adults. Neurobiol Aging93, 124–130.
MartensYA, ZhaoN, LiuCC, KanekiyoT, YangAJ, GoateAM, HoltzmanDM, BuG (2022) ApoE Cascade Hypothesis in the pathogenesis of Alzheimer’s disease and related dementias. Neuron110, 1304–1317.
MoserVA, PikeCJ (2017) Obesity accelerates Alzheimer-related pathology in APOE4 but not APOE3 mice. eNeuro4, ENEURO.0077–17.201.
22.
ZhaoN, LiuCC, Van IngelgomAJ, MartensYA, LinaresC, KnightJA, PainterMM, SullivanPM, BuG (2017) Apolipoprotein E4 impairs neuronal insulin signaling by trapping insulin receptor in the endosomes. Neuron96, 115–129.e5.
23.
BlautzikJ, KotzS, BrendelM, SauerbeckJ, VettermannF, WinterY, BartensteinP, IshiiK, RomingerA (2018) Relationship between body mass index, ApoE4 Status, and PET-Based amyloid and neurodegeneration markers in amyloid-positive subjects with normal cognition or mild cognitive impairment. J Alzheimers Dis65, 781–791.
HuangSJ, MaYH, BiYL, ShenXN, HouXH, CaoXP, OuYN, ZhaoB, DongQ, TanL, YuJT (2021) Metabolically healthy obesity and lipids may be protective factors for pathological changes of Alzheimer’s disease in cognitively normal adults. J Neurochem157, 834–845.
27.
DesikanRS, SégonneF, FischlB, QuinnBT, DickersonBC, BlackerD, BucknerRL, DaleAM, MaguireRP, HymanBT, AlbertMS, KillianyRJ (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage31, 968–980.
28.
LandauSM, FeroA, BakerSL, KoeppeR, MintunM, ChenK, ReimanEM, JagustWJ (2015) Measurement of longitudinal β-amyloid change with 18F-florbetapir PET and standardized uptake value ratios. J Nucl Med56, 567–574.
29.
GuoT, ShawLM, TrojanowskiJQ, JagustWJ, LandauSM (2020) Association of CSF Aβ, amyloid PET, and cognition in cognitively unimpaired elderly adults. Neurology95, E2075–E2085.
30.
MaassA, LandauS, HorngA, LockhartSN, RabinoviciGD, JagustWJ, BakerSL, La JoieR (2017) Comparison of multiple tau-PET measures as biomarkers in aging and Alzheimer’s disease. Neuroimage157, 448–463.
LandauSM, HarveyD, MadisonCM, KoeppeRA, ReimanEM, FosterNL, WeinerMW, JagustWJ (2011) Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging32, 1207–1218.
CranePK, CarleA, GibbonsLE, InselP, MackinRS, GrossA, JonesRN, MukherjeeS, CurtisSMK, HarveyD, WeinerM, MungasD (2012) Development and assessment of a composite score for memory in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Brain Imaging Behav6, 502–516.
35.
GibbonsLE, CarleAC, MackinRS, HarveyD, MukherjeeS, InselP, CurtisSMK, MungasD, CranePK (2012) A composite score for executive functioning, validated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging Behav6, 517–527.
36.
GuoT, LandauSM, JagustWJ (2020) Detecting earlier stages of amyloid deposition using PET in cognitively normal elderly adults. Neurology94, E1512–E1524.
37.
JonesNS, WatsonKQ, RebeckGW (2021) High-fat diet increases gliosis and immediate early gene expression in APOE 3 mice, but not APOE4 mice. J Neuroinflammation18, 214.
38.
EwersM, BiecheleG, Suárez-CalvetM, SacherC, BlumeT, Morenas-RodriguezE, DemingY, PiccioL, CruchagaC, KleinbergerG, ShawL, TrojanowskiJQ, HermsJ, DichgansM, BrendelM, HaassC, FranzmeierN (2020) Higher CSF sTREM2 and microglia activation are associated with slower rates of beta-amyloid accumulation. EMBO Mol Med12, e12308.
39.
EwersM, SchmitzS, HanssonO, WalshC, FitzpatrickA, BennettD, MinthonL, TrojanowskiJQ, ShawLM, FaluyiYO, VellasB, DuboisB, BlennowK, BuergerK, TeipelSJ, WeinerM, HampelH (2012) Body mass index is associated with biological CSF markers of core brain pathology of Alzheimer’s disease. Neurobiol Aging33, 1599–1608.
40.
ShiD, XieS, LiA, WangQ, GuoH, HanY, XuH, GanWB, ZhangL, GuoT (2022) APOE-ɛ4 modulates the association among plasma Aβ42/Aβ40, vascular diseases, neurodegeneration and cognitive decline in non-demented elderly adults. Transl Psychiatry12, 128.
41.
SalaA, MalpettiM, FerrulliA, GianolliL, LuziL, PeraniD, Alzheimer’s Disease Neuroimaging Initiative A (2019) High body mass index, brain metabolism and connectivity: An unfavorable effect in elderly females. Aging (Albany NY)11, 8573.
42.
CraftS, Stennis WatsonG (2004) Insulin and neurodegenerative disease: Shared and specific mechanisms. Lancet Neurol3, 169–178.
43.
SmithE, BaileyPE, CrawfordJ, SamarasK, BauneBT, CampbellL, KochanN, MenantJ, SturnieksDL, BrodatyH, SachdevP, TrollorJN (2014) Adiposity estimated using dual energy x-ray absorptiometry and body mass index and its association with cognition in elderly adults. J Am Geriatr Soc62, 2311–2318.
44.
CovaI, PomatiS, MaggioreL, ForcellaM, CucumoV, GhirettiR, GrandeG, MuzioF, MarianiC (2017) Nutritional status and body composition by bioelectrical impedance vector analysis: A cross sectional study in mild cognitive impairment and Alzheimer’s disease. PLoS One12, e0171331.
