Executive dysfunction in mild cognitive impairment (MCI) has been associated with gray matter atrophy. Prior studies have yielded limited insight into associations between gray matter volume and executive function in early and late amnestic MCI (aMCI).
Objective:
To examine the relative importance of predictors of executive function at 24 months and relationships between baseline regional gray matter volume and executive function performance at 24-month follow-up in non-demented older adults.
Methods:
147 participants from the Alzheimer’s Disease Neuroimaging Initiative (mean age = 70.6 years) completed brain magnetic resonance imaging and neuropsychological testing and were classified as cognitively normal (n = 49), early aMCI (n = 60), or late aMCI (n = 38). Analyses explored the importance of demographic, APOEɛ4, biomarker (p-tau/Aβ42, t-tau/Aβ42), and gray matter regions-of-interest (ROI) variables to 24-month executive function, whether ROIs predicted executive function, and whether relationships varied by baseline diagnostic status.
Results:
Across all participants, baseline anterior cingulate cortex and superior parietal lobule volumes were the strongest predictors of 24-month executive function performance. In early aMCI, anterior cingulate cortex volume was the strongest predictor and demonstrated a significant interaction such that lower volume related to worse 24-month executive function in early aMCI. Educational attainment and inferior frontal gyrus volume were the strongest predictors of 24-month executive function performance for cognitively normal and late aMCI groups, respectively.
Conclusions:
Baseline frontoparietal gray matter regions were significant predictors of executive function performance in the context of aMCI and may identify those at risk of Alzheimer’s disease. Anterior cingulate cortex volume may predict executive function performance in early aMCI.
AlbertMS, DeKoskyST, DicksonD, DuboisB, FeldmanHH, FoxNC, GamstA, HoltzmanDM, JagustWJ, PetersenRC, SnyderPJ, CarrilloMC, ThiesB, PhelpsCH (2011) The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement7, 270–279.
PetersenRC, KnopmanDS, BoeveBF, GedaYE, IvnikRJ, SmithGE, RobertsRO, JackCR (2009) Mild cognitive impairment: Ten years later. Arch Neurol66, 1447–1455.
7.
JohnsEK, PhillipsNA, BellevilleS, GoupilD, BabinsL, KelnerN, SkaB, GilbertB, MassoudF, de BoyssonC, DuncanHD, ChertkowH (2012) The profile of executive functioning in amnestic mild cognitive impairment: Disproportionate deficits in inhibitory control. J Int Neuropsychol Soc18, 541–555.
8.
RobertsR, KnopmanDS (2013) Classification and epidemiology of MCI. Clin Geriatr Med29, 753–772.
9.
BrandtJ, AretouliE, NeijstromE, SamekJ, ManningK, AlbertMS, Bandeen-RocheK (2009) Selectivity of executive function deficits in mild cognitive impairment. Neuropsychology23, 607–618.
10.
LeyheT, SaurR, EschweilerGW, MilianM (2011) Impairment in proverb interpretation as an executive function deficit in patients with amnestic mild cognitive impairment and early Alzheimer’s disease. Dement Geriatr Cogn Disord EXTRA1, 51–61.
AlvarezJA, EmoryE (2006) Executive function and the frontal lobes: A meta-analytic review. Neuropsychol Rev16, 17–42.
13.
GoldsteinS, NaglieriJA, PrinciottaD, OteroTM (2014) Introduction: A history of executive functioning as a theoretical and clinical construct. In Handbook of executive functioning, Springer Science+Business Media, New York, NY, US, pp. 3–12.
14.
RozziniL, ChiloviBV, ContiM, BertolettiE, DelrioI, TrabucchiM, PadovaniA (2007) Conversion of amnestic mild cognitive impairment to dementia of Alzheimer type is independent to memory deterioration. Int J Geriatr Psychiatry22, 1217–1222.
15.
MarshallGA, RentzDM, FreyMT, LocascioJJ, JohnsonKA, SperlingRA (2011) Executive function and instrumental activities of daily living in mild cognitive impairment and Alzheimer’s disease. Alzheimers Dement7, 300–308.
16.
EdmondsEC, McDonaldCR, MarshallA, ThomasKR, EppigJ, WeigandAJ, Delano-WoodL, GalaskoDR, SalmonDP, BondiMW (2019) Early versus late MCI: Improved MCI staging using a neuropsychological approach. Alzheimers Dement15, 699–708.
LeeS, SeoJ, LeeJ, ParkH, AdniT (2014) Differences in early and late mild cognitive impairment tractography using a diffusion tensor MRI. Neuroreport25, 1393–1398.
19.
YeBS, SeoSW, YangJJ, KimHJ, KimYJ, YoonCW, ChoH, NohY, KimGH, ChinJ, KimJ-H, JeonS, LeeJM, NaDL (2014) Comparison of cortical thickness in patients with early-stage versus late-stage amnestic mild cognitive impairment. Eur J Neurol21, 86–92.
JessenF, WolfsgruberS, WieseB, BickelH, MöschE, KaduszkiewiczH, PentzekM, Riedel-HellerSG, LuckT, FuchsA, WeyererS, WerleJ, van den BusscheH, SchererM, MaierW, WagnerM (2014) AD dementia risk in late MCI, in early MCI, and in subjective memory impairment. Alzheimers Dement10, 76–83.
22.
QiuY, LiL, ZhouT, LuW (2014) Alzheimer’s disease progression model based on integrated biomarkers and clinical measures. Acta Pharmacol Sin35, 1111–1120.
23.
WeiH, KongM, ZhangC, GuanL, BaM (2018) The structural MRI markers and cognitive decline in prodromal Alzheimer’s disease: A 2-year longitudinal study. Quant Imaging Med Surg8, 1004–1019.
24.
LinS, LinP, LinY, LeeY, WangC, PengS, WangP (2022) The clinical course of early and late mild cognitive impairment. Front Neurol13, 685636.
25.
CardenasVA, ChaoLL, StudholmeC, YaffeK, MillerBL, MadisonC, BuckleyST, MungasD, SchuffN, WeinerMW (2011) Brain atrophy associated with baseline and longitudinal measures of cognition. Neurobiol Aging32, 572–580.
26.
ManardM, BahriMA, SalmonE, ColletteF (2016) Relationship between grey matter integrity and executive abilities in aging. Brain Res1642, 562–580.
27.
StussDT, AlexanderMP (2000) Executive functions and the frontal lobes: A conceptual view. Psychol Res63, 289–298.
28.
ZhangH, SachdevPS, WenW, KochanNA, ZhuW, CrawfordJD, BrodatyH, SlavinMJ, ReppermundS, KangK, TrollorJN (2011) Neuroanatomical correlates of cognitive performance in late life. Dement Geriatr Cogn Disord32, 216–226.
29.
van de MortelLA, ThomasRM, van WingenGA, Initiative for the ADN (2021) Grey matter loss at different stages of cognitive decline: A role for the thalamus in developing Alzheimer’s disease. J Alzheimers Dis83, 705–720.
30.
KangDW, LimHK, JooS, LeeNR, LeeCU (2019) Differential associations between volumes of atrophic cortical brain regions and memory performances in early and late mild cognitive impairment. Front Aging Neurosci11, 245.
31.
LeeP, RyooH, ParkJ, JeongY (2017) Morphological and microstructural changes of the hippocampus in early MCI: A study utilizing the Alzheimer’s Disease Neuroimaging Initiative database. J Clin Neurol13, 144–154.
32.
GibbonsLE, CarleAC, MackinRS, HarveyD, MukherjeeS, InselP, CurtisSM, 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.
MenonV, D’EspositoM (2022) The role of PFC networks in cognitive control and executive function. Neuropsychopharmacology47, 90–103.
35.
ChételatG, DesgrangesB, de la SayetteV, ViaderF, EustacheF, BaronJ-C (2002) Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment. Neuroreport13, 1939–1943.
36.
DuarteA, HayasakaS, DuA, SchuffN, JahngG-H, KramerJ, MillerB, WeinerM (2006) Volumetric correlates of memory and executive function in normal elderly, mild cognitive impairment and Alzheimer’s disease. Neurosci Lett406, 60–65.
37.
KarasGB, ScheltensP, RomboutsSARB, VisserPJ, van SchijndelRA, FoxNC, BarkhofF (2004) Global and local gray matter loss in mild cognitive impairment and Alzheimer’s disease. Neuroimage23, 708–716.
38.
ZhangJ, LiuY, LanK, HuangX, HeY, YangF, LiJ, HuQ, XuJ, YuH (2021) Gray matter atrophy in amnestic mild cognitive impairment: A voxel-based meta-analysis. Front Aging Neurosci13, 627919.
39.
JapeeS, HolidayK, SatyshurMD, MukaiI, UngerleiderLG (2015) A role of right middle frontal gyrus in reorienting of attention: A case study. Front Syst Neurosci9, 23.
40.
HuS, IdeJS, ZhangS, LiCR (2016) The right superior frontal gyrus and individual variation in proactive control of impulsive response. J Neurosci36, 12688–12696.
ShiC, DengH, DengX, RaoD, YueW (2023) The structural changes of frontal subregions and their correlations with cognitive impairment in patients with Alzheimer’s disease. J Integr Neurosci22, 99.
43.
PaJ, PossinKL, WilsonSM, QuitaniaLC, KramerJH, BoxerAL, WeinerMW, JohnsonJK (2010) Gray matter correlates of set-shifting among neurodegenerative disease, mild cognitive impairment, and healthy older adults. J Int Neuropsychol Soc16, 640–650.
44.
VickeryTJ, JiangYV (2009) Inferior parietal lobule supports decision making under uncertainty in humans. Cereb Cortex19, 916–925.
45.
JacobsHIL, Van BoxtelMPJ, JollesJ, VerheyFRJ, UylingsHBM (2012) Parietal cortex matters in Alzheimer’s disease: An overview of structural, functional and metabolic findings. Neurosci Biobehav Rev36, 297–309.
46.
JacobsHIL, Van BoxtelMPJ, UylingsHBM, GronenschildEHBM, VerheyFR, JollesJ (2011) Atrophy of the parietal lobe in preclinical dementia. Brain Cogn75, 154–163.
47.
ShomsteinS (2012) Cognitive functions of the posterior parietal cortex: Top-down and bottom-up attentional control. Front Integr Neurosci6, 38.
48.
DuAT, SchuffN, AmendD, LaaksoMP, HsuYY, JagustWJ, YaffeK, KramerJH, ReedB, NormanD, ChuiHC, WeinerMW (2001) Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J Neurol Neurosurg Psychiatry71, 441–447.
MuY, GageFH (2011) Adult hippocampal neurogenesis and its role in Alzheimer’s disease. Mol Neurodegener6, 85.
51.
GrömpingU (2006) Relative importance for linear regression in R: The Package relaimpo. J Stat Softw17, 1–27.
52.
HanssonO, SeibylJ, StomrudE, ZetterbergH, TrojanowskiJQ, BittnerT, LifkeV, CorradiniV, EichenlaubU, BatrlaR, BuckK, ZinkK, RabeC, BlennowK, ShawLM (2018) CSF biomarkers of Alzheimer’s disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement14, 1470–1481.
53.
YekutieliD, BenjaminiY (1999) Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics. J Stat Plan Inference82, 171–196.
54.
CranePK, CarleA, GibbonsLE, InselP, MackinRS, GrossA, JonesRN, MukherjeeS, CurtisSM, 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.
55.
JackCR, KnopmanDS, JagustWJ, ShawLM, AisenPS, WeinerMW, PetersenRC, TrojanowskiJQ (2010) Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol9, 119.
56.
CarterCS, MacdonaldAM, BotvinickM, RossLL, StengerVA, NollD, CohenJD (2000) Parsing executive processes: Strategic vs. evaluative functions of the anterior cingulate cortex. Proc Natl Acad Sci U S A97, 1944–1948.
57.
SalehinejadMA, GhanavatiE, RashidMHA, NitscheMA (2021) Hot and cold executive functions in the brain: A prefrontal-cingular network. Brain Neurosci Adv5, 23982128211007769.
58.
GläscherJ, AdolphsR, DamasioH, BecharaA, RudraufD, CalamiaM, PaulLK, TranelD (2012) Lesion mapping of cognitive control and value-based decision making in the prefrontal cortex. Proc Natl Acad Sci U S A109, 14681–14686.
59.
Elderkin-ThompsonV, BallmaierM, HellemannG, PhamD, KumarA (2008) Executive function and MRI prefrontal volumes among healthy older adults. Neuropsychology22, 626–637.
KoenigsM, BarbeyAK, PostleBR, GrafmanJ (2009) Superior parietal cortex is critical for the manipulation of information in working memory. J Neurosci29, 14980–14986.
62.
AlahmadiAAS (2021) Investigating the sub-regions of the superior parietal cortex using functional magnetic resonance imaging connectivity. Insights Imaging12, 47.
63.
MolenberghsP, MesulamMM, PeetersR, VandenbergheRRC (2007) Remapping attentional priorities: Differential contribution of superior parietal lobule and intraparietal sulcus. Cereb Cortex17, 2703–2712.
64.
AmaefuleCO, DyrbaM, WolfsgruberS, PolcherA, SchneiderA, FliessbachK, SpottkeA, MeiberthD, PreisL, PetersO, IncesoyEI, SpruthEJ, PrillerJ, AltensteinS, BartelsC, WiltfangJ, JanowitzD, BürgerK, LaskeC, MunkM, RudolphJ, GlanzW, DobischL, HaynesJD, DechentP, Ertl-WagnerB, SchefflerK, KilimannI, DüzelE, MetzgerCD, WagnerM, JessenF, TeipelSJ (2020) Association between composite scores of domain-specific cognitive functions and regional patterns of atrophy and functional connectivity in the Alzheimer’s disease spectrum. Neuroimage Clin29, 102533.
65.
ChetelatG, BaronJ-C (2003) Early diagnosis of Alzheimer’s disease: Contribution of structural neuroimaging. Neuroimage18, 525–541.
66.
KillianyRJ, Gomez-IslaT, MossM, KikinisR, SandorT, JoleszF, TanziR, JonesK, HymanBT, AlbertMS (2000) Use of structural magnetic resonance imaging to predict who will get Alzheimer’s disease. Ann Neurol47, 430–439.
67.
RollsET (2019) The cingulate cortex and limbic systems for emotion, action, and memory. Brain Struct Funct224, 3001–3018.
68.
Bell-McGintyS, LopezOL, MeltzerCC, ScanlonJM, WhyteEM, DekoskyST, BeckerJT (2005) Differential cortical atrophy in subgroups of mild cognitive impairment. Arch Neurol62, 1393–1397.
69.
HanY, LuiS, KuangW, LangQ, ZouL, JiaJ (2012) Anatomical and functional deficits in patients with amnestic mild cognitive impairment. PLoS One7, e28664.
70.
ScahillRI, SchottJM, StevensJM, RossorMN, FoxNC (2002) Mapping the evolution of regional atrophy in Alzheimer’s disease: Unbiased analysis of fluid-registered serial MRI. Proc Natl Acad Sci U S A99, 4703–4707.
71.
WhitwellJL (2010) Progression of atrophy in Alzheimer’s disease and related disorders. Neurotox Res18, 339–346.
72.
ThompsonPM, HayashiKM, DuttonRA, ChiangM-C, LeowAD, SowellER, De ZubicarayG, BeckerJT, LopezOL, AizensteinHJ, TogaAW (2007) Tracking Alzheimer’s disease. Ann N Y Acad Sci1097, 183–214.
73.
van HoorenSAH, ValentijnAM, BosmaH, PondsRWHM, van BoxtelMPJ, JollesJ (2007) Cognitive functioning in healthy older adults aged 64–81: A cohort study into the effects of age, sex, and education. Aging Neuropsychol Cogn14, 40–54.
74.
BosmaH, van BoxtelMPJ, PondsRWHM, HouxPJH, JollesJ (2003) Education and age-related cognitive decline: The contribution of mental workload. Educ Gerontol29, 165–173.
75.
TunPA, LachmanME (2008) Age differences in reaction time and attention in a national telephone sample of adults: Education, sex, and task complexity matter. Dev Psychol44, 1421–1429.
BrooksBL, WeaverLE, ScialfaCT (2006) Does impaired executive functioning differentially impact verbal memory measures in older adults with suspected dementia?Clin Neuropsychol20, 230–242.
78.
ChangY, JacobsonMW, Fennema-NotestineC, HaglerDJ, JenningsRG, DaleAM, McEvoyLK, Alzheimer’s Disease Neuroimaging Initiative (2010) Level of executive function influences verbal memory in amnestic mild cognitive impairment and predicts prefrontal and posterior cingulate thickness. Cereb Cortex20, 1305–1313.
79.
CabezaR, DolcosF, GrahamR, NybergL (2002) Similarities and differences in the neural correlates of episodic memory retrieval and working memory. Neuroimage16, 317–330.
80.
YuanB, ChenJ, GongL, ShuH, LiaoW, WangZ, LiuD, XieC, ZhangZ (2016) Mediation of episodic memory performance by the executive function network in patients with amnestic mild cognitive impairment: A resting-state functional MRI study. Oncotarget7, 64711–64725.
81.
SquireLR, KnowltonB, MusenG (1993) The structure and organization of memory. Annu Rev Psychol44, 453–495.
82.
SchacterDL, WagnerAD (1999) Medial temporal lobe activations in fMRI and PET studies of episodic encoding and retrieval. Hippocampus9, 7–24.
HaydenKM, JonesRN, ZimmerC, PlassmanBL, BrowndykeJN, PieperC, WarrenLH, Welsh-BohmerKA (2011) Factor structure of the National Alzheimer’s Coordinating Centers Uniform Dataset Neuropsychological Battery: An evaluation of invariance between and within groups over time. Alzheimer Dis Assoc Disord25, 128.
85.
ParkLQ, GrossAL, McLarenDG, PaJ, JohnsonJK, MitchellM, ManlyJJ, for the Alzheimer’s Disease Neuroimaging Initiative (2012) Confirmatory factor analysis of the ADNI neuropsychological battery. Brain Imaging Behav6, 528–539.
BrooksBL, ShermanEMS, IversonGL, SlickDJ, StraussE (2011) Psychometric foundations for the interpretation of neuropsychological test results. In The little black book of neuropsychology: A syndrome-based approach, Springer Science + Business Media, New York, NY, US, pp. 893–922.
