The impact of APOE ε4 in Alzheimer’s disease: a meta-analysis of voxel-based morphometry studies

The impact of APOE ε4 in Alzheimer’s disease: a meta-analysis of voxel-based morphometry studies | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search The impact of APOE ε4 in Alzheimer’s disease: a meta-analysis of voxel-based morphometry studies Madison Bailey , View ORCID Profile Zlatomira Georgieva Ilchovska , Akram A. Hosseini , View ORCID Profile JeYoung Jung doi: https://doi.org/10.1101/2024.05.10.24307165 Madison Bailey a School of Medicine, University of Nottingham , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zlatomira Georgieva Ilchovska b School of Psychology, University of Nottingham , UK c School of Psychology, University of Birmingham , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Zlatomira Georgieva Ilchovska Akram A. Hosseini a School of Medicine, University of Nottingham , UK d Department of Academic Neurology, Nottingham University Hospitals NHS Trust, Queens Medical Centre , Nottingham, UK e Centre for Dementia, Institute of Mental Health, University of Nottingham , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site JeYoung Jung b School of Psychology, University of Nottingham , UK e Centre for Dementia, Institute of Mental Health, University of Nottingham , UK f Precision Imaging, University of Nottingham , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for JeYoung Jung For correspondence: jeyoung.jung{at}nottingham.ac.uk Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background Alzheimer’s disease (AD) is the most prevalent form of dementia, exerting substantial personal and societal impacts. The apolipoprotein E (APOE) ε4 allele is a known genetic factor that increases the risk of AD, contributing to more severe brain atrophy and exacerbated symptoms. Purpose We aim to provide a comprehensive review of the impacts of the APOE ε4 allele on brain atrophy in AD and mild cognitive impairment (MCI) as a transitional stage of AD. Methods We performed a coordinate-based meta-analysis of voxel-based morphometry (VBM) studies to identify the patterns of grey matter atrophy in APOE ε4 carriers vs. non-carriers. We obtained coordinate-based structural magnetic resonance imaging (MRI) data for 1135 individuals from 12 studies on PubMed and Google Scholar that met our inclusion criteria. Results We found significant atrophy in the hippocampus and parahippocampus of APOE ε4 carriers compared to non-carriers, especially within the AD and MCI groups, while healthy controls showed no significant atrophy in these regions. Conclusion Our meta-analysis sheds light on the significant link between the APOE ε4 allele and hippocampal atrophy in both AD and MCI, emphasizing the allele’s critical influence on neurodegeneration, especially in the hippocampus. Our findings contribute to the understanding of the disease’s pathology, potentially facilitating progress in early detection, targeted interventions, and personalized care strategies for individuals with the APOE ε4 allele who are at risk for Alzheimer’s Disease. Introduction Alzheimer’s disease (AD) remains one of the most pressing challenges in healthcare, imposing significant burdens on individuals, families, and societies worldwide ( Lanctot et al. 2024 ). Currently, there are approximately 50 million AD patients worldwide, with projections indicating a doubling every five years, expected to reach 152 million by 2050 (2022). AD, the most prevalent form of dementia, progresses slowly but inevitably leads to substantial neuronal loss, especially in the medial temporal lobe and hippocampus ( Pini et al. 2016 ), manifesting as memory decline, cognitive impairment, and changes in personality and language abilities ( Corey-Bloom 2002 ; Jahn 2013 ). Although the disease’s causes are complex, involving genetic, environmental, and lifestyle factors ( Eid et al. 2019 ), the ε4 allele of the apolipoprotein E (APOE) gene emerges as the strongest risk factor for AD ( Liu et al. 2013 ). Approximately 60% of AD patients carry an ε4 allele ( Corder et al. 1993 ; Liu et al. 2013 ). Carrying one ε4 allele raises the risk of AD by 2-3 times, while those with two ε4 alleles face a 15-fold increased risk of developing AD ( Farrer et al. 1997 ). The presence of the APOE ε4 allele not only increases the risk of developing AD but also can influence the age of onset, progression rate, and severity of the disease ( Frisoni et al. 1995 ; Corder et al. 1996 ; Cosentino et al. 2008 ). The current study aims to elucidate the impacts of the APOE ε4 allele on brain structure in AD, drawing upon a comprehensive review of neuroimaging studies. AD is characterised by the amyloid plaques ( Li et al. 2022 ) and neurofibrillary tangles ( Goedert et al. 1991 ), and these result in synaptic loss, neuronal loss and brain atrophy ( Pini et al . 2016 ). In particular, the progressive atrophy of the hippocampus and parahippocampal gyrus disrupts this memory network in AD ( Rao et al. 2022 ). This disruption is further compounded by the accumulation of neurofibrillary tangles and amyloid plaques, the primary pathological features of AD, which contribute to neuronal loss and decreased synaptic functionality ( Chu 2012 ; Josephs et al. 2017 ). Notably, individuals carrying the APOE ε4 allele show heightened concentrations of amyloid-β42 and tau proteins, correlating with accelerated cognitive decline ( Benson et al. 2022 ). The APOE gene, located on chromosome 19 ( Moreno-Grau et al. 2018 ) is crucial for synthesizing the APOE, which plays a vital role in transport of cholesterol and other lipids across cells in various tissues in the body ( Mahley 1988 ). In the brain, the APOE protein predominantly produced by astrocytes is critical for the maintenance and repair of neurons ( Husain et al. 2021 ). This gene exists in three main isoforms—ε2, ε3, and ε4—each of which has a unique impact on lipid metabolism and neuronal health ( Phillips 2014 ). The ε4 variant is strongly associated with AD risk, playing a role in the disease’s progression by promoting amyloid β build up and impairing the physiology of the medial temporal lobe ( DiBattista et al. 2016 ). The ε4 allele’s association with increased brain amyloid level is evident in both the early ( Caselli et al. 2009 ; Villemagne et al. 2013 ) and advanced stages of AD ( Nelson et al. 2013 ; Tai et al. 2013 ). Additionally, this genetic variant is associated with reduced hippocampal volumes ( Manning et al. 2014 ) and more significant memory deficits in AD patients ( Wolk et al. 2010 ). Advances in neuroimaging, particularly magnetic resonance imaging (MRI) have been indispensable in identifying and quantifying brain atrophy in AD ( Dona et al. 2016 ). Voxel-based morphometry (VBM) is a neuroimaging analysis technique to investigate focal differences in brain volume using the statistical approach of voxel-wise comparison ( Ashburner & Friston 2000 ). Meta-analysis studies of AD using VBM have focused on comparing AD patients to healthy controls, revealing the atrophy in hippocampus and parahippocampal gyrus ( Ferreira et al. 2011 ; Li et al. 2012 ; Wang et al. 2015 ). Despite existing studies on AD, there’s a notable gap in research comparing brain atrophy between APOE ε4 carriers and non-carriers. Our study aims to fill this gap using a coordinate-based meta-analysis (CBMA) to synthesize data across studies, providing a comprehensive understanding of the APOE ε4 allele’s impact on brain structure through various stages of cognitive decline. We compared brain atrophy in APOE ε4 carriers vs. non-carriers across AD, mild cognitive impairment (MCI), and healthy control (HC) groups. By employing activation likelihood estimation (ALE), we analysed data from multiple studies to identify significant patterns of brain atrophy, offering new insights into the relationship between the APOE ε4 allele and AD pathology. Materials and Methods Literature search, selection criteria, and quality appraisal We conducted a comprehensive literature search from Oct 2023 to Feb 2024. This search spanned PubMed and Google Scholar, aiming to find structural neuroimaging studies written in English that compare APOE ε4 carriers with non-carriers. Our search strategy involved the following combination of keywords: 1) (Alzheimer) AND (voxel-based morphometry or VBM) AND APOE (apolipoprotein or APOE), 2) (mild cognitive impairment or MCI) AND (voxel-based morphometry or VBM) AND APOE (apolipoprotein or APOE). This search strategy yielded 83 studies, of which 12 were relevant to the following inclusion criteria: i) studies that used VBM as the imaging modality; ii) studies that reported brain coordinates in a standardised stochastic space, either Montreal Neurological Institute (MNI) or Talairach templates; iii) studies that compared group contrasts between APOE ε4 carriers and non-carriers; iv) studies that reported atrophy of grey matter; v) studies that performed a whole-brain analysis. After the initial screening process, 33 studies were eligible for assessment; of these, we excluded 24 for the following reasons: i) comparative studies (n = 6); ii) reviews (n = 1); iii) case reports (n = 1); iv) no genetic information (n = 4); v) no contrast information (n = 2); vi) white matter studies (n = 2); vii) no whole brain analysis (n = 2); viii) non-human studies (n = 3). Figure 1 illustrates how we applied the inclusion and exclusion criteria to the study selection process using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 flow diagram for new systematic reviews {Page, 2021 #105}. MB, ZI, and JJ conducted all steps. The articles that met the criteria after the screening process were included in the meta-analysis. Download figure Open in new tab Figure 1. PRISMA flowchart of study selection. Activation likelihood estimation (ALE) analysis For a comprehensive investigation into the impact of APOE ε4 status on brain atrophy, we conducted meta-analysis using ALE algorithm by BrainMap GingerALE 3.0.2 ( https://brainmap.org ) {Eickhoff, 2009 #78}. The experiments were categorised into AD, MCI, and HC groups ( Table 1 ). Separate ALE meta-analyses were performed on four subsets of the experiments: (1) all patient experiments combined (AD + MCI); (2) experiments per each group (AD, MCI, and HC). Some studies included multiple experiments; hence, the total number of experiments (n = 25) exceeds the total number of studies (n = 12). All Talairach coordinates were transformed into MNI space. Threshold was set to uncorrected p < 0.001 with a 1000 permutation. The minimum cluster volume was set to 200 mm 3 . View this table: View inline View popup Download powerpoint Table 1. The list of 12 studies included in the meta-analysis. Neurosynth To link the patterns of brain atrophy identified from our meta-analysis to functional networks, we performed additional meta-analyses using Neurosynth ( Yarkoni et al. 2011 ) ( http://neurosynth.org ). We selected the peak coordinates from each cluster identified in our meta-analysis as a seed region to create meta-analytic coactivation maps and to identify keywords related to these maps. Neurosynth generates a z-score map, indicating the probability that a specific term was mentioned in a research article in association with an activation site. We applied a voxel-wise threshold to the Neurosynth outcomes at a significance level of 0.01, adjusted for false discovery rate (FDR). Keywords were selected based on their z-scores being greater than 0, with up to 5 keywords chosen according to their z-score magnitude. Results ALE meta-analysis results Twelve studies, 25 experiments with 1135 participants, yielding 164 foci met the relevant inclusion criteria and were entered into the analysis. The results are summarised in Fig. 2 and Table 2 . The primary analysis with all patients (AD + MCI, 10 experiments, 46 foci, 608 patients) revealed that patients carrying the APOE ε4 allele exhibited significant atrophy in the bilateral hippocampus and paraphippocampal regions compared to those without the allele ( Fig. 2A ). Further detailed analyses by patient category revealed that, in AD patients (6 experiments, 35 foci, 405 ADs), APOE ε4 carriers showed notable atrophy in the bilateral hippocampus, the right parahippocampal gyrus, and the posterior cingulate cortex ( Fig. 2B ). In MCI patients (4 experiments, 11 foci, 203 MCIs), carriers of the APOE ε4 allele exhibited atrophy in the bilateral paraphippocampal gyrus and the globus pallidus ( Fig. 2C ). Among HCs (12 experiments, 113 foci, 527 HCs), those with the APOE ε4 allele had atrophy in the right superior temporal gyrus (STG) ( Fig. 2D ). Download figure Open in new tab Figure 2. The results of ALE meta-analysis. A) The results of all patients (AD + MCI) carriers < non-carriers. B) The results of AD carriers < non-carriers. C) The results of MCI carriers < non-carriers. D) The results of HC carriers < non-carriers. Colour bar indicates Z-score. View this table: View inline View popup Table 2. The results of ALE meta-analysis NeuroSynth results To explore the functional networks linked with the patterns observed in our meta-analysis, specifically comparing AD carriers to non-carriers, we utilized Neurosynth for a meta-analytic coactivation analysis. The results are summarized in the Fig. 3 . Analysis of the coactivation map for the parahippocampal gyrus cluster (MNI coordinates 26, -34, -2) uncovered connectivity with the bilateral hippocampus, parahippocampal gyrus, and posterior cingulate cortex (PCC) ( Figure 3A ). The hippocampal clusters (MNI 32, -22, -10 and -26, -39, -2) were primarily linked with the bilateral hippocampus ( Fig. 3B and C ). The coactivation analysis of the posterior cingulate cortex showed its association with the medial prefrontal cortex, precuneus, posterior cingulate cortex, bilateral angular gyrus, middle temporal gyrus, and hippocampus ( Fig. 3D ). Additionally, word clouds generated from Neurosynth meta-analysis decoding revealed the most frequently associated terms with the brain activity patterns in these coactivation maps, including ‘episodic’, ‘memory’, ‘encoding’, ‘retrieval’, among others ( Fig. 3E ). Download figure Open in new tab Figure 3. The results of NeuroSynth. A) The meta-analytic coactivation map of the parahippocampal gyrus cluster. B) The meta-analytic coactivation map of the right hippocampus cluster. C) The meta-analytic coactivation map of the left hippocampus cluster. D) B) The meta-analytic coactivation map of the posterior cingulate cortex cluster. E) Word clouds illustrate the findings of a meta-analysis conducted with Neurosynth, showing the terms most commonly associated with the brain activity patterns of seed regions identified when comparing AD carriers to non-carriers. Colour bar represents Z-score. Discussion Our meta-analysis aimed to explore how the APOE ε4 allele influences brain atrophy in AD, offering insights into the underpinning of brain atrophy in this condition. By examining the effects of the APOE ε4 allele in individuals at various stages of clinical progression, AD and MCI, we revealed the APOE ε4 allele’s impact on the hippocampus and parahippocampus, areas vulnerable to neurodegenerative changes. Our findings demonstrated significant atrophy in the hippocampus and parahippocampus of APOE ε4 carriers compared to non-carriers, especially within the AD and MCI groups, while healthy controls despite being carriers showed no significant atrophy in these regions. This finding is consistent with existing research highlighting the hippocampus’s susceptibility to early degenerative changes in AD, where it plays a critical role in memory formation, storage, and retrieval ( Ferreira et al . 2011 ; Li et al . 2012 ; Wang et al . 2015 ; Pini et al . 2016 ). The observed atrophy in these critical memory regions among APOE ε4 carriers suggests the allele may contribute to the exacerbation of memory loss in AD, supporting the notion that this genetic variant is a significant risk factor for accelerated neurodegeneration ( Corder et al . 1993 ; Liu et al . 2013 ; Lancaster et al. 2019 ). The APOE ε4 allele’s presence has been associated with diminished volumes in the hippocampus, particularly evident in older individuals with AD and MCI, revealing an average volume decrease of about 4% in the hippocampus per APOE ε4 allele ( Fleisher et al. 2005 ; Fleisher et al. 2013 ; Chauhan et al. 2015 ). Utilizing findings from large-scale Genome Wide Association Study Meta Analyses (GWASMA), Lupton et al (2016) further confirmed the link between the APOE ε4 allele and hippocampal volume reduction in AD and MCI, indicating that carriers of the ε4 allele exhibit smaller hippocampal volumes than non-carriers. Moreover, Kerchner et al (2014) reported that APOE ε4 carriers in MCI and AD patients had thinner hippocampal subregions and showed poorer episodic memory abilities compared to non-carriers. Moreover, our NeuroSynth analysis demonstrated the hippocampal network associated with memory function. Located in the medial temporal lobe, the hippocampus is among the initial regions to exhibit damage in AD ( Pini et al . 2016 ). This early vulnerability is attributed to its critical role in encoding new memories and navigating spatial environments ( Bird and Burgess 2008 ). The parahippocampal gyrus, surrounding the hippocampus, supports memory encoding and retrieval by processing environmental contextual information ( Aminoff et al. 2013 ). Together, these structures are crucial components of the brain’s memory network, facilitating the transition of short-term memories to long-term storage ( van Strien et al. 2009 ). Our meta-analysis corroborates these genomic and neuroimaging findings, demonstrating the significant influence of the APOE ε4 allele on hippocampal atrophy within AD and related their memory impairments. Furthermore, our analysis revealed atrophy in the posterior cingulate cortex (PCC) among AD patients carrying the APOE ε4 allele compared to non-carriers. The PCC is an integral part of the Papez circuit, which also includes the hippocampus, mammillary bodies, thalamus, and parahippocampal gyrus ( Aggleton et al. 2022 ). This circuit plays a pivotal role in memory formation, emotional regulation, and is implicated in the episodic memory and spatial navigation challenges seen in AD ( Forno et al. 2021 ). The PCC is also a central element of the default mode network (DMN), which is known to be affected by AD pathology ( Callen et al. 2001 ; Buckner et al. 2008 ). Studies repeatedly have reported the decreased volume of PCC ( Callen et al . 2001 ) and disrupted functional connectivity of the PCC in AD ( Buckner et al . 2008 ). Importantly APOE ε4 carriers, both in AD and MCI stages, have been observed to exhibit loss of grey matter in the PCC ( Haller et al. 2017 ) and impaired functional connectivity ( Sheline et al. 2010 ). Aligned with existing evidence, our findings suggest the influence of the APOE ε4 allele on PCC abnormalities, supporting he notion of PCC atrophy as a distinctive cortical feature of AD ( Dickerson et al. 2009 ). Overall, our results highlight the contribution of APOE ε4 carriers at genetic risk for AD to the brain atrophy and the cognitive deficits associated with AD. Despite the robust associations observed, our study’s limitations, including a relatively small sample size and the scarcity of studies directly comparing APOE ε4 carriers to non-carriers, necessitate cautious interpretation of our results. This study is not a mechanistic study, and more studies are needed to better understand if the APOE has a direct or indirect impact on the Alzheimer’s pathology, focal brain atrophy/neurodegeneration, or conversion of MCI to AD, or disease progression. However, our analysis lays a foundational basis for future research in this field, suggesting the importance of genetic screening in tailoring potential prevention and treatment strategies for AD. APOE genetic test is also important for monitoring the amyloid-therapy (e.g. Donanemab, Lecanemab), and it could be useful to study the influence of amyloid therapy in slowing down the hippocampal atrophy in the carriers vs non-carriers. Recognizing the multifactorial nature of AD, further studies are essential to unravel the complex interplay of genetic and neuronal factors underlying the disease, providing the way for more effective interventions and a deeper understanding of its pathophysiology. By performing a meta-analysis on structural neuroimaging data, we showed how this genetic variant contributes to the understanding of disease and its impact on brain structure. By identifying specific brain atrophy patterns associated with the APOE ε4 allele, our meta-analysis provides the significant link between genetic factors and neurodegeneration, offering potential pathways for targeted interventions and treatments. The recognition that APOE ε4 carriers in AD exhibit distinct patterns of brain atrophy, especially in the hippocampus and Papez circuit, enables more accurate risk assessment and individualized approaches to mitigating neurodegenerative progression. Data Availability All data produced in the present work are contained in the manuscript. Conflict of interest The authors declare no competing financial interests. Acknowledgements This research was supported by AMS Springboard (SBF007\100077) to JJ. AAH has received funding from the Medical Research Council, UK (Grant MR/T005580/1 ) and National Institute of Health/NIA, USA (Grant 1R56AG074467-01 ). She has received honoraria from Biogen, Eisai, and Lilly for advisory consultations and teaching related to Alzheimer’s disease. Footnotes ↵ † Joint first authors References 2022 . 2022 Alzheimer’s disease facts and figures . Alzheimers Dement . 18 : 700 – 789 . OpenUrl ↵ Aggleton JP , Nelson AJD , O’Mara SM . 2022 . Time to retire the serial Papez circuit: Implications for space, memory, and attention . Neurosci Biobehav Rev . 140 : 104813 . OpenUrl PubMed ↵ Aminoff EM , Kveraga K , Bar M. 2013 . The role of the parahippocampal cortex in cognition . Trends Cogn Sci . 17 : 379 – 390 . OpenUrl CrossRef PubMed Web of Science ↵ Ashburner J , Friston KJ . 2000 . Voxel-based morphometry--the methods . Neuroimage . 11 : 805 – 821 . OpenUrl CrossRef PubMed Web of Science ↵ Benson GS , Bauer C , Hausner L , Couturier S , Lewczuk P , Peters O , Hüll M , Jahn H , Jessen F , Pantel J , Teipel SJ , Wagner M , Schuchhardt J , Wiltfang J , Kornhuber J , Frölich L. 2022 . Don’t forget about tau: the effects of ApoE4 genotype on Alzheimer’s disease cerebrospinal fluid biomarkers in subjects with mild cognitive impairment-data from the Dementia Competence Network . Journal of Neural Transmission . 129 : 477 – 486 . OpenUrl ↵ Bird CM , Burgess N. 2008 . The hippocampus and memory: insights from spatial processing . Nat Rev Neurosci . 9 : 182 – 194 . OpenUrl CrossRef PubMed Web of Science ↵ Buckner RL , Andrews-Hanna JR , Schacter DL . 2008 . The brain’s default network: anatomy, function, and relevance to disease . Ann N Y Acad Sci . 1124 : 1 – 38 . OpenUrl CrossRef PubMed Web of Science ↵ Callen DJ , Black SE , Gao F , Caldwell CB , Szalai JP . 2001 . Beyond the hippocampus: MRI volumetry confirms widespread limbic atrophy in AD . Neurology . 57 : 1669 – 1674 . OpenUrl CrossRef PubMed ↵ Caselli RJ , Dueck AC , Osborne D , Sabbagh MN , Connor DJ , Ahern GL , Baxter LC , Rapcsak SZ , Shi J , Woodruff BK , Locke DE , Snyder CH , Alexander GE , Rademakers R , Reiman EM . 2009 . Longitudinal modeling of age-related memory decline and the APOE epsilon4 effect . N Engl J Med . 361 : 255 – 263 . OpenUrl CrossRef PubMed Web of Science ↵ Chauhan G , Adams HHH , Bis JC , Weinstein G , Yu L , Toglhofer AM , Smith AV , van der Lee SJ , Gottesman RF , Thomson R , Wang J , Yang Q , Niessen WJ , Lopez OL , Becker JT , Phan TG , Beare RJ , Arfanakis K , Fleischman D , Vernooij MW , Mazoyer B , Schmidt H , Srikanth V , Knopman DS , Jack CR , Jr. , Amouyel P , Hofman A , DeCarli C , Tzourio C , van Duijn CM , Bennett DA , Schmidt R , Longstreth WT , Jr. , Mosley TH , Fornage M , Launer LJ , Seshadri S , Ikram MA , Debette S. 2015 . Association of Alzheimer’s disease GWAS loci with MRI markers of brain aging . Neurobiol Aging . 36 : 1765 e1767 – 1765 e1716 . OpenUrl CrossRef ↵ Chu LW . 2012 . Alzheimer’s disease: early diagnosis and treatment . Hong Kong Med J . 18 : 228 – 237 . OpenUrl PubMed ↵ Corder EH , Basun H , Lannfelt L , Viitanen M , Winblad B. 1996 . Attenuation of apolipoprotein E Epsilon4 allele gene dose in late age . Lancet . 347 : 542 . OpenUrl PubMed ↵ Corder EH , Saunders AM , Strittmatter WJ , Schmechel DE , Gaskell PC , Small GW , Roses AD , Haines JL , Pericak-Vance MA . 1993 . Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families . Science . 261 : 921 – 923 . OpenUrl Abstract / FREE Full Text ↵ Corey-Bloom J. 2002 . The ABC of Alzheimer’s disease: cognitive changes and their management in Alzheimer’s disease and related dementias . Int Psychogeriatr. 14 Suppl 1 : 51 – 75 . OpenUrl CrossRef ↵ Cosentino FI , Bosco P , Drago V , Prestianni G , Lanuzza B , Iero I , Tripodi M , Spada RS , Toscano G , Caraci F , Ferri R. 2008 . The APOE epsilon4 allele increases the risk of impaired spatial working memory in obstructive sleep apnea . Sleep Med . 9 : 831 – 839 . OpenUrl CrossRef PubMed Web of Science ↵ DiBattista AM , Heinsinger NM , Rebeck GW . 2016 . Alzheimer’s Disease Genetic Risk Factor APOE-ε4 Also Affects Normal Brain Function . Current Alzheimer Research . 13 : 1200 – 1207 . OpenUrl ↵ Dickerson BC , Bakkour A , Salat DH , Feczko E , Pacheco J , Greve DN , Grodstein F , Wright CI , Blacker D , Rosas HD , Sperling RA , Atri A , Growdon JH , Hyman BT , Morris JC , Fischl B , Buckner RL . 2009 . The Cortical Signature of Alzheimer’s Disease: Regionally Specific Cortical Thinning Relates to Symptom Severity in Very Mild to Mild AD Dementia and is Detectable in Asymptomatic Amyloid-Positive Individuals . Cereb Cortex . 19 : 497 – 510 . OpenUrl CrossRef PubMed Web of Science ↵ Dona O , Thompson J , Druchok C. 2016 . Comprehensive Review on Magnetic Resonance Imaging in Alzheimer’s Disease . Crit Rev Biomed Eng . 44 : 213 – 225 . OpenUrl ↵ Eid A , Mhatre I , Richardson JR . 2019 . Gene-environment interactions in Alzheimer’s disease: A potential path to precision medicine . Pharmacol Ther . 199 : 173 – 187 . OpenUrl ↵ Farrer LA , Cupples LA , Haines JL , Hyman B , Kukull WA , Mayeux R , Myers RH , Pericak-Vance MA , Risch N , van Duijn CM . 1997 . Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease . A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA . 278 : 1349 – 1356 . OpenUrl ↵ Ferreira LK , Diniz BS , Forlenza OV , Busatto GF , Zanetti MV . 2011 . Neurostructural predictors of Alzheimer’s disease: A meta-analysis of VBM studies . Neurobiology of Aging . 32 : 1733 – 1741 . OpenUrl CrossRef PubMed Web of Science ↵ Fleisher A , Grundman M , Jack CR , Jr. , Petersen RC , Taylor C , Kim HT , Schiller DH , Bagwell V , Sencakova D , Weiner MF , DeCarli C , DeKosky ST , van Dyck CH , Thal LJ , Alzheimer’s Disease Cooperative S . 2005 . Sex, apolipoprotein E epsilon 4 status, and hippocampal volume in mild cognitive impairment . Arch Neurol . 62 : 953 – 957 . OpenUrl CrossRef PubMed Web of Science ↵ Fleisher AS , Chen K , Liu X , Ayutyanont N , Roontiva A , Thiyyagura P , Protas H , Joshi AD , Sabbagh M , Sadowsky CH , Sperling RA , Clark CM , Mintun MA , Pontecorvo MJ , Coleman RE , Doraiswamy PM , Johnson KA , Carpenter AP , Skovronsky DM , Reiman EM . 2013 . Apolipoprotein E epsilon4 and age effects on florbetapir positron emission tomography in healthy aging and Alzheimer disease . xNeurobiol Aging . 34 : 1 – 12 . OpenUrl ↵ Forno G , Llado A , Hornberger M. 2021 . Going round in circles-The Papez circuit in Alzheimer’s disease . Eur J Neurosci . 54 : 7668 – 7687 . OpenUrl ↵ Frisoni GB , Govoni S , Geroldi C , Bianchetti A , Calabresi L , Franceschini G , Trabucchi M. 1995 . Gene dose of the epsilon 4 allele of apolipoprotein E and disease progression in sporadic late-onset Alzheimer’s disease . Ann Neurol . 37 : 596 – 604 . OpenUrl CrossRef PubMed Web of Science ↵ Goedert M , Sisodia SS , Price DL . 1991 . Neurofibrillary tangles and beta-amyloid deposits in Alzheimer’s disease . Curr Opin Neurobiol . 1 : 441 – 447 . OpenUrl CrossRef PubMed ↵ Haller S , Montandon ML , Rodriguez C , Ackermann M , Herrmann FR , Giannakopoulos P. 2017 . * Is Associated with Gray Matter Loss in the Posterior Cingulate Cortex in Healthy Elderly Controls Subsequently Developing Subtle Cognitive Decline . Am J Neuroradiol . 38 : 1335 – 1342 . OpenUrl Abstract / FREE Full Text ↵ Husain MA , Laurent B , Plourde M. 2021 . APOE and Alzheimer’s Disease: From Lipid Transport to Physiopathology and Therapeutics . Frontiers in Neuroscience . 15 . Iqbal K , Liu F , Gong CX , Grundke-Iqbal I. 2010 . Tau in Alzheimer disease and related tauopathies . Curr Alzheimer Res . 7 : 656 – 664 . OpenUrl CrossRef PubMed Web of Science ↵ Jahn H. 2013 . Memory loss in Alzheimer’s disease . Dialogues Clin Neurosci . 15 : 445 – 454 . OpenUrl CrossRef PubMed ↵ Josephs KA , Dickson DW , Tosakulwong N , Weigand SD , Murray ME , Petrucelli L , Liesinger AM , Senjem ML , Spychalla AJ , Knopman DS , Parisi JE , Petersen RC , Jack CR , Jr. , Whitwell JL . 2017 . Rates of hippocampal atrophy and presence of post-mortem TDP-43 in patients with Alzheimer’s disease: a longitudinal retrospective study . Lancet Neurol . 16 : 917 – 924 . OpenUrl CrossRef ↵ Kerchner GA , Berdnik D , Shen JC , Bernstein JD , Fenesy MC , Deutsch GK , Wyss-Coray T , Rutt BK . 2014 . APOE epsilon4 worsens hippocampal CA1 apical neuropil atrophy and episodic memory . Neurology . 82 : 691 – 697 . OpenUrl CrossRef PubMed ↵ Lancaster TM , Hill MJ , Sims R , Williams J. 2019 . Microglia - mediated immunity partly contributes to the genetic association between Alzheimer’s disease and hippocampal volume . Brain Behav Immun . 79 : 267 – 273 . OpenUrl CrossRef ↵ Lanctot KL , Hviid Hahn-Pedersen J , Eichinger CS , Freeman C , Clark A , Tarazona LRS , Cummings J. 2024 . Burden of Illness in People with Alzheimer’s Disease: A Systematic Review of Epidemiology, Comorbidities and Mortality . J Prev Alzheimers Dis . 11 : 97 – 107 . OpenUrl ↵ Li JP , Pan PL , Huang R , Shang HF . 2012 . A meta-analysis of voxel-based morphometry studies of white matter volume alterations in Alzheimer’s disease . Neuroscience and Biobehavioral Reviews . 36 : 757 – 763 . OpenUrl CrossRef PubMed ↵ Li KD , Qu H , Ma MY , Xia CY , Cai M , Han F , Zhang Q , Gu XY , Ma Q. 2022 . Correlation Between Brain Structure Atrophy and Plasma Amyloid-β and Phosphorylated Tau in Patients With Alzheimer’s Disease and Amnestic Mild Cognitive Impairment Explored by Surface-Based Morphometry . Frontiers in Aging Neuroscience . 14 . ↵ Liu CC , Liu CC , Kanekiyo T , Xu H , Bu G. 2013 . Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy . Nat Rev Neurol . 9 : 106 – 118 . OpenUrl CrossRef PubMed ↵ Lupton MK , Strike L , Hansell NK , Wen W , Mather KA , Armstrong NJ , Thalamuthu A , McMahon KL , de Zubicaray GI , Assareh AA , Simmons A , Proitsi P , Powell JF , Montgomery GW , Hibar DP , Westman E , Tsolaki M , Kloszewska I , Soininen H , Mecocci P , Velas B , Lovestone S , Alzheimer’s Disease Neuroimaging I , Brodaty H , Ames D , Trollor JN , Martin NG , Thompson PM , Sachdev PS , Wright MJ . 2016 . The effect of increased genetic risk for Alzheimer’s disease on hippocampal and amygdala volume . Neurobiol Aging . 40 : 68 – 77 . OpenUrl CrossRef PubMed ↵ Mahley RW . 1988 . Apolipoprotein E: cholesterol transport protein with expanding role in cell biology . Science . 240 : 622 – 630 . OpenUrl Abstract / FREE Full Text ↵ Manning EN , Barnes J , Cash DM , Bartlett JW , Leung KK , Ourselin S , Fox NC , Alzheimer’s Disease NeuroImaging I . 2014 . APOE epsilon4 is associated with disproportionate progressive hippocampal atrophy in AD . PLoS One . 9 : e97608 . OpenUrl CrossRef PubMed ↵ Moreno-Grau S , Hernandez I , Heilmann-Heimbach S , Ruiz S , Rosende-Roca M , Mauleon A , Vargas L , Rodriguez-Gomez O , Alegret M , Espinosa A , Ortega G , Aguilera N , Abdelnour C , Neuroimaging Initiative AD , Gil S , Maier W , Sotolongo-Grau O , Tarraga L , Ramirez A , Lopez-Arrrieta J , Antunez C , Serrano-Rios M , Boada M , Ruiz A. 2018 . Genome-wide significant risk factors on chromosome 19 and the APOE locus . Oncotarget . 9 : 24590 – 24600 . OpenUrl ↵ Nelson PT , Pious NM , Jicha GA , Wilcock DM , Fardo DW , Estus S , Rebeck GW . 2013 . APOE-epsilon2 and APOE-epsilon4 correlate with increased amyloid accumulation in cerebral vasculature . J Neuropathol Exp Neurol . 72 : 708 – 715 . OpenUrl CrossRef PubMed ↵ Phillips MC . 2014 . Apolipoprotein E isoforms and lipoprotein metabolism . IUBMB Life . 66 : 616 – 623 . OpenUrl CrossRef PubMed ↵ Pini L , Pievani M , Bocchetta M , Altomare D , Bosco P , Cavedo E , Galluzzi S , Marizzoni M , Frisoni GB . 2016 . Brain atrophy in Alzheimer’s Disease and aging . Ageing Res Rev . 30 : 25 – 48 . OpenUrl CrossRef PubMed ↵ Rao YL , Ganaraja B , Murlimanju BV , Joy T , Krishnamurthy A , Agrawal A. 2022 . Hippocampus and its involvement in Alzheimer’s disease: a review . 3 Biotech . 12 : 55 . OpenUrl ↵ Sheline YI , Morris JC , Snyder AZ , Price JL , Yan Z , D’Angelo G , Liu C , Dixit S , Benzinger T , Fagan A , Goate A , Mintun MA . 2010 . APOE4 allele disrupts resting state fMRI connectivity in the absence of amyloid plaques or decreased CSF Abeta42 . J Neurosci . 30 : 17035 – 17040 . OpenUrl Abstract / FREE Full Text ↵ Tai LM , Bilousova T , Jungbauer L , Roeske SK , Youmans KL , Yu C , Poon WW , Cornwell LB , Miller CA , Vinters HV , Van Eldik LJ , Fardo DW , Estus S , Bu G , Gylys KH , Ladu MJ . 2013 . Levels of soluble apolipoprotein E/amyloid-beta (Abeta) complex are reduced and oligomeric Abeta increased with APOE4 and Alzheimer disease in a transgenic mouse model and human samples . J Biol Chem . 288 : 5914 – 5926 . OpenUrl Abstract / FREE Full Text Thal DR , Walter J , Saido TC , Fandrich M. 2015 . Neuropathology and biochemistry of Abeta and its aggregates in Alzheimer’s disease . Acta Neuropathol . 129 : 167 – 182 . OpenUrl CrossRef PubMed ↵ van Strien NM , Cappaert NL , Witter MP . 2009 . The anatomy of memory: an interactive overview of the parahippocampal-hippocampal network . Nat Rev Neurosci . 10 : 272 – 282 . OpenUrl CrossRef PubMed Web of Science ↵ Villemagne VL , Burnham S , Bourgeat P , Brown B , Ellis KA , Salvado O , Szoeke C , Macaulay SL , Martins R , Maruff P , Ames D , Rowe CC , Masters CL , Australian Imaging B, Lifestyle Research G . 2013 . Amyloid beta deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study . Lancet Neurol . 12 : 357 – 367 . OpenUrl CrossRef PubMed ↵ Wang WY , Yu JT , Liu Y , Yin RH , Wang HF , Wang J , Tan L , Radua J , Tan L. 2015 . Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease . Translational Neurodegeneration . 4 . ↵ Wolk DA , Dickerson BC , Alzheimer’s Disease Neuroimaging I . 2010 . Apolipoprotein E (APOE) genotype has dissociable effects on memory and attentional-executive network function in Alzheimer’s disease . Proc Natl Acad Sci U S A . 107 : 10256 – 10261 . OpenUrl Abstract / FREE Full Text ↵ Yarkoni T , Poldrack RA , Nichols TE , Van Essen DC , Wager TD . 2011 . Large-scale automated synthesis of human functional neuroimaging data . Nat Methods . 8 : 665 – 670 . OpenUrl CrossRef PubMed Web of Science View the discussion thread. Back to top Previous Next Posted May 10, 2024. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following The impact of APOE ε4 in Alzheimer’s disease: a meta-analysis of voxel-based morphometry studies Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share The impact of APOE ε4 in Alzheimer’s disease: a meta-analysis of voxel-based morphometry studies Madison Bailey , Zlatomira Georgieva Ilchovska , Akram A. Hosseini , JeYoung Jung medRxiv 2024.05.10.24307165; doi: https://doi.org/10.1101/2024.05.10.24307165 Share This Article: Copy Citation Tools The impact of APOE ε4 in Alzheimer’s disease: a meta-analysis of voxel-based morphometry studies Madison Bailey , Zlatomira Georgieva Ilchovska , Akram A. Hosseini , JeYoung Jung medRxiv 2024.05.10.24307165; doi: https://doi.org/10.1101/2024.05.10.24307165 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Radiology and Imaging Subject Areas All Articles Addiction Medicine (573) Allergy and Immunology (865) Anesthesia (303) Cardiovascular Medicine (4457) Dentistry and Oral Medicine (445) Dermatology (383) Emergency Medicine (610) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1517) Epidemiology (15244) Forensic Medicine (30) Gastroenterology (1132) Genetic and Genomic Medicine (6620) Geriatric Medicine (669) Health Economics (1002) Health Informatics (4557) Health Policy (1372) Health Systems and Quality Improvement (1615) Hematology (543) HIV/AIDS (1272) Infectious Diseases (except HIV/AIDS) (15936) Intensive Care and Critical Care Medicine (1106) Medical Education (624) Medical Ethics (147) Nephrology (670) Neurology (6634) Nursing (346) Nutrition (999) Obstetrics and Gynecology (1148) Occupational and Environmental Health (957) Oncology (3348) Ophthalmology (980) Orthopedics (369) Otolaryngology (421) Pain Medicine (436) Palliative Medicine (130) Pathology (665) Pediatrics (1696) Pharmacology and Therapeutics (693) Primary Care Research (714) Psychiatry and Clinical Psychology (5463) Public and Global Health (9257) Radiology and Imaging (2210) Rehabilitation Medicine and Physical Therapy (1371) Respiratory Medicine (1198) Rheumatology (598) Sexual and Reproductive Health (716) Sports Medicine (532) Surgery (714) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a031e80d4a4941e2',t:'MTc4MDAyMDAzNg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();