Genotypic effects ofAPOE-ε4 on resting-state connectivity in cognitively intact individuals support functional brain compensation

Abstract

The investigation of resting-state functional connectivity (rsFC) in asymptomatic individuals at genetic risk for Alzheimer’s disease (AD) enables discovering the earliest brain alterations in preclinical stages of the disease. The APOE-ε4 variant is the major genetic risk factor for AD, and previous studies have reported rsFC abnormalities in carriers of the ε4 allele. Yet, no study has assessed APOE-ε4 gene-dose effects on rsFC measures, and only a few studies included measures of cognitive performance to aid a clinical interpretation. We assessed the impact of APOE-ε4 on rsFC in a sample of 429 cognitively unimpaired individuals hosting a high number of ε4 homozygotes (n = 58), which enabled testing different models of genetic penetrance. We used independent component analysis and found a reduced rsFC as a function of the APOE-ε4 allelic load in the temporal default-mode and the medial temporal networks, while recessive effects were found in the extrastriate and limbic networks. Some of these results were replicated in a subsample with negative amyloid markers. Interaction with cognitive data suggests that such a network reorganization may support cognitive performance in the ε4-homozygotes. Our data indicate that APOE-ε4 shapes the functional architecture of the resting brain and favor the idea of a network-based functional compensation.

Interactions between physical exercise, associative memory, and genetic risk for Alzheimer’s disease

“…This is also consistent with Caccaglia et al. ( 2023 ) suggesting network-based functional compensation mainly in the temporal lobe in APOE ε4 carriers. Further, by combining these imaging results with AEA biomarker measures, we found different relationships as a function of genetic group.…”

“…2010 ). Cacciaglia et al. (2023) showed decreased connectivity specifically in the left medial temporal lobe network and centered on the hippocampus proper correlating with the higher number of ε4 alleles in the genome of the participants (zero ε4 allele for ε3/ε3 participants, one ε4 allele for ε3/ε4 and ε2/ε4 participants, and two ε4 alleles for ε4/ε4 participants), but this report also pertains to older participants (mean age above 50 years old).…”

Genetic risk of late-onset Alzheimer’s disease is associated with longitudinal loss of functional brain network segregation in middle-aged cognitively healthy individuals: The PREVENT-Dementia Study

“…Critically, the third novel finding of this study was that cross-sectionally, cognitively healthy middle-aged adults carrying an APOE ε4 allele showed greater global network segregation compared to non-carriers. This change in direction is consistent with previous studies of the same and other similar midlife cohorts showing better cognition (Deng et al, 2022;Gharbi-Meliani et al, 2021;Ritchie et al, 2017;Zokaei et al, 2020), cerebral hyperperfusion (Dounavi et al, 2021;Mak et al, 2021;McKiernan et al, 2020) and hyperconnectivity within the DMN (Cacciaglia et al, 2022;Westlye et al, 2011) in APOE ε4 carriers than in non-carriers. Importantly, greater network segregation, particularly in the DMN, was significantly associated with better episodic and relational memory cross-sectionally in this midlife cohort.…”

APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure

“…The APOE ɛ4 allele is the strongest genetic risk factor for both sporadic early and late-onset Alzheimer’s disease. 1 , 2 A growing body of neuroimaging studies has delineated the imaging phenotypes of APOE ɛ4 in cognitively normal individuals as a means to detect preclinical changes that may occur before cognitive impairment (for systematic reviews, see 3 , 4 ) Some notable findings in middle-aged APOE ɛ4 carriers include (i) grey matter atrophy in typical Alzheimer’s disease regions, 5-7 (ii) diffusion tensor imaging (DTI) changes in white matter tracts, 8 (iii) functional deficits in cerebral perfusion and glucose metabolism 9-11 as well as (iv) disruptions in both task-based functional MRI 12 , 13 and intrinsic connectivity within resting-state networks. 14 …”