APOE ε4-specific Associations of VEGF Gene Family Expression with Cognitive Aging and Alzheimer’s Disease

Abstract

Literature suggests vascular endothelial growth factor A (VEGFA) is protective among those at highest risk for Alzheimer’s disease (AD). Apolipoprotein E (APOE) ε4 allele carriers represent a highly susceptible population for cognitive decline, and VEGF may confer distinct protection among APOE-ε4 carriers. We evaluated interactions between cortical expression of 10 VEGF gene family members and APOE-ε4 genotype to clarify which VEGF genes modify the association between APOE-ε4 and cognitive decline. Data were obtained from the Religious Orders Study and Rush Memory and Aging Project (N=531). Linear regression assessed interactions on global cognition. VEGF genes NRP1 and VEGFA interacted with APOE-ε4 on cognitive performance (p.fdr<0.05). Higher NRP1 expression correlated with worse outcomes among s4 carriers but better outcomes among s4 non-carriers, suggesting NRP1 modifies the risk for poor cognitive scores based upon APOE-ε4 status. NRP1 regulates angiogenesis, and literature suggests vessels in APOE-ε4 brains are more prone to leaking, perhaps placing young vessels at risk for ischemia. Results suggest that future therapeutics targeting brain angiogenesis should also consider ε4 allele status.

1. Introduction

Alzheimer’s disease (AD) is one of the most devastating and fastest growing neurological disorders in the world. With no available treatments to halt the progression of this disease, it is of monumental importance that novel insights into the underlying biology surrounding AD-associated cognitive decline are elucidated to generate effective therapeutic targets. Vascular endothelial growth factor A (VEGFA) has been studied as an emerging therapeutic candidate for AD (Hohman et al., 2015; Religa et al., 2013; Shim and Madsen, 2018; Storkebaum and Carmeliet, 2004), however the role of VEGFA in the development and progression of AD is debated. The vascular endothelial growth factor (VEGF) family plays a critical role in neuronal as well as vascular processes and is heavily involved in angiogenic regulation, neurogenesis and neuronal survival (Beazley-Long et al., 2013; Lange et al., 2016; Zacchigna et al., 2008). Some studies have found decreased protein levels of VEGFA in serum and cerebrospinal fluid (CSF) are associated with increased risk of AD and cognitive decline (Almodovar et al., 2009; Hohman et al., 2015; Huang et al., 2013), while others have found the opposite (Chiappelli et al., 2006; Tarkowski et al., 2002). In support of VEGFA’s neuroprotective role, studies have shown that AD model mice treated VEGFA recover from cognitive deficits (Garcia et al., 2014; Spuch et al., 2010). Additionally, our group has demonstrated that higher CSF VEGFA concentration is associated with slower rates of hippocampal atrophy and cognitive decline, particularly among AD biomarker-positive participants (Hohman et al., 2015). These studies suggest VEGFA is especially protective among participants at highest risk for AD and cognitive decline.

The polymorphic apolipoprotein E (APOE) gene is a strong genetic risk factor for late-onset AD, with the ε4 allele conferring the greatest risk and the ε2 allele conferring protection relative to the most common isoform, ε3 (Corder et al., 1993; Hohman et al., 2018; Liu et al., 2013). The molecular mechanism by which ApoE contributes to AD pathophysiology is still debated (Wu et al., 2018); however, well-characterized effects of APOE-ε4 include compromised blood-brain barrier integrity (Halliday et al., 2016), increased amyloid-p accumulation (Lim et al., 2017), and alterations in amyloid-β metabolism (Kim et al., 2009). ApoE4 has been strongly associated with cerebrovascular deficits, including a greater decline in cerebral blood flow with aging (Tai et al., 2016) and a significantly enhanced risk for ischemic stroke (Belloy et al., 2019).

Interestingly, VEGFA has also shown a comparable neuroprotective effect in humanized APOE-ε4 mice, whereby treatment with VEGF results in a recovery of behavioral deficits (Salomon-Zimri S, 2016). Given that APOE-ε4 carriers are at heightened risk for clinical AD, it may be that VEGF-mediated neuroprotection is particularly beneficial among this high-risk population. An increase in angiogenesis through VEGF signaling can initiate the growth of new vessels, which may serve as a mechanism to protect against APOE-related cognitive decline by preventing ischemia and downstream neurodegeneration. We hypothesize that APOE-ε4 carriers will show protection against AD and cognitive decline as a result of high angiogenesis-related VEGF gene expression in the brain, which may act to compensate against the multitude of biological vulnerabilities that make this population susceptible to cognitive decline.

The VEGF signaling family is large, with five genes encoding ligands (VEGFA, VEGFB, VEGFC, VEGFD, and PGF), 3 receptor genes (FLT1, KDR and FLT4), and 2 co-receptor genes (NRP1, NRP2), each with multiple isoforms (Almodovar et al., 2009; Carmeliet and de Almodovar, 2013). VEGFA, the most studied protein of the VEGF family, is a known key regulator of blood vessel growth (Shibuya, 2011, 2014) that is alternatively spliced into pro-or anti-angiogenic isoforms that also show opposing actions on vascular permeability and vasodilation (Beazley-Long et al., 2013). Additionally, the VEGFR-1 (FLT1), VEGFR-2 (KDR) and NRP1 receptors can be spliced into either transmembrane forms that signal through intracellular receptor tyrosine kinase (RTK) cascades or into soluble forms that act as scavengers of free ligand (Almodovar et al., 2009; Cackowski et al., 2004; Ebos et al., 2004). These points highlight the complexity of the VEGF signaling family and the need for comprehensive investigations of the entire VEGF gene family in the context of AD.

The present study investigates the interaction of prefrontal cortex VEGF gene and isoform expression with APOE-ε4 allele status on clinical AD, cognition and cognitive decline, as well as AD-related neuropathology. We hypothesize that higher expression of angiogenesis-specific VEGF genes and isoforms will modify the association between APOE-ε4 status and AD-related outcomes, such that ε4 carriers will show enhanced protection compared to non-carriers.

2. Methods

2.1. Participants

Data collected as part of the Rush University Religious Orders Study (ROS) and Memory and Aging Project (MAP) were utilized for this study. ROS data collection began in 1994 with Catholic clergy from across the USA, and MAP data collection began in 1997 across the Chicago area (Bennett et al., 2018). In both studies, older participants were non-demented at the time of enrollment, agreed to yearly clinical evaluation, and signed an informed consent, a repository consent for resource sharing, and an Anatomical Gift Act. The goal of these studies was to identify factors important for cognitive health during aging while monitoring the development of cognitive impairment, AD, and pathology of related disorders. Both studies were approved by an Institutional Review Board of Rush University Medical Center. Data sharing was carried out within the guidelines of Institutional Review Board (IRB)-protocols, and analyses were approved by the Vanderbilt University Medical Center IRB.

2.2. Neuropsychological Composites

Neuropsychological testing details have been previously published (Bennett et al., 2012a; Bennett et al., 2012b). Multiple aspects of cognition and memory were assessed using established protocols (Bennett et al., 2018). Z-score composites were then calculated in the domains of episodic memory, perceptual orientation, perceptual speed, semantic memory, and working memory. An average score across all 17 neuropsychological tests was calculated to represent global cognition.

2.3. Genotyping

DNA was extracted from peripheral blood monocytes (PBMCs) or brain tissue and underwent quality control measures as previously described (Keenan et al., 2012). APOE genotyping was performed by Polymorphic DNA Technologies using high-throughput sequencing of codons 112 and 158 of APOE exon 4, located on chromosome 19 (Oveisgharan et al., 2018).

2.4. Autopsy Measures of VEGF and APOE Gene Expression

Autopsies were performed to dissect and preserve tissue blocks from discrete brain regions. RNA was extracted from prefrontal cortices and sequenced using the Illumina HiSeq platform with 101 base paired-end reads. Details of sample processing and quality control measures have been previously published (Lim et al., 2014; Mostafavi et al., 2018). We analyzed RNA isoform expression of VEGF genes that interacted with APOE-ε4 on cognitive outcomes with the following number of isoforms available for each gene: VEGFA (14), NRP1 (12), VEGFB (3), VEGFC (2), VEGFD (2), NRP2 (13), FLT1 (3), FLT4 (8), KDR (1), PGF (5). RNA-Seq by Expectation Maximization (RSEM) was used in secondary analyses to assess isoform abundance, and isoforms of very low abundance (<10% expression in the cohort) were removed. Outliers, classified as values four standard deviations in either direction from the combined sample mean, were removed.

2.5. Neuropathological Measures

All neuropathological marker quantifications have been previously described (Bennett et al., 2012a; Bennett et al., 2012b). Briefly, amyloid load and paired helical filament tau density were quantified in eight brain regions (Bennett et al., 2006). Quantification of neuritic plaques and neurofibrillary tangles was based on silver staining of five brain regions (midfrontal cortex, midtemporal cortex, inferior parietal cortex, entorhinal cortex and hippocampus) to calculate the overall burden (Bennett et al., 2012b). TDP-43 immunoreactivity was assessed in the amygdala, nucleus accumbens, middle frontal gyrus, cingulate gyrus, dentate fascia, and inferior temporal cortex and scored on a graded scale (0=no pathology, 4=pathology in all regions) (Amador-Ortiz et al., 2007). Cerebral amyloid angiopathy (CAA) was measured by p-amyloid immunostaining in the midfrontal, midtemporal, angular, and calcarine cortices, and was scored on a scale from 0 – 4 (0=no pathology, 4=severe pathology) (Boyle et al., 2015; Love et al., 2014). Assessment of atherosclerosis was performed by visual inspection of the vertebral, basilar, posterior cerebral, middle cerebral, and anterior cerebral arteries of the Circle of Willis, as well as proximal branches and graded based on severity (0=no pathology, 4=severe pathology) (Arvanitakis et al., 2017). Arteriolosclerosis severity was classified by a semi-quantitative grading scale (0=no pathology, 3=severe pathology) after characterization of histologic changes in the vascular lumen (Buchman et al., 2011). Gross and micro infarcts were categorized as present (1) or absent (0) based upon visual inspection in nine brain regions (midfrontal, middle temporal, entorhinal, hippocampal, inferior parietal and anterior cingulate cortices, anterior basal ganglia, midbrain, and thalamus; (Arvanitakis et al., 2011; Schneider et al., 2007; Schneider et al., 2003).

2.6. Statistical Analyses

Data were analyzed using R (version 3.5.1, https://www.r-project.org) with APOE-ε4 allele status categorized using a dominant model (absence or presence). Linear regression models covaried for age at death, sex, postmortem interval, and interval between final visit and death assessed VEGF family gene expression associations with APOE-ε4 allele status and with APOE expression. A linear mixed effects regression model covaried for sex, age at death, postmortem interval, and interval between final visit and death, assessed VEGF family gene expression interactions with APOE expression on global cognitive change.

A binary logistic regression model assessed APOE-ε4 by VEGF family gene expression interactions on diagnosis (normal cognition [NC] compared to AD, mild cognitive impairment subjects were excluded from this analysis). Covariates included sex, age at time of death, postmortem interval, and interval between the last documented clinical visit and time of death.

A linear regression model covaried for sex, age at death, postmortem interval, and interval between final visit and death, was used to test for APOE-ε4 × VEGF family gene expression interactions on global cognition. Secondary analyses stratified by APOE-ε4 status investigated VEGF family gene expression associations with global cognition in ε4 carriers and non-carriers. This model was also used to investigate VEGF expression associations with APOE genotype and VEGF × APOE expression on global cognition. Additionally, a linear regression model covaried for sex, age at death, postmortem interval, and interval between final visit and death, was used to assess APOE-ε4 × VEGF family gene expression interactions on the following cognitive domains: episodic memory, perceptual orientation, perceptual speed, semantic memory, and working memory. Further, this linear regression model was also used to assess genome-wide interactions with the APOE-ε4 allele on cross-sectional global cognition.

A mixed effects regression model was used to analyze APOE-ε4 × VEGF family gene expression interactions on annual cognitive change. Fixed effects included age at death, APOE-ε4 status, sex, VEGF family expression, postmortem interval, years before death, and interval (years between last visit and the current visit). A three-way APOE-ε4 × VEGF × interval interaction was the term of interest. Random effects included the interval and intercept. Secondary analyses were stratified by APOE-ε4 status. All models were subjected to the Benjamini-Hochberg false discovery rate procedure (Benjamini and Hochberg, 1995) to correct for multiple comparisons (ie, correction for all 10 VEGF family genes).

AD-related neuropathological outcomes included amyloid load, paired helical filament tau density, neuritic plaques, and neurofibrillary tangles, all of which were square-root transformed. Linear models, covaried for age at death, postmortem interval, and sex, assessed APOE-ε4 × VEGF expression interactions on AD-related neuropathological outcomes. Non-AD neuropathological outcomes were assessed for APOE-ε4 × VEGF expression interactions using a binary logistic model for hippocampal sclerosis, gross infarcts and microinfarcts. A proportional odds logistic regression model evaluated APOE-ε4 × VEGF expression interactions on cerebral amyloid angiopathy (CAA), atherosclerosis, arteriolosclerosis, and TDP-43 reactivity. Macroinfarct count was analyzed using a Poisson regression model, and macroinfarct volume was square-root transformed and assessed using linear regression.

Sensitivity analyses were carried out for the cognitive and neuropathology models described above excluding individuals diagnosed with clinical AD to test if diagnostic status accounted for significant results. In addition, models were run using unique isoforms of VEGF genes that showed significant interactions with APOE-ε4 to determine if isoform-specific expression was responsible for significant interaction results. Isoform-specific models were corrected for multiple comparisons using the FDR procedure with the a priori threshold for statistical significance set to P.fdr<0.05.

Additional sensitivity analyses were performed to determine if cell-type marker expression, included as a covariate, would significantly alter model predictions. We first analyzed correlations between VEGF family expression and cell-type marker expression. Models were then re-run covarying for expression of either neuronal marker ENO2 or expression of all other available cell-type markers (OLIG2, oligodendrocytes; GFAP, astrocytes; CD34, endothelial cells; CD38, microglia,). These cell-type markers have been previously validated after comparisons of expression profiles and cell population frequency in cortical tissue in this cohort (Mostafavi et al., 2018; Patrick et al., 2019) and have been utilized to examine cell-type effects in previous analyses (Mahoney et al., 2019). Additionally, we calculated adjusted VEGF expression by residualizing the association between each gene and cell-type marker. This adjusted expression was then used to re-run the models described above.

3. Results

3.1. Participant Demographics

Summary demographic data are presented in Table 1. This cohort was long-lived, highly educated, with the majority self-identifying as non-Hispanic White. As expected, the proportion of APOE-ε4 carriers was higher among AD cases (35%) compared to NC (14%), and baseline global cognition scores declined across diagnostic groups (NC highest, AD lowest). It is noteworthy that the prevalence of APOE-ε4 carriers among participants diagnosed with clinical AD is less than other AD cohorts (Frisoni et al., 1998; Heffernan et al., 2016; Ward et al., 2012), however this is likely due to enrollment criteria that required participants to be non-demented at time of enrollment and the community-based nature of studies. The average age of AD diagnosis in this cohort was 82.1 ± 6.3 years of age. Age at time of death was also significantly different across diagnostic groups, with AD cases being the oldest at time of death.

Table 1.

Cohort demographics and summary statistics

	Clinical Diagnosis			Total (N=531)	P
	Normal Cognition (N=180)	Mild Cognitive Impairment (N=148)	Alzheimer’s Disease (N=203)
Age of death, years	86±7	89±6	91±6	89±7	<0.001
Male, no. (%)	70 (39)	54 (36)	70 (34)	194 (37)	0.67
Non-Hispanic white, no. (%)	177 (98)	146 (99)	195 (96)	518 (98)	0.21
Education, years	17±4	16±3	17±4	17±4	0.59
Global cognition composite z score (at last visit)	0.14±0.42	−0.49±0.45	−1.85±0.91	−0.80±1.09	<0.001
Average number of visits	7.12±4.04	6.93±3.65	7.55±3.69	7.23±3.8	0.26
APOE-ε4 carriers, no. (%)	25 (14)	30 (20)	72 (35)	127 (24)	<0.001
APOE-ε2 carriers, no. (%)	32 (18)	19 (13)	36 (18)	87 (16)	0.39

Values are presented as mean±standard deviation, unless otherwise indicated. Boldface indicates P<0.05.

3.2. VEGF Gene Expression Associations with APOE-ε4 Allele Status and APOE Expression

No VEGF ligand or receptor genes were differentially expressed between APOE-ε4 carriers and non-carriers (p-values>0.09, Supplemental Table 1). Additionally, no VEGF genes interacted with APOE expression on global cognition prior to death or cognitive change (p-values>0.06, Supplemental Table 2).

3.3. VEGF Gene Expression Interactions with APOE-ε4 Allele Status on Diagnosis

Using a binary logistic regression model, we found that NRP1 (β=0.77, p.fdr=0.037) expression interacted with APOE-ε4 status on clinical diagnosis (NC compared to AD). NRP2 expression fell just beyond the threshold for APOE-ε4 interaction significance after correction for multiple comparisons (p.fdr=0.060). After stratifying participants by APOE-ε4 status, lower NRP1 expression was significantly associated with AD diagnosis in ε4 non-carriers. Interaction and stratified results are presented in Supplemental Table 3.

3.4. VEGF Gene Expression Interactions with APOE-ε4 Allele Status on Cognitive Performance

Cross-sectional analyses revealed NRP1 and VEGFA interacted with APOE-ε4 on global cognitive performance at the final neuropsychological assessment (NRP1: β=−0.287, p.fdr=0.004; VEGFA: β=−0.03, p.fdr=0.026; Table 2, Figure 1). We interpreted this interaction as evidence that NRP1 and VEGFA expression associations with late life cognition differ by APOE-ε4 status. To clarify the nature of these interaction results on cross-sectional cognition, stratified analyses showed that in APOE-ε4 carriers, higher expression of NRP1 (β=−0.176, p=0.034) and VEGFA (β=−0.027, p=0.019) were associated with worse global cognition scores; whereas in APOE-ε4 non-carriers, higher NRP1 (β=0.112, p=0.003) expression predicted better global cognition scores. Both interaction and stratified results on cognitive performance are summarized in Table 2. These APOE-ε4 interactions on global cognition did not survive a genome-wide correction in this cohort (Supplemental Figure 1), however the power for genome-wide analyses was quite low given the sample size.

Table 2.

Cross-sectional VEGF × APOE-ε4 interactions and stratified results on global cognition

	Interaction				APOE-ε4 Carriers (N=127)				APOE-ε4 Non-Carriers (N=404)
Gene	β	SE	P	P.fdr	β	SE	P	P.fdr	β	SE	P	P.fdr
NRP1	−0.287	0.080	3.58E-04*	0.004	−0.176	0.082	0.034	0.114	0.112	0.037	0.003	0.015
VEGFA	−0.030	0.011	0.005	0.026	−0.027	0.011	0.019	0.097	0.004	0.005	0.416	0.594
FLT1	−0.055	0.026	0.035	0.118	−0.065	0.026	0.015	0.097	−0.005	0.013	0.711	0.790
FLT4	−0.237	0.164	0.148	0.304	−0.333	0.168	0.049	0.124	−0.110	0.085	0.196	0.538
VEGFB	0.005	0.004	0.152	0.304	−0.003	0.004	0.522	0.663	−0.007	0.002	3.48E-05*	3.48E-04*
KDR	0.292	0.258	0.259	0.431	0.229	0.280	0.416	0.663	0.017	0.120	0.884	0.884
VEGFD	0.240	0.305	0.433	0.618	0.140	0.316	0.657	0.720	−0.153	0.147	0.299	0.594
PGF	−0.023	0.062	0.707	0.809	−0.069	0.065	0.294	0.589	−0.038	0.030	0.215	0.538
VEGFC	−0.136	0.391	0.728	0.809	−0.267	0.424	0.531	0.663	−0.072	0.169	0.669	0.790
NRP2	0.023	0.153	0.883	0.883	0.058	0.160	0.720	0.720	0.056	0.069	0.416	0.594

P.fdr represents corrected P-values. Boldface signifies P≤0.05.

^*denotes results that were significant after adjusting for all models tested for main outcomes (cognition, diagnosis)

Figure 1.

(A) NRP1 expression associations with global cognitive performance at the final neuropsychological assessment, stratified by APOE-ε4 allele status. Overall interaction: NRP1 × APOE-ε4, β=−0.28, p.fdr=0.007; APOE-ε4 carriers, β=−0.17, p=0.038; APOE-ε4 non-carriers, β=0.11, p=0.004. (B) VEGFA expression associations with global cognitive performance at the final neuropsychological assessment, stratified by APOE-ε4 allele status. Overall interaction: VEGFA × APOE-ε4, β=−0.03, p.fdr=0.026; APOE-ε4 carriers, β=−0.03, p=0.019; APOE-ε4 non-carriers, β=0.004, p=0.4.

Additional models to assess VEGF × APOE-ε4 interactions on specific cognitive domains did not reveal novel interactions compared to the global cognition results. These separated cognitive domain analyses did reveal that working memory, semantic memory and perceptual orientation appear to drive the NRP1 × APOE-ε4 interaction on global cognition. Further, stratified analyses of this model showed the same interaction trend among APOE-ε4 non-carriers as the global cognition results. Specifically, higher NRP1 expression was associated with better working and semantic memory, as well as better perceptual orientation among APOE-ε4 non-carriers (Supplemental Figure 2, Supplemental Tables 4 – 7).

Longitudinally, no VEGF genes interacted with APOE-ε4 on global cognitive change (Table 3). These results indicate that VEGF family expression associations with cognitive decline did not differ by APOE-ε4 status.

Table 3.

Longitudinal VEGF × APOE-ε4 interactions and stratified results on global cognitive change

	Interaction				APOE-ε4 Carriers (N=127)				APOE-ε4 Non-Carriers (N=404)
Gene	β	SE	P	P.fdr	β	SE	P	P.fdr	β	SE	P	P.fdr
NRP1	−0.015	0.009	0.084	0.439	−0.008	0.009	0.388	0.583	0.007	0.004	0.104	0.207
KDR	0.044	0.028	0.120	0.439	0.034	0.030	0.260	0.544	−0.015	0.012	0.211	0.351
VEGFB	0.001	4.16E-04	0.155	0.439	−3.28E-04	4.48E-04	0.465	0.583	−0.001	1.92E-04	1.46E-06*	1.46E-05*
VEGFA	−0.002	0.001	0.176	0.439	−0.002	0.001	0.135	0.544	−1.95E-04	0.001	0.709	0.788
VEGFD	0.036	0.034	0.285	0.571	0.021	0.035	0.546	0.607	−0.012	0.016	0.441	0.552
NRP2	0.012	0.017	0.492	0.819	0.013	0.018	0.466	0.583	−7.41E-06	0.008	0.999	0.999
VEGFC	0.023	0.044	0.608	0.869	0.006	0.048	0.909	0.909	−0.020	0.018	0.282	0.403
FLT4	−0.007	0.018	0.723	0.904	−0.032	0.019	0.090	0.544	−0.025	0.009	0.006	0.021
FLT1	−4.65E-04	0.003	0.874	0.918	−0.004	0.003	0.229	0.544	−0.004	0.001	0.011	0.028
PGF	0.001	0.007	0.918	0.918	−0.008	0.007	0.272	0.544	−0.009	0.003	0.004	0.021

P.fdr represents corrected P-values. Boldface signifies P≤0.05.

^*denotes results that were significant after adjusting for all models tested for main outcomes (cognition, diagnosis)

3.5. VEGF Gene Expression Interactions with APOE-ε4 Allele Status on Neuropathology

No significant interactions were observed between APOE-ε4 and VEGF expression on AD neuropathology (Supplemental Table 8). Models to assess VEGF × APOE interactions on other neuropathological measures showed no significant interaction on CAA, cerebral atherosclerosis, arteriolosclerosis, TDP-43, hippocampal sclerosis, gross infarcts, or microinfarcts (Supplemental Table 9).

3.6. Sensitivity Analyses

NRP1 and VEGFA interacted with APOE-ε4 on cross-sectional global cognition, so we analyzed VEGFA and NRP1 isoform-specific interactions with APOE-ε4 on this outcome, which showed that pro-angiogenic coding transcripts of VEGFA (VEGFA-207, VEGFA-205) and several protein coding transcripts of NRP1 interacted with APOE-ε4 on global cognition (Supplemental Table 10).

Additionally, models were run using an adjusted VEGF gene expression value that was calculated by residualizing the association between expression and a given cell marker on global cognition. A correlation matrix for VEGF family and cell-type marker expression can be found in Supplemental Figure 3. Due to the fact that expression data were derived from tissue homogenate, we re-analyzed cross-sectional and longitudinal cognition interaction models to determine if significant VEGF expression × APOE-ε4 allele status interaction results persisted after adjusting for cell-specific effects. Cross-sectional results were generally consistent across cell-type marker adjustments and additional covariate models. Longitudinal results were consistent between the adjusted and unadjusted expression models. Cross-sectional results can be found in Supplemental Table 11 and longitudinal results can be found in Supplemental Table 12.

4. Discussion

We set out to determine how differences in VEGF gene family expression might interact with one of the strongest genetic risk factors for sporadic AD, APOE-ε4 status, to predict age-related cognitive decline and clinical AD diagnosis. NRP1 and VEGFA interacted with APOE-ε4 to modify the association between ε4 and the final global cognition score. Interestingly, effects of NRP1 expression on cognition in ε4 carriers compared to non-carriers was the opposite of expectation, such that higher expression of NRP1 was associated with worse outcomes in carriers and better outcomes in non-carriers. VEGF × APOE-ε4 interactions were not observed on AD pathology, suggesting these gene expression interactions were not driven by neuropathological changes. Further, no significant VEGF × APOE-ε4 interactions on pathological outcomes such as CAA suggest that amyloid build-up in vasculature does not drive the associations we observe on cognition.

The VEGF genes that modified the association between APOE-ε4 and cross-sectional cognition (NRP1 and VEGFA) are positive modulators of angiogenic signaling (Almodovar et al., 2009; Lee et al., 2011; Soker et al., 1998; Zhang et al., 2010). VEGFA binds NRP1, which forms a complex with KDR on endothelial cells to initiate intracellular signaling associated with the proliferation, migration, and survival of endothelial cells (Lee et al., 2011; Lee et al., 1996; Soker et al., 1998). Cerebrovascular deficits are an early feature of AD and cognitive decline with aging, and cerebrovascular ischemic disease has been found to contribute to the severity of cognitive decline (Love and Miners, 2016; Serrano-Pozo, 2019). The protective effects associated with high expression of angiogenesis relevant genes in ε4 non-carriers could reflect a mechanism to prevent ischemia and downstream neurodegeneration. However, angiogenic mechanisms may become damaging in the presence of the ε4 allele due to an over production of new vessels that are especially prone to leaking, as APOE-ε4 has been associated with increased blood-brain barrier leakiness resulting in cognitive decline (Serrano-Pozo, 2019; Tai et al., 2016). It is also possible that an increase in NRP1 expression in ε4 carriers causes an over-permeabilization of existing vessels as VEGF signaling is closely tied to vascular permeability (Bates, 2010). In opposition to our original hypothesis for this study, results suggest that VEGF signaling may be beneficial in APOE-ε4 non-carriers but detrimental in carriers, and it seems most plausible that this effect is mediated through angiogenic or endothelial cell remodeling processes.

It is interesting to note that we did not observe significant VEGF × APOE-ε4 interactions on neuropathology. Beta-amyloid peptides have been shown to antagonize VEGFR-2 (Patel et al., 2010), suggesting amyloid accumulation could represent a potential modulator of receptor mRNA expression. Additionally, the build-up of amyloid plaques has been hypothesized to trap free VEGFA and contribute to an up-regulation in expression (Almodovar et al., 2009), but our data do not suggest that the interactions between any VEGF family genes and APOE are driven primarily by alterations in amyloid, tau, or any of the other measured neuropathologies. It is notable that, as reported in earlier work from our group (Mahoney et al., 2019), there are main effects of VEGF family genes on AD neuropathology, but these associations do not differ by ε4 status. Thus, it is likely that the APOE-specific vulnerability is due either to a process downstream of neuropathology, such as a unique vulnerability to repair processes highlighted above, or a process that is entirely independent of measured neuropathology. It is also possible that differences in VEGF expression could influence subclinical brain alterations that may not be overtly detectable upon post-mortem observation but could manifest differentially between ε4-carriers and non-carriers. Future studies which incorporate markers of angiogenesis or vascular health may help elucidate underlying brain or vascular changes which may be influenced by VEGF expression.

While significant cross-sectional cognition interaction results did not survive genome-wide correction, results of this study contribute insight for the main effects of the VEGF family on global cognition in this cohort (Mahoney et al., 2019). Main effects results compared with APOE-ε4 interaction results showed that VEGFA and NRP1 expression are not associated with global cognition unless the APOE-ε4 allele is taken into account. This is particularly interesting given the literature that connects VEGFA to cognition without consideration of APOE-ε4. It is notable that our observed results appear to be counter to the protective effects of VEGFA that have been reported in humanized APOE-ε4 mouse models (Salomon-Zimri S, 2016). It is possible that the association between high VEGF expression and worse cognitive trajectories in ε4 carriers is reflective of upregulation by inflammatory cytokines (Angelo and Kurzrock, 2007; Maloney and Gao, 2015; Nagineni et al., 2012), which are also associated with AD progression (Heppner et al., 2015; Kinney et al., 2018), and that the observed VEGF expression effects could be a consequence of AD-related inflammation. The reparative role of angiogenesis in other conditions, such as cerebral ischemia and stroke, has also been well characterized (Li WW, 2005; Uccelli Andrea, 2019), and it is possible that the upregulation in VEGF expression is a compensatory mechanism that fails to rescue cognitive decline. It could also be the case that transcript levels are not reflective of protein VEGF levels. Future proteomic analyses could help to shed light on the underlying expression differences we observed.

Due to the heterogeneity of cell types in brain homogenates, we considered models that covaried or residualized for expression of a neuronal-specific marker (ENO2) as well as cell-type markers for astrocytes (GFAP), microglia (CD68), endothelial cells (CD34), and oligodendrocytes (OLIG2). Results were not significantly altered by adjusting for these cell-type markers.

Another interesting result was the lack of interaction between APOE expression and VEGF expression. Previous literature has debated the influence of genotype on APOE expression (Beffert et al., 1999; Harr et al., 1996; Kim et al., 2009) and the significance of APOE expression in AD (Bertrand et al., 1995; Pirttilä et al., 1996). Our study suggests that the interactions between VEGF genes and APOE-ε4 on cognition are driven by genotype-specific effects of APOE rather than brain APOE expression levels.

Several factors of this study limit generalizability, including the high level of participant education, lack of racial diversity and use of brain homogenate data which limits cell-type specific conclusions. An additional consideration is the inability to discern causal relationships given that the expression levels likely reflect a combination of cause and consequence of disease. It is also important to note the preliminary nature of the findings reported in this study, as the global cognition findings have not been replicated in another dataset. As no comparable data sets exist in the public domain, replication of this study remains a future goal.

However, this analysis also possesses several strengths, including the rich longitudinal cognitive data, measurable expression of all genes in the VEGF family in brain tissue, ample neuropathological data, and the comprehensive clinical characterization of the cohort. Future work should replicate these findings in other cohorts and investigate the underlying biological mechanisms driving these interactions on cognition through detailed proteomic and angiogenesis pathway analyses.

5. Conclusion

In summary, we found that NRP1 and VEGFA interacted with APOE-ε4 on cognition. Interestingly, higher expression of NRP1 was associated with beneficial outcomes in ε4 non-carriers and cognitive decline in ε4 carriers. These results suggest that angiogenic signaling may have different effects based upon an individual’s APOE-ε4 status. Further investigation of the biological interaction between the VEGF family, especially components relevant to angiogenesis, and APOE genotype, as well as replication of cognitive associations in an independent data set, is warranted to better understand how these genes and proteins impact cognitive outcomes in older adults.