Research Paper Volume 14, Issue 6 pp 2524—2536

VEGF-A-related genetic variants protect against Alzheimer’s disease

Alexandros M. Petrelis1, , Maria G. Stathopoulou2, , Maria Kafyra1,3, , Helena Murray4, , Christine Masson1, , John Lamont4, , Peter Fitzgerald4, , George Dedoussis1,3, , Frances T. Yen5, , Sophie Visvikis-Siest1, ,

  • 1 IGE-PCV, Université de Lorraine, Nancy 54000, France
  • 2 Inserm, C3M, Team Control of Gene Expression (10), Université Cote d’Azur, Nice, France
  • 3 Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece
  • 4 Randox Laboratories Limited, Crumlin, County Antrim BT29 4QY, United Kingdom
  • 5 Qualivie, UR AFPA laboratory, University of Lorraine, Vandoeuvre-les-Nancy, Lorraine, France

Received: December 31, 2021       Accepted: March 14, 2022       Published: March 28, 2022
How to Cite

Copyright: © 2022 Petrelis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


The Apolipoprotein E (APOE) genotype has been shown to be the strongest genetic risk factor for Alzheimer’s disease (AD). Moreover, both the lipolysis-stimulated lipoprotein receptor (LSR) and the vascular endothelial growth factor A (VEGF-A) are involved in the development of AD. The aim of the study was to develop a prediction model for AD including single nucleotide polymorphisms (SNP) of APOE, LSR and VEGF-A-related variants.

The population consisted of 323 individuals (143 AD cases and 180 controls). Genotyping was performed for: the APOE common polymorphism (rs429358 and rs7412), two LSR variants (rs34259399 and rs916147) and 10 VEGF-A-related SNPs (rs6921438, rs7043199, rs6993770, rs2375981, rs34528081, rs4782371, rs2639990, rs10761741, rs114694170, rs1740073), previously identified as genetic determinants of VEGF-A levels in GWAS studies. The prediction model included direct and epistatic interaction effects, age and sex and was developed using the elastic net machine learning methodology.

An optimal model including the direct effect of the APOE e4 allele, age and eight epistatic interactions between APOE and LSR, APOE and VEGF-A-related variants was developed with an accuracy of 72%. Two epistatic interactions (rs7043199*rs6993770 and rs2375981*rs34528081) were the strongest protective factors against AD together with the absence of ε4 APOE allele. Based on pathway analysis, the involved variants and related genes are implicated in neurological diseases.

In conclusion, this study demonstrated links between APOE, LSR and VEGF-A-related variants and the development of AD and proposed a model of nine genetic variants which appears to strongly influence the risk for AD.


AD: Alzheimer’s disease; APOE/ApoE: Apolipoprotein E; APP: Amyloid Beta Precursor; ARHGAP27: Rho GTPase Activating Protein 27; BBB: Blood-brain barrier; ECs: Endothelial Cells; EN: Elastic Net; EPB41L4A: Erythrocyte Membrane Protein Band 4.1 Like 4A; EPO: Erythropoietin; GTDC1: Glycosyltransferase Like Domain Containing 1; LRRTM3: Leucine Rich Repeat Transmembrane Neuronal 3; LSR: Lipolysis Stimulated Lipoprotein Receptor; MPV17L: Mitochondrial Inner Membrane Protein Like; NPL: N-Acetylneuraminate Pyruvate Lyase; PI3K: Phospoinositide 3-kinase; SNP(s): Single Nucleotide Polymorphism(s); TRIM25: Tripartite Motif Containing 25; VASH2: Vasohibin 2; VLDL: Very low-density lipoprotein; ZADH2: Zinc Binding Alcohol Dehydrogenase Domain Containing 2; SD: Standard deviation; MAF: Minor allele frequency; HW: Hardy-Weinberg; ZFPM2: Zinc finger protein, FOG family member 2; NFT: Neurofibrillary tangles; IPA: Ingenuity Pathway Analysis; VEGF-A: Vascular endothelial growth factor A; CVD: Cardiovascular disease.