Affiliations: [a] Department of Biostatistics, University of NorthCarolina at Chapel Hill, Chapel Hill, NC, USA
| [b] Department of Psychiatry, University of NorthCarolina at Chapel Hill, Chapel Hill, NC, USA
| [c] Department of Computer Science, University ofNorth Carolina at Chapel Hill, Chapel Hill, NC, USA
Correspondence:
[*]
Correspondence to: Guorong Wu, PhD, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Tel.: +1 919 966 2216; E-mail: [email protected].
Note: [1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (https://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: https://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.
Abstract: Background:With the rapid development of neurobiology and neuroimaging technologies, mounting evidence shows that Alzheimer’s disease (AD) is caused by the build-up of two abnormal proteins, amyloid-β plaques (A) and neurofibrillary tangles (T). Over time, these AD-related neuropathological burdens begin to spread throughout the brain, which results in the characteristic progression of symptoms in AD. Objective:Although tremendous efforts have been made to link biological indicators to the progression of AD, limited attention has been paid to investigate the multi-factorial role of socioeconomic status (SES) in the prevalence or incidence of AD. There is high demand to explore the synergetic effect of sex and SES factors in moderating the neurodegeneration process caused by the accumulation of A and T biomarkers. Methods:We carry out a meta-data analysis on the longitudinal neuroimaging data, clinical outcomes, genotypes, and demographic data in Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). Results:Our major findings include 1) education and occupation show resilience effects at the angular gyrus, superior parietal lobule, lateral occipital-temporal sulcus, and posterior transverse collateral sulcus where we found significant slowdown of neurodegeneration due to higher education level or more advanced occupation rank; 2) A and T biomarkers manifest different spatial patterns of brain resilience; 3) BDNF (brain-derived neurotrophic factor) single nucleotide polymorphism (SNP) rs10835211 shows strong association to the identified resilience effect; 4) the identified resilience effect is associated with the clinical manifestation in memory, learning, and organization performance. Conclusion:Several brain regions manifest resilience from SES to A and T biomarkers. BDNF SNPs have a potential association with the resilience effect from SES. In addition, cognitive measures of learning and memory demonstrate the resilience effect.
