An $L_0$ Regularization Method for Imaging Genetics and Whole Genome Association Analysis on Alzheimer's Disease

Although the neuroimaging measures build a bridge between genetic variants and disease phenotypes, an assessment of single nucleotide variants changes in brain structure and their clinically influence on the progression of Alzheimer's disease remain largely preliminary. Note that each variant has very weak correlation signal to neuroimaging measures or Alzheimer's disease phenotypes. Therefore, traditional sparse regression-based image genetics approaches confront with unresolvable features, relative high regression error or inapplicability of high-dimensional data. Adopting an $\text{L}_0$ regularization method, we significantly elevate the regression accuracy of imaging genetics compared with group-sparse multitask regression method. With further analysis on the simulation results, we conclude that multiple regression tasks model may be unsuitable for image genetics. In addition, we carried out a whole genome association analysis between genetic variants (about 388 million loci) and phenotypes (cognition normal, mild cognitive impairment and Alzheimer's disease) with using the $\text{L}_0$ regularization method. After annotating the effect of all variants by Ensembl Variant Effect Predictor (VEP), our method locates 33 missense variants which can explain 40% phenotype variance. Then, we mapped each missense variant to the nearest gene and carried out pathway enrichment analysis. The Notch signaling pathway and Apoptosis pathway have been reported to be related to the formation of Alzheimer's disease.

I. Introduction

Alzheimer disease (AD) is a chronic neurodegenerative disease and causes cognitive decline in elderly individuals. AD is pathologically defined by the presence of amyloid- (A) accumulation in amyloid plaques, tau aggregation in neurofibrillary tangles and brain atrophy caused by loss of neurons and synapses [1]. Apolipoprotein 4 allele (APOE4) is considered as a risk factor for AD [2]. APOE is highly expressed in astrocytes and disease-associated microglia (or DAMs) in the brain, implicating a role for these cell types in pathogenesis. Studies [3], [4] declared that the innate immune system and inflammation play a key role in formation of AD, so that those genes encoding triggering receptor expressed on myeloid cells 2 (TREM2), complement receptor 1 (CR1), CD33 and inositol polyphosphate-5-phosphatase (INPP5D) are also potent risk factors. In addition to tumorigenesis, Notch signaling is also involved in determining the fates of neural and nonneural cells and alterations in proteolysis of the Notch by -secretase could play key role in the pathogenesis of AD [5]–[7]. Studies have indicated that apoptotic mechanisms could be instrumental in neurodegeneration in AD. Therefore, detailed and precise study of apoptotic mechanisms in AD is important for treating and preventing AD [8], [9].