Presentation Title (IN ALL CAPS)

GENE EXPRESSION PROFILES OF BRAIN TISSUES: CONSIDERING AGING POPULATION IN THE INVERSE RELATIONSHIP BETWEEN ALZHEIMER’S AND CANCER

Departmental Affiliation and City, State, Zip for All Authors

Department of Microbiology, Immunology and Genetics, Department of Pharmacology & Neuroscience, Graduate School of Biomedical Sciences, UNT Health Science Center, Fort Worth, TX

Classification

GSBS Student (For Competition)

Research Presentation Category

Health Disparities

Layperson Narrative or Summary (3-5 sentences)

Recent disease surveillance studies have observed that individuals with Alzheimer’s disease have a lower risk of cancer history and both diseases are highly prevalent in the aging population. To attain effective personalized therapeutics, understanding the implications of genetic variants (SNPs) on disease biology is necessary. Therefore, this study investigates the influence of SNPs on gene expression profile of Alzheimer’s, breast and prostate cancer to identify inversely regulated gene expression signatures that may be contributing to disease risk.

Scientific Abstract

Large-scale epidemiological studies have reported that individuals with Alzheimer’s disease have a lower risk of cancer history, and both diseases are highly prevalent in the aging population. The inverse relationship between Alzheimer’s and cancer provides an opportunity to better understand their protective pathogenicity over each other. In this study, the authors explore the inverse association of Alzheimer’s and cancer in gene expression profiles predicted from cis-SNPs within 1kb of the gene position. The genetic data was acquired from Alzheimer’s Disease Neuroimaging Initiative (ADNI) and dbGaP’s Breast and Prostate Cancer Cohort Consortium (BPC3) via authorized access application. The datasets – ADNI, Breast, and Prostate cancer had 677, 578 and 3857 individuals, respectively with ~550,000 SNPs, and all subjects were more than 50 years old. The genotype-derived transcriptomic profiles were investigated in five brain tissues from the GTEx consortium using PrediXcan. The expression profiles of Alzheimer’s, breast and prostate cancer were analyzed using hierarchical clustering and pathway enrichment analysis to identify inversely regulated gene expression signatures. Single nucleotide variations have contributed tremendously towards identifying risk variants for complex diseases, however, their influence on the functional biology of the disease phenotype remains understudied. Therefore, the goal of this explorative study is to identify which variants may be affecting the opposite functional association between Alzheimer’s and cancer to allow for precision healthcare in geriatric populations.

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GENE EXPRESSION PROFILES OF BRAIN TISSUES: CONSIDERING AGING POPULATION IN THE INVERSE RELATIONSHIP BETWEEN ALZHEIMER’S AND CANCER

Large-scale epidemiological studies have reported that individuals with Alzheimer’s disease have a lower risk of cancer history, and both diseases are highly prevalent in the aging population. The inverse relationship between Alzheimer’s and cancer provides an opportunity to better understand their protective pathogenicity over each other. In this study, the authors explore the inverse association of Alzheimer’s and cancer in gene expression profiles predicted from cis-SNPs within 1kb of the gene position. The genetic data was acquired from Alzheimer’s Disease Neuroimaging Initiative (ADNI) and dbGaP’s Breast and Prostate Cancer Cohort Consortium (BPC3) via authorized access application. The datasets – ADNI, Breast, and Prostate cancer had 677, 578 and 3857 individuals, respectively with ~550,000 SNPs, and all subjects were more than 50 years old. The genotype-derived transcriptomic profiles were investigated in five brain tissues from the GTEx consortium using PrediXcan. The expression profiles of Alzheimer’s, breast and prostate cancer were analyzed using hierarchical clustering and pathway enrichment analysis to identify inversely regulated gene expression signatures. Single nucleotide variations have contributed tremendously towards identifying risk variants for complex diseases, however, their influence on the functional biology of the disease phenotype remains understudied. Therefore, the goal of this explorative study is to identify which variants may be affecting the opposite functional association between Alzheimer’s and cancer to allow for precision healthcare in geriatric populations.