Molecular Genetics
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/21632
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Browsing Molecular Genetics by Author "Pathak, Gita"
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Item Candidate Gene Association Study of Low Back Pain Using SNP Derived Gene Expression Profiling: A PRECISION PAIN Research Registry Study(2019-03-05) Pathak, Gita; Aryal, Subhash; Phillips, Nicole R.; Licciardone, John C.; Bhatnagar, ShwetaCandidate Gene Association Study of Low Back Pain Using SNP Derived Gene Expression Profiling: A PRECISION PAIN Research Registry Study Shweta Bhatnagar, Gita Pathak, Subhash Aryal, Nicole Phillips, John Licciardone Abstract Objective: The Global Burden of Disease Study estimated that 632 million persons worldwide are affected by low back pain (LBP), making it the leading cause of disability worldwide. Furthering our understanding of genetic-based risk for LBP may allow for development of targeted gene therapy for pain which may help mitigate the healthcare and financial burden. Inflammatory genes have been implicated in pain disorders. Variability in how these genes are expressed may determine their association in low back pain. This study aims to predict the expression of candidate genes and their association with pain in participants of the PRECISION Pain Research Registry. Hypothesis: Elevated self-reported pain intensity and disability from LBP is associated with the higher expression of inflammatory genes. Methods: The DNA was collected, extracted, and genotyped using the Infinium® Global Screening Array (Illumina). Data were filtered based on standard quality control protocols (Anderson et al., 2010). Gene expression data of monocytes from the Multi-Ethnic Study for Atherosclerosis (MESA) was used for gene expression imputation using PrediXcan. Twenty-six candidate genes involved with inflammation and immune response processes (based on Gene Ontology Analysis) were analyzed. The imputed gene expression levels were transformed to dichotomized gene expression levels, over-expressed and under-expressed. The highly expressed gene levels were then tested for association with PRECISION participant outcomes data, including Roland-Morris Disability Score and a pain intensity score using SPSS. Results: Seven genes showed positive correlation between their predicted expression levels and scores on the Roland-Morris Questionnaire and the pain intensity scale for LBP: STAT-1, STAT-2, HLA-A, CD48, CD209, CLEC4G and SLAMF8. Also, as expected, many of these genes demonstrated co-expression patterns due to their common role in immune mediation. Conclusions: The results demonstrate a positive correlation between the increased expression of inflammatory genes and how the subjects perceived and reported LBP. Understanding the relationship between pain and variability in inflammatory genes could play a role in future precision medicine and pain management.Item Mito-nuclear compatibility in risk for cognitive decline in admixed populations(2019-03-05) Pathak, Gita; Barber, Robert C.; Phillips, Nicole R.; Silzer, Talisa K.Background. The issue of missing heritability has vexed the study of many complex diseases, Alzheimer’s disease (AD) not excluded. Only ~35% of the heritability of AD has been accounted for, the majority of which lies in APOE allele e4, which has a less-pronounced effect in certain admixed populations. There are few genetic and/or mitochondrial studies of admixed populations, and our understanding of mitochondrially-related cognitive decline has largely been based on studies of highly homogenous populations (by design). The concept of mito-nuclear compatibility states that optimization of mitochondrial DNA (mtDNA) with nuclear genetic background is a source of significant selective evolutionary pressure. Evidence for this phenomenon in human populations is emerging (Zaidi and Makova, 2019), and opens the door for studies in the context of human disease. Purpose. The purpose of this study is to determine whether divergent nuclear and mitochondrial genomes confer risk for cognitive impairment and decline in admixed populations. Methods. Participants in the Texas Alzheimer’s Research and Care Consortium (TARCC) were used for this study. DNA extracts from peripheral blood buffy coat were genotyped on the Multi-Ethnic Genotyping Array (Illumina) which types 1.7 million SNPs and includes ancestry specific genetic variation. The top 10 eigenvectors (smartpca via Eigensoft) were generated via principle component analysis of nuclear DNA (nDNA) and used to cluster subjects with the 1000 Genomes population data in order to ascertain global, ancestral nDNA background. Mitochondrial DNA variants from the array were analyzed using HaploGrep/MitoTool for mtDNA haplotype assignment. Non-concordance of mtDNA:nDNA ancestry will be identified and scored as in Zaidi and Makova, 2019 and tested for association with cognitive state (normal, mild cognitive impairment, or Alzheimer’s disease) as well as cognitive decline between time points. Results. Preliminary studies indicate that cognitive decline is associated with mitochondrial phenotypes in Caucasian subjects; these results were dependent on sex. Mitochondrial copy number was a main driver in the predictive model in both males and females, but to a differing degree. Conclusion. Discrepancy between mtDNA and nDNA genomic backgrounds has been previously correlated with mtDNA copy number (Zaidi and Makova, 2019); similar discrepancy may explain health disparities in complex diseases that are more prevalent in particular admixed populations.