Gloriia Novikova, United States of America

Icahn School of Medicine at Mount Sinai Neuroscience

Gloriia is a PhD candidate at Icahn School of Medicine at Mount Sinai, where her research focuses on applying integrative statistical methods for large-scale genomics data to study the role of the innate immune system in Alzheimer’s disease. Gloriia graduated from Purdue University with a degree in Chemical Engineering. At Purdue, she studied the chemistry of nanowire synthesis as well as nanobubble drug delivery vehicles for treatment of bladder cancer. Gloriia is also currently working on her Master’s program in Analytics at Georgia Tech, where she hopes to deepen her quantitative skills to build robust and scalable statistical methods to translate the findings from genomic data to novel treatments. Gloriia is interested in expanding her knowledge of neurodegenerative diseases and is excited to learn more about therapeutic approaches to treat them.

Presenter of 2 Presentations

Conference Calendar

INTEGRATION OF ALZHEIMER'S DISEASE GENETICS, MYELOID CELL GENOMICS AND GENE REGULATORY NETWORKS REVEALS NOVEL DISEASE RISK MECHANISMS

Session Name

GENETICS AND EPIGENETICS OF NEURODEGENERATION

Session Type

SYMPOSIUM

Date

14.03.2021, Sunday

Session Time

12:00 - 14:00

Room

On Demand Symposia C

Lecture Time

12:00 - 12:15

Presenter

Gloriia Novikova, United States of America

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Abstract

Abstract

Aims

We aim to identify myeloid regulatory elements that are enriched in Alzheimer’s disease (AD) risk alleles, identify their target genes and nominate candidate causal variants in disease risk loci. We also want to study the likely downstream effects of AD risk genes and functionally validate these findings in microglia.

Methods

Integration of myeloid epigenomic, chromatin interactions and quantitative trait loci (QTL) datasets as well as a Mendelian Randomization framework were used to link AD enhancers to their target genes. Fine-mapping analyses were used to nominate candidate causal variants and generate the mechanism of action hypotheses. Gene regulatory networks were used to study the regulons of AD risk genes. Knockdown and overexpression studies were utilized to validate these findings.

Results

We found that myeloid active enhancers are enriched in AD risk alleles. We linked these enhancers to their likely target genes, nominating AD risk genes in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants in these loci. In the MS4A locus we identified a candidate functional variant and validated it in microglia and the brain. We highlight the coalescence of candidate causal genes in the myeloid endolysosomal system. We constructed myeloid single-cell gene regulatory networks and found that the predicted targets of SPI1, an AD risk gene, were enriched in the endolysosomal compartment. We validate these findings in Spi1 knockdown and overexpression experiments in microglia.

Conclusions

This study explores the links between AD risk variants, myeloid enhancer activity, gene expression and subsequent network-level dysregulations that likely contribute to AD risk modification.

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