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Research

A key challenge in precision medicine is understanding the drivers of inter-individual variability, and how they mediate variability in disease risk and outcomes. The goal is to enable personalized risk assessments and treatment strategies to enhance patient outcomes and minimize unnecessary interventions. This is particularly challenging for common non-communicable diseases (NCDs) and complex traits, which are polygenic, influenced by multiple environmental factors and pose the greatest healthcare burden on the society. My research work has been motivated towards the advancement of precision genomic medicine using integrative genomics strategies broadly covering four areas:

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  1. The role of polygenic risk score-by-environmental interactions on disease risk and prevalence of NCDs.

  2. The ability of integrative genomic approaches, namely integrating gene expression profile with genetics in disease risk progression.

  3. The role of monogenic vs polygenic risk on rare disease risk.

  4. The role of ancestry-specific genetic effects on the estimation of disease risk.

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1. Role of polygenic risk score-by-environmental interactions (PRSxE) on common disease risk

Polygenic risk scores (PRSs) offer a significant value in risk stratification rather than overall prediction or diagnosis. Thus, PRS-based approaches may offer clinical utility in screening strategies, which when integrated with environmental and clinical risk factors enhance the ability to identify individuals on whom preventative interventions would be most impactful. My work has demonstrated pervasive evidence of PRSxE interactions influencing common diseases underscoring their relevance, context-dependency of PRSs and the utility of these approaches. 

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Publications:

  • Nagpal S and Gibson G. Pervasive Interactions between Exposures and Polygenic Risk can Inform more Effective Clinical and Behavioral Intervention (Manuscript submitted). 

  • Nagpal S, Tandon R, Gibson G. Canalization of the polygenic risk of common diseases and traits in the UK Biobank. Molecular Biology and Evolution (2022).

  • Nagpal S, Gibson G, Marigorta UM. Pervasive modulation of obesity risk by the environment and genomic background. Genes (2018).

  • Astore C, Nagpal S, Gibson G. Mendelian randomization indicates a causal role for omega-3 fatty acids in inflammatory bowel disease. International Journal of Molecular Sciences (2022).

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2. Ability of integrative genomic approaches for predicting disease progression.  

An important goal of clinical genomics is to be able to understand the underlying drivers of this inter-individual variability by predicting the risk of adverse outcomes and tailoring interventions accordingly. Polygenic risk scores utilizing findings from GWAS are useful in prediction of disease onset but are unable to provide meaningful predictions of adverse outcomes. Integrative genomics enables the integration of genetics with dynamic variables such as transcriptomics, which helps to unravel the complexity of common disease. 

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Publications:

  • Gettler K, Nagpal S, Washburn S, et al. Post-operative ileum transcriptomics implicates sex-biased mechanisms of Crohn's disease recurrence. Gastroenterology (2025).

  • Mo A*, Nagpal S*, Gettler K, et al. Stratification of risk of progression to colectomy in ulcerative colitis via measured and predicted gene expression. American Journal of Human Genetics (2021). 

  • Nagpal S*, Meng X*, Epstein MP, et al. TIGAR: An improved Bayesian tool for transcriptomic data imputation enhances gene mapping of complex traits. American Journal of Human Genetics (2019).

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3. Role of monogenic vs polygenic risk on rare disease risk

PRSs can identify subgroups of individuals with disease risk considered equivalent to monogenic mutations. A small subset of the population carries pathogenic or likely pathogenic variants of both common and rare diseases which are associated with several fold increased risk. However, there is large clinical variability among affected individuals due to incomplete penetrance and variable expressivity. A key question is how monogenic and polygenic risk interact i.e. to what extent can disease risk caused by a rare pathogenic variant be modulated by the polygenic background and vice versa? There is increasing evidence that polygenic background modulates the risk of monogenic variants for both common and rare disease leading to differential expressivity. Thus, disentangling the rare vs common variant contribution on a disease has implications on both understanding the disease physiology and therapeutic interventions. 

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Publications:

Nagpal S, Hooshmand K, et al. A genome-wide association study implicates the glutamate signaling pathway in sarcoma susceptibility. (Manuscript submitted). 

4. Role of ancestry-specific genetic effects on the estimation of disease risk

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Since genomic studies are largely European-biased, the risk predictors are not translatable to individuals of non-European and mixed-ancestries leading to exacerbation of health disparities. As we move towards the era of precision medicine, it is highly important to include understudied populations in genomic analyses to ensure equitable benefit of these advancements across ancestries. The prevalence of diseases, their progression as well outcomes vary across populations. Thus it is important to study the differential genetic architecture of diseases across populations and develop ancestry-informed risk assessment tools. 

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Publications:

  • Somenini H, Nagpal S, Venkatesqaran S, et al. Whole-genome sequencing of African Americans implicates differential genetic architecture in inflammatory bowel disease. American Journal of Human Genetics (2021).

  • Astore C, Sharma S, Nagpal S, IBD Genetics Consortium, et al. The role of admixture in rare variant contributions to inflammatory bowel disease. Genome Medicine (2023).

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