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Principal Investigator: Daniel Levy
Organization: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
Fiscal Year: 2022
Award: $2,703,246
Funding agency: National Heart Lung and Blood Institute
As part of the Population Sciences Branch (PSB), the Levy Lab conducts genetic and multidimensional omics research focused on cardiovascular disease (CVD) and its risk factors. Two important areas of the Levy Lab's intramural research are:
1) blood pressure (BP) genetics
2) multidimensional omics of BP and CVD
The Levy Lab leverages the genotype and phenotype resources of the Framingham Heart Study (FHS) as well as NIH intramural resources including NHLBI's DNA Sequencing and Genomics Core Laboratory, CIT's Mathematical and Statistical Computing Laboratory, and NCBI's Computational Biology and Informational Engineering Branches.
Goals for the PSB and Levy Lab:
Goal 1: Identify genetic contributions to BP. Hypertension affects 80 million adults in the U.S. and it is a major contributor to multiple forms of CVD including coronary heart disease (CHD), stroke, and heart failure. Dr. Levy's research in hypertension focuses on cross-cutting studies of its genetic, transcriptomic, and epigenetic underpinnings. To advance research in the area of BP genetics, Dr. Levy leads or co-leads several large BP consortium working groups. The results of Dr. Levy's research provide clues to novel genes and pathways involved in BP regulation and highlight potential therapeutic targets for the treatment of hypertension and the prevention of its sequelae.
Goal 2: Apply multidimensional omics to identify biomarker signatures of BP and CVD related conditions. Identifying novel CVD biomarkers has important implications for understanding disease biology and developing targeted prevention strategies in the preclinical phase of CVD when intervention is most likely to be effective. Discovering highly predictive biomarkers of CVD risk could represent a breakthrough for risk stratification if this approach improves upon current risk assessment methods.
Most recently PSB initiated four new research programs:
1. Inflammatory biomarker research
2. Conduct state of the art RNA Sequencing in over 1300 Framingham participants (in conjunction with NHLBI's TOPMed Program)
3. Molecular mechanisms of susceptibility to severe COVID infection
4. Proteomics programs: Protein biomarkers of chronic lung disease
1. Rage/sRage Axis:
Low plasma sRAGE levels have been observed in asthmatic patients relative to healthy controls. Lower levels of sRAGE have been observed in the bronchoalveolar lavage fluid of asthma-induced mice compared to healthy controls. New research from Dr. Levy's lab reveals a causal role of the AGER-mRAGE-sRAGE axis in asthma and chronic lung disease in humans and suggests a strategy for targeting this pathway as a means to prevent or treat asthma and smoking-related lung inflammation.
The experimental treatment that we are testing reduces levels of mRAGE and increases expression of sRAGE. We posit that this strategy will have the dual effect of increasing the anti-inflammatory properties and reducing the pro-inflammatory properties of the RAGE proteins.
For the purposes of establishing a murine model, we have selected to separate our sample size into three separate treatment arms:
A) Mice treated with intervention, then sensitized and challenged with allergen
Treatment+ // OVA +
B) Mice treated with placebo, then sensitized and challenged with allergen
Treatment - // OVA +
C) Mice not treated, then sensitized and challenged with phosphate buffered saline
Treatment - // OVA -
2. RNA Sequencing
The primary aim RNA Seq will be the identification of expression quantitative trait loci (eQTLs) genome wide via the alignment of whole genome DNA seq and RNA seq. This approach will also permit the assessment of allele specific expression genome wide and alternative splicing QTLs (sQTLs) genome wide. These data are ready for analysis by TOPMed investigators through the dbGaP data exchange portal and by PSB staff utilizing a cloud computing structure.
3. COVID-19 Efforts (SARS-CoV-2)
We used our derived eQTL resources in conjunction with genetic variants from prior published genome-wide association studies (GWAS) in causal inference testing to identify putatively causal genes for COVID-19 severity. This approach identified two genes, OAS1 and IFNAR2 with putatively causal relations to COVID-19 severity.
OAS1 has been identified as a risk locus for COVID-19 severity. A recent study identified an alternative splicing variant, rs10774671, at exon 7 of OAS1 for which the G allele leads to a prenylated protein that is more protective against severe COVID. In Mendelian randomization analysis, we confirmed that OAS1 splice variation is causal for COVID-19 severity. Plots of
expression of three transcripts of OAS1 reveal trimodal distributions that are linked to the three
genotypes of rs10774671. With increasing dose of the minor G allele, there is increased
fractional expression of the protective isoform (Transcript 1) and decreased fractional expression of the other isoforms. Thus, our findings help interpret GWAS findings that implicate OAS1 in COVID-19 severity.
IFNAR2 encodes a type II cytokine receptor family protein. A targeted resequencing study
reported that IFNAR2 plays an essential role in human antiviral immunity. A recent study
showed that loss-of-function mutations in IFNAR2 are associated with severe COVID-19.
We demonstrate that our eQTL resource provides biologically plausible evidence linking
IFNAR2 expression to COVID-19 severity.
4. Proteomics Programs
PSB has embarked on a proteomics study to identity biomarkers of chronic obstructive lung disease (COPD). COPD was the seventh leading cause of early death globally in a 2017 study of global burdens of disease, rising in the ranks from the eleventh cause of early death in 1990. Due to an aging population and prolonged exposure to environmental risk factors, global COPD prevalence is projected to increase in the next decade.
Given the lack of clinically useful COPD biomarkers and the scarcity of population-based studies, identifying predictive COPD biomarkers would help discern high-risk individuals who may benefit from early preventive therapies. Furthermore, biomarkers of COPD progression may provide insights into causal mechanisms for the disease and provide insight into new therapies
Purpose/Aims
1. Identify proteomic biomarkers of prevalent COPD (using GOLD Stage 2 criteria).
2. Identify proteomic biomarkers of prevalent restrictive lung disease.
3. Identify proteomic biomarkers of continuous measures of lung function.
In the past year, PSB has made several recent advances in analysis of multidimensional omics data including: discovery and targeted proteomics of CHD, transcriptomic and systems biology analyses of BP and CHD, DNA methylation signatures of BP, and integrative genomic approaches to identify mechanisms underlying CVD traits
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