Lan Jiang
Vanderbilt University Medical Center
9 active projects
version 7 dup of Genetics and Triglycerides
Scientific Questions Being Studied
Coronary heart disease (CHD) accounts for 1 in 7 deaths in the US and 8.2 million Americans ≥20 years old have CHD. Despite intensive treatment to lower low-density lipoprotein cholesterol (LDL-C), CHD remains the leading cause of death in the US. Plasma triglyceride (TG) levels are a strong predictor for CHD even after LDL-C lowering. The status quo is that most TG-lowering drugs in development focus on the LPL pathway--we need to identify new TG targets in other pathways.
Project Purpose(s)
- Population Health
- Ancestry
Scientific Approaches
We will identify individuals with Triglycerides (TG) measurement and genetic information. We will conduct genetic analyses to identify novel genetic variants associated with TG levels.
Anticipated Findings
We anticipate identifying genetic variations associated with TG levels.
Demographic Categories of Interest
- Race / Ethnicity
- Age
Data Set Used
Controlled TierResearch Team
Owner:
- QiPing Feng - Early Career Tenure-track Researcher, Vanderbilt University Medical Center
- Lan Jiang - Other, Vanderbilt University Medical Center
- Elliot Outland - Project Personnel, Vanderbilt University Medical Center
Collaborators:
- Srushti Gangireddy - Project Personnel, Vanderbilt University Medical Center
- Alyson Dickson - Project Personnel, Vanderbilt University Medical Center
OLD_Genetics and Triglycerides_OLD
Scientific Questions Being Studied
Coronary heart disease (CHD) accounts for 1 in 7 deaths in the US and 8.2 million Americans ≥20 years old have CHD. Despite intensive treatment to lower low-density lipoprotein cholesterol (LDL-C), CHD remains the leading cause of death in the US. Plasma triglyceride (TG) levels are a strong predictor for CHD even after LDL-C lowering. The status quo is that most TG-lowering drugs in development focus on the LPL pathway--we need to identify new TG targets in other pathways.
Project Purpose(s)
- Ancestry
Scientific Approaches
We will identify individuals with Triglycerides (TG) measurement and genetic information. We will conduct genetic analyses to identify novel genetic variants that associated with TG levels.
Anticipated Findings
We anticipate identifying novel genes associated with TGs. These findings will further our understanding of TG regulation and may lead to novel TG-lowering targets.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Registered TierResearch Team
Owner:
- QiPing Feng - Early Career Tenure-track Researcher, Vanderbilt University Medical Center
- Lan Jiang - Other, Vanderbilt University Medical Center
Genetics and Triglycerides
Scientific Questions Being Studied
Coronary heart disease (CHD) accounts for 1 in 7 deaths in the US and 8.2 million Americans ≥20 years old have CHD. Despite intensive treatment to lower low-density lipoprotein cholesterol (LDL-C), CHD remains the leading cause of death in the US. Plasma triglyceride (TG) levels are a strong predictor for CHD even after LDL-C lowering. The status quo is that most TG-lowering drugs in development focus on the LPL pathway--we need to identify new TG targets in other pathways.
Project Purpose(s)
- Population Health
- Ancestry
Scientific Approaches
We will identify individuals with Triglycerides (TG) measurement and genetic information. We will conduct genetic analyses to identify novel genetic variants associated with TG levels.
Anticipated Findings
We anticipate identifying genetic variations associated with TG levels.
Demographic Categories of Interest
- Race / Ethnicity
- Age
Data Set Used
Controlled TierResearch Team
Owner:
- QiPing Feng - Early Career Tenure-track Researcher, Vanderbilt University Medical Center
- Lan Jiang - Other, Vanderbilt University Medical Center
- Elliot Outland - Project Personnel, Vanderbilt University Medical Center
Collaborators:
- Srushti Gangireddy - Project Personnel, Vanderbilt University Medical Center
- Alyson Dickson - Project Personnel, Vanderbilt University Medical Center
Genetics of infections and sepsis
Scientific Questions Being Studied
Sepsis, an outcome of severe infection, is present in 30-50% of hospitalizations that culminate in death and is the single most expensive medical condition, accounting for 13% of total US hospital costs. There is marked inter-individual variability in susceptibility to infection and progression to sepsis and death. Susceptibility to infection is highly heritable, likely due to major selection pressure over millennia when infection was the leading cause of death, and no effective treatments existed. Surprisingly, there is almost no large-scale information about the genetic determinants of 1) severe infection, 2) sepsis, and 3) death from sepsis.
Project Purpose(s)
- Population Health
- Ancestry
Scientific Approaches
We will identify individuals with infection and matched controls without infection. Within the cohort of patients with infection, we will identify those who developed sepsis and who died in the hospital. We will apply genetic approaches to identify the genetic determinants of susceptibility to severe infection, sepsis and its most serious complication, death.
Anticipated Findings
Findings from the proposed study will define the underlying mechanisms of sepsis and may reveal new candidates for early detection, prevention, and treatment of the progression from infection to sepsis and from sepsis to death.
Demographic Categories of Interest
- Race / Ethnicity
- Age
Data Set Used
Controlled TierResearch Team
Owner:
- QiPing Feng - Early Career Tenure-track Researcher, Vanderbilt University Medical Center
- Lan Jiang - Other, Vanderbilt University Medical Center
Duplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6)
Scientific Questions Being Studied
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Project Purpose(s)
- Other Purpose (Demonstrate to the All of Us Researcher Workbench users how to get started with the All of Us genomic data and tools. It includes an overview of all the All of Us genomic data and shows some simple examples on how to use these data.)
Scientific Approaches
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Anticipated Findings
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Lan Jiang - Other, Vanderbilt University Medical Center
- Jun Qian - Other, All of Us Program Operational Use
- Jeffrey Haessler - Project Personnel, Fred Hutchinson Cancer Research Center
- Jennifer Zhang - Project Personnel, All of Us Program Operational Use
- Tabitha Harrison - Graduate Trainee, University of Washington
- Will Dolbeer - Other, All of Us Program Operational Use
Collaborators:
- Henry Condon - Project Personnel, All of Us Program Operational Use
Duplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6) testrun
Scientific Questions Being Studied
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Project Purpose(s)
- Other Purpose (Demonstrate to the All of Us Researcher Workbench users how to get started with the All of Us genomic data and tools. It includes an overview of all the All of Us genomic data and shows some simple examples on how to use these data.)
Scientific Approaches
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Anticipated Findings
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierDuplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6) Sepsis
Scientific Questions Being Studied
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Project Purpose(s)
- Other Purpose (Demonstrate to the All of Us Researcher Workbench users how to get started with the All of Us genomic data and tools. It includes an overview of all the All of Us genomic data and shows some simple examples on how to use these data.)
Scientific Approaches
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Anticipated Findings
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierDuplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6)
Scientific Questions Being Studied
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Project Purpose(s)
- Other Purpose (Demonstrate to the All of Us Researcher Workbench users how to get started with the All of Us genomic data and tools. It includes an overview of all the All of Us genomic data and shows some simple examples on how to use these data.)
Scientific Approaches
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Anticipated Findings
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierDuplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6)
Scientific Questions Being Studied
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Project Purpose(s)
- Other Purpose (Demonstrate to the All of Us Researcher Workbench users how to get started with the All of Us genomic data and tools. It includes an overview of all the All of Us genomic data and shows some simple examples on how to use these data.)
Scientific Approaches
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Anticipated Findings
Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierRequest a Review of this Research Project
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