Matthew Oetjens

Senior Researcher, Geisinger Clinic

6 active projects

FH & ASCVD Risk

Familial hypercholesterolemia (FH) is an inherited disorder characterized by lifelong elevated low density lipoprotein cholesterol (LDL-C) and dramatically increased risk for premature atherosclerotic cardiovascular disease (ASCVD). Genetic studies now suggest that familial hypercholesterolemia (FH) encompasses five discrete subtypes based on…

Scientific Questions Being Studied

Familial hypercholesterolemia (FH) is an inherited disorder characterized by lifelong elevated low density lipoprotein cholesterol (LDL-C) and dramatically increased risk for premature atherosclerotic cardiovascular disease (ASCVD). Genetic studies now suggest that familial hypercholesterolemia (FH) encompasses five discrete subtypes based on LDL-c levels, 1) a monogenic FH variant, 2) a high low density lipoprotein cholesterol (LDL-c) polygenic score, 3) elevated lipoprotein(a), 4) elevated LDL-c polygenic score with elevated lipoprotein(a), and 5) a positive family history without an identifiable genetic cause, or true “phenotypic FH.” The primary question of this project is: Are there differences in treatment, comorbidities, and ASCVD outcomes between FH subtypes?

Project Purpose(s)

  • Disease Focused Research (familial hypercholesterolemia)
  • Ancestry

Scientific Approaches

We plan to screen all individuals with whole genome sequences available for monogenic variants in an FH gene. We will calculate an LDL cholesterol polygenic risk score from each participant’s whole genome sequence. Using labs and measurements, we will identify individuals with an FH subtype. Additionally, we will stratify the cohort into statin treated and untreated individuals using medication data. Finally, we will use EH data to determine comorbidities and ASCVD outcomes. We will primarily use regression analyses to compare ASCVD risk in those with each FH subtype to individuals without FH.

Anticipated Findings

We expect ASCVD risk to vary among FH subtypes and to be more pronounced in each of the subtypes, relative to those without FH. We also anticipate ASCVD risk and comorbidities to vary between individuals using lipid-lowering medication and those not using medication. Our findings may demonstrate the importance of considering subtypes in ASCVD risk assessment for patients with the FH phenotype.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Alex Winters - Research Associate, Geisinger Clinic

X and Y Chromosome Intensity

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.

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 Tier

Research Team

Owner:

Sex Chromosome Aneuploidies and Neuropsychiatric Disorders

Some individuals are born with sex chromosome aneuploidies, an extra or loss of an X or Y chromosome. Sex chromosome aneuploidies are known to associate with cognitive impairment, but the full spectrum of brain disorders is not well described. The…

Scientific Questions Being Studied

Some individuals are born with sex chromosome aneuploidies, an extra or loss of an X or Y chromosome. Sex chromosome aneuploidies are known to associate with cognitive impairment, but the full spectrum of brain disorders is not well described. The primary question of this project is “What is the relationship between sex chromosome aneuploidies and neuropsychiatric disorders?”

Project Purpose(s)

  • Disease Focused Research (Sex chromosome aneuploidies)
  • Ancestry

Scientific Approaches

Sex-chromosome aneuploidies will be identified from the array of genotype data. We will screen for sex-chromosome imbalances by identifying outliers in the array intensity values. We will use whole-genome data to orthogonally confirm the presence of a sex-chromosome aneuploidy called from the genotype array data. We plan to use comprehensive EHR data, conditions, drug exposures, lab/measurements, and procedures to create NPD outcomes and exposure variables. We will primarily use regression analyses to compare the rates of NPD in those with a sex chromosome aneuploidy compared to those without a sex chromosome aneuploidy.

Anticipated Findings

We will derive population-based estimates for NPD risk caused by the presence of a sex chromosome aneuploidy. Our findings may demonstrate the importance of considering sex chromosome aneuploidies as a common cause of NPD.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Duplicate of How to Work with Genomics Data (CRAM_Processing and IGV)

This workspace and its notebooks neither ask nor answer any scientific questions. The purpose of this workspace is to serve as a tutorial which shows how to localize the All of Us (AoU) CRAM files individually or in groups via…

Scientific Questions Being Studied

This workspace and its notebooks neither ask nor answer any scientific questions. The purpose of this workspace is to serve as a tutorial which shows how to localize the All of Us (AoU) CRAM files individually or in groups via the CRAM manifest in addition to showing how to render the Integrated Genome Viewer (IGV) on the AoU workbench to explore the CRAM files.

Project Purpose(s)

  • Methods Development

Scientific Approaches

This workspace conducts no study and applies no scientific approaches. This workspace and its notebooks are tutorials for localizing AoU CRAM files with R commands and using IGV to explore their contents. The methods and tools employed include R system commands for localizing individual CRAM files, an R for loop for localizing multiple CRAM files by referencing the manifest, and the commands for importing and rendering IGV to view the localized CRAM files.

Anticipated Findings

There will be no findings or contribution to scientific knowledge as there is no study being conducted nor questions asked. Informal 'findings' include the usability of the aforementioned tools and AoU CRAM files on the All of Us workbench.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Duplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6)

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.

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 Tier

Research Team

Owner:

Duplicate of Phenotype - Test

The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.

Scientific Questions Being Studied

The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Phenotype Library Workspace created by the Researcher Workbench Support team. It is meant to demonstrate the implementation of key phenotype algorithms within the All of Us Research Program cohort.)

Scientific Approaches

Not Applicable

Anticipated Findings

By reading and running the Notebooks in this Phenotype Library Workspace, researchers can implement the following phenotype algorithms:

Ritchie, M., Denny, J., Crawford, D., Ramirez, A., Weiner, J., … Roden, D. (2010). Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record. American Journal of Human Genetics. 87(2):310 doi: 10.1016/j.ajhg.2010.03.003

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

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