Patrick Allaire

Research Associate, Marshfield Clinic Research Institute

7 active projects

PheRS-WAS of TL-GRS and PheRS - CDRv9may2023

Main question: "Does telomere length (TL) genetics associates phenotypes explaining Mendelian disease syndrome (MDS)?" Secondary questions: 1. What are the TL variants and MDS phenotypes driving the associations? 2. Do pathogenic variants leading to telomeropathies associate with MDS. 3. Do…

Scientific Questions Being Studied

Main question: "Does telomere length (TL) genetics associates phenotypes explaining Mendelian disease syndrome (MDS)?"
Secondary questions:
1. What are the TL variants and MDS phenotypes driving the associations?
2. Do pathogenic variants leading to telomeropathies associate with MDS.
3. Do pathogenic variants driving MDS associate with TL genetics or TL phenotypes?
4. Are the associations clinically useful?

Project Purpose(s)

  • Disease Focused Research (cancers and telomerapathies)
  • Methods Development
  • Control Set
  • Ancestry
  • Other Purpose (The purpose of this study is to determine if there are any correlation between Mendelian disease syndromes (define as combination of phenotypes describing the diseases) and genetics of telomere length (defines as individual variants or combination of variants).)

Scientific Approaches

Dataset: All participants with genetic and phenotypic data.
Methods:
1.For each participant, we will first construct a polygenic risk (GRS) score for telomere length and phenotype risk score (PheRS) for each disease syndrome. A PheRS derived from our own phenome-wide association study (PheWAS) of telomere length data will also be established.
2.A linear regression will test whether a correlation exist between GRS and individual PheRS.
3.For significant associations, the individual elements constructing the score will be tested individually in a linear regression to determine which ones are driving the associations.
4.Pathogenic variants leading to disease syndrome will be tested in a linear model for correlation with PheRS of disease syndromes and telomere length.
5.To determine clinical significance of association we will conduct various risk modelling techniques including risk acceptance, risk transference, risk avoidance, risk reduction.
Tools: Jupyter with user R scripts.

Anticipated Findings

We have preliminary data associating genetically determined TL with phenotypes of several cancers defined as Mendelian disease syndromes (MDS). We expect to reproduce this data. After this, the project is mostly exploratory. We will establish how MDS phenotypes and genetics interact with telomere length (TL) genetics and phenotypes. Additionally, we will determine if the correlation have clinical utility. The data will add knowledge on how genetics of TL correlates with phenotypes of MDS, and whether we can use TL genetics to assess to survey risk of Mandelian disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute

Collaborators:

  • John Mayer - Project Personnel, Marshfield Clinic Research Institute
  • Rachel Gabor - Project Personnel, Marshfield Clinic Research Institute

WGS_TLtyping_machine1

The main objective is to measure telomere length through whole genome sequence data utilizing CRAM files. Additionally, the goal is to confirm the obtained telomere length by conducting GWAS and PheWAS analyses to determine if they can replicate previous findings…

Scientific Questions Being Studied

The main objective is to measure telomere length through whole genome sequence data utilizing CRAM files. Additionally, the goal is to confirm the obtained telomere length by conducting GWAS and PheWAS analyses to determine if they can replicate previous findings from GWAS and PheWAS studies on telomere length.

Project Purpose(s)

  • Methods Development
  • Ancestry

Scientific Approaches

The project aims to measure telomere length using whole genome sequencing data. Several Python and Java packages are available for this purpose, which utilize whole genome sequencing data. We will utilize these packages along with the All of Us cram files to estimate telomere length.

Anticipated Findings

The expected findings from this study include:
1. Telomere length measurement for each individual with available whole genome sequencing data.
2. Identification of known genetic variants associated with telomere length, as well as the possibility of discovering new variants.
3. Identification of reported and potentially new phenotypes associated with telomere length.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute

Collaborators:

  • John Mayer - Project Personnel, Marshfield Clinic Research Institute
  • Rachel Gabor - Project Personnel, Marshfield Clinic Research Institute

April10th2024_PheRSWAS_pTL_gTL

Main question: "Does telomere length (TL) genetics associates phenotypes explaining Mendelian disease syndrome (MDS)?" Secondary questions: 1. What are the TL variants and MDS phenotypes driving the associations? 2. Do pathogenic variants leading to telomeropathies associate with MDS. 3. Do…

Scientific Questions Being Studied

Main question: "Does telomere length (TL) genetics associates phenotypes explaining Mendelian disease syndrome (MDS)?"
Secondary questions:
1. What are the TL variants and MDS phenotypes driving the associations?
2. Do pathogenic variants leading to telomeropathies associate with MDS.
3. Do pathogenic variants driving MDS associate with TL genetics or TL phenotypes?
4. Are the associations clinically useful?

Project Purpose(s)

  • Disease Focused Research (cancers and telomerapathies)
  • Methods Development
  • Control Set
  • Ancestry
  • Other Purpose (The purpose of this study is to determine if there are any correlation between Mendelian disease syndromes (define as combination of phenotypes describing the diseases) and genetics of telomere length (defines as individual variants or combination of variants).)

Scientific Approaches

Dataset: All participants with genetic and phenotypic data.
Methods:
1.For each participant, we will first construct a polygenic risk (GRS) score for telomere length and phenotype risk score (PheRS) for each disease syndrome. A PheRS derived from our own phenome-wide association study (PheWAS) of telomere length data will also be established.
2.A linear regression will test whether a correlation exist between GRS and individual PheRS.
3.For significant associations, the individual elements constructing the score will be tested individually in a linear regression to determine which ones are driving the associations.
4.Pathogenic variants leading to disease syndrome will be tested in a linear model for correlation with PheRS of disease syndromes and telomere length.
5.To determine clinical significance of association we will conduct various risk modelling techniques including risk acceptance, risk transference, risk avoidance, risk reduction.
Tools: Jupyter with user R scripts.

Anticipated Findings

We have preliminary data associating genetically determined TL with phenotypes of several cancers defined as Mendelian disease syndromes (MDS). We expect to reproduce this data. After this, the project is mostly exploratory. We will establish how MDS phenotypes and genetics interact with telomere length (TL) genetics and phenotypes. Additionally, we will determine if the correlation have clinical utility. The data will add knowledge on how genetics of TL correlates with phenotypes of MDS, and whether we can use TL genetics to assess to survey risk of Mandelian disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute

Collaborators:

  • John Mayer - Project Personnel, Marshfield Clinic Research Institute
  • Rachel Gabor - Project Personnel, Marshfield Clinic Research Institute

SGLT2

The objective of this research is to identify genetic coding variants within the SGLT2 gene that are associated with renal glycosuria. Previous studies have shown that mutations within this gene can lead to renal glycosuria. Medications targeting SGLT2 have been…

Scientific Questions Being Studied

The objective of this research is to identify genetic coding variants within the SGLT2 gene that are associated with renal glycosuria. Previous studies have shown that mutations within this gene can lead to renal glycosuria. Medications targeting SGLT2 have been developed, demonstrating benefits for the management of conditions such as diabetes and obesity. We intend to identify individuals from a local population who harbor mutations associated with renal glycosuria, and investigate their response to SGLT2 inhibitors through a prospective pharmacogenetic clinical study.

Project Purpose(s)

  • Disease Focused Research (renal glycosuria)
  • Ancestry

Scientific Approaches

The scientific methodology primarily involves scanning the SGLT2 gene for variants associated with renal glycosuria. The dataset will encompass all participants who have undergone whole genome sequencing. We will employ a logistic regression model to evaluate the associations between genetic variants and International Classification of Diseases (ICD) codes for renal glycosuria. Data analysis will be conducted in Jupyter notebooks using R programming language.

Anticipated Findings

We anticipate not only the re-identification of known coding variants associated with renal glycosuria, but also the discovery of novel variants that could have significant implications for the fields of diabetes and obesity.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute

WGS_TLtyping_machine2

The main objective is to measure telomere length through whole genome sequence data utilizing CRAM files. Additionally, the goal is to confirm the obtained telomere length by conducting GWAS and PheWAS analyses to determine if they can replicate previous findings…

Scientific Questions Being Studied

The main objective is to measure telomere length through whole genome sequence data utilizing CRAM files. Additionally, the goal is to confirm the obtained telomere length by conducting GWAS and PheWAS analyses to determine if they can replicate previous findings from GWAS and PheWAS studies on telomere length.

Project Purpose(s)

  • Methods Development
  • Ancestry

Scientific Approaches

The project aims to measure telomere length using whole genome sequencing data. Several Python and Java packages are available for this purpose, which utilize whole genome sequencing data. We will utilize these packages along with the All of Us cram files to estimate telomere length.

Anticipated Findings

The expected findings from this study include:
1. Telomere length measurement for each individual with available whole genome sequencing data.
2. Identification of known genetic variants associated with telomere length, as well as the possibility of discovering new variants.
3. Identification of reported and potentially new phenotypes associated with telomere length.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute

Collaborators:

  • John Mayer - Project Personnel, Marshfield Clinic Research Institute
  • Rachel Gabor - Project Personnel, Marshfield Clinic Research Institute

Staph_Infection_PheWAS_may2023_V7

The primary objective of this study is to identify the phenotypes associated with Staphylococcus aureus infection by utilizing the Phenome-Wide Association Study (PheWAS) approach. The outcomes will be juxtaposed with those derived from both the Marshfield Clinic Medical System and…

Scientific Questions Being Studied

The primary objective of this study is to identify the phenotypes associated with Staphylococcus aureus infection by utilizing the Phenome-Wide Association Study (PheWAS) approach. The outcomes will be juxtaposed with those derived from both the Marshfield Clinic Medical System and the TriNetX cohorts. Understanding the comprehensive range of conditions that make an individual susceptible to infection, and taking possible preventive measures, is of utmost importance. Furthermore, it's crucial to comprehend the entire array of conditions resulting from such infections and take potential necessary actions.

The secondary goal is to discover genetic variants that may predispose an individual to a Staphylococcus aureus infection.

Collectively, these findings will steer further research into investigating the impacts of these associations on clinical care.

Project Purpose(s)

  • Disease Focused Research (staphylococcus aureus)
  • Control Set
  • Ancestry

Scientific Approaches

Our study will primarily employ two methodologies: a Phenome-Wide Association Study (PheWAS) and a Genome-Wide Association Study (GWAS). The data set for our investigation will be comprised of a refined All of Us (AoU) cohort, specifically tailored for studying Staphylococcus aureus infection. This will include comprehensive Electronic Health Records (EHR) spanning a minimum of five years to ensure that the disease patterns can be adequately captured and correlated with other phenotypes or genetic attributes. As the project evolves, we may introduce additional filters to refine our dataset.

Anticipated Findings

This project adopts an exploratory approach. Our aim is to compile a comprehensive catalog of significant phenotype and genetic variants related to Staphylococcus aureus infection that also display consistent correlations across our other cohorts.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute

WGS_TLtyping_machine3

The main objective is to measure telomere length through whole genome sequence data utilizing CRAM files. Additionally, the goal is to confirm the obtained telomere length by conducting GWAS and PheWAS analyses to determine if they can replicate previous findings…

Scientific Questions Being Studied

The main objective is to measure telomere length through whole genome sequence data utilizing CRAM files. Additionally, the goal is to confirm the obtained telomere length by conducting GWAS and PheWAS analyses to determine if they can replicate previous findings from GWAS and PheWAS studies on telomere length.

Project Purpose(s)

  • Methods Development
  • Ancestry

Scientific Approaches

The project aims to measure telomere length using whole genome sequencing data. Several Python and Java packages are available for this purpose, which utilize whole genome sequencing data. We will utilize these packages along with the All of Us cram files to estimate telomere length.

Anticipated Findings

The expected findings from this study include:
1. Telomere length measurement for each individual with available whole genome sequencing data.
2. Identification of known genetic variants associated with telomere length, as well as the possibility of discovering new variants.
3. Identification of reported and potentially new phenotypes associated with telomere length.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Patrick Allaire - Research Associate, Marshfield Clinic Research Institute
  • John Mayer - Project Personnel, Marshfield Clinic Research Institute
  • Rachel Gabor - Project Personnel, Marshfield Clinic Research Institute
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