Kiana Martinez

Research Fellow, University of Arizona

5 active projects

ABO PheWAS

Research questions: 1) Can our novel ABO blood typing algorithm using genetic data be used effectively to extensively type ABO subtypes from whole genome sequencing and array data in a diverse cohort? 2) Will a SNP approach for ABO blood…

Scientific Questions Being Studied

Research questions:

1) Can our novel ABO blood typing algorithm using genetic data be used effectively to extensively type ABO subtypes from whole genome sequencing and array data in a diverse cohort?
2) Will a SNP approach for ABO blood typing be concordant with available serotype?
3) What disease association ABO blood types can be replicated using the AllofUs dataset?
4) What novel disease associations, if any, with ABO blood types can be identified in a diverse cohort?

Relevance: Genomic variation in RBC and antigens is associated with a myriad of conditions. The ABO locus alone is associated with many conditions including venous thromboembolism (VTE), pancreatic cancer, malaria, and COVID-19. Furthermore, it is not common practice to extensively type beyond the traditional ABO blood groups, and the studies that do so are primarily done in individuals of European ancestry. Thus, we seek to do the first PheWAS on extensively typed RBC antigens and to do so in a diverse cohort.

Project Purpose(s)

  • Disease Focused Research (red blood cell (RBC) antigen-associated diseases)

Scientific Approaches

We plan to employ a blood typing algorithm to extensively type RBC antigens from 1) whole genome sequencing and 2) array data in the AllofUs cohort, and compare the two outcomes. Then, we plan to employ the phenome-wide association study (PheWAS) approach to identify associations between RBC antigen types and other clinical phenotypes. PheWAS will be carried out using multivariable linear regression and logistic regressions with ABO blood groups with our novel ABO blood type. For example, in the case of the ABO blood group, ABO blood subtypes (A101, A102, Aw01, B101, etc.) will act as the independent variable and phenotypes, derived from participant provided information (PPI) electronic health records (EHR), as the dependent variable. Initial models will include adjustments for age, gender, and race/ethnicity. Differential associations by race/ethnicity, gender, and sex will also be evaluated.

Anticipated Findings

This proposed project aims to test our novel ABO blood typing algorithm on WGS and array data in the diverse AllofUs cohort. We also aim to replicate known RBC-disease associations as well as identify any novels ones that may be identified within a diverse cohort.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Juvief Farol - Graduate Trainee, University of Arizona

Heparin-induced Thrombocytopenia (HIT) GWAS

Research questions: Can we identify novel genomic associations with heparin-induced thrombocytopenia (HIT). Relevance: Heparin is a widely used anticoagulant that carries the risk of an antibody-mediated adverse drug reaction referred to as heparin-induced thrombocytopenia (HIT). A subset of heparin-treated patients…

Scientific Questions Being Studied

Research questions: Can we identify novel genomic associations with heparin-induced thrombocytopenia (HIT).
Relevance: Heparin is a widely used anticoagulant that carries the risk of an antibody-mediated adverse drug reaction referred to as heparin-induced thrombocytopenia (HIT). A subset of heparin-treated patients produces detectable levels of antibodies against complexes of heparin bound to circulating platelet factor 4 (PF4). We aim to identify genetic variants associated with HIT using a genome-wise association study (GWAS) approach.

Project Purpose(s)

  • Disease Focused Research (heparin-induced thrombocytopenia)

Scientific Approaches

We plan to identify a HIT-positive cohort as well as a healthy control group that have genotype data available to perform a GWAS using PLINK. Our primary GWAS will feature a logistic regression of HIT status. Regression models will be adjusted for age, sex, and principal components 1 to 3.

Anticipated Findings

This proposed project aims to replicate known associations between genetic variants and HIT as well as identify any novels ones that may be identified within a diverse cohort.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Kiana Martinez - Research Fellow, University of Arizona
  • Jason Karnes - Early Career Tenure-track Researcher, University of Arizona

Collaborators:

  • Juvief Farol - Graduate Trainee, University of Arizona

ABO PheWAS - Registered Tier

What novel disease associations, if any, with RBC and antigen types can be identified in a diverse cohort? Relevance: Approximately fifteen percent of documented transfusion-related fatalities are the result of hemolytic transfusion reactions due to blood group antibodies. Sensitization to…

Scientific Questions Being Studied

What novel disease associations, if any, with RBC and antigen types can be identified in a diverse cohort?
Relevance: Approximately fifteen percent of documented transfusion-related fatalities are the result of hemolytic transfusion reactions due to blood group antibodies. Sensitization to RBC antigens can also result in a risk for delayed or acute hemolytic transfusion reactions, for fetal anemia, and complications in pregnancy. In addition, genomic variation in RBC and PLT antigens is associated with a myriad of conditions. The ABO locus alone is associated with many conditions including venous thromboembolism (VTE), pancreatic cancer, malaria, and COVID-19. Furthermore, it is not common practice to extensively type beyond the traditional ABO and RhD blood groups, and the studies that do so are primarily done in individuals of European ancestry. Thus, we seek to do the first PheWAS on extensively typed RBC and PLT antigens and to do so in a diverse cohort.

Project Purpose(s)

  • Disease Focused Research (red blood cell (RBC) antigen-associated diseases)

Scientific Approaches

We plan to employ the phenome-wide association study (PheWAS) approach to identify associations between RBC and PLT antigen types and other clinical phenotypes. Separate PheWAS will be carried out using multivariable linear regression and logistic regressions with each blood and platelet group (ABO, RH, MNS, GPIV, etc.) that can be automatically typed by bloodTyper and is described in BloodAntigens.com. For example, in the case of the ABO blood group, ABO blood subtypes (A101, A102, Aw01, B101, etc.) will act as the independent variable and phenotypes, derived from participant provided information (PPI) electronic health records (EHR), as the dependent variable. Initial models will include adjustments for age, gender, race/ethnicity, BMI, and smoking status. We will also carry out sex-specific analyses (reported sex at birth: male or female) and race/ethnicity-specific analyses (self-reported race/ethnicity: White, Black, Hispanic, and Asian).

Anticipated Findings

We also aim to replicate known RBC-disease associations as well as identify any novels ones that may be identified within a diverse cohort.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

HLA PheWAS

Research questions: 1) What disease associations with HLA can be replicated using the AllofUs dataset? 2) What novel disease associations with HLA can be identified using the AllofUs dataset? Relevance: The human leukocyte antigen (HLA) system is the most polymorphic…

Scientific Questions Being Studied

Research questions:

1) What disease associations with HLA can be replicated using the AllofUs dataset?
2) What novel disease associations with HLA can be identified using the AllofUs dataset?

Relevance: The human leukocyte antigen (HLA) system is the most polymorphic in the human genome that has been associated with protection and predisposition to a broad array of infectious, autoimmune, and malignant diseases. Further research needs to be done in diverse populations to identify the full scope of phenotypes potentially associated with the HLA system.

Project Purpose(s)

  • Disease Focused Research (HLA-associated diseases)
  • Methods Development

Scientific Approaches

Prior to PheWAS analyses, HLA alleles will be imputed for each participant with whole-genome sequencing (WGS) data using a novel approach referencing the IPD-IMGT/HLA Database which defines the official HLA sequences named by the WHO Nomenclature Committee for Factors of the HLA System. Demographic characteristics will be acquired for the study population and summary statistics related to HLA-relevant variables will also be performed.

Primary statistical analyses will be carried out using multivariable linear regression HLA alleles as the independent variable and individual phecodes as dependent variables. Initial models will include adjustment for age, gender, and select variables from participant provided information (PPI). Differential associations by race/ethnicity, gender, and sex will also be evaluated.

Anticipated Findings

Our project expects to successfully generate HLA alleles for all AllofUs participants with available WGS data. We then expect to validate past phenotypic associations with HLA alleles as well as discover novel ones as this work will be performed in a diverse cohort.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Estimating Local Ancestry in the AllofUs Cohort to be Utilized in GWAS

Research questions: 1) Is there a correlation between global and local ancestry in pharmacogenomic (PGx) variants? 2) What novel PGx variants, if any, with pharmacogenomic traits can be identified in a diverse cohort using a GWAS approach and adjusting for…

Scientific Questions Being Studied

Research questions:

1) Is there a correlation between global and local ancestry in pharmacogenomic (PGx) variants?
2) What novel PGx variants, if any, with pharmacogenomic traits can be identified in a diverse cohort using a GWAS approach and adjusting for local ancestry?

Relevance: While some studies have moved beyond race-based research in relation to pharmacogenomic (PGx) traits and have instead considered global ancestry, such studies rarely consider the influence of local ancestry (LA). Adding LA estimates into association analyses will provide a more comprehensive and inclusive approach to adjusting for population stratification and allow for research to better utilize diverse and admixed cohorts. Thus, we seek to focus our efforts on identifying novel PGx variants in relation to pharmacogenomic traits in a diverse cohort that includes admixed populations by incorporating local ancestry into association analyses in an effort to reduce adverse pharmacogenomic outcomes.

Project Purpose(s)

  • Disease Focused Research (pharmacogenomic-associated diseases)

Scientific Approaches

We plan to generate LA estimates, using RFMix with different iterations of K, per chromosome in the AllofUs cohort with available whole-genome sequencing (WGS) data. Appropriate reference populations will be informed from global ancestry estimates and retrieved from merged 1000 Genomes and Human Genome Diversity Project (HGDP) datasets. LA, which can be represented as the number of inherited alleles (0, 1, or 2) from each ancestral population at a particular locus, will be defined in a gene-specific manner, plus and minus 5000 base pairs to capture relevant regulatory regions. Since transitions may occur within genes, gene-based LA will also be calculated as a within-gene proportion of ancestry per individual. The LA at each clinically relevant pharmacogene will be represented as a percentage using descriptive statistics. Then, we plan to perform a GWAS analysis on pharmacogenomic traits of interest.

Anticipated Findings

Given our sample size, we expect to be able to confirm or deny the presence of correlation between LA, global ancestry, and PGx variant carriage. We expect that these approaches will be applicable to a broad range of PGx phenotypes, providing a proof of concept for the use of LA in PGx studies of admixed and diverse populations. We also expect to identify novel variants associated with drug safety and efficacy. These variants will most likely be more prevalent in admixed individuals and thus will partly address racial disparities in pharmacogenomics.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

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