Research Projects Directory

Sickle Cell Disease and Chronic Conditions

The primary scientific question driving this exploration is: How do chronic conditions impact the clinical outcomes, healthcare utilization, and quality of life among patients with sickle cell disease? To address this overarching question, several sub-questions can be formulated: Epidemiological Patterns,…

Scientific Questions Being Studied

The primary scientific question driving this exploration is: How do chronic conditions impact the clinical outcomes, healthcare utilization, and quality of life among patients with sickle cell disease?

To address this overarching question, several sub-questions can be formulated: Epidemiological Patterns, Clinical Outcomes, Healthcare Utilization, Quality of Life, Intervention Strategies. Exploring the data on sickle cell disease and chronic conditions is a critical step towards improving the care and outcomes of SCD patients. By addressing the complex interactions between SCD and chronic conditions, this research aims to provide a comprehensive understanding that informs clinical practice, policy, and personalized medicine. The ultimate goal is to enhance the quality of life and clinical outcomes for SCD patients, ensuring equitable and effective care for this vulnerable population.

Project Purpose(s)

Disease Focused Research (Sickle Cell Disease)
Population Health
Social / Behavioral
Drug Development
Methods Development
Control Set
Ancestry
Ethical, Legal, and Social Implications (ELSI)

Scientific Approaches

For my study on sickle cell disease (SCD) and chronic conditions, I will leverage the available datasets. My scientific approaches include:

Datasets: Utilizing electronic health records (EHRs), genomic data, and patient-reported outcomes (PROs) available in the All of Us database to analyze SCD patients with chronic conditions.

Research Methods:

Descriptive statistics to determine prevalence and incidence rates.
Multivariate regression to evaluate the impact of chronic conditions on SCD outcomes.
Genome-wide association studies (GWAS) to identify genetic markers.
Cost-analysis models for healthcare utilization.
Tools:

Bioinformatics tools for genomic data analysis.
Statistical software (R) for data analysis.
These methods will provide insight to the interactions between SCD and chronic conditions, improving patient care and outcomes.

Anticipated Findings

The anticipated findings include identifying the most prevalent chronic conditions among SCD patients, understanding how these conditions exacerbate SCD complications, and uncovering genetic markers associated with increased susceptibility. We expect to find specific chronic conditions that significantly worsen clinical outcomes and patterns in healthcare utilization linked to these conditions.

These findings will contribute to the body of scientific knowledge by:

Providing a comprehensive epidemiological profile of chronic conditions in SCD patients.
Enhancing the understanding of genetic factors influencing SCD and chronic conditions.
Informing the development of targeted, personalized treatment plans.
Guiding healthcare policies to improve resource allocation and patient care.
Ultimately, this study aims to improve the quality of life and clinical outcomes for SCD patients by addressing both SCD and co-occurring chronic conditions comprehensively.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Keesha Roach - Early Career Tenure-track Researcher, University of Tennessee Health Science Center, Memphis
Kosaku Aoyagi - Early Career Tenure-track Researcher, University of Texas at El Paso

Collaborators:

Xueyuan Cao - Mid-career Tenured Researcher, University of Tennessee Health Science Center, Memphis

Representative Phenotype Discovery Methods

We are developing AI methods to support discovery of phenotype to genotype associations in the context of rare disease. The methods are intended to support a gene-to-patient [Seaby 2020] paradigm in which the starting point is identification of an in-silico…

Scientific Questions Being Studied

We are developing AI methods to support discovery of phenotype to genotype associations in the context of rare disease. The methods are intended to support a gene-to-patient [Seaby 2020] paradigm in which the starting point is identification of an in-silico predicted pathogenic variant(s). From there, one identifies a cohort of individuals with the predicted pathogenic variants to determine if they share a common phenotype that may be associated. In this project, we seek to validate the performance of methods we're developing to automate the analysis of individuals in the cohort to identify a representative phenotype. The planned validation process will include the following steps:

1. Select a rare disease with known phenotype and genotype
2. Identify a cohort with the disease. Apply the automated method to the cohort and compare the solution to the known phenotype.

We intend initially to consider Cystic Fibrosis and Sickle Cell Disease. Additional cohorts may be considered.

Project Purpose(s)

Methods Development

Scientific Approaches

Our method uses NLP methods to transform text descriptions of ontology concepts to numerical representations called embeddings. We represent individuals by collections of ontology terms as embeddings. We then use novel methods to identify a subset of ontology terms that best describes the overall cohort. We will apply this method to cohorts with rare disease diagnosis to determine if the method is able to recover the known disease phenotype. Specifically, we will identify individuals with a known rare disease by presence of selected SNOMED-CT diagnoses codes in the Condition Occurrence table or by presence of known disease causing genetic variants. We will then extract signs and symptoms for this cohort and apply our methods. We will conduct statistical analyses to assess method performance. The methods are implemented in Python using a variety of AI techniques.

Anticipated Findings

We anticipate that the results of this study will demonstrate validate the use of our methods in real-world data settings and identify potential limitations for method refinement. Ultimately, we expect that the methods will enable more rapid discovery of genotype-phenotype associations, thereby increasing rare disease diagnostic rates.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Aaron Masino - Early Career Tenure-track Researcher, Clemson University

Collaborators:

Amna Islam - Graduate Trainee, Clemson University
Ranga Baminiwatte - Graduate Trainee, Clemson University

Sickle Cell Disease NYS Outcomes

My research focuses on understanding the disparities in healthcare outcomes for individuals with Sickle Cell Disease (SCD) in New York State. Specifically, I aim to investigate the factors influencing variations in severity of illness, risk of mortality, and healthcare access…

Scientific Questions Being Studied

My research focuses on understanding the disparities in healthcare outcomes for individuals with Sickle Cell Disease (SCD) in New York State. Specifically, I aim to investigate the factors influencing variations in severity of illness, risk of mortality, and healthcare access across different regions and demographic groups. The research is critical for addressing healthcare inequities and improving outcomes for populations disproportionately affected by SCD, particularly among historically underserved communities. By examining regional and facility-level data, this study seeks to inform public health policies and improve SCD care delivery.

Project Purpose(s)

Disease Focused Research (Sickle Cell)
Population Health

Scientific Approaches

This study will utilize a combination of quantitative analyses, using statistical methods such as generalized linear models and regression analysis, to examine associations between healthcare outcomes (severity of illness, risk of mortality, etc.) and various factors like geographical location, demographics, and hospital characteristics. The data will be sourced from the SPARCS dataset, which includes claim transaction IDs, personal identifiers, and ZIP code information. Tools such as R, SAS, and Python will be used to analyze the data, while AWS will provide the secure cloud environment necessary for data storage and computation.

Anticipated Findings

The study anticipates finding significant regional disparities in the management and outcomes of Sickle Cell Disease patients in New York. It is expected that these findings will highlight differences in access to care, severity of illness, and mortality risk based on race, socioeconomic status, and geographic location. These results could contribute to developing targeted interventions, improving healthcare policies, and promoting equity in healthcare delivery, ultimately enhancing the quality of care for underrepresented populations suffering from SCD.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Emeka Iloegbu - Graduate Trainee, New York University

Sickle Cell Disease in New York State

My research focuses on understanding the disparities in healthcare outcomes for individuals with Sickle Cell Disease (SCD) in New York State. Specifically, I aim to investigate the factors influencing variations in severity of illness, risk of mortality, and healthcare access…

Scientific Questions Being Studied

My research focuses on understanding the disparities in healthcare outcomes for individuals with Sickle Cell Disease (SCD) in New York State. Specifically, I aim to investigate the factors influencing variations in severity of illness, risk of mortality, and healthcare access across different regions and demographic groups. The research is critical for addressing healthcare inequities and improving outcomes for populations disproportionately affected by SCD, particularly among historically underserved communities. By examining regional and facility-level data, this study seeks to inform public health policies and improve SCD care delivery.

Project Purpose(s)

Disease Focused Research (Sickle Cell Disease)
Population Health
Control Set

Scientific Approaches

This study will utilize a combination of quantitative analyses, using statistical methods such as generalized linear models and regression analysis, to examine associations between healthcare outcomes (severity of illness, risk of mortality, etc.) and various factors like geographical location, demographics, and hospital characteristics. The data will be sourced from the SPARCS dataset, which includes claim transaction IDs, personal identifiers, and ZIP code information. Tools such as R, SAS, and Python will be used to analyze the data, while AWS will provide the secure cloud environment necessary for data storage and computation.

Anticipated Findings

The study anticipates finding significant regional disparities in the management and outcomes of Sickle Cell Disease patients in New York. It is expected that these findings will highlight differences in access to care, severity of illness, and mortality risk based on race, socioeconomic status, and geographic location. These results could contribute to developing targeted interventions, improving healthcare policies, and promoting equity in healthcare delivery, ultimately enhancing the quality of care for underrepresented populations suffering from SCD.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Emeka Iloegbu - Graduate Trainee, New York University

Sickle Cell Disease

My research focuses on understanding the disparities in healthcare outcomes for individuals with Sickle Cell Disease (SCD) in New York State. Specifically, I aim to investigate the factors influencing variations in severity of illness, risk of mortality, and healthcare access…

Scientific Questions Being Studied

My research focuses on understanding the disparities in healthcare outcomes for individuals with Sickle Cell Disease (SCD) in New York State. Specifically, I aim to investigate the factors influencing variations in severity of illness, risk of mortality, and healthcare access across different regions and demographic groups. The research is critical for addressing healthcare inequities and improving outcomes for populations disproportionately affected by SCD, particularly among historically underserved communities. By examining regional and facility-level data, this study seeks to inform public health policies and improve SCD care delivery.

Project Purpose(s)

Disease Focused Research (Sickle Cell Disease)
Population Health

Scientific Approaches

This study will utilize a combination of quantitative analyses, using statistical methods such as generalized linear models and regression analysis, to examine associations between healthcare outcomes (severity of illness, risk of mortality, etc.) and various factors like geographical location, demographics, and hospital characteristics. The data will be sourced from the SPARCS dataset, which includes claim transaction IDs, personal identifiers, and ZIP code information. Tools such as R, SAS, and Python will be used to analyze the data, while AWS will provide the secure cloud environment necessary for data storage and computation.

Anticipated Findings

The study anticipates finding significant regional disparities in the management and outcomes of Sickle Cell Disease patients in New York. It is expected that these findings will highlight differences in access to care, severity of illness, and mortality risk based on race, socioeconomic status, and geographic location. These results could contribute to developing targeted interventions, improving healthcare policies, and promoting equity in healthcare delivery, ultimately enhancing the quality of care for underrepresented populations suffering from SCD.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Emeka Iloegbu - Graduate Trainee, New York University

RBC traits and sickle cell disease

To understand how red blood cell traits may vary in sickle cell disease and its clinical complications

Scientific Questions Being Studied

To understand how red blood cell traits may vary in sickle cell disease and its clinical complications

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Ancestry

Scientific Approaches

I plan to use the summary statistics of red blood cell traits and develop polygenic scores for another dataset

Anticipated Findings

These findings would allow us to understand if hematologic traits can be used to stratify SCD patients with chronic pain

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Varsha Bhat - Graduate Trainee, Georgia Institute of Technology

select cohort to study alloimmunization progression

Our scientific question is to find out if a certain gene carriers (based on previous study) has an increased risk to develop alloimmunization among patients with sickle cell diseases. Because we need to select a subset of patients with sickle…

Scientific Questions Being Studied

Our scientific question is to find out if a certain gene carriers (based on previous study) has an increased risk to develop alloimmunization among patients with sickle cell diseases. Because we need to select a subset of patients with sickle cell disease who received blood transfusion. We need to obtain their medical history data to see if they developed the alloimmunization within a certain period. We also need to exclude certain patients who has other comorbidities that will have a confounding effects on the alloimmunization outcome. We will need to see if the dataset we query from the CDR reflect a nature history of the disease progression, and decide if a case control design or a survival type of analysis is more appropriate.

Project Purpose(s)

Educational

Scientific Approaches

We plan to query the condition and procedure domain to build our cohort. We also plan to query the drug, labs and measurements tables to see if we can build a disease progression history that can help us to pinpoint the correct cohort.

Anticipated Findings

We will be able to see if our query will produce adequate dataset with variable that represents our study cohort. This will help us to see if we can use the EHR data to track the alloimmunization disease progression. To couple with genomic data, we will be able to find out if genetic play an important role in the alloimmunization.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Qing Li - Research Associate, National Human Genome Research Institute (NIH-NHGRI)

Postdoc

I am exploring the data to formalize a specific research question. I am interested in possible genetic variants other than HBB that are associated with sickle cell disease.

Scientific Questions Being Studied

I am exploring the data to formalize a specific research question. I am interested in possible genetic variants other than HBB that are associated with sickle cell disease.

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Ancestry

Scientific Approaches

I plan to use genomic data and social determinant of health. I am not sure if electronic health records data will be helpful, but I will investigate its usefulness.

Anticipated Findings

The study will likely show genes other than HBB that are associated with sickle cell disease. It may also uncover social determinants of health that are associated with this disease.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Brittany Taylor - Research Fellow, University of Pittsburgh

Sickle Cell Disease

I wish to study variants that exist across populations to do with sickle cell disease. I hope to be able to contribute to sickle cell disease treatment and the inclusivity of the treatment.

Scientific Questions Being Studied

I wish to study variants that exist across populations to do with sickle cell disease. I hope to be able to contribute to sickle cell disease treatment and the inclusivity of the treatment.

Project Purpose(s)

Disease Focused Research (Sickle Cell Disease)
Ancestry

Scientific Approaches

I will look at primarily populations of African and European descent, those with and without sickle cell disease.

Anticipated Findings

I anticipate to find variants that segregate across different populations in an observable pattern. Perhaps this pattern will present a novel modifier of sickle cell disease genes that can be targeted for therapeutics.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Fujr Osman Ibrahim Osman - Graduate Trainee, Johns Hopkins University

Sickle_Cell_Disease_2

I wish to study variants that exist across populations to do with sickle cell disease. I hope to be able to contribute to sickle cell disease management and treatment while remaining inclusive.

Scientific Questions Being Studied

I wish to study variants that exist across populations to do with sickle cell disease. I hope to be able to contribute to sickle cell disease management and treatment while remaining inclusive.

Project Purpose(s)

Disease Focused Research (Sickle Cell Disease)
Ancestry

Scientific Approaches

I will analyze the association of genetic variants across individuals with varying phenotypes with sickle cell disease.

Anticipated Findings

I anticipate to find variants that segregate across different populations in an observable pattern. Perhaps this pattern will present a novel modifier of sickle cell disease genes that can be targeted for therapeutics.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Fujr Osman Ibrahim Osman - Graduate Trainee, Johns Hopkins University

Sickle Cell Anemia

What are the current treatments available for sickle cell disorder. How do factor such as age, gender and availability effect treatment course. From current treatment methods, how can these be improved?

Scientific Questions Being Studied

What are the current treatments available for sickle cell disorder. How do factor such as age, gender and availability effect treatment course. From current treatment methods, how can these be improved?

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Educational

Scientific Approaches

Observe current datasets available. We will use and analyze current research studies and study previous treatment methods.

Anticipated Findings

We anticipate on finding treatment "holes". Our goal is to understand the most optimal treatment approach available for sickle cell disorder.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Matt Teel - Undergraduate Student, Arizona State University
Imerson Macon-Wagner - Undergraduate Student, Arizona State University
Daniel Armstrong - Undergraduate Student, Arizona State University
Angelina Mollins - Undergraduate Student, Arizona State University

Sickle Cell Trait (CDR v7)

Filtering and extracting variants from All of Us data to look at sickle cell traits to identify phenotypes and genotypes and to run PheWAS/GWAS analyses

Scientific Questions Being Studied

Filtering and extracting variants from All of Us data to look at sickle cell traits to identify phenotypes and genotypes and to run PheWAS/GWAS analyses

Project Purpose(s)

Disease Focused Research (Sickle Cell Traits)

Scientific Approaches

Developing workflows and pipelines using HAIL (in Python) to extract variants and conduct PheWAS and GWAS analyses using AoU data for sickle cell traits

Anticipated Findings

The findings from this study can include disease associations linked to sickle cell traits. These findings (and more) would help researchers with experimental design and analysis and to better understand sickle cell traits.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Huan Mo - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
Anas Awan - Project Personnel, National Human Genome Research Institute (NIH-NHGRI)

Collaborators:

Hasmin Ramirez - Project Personnel, National Human Genome Research Institute (NIH - NHGRI)
Bennett Waxse - Research Fellow, National Institute of Allergy and Infectious Diseases (NIH - NIAID)
Anirudh Kesanapally - Research Assistant, National Human Genome Research Institute (NIH - NHGRI)

Sickle cell disease

Scientific question: How do specific genetic variants in the beta-globulin gene influence the clinical severity of sickle cell disease? This question is important for personalized medicine approaches. It would aid identifying specific gene variants linked to disease severity to be…

Scientific Questions Being Studied

Scientific question: How do specific genetic variants in the beta-globulin gene influence the clinical severity of sickle cell disease? This question is important for personalized medicine approaches. It would aid identifying specific gene variants linked to disease severity to be able to help in developing targeted therapies, It would give knowledge of how genetic differences influence disease outcomes, Insights gained form the research could also inform studies on other genetic disorders. This question not only advances knowledge but potentially improve patient care and outcomes to people with the disease.

Project Purpose(s)

Educational

Scientific Approaches

Some scientific approaches to this research would be Genomic databases, disease specific repositories such as a sickle cell disease genetic network, Gene expression database, statistical analysis database, Gene editing tools, and clinical data management systems. These tools and methods can conduct comprehensive research.

Anticipated Findings

Anticipated findings : Identification of specific gene variants, Gene environment interactions, functional consequences of variants, and understanding the molecular mechanisms. My findings can contribute to personalized treatment approaches.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Matt Teel - Undergraduate Student, Arizona State University

SCA-TBI Exploratory Analysis

1. Characterize the prevalence of spine pathologies that contribute to adverse outcomes in patients with sickle cell disease (SCD). 2. Understand factors, variables, and diagnostics relating to neurological care for patients with sickle cell disease (SCD).

Scientific Questions Being Studied

1. Characterize the prevalence of spine pathologies that contribute to adverse outcomes in patients with sickle cell disease (SCD).
2. Understand factors, variables, and diagnostics relating to neurological care for patients with sickle cell disease (SCD).

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Population Health
Ancestry

Scientific Approaches

These questions will be answered through a mixed-methods approach to understand variables and factors contributing to adverse outcomes in patients with SCD. These methods will include decision tree analysis, cox regression modeling, t-tests, ANOVA, etc to compare those with SCD and non-SCD patients.

Anticipated Findings

The literature is dearth surrounding neurological and surgical outcomes in patients with SCD. This exploratory analysis will be the first of our knowledge in an effort to tailor personalized preventative interventions in this patient population.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Ektha Parchuri - Graduate Trainee, University of Pittsburgh

Duplicate of Pathogenic allele frequency - exploration

I am exploring the dataset for likely pathogenic and pathogenic alleles for variety of genetic diseases (e.g. Sickle Cell disease). The question I hope to answer using the data is: what is the frequency of pathogenic alleles for a specific…

Scientific Questions Being Studied

I am exploring the dataset for likely pathogenic and pathogenic alleles for variety of genetic diseases (e.g. Sickle Cell disease). The question I hope to answer using the data is: what is the frequency of pathogenic alleles for a specific disease?

Project Purpose(s)

Ancestry

Scientific Approaches

I plan to use the data in the All of Us Research biobank to determine the frequency of pathogenic alleles for a variety of genetic diseases.

Anticipated Findings

I anticipate that the broad and diverse sample set provided by the All of Us Research database will provide the most updated pathogenic allele frequency.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Jennifer Cohen - Early Career Tenure-track Researcher, Duke University

Variation in ED care and outcomes for young adults with suicide attempts

Brief Background: Adolescents and young adults are increasingly admitted to medical hospitals following suicide attempts. Prior studies have found often limited and varied psychiatric care provided during such admissions based on geographic location and resource availability. In addition to high…

Scientific Questions Being Studied

Brief Background: Adolescents and young adults are increasingly admitted to medical hospitals following suicide attempts. Prior studies have found often limited and varied psychiatric care provided during such admissions based on geographic location and resource availability. In addition to high rates of mental health conditions, the young adult population also faces unique vulnerability during the transition period between pediatric- to adult-focused care. Differences in care and outcomes have been found for this population for specific medical conditions such as sickle cell disease and sepsis based on admission to either an adult or pediatric hospital but little is known on variation in care and outcomes for those with mental health conditions.

Research question(s): Is there a difference in care and outcomes for young adults presenting for acute medical care following suicide attempt dependent on presentation to an adult versus pediatric facility and has this changed over time?

Project Purpose(s)

Population Health
Social / Behavioral

Scientific Approaches

We will access Electronic Health Records in the AllofUS dataset to identify young adults (ages 16-24) who have presented to an emergency department (ED) following a suicide attempt using relevant ICD diagnosis codes. Information about the ED itself (adult vs. pediatric) as well as the care received during the visit will be gathered, such as length of stay, psychiatric medications received, consultations, lab work, and disposition at discharge as available. Information will then be gathered on the individuals after discharge, including repeated presentations for mental health crisis, follow-ups with primary care or psychiatry/psychology, self-reported symptoms, and medication usage as available. Analyses will then be conducted to investigate how ED visits may differ for individuals in terms of care and outcomes based on whether the department is an adult or pediatric focused unit. Also of interest is the geographic location of the ED visited to examine access / barriers to care.

Anticipated Findings

We hypothesize that more resources and detailed care will be given at pediatric emergency departments compared to adult emergency departments for young adults presenting with suicide attempts. We also hypothesize that those seen at pediatric emergency departments, compared to adult emergency departments, will have better long-term outcomes (e.g., lower likelihood of repeated presentations for mental health crises, more consultation visits, medication adherence, etc.). Given the increasing population of young adults with mental health crisis as well as increasing hospitalizations, this research will help identify factors associated with meaningful outcomes and could help inform both pediatric and adult health systems on resource allocation and operational planning to best support this population. It may also help hospital systems in designing triage guidelines for the young adult population presenting with suicide attempt if significant differences in outcomes are found.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Emily Urban-Wojcik - Other, University of Michigan

Sickle Cell Trait (SCT) Associated Clinical Outcomes (SEP 2022)

Sickle cell trait (SCT) is largely a benign carrier state; however, a growing body of research has reported evidence on associated clinical complications. The primary purpose of this project is to identify differences in frequency of reported SCT associated clinical…

Scientific Questions Being Studied

Sickle cell trait (SCT) is largely a benign carrier state; however, a growing body of research has reported evidence on associated clinical complications. The primary purpose of this project is to identify differences in frequency of reported SCT associated clinical outcomes in a cohort of SCT and non-SCT carriers. In addition, social and environmental factors will be examined to identify potential risk modifiers of the carrier state. Specific questions for this project include:

1. Does the prevalence of clinical complication differ between SCT and non-SCT carriers?
2. What factors may increase the risk of developing clinical outcomes among SCT carriers?

As our understanding of SCT continues to develop, accurately assessing possible related clinical complications and the factors that put carriers at higher risk of developing them will assist healthcare providers with counseling and treatment for individuals who are carriers for sickle cell anemia (sickle cell trait).

Project Purpose(s)

Disease Focused Research (sickle cell anemia, sickle cell trait )

Scientific Approaches

In this study, electronic health records (EHRs) and survey data of identified SCT carriers will be analyzed to assess frequency of reported SCT associated clinical outcomes to help strengthen or refute current evidence on SCT association. High frequency of clinical outcomes with no reported association to SCT will also be accounted for.
EHRs and survey data for a comparison group of All of Us participants that do not have SCT will also be assessed, to identify any significant differences in SCT associated clinical complication manifestation. Additionally, EHRs and survey data will be analyzed to explore factors identified within SCT literature that may put carriers at higher risk of developing complications. We will use R to complete all analysis.

The cross-sectional design for this analysis limits our ability to ascertain causation for diagnoses of clinical complications of interest.

Anticipated Findings

A poor understanding of SCT has contributed to its stigmatization, affecting screening efforts, policy decisions, and clinical treatment of carriers. By utilizing a large sample of confirmed SCT carriers, our study sets out to provide a better understanding of the carrier state in an effort to combat stigma and misinformation that has plagued this population in the past. In addition, our findings will report of the rarity of complications among this population. We anticipate that our findings will strengthen current evidence on the association or not of certain clinical outcomes with SCT. Overall, we hope that our findings will provide a better understanding of this carrier state, to improve health care providers and individuals living with sickle cell trait knowledge of the carrier state.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Hasmin Ramirez - Project Personnel, National Human Genome Research Institute (NIH - NHGRI)

Collaborators:

Faeben Wossenseged - Other, National Human Genome Research Institute (NIH-NHGRI)

Prediction Of The Sickle Cell Anaemia

Sickle Cell Disease (SCD) is a genetic disorder that affects millions worldwide, particularly those of African descent. Predicting its prevalence within a specific cohort is crucial for healthcare planning, resource allocation, and preventive measures. In this project, we aim to…

Scientific Questions Being Studied

Sickle Cell Disease (SCD) is a genetic disorder that affects millions worldwide, particularly those of African descent. Predicting its prevalence within a specific cohort is crucial for healthcare planning, resource allocation, and preventive measures. In this project, we aim to develop a machine learning model to predict the prevalence of SCD within a given cohort based on various demographic, genetic, and environmental factors.

Project Purpose(s)

Educational
Methods Development

Scientific Approaches

We will utilize a comprehensive dataset containing demographic information (age, gender, ethnicity), genetic data (genetic markers associated with SCD), and environmental factors (geographical location, climate data) for individuals within the cohort. The dataset will also include SCD prevalence information, either confirmed through medical records or inferred from genetic markers. We will experiment with various machine learning algorithms such as logistic regression, decision trees, random forests, and gradient boosting methods to determine the most suitable model for predicting SCD prevalence. The dataset will be split into training and validation sets for model training and evaluation, respectively. We will employ techniques like cross-validation and hyperparameter tuning to optimize model performance.

Anticipated Findings

Once the model is trained and evaluated satisfactorily, it can be deployed as a predictive tool for estimating SCD prevalence within similar cohorts. Continuous monitoring and updating of the model with new data will be necessary to ensure its accuracy and relevance over time. Furthermore, collaboration with healthcare professionals and policymakers will facilitate the integration of the model into clinical practice and public health initiatives aimed at managing and preventing SCD.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Ranga Baminiwatte - Graduate Trainee, Clemson University

TNBC and Sickle Cell Anemia

This research project seeks to better understand the treatment strategies used for African American/black women with sickle cell disease who are diagnosed with triple negative breast cancer. Given the cadre of treatment strategies for this special population, we may be…

Scientific Questions Being Studied

This research project seeks to better understand the treatment strategies used for African American/black women with sickle cell disease who are diagnosed with triple negative breast cancer. Given the cadre of treatment strategies for this special population, we may be able to identify a novel treatment strategy for those with TNBC to treat other patients who do not have sickle cell disease.

Project Purpose(s)

Disease Focused Research (TNBC and Sickle Cell Disease)
Population Health
Drug Development
Ancestry

Scientific Approaches

Establishing a dataset of women diagnosed with sickle cell disease and who are diagnosed with breast cancer with the subtype of triple negative breast cancer will be the initial approach.

Anticipated Findings

Our biggest concern is that the numbers who match all criteria be low. However, the strategy may help identify a novel drug treatment approaches for women diagnosed with TNBC and have no targeted therapeutic options.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Kitani Lemieux - Mid-career Tenured Researcher, Xavier University of Louisiana

Stigma in Sicke Cell Patients

The exploration of psychological stigmas experienced by patients afflicted with Sickle Cell Anemia. The purpose is to study how having this disease impacts those who are in cultures who discriminate and isolate those impacted with this disease. Focusing primarily on…

Scientific Questions Being Studied

The exploration of psychological stigmas experienced by patients afflicted with Sickle Cell Anemia. The purpose is to study how having this disease impacts those who are in cultures who discriminate and isolate those impacted with this disease. Focusing primarily on African nations and isolated populations who have members of their community afflicted with this disease and the psychological impact on the individuals.

Project Purpose(s)

Educational

Scientific Approaches

Would like to use currently published data sets, statements from those afflicted and cultural influences that are causing sickle cell patients to be stigmatized in their communties.

Anticipated Findings

The hope to is illustrate the psychological impacts of having sickle cell on those afflicted. How it affects their daily lives in a community and what psychologists can do to alleviate the stigmatism being afflicted on those in the community by the greater surrounding community.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Catherine Williams - Undergraduate Student, Arizona State University

Sickle Cell Trait Associated Clinical Outcomes (V6)

Sickle cell trait (SCT) is largely considered a benign carrier state; however, a growing body of research has found evidence on associated clinical complications. This analysis will build on our initial examination of the prevalence of clinical complications between SCT…

Scientific Questions Being Studied

Sickle cell trait (SCT) is largely considered a benign carrier state; however, a growing body of research has found evidence on associated clinical complications. This analysis will build on our initial examination of the prevalence of clinical complications between SCT and non-SCT carriers.
Our question is: Is there a prevalence of clinical complications among newly identified SCT carriers?

As our understanding of SCT continues to develop, accurately assessing possible related clinical complications and the factors that put carriers at higher risk of developing them will assist healthcare providers with counseling and treatment interventions for carriers.

Project Purpose(s)

Disease Focused Research (Sickle Cell Trait)
Ancestry

Scientific Approaches

In this study, individuals with sickle cell trait will be identified using genomic data. Electronic health records (EHRs) of identified SCT carriers will be analyzed to assess frequency of reported SCT associated clinical outcomes to help strengthen or refute current evidence on SCT association. High frequency of clinical outcomes with no reported association to SCT will also be accounted for.

Anticipated Findings

We anticipate that our findings will strengthen current evidence on the association of certain clinical outcomes with SCT. Overall, we hope that our findings will provide a better understanding of this carrier state, to improve genetic counseling and treatment for those living with sickle cell trait.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Hasmin Ramirez - Project Personnel, National Human Genome Research Institute (NIH - NHGRI)

Collaborators:

Yupeng Wang - Other, National Institute on Alcohol Abuse and Alcoholism (NIH - NIAAA)
Faeben Wossenseged - Other, National Human Genome Research Institute (NIH-NHGRI)
Huan Mo - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
Anas Awan - Project Personnel, National Human Genome Research Institute (NIH-NHGRI)

Sickle Cell Trait Associated Clinical Outcomes (V7)

Sickle cell trait (SCT) is largely a benign carrier state; however, a growing body of research has reported evidence on associated clinical complications. The primary purpose of this project is to identify differences in frequency of reported SCT associated clinical…

Scientific Questions Being Studied

Sickle cell trait (SCT) is largely a benign carrier state; however, a growing body of research has reported evidence on associated clinical complications. The primary purpose of this project is to identify differences in frequency of reported SCT associated clinical outcomes in a cohort of SCT and non-SCT carriers. In addition, social and environmental factors will be examined to identify potential risk modifiers of the carrier state. Specific questions for this project include:

1. Does the prevalence of clinical complication differ between SCT and non-SCT carriers?
2. What factors may increase the risk of developing clinical outcomes among SCT carriers?

As our understanding of SCT continues to develop, accurately assessing possible related clinical complications and the factors that put carriers at higher risk of developing them will assist healthcare providers with counseling and treatment for individuals who are carriers for sickle cell anemia (sickle cell trait).

Project Purpose(s)

Disease Focused Research (Sickle Cell Trait)
Ancestry

Scientific Approaches

In this study, electronic health records (EHRs) and survey data of identified SCT carriers will be analyzed to assess frequency of reported SCT associated clinical outcomes to help strengthen or refute current evidence on SCT association. High frequency of clinical outcomes with no reported association to SCT will also be accounted for.
EHRs and survey data for a comparison group of All of Us participants that do not have SCT will also be assessed, to identify any significant differences in SCT associated clinical complication manifestation. Additionally, EHRs and survey data will be analyzed to explore factors identified within SCT literature that may put carriers at higher risk of developing complications. We will use R to complete all analysis.

Anticipated Findings

A poor understanding of SCT has contributed to its stigmatization, affecting screening efforts, policy decisions, and clinical treatment of carriers. By utilizing a large sample of confirmed SCT carriers, our study sets out to provide a better understanding of the carrier state in an effort to combat stigma and misinformation that has plagued this population in the past. In addition, our findings will report of the rarity of complications among this population. We anticipate that our findings will strengthen current evidence on the association or not of certain clinical outcomes with SCT. Overall, we hope that our findings will provide a better understanding of this carrier state, to improve health care providers and individuals living with sickle cell trait knowledge of the carrier state.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Hasmin Ramirez - Project Personnel, National Human Genome Research Institute (NIH - NHGRI)

Collaborators:

Yupeng Wang - Other, National Institute on Alcohol Abuse and Alcoholism (NIH - NIAAA)
Faeben Wossenseged - Other, National Human Genome Research Institute (NIH-NHGRI)
Huan Mo - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
Anas Awan - Project Personnel, National Human Genome Research Institute (NIH-NHGRI)

Genetic Contribution to the reduced risk of HIV in Sickle Cell Disease

This study will explore data to determine whether there is sufficient information to study genetic contributions to the reduced risk of HIV in individuals with sickle cell disease (SCD). Individuals with SCD are reported to have low rates of HIV…

Scientific Questions Being Studied

This study will explore data to determine whether there is sufficient information to study genetic contributions to the reduced risk of HIV in individuals with sickle cell disease (SCD). Individuals with SCD are reported to have low rates of HIV infection, slower progression to AIDS and lower HIV-associated mortality when compared to the general population. Most of the studies to date have focused on mechanisms that underly this relationship. To our knowledge, no studies have evaluated whether there is a genetics contribution.

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Ancestry

Scientific Approaches

We will utilize clinical measures (i.e. diagnostic categories) and genomic data to determine if there is a genetic association. We will evaluate three population groups : Individuals with SCD only, individuals with SCD and HIV and those with HIV only.

Anticipated Findings

I anticipate identifying the amount of individuals that fall into each of the categories. If a sufficient sample size is determined, I anticipate that I will identify a variant that protects against HIV in individuals with SCD.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Raven Hardy Richard - Research Fellow, National Human Genome Research Institute (NIH - NHGRI)

Sicke Cell and CRISPR treatment

The purpose is to explore the causes of Sickle Cell anemia in connection with the current treatment of CRISPR to Sickle Cell patients. Is it working and if so how can it be made more available for those stricken with…

Scientific Questions Being Studied

The purpose is to explore the causes of Sickle Cell anemia in connection with the current treatment of CRISPR to Sickle Cell patients. Is it working and if so how can it be made more available for those stricken with it.

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Educational
Ancestry

Scientific Approaches

Approaches are to explore current data sets of patients with the disease. Particularly focusing on African American patients who have a higher level of this disease.Explore why this is the case in terms of genetics and look at environmental disparities that may be causing treatment to be hindered as well as access to CRISPR as a treatment for this disease.

Anticipated Findings

Findings would highlight the continued push to find environmental influences on those who have the disease and why it is continued to be passed on. In addition, close attention to current advances in CRISPR treatment and how it's use could be used to expand treatment for those stricken with the disease.The overarching goal would be to explore if CRISPR treatments are long lasting for current and patients and could this be a road map to a cure.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Catherine Williams - Undergraduate Student, Arizona State University

Health Disparities of Minorites with Sickle Cell Disease

RQ1: What health disparities do individuals with sickle cell disease face that limit their ability to receive care? RQ2: How do individuals with sickle cell disease communicate stigma to their (a) families and (b) providers.

Scientific Questions Being Studied

RQ1: What health disparities do individuals with sickle cell disease face that limit their ability to receive care?
RQ2: How do individuals with sickle cell disease communicate stigma to their (a) families and (b) providers.

Project Purpose(s)

Disease Focused Research (sickle cell anemia)
Population Health
Social / Behavioral

Scientific Approaches

I plan to utilize both health and interpersonal theories to better understand sickle cell disease from the patient prospective.

Anticipated Findings

I believe that there will be connections between socioeconomics and communication of stigma. In addition I believe that I may find age factors that play a role in both how the disease is managed and how it is communicated.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Jorlanditha Austin - Graduate Trainee, Rutgers, The State University of New Jersey

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