Huan Mo

Research Fellow, National Institutes of Health (NIH)

6 active projects

Role of pathogenic alleles in a general population

Pathogenic variants (alleles) of genes are diagnosed with ACMG criteria and reported in ClinVar. However, although each of these alleles are very rare (as one of the ACMG diagnostic criteria) in the population, each healthy person may carry multiple of…

Scientific Questions Being Studied

Pathogenic variants (alleles) of genes are diagnosed with ACMG criteria and reported in ClinVar. However, although each of these alleles are very rare (as one of the ACMG diagnostic criteria) in the population, each healthy person may carry multiple of pathogenic variants due to the large number of kinds of these variants across the human genome. Also, most of these pathogenic variants were discovered from patients with diseases and the penetrance of the phenotypes can be over-estimated. In this study, we will survey the carriers of these pathogenic variants in the general population and understand their true phenotypes in an unbiased cohort. Particularly, we are interested in pathogenic variants that are associated with malignant hyperthermia during anesthesia .

Project Purpose(s)

  • Disease Focused Research (malignant hyperthermia)
  • Drug Development
  • Methods Development

Scientific Approaches

Data: Whole genome sequencing and phenotype.
Methods: GWAS, PheWAS, Reversed Phenotyping, Phenomic risk scores.
We will first identified individuals who carries the pathogenic alleles, and perform PheWAS and reversed phenotyping to evaluate the behaviors of these alleles in an unbiased population. We will also validate phenomic risk scores (PheRS) to predict the carrier status of these pathogenic alleles.

Anticipated Findings

1. The prevalence of the carrier status of pathogenic alleles.
2. The phenotype impacts of these alleles in the general population
3. Validation of PheRS

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 Institutes of Health (NIH)

Collaborators:

  • Tam Tran - Other, National Institutes of Health (NIH)
  • Onajia Stubblefield - Graduate Trainee, National Institutes of Health (NIH)
  • Slavina Goleva - Research Fellow, National Institutes of Health (NIH)
  • David Schlueter - Research Fellow, National Institutes of Health (NIH)
  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)
  • Ariel Williams - Research Fellow, National Institutes of Health (NIH)

Genetic predisposition of SIADH during antidepressant treatment

The goal of this study is to identify genetic variants that predispose patients to adverse reactions (such as Syndrome of inappropriate antidiuretic hormone [SIADH]) during antidepressant treatments (such as selective serotonin reuptake inhibitor [SSRI]). SIADH is a common cause of…

Scientific Questions Being Studied

The goal of this study is to identify genetic variants that predispose patients to adverse reactions (such as Syndrome of inappropriate antidiuretic hormone [SIADH]) during antidepressant treatments (such as selective serotonin reuptake inhibitor [SSRI]).
SIADH is a common cause of hyponatremia, and many cases represent adverse reactions to drugs that alter ion channels of the posterior pituitary. The frequency of drug-induced SIADH increases with age; as many as 20% of patients residing in nursing homes have serum sodium levels below 135 mEq/L. Severe hyponatremia is associated with cerebral edema, seizures, permanent disability, and/or death. Work is needed in large observational cohorts to quantify the strength of association between pharmacogene variants and drug-induced SIADH so that decision support can be developed to identify patients at high risk. (PMID: 34575630).

Project Purpose(s)

  • Disease Focused Research (inappropriate ADH syndrome)
  • Ancestry

Scientific Approaches

1. Identify a cohort of patients who developed hyponatremia during SSRI treatment. 2. Identify a control cohort of patients with matched demographic data (particularly ages and SSRI use) who did not develop hyponatremia. 3. Compare the genetic and other risk factors between these two cohorts.

Anticipated Findings

We anticipate to develop a genetic and risk model to identify patients who have higher risks of developing SIADH in SSRI treatment. Therefore, they can use alternative medications or increase monitoring.

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 Institutes of Health (NIH)

Collaborators:

  • Tracey Ferrara - Project Personnel, National Institutes of Health (NIH)
  • Thomas Cassini - Research Fellow, National Institutes of Health (NIH)
  • Tam Tran - Other, National Institutes of Health (NIH)
  • Josh Denny - Other, All of Us Program Operational Use
  • Jian Dai - Project Personnel, National Institutes of Health (NIH)
  • Jacob Keaton - Other, National Institutes of Health (NIH)
  • Slavina Goleva - Research Fellow, National Institutes of Health (NIH)
  • David Schlueter - Research Fellow, National Institutes of Health (NIH)
  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)
  • Ariel Williams - Research Fellow, National Institutes of Health (NIH)
  • Anav Babbar - Other, National Institutes of Health (NIH)

Validation of Phenotype Risk Scores

Many genetic syndromes (described in OMIM) manifest as constellations of disease. As most of these genetic diseases are rare individually but not uncommon as a whole, many patients can be misdiagnosed and did not have correct genetic tests. In this…

Scientific Questions Being Studied

Many genetic syndromes (described in OMIM) manifest as constellations of disease. As most of these genetic diseases are rare individually but not uncommon as a whole, many patients can be misdiagnosed and did not have correct genetic tests. In this project, we want to use the diagnostic codes (conditions) recorded in the AoU to identify potential missed cases and test them with the genomic data.

Phenotype risk score (PheRS) is calculated with presence of weighed numbers of manifestations as described in the following publication.

Bastarache, L., Hughey, J.J., Goldstein, J.A., Bastraache, J.A., Das, S., Zaki, N.C., Zeng, C., Tang, L.A., Roden, D.M., Denny, J.C. (2019). Improving the phenotype risk score as a scalable approach to identifying patients with Mendelian disease. J Am Med Inform Assoc, 26(12):1437-1447.

Project Purpose(s)

  • Methods Development

Scientific Approaches

1. Conditions / diagnostic codes are used to calculate PheRS
2. Genomic data: to identify carriers of undiagnosed genetic diseases.

Anticipated Findings

Validation of the application of PheRS in predicting carrier status. If this approach is valid, it would be useful to implement in clinical decision support (CDS).

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 Institutes of Health (NIH)

Clonal hematolymphoid cells in general population

Clonal, presumptively pre-neoplastic expansion of myeloid (such as Clonal Hematopoiesis of Indeterminate Potential [CHIP]) and lymphoid (such as Monoclonal B-cell lymphocytosis [MBL]) cells are observed in healthy populations. A small percentage of these patients may progress to overt leukemia or…

Scientific Questions Being Studied

Clonal, presumptively pre-neoplastic expansion of myeloid (such as Clonal Hematopoiesis of Indeterminate Potential [CHIP]) and lymphoid (such as Monoclonal B-cell lymphocytosis [MBL]) cells are observed in healthy populations. A small percentage of these patients may progress to overt leukemia or lymphoma. This study is to identify individuals who carry these abnormal clones of blood cells and the characterize the health impact and genetic natures.

Project Purpose(s)

  • Disease Focused Research (chronic lymphocytic leukemia)

Scientific Approaches

We will use the CRAM files for the WGS to calculate the presence of clonal chromosomal aberrance such as gain, loss, or loss of heterozygosity. We will also try to identify the presence of recurrent somatic mutations that are commonly seen in hematolymphoid neoplasms.

We will also run PheWAS and GWAS to characterize the patients who are identified carrying these clones of blood cells.

Anticipated Findings

In previous studies (especially those with UK Biobank data), myeloid and lymphoid clones were not separated in characterization. However, they are completely different diseases. In this study, we did not only expand the survey to AoU population, but will also explore the relationship of the clones to a more granular classification of hematolymphoid neoplasms.

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 Institutes of Health (NIH)

Duplicate HM of 2021 Update: DJS: PheWAS Final Review 11-01-2021

As a demonstration project, this study will present the results of Phenome-Wide Association Studies (PheWAS) to show how the various sources of data contained within All of Us research dataset can be used to inform scientific discovery. We will perform…

Scientific Questions Being Studied

As a demonstration project, this study will present the results of Phenome-Wide Association Studies (PheWAS) to show how the various sources of data contained within All of Us research dataset can be used to inform scientific discovery. We will perform separate PheWAS studies with smoking status as the independent variable. Specific questions include:

1. How can one implement a PheWAS within the All of Us Researcher Workbench?
2. How can one use heterogeneous data sources within the All of Us dataset to explore disease associations using self-reported exposures (Participant Provided Information, or “PPI”) and exposures captured in the electronic medical record (EHR).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

Project Purpose(s)

  • Methods Development
  • Other Purpose (This work is a result of an All of Us Research Program Demonstration Project. The projects are efforts by the Program designed to meet the program's goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. This work was reviewed and overseen by the All of Us Research Program Science Committee and the Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use.)

Scientific Approaches

As a demonstration project, this study will present the results of Phenome-Wide Association Studies (PheWAS) to show how the various sources of data contained within All of Us research dataset can be used to inform scientific discovery. We will perform separate PheWAS studies with smoking status as the independent variable. Specific questions include:

1. How can one implement a PheWAS within the All of Us Researcher Workbench?
2. How can one use heterogeneous data sources within the All of Us dataset to explore disease associations using self-reported exposures (Participant Provided Information, or “PPI”) and exposures captured in the electronic medical record (EHR).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

Anticipated Findings

For this study, we anticipate that we will be able to replicate known disease associations with smoking exposure. This will serve to demonstrate the quality, utility, and diversity of the All of Us data and tools and the power of gathering multiple data sources for a single phenotype, providing researchers options for study design and validation. Importantly the entire PheWAS package is made available for reuse by researchers in the Workbench, for new hypothesis generation.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Huan Mo - Research Fellow, National Institutes of Health (NIH)

SIADH in SSRI Treatment

Syndrome of inappropriate antidiuretic hormone (SIADH) is a common cause of hyponatremia, and many cases represent adverse reactions to drugs that alter ion channels of the posterior pituitary. The frequency of drug-induced SIADH increases with age; as many as 20%…

Scientific Questions Being Studied

Syndrome of inappropriate antidiuretic hormone (SIADH) is a common cause of hyponatremia, and many cases represent adverse reactions to drugs that alter ion channels of the posterior pituitary. The frequency of drug-induced SIADH increases with age; as many as 20% of patients residing in nursing homes have serum sodium levels below 135 mEq/L. Severe hyponatremia is associated with cerebral edema, seizures, permanent disability, and/or death. The implementation of these tests has been based upon the prior known association of these drugs with other serious adverse drug reactions (e.g., electrocardiographic abnormalities). Work is needed in large observational cohorts to quantify the strength of association between pharmacogene variants and drug-induced SIADH so that decision support can be developed to identify patients at high risk. (PMID: 34575630)
SSRI (a most commonly used antidepressants) can cause SIADH. We are to identify genetic factors that predisposition this adverse effect.

Project Purpose(s)

  • Disease Focused Research (inappropriate ADH syndrome)
  • Drug Development
  • Ancestry

Scientific Approaches

1. Identify a cohort of patients who developed hyponatremia during SSRI treatment.
2. Identify a control cohort of patients with matched demographic data (particularly ages and SSRI use) who did not develop hyponatremia.
3. Compare the genetic and other risk factors between these two cohorts.

Anticipated Findings

We anticipate to develop a genetic and risk model to identify patients who have higher risks of developing SIADH in SSRI treatment. Therefore, they can use alternative medications or increase monitoring.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Huan Mo - Research Fellow, National Institutes of Health (NIH)
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