A Case Report Using Ancestry-adjusted Genome-wide Polygenic Risk Scores with 7,000 Serum Protein Testing to Improve Intervention and Outcome
Clinical Genetics and Therapeutics
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Introduction
Chronic diseases are multifactorial conditions involving complex interactions between genetic and environmental factors.
Genome sequencing-based pathogenic variant reporting and ethnic-specific polygenic risk score (PRS) analysis, coupled with proteomic assessment, may allow clinicians to obtain lifetime and 4-year risks associated with major adverse cardiac events. This information may change patient management, leading to improved outcomes.
Here we present a case study of a patient with elevated cardiovascular risk factors but who was non-compliant of statin treatment due to drug side effects. Multimodal testing showed he had a high risk of cardiometabolic diseases and their risk factors. This, together with pharmacogenetic testing led the patient to agree to a new statin treatment using a drug without adverse pharmacogenetic profile.
Case Presentation
The patient is a businessman, self-reported “Asian”, aged 56, overweight, and is taking medications to control his type 2 diabetes (T2D) and hypertension. He is affected by
Lifestyle
Diagnostic Workup
Clinical genome sequencing and clinical interpretation were performed at Rainbow Genomics according to ACMG guidelines. Galatea Bio (GB) determined that the patient has admixed ancestry of East Asia and South Asia.
Ancestry-adjusted, genome-wide PRS taking into account the patient’s admixed ancestry, was determined for multiple cardiometabolic traits by GB using approximately one million SNPs.
Pharmacogenomic analysis was performed using the genomic data. 7,000 serum protein testing was performed at a US CLIA-accredited and CAP-certified clinical laboratory.
Diagnostic results
Treatment and Management
Change of Management
Outcome and Follow-Up
Outcome:
Follow-up:
Discussion
Conclusion
This case report showcases the possibility of using multi-omics as a more comprehensive risk assessment beyond conventional risk factors for cardiovascular diseases to guide interventions for reducing chronic diseases.
Chronic diseases are multifactorial conditions involving complex interactions between genetic and environmental factors.
Genome sequencing-based pathogenic variant reporting and ethnic-specific polygenic risk score (PRS) analysis, coupled with proteomic assessment, may allow clinicians to obtain lifetime and 4-year risks associated with major adverse cardiac events. This information may change patient management, leading to improved outcomes.
Here we present a case study of a patient with elevated cardiovascular risk factors but who was non-compliant of statin treatment due to drug side effects. Multimodal testing showed he had a high risk of cardiometabolic diseases and their risk factors. This, together with pharmacogenetic testing led the patient to agree to a new statin treatment using a drug without adverse pharmacogenetic profile.
Case Presentation
The patient is a businessman, self-reported “Asian”, aged 56, overweight, and is taking medications to control his type 2 diabetes (T2D) and hypertension. He is affected by
- Severe obstructive sleep apnea
- T2D
- Hypertension
- Hyperlipidemia
Lifestyle
- He is a social drinker without smoking.
- He does not exercise and has a diet rich in proteins and fat.
Diagnostic Workup
Clinical genome sequencing and clinical interpretation were performed at Rainbow Genomics according to ACMG guidelines. Galatea Bio (GB) determined that the patient has admixed ancestry of East Asia and South Asia.
Ancestry-adjusted, genome-wide PRS taking into account the patient’s admixed ancestry, was determined for multiple cardiometabolic traits by GB using approximately one million SNPs.
Pharmacogenomic analysis was performed using the genomic data. 7,000 serum protein testing was performed at a US CLIA-accredited and CAP-certified clinical laboratory.
Diagnostic results
- Monogenic Genetic Risk: Genome-wide analysis of high-risk variants associated with abnormality of the cardiovascular system, familial cardiomyopathy, arrhythmia, hypercholesterolemia, diabetes mellitus, and hypertension was performed. No pathogenic (monogenic) variant was detected, indicating that the cardiometabolic symptoms may not have a hereditary genetic cause.
- Polygenic Risk was detected for decreasing HDL. The risk is for future low HDL which is a risk for cardiovascular events beyond his known conventional risk factors of hypertension, increased LDL, T2D, and OSA.
- Proteomic Risk:
- 2.5x risk for developing dementia in 20 years, compared to the general Asian population.
- 4-year imminent cardiovascular disease risk (heart attack, stroke, and heart failure) of 3x.
- Excess fat in the liver, and excess visceral fat around his vital organs.
- Cardio-respiratory fitness, represented by VO2Max, is poor.
- Pharmacogenomics
- Significant gene-drug interactions for
- Lovastatin
- Pitavastatin
- Simvastatin
- Significant gene-drug interactions for
Treatment and Management
Change of Management
- The patient was put on a statin not affected by his pharmacogenetic profile with an intervention target established based on current guidelines in association with his combined clinical, genetic, and proteomic risks.
- Lovastatin, Pitavastatin, and Simvastatin were avoided due to significant gene-drug interactions.
- He is being monitored for the development of cardiac events and symptoms in the near-term, and longer-term vascular dementia.
Outcome and Follow-Up
Outcome:
- The patient agreed to the new statin treatment and to reduce weight.
Follow-up:
- A list of diet, activities, and lifestyle interventions for preventing cardiac events, and dementia was provided to him.
- He was also referred to a cardiologist and dietician for follow-up.
Discussion
- Poor cardiorespiratory fitness coupled with excess liver and visceral fats, further increases the risk for a cardiac event within 4 years, which is predicted based on his protein profile.
- The patient had bad experiences in past statin use, due to adverse drug reactions because he is a poor metabolizer of multiple statins based on the pharmacogenetic analysis above.
Conclusion
This case report showcases the possibility of using multi-omics as a more comprehensive risk assessment beyond conventional risk factors for cardiovascular diseases to guide interventions for reducing chronic diseases.