Integrating Whole Genome Sequencing and Digital Twins Into the Management of Hypercholesterolemia in Emiratis

A Randomized Trial of Integrating Whole Genome Sequencing and Digital Twins Into the Management of Hypercholesterolemia in Emiratis

This pilot study investigates integrating whole genome sequencing and digital twin technology for managing hypercholesterolemia in Abu Dhabi clinics. It aims to establish protocols for larger future studies and incorporate genomic insights into routine medical care.

Study Overview

• Status: Recruiting
• Conditions: Hypercholesterolemia, Autosomal Dominant; Familial Combined Hypercholesterolemia; Hypercholesterolemia, Autosomal Recessive
• Intervention / Treatment: Genetic: Whole Genome Sequencing

Detailed Description

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death in the Middle East, with hypercholesterolemia being a significant contributor. Genetic mechanisms of hypercholesterolemia in this region are not well understood. Autosomal dominant hypercholesterolemia is a major factor, yet only ~7% of Emiratis with familial hypercholesterolemia (FH) have these mutations. In 2013, Talmud et al. identified common variants through genome-wide association studies (GWAS) that suggest a polygenic cause for hypercholesterolemia in mutation-negative FH patients. A polygenic risk score based on 12 SNPs was validated in White European populations and is used in the UK's NHS diagnostic pipeline. Distinguishing polygenic hypercholesterolemia from FH without genetic testing is challenging. These patients exhibit familial moderate hypercholesterolemia and early coronary heart disease, with elevated LDL-C, normal triglycerides, and no tendon xanthoma. Their cardiovascular risk is similar to monogenic FH with age.

Statins, though commonly prescribed for ASCVD prevention, can cause musculoskeletal symptoms leading to poor adherence, discontinuation, elevated cholesterol, and increased cardiovascular risk. Many patients fail to achieve target LDL-C levels due to suboptimal dosing. Certain gene variants increase the risk of statin side effects.

This study seeks to integrate whole genome sequencing (WGS) technology in a clinical setting through an innovative digital twin platform. This platform allows clinicians to assess monogenic and polygenic risks in real-time and make informed statin prescribing and management decisions.

• Study Type: Interventional
• Enrollment (Estimated): 40
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Alina Naeem, MBBS; Phone Number: +97124102534; Email: alnaeem@seha.ae
• Study Contact Backup: Name: Mhy-Lanie Adduru, MD; Phone Number: +14088311991; Email: mhy-lanie@predictivcare.com

Study Locations

• United Arab Emirates
  • Abu Dhabi, United Arab Emirates
    • Recruiting
    • Abu Dhabi Health Research Center
    • Contact: Salah Eldin HM Hussein, MD; Phone Number: 0504485852; Email: sahussein@seha.ae
    • Contact: Antoniette C Cano, BSc; Phone Number: 0558873919; Email: o-acano@seha.ae
    • Contact: Ali H Muwaili, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Patients with 2 or more LDL-C levels greater than 190 mg/dL or 5.0 mmol/L in the past 12 months
• Undiagnosed patients meeting Possible, Probable or Definitive FH criteria according to Dutch Lipid Clinic Network (DLCN) criteria (Eur Heart J. 2011 Jul;32(14):1769-818. doi: 10.1093/eurheartj/ehr158. Epub 2011 Jun 28.)
• Patients who have not been on anti-lipidemic medication in the past 3 months
• Ages 18-55
• Emirati national
• All patients must be fluent in English or Arabic

Exclusion Criteria:

• - Patients who do not meet the above criteria
• Patients with a previous diagnosis of FH
• Patients with a progressive debilitating illness
• Patient with untreated hypothyroidism, history of proteinuria, obstructive liver disease, chronic renal failure, human immunodeficiency virus infection, or on immunosuppressant or steroid or psychiatric medications
• Patients with untreated clinical anxiety or depression (as measured by a Hospital Anxiety and Depression Scale (HADS) score of ≥ 16 on the depression subscale)
• Patients who are pregnant

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Triple

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: WGS + Digital Twin Group; 20 participants who are randomized to have whole-genome sequencing performed on their sample and given access to Predictiv™ Digital Twin. These participants will meet with a genetic counselor for results disclosure and training to access the Predictiv™ Digital Twin platform.	Genetic: Whole Genome Sequencing; Participants in this arm will have their blood sample analyzed by whole-genome sequencing (WGS) and will be given access to Predictiv™ Deoxyribonucleic acid (DNA)-based digital twin platform, a web-based interactive application with WGS results. The platform will include positive monogenic and polygenic Familial Hypercholesterolemia results and pharmacogenomics results on statins and clopidogrel. A report of positive monogenic variants will be included in their medical record. This may also include genes on the American College of Medical Genetics and Genomics (ACMG) secondary findings (SF) version 3.2 list if the participant consents to receive these incidental findings. The report will only include pathogenic, likely pathogenic, and variant of uncertain significance (VUS) results.
No Intervention: Standard of Care Group; 20 participants who are randomized to not have whole-genome sequencing performed on their sample. These participants will have standard-of-care familial hypercholesterolemia (FH) evaluation using medical history and family history only. They will not receive genetic results or Predictiv™ Digital Twin results as part of this study.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic capabilities	Diagnostic yield of standard-of-care (based on medical and family history) versus whole genome sequencing (WGS) for identifying monogenic and polygenic familial hypercholesterolemia.	From consent date until first documented report, up to 6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Prognostic capabilities of standard-of-care	Prognostic capabilities of standard-of-care (based on medical and family history) versus whole genome sequencing for predicting outcomes and management in monogenic and polygenic familial hypercholesterolemia.	Baseline to End of Study, up to 12 months
Resources Implementation for WGS in a clinical setting	Assessed by documenting resources necessary for each phase, including execution of WGS, reporting of results, and overall evaluation,	Baseline to End of Study, up to 12 months
Participant characteristics	Age, sociodemographic, personal and family history	Baseline
Change in Perceived Utility	Assessed using novel participant surveys via questions including: attitudes towards DNA testing and results, understanding of results, change in expectations, confidence, concerns.	Baseline, post-disclosure of results (approximately 2-3 months after enrollment), 6 months post-enrollment
Changes in Health Care Utilization	Assessed by reviewing medical records comparing number of services and procedures received related to the diagnosis.	Baseline to End of Study, up to 12 months
Clinician Attitudes About WGS	A self-built survey was created to assess physicians' perspective and attitude toward WGS	Baseline

Collaborators and Investigators

• Sponsor: Abu Dhabi Health Services Company
• Collaborators: Predictiv Care, Inc.
• Investigators: Principal Investigator: Abdulmajeed BS Alzubaidi, MD, Abu Dhabi Health Services Co. -SEHA; Study Director: Erik J Koornneef, PHD, Abu Dhabi Health Services Co. -SEHA; Study Director: Mhy-Lanie Adduru, MD, Predictiv Care, Inc.; Study Chair: Salah Eldin HM Hu, MD, Abu Dhabi Health Services Co. -SEHA

Publications and helpful links

General Publications

• Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005 Nov;15(9):1277-88. doi: 10.1177/1049732305276687.
• Wang J, Dron JS, Ban MR, Robinson JF, McIntyre AD, Alazzam M, Zhao PJ, Dilliott AA, Cao H, Huff MW, Rhainds D, Low-Kam C, Dube MP, Lettre G, Tardif JC, Hegele RA. Polygenic Versus Monogenic Causes of Hypercholesterolemia Ascertained Clinically. Arterioscler Thromb Vasc Biol. 2016 Dec;36(12):2439-2445. doi: 10.1161/ATVBAHA.116.308027. Epub 2016 Oct 20.
• Futema M, Bourbon M, Williams M, Humphries SE. Clinical utility of the polygenic LDL-C SNP score in familial hypercholesterolemia. Atherosclerosis. 2018 Oct;277:457-463. doi: 10.1016/j.atherosclerosis.2018.06.006.
• Talmud PJ, Shah S, Whittall R, Futema M, Howard P, Cooper JA, Harrison SC, Li K, Drenos F, Karpe F, Neil HA, Descamps OS, Langenberg C, Lench N, Kivimaki M, Whittaker J, Hingorani AD, Kumari M, Humphries SE. Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study. Lancet. 2013 Apr 13;381(9874):1293-301. doi: 10.1016/S0140-6736(12)62127-8. Epub 2013 Feb 22.
• Rimbert A, Daggag H, Lansberg P, Buckley A, Viel M, Kanninga R, Johansson L, Dullaart RPF, Sinke R, Al Tikriti A, Kuivenhoven JA, Barakat MT. Low Detection Rates of Genetic FH in Cohort of Patients With Severe Hypercholesterolemia in the United Arabic Emirates. Front Genet. 2022 Jan 3;12:809256. doi: 10.3389/fgene.2021.809256. eCollection 2021.
• Bamimore MA, Zaid A, Banerjee Y, Al-Sarraf A, Abifadel M, Seidah NG, Al-Waili K, Al-Rasadi K, Awan Z. Familial hypercholesterolemia mutations in the Middle Eastern and North African region: a need for a national registry. J Clin Lipidol. 2015 Mar-Apr;9(2):187-94. doi: 10.1016/j.jacl.2014.11.008. Epub 2014 Nov 29.

Helpful Links

• The Human Genome Project Completion: Frequently Asked Questions.
• Catalog of Published Genome-Wide Association Studies.
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• The West Midland Familial Hypercholesterolaemia (FH) screening programme: Evaluating the utility of the 12 SNP polygenic risk score (PRS) across ethnic groupings

Study record dates

Study Major Dates

• Study Start (Actual): July 29, 2024
• Primary Completion (Estimated): December 15, 2025
• Study Completion (Estimated): July 15, 2026

Study Registration Dates

• First Submitted: June 28, 2024
• First Submitted That Met QC Criteria: July 30, 2024
• First Posted (Actual): August 2, 2024

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: March 24, 2025
• Last Verified: March 1, 2025

More Information

Terms related to this study

• Keywords: Randomized Controlled Trial; Pharmacogenomics; Precision Medicine; Familial Hypercholesterolemia; LDH; Whole Genome Sequencing; Genomic Medicine; Digital Twins; Management of Hypercholesterolemia; Emirati; Sanger Sequencing; Predictiv Care
• Additional Relevant MeSH Terms: Metabolism, Inborn Errors; Genetic Diseases, Inborn; Metabolic Diseases; Hyperlipidemias; Dyslipidemias; Lipid Metabolism Disorders; Lipid Metabolism, Inborn Errors; Hyperlipoproteinemias; Hypercholesterolemia; Hyperlipoproteinemia Type II; Hyperlipoproteinemia Type III
• Other Study ID Numbers: WGS_DT_2023; DOH/CVDC/2023/926 (Other Grant/Funding Number: Abu Dhabi Department of Health (DOH))

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Data requests can be submitted 9 months after article publication, and the data will be made accessible for up to 12 months. Extensions will be considered on a case-by-case basis.
• IPD Sharing Time Frame: 9-12 months
• IPD Sharing Access Criteria: Qualified researchers engaged in independent scientific research can request access to trial IPD, which will be provided following the review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA). For more information or to submit a request, please contact mhy-lanie@predictivcare.com.
• IPD Sharing Supporting Information Type: SAP; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No