Integrating Whole Genome Sequencing and Digital Twins Into the Management of Hypercholesterolemia in Emiratis
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Whole Genome Sequencing.
- Who it may be relevant to
- Registry conditions: Hypercholesterolemia, Autosomal Dominant, Hypercholesterolemia, Autosomal Recessive, Familial Combined Hypercholesterolemia. Basic parameters: 18 years — 55 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United Arab Emirates
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
A Randomized Trial of Integrating Whole Genome Sequencing and Digital Twins Into the Management of Hypercholesterolemia in Emiratis
Overview
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.
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.
Interventions
- 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 incl
Primary outcome measures
- Diagnostic capabilities [Time frame: From consent date until first documented report, up to 6 months]
Secondary outcome measures (6)
- Prognostic capabilities of standard-of-care [Time frame: Baseline to End of Study, up to 12 months]
- Resources Implementation for WGS in a clinical setting [Time frame: Baseline to End of Study, up to 12 months]
- Participant characteristics [Time frame: Baseline]
- Change in Perceived Utility [Time frame: Baseline, post-disclosure of results (approximately 2-3 months after enrollment), 6 months post-enrollment]
- Changes in Health Care Utilization [Time frame: Baseline to End of Study, up to 12 months]
- Clinician Attitudes About WGS [Time frame: Baseline]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Triple blind
- Primary purpose
- Diagnostic
Study locations
United Arab Emirates · 1 center
- Abu Dhabi Health Research Center — Abu Dhabi
Publications
- Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005 Nov;15(9):1277-88. doi: 10.1177/1049732305276687. PMID 16204405
- 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. PMID 27765764
- 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. PMID 30270085
- 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):1 PMID 23433573
- 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. PMID 35047021
- 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. PMID 25911074
Identifiers
NCT: NCT06535542 · WGS_DT_2023 · DOH/CVDC/2023/926