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| ID | Type | Description | Link |
|---|---|---|---|
| DOH/CVDC/2023/926 | Other Grant/Funding Number | Abu Dhabi Department of Health (DOH) |
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| Name | Class |
|---|---|
| Predictiv Care, Inc. | INDUSTRY |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| WGS + Digital Twin Group | Experimental | 20 participants who are randomized to have whole-genome sequencing performed on their sample and given access to Predictivâ„¢ Digital Twin. These participants will meet with a genetic counselor for results disclosure and training to access the Predictivâ„¢ Digital Twin platform. |
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| Standard of Care Group | No Intervention | 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 Predictivâ„¢ Digital Twin results as part of this study. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Whole Genome Sequencing | Genetic | Participants in this arm will have their blood sample analyzed by whole-genome sequencing (WGS) and will be given access to Predictivâ„¢ 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. |
| 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 |
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Alina Naeem, MBBS | Contact | +97124102534 | alnaeem@seha.ae | |
| Mhy-Lanie Adduru, MD | Contact | +14088311991 | mhy-lanie@predictivcare.com |
| Name | Affiliation | Role |
|---|---|---|
| Abdulmajeed BS Alzubaidi, MD | Abu Dhabi Health Services Co. -SEHA | Principal Investigator |
| Erik J Koornneef, PHD | Abu Dhabi Health Services Co. -SEHA | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Abu Dhabi Health Research Center | Recruiting | Abu Dhabi | Abu Dhabi Emirate | United Arab Emirates |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 16204405 | Background | Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005 Nov;15(9):1277-88. doi: 10.1177/1049732305276687. | |
| 27765764 | Background | 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. |
| Label | URL |
|---|---|
| The Human Genome Project Completion: Frequently Asked Questions. | View source |
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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.
9-12 months
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.
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A randomized controlled clinical trial of whole-genome sequencing.
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Investigative site personnel will obtain the subject's identification number and study treatment assignment from the randomizer. Participants and all personnel directly involved in the study conduct will be blinded to the arm assignment until 2-3 months after enrollment when the whole-genome sequencing (WGS) report is generated.
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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 |
| Mhy-Lanie Adduru, MD |
| Predictiv Care, Inc. |
| Study Director |
| Salah Eldin HM Hu, MD | Abu Dhabi Health Services Co. -SEHA | Study Chair |
| 30270085 | Background | 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. |
| 23433573 | Background | 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. |
| 35047021 | Background | 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. |
| 25911074 | Background | 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. |
| Catalog of Published Genome-Wide Association Studies. | View source |
| Checklists for improving rigour in qualitative research: a case of the tail wagging the dog? | View source |
| The West Midland Familial Hypercholesterolaemia (FH) screening programme: Evaluating the utility of the 12 SNP polygenic risk score (PRS) across ethnic groupings | View source |
| ID | Term |
|---|---|
| D006938 | Hyperlipoproteinemia Type II |
| D006952 | Hyperlipoproteinemia Type III |
| ID | Term |
|---|---|
| D008052 | Lipid Metabolism, Inborn Errors |
| D008661 | Metabolism, Inborn Errors |
| D030342 | Genetic Diseases, Inborn |
| D009358 | Congenital, Hereditary, and Neonatal Diseases and Abnormalities |
| D006951 | Hyperlipoproteinemias |
| D006949 | Hyperlipidemias |
| D050171 | Dyslipidemias |
| D052439 | Lipid Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D000073336 | Whole Genome Sequencing |
| ID | Term |
|---|---|
| D017422 | Sequence Analysis, DNA |
| D017421 | Sequence Analysis |
| D005821 | Genetic Techniques |
| D008919 | Investigative Techniques |
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