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Innovation 'Elevator Pitch':
Heart DNA is a genetic testing kit for patients at increased risk of developing atrial fibrillation and other cardiovascular diseases, the results are reviewed and assessed by a consultant who is well informed about the patient’s medical history.
Overview of Innovation:
“Heart DNA” is a genetic testing service for patients at increased risk of developing cardiovascular diseases and for cardiologists and genetic counseling officers/geneticists who would want to work with us in delivering this service to the public.

We are partnering with healthcare professionals who will review (online) the genotyping reports coming from our well established partner lab and will be giving their health assessment based on both: the patient’s health profile/medical record, which our users will be asked to fill in early on our website, and on the genetic predispositions that may be found in the patients DNA. In esssence, our consultants will be able to give an informed screening assessment that covers: the detection of inherited conditions and an assessment to the patients’ response to certain drugs that may well be administered to treat CVDs.

Heart DNA is a simple saliva-based test that is supported by scientifically validated research and an extensive amount of studies. Heart DNA analyses the patient’s unique genetic markers, which influence a broad range of heart-related conditions, our gene panel list consistc of 96 markers that cover: Atrial Fibrillation, Coronary Artery Disease, Myocardial Infraction, Cholesterol levels, and risks for hypertension. It can also help identify a patient’s propensity for increased risk towards certain heart medications, eight classes of drugs that affect the cardiovascular system are examined; anti-platelets, anti-coagulants, statins, stimulants, beta-blockers, ACE inhibitors, calcium channel blockers and hormone therapies.

Our test provides information that allows Doctors to;
1. Monitor a patient’s specific health conditions thoroughly.
2. Prescribe a more optimal medication and dosage for a patient.
3. Suggest early lifestyle and diet interventions to help combat and prevent certain heart conditions.

Overall, the aim is to enable doctors and patients to bridge the gap in genetic information that has proved over an extensive amount of studies and research to be pivotal in the design of better prevention and treatments regimens. Our focus is to cause a change in the architecture of complex care routines that would address the challenges of working at scale, and which can capitalize on the associated opportunities that we will enable by striking business partnerships with medical consultants to create and deliver a distinctive competitive advantage over all competing genetic testing companies. 
Stage of Development:
Trial stage - Trial stage to prove that the idea actually works as intended
Comments10
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Comments

From Yassir Javaid, GP Advisor to WM AHSN AF Advisory Group
I find Q lifetime risk and JBS 3 even more impactful tools, for patients and in particular getting younger patients to “buy in” to the value of lifestyle changes to improve their “event free survival”. Q-risk 2 can result in under perception of true risk in young patients with a full house of CV risk factors purely because it looks at risk over only a 10 year period. 
I completely agree with you on that Qrisk and JBS 3 are quite impactful tools, we are not here to subsidies their existence, instead we are going to make the self-reported data ready for you to use for scoring purposes.

The questionnaire we are implementing will gather all the required information for a cardiac health assessment (age, sex, ethnicity, BMI score, previous episodes of CVD related events, diabetes, Rheumatoid arthritis, Chronic kidney disease, family history, smoking and exercising habits) along with a description of any symptoms and/or medications that the patient has been taking, all this information will be ready for review upon the first face to face meeting with the patient.
 
In addition, you would have a personalized report (reviewed by our in-house geneticist) on the patient’s genetic risk factors to develop certain types of CVDs, as well as the associated risks in drug response to Warfarin, Clopidogrel metabolism, Simvastatins, and other classes of drugs; assisting you in your clinical decision, and keeping drug prescription in accordance with the FDA/MHRA/NICE guidelines for genetic testing. And that’s something no risk assessment application can provide.
 
Moreover, if we were to consider the younger generation perception of the value of genetic risk factors, we are certainly at the “quantified self” era, where genetic testing is a booming market and the younger generation are more inclined to learn and know more about themselves than the older geenration, as it represents a novel way of approaching healthcare and providing a complete view of their health.

​We are not advocating for the replacement of what is working but we are optimizing the process for obtaining the relevant data needed to personalise the healthcare of cardiac patients, while cutting the costs down to the NHS; making its service sustainable on the long run at a pioneering level and efficient in terms of costing and turnaround time.
 
From Tom Marshall - Institute of Applied Health Research, (Birmingham)

It is hard to see what the purpose of this Heart DNA test is. A randomised controlled trial investigated the effects of either lifestyle advice alone, lifestyle advice in combination with a genetic risk of diabetes and lifestyle advice in combination with phenotypic risk of diabetes (based on known risk factors). Providing genetic risk had no effect on objectively measured physical activity or several secondary outcomes (self-reported diet, self-reported weight, worry, anxiety, and perceived risk). A similar study by the same researchers is about to report the effects of communicating CVD risk (genetic and phenotypic) alongside lifestyle advice compared to lifestyle advice alone. However initial findings from the qualitative part to this study are that providing risk information (risk scores) does not generally generate concerns about CHD risk and but where it does, the concept of 'heart age' seems to work better in communicating a message of sub-optimal lifestyle. However intentions to and attempts to make lifestyle changes were prompted by the web-based lifestyle advice and not related to information about risk. In short, we have better ways of estimating CVD risk than using DNA tests. QRisk is available online https://qrisk.org/2016/ but even asking someone their age and sex provides a better estimate of CVD risk in the next 10 years than any genetic profile. Providing risk estimates is unlikely to have any beneficial effect on patient behaviour over and above providing lifestyle advice.
 
Ref:
https://www.ncbi.nlm.nih.gov/pubmed/27898672
https://www.ncbi.nlm.nih.gov/pubmed/27914472
I believe RCTs are not applicable to implement in this field of educational studies. There are so many dependent variables that were outside the control of the researchers, such as: the mean of communicating the genetic data, the level of literacy in this filed before imposing the intervention on their cognitive judgment/behavior, the prior knowledge of the individuals being studied and that alone could have affected their responses, and many more... Thus, making the findings of these two studies invalid for giving an evaluation to the potential of genetic testing to induce a behavioral change.  An observational study would have resulted in more reliable data.
 
As far as Heart DNA test is concerned, we see that an easy to comprehend website, like the one we are building (www.rightangled.co.uk), can communicate these risk factors to the patient in an easy to follow, yet in a resourceful manner to learn from. We do not guarantee that patients will quit smoking or start exercising after learning about their genetic risk factors, but we are sure that they will be more informed when the time is ready for them to make that decision on their behavioral change. 
Please can the author of the Meridian submission add in the publication details of the validated research that they cite - for specific cardiovascular condition eg AF; as the tone of the final paragraph of the submission is for a proof of concept, and yet the validated research suggests that  there is already evidence of benefit.
Needs more detail on patient selection criteria; and how a genetic test compares with an opportunistic feel of the pulse rate. Is the genetic test to be focused on selected citizens/patients or opportunistic?
What is the likely specificity/sensitivity of the proposed test for eg AF; and what are the likely unintended consequences (eg false positive or false negative)?
But overall genetic testing is likely to be key in any prevention programme in the future - so worth the authors developing a more defined submission
Many thanks for your comment Ruth,

Below you can view a list of AF related research that we have based our AF marker selection upon, ofcours the list covering the remaining markers is too long and can't be listed here, but here are the ones relevant to AF:

Alonso A., Agarwal S. K., et al (2010) Incidence of atrial fibrillation in whites and African-Americans: the Atherosclerosis Risk in Communities (ARIC) Study American Heart Journal 158(1):111-7 Availiblehttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2720573/
 
Chen F, Yang Y, Zhang R, Zhang S, Dong Y, Yin X, Chang D, Yang Z, Wang K, Gao L, Xia Y.. (2016). Polymorphism rs2200733 at chromosome 4q25 is associated with atrial fibrillation recurrence after radiofrequency catheter ablation in the Chinese Han population.. The American Journal of translational research. 8 (2), 688-697. Availible: https://www.ncbi.nlm.nih.gov/pubmed/27158361
 
Daniel F. Gudbjartsson, David O. Arnar2, Anna Helgadottir, Solveig Gretarsdottir, Hilma Holm. (2007). Variants conferring risk of atrial fibrillation on chromosome 4q25. Nature. 448 (1), 353-357. Available:http://www.nature.com/nature/journal/v448/n7151/full/nature06007.html
 
Gretarsdottir S, Thorleifsson G, Manolescu A, Styrkarsdottir U, Helgadottir A, Gschwendtner A. (2008). Risk variants for atrial fibrillation on chromosome 4q25 associate with ischemic stroke.. Annals of Neurology. 64 (4), 402-409.
Avaible: https://www.ncbi.nlm.nih.gov/pubmed/18991354?dopt=Abstract
 
Gudbjartsson DF, Arnar DO, Helgadottir A, Gretarsdottir S, Holm H. (2007). Variants conferring risk of atrial fibrillation on chromosome 4q25.. Nature. 448 (7151), 353-357. Availible: https://www.ncbi.nlm.nih.gov/pubmed/17603472
 
 

Kääb S, Darbar D, van Noord C, Dupuis J, Pfeufer A, Newton-Cheh C, Schnabel R, Makino S, Sinner MF, Kannankeril PJ. (2009). Large scale replication and meta-analysis of variants on chromosome 4q25 associated with atrial fibrillation.. European Heart Journal. 30 (7), 813-819. Available: https://www.ncbi.nlm.nih.gov/pubmed/19141561?dopt=Abstract
 
Lee KT, Yeh HY, Tung CP, Chu CS, Cheng KH, Tsai WC, Lu YH, Chang JG, Sheu SH, Lai WT.. (2010). Association of RS2200733 but not RS10033464 on 4q25 with atrial fibrillation based on the recessive model in a Taiwanese population.. Cardiology. 116 (3), 151-156.
Availible: https://www.ncbi.nlm.nih.gov/pubmed/20606429?dopt=Abstract
 
Lubitz S. A., Sinner M.F., et al (2010) Independent susceptibility markers for atrial fibrillation on chromosome 4q25 Circulation 122(10):976-84. Available at: http://circ.ahajournals.org/content/122/10/976.long#sec-1
 
Shen AY1, Contreras R, Sobnosky S, Shah AI, Ichiuji AM, Jorgensen MB, Brar SS, Chen W.. (2010). Racial/ethnic differences in the prevalence of atrial fibrillation among older adults--a cross-sectional study.. Journal of the National medical association. 102 (10), 906-913.Availible: https://www.ncbi.nlm.nih.gov/pubmed/21053705
 
Smith JG, Almgren P, Engström G, Hedblad B, Platonov PG, Newton-Cheh C, Melander O.. (2012). Genetic polymorphisms for estimating risk of atrial fibrillation: a literature-based meta-analysis.. Journal of International Medicine. 272 (6), 573-582. Availible: https://www.ncbi.nlm.nih.gov/pubmed/22690879
 
Viviani Anselmi C, Novelli V, Roncarati R, Malovini A, Bellazzi R, Bronzini R, Marchese G, Condorelli G, Montenero AS, Puca AA.. (2008). Association of rs2200733 at 4q25 with atrial flutter/fibrillation diseases in an Italian population.. Heart. 94 (11), 1394-1396. Availible: https://www.ncbi.nlm.nih.gov/pubmed/18931155
 
Our gene panel list consists of 96 SNPs that cover: Coronary artery disease, Myocardial Infraction, cholesterol levels, and risks for hypertension and atrial fibrillation. It can also help identify a patient’s propensity for increased risk of certain heart medications, eight classes of drugs that affect the cardiovascular system are examined; anti-platelets, anti-coagulants, statins, stimulants, beta-blockers, ACE inhibitors, calcium channel blockers and hormone therapies.
 
These markers will be assayed through a genotyping technology that utilises competitive allele-specific PCR, which enables highly accurate bi-allelic scoring of SNPs (>99.8% accurate) and InDels (Insertions and Deletions) at specific loci across a wide range of genomic DNA samples (industry leading SNP & InDel assay conversion rate >90%).
More refs on pharmacogenetic profiling:

Brixner, D., Biltaji, E., Bress, A., Unni, S., Ye, X., Mamiya, T., … Biskupiak, J. (2016). The effect of pharmacogenetic profiling with a clinical decision support tool on healthcare resource utilization and estimated costs in the elderly exposed to polypharmacy. Journal of Medical Economics, 19(3), 213–228. https://doi.org/10.3111/13696998.2015.1110160

Caglayan, A. O. (2010). Different aspects of atrial fibrillation genetics. Interactive CardioVascular and Thoracic Surgery, 11(6), 779–783. https://doi.org/10.1510/icvts.2010.245910

Caudle, K. E., Gammal, R. S., Whirl-Carrillo, M., Hoffman, J. M., Relling, M. V., & Klein, T. E. (2016). Evidence and resources to implement pharmacogenetic knowledge for precision medicine. American Journal of Health-System Pharmacy, 73(23), 1977–1985. https://doi.org/10.2146/ajhp150977

Marin-Leblanc, M., Perreault, S., Bahroun, I., Lapointe, M., Mongrain, I., Provost, S., … Dubé, M.-P. (2012). Validation of warfarin pharmacogenetic algorithms in clinical practice. Pharmacogenomics, 13(1), 21–29. https://doi.org/10.2217/pgs.11.120

Roden, D. M. (2016). Cardiovascular pharmacogenomics: current status and future directions. Journal of Human Genetics, 61(1), 79–85. https://doi.org/10.1038/jhg.2015.78

Tsai, C.-T., Chang, S.-N., Chang, S.-H., Lee, J.-K., Lin, L.-Y., Wu, C.-K., … Lin, J.-L. (2014). Renin–angiotensin system gene polymorphisms predict the risk of stroke in patients with atrial fibrillation: A 10-year prospective follow-up study. Heart Rhythm, 11(8), 1384–1390. https://doi.org/10.1016/j.hrthm.2014.04.014

Verhoef, T. I., Redekop, W. K., de Boer, A., Maitland-van der Zee, A. H., & EU-PACT group. (2015). Economic evaluation of a pharmacogenetic dosing algorithm for coumarin anticoagulants in The Netherlands. Pharmacogenomics, 16(2), 101–114. https://doi.org/10.2217/pgs.14.149


 
In terms of patient’s selection, I see that being rolled out in a systematic and structured manner, as we can use the generated data to draw family tress within a robust referral system that can result in a more impactful CVD prevention program.
 
First stage (Detection) - We can have the test focused on high risk individuals; 2 case scenarios:
  1. New patients, upon their initial phone call a criteria based on (sex, age and ethnicity) could be applied to offer the test and have it sent to the patient 2 weeks ahead of his/her appointment.
  2. Existing patients who have already been assessed and have scored high in their cardiac risk assessment, the test can be offered as a starting point to optimize their drug therapy.
 
Second stage (Prevention) - our program could then be channeled to 1st degree relatives of patients who their screening analysis showed a genetic mutation affecting their cardiac health. These relatives will then be filtered based on information derived from the original patient, whom we may call “patient zero”– this will allow a CVD prevention criteria targeting subpopulation candidates that take into consideration their ethnicity, sex, age and smoking/exercising habits.
 
A referral system that is patient centered will be critical to maximize the efficacy of our program.  And by that we can simply detect, prevent and perfect. 
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