Cardiology Plus

: 2019  |  Volume : 4  |  Issue : 2  |  Page : 43--46

Visual and measured clinical phenotypes: Potential targets for cardiovascular prevention

Chunsong Hu1, Tengiz Tkebuchava2,  
1 Department of Cardiovascular Medicine, Jiangxi Academy of Medical Science, Hospital of Nanchang University, Nanchang University, Nanchang, Jiangxi, China
2 Office of the President/CEO, Boston TransTec, LLC, Boston, MA, USA

Correspondence Address:
Chunsong Hu
Department of Cardiovascular Medicine, Jiangxi Academy of Medical Science, Hospital of Nanchang University, Nanchang University, No. 461 Bayi Ave, Nanchang 330006, Jiangxi


This article discusses and briefly reviews several visual and measured clinical phenotypes, which include height, birth weight or preterm birth body mass index, index finger to ring finger distance ratio (2D: 4D), earlobe creases, hair graying or whitening, and xanthoma. As modifiable risk factors and non-modifiable clinical phenotypes (NMCPs), these factors are potential targets for cardiovascular prevention in the new era of precision medicine. A novel score method based on modifiable risk factors and NMCPs can help for more precise diagnosis and prevention of cardiovascular disease.

How to cite this article:
Hu C, Tkebuchava T. Visual and measured clinical phenotypes: Potential targets for cardiovascular prevention.Cardiol Plus 2019;4:43-46

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Hu C, Tkebuchava T. Visual and measured clinical phenotypes: Potential targets for cardiovascular prevention. Cardiol Plus [serial online] 2019 [cited 2020 May 27 ];4:43-46
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Cardiovascular diseases (CVD) are prevalent and challenging illnesses globally, and their related economic and social burdens are extremely high. Thus, it is extremely important to pursue cardiovascular prevention (CVP). Currently, CVP aims to control two groups of risk factors: those that are modifiable and those that are nonmodifiable. The former covers lifestyle, biochemical and physiological indexes, such as heart rate, blood pressure, lipid, serum sugar, and other biomarkers; the latter includes gender, blood types, ethnic groups, and family history. A study found ten potentially modifiable risk factors are associated with about 90% of stroke cases in different regions of the world.[1] However, there is not enough attention paid to nonmodifiable clinical phenotypes (NMCPs). In fact, increasing evidence shows that there is an association between NMCPs and susceptibility to CVD.

 Clinical Phenotypes and Cvp

Conventionally, genotype decides phenotype, but both genotypes and monogenic or polygenic human phenotypes may link to CVD during early or later life. For example, a recent study found Sirtuin 1 regulates cardiac electrical activity by deacetylating the cardiac sodium channel gene, which is associated with various arrhythmia phenotypes.[2] Distinct NMCPs have resulted from multilocus genomic variation, which affects different organ systems.[3] An early study found that SCN5A mutations are associated with susceptibility to early-onset dilated cardiomyopathy, atrial fibrillation (AF), and heart failure.[4] A multicenter registry study found that the genotype-phenotype correlation of SCN5A mutations in Brugada syndrome showed more arrhythmia and higher risk for cardiac events.[5]

It is well known that the height is a highly heritable, classic polygenic NMCP. So far, there are 83 height-associated variants which were identified through genome-wide association studies,[6] and some rare and low-frequency variants may alter adult height, which is highly associated with risk of CVD, including coronary artery disease (CAD), AF, and venous thromboembolisms.[7] Shorter height in adulthood is linked to an increased risk of CAD due to the association between shorter height and an adverse lipid profile, which can lead to the development of atherosclerosis.[8] Adult height is also a marker of altered cardiac conduction.[9] For example, one height-associated nonsynonymous single nucleotide polymorphisms (rs1046934) is independently associated with AF.[10]

Birth weight was associated with 60 loci, and approximately 15% of the variance was captured by assays of fetal genetic variation.[11] There are strong inverse genetic correlations between birth weight and systolic blood pressure or CAD. Therefore, both height and birth weight could be used as a marker for prediction and prevention of CAD as assessed by coronary angiography. One study showed that preterm birth may be a new risk factor or a phenotype for early heart failure, probably due to lower birth weight.[12] There is an association between high index finger to ring finger length ratio (2D: 4D) and CAD in both hands in Chinese men,[13] but there were no significant differences in women.

Genetic association analyses show that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause.[14] Obesity is a classic phenotype of CVD, and DNA methylation may predict future development of obesity-related CVD, diabetes, cancer, and CVD, diabetes and cancers strips.[15] Due to a potential proatherogenic role, ADAMTS-7 is associated with a high-risk plaque phenotype in human carotid lesions.[16] The presence of premature hair whitening is independently related to carotid artery intima-media thickness,[17] it may be useful in identifying individuals with an increased risk of CVD.

Earlobe creases (Frank's sign) as a risk factor and easily identifiable phenotype is significantly and independently associated with CVD,[18] such as hypertension and CAD, probably due to vascular inflammation and oxidative stress. Resistant hypertension is relevant to age; younger individuals have distinct phenotypes when compared with elderly.[19] As a positive phenotype, xanthomas links to genetic familial hypercholesterolemia diagnosis and CAD risk.[20],[21] Phenotypic factors influencing the variation in response to circulating cholesterol level to personalized dietary advice, and may help to develop precision nutrition.[22] These studies help to find and understand visual and measured phenotypes as potential targets for CVP [Figure 1].{Figure 1}

As potential risk factors for CVD and stroke, NMCPs could be changed in the future by revision of individual's genotypes with a structure or gene-editing technology, for example, CRISPR/cas9 or Cpf1. Some phenotypes are highly associated with CVD; others like the unique lipoprotein phenotype are associated with healthy aging and exceptional longevity. For example, the variant distribution of NKX2-5, GATA4, and TBX5 genes is tightly associated with particular congenital heart disease subtypes.[23] Thus, gene-linked NMCPs and mutation detection can help guide treatment and prevention of CVD[5],[24] and cancer,[25],[26] they are potential targets for CVP in the era of precision medicine.


With the development of advanced instruments (e.g., single-particle cryo-electron microscopy)[27] and new technologies (e.g., single-cell sequencing),[28],[29] it is possible to determine early cell or gene structure and mutation and linked NMCPs, function and diseases, so that we can easily realize our expectation in CVP by SEEDi1.0–3.0 technologies,[30],[31],[32],[33] especially in improving atherosclerotic CVD (ASCVD) prevention through a combination of various new drugs, for example, proprotein convertase subtilisin/kexin 9 inhibitors.[34]

Obesity is an important biomarker and a modifiable phenotype for women and men, even in childhood. There is still no evidence of vascular damage in younger individuals due to physiological adaptation;[35] however, it represents a good opportunity for early prevention of obese cardiovascular risk in adulthood. The left ventricular hypertrophy is a detectable and modifiable target for the prevention of heart failure.[36] There are several inflammatory biomarkers for lower extremity peripheral arterial disease (PAD); however, a genetic marker for PAD has not been identified.[37] The chromosome 4q25 locus associated with AF risk is a detectable but not modifiable biomarker,[38] and will help to determine mechanisms and explore genetic associated new strategy for AF prevention in the future.

Thus, a novel score method based on modifiable risk factors and NMCPs screening for more precise diagnosis and prevention of CVD, which includes C-type hypertension[39] and emotionally induced cardiovascular events,[40] can be developed in the future to enhance rare-variant interpretation and identify distinct genetic causes for common diseases.[41] Simultaneously, enhancing policy prevention or grade-zero prevention[42] and developing novel technologies such as the “polypill” (SEEDi1.5)[43] or other SEEDi1.0–3.0 technologies,[30] will help increase CVP through lifestyle choices that may affect or change the function of genes and NMCPs.[44] Of course, the novel score method will also help to choose statins-based lipid-lowering and percutaneous coronary intervention for ASCVD.[45],[46]


The editors and reviewers are gratefully acknowledged for critical review.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.


1O'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H, et al. Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): A case-control study. Lancet 2016;388:761-75.
2Vikram A, Lewarchik CM, Yoon JY, Naqvi A, Kumar S, Morgan GM, et al. Sirtuin 1 regulates cardiac electrical activity by deacetylating the cardiac sodium channel. Nat Med 2017;23:361-7.
3Posey JE, Harel T, Liu P, Rosenfeld JA, James RA, Coban Akdemir ZH, et al. Resolution of disease phenotypes resulting from multilocus genomic variation. N Engl J Med 2017;376:21-31.
4Olson TM, Michels VV, Ballew JD, Reyna SP, Karst ML, Herron KJ, et al. Sodium channel mutations and susceptibility to heart failure and atrial fibrillation. JAMA 2005;293:447-54.
5Yamagata K, Horie M, Aiba T, Ogawa S, Aizawa Y, Ohe T, et al. Genotype-phenotype correlation of SCN5A mutation for the clinical and electrocardiographic characteristics of probands with Brugada syndrome: A Japanese multicenter registry. Circulation 2017;135:2255-70.
6Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR, Kjaer TR, et al. Rare and low-frequency coding variants alter human adult height. Nature 2017;542:186-90.
7Lai FY, Nath M, Hamby SE, Thompson JR, Nelson CP, Samani NJ, et al. Adult height and risk of 50 diseases: A combined epidemiological and genetic analysis. BMC Med 2018;16:187.
8Nelson CP, Hamby SE, Saleheen D, Hopewell JC, Zeng L, Assimes TL, et al. Genetically determined height and coronary artery disease. N Engl J Med 2015;372:1608-18.
9Kofler T, Thériault S, Bossard M, Aeschbacher S, Bernet S, Krisai P, et al. Relationships of measured and genetically determined height with the cardiac conduction system in healthy adults. Circ Arrhythm Electrophysiol 2017;10. pii: e004735.
10Rosenberg MA, Kaplan RC, Siscovick DS, Psaty BM, Heckbert SR, Newton-Cheh C, et al. Genetic variants related to height and risk of atrial fibrillation: The cardiovascular health study. Am J Epidemiol 2014;180:215-22.
11Horikoshi M, Beaumont RN, Day FR, Warrington NM, Kooijman MN, Fernandez-Tajes J, et al. Genome-wide associations for birth weight and correlations with adult disease. Nature 2016;538:248-52.
12Carr H, Cnattingius S, Granath F, Ludvigsson JF, Edstedt Bonamy AK. Preterm birth and risk of heart failure up to early adulthood. J Am Coll Cardiol 2017;69:2634-42.
13Wu XL, Yang DY, Chai WH, Jin ML, Zhou XC, Peng L, et al. The ratio of second to fourth digit length (2D: 4D) and coronary artery disease in a Han Chinese population. Int J Med Sci 2013;10:1584-8.
14Wahl S, Drong A, Lehne B, Loh M, Scott WR, Kunze S, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 2017;541:81-6.
15Hu CS, Wu QH, Hu DY. Cardiovascular, diabetes, and cancer strips: Evidences, mechanisms, and classifications. J Thorac Dis 2014;6:1319-28.
16Bengtsson E, Hultman K, Dunér P, Asciutto G, Almgren P, Orho-Melander M, et al. ADAMTS-7 is associated with a high-risk plaque phenotype in human atherosclerosis. Sci Rep 2017;7:3753.
17Erdoǧan T, Kocaman SA, Çetin M, Durakoǧlugil ME, Uǧurlu Y, Şahin İ, et al. Premature hair whitening is an independent predictor of carotid intima-media thickness in young and middle-aged men. Intern Med 2013;52:29-36.
18Zapata-Wainberg G, Vivancos J. Images in clinical medicine: Bilateral earlobe creases. N Engl J Med 2013;368:e32.
19Ghazi L, Oparil S, Calhoun DA, Lin CP, Dudenbostel T. Distinctive risk factors and phenotype of younger patients with resistant hypertension: Age is relevant. Hypertension 2017;69:827-35.
20Tada H, Kawashiri MA, Nohara A, Inazu A, Mabuchi H, Yamagishi M, et al. Impact of clinical signs and genetic diagnosis of familial hypercholesterolaemia on the prevalence of coronary artery disease in patients with severe hypercholesterolaemia. Eur Heart J 2017;38:1573-9.
21Poonia A, Giridhara P. Xanthomas in familial hypercholesterolemia. N Engl J Med 2017;377:e7.
22Kirwan L, Walsh MC, Celis-Morales C, Marsaux CF, Livingstone KM, Navas-Carretero S, et al. Phenotypic factors influencing the variation in response of circulating cholesterol level to personalized dietary advice in the food4me study. Br J Nutr 2016;116:2011-9.
23Su W, Zhu P, Wang R, Wu Q, Wang M, Zhang X, et al. Congenital heart diseases and their association with the variant distribution features on susceptibility genes. Clin Genet 2017;91:349-54.
24Cao Q, Shen Y, Liu X, Yu X, Yuan P, Wan R, et al. Phenotype and functional analyses in a transgenic mouse model of left ventricular noncompaction caused by a DTNA mutation. Int Heart J 2017;58:939-47.
25Mandelker D, Zhang L, Kemel Y, Stadler ZK, Joseph V, Zehir A, et al. Mutation detection in patients with advanced cancer by universal sequencing of cancer-related genes in tumor and normal DNA vs. guideline-based germline testing. JAMA 2017;318:825-35.
26Bausch B, Schiavi F, Ni Y, Welander J, Patocs A, Ngeow J, et al. Clinical characterization of the pheochromocytoma and paraganglioma susceptibility genes SDHA, TMEM127, MAX, and SDHAF2 for gene-informed prevention. JAMA Oncol 2017;3:1204-12.
27Agafonov DE, Kastner B, Dybkov O, Hofele RV, Liu WT, Urlaub H, et al. Molecular architecture of the human U4/U6.U5 tri-snRNP. Science 2016;351:1416-20.
28Sousa AM, Zhu Y, Raghanti MA, Kitchen RR, Onorati M, Tebbenkamp ATN, et al. Molecular and cellular reorganization of neural circuits in the human lineage. Science 2017;358:1027-32.
29Lodato MA, Rodin RE, Bohrson CL, Coulter ME, Barton AR, Kwon M, et al. Aging and neurodegeneration are associated with increased mutations in single human neurons. Science 2018;359:555-9.
30Hu CS, Tkebuchava T. SEEDi1.0-3.0 strategies for major noncommunicable diseases in China. J Integr Med 2017;15:265-9.
31Hu CS, Wu QH, Hu DY, Tkebuchava T. Novel strategies halt cardiovascular, diabetes, and cancer strips. Chronic Dis Transl Med 2017;3:159-64.
32Hu C. SEEDi: Basic strategies for the primary and secondary prevention of atherosclerotic cardiovascular disease. Zhong Nan Da Xue Xue Bao Yi Xue Ban 2017;42:575-80.
33Hu CS, Tkebuchava T. New “P” in medical model. Chin Med J (Engl) 2016;129:492-3.
34Hess GP, Natarajan P, Faridi KF, Fievitz A, Valsdottir L, Yeh RW, et al. Proprotein convertase subtilisin/Kexin type 9 inhibitor therapy: Payer approvals and rejections, and patient characteristics for successful prescribing. Circulation 2017;136:2210-9.
35Charakida M, Jones A, Falaschetti E, Khan T, Finer N, Sattar N, et al. Childhood obesity and vascular phenotypes: A population study. J Am Coll Cardiol 2012;60:2643-50.
36Seliger SL, de Lemos J, Neeland IJ, Christenson R, Gottdiener J, Drazner MH, et al. Older adults, “Malignant” left ventricular hypertrophy, and associated cardiac-specific biomarker phenotypes to identify the differential risk of new-onset reduced versus preserved ejection fraction heart failure: CHS (Cardiovascular health study). JACC Heart Fail 2015;3:445-55.
37McDermott MM, Lloyd-Jones DM. The role of biomarkers and genetics in peripheral arterial disease. J Am Coll Cardiol 2009;54:1228-37.
38Lubitz SA, Lunetta KL, Lin H, Arking DE, Trompet S, Li G, et al. Novel genetic markers associate with atrial fibrillation risk in Europeans and Japanese. J Am Coll Cardiol 2014;63:1200-10.
39Hu CS, Tkebuchava T, Wu QH, Hu DY. C-type hypertension: An ignored new killer? Cardiol Plus 2017;2:1-3.
40Hu C, Tkebuchava T. Soccer related emotion and stress-induced cardiovascular events. Cardiol Plus 2018;3:66-70.
41Bastarache L, Hughey JJ, Hebbring S, Marlo J, Zhao W, Ho WT, et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 2018;359:1233-9.
42Hu C, Wu Q. Health: A dream from reality to the future. Front Med 2016;10:233-5.
43Hu C. Grants supporting research in China. Eur Heart J 2018;39:2342-4.
44Saleheen D, Zhao W, Young R, Nelson CP, Ho W, Ferguson JF, et al. Loss of cardioprotective effects at the ADAMTS7 locus as a result of gene-smoking interactions. Circulation 2017;135:2336-53.
45Peng D. From intensive statins to intensive lipid lowering: Amplitude of low-density lipoprotein-cholesterol lowering is the core for atherosclerosis cardiovascular disease prevention. Cardiol Plus 2018;3:122-6.
46Junbo Ge on behalf of Chronic Total Occlusion Club China. Strategic roadmap of percutaneous coronary intervention for chronic total occlusions. Cardiol Plus 2018;3:30-7.