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Genomics, Epigenetics, and Precision Medicine in Integrative Preventive Medicine 

Genomics, Epigenetics, and Precision Medicine in Integrative Preventive Medicine
Genomics, Epigenetics, and Precision Medicine in Integrative Preventive Medicine
Integrative Preventive Medicine

Nancy G. Casanova

, Ting Wang

, Eddie T. Chiang

, and Joe G. N. Garcia



We briefly review the use of genomewide screening for early detection, treatment, and prevention and the utility of genome-based biomarkers as a tool for precision medicine and its application to population and integrative preventive medicine.


The holistic approach of integrative preventive medicine (IPM) convenes the integration of proactive prevention with the purpose of prolonging health, preventing chronic diseases, improving life quality, decreasing healthcare expenses, limiting the risk of adverse interactions, and reducing gaps in care. At the core of IPM primary prevention are integrative modalities effective in health promotion, including lifestyle counseling, dietary guidance, stress mitigation techniques, interventions to improve sleep quality, and use of nutriceuticals and herbal supplements. The exact mechanisms by which these modalities influence health are poorly understood; however, there is increasing evidence that these strategies may involve common genomic and epigenetic effects. Integrative preventive medicine is well positioned in modern healthcare to incorporate the vast, rapidly advancing, and increasingly available genomic-related data to benefit individual-level clinical care and to improve population interventions and preventive medicine. The integration of genetic, epigenetic, and precision medicine strategies into IPM approaches has the very real potential to maximize health benefits, minimize harm, and possibly avoid unnecessary healthcare costs.

Leveraging the most advanced scientific evidence is an essential process to understanding complex systems, such as development, homeostasis, and responses to the environment.1 Likewise, understanding the impact of genetics and epigenetics on human health advances our insights into human pathobiology, particularly complex diseases. David Hilbert, the brilliant 20th-century German mathematician, said, “rapid advances come from the development of sharper tools for exploration.” Indeed, a critical consequence of the human genome project was the rapid and continued development of multiple high-throughput technologies including rapid whole-genome sequencing, genomewide association studies (GWAS), ChIP-Seq, RNA-Seq, epigenetics, transcriptomics, and mass spectroscopy-based proteomics. These tools have generated a different vision of genome functionality that has retreated from the notion of a single gene causing a single disease. State-of-the-art healthcare delivery is rapidly incorporating these high-throughput tools to enable accurate risk prediction and therapeutic targeting. Precision medicine and clinical translational medicine are elements of this integrative concept, a concept that enables individualized approaches to health and complex disease.

Precision Medicine

Precision medicine is revolutionizing the manner by which one improves health and alleviates suffering from disease, by considering individual genetic differences as well as differences in lifestyles and environment.2 This visionary approach is built on the premise that treatment decisions should be based on individual genetic variability, taking advantage of already available large-scale genomic, metabolomics, and proteomic databases. The National Institutes of Health (NIH) Precision Medicine Initiative (PMI)3 aims to integrate a national longitudinal research cohort with social, racial/ethnic diverse backgrounds representing the nation demographics. This cohort will provide genetic data, biological samples, and other health information to researchers and translational clinicians.

Genomic Biomarkers of Health and Disease

Biological markers or biomarkers are indicators of normal biological and pathological processes. Measurements such as blood pressure, body mass index, and cholesterol levels have been successfully correlated with metabolic diseases. Disease biomarkers are used to diagnose various phases of disease, monitor severity of disease and responses to therapy, and serve as potential predictors of prognosis and responses to therapy.4 Multiple methodologies have been applied for biomarker detection in biological fluids and tissues (serum, cerebral spinal fluid, bronchoalveolar lavage fluid, etc.) using enzyme-linked immunosorbent assays (ELISA), proteomic analysis, and mass spectrometry.

Molecular biomarkers have been applied in detection, screening, diagnosis, treatment, and monitoring of cancer. These biomarkers can be macromolecules such as proteins or other biomolecules such as messenger RNAs (mRNAs), microRNAs (miRNAs), or other metabolites. Peripheral blood provides easy access for obtaining levels of these biomarkers and for assessment of organs that are ordinarily difficult to access. Multiple biomarkers have been identified from preclinical research, but few have been proven useful in clinical practice. Despite limitations, the use of biomarkers to enhance accurate diagnosis and prediction of disease activity remains a focal point in routine clinical care and preventive medicine. Criteria used to evaluate the value of disease biomarkers include disease-associated specificity, sensitivity, traceability, stability, repeatability, and reliability.4,5 These markers must be detectable in the blood, since the blood is in contact with all organs; however, biomarker validation is complex, often requiring validation in human tissues, with overexpression of targeted candidates correlated with dysfunction of specific organs or tissues.6 Likewise, in order to assess the transition from health to disease, biomarker assessment should occur in a longitudinal manner, with each individual serving as his/her own control for the changing levels of biomarkers in the blood.

Gene expression-based microarrays and RNA sequencing strategies provide opportunities to discover novel disease mechanisms.7 Microarray technology allows the simultaneous measurement of mRNA transcripts for assessment of gene expression across the entire genome providing insight into the overall level of gene activity and protein expression.8 A gene signature is a group of genes derived from a specific tissue or biological fluid, whose combined expression pattern is characteristic of a biological, cellular, or molecular phenotype. The signature is composed of a set of genes whose expression is dysregulated (either increased or decreased expression) compared to normal tissues. Gene expression signatures are potentially powerful tools that can reveal a range of biologically and clinically important characteristics of biological samples9 and are used to differentiate diseases phenotypes, including disease severity.10 For example, sepsis is an important cause of hospitalization and death. Recently the reactive oxygen species (ROS)-associated molecular signatures were assessed as biomarkers to predict survival in sepsis. In silico analyses of gene expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients.11Likewise, we analyzed genomewide gene expression in peripheral blood mononuclear cells (PBMCs) in sarcoidosis patients and identified a gene signature that distinguishes complicated versus uncomplicated sarcoidosis.12,13 This signature revealed a predictive accuracy when classifying sarcoidosis patients from healthy controls in two independent external cohorts.12,13Figure 4.1 provides an example of using gene signature for diagnosis.14 Similarly, PBMC gene expression profiles were compared in patients with either sarcoidosis or sickle cell disease with a goal of identifying those with concomitant pulmonary hypertension, a serious complication of both disorders. Two gene signatures were identified;15,16 however, comparison of both signatures failed to identify overlap between the gene signatures, suggesting that the mechanisms for development of pulmonary hypertension in sarcoidosis may be distinct from sickle cell disease.

Figure 4.1 Example of using a 20-gene signature for the diagnosis of sarcoidosis.14 Identifying gene signatures in sarcoidosis. Principal component analysis on expression values of the 20-gene signature. X-axis: principal component 1 with eigenvalue; Y-axis: principal component 2 with eigenvalue. Left panel: patients with complicated sarcoidosis and healthy controls; middle panel: patients with complicated sarcoidosis, uncomplicated sarcoidosis, and healthy controls; and right panel: patients with complicated sarcoidosis and uncomplicated sarcoidosis. HC: healthy controls; US: patients with uncomplicated sarcoidosis; and CS: patients with complicated sarcoidosis

Figure 4.1 Example of using a 20-gene signature for the diagnosis of sarcoidosis.14 Identifying gene signatures in sarcoidosis. Principal component analysis on expression values of the 20-gene signature. X-axis: principal component 1 with eigenvalue; Y-axis: principal component 2 with eigenvalue. Left panel: patients with complicated sarcoidosis and healthy controls; middle panel: patients with complicated sarcoidosis, uncomplicated sarcoidosis, and healthy controls; and right panel: patients with complicated sarcoidosis and uncomplicated sarcoidosis. HC: healthy controls; US: patients with uncomplicated sarcoidosis; and CS: patients with complicated sarcoidosis


The integration of genome-generated big data has spawned new fields within precision medicine, transforming the traditional clinical therapeutic approach. Pharmacogenomics is defined as the science of determining benefit–risk balance based on race- and ethnic-specific genomic variants of the patient’s germ line and/or diseased tissue.17 The hallmark of pharmacogenomics is to target a specific drug to a precise patient subphenotype.

Single nucleotide polymorphisms (SNPs) are gene variations occurring approximately every 500–1000 base pairs of the genome that serve as biological markers and potentially predict drug responses, susceptibility to certain toxins, or predisposition to disease. As an example, the class of drugs known as the statins comprises HMG-CoA reductase inhibitors commonly used to treat hypercholesterolemia. Statins are well tolerated, but elicit myalgias and creatinine kinase elevation in a percentage of users and, in rare cases, induce rhabdomyolysis. Studies to date indicate that statins induce blood and tissue coenzyme Q-10 (CoQ10) depletion, which may be prevented by supplemental CoQ10.18 Two SNPs in the COQ2 gene, a gene involved in the coenzyme Q (ubiquinone) biosynthetic pathway, have been linked to statin-induced myopathy.19,20 Other SNPs in genes involved in statin pharmacokinetics (SLCO1B1 and OATP1B1) are genetic risk factors for myopathy.20

Another example of the impact of pharmacogenomics is cystic fibrosis (CF), an autosomal recessive condition affecting the lungs and the digestive systems. Although the mutated chloride channel is well known, CF now can be subclassified according to the defective channel characteristics. Ivacaftor is a drug only effective in a subset of CF patients in whom the channel reaches the surface.21 Drug development research is currently taking advantage of genomic signatures to stratify patients for phase III trials. Genomic signatures may also be useful in identifying subjects likely to benefit from adjuvant dietary strategies such as probiotics and prebiotics, which have shown initial promise in improving CF-related chronic inflammation.22

Precision oncology is an area where pharmacogenomics has achieved significant progress due to the now-routine incorporation of molecular testing into clinical care. For example, oncogene-targeted therapies based on tumor-borne mutations have led to clinically validated therapies targeting genes in pathways related to proliferation or apoptosis inhibition.23,24

Epigenetics in Disease Development

Epigenetics is an important mechanism for gene expression during uterine development, childhood, and aging. At the cellular level, epigenetic mechanisms are involved in regulation of cell cycles and DNA repair secondary to carcinogen exposures. Therefore, epigenetics is also viewed as the interface modulator between the genome and the environmental stressors and endogenous factors that may promote tumor development and disease progression.25 Epigenetics controls transcriptional output and, therefore, traits. Correlating epigenomic and transcriptomic information can be highly informative1 in order to corroborate the etiology of many diseases and the influence of elements such as environment, diet, chemicals, drugs and pharmaceutical products.

Epigenetic Mechanisms

Independent modifications to the linear DNA sequence, include DNA methylation, histone acetylation, methylation, phosphorylation, ubiquitination, citrullination, sumoylation, and ADP ribosylation.26 Histone modification influences DNA methylation, thus, gene expression is controlled by activation and repression mechanisms. An example is the effects of decreased dietary folate intake on DNA methylation and biosynthesis. This results in reduced levels of S-adenosylmethionine (SAM) leading to DNA hypomethylation and inappropriate protoconcogene activation, activation of latent transposons, and chromosome rearrangement and instability, commonly seen in colorectal cancer.27 The effects of folate and methionine in DNA methylation are depicted on Figure 4.2.

Figure 4.2 Folate and methionine metabolism effects on DNA methylation. DNMT, DNA methyltransferases; SAH, S-adenosyl homocystein; MS, methionine synthase; SAM, S-adenosyl methionine

Figure 4.2 Folate and methionine metabolism effects on DNA methylation. DNMT, DNA methyltransferases; SAH, S-adenosyl homocystein; MS, methionine synthase; SAM, S-adenosyl methionine

Epigenetic features can control transcriptional output, and DNA methylation and demethylation are the best-characterized epigenetic modifications. Methylation/demethylation of DNA involves the addition or deletion of a methyl group at the 5’ position on the pyrimidine ring of cytosines, creating 5-methylcytosine (5-mC).28

Functionally, the methylation primarily prevents the binding of specific transcription factors to DNA at the gene promoter region, thereby suppressing gene expression,29 although hypermethylation may also induce enhanced expression.30 Additionally, DNA methylation interferes with alternative splicing, thereby generating splicing variants.31 The DNA methyltransferases (DNMT) are responsible for maintenance of DNA methylation32 with four known types of DNMTs: DNMT1, DNMT2, DNMT3a, and DNMT3b, all of which utilize S-adenosylmethionine as the methyl donor.32 (Figure 4.3).

Figure 4.3 Overview of the various epigenetic mechanisms. Epigenetics include the interplay between DNA methylation, histone modification, and RNA-mediated post-transcriptional regulation that alters the generation and stability of transcripts

Figure 4.3 Overview of the various epigenetic mechanisms. Epigenetics include the interplay between DNA methylation, histone modification, and RNA-mediated post-transcriptional regulation that alters the generation and stability of transcripts

Diseases Associated with Alterations in DNA Methylation

The DNA methyltransferase–mediated altered methylation of the genome is associated with increasing age and increased cancer risk.33,34 Hypermethylation of tumor suppressor gene promoter sites may lead to increased carcinogenesis, while oncogene hypomethylation stimulates tumor growth. Therapeutic modification of DNA methylation may contribute to better outcomes in integrative medicine or IPM. For example, one rodent study confirmed that offspring from mothers supplemented with methyl donors were brown in color and lean compared to nonsupplemented mothers who produced yellow, obese offspring, with increased incidence of diabetes and cancer.33

Owing to the relative simplicity of the assay, methylation levels in the long interspersed nucleotide element-1 (LINE-1) have commonly been used as a surrogate measurement of cellular global DNA methylation. LINE-1 hypomethylation is shown to be associated with more chromosomal instability in colorectal cancer.35 The LINE-1 hypomethylation is also associated with poor outcome in several cancer types.36,37,38 Average LINE-1 methylation levels in colorectal tumors decline as tumors progress.39 With regard to IPM, LINE-1 methylation may be a risk factor40 for colorectal cancer, with LINE-1 hypomethylation indicating an aggressive subtype, prevented by adequate folate intake and avoidance of alcohol.41

Another key component of epigenetic regulation of gene expression is histone modification. The DNA is tightly packed into the nucleus as chromatin consisting of 147 base pairs of DNA wrapped around a histone octamer. When DNA transcription occurs, the histones are required to open to allow access to the DNA. Modifications on histone proteins control transcription through phosphorylation, acetylation, sumoylation, methylation, ubiquitylation, prolyl-isomeryzation, and ADP-ribosylation, and these enzymes rely on a number of cofactors and metabolites.42 The most well studied of these modifications is histone acetylation, with increased histone acetylation enhancing active transcription while decreased acetylation tightens histone structures with reduced active transcription.42 Histone acetylation and deacetylation are catalyzed by two groups of enzymes called histone acetyltransferases (HATs) and histone deacetylases (HDACs). Acetyl coenzyme A serves as donor of the acetyl group, which is transferred to lysines of histone tails by HATs.43 There are five groups of HATs and four classes of HDACs, due to structural and activity differences.44 Due to the complexity of histone modifications and number of different enzymes that can occur on histones regulating DNA transcription, substantial research is still required to determine clinical relevance. Nevertheless, the histone acetylation regulation via HDAC implicates metabolic control in human disease.45,46,47

Cigarette smoking is a major environmental hazard associated with lung cancer development. Studies using epigenome-wide association studies (EWASs) have identified 1,450 smoking-associated CpG sites.48,49 Genomewide association studies confirmed associations with smoking for a previously identified CpG site within the KLF6 gene and identified 12 novel sites located in 7 genes: STK32A, TERT, MSH5, ACTA2, GATA3, VTI1A, and CHRNA5 (FDR < 0.05).49 These examples demonstrate the progress in understanding of epigenetics and its relevance to IPM.

Complementary Alternative Medicine Epigenetic Effects

The use of complementary and alternative medicine (CAM) approaches to clinical care is a common practice and includes herbs, dietary treatment, meditation, relaxation, homeopathy, hypnotherapy, aromatherapy, and multivitamins.50 While the combined use of alternative and conventional medicine has been deemed to be beneficial in improving psychological distress and adjustment, the sole use of CAM as an alterative to standard of care in cancer patients carries the potential for treatment delays, increased recurrence, and death.51 As highlighted later, the key gap is the absence of sufficient numbers of clinical trials conducted to assess the efficacy of CAM approaches and any untoward risk in such approaches.

Cancer Chemopreventive Agents

Cancer chemopreventive agents include resveratrol, a phytoalexin found in grapes, berries, and peanuts, which exhibits chemopreventive activity in three different stages: tumor initiation, promotion, and progression.52 Resveratrol acts as a selective estrogen receptor modulator (SERM) and regulates proteins involved in DNA synthesis and cell cycle, such as p53 and Rb/E2F, and cyclins. Cyclin-dependent kinases affect the activity of transcriptional factors involved in proliferation and stress responses, such as NF-kB, AP1, and Egr1.53,54

Epidemiological studies have shown that a soy-rich diet decreases the incidence of some human cancers, including breast and prostate cancers. Genistein, the active component found in soy, exerts its cancer preventive effects by targeting various pathways relevant in the development of cancer, and may affect cancer progression.55,56 Curcumin, a compound found in the Asian spice known as turmeric, exhibits anticancer properties via acetylation of lysine residues that regulates NF-κ‎B, including transcriptional activation, DNA binding affinity, I-κ‎Bα‎ degradation, and NF-kB nuclear translocation.57,58 Curcumin-treated cells demonstrate inhibition of epigenetic regulators such as the histone deacetylases: HDAC1, HDAC3, and p300/, which decreases NF-κ‎B and Notch1 activity with significant inhibition of cell proliferation. The effect of curcumin on HDACs and HATs was partially due to increased proteasomal degradation.57

Organosulfur compounds present in allium vegetables, such as garlic, chives, and leeks, are used to improve immunity and cardiovascular health, responses to radiation, cancer protection, and as hypoglycemic agents in traditional medicine.55 Risk of stomach and colon cancers is significantly reduced if allium vegetables are consumed regularly,59 attributed to organosulfur compounds such as diallyl sulfide [DAS], diallyl disulfide [DADS], and diallyl trisulfide [DATS] that induce cell cycle arrest and apoptosis and inhibit cancer growth, angiogenesis, and metastasis.60 The epigenetic modulation of some phytochemicals is summarized in Table 4.1.

Table 4.1 Dietary Agents as Epigenetics Modulators



Epigenetic Effect

Disease Correlation



Grapes, peanuts, apples, some berries

Histone modification—decrease acetylation of histone H3K9 by inducing SIRT1 expression, DNMT down-regulation, miRNA modulation

Tumor suppression, antimetastasis




DNMT1 inhibition, Histone modulation—HDAC1, HDAC3, and NF-kB decreased activity; miRNA expression modulation

Cancer protection



Green, black tea

DNMT1 inhibition, folate cycle disruption and increased SAM level, modify expression of miRNAs

Cancer protection



Broccoli, sprouts, kale, cabbage

DNMT1 down regulation, Histone modulation—increased acetylation H3 and H4 and HDAC decreased activity

Tumor suppression, cardiovascular protection




Histone acetylation induction—H3 and H4 increased binding on promoter of p21

Cancer, cardiovascular protection




DNMT inhibition, cell growth inhibition

Cancer protection


Similarly, high consumption of fish oil or ω‎-3 PUFAs, including docosahexaenoic acid (DHA), reduces the risk of colon, pancreatic, and endometrial cancers by inducing human cancer cell apoptosis without limited toxicity. In addition, DHA enhanced the efficacy of anticancer drugs by increasing drug uptake and suppressing survival pathways in cancer cells.68


Inflammation is a common feature across many chronic diseases including diabetes, heart disease, digestive disorders, and cancer. Dietary patterns modify inflammation, and the traditional Mediterranean diet (fruit, green vegetables, legumes, nuts, whole grains, moderate consumption of olive oil and alcohol, low consumption of red meat and butter) has been demonstrated to reduce inflammation.69,70 In addition, the Mediterranean diet exerts cardiovascular protection over a 10-year period of observation.

Myriocin is a natural product derived from a type of entomopathogenic fungus Isaria sinclairii (vegetative wasp), with strong immunosuppressant effects through inhibition of serine palmitoyl transferase, the initial enzyme in the biosynthesis of sphingolipids. This natural product led to the discovery of Fingolimod FTY720,71 a chemically modified myriocin. Fingolimod is now recognized as an immunosuppressant72 via specific receptor ligation.73,74 Fingolimod undergoes rapid phosphorylation in vivo by sphingosine kinase 2 to produce phosphor-FTY720 or fingolimod-phosphate,75 a structural analog of natural sphingosine-1-phosphate (S1P), which binds and activates S1P receptors with high affinity to exert biological effects.76 This leads to internalization of S1P receptor 1 (S1PR1) in lymphocytes, inhibiting the migration of lymphocytes toward S1P, an immunosuppressive mechanism highly effective in multiple sclerosis76,77 and proposed for use in other inflammatory lung diseases74 and chronic inflammatory demyelinating polyneuropathy.78 Interestingly, genetic variation within S1P receptors exert strong effects on receptor function, therapeutic efficacy of FTY720, and disease outcome.79,80 Genetic screening of SNPs in S1P receptor genes will significantly enhance precision medicine approaches to prescribing FTY720 as an immunosuppressant therapy.

Probiotics regulate immune responses by inhibiting pathogen growth in colonic mucosa via bacteriocin production, toxin inactivation, and interference with pathogen adherence. Lactobacillus strains, such as Lactobacillus GG and Saccharomyces. boulardii, demonstrate significant strain- and dose-dependent clinical benefit in the treatment of acute watery diarrhea.81,82,83

Chinese Herb Medicine

Chinese traditional herb medicine, used for thousands of years in China and Asian countries, have selectively been proven effective, with a recent Nobel Prize in Physiology or Medicine (2014), shared by Chinese scientist Youyou Tu for her development of an effective antimalarial treatment derived from the wormwood plant, Artemisia annua. Although clinical outcomes are inconsistent, modern genetic techniques show epigenetic effects of traditional Chinese herbs via influences on gene expression. Hsieh et al. found 36% of 3,294 medicinal herbs analyzed influenced histone-modifying enzymes, chromatin condensation, or miRNA- or methyl CpG-binding proteins.84 Effects of Chinese herb medicine on epigenetic gene expression regulation and potential health effects are summarized in Table 4.2.

Table 4.2 Chinese Herb Medicines as Epigenetic Modulators (2010–2016)


Epigenetic Effect

Clinical/Biological Outcome


Andrographis paniculata

Increased expression of 22 miRNAs and decrease of 10 miRNAs

Inhibition on hepatoma tumor growth


Hedyotis diffusa plus Scutellaria barbata

miR-155 reduction

Induction of bladder cancer cell apoptosis


Herb-partitioned moxibustion

miR-147 and miR-205 down-regulation

Protection against Crohn’s disease


Radix Astragali

miR-375 up-regulation

Neuroprotective effects in cerebral ischemia/reperfusion


Chinensis Franch, Astragalus membranaceus, and Lonicera japonica

Down-regulation of miR29-b

Sustained antidiabetic effects


Salvia miltiorrhiza

Upregulation of miR-133 expression

Protection against hypoxic cardiac myocytes


Salvia miltiorrhiza

Reduced acetylation of histone H3

Therapy and prevention of breast cancer


Tripterygium wilfordii Hook f

Reduced demethylation of histone H3 lysine 9

Antifertility and anticancer effects


Acanthopanax senticosus

HDAC inhibition

Inducing apoptosis of leukemia cells


Trichosanthes kirilowi

DNA demethylation via DNMT1 inhibition

Human cervical cancer suppression


Radix Angelicae Sinensis

DNA demethylation via DNA methyltransferase inhibition

Anticancer effect


Adjuvant Preventive Modalities in Integrative Preventive Medicine

As noted throughout this book, IPM modalities may influence health via common genomic and epigenetic impact and effects. Acupuncture at the SJ5 acupoint exerts neuroprotective effects via increased expression of Bcl-2, an antiapoptotic gene and Birc1b mRNA.98 Acupuncture in ischemic stroke patients specifically alters brain function in regions associated with sensation, vision, and motion, whereas this generally activates brain areas associated with insomnia and other functions in normal individuals.99 Acupuncture increased the glucose metabolism in local cerebral regions in patients with cerebral infarction measured by positron emission computer tomography (PET/CT).100

Personalized Medicine Applied to Population Health

The concept of population health is a true integration of numerous biologic molecular data points, cellular and phenotypic measurements, and individual genome sequences.5 The balance between individual and population interventions for improving health101 considers assessing micro- and macro-level factors as determinants of health and disease through complex population-based, longitudinal epidemiologic studies that consider endogenous factors, such as gene expression; individual factors, such as dietary intake and exercise habits; and socioeconomic factors.102 However, a new phenomenon is observed with regard to our ability to generate and analyze “omics” data that may delay the transition to personalized medicine application to population health. Currently, availability of “omics” facilities are heterogeneous, with personalized medicine likely to widen the growing disparity/equity in health systems between high- and low-income populations.103 There is a dramatic challenge for academic medicine to merge integrative approaches into the educative model for future generations of physicians and health professionals, thereby optimizing health and well-being through evidence-based, sustainable, integrative approaches.

Precision Medicine Integrated in Preventive Models

We have entered an era in disease-prevention approaches, disease treatment, and prevention, that now takes into account the issues of individual variability in genes, environment, and lifestyle for each person. However, as prevention is an area that has received less emphasis in precision medicine,21 the integrative model offers an opportunity to mine the interface between genomics and risk assessment, family health history, and clinical decision support. The availability of abundant genomic data sets collected in cell and animal models provides the opportunity for integration into a clinically meaningful and practical use that could be translated into population risk management.

Data Integration

The critical challenge of integrating and sharing personal health information in a secure way is a global concern. Countries such as Denmark, United Kingdom, Belgium, Norway, and Estonia have developed large-scale research data set of genomic data linked to electronic medical records. Examples include the EasyGenomics cloud in Beijing Genomics Institute (BGI), and “Embassy” clouds as part of the ELIXIR project in collaboration with multiple European countries.26 In the United States, academic centers, government organizations such as the National Human Genome Research Institute, and private industry have obtained massive data sets derived from a variety of genomic platforms. Data identifying genetic variants from individuals willing to share their electronic medical records with the aim of fostering clinical and genomic discovery is growing exponentially.

Biologists have studied specific proteins and molecular pathways individually, describing local interactions and perturbations in detail, with understanding the individual components as an important first step. However, to truly understand complex biological systems requires an integrated approach.5 The ability to share genomic data and clinical data and both integrate and translate these data into healthcare models and population health policies will pose a challenge for clinicians, scientists, and biostatisticians and public health policy makers. This integrated preventive model conceives a level of integration that requires incorporating “omics” data in the preventive intervention platform according to the level of risk of certain groups (Figure 4.4).

Figure 4.4 Integration of genomics and bioinformatics in IPM

Figure 4.4 Integration of genomics and bioinformatics in IPM

Increased cost-effectiveness is one potential advantage of precision medicine in the preventive field, where genome sequencing identifies actionable gene variants, defective genes with potential negative health effects.5 A recent study in familial hypercholesterolemia revealed that DNA testing for known family mutations and LDL-cholesterol levels is more cost-effective than current primary prevention.104 Likewise, US Preventive Services Task Force (USPSTF) current guidelines recommend genetic risk assessment and BRCA mutation testing for breast and ovarian cancer susceptibility in women with increased risk who have family members with breast, ovarian, tubal, or peritoneal cancer.105 Although BRCA 1-2 mutation gene testing remains cost-prohibitive in many circumstances, the charge is likely to decrease once the testing market is available in more labs.106

Complex illnesses involve the interplay of environmental, genetic, and epigenetic factors. Genomic-derived biomarkers are useful tools in the preventive model to predict disease susceptibility and implement directed therapy to avoid future disease-related complications. Similarly, allele frequency estimation, studied in population genetics, is relevant to define public health policies for common and rare but lethal diseases in certain groups at risk, such as African Americans and Hispanics. Ashkenazi Jews are a good example, in which preconception carrier prescreening is recommended107 for certain rare conditions (Tay-Sachs, alpha and beta thalassemia, etc.).


A key goal of integrative medicine is to provide the availability of diverse and appropriate options for patients, ultimately blurring the boundaries between conventional care and CAM. Genomic and epigenetic approaches exist within those blurred boundaries. Although the strength of current scientific evidence is incomplete, IPM in the modern healthcare era is well positioned to lead the integration of the vast and rapidly proliferating genomic-related information to improve population interventions in preventive medicine. Future research strategies are needed to more fully integrate the application of genomic and epigenetic data into synergies of integrative medicine and primary, secondary, and tertiary prevention levels. In doing so, IPM will have even greater capacity to maximize health benefits, minimize harm, and prevent unnecessary healthcare costs. As scientific findings begin to advance from a purely translational, genome-research phase to full clinical application, the regulatory and reimbursement policies barriers will need to be circumvented as well as legislative protections for privacy for systemwide adoption108 for the full application of genomic and personalized medicine in preventive medicine.


1. Hawkins RD, Hon GC, Ren B. Next-generation genomics: an integrative approach. Nat Rev Genet 2010;11:476–486. doi:10.1038/nrg2795.Find this resource:

2. The White House, Office of the Press Secretary. Fact Sheet: President Obama’s Precision Medicine Initiative. Accessed January 30, 2015.

3. Fradkin JE, Hanlon MC, Rodgers GP. NIH precision medicine initiative: implications for diabetes research. Diabetes Care 2016;39:1080–1084. doi:10.2337/dc16-0541.Find this resource:

4. Wang X, Ward PA. Opportunities and challenges of disease biomarkers: a new section in the Journal of Translational Medicine. J Transl Med 2012;10:240. doi:10.1186/1479-5876-10-240.Find this resource:

5. Hood L. Systems biology and p4 medicine: past, present, and future. Rambam Maimonides Med J 2013;4:e0012. doi:10.5041/rmmj.10112.Find this resource:

6. Cooke CR, Erickson SE, Watkins TR, Matthay, MA, Hudson LD, Rubenfeld GD, Age-, sex-, and race-based differences among patients enrolled versus not enrolled in acute lung injury clinical trials. Crit Care Med 2010;38:1450–1457. doi:10.1097/CCM.0b013e3181de451b.Find this resource:

7. Casanova N, Zhou, T, Knox KS, Garcia JG. Identifying novel biomarkers in sarcoidosis using genome-based approaches. Clin Chest Med 2015;36:621–630. doi:10.1016/j.ccm.2015.08.005.Find this resource:

8. Sealfon SC, Chu TT. RNA and DNA microarrays. Methods Mol Biol 2011;671:3–34. doi:10.1007/978-1-59745-551-0_1.Find this resource:

9. Chang JT, et al. SIGNATURE: a workbench for gene expression signature analysis. BMC Bioinformatics 2011;12:443. doi:10.1186/1471-2105-12-443.Find this resource:

10. Wen Q, Kim CS, Hamilton PW, Zhang SD. A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping. BMC Bioinformatics 2016;17:211. doi:10.1186/s12859-016-1066-x.Find this resource:

11. Bime C, et al. Reactive oxygen species-associated molecular signature predicts survival in patients with sepsis. Pulm Circ 2016;6:196–201. doi:10.1086/685547.Find this resource:

12. Akahoshi M, et al. Association between IFNA genotype and the risk of sarcoidosis. Hum Genet 2004;114:503–509.Find this resource:

13. Zhou T, et al. GSE37912: Peripheral blood gene expression as a novel genomic biomarker in complicated sarcoidosis. Gene Expression Omnibus 2012. this resource:

14. Zhou T, et al. Peripheral blood gene expression as a novel genomic biomarker in complicated sarcoidosis. PLoS One 2012;7:e44818. doi:10.1371/journal.pone.0044818.Find this resource:

15. Desai AA, et al. A novel molecular signature for elevated tricuspid regurgitation velocity in sickle cell disease. Am J Respir Crit Care Med 2012;186:359–368. doi:10.1164/rccm.201201-0057OC.Find this resource:

16. Singla S, et al. Expression profiling elucidates a molecular signature for pulmonary hypertension in sarcoidosis. Pulm Circ NA 2016;6:465–471. doi:0.1086/688316.Find this resource:

17. Simon R, Wang SJ. Use of genomic signatures in therapeutics development in oncology and other diseases. Pharmacogenomics 2006;6:166–173. doi:10.1038/sj.tpj.6500349.Find this resource:

18. Littarru GP, Langsjoen P. Coenzyme Q10 and statins: biochemical and clinical implications. Mitochondrion 2007;7 Suppl:S168–S174. doi:10.1016/j.mito.2007.03.002.Find this resource:

19. Oh J, Ban MR, Miskie BA, Pollex RL, Hegele RA. Genetic determinants of statin intolerance. Lipids Health Dis 2007;6:7. doi:10.1186/1476-511X-6-7.Find this resource:

20. Vladutiu GD. Genetic predisposition to statin myopathy. Curr Opin Rheumatol 2008;20:648–655. doi:10.1097/BOR.0b013e328314b7b4.Find this resource:

21. Ashley EA. The precision medicine initiative: a new national effort. JAMA 2015;313:2119–2120. doi:10.1001/jama.2015.3595.Find this resource:

22. Li L, Somerset S. The clinical significance of the gut microbiota in cystic fibrosis and the potential for dietary therapies. Clin Nutr 2014;33:571–580. doi:10.1016/j.clnu.2014.04.004.Find this resource:

23. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144:646–674. doi:10.1016/j.cell.2011.02.013.Find this resource:

24. Zugazagoitia J, et al. Current challenges in cancer treatment. Clin Ther 2016;38:1551–1566. doi:10.1016/j.clinthera.2016.03.026.Find this resource:

25. Herceg Z. Epigenetic mechanisms as an interface between the environment and genome. Adv Exp Med Biol 2016;903:3–15. doi:10.1007/978-1-4899-7678-9_1.Find this resource:

26. Marx V. Biology: the big challenges of big data. Nature 2013;498:255–260. doi:10.1038/498255a.Find this resource:

27. Lamprecht SA, Lipkin M. Chemoprevention of colon cancer by calcium, vitamin D and folate: molecular mechanisms. Nat Rev Cancer 2003;3:601–614. doi:10.1038/nrc1144.Find this resource:

28. Razin A, Riggs AD. DNA methylation and gene function. Science 1980;210:604–610.Find this resource:

29. Miller CA, Sweatt JD. Covalent modification of DNA regulates memory formation. Neuron 2007;53:857–869. doi:10.1016/j.neuron.2007.02.022.Find this resource:

30. Silva FP, et al. Enhanced methyltransferase activity of SMYD3 by the cleavage of its N-terminal region in human cancer cells. Oncogene 2008;27:2686–2692. doi:10.1038/sj.onc.1210929.Find this resource:

31. Lyko F, et al. The honey bee epigenomes: differential methylation of brain DNA in queens and workers. PLoS Biol 2010;8:e1000506. doi:10.1371/journal.pbio.1000506.Find this resource:

32. Mastroeni D, et al. Epigenetic changes in Alzheimer’s disease: decrements in DNA methylation. Neurobiol Aging 2010;31:2025–2037. doi:10.1016/j.neurobiolaging.2008.12.005.Find this resource:

33. Davis CD, Uthus EO. DNA methylation, cancer susceptibility, and nutrient interactions. Exp Biol Med (Maywood) 2004;229:988–995.Find this resource:

34. Johansson A, Enroth S, Gyllensten U. Continuous aging of the human DNA methylome throughout the human lifespan. PLoS One 2013;8:e67378. doi:10.1371/journal.pone.0067378.Find this resource:

35. Ogino S, et al. LINE-1 hypomethylation is inversely associated with microsatellite instability and CpG island methylator phenotype in colorectal cancer. Int J Cancer 2008;122:2767–2773. doi:10.1002/ijc.23470.Find this resource:

36. Bae JM, et al. ALU and LINE-1 hypomethylations in multistep gastric carcinogenesis and their prognostic implications. Int J Cancer 2012;131:1323–1331. doi:10.1002/ijc.27369.Find this resource:

37. Hoshimoto S, et al. AIM1 and LINE-1 epigenetic aberrations in tumor and serum relate to melanoma progression and disease outcome. J Invest Dermatol 2012;132:1689–1697. doi:10.1038/jid.2012.36.Find this resource:

38. Pattamadilok J, et al. LINE-1 hypomethylation level as a potential prognostic factor for epithelial ovarian cancer. Int J Gynecol Cancer 2008;18:711–717. doi:10.1111/j.1525-1438.2007.01117.x.Find this resource:

39. Sunami E, de Maat, M, Vu A, Turner RR, Hoon DS. LINE-1 hypomethylation during primary colon cancer progression. PLoS One 2011;6:e18884. doi:10.1371/journal.pone.0018884.Find this resource:

40. Ogino S, et al. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod Pathol 2013;26:465–484. doi:10.1038/modpathol.2012.214.Find this resource:

41. Schernhammer ES, et al. Dietary folate, alcohol and B vitamins in relation to LINE-1 hypomethylation in colon cancer. Gut 2010;59:794–799. doi:10.1136/gut.2009.183707.Find this resource:

42. Delage B, Dashwood RH. Dietary manipulation of histone structure and function. Annu Rev Nutr 2008;28:347–366. doi:10.1146/annurev.nutr.28.061807.155354.Find this resource:

43. Marmorstein R, Roth SY. Histone acetyltransferases: function, structure, and catalysis. Curr Opin Genet Dev 2001;11:155–161.Find this resource:

44. Lardenoije R, et al. The epigenetics of aging and neurodegeneration. Prog Neurobiol 2015;131:21–64. doi:10.1016/j.pneurobio.2015.05.002.Find this resource:

45. Su X, Wellen KE, Rabinowitz JD. Metabolic control of methylation and acetylation. Curr Opin Chem Biol 2016;30:52–60. doi:10.1016/j.cbpa.2015.10.030.Find this resource:

46. Shimazu T, et al. Suppression of oxidative stress by beta-hydroxybutyrate, an endogenous histone deacetylase inhibitor. Science 2013;339:211–214. doi:10.1126/science.1227166.Find this resource:

47. Kim DY, et al. Ketone bodies are protective against oxidative stress in neocortical neurons. J Neurochem 2007;101:1316–1326. doi:10.1111/j.1471-4159.2007.04483.x.Find this resource:

48. Bauer M, et al. Tobacco smoking differently influences cell types of the innate and adaptive immune system-indications from CpG site methylation. Clin Epigenetics 2015;7:83. doi:10.1186/s13148-016-0249-7.Find this resource:

49. Gao X, Jia M, Zhang Y, Breitling LP, Brenner H. DNA methylation changes of whole blood cells in response to active smoking exposure in adults: a systematic review of DNA methylation studies. Clin Epigenetics 2015;7:113. doi:10.1186/s13148-015-0148-3.Find this resource:

50. Adams M., Jewell AP. The use of complementary and alternative medicine by cancer patients. Int Semin Surg Oncol 2007;4:10. doi:10.1186/1477-7800-4-10.Find this resource:

51. Chang EY, Glissmeyer M, Tonnes S, Hudson T, Johnson N. Outcomes of breast cancer in patients who use alternative therapies as primary treatment. Am J Surg 1997;192:471–473. doi:10.1016/j.amjsurg.2006.05.013x.Find this resource:

52. Jang M, et al. Cancer chemopreventive activity of resveratrol, a natural product derived from grapes. Science 1997;275:218–220.Find this resource:

53. Shakibaei M, Harikumar KB, Aggarwal BB. Resveratrol addiction: to die or not to die. Mol Nutr Food Res 2009;53:115–128. doi:10.1002/mnfr.200800148.Find this resource:

54. Signorelli P, Ghidoni R. Resveratrol as an anticancer nutrient: molecular basis, open questions and promises. J Nutr Biochem 2005;16:449–466. doi:10.1016/j.jnutbio.2005.01.017.Find this resource:

55. Thakur VS, Deb, G, Babcook MA, Gupta S. Plant phytochemicals as epigenetic modulators: role in cancer chemoprevention. AAPS J 2014;16:151–163. doi:10.1208/s12248-013-9548-5.Find this resource:

56. Banerjee S, Li Y, Wang Z, Sarkar FH. Multi-targeted therapy of cancer by genistein. Cancer Lett 2008;269:226–242. doi:10.1016/j.canlet.2008.03.052.Find this resource:

57. Chen Y, et al. Curcumin, both histone deacetylase and p300/CBP-specific inhibitor, represses the activity of nuclear factor kappa B and Notch 1 in Raji cells. Basic Clin Pharmacol Toxicol 2007;101:427–433. doi:10.1111/j.1742-7843.2007.00142.x.Find this resource:

58. Greene WC, Chen LF. Regulation of NF-kappaB action by reversible acetylation. Novartis Found Symp 2004;259:208–217; discussion 218–225.Find this resource:

59. Druesne N, et al. Diallyl disulfide (DADS) increases histone acetylation and p21(waf1/cip1) expression in human colon tumor cell lines. Carcinogenesis 2004;25:1227–1236. doi:10.1093/carcin/bgh123.Find this resource:

60. Ariga T, Seki T. Antithrombotic and anticancer effects of garlic-derived sulfur compounds: a review. Biofactors 2006;26:93–103.Find this resource:

61. Tili E, et al. Resveratrol modulates the levels of microRNAs targeting genes encoding tumor-suppressors and effectors of TGFbeta signaling pathway in SW480 cells. Biochem Pharmacol 2010;80:2057–2065. doi:10.1016/j.bcp.2010.07.003.Find this resource:

62. Papoutsis AJ, Lamore SD, Wondrak GT, Selmin OI, Romagnolo DF. Resveratrol prevents epigenetic silencing of BRCA-1 by the aromatic hydrocarbon receptor in human breast cancer cells. J Nutr 2010;140:1607–1614. doi:10.3945/jn.110.123422.Find this resource:

63. Marcu MG, et al. Curcumin is an inhibitor of p300 histone acetylatransferase. Med Chem 2006;2:169–174.Find this resource:

64. Fix LN, Shah M, Efferth T, Farwell MA, Zhang B. MicroRNA expression profile of MCF-7 human breast cancer cells and the effect of green tea polyphenon-60. Cancer Genom Proteom 2010;7:261–277.Find this resource:

65. Traka M, et al. Transcriptome analysis of human colon Caco-2 cells exposed to sulforaphane. J Nutr 2005;135:1865–1872.Find this resource:

66. Clarke JD, Dashwood RH, Ho E. Multi-targeted prevention of cancer by sulforaphane. Cancer Lett 2008;269:291–304. doi:10.1016/j.canlet.2008.04.018.Find this resource:

67. Seki T, et al. Anticancer effects of diallyl trisulfide derived from garlic. Asia Pac J Clin Nutr 2008;17 Suppl 1:249–252.Find this resource:

68. Song EA, Kim H. Docosahexaenoic acid induces oxidative DNA damage and apoptosis, and enhances the chemosensitivity of cancer cells. Int J Mol Sci 2016;17:1–10. doi:10.3390/ijms17081257.Find this resource:

69. Panagiotakos DB, et al. Exploring the path of Mediterranean diet on 10-year incidence of cardiovascular disease: the ATTICA study (2002-2012). Nutr Metab Cardiovasc Dis 2015;25:327–335. doi:10.1016/j.numecd.2014.09.006.Find this resource:

70. Sofi F, Cesari F, Abbate R, Gensini GF, Casini A. Adherence to Mediterranean diet and health status: meta-analysis. BMJ 2008;337:a1344. doi:10.1136/bmj.a1344.Find this resource:

71. Zecri FJ. From natural product to the first oral treatment for multiple sclerosis: the discovery of FTY720 (Gilenya)? Curr Opin Chem Biol 2016;32:60–66. doi:10.1016/j.cbpa.2016.04.014.Find this resource:

72. Fujitac T, et al. Simple compounds, 2-alkyl-2-amino-1,3-propanediols have potent immunosuppressive activity. Bioorg Med Chem 1995;Lett 5:6.Find this resource:

73. Natarajan V, et al. Sphingosine-1-phosphate, FTY720, and sphingosine-1-phosphate receptors in the pathobiology of acute lung injury. Am J Respir Cell Mol Biol 2013;49:6–17. doi:10.1165/rcmb.2012-0411TR.Find this resource:

74. Wang L, et al. FTY720 (s)-phosphonate preserves sphingosine 1-phosphate receptor 1 expression and exhibits superior barrier protection to FTY720 in acute lung injury. Crit Care Med 2014;42:e189–e199. doi:10.1097/CCM.0000000000000097.Find this resource:

75. Billich A, et al. Phosphorylation of the immunomodulatory drug FTY720 by sphingosine kinases. J Biol Chem 2003;278:47408–47415. doi:10.1074/jbc.M307687200.Find this resource:

76. Chun J., Hartung HP. Mechanism of action of oral fingolimod (FTY720) in multiple sclerosis. Clin Neuropharmacol 2010;33:91–101. doi:10.1097/WNF.0b013e3181cbf825.Find this resource:

77. Chiba K. [A new therapeutic approach for autoimmune diseases by the sphingosine 1-phosphate receptor modulator, fingolimod (FTY720)]. Nihon Rinsho Meneki Gakkai Kaishi 2009;32:92–101.Find this resource:

78. Erdener SE, Nurlu G, Gocmen R, Erdem-Ozdamar S, Kurne A. Remission with fingolimod in a case of demyelinating polyneuropathy. Muscle Nerve 2014;50:615–617. doi:10.1002/mus.24311.Find this resource:

79. Obinata H, et al. Individual variation of human S1P(1) coding sequence leads to heterogeneity in receptor function and drug interactions. J Lipid Res 2014;55:2665–2675. doi:10.1194/jlr.P054163.Find this resource:

80. Sun X, et al. Functional promoter variants in sphingosine 1-phosphate receptor 3 associate with susceptibility to sepsis-associated acute respiratory distress syndrome. Am J Physiol Lung Cell Mol Physiol 2013;305L467–L477. doi:10.1152/ajplung.00010.2013.Find this resource:

81. Guandalini S. Probiotics for prevention and treatment of diarrhea. J Clin Gastroenterol 2011;45 Suppl:S149–S153. doi:10.1097/MCG.0b013e3182257e98.Find this resource:

82. Floch MH, et al. Recommendations for probiotic use-2011 update. J Clin Gastroenterol 2011;45 Suppl, S168–S171. doi:10.1097/MCG.0b013e318230928b.Find this resource:

83. McFarland LV. From yaks to yogurt: the history, development, and current use of probiotics. Clin Infect Dis 2015;60 Suppl 2:S85–S90. doi:10.1093/cid/civ054.Find this resource:

84. Hsieh HY, Chiu PH, Wang SC. Epigenetics in traditional Chinese pharmacy: a bioinformatic study at pharmacopoeia scale. Evid Based Complement Alternat Med 2011;2011:816714. doi:10.1093/ecam/neq050.Find this resource:

85. Lu B, Sheng Y, Zhang J, Zheng Z, Ji L. The altered microRNA profile in andrographolide-induced inhibition of hepatoma tumor growth. Gene 2016;588:124–133. doi:10.1016/j.gene.2016.05.012.Find this resource:

86. Pan LT, Sheung Y, Guo WP, Rong ZB, Cai ZM. Hedyotis diffusa plus Scutellaria barbata induce bladder cancer cell apoptosis by inhibiting Akt signaling pathway through downregulating miR-155 Expression. Evid Based Complement Alternat Med 2016;2016:9174903. doi:10.1155/2016/9174903.Find this resource:

87. Wei K, et al. Herb-Partitioned Moxibustion and the miRNAs Related to Crohn’s Disease: A Study Based on Rat Models. Evid Based Complement Alternat Med 2015;2015:265238. doi:10.1155/2015/265238.Find this resource:

88. Wang Y, et al. Downregulated RASD1 and upregulated miR-375 are involved in protective effects of calycosin on cerebral ischemia/reperfusion rats. J Neurol Sci 2014;339:144–148. doi:10.1016/j.jns.2014.02.002.Find this resource:

89. Zhao HL, et al. Sustained antidiabetic effects of a berberine-containing Chinese herbal medicine through regulation of hepatic gene expression. Diabetes 2012;61:933–943. doi:10.2337/db11-1164.Find this resource:

90. Zhang L, et al. Tanshinone IIA improves miR-133 expression through MAPK ERK1/2 pathway in hypoxic cardiac myocytes. Cell Physiol Biochem 2012;30:843-852. doi:10.1159/000341462.Find this resource:

91. Gong Y, Li Y, Abdolmaleky HM, Li L, Zhou JR. Tanshinones inhibit the growth of breast cancer cells through epigenetic modification of Aurora A expression and function. PLoS One 2012;7:e33656. doi:10.1371/journal.pone.0033656.Find this resource:

92. Xiong J, et al. Male germ cell apoptosis and epigenetic histone modification induced by Tripterygium wilfordii Hook F. PLoS One 2011;6:e20751. doi:10.1371/journal.pone.0020751.Find this resource:

93. Wen L, et al. Triptolide induces cell apoptosis by targeting H3K4me3 and downstream effector proteins in KM3 multiple myeloma cells. Curr Pharm Biotechnol 2015;17:147–160.Find this resource:

94. Zhao F, et al. Role of triptolide in cell proliferation, cell cycle arrest, apoptosis and histone methylation in multiple myeloma U266 cells. Eur J Pharmacol 2010;646:1–11. doi:10.1016/j.ejphar.2010.05.034.Find this resource:

95. Wang QY, et al. A preliminary study on epigenetic regulation of Acanthopanax senticosus in leukemia cell lines. Exp Hematol 2016;44:466–473. doi:10.1016/j.exphem.2016.03.002.Find this resource:

96. Huang Y, et al. Trichosanthin inhibits DNA methyltransferase and restores methylation-silenced gene expression in human cervical cancer cells. Mol Med Rep 2012;6:872–878. doi:10.3892/mmr.2012.994.Find this resource:

97. Su ZY, et al. Epigenetic reactivation of Nrf2 in murine prostate cancer TRAMP C1 cells by natural phytochemicals Z-ligustilide and Radix angelica sinensis via promoter CpG demethylation. Chem Res Toxicol 2013;26:477–485. doi:10.1021/tx300524p.Find this resource:

98. Lin D, Lin LL, Sutherland K, Cao CH. Manual acupuncture at the SJ5 (Waiguan) acupoint shows neuroprotective effects by regulating expression of the anti-apoptotic gene Bcl-2. Neural Regen Res 2016;11:305–311. doi:10.4103/1673-5374.177740.Find this resource:

99. Chen J, et al. Acupuncture at Waiguan (TE5) influences activation/deactivation of functional brain areas in ischemic stroke patients and healthy people: a functional MRI study. Neural Regen Res 2013;8:226–232. doi:10.3969/j.issn.1673-5374.2013.03.004.Find this resource:

100. Liu ET, et al. [Effect of needling at waiguan (SJ5) on brain glucose metabolism in patients with cerebral infarction]. Zhongguo Zhong Xi Yi Jie He Za Zhi 2013;33:1345–1351.Find this resource:

101. Khoury MJ, Gwinn ML, Glasgow RE, Kramer BS. A population approach to precision medicine. Am J Prev Med 2012;42:639–645. doi:10.1016/j.amepre.2012.02.012.Find this resource:

102. Khoury MJ, Gwinn M, Bowen MS, Dotson WD. Beyond base pairs to bedside: a population perspective on how genomics can improve health. Am J Public Health 2012;102:34–37. doi:10.2105/AJPH.2011.300299.Find this resource:

103. Alyass A, Turcotte M, Meyre D. From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med Genomics 2015;8:33. doi:10.1186/s12920-015-0108-y.Find this resource:

104. Nherera L, Marks D, Minhas R, Thorogood M., Humphries SE. Probabilistic cost-effectiveness analysis of cascade screening for familial hypercholesterolaemia using alternative diagnostic and identification strategies. Heart 2011;97:1175–1181. doi:10.1136/hrt.2010.213975.Find this resource:

105. Moyer VA; US Preventive Services Task Force. Risk assessment, genetic counseling, and genetic testing for BRCA-related cancer in women: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2014;160:271–281. doi:10.7326/M13-2747.Find this resource:

106. McCarthy AM, Armstrong K. The role of testing for BRCA1 and BRCA2 mutations in cancer prevention. JAMA Intern Med 2014;174:1023–1024. doi:10.1001/jamainternmed.2014.1322.Find this resource:

107. Jewish Genetic Diseases Consortium. (NA).

108. Ginsburg GS, Willard HF. Genomic and personalized medicine: foundations and applications. Transl Res 2009;154:277–287. doi:10.1016/j.trsl.2009.09.005.Find this resource:

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