A comprehensive narrative review on precision medicine approach to hypertension: exploring the role of genetics, epigenetics, microbiome, and artificial intelligence

Background

Hypertension (HTN) impacts approximately 1.28 billion individuals globally and poses a great burden of disease. The objectives of this study are to explore the role of genetics, epigenetics, microbiome, and artificial intelligence (AI) in the management of HTN. A thorough literature search was conducted across various databases including PubMed, Google Scholar, Web of Science (WoS), and Medline to retrieve articles related to the role of genetics, epigenetics, microbiome, and AI in the precision medicine of HTN. Genes—including ACE, NOS3, ADD1, CYP11B2, NPPA, and NPPB—have a profound impact on blood pressure (BP) regulation in our body and polymorphism in these key genes can lead to HTN. Up or down-regulation of genes by epigenetic factors such as miRNA-155, miRNA-210, and miRNA-122 can significantly contribute to the development of HTN. These genetic and epigenetic factors can also be used as specific targets for gene editing and gene therapy for long-term management of HTN. However, the implementation of these techniques has not been possible in clinical settings due to lack of human studies and safety concerns related to unpredictable DNA alterations, nucleotide deletions, and loss of allele-specific chromosomes. Modulation of gut microbiome through oral supplements, fecal microbiota transplant (FMT), and dietary interventions has emerged as one the most effective and safe techniques for managing HTN in human models. AI-based cutting-edge models have helped curate personalized diet plans based on an individual’s unique microbiome, genomic information, and physiological conditions leading to a reduction in BMI, fat, BP, and heart rate while improving overall cardiac health and gut microbial diversity. Despite the significant advantages offered by AI-based medicine, ethical concerns—related to data privacy, bias, and discrimination—and ineffective models have led to limited integration of AI in precision medicine of HTN. The integration of genetics, epigenetics, microbiome, and AI-based models can play a key role in improving the current landscape of precision medicine of HTN. These cutting-edge techniques can lead to a shift from the current one-size-fits all approach to more personalized treatment plan however further research in human models is needed to determine the safety and true efficacy of these techniques. Additionally, new AI-models need to be developed that address ethical concerns and are effective in real-world clinical settings.

Introduction

Hypertension (HTN) is a long-term medical condition characterized by persistently elevated arterial blood pressure (BP) [1]. According 2017 guidelines of American College of Cardiology (ACC) and American Heart Association (AHA), stage 1 HTN is defined as systolic blood pressure (SBP) of 130–139 mmHg and a diastolic blood pressure (DBP) of 80–89 mmHg. HTN is classified as stage 2 if SBP is 140 mmHg or higher and DBP is 80 mmHg or above [2].

According to the latest statistics, HTN currently affects 1.28 billion people worldwide, with the number projected to reach 1.56 billion by 2025 [3, 4]. In the USA, 116 million individuals are affected by HTN [1], while in China, the prevalence among adults stands at 27.5% [5]. In 2024, the prevalence of HTN in India is 22.6% [6]. In Pakistan, the condition affects 18.9% of individuals over the age of 15 and 33% of those over 45 [7–9]. The increasing global prevalence of HTN highlights its growing public health burden, contributing significantly to disease morbidity and adverse health outcomes.

HTN is a major risk factor for a number of health complications, particularly cardiovascular diseases (CVDs), including valvular disorders, cardiac arrhythmias, left ventricular hypertrophy (LVH), myocardial infarction (MI), and heart failure (HF) [10]. Persistently high BP increases the likelihood of CVD-related morbidity and mortality by two to four folds [11]. Chronic HTN also contributes to blood vessel weakening, predisposing individuals to aneurysms. Notably, aortic aneurysms, characterized by pathological dilation of the aorta, are commonly linked to HTN and can lead to rupture, posing a life-threatening risk [12]. Moreover, HTN has detrimental effects on renal function, increasing the probability of kidney disorders [13]. The nervous system is also adversely affected by HTN, with increased risks of ischemic and hemorrhagic strokes, hypertensive encephalopathy, and other cerebrovascular conditions [14, 15]. Furthermore, HTN generally coexists with comorbidities like diabetes [16], obesity, dyslipidemia, and metabolic syndrome further compounding the risk of serious health complications [17, 18].

HTN is linked to a multitude of environmental, lifestyle, biological and genetic factors. Understanding these factors is essential for development of personalized medicine [19, 20]. Our environment has a profound impact on our BP with clear variations based on seasons, with an increase in BP observed during colder seasons [21]. Noise and air pollution are significant environmental factors that contribute to the development of HTN. Prolonged exposure to high levels of noise, especially from traffic, aircraft, and occupational sources, can initiate the formation of ROS. Additionally, pollutants such as pesticides, plastics, and heavy metals play a complementary role in development of HTN [21–23]. Unhealthy eating habits, such as consuming a diet high in saturated fats, trans fats, sugar and processed food increase the risk of developing HTN [24, 25]. One of the major risk factors for HTN is smoking, with studies suggesting that smoking can increase the probability of developing HTN by 5.7% [26–28]. A sedentary lifestyle leads to obesity, which ultimately causes inflammation and oxidative stress [29]. Age is strongly associated with HTN, affecting 26% of individuals between 20 and 44 years old, with its prevalence increasing to 78% in those over the age of 65. Other factors, such as increased anxiety with age and decreasing levels of protective hormones like estrogen, also contribute to the development of HTN [29]. The prevalence of HTN varies greatly based on gender with the heart disease and stroke statistics estimating the prevalence of HTN in the US was 51.7% among males and 42.8% among females aged 20 years and older [30, 31].

The severe and often silent progression of HTN makes it a formidable global health challenge. Despite its high prevalence, there is currently no definitive cure. The conventional treatment strategy relies on a generalized, one-size-fits-all approach, which has its limitations. The first-line interventions for HTN management typically involve lifestyle modifications, including stress reduction, smoking cessation, alcohol avoidance, adoption of a healthy diet, sodium restriction, weight loss, and regular physical activity [1, 32]. Currently available pharmacological therapies include calcium channel blockers (CCB), diuretics, angiotensin-converting enzyme (ACE) inhibitors, and beta-blockers among several other options [1, 33]. While these therapies have been widely used for decades, their effectiveness varies among individuals, and challenges such as treatment-resistant HTN, adverse effects, limited patient tolerance, and a lack of personalized approaches persist.

These limitations underscore the need for a paradigm shift toward precision medicine. Precision medicine in HTN defined as the approach towards disease prevention, diagnosis, management and treatment tailored to an individual’s unique genetic, epigenetic, and biological makeup. These developments pave the way for more targeted, personalized treatment strategies that address the condition at its root cause. The landscape of HTN treatment has been changing drastically. These breakthroughs have revolutionized the treatment of HTN, due to the development of novel therapeutic interventions, including gene therapy and gene editing. Alongside genetics, epigenetic modifications play a crucial role in BP regulation. MicroRNAs (miRNAs) reinforce the importance of epigenetics in precision medicine due to their role in gene expression. Moreover, gut microbiome is a key factor in pathophysiology of HTN. The composition of intestinal microbiota plays a role in modulating the metabolic and inflammatory pathways in the body linked to BP regulation. Understanding these interactions can pave the way for development of microbiome-targeted therapies. AI has played a revolutionary role in the field of precision medicine by integrating complex genetic, epigenetic, and microbiome data to develop highly personalized treatment strategies.

In this review we explore the new advances in precision medicine, highlighting the importance of genetics, gene modification tools, epigenetics, gut microbiome, and AI in the ongoing transition toward precision medicine.

Methodology

A comprehensive literature search was conducted from 25 January to 11 February 2025 across various databases to retrieve articles related to precision medicine and HTN. The databases include PubMed, Google Scholar, Web of Science (WoS), and Medline. The search employed a strategy that integrated both keywords and Medical Subject Headings (MeSH) terms to cover a wide range of relevant literature, including ‘Hypertension’, ‘Artificial Intelligence’, ‘Precision Medicine’, ‘Gut Microbiome’, ‘Genetics’, ‘Epigenetics’, and ‘miRNA’. The search focused on identifying high-quality articles published in the past decade (i.e. 1 January 2015 to 25 January 2025). We screened free full-text articles published in the English language focusing on human, animal, and AI models. We included case-control studies, cohort studies, randomized control trails, cross-sectional studies, narrative reviews, systematic reviews, and meta-analysis while excluding conference abstracts, editorials and, pre-print studies from our study.

The cellular and molecular mechanism of hypertension

Primary or essential HTN (EH) accounts for approximately 90–95% of all HTN cases [34]. The development of HTN is primarily driven by pathological disruptions in the body’s regulatory mechanisms, including arterial stiffness, dysregulation of the sympathetic nervous system, water and sodium retention, salt sensitivity, and hyperactivation of the renin-angiotensin-aldosterone system (RAAS) [35].

One of the key contributors to HTN is arterial stiffening, which refers to the reduced ability of arteries to expand and contract in response to physiological stimuli. With aging and disease progression, the arterial walls undergo structural changes, characterized by a decline in elastin and an increase in collagen fibers within the tunica media (middle layer of the artery). This leads to reduced arterial flexibility and an impaired ability to accommodate fluctuations in BP. Additionally, as arterial stiffness progresses, pulse wave velocity increases, causing the reflected wave to return to the heart more rapidly and coincide with the systolic phase of the cardiac cycle. As a result, SBP rises while DBP decreases, perpetuating a cycle that further exacerbates arterial stiffening [36].

The dysregulation of the autonomic nervous system can lead to persistently elevated BP. In HTN, there is a reduction in the parasympathetic tone, while simultaneously sympathetic stimulation is heightened, leading to an imbalance in the autonomic regulation. An increased sympathetic stimulation causes the contractility and heart rate to increase leading to elevated SBP. Increased sympathetic stimulation also causes vasoconstriction in peripheral vessels further increasing arterial BP [37]. The RAAS system is the body’s key BP regulator, influencing both vascular tone and fluid balance. Overactivation of RAAS leads to HTN through increased vascular resistance and fluid retention [38, 39].

Another component in the development of HTN is the combined effect of inflammation, oxidative stress, and dysfunction of the immune system. As a result of old age, obesity, vascular damage, or numerous other causes, there is a release of super-oxides (O₂⁻) and H₂O₂ by endothelial cells and immune cells. This oxidative stress causes inflammation and stimulates the production of cytokines and chemokines from the endothelium. Leukocytes are then attracted to this area of inflammation due to cytokines and chemokines. The aggregation of leukocytes, which release proinflammatory molecules, further promotes inflammation and oxidative stress, setting up a vicious cycle [40, 41].

Nitric Oxide (NO) is a major regulator of vascular tone. In the body, it is produced by endothelial NO synthase (eNOS). NO is a vasodilator and adjusts vascular tone based on changes in blood pressure. In HTN, due to oxidative stress, inflammation, adhesion of leukocytes, and platelet activation, there is endothelial dysfunction [40, 42]. This causes a reduced amount of NO production, and the body is unable to regulate vascular tone, leading to an increase in BP. The various pathological changes occurring in the body that contribute to the development of HTN have been illustrated in Fig. 1.

Fig. 1.

The Underlying Pathophysiological Mechanism of Hypertension. Abbreviations: RAAS: Renin-Angiotensin-Aldosterone System

Current landscape of hypertension treatment

The current treatment of HTN encompasses various pharmacological therapies including diuretics, β-blockers, ACE inhibitors, ARB, mineralocorticoid receptor antagonists (MRAs) and calcium channel blockers (CCBs) among other pharmacological approaches [33]. Figure 2 depicts the mechanism of action of various pharmacological therapies currently being utilized in clinical settings.

Fig. 2.

The image illustrates the mechanism of action of the current pharmacological therapies a) Thiazide diuretics act on the distal convoluted tubules and blocks the reabsorption of Na + by blocking the Na/Cl channel b) ACE inhibitors blocks the RAAS pathway c) Angiotensin II receptor blockers selectively bind to ARB type 1 receptors, preventing angiotensin II from exerting its effects d) Mineralocorticoid receptor antagonists competitively bind to mineralocorticoid receptors and block the action of aldosterone e) CCBs exert their action by binding to and blocking the L-type voltage gated calcium channels in heart and smooth muscles

Pharmacological treatments for HTN have evolved over the span of decades, but they have been ineffective in definitively managing HTN. Moreover, the current treatment option have several limitations and can exert adverse effects. For instance, thiazide diuretics have a shallow dose response curve, meaning that increasing dose has minimal effect on BP reduction [43]. Similarly, ACE inhibitors can have adverse effects including hypotension, hyperkalemia, dry cough, dizziness, syncope and renal failure [44] while CCBs can cause light headedness, flush, headaches, peripheral edema. The condition can worsen to MI, angina pectoris, and acute hypotension [45]. Additionally, inadequate BP management, lack of tolerability, adverse effects, variable outcomes from individual to individual and lack of compliance remain key challenges of traditional pharmacological treatment. Currently, there is a need for emphasis on prevention, early diagnosis, and long-term management of HTN. The shortcomings of traditional HTN therapies underscore the need for paradigm shift towards a more tailored and effective approach: precision medicine.

Results and discussion

The shift towards precision medicine in hypertension management

Precision medicine is defined as the approach towards disease prevention, diagnosis, management and treatment tailored to an individual’s unique genetic, epigenetic, and biological makeup [46]. The evolving landscape of HTN treatment, coupled with the new insights into the role genetics, epigenetics, and the microbiome in underlying mechanism of HTN, underscores the need for precision medicine. Development of cutting-edge techniques like gene therapy and gene editing has enhanced the field of precision medicine. Additionally, integration of genetic markers, RNA based treatments, pharmacogenomics, and AI has optimized HTN outcomes.

Genetics of hypertension

HTN is a complex, multifactorial disorder, with a strong hereditary component. A number of genes encode for proteins involved in BP regulation pathways. Mutations in these genes contribute to the disruption of the BP regulatory pathways, leading to the development of HTN. In recent years, utilization in of advance techniques like gene-wide association studies (GWAS), next generation sequencing (NGS), and high-resolution genotyping have led to improved understanding of genes and their mutations [16]. Research have identified more than 150 susceptibility genes, underscoring the importance of understanding the genetic component of HTN [47].

Angiotensin converting enzyme (ACE) gene

ACE enzyme is an important component of the RAAS system and is involved in regulation of BP [47, 48]. A 2021 meta-analysis, analyzed 32,862 patients for the association between polymorphism in ACE gene and HTN. The study observed a significant relationship between the D allele of ACE gene and higher susceptibility to HTN. Additionally, the study highlights the impact ACE gene polymorphism across various ethnicities. Though polymorphism in D allele was linked to EH in all study populations including Asians, Caucasians, and mixed individuals, a stronger link was found among Asian population [49]. Similarly, a 2022 study analyzed the association between insertion/deletion polymorphism in the ACE gene and HTN. The prevalence of the DD genotype and the D allele of the ACE was more prevalent in HTN patients (48.4% and 63%, respectively) compared to healthy controls (HCs) (29.7% and 42.2%, respectively). The frequency of the DD genotype and the D allele was significantly linked to HTN in patients [50]. Fan et al., explored the link between ACE2 polymorphism and HTN. They investigated the link between rs2074192, rs4646176, rs4646155, and rs2106809 SNP of the ACE2 gene and HTN. In females, ACE2 rs2074192 and rs2106809 variants increased the risk of left ventricular hypertrophy by 2.1 and 2.0 times, respectively. The haplotype TCGT of ACE2 also increased the risk of left ventricular hypertrophy (LVH) in females. In contrast, the haplotype CCGC was linked to a decreased risk of LVH in females a well as decreased SBP of 3.4 mm Hg was also observed. In males, this haplotype decreased SBP by 2.4 mm Hg. The study concluded that SNPs rs2074192 and rs2106809 as well as major haplotypes CCGC and TCGT were significantly linked to HTN and LVH, and could potentially serve as biomarkers for HTN [51]. The studies discussed above highlight the role of ACE gene in BP regulation and demonstrate the effects of polymorphism on development of HTN.

Nitric oxide synthase 3 (NOS 3) gene

The NOS3 gene on chromosome 7 encodes the enzyme endothelial NO synthase (eNOS) [52]. The enzyme is involved in the production of NO, which is an important vasodilator [53]. The 2017 study by Gamil et al., analyzed the link between polymorphisms in the NOS3 gene and HTN, among 157 Sudanese subjects. The rs2070744 polymorphism in NOS3 was significantly linked to essential hypertension, with patients having a higher frequency of the CC genotype compared to healthy controls (HC) (6.6% vs. 6.1%, respectively). In contrast, the TT genotype was more frequent in HC compared to patients (65.9% vs. 47.4%, respectively) [52][52]. Another study by Wang et al., investigated the link between NOS3 and HTN. The study was conducted among the Han Chinese population among a cohort of 2012 HTN patients and 2210 HCs. The study found that rs4496877, rs1808593, and rs3918186 polymorphism in the NOS3 gene was significantly linked to HTN. Furthermore, rs3918186 was linked to SBP [54].

Alpha-adducin-1 (ADD1) gene

The alpha-adducin-1 gene is involved in salt sensitivity and plays a role in sodium reabsorption by activating the Na⁺-K⁺ pump. Polymorphism in this gene causes overactivation of the Na⁺-K⁺ pump, leading to excessive sodium reabsorption [55, 56]. A 2022 study by Zhang et al., examined the link between ADD1 polymorphisms and the risk of HTN among the Han and Mongolian population. The ADD1 rs2239728-A allele showed a 0.74 times higher risk of HTN compared to the rs2239728-C variant. Furthermore, in this population, the ADD1 rs4961-T allele was linked to a 1.37 times higher risk of HTN compared to the G allele [57]. The study highlights the important role of ADD1 gene plays in regulation of BP and polymorphism in the ADD1 can lead to the development of HTN.

Natriuretic peptide A and natriuretic peptide B genes

The NPPA and NPPB genes code for the atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP), respectively [58]. ANP is released from cardiac atrium and BNP is produced from cardiac ventricles [59]. Physiologically, ANP and BNP when produced from the heart causes diuresis, natriuresis, vasodilation, antagonize RAAS, inhibit aldosterone synthesis and renin secretion. All of these processes cause a decrease in blood volume by excretion of salt and water and overall decreases BP [60].

A 2019 study explored the correlation of NPPA gene polymorphism and the serum ANP levels among the Chinese Han population. The study included 736 HTN patients and 736 HCs. The study found that serum ANP levels were significantly lower in HTN patients than in HCs. The researchers also highlighted that individuals with highest ANP levels were at the least risk of HTN. The SNP rs5063 of NPPA gene was significantly linked to HTN [61]. Similarly, the study by Seidelmann et al., investigated the effect of NPPB promoter polymorphism on BP and by extension development of HTN. The study had a cohort of 11,361 black and white patients. They investigated the effect of the rs198389 variant on BP outcomes. The study found that GG genotype was linked to reduced SBP and DBP in comparison to AA genotype. The AG genotype has an intermediate effect on levels of systolic and diastolic BP. The GG genotype was linked to reduced risk of cardiac disease and hence cardiac related mortality [62]. These studies provide important insights for gene therapy and gene editing.

Angiotensinogen (AGT) genes

The AGT gene encodes for one of the most important components of the RAAS: angiotensinogen [63–65]. A 2024 research by Sharma et al., explained the role of SNPs in AGT gene with HTN among the North Indian population. The researchers found that the rs699 variant of AGT was significantly linked to risk of HTN. Furthermore, they also found that rs4762 had a protective effect against HTN. The study also established that rs699 and rs4762 are among the most common SNPs linked to AGT gene and are linked to altered levels of angiotensin in plasma [66]. A 2024 meta-analysis also studied the link between AGT rs699 gene and HTN among various populations. It was observed that this variant of the AGT gene was significantly linked to elevated levels of angiotensin in plasma and consequently led to elevated BP. Another significant finding was that the gene polymorphism didn’t have the same effect across the population. The gene was seen to be linked to HTN in the Indian population but not in the European and East Asian populations [67]. This further emphasizes the need for precision medicine tailored to an individual’s needs and the unique gene interactions.

CYP11B2 gene

The CYP11B2 gene encodes for the enzyme aldosterone synthase. In the body, its expression is linked to sodium levels. Sodium restriction or an increase in levels of angiotensin II levels increase the mRNA levels of CYP11B2. The important function of aldosterone synthase highlights the mechanism through which polymorphism in the gene could lead to disruption of BP regulation and lead to HTN [68]. Study by Abdelet et al., investigated the link between CYP11B2 polymorphism and EH among Egyptian population. The study found that CYP11B2 (− 344T) allele was significantly higher among hypertensive patients compared to health controls (HCs). Furthermore, − 344TT genotype was linked to left ventricular hypertrophy. The researchers concluded that polymorphism in the gene was linked to EH [69]. Similarly, a 2013 study by Shah et al., also investigated the link between aldosterone synthase gene and HTN among the Pashtun population of Khyber Pakhtunkwha, Pakistan. The study found that the frequency of minor allele T was higher among HTN patients compared to HCs (42% vs. 30% respectively) [70].

A comprehensive understanding of the genetics of HTN is essential for unravelling its complex mechanisms. Extensive research has established a clear pattern between the above-mentioned genes i.e. ACE, AGT, NPPA, NPPB, ADD1, and CYP11B2 and hypertension across various ethnic populations. Table 1 summarizes the role of various genes involved in BP regulation. These genes play a role in the key biological processes of BP regulation such as sodium regulation, vascular tone, and the function of the RAAS. By identifying the specific genes involved, we can gain deeper insights into the pathways driving the disease. Genetics are the key to revolutionizing the treatment of HTN through advanced gene editing and gene therapy techniques. Developing treatments tailored to an individual’s unique genetic makeup can enhance health outcomes while minimizing adverse effects. Additionally, genetic markers can aid in early diagnosis of high-risk individuals enabling early interventions and more effective management. Together, these approaches offer the promise of a definitive solution for HTN, transforming treatment paradigms and significantly improving patient outcomes.

Table 1.

Genes involved in the development of HTN

Genes	Chromosome	Function	References
ACE	Ch.17	The gene ACE codes for the ACE. ACE converts angiotensin I into angiotensin II. Angiotensin is a regulator of BP, through its action of vasoconstriction, salt-water retention, and stimulates production of aldosterone. Dysfunction of this key gene can lead to increased BP and CVDs.	[71, 72]
NOS3	Ch.7	NOS3 gene codes for the enzyme eNOS, responsible for the production of NO. NO is an important vasodilator and regulates BP by modulating vascular tone. Dysfunction of this gene causes the blood vessels to lose their BP adaptability leading to increased BP.	[73]
CYP11B2	Ch.8	The CYP11B2 gene encodes for cytochrome P450, involved in the synthesis of aldosterone. Aldosterone is a key hormone of RAAS, and regulates BP through vasoconstriction and salt-water retention. Overexpression of this gene can lead to increased activity of RAAS leading to HTN.	[57]
AGT	Ch.1	The gene codes for peptide angiotensinogen. Angiotensin is the precursor of angiotensin II, an important regulator of BP. Polymorphism of this gene can lead to development of HTN.	[74]
AGTR1	Ch.8	AGTR1 gene encodes for angiotensin II receptor 1. Angiotensin II performs its function by binding to this receptor and increasing BP.	[72]
NPPA	Ch.1	NPPA gene encodes for ANP. ANP is produced as a response of stretching of the atria. ANP regulates the BP by causing natriuresis and diuresis in the kidneys.	[71]
NPPB	Ch.1	NPPB gene encodes for BNP, a peptide produced from the cardiac ventricles in response to excessive stretch on ventricles. BNP exerts its action by causing natriuresis and diuresis in kidneys. Furthermore, it suppresses the RAAS and causes vasodilation. The combined effect of all these actions leads to a decrease in BP.	[75]

Gene editing

Gene editing is a revolutionary technology that has transformed the therapeutics of HTN. It enables the modification of DNA at specific genomic locations by introducing targeted alterations to the genetic sequence [76]. CRISPR-Cas9 system, antisense oligonucleotides (ASO), TALENs, and zinc-finger nucleases, and siRNA are among the most prominent techniques utilized for gene editing [77, 78]. Currently, the primary focus of gene editing in HTN is down regulation of genes like ACE, AT1R, mineralocorticoid receptor gene and AT1R while upregulating protective genes like AT2R, ANP, BNP, and eNOS [79].

CRISPR-Cas9 gene editing system

Among the various gene-editing technologies, CRISPR-Cas9 is the most effective method. A 2020 study, used CRISPR-Cas9 system to target the AGT gene in the hepatocytes. The intervention led to a 70% decrease in the levels of AGT mRNA, 50% decrease in the levels of circulating AGT protein, and a 33% decrease in angiotensin II levels. Notably, the SBP dropped by 30–35 mm of Hg among study subjects. The researchers concluded that the intervention was effective in the prevention of HTN among pre-hypertensive subjects, with results sustaining up-to 4 months after the intervention [80][80]. Building on the findings of previous study, a 2021 study used the CRISPR-Cas9 system to target the AGT gene in liver cells to cure HTN. The study demonstrated a 40% reduction in AGT gene expression and a 30% decrease in circulating AGT protein levels. Furthermore, subjects with a history of hypertension experienced a sustained reduction in blood pressure. Remarkably, the beneficial effects persisted throughout a one-year follow-up period, reinforcing the potential of CRISPR-Cas9 as a long-term therapeutic strategy for hypertension management. These findings highlight the promise of gene editing in providing a durable and personalized approach to hypertension treatment [80].

A 2023 study explored the use of Endothelium-Targeted Nanoparticle Delivery of the CRISPR/Cas9 system to target endothelial FABP4 gene. The FABP4 gene is a key regulator of inflammation, insulin, and vascular function in the body, and has been linked to the development of HTN. In this study, the researchers edited the gene to knock out the expression of FABP4. This genetic intervention led to reduction in right ventricular SBP, right ventricular hypertrophy and pulmonary vascular remodeling. The study demonstrated that utilizing nanoparticle-based gene editing systems is a safe and effective approach towards treating pulmonary HTN [81].

LDL-R gene encoding the receptor of LDL, is another important name in the HTN discussion due to its role in metabolism of LDL. Mutation in the LDL-R gene leads to development of familial hypercholesterolemia, a risk factor for HTN, atherosclerosis, and vascular dysfunction, and HTN. A 2019 study, employed gene editing on the LDL-R gene. The study employed an in vivo CRISPR/Cas9 system delivered by adeno-associated virus (AAV) to treat mutant LDL-R gene in mice hepatocytes. The study found that the expression of LDL-R function was restored after AAV-CRISPR/Cas9 editing. There was significant reduction in total cholesterol, total triglycerides, and serum LDL. Furthermore, a decrease in aortic atherosclerotic plaques as well as macrophage infiltration was observed in the subjects. The study concluded that in vivo CRISPR/Cas9 systems delivered by the AAV technique can serve as a potential cure for familial hypercholesterolemia [82]. Chadwick et al., conducted a groundbreaking gene-editing study by targeting and disrupting the function of the PCSK9 gene. The gene encodes the PCSK9 protein and is involved in regulation of cholesterol levels. Increased levels of PCSK9 are linked to higher LDL cholesterol levels in blood and is a major risk factor for HTN, atherosclerosis and CVDs. The study employed CRISPR-Cas9 system fused to a cytosine deaminase domain to cause mutation in the gene. The researchers wanted to investigate whether in-vivo base editing to mutate the PCSK9 gene could be achieved. The researchers observed that there was 34% editing in liver cell alleles of PCSK9. A significant decrease in PCSK9 plasma levels (more than 50%) was also observed. Furthermore, there was a significant decrease in cholesterol levels (30%). The study confirmed that the technique was safe, as there were no off-target mutations. The researchers concluded that CRISPR-Cas9 fused to a cytosine deaminase domain is an effective and safe technique for gene editing, and holds potential in treatment of atherosclerosis and by extension HTN [83].

Despite significant advances in gene editing techniques, most of the research has been conducted on animal models or in vitro, which limit their applicability of gene editing techniques on humans. The concerns related to gene-altering systems are further exacerbated by findings of recent studies in human embryos that showed unpredictable DNA alterations, nucleotide deletions, and loss of allele-specific chromosomes. Scientists have voiced concerns over the safety of gene editing techniques potentially leading to off-target effects, mosaicism, and unintended long-term outcomes. In current state, gene editing techniques have not reached high precision, DNA and genetic sequences similar to the target sequence can be modified leading to DNA mutations. Further research is needed to achieve precision and safety in gene editing techniques. Additionally, ethical concerns have been raised regarding the germline editing. Germline editing can enable permanent genetic changes to off springs raising ethical questions regarding “designer babies” [76]. Moreover, the majority of the studies target a narrow subset of genes—primarily AGT and LDLR—limiting the broader applicability of these techniques. In order to form a more definitive treatment for HTN it is important that more genetic loci be explored for improved and long-lasting effects. Genes such as APOB, ADDI gene and ACE genes can serve as potential loci for gene editing. Additionally, downregulation of genes is not the sole approach, upregulation of protective genes such as NOS3, ANP, and BNP can also prove beneficial in the treatment of HTN. Gene editing holds the promise for the future of precision medicine. Cutting-edge techniques like the CRISPR-Cas9 system have been effective in reducing gene expression, BP, ventricular pressure and ventricular hypertrophy. Over time, targeting these key risk factors can lead to effective management of HTN.

Epigenetics in precision medicine of precision medicine of hypertension

MiRNAs

Epigenetics serve as the body’s physiological BP regulation pathways exerting their action by altering gene expression [84] [84]. DNA expression can be altered by processes such as DNA methylation, histone modifications, chromatin remodeling and by action of miRNA [85]. Epigenetics ensure proper functioning in the body, by upregulation and downregulation of specific genes. In recent years, epigenetics, specifically miRNAs, have become a central focus in the discussion of precision medicine for HTN. A wide range of miRNA are involved in regulation of BP in the body, and dysfunction of miRNAs can lead to development of HTN. Newer studies have explored the possibility of targeting miRNA to modulate their expression—either increasing, decreasing, or inhibiting them—as treatment of HTN. Another important aspect of miRNAs is their interaction with drugs, altering their efficacy by influencing their metabolism in the body. A deeper understanding of epigenetics and their interaction with drugs can optimize efficacy of these therapies.

Ren1 gene codes for the important enzyme renin, involved in BP regulation. MiRNA-181a is a regulator of Ren1 mRNA. When miRNA-181a levels are reduced, it leads to negative regulation of Ren1 mRNA, causing elevation in BP. Similarly, elevated levels of miRNA-132 and miRNA-212 are linked to angiotensin II-induced HTN. This association was confirmed by administering angiotensin II type 1 receptor blockers resulting in decreased miRNA levels, while beta-blockers did not show similar outcomes [86].

MiRNA-122, found primarily in the liver, is linked to HTN and cardiovascular fibrosis. MiRNA-122 regulates numerous genes involved in RAAS and cardiac remodeling in the body. An increase in miRNA-122 is linked to increased angiotensinogen II activity and consequently, endothelial dysfunction and vascular fibrosis. Studies have shown that inhibition of miRNA-122 decreased pulmonary HTN, and right ventricular remodeling. Furthermore, miRNA-122 is also involved in regulating levels of molecules involved in cardiovascular function e.g. SIRT6, GDF15, porimin, and CTGF. MiRNA-122 presents a potential target for future HTN therapeutics [87].

MiRNA-155 is a microRNA implicated in development of HTN. Elevated levels of miRNA-155 are associated with inflammation and vascular dysfunction. Firstly, miRNA-155 is linked to regulation of C reactive protein (CPR) and inflammatory molecules such as IL-6. Overexpression of these inflammatory mediators induces a state of inflammation in the body leading to HTN. Secondly, miRNA-155 modulates the production of eNOS. Due to oxidative stress, inflammation, and downregulation of eNOS there is a reduced bioavailability of NO which leads to vascular dysfunction. Recent studies have targeted miRNA-155 to treat HTN and positive results have been observed. Recent studies have explored miRNA-155 as a therapeutic target in hypertensive rats, administration of miRNA-155 inhibitors e.g. antagomiR-155 lead to reduction in SBP and DBP. MiRNA-155 is also involved in development of numerous other comorbidities linked to HTN e.g. CVDs, atherosclerosis, atrial fibrillation, and aortic aneurysms among other diseases. Animal-model studies and emerging observational pre-clinical studies suggest that higher levels of miRNA-155 are linked to development of HTN therefore establishing role of miRNA-155 as a biomarker for early diagnosis of HTN and a potential therapeutic target for precision medicine [88].

MiRNA-210 is one of the most extensively studied miRNA in the context of HTN. It has a significant role in development of HTN and related conditions, specifically pre-eclampsia [89, 90]. A 2024 study investigated the link between miRNA-210 and pulmonary HTN. The study administered hypoxic treatment (10.5% O₂) to two groups of mice, adult wildtype (WT) and miRNA-210 knockout (KO) mice for 4 weeks. Hypoxia induced right ventricular hypertrophy and pulmonary wall thickening was observed in WT mice, whereas miRNA-210 KO mice did not develop these conditions. Mitochondria is one of the major organelles involved in ROS production. The study further noted that miRNA-210 is involved in upregulation of mitochondrial ROS production leading to vascular dysfunction, inflammation and subsequently HTN [91] [91]. The study highlights miRNA-210 as a potential therapeutic target for pulmonary HTN and ventricular remodeling. Numerous studies have highlighted the link between miRNA-210 and pre-eclampsia, with elevated levels of miRNA-210 observed in preeclampsia [92] [92]. A 2023 prospective cohort study explored the potential of miRNA-210 as a biomarker for preeclampsia. Plasma miRNA-210 was significantly higher in women that developed preeclampsia (19.23) vs. those without preeclampsia (4.29). The researchers established a cut-off value of 2.28 times change than normal, with a sensitivity of 87.5% and specificity of 68.8% for pre-eclampsia diagnosis [93]. MiRNA-210 can serve as a non-invasive biomarker for pre-eclampsia.

MiRNA are not only associated with development of HTN but also exhibit protective effects against HTN in our body. One prominent example is miRNA-483, linked to down-regulation of many genes and molecules involved in pulmonary vascular remodeling, inflammation, endothelial dysfunction and fibrosis. A 2020 study by Zhang et al., investigated the impact of miRNA-483 on pulmonary HTN. The study observed a strong link between low levels of miRNA-483 and idiopathic pulmonary HTN as well as the severity of the disease. The study also found that miRNA-483 is involved in lowering the expression of TGF-β, TGFBR2, IL-1β, β-catenin, CTGF, and ET-1 genes involved in inflammation. Overexpression of miRNA-483 inhibits the expression of these genes as well as linked to improvement of pulmonary HTN and right ventricular hypertrophy. Similar results were recorded when researchers exogenously delivered miRNA-483, leading to suppression of pulmonary HTN genes and reversed the pathogenesis of pulmonary HTN [94].

Pharmaco-epigenetics in hypertension precision medicine

An essential aspect of epigenetics is their interaction with pharmacological drugs. Epigenetics are involved in metabolism of drugs, potentially enhancing or decreasing their efficacy, by converting them into active or inactive metabolites. Understanding the unique interaction between epigenetics and drugs can help in the development of precision medicine. One example of epigenetic drug interaction involves aspirin. Studies suggest that effectiveness of aspirin is associated with miRNA-135a-5p and miRNA-204-5p, due to their role in aspirin resistance. These miRNAs modulate the expression of various genes such as THBS1, CORO1C, CDC42, and MAPRE2. Aspirin helps in prevention of atherosclerosis and is a drug of choice for preeclampsia. Targeting these miRNAs can improve the efficacy of aspirin and help in improved treatment of HTN [86].

Mounting evidence in recent years suggests that miRNA plays an important role in modulating the response of statin drugs. In their study Liu et al., observed that miRNA-27b and miRNA-206 has an impact on statin metabolism. Atorvastatin, a popular lipid reducing therapy, exhibits 6 times variability of effectiveness based on subjects. This variability is largely attributed to CYP3A enzyme responsible for drug metabolism. MiRNA-27b and miRNA-206 are linked to regulation of CYP3A and consequently linked to effectiveness of stains. The study found that miRNA-27b and miRNA-206 were linked to decreased expression of CYP3A leading to decreased metabolism of stains making them more effective [95].

A 2019 study by Solayman et al., investigated the effect of miRNAs on β-blockers metoprolol and atenolol. The study observed that the serum miRNA-19a was linked to improved response of the β-blockers metoprolol and atenolol. Similarly, miR-101 and let-7e also showed positive correlation with effectiveness of β-blocker therapy [96]. The study highlights the important role of circulating plasma miRNAs, specifically miRNA-19a, miR-101, and let-7e, as reliable and non-invasive biomarkers for predicting the antihypertensive response to β-blockers. Furthermore, administration of miRNAs e.g. miRNA-19a in combination with anti-hypertensive therapies can lead to improved outcomes in patients. As discussed earlier, thiazide diuretics are crucial for the treatment of HTN. A 2024 study by Chekka et al., explored several miRNAs as predictive biomarkers for thiazide therapy response. The study analyzed 754 miRNAs, and identified that miRNAs 193b-3p, miR‐30d, miR‐142‐3p, and miR‐423‐5p were linked with thiazide therapy response [97]. The study highlights an important role that miRNAs can play in monitoring the effectiveness of anti-hypertensive therapies, enabling optimization of treatments based on individuals.

MiRNAs can significantly alter the efficacy of pharmacological HTN therapies. Tailoring clinical decision-making in HTN treatment based on an individual’s unique epigenetic profile can potentially improve the current landscape of HTN treatment. Due to the crucial role miRNA’s play in the various BP regulation pathways they can effectively serve as biomarkers for early diagnosis, real-time monitoring, and prognosis of HTN. Furthermore, leveraging AI-based systems to interpret miRNA profiles and recommend pharmacological treatments can enhance therapeutic effects and optimize disease management [98].

Despite exhibiting strong potential, challenges surrounding the integration of miRNA in clinical practice remain. Although studies demonstrate association between altered miRNA profile and HTN, correlation does not equate to causation. Thus, while miRNA can serve as clinical biomarkers, direct targeting of miRNA as potential therapeutic strategy remains ambiguous [99]. Additionally, due to limited literature on the therapeutics of miRNA in HTN drawing conclusion on the true efficacy of miRNA-based treatments is difficult. Technical limitations such as lack of specificity and sensitivity raises the risk of error or misinterpretation. To truly establish the role of miRNA clinical precision medicine of HTN there is a need for large-scale clinical trials with well-stratified patient groups in human model studies to validate the abilities of miRNAs. A crucial issue related to miRNA that needs further examination is the variability across ethnicities. As already established genetic polymorphism can be linked to HTN variably. Since miRNA exert their effect by regulating genes it is important to understand the interaction between miRNA and genes in various ethnic populations [100] (Table 2).

Table 2.

Role of MiRNAs in BP regulation of the body

MiRNA	Function & Role in Hypertension	References
MiRNA-27b	• MiRNA-27b is linked to endothelial function and production of NO. • Dysregulation of miRNA-27b causes excess proliferation of cells, vascular remodeling, vascular dysfunction and eventually leads to HTN.	[101]
MiRNA-122	• Role in synthesis of NO. • Dysfunction of miRNA-122 leads to impaired production of NO, increased BP and eventually HTN.	[102]
MiRNA-155	• MiRNA-155 is involved in regulation of inflammatory response and immune function. It regulates the expression of cytokines and inflammatory molecules e.g. CRP, and IL-6. • Dysregulation of this miRNA causes a proinflammatory state in the body leading to vascular dysfunction, vascular remodeling and eventually development of HTN.	[103, 104]
MiRNA-181a	• MiRNA-188a is a post-translational inhibitor of renin and modulates levels of renin. • Altered levels of miRNA-188a leads to overstimulation of RAAS, and eventually HTN.	[103]
MiRNA-206	• MiRNA-206 is involved in protective effects against vasoconstriction and vascular remodeling due to hypoxia. • Low levels of miRNA-206 are linked to increased vasoconstriction and vascular remodeling due to hypoxia and eventual development of HTN.	[105]
MiRNA-210	• MiRNA-210 is involved in vascular remodeling and ischemia. • Elevated levels of miRNA-210, is linked to vascular dysfunction, vascular remodeling, and increased BP.	[89, 106, 107]

The role of microbiome in personalized hypertension management

The human body is inhabited by hundreds of trillions of microbes, e.g. bacteria, and fungi, constituting the body’s ‘microbiome’. These microbes possess more than 100 times more genes than humans and perform a myriad of functions in our body. Our body’s microbiome is involved in energy liberation, metabolic function, and modulates the immune system. One of the major ways microbes contribute to the functioning of our body is through production of metabolites such as amino acids, enzymes, proteins, vitamins and hormones. Specific bioactive metabolites including SCFA, trimethylamine N-oxide, indoles, and phenylacetylglutamine are essential for the body. Research has established a strong link between microbiome-derived metabolites and BP regulation, with short-chain fatty acids demonstrating the ability to reduce BP. Furthermore, microbiome also influences drug metabolism, underscoring its relevance in precision medicine [108, 109].

The most common techniques utilized to analyze the microbiome in humans include metatranscriptomics, metaproteomics, metagenomics and metabolics. Furthermore, advanced AI tools have enabled analysis and prediction of gut microbiome [110, 111]. AI models analyze 16s rRNA from fecal samples to predict microbiome and differentiate among various groups e.g. CVD and non-CVD patients. Machine learning plays an important role in training these models refining their accuracy and clinical applicability [112].

A 2023 study by Bianchetti et al., among 7 participants used cutting-edge technology to curate a personalised diet plan based on the subject’s unique gut microbiome, genomic information (e.g. SNPs), physiological parameters, and physical activity levels, among other factors. It was observed that the diet based on recommendations from the model helped in significant reduction in BMI, as well as fat and weight loss. Additionally, participants experienced an increase in muscle mass and a positive shift in body percentages. Body’s physiological markers also improved including decreased heart rate and an overall enhanced cardiac health. Moreover, the overall microbial diversity improved, with a substantial increase in unique microbial species. Specifically, an increase in Lachnospiraceae bacterium, which is involved in the production of SCFAs, and an increase in Lachnobacterium, which is positively associated with animal-based nutrients [113].

Similarly, a 2024 study by Kallapura et al., explored the impact of microbiome-based nutrition among 30 participants on several parameters of diabetes and HTN. The microbiome analysis was performed on test arm participants (n = 15) using whole genome shotgun metagenomics. The test arm was given a personalized diet while the other participants were given general diabetes food guidance. After 90 days the test arm participants showed significantly decreased HBAc1 level, with 5% decrease in SBP. Additionally, there was a 19.5% decrease in CRP levels, a marker of inflammation. An increase in alpha diversity of the microbiome was recorded in the subjects. Notably, a two-fold increase was seen in Phascolarctobacterium succinatutens, Bifidobacterium angulatum, and Levilactobacillus brevis species that have positive impact on host, in contrast there was decrease in Alistipes finegoldii, and Sutterella faecalis species, that have a negative impact on the host [114].

In addition to dietary intervention, fecal microbiota transplant (FMT) has emerged as an effective technique to modulate gut microbiota and in extension manage HTN. A 2025 randomised, placebo-controlled clinical trial by Fan et al., among 124 patients explored the impact of FMT on HTN. The FMT interventional group showed decrease in SBP but the results did not persist after repeated intervention. Additionally, an increase in species such as Eubacterium sp. CAG 180, Parabacteroides merdae, Desulfovibrio piger Prevotella copri, Bacteroides galacturonicus among other were seen that were linked to improved SBP as well as metabolites such as aspartate, phenylalanine, methionine serine, glutamine, and sarcosine [111]. The study shows that FMT has the potential to improve HTN management by decreasing SBP and improving the gut microbiota.

Microbiome plays an important role in metabolism of drugs for HTN [109]. An important example of the impact of microbiome on drugs is the microbiome-drug interaction with statins. Statins are cholesterol reducing drugs, with high dose statins expected to reduce LDL-C by 50%. The efficacy of statins can vary based on gut bacteria. Studies have shown that acids derived from bacteria such as lithocholic acid, taurolithocholic acid, and glycolithocholic acid are linked to simvastatin induced lowering of LDL-C. Furthermore, phyla Firmicutes and Fusobacteria have been linked to reduced levels of LDL-C [115]. A 2024 study by Li et al., examined the effect of Angiotensin II Receptor Blocker (ARB) modified microbiota on BP, vasculature and intestines. 16 S rRNA amplicon sequencing was employed to analyze gut microbiome and microbiota-derived metabolites. The results showed that after administration of ARB modified microbiome there was marked decrease in SBP, ROS and deposition of collagen in vasculature. Structural modification in the intestine, along with decrease in 6 beta-Hydroxy testosterone and Thromboxane B2 in blood was observed. The researchers concluded that ARB modified microbiota had a protective effect against inflammation, vascular remodeling, metabolic dysfunction, internal dysfunction and overall HTN [116].

In recent years, there has been an increased focus on the potential of gut microbiota in the treatment of HTN. Though previous studies mainly focused on the effect of gut microbiome modulation on HTN in animal models the results of these experimental studies have been verified in human models to some extent. In this context, a meta-analysis conducted by Khalesi et al., of nine human randomized control trials with study size of 543 participants examined the effect of probiotic therapy on BP. The study findings showed a significant reduction in SBP (-3.56 mm of Hg) and DBP (-2.38 mm of Hg) [117]. Additionally, administration of more than one probiotic species led greater reduction in BP. In clinical practice, oral probiotics supplementation can act as a strong tool to alter microbiota, improving the management of HTN [115]. Probiotics containing microbes such as Lactobacillus, Bifidobacterium, and Enterococcus provide patients with a variety of SCFA leading to anti-inflammatory and beneficial metabolic effects. Administration of probiotics have shown BP lowering effects in humans. In addition to oral probiotics, dietary interventions to target gut microbiota composition can improve BP regulation in the body [116]. Study by Bianchetti et al., showed that personalised diet plan based on the subject’s unique gut microbiome, genomic information (e.g. SNPs), physiological parameters, and physical activity levels, was effective in BMI reduction, as well as fat and weight loss. The personalised diet helps in improving the body’s physiological markers also improved including decreased heart rate and an overall enhanced cardiac health. Kallapura et al., further strengthens the evidence as results from the study show dietary interventions targeting microbiota were successful in improving SBP, and improving the markers of inflammation (CRP) and diabetes (HBA1c) [110]. Moreover, FMT represents another technique currently being utilized to modulate gut microbiome with initial studies—such as by Fan et al. [111], —showing positive results, still a need for further examination is needed to determine the true validity of these techniques [117].

A thorough examination of the available literature shows that high efficacy, limited adverse effects, cost-effectiveness, and convenience of oral administration, microbiota modulation within the framework of precision medicine is a highly effective therapeutic strategy for clinical management and treatment of HTN. Collectively, these studies highlight the benefits of personalized interventions and management based on microbiome data. These therapeutic approaches in precision medicine of HTN can enhance the overall health outcomes in HTN patients.

AI-based models for personalized treatment of HTN

The advances in AI have been remarkable over the past few decades, and AI tools hold potential to revolutionise medicine [118, 119]. AI has been the unifying force in precision medicine by integrating the key components of genetics, epigenetics and microbiome enabling the development of personalized healthcare.

Currently, sophisticated AI-based models are being utilized in early detection, diagnosis, management, and treatment of HTN. By digitising daily BP records and converting them into time-series data, AI-based predictive models can forecast BP variances with remarkable accuracy up to 4 weeks in advance. These models can improve management of HTN, reduce hypertensive episodes and protect against complications linked to chronic HTN [120]. Predictive AI models leverage genomics, medical history, behavioral, environmental and socioeconomic factors to highlight individuals at high risk of HTN, enabling early preventative interventions. Similarly, newer AI models can accurately diagnose HTN, monitor BP, and provide target sites for precision therapy [121–123] (Table 3).

Table 3.

AI-based models in precision medicine of HTN

Study	Study Population	Type of Model	Results
Wu et al., 2023 [125]	Training data set: 9624 Test data set: 2337	AI-based Clinical Diagnosis model	1. The AI model (0.7421) had a higher accuracy than a medical intern (0.7262) but lower than am experienced cardiologist (0.8959).
Leitner et al., 2024 [126]	141 subjects	AI-based model for Management	1. At12 weeks there was a decrease in SBP and DBP by 5.6 and 3.8 mm of Hg.
Nakai et al., 2021 [110]	40 metropolitan areas participants vs. 30 regional clinic participants	AI-based Gut microbiome model	1. Normotensive patients had higher levels of Ruminococcus spp. and Eubacterium eligens 2. EH subjects had higher levels of Acidaminococcus spp., Eubacterium fissicatena and Muribaculaceae spp. 3. Masked HTN patients had higher levels of Alistipes spp. and Muribaculaceae spp. 4. HTN patients had higher levels of SCFA but lower levels of SCFA receptor leading to decreased protective effects 5. Altered gut microbiota-derived gene pathways in HTN patients.
Oh et al., 2022 [127]	Training data set:14,934 patient with T2DM	AI-based model for Treatment	1. The model was designed to recommend mono, dual and triple HTN therapies based on patients’ requirements. 2. Based on expert evaluation the concordance rate for recommended therapies was 85.18% for male and 81.48% for females.

In 2023 Wu et al., developed an AI-based model in line with the clinical diagnosis process to diagnose secondary HTN. They trained and validated the model on a data set of 9624 individuals. The test set consisted of 2337 individuals. In the final outcome, the accuracy of the model was 0.7421. The accuracy was more than that of a medical intern with an accuracy of 0.7262, but the accuracy of experienced cardiologist (0.8959) and internal medicine resident (0.8824) was superior. The researchers concluded that this model was a great alternative for secondary HTN diagnosis and would reduce strain on medical professionals as well as minimising redundant examination [124].

The 2024 study by Leitner et al., utilized a fully digital, autonomous, AI–based lifestyle coaching program to manage BP. In this single-arm non randomised trial 141 subjects were recruited. They were given BP monitors and activity trackers. Participants completed an app-based survey to train a personalised machine learning model. The participants were monitored over 24 weeks. The AI model collected data in various categories such as step count, sleep time and salt intake to train the AI model. The AI model would help in moderating behavioural changes like stress management, sleep, hygiene, physical activity and dietary choices to regulate BP. The study found that by 12 weeks there was a decrease in SBP and DBP by 5.6 and 3.8 mm of Hg, respectively. The model proved especially effective on stage-2 HTN patients, SBP and DBP decreased by 9.6 and 5.7 mm of Hg, respectively. The percentage of subjects with controlled BP increased by 17.2% and 26.5% at weeks 12 and 24, respectively. The researchers concluded that AI-based HTN management models are a great alternative to the current generic, non-personalized HTN management techniques [125].

A 2021 study by c explored the application of AI in precision medicine HTN, focusing on analyzing and predicting gut microbiome and its link to BP. The model can be used to optimize gut microbiome through personalised diet plans. The study employed machine learning multivariate covariance analyses to predict HTN outcomes among various groups based on microbiome. The microbiome was predicted using two primary methods. Firstly, they analyzed plasma and fecal metabolites e.g. SCFA, as well as using an AI-based model to analyze and predict fecal microbiome by performing 16 S rRNA gene sequencing. The study included 40 participants from metropolitan areas and 30 from regional clinics. The results revealed that there was no significant difference in α- and β-diversity of gut microbiome between healthy controls, essential HTN, and masked HTN patients. However, there were some differences between the species found in various groups; normotensive patients had higher levels of Ruminococcus spp. and Eubacterium eligens, EH subjects had higher levels of Acidaminococcus spp., Eubacterium fissicatena and Muribaculaceae spp., while masked HTN patients had higher levels of Alistipes spp. and Muribaculaceae spp. The major finding of the study was that, despite the limited difference in taxa between microbiomes of various groups, there was significant difference in gut microbiota-derived gene pathways, especially between normotensive and HTN patients. Another notable finding of the study was that the hypertensive patients exhibited higher levels of SCFA, such as acetate and butyrate, despite their known association with lower blood pressure. This paradoxical finding was attributed to a decreased expression of SCFA receptors, such as GPR43, on immune cells. This dysfunction in the molecule signalling pathway gives rise to a proinflammatory state in the body, characterized by increased number of neutrophils and cytokines, linked to HTN. The study highlights the potential of AI-based models in precision medicine in conjunction to microbiome [110].

In 2022 Oh et al., developed an AI-based precision medicine model employing reinforcement learning to treat HTN in patients with T2DM. The AI based model recommended mono, dual and triple HTN therapies based on patients’ requirements. To assess the accuracy, researchers evaluated the concordance rate of the recommended therapies. The concordance rate was 85.18% for male and 81.48% for females. Furthermore, there was a decrease in comorbidities linked to HTN due to effective treatment recommendation by the AI-based precision medicine model to the patients. Furthermore, a decrease in BP was also seen among subjects. The researchers concluded that this AI model was effective in providing reinforcement learning based antihypertensive treatment recommendation to real life HTN patients [126].

AI offers great promise for precision medicine of HTN, but it also has certain limitations. Key concerns of AI-based models include ethical concerns, privacy issues, and biases among others challenges. A systematic review of 24 studies conducted in 2023 highlighted eight main themes related to patients concerns towards AI in precision medicine—the most common concern being regarding privacy and data security followed by economic impacts and discrimination based on ethnicity. Other concerns included deterioration of informed consent, privacy related to genetic information, diagnostic accuracy, and impact on doctor-patient relation [126].

Overfitting and underfitting remain a critical challenge associated with AI-based models. Overfitting models become overly attenuated to training data sets and cannot generalize to newer data sets. In contrast, an underfitting model algorithm cannot fully harness the underlying patterns within the dataset leading to poor predictive power performance. Future research needs to address the technical, ethical, and patient-related limitations of AI-based models in precision medicine of HTN. The overfitting and underfitting models can be improved by modifying model parameters and enhancing training data sets. Additionally, AI-models need to be trained on large data sets encompassing populations of variable age, gender, race, and, geographical locations to increase generalizability and reduce bias. However, utilization of large data sets raise concern regarding the data privacy; a concern still rampant across patients. Currently, laws and regulatory framework do not address the use of data obtained from AI model leaving a gap for unethical use of this data. Ethical issues posed by AI-based models need to eradicated through development of regulatory framework such as Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis-AI (TRIPOD-ML) and Standard Protocol Items: Recommendations for Interventional Trials–Artificial Intelligence-AI (SPIRIT AI). While, these guidelines govern protocols related to AI in research expanded guidelines are needed that address all aspects of AI in medicine. Additionally, educational initiatives aimed at health professionals and patients are important to enhance trust and support for AI in clinical practice. While AI models show acceptable accuracy, users report several instances of inaccurate content generation, non-existent reference generation, and hallucination. The situation becomes especially dire as incorrect information and diagnosis can cause harm to the patients, deteriorate doctor-patient trust, and lead to loss of confidence on AI-models. It is crucial that experts continuously monitor AI generated content for quality and accuracy to enhance the trust of patients. AI-based models have shown promising results in clinical studies but its integration in clinical practice remains a challenge. It is crucial that newer generations of AI models address these concerns to improve the integration of AI in clinical practice [127].

Weighing both the advantages and limitations of AI-driven precision medicine of HTN it can be concluded that AI represents the most effective strategy in clinical HTN management due to its binding capacity of all other aspects of precision medicine. By leveraging synergy between genetics, miRNA, microbial profile, dietary patterns, and unique biological profile, AI enables a highly personalized and holistic approach towards HTN. The potential of AI has been made evident by numerous studies—most notably the study by Leitner et al., discussed above that utilized a fully digital, autonomous, AI–based lifestyle coaching program to manage BP. The model considered various factor such as activity level, food habits, and sleep patterns to moderate behavioral changes like stress management, sleep, hygiene, physical activity and dietary choices to regulate BP. Moreover, as discussed in Sect. 6.3 the role of microbiome in HTN, AI-based tools can help optimize management of HTN by modulating microbiome. AI-based tools can help in microbiome optimization by considering factors such as genetics, age, diet, and unique microbiota to propose an optimal regiment based on prebiotics and dietary interventions. Additionally, in terms of fecal microbiota transplant (FMT) AI-based tools can improve the approach by optimizing selection of donors and recommending therapy according to individual’s unique requirements [127]. Due to the multifaceted capabilities, AI holds the capability of improving all aspects of clinical HTN from prevention, early diagnosis, therapeutics, to ensuring long-term disease management. Through continuous monitoring of blood pressure and biomarkers, coupled with automated reminders and patient engagement tools AI-based systems in medicine can reshape clinical HTN [121].

Conclusion

In conclusion, precision medicine holds the future for effective treatment of HTN. Genetic polymorphism and mutation in key genes disrupt the critical BP regulation pathways, contributing to development of HTN. MiRNAs are significant factors impacting expression of genes linked to HTN. Microbiome-based nutrition has helped in improving overall microbial biodiversity. AI-based models integrate the genomic, epigenetic, and microbiome information and provide effective diet plans, lifestyle changes and recommend therapeutic strategies. These models have demonstrated improvements in SBP, DBP, vascular remodeling, pulmonary HTN, and overall physiological parameters. Despite the immense potential offered by these cutting-edge techniques their implementation in clinical setting remains a challenge. Researchers have raised concerns about the safety and efficacy of techniques like gene-editing and epigenetic manipulation. Ethical concerns related to AI-based models has led to limited implementation of this revolutionary technology in management of HTN.

Author contributions

Conceptualization methodology, Y.W. validation, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; formal analysis, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; investigation, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; resources, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; data curation, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; writing—original draft preparation, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; writing—review and editing, A.S., R.A., S.N., Z.H.M., A.J., D.U.O., Y.W.; supervision, Y.W.; project administration, Y.W.; funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

Not applicable.

Data availability

Additional data will be provided on suitable request to corresponding author.

Declarations

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Competing interests

The authors declare no competing interests.