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Hypertension, defined as a condition associated with ≥140 mm Hg systolic blood pressure or ≥90 mm Hg diastolic blood pressure, affects over one billion people worldwide1 and in 2009 it cost the US health care system more than $73 billion2. Despite the availability of many anti-hypertensive therapies, individual responses vary and efficacy remains a concern. Current treatments have yielded only modest reductions in the overall disease risk even in countries where therapeutics are available and affordable. The initiating causes and the pathogenic mechanisms for disease and its comorbidities remain largely unknown, and prognostic markers for adult hypertension that could improve its diagnosis, prevention, and ultimately its management are not yet available. As a result, nearly 28% of the US population and a similar proportion of the adult Western European and Canadian populations suffer from what is known as “essential hypertension”3, which is a primary component of several complex, multifactorial, multigenic conditions that are commonly associated with high levels of morbidity and mortality from diabetes, cardiovascular and renal disease. If the current rise in the number of hypertension cases is not abated, total annual global healthcare costs resulting from suboptimal blood pressure for those older than 30 years of age could amount to $3.6 trillion over the next 10 years4.
The causes of essential hypertension remain poorly understood even though the complex mechanisms for blood pressure (BP) regulation have been extensively characterized in both humans and animal models5,6,7. Comprehensive study of more than a dozen inbred rat strains that recapitulate many aspects of hereditary human hypertension has added substantially throughout the years to our understanding of the underlying physiological and molecular pathways, the genetic complexity of risk and treatment responses, as well as the pathological consequences of hypertension8. In fact, many interventions that lead to a lowering of blood pressure were identified first with these experimental model systems9,10. Detailed annotations of such experimental models are currently available (PhysGen Knockout Program, http://rgd.mcw.edu). These studies in experimental models are however only the first step in the quest to clarify the genetic and phenotypic architecture of this complex human disease11,12,13,14,15.
Hypertension is a highly heritable trait16,17 and recent genome-wide linkage and association studies (GWAS) as well as candidate gene approaches clearly demonstrate the multigenic complexity of essential hypertension18,19,20,21,22. The International Consortium for Blood Pressure Genome-Wide Association Studies, which used a multistage design in 200,000 individuals of European descent, recently identified 16 novel functional genetic variants, associated with high blood pressure in human populations20. (These variants are commonly known as quantitative trait loci, or QTLs.) Six of these loci involve genes previously known or suspected to regulate blood pressure, with the other genetic variants pointing to novel pathways that influence blood pressure and cardiovascular disease risk.
An unexpected and disconcerting observation from these genetic studies is that the discovered genetic variants, individually and collectively, account for only a small fraction of phenotypic variation and disease risk. For example, these blood pressure QTLs together account for only a small proportion of BP variation (up to 5 mmm Hg), yet their typical effect size is sufficient to raise cardiovascular disease risk in human populations18,19,20,21,22. Importantly, although the CHARGE and GlobalBPgen consortia established and replicated the effects of 8 novel loci on BP, the cumulative effect of these 8 loci explained only ~1% of BP variance18,19. These results are especially surprising given the substantial heritability of BP, estimated between 30% and 40%15,16. Similar results have emerged in GWAS of other complex conditions in humans and genetic studies of other species11,12,13,14,15. This difference between estimated and observed variance is termed ‘missing heritability’, the search for which has now become one of the primary goals for research on hypertension and other complex conditions11.
To explain the ‘missing heritability’ of complex traits, several hypotheses have been proposed, including over-estimates of heritability, unexplored regions of the genome, untested classes of genetic variants, the action of many rare genetic variants, and gene interactions11,23,24. Phenotypic variation can also be regulated independently of changes in DNA sequence, thereby escaping detection with classical genetic approaches25,26,27,28,29,30,31. These heritable epigenetic changes could explain some of the ‘missing heritability’ in hypertension, and some circumstantial evidence involving modification of genes that could affect important pathways in hypertension is beginning to emerge, further prompting the need for experiments specifically designed to prove a causal relationship32.
Epigenetics is defined as the transmission from one cell generation to the next (through mitosis) or from one organismal generation to the next (through meiosis) of gene expression patterns that do not rely explicitly on differences in DNA sequence25. The term was originally introduced to account for the maintenance of cell- and tissue-specific gene expression patterns across mitotic cell divisions throughout somatic development. Many cell functions such as tissue-specificity, germline-specificity, imprinting and X-chromosome inactivation, rely on correct epigenetic control of gene expression30,31. Introduction of high-throughput technologies, which now enable epigenetic features to be comprehensively and quantitatively profiled across the genome, has led to exciting evidence in animal models where epigenetic changes have been documented not only during development but also in adult conditions such as cancer33, cardiovascular disease34, diabetes35, obesity36, and longevity37. Evidence for epigenetic effects in humans is more limited because of the considerable challenges in study design needed to reliably distinguish the various sources of phenotypic variation. As a result, many questions remain, such as defining the environmental and genetic factors that trigger epigenetic changes, defining the molecular mechanisms that maintain and where necessary reverse epigenetic features, assessing the relative contributions of genetic, environmental and epigenetic factors, and characterizing the impact of epigenetic changes on phenotypic variation and disease risk within and across generations.
Epigenetic changes are orchestrated by several molecular processes, including nucleic acid methylation, histone modification, nucleosome positioning, transcription control with DNA binding proteins and noncoding RNAs, and translation control with microRNAs and RNA binding proteins26,27,28,29,30,31. Of the many modes of epigenetic control, the best studied are histone modification and DNA methylation. Histone modification is an important mechanism that leads to changes in the nucleosome to constrain DNA wrapping around its histone core (nucleosome positioning). Chemical modification of the N-terminal tails of histone proteins forms a “histone code” that regulates gene activity. DNA methylation is another important mechanism of epigenetic control in which methylation of DNA occurs at the cytosine base of DNA, often in the context of CpG dinucleotides. In addition, other forms of chemically modified DNA have recently been reported26. An important but less studied mode of epigenetic control involves noncoding-RNAs (microRNAs as well as other long and short RNAs) that regulate gene expression and mRNA translation. Systematically characterizing these various kinds of epigenetic marks across the genome, during development and throughout the life of an organism, is a major challenge, as is dealing with cellular and temporal heterogeneity in these marks.
Studies in experimental animals show that epigenetic changes can arise throughout life, from early embryos to old age, as a result of developmental and physiological processes, environmental exposure, and stochastic events. The epigenome is thought to be most vulnerable to modification during embryogenesis when DNA synthesis is rapid and when both DNA methylation patterns and chromatin structure required for normal development are established. During development for example, maternal nutritional status as well as altered hormonal and stress profiles can profoundly affect epigenetic features with long-term impacts on disease risk. In addition, studies in twins at different ages show that, although identical at birth, the epigenome diverges during lifetime38. An understanding of the mechanisms that transmit environmental and genetic signals to the molecular machinery responsible for epigenetic changes that will undoubtedly emerge would mechanistically explain the molecular embedding of early childhood experiences (“nurture”) onto the genome (“nature”)39.
In many organisms, some epigenetic changes are not erased during gametogenesis and can affect the phenotype and health not only of immediate offspring, but also of future generations through transgenerational effects27,28,29,30,40,41,42,43,44,45,46,47,48. Several studies in rodents and other species have revealed remarkable evidence for heritable epigenetic changes where the phenotypic effects of environmental exposure and genetic variants can be transmitted epigenetically across multiple generations. In some circumstances, these effects can be as strong as conventional genetic effects, endure across multiple generations, transmit through the male or the female germ-lineage, and reverse under certain conditions44,45. Epigenetic inheritance is usually determined by a combination of genetically-controlled susceptibility of the parental genome to various stressors and the vulnerability of the offspring’s genome to these inherited epigenetic changes. Such changes enable homeostatic adaptations of the epigenetic code in response to various environmental and genetic stressors within a parent’s lifetime to be communicated to the offspring as “preadaptations” to the particular environment in which they live and the family to which they belong27,28,49,50,51,52.
Many questions emerge from these considerations: Are epigenetic marks and features a cause or consequence of hypertension? Do epigenetic changes contribute to comorbidities of hypertension such as diabetes, cardiovascular and renal disease? Are epigenetic features indicative prognostic or diagnostic biomarkers for human hypertension? Are epigenetic marks of hypertension fixed early in life rather than changing dynamically in response to various perturbations? To what extent are these epigenetic features reversible in a general or in a targeted manner? What is the molecular basis for epigenetic memory related to hypertension within and across multiple generations, how are these marks established, and how do they differ from other epigenetic features?
In parallel with studying conventional epigenetic features such as methylation profiles and histone modification, important insights could be gained from investigating the effects of environmental perturbations on mRNA, microRNA and non-coding RNA expression patterns, and their potential associations with the physiological changes during tissue and organ development as well as disease initiation and progression.
The Working Group prioritized three questions that require immediate attention:
The WG recognizes that these proposals raise considerable challenges. Epigenetic studies, especially those that involve transgenerational effects, will be complicated in humans because of issues related to study design, statistical power, environmental and genetic heterogeneity among families and populations, and the dynamic nature of epigenetic changes compared to the stability of DNA sequences. Studies with animal models face similar challenges. In addition, physiological and pharmacological research has made important contributions to treatment, and studies of both monogenic and multigenic variation have provided important insights about molecular functions and pathogenic mechanisms. But substantial problems remain for BP management. Integrating epigenetic studies with ongoing studies may lead to breakthroughs in our understanding of BP control.
The NHLBI Working Group identified a remarkable number of currently existing molecular, genomic, physiological and computational tools and approaches that could meaningfully move this field forward. The WG also identified several important technology needs.
Over the past decade many genomic and proteomic databases and technologies have been developed. These databases enable systematic collection, storage, and distribution for research of tissues and cells. Appropriate databases of patient information, including their genetics, lifestyle, clinical history, and other relevant information, have also emerged. Similar databases are related to studies of model organisms so that efficient comparative analyses are increasingly feasible. Numerous experimental models are already available and continue to be developed as information resources for many aspects of mouse genetics and biology, including the NIH-funded initiative the “Knockout Mouse Project” (KOMP) http://www.nih.gov/science/models/mouse/knockout), the Mouse Genome Database (http://www.informatics.jax.org), and the Mouse Phenome Database (www.phenome.jax.org). The Rat Genome Database (http://rgd.mcw.edu) contains all of the genomic rat model systems including inbred, consomic and knockout strains. Other resources help researchers identify appropriate model organisms, e.g. “Link Animal Models to Human Disease” (LAMHDI) (http://www.lamhdi.org), existing clinical cohorts (e.g., http://web.chargeconsortium.com) or access other information relevant for the relation between genotype and phenotype, e.g., Genotypes and Phenotypes (dbGaP) database (http://www.ncbi.nlm.nih.gov/gap). A specific catalogue enabling inquiries on the parent-of-origin effects and imprinting in mice can be found at http://igc.otago.ac.nz/home.html. Databases as well as analytical and graphical tools that specifically enable investigation of new levels of regulation and complexity associated with epigenetic studies will need continuous development and wide availability to facilitate data-mining. Computational methods to manage large genomic data sets are becoming increasingly sophisticated. Such tools can integrate information from various levels of functionality that include DNA sequence, RNA expression, protein isoforms and their post-translational modifications cell, tissue, organ and organismal phenotypes, as well as lifestyle, environmental, dietary and microbial information.
Particularly urgent research needs include development of new technologies to assess epigenetic features in single cells in vitro and in specific cell types in vivo. Surrogate markers in blood cells must also be identified as a way to interrogate cell populations that are generally inaccessible for direct analysis in humans. Finally, technologies are needed to modulate epigenetic changes with greater specificity than genome-wide targeting.
The working group concluded that epigenetics research should incorporate multispecies comparisons to benefit from evolutionary insights and perspectives. Studies will require coordination of multidisciplinary teams combining expertise in clinical and basic research, as well as in computational and modeling methods. New insights and hypotheses will be generated through genomic and epidemiological surveys, including leveraging existing clinical and epidemiological cohorts, experimental animal models and biological materials to test in new experimental and clinical studies. Study designs will need to be based on sufficient statistical power to handle the likely complexity associated with the heterogeneous causes and consequences of epigenetic changes. Phenotyping at a comparable level of rigor, accuracy, and detail as surveys of epigenetic features will be required. Multiple levels of functionality, from cells to the intact organism, should be studied, and the use of several modalities for inducing experimental hypertension in various model systems would help establish general versus context-specific principles. Finally, such endeavors will require the use and continued development of technologies that enable rigorous and quantitative measures of epigenetic and physiological changes.
Sources of Funding: The proceedings of the Epigenetics and Hypertension WG were supported though funds provided by the National Heart Lung and Blood Institute.
Useful resources links mentioned in the text
PhysGen Knockout program (“Mechanistic Characterization of Genes for Hypertension and Renal Disease”) http://rgd.mcw.edu
The Knockout Mouse Project (KOMP) http://www.nih.gov/science/models/mouse/knockout/
Link Animal Models to Human Disease http://www.lamhdi.org/
Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium http://web.chargeconsortium.com
Genotypes and Phenotypes (dbGaP) database (http://www.ncbi.nlm.nih.gov/gap)
Database of parental origin effect on mouse gene imprinting http://igc.otago.ac.nz/home.html
Allen W. Cowley, Jr., Department of Physiology, Cardiovascular Center, Medical College of Wisconsin, Milwaukee, WI.
Joseph H. Nadeau, Institute for Systems Biology, Seattle, WA.
Andrea Baccarelli, Laboratory of Environmental Epigenetics, Exposure Epidemiology and Risk Program, Departments of Environmental Health and Epidemiology, Harvard School of Public Health, Boston, MA.
Kathleen Berecek, Department of Physiology & Biophysics, UAB Comprehensive Diabetes Center, University of Alabama at Birmingham, Birmingham, AL.
Myriam Fornage, Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX.
Gary H. Gibbons, Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, GA.
David G. Harrison, Clinical Pharmacology, Vanderbilt School of Medicine, Nashville, TN.
Mingyu Liang, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI.
Peter W. Nathanielsz, Center for Pregnancy and Newborn Research, Dept. OB/GYN, The University of Texas Health Science Center at San Antonio, San Antonio, TX.
Daniel T. O’Connor, Department of Medicine, University of California at San Diego, San Diego, CA.
Jose Ordovas, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA., The Department of Epidemiology and Population Genetics. Centro Nacional Investigación Cardiovasculares (CNIC) Madrid, Spain; and IMDEA Alimentacion, Madrid, Spain.
Weiqun Peng, Department of Physics, The George Washington University, Washington, D.C.
Marcelo Bento Soares, Children’s Memorial Research Center, Falk Brain Tumor Center, Northwestern University, Chicago, IL.
Moshe Szyf, Department of Pharmacology and Therapeutics, McGill University, Montreal Quebec, Canada.
H. Eser Tolunay, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD.
Katherine C. Wood, Hematology Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD.
Keji Zhao, Division of Intramural Research, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD.
Zorina S. Galis, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD.