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Translating Genomic Advances to Physical Therapist Practice: A Closer Look at the Nature and Nurture of Common Diseases

Catherine L. Curtis, Allon Goldberg, Jeffrey A. Kleim, Steven L. Wolf
DOI: 10.2522/ptj.20150112 Published 1 April 2016
Catherine L. Curtis
C.L. Curtis, PT, EdD, Department of Physical Therapy, School of Health Sciences and Practice, Institute of Public Health, New York Medical College, Valhalla, NY, 10595 (USA).
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Allon Goldberg
A. Goldberg, PT, PhD, Physical Therapy Department, School of Health Professions and Studies, University of Michigan–Flint, Flint, Michigan.
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Jeffrey A. Kleim
J.A. Kleim, PhD, School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona.
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Steven L. Wolf
S.L. Wolf, PT, PhD, FAPTA, FAHA, Department of Rehabilitation Medicine, Division of Physical Therapy, and Departments of Medicine and Cell Biology, Emory University School of Medicine, Atlanta, Georgia, and VA Center for Visual and Neurocognitive Rehabilitation, Atlanta, Georgia.
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Abstract

The Human Genome Project and the International HapMap Project have yielded new understanding of the influence of the human genome on health and disease, advancing health care in significant ways. In personalized medicine, genetic factors are used to identify disease risk and tailor preventive and therapeutic regimens. Insight into the genetic bases of cellular processes is revealing the causes of disease and effects of exercise. Many diseases known to have a major lifestyle contribution are highly influenced by common genetic variants. Genetic variants are associated with increased risk for common diseases such as cardiovascular disease and osteoarthritis. Exercise response also is influenced by genetic factors. Knowledge of genetic factors can help clinicians better understand interindividual differences in disease presentation, pain experience, and exercise response. Family health history is an important genetic tool and encourages clinicians to consider the wider client-family unit. Clinicians in this new era need to be prepared to guide patients and their families on a variety of genomics-related concerns, including genetic testing and other ethical, legal, or social issues. Thus, it is essential that clinicians reconsider the role of genetics in the preservation of wellness and risk for disease to identify ways to best optimize fitness, health, or recovery. Clinicians with knowledge of the influence of genetic variants on health and disease will be uniquely positioned to institute individualized lifestyle interventions, thereby fulfilling roles in prevention and wellness. This article describes how discoveries in genomics are rapidly evolving the understanding of health and disease by highlighting 2 conditions: cardiovascular disease and osteoarthritis. Genetic factors related to exercise effects also are considered.

“Virtually every human ailment, except perhaps trauma, has some genetic basis.”1

The above quote leads the National Human Genome Research Institute's (NHGRI, http://www.genome.gov/) summary of the implications of the Human Genome Project (HGP) for medical science. The completion of the HGP in 2003 marked the dawn of what has been called the “genomic era”2,3 and has led to biological discoveries that are advancing the understanding of human health and disease.4 Individuals at risk for various conditions are being identified prior to the onset of symptoms, facilitating presymptomatic surveillance, prevention, and early treatment.4,5 In pharmacogenetics, innovative methods are guiding drug design, and some drugs are being prescribed specific to an individual's genotype,4,5 as with some new chemotherapeutic agents.6 Such advances will benefit individuals with rare (monogenic) disorders related to a single gene and those with common (polygenic or multigenic) diseases involving multiple genes.4,5 New understanding of the genetic and molecular basis of cellular processes is yielding insight into the causes of disease4 and the effects of exercise on health-related traits.7 Clinicians, with knowledge of the effects of both disease and exercise, are uniquely positioned to fulfill roles in recovery and wellness in this new era of health care.

The HGP generated an accurate reference sequence of the human genome8 and, subsequently the HapMap Project produced a catalog of common genetic variants9 (see Figs. 1, 2, and 3 for a review of genetic terminology). Humans share more than 99.9% DNA sequence similarity, with sequences among individuals differing by less than 0.1%.10 Single-nucleotide polymorphisms (SNPs, pronounced “snips”), the most common of the genetic variants, are alterations in a single base pair in either protein-coding regions (exons) or non–protein-coding regions of the genome11 (see Figs. 4 and 5 for more on SNPs and exons). Single-nucleotide polymorphisms are markers for diversity (ie, the traits that make us unique and confer disease risk).3,11 A goal of this new era is personalized medicine, where genetic factors are used to identify risk and individualize preventive and therapeutic regimens.3,5 Clinicians keenly attuned to the environmental contributions to health and disease may be surprised that many chronic diseases known to have a major lifestyle component, such as cardiovascular disease (CVD) and osteoarthritis (OA), also are highly influenced by genetics. In this new frontier, clinicians should reconsider the role of genetics in the preservation of wellness and risk for disease to identify ways to best ward off functional decline or optimize recovery.

Figure 1.
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Figure 1.

Genome. The genome is the entire set of genetic instructions found in a cell. In humans, the genome consists of 23 pairs of chromosomes, found in the nucleus, as well as a small chromosome found in the cells' mitochondria. These chromosomes, taken together, contain approximately 3.1 billion bases of DNA sequence. Courtesy of Darryl Leja of the National Human Genome Research Institute, National Institutes of Health, http://www.genome.gov/. Accessed August 30, 2015.

Figure 2.
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Figure 2.

Chromosome. A chromosome is an organized package of DNA found in the nucleus of the cell. Different organisms have different numbers of chromosomes. Humans have 23 pairs of chromosomes: 22 pairs of numbered chromosomes, called autosomes, and 1 pair of sex chromosomes, X and Y. Each parent contributes 1 chromosome to each pair so that offspring get half of their chromosomes from their mother and half from their father. Courtesy of Darryl Leja of the National Human Genome Research Institute, National Institutes of Health, http://www.genome.gov/. Accessed August 30, 2015.

Figure 3.
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Figure 3.

Base pair. A base pair is 2 chemical bases bonded to one another, forming a “rung of the DNA ladder.” The DNA molecule consists of 2 strands that wind around each other like a twisted ladder. Each strand has a backbone made of alternating sugar (deoxyribose) and phosphate groups. Attached to each sugar is 1 of 4 bases—adenine (A), cytosine (C), guanine (G), or thymine (T). The 2 strands are held together by hydrogen bonds between the bases, with adenine forming a base pair with thymine and cytosine forming a base pair with guanine. Courtesy of Darryl Leja of the National Human Genome Research Institute, National Institutes of Health, http://www.genome.gov/. Accessed August 30, 2015.

Figure 4.
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Figure 4.

Polymorphism. Polymorphism involves 1 of 2 or more variants of a particular DNA sequence. The most common type of polymorphism involves variation at a single base pair. Polymorphisms also can be much larger and involve long stretches of DNA. Called a single-nucleotide polymorphism (SNP, pronounced “snip”), scientists are studying how SNPs in the human genome correlate with disease, drug response, and other phenotypes. Courtesy of Darryl Leja of the National Human Genome Research Institute, National Institutes of Health, http://www.genome.gov/. Accessed August 30, 2015.

Figure 5.
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Figure 5.

Exon. An exon is the portion of a gene that codes for amino acids. In the cells of plants and animals, most gene sequences are broken up by one or more DNA sequences called introns. The parts of the gene sequence that are expressed in the protein are called exons because they are expressed, whereas the parts of the gene sequence that are not expressed in the protein are called introns, because they come in between—or interfere with—the exons. [Exon sequences are specified in a particular order to form messenger RNA (mRNA), which determines the amino acids that make up a protein. The 5′UTR (untranslated region) and 3′UTR sequences do not code for protein but do mark the first and last exon coding mRNA. Introns are noncoding sequences of DNA separating the exons of a gene; DNA sequences associated with introns are not specified in mRNA.] Author's note: Bracketed text added to figure caption from the genome.gov website. Courtesy of Darryl Leja of the National Human Genome Research Institute, National Institutes of Health, http://www.genome.gov/. Accessed August 30, 2015.

The purpose of this perspective article is to describe how new discoveries in genomics are rapidly evolving the understanding of health and disease by highlighting 2 conditions commonly encountered in clinical physical therapist practice: CVD and OA. Implications of genetic factors related to health-related traits and response to exercise also will be considered. Epigenetic mechanisms (DNA methylation and histone modification) and transcriptional regulation, although important in CVD12 and OA,13 as well as in exercise response,7 are beyond the scope of this review.

Genetic Factors Implicated in CVD

The CVD mortality rate has declined steadily over the past several decades, but CVD is still the leading cause of death in the United States.14 Management of risk factors, such as hypertension, dyslipidemia, type 2 diabetes, obesity, cigarette smoking, and physical inactivity, has contributed to this decline,15 but genetic factors remain major contributors to CVD. Rare Mendelian (monogenic) forms of CVD include types of premature myocardial infarction (MI), cardiomyopathy, or arrhythmia.16,17 Some familial forms of risk factors, such as hypertension or hypercholesterolemia, also are monogenic.15,16 Identification of genes implicated in monogenic types of CVD has led to diagnostic tests that can guide the care of patients and families12 and important discoveries in CVD pathogenesis and treatment.15 One Nobel Prize–winning discovery18 identified that mutations in the low-density lipoprotein (LDL) receptor gene, mediating LDL cholesterol removal from the blood, causes hypercholesterolemia.15,16 This finding was the impetus to develop statins.

Family History and Disease Heritability Studies: CVD

Parental history of premature CVD (onset age <55 years in father, <65 years in mother) increases risk 2.0-fold in men and 1.7-fold in women.19 Most CVD is polygenic.15 Twin and family studies have reported that 40% to 50% of the risk for coronary artery disease (CAD) is heritable.20,21 In classic twin studies, the variation in a phenotype (an observable trait such as eye color or height) is considered to be due to genetic and environmental influences, including environmental influences shared by a twin pair or unique to each individual.22 Heritability is the proportion of total phenotypic variation of a trait due to the variation in genetic factors among individuals.22,23 Heritability is calculated in twin studies by comparing the occurrence of a trait in monozygotic versus dizygotic twins, with the variance divided into genetic and environmental components.22,23 Monozygotic twins are genetically identical, whereas dizygotic twins share about 50% of their genetic material, which is comparable to ordinary siblings.22 Heritability estimates for a trait range from 0% (no genetic influence) to 100% (totally influenced by genetic factors). The longitudinal Swedish Twin Registry revealed that heritability for death due to coronary heart disease was 57% in men and 38% in women.21,24 Many risk factors also are heritable, as noted in the Framingham Heart Study for body mass index (52% for individuals with a mean age of 60 years), blood pressure (BP; systolic 42%, diastolic 39%), and total cholesterol (57%).14

Candidate Gene Studies and Genome-wide Association Studies (GWAS): CVD

Candidate gene approaches have been used to identify SNPs and other polymorphisms in genes thought to be implicated in CVD.16,17,25 Genes in this approach are selected because they are already partially understood and suspected to be associated with a disease or trait of interest.25 These “candidate” genes are then genotyped, and the frequencies of SNPs or other variants are compared in cases (unrelated people with the given disease or trait) versus controls.25 Single-nucleotide polymorphisms and other DNA polymorphisms have been associated with MI and congestive heart failure16 and with common risk factors.26,27 For example, the insertion/deletion (I/D) polymorphism of the angiotensin-converting enzyme (ACE) gene was associated with hypertension in older, but not younger, Japanese men.26 Systolic BP in older men (>50 years of age) with ID genotype was, on average, 5.9 mm Hg higher than those with II genotype. Apolipoprotein E (APOE) genotype also affects risk for CVD. Human APOE regulates lipid metabolism and transport and has 3 major protein isoforms (apoE2, apoE3, and apoE4) encoded by 3 APOE (ε2, ε3, and ε4) alleles.27 The ε4 allele has been associated with an increased risk for CAD27 (see Fig. 6 for a description of an allele).

Figure 6.
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Figure 6.

Allele. An allele is 1 of 2 or more versions of a gene. An individual inherits 2 alleles for each gene, 1 from each parent. If the 2 alleles are the same, the individual is homozygous for that gene. If the alleles are different, the individual is heterozygous. Though the term “allele” was originally used to describe variation among genes, it now also refers to variation among noncoding DNA sequences. Courtesy of Darryl Leja of the National Human Genome Research Institute, National Institutes of Health, http://www.genome.gov/. Accessed August 30, 2015.

Although candidate genes have been identified and studied for many diseases, including CVD, few associations have been replicated17,25,28 due to insufficient statistical power, other genetic or environmental influences, and phenotypic heterogeneity (ie, CVD has many causes, and certain genetic factors may play a greater role in some forms than others).28 The candidate gene approach also is limited because the search for associations targets known genes thought to be involved in a disease, precluding discovery of novel loci associated with disease.12,17

Genome-wide association studies genotype millions of SNPs, comparing the frequency in cases versus controls.12,17 The first well-replicated SNP locus for CVD to emerge from GWAS was localized to 9p21 (on the short p-arm of chromosome 9).17,21 Fine mapping of the risk region on 9p21 identified several tightly linked SNPs significantly associated with CAD.17 The frequency of the 9p21 risk allele variants (eg, G allele of SNP rs4977574 and C allele of SNP rs1333049) was found to be common in a large cohort of individuals of European and South Asian descent, with approximately 50% having 1 copy and 25% having 2 copies.12,17,20,21 A 9p21 risk allele variant (SNP rs1333049) also was predictive of CAD severity, as determined by the number of vessels involved based on coronary angiography.17,29 In addition, the magnitude of the risk for CAD was found to be associated with SNP variants in the 9p21 region, with 1 allele copy increasing risk by approximately 15% to 20% and 2 allele copies increasing risk by approximately 30% to 40%.29,30 The 9p21 variants associated with CAD risk have been identified in several ethnic populations,12,17,21 although data from individuals of African or other non-European ancestry ethnic groups are limited.12 The 9p21 variants are located in a noncoding region17,21 and, although the mechanism is not fully understood, may play a role in the development of atherosclerosis at the vessel wall.12,17,25,29

Given the importance of the 9p21 locus to CAD risk, considerable effort is being made to find other key loci. Two GWAS meta-analyses conducted by the CARDIoGRAM and C4D consortia together scanned nearly 40,000 coronary heart disease cases to confirm previous GWAS associations and identify novel variants.21 These findings, along with those from other large-scale studies, yielded 35 coronary disease variants, some near protein-coding regions and others not.21 Later, the CARDIoGRAMplusC4D Consortium20 found 15 novel loci, for a total of 46 loci at that time and explaining approximately 10.6% of CAD heritability. To identify key biological pathways involved in CAD pathogenesis, this consortium also performed computational analyses to study gene-gene interactions using 233 candidate genes, including the genes associated with the 46 SNP loci. Of the 5 networks generated, the 4 most significant pathways were linked to lipid metabolism and inflammation. Currently, 50 genetic CAD risk variants have been identified.17

Personalized Medicine and Pharmacogenomic Considerations: CVD

Although CVD variants have been identified through GWAS and meta-analyses of GWAS,20,21 each variant confers only a small risk effect, with cumulative small effects of many variants predicting susceptibility for common diseases.31 Currently, routine genetic testing for common CVD variants at the level of the individual is not recommended,12 as many variants have at best only a modest impact on risk and uncertain significance in predicting future disease.12,32–34 Nonetheless, progress is being made to elucidate cellular mechanisms and identify important therapeutic targets.12 In pharmacogenetics, genotype has been found to influence individual response to CVD drugs.15 For example, statin-induced myopathy has been strongly associated with certain genetic variants.12 Also, variants in the CYP2C9 and VKORC1 genes together account for up to 40% of the variation in final adjusted warfarin dose such that the Food and Drug Administration stipulates genotype-specific dose ranges.15,35 Similarly, other drug-genotype responses have been found for the antiplatelet drug clopidogrel and the use of beta-blockers in heart failure.15,35

Genetic Factors Implicated in OA

Osteoarthritis is the most common type of arthritis and the primary cause of lower extremity disability in older adults.36 Often considered a disorder of wear and tear,13 the genetic influences on OA have been intimated at least since the hereditary nature of Heberden's nodes was recognized in the 19th century.37 Subsequently, Heberden's nodes were found to have a Mendelian inheritance pattern, transmitted as a dominant trait in women and as a recessive trait in men.38 However, nodal OA is only one of many phenotypes, as OA is mainly inherited in a non-Mendelian manner.13 Risk factors for OA, such as age, sex, obesity, diet, and bone mineral density, can be specific to the individual, affecting all joints.36 Risk factors also can be specific to the joint, including injury, malalignment, muscle weakness, and excessive loading (eg, occupation or physical activity related).36,39 Although the interaction of these risk factors is complex,36 they lead to normal loading on abnormal joints or excessive loading on normal joints.39

Family History and Disease Heritability Studies: OA

The risk of OA and the risk of progression are familial. Siblings of patients undergoing total hip or knee replacement have increased risk of OA in the same joint.40,41 In the GARP (Genetics, Arthrosis, and Progression) study, siblings of probands (first identified family member) with OA at multiple sites and a family history of OA had increased risk for OA at the same sites as the proband for the hand (odds ratio [OR]=4.4), hip (OR=3.9), spine (OR=2.2), hip and spine (OR=4.7), and hand and hip (OR=3.4).37,42 Twin studies also have shown moderate heritability (39%–60%) for the risk of OA of the hand, knee, and hip.37 Similarly, high estimated heritability was found for knee total cartilage volume (73%) in twins.43

Candidate Gene Studies and GWAS: OA

Osteoarthritis candidate genes and genetic variants have been linked to joint structure (eg, articular cartilage integrity), risk factors (eg, obesity), and clinical outcomes (eg, pain).13,37,39,44,45 Collagen, type IX, alpha-2 (COL9A2) gene, which encodes 1 of 3 alpha chains of type IX collagen, was associated with both lumbar disk degeneration and hip OA in twins.46 One candidate gene study47 and several large-scale GWAS (see review by Panoutsopoulou and Zeggini13 for additional details) identified common variants at 15 loci associated with hip or knee OA attaining genome-wide significance, but together explained <10% of the genetic component.13 The largest of these GWAS by the arcOGEN Consortium compared 7,410 cases with severe hip or knee OA (80% had undergone a total joint replacement) and 11,009 population-based controls from the United Kingdom and replicated the most significant loci in 7,473 cases and 42,938 controls of European descent.48 The biological contribution of many of these 15 variants (in both coding and noncoding regions) to OA is unknown, as the associated genes and pathways have not been fully characterized.13 Some of these loci given the nearest identified gene, however, may play a role in the immune response, pain, obesity, or development and homeostasis of cartilage or bone.13 Of these 15 variants, the locus associated with growth differentiation factor 5 (GDF5) is one of the most robustly replicated and best understood.13,39,44,45

The GDF5 protein is a growth factor that induces cartilage and bone growth when implanted subcutaneously.13,39 The GDF5 protein is important for the development, maintenance, and repair of synovial joint elements,13 and GDF5 mutations result in skeletal dysplasias.39 Miyamoto and colleagues47 found that the GDF5 rs143383 (T/C) SNP was associated with hip and knee OA in Japanese and Chinese cohorts (OR=1.30–1.79) with the T allele conferring increased risk. Subsequent large-scale meta-analyses confirmed the rs143383 association with hip and knee OA in European and Asian cohorts,13,39,49 with the T allele increasing knee OA risk by 17% (OR=1.17).49 The GDF5 rs143383 SNP also is associated with risk for lumbar disk degeneration.50

Personalized Medicine and Pharmacogenomic Considerations: OA

Osteoarthritis has a long asymptomatic molecular phase, a preradiographic phase, and a final radiographic phase with hallmark structural joint changes.51 Efforts are being made to identify cellular, biochemical, molecular, and genomic (RNA and DNA) biomarkers to define subtypes, identify those at risk, monitor progression, and develop disease-modifying agents.51,52 Biomarkers, along with new therapies, have the potential to alter the course of OA, as in rheumatoid arthritis.51,52 Currently, no OA disease-modifying drugs are universally recommended,45,53,54 but drugs in development exhibit disease-modifying effects, such as those targeting cartilage or inflammatory pathways.53 Three available supplements (glucosamine sulphate, chondroitin sulphate, and diacerein) that are recommended for symptomatic relief of knee or hip OA also may have disease-modifying effects.53,54 Current surgical or analgesic treatment options54 primarily offer symptomatic relief and are largely palliative.51 Genetic factors, however, still play a role in aseptic loosening following arthroplasty55 or response to opioids56 used to manage OA-related pain.

Osteoarthritis pain is highly variable and can be discordant with radiographic features.13,44,57 Depression, anxiety, and stress also play a role in the experience of pain.56,58 Pain heritability was found to be 28% to 44%, depending on the site (neck, back, elbow, knee, thigh, hand, foot).57 Considering the genetic contribution to individual differences in pain perception and analgesia response, familial effects in twins accounted for 24% to 32% of the observed variance in experimental heat and cold pressor pain thresholds and elevation in cold pressor pain tolerance following opioid administration.56 One experimental study showed that pain sensitivity was influenced by a complex interplay of SNPs, sex, ethnicity, and psychological state.58 Efforts such as these to elucidate the genetic contributions to pain are on the forefront of pharmacogenetics, with the end goal being more personalized approaches to improve the efficacy and safety of pain management.59

Genetic Factors and Response to Exercise Interventions

According to Bray,60 genes and exercise interact to affect health. Exercise can yield different direct effects in genetically dissimilar individuals (eg, exercise-induced asthma) or act indirectly by influencing gene expression for intermediate phenotypes (eg, lipoprotein lipids, BP). Genetic factors have been found to be associated with cardiorespiratory, cardiovascular, and skeletal muscle fitness performance and training responses.7 For example, familial influences were found for response to a 20-week cycle ergometry training program in 481 healthy but sedentary individuals from 98 two-generation families in the HERITAGE Family Study.7,61 Although maximum oxygen consumption (V̇o2max) training response ranged from none (nonresponders or low responders) to more than 1,000 mL/min (high responders), 2.5 times more variability was found between rather than within families, with an estimated heritability of 47% for the V̇o2max response to training.

Heritability of Physical Activity and Fitness Attributes

Physical activity participation was found to have an estimated heritability of 57% based on accelerometry data in twins.62 In adult twins (mean age=50.4 years), low diastolic but not low systolic BP was associated with aerobic exercise performed in adolescence and intensity over the lifetime.63 Although environmental effects, including exercise participation, explained the majority of BP variance, 35% of the variance in diastolic BP and 39% of the variance in systolic BP were attributable to genetic factors. Genetic factors also can influence the variation in musculoskeletal and performance phenotypes.7 For example, the heritability for total lumbar range of motion was estimated to be 47%.23 Katzmarzyk and colleagues64 reported moderate heritability for grip strength (48%), number of push-ups (37%), number of sit-ups in 60 seconds (59%), and sit-and-reach distance (64%).

Candidate Gene Studies and GWAS: Physical Activity and Exercise Response

Genetic variants in candidate genes have been linked to physical activity participation and exercise response. The Québec Family Study showed that a C/T polymorphism of the melanocortin-4 receptor (MC4R) gene, which plays a role in feeding behavior and energy homeostasis, was associated with physical activity.7,65 Individuals with the T/T genotype reported lower moderate-to-strenuous physical activity and higher inactivity than those with the C allele. In white male military recruits, left ventricular mass increased for those with ACE DD but not II genotype after 10 weeks of physical training.66 Obisesan and colleagues67 found that ethnicity, defined as black or white Americans, interacts with the APOE ε2/ε3 genotype, influencing response to 24 weeks of endurance training on the advantageous high-density lipoprotein cholesterol (HDL-C) subfractions. Black American APOE ε2/ε3 carriers, compared with white Americans, had greater exercise training–induced improvements in HDL-C particle size and concentration, whereas no black or white American differences were found for ε4 carriers. Obisesan and colleagues67 suggested that APOE genotype may help target high-risk populations who may benefit more readily from aerobic training to reduce CVD risk. Genotype also was found to influence response to a walking and weight lifting intervention in sedentary adults with knee OA who were older and obese or overweight.68 Individuals with an A allele at position −308 in the promoter (regulatory) region of the tumor necrosis factor alpha (TNFα) gene had greater improvements after the intervention than those homozygous for the G allele in stair climbing time at 6 months and physical disability at 18 months.68 Also, the alpha-actinin-3 (ACTN3) genotype influenced knee extensor peak power with strength training in older adults.7,69

Although few exercise performance GWAS have been conducted, due, in part, to issues identifying large populations to participate in exercise training,7,70 findings in this area are highly relevant to physical therapist practice. Rankinen and colleagues71 in a GWAS involving a HERITAGE Family Study group of 472 healthy but sedentary individuals from 99 families, identified 40 SNPs associated with submaximal HR training-induced changes following 20 weeks of cycle ergometry. Of the 40 SNPs identified, 9 of the most significant SNPs fully accounted for the maximal estimated heritability of 34% for changes in steady-state HR in response to endurance training and are implicated in cardiomyocyte and neuronal functions. They also calculated a SNP summary score based on the number of alleles of the 10 most favorable training SNPs. They found that participants with ≤9 of these favorable alleles showed no training improvements in their submaximal steady-state HR, whereas those with ≥16 of these alleles decreased their HR by more than 20 bpm. Rankinen and colleagues71 suggested that the identification of these novel variants provides an alternative explanation for the variability in HR training response beyond an insufficient exercise prescription or lack of training adherence.

Clinical Application

Medical care in the genomic era has been called the “science of the individual,” capturing the unique genetic, developmental, and experiential aspects of a person that influence health and disease.72 Disease presentation in individuals varies greatly, suggesting that some common conditions may not be a single disease entity but rather a group of disorders sharing an end-stage pathology.28,36 Although the specification of CVD and OA phenotypes is expected to aid the discovery of key molecular and biochemical pathways and pharmacological treatments,28,52 phenotypes also can help clinicians understand the variability in patient presentation. For example, hand OA (thought to be highly heritable) was associated with increased risk of knee OA in patients requiring menisectomy after injury.73 Applying Bouchard's70 recommendations for “exercise genomics” to rehabilitation and prevention, personalized programs could be based on the identification of excellent, average, low, and even adverse responders with respect to DNA sequence variation70 or possibly family history.61

Looking toward the future, Ashley and colleagues74 described a case of whole genome sequencing for a 40-year-old man with a family history of vascular disease and sudden death. He had no significant medical history or prescribed medications and exercised regularly. A cardiac workup was performed with a full genome sequence analysis and genetic counseling. The genetic analysis revealed increased risk for MI, type 2 diabetes, and some forms of cancer. Rare variants were detected in 3 genes associated with sudden cardiac death and risk markers at the 9p21 locus. A variant in the apolipoprotein A precursor, lipoprotein(a) (LPA) gene was consistent with very high LPA concentrations and a family history of CAD. A variant associated with OA was consistent with family history and possibly his chronic knee pain. He also had a mutation in CYP2C19, suggesting resistance to clopidogrel; variants associated with a beneficial response to statins with reduced risk for myopathy; and variants in 2 genes, including VKORC1, indicating increased risk of bleeding if treated with warfarin. Given these results, this patient and his physician considered preventative options.74 This type of personal genome assessment is not widely available, as current analytical methods fall short in making genomic data accessible for clinical purposes,74 given the size and complexity of the data sets,74 accuracy limitations in sequence variation identification,75 and unknown significance of many of the variants identified.76 When more consistently available, however, the type of disease-associated genetic risk analyzed in the context of predisposing disorders and environmental and behavioral factors, as determined by Ashley and colleagues,74 would be highly relevant to a physical therapist enhancing this individual's wellness program as part of the medical team. It is essential, therefore, that clinicians be prepared to understand and integrate genomic-related information to offer the best care possible.

As testing for common disease variants becomes more routine,5 genetic information will be increasingly available in clinical settings, enabling phenotypic stratification based on specific genotypes and allele patterns. For example, variations of the catechol-O-methyltransferase (COMT) gene have been associated with human pain sensitivity77,78 and analgesic response,79 and early work has identified COMT genotype associations with baseline scores on the Oswestry Disability Index in individuals with chronic low back pain80 and 1-year changes after lumbar spine surgery.81 Although still an emerging area, the end goal of exercise genomics70 is the use of genetic information to generate more individualized prescriptions to improve the effectiveness of exercise in the prevention of chronic disease.60 For example, Obisesan and colleagues67 suggested that the APOE genotype could help identify individuals most likely to respond to aerobic training to reduce CVD risk.

Regular testing for common disease variants in clinical practice, such as through whole genome sequencing, is not currently performed due to a variety of implementation challenges,33 which at a minimum include screening accuracy and sensitivity, unclear clinical significance of identified variants, and lack of professionals with relevant knowledge.33,75,82 In addition, a current debate revolves around ethical concerns and the clinical utility of disclosure of incidental findings that are inherent in whole genome and exome sequencing.76,83 Addressing these and other challenges, Manolio and colleagues33 described early adopter sites that have implemented successful screening programs and outline key infrastructure and research needed to support greater application of genomic medicine in clinical settings. In the absence of widespread testing in clinical settings for common genetic variants, clinicians should consider an individual's family health history as a valuable personalized “genomic tool.”84 Individuals share approximately 50% of their genetic variation with their first-degree relatives (siblings, offspring, and parents), and the family history includes shared environmental and lifestyle factors,14 thus giving clinicians important insight into heritable traits and underlying risks for common conditions. Although lifestyle modification, including physical activity participation, has been suggested to be protective against diseases such as CVD, even for people with a parental history of CVD,85 challenges exist in the realization of actual improved health outcomes.5 To address this issue, individual states and the Centers for Disease Control and Prevention (CDC) have developed pilot programs to explore the use of genomic information in disease prevention.86

Physical therapists need to be knowledgeable and prepared to guide patients and their families on a variety of genomics issues.87 Clinicians must be aware of the psychological impact of genetic information,5 as testing may reveal increased risk for serious or possibly life-threatening conditions, especially as whole genome sequencing becomes more available in clinical settings.74 Clinicians must be able to engage patients as they contemplate genetic testing, interpret findings, consider implications for other family members, and identify medical or genetic counseling needs.87 Ethical, legal, and social issues also accompany genetic information.35,88 The biological influences of genetics pertain not only to health and disease but also are intimately interwoven with individual traits and behaviors and perceptions of race and ethnicity.3 Given these sensitive matters, clinicians must be aware of the potential for stigmatization or discrimination related to genetic information. Legal safeguards, under the 2008 Genetic Information Nondiscrimination Act (GINA) and the 2010 Patient Protection and Affordable Care Act (ACA), have been enacted to ensure confidentiality and deter discriminatory practices related to insurance coverage or employment, despite the fact that these laws have gaps and have not been fully tested.35

Consistent with recommendations of the 2009 Physical Therapy and Society Summit,89 health care in this new genomic era provides unique leadership opportunities for physical therapists in the area of health and wellness to mitigate common chronic diseases. Using family health history, physical therapists can assist clients in recognizing areas of greatest risk, recommend physical training regimens, or, when necessary, refer clients to a physician or genetics counselor for further assessment. To this end, the Annual Physical Therapy Checkup90 initiative of the American Physical Therapy Association (APTA) promotes an annual examination by a physical therapist to help determine an individual's health status, identify risk factors, and make wellness-related recommendations. Beyond the client in front of us, clinical care in this new era encourages us to look at the family as a unit, particularly children and youth, for future risk reduction. The American Heart Association's cardiovascular health initiative specifies ideal levels on 7 metrics for adults and youth, including health behaviors (not smoking, sufficient physical activity, healthy diet, and appropriate body mass index) and health factors (optimal untreated BP, total cholesterol, and fasting blood sugar), with family history influencing the risk for several of these metrics.14 Leadership in prevention, health, and wellness also encourages us as a profession to assume a larger role in the public health arena, to use our skill set, and, in collaboration with others, to optimize the fitness and health of our society.89

Conclusion

The genomic era of health care is upon us—an era envisioned to be more personalized as genetic factors are used to determine risk for disease and design preventive and therapeutic regimens, such as new pharmacogenetic agents. Many chronic diseases with notable lifestyle contributions, such as CVD and OA, are now known to be influenced by a variety of common genetic variants. This era is generating new insight not only into the biological and molecular basis of disease but also into exercise response. Physical therapists who prescribe exercise regimens to thwart the effects of chronic disease have much to gain from this knowledge, as well as much to offer, in this new era. Although genetic testing for common diseases currently is not widely available, consideration of genetic factors can help clinicians better understand interindividual differences in the presentation of disease, experience of pain, and response to exercise training. Clinicians can view family history as an important genetic tool, widening the scope to the entire family unit. In this new era, it is essential that physical therapists be prepared to assist patients and their families with genomics-related concerns, including those pertaining to genetic testing or other ethical, legal, or social issues. To achieve these goals, physical therapy educators and clinicians must become familiar with new genetics concepts and terminology,87 but should not be daunted, as resources are available that can serve as a place to start (see APTA's Genetics in Physical Therapy [http://www.apta.org/Genetics/] and NHGRI [http://www.genome.gov/]). Physical therapists also will need to engage in interdisciplinary clinical and research-based projects to help translate genomic advances to prevention or direct patient care. This era, lastly, provides a key leadership opportunity for physical therapists in prevention, health, and wellness to utilize new understanding of the nature and nurture of common chronic diseases in order to improve the mobility and health of many in our society.

Footnotes

  • All authors provided concept/idea/design and writing. Dr Goldberg and Dr Wolf provided consultation (including review of manuscript before submission).

  • The authors acknowledge Darryl Leja and the National Human Genome Research Institute, National Institutes of Health (http://www.genome.gov/), for generously providing public rights for use of all graphic images included in this article.

  • Received February 25, 2015.
  • Accepted November 23, 2015.
  • © 2016 American Physical Therapy Association

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Vol 96 Issue 4 Table of Contents
Physical Therapy: 96 (4)

Issue highlights

  • Confidence and Fear of Falling Avoidance Behavior in Older Adults
  • Reliability of the ECHOWS Tool
  • Functional Gait Assessment in Older Adults
  • Community-Based Exercise for People With Stroke
  • Knee Osteoarthritis and Promoting Exercise Adherence
  • Test Comparisons in Predicting Falls in Parkinson Disease
  • Scapular Position Using the Protractor Method
  • Physical Activity and Physical Fitness in Autism
  • Disability and Active Video Gaming
  • BNDF Genotype and Brain Function After Stroke
  • Electrodiagnostic Evaluation and Individuals With Volumetric Muscle Injury
  • Regenerative Rehabilitation and Advanced Technologies in Physical Therapy
  • Physical Therapists and Mechanotherapy
  • Translating Genomic Advances to Physical Therapist Practice
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Translating Genomic Advances to Physical Therapist Practice: A Closer Look at the Nature and Nurture of Common Diseases
Catherine L. Curtis, Allon Goldberg, Jeffrey A. Kleim, Steven L. Wolf
Physical Therapy Apr 2016, 96 (4) 570-580; DOI: 10.2522/ptj.20150112

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Translating Genomic Advances to Physical Therapist Practice: A Closer Look at the Nature and Nurture of Common Diseases
Catherine L. Curtis, Allon Goldberg, Jeffrey A. Kleim, Steven L. Wolf
Physical Therapy Apr 2016, 96 (4) 570-580; DOI: 10.2522/ptj.20150112
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  • Article
    • Abstract
    • Genetic Factors Implicated in CVD
    • Genetic Factors Implicated in OA
    • Genetic Factors and Response to Exercise Interventions
    • Clinical Application
    • Conclusion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
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Show more Regenerative Rehabilitation and Genomics Special Series

Subjects

  • Perspectives
  • Other Diseases/Conditions
    • Other Diseases or Conditions
  • Physical Therapist Practice
    • Professional Issues
  • Special Series and Special Issues
    • Special Series on Regenerative Rehabilitation and Genomics
  • Musculoskeletal System/Orthopedic
    • Osteoarthritis
  • Cardiovascular/Pulmonary System
    • Cardiac Conditions
  • Geriatrics
    • Osteoarthritis

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