Current pharmacogenomic recommendations in chronic respiratory diseases: Is there a biomarker ready for clinical implementation?

ABSTRACT

Introduction

The study of genetic variants in response to different drugs has predominated in fields of medicine such as oncology and infectious diseases. In chronic respiratory diseases, the available pharmacogenomic information is scarce but not less relevant.

Areas Covered

We searched the pharmacogenomic recommendations for respiratory diseases in the Table of Pharmacogenomic Biomarkers in Drug Labeling (U.S. Food and Drug Administration), the Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB. The main pharmacogenomics recommendation in this field is to assess CFTR variants for using ivacaftor and its combination. The drugs’ labels for arformoterol, indacaterol, and umeclidinium indicate a lack of influence of genetic variants in the pharmacokinetics of these drugs. Further studies should evaluate the contribution of CYP2D6 and CYP2C19 variants for formoterol. In addition, there are reports of potential pharmacogenetic variants in the treatment with acetylcysteine (TOLLIP rs3750920) and captopril (ACE rs1799752). The genetic variations for warfarin also are presented in PharmGKB and CPIC for patients with pulmonary hypertension.

Expert opinion

The pharmacogenomics recommendations for lung diseases are limited. The clinical implementation of pharmacogenomics in treating respiratory diseases will contribute to the quality of life of patients with chronic respiratory diseases.

KEYWORDS:

• CFTR
• clinical implementation
• formoterol
• ivacaftor
• pharmacogenomics
• TOLLIP
• umeclidinium
• warfarin

1. Introduction

Respiratory diseases are diseases of the airways and other lung structures. They are considered a significant public health concern and a common cause of morbidity worldwide. Chronic obstructive pulmonary disease (COPD), asthma, interstitial lung disease, cystic fibrosis (CF), pulmonary hypertension (PAH), and pulmonary sarcoidosis represent a socioeconomic burden to patients and governments. Nevertheless, respiratory diseases are severely neglected compared to other chronic diseases like diabetes and cardiovascular disorders [1].

In the last years, the cases of chronic respiratory diseases have increased worldwide, with reported differences in frequencies according to age, sex, and ethnicity. COPD and asthma represent a large proportion of these diseases’ burdens [2].

Chronic respiratory diseases are not curable; the current treatments are focused on dilating major air passages and improving shortness of breath which contributes to controlling symptoms and increasing the quality of life for patients and their families [3]. Thus, drugs prescribed for chronic respiratory diseases vary according to the specific disorder and patients’ symptoms, but the clinical outcome and adverse reactions present an interindividual variability currently investigated by the pharmacogenomics of respiratory diseases.

For instance, several pharmacogenetic variants have been explored in the treatment of COPD [4,5], asthma [6,7], interstitial lung disease [8,9], and sarcoidosis [10], and the findings remain controversial. However, after several consensuses, there is relevant pharmacogenomic information stated by International Health Agencies [11,12] and Consortiums [13,14] about specific drugs prescribed for some respiratory diseases.

The clinical implementation of pharmacogenomics in routine health care is still in process, and several challenges must be overcome. However, scientific and concise information should be readily available to facilitate the clinical practice of pharmacogenomics biomarkers.

Herein, we aim to present the current pharmacogenomics recommendations in chronic respiratory diseases from official databases. For this purpose, we performed a search of the pharmacogenomic recommendations for respiratory diseases in the Table of Pharmacogenomic Biomarkers in Drug Labeling (U.S. Food and Drug Administration) [12], the Clinical Pharmacogenomics Implementation Consortium (CPIC) [15], and PharmGKB [13], in January and February 2022. The information is summarized and discussed in the following sections.

Although there are relevant advances in the pharmacogenomics of lung cancer diseases, both the design of targeted therapies and the response rate, we did not include these pharmacogenomic biomarkers since this subject matter requires a dedicated review and there is available information in this regard [16–18]. Likewise, the pharmacogenomics of inhalational anesthetic agents keeps out of the scope; however, we acknowledge that this is an emerging field for more safety uses of these drugs [19,20].

2. Available pharmacogenomic recommendations in official databases

2.1. U.S. food and drug administration

The Table of Pharmacogenomic Biomarkers in Drug Labeling is a list of FDA-approved drugs whose labels include pharmacogenomic information derived from clinical trials. The labeling for some, but not all, of the products includes specific actions to be taken based on the biomarker information. Pharmacogenomic information can appear in different sections of the labeling depending on the clinical recommendation [12].

Arformoterol, ivacaftor, formoterol, indacaterol, and umeclidinium are currently prescribed for pulmonary diseases listed in the Table of Pharmacogenomic Biomarkers in Drug Labeling FDA [12] (Table 1).

Table 1. Clinical implication of pharmacogenomic biomarkers for respiratory diseases included by the Food and Drug Administration.

Drug	Pharmacogene biomarker	Main clinical implication
Arformoterol	UGT1A1 CYP2D6	There was no impact on systemic exposure to arformoterol comparing subjects with different CYP2D6 and/or UGT1A1 enzyme activities.
Elexacaftor, Ivacaftor, and Tezacaftor	CFTR	The treatment is indicated in patients with at least one F508del mutation in the CFTR gene or a mutation in the CFTR that is responsive based on in vitro assay data.
Ivacaftor		It is indicated for patients with one CFTR mutation responsive to ivacaftor based on clinical or in vitro assay data. Trials studies performed in Caucasians.
Ivacaftor and Lumacaftor		It is indicated for patients homozygous for the F508del mutation in the CFTR. Clinical trials performed in a 99% Caucasian population.
Ivacaftor and Tezacaftor		It is indicated for homozygous patients for the F508del mutation or have at least one CFTR mutation responsive to tezacaftor/ivacaftor based on in vitro data and/or clinical evidence.
Formoterol	CYP2D6 CYP2C19	Whether a deficiency in one or both of CYP2D6 or CYP2C19 results in elevated systemic exposure to formoterol or systemic adverse effects has not been adequately explored. The report was performed in a population mostly Caucasian (88%).
Indacaterol	UGT1A1	Studies in Caucasians suggest no relevant effect of the UGT1A1 genotype on indacaterol exposure.
Umeclidinium	CYP2D6	No clinically meaningful difference in systemic exposure to umeclidinium was observed following repeat daily inhaled dosing to normal (ultrarapid, extensive, and intermediate metabolizers) and CYP2D6 poor metabolizer subjects. The study included a population described as 89% white.

Arformoterol is an (R,R) enantiomer of formoterol [21]. Both drugs are nebulized long-acting β-agonists (LABA) prescribed in COPD [22], although arformoterol has been reported to be more potent than formoterol owing to its greater affinity for the β₂-adrenergic receptor [21]. Due to their metabolic pathways, the pharmacogenomic information included in the approved labels is focused on the UGT1A1, CYP2D6, and CYP2C19 genes. Apparently, for arformoterol, the pharmacogenetic variants do not affect the systemic exposure to the drug; meanwhile, there is a lack of studies on the pharmacogenetics of formoterol. There are no reports about studying these or other enzymes in the pharmacogenetics of formoterol and arformoterol. On the contrary, the studies found in the scientific literature comprise the evaluation of ADRB2 genetic variants in the combined therapy, including formoterol, but these have reported controversial results [23–26].

Similarly, the official information for indacaterol reports that UGT1A1 variants do not affect indacaterol exposure, while there are only two reports about the pharmacogenetics of this drug, including the study of ADRB2 genetic variants [27,28].

Ivacaftor is a selective small-molecule potentiator of the Cystic Fibrosis Transmembrane Conductance Regulator Protein (CFTR) designed to restore protein function [29]. It is indicated for Cystic Fibrosis (CF) treatment, an autosomal disorder caused by the inheritance of two detrimental copies of one or more variants in the CFTR gene [30]. There are more than 2000 variants identified in CFTR, of which 127 are pathogenic, and they are categorized into five classes based on their effect on CFTR function [31]. Ivacaftor targets class III variants which produce proteins that fold and localize appropriately but cannot be regulated by ATP or phosphorylation as needed for normal gating function [32]. Thus, patients carrying other classes of variants may not present an adequate response to ivacaftor. For instance, patients homozygous for the specific F508del variant showed no improvement with ivacaftor treatment alone [33], and there is available combined therapy of ivacaftor for these cases [34]. In this sense, the CFTR genotype is critical for indicating ivacaftor and its combination. A CPIC guideline is available for ivacaftor therapy in the context of CFTR genotype, which provides therapeutic recommendations for ivacaftor based on preemptive CFTR genotype results [35]. This is the only drug in the respiratory-diseases class with an available CPIC guideline as it will be mentioned above.

Umeclidinium is an effective and well-tolerated long-acting muscarinic receptor antagonist (LAMA) for COPD treatment [36]. Currently, the information indicates that CYP2D6 variants do not affect the exposure of LAMA [37] and that it is also a substrate of P-glycoprotein and CYP3A4. However, there are no significant variations in umeclidinium treatment due to these gene–drug interactions [38]. Moreover, two pharmacogenetic studies found a lack of association of genetic variants with the umeclidinium response as monotherapy or combination in patients with COPD [39,40]. According to this information, umeclidinium will not be a drug with an effective genotype-guided prescription.

2.2. Pharmacogenomics knowledgebase (PharmGKB)

PharmGKB is a comprehensive resource for clinicians and researchers to present selected pharmacogenetic information. PharmGKB collects, curates, and disseminates knowledge about clinically actionable gene-drug associations and genotype–phenotype relationships. There are available different levels of clinical annotations according to the source of information: a) variant annotations from peer-reviewed published literature in PubMed; b) PGx guideline annotations, guidelines from CPIC and/or Royal Dutch Association for the Advancement of Pharmacy; and c) Drug Label Annotations, taken from Agencies’ Recommendations [41]. Clinical annotations summarize all PharmGKB’s annotations of published evidence for the relationship between a particular genetic variant and a medication. PharmGKB gives them a rating depending on how much published proof there is for a connection found in PharmGKB and the quality of that evidence. We found 54 results when searching for pulmonary diseases (search term: pulmonary) and filtering by annotation types (Clinical Guideline Annotation, Drug Label Annotation, Clinical Annotation, and Variant Annotation). Several annotations can be found, including negative and positive associations with different levels of evidence. The pharmacogenetic variants significantly associated with the variability in response to drugs employed for the treatment of chronic respiratory diseases are included in Table 2.

Table 2. Annotations of pharmacogenetic variants included for respiratory diseases in PharmGKB.

Drug	PGx variant	Annotation	Biogeographical group ^a	Level of evidence ^b
Warfarin	CYP4F2 rs2108622	Genotype TT is associated with an increased warfarin dose in people with atrial fibrillation, heart valve replacement, pulmonary hypertension, pulmonary embolism, and venous thrombosis.	East Asian	1A
	CYP2C9 rs1057910	Genotypes AC + CC are associated with a decreased warfarin dose in people with atrial fibrillation, heart valve replacement, pulmonary hypertension, pulmonary embolism, and venous thrombosis.	East Asian
	VKORC1 rs9923231	Genotypes AC + CC are associated with a decreased warfarin dose in people with atrial fibrillation, heart valve replacement, pulmonary hypertension, pulmonary embolism, and venous thrombosis.	East Asian
	rs7196161	Allele A is associated with dosage in people with atrial fibrillation, pulmonary embolism, stroke, and venous thrombosis.	Chinese, Malay, Indian, Other	3
	rs9934438	Genotype AG is associated with increased dose in people with atrial fibrillation, cardiomyopathies, heart valve replacement, peripheral vascular diseases, pulmonary embolism, and venous thrombosis.	Sub-Saharan African	1B
	APOE rs7412	Genotype CC is associated with increased dose in people with atrial fibrillation, pulmonary embolism, or venous thrombosis.	East Asian	NA
Theophylline	CYP1A2 rs35694136	Genotypes TT + T/del are associated with increased severity of COPD when treated with theophylline.	Near Eastern	NA
N-acetylcysteine	TOLLIP rs3750920	Patients have different responses according to CC, CT, or TT genotypes and pulmonary fibrosis.	European	3
	EPHX1	EPHX1 poor metabolizer is associated with increased response in people with COPD.	East Asian	NA
Ivacaftor	CFTR rs75527207	When treated with ivacaftor, allele A is associated with a decreased likelihood of cystic fibrosis pulmonary exacerbation.	Not reported	1A
	rs113993960	Genotype del/del is associated with decreased cystic fibrosis pulmonary exacerbation when treated with ivacaftor and tezacaftor.	Multiple groups	NA
Captopril	ACE rs1799752	Genotype del/del is associated with different responses in men with COPD.	East Asian	2A
Nintedanib	DSP rs2076295	Genotype TT is associated with decreased overall survival in people with pulmonary fibrosis	European	NA
Nitroglycerin	ALDH2 rs671	Genotypes AA + AG are associated with increased drug concentrations in children with congenital heart defects and pulmonary hypertension.	East Asian	NA
Fluticasone/ salmeterol	CRHR1 rs242941	Genotype CC is associated with increased mean change in FEV when treated with this combination in people with COPD.	East Asian	NA
ACE inhibitors	CLASP1 rs62151109	Allele C is associated with an increased likelihood of cough in people with asthma, diabetes mellitus, heart failure, hypertension, and COPD.	European	NA

^aPharmGKB uses a system of nine biogeographical groups to indicate racial and ethnicity information about participants in pharmacogenomic studies, for further information please visit https://www.pharmgkb.org/page/biogeographicalGroups; ^b Clinical Annotations Levels of Evidence [42]: Level 4, unsupported; Level 3, Low; Level 2, Moderate (2A: variant found in PharmGKB’s Tier 1 Very Important Pharmacogenes, 2B: variant not found in PharmGKB’s Tier 1 Very Important Pharmacogenes); Level 1, High (1A: with a variant-specific prescribing guidance available, 1B: no available variant-specific prescribing guidance). ACE, angiotensin-converting enzyme; COPD, Chronic obstructive pulmonary disease; FEV, forced expiratory volume; NA, this annotation has not been used as evidence for any clinical annotations

The most substantial level of evidence of clinical annotations is reported for warfarin dosage adjustment according to CYP4F2, CYP2C9, and VKORC1 variants. The study and recommendations for warfarin adjustment based on genotypes and non-genetic factors are widely known in the pharmacogenetic literature [43], and herein it is linked to pulmonary hypertension and pulmonary embolism. These disorders result from the obstruction of major pulmonary vessels by organized blood clots, as an idiopathic process [44] or secondary to other conditions such as sickle cell anemia [45].

Likewise, the relevance of the CFTR genotype in the treatment with ivacaftor is another pharmacogenetic prime in respiratory diseases. However, the remaining pharmacogenetic variants reported in annotations of PharmGKB present a moderate to low or no level of evidence, which deserves further studies. For instance, a contrary response to N-Acetylcysteine has been reported for individuals with idiopathic pulmonary fibrosis carrying TT or CC genotype of the TOLLIP rs3750920 [46]. Therefore, further prospective studies can add evidence for the final recommendations based on this gene. Few pharmacogenetic investigations have been conducted in patients with interstitial lung disease, so ample opportunities for pharmacogenetic exploration exist in this patient population [8].

2.3. Clinical pharmacogenetics implementation consortium (CPIC)

The CPIC is an international consortium interested in facilitating the use of pharmacogenetic test for patient care by creating, curating, and posting freely available, peer-reviewed, evidence-based, updatable, and detailed gene/drug clinical practice guidelines. CPIC guidelines follow standardized formats, include systematic grading of evidence and clinical recommendations, use standardized terminology, are peer-reviewed, and are published in a leading journal [15].

In the Guidelines section of the CPIC website, 26 guidelines for drugs are currently available for different diseases. Regarding chronic respiratory diseases, there is only one available, the Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for Ivacaftor Therapy in the Context of CFTR Genotype, published in 2014, and contains the therapeutic recommendations for ivacaftor based on preemptive CFTR genotype results [35]. Two guidelines for drugs related to the pulmonary system but not chronic respiratory diseases can also be found, such as the one for potent volatile anesthetic agents [47] and the other for codeine [48]. As previously described, there is also a guideline for warfarin employed for treating pulmonary hypertension or embolism [49].

In the Genes-Drugs section, the CPIC presents information on 463 genes related to drugs’ usage, categorized with a CPIC level assigned according to (1) PharmGKB Clinical Annotation Levels of Evidence or (2) a PharmGKB PGx level for FDA-approved drug labels of ‘actionable pgx,’ ‘genetic testing recommended,’ or ‘genetic testing required,’ or (3) based on the nomination to CPIC for consideration [50].

The information on pharmacogenomics biomarkers found in the CPIC database for chronic respiratory diseases is consistent with that previously described in FDA and PharmGKB sections (Table 3). The level of evidence is higher for ivacaftor and warfarin; meanwhile, other gene/drug pairs can be observed but with the lowest CPIC level. Thus, there is available pharmacogenetic information for budesonide, fluticasone, salbutamol, salmeterol, and triamcinolone, but this is not robust enough to generate a clinical recommendation. In addition, some other drugs prescribed in acute respiratory disorders were observed, and these are also classified with a low CPIC level, for instance, dextromethorphan (B/C), codeine (C), bupropion (B/C), and hydrocodone (C) [50].

Table 3. Gene/drug pairs related to chronic respiratory diseases reported by the clinical pharmacogenetics implementation consortium [50].

Drug	Gene	CPIC level^a	PharmGKB level of evidence ^b	PGx on FDA label
Ivacaftor	CFTR	A	1A	Testing required
Warfarin	CYP2C9, CYP4F2, VKORC1	A	1A	Actionable PGx
	CALU, GGCX,	D	3	NA
	PROC, PROS1	D	NA
Budesonide	CRHR1	D	NA	NA
Fluticasone propionate	CRHR1	D	NA	NA
Fluticasone/ salmeterol	CRHR1	D	NA	NA
Salbutamol	ADRB2, COL22A1, CRHR2	D	3	NA
Salmeterol	ADRB2	D	2A	NA
Triamcinolone	CRHR1	D	NA	NA

^aCPIC level A and B gene/drug pairs have sufficient evidence for at least one prescribing action to be recommended, meanwhile CPIC level C and D gene/drug pairs are not considered to have adequate evidence or actionability to have prescribing recommendations. ^b Clinical Annotations Levels of Evidence reported by PharmGKB: Level 4, unsupported; Level 3, Low; Level 2, Moderate (2A: variant found in PharmGKB’s Tier 1 Very Important Pharmacogenes, 2B: variant not found in PharmGKB’s Tier 1 Very Important Pharmacogenes); Level 1, High (1A: with a variant-specific prescribing guidance available, 1B: no available variant-specific prescribing guidance). NA; not available information; PGx, pharmacogenomics.

3. Clinical implementation of pharmacogenomics in chronic respiratory diseases

Pharmacogenomics aims to contribute to personalized medicine to achieve maximal efficacy and decrease the adverse effects of pharmacological therapy. Over the last years, clinical implementation has gained significant interest due to the availability of specific pharmacogenomic recommendations for the indications and safety of certain drugs [51]. Nevertheless, translating pharmacogenomic results into actionable prescribing decisions has faced numerous problems mentioned in the literature for experts. To name a few, the availability of the clinical guidelines and tests, variability in the methodologies and interpretations of results, lack of data or information of different populations, lack of interest of stakeholders, and the training requirement [52–54].

Nevertheless, there is still a lack of information regarding specific biomarkers to ponder their clinical implementation in respiratory diseases. Only 0.81% of the drugs with label pharmacogenetic information in the FDA belong to the group of Pulmonary diseases [55]. For instance, for COPD, there have been several published genome-wide association studies and other omics studies in pharmacogenomics; but the current evidence limits the possibilities of a future clinical implementation of pharmacogenomics in this disease. Nevertheless, experts suggest that there are relevant information to include in future research in COPD pharmacogenomics, for instance, the incorporation of extensive biobank data linked to the electronic medical records, as well as studies in non-European derived populations [4]. In addition, as can be observed in both Tables 1 and 2, the availability of biomarkers for other respiratory diseases is not different from the COPD status.

It is worth mentioning that the source of the information in the consulted databases also present a grade of variability. The one reported in the FDA was generated during the clinical trials, mainly performed in Caucasian populations. Therefore, some information could still require further investigation to precise the pharmacogenomics statements in this database. Regarding PharmGKB and CPIC, there is a curated and standardized process for the selection of data to include in the databases, performed by experts. This information present different level of evidence. The strongest evidence has resulted in clinical recommendations and guidelines. However, most of the information present a moderate to low level of evidence probably due to the sample size included in the studies and the studies’ design. The investigation of candidate genes in retrospective studies do not represent the best choice for generating pharmacogenomics information, but they hint the relevance of some pharmacogenes in a particular treatment. On the contrary, prospective studies employing GWAS could provide a deeper analysis that leads to a pharmacogenomic clinical recommendation.

However, besides the evident opportunity for identifying and validating pharmacogenomic variants in respiratory diseases, there are two drugs for which pharmacogenomic biomarkers have been well established: ivacaftor and its combinations, and warfarin. The indication of ivacaftor is guided by a genetic study for its specific use in patients carrying particular variants of CF. Notwithstanding, this is a rare disease with an estimated incidence between 1/3000 and 1/6000 among individuals from Europe, but even rarer in subjects from America and Asia. The CFTR modulators (ivacaftor, lumacaftor, elexacaftor, tezacaftor, and their combinations) have transformed the lives of patients with CF and the incidence of the disease among the different stages of life [56]. In this case, the genetic test is part of the diagnosis, but the link to pharmacological therapy is a relevant application of pharmacogenomic knowledge in respiratory diseases.

Warfarin is often recommended for PAH management to mitigate thrombotic risk and improve survival [57]; it is one of the top drugs studied in pharmacogenomics and for which different biomarkers have been identified. For this oral anticoagulant, there is a CPIC guideline for a genotype-guided warfarin dosing according to genotyping of CYP2C9, VKORC1, CYP4F2, and rs12777823 variants [49]. Warfarin is also a relevant example of the translation of pharmacogenetic traits from one population to others since the impact of genetic CYP2C9 and VKORC1 variants on warfarin’s anticoagulant effect has been reported to be population-specific [58].

This ethnicity relevance in pharmacogenomics highlights another concern in its clinical implementation. As can be observed in Tables 1 and 2, the pharmacogenomic information reported was generated mainly through studies including Caucasians. Although other investigations are performed in populations from Asia and Africa, these are underrepresented, and there are so many worldwide geographical regions in which pharmacogenomics exploration remains far away. Investigating the inter-ethnic and intra-ethnic variability in drug response related to pharmacogene variants would elucidate relevant information to guide prescription based on the local characteristics of each population.

The remaining biomarkers reported by the FDA, PharmGKB, and CPIC (Tables 1–3) still warranted further studies to determine their utility in guiding the prescription of drugs employed to treat chronic respiratory diseases. Thus, their clinical implementation is further away.

4. Conclusion

There is available pharmacogenomic information for chronic respiratory diseases with distinct levels of evidence. In this review it can be observed that treating drugs such as arformoterol, indacaterol, and umeclidinium would not benefit from pharmacogenomics tools. Meanwhile, labels of ivacaftor and other CFTR modulators already include the genetic information necessary for prescribing these drugs. The pharmacogenomics of warfarin, administered in patients with PAH, highlights the relevance of pharmacogenomics in patients co-treated with a non-pulmonary therapy.

5. Expert opinion

Chronic respiratory diseases impact the life quality of the individuals affected and their families. The goal of personalized therapy in patients with chronic diseases is to improve the efficacy and security of available treatments to alleviate the health conditions of the affected people. Nevertheless, the benefit of pharmacogenomics in pulmonary drugs is still limited.

Although it is considered that the research on pharmacogenomics in respiratory diseases is scarce [8,55], several studies are reporting the evaluation of genetic variants in the treatment of disorders such as asthma [59], COPD [39], and CF [60]. However, it is necessary to fill the gaps to identify a pharmacogenomic biomarker recognized by the official agencies and work into its implementation in clinical practice.

The pharmacogenomics of chronic respiratory diseases faces the same barriers as other areas of pharmacogenomics. Though not for pulmonary drugs, well-established biomarkers are available for their implementation in the clinical practice of chronic respiratory diseases. For instance, warfarin is one of the most consolidated biomarkers in pharmacogenomics. Nevertheless, the use of warfarin in pulmonary hypertension remains controversial [57,61,62], as well as the genotype-guided dosing of warfarin [58] due to the influence of the ethnic origin on the relation of genetic variants with the anticoagulant effects. Thus, for warfarin and different drugs, the impact of ethnicity on the benefit of individualizing therapy based on genetic tests must be assessed, mainly for the most important drugs in underrepresented populations in pharmacogenomic studies [58,63,64].

In addition, patients with chronic respiratory diseases may require using other drug classes for which CPIC actionable guidelines are available to guide therapy. This has been recently described for patients with CF, which 87% received at least one drug that could be dosed according to CPIC guidelines (i.e. serotonin 5‐HT₃ receptor antagonist, opioids, proton pump inhibitors, nonsteroidal anti-inflammatory, selective serotonin reuptake inhibitor, tricyclic antidepressants, warfarin, anticonvulsants) [60]. Likewise, rheumatic diseases can present pulmonary manifestations, and consolidated pharmacogenomic biomarkers are available to guide the prescription of rheumatology drugs [65,66].

In sum, pharmacogenomic biomarkers are available for drugs prescribed for chronic respiratory diseases belonging to pulmonary illness and other drug classes. The healthcare professionals and respiratory health services can consider the clinical implementation of genotype-guided dosing and/or prescription. The decision should be pondered in terms of the population involved, the tests’ availability, stakeholders’ support and interest, and economic resources for health services. Moreover, the incoming evidence on the cost-benefit of the pharmacogenomics practice in each local population could motivate the regulatory agencies and government to move toward a personalized therapy implementation. This will improve the health and life quality of patients with chronic respiratory diseases and optimize health resources.

We need to start moving on to the clinical implementation of pharmacogenomic-guided prescription. In the near future, the reports should be based on the results and the experience of the clinical use of pharmacogenomic biomarkers, including how they can be improved, the incorporation of new biomarkers, and the social and economic benefits of the pharmacogenomic practice.

Article highlights

• For chronic respiratory diseases, the availability of guidelines and recommended pharmacogenomics biomarkers has limited the clinical practice of personalized therapy, but some information can be used to improve the therapy of individuals with these diseases.

• The drugs’ labels for arformoterol, indacaterol, and umeclidinium indicate a lack of influence of genetic variants in the pharmacokinetics of these drugs.

• The main pharmacogenomic recommendations in chronic pulmonary diseases are for the indication of ivacaftor and other drugs for cystic fibrosis.

• There are available pharmacogenomic recommendations for other drugs that can be used to treat chronic respiratory diseases, such as warfarin.

Author contributions

R.F.V. and I.F.G. contributed to the manuscript’s conception, design, and writing. Both authors contributed to manuscript revision and read and approved the submitted version.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patterns received or pending, or royalties.

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