Elsevier

Sleep Medicine Reviews

Volume 35, October 2017, Pages 113-123
Sleep Medicine Reviews

Clinical Review
Phenotypes in obstructive sleep apnea: A definition, examples and evolution of approaches

https://doi.org/10.1016/j.smrv.2016.10.002Get rights and content

Summary

Obstructive sleep apnea (OSA) is a complex and heterogeneous disorder and the apnea hypopnea index alone can not capture the diverse spectrum of the condition. Enhanced phenotyping can improve prognostication, patient selection for clinical trials, understanding of mechanisms, and personalized treatments. In OSA, multiple condition characteristics have been termed “phenotypes.” To help classify patients into relevant prognostic and therapeutic categories, an OSA phenotype can be operationally defined as: “A category of patients with OSA distinguished from others by a single or combination of disease features, in relation to clinically meaningful attributes (symptoms, response to therapy, health outcomes, quality of life).” We review approaches to clinical phenotyping in OSA, citing examples of increasing analytic complexity. Although clinical feature based OSA phenotypes with significant prognostic and treatment implications have been identified (e.g., excessive daytime sleepiness OSA), many current categorizations lack association with meaningful outcomes. Recent work focused on pathophysiologic risk factors for OSA (e.g., arousal threshold, craniofacial morphology, chemoreflex sensitivity) appears to capture heterogeneity in OSA, but requires clinical validation. Lastly, we discuss the use of machine learning as a promising phenotyping strategy that can integrate multiple types of data (genomic, molecular, cellular, clinical) to identify unique, meaningful OSA phenotypes.

Introduction

Obstructive sleep apnea (OSA) is increasingly recognized as a complex and heterogeneous disorder [1]. Recent work shows that this heterogeneity exists in the domains of the presenting symptoms [2], physiologic etiology [3], comorbid conditions [4], and important outcomes [5], ∗[6], [7]. Despite this recognition, the diagnosis, assessment of severity, and management of OSA remains intimately linked to a single indicator, the apnea hypopnea index (AHI) [8]. An AHI-centered approach, with its lack of stratification by other syndrome characteristics likely contributes to the challenges of better understanding the genetic and biological underpinnings of the disorder [9] as well as to the modest treatment effects found in large randomized trials using continuous positive airway pressure (CPAP) [10], [11], [12].

One way to address these challenges is to classify the disorder into smaller, more homogeneous categories. Such classifications, sometimes referred to as “phenotypes,” can be based on clinical, pathophysiologic, cellular, or molecular characteristics [13]. Recent data suggest that patients may respond differently to non-positive airway pressure (non-PAP) treatments depending on their pathophysiologic characteristics such as arousal propensity or ventilatory sensitivity [14]. Successful therapeutic clinical trials can also be designed if patient categories more likely to respond to a given therapy are selected, such as those without complete concentric palatal collapse treated with upper airway neuro-stimulation [15]. These examples suggest that improved phenotyping approaches are an important step towards the goal of personalized medicine for OSA patients.

This manuscript provides an overview of the OSA phenotype literature in the context of various approaches to phenotyping. Specifically, the goals of this review are to:

  • 1)

    Explore how phenotype identification can improve understanding of heterogeneous disorders (illustrated through other conditions) and propose a working definition of a phenotype in OSA for research and patient care

  • 2)

    Summarize the OSA “phenotype literature” to-date, using key examples of OSA phenotyping approaches and their utility

  • 3)

    Identify gaps in the current approaches and propose means to address them with a goal of personalizing care of patients with OSA

Section snippets

Role of phenotyping and lessons from other conditions

The aims of phenotyping include improving understanding of disease mechanisms, predicting response to therapy, risk for adverse events and reducing heterogeneity in clinical trials [16].

Similar to OSA, asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous disorders whose diagnosis and management have been traditionally based on measures of physiological (expiratory volumes) and functional impairment. By better understanding the heterogeneity of these conditions, marked

OSA phenotype, a definition

Ideally, the phenotype serves as an expression of an “endotype,” a subtype of disease defined by “a unifying and consistent natural history, clinical and physiological characteristics, an underlying pathobiology with identifiable biomarkers and genetics and a predictable response to general and specific therapies that impact relevant patient outcomes” [13]. Current categorizations of OSA patients, however, have not yet advanced to the status of endotype definition. At this point we believe that

Phenotyping approaches

Phenotyping strategies can be grouped by features (e.g., clinical vs. molecular) and by experimental approaches (e.g., supervised vs. unsupervised) (Table 1) [16]. Clinical phenotyping focuses on identifying unique patient categories based on measures such as signs, symptoms, demographics, comorbidities, physiological and anatomic measures, or treatment responsiveness. Molecular phenotyping aims to classify individuals based on molecular features: DNA, RNA, mRNA, miRNA, proteins, metabolites

Literature search

A literature search for key concepts related to sleep apnea and phenotypes was performed (see Supplement [Part A], for methods and article inclusion/exclusion criteria). Table of potential phenotypes and their characteristics can be viewed in the Supplement (Part B).

a. Symptom and demographics based features

The concept that differing presenting symptoms may have implications for pathogenesis and outcomes has been used to phenotype OSA individuals for decades. Up to sixty percent of OSA patients can be excessively sleepy [30] and report

Summary and future directions

Evidence is accumulating and consensus is building that AHI alone is insufficient for diagnosis and management of individuals with OSA. Complementary to molecular phenotyping, clinical phenotyping may serve as an intermediate step towards personalized medicine in OSA. Emerging themes from current literature include needs for: 1) improved anchoring of phenotypes to clinically relevant outcomes and 2) addressing the interplay of features important in pathogenesis of OSA though advanced analytic

Acknowledgments

This work was supported by Robert E. Leet and Clara Guthrie Patterson Trust Fellowship Program in Clinical Research, Bank of America, N.A., Trustee and by the National Institutes of Health training grant T32 HL007778-21.

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