Why identify genetic risk factors for disease?

One major reason to identify genetic risk factors for a clinical disease is to advance scientific knowledge about the pathophysiology of the disease to facilitate targeted diagnostic, therapeutic, and preventative interventions. For example, pelvic organ prolapse is thought to have a multifactorial etiology with a genetic component ; however, the underlying mechanisms that lead to defects are not yet known. By understanding the genetic susceptibility for a disease, mutation screening may be developed and utilized for risk stratification to individualize recommendations for prevention or treatment.

In studies of common, complex diseases, a critical component is to characterize, or phenotype, the disorder accurately to facilitate the identification of genetic effects. The process of developing a phenotype definition involves the use of epidemiological, biological, molecular, and/or bioinformatic methods to systematically select characteristics of a disorder that might result from distinct genetic influences.

Defining the phenotype is critical because poorly phenotyped studies will misclassify participants, which decreases the power to identify significant genetic effects. Although it is important to carefully define and phenotype cases with a disease, trait, or susceptibility, it is also necessary to define controls without disease because genetic epidemiological studies will often compare cases with controls. To illustrate these concepts in further detail and to discuss the nuances of designing genetic epidemiological studies, we will use pelvic organ prolapse as an example to highlight critical considerations in phenotyping clinical disorders.

Pelvic organ prolapse as an example

Pelvic organ prolapse is a major women’s health issue with a prevalence as high as 40% in postmenopausal women. Risk factors for prolapse include advancing age, white race, higher body mass index, increasing parity, smoking, chronic constipation, chronic cough, and family history of prolapse. Although childbirth is often considered a major risk factor, a majority of parous women do not develop prolapse, whereas some nulliparous women do develop the condition. Furthermore, the development of prolapse is often temporally distant from birth injury, thereby strongly suggesting that additional factors beyond vaginal parity, such as genetic susceptibility, that contribute to or protect against prolapse.

Pelvic organ prolapse as an example

Pelvic organ prolapse is a major women’s health issue with a prevalence as high as 40% in postmenopausal women. Risk factors for prolapse include advancing age, white race, higher body mass index, increasing parity, smoking, chronic constipation, chronic cough, and family history of prolapse. Although childbirth is often considered a major risk factor, a majority of parous women do not develop prolapse, whereas some nulliparous women do develop the condition. Furthermore, the development of prolapse is often temporally distant from birth injury, thereby strongly suggesting that additional factors beyond vaginal parity, such as genetic susceptibility, that contribute to or protect against prolapse.

General principles in genetic epidemiological studies

In developing a study to evaluate the genetic epidemiology of prolapse, a common approach is to recruit cases with prolapse vs controls without prolapse; however, a critical scientific question is how will pelvic organ prolapse be defined. Prior to discussing different approaches to defining prolapse, it is important to discuss key principles that are unique to genetic epidemiologic studies.

Diseases that become more prevalent with advancing age

It is important to consider the age of onset and natural history of the disease of interest because this will directly have an impact on who to recruit for cases and controls. For example, a 45 year old woman may not show any evidence of prolapse and thus could be considered a control subject. However, it is possible that she may not develop prolapse until 50 or 60 years of age. In many genetic epidemiological schemes, these younger unaffected subjects are considered unknowns. Thus, older women without evidence of prolapse are more ideal control subjects. The same rationale applies to studying other phenotypes, which are characterized by older age at onset, such as coronary artery disease and breast cancer.

Important considerations regarding race and ethnicity

It is critical to carefully consider race and ethnicity in genetic epidemiological studies because different racial/ethnic groups may have different frequencies of genetic variants, which is a concept known as population stratification. These systematic differences in allele frequencies exist because of differences in ancestry rather than the association between genes and diseases. Confounding by race results when race is associated with both differences in genetic variant frequencies as well as differences in disease prevalence, but there is no association between the genetic variants and disease. Thus, population stratification in genetic studies can lead to excess false-positive results and failures to detect true associations. Because of population stratification, genetic studies will often focus on 1 specific race/ethnicity or utilize advanced analytic techniques to adjust for racial genetic differences.

Consequences of heterogeneity in phenotype definitions

Heterogeneities in complex disease, such as prolapse, arise because of different clinical manifestations, differences in biological pathways leading to disease, and differences in symptom severity. Often phenotypic heterogeneity (inconsistency in the definition of phenotype) across studies makes it difficult to generalize study findings and to replicate genetic associations. This inconsistency in trait definition may be due to a lack of consensus or a general disagreement among researchers in the field as to the correct phenotypic definition. Establishing a consistent operational definition and description of the phenotype to be used across studies may help avoid this dilemma. In the following text, we will discuss different methods of phenotyping prolapse and make a recommendation regarding how to phenotype prolapse to move toward developing a consistent phenotype definition for future genetic epidemiological studies.

Defining the phenotype of pelvic organ prolapse

There are several different clinical definitions for prolapse, and none are universally accepted. Possible definitions include the following: (1) bothersome symptoms, which focus on subjective factors, (2) surgical treatment for prolapse, and (3) the stage of prolapse, which is an objective measure of severity.

It has been shown that bothersome symptoms are a critical component of evaluating prolapse, and validated questionnaires include a question regarding bothersome prolapse symptoms: “Do you usually have a bulge of something falling out that you can see or feel in the vaginal area? If yes, how much does it bother you?” Although this is key to evaluating treatment outcomes, it is less suited to designing early genetic association studies.

Another option for phenotyping prolapse is to define prolapse based on those who have chosen to undergo surgery. Presumably only women with severe enough bothersome symptoms warrant surgical management. One important consideration is that it is necessary to confirm the procedures performed and the indication for surgery. Obtaining prior operative reports can be somewhat challenging, especially if the surgery was in the distant past. Furthermore, this phenotype definition fails to capture women who may have very advanced prolapse but pursue nonsurgical treatment options.

A more objective method of phenotyping is based on examination findings, and for prolapse, the 2 primary examination techniques are the pelvic organ prolapse quantification (POP-Q) or the Baden-Walker system. A common strategy is to compare cases with POP-Q stage III/IV prolapse vs controls with stage 0/I prolapse. The rationale is that there may be some degree of prolapse that occurs as a normal part of aging because the proportion of postmenopausal women with a mild degree of prolapse is relatively high. By excluding stage II, the more extreme phenotypes are captured.

Selective sampling of more extreme phenotypes is a common approach in genetic epidemiological studies because recruitment of more extreme phenotypes increases the probability of observing a genetic effect. For example, a woman with a high genetic risk might be a young, premenopausal, nulliparous woman with stage IV prolapse and a family history of prolapse. In contrast, a low-genetic-risk woman might be an 80 year old woman who has had 5 vaginal deliveries yet has stage 0 prolapse.

Although it may be difficult to identify and recruit these ideal extreme phenotypes, it is important to select cases and controls that are clinically disparate. Thus far, a majority of case control association studies have defined cases and controls based on physical examination findings. Currently we recommend using physical examination findings to phenotype prolapse, given that it is an objective measure that is likely to be more reproducible. Also, for initial genetic epidemiological studies, the definition of cases as stage III-IV and controls as stage 0-I may increase the power to identify a genetic effect.

Although we have focused on the definition of cases for this phenotype, it is also critically important to define control subjects carefully to decrease the risk of misclassification bias. It is necessary to ensure that controls have been evaluated fully for the disease/phenotype of interest and have had equal opportunity for detection of the condition. For example, if we defined prolapse solely based on symptoms, it is possible that an asymptomatic woman who actually has prolapse on examination could be selected as a control. It is important to exclude those who have had prior surgery for prolapse; thus, a careful medical and surgical history and physical examination are needed.

Role of risk factors and confounders

After defining the cases and controls, it is necessary to identify risk factors and potential confounders. The presence of risk factors, in either cases or controls, will be adjusted for in the statistical analysis to ultimately estimate the contribution from genetic factors. Family history may be used to further refine the phenotype, if desired.

Risk factors for prolapse

Given that the etiology of prolapse is likely multifactorial with a genetic component as well as environmental factors, which include health behaviors, medical conditions, and exposures, it is important to collect data on other risk factors and to think about potential exclusion criteria. The presence of risk factors, in either cases or controls, will be adjusted for in the statistical analysis to ultimately estimate the contribution from genetic factors. Data collection should include detailed information regarding obstetrics history, including parity; mode of deliveries (vaginal, cesarean, and assisted vaginal deliveries), age at first delivery, infant birthweight, and perineal trauma; diseases associated with Valsalva maneuvers, such as emphysema/chronic obstructive pulmonary disease or constipation; prior surgical history, including hysterectomy; prior antiincontinence and prolapse procedures; medications, especially hormone replacement therapy and steroid use; smoking history; and body mass index.

Another consideration is to collect additional markers for connective tissue issues such as joint hypermobility, varicose veins, rectal prolapse, and hernias. However, those with connective tissue disease, such as Ehlers-Danlos or Marfans syndrome, should be excluded because these subjects may have an inherently higher risk for prolapse.