Methodologic Pitfalls in the Determination of Genetic Anticipation: The Case of Crohn Disease

Genetic anticipation is a phenomenon in which genetic transmission of disease is accompanied by changes in the genome such that the disease may manifest at a younger age and is often more severe in offspring than in the affected parents. In several monogenic illnesses (1), including Huntington disease, myotonic dystrophy, and Friedreich ataxia, the biological basis for genetic anticipation is suggested to be expansion of unstable genomic triplet repeats. Although there is no accepted biological mechanism for genetic anticipation in complex or polygenic disease, some have suggested that it exists in such illnesses as Crohn disease, bipolar disorder, schizophrenia, Behet disease, and rheumatoid arthritis (2-6). The basis of these claims is typically a comparison of the age at diagnosis in parents and children. Crohn disease is an idiopathic chronic inflammatory bowel disease with apparent genetic transmission in some families. The earliest report suggesting genetic anticipation in Crohn disease (2) was based on cross-sectional data from a cohort assembled at Johns Hopkins Hospital in Baltimore, Maryland, in which it was noted that 52 of 55 affected children had younger ages at diagnosis than their affected parents, with an average difference of 15 years. This observation was replicated, and the claim of genetic anticipation reinforced, in subsequent different reports (2, 7, 8) of additional parentchild pairs (Figure 1). Figure 1. Evidence of genetic anticipation in Crohn disease from different centers based on differences in age at diagnosis between parents ( white bars ) and children ( gray bars ). P One characteristic common to almost all of those reports was that the cohort of children was typically followed for a much shorter time than their parentsthat is, up to a lower average age. This creates a bias, called inadequate follow-up time bias (9, 10), wherein persons who have not completed the risk period for a disease are included with those who have. In this context, follow-up means follow-up from birth rather than from time of disease diagnosis. This bias can occur in cross-sectional data (a single look at a single time), when parents who have all passed through most of the period of risk for the disease are compared with children who have not yet completed the risk period. Children who are unaffected at the time of analysis but would go on to manifest the disease at later ages are not included in the calculation of average age at onset. This makes the average age of disease onset in children appear lower than it would be if this group were followed for a longer time, which in turn produces a false impression of genetic anticipation. Secular trends, such as age, period, and cohort effects (11), can also complicate the interpretation of age at diagnosis data. In this paper, cohort means birth cohort: a group of persons born within a particular time period that is followed as it ages. If all cohorts show different risks for disease at different ages, such as increased risk for cancer with age, that is an age effect. A cohort effect is a factor that makes one cohort different from another, such as younger exposure to a causative agent for successive birth cohorts, which might decrease the age of disease onset in younger groups. A period effect is an event that occurs within or after a certain calendar period, such as development of a better diagnostic test that improves early detection of disease. We use data on Crohn disease to review the pitfalls of analyzing age-at-diagnosis data to draw conclusions about the presence of genetic anticipation and secular trends. Using a referral population of patients with Crohn disease, we show how inadequate follow-up time bias (9, 10) has operated in reports of genetic anticipation in Crohn disease, and we present simple analytical methods that can reveal and remove this bias. Specifically, we examine the questions, Is the age at diagnosis of Crohn disease changing? and Could inadequate follow-up time bias lead to a false impression of genetic anticipation? Methods Patient Sample We analyzed data on 928 consecutive outpatients with Crohn disease seen at the Meyerhoff Center for Inflammatory Bowel Disease at Johns Hopkins Hospital, Baltimore, Maryland, from 1 January 1985 through 1 July 1997. The sample included the 552 patients who served as the source population for 25 of the parentchild pairs in the original report that suggested genetic anticipation (2). In these 552 patients and in a sample of 203 patients from the remaining cohort, 15% and 14.4% of patients, respectively, had a first-degree relative with inflammatory bowel disease; this rate was similar to that in other published series (12). In this referral-based population, 95% percent of patients were white. The diagnosis of Crohn disease was confirmed by using standard criteria (13). The distribution of disease location and behavior was similar to that in other referral centers worldwide (14). Data Collection We recorded age at diagnosis, year of diagnosis, and birth date. We divided participants into six 10-year birth cohorts: before 1930, 1930 to 1939, 1940 to 1949, 1950 to 1959, 1960 to 1969, and 1970 to 1979. Adjustment for Period of Risk The methods used to correct for follow-up time bias involve constructing comparison cohorts that have been observed for the same amount of time or making statistical adjustments for the failure to observe some persons for the full risk period. The latter methods are complex but may be necessary when cohorts with equivalent observation time cannot be constructed from a given patient sample (15-17). We used the simpler former method here, basing our age-at-diagnosis analysis on patients with Crohn disease who were observed for the same amount of time and received a diagnosis within that time. To compare different generations, we analyzed differences in average age at diagnosis (18, 19), with and without adjustment for inadequate follow-up time, by calculating Pearson correlation coefficients and using KaplanMeier analysis. Log-rank tests were used to assess differences between KaplanMeier curves. Determination of adequate follow-up time was based on the bimodal distribution for age at diagnosis of Crohn disease, which is the third decade of life for approximately 75% of patients (early onset) and the seventh decade of life for a smaller proportion of patients (late onset) (20-22). These two groups may represent distinct phenotypes with different genetic and environmental influences (23), and trends in age at diagnosis may differ. We chose to focus on the early-onset group. To ensure equal follow-up times, we restricted our analysis to patients who had lived at least 40 years and had received a diagnosis by 40 years of age. This restriction excludes, for example, persons in whom disease was diagnosed at 45 years of age or persons who received a diagnosis by 25 years of age and were 38 years of age at the time of analysis. However, if the latter patient was 41 years of age at the time of analysis, he or she would be included. This eliminates from analysis all patients from later birth cohortsfor example, those born after 1960, who could not be 40 years of age by 1997. Results Unadjusted Analyses The mean age at diagnosis of the 928 patients was 26.6 years and was bimodal, with a major peak in the third decade of life and a minor peak in the seventh decade of life. In the unadjusted analysis, we calculated the average age at diagnosis of patients born within each decade. This analysis seemed to show that the mean age at diagnosis decreased by an average of 5 years with each successive 10-year birth cohort as age at study entry decreased (Figure 2). For example, the mean age at diagnosis was 31.2 years in the cohort born in the 1940s but 15.9 years in the cohort born in the 1970s. Thus, persons of two generations 30 years apart, such as parent and child, would appear to have a 15-year difference in age at diagnosis. KaplanMeier (24) estimates of patients in whom disease remained undiagnosed at a given age also demonstrated that the median age at diagnosis decreased with each successive birth cohort (Figure 3). Figure 2. Age at study entry ( white bars ) and mean age at diagnosis ( gray bars ) in six birth cohorts of patients with Crohn disease. P r P r P Figure 3. KaplanMeier estimates of the proportion of patients with undiagnosed Crohn disease in successive 10-year birth cohorts according to age, before adjustment for period of risk. P Adjusted Analyses Adjustment consisted of restricting all analyses to patients who were at least 40 years of age at the time of study entry and who had received a diagnosis before 40 years of age. Of the 928 patients, 289 satisfied this criterion. When we calculated age at diagnosis after this adjustment, the trend of decreasing age at diagnosis with each successive birth cohort was markedly reduced from 5 years to about 1 year per 10-year birth cohort, and birth cohort and age at diagnosis were poorly correlated (P=0.02). Thus, ensuring that everyone analyzed had been observed for the entire risk period almost eliminated what appeared to be a very large generational effect. KaplanMeier plots for each birth cohort within this restricted sample were almost indistinguishable (Figure 4), showing the same pattern as the mean age calculations. We conclude from these analyses that the mean age at diagnosis of Crohn disease has shown, at the most, a modest (approximately 1-year) decrease (cohort effect) with successive 10-year birth cohorts over the past 60 years. If true, this may have been the result in part of a heightened awareness of disease in the younger cohorts. Time of symptom onset, available for 194 of our patients, showed that cohorts born before 1960 had symptoms for 2 years longer before diagnosis than did those born after 1960, suggesting that diagnosis may be occurring earlier in the course of disease for younger patients. Figure 4. Ka