grading would be preferred when possible for genetic association studies. Nonetheless, we sought to compare the observed frequency of complex traits in our 100 patients to the previous reports of prevalence of the ten common complex traits (Table 1), because this information is important in designing future studies using case-control studies. Prevalence studies of corneal guttae have not been performed in North American populations. The Reykjavik study estimated an overall 9% prevalence in a Caucasian population, while a study on Asians estimated 3.5% to 6.5% depending on the population [30,31]. ABMD may be present in about 5% of the population, based on a prior prevalence study in North Americans [32]. The prevalence of cataract was estimated to be about 50% [33,34]. The much higher prevalence in our patients is due to the difference in definition of the age-related lens changes to diagnose a cataract, since almost all patients have some age-related lens change by the age of 60. Use of one of the quantitative scales would be preferred for a genetic association study [35]. The prevalence of pseudoexfoliation varies greatly across populations, and no previous studies appeared to be a good fit the population of Minnesota and an estimate of 5% was assumed based on other populations [36–38]. The much higher prevalence of AMD in our patients, compared to the population estimate of 15%, is due to referral bias, since this was the leading cause of presenting diagnosis [39]. The population prevalence of glaucoma is about 5% based on the Beaver Dam study [40]. The observed prevalence of posterior vitreous separation in our study was similar to published reports [41]. The prevalence of epiretinal membranes and retinal vascular occlusion in the Blue Mountains Eye Study was about 10%, and 2% respectively [42,43]. The prevalence of retinal tears in autopsy eyes was 3.3% [44]. These latter three traits are also common reasons for referral. Thus, with the exception of the traits representing common reasons for referral to the examiner and the lower threshold for diagnosis of cataract, the observed prevalence of these 10 complex traits is a reasonable approximation to published reports (Table 1). It was notable how little prevalence information, population-based or otherwise, was actually available for most common ocular traits in North America. Genetic association studies on age-related ocular traits often use age 60 or older for controls, under the assumption that subjects in this age range are unlikely to develop the trait under study at a later age. Our observation of a steady increase in the density of complex traits with age might be explained by only older subjects symptomatic or having vision threatening eye diseases coming to the clinic. We have no method for controlling for this possibility, but our observations are consistent with the already established increase in disease prevalence for AMD, glaucoma, and RVO [40,43,45]. Further, for PVD which is known to stabilize with age, we did not observe an age-dependent increase [46]. Thus, the selection of an age-cut off for controls should be selected based upon the age-dependent prevalence of the disease or preferably either frequency or exact matched for age. The commonly held opinion that age 60 is the lowest acceptable minimal age for controls used in studies on AMD, glaucoma, and other eye traits is not supported by our data. In addition to these complex traits affecting the eye, there are a number of quantitative biomorphic and biochemical variables of interest in eye development and disease risk. For example, central corneal thickness has been associated with risk of development of glaucoma and many investigators believe that macular pigment and macular autofluorescence alter the risk of macular degener- ation [17,19,47]. Although there are few studies exploring the heritability of such quantitative variables in humans, available Density Complex Ocular Traits evidence suggests that biomorphic ocular variables are highly hereditary [48–52]. In addition to demographic and epidemio- logical variables such as dietary and drug exposures, these variables should be considered for inclusion in a comprehensive study of complex ocular traits. The density of complex traits in these patients and our modeling studies suggest that future studies of complex ocular traits would benefit from the systematic documentation of secondary traits. An ascertainment strategy that focused on the diseases of highest priority (e.g., AMD, glaucoma, Fuchs, cataract) could be employed to optimize the case-control study for detection of other traits of secondary interest. There is substantial evidence that many of the common traits have genetic influences, as illustrated in Table 1. Of course, the lack of strong evidence does not imply the absence of a genetic effect as was recently demonstrated for pseudoexfoliation [3]. Inclusion of biomorphic and biochemical endpoints would further expand the value of the study. This type of approach would offer advantages over the standard approach looking at a single trait including the ability to look for shared genetic risks directly, the ability to detect trait-trait association, and overall lower cost. Although our model for this study was the aging eye, there is evidence that similar concepts apply to other organs such as the skin [53]. A number of study designs are available to study common complex traits. The Wellcome Trust Case Control Consortium used a pool of unexamined subjects as the controls for each of the seven traits studied [54]. While this is a reasonable approach, it does not appear to have any major advantages over sequentially studying secondary traits in a case-control study. For example, both could be influenced by referral biases and geographic differences in genetics or exposures. Further, the unexamined control strategy results in loss of power for very common traits, because a certain proportion of the controls have disease. The approach we are suggesting can control for the various biases in subject ascertainment and exposures, maximizes power because all subjects are phenotyped, and minimizes genotyping costs because most (or all) subjects have one or more diseases of clinical interest. Methods Patient chart review This retrospective chart review was approved by the institu- tional review board of the Mayo Clinic and patient consent was not required. The data was extracted twice and any discrepancies resolved by the first author. The initial visit was reviewed first and subsequent visits reviewed to look for diseases present at the first examination, but that were not documented. Although this study is retrospective, the retina specialist performed a systematic and comprehensive eye examination documenting all ocular diagnoses, including the complex traits listed in Table 1 on all patients examined during their initial visit. Note that these common traits extracted from the medical record were selected in advance, prior to the start of the study, because they are documented on most visits due to their relevance to the performance or complications of surgery and/or potential impact on vision. Thus, the number of diagnoses overlooked is expected to be modest. Age and gender were recorded in order to stratify the density of complex traits by these two variables. The final diagnosis underlying the reason for the patient’s initial consultation was recorded as the presenting diagnosis. Ethnicity was not considered in the analysis because over 90% of the patients were Caucasian, reflecting the frequency of this population in southeastern Minnesota. The diagnostic criteria followed standard clinical criteria. The diagnosis of AMD was made based on a published classification system [55]. Fuchs was diagnosed based on having two or more PLoS ONE | www.plosone.org 5 June 2008 | Volume 3 | Issue 6 | e2510