The German AugUR study: study protocol of a prospective study to investigate chronic diseases in the elderly

Abstract

BackgroundThe majority of patients suffering from chronic health disabilities is beyond 70 years of age. Typical late-onset chronic diseases include those affecting the heart, the kidney, cancer, and conditions of the eye such as age-related macular degeneration. These diseases disable patients for many years and largely compromise autonomy in daily life. Due to challenges in recruiting the elderly, the collection of population-based epidemiological data as a prerequisite to understand associated risk factors and mechanisms is commonly done in the general population within an age-range of 20 to 70 years.Methods/DesignWe establish the German AugUR study (Age-related diseases: understanding genetic and non-genetic influences - a study at the University of Regensburg), a prospective study in the mobile elderly general population in and around Regensburg in eastern Bavaria. In the long term, we aim to recruit 3,000 persons of Caucasian ethnicity with at least 70 years of age via residents’ registration offices and conduct 3-year follow-ups.The study protocol includes a standardized interview regarding social and life-style factors, medication history, quality-of-life, and existing diagnoses of common diseases. The participants undergo medical examinations for ophthalmological, cardiovascular or diabetes-related conditions, and general measurements of body shape and fitness. The program is particularly tailored for the elderly. Biobanking of whole blood, serum, plasma, and urine is conducted and standard laboratory measurements are performed in fresh samples.DiscussionAugUR is specifically designed as a research platform to host studies of late onset diseases. Consequently, this platform will help (1) to unravel the genetic and non-genetic etiology of disease development and progression, (2) to serve as control group of elderly individuals for comparisons with various patient groups, (3) to derive prevalence and incidence data on chronic diseases, and (4) to provide clinical reference parameters for the elderly mobile general population. This data will foster our understanding of disease mechanisms, which may ultimately help to improve prevention, diagnosis, and therapy for frequent chronic diseases. Here we present the baseline study protocol of AugUR.

Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals

“…(1) Using LD-score regression ((LDSC)) 32 , we estimated the additive contribution of all analyzed variants, i.e., narrow-sense heritability, h 2 =13.4% (based on unrelated individuals of European-ancestry from UKB, N = 364,674, Table 5). (4) Finally, we observed significant and very similar GRS effects across two studies, in UKB as the largest source of our GWAS and in AugUR 34 as an independent population-based study (UKB, bGRS=-0.24 ml/min/1.73m 2 per allele, PGRS = 6.7 x 10 -5847 ; AugUR, bGRS=-0.21 ml/min/1.73m 2 per allele, PGRS = 1.6 x 10 -9 ; Table 4). In AugUR, individuals with a high versus low genetic risk (95% percentile of GRS versus 5%, i.e.…”

“…To estimate an average and cumulative effect of genetic variants on eGFRcrea, we conducted GRS analyses in two studies: The German AugUR study (prospective study in the mobile elderly general population around Regensburg, Germany, age range 70-95y, mean +/-SD eGFRcrea = 70.0 +/-15.5 ml/min/1.73m 2 , n = 1,105) 34 , and UKB (prospective cohort study from UK, age range 40-69y, mean +/-SD eGFRcrea = 90.6 +/-13.2 ml/min/1.73m 2 , n ~ 500,000) 14 . While UKB was part of our variant identifying discovery meta-analysis, AugUR…”

Response misclassification in studies on bilateral diseases

“…Detailed information on this data can be found in Stark et al. (). Briefly, the AugUR study is a prospective study in the elderly population in the city and county of Regensburg in Eastern Bavaria, Germany.…”

“…We derive the model‐based conditional probability of disease in randomly selected single entities and propose to optimise a likelihood based on the derived conditional probabilities to estimate regression parameters. In Section 2.3, we discuss additional misclassification in the single entity disease diagnosis and, in Sections 3 and 4, we compare the different estimation approaches in a real data example of the AugUR study on AMD (Age‐related diseases: Understanding genetic and nongenetic influences—a study at the University of Regensburg, Stark et al., ) and based on simulated data. In Section 5, we discuss the proposed modelling approach and its assumptions and give recommendations for application.…”

IDGenerator: unique identifier generator for epidemiologic or clinical studies

“…We developed a software program that guarantees unique IDs, supports the generation of structured IDs to facilitate study organization, provides layered IDs to enhance data protection, and can extend existing IDs with new non-overlapping batches. While IDGenerator was originally developed for the needs of the AugUR study [ 13 ], it allows for different parametrization and therefore can be applied to epidemiological studies with different requirements.…”