Identification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10−11) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.
Widespread access to the Internet and an increasing number of Internet users offers the opportunity of using Web-based recalls to collect detailed physical activity data in epidemiologic studies.The aim of this investigation was to evaluate the validity and reliability of a computer-based 24-hour physical activity recall (cpar24) instrument with respect to the recalled 24-h period.A random sample of 67 German residents aged 22 to 70 years was instructed to wear an ActiGraph GT3X+ accelerometer for 3 days. Accelerometer counts per min were used to classify activities as sedentary (<100 counts per min), light (100-1951 counts per min), and moderate to vigorous (≥1952 counts per min). On day 3, participants were also requested to specify the type, intensity, timing, and context of all activities performed during day 2 using the cpar24. Using metabolic equivalent of task (MET), the cpar24 activities were classified as sedentary (<1.5 MET), light (1.5-2.9 MET), and moderate to vigorous (≥3.0 MET). The cpar24 was administered twice at a 3-h interval. The Spearman correlation coefficient (r) was used as primary measure of concurrent validity and test-retest reliability.As compared with accelerometry, the cpar24 underestimated light activity by -123 min (median difference, P difference <.001) and overestimated moderate to vigorous activity by 89 min (P difference <.001). By comparison, time spent sedentary assessed by the 2 methods was similar (median difference=+7 min, P difference=.39). There was modest agreement between the cpar24 and accelerometry regarding sedentary (r=.54), light (r=.46), and moderate to vigorous (r=.50) activities. Reliability analyses revealed modest to high intraclass correlation coefficients for sedentary (r=.75), light (r=.65), and moderate to vigorous (r=.92) activities and no statistically significant differences between replicate cpar24 measurements (median difference for sedentary activities=+10 min, for light activities=-5 min, for moderate to vigorous activities=0 min, all P difference ≥.60).These data show that the cpar24 is a valid and reproducible Web-based measure of physical activity in adults.
Abstract Genome-wide association studies (GWAS) for late stage age-related macular degeneration (AMD) have identified 52 independent genetic variants with genome-wide significance at 34 genomic loci. Typically, such an approach rarely results in the identification of functional variants implicating a defined gene in the disease process. We now performed a transcriptome-wide association study (TWAS) allowing the prediction of effects of AMD-associated genetic variants on gene expression. The TWAS was based on the genotypes of 16,144 late-stage AMD cases and 17,832 healthy controls, and gene expression was imputed for 27 different human tissues which were obtained from 134 to 421 individuals. A linear regression model including each individuals imputed gene expression data and the respective AMD status identified 106 genes significantly associated to AMD variants in at least one tissue (Q-value < 0.001). Gene enrichment analysis highlighted rather systemic than tissue- or cell-specific processes. Remarkably, 31 of the 106 genes overlapped with significant GWAS signals of other complex traits and diseases, such as neurological or autoimmune conditions. Taken together, our study highlights the fact that expression of genes associated with AMD is not restricted to retinal tissue as could be expected for an eye disease of the posterior pole, but instead is rather ubiquitous suggesting processes underlying AMD pathology to be of systemic nature.
Purpose Population‐based epidemiological data on eye diseases are important determinants to steer health care. However, these data on prevalence, incidence, and risk factors are scarce in Central Europe and particularly in Germany. We therefore sought to establish such data for Bavaria, here focusing on age‐related macular degeneration (AMD). Methods The AugUR study (Age‐related diseases: understanding genetic and non‐genetic influences – a study at the University of Regensburg) is a population‐based prospective study in the mobile general population of Caucasian ethnicity aged 70 years and older in and around Regensburg, Bavaria. The study protocol includes ophthalmological anamnesis and examinations with testing of central retinal function (visual acuity, photostress test, Amsler Grid) as well as retinal imaging (standardized color fundus photographs of the central retina, confocal laser scanning ophthalmoscopy and spectral domain optical coherence tomography). The presence and extend of AMD is categorized via color fundus photographs into early and late stages. Results Since 2013, AugUR has recruited 1,133 participants, with 1,041 (92%) having gradable fundus images for at least one eye. A total of 418 (37% of the 1,041) individuals showed drusen and pigmentary abnormalities corresponding to early AMD findings, 69 (6%) participants demonstrated late‐stage AMD with neovascular or atrophic lesions. Importantly, we detected 83 (8%) persons with ‘latent’ AMD, i.e. being anamnestically unknown to the participant; 29 (3%) of those individuals revealed late AMD stages. Conclusions AugUR provides the first AMD prevalence estimates in an elderly German population. With an ongoing 3‐year‐follow‐up, this data will help to better understand disease development and progression.
Nowadays, replacing traditional authentication methods with authentication and authorization infrastructures (AAIs) comes down to trading several passwords for one master password, which allows users to access all services in a federation. Having only one password may be comfortable for the user, but it also raises the interest of potential impostors, who may try to overcome the weak security that a single password provides. A solution to this issue would be a more-factor AAI, combining the password with a biometric method of authentication that can work on the internet. The model presented in this work is based on typing behaviour biometrics, which can recognize a user by the way he/she types. This biometric method uses the keyboard as a sensor and is a pure software solution that can function in a web browser.
Due to the fact that biometrics do not require any knowledge-based features (like passwords), biometric AAIs based on typing behaviour are comfortable for the user. Also, no special devices (like tokens) are necessary for the authentication. Additionally, biometric AAIs provide high protection against attacks by uniquely assigning a username to a certain person. These advantages make biometric AAIs interesting for practical use.
As common AAIs were not especially designed to be used with biometrics, their architectures do not foresee specific biometric issues like the process of enrolment on different servers, template aging and synchronisation of biometric data (e.g. for the purpose of recognizing replay attacks). They also do not include methods of delivering information about the quality of biometric data upon the login process. A part of this research will concentrate itself upon the problems of biometrics in combination with AAIs, which will be studied both at the level of the typing behaviour biometric as well as at the level of AAIs. For this, different AAI architectures will be investigated in order to see whether they permit the use of biometrics as authentication technology and to research the necessary changes in their architectures in order to provide a reference model for a biometric AAI.
Creating study identifiers and assigning them to study participants is an important feature in epidemiologic studies, ensuring the consistency and privacy of the study data. The numbering system for identifiers needs to be random within certain number constraints, to carry extensions coding for organizational information, or to contain multiple layers of numbers per participant to diversify data access. Available software can generate globally-unique identifiers, but identifier-creating tools meeting the special needs of epidemiological studies are lacking. We have thus set out to develop a software program to generate IDs for epidemiological or clinical studies. Our software IDGenerator creates unique identifiers that not only carry a random identifier for a study participant, but also support the creation of structured IDs, where organizational information is coded into the ID directly. This may include study center (for multicenter-studies), study track (for studies with diversified study programs), or study visit (baseline, follow-up, regularly repeated visits). Our software can be used to add a check digit to the ID to minimize data entry errors. It facilitates the generation of IDs in batches and the creation of layered IDs (personal data ID, study data ID, temporary ID, external data ID) to ensure a high standard of data privacy. The software is supported by a user-friendly graphic interface that enables the generation of IDs in both standard text and barcode 128B format. Our software IDGenerator can create identifiers meeting the specific needs for epidemiologic or clinical studies to facilitate study organization and data privacy. IDGenerator is freeware under the GNU General Public License version 3; a Windows port and the source code can be downloaded at the Open Science Framework website: https://osf.io/urs2g/ .
Scientific Reports 7: Article number: 45040; published online: 28 April 2017; updated: 26 May 2017 The original version of this Article contained a typographical error in the spelling of the author Martin H. de Borst, which was incorrectly given as Martin de Borst. This has now been corrected in both the PDF and HTML versions of the Article.
Advanced age-related macular degeneration (AMD) is a leading cause of blindness in Western countries. Causal, modifiable risk factors need to be identified to develop preventive measures for advanced AMD.To assess whether smoking, alcohol consumption, blood pressure, body mass index, and glycemic traits are associated with increased risk of advanced AMD.This study used 2-sample mendelian randomization. Genetic instruments composed of variants associated with risk factors at genome-wide significance (P < 5 × 10-8) were obtained from published genome-wide association studies. Summary-level statistics for these instruments were obtained for advanced AMD from the International AMD Genomics Consortium 2016 data set, which consisted of 16 144 individuals with AMD and 17 832 control individuals. Data were analyzed from July 2020 to September 2021.Smoking initiation, smoking cessation, lifetime smoking, age at smoking initiation, alcoholic drinks per week, body mass index, systolic and diastolic blood pressure, type 2 diabetes, glycated hemoglobin, fasting glucose, and fasting insulin.Advanced AMD and its subtypes, geographic atrophy (GA), and neovascular AMD.A 1-SD increase in logodds of genetically predicted smoking initiation was associated with higher risk of advanced AMD (odds ratio [OR], 1.26; 95% CI, 1.13-1.40; P < .001), while a 1-SD increase in logodds of genetically predicted smoking cessation (former vs current smoking) was associated with lower risk of advanced AMD (OR, 0.66; 95% CI, 0.50-0.87; P = .003). Genetically predicted increased lifetime smoking was associated with increased risk of advanced AMD (OR per 1-SD increase in lifetime smoking behavior, 1.32; 95% CI, 1.09-1.59; P = .004). Genetically predicted alcohol consumption was associated with higher risk of GA (OR per 1-SD increase of log-transformed alcoholic drinks per week, 2.70; 95% CI, 1.48-4.94; P = .001). There was insufficient evidence to suggest that genetically predicted blood pressure, body mass index, and glycemic traits were associated with advanced AMD.This study provides genetic evidence that increased alcohol intake may be a causal risk factor for GA. As there are currently no known treatments for GA, this finding has important public health implications. These results also support previous observational studies associating smoking behavior with risk of advanced AMD, thus reinforcing existing public health messages regarding the risk of blindness associated with smoking.
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