Glucose tolerance and insulin resistance/sensitivity associate with retinal layer characteristics: the LIFE-Adult-Study.

AIMS/HYPOTHESIS: As the prevalence of insulin resistance and glucose intolerance is increasing throughout the world, diabetes-induced eye diseases are a global health burden. We aim to identify distinct optical bands which are closely related to insulin and glucose metabolism, using non-invasive, high-resolution spectral domain optical coherence tomography (SD-OCT) in a large, population-based dataset. METHODS: The LIFE-Adult-Study randomly selected 10,000 participants from the population registry of Leipzig, Germany. Cross-sectional, standardised phenotyping included the assessment of various metabolic risk markers and ocular imaging, such as SD-OCT-derived thicknesses of ten optical bands of the retina. Global and Early Treatment Diabetic Retinopathy Study (ETDRS) subfield-specific optical retinal layer thicknesses were investigated in 7384 healthy eyes of 7384 participants from the LIFE-Adult-Study stratified by normal glucose tolerance, prediabetes (impaired fasting glucose and/or impaired glucose tolerance and/or HbA1c 5.7-6.4% [39-47 mmol/mol]) and diabetes. The association of optical retinal band characteristics with different indices of glucose tolerance (e.g. fasting glucose, area under the glucose curve), insulin resistance (e.g. HOMA2-IR, triglyceride glucose index), or insulin sensitivity (e.g. estimated glucose disposal rate [eGDR], Stumvoll metabolic clearance rate) was determined using multivariable linear regression analyses for the individual markers adjusted for age, sex and refraction. Various sensitivity analyses were performed to validate the observed findings. RESULTS: In the study cohort, nine out of ten optical bands of the retina showed significant sex- and glucose tolerance-dependent differences in band thicknesses. Multivariable linear regression analyses revealed a significant, independent, and inverse association between markers of glucose intolerance and insulin resistance (e.g. HOMA2-IR) with the thickness of the optical bands representing the anatomical retinal outer nuclear layer (ONL, standardised ß=-0.096; p<0.001 for HOMA2-IR) and myoid zone (MZ; ß=-0.096; p<0.001 for HOMA2-IR) of the photoreceptors. Conversely, markers of insulin sensitivity (e.g. eGDR) positively and independently associated with ONL (ß=0.090; p<0.001 for eGDR) and MZ (ß=0.133; p<0.001 for eGDR) band thicknesses. These global associations were confirmed in ETDRS subfield-specific analyses. Sensitivity analyses further validated our findings when physical activity, neuroanatomical cell/tissue types and ETDRS subfield categories were investigated after stratifying the cohort by glucose homeostasis. CONCLUSIONS/INTERPRETATION: An impaired glucose homeostasis associates with a thinning of the optical bands of retinal ONL and photoreceptor MZ. Changes in ONL and MZ thicknesses might predict early metabolic retinal alterations in diabetes.

Retinal OCT biomarkers and their association with cognitive function-clinical and AI approaches.

Retinal optical coherence tomography (OCT) biomarkers have the potential to serve as early, noninvasive, and cost-effective markers for identifying individuals at risk for cognitive impairments and neurodegenerative diseases. They may also aid in monitoring disease progression and evaluating the effectiveness of interventions targeting cognitive decline. The association between retinal OCT biomarkers and cognitive performance has been demonstrated in several studies, and their importance in cognitive assessment is increasingly being recognized. Machine learning (ML) is a branch of artificial intelligence (AI) with an exponential number of applications in the medical field, particularly its deep learning (DL) subset, which is widely used for the analysis of medical images. These techniques efficiently deal with novel biomarkers when their outcome for the applications of interest is unclear, e.g., for diagnosis, prognosis prediction, disease staging, or any other relevance to clinical practice. However, using AI-based tools for medical purposes must be approached with caution, despite the many efforts to address the black-box nature of such approaches, especially due to the general underperformance in datasets other than those used for their development. Retinal OCT biomarkers are promising as potential indicators for decline in cognitive function. The underlying mechanisms are currently being explored to gain deeper insights into this relationship linking retinal health and cognitive function. Insights from neurovascular coupling and retinal microvascular changes play an important role. Further research is needed to establish the validity and utility of retinal OCT biomarkers as early indicators of cognitive decline and neurodegenerative diseases in routine clinical practice. Retinal OCT biomarkers could then provide a new avenue for early detection, monitoring and intervention in cognitive impairment with the potential to improve patient care and outcomes.

[Retinal optical coherence tomography biomarkers and their association with cognitive functions : Clinical and artificial intelligence approaches. German version]. / Retinale optische Kohärenztomographie Biomarker und ihr Zusammenhang mit kognitiven Funktionen : Klinische Praxis und künstliche Intelligenz Ansätze.

Retinal optical coherence tomography (OCT) biomarkers have the potential to serve as early, noninvasive, and cost-effective markers for identifying individuals at risk for cognitive impairments and neurodegenerative diseases. They may also aid in monitoring disease progression and evaluating the effectiveness of interventions targeting cognitive decline. The association between retinal OCT biomarkers and cognitive performance has been demonstrated in several studies, and their importance in cognitive assessment is increasingly being recognized. Machine learning (ML) is a branch of artificial intelligence (AI) with an exponential number of applications in the medical field, particularly its deep learning (DL) subset, which is widely used for the analysis of medical images. These techniques efficiently deal with novel biomarkers when their outcome for the applications of interest are unclear, e.g., for the diagnosis, prognosis prediction and disease staging. However, using AI-based tools for medical purposes must be approached with caution, despite the many efforts to address the black-box nature of such approaches, especially due to the general underperformance in datasets other than those used for their development. Retinal OCT biomarkers are promising as potential indicators for decline in cognitive function. The underlying mechanisms are currently being explored to gain deeper insights into this relationship linking retinal health and cognitive function. Insights from neurovascular coupling and retinal microvascular changes play an important role. Further research is needed to establish the validity and utility of retinal OCT biomarkers as early indicators of cognitive decline and neurodegenerative diseases in routine clinical practice. Retinal OCT biomarkers could then provide a new avenue for early detection, monitoring and intervention in cognitive impairment with the potential to improve patient care and outcomes.

Phenome- and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health.

The human retina is a multilayered tissue that offers a unique window into systemic health. Optical coherence tomography (OCT) is widely used in eye care and allows the noninvasive, rapid capture of retinal anatomy in exquisite detail. We conducted genotypic and phenotypic analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed OCT layer cross-phenotype association analyses (OCT-XWAS), associating retinal thicknesses with 1866 incident conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association studies (GWASs), identifying inherited genetic markers that influence retinal layer thicknesses and replicated our associations among the LIFE-Adult Study (N = 6313). Last, we performed a comparative analysis of phenome- and genome-wide associations to identify putative causal links between retinal layer thicknesses and both ocular and systemic conditions. Independent associations with incident mortality were detected for thinner photoreceptor segments (PSs) and, separately, ganglion cell complex layers. Phenotypic associations were detected between thinner retinal layers and ocular, neuropsychiatric, cardiometabolic, and pulmonary conditions. A GWAS of retinal layer thicknesses yielded 259 unique loci. Consistency between epidemiologic and genetic associations suggested links between a thinner retinal nerve fiber layer with glaucoma, thinner PS with age-related macular degeneration, and poor cardiometabolic and pulmonary function with a thinner PS. In conclusion, we identified multiple inherited genetic loci and acquired systemic cardio-metabolic-pulmonary conditions associated with thinner retinal layers and identify retinal layers wherein thinning is predictive of future ocular and systemic conditions.

Pregnancy induces retinal microvascular changes indicating cardio-metabolic stress.

We performed longitudinal examinations of the arterial retinal microvasculature using Adaptive Optics Retinal Imaging in a 30-year-old healthy woman with twin pregnancy from the 23rd week of gestation (wog) to three days postpartum. Two blinded graders recorded the average wall-to-lumen ratio (WLR) of the examined retinal artery. There was a significant increase in the mean WLR over the course of pregnancy followed by a decreasing WLR from the 37th wog. The demonstrated changes in WLR may be an expression of vascular remodeling and adaptation to volume load which indicates that pregnancy can be viewed as a cardiovascular stress test.

Normative Percentiles of Retinal Nerve Fiber Layer Thickness and Glaucomatous Visual Field Loss.

Purpose: Circumpapillary retinal nerve fiber layer thickness (RNFLT) measurement aids in the clinical diagnosis of glaucoma. Spectral domain optical coherence tomography (SD-OCT) machines measure RNFLT and provide normative color-coded plots. In this retrospective study, we investigate whether normative percentiles of RNFLT (pRNFLT) from Spectralis SD-OCT improve prediction of glaucomatous visual field loss over raw RNFLT. Methods: A longitudinal database containing OCT scans and visual fields from Massachusetts Eye & Ear glaucoma clinic patients was generated. Reliable OCT-visual field pairs were selected. Spectralis OCT normative distributions were extracted from machine printouts. Supervised machine learning models compared predictive performance between pRNFLT and raw RNFLT inputs. Regional structure-function associations were assessed with univariate regression to predict mean deviation (MD). Multivariable classification predicted MD, pattern standard deviation, MD change per year, and glaucoma hemifield test. Results: There were 3016 OCT-visual field pairs that met the reliability criteria. Spectralis norms were found to be independent of age, sex, and ocular magnification. Regional analysis showed significant decrease in R2 from pRNFLT models compared to raw RNFLT models in inferotemporal sectors, across multiple regressors. In multivariable classification, there were no significant improvements in area under the curve of receiver operating characteristic curve (ROC-AUC) score with pRNFLT models compared to raw RNFLT models. Conclusions: Our results challenge the assumption that normative percentiles from OCT machines improve prediction of glaucomatous visual field loss. Raw RNFLT alone shows strong prediction, with no models presenting improvement by the manufacturer norms. This may result from insufficient patient stratification in tested norms. Translational Relevance: Understanding correlation of normative databases to visual function may improve clinical interpretation of OCT data.

Automated detection of genetic relatedness from fundus photographs using Siamese Neural Networks.

Heritability of common eye diseases and ocular traits are relatively high. Here, we develop an automated algorithm to detect genetic relatedness from color fundus photographs (FPs). We estimated the degree of shared ancestry amongst individuals in the UK Biobank using KING software. A convolutional Siamese neural network-based algorithm was trained to output a measure of genetic relatedness using 7224 pairs (3612 related and 3612 unrelated) of FPs. The model achieved high performance for prediction of genetic relatedness; when computed Euclidean distances were used to determine probability of relatedness, the area under the receiver operating characteristic curve (AUROC) for identifying related FPs reached 0.926. We performed external validation of our model using FPs from the LIFE-Adult study and achieved an AUROC of 0.69. An occlusion map indicates that the optic nerve and its surrounding area may be the most predictive of genetic relatedness. We demonstrate that genetic relatedness can be captured from FP features. This approach may be used to uncover novel biomarkers for common ocular diseases.

Insights into human health from phenome- and genome-wide analyses of UK Biobank retinal optical coherence tomography phenotypes.

The human retina is a complex multi-layered tissue which offers a unique window into systemic health and disease. Optical coherence tomography (OCT) is widely used in eye care and allows the non-invasive, rapid capture of retinal measurements in exquisite detail. We conducted genome- and phenome-wide analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed phenome-wide association analyses, associating retinal thicknesses with 1,866 incident ICD-based conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association analyses, identifying inherited genetic markers which influence the retina, and replicated our associations among 6,313 individuals from the LIFE-Adult Study. And lastly, we performed comparative association of phenome- and genome- wide associations to identify putative causal links between systemic conditions, retinal layer thicknesses, and ocular disease. Independent associations with incident mortality were detected for photoreceptor thinning and ganglion cell complex thinning. Significant phenotypic associations were detected between retinal layer thinning and ocular, neuropsychiatric, cardiometabolic and pulmonary conditions. Genome-wide association of retinal layer thicknesses yielded 259 loci. Consistency between epidemiologic and genetic associations suggested putative causal links between thinning of the retinal nerve fiber layer with glaucoma, photoreceptor segment with AMD, as well as poor cardiometabolic and pulmonary function with PS thinning, among other findings. In conclusion, retinal layer thinning predicts risk of future ocular and systemic disease. Furthermore, systemic cardio-metabolic-pulmonary conditions promote retinal thinning. Retinal imaging biomarkers, integrated into electronic health records, may inform risk prediction and potential therapeutic strategies.

Association of Systemic Medication Use with Glaucoma and Intraocular Pressure: The European Eye Epidemiology Consortium.

PURPOSE: To investigate the association of commonly used systemic medications with glaucoma and intraocular pressure (IOP) in the European population. DESIGN: Meta-analysis of 11 population-based cohort studies of the European Eye Epidemiology Consortium. PARTICIPANTS: The glaucoma analyses included 143 240 participants and the IOP analyses included 47 177 participants. METHODS: We examined associations of 4 categories of systemic medications-antihypertensive medications (ß-blockers, diuretics, calcium channel blockers [CCBs], α-agonists, angiotensin-converting enzyme inhibitors, and angiotensin II receptor blockers), lipid-lowering medications, antidepressants, and antidiabetic medications-with glaucoma prevalence and IOP. Glaucoma ascertainment and IOP measurement method were according to individual study protocols. Results of multivariable regression analyses of each study were pooled using random effects meta-analyses. Associations with antidiabetic medications were examined in participants with diabetes only. MAIN OUTCOME MEASURES: Glaucoma prevalence and IOP. RESULTS: In the meta-analyses of our maximally adjusted multivariable models, use of CCBs was associated with a higher prevalence of glaucoma (odds ratio [OR], 1.23; 95% confidence interval [CI], 1.08 to 1.39). This association was stronger for monotherapy of CCBs with direct cardiac effects (OR, 1.96; 95% CI, 1.23 to 3.12). No other antihypertensive medications, lipid-lowering medications, antidepressants, or antidiabetic medications were associated with glaucoma. Use of systemic ß-blockers was associated with a lower IOP (ß coefficient, -0.33 mmHg; 95% CI, -0.57 to -0.08 mmHg). Monotherapy of both selective systemic ß-blockers (ß coefficient, -0.45 mmHg; 95% CI -0.74 to -0.16 mmHg) and nonselective systemic ß-blockers (ß coefficient, -0.54 mmHg; 95% CI, -0.94 to -0.15 mmHg) was associated with lower IOP. A suggestive association was found between use of high-ceiling diuretics and lower IOP (ß coefficient, -0.30 mmHg; 95% CI, -0.47 to -0.14 mmHg) but not when used as monotherapy. No other antihypertensive medications, lipid-lowering medications, antidepressants, or antidiabetic medications were associated with IOP. CONCLUSIONS: We identified a potentially harmful association between use of CCBs and glaucoma prevalence. Additionally, we observed and quantified the association of lower IOP with systemic ß-blocker use. Both findings potentially are important, given that patients with glaucoma frequently use systemic antihypertensive medications. Determining causality of the CCB association should be a research priority. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Monochromatic ocular high-order aberrations in children and adolescents.

PURPOSE: To investigate the prevalence and repeatability of high-order aberrations (HOAs) from non-cyclopleged eyes in 1515 children and adolescents 2.5-18 years of age. METHODS: The Leipzig Research Centre for Civilization Diseases (LIFE)-Child study is a population-based, prospective, observational single-centre study that investigates the development of children and adolescents in Germany. Wavefront measurements were repeated three times in each eye of 1515 healthy subjects. Results were described by 36 Zernike coefficients for a 5 mm reference pupil diameter. Short-term repeatability is given for each coefficient. The impact on vision is described by the root mean squared (RMS) value of the HOA Zernike coefficients. RESULTS: High-order aberrations were dominated by five contributions. For 1004 right eyes: spherical aberration (c12 = 0.06 ± 0.07 µm), coma (c7 = 0.03 ± 0.09 µm, c8 = 0.03 ± 0.06 µm) and trefoil (c6 = -0.01 ± 0.07 µm, c9 = 0.008 ± 0.06 µm). The RMS value was 0.18 ± 0.06 µm. Modes higher than fourth order do not contribute clinically to the aberrations. HOAs show no clinically significant dependency with age. Instead, HOA values agree well with previous results on aberrations in adult eyes. Spherical aberration was highly correlated between the two eyes. Repeatability was worst for coma, 0.033 µm, due to variability in the alignment of the pupil centre. The left eye showed, on average, a 0.08 mm larger pupil diameter than the right eye (p < 0.02). CONCLUSIONS: Across the age span from 2.5 to 18 years, we see the same distribution of HOA as for adults. We established that only five Zernike coefficients, spherical aberration, coma and trefoil were of clinical significance in healthy eyes. A high correlation between the two eyes for spherical aberration suggests a common blueprint for each eye in any one subject.

The impact of the image conversion factor and image centration on retinal vessel geometric characteristics.

Background: This study aims to use fundus image material from a long-term retinopathy follow-up study to identify problems created by changing imaging modalities or imaging settings (e.g., image centering, resolution, viewing angle, illumination wavelength). Investigating the relationship of image conversion factor and imaging centering on retinal vessel geometric characteristics (RVGC), offers solutions for longitudinal retinal vessel analysis for data obtained in clinical routine. Methods: Retinal vessel geometric characteristics were analyzed in scanned fundus photographs with Singapore-I-Vessel-Assessment using a constant image conversion factor (ICF) and an individual ICF, applying them to macula centered (MC) and optic disk centered (ODC) images. The ICF is used to convert pixel measurements into µm for vessel diameter measurements and to establish the size of the measuring zone. Calculating a constant ICF, the width of all analyzed optic disks is included, and it is used for all images of a cohort. An individual ICF, in turn, uses the optic disk diameter of the eye analyzed. To investigate agreement, Bland-Altman mean difference was calculated between ODC images analyzed with individual and constant ICF and between MC and ODC images. Results: With constant ICF (n = 104 eyes of 52 patients) the mean central retinal equivalent was 160.9 ± 17.08 µm for arteries (CRAE) and 208.7 ± 14.7.4 µm for veins (CRVE). The individual ICFs resulted in a mean CRAE of 163.3 ± 15.6 µm and a mean CRVE of 219.0 ± 22.3 µm. On Bland-Altman analysis, the individual ICF RVGC are more positive, resulting in a positive mean difference for most investigated parameters. Arteriovenous ratio (p = 0.86), simple tortuosity (p = 0.08), and fractal dimension (p = 0.80) agreed well between MC and ODC images, while the vessel diameters were significantly smaller in MC images (p < 0.002). Conclusion: Scanned images can be analyzed using vessel assessment software. Investigations of individual ICF versus constant ICF point out the asset of utilizing an individual ICF. Image settings (ODC vs. MC) were shown to have good agreement.

Feasibility and repeatability of ocular biometry measured with IOLMaster 700 in a large population-based study.

PURPOSE: To evaluate the feasibility and repeatability of IOLMaster 700 biometry measurements in an adult population. Furthermore, to assess the value of the Quality Indicators (QIs) provided by the device. METHOD: As part of the large population-based Leipzig Research Centre for Civilization Diseases (LIFE) Adult-Study, randomly selected participants from Leipzig, Germany were evaluated with the ZEISS IOLMaster 700. Age range was 26-85 years, with 53% of participants above 70 years of age. Axial length (AL), central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT) and keratometry (K) were assessed in 1767 right eyes. Measurements were repeated twice and in a subset of 1331 eyes, three times. Measurement feasibility was evaluated for three levels; successful, with warnings and failed, using the inbuilt QIs. Repeatability was assessed as within-subject standard deviation (SD) and repeatability limits were calculated. RESULTS: First measurement success rate for phakic eyes was over 99% for AL, CCT, ACD, over 98% for LT and over 97% for K. K had 16% eyes with warnings and the recommendation to repeat the measurement. Excluding the measurements with warnings resulted in a reduction of mean SD for AL from 48 to 4 µm and for mean K from 0.08 to 0.04 D. Repeatability for phakic eyes was 8 µm for AL, CCT, ACD and LT and 2.3 µm for CCT; 0.07 D and 0.12 D for mean K and delta K, respectively, for phakic cases without warnings (two measurements). CONCLUSIONS: In our population-based sample, the IOLMaster 700 collected data for AL, CCT, ACD, LT and K from the vast majority of eyes. Considering the built-in QIs improved the measurement variability substantially. Repeatability measurements indicate that clinically meaningful changes can be detected reliably with this instrument.

Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects.

This work presents a novel fully automated method for retinal analysis in images acquired with a flood illuminated adaptive optics retinal camera (AO-FIO). The proposed processing pipeline consists of several steps: First, we register single AO-FIO images in a montage image capturing a larger retinal area. The registration is performed by combination of phase correlation and the scale-invariant feature transform method. A set of 200 AO-FIO images from 10 healthy subjects (10 images from left eye and 10 images from right eye) is processed into 20 montage images and mutually aligned according to the automatically detected fovea center. As a second step, the photoreceptors in the montage images are detected using a method based on regional maxima localization, where the detector parameters were determined with Bayesian optimization according to manually labeled photoreceptors by three evaluators. The detection assessment, based on Dice coefficient, ranges from 0.72 to 0.8. In the next step, the corresponding density maps are generated for each of the montage images. As a final step, representative averaged photoreceptor density maps are created for the left and right eye and thus enabling comprehensive analysis across the montage images and a straightforward comparison with available histological data and other published studies. Our proposed method and software thus enable us to generate AO-based photoreceptor density maps for all measured locations fully automatically, and thus it is suitable for large studies, as those are in pressing need for automated approaches. In addition, the application MATADOR (MATlab ADaptive Optics Retinal Image Analysis) that implements the described pipeline and the dataset with photoreceptor labels are made publicly available.

Association of lipid-lowering drugs and antidiabetic drugs with age-related macular degeneration: a meta-analysis in Europeans.

BACKGROUND/AIMS: To investigate the association of commonly used systemic medications with prevalent age-related macular degeneration (AMD) in the general population. METHODS: We included 38 694 adults from 14 population-based and hospital-based studies from the European Eye Epidemiology consortium. We examined associations between the use of systemic medications and any prevalent AMD as well as any late AMD using multivariable logistic regression modelling per study and pooled results using random effects meta-analysis. RESULTS: Between studies, mean age ranged from 61.5±7.1 to 82.6±3.8 years and prevalence ranged from 12.1% to 64.5% and from 0.5% to 35.5% for any and late AMD, respectively. In the meta-analysis of fully adjusted multivariable models, lipid-lowering drugs (LLD) and antidiabetic drugs were associated with lower prevalent any AMD (OR 0.85, 95% CI=0.79 to 0.91 and OR 0.78, 95% CI=0.66 to 0.91). We found no association with late AMD or with any other medication. CONCLUSION: Our study indicates a potential beneficial effect of LLD and antidiabetic drug use on prevalence of AMD across multiple European cohorts. Our findings support the importance of metabolic processes in the multifactorial aetiology of AMD.

The relationship between myopia and near work, time outdoors and socioeconomic status in children and adolescents.

BACKGROUND: To investigate environmental and social risk factors for myopia in children and adolescents in Germany. METHODS: 1437 children aged between 3 and 18 inclusive were examined as part of the LIFE Child study based in Leipzig, Germany. Information about leisure time activities and social status was ascertained by parents and children in a questionnaire. Refractive status was attained by measuring noncycloplegic autorefraction. Myopia was defined as spherical equivalent (SE) ≤ - 0.75 D. Risk factors were identified using multiple logistic regression analysis. RESULTS: In multiple logistic regression analysis, myopia was significantly associated with less frequent outdoor activity ("once a week" vs. "twice a week or more": odds ratio (OR) 4.35, 95% confidence interval (CI) 1.89-9.98, p<0.01) and longer near work sessions (1-2 h vs. < 1 h: OR 1.83, CI 1.10-3.04, p=0.02; > 3 h vs. < 1 h: OR 3.71, CI 1.43-9.61, p<0.01) after adjustment for age, sex and socioeconomic status (SES). Duration of outdoor activity, near work frequency and SES showed no significant association with myopia (p > 0.05). Children with a lower SES were involved in longer periods of outdoor and near work activities but on fewer occasions over the course of the week, although this connection was not significant. CONCLUSION: Myopia is associated with environmental factors. The present findings suggest that daily exposure to sunlight and a restriction of long-duration near work activities might protect against pathological eye growth. Prevention strategies should be implemented for children at all ages.

The Leipzig Health Atlas-An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online.

BACKGROUND: Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains. OBJECTIVE: The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects. METHODS: Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups. RESULTS: The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

Changes in bodily complaints (PHQ-15) over six years in a large general population sample.

OBJECTIVE: The Patient Health Questionnaire-15 (PHQ-15) is a widely used instrument for measuring bodily complaints. The aims of this study were to analyze changes of bodily complaints over a six-year period in a large general population community sample, to test age and sex differences in these changes, and to examine associations between these changes and changes in other health-related variables. METHODS: A total of 4821 adult subjects took part this longitudinal study at baseline (t1) and six years later (t2). The participants completed the PHQ-15 and several other questionnaires. RESULTS: Over the six-year period, the mean score of the complaints increased from 5.18 ± 3.67 to 5.75 ± 3.97. The highest increase in terms of effect sizes was found for sexual pain/problems. While the increase in the PHQ-15 mean score was nearly identical for males and females, there were age differences in these increase rates: Participants of the oldest age group (70 years and above) experienced the greatest increase in complaints. Participants from lower socioeconomic levels also reported high increases in complaints. The correlation between the t1 and the t2 PHQ-15 score was r = 0.66. Changes in complaints from t1 to t2 were associated with changes in multiple other variables such as anxiety, social support, optimism, life satisfaction, and quality of life. CONCLUSION: The data reported here can be used to better interpret changes in patients' health state over several years.