Association of age at diagnosis of diabetes with subsequent risk of age-related ocular diseases and vision acuity.

BACKGROUND: The importance of age on the development of ocular conditions has been reported by numerous studies. Diabetes may have different associations with different stages of ocular conditions, and the duration of diabetes may affect the development of diabetic eye disease. While there is a dose-response relationship between the age at diagnosis of diabetes and the risk of cardiovascular disease and mortality, whether the age at diagnosis of diabetes is associated with incident ocular conditions remains to be explored. It is unclear which types of diabetes are more predictive of ocular conditions. AIM: To examine associations between the age of diabetes diagnosis and the incidence of cataract, glaucoma, age-related macular degeneration (AMD), and vision acuity. METHODS: Our analysis was using the UK Biobank. The cohort included 8709 diabetic participants and 17418 controls for ocular condition analysis, and 6689 diabetic participants and 13378 controls for vision analysis. Ocular diseases were identified using inpatient records until January 2021. Vision acuity was assessed using a chart. RESULTS: During a median follow-up of 11.0 years, 3874, 665, and 616 new cases of cataract, glaucoma, and AMD, respectively, were identified. A stronger association between diabetes and incident ocular conditions was observed where diabetes was diagnosed at a younger age. Individuals with type 2 diabetes (T2D) diagnosed at < 45 years [HR (95%CI): 2.71 (1.49-4.93)], 45-49 years [2.57 (1.17-5.65)], 50-54 years [1.85 (1.13-3.04)], or 50-59 years of age [1.53 (1.00-2.34)] had a higher risk of AMD independent of glycated haemoglobin. T2D diagnosed < 45 years [HR (95%CI): 2.18 (1.71-2.79)], 45-49 years [1.54 (1.19-2.01)], 50-54 years [1.60 (1.31-1.96)], or 55-59 years of age [1.21 (1.02-1.43)] was associated with an increased cataract risk. T2D diagnosed < 45 years of age only was associated with an increased risk of glaucoma [HR (95%CI): 1.76 (1.00-3.12)]. HRs (95%CIs) for AMD, cataract, and glaucoma associated with type 1 diabetes (T1D) were 4.12 (1.99-8.53), 2.95 (2.17-4.02), and 2.40 (1.09-5.31), respectively. In multivariable-adjusted analysis, individuals with T2D diagnosed < 45 years of age [ß 95%CI: 0.025 (0.009,0.040)] had a larger increase in LogMAR. The ß (95%CI) for LogMAR associated with T1D was 0.044 (0.014, 0.073). CONCLUSION: The younger age at the diagnosis of diabetes is associated with a larger relative risk of incident ocular diseases and greater vision loss.

Epidemiologic association and shared genetic architecture between cataract and hearing difficulties among middle-aged and older adults.

Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98-2.27; OR, 2.03; 95% CI, 1.86-2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

Shared genetic aetiology of Alzheimer's disease and age-related macular degeneration by APOC1 and APOE genes.

Background: Alzheimer's disease (AD) and age-related macular degeneration (AMD) share similar pathological features, suggesting common genetic aetiologies between the two. Investigating gene associations between AD and AMD may provide useful insights into the underlying pathogenesis and inform integrated prevention and treatment for both diseases. Methods: A stratified quantile-quantile (QQ) plot was constructed to detect the pleiotropy among AD and AMD based on genome-wide association studies data from 17 008 patients with AD and 30 178 patients with AMD. A Bayesian conditional false discovery rate-based (cFDR) method was used to identify pleiotropic genes. UK Biobank was used to verify the pleiotropy analysis. Biological network and enrichment analysis were conducted to explain the biological reason for pleiotropy phenomena. A diagnostic test based on gene expression data was used to predict biomarkers for AD and AMD based on pleiotropic genes and their regulators. Results: Significant pleiotropy was found between AD and AMD (significant leftward shift on QQ plots). APOC1 and APOE were identified as pleiotropic genes for AD-AMD (cFDR <0.01). Network analysis revealed that APOC1 and APOE occupied borderline positions on the gene co-expression networks. Both APOC1 and APOE genes were enriched on the herpes simplex virus 1 infection pathway. Further, machine learning-based diagnostic tests identified that APOC1, APOE (areas under the curve (AUCs) >0.65) and their upstream regulators, especially ZNF131, ADNP2 and HINFP, could be potential biomarkers for both AD and AMD (AUCs >0.8). Conclusion: In this study, we confirmed the genetic pleiotropy between AD and AMD and identified APOC1 and APOE as pleiotropic genes. Further, the integration of multiomics data identified ZNF131, ADNP2 and HINFP as novel diagnostic biomarkers for AD and AMD.

Seasonal Variations in Vitamin D Levels and the Incident Dementia Among Older Adults Aged ≥60 Years in the UK Biobank.

Background: Limited knowledge exists regarding the association between dementia incidence and vitamin D insufficiency/deficiency across seasons. Objective: This study aimed to evaluate the impact of seasonal serum vitamin D (25(OH)D) levels on dementia and its subtypes, considering potential modifiers. Methods: We analyzed 193,003 individuals aged 60-73 at baseline (2006-2010) from the UK Biobank cohort, with follow-up until 2018. 25(OH)D were measured at baseline, and incident dementia cases were identified through hospital records, death certificates, and self-reports. Results: Out of 1,874 documented all-cause dementia cases, the median follow-up duration was 8.9 years. Linear and nonlinear associations between 25(OH)D and dementia incidence across seasons were observed. In multivariable-adjusted analysis, 25(OH)D deficiency was associated with a 1.5-fold (95% CIs: 1.2-2.0), 2.2-fold (1.5-3.0), 2.0-fold (1.5-2.7), and 1.7-fold (1.3-2.3) increased incidence of all-cause dementia in spring, summer, autumn, and winter, respectively. Adjusting for seasonal variations, 25(OH)D insufficiency and deficiency were associated with a 1.3-fold (1.1-1.4) and 1.8-fold (1.6-2.2) increased dementia incidence, respectively. This association remained significant across subgroups, including baseline age, gender, and education levels. Furthermore, 25(OH)D deficiency was associated with a 1.4-fold (1.1-1.8) and 1.5-fold (1.1-2.0) higher incidence of Alzheimer's disease and vascular dementia, respectively. These associations remained significant across all subgroups. Conclusions: 25(OH)D deficiency is associated with an increased incidence of dementia and its subtypes throughout the year.

Diagnostic Accuracy of Artificial Intelligence-Based Automated Diabetic Retinopathy Screening in Real-World Settings: A Systematic Review and Meta-Analysis.

PURPOSE: To evaluate the diagnostic accuracy of artificial intelligence (AI)-based automated diabetic retinopathy (DR) screening in real-world settings. DESIGN: Systematic review and meta-analysis METHODS: We conducted a systematic review of relevant literature from January 2012 to August 2022 using databases including PubMed, Scopus and Web of Science. The quality of studies was evaluated using Quality Assessment for Diagnostic Accuracy Studies 2 (QUADAS-2) checklist. We calculated pooled accuracy, sensitivity, specificity, and diagnostic odds ratio (DOR) as summary measures. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO - CRD42022367034). RESULTS: We included 34 studies which utilized AI algorithms for diagnosing DR based on real-world fundus images. Quality assessment of these studies indicated a low risk of bias and low applicability concern. Among gradable images, the overall pooled accuracy, sensitivity, specificity, and DOR were 81%, 94% (95% CI: 92.0-96.0), 89% (95% CI: 85.0-92.0) and 128 (95% CI: 80-204) respectively. Sub-group analysis showed that, when acceptable quality imaging could be obtained, non-mydriatic fundus images had a better DOR of 143 (95% CI: 82-251) and studies using 2 field images had a better DOR of 161 (95% CI 74-347). Our meta-regression analysis revealed a statistically significant association between DOR and variables such as the income status, and the type of fundus camera. CONCLUSION: Our findings indicate that AI algorithms have acceptable performance in screening for DR using fundus images compared to human graders. Implementing a fundus camera with AI-based software has the potential to assist ophthalmologists in reducing their workload and improving the accuracy of DR diagnosis.

Evaluation of the Observational Associations and Shared Genetics Between Glaucoma With Depression and Anxiety.

Purpose: Glaucoma, a leading cause of blindness worldwide, is suspected to exhibit a notable association with psychological disturbances. This study aimed to investigate epidemiological associations and explore shared genetic architecture between glaucoma and mental traits, including depression and anxiety. Methods: Multivariable logistic regression and Cox proportional hazards regression models were employed to investigate longitudinal associations based on UK Biobank. A stepwise approach was used to explore the shared genetic architecture. First, linkage disequilibrium score regression inferred global genetic correlations. Second, MiXeR analysis quantified the number of shared causal variants. Third, specific shared loci were detected through conditional/conjunctional false discovery rate (condFDR/conjFDR) analysis and characterized for biological insights. Finally, two-sample Mendelian randomization (MR) was conducted to investigate bidirectional causal associations. Results: Glaucoma was significantly associated with elevated risks of hospitalized depression (hazard ratio [HR] = 1.54; 95% confidence interval [CI], 1.01-2.34) and anxiety (HR = 2.61; 95% CI, 1.70-4.01) compared to healthy controls. Despite the absence of global genetic correlations, MiXeR analysis revealed 300 variants shared between glaucoma and depression, and 500 variants shared between glaucoma and anxiety. Subsequent condFDR/conjFDR analysis discovered 906 single-nucleotide polymorphisms (SNPs) jointly associated with glaucoma and depression and two associated with glaucoma and anxiety. The MR analysis did not support robust causal associations but indicated the existence of pleiotropic genetic variants influencing both glaucoma and depression. Conclusions: Our study enhances the existing epidemiological evidence and underscores the polygenic overlap between glaucoma and mental traits. This observation suggests a correlation shaped by pleiotropic genetic variants rather than being indicative of direct causal relationships.

Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study.

BACKGROUND: Little is known regarding the leading risk factors for dementia/Alzheimer's disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer's disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health. METHODS: Our analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40-73 years at baseline (between 2006-2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors. RESULTS: During a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55-2.85) and 3.72(3.40-4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother's history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers. CONCLUSIONS: Our findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother's history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

Metabolomic age and risk of 50 chronic diseases in community-dwelling adults: A prospective cohort study.

It is unclear how metabolomic age is associated with the risk of a wide range of chronic diseases. Our analysis included 110,692 participants (training: n = 27,673; testing: n = 27,673; validating: n = 55,346) aged 39-71 years at baseline (2006-2010) from the UK Biobank. Incident chronic diseases were identified using inpatient records, or death registers until January 2021. Predicted metabolomic age was trained and tested based on 168 metabolomics. Metabolomic age was linked to the risk of 50 diseases in the validation dataset. The median follow-up duration for individual diseases ranged from 11.2 years to 11.9 years. After controlling for false discovery rate, chronological age-adjusted age gap (CAAG) was significantly associated with the incidence of 25 out of 50 chronic diseases. After adjustment for full covariates, associations with 15 chronic diseases remained significant. Greater CAAG was associated with increased risk of eight cardiometabolic disorders (including cardiovascular diseases and diabetes), some cancers, alcohol use disorder, chronic obstructive pulmonary disease, chronic kidney disease, chronic liver disease and age-related macular degeneration. The association between CAAG and risk of peripheral vascular disease, other cardiac diseases, fracture, cataract and thyroid disorder was stronger among individuals with unhealthy diet than in those with healthy diet. The association between CAAG and risk of some conditions was stronger in younger individuals, those with metabolic disorders or low education. Metabolomic age plays an important role in the development of multiple chronic diseases. Healthy diet and high education may mitigate the risk for some chronic diseases due to metabolomic age acceleration.

Retinal Vascular Measurements and Mortality Risk: Evidence From the UK Biobank Study.

Purpose: This study aimed to investigate the association between quantitative retinal vascular measurements and the risk of all-cause and premature mortality. Methods: In this population-based cohort study using the UK Biobank data, we employed the Retina-based Microvascular Health Assessment System to assess fundus images for image quality and extracted 392 retinal vascular measurements per fundus image. These measurements encompass six categories of vascular features: caliber, density, length, tortuosity, branching angle, and complexity. Univariate Cox regression models were used to identify potential indicators of mortality risk using data on all-cause and premature mortality from death registries. Multivariate Cox regression models were then used to test these associations while controlling for confounding factors. Results: The final analysis included 66,415 participants. After adjusting for demographic, health, and lifestyle factors and genetic risk score, 18 and 10 retinal vascular measurements were significantly associated with all-cause mortality and premature mortality, respectively. In the fully adjusted model, the following measurements of different vascular features were significantly associated with all-cause mortality and premature mortality: arterial bifurcation density (branching angle), number of arterial segments (complexity), interquartile range and median absolute deviation of arterial curve angle (tortuosity), mean and median values of mean pixel widths of all arterial segments in each image (caliber), skeleton density of arteries in macular area (density), and minimum venular arc length (length). Conclusions: The study revealed 18 retinal vascular measurements significantly associated with all-cause mortality and 10 associated with premature mortality. Those identified parameters should be further studied for biological mechanisms connecting them to increased mortality risk. Translational Relevance: This study identifies retinal biomarkers for increased mortality risk and provides novel targets for investigating the underlying biological mechanisms.

The sonic hedgehog pathway suppresses oxidative stress and senescence in nucleus pulposus cells to alleviate intervertebral disc degeneration via GPX4.

Disruption of intervertebral disc (IVD) homeostasis caused by oxidative stress and nucleus pulposus cell (NPC) senescence is a main cause of intervertebral disc degeneration (IDD). The sonic hedgehog (Shh) pathway plays an important role in IVD development, but its roles in IDD are unknown. This study aimed to investigate the effects of the Shh pathway on the alleviation of IDD and the related mechanisms. In vivo, the effect of the Shh pathway on IVD homeostasis was studied by intraperitoneal injection of recombinant Shh (rShh) and GANT61 based on puncture-induced IDD. GANT61, lentivirus-coated sh-Gli1 and rShh were used to investigate the role and mechanism of the Shh pathway in NPCs based on senescence induced by Braco19 and oxidative stress induced by TBHP. Shh pathway expression decreased, and senescence and oxidative stress increased with age. Intraperitoneal injection of rShh activated the Shh pathway to suppress oxidative stress and NPC senescence and consequently alleviated needle puncture-induced IDD. In vitro, the Shh pathway upregulated glutathione peroxidase 4 (GPX4) expression to suppress oxidative stress and senescence in NPCs. Moreover, GPX4 suppression in NPCs by si-GPX4 significantly reduced the protective effect of the Shh pathway on oxidative stress and senescence in NPCs. Our results demonstrate for the first time that the Shh pathway plays a key role in the alleviation of IDD by suppressing oxidative stress and cell senescence in NP tissues. This study provides a new potential target for the prevention and reversal of IDD.

Exploring multimorbidity profiles in middle-aged inpatients: a network-based comparative study of China and the United Kingdom.

BACKGROUND: Multimorbidity is better prevented in younger ages than in older ages. This study aims to identify the differences in comorbidity patterns in middle-aged inpatients from China and the United Kingdom (UK). METHODS: We utilized 184,133 and 180,497 baseline hospitalization records in middle-aged populations (40-59 years) from Shaanxi, China, and UK Biobank. Logistic regression was used to calculate odds ratios and P values for 43,110 unique comorbidity patterns in Chinese inpatients and 21,026 unique comorbidity patterns in UK inpatients. We included the statistically significant (P values adjusted by Bonferroni correction) and common comorbidity patterns (the pattern with prevalence > 1/10,000 in each dataset) and employed network analysis to construct multimorbidity networks and compare feature differences in multimorbidity networks for Chinese and UK inpatients, respectively. We defined hub diseases as diseases having the top 10 highest number of unique comorbidity patterns in the multimorbidity network. RESULTS: We reported that 57.12% of Chinese inpatients had multimorbidity, substantially higher than 30.39% of UK inpatients. The complete multimorbidity network for Chinese inpatients consisted of 1367 comorbidities of 341 diseases and was 2.93 × more complex than that of 467 comorbidities of 215 diseases in the UK. In males, the complexity of the multimorbidity network in China was 2.69 × more than their UK counterparts, while the ratio was 2.63 × in females. Comorbidities associated with hub diseases represented 68.26% of comorbidity frequencies in the complete multimorbidity network in Chinese inpatients and 55.61% in UK inpatients. Essential hypertension, dyslipidemia, type 2 diabetes mellitus, and gastritis and duodenitis were the hub diseases in both populations. The Chinese inpatients consistently demonstrated a higher frequency of comorbidities related to circulatory and endocrine/nutritional/metabolic diseases. In the UK, aside from these comorbidities, comorbidities related to digestive and genitourinary diseases were also prevalent, particularly the latter among female inpatients. CONCLUSIONS: Chinese inpatients exhibit higher multimorbidity prevalence and more complex networks compared to their UK counterparts. Multimorbidity with circulatory and endocrine/nutritional/metabolic diseases among both Chinese and UK inpatients necessitates tailored surveillance, prevention, and intervention approaches. Targeted interventions for digestive and genitourinary diseases are warranted for the UK.

Healthy dietary patterns and the risk of individual chronic diseases in community-dwelling adults.

It is unclear regarding associations of dietary patterns with a wide range of chronic diseases and which dietary score is more predictive of major chronic diseases. Using the UK Biobank, we examine associations of four individual healthy dietary scores with the risk of 48 individual chronic diseases. Higher Alternate Mediterranean Diet score is associated with a lower risk of 32 (all 8 cardiometabolic disorders, 3 out of 10 types of cancers, 7 out of 10 psychological/neurological disorders, 5 out of 6 digestive disorders, and 9 out of 14 other chronic diseases). Alternate Healthy Eating Index-2010 and Healthful Plant-based Diet Index are inversely associated with the risk of 29 and 23 individual chronic diseases, respectively. A higher Anti-Empirical Dietary Inflammatory Index is associated with a lower risk of 14 individual chronic diseases and a higher incidence of two diseases. Our findings support dietary guidelines for the prevention of most chronic diseases.

Determinants of incident atherosclerotic cardiovascular disease events among individuals with type 2 diabetic microvascular complications in the UK: a prospective cohort study.

OBJECTIVE: To evaluate the association of atherosclerotic cardiovascular disease (ASCVD) risk factors with incident ASCVD events among type 2 diabetes (T2D) individuals with microvascular complications. METHODS: We included T2D participants with only microvascular complications from the UK Biobank cohort at baseline (2006-2010). Multivariable-adjusted Cox proportional hazards models were used to study the association between ASCVD risk factors with adjudicated incident ASCVD in T2D participants with only microvascular complications. A restricted cubic spline approach was employed to evaluate potential nonlinear associations between ASCVD risk factors and ASCVD. RESULTS: We studied 4,129 T2D individuals with microvascular complications at baseline. Over a median follow-up of 11.7 years, a total of 1,180 cases of incident ASCVD were documented, of which 1,040 were CHD, 100 were stroke, and 40 were both CHD and stroke events. After multivariable-adjustment, high-density lipoprotein cholesterol (HDL-C) level was linearly associated with a decreased risk of incident ASCVD [hazard ratio (HR): 0.49, 95% Confidence interval (CI): 0.32-0.75, Plinear = 0.011] and each 10 nmol/L increase of lipoprotein(a) [Lp(a)] level (HR: 1.02, 95% CI: 1.00-1.04, Plinear = 0.012) was linearly associated with an increased risk of incident ASCVD in T2D participants with only microvascular complications. CONCLUSION: HDL-C levels and Lp(a) levels (per 10 nmol/L) showed an independent linear relation with ASCVD risk among T2D individuals with only microvascular complications at long-term follow-up.

A Systematic Review and Meta-Analysis of Applying Deep Learning in the Prediction of the Risk of Cardiovascular Diseases From Retinal Images.

Purpose: The purpose of this study was to perform a systematic review and meta-analysis to synthesize evidence from studies using deep learning (DL) to predict cardiovascular disease (CVD) risk from retinal images. Methods: A systematic literature search was performed in MEDLINE, Scopus, and Web of Science up to June 2022. We extracted data pertaining to predicted outcomes, model development, and validation and model performance metrics. Included studies were graded using the Quality Assessment of Diagnostic Accuracies Studies 2 tool. Model performance was pooled across eligible studies using a random-effects meta-analysis model. Results: A total of 26 studies were included in the analysis. There were 42 CVD risk-related outcomes predicted from retinal images were identified, including 33 CVD risk factors, 4 cardiac imaging biomarkers, 2 CVD risk scores, the presence of CVD, and incident CVD. Three studies that aimed to predict the development of future CVD events reported an area under the receiver operating curve (AUROC) between 0.68 and 0.81. Models that used retinal images as input data had a pooled mean absolute error of 3.19 years (95% confidence interval [CI] = 2.95-3.43) for age prediction; a pooled AUROC of 0.96 (95% CI = 0.95-0.97) for gender classification; a pooled AUROC of 0.80 (95% CI = 0.73-0.86) for diabetes detection; and a pooled AUROC of 0.86 (95% CI = 0.81-0.92) for the detection of chronic kidney disease. We observed a high level of heterogeneity and variation in study designs. Conclusions: Although DL models appear to have reasonably good performance when it comes to predicting CVD risk, further work is necessary to evaluate the real-world applicability and predictive accuracy. Translational Relevance: DL-based CVD risk assessment from retinal images holds great promise to be translated to clinical practice as a novel approach for CVD risk assessment, given its simple, quick, and noninvasive nature.

Central obesity and its association with retinal age gap: insights from the UK Biobank study.

BACKGROUND: Conflicting evidence exists on the association between ageing and obesity. Retinal age derived from fundus images has been validated as a novel biomarker of ageing. In this study, we aim to investigate the association between different anthropometric phenotypes based on body mass index (BMI) and waist circumference (WC) and the retinal age gap (retinal age minus chronological age). METHODS: A total of 35,550 participants with BMI, WC and qualified retinal imaging data available were included to investigate the association between anthropometric groups and retinal ageing. Participants were stratified into 7 different body composition groups based on BMI and WC (Normal-weight/Normal WC, Overweight/Normal WC, Mild obesity/Normal WC, Normal-weight/High WC, Overweight/High WC, Mild obesity/High WC, and Severe obesity/High WC). Linear regression and logistic regression models were fitted to investigate the association between the seven anthropometric groups and retinal age gap as continuous and categorical outcomes, respectively. RESULTS: A total of 35,550 participants (55.6% females) with a mean age 56.8 ± 8.04 years were included in the study. Individuals in the Overweight/High WC, Mild obesity/High WC and Severe obesity/High WC groups were associated with an increase in the retinal age gap, compared with those in the Normal Weight/Normal WC group (ß = 0.264, 95% CI: 0.105-0.424, P =0.001; ß = 0.226, 95% CI: 0.082-0.371, P = 0.002; ß = 0.273, 95% CI: 0.081-0.465, P = 0.005; respectively) in fully adjusted models. Similar findings were noted in the association between the anthropometric groups and retinal ageing process as a categorical outcome. CONCLUSION: A significant positive association exists between central obesity and accelerated ageing indexed by retinal age gaps, highlighting the significance of maintaining a healthy body shape.

Glycemic status and its association with retinal age gap: Insights from the UK biobank study.

OBJECTIVE: To investigate associations between different glycemic status and biological age indexed by retinal age gap. METHODS: A total of 28,919 participants from the UK Biobank study with available glycemic status and qualified retinal imaging data were included in the present analysis. Glycemic status included type 2 diabetes mellitus (T2D) disease status and glycemic indicators of plasma glycated hemoglobin (HbA1c) and glucose. Retinal age gap was defined as the difference between the retina-predicted age and chronological age. Linear regression models estimated the association of different glycemic status with retinal age gap. RESULTS: Prediabetes and T2D was significantly associated with higher retinal age gaps compared to normoglycemia (regression coefficient [ß] = 0.25, 95% confidence interval [CI]: 0.11-0.40, P = 0.001; ß = 1.06, 95% CI: 0.83-1.29, P < 0.001; respectively). Multi-variable linear regressions further found an increase of HbA1c was independently associated with higher retinal age gaps among all subjects or subjects without T2D. Significant positive associations were noted across the increasing HbA1c and glucose groups with retinal age gaps compared to the normal level group. These findings remained significant after excluding diabetic retinopathy. CONCLUSIONS: Dysglycemia was significantly associated with accelerated ageing indexed by retinal age gaps, highlighting the importance of maintaining glycemic status.

Analysis of Plasma Metabolic Profile on Ganglion Cell-Inner Plexiform Layer Thickness With Mortality and Common Diseases.

Importance: The neural retina is considered a unique window to systemic health, but its biological link with systemic health remains unknown. Objective: To investigate the independent associations of retinal ganglion cell-inner plexiform layer thickness (GCIPLT) metabolic profiles with rates of mortality and morbidity of common diseases. Design, Setting, and Participants: This cohort study evaluated UK Biobank participants enrolled between 2006 and 2010, and prospectively followed them up for multidisease diagnosis and mortality. Additional participants from the Guangzhou Diabetes Eye Study (GDES) underwent optical coherence tomography scanning and metabolomic profiling and were included for validation. Main Outcomes and Measures: Systematic analysis of circulating plasma metabolites to identify GCIPLT metabolic profiles; prospective associations of these profiles with mortality and morbidity of 6 common diseases with their incremental discriminative value and clinical utility. Results: Among 93 838 community-based participants (51 182 [54.5%] women), the mean (SD) age was 56.7 (8.1) years and mean (SD) follow-up was 12.3 (0.8) years. Of 249 metabolic metrics, 37 were independently associated with GCIPLT, including 8 positive and 29 negative associations, and most were associated with the rates of future mortality and common diseases. These metabolic profiles significantly improved the models for discriminating type 2 diabetes over clinical indicators (C statistic: 0.862; 95% CI, 0.852-0.872 vs clinical indicators only, 0.803; 95% CI, 0.792-0.814; P < .001), myocardial infarction (0.792; 95% CI, 0.775-0.808 vs 0.768; 95% CI, 0.751-0.786; P < .001), heart failure (0.803; 95% CI, 0.786-0.820 vs 0.790; 95% CI, 0.773-0.807; P < .001), stroke (0.739; 95% CI, 0.714-0.764 vs 0.719; 95% CI, 0.693-0.745; P < .001), all-cause mortality (0.747; 95% CI, 0.734-0.760 vs 0.724; 95% CI, 0.711-0.738; P < .001), and cardiovascular disease mortality (0.790; 95% CI, 0.767-0.812 vs 0.763; 95% CI, 0.739-0.788; P < .001). Additionally, the potential of GCIPLT metabolic profiles for risk stratification of cardiovascular diseases were further confirmed in the GDES cohort using a different metabolomic approach. Conclusions and Relevance: In this prospective study of multinational participants, GCIPLT-associated metabolites demonstrated the potential to inform mortality and morbidity risks. Incorporating information on these profiles may facilitate individualized risk stratification for these health outcomes.

Determinants of Incident Atherosclerotic Cardiovascular Disease Events and All-Cause Mortality in Patients With Age-Related Macular Degeneration: Prospective Cohort Study of UK Biobank.

PURPOSE: Major risk factors of atherosclerotic cardiovascular disease (ASCVD) and mortality have been well-established in the general population. Our study is aimed at assessing longitudinal relationships between ASCVD risk factors and incident ASCVD events or all-cause mortality in patients with age-related macular degeneration (AMD). METHODS: Multivariable-adjusted Cox proportional hazards models were used to study the association between cardiovascular risk factors with adjudicated incident ASCVD events and all-cause mortality outcomes followed until 2021. A restricted cubic spline approach was utilized to assess nonlinear associations between potential cardiovascular risk factors and ASCVD or mortality. RESULTS: We identified 3508 eligible patients [mean (SD) age = 61.45 (6.43) years; 37.76% males] with AMD at baseline. During a median follow-up year of 12, there were 110 cases of ASCVD events and 186 cases of all-cause mortality. After multivariable adjustment, each 10 U/L increase of serum gamma-glutamyl transferase level was linearly associated with incident ASCVD [hazard ratio (HR) = 1.03, 95% CI = 1.00-1.07, Pnonlinear = 0.85)] in AMD. A history of chronic kidney disease (HR = 1.94, 95% CI = 1.09-3.46) and lower vitamin D [HR = 0.98, 95% CI = 0.97-0.99, per nanomoles per liter (nmol/L)] were significantly associated with all-cause mortality in patients with AMD, with the association between vitamin D and all-cause mortality presenting a U shape (Pnonlinear = 0.02). In contrast, risk factors significantly associated with ASCVD and all-cause mortality in healthy controls differed from patients with AMD. CONCLUSIONS: Our findings demonstrate risk factors associated with ASCVD events and all-cause mortality among individuals with AMD differed from healthy controls and suggest the long-term management of risk factors in patients with AMD.

Optic Nerve Head Capillary Network Quantified by Optical Coherence Tomography Angiography and Decline of Renal Function in Type 2 Diabetes: A Three-Year Prospective Study.

PURPOSE: To assess the association of optic capillary perfusion with decline in the estimated glomerular filtration rate (eGFR) and to clarify its added value. DESIGN: Prospective, observational cohort study. METHODS: Patients with type 2 diabetes mellitus without diabetic retinopathy (non-DR) underwent standardized examinations annually during a 3-year follow-up period. The superficial capillary plexus (SCP), deep capillary plexus (DCP), and radial peripapillary plexus (RPC) of optic nerve head (ONH) were visualized using optical coherence tomography angiography (OCTA), and the perfusion density (PD) and vascular density were quantified for the whole image and circumpapillary regions of the ONH.  The lowest tercile of annual eGFR slope was defined as the rapidly progressive group, and the highest tercile was considered the stable group. RESULTS: A total of 906 patients were included for 3-mm × 3-mm OCTA analysis. After adjusting for other confounders, each 1% decrease in baseline whole en face PD in SCP and RPC was associated with accelerated rates of decline in eGFR by -0.53 mL/min/1.73/m2 per year (95% confidence interval [CI] -0.17 to -0.90; P = .004) and -0.60 mL/min/1.73/m2 per year (95% CI 0.28-0.91), respectively. Adding both whole-image PD in SCP and whole-image PD in RPC to the conventional model increased the area under the curve from 0.696 (95% CI 0.654-0.737) to 0.725 (95% CI 0.685-0.765; P = .031). Another cohort of 400 eligible patients with 6-mm × 6 mm OCTA imaging validated the significant associations between ONH perfusion and rate of eGFR decline (P < .05). CONCLUSIONS: Reduced capillary perfusion of ONH in patients with type 2 diabetes mellitus is associated with a greater eGFR decline, and it has additional predictive value for detecting an early stage and progression.

EBD: an eye biomarker database.

MOTIVATION: Many ophthalmic disease biomarkers have been identified through comprehensive multiomics profiling, and hold significant potential in advancing the diagnosis, prognosis, and management of diseases. Meanwhile, the eye itself serves as a natural biomarker for several systemic diseases including neurological, renal, and cardiovascular systems. We aimed to collect and standardize this eye biomarkers information and construct the eye biomarker database (EBD) to provide ophthalmologists with a platform to search, analyze, and download these eye biomarker data. RESULTS: In this study, we present the EBD , a world-first online compilation comprising 889 biomarkers for 26 ocular diseases and 939 eye biomarkers for 181 systemic diseases. The EBD also includes the information of 78 "nonbiomarkers"-the objects that have been proven cannot be biomarkers. Biological function and network analysis were conducted for these ocular disease biomarkers, and several hub pathways and common network topology characteristics were newly identified, which may promote future ocular disease biomarker discovery and characterizes the landscape of biomarkers for eye diseases at the pathway and network level. The EBD is expected to yield broader utility among developmental biologists and clinical scientists in and outside of the eye field by assisting in the identification of biomarkers linked to eye disorders and related systemic diseases. AVAILABILITY AND IMPLEMENTATION: EBD is available at http://www.eyeseeworld.com/ebd/index.html.