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.

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.

Development and validation of a simple and practical model for early detection of diabetic macular edema in patients with type 2 diabetes mellitus using easily accessible systemic variables.

OBJECTIVE: Diabetic macular edema (DME) is the leading cause of visual impairment in patients with diabetes mellitus (DM). The goal of early detection has not yet achieved due to a lack of fast and convenient methods. Therefore, we aim to develop and validate a prediction model to identify DME in patients with type 2 diabetes mellitus (T2DM) using easily accessible systemic variables, which can be applied to an ophthalmologist-independent scenario. METHODS: In this four-center, observational study, a total of 1994 T2DM patients who underwent routine diabetic retinopathy screening were enrolled, and their information on ophthalmic and systemic conditions was collected. Forward stepwise multivariable logistic regression was performed to identify risk factors of DME. Machine learning and MLR (multivariable logistic regression) were both used to establish prediction models. The prediction models were trained with 1300 patients and prospectively validated with 104 patients from Guangdong Provincial People's Hospital (GDPH). A total of 175 patients from Zhujiang Hospital (ZJH), 115 patients from the First Affiliated Hospital of Kunming Medical University (FAHKMU), and 100 patients from People's Hospital of JiangMen (PHJM) were used as external validation sets. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity, and specificity were used to evaluate the performance in DME prediction. RESULTS: The risk of DME was significantly associated with duration of DM, diastolic blood pressure, hematocrit, glycosylated hemoglobin, and urine albumin-to-creatinine ratio stage. The MLR model using these five risk factors was selected as the final prediction model due to its better performance than the machine learning models using all variables. The AUC, ACC, sensitivity, and specificity were 0.80, 0.69, 0.80, and 0.67 in the internal validation, and 0.82, 0.54, 1.00, and 0.48 in prospective validation, respectively. In external validation, the AUC, ACC, sensitivity and specificity were 0.84, 0.68, 0.90 and 0.60 in ZJH, 0.89, 0.77, 1.00 and 0.72 in FAHKMU, and 0.80, 0.67, 0.75, and 0.65 in PHJM, respectively. CONCLUSION: The MLR model is a simple, rapid, and reliable tool for early detection of DME in individuals with T2DM without the needs of specialized ophthalmologic examinations.

Global, regional, and national burden of blindness and vision loss attributable to high fasting plasma glucose from 1990 to 2019, and forecasts to 2030: A systematic analysis for the Global Burden of Disease Study 2019.

AIMS: To systematically clarify the spatiotemporal trends, and age-sex-specific blindness and vision loss (BVL) burden due to high fasting plasma glucose (HFPG) from 1990 to 2019, and project this burden over the next decade. MATERIALS AND METHODS: We obtained the number and rate of years lived with disability (YLDs) for the BVL burden attributable to HFPG by age, sex, socio-demographic index (SDI), and location between 1990 and 2019 from the Global Burden of Disease (GBD) 2019 database. The average annual percentage changes (AAPCs) were calculated to assess the temporal trends of HFPG-attributable BVL burden. The Bayesian age-period-cohort model was used to predict the HFPG-attributable BVL burden. RESULTS: In 2019, the global number and age-standardized rate (ASR) for YLDs of BVL attributable to HFPG were 673.13 (95% UI: 159.52 to 1565.34) thousand and 8.44 (95% UI: 2.00 to 19.63) per 100,000 people, respectively. The highest burdens were found in Oceania, South Asia, and Southeast Asia, and the BVL burden due to HFPG was higher in the elderly and lower SDI regions. From 1990 to 2019, the global ASR of HFPG-attributable BVL gradually increased with AAPC (95% CI) being 0.80 (0.74 to 0.86). In addition, the HFPG-attributable BVL burden will slightly increase in the future decade. CONCLUSIONS: The HFPG remains the important cause of BVL worldwide, placing a substantial disease burden. From 1990 to 2019, the age-standardized burden of BVL due to HFPG increased, and will consistently increase in the future decade, particularly in the elderly and in regions with middle SDI or below.

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.

Alterations of outer retinal reflectivity in diabetic patients without clinically detectable retinopathy.

PURPOSE: This study aimed to investigate alterations of outer retinal reflectivity on spectral-domain optical coherence tomography (OCT) in diabetic patients without clinically detectable retinopathy (NDR). METHODS: In this retrospective study, 64 NDR patients and 71 controls were included. Relative reflectivity (RR) of the ellipsoid zone (EZ), photoreceptor outer segment (OS) and inner segment (IS), and outer nuclear layer (ONL) at the foveola and at 500 µm, 1000 µm, and 2000 µm nasal (N), temporal (T), superior (S), and inferior (I) to the foveola was measured by cross-line OCT and ImageJ. Retinal vessel densities (VD) in fovea, parafovea, and perifovea areas were detected by OCT angiography (OCTA). RESULTS: EZ RR in most retinal locations was significantly lower in NDR eyes compared to controls (all P < 0.05), except the foveola. Compared with controls, NDR eyes also displayed lower RR at N2000, T2000, S1000, and I1000 of OS, at S500 and I500 of IS, and at I500 of ONL (all P < 0.05). Negative correlations could be observed between retinal RR and diabetes duration, HbA1c, and best-corrected visual acuity (BCVA) (r = - 0.303 to - 0.452). Compared to controls, EZ, OS, and IS RR of the NDR eyes showed lower correlation coefficients with whole image SCP and DCP VD of parafovea and perifovea regions. CONCLUSION: Outer retinal reflectivity, along with the coefficients between retinal reflectivity and VD, is reduced in NDR patients and is correlated with diabetes duration, HbA1c, and BCVA. The reduction of outer retinal reflectivity may be a potential biomarker of early retinal alterations in diabetic patients.

Association of Retinal Age Gap and Risk of Kidney Failure: A UK Biobank Study.

RATIONALE & OBJECTIVE: The incidence of kidney failure is known to increase with age. We have previously developed and validated the use of retinal age based on fundus images as a biomarker of aging. However, the association of retinal age with kidney failure is not clear. We investigated the association of retinal age gap (the difference between retinal age and chronological age) with future risk of kidney failure. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 11,052 UK Biobank study participants without any reported disease for characterizing retinal age in a deep learning algorithm. 35,864 other participants with retinal images and no kidney failure were followed to assess the association between retinal age gap and the risk of kidney failure. EXPOSURE: Retinal age gap, defined as the difference between model-based retinal age and chronological age. OUTCOME: Incident kidney failure. ANALYTICAL APPROACH: A deep learning prediction model used to characterize retinal age based on retinal images and chronological age, and Cox proportional hazards regression models to investigate the association of retinal age gap with incident kidney failure. RESULTS: After a median follow-up period of 11 (IQR, 10.89-11.14) years, 115 (0.32%) participants were diagnosed with incident kidney failure. Each 1-year greater retinal age gap at baseline was independently associated with a 10% increase in the risk of incident kidney failure (HR, 1.10 [95% CI, 1.03-1.17]; P=0.003). Participants with retinal age gaps in the fourth (highest) quartile had a significantly higher risk of incident kidney failure compared with those in the first quartile (HR, 2.77 [95% CI, 1.29-5.93]; P=0.009). LIMITATIONS: Limited generalizability related to the composition of participants in the UK Biobank study. CONCLUSIONS: Retinal age gap was significantly associated with incident kidney failure and may be a promising noninvasive predictive biomarker for incident kidney failure.

Global, Regional, and National Burdens of Blindness and Vision Loss in Children and Adolescents from 1990 to 2019: A Trend Analysis.

PURPOSE: To provide estimates for regional and national burdens of blindness and vision loss among children and adolescents between 1990 and 2019 by disease, age, and sociodemographic index (SDI). DESIGN: This was a retrospective demographic analysis based on aggregated data. METHODS: This was a population-based study using 1990-2019 data on the burden of vision loss and blindness from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. The burden of vision loss and blindness was evaluated in terms of case numbers, rates per 100 000 population, and average annual percentage changes (AAPCs) in prevalence rates and years lived with disability (YLDs). RESULTS: Globally, the rates of blindness and vision loss per 100 000 population decreased in all age groups between 1990 and 2019, with prevalence rates decreasing from 1091.4 (95% uncertainty interval [UI], 895.2-1326.1) to 1036.9 (95% UI, 847.8-1265.9, AAPC, -0.2) and YLDs decreasing from 44.5 (95% UI, 28.1-66.5) to 40.2 (95% UI, 25.1-60.7, AAPC, -0.4). Most of these reductions in prevalence rates (AAPC, -0.2, 95% confidence interval [CI], -0.2 to -0.1) and YLDs (AAPC, -0.2, 95% CI, -0.3 to -0.2) were due to decreases in refractive disorder. Notably, near-vision loss prevalence (AAPC, 0.3, 95% CI, 0.2-0.4) and YLDs (AAPC, 0.3, 95% CI, 0.2-0.4) substantially increased in all age groups. Children and adolescents in low- and low-middle SDI countries exhibited substantial decreases in the prevalence rates and YLDs of blindness and vision loss, but their counterparts in high- and middle-high SDI countries experienced a substantial increase in prevalence. CONCLUSIONS: Globally, efforts in the past 3 decades have substantially decreased the burdens of blindness and vision loss among children and adolescents. However, there is extensive variation according to the kind of impairment, age group, and country SDI. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Impaired retinal microcirculation in patients with non-obstructive coronary artery disease.

PURPOSE: To quantitatively investigate alterations of retinal microcirculation in patients with non-obstructive coronary artery disease (NOCAD) using optical coherence tomography angiography (OCTA), and to identify the ability of retinal microcirculation parameters in differentiating coronary artery disease (CAD) subtypes. METHODS: All participants with angina pectoris underwent coronary computed tomography angiography. Patients with lumen diameter reduction of 20-50 % in all major coronary arteries were defined as NOCAD, while patients with at least one major coronary artery lumen diameter reduction ≥ 50 % were recruited as obstructive coronary artery disease (OCAD). Participants without a history of ophthalmic or systemic vascular disease were recruited as healthy controls. Retinal neural-vasculature was measured quantitatively by OCTA, including peripapillary retinal nerve fiber layer (RNFL) thickness and vessel density (VD) of the optic disc, superficial vessel plexus (SVP), deep vessel plexus (DVP), and foveal density (FD 300). p < 0.017 is considered significant in multiple comparisons. RESULTS: A total of 185 participants (65 NOCAD, 62 OCAD, and 58 controls) were enrolled. Except for the DVP fovea (p = 0.069), significantly reduced VD in all other regions of SVP and DVP was detected in both the NOCAD and OCAD groups compared to control group (all p < 0.017), while a more significant decrease was found in OCAD compared to NOCAD. Multivariate regression analysis showed that lower VD in superior hemi part of whole SVP (OR: 0.582, 95 % CI: 0.451-0.752) was an independent risk factor for NOCAD compared to controls, while lower VD in the whole SVP (OR: 0.550, 95 % CI: 0.421-0.719) was an independent risk factor for OCAD compared to NOCAD. Using the integration of retinal microvascular parameters, the area under the receiver operating characteristic curve (AUC) for NOCAD versus control and OCAD versus NOCAD were 0.840 and 0.830, respectively. CONCLUSION: Significant retinal microcirculation impairment, while milder than that in OCAD was observed in NOCAD patients, indicating retinal microvasculature assessment might provide a new systemic microcirculation observation window for NOCAD. Furthermore, retinal microvasculature may serve as a new indicator to assess the severity of CAD with good performance of retinal microvascular parameters in identifying different CAD subtypes.

Association of Retinal Age Gap With Arterial Stiffness and Incident Cardiovascular Disease.

BACKGROUND: Retinal parameters could reflect systemic vascular changes. With the advances of deep learning technology, we have recently developed an algorithm to predict retinal age based on fundus images, which could be a novel biomarker for aging and mortality. Therefore, we aim to investigate associations of retinal age gap with arterial stiffness index and incident cardiovascular disease (CVD). METHODS: A deep learning model was trained based on 19 200 fundus images of 11 052 participants without any medical history at baseline to predict the retinal age. Retinal age gap (retinal age predicted minus chronological age) was generated for the remaining 35 917 participants. Regression models were used to assess the association between retinal age gap and arterial stiffness index. Cox proportional hazards regression models and restricted cubic splines were used to explore the association between retinal age gap and incident CVD. RESULTS: We found each 1-year increase in retinal age gap was associated with increased arterial stiffness index (ß=0.002 [95% CI, 0.001-0.003]; P<0.001). After a median follow-up of 5.83 years (interquartile range: 5.73-5.97), 675 (2.00%) developed CVD. In the fully adjusted model, each 1-year increase in retinal age gap was associated with a 3% increase in the risk of incident CVD (hazard ratio=1.03 [95% CI, 1.01-1.06]; P=0.014). In the restricted cubic splines analysis, the risk of incident CVD increased significantly when retinal age gap reached 1.21 (hazard ratio=1.05 [95% CI, 1.00-1.10]; P-overall <0.0001; P-nonlinear=0.0681). CONCLUSIONS: We found that retinal age gap was significantly associated with arterial stiffness index and incident CVD events, supporting the potential of this novel biomarker in identifying individuals at high risk of future CVD events.

Temporal trajectories of important diseases in the life course and premature mortality in the UK Biobank.

BACKGROUND: Little is known regarding life-course trajectories of important diseases. We aimed to identify diseases that were strongly associated with mortality and test temporal trajectories of these diseases before mortality. METHODS: Our analysis was based on UK Biobank. Diseases were identified using questionnaires, nurses' interviews, or inpatient data. Mortality register data were used to identify mortality up to January 2021. The association between 60 individual diseases at baseline and in the life course and incident mortality was examined using Cox proportional regression models. Those diseases with great contribution to mortality were identified and disease trajectories in life course were then derived. RESULTS: During a median follow-up of 11.8 years, 31,373 individuals (median age at death (interquartile range): 70.7 (65.3-74.8) years, 59.4% male) died of all-cause mortality (with complete data on diagnosis date of disease), with 16,237 dying with cancer and 6702 with cardiovascular disease (CVD). We identified 37 diseases including cancers and heart diseases that were associated with an increased risk of mortality independent of other diseases (hazard ratio ranged from 1.09 to 7.77). Among those who died during follow-up, 2.2% did not have a diagnosis of any disease of interest and 90.1% were diagnosed with two or more diseases in their life course. Individuals who were diagnosed with more diseases in their life course were more likely to have longer longevity. Cancer was more likely to be diagnosed following hypertension, hypercholesterolemia, CVD, or digestive disorders and more likely to be diagnosed ahead of CVD, chronic kidney disease (CKD), or digestive disorders. CVD was more likely to be diagnosed following hypertension, hypercholesterolemia, or digestive disorders and more likely to be diagnosed ahead of cancer or CKD. Hypertension was more likely to precede other diseases, and CKD was more likely to be diagnosed as the last disease before more mortality. CONCLUSIONS: There are significant interplays between cancer and CVD for mortality. Cancer and CVD were frequently clustered with hypertension, CKD, and digestive disorders with CKD highly being diagnosed as the last disease in the life course. Our findings underline the importance of health checks among middle-aged adults for the prevention of premature mortality.

Retinal age gap as a predictive biomarker of stroke risk.

BACKGROUND: The aim of this study is to investigate the association of retinal age gap with the risk of incident stroke and its predictive value for incident stroke. METHODS: A total of 80,169 fundus images from 46,969 participants in the UK Biobank cohort met the image quality standard. A deep learning model was constructed based on 19,200 fundus images of 11,052 disease-free participants at baseline for age prediction. Retinal age gap (retinal age predicted based on the fundus image minus chronological age) was generated for the remaining 35,917 participants. Stroke events were determined by data linkage to hospital records on admissions and diagnoses, and national death registers, whichever occurred earliest. Cox proportional hazards regression models were used to estimate the effect of retinal age gap on risk of stroke. Logistic regression models were used to estimate the predictive value of retinal age and well-established risk factors in 10-year stroke risk. RESULTS: A total of 35,304 participants without history of stroke at baseline were included. During a median follow-up of 5.83 years, 282 (0.80%) participants had stroke events. In the fully adjusted model, each one-year increase in the retinal age gap was associated with a 4% increase in the risk of stroke (hazard ratio [HR] = 1.04, 95% confidence interval [CI]: 1.00-1.08, P = 0.029). Compared to participants with retinal age gap in the first quintile, participants with retinal age gap in the fifth quintile had significantly higher risks of stroke events (HR = 2.37, 95% CI: 1.37-4.10, P = 0.002). The predictive capability of retinal age alone was comparable to the well-established risk factor-based model (AUC=0.676 vs AUC=0.661, p=0.511). CONCLUSIONS: We found that retinal age gap was significantly associated with incident stroke, implying the potential of retinal age gap as a predictive biomarker of stroke risk.

Plasma metabolomic profiles of dementia: a prospective study of 110,655 participants in the UK Biobank.

BACKGROUND: Plasma metabolomic profile is disturbed in dementia patients, but previous studies have discordant conclusions. METHODS: Circulating metabolomic data of 110,655 people in the UK Biobank study were measured with nuclear magnetic resonance technique, and incident dementia records were obtained from national health registers. The associations between plasma metabolites and dementia were estimated using Cox proportional hazard models. The 10-fold cross-validation elastic net regression models selected metabolites that predicted incident dementia, and a 10-year prediction model for dementia was constructed by multivariable logistic regression. The predictive values of the conventional risk model, the metabolites model, and the combined model were discriminated by comparison of area under the receiver operating characteristic curves (AUCs). Net reclassification improvement (NRI) was used to estimate the change of reclassification ability when adding metabolites into the conventional prediction model. RESULTS: Amongst 110,655 participants, the mean (standard deviation) age was 56.5 (8.1) years, and 51 186 (46.3%) were male. A total of 1439 (13.0%) developed dementia during a median follow-up of 12.2 years (interquartile range: 11.5-12.9 years). A total of 38 metabolites, including lipids and lipoproteins, ketone bodies, glycolysis-related metabolites, and amino acids, were found to be significantly associated with incident dementia. Adding selected metabolites (n=24) to the conventional dementia risk prediction model significantly improved the prediction for incident dementia (AUC: 0.824 versus 0.817, p =0.042) and reclassification ability (NRI = 4.97%, P = 0.009) for identifying high risk groups. CONCLUSIONS: Our analysis identified various metabolomic biomarkers which were significantly associated with incident dementia. Metabolomic profiles also provided opportunities for dementia risk reclassification. These findings may help explain the biological mechanisms underlying dementia and improve dementia prediction.

Mendelian randomization analyses in ocular disease: a powerful approach to causal inference with human genetic data.

Ophthalmic epidemiology is concerned with the prevalence, distribution and other factors relating to human eye disease. While observational studies cannot avoid confounding factors from interventions, human eye composition and structure are unique, thus, eye disease pathogenesis, which greatly impairs quality of life and visual health, remains to be fully explored. Notwithstanding, inheritance has had a vital role in ophthalmic disease. Mendelian randomization (MR) is an emerging method that uses genetic variations as instrumental variables (IVs) to avoid confounders and reverse causality issues; it reveals causal relationships between exposure and a range of eyes disorders. Thus far, many MR studies have identified potentially causal associations between lifestyles or biological exposures and eye diseases, thus providing opportunities for further mechanistic research, and interventional development. However, MR results/data must be interpreted based on comprehensive evidence, whereas MR applications in ophthalmic epidemiology have some limitations worth exploring. Here, we review key principles, assumptions and MR methods, summarise contemporary evidence from MR studies on eye disease and provide new ideas uncovering aetiology in ophthalmology.

Retinal age gap as a predictive biomarker of future risk of Parkinson's disease.

INTRODUCTION: retinal age derived from fundus images using deep learning has been verified as a novel biomarker of ageing. We aim to investigate the association between retinal age gap (retinal age-chronological age) and incident Parkinson's disease (PD). METHODS: a deep learning (DL) model trained on 19,200 fundus images of 11,052 chronic disease-free participants was used to predict retinal age. Retinal age gap was generated by the trained DL model for the remaining 35,834 participants free of PD at the baseline assessment. Cox proportional hazards regression models were utilised to investigate the association between retinal age gap and incident PD. Multivariable logistic model was applied for prediction of 5-year PD risk and area under the receiver operator characteristic curves (AUC) was used to estimate the predictive value. RESULTS: a total of 35,834 participants (56.7 ± 8.04 years, 55.7% female) free of PD at baseline were included in the present analysis. After adjustment of confounding factors, 1-year increase in retinal age gap was associated with a 10% increase in risk of PD (hazard ratio [HR] = 1.10, 95% confidence interval [CI]: 1.01-1.20, P = 0.023). Compared with the lowest quartile of the retinal age gap, the risk of PD was significantly increased in the third and fourth quartiles (HR = 2.66, 95% CI: 1.13-6.22, P = 0.024; HR = 4.86, 95% CI: 1.59-14.8, P = 0.005, respectively). The predictive value of retinal age and established risk factors for 5-year PD risk were comparable (AUC = 0.708 and 0.717, P = 0.821). CONCLUSION: retinal age gap demonstrated a potential for identifying individuals at a high risk of developing future PD.

Global Incidence, Progression, and Risk Factors of Age-Related Macular Degeneration and Projection of Disease Statistics in 30 Years: A Modeling Study.

OBJECTIVE: Age-related macular degeneration(AMD) has become a major cause of visual impairment worldwide, especially in the elderly. Estimates of incidence, progression rates, and risk factors of AMD vary among studies, complicating the understanding of its epidemiology. METHODS: For this systematic review and meta-analysis, literature published up to March 1, 2021, was searched in both English and Chinese databases. Hierarchical Bayesian approaches were used to estimate pooled incidence, progression, and 95% credible intervals (CrIs). RESULTS: Thirty studies were included. The pooled annual early and late AMD incidence rates were 1.59 (95% CrI: 1.18-2.11) and 0.23 (95% CrI: 0.14-0.34) per 100 person-years, respectively. The annual progression rate of AMD was 5.5 (95% CrI: 2.3-8.8) per 100 person-years. Smoking was an independent risk factor for both early and late AMD, whereas age, high-density lipoprotein cholesterol, and alcohol consumption were risk factors for early AMD incidence only. The projected number of new cases of early and late AMD in 2050 would be 39.05 million (95% CrI: 23.12-63.57) and 6.41 million (95% CrI: 3.37-13.22), respectively. CONCLUSION: The prediction the number of new cases of AMD is not equal across the globe. Our findings indicate the need for more rigorous control and prevention measures in AMD focus on its risk factors for early intervention. The epidemiological estimates reported in this study could inform to identify effective strategies for preventing AMD worldwide.

Association between dual sensory impairment and risk of mortality: a cohort study from the UK Biobank.

BACKGROUND: Dual sensory impairment is affecting over 10% of older adults worldwide. However, the long-term effect of dual sensory impairment (DSI) on the risk of mortality remains controversial. We aim to investigate the impact of single or/and dual sensory impairment on the risk of mortality in a large population-based sample of the adult in the UK with 14-years of follow-up. METHODS: This population-based prospective cohort study included participants aged 40 and over with complete records of visual and hearing functions from the UK Biobank study. Measurements of visual and hearing functions were performed at baseline examinations between 2006 and 2010, and data on mortality was obtained by 2021. Dual sensory impairment was defined as concurrent visual and hearing impairments. Cox proportional hazards regression models were employed to evaluate the impact of sensory impairment (dual sensory impairment, single visual or hearing impairment) on the hazard of mortality. RESULTS: Of the 113,563 participants included in this study, the mean age (standard deviation) was 56.8 (8.09) years, and 61,849 (54.5%) were female. At baseline measurements, there were 733 (0.65%) participants with dual sensory impairment, 2,973 (2.62%) participants with single visual impairment, and 13,560 (11.94%) with single hearing impairment. After a follow-up period of 14 years (mean duration of 11 years), 5,992 (5.28%) participants died from all causes. Compared with no sensory impairment, dual sensory impairment was significantly associated with an estimated 44% higher hazard of mortality (hazard ratio: 1.44 [95% confidence interval, 1.11-1.88], p = 0.007) after multiple adjustments. CONCLUSIONS: Individuals with dual sensory impairment were found to have an independently 44% higher hazard of mortality than those with neither sensory impairment. Timely intervention of sensory impairment and early prevention of its underlying causes should help to reduce the associated risk of mortality.

[Comparative study of rat serum pharmacochemistry between Puerariae Lobatae Radix and Puerariae Thomsonii Radix based on UPLC-Q-TOF-MS].

UPLC-Q-TOF-MS and serum pharmacochemistry were employed to study the migrating components in rat sera after intragastric administration of the water extracts of Puerariae Lobatae Radix(PLR) and Puerariae Thomsonii Radix(PTR). After the respective intragastric administration of PLR and PTR extracts, blood samples were collected from the orbital vein. The serum samples were treated by protein precipitation method with methanol and acetonitrile at a ratio of 1∶1 and then passed through Agilent ZORBAX RRHD SB-C_(18) column(3 mm×100 mm, 1.8 µm) and Agilent SB-C_(18) pre-column(3 mm×5 mm, 1.8 µm) with 0.1% formic acid aqueous solution(A)-acetonitrile(B) as the mobile phase. The elution was performed at the flow rate of 0.25 mL·min~(-1), the column temperature of 40 ℃, and the injection volume of 2 µL. By comparison of the total ion chromatogram and secondary fragment ion information of PLR and PTR water extracts, PLR-and PTR-containing sera, and blank serum, we found 42 migrating components(including 17 prototype components and 25 metabolites) in the sera of rats treated with PLR and 35 migrating components(including 15 prototype components and 20 metabolites) in the sera of rats treated with PTR. Thirty-three common components were shared by the two treatments, including 13 prototype components and 20 metabolites. The differences of migrating components in the PLR-and PTR-treated rat sera provide a scientific basis for further study of the active components and quality markers of PLR and PTR.

[Quality evaluation of Dalbergiae Odoriferae Lignum by HPLC fingerprint and multi-component quantitative analysis].

The present study detected the component content in Dalbergiae Odoriferae Lignum by HPLC fingerprint and the multi-component determination method. HPLC analysis was performed on the Agilent ZORBAX SB-C_(18) column(4.6 mm×250 mm, 5 µm). Acetonitrile-0.5% phosphoric acid aqueous solution with gradient elution was employed as the mobile phase. The flow rate was 1.0 mL·min~(-1) and the column temperature was maintained at 30 ℃. The detection wavelength was 210 nm and the sample volume was 10 µL. The similarity of 18 batches of Dalbergiae Odoriferae Lignum was 0.343-0.779, indicating that there were great differences between different batches of Dalbergiae Odoriferae Lignum. Eighteen common peaks were identified, including eight flavonoids such as liquiritigenin and latifolin. The mass fractions of liquiritigenin, luteolin, naringenin, isoliquiritigenin, formononetin, dalbergin, latifolin, and pinocembrin were in the ranges of 0.134 1%-0.495 2%, 0.028 2%-0.167 0%, 0.016 3%-0.591 3%, 0.053 5%-0.188 0%, 0.142 4%-0.640 1%, 0.068 0%-0.590 7%, 0.003 2%-1.980 7%, and 0.009 6%-0.740 2%, respectively. Eighteen batches of Dalbergiae Odoriferae Lignum were divided into three categories by cluster analysis and eight differential components in Dalbergiae Odoriferae Lignum were marked by partial least-squares discriminant analysis(PLS-DA). The cumulative variance contribution rate was 90.5%. The HPLC fingerprint combined with the multi-component determination method for Dalbergiae Odoriferae Lignum is easy in operation and accurate in results, with good repeatability and reliability. The quality of Dalbergiae Odoriferae Lignum can be evaluated and analyzed by the PLS-DA model. This study is expected to provide a reference for the quality control and clinical application of Dalbergiae Odoriferae Lignum.

VDAC1 regulates mitophagy in NLRP3 inflammasome activation in retinal capillary endothelial cells under high-glucose conditions.

Diabetic retinopathy (DR) has been considered to involve mitochondrial alterations and be related to the nucleotide-binding oligomerization domain-like receptors 3 (NLRP3) inflammasome activation. The voltage-dependent anion channel 1 (VDAC1) protein is one of the key proteins that regulates the metabolic and energetic functions of the mitochondria. To explore the involvement of VDAC1 in mitophagy regulation of NLRP3 inflammasome activation under high-glucose (HG) conditions, this study examined expressions of VDAC1, mitochondrial function and mitophagy-related proteins, and NLRP3 inflammasome-related proteins in human retinal capillary endothelial cells (HRCECs) cultured with 30 mM of glucose in the presence or absence of mitophagy inhibitor (Mdivi-1) using Western blot. Mitochondrial membrane potential and mitochondrial reactive oxygen species (mtROS) were detected using flow cytometry. GFP-tagged pAdTrack-VDAC1 adenovirus was used to overexpress VDAC1. Cell biological behaviors, including proliferation, migration, tubule formation, and apoptosis, were also observed. Our results showed that when compared to the normal glucose and high mannitol groups, increased amounts of mitochondrial fragments, reduced mitochondrial membrane potential, increased expression of mitochondrial fission protein Drp 1, decreased expression of mitochondrial fusion protein Mfn 2, accumulation of mtROS, and activation of the NLRP3 inflammasome were observed in the HG group. Meanwhile, HG markedly reduced the protein expressions of PINK1, Parkin and VDAC1. Inhibition of mitophagy reduced PINK1 expression, enhanced NLRP3 expression, but failed to alter VDAC1. VDAC1 overexpression promoted PINK1 expression, inhibited NLRP3 activation and changed the cell biological behaviors under HG conditions. These findings demonstrate that VDAC1-mediated mitophagy plays a crucial role in regulating NLRP3 inflammasome activation in retinal capillary endothelial cells under HG conditions, suggesting that VDAC1 may be a potential target for preventing or treating DR.