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Abstract The etiology of primary open angle glaucoma is constituted by both intraocular pressure-dependent and intraocular pressure-independent mechanisms. However, GWASs of traits affecting primary open angle glaucoma through mechanisms independent of intraocular pressure remains limited. Here, we address this gap by subtracting the genetic effects of a GWAS for intraocular pressure from a GWAS for primary open angle glaucoma to reveal the genetic contribution to primary open angle glaucoma via intraocular pressure-independent mechanisms. Seventeen independent genome-wide significant SNPs were associated with the intraocular pressure-independent component of primary open angle glaucoma. Of these, 7 are located outside known normal tension glaucoma loci, 11 are located outside known intraocular pressure loci, and 2 are novel primary open angle glaucoma loci. The intraocular pressure-independent genetic component of primary open angle glaucoma is associated with glaucoma endophenotypes, while the intraocular pressure-dependent component is associated with blood pressure and vascular permeability. A genetic risk score for the intraocular pressure-independent component of primary open angle glaucoma is associated with 26 different retinal micro-vascular features, which contrasts with the genetic risk score for the intraocular pressure-dependent component. Increased understanding of these intraocular pressure-dependent and intraocular pressure-independent components provides insights into the pathogenesis of glaucoma.

Abstract Alzheimer's disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers. Graphical Abstract Study pipeline.

Abstract The metabolic profile predating the onset of Parkinson’s disease (PD) remains unclear. We aim to investigate the metabolites associated with incident and prevalent PD and their predictive values in the UK Biobank participants with metabolomics and genetic data at the baseline. A panel of 249 metabolites was quantified using a nuclear magnetic resonance analytical platform. PD was ascertained by self-reported history, hospital admission records and death registers. Cox proportional hazard models and logistic regression models were used to investigate the associations between metabolites and incident and prevalent PD, respectively. Area under receiver operating characteristics curves (AUC) were used to estimate the predictive values of models for future PD. Among 109,790 participants without PD at the baseline, 639 (0.58%) individuals developed PD after one year from the baseline during a median follow-up period of 12.2 years. Sixty-eight metabolites were associated with incident PD at nominal significance (P

Objective Glaucoma is an optic neuropathy and the leading cause of irreversible blindness worldwide. However, the early detection of glaucoma remains challenging, as chronic forms of glaucoma remain largely asymptomatic until considerable irreversible visual field deficits have ensued. Thus, biomarkers that facilitate early diagnosis and treatment for glaucoma patients with a high risk of progression are pressing.Methods and analysis Human disease–biomarker interactions network and human disease–target–drug interactions network were first constructed based on multiomics data. The greedy search algorithm was used to search for the hub biomarkers and drug targets for glaucoma. Genome-wide association studies and epidemiological data from the UK Biobank were used to verify our results. Biological network and functional analysis was conducted to find common network features and pathways.Results We identified 10 hub biomarkers/drug targets for the diagnosis, treatment and prognosis for glaucoma. These results were verified by text mining and genomic/epidemiology data. We also predicted the new application of BMP1 and MMP9 to diagnose glaucoma and confirm the theory of hub biomarkers with multiple clinical applications. Further, relevant pivotal pathways for these hub biomolecules were discovered, which may serve as foundations for future biomarker and drug target prediction for glaucoma.Conclusion We have used a network-based approach to identify hub diagnostic and therapeutic biomarkers for glaucoma and detected relationships between glaucoma and associated diseases. Several hub biomarkers were identified and verified, which may play more important roles in the diagnosis and treatment of glaucoma.

Summary: Intraocular pressure (IOP) is closely correlated with blood pressure (BP), and while BP has been linked to brain volumes, the effect of IOP on brain volumes remains unclear. This study analyzed participants from the UK Biobank with MRI-measured brain volumes. Observational analyses included 8,634 participants for IOP and 36,069 for BP, followed by Mendelian randomization (MR) analyses of 37,410 participants. Observational analyses revealed that each 10-mmHg increase in diastolic BP was linked to a 0.13 mL larger white matter hyperintensity (WMH) after adjusting for covariates. Associations between IOP and brain volumes were more pronounced in younger individuals or those without hypertension. MR analyses confirmed significant relationships between diastolic BP and WMH, and each 5-mmHg increase in IOP reduced gray matter volumes by 3.24 mL. The study suggests that targeting IOP and BP could help prevent brain volume reduction.

Abstract 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.

Abstract 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.

Abstract 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.

Background/Objectives: Glaucoma is the leading cause of irreversible blindness, with a significant proportion of cases remaining undiagnosed globally. The interpretation of optic disc and retinal nerve fibre layer images poses challenges for optometrists and ophthalmologists, often leading to misdiagnosis. AI has the potential to improve diagnosis. This study aims to validate an AI system (a convolutional neural network based on the Inception-v3 architecture) for detecting glaucomatous optic neuropathy (GON) using colour fundus photographs from a UK population and to compare its performance against Australian optometrists. Methods: A retrospective external validation study was conducted, comparing AI’s performance with that of 11 AHPRA-registered optometrists in Australia on colour retinal photographs, evaluated against a reference (gold) standard established by a panel of glaucoma specialists. Statistical analyses were performed using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Results: For referable GON, the sensitivity of the AI (33.3% [95%CI: 32.4–34.3) was significantly lower than that of optometrists (65.1% [95%CI: 64.1–66.0]), p < 0.0001, although with significantly higher specificity (AI: 97.4% [95%CI: 97.0–97.7]; optometrists: 85.5% [95%CI: 84.8–86.2], p < 0.0001). The optometrists demonstrated significantly higher AUROC (0.753 [95%CI: 0.744–0.762]) compared to AI (0.654 [95%CI: 0.645–0.662], p < 0.0001). Conclusion: The AI system exhibited lower performance than optometrists in detecting referable glaucoma. Our findings suggest that while AI can serve as a screening tool, both AI and optometrists have suboptimal performance for the nuanced diagnosis of glaucoma using fundus photographs alone. Enhanced training with diverse populations for AI is essential for improving GON detection and addressing the significant challenge of undiagnosed cases.

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 0.65) 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.

Abstract 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.

Abstract Background Dietary patterns are crucial for maintaining cognitive health among older people and can be modified through lifestyle interventions. We investigated the associations between dietary patterns, changes in these patterns over time, and cognitive function. Methods This cohort study utilized data from the Chinese Longitudinal Healthy Longevity Survey conducted between 2005 and 2014. The sample included 7472 participants (mean age: 81.45 ± 10.88 years). Dietary patterns were derived using cluster analysis. Cognitive function was assessed using the Mini‐Mental State Examination (MMSE). The relationships between dietary patterns/changes, MMSE scores, changes in MMSE scores, and cognitive impairment were analyzed using the generalized estimating equation method, linear regression, and logistic regression. Results Cluster analysis identified three major dietary patterns: balanced diet, relatively balanced diet, and unbalanced diet. Mean MMSE scores decreased from 24.71 ± 7.24 in 2005 to 22.22 ± 9.29 in 2008, then increased to 24.10 ± 7.76 in 2014. Participants who adhered to balanced diet patterns exhibited significantly higher MMSE scores (1.56; 95% confidence interval: 1.34, 1.78) than those who followed unbalanced diet patterns. This association was particularly prominent among older individuals, women, individuals with no education, and underweight individuals. Participants with relatively balanced or balanced diets showed a significantly lower risk of cognitive impairment (adjusted odds ratio (OR) = 0.72, 95% CI: 0.65, 0.80; OR = 0.47, 95% CI: 0.42, 0.53, respectively) than those with unbalanced diets. Transitioning from an unhealthy diet to a healthy diet was associated with a smaller decline in MMSE scores and reduced risk of cognitive impairment. Conclusions These findings emphasize the importance of balanced or relatively balanced diets in preserving cognitive health in older individuals. These patterns relate to better MMSE scores and reduced cognitive impairment risk. Shifting from unhealthy to healthy diets is linked to improved MMSE scores and lower cognitive impairment risk. These results underscore the importance of dietary interventions in mitigating cognitive decline in older adults. Further research is warranted to understand the underlying mechanisms and develop targeted strategies for promoting healthy dietary habits in this population.

Abstract 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.

BackgroundData regarding the association between antioxidant supplementation and incident dementia are limited.MethodsWe included 494,632 adults (54.5% females) aged 40–71 years at baseline from the United Kingdom Biobank in the final analysis. Incident dementia was ascertained using hospital inpatient and death records up to January 2021.ResultsOver a median follow-up of 11.9 years, 7,128 new cases of all-cause dementia, 2,772 cases of Alzheimer’s disease, and 1,397 cases of vascular dementia were recorded. The hazard ratio (95% CI) for incident dementia associated with zinc supplementation was 0.84 (0.74–0.96), and the association remained significant after adjusting for all confounders (0.84 (0.74–0.96)). In the full model, zinc supplementation was associated with a reduced risk of Alzheimer’s disease [HR (95% CI): 0.71 (0.57–0.88)]. There was no significant association between zinc supplementation and the risk of vascular dementia. No significant associations with incident dementia were observed for other antioxidant supplementation. The association between zinc supplementation and incident dementia was significant among individuals with [HR (95% CI): 0.34 (0.15–0.77)] and without cataract [0.87 (0.77–0.99)] but it was stronger among those with cataract (p value for interaction = 0.0271).ConclusionOur findings suggest that zinc supplementation may help reduce the risk of all-cause dementia and Alzheimer’s disease in middle-aged or older adults, especially among those with cataracts.

Abstract Background Metabolic syndrome (MetS) is a clustering of cardiometabolic components, posing tremendous burdens in the aging society. Retinal age gap has been proposed as a robust biomarker associated with mortality and Parkinson's disease. Although MetS and chronic inflammation could accelerate the aging process and increase the risk of mortality, the association of the retinal age gap with MetS and inflammation has not been examined yet. Methods Retinal age gap (retina‐predicted age minus chronological age) was calculated using a deep learning model. MetS was defined as the presence of three or more of the following: central obesity, hypertension, dyslipidemia, hypertriglyceridemia, and hyperglycemia. Inflammation index was defined as a high‐sensitivity C‐reactive protein level above 3.0 mg/L. Logistic regression models were used to examine the associations of retinal age gaps with MetS and inflammation. Results We found that retinal age gap was significantly associated with MetS and inflammation. Specifically, compared to participants with retinal age gaps in the lowest quartile, the risk of MetS was significantly increased by 10% and 14% for participants with retinal age gaps in the third and fourth quartile (odds ratio [OR]:1.10; 95% confidence interval [CI], 1.01,1.21;, p = .030; OR: 1.14, 95% CI, 1.03,1.26; p = .012, respectively). Similar trends were identified for the risk of inflammation and combined MetS and inflammation. Conclusion We found that retinal age gaps were significantly associated with MetS as well as inflammation. Given the noninvasive and cost‐effective nature and the efficacy of the retinal age gap, it has great potential to be used as a screening tool for MetS in large populations.

Abstract Background Little is known regarding whether sex assigned at birth modifies the association between several predictive factors for dementia and the risk of dementia itself. Methods Our retrospective cohort study included 214,670 men and 214,670 women matched by age at baseline from the UK Biobank. Baseline data were collected between 2006 and 2010, and incident dementia was ascertained using hospital inpatient or death records until January 2021. Mediation analysis was tested for 133 individual factors. Results Over 5,117,381 person-years of follow-up, 5928 cases of incident all-cause dementia (452 cases of young-onset dementia, 5476 cases of late-onset dementia) were documented. Hazard ratios (95% CI) for all-cause, young-onset, and late-onset dementias associated with the male sex (female as reference) were 1.23 (1.17–1.29), 1.42 (1.18–1.71), and 1.21 (1.15–1.28), respectively. Out of 133 individual factors, the strongest mediators for the association between sex and incident dementia were multimorbidity risk score (percentage explained (95% CI): 62.1% (45.2–76.6%)), apolipoprotein A in the blood (25.5% (15.2–39.4%)), creatinine in urine (24.9% (16.1–36.5%)), low-density lipoprotein cholesterol in the blood (23.2% (16.2–32.1%)), and blood lymphocyte percentage (21.1% (14.5–29.5%)). Health-related conditions (percentage (95% CI) explained: 74.4% (51.3–88.9%)) and biomarkers (83.0% (37.5–97.5%)), but not lifestyle factors combined (30.1% (20.7–41.6%)), fully mediated sex differences in incident dementia. Health-related conditions combined were a stronger mediator for late-onset (75.4% (48.6–90.8%)) than for young-onset dementia (52.3% (25.8–77.6%)), whilst lifestyle factors combined were a stronger mediator for young-onset (42.3% (19.4–69.0%)) than for late-onset dementia (26.7% (17.1–39.2%)). Conclusions Our analysis matched by age has demonstrated that men had a higher risk of all-cause, young-onset, and late-onset dementias than women. This association was fully mediated by health-related conditions or blood/urinary biomarkers and largely mediated by lifestyle factors. Our findings are important for understanding potential mechanisms of sex in dementia risk.

Objectives: This study assessed the efficacy, safety, pharmacokinetics (PK), and immunogenicity profiles of a denosumab biosimilar (LY06006) in Chinese postmenopausal osteoporotic women with a high risk of fracture. Methods: In this multicenter, randomized, double-blind, placebo-controlled, phase 3 trial, 448 postmenopausal women aged 50–85 years with osteoporosis were enrolled at 49 centers in China and were randomly assigned (3:1) to receive 60 ​mg of the denosumab biosimilar (LY06006) or placebo subcutaneously every 6 months for 1 year. Lumbar spine bone mineral density (BMD) change was the primary endpoint. Results: Of the 448 randomized patients, 409 (LY06006, n ​= ​311; placebo, n ​= ​98) completed the study. All 448 (100.0%) subjects were included in the intent-to-treat (ITT) trial, 427 (95.3%) were included in the full analysis set (FAS), 408 (91.1%) were included in the per protocol set (PPS), 446 (99.6%) were included in the safety set (SS), and 336 (75.0%) were included in the pharmacokinetics concentration set (PKCs). For the primary endpoint, a 4.71% (95% CI, 3.81%, 5.60%) treatment difference in percent change in lumbar spine BMD from baseline to month 12 was observed in the LY06006 group compared with the placebo group (P ​

Abstract 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.

Abstract Given the unprecedented phenomenon of population ageing, studies have increasing captured the heterogeneity within the ageing process. In this context, the concept of “biological age” has been introduced as an integrated measure reflecting the individualized ageing pace. Identifying reliable and robust biomarkers of age is critical for the accurate risk stratification of individuals and exploration into antiageing interventions. Numerous potential biomarkers of ageing have been proposed, spanning from molecular changes and imaging characteristics to clinical phenotypes. In this review, we will start off with a discussion of the development of ageing biomarkers, then we will provide a comprehensive summary of currently identified ageing biomarkers in humans, discuss the rationale behind each biomarker and highlight their accuracy and clinical value with a contemporary perspective. Additionally, we will discuss the challenges, potential applications, and future opportunities in this field. While research on ageing biomarkers has led to significant progress and applications, further investigations are still necessary. We anticipate that future breakthroughs in this field will involve exploring potential mechanisms, developing biomarkers by combining various data sources or employing new technologies, and validating the clinical value of existing and emerging biomarkers through comprehensive collaboration and longitudinal studies.

Abstract 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.

Abstract 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.

Abstract 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.

Background: Diabetic retinopathy, a common microvascular complication of diabetes mellitus, is one of the leading causes of vision loss worldwide. Although some oral drugs have been suggested to affect the risk of diabetic retinopathy, systematic evaluation about the associations between medications and diabetic retinopathy is still absent. Objective: To comprehensively investigate associations of systemic medications with incident clinically significant diabetic retinopathy (CSDR). Design: Population-based cohort study. Methods: From 2006 to 2009, more than 26 000 participants residing in New South Wales were enrolled in the 45 and Up study. Diabetic participants with self-reported physician diagnosis or records of anti-diabetic medication prescriptions were finally included in the current analysis. CSDR was defined as diabetic retinopathy cases requiring retinal photocoagulation recorded in the Medicare Benefits Schedule database from 2006 to 2016. Prescriptions of systemic medication from 5 years to 30 days prior to CSDR were retrieved from the Pharmaceutical Benefits Scheme. The study participants were equally split into training and testing datasets. Logistic regression analyses were performed for the association between each of systemic medication and CSDR in the training dataset. After controlling the false discovery rate (FDR), significant associations were further validated in the testing dataset. Results: The 10-year incidence of CSDR was 3.9% ( n = 404). A total of 26 systemic medications were found to be positively associated with CSDR, among which 15 were validated by the testing dataset. Additional adjustments for pertinent comorbidities suggested that isosorbide mononitrate (ISMN) (OR: 1.87, 95%CI: 1.00–3.48), calcitriol (OR: 4.08, 95% CI: 2.02–8.24), three insulins and analogues (e.g., intermediate-acting human insulin, OR: 4.28, 95% CI: 1.69–10.8), five anti-hypertensive medications (e.g., furosemide, OR: 2.53, 95% CI: 1.77–3.61), fenofibrate (OR: 1.96, 95% CI: 1.36–2.82) and clopidogrel (OR: 1.72, 95% CI: 1.15–2.58) were independently associated with CSDR. Conclusion: This study investigated the association of a full spectrum of systemic medications with incident CSDR. ISMN, calcitriol, clopidogrel, a few subtypes of insulin, anti-hypertensive and cholesterol-lowering medications were found to be associated with incident CSDR.

BackgroundConsidered as the representatives of neurodegenerative diseases, Alzheimer’s disease (AD) and glaucoma are complex progressive neuropathies affected by both genetic and environmental risk factors and cause irreversible damages. Current research indicates that there are common features between AD and glaucoma in terms of epidemiology and pathophysiology. However, the understandings and explanations of their comorbidity and potential genetic overlaps are still limited and insufficient.MethodGenetic pleiotropy analysis was performed using large genome-wide association studies summary statistics of AD and glaucoma, with an independent cohort of glaucoma for replication. Conditional and conjunctional false discovery rate methods were applied to identify the shared loci. Biological function and network analysis, as well as the expression level analysis were performed to investigate the significance of the shared genes.ResultsA significant positive genetic correlation between AD and glaucoma was identified, indicating that there were significant polygenetic overlaps. Forty-nine shared loci were identified and mapped to 11 shared protein-coding genes. Functional genomic analyses of the shared genes indicate their modulation of critical physiological processes in human cells, including those occurring in the mitochondria, nucleus, and cellular membranes. Most of the shared genes indicated a potential modulation of metabolic processes in human cells and tissues. Furthermore, human protein–protein interaction network analyses revealed that some of the shared genes, especially MTCH2, NDUFS3, and PTPMT1, as well as SPI1 and MYBPC3, may function concordantly. The modulation of their expressions may be related to metabolic dysfunction and pathogenic processes.ConclusionOur study identified a shared genetic architecture between AD and glaucoma, which may explain their shared features in epidemiology and pathophysiology. The potential involvement of these shared genes in molecular and cellular processes reflects the “inter-organ crosstalk” between AD and glaucoma. These results may serve as a genetic basis for the development of innovative and effective therapeutics for AD, glaucoma, and other neurodegenerative diseases.

IntroductionThe relationship between sensory impairments and the risk of dementia is inconclusive. We aim to investigate the association of visual impairment (VI), hearing impairment (HI), and dual sensory impairment (DSI) with incident dementia.MethodsThe UK Biobank study recruited more than 500,000 participants aged 40–69 years across the United Kingdom. Participants with available visual acuity (VA) measurements and speech-reception-threshold (SRT) information and free of dementia at the baseline assessment were included in the analysis. VI was defined as VA worse than 0.3 LogMAR units and HI were defined as an SRT of −5.5 dB or over. DSI was defined as the presence of both VI and HI. Incident dementia was identified through linked data to primary care or hospital admission records and death registries. Multivariable Cox proportional hazard regression models were used to examine the association of VI, HI, and DSI with incident dementia.ResultsAmong 113,511 participants (mean age: 56.8 ± 8.09 years, female: 54.4%), a total number of 1,135 (1.00%) cases of incident dementia were identified during a median follow up period of 11.1 years [interquartile range (IQR): 10.9–11.4 years]. The incidence of dementia showed significant differences among the non-sensory impairment (NSI) group, VI-only group, HI-only group, and DSI group (p < 0.001). After adjusting for demographic, lifestyle, health, and genetic factors, isolated VI (HR = 1.50, 95% CI: 1.06–2.12, p = 0.023), isolated HI (HR = 1.42, 95% CI:1.20–1.69, p < 0.001), and DSI (HR = 1.82, 95% CI: 1.10–3.00, p = 0.020) were independently associated with higher risks of incident dementia.ConclusionsVisual, hearing, and dual sensory impairments were associated with an increased risk of developing dementia, suggesting that visual and hearing impairments are modifiable risk factors that can be targeted to prevent dementia.

Summary: Background: Little is known regarding associations of conventional and emerging diseases and their multimorbidity with brain volumes. Methods: This cross-sectional study included 36,647 European ancestry individuals aged 44–81 years with brain magnetic resonance imaging data from UK Biobank. Brain volumes were measured between 02 May 2014 and 31 October 2019. General linear regression models were used to associate 57 individual major diseases with brain volumes. Latent class analysis was used to identify multimorbidity patterns. A multimorbidity score for brain volumes was computed based on the estimates for individual groups of diseases. Findings: Out of 57 major diseases, 16 were associated with smaller volumes of total brain, 14 with smaller volumes of grey matter, and six with smaller hippocampus volumes, and four major diseases were associated with higher white matter hyperintensity (WMH) load after adjustment for all other diseases. The leading contributors to the variance of total brain volume were hypertension (R2=0·0229), dyslipidemia (0·0190), cataract (0·0176), coronary heart disease (0·0107), and diabetes (0·0077). We identified six major multimorbidity patterns and multimorbidity patterns of cardiometabolic disorders (CMD), and CMD-multiple disorders, and metabolic disorders were independently associated with smaller volumes of total brain (β (95% CI): -6·6 (-8·9, -4·3) ml, -7·3 (-10·4, -4·1) ml, and -10·4 (-13·5, -7·3) ml, respectively), grey matter (-7·1 (-8·5, -5·7) ml, -9·0 (-10·9, -7·1) ml, and -11·8 (-13·6, -9·9) ml, respectively), and higher WMH load (0·23 (0·19, 0·27), 0·25 (0·19, 0·30), and 0·33 (0·27, 0·39), respectively) after adjustment for geographic, socioeconomic, and lifestyle factors (all P-values

PurposeTo investigate the association between myopia and risk of metabolic syndrome (MetS) in a prospective cohort from the UK Biobank Study.MethodsVolunteers (aged 40 years and above) free of baseline MetS and cataract included from the UK Biobank Study, a prospective follow-up cohort. Myopia was defined using uncycloplegic autorefraction, self-report-myopia, and medical records for refractive error at baseline. MetS as well as components of MetS were diagnosed based on health records, blood biochemistry, and questionnaires. Questionnaires determined the status of smoking, drinking, physical activity and dietary supplements, as well as ethnicity and education.ResultsA total of 91,591 participants were available in the analysis, with a mean age of 55.37 ± 8.07 years at baseline and a median follow-up years of 11.16 years. The proportion of myopia was 49.7%, and a total of 937 (1.0%) participants were identified as having incident MetS (0.09/100 person years). Subjects with myopia were more likely to have MetS compared with non-myopic subjects (0.82 vs. 0.21%, Log-rank test P < 0.001). Mopes had greater risk of incident MetS (Hazard ratio [HR] = 4.19, 95% confidence interval [CI] 3.57–4.93, P < 0.001) adjusting for baseline age, gender, education and ethnicity. After further controlling for lifestyle factors (smoking, drinking, physical activity, and fish oil supplement) or baseline metabolic disorders, the risk of incident MetS were 3.88- and 4.06-fold greater in myopic subjects than those without myopia, respectively (P < 0.001 for both models). The severity of myopia was not significantly correlated to incident MetS in multivariate-adjusted models.ConclusionsAn increased risk of incident MetS among the elderly is associated with myopia, but not the degree of myopia. These findings highlighted the need of prevention of MetS among older adults with myopia.

Summary: Background: Identifying independent and interactive associations of a wide range of diseases and multimorbidity and apolipoprotein E4 (APOE4) with dementia may help promote cognitive health. The main aim of the present study was to investigate associations of such diseases and their multimorbidity with incident dementia. Methods: In this retrospective cohort study, we included 471,485 individuals of European ancestry from the UK Biobank, aged 38–73 years at baseline (2006–10). Dementia was identified using inpatient records and death registers. The follow-up period was between March 16, 2006, and Jan 31, 2021. Findings: During a median follow-up of 11·9 years, 6189 cases of incident all-cause dementia (503 young-onset cases, 5686 late-onset cases) were documented. In multivariable-adjusted analysis, 33 out of 63 major diseases were associated with an increased risk of dementia. The hazard ratio (HR [95% CI]) ranged from 1·12 (1·06–1·19) for obesity to 14·22 (12·33–16·18) for Parkinson's disease. In addition to conventional diseases, respiratory disorders, musculoskeletal disorders, digestive disorders, painful conditions, and chronic kidney disease were associated with increased dementia risk. A larger HR for dementia was observed for a larger number of diseases (3·97 [3·51–4·48] for ≥6 diseases versus no disease). These individual diseases and multimorbidity were more predictive of young-onset dementia than of late-onset dementia. Dementia risk score incorporating multimorbidity, age, and APOE4 status had strong prediction performance (area under the curve [95% CI]: 82·2% [81·7–82·7%]). APOE4 was more predictive of late-onset dementia (HR [95% CI]: 2·90 [2·75–3·06]) than of young-onset dementia (1·26 [1·03–1·54]). Associations of painful conditions, depression, obesity, diabetes, stroke, Parkinson's disease, high cholesterol, and their multimorbidity with incident dementia were stronger among non-APOE4 carriers. Interpretation: Besides conventional diseases, numerous diseases are associated with an increased risk of dementia. These individual diseases and multimorbidity are more predictive of young-onset dementia, whereas APOE4 is more predictive of late-onset dementia. Individual diseases and multimorbidity are stronger predictors of dementia in non-APOE4 carriers. Although multiple risk factors have been adjusted for in the analysis, potential confounding from unknown factors may have biased the associations. Funding: The Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075), Science and Technology Program of Guangzhou, China (202,002,020,049).

MotivationRetinal microvasculature is a unique window for predicting and monitoring major cardiovascular diseases, but high throughput tools based on deep learning for in-detail retinal vessel analysis are lacking. As such, we aim to develop and validate an artificial intelligence system (Retina-based Microvascular Health Assessment System, RMHAS) for fully automated vessel segmentation and quantification of the retinal microvasculature.ResultsRMHAS achieved good segmentation accuracy across datasets with diverse eye conditions and image resolutions, having AUCs of 0.91, 0.88, 0.95, 0.93, 0.97, 0.95, 0.94 for artery segmentation and 0.92, 0.90, 0.96, 0.95, 0.97, 0.95, 0.96 for vein segmentation on the AV-WIDE, AVRDB, HRF, IOSTAR, LES-AV, RITE, and our internal datasets. Agreement and repeatability analysis supported the robustness of the algorithm. For vessel analysis in quantity, less than 2 s were needed to complete all required analysis.

Abstract Background Identifying leading dietary determinants for cardiometabolic risk (CMR) factors is urgent for prioritizing interventions in children. We aimed to identify leading dietary determinants for the change in CMR and create a healthy diet score (HDS) to predict CMR in children. Methods We included 5676 children aged 6–13 years in the final analysis with physical examinations, blood tests, and diets assessed at baseline and one year later. CMR score (CMRS) was computed by summing Z-scores of waist circumference, an average of systolic and diastolic blood pressure (SBP and DBP), fasting glucose, high-density lipoprotein cholesterol (HDL-C, multiplying by − 1), and triglycerides. Machine learning was used to identify leading dietary determinants for CMR and an HDS was then computed. Results The nine leading predictors for CMRS were refined grains, seafood, fried foods, sugar-sweetened beverages, wheat, red meat other than pork, rice, fungi and algae, and roots and tubers with the contribution ranging from 3.9 to 19.6% of the total variance. Diets high in seafood, rice, and red meat other than pork but low in other six food groups were associated with a favorable change in CMRS. The HDS was computed based on these nine dietary factors. Children with HDS ≥8 had a higher decrease in CMRS (β (95% CI): − 1.02 (− 1.31, − 0.73)), BMI (− 0.08 (− 0.16, − 0.00)), SBP (− 0.46 (− 0.58, − 0.34)), DBP (− 0.46 (− 0.58, − 0.34)), mean arterial pressure (− 0.50 (− 0.62, − 0.38)), fasting glucose (− 0.22 (− 0.32, − 0.11)), insulin (− 0.52 (− 0.71, − 0.32)), and HOMA-IR (− 0.55 (− 0.73, − 0.36)) compared to those with HDS ≦3. Improved HDS during follow-up was associated with favorable changes in CMRS, BMI, percent body fat, SBP, DBP, mean arterial pressure, HDL-C, fasting glucose, insulin, and HOMA-IR. Conclusion Diets high in seafood, rice, and red meat other than pork and low in refined grains, fried foods, sugar-sweetened beverages, and wheat are leading healthy dietary factors for metabolic health in children. HDS is strongly predictive of CMR factors.

Purpose. To study the prevalence, causes, and risk factors of visual impairment (VI) among the Dubai Emiratis and non-Emiratis. Methods. The survey was a population-based cross-sectional eye health study conducted 2019-2020. Cluster sampling was used to randomly select local (Emirati) and expatriate (non-Emirati) Dubai residents aged 40 years and older. Ocular examinations were conducted in selected eye clinics to determine the visual acuity (VA) and cause(s) of VI if any. Trained nurses, optometrists, and ophthalmologists did the examinations. VA was measured using ETDRS visual chart. The World Health Organization VI and blindness definitions and classifications for the cause(s) of VI were used. Results. A total of 892 participants were included in the final analysis. The mean age [SD] was 52.09 [9.48] years, with 55.8% as males. Prevalence of presenting mild, moderate, and severe VI was 4.7% (2.94–7.11%), 1.8% (0.78–3.5%), and 0% for Emiratis, and 3.6% (2.06–5.76), 1.6% (0.63–3.21), and 0% for non-Emiratis, respectively. Four Emirati participants were blind, with a prevalence of 0.9% (0.25%–2.28%). Men had lower likelihood of VI than women (odds ratio [OR] (95% CI): 0.42 (0.24–0.77)) after adjustment for covariates. Diabetes (OR (95% CI): 1.91 (1.04–3.52)) was an independent risk factor for VI. Higher education level was associated with a lower likelihood of VI (OR (95% CI): 0.34 (0.13–0.89). Leading causes of VI among Emiratis were uncorrected refractive error (52%) and cataract (17.2%). Glaucoma, optic atrophy, and absent globe were the causes of blindness. Conclusions. Prevalence of VI is comparably low with leading causes readily treatable. An effective strategy to improve spectacle correction and cataract services would reduce the VI burden.

PurposeTo assess the impact of retinopathy and systemic vascular comorbidities on the all-cause mortality in a representative U.S. sample.MethodsA total of 5703 participants (≥40 years old) from the 2005-2008 National Health and Nutrition Examination Survey. The Early Treatment Diabetic Retinopathy Study grading scale was used to evaluate the retinopathy status. Systemic vascular comorbidities included diabetes mellitus (DM), high blood pressure (HBP), chronic kidney disease (CKD) and cardiovascular disease (CVD). Time to death was calculated as the time from baseline to either the date of death or censoring (December 31st, 2015), whichever came first. Risks of mortality were estimated using Cox proportional hazards models after adjusting for confounders and vascular comorbidities.ResultsAfter a median follow-up of 8.33 years (IQR: 7.50-9.67 years), there were 949 (11.8%) deaths from all causes. After adjusting for confounders, the presence of retinopathy predicted higher all-cause mortality (hazard ratio (HR), 1.41; 95% confidence interval (CI), 1.08-1.83). The all-cause mortality among participants with both retinopathy and systemic vascular comorbidities including DM (HR, 1.72; 95% CI, 1.21-2.43), HBP (HR, 1.47; 95% CI, 1.03-2.10), CKD (HR, 1.73; 95% CI, 1.26-2.39) and CVD (HR, 1.92; 95% CI, 1.21-3.04) was significantly higher than that among those without either condition. When stratified by diabetic or hypertension status, the co-occurrence of retinopathy and CKD or CVD further increased the all-cause mortality compared to those without either condition.ConclusionsThe co-occurrence of retinopathy and systemic vascular conditions predicted a further increase in the risk of mortality. More extensive vascular risk factor assessment and management are needed to detect the burden of vascular pathologies and improve long-term survival in individuals with retinopathy.

ObjectivesTo investigate the spatial distribution of 10-year incidence of diagnosed type 2 diabetes mellitus (T2DM) and its association with obesity and physical inactivity at a reginal level breakdown.MethodsDemographic, behavioral, medical and pharmaceutical and diagnosed T2DM incidence data were collected from a cohort of 232,064 participants who were free of diabetes at enrolment in the 45 and Up Study, conducted in the state of New South Wales (NSW), Australia. We examined the geographical trend and correlation between obesity prevalence, physical inactivity rate and age-and-gender-adjusted cumulative incidence of T2DM, aggregated based on geographical regions.ResultThe T2DM incidence, prevalence of obesity and physical inactivity rate at baseline were 6.32%, 20.24%, and 18.7%, respectively. The spatial variation of T2DM incidence was significant (Moran’s I=0.52; p

Background: Long-term cancer, cardiovascular disease, diabetes and osteoarthritis may increase the risk of mental disorders, but which was more harmful and whether the associations differed between genders is unclear. Methods: We included 115,094 participants (54.3% women) aged 45–64 years from the 45 and Up Study who were free of depression, anxiety, and Parkinson's disease at baseline (2006–2009). The incidence of depression and anxiety was identified using claim databases during follow-up until December 2016. Cox regression models were used to examine the association of cancer, cardiovascular disease, diabetes, and osteoarthritis at baseline with incident depression and anxiety. Findings: During a mean eight-year follow-up (958,785 person-year), the cumulative incidence of depression and anxiety was 12.5% and 5.9% in the healthy population. Hazard ratios ([HRs] (95% CI) versus healthy population) for incident depression associated with long-term cancer, cardiovascular disease, diabetes, and osteoarthritis were 1.19 (95% CI: 1.13–1.25), 1.08 (1.00–1.16)), 1.18 (1.09–1.28), and 1.94 (1.80–2.10), respectively. The corresponding HRs (95% CIs) for incident anxiety were 1.11 (1.03–1.20), 1.26 (1.14–1.39), 1.10 (0.98–1.24), and 2.01 (1.80–2.23), respectively. The positive association between cancer and incident depression was more evident in men (HR (95% CI): 1.24 (1.13–1.35) than in women (1.14 (1.07–1.21). Long-term diabetes was an independent risk factor for incident anxiety in men (1.21 (1.02–1.44) but not in women (1.09 (0.93–1.28)). Interpretation: Long-term osteoarthritis, cardiovascular disease, and cancer were independent risk factors for incident depression and anxiety in both genders with osteoarthritis having the highest relative risk. Keywords: Cardiovascular disease, Cancer, Diabetes, Osteoarthritis, Depression, Anxiety

ObjectiveTo examine the association of physical activities (PA) with diabetic retinopathy (DR) progression based on a 10-year follow-up of a large cohort of working-aged diabetic populations in Australia.MethodsNine thousand and eighteen working-aged diabetic patients were enrolled from the baseline of the 45 and Up Study from New South Wales, Australia. Self-reported PA collected by questionnaire at baseline in 2006 was graded into low (ResultsIn the fully adjusted model, higher PA level was significantly associated with a lower risk of RPC incident (Cox-regression, p-value for trend = 0.002; medium vs. low, hazard ratio (HR) = 0.78, 95% Confidence Interval (CI): 0.61-0.98; high vs. low, HR = 0.61, 95%CI: 0.36-0.84. In addition, gender, body mass index, insulin treatment, family history of diabetes, history of cardiovascular disease were significant effect modifiers for the association between PA and RPC.ConclusionsHigher PA level was independently associated with a lower risk of DR progression among working-aged diabetic populations in this large cohort study.

Background: Determining the incidence, progression, and patterns of multimorbidity are important for the prevention, management, and treatment of concurrence of multiple conditions. This study aimed to analyze major multimorbidity patterns and the association of the onset of a primary condition or combinations of a primary and a secondary condition with the progression to subsequent conditions.Methods: We included 53,867 participants aged 45–64 years from the 45 and Up Study who were free of 10 predefined chronic conditions at baseline (2006–2009). The incidence of multimorbidity (coexistence of ≥2, ≥3, and ≥4 conditions) was identified using the claims database until December 31, 2016. The primary, secondary, tertiary, and quaternary condition for each participant was defined according to its temporal order of onset.Results: During a mean 9-years follow-up, the cumulative incidence of primary, secondary, tertiary, and quaternary conditions was 49.6, 23.7, 9.0, and 2.9%, respectively. The time to develop a subsequent condition decreased with the accumulation of conditions (P < 0.0001). Two concurrent cardiometabolic disorders (CMDs, 30.4%) and CMDs clustered with musculoskeletal disorders (15.2%), mental disorders (13.5%), asthma (12.0%), or cancer (8.7%) were the five most common multimorbidity patterns. CMDs tended to occur prior to mental or musculoskeletal disorders but after the onset of cancers or asthma. Compared with all participants who developed cancer as a primary condition, individuals who experienced mental disorders/neurodegenerative disorders and a comorbidity as cardiovascular disease, hypertension, dyslipidemia, diabetes, asthma, or osteoarthritis were 3.36–10.87 times more likely to develop cancer as a tertiary condition. Individuals with neurodegenerative disorders and a comorbidity as hypertension, dyslipidemia, osteoarthritis, or asthma were 5.14–14.15 times more likely to develop mental disorders as a tertiary condition.Conclusions: A high incidence of multimorbidity in middle-aged adults was observed and CMDs were most commonly seen in multimorbidity patterns. There may be accelerated aging after a primary condition occurs. Our findings also reveal a potential preventative window to obviate the development of secondary or tertiary conditions.

Background: Findings for associations between cardiorespiratory fitness (CRF) and cardiometabolic risk (CMR) factors are inconsistent, and the interactive association between CRF and fatness with CMR factors is unclear in children. Our study aimed to examine whether CRF and fatness are independently and interactively associated with CMR factors.Methods: We included 5,869 children aged 6–13 years in the analysis. Physical examinations, blood tests, and CRF were measured at baseline and 1 year later. Cardiometabolic risk score (CMRS) was computed by summing Z scores of waist circumference (WC), averaged systolic and diastolic blood pressure, glucose, high-density lipoprotein cholesterol (HDL-C, multiplied by −1), and triglycerides.Results: There was a high correlation between fatness and CRF in both boys and girls. High baseline CRF was independently associated with favorable changes in CMRS, BMI, WC, percent body fat (PBF), total cholesterol, LDL-C, and HDL-C (all P < 0.025). Improved CRF was independently associated with favorable changes in CMRS, BMI, WC, PBF, total cholesterol, LDL-C, HDL-C, triglycerides, and fasting glucose (all P < 0.0321). Baseline BMI was positively associated with changes in CMRS, WC, blood pressure, triglycerides, insulin, and HOMA-IR (all P < 0.0462). Low PBF at baseline was associated with favorable changes in CMRS, BMI, WC, blood pressure, HDL-C, triglycerides, insulin, and HOMA-IR (all P < 0.0423). The percentage of the total effect of baseline CRF on changes in CMRS, triglycerides, HDL-C, PBF, and WC mediated by baseline BMI was 66.0, 61.6, 40.3, 20.7, and 9.2%, respectively. Baseline CRF was a significant mediator for the association between baseline BMI and changes in CMRS (mediated by 4.3%), triglycerides (5.1%), and HDL-C (12.0%). An inverse association was found between baseline CRF and CMRS in children with high baseline BMI/PBF only. Improved CRF was associated with decreased BMI and WC in children with low baseline CRF.Conclusions: Fatness and CRF are each independently associated with changes in CMR factors. Fatness is a major mediator for the association between CRF and CMR factors, whereas the association between fatness and CMR factors is also mediated by CRF. The beneficial effect of high CRF on CMR factors was more evident in obese or unfit children.

Abstract Background Malleolar fracture, which is present in 37–53% of human ankle osteoarthritis (OA), is the most common type of fracture in the ankle joint. In spite of this, no rat animal model has been developed for this type of injury to date. Here, we established a rat ankle post-traumatic OA (PTOA) model induced by malleolar fracture; this model will be useful in ankle OA research. Methods Two-month-old male Sprague Dawley (SD) rats were randomized into 2 groups (n = 19 per group): 1) malleolus articular fracture, dislocation, and immediate reduction on the right joints and 2) malleolus articular fracture on the right ankle. The contralateral ankle joints were used as controls. The fracture and healing processes were confirmed and monitored by radiography. Changes in inflammation were monitored in vivo by fluorescence molecular tomography (FMT). Cartilage damage and changes in expression of OA-related genes were analyzed by histology, immunohistochemistry, Real-time quantitative PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA) at 8 weeks post-surgery. Results X-rays showed that all fractures were healed at 8 weeks post-surgery. A reproducible, mild to moderate degree of OA cartilage damage with reduced aggrecan was detected by histology in all animals in both groups but there was no significant difference between the two groups. Decreased Col-II and increased Col-X and MMP-13 levels were detected by qPCR, immunohistochemistry, ELISA and FMT from both groups cartilage. Conclusions Malleolus articular fracture alone induces ankle OA with lesions on the central weight bearing area of the tibiotalar joint in rats. This model will provide a reproducible and useful tool for researchers to study ankle OA.

Background: Identifying leading determinants for disease-free status may provide evidence for action priorities, which is imperative for public health with an expanding aged population worldwide. This study aimed to identify leading determinants, especially modifiable factors for disease-free status using machine learning methods.Methods: We included 52,036 participants aged 45–64 years from the 45 and Up Study who were free of 13 predefined chronic conditions at baseline (2006–2009). Disease-free status was defined as participants aging from 45–64 years at baseline to 55–75 years at the end of the follow-up (December 31, 2016) without developing any of the 13 chronic conditions. We used machine learning methods to evaluate the importance of 40 potential predictors and analyzed the association between the number of leading modifiable healthy factors and disease-free status.Results: Disease-free status was found in about half of both men and women during a mean 9-year follow-up. The five most common leading predictors were body mass index (6.4–9.5% of total variance), self-rated health (5.2–8.2%), self-rated quality of life (4.1–6.8%), red meat intake (4.5–6.5%), and chicken intake (4.5–5.9%) in both genders. Modifiable behavioral factors including body mass index, diets, smoking, alcohol consumption, and physical activity, contributed to 37.2–40.3% of total variance. Participants having six or more modifiable health factors were 1.63–8.76 times more likely to remain disease-free status and had 0.60–2.49 more disease-free years (out of 9-year follow-up) than those having two or fewer. Non-behavioral factors including low levels of education and income and high relative socioeconomic disadvantage, were leading risk factors for disease-free status.Conclusions: Body mass index, diets, smoking, alcohol consumption, and physical activity are key factors for disease-free status promotion. Individuals with low socioeconomic status are more in need of care.

ObjectiveTo determine whether educational level and overweight/obesity was associated with the development of diabetes among Chinese adult men and women.MethodsA cohort (2000-2011) of 10 704 participants aged 18-59 years (8 238 men, 2 466 women) in Qingdao Port Health Study (QPHS) were recruited in this study. The personal lifestyle, height, weight, waist circumference, resting heart rate, blood pressure, fasting blood glucose, total cholesterol, triglycerides and plasma uric acid were collected annually in a comprehensive health checkup program. Cox proportional hazards regression models were used to estimate the association of factors and incidence of diabetes.ResultsDuring 110 825 person-years of follow-up, 1 056 new onset cases (9.5 per 1 000 person-years) of diabetes were identified. With normal weight as reference, the multiple-adjusted hazard ratio (HR) (95%CI) of diabetes was 1.69(1.38-2.09) for overweight and 2.24(1.66-3.02) for obesity among men, which was 1.81(1.12-2.92) and 2.58(1.37-4.86) among women, respectively. Compared with the participants with high educational level, those with low educational level had a higher risk of diabetes (multiple-adjusted HR (95%CI): 1.43(1.11-1.86)) among men. The association was not found among women and the adjusted HR (95%CI) of diabetes was 1.56(0.89-2.76). The increased risks of low educational level were independent of mediators among men, through normal weight (P for trend = 0.0313) and overweight (P for trend = 0.0212) group but not obesity group (P for trend = 0.0957).ConclusionBaseline overweight/obesity was an independent risk factor for diabetes for both men and women. Low educational level was adversely associated with incidence of diabetes through normal weight, overweight and obesity groups, with the association being substantially attenuated by mediating factors only in the obesity group among men. The association was not found among women.

BackgroundThe association of dietary pattern with chronic diseases has been investigated widely in western countries. However, information is quite limited among children in China. Our study is aimed to identify the dietary patterns of Chinese children and examine their association with obesity and related cardiometabolic risk factors.MethodsA total of 5267 children were selected using multistage random sampling from 30 primary schools of 5 provincial capital cities in China. Dietary intake was derived from 24 hour dietary recall for three consecutive days. Anthropometric measurements, glucose and lipid profiles were obtained. Factor analysis combined with cluster analysis was used for identifying major dietary patterns. The associations of dietary patterns with obesity and related cardiometabolic risk factors were examined by logistic regression analysis.ResultsThree mutually exclusive dietary patterns were identified, which were labeled as the healthy dietary pattern, the transitive dietary pattern, and the Western dietary pattern. Compared with children of the healthy dietary pattern, the multiple-adjusted odds ratios (95% confidence interval (CI)) of obesity were 1.11 (0.89-1.38) for children with the transitive dietary pattern and 1.80 (1.15-2.81) for children with the Western dietary pattern, which was 1.31 (95%CI 1.09-1.56) and 1.71 (95%CI: 1.13-2.56), respectively, for abdominal obesity. The Western dietary pattern was associated with significantly higher concentrations of low-density lipoprotein cholesterol (PConclusionsThe Western dietary pattern characterized by red meat, eggs, refined grain and products, was positively associated with odds of obesity, the levels of plasma glucose, low-density lipoprotein cholesterol and triglycerides, and was inversely associated with the level of high-density lipoprotein cholesterol.

Objective. To investigate the association of weight status with physical fitness among Chinese children. Methods. A total of 6929 children aged 6–12 years were selected from 15 primary schools of 5 provincial capital cities in eastern China. The height and fasting body weight were measured. The age-, sex-specific BMI WHO criteria was used to define underweight, overweight and obesity. Physical fitness parameters including standing broad jump, 50 m sprint, and 50 m∗8 shuttle run were tested. Results. The prevalence of underweight, overweight, and obesity was 3.1%, 14.9%, and 7.8%, respectively. Boys performed better than girls, and the older children performed better than their younger counterparts for all physical fitness tests. No significant difference in all three physical fitness tests were found between children with underweight and with normal weight, and they both performed better than their counterparts with overweight and obese in all three physical fitness tests. The likelihood of achieving good performance was much lower among overweight and obese children in comparison with their counterparts with normal weight (OR=0.13–0.54). Conclusions. An inverse association of obesity with cardiorespiratory fitness, muscle explosive strength, and speed was identified among Chinese children.