Ophthalmology (Eye & Ear Hospital) - Research Publications

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    Retinal age gap as a predictive biomarker of stroke risk
    Zhu, Z ; Hu, W ; Chen, R ; Xiong, R ; Wang, W ; Shang, X ; Chen, Y ; Kiburg, K ; Shi, D ; He, S ; Huang, Y ; Zhang, X ; Tang, S ; Zeng, J ; Yu, H ; Yang, X ; He, M (BMC, 2022-11-30)
    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.
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    Association between dual sensory impairment and risk of mortality: a cohort study from the UK Biobank (vol 22, 631, 2022)
    Zhang, X ; Wang, Y ; Wang, W ; Hu, W ; Shang, X ; Liao, H ; Chen, Y ; Kiburg, KV ; Huang, Y ; Zhang, X ; Tang, S ; Yu, H ; Yang, X ; He, M ; Zhu, Z (BMC, 2022-08-26)
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    Plasma metabolomic profiles of dementia: a prospective study of 110,655 participants in the UK Biobank
    Zhang, X ; Hu, W ; Wang, Y ; Wang, W ; Liao, H ; Zhang, X ; Kiburg, K ; Shang, X ; Bulloch, G ; Huang, Y ; Zhang, X ; Tang, S ; Hu, Y ; Yu, H ; Yang, X ; He, M ; Zhu, Z (BMC, 2022-08-15)
    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.
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    Association between dual sensory impairment and risk of mortality: a cohort study from the UK Biobank
    Zhang, X ; Wang, Y ; Wang, W ; Hu, W ; Shang, X ; Liao, H ; Chen, Y ; Kiburg, KV ; Huang, Y ; Zhang, X ; Tang, S ; Yu, H ; Yang, X ; He, M ; Zhu, Z (BMC, 2022-08-01)
    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.
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    Association of Visual, Hearing, and Dual Sensory Impairment With Incident Dementia
    Hu, W ; Wang, Y ; Wang, W ; Zhang, X ; Shang, X ; Liao, H ; Chen, Y ; Huang, Y ; Zhang, X ; Tang, S ; Yu, H ; Yang, X ; He, M ; Zhu, Z (FRONTIERS MEDIA SA, 2022-06-14)
    INTRODUCTION: The 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. METHODS: The 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. RESULTS: Among 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. CONCLUSIONS: Visual, 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.
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    Retinal age gap as a predictive biomarker of future risk of Parkinson's disease
    Hu, W ; Wang, W ; Wang, Y ; Chen, Y ; Shang, X ; Liao, H ; Huang, Y ; Bulloch, G ; Zhang, S ; Kiburg, K ; Zhang, X ; Tang, S ; Yu, H ; Yang, X ; He, M ; Zhu, Z (OXFORD UNIV PRESS, 2022-03-01)
    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.
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    Association of visual impairment with risk for future Parkinson's disease
    Zhu, Z ; Hu, W ; Liao, H ; Tan, Z ; Chen, Y ; Shi, D ; Shang, X ; Zhang, X ; Huang, Y ; Yu, H ; Wang, W ; He, M ; Yang, X (ELSEVIER, 2021-12)
    BACKGROUND: Although visual dysfunction is one of the most common non-motor symptoms among patients with Parkinson's disease (PD), it is not known whether visual impairment (VI) predates the onset of clinical PD. Therefore, we aim to examine the association of VI with the future development of PD in the UK Biobank Study. METHODS: The UK Biobank Study is one of the largest cohort studies of health, enrolling over 500,000 participants aged 40-69 years between 2006 and 2010 across the UK. VI was defined as a habitual distance visual acuity (VA) worse than 0·3 logarithm of the minimum angle of resolution (LogMAR) in the better-seeing eye. Incident cases of PD were determined by self report data, hospital admission records or death records, whichever came first. Multivariable Cox proportional hazard regression models were used to investigate the association between VI and the risk of incident PD. FINDINGS: A total of 117,050 participants were free of PD at the baseline assessment. During the median observation period of 5·96 (IQR: 5·77-6·23) years, PD occurred in 222 (0·19%) participants. Visually impaired participants were at a higher risk of developing PD than non-VI participants (p < 0·001). Compared with the non-VI group, the adjusted hazard ratio was 2·28 (95% CI 1·29-4·05, p = 0·005) in the VI group. These results were consistent in the sensitivity analysis, where incident PD cases diagnosed within one year after the baseline assessment were excluded. INTERPRETATION: This cohort study found that VI was associated with an increased risk of incident PD, suggesting that VI may serve as a modifiable risk factor for prevention of future PD.