Contributing ocular comorbidity to end-of-life visual acuity in medically treated glaucoma patients, ocular hypertension and glaucoma suspect patients

Mokhles, Palwasha; Gorcom, Luuk van; Schouten, Jan S. A. G.; Berendschot, Tos T. J. M.; Beckers, Henny J. M.; Webers, Carroll A.B.

doi:10.1038/s41433-020-0991-0

Cited by 7 publications

(8 citation statements)

References 28 publications

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“…To get a visual and more confident observation, we have constructed a high-confidence multimorbidity network comprised of multimorbidities with RR > 15 (Fig. 1 d) and observed small and large clusters of multimorbidities affecting the same physiological systems, many of which are supported by previous studies—for examples, multimorbidity clusters affecting the “Cardiovascular” [ 40 ], the “Ophthalmological” [ 41 ], the “Ear, Nose, Throat” [ 42 ], and the “Psychiatric” [ 43 ] categories. These findings suggest the existence of shared mechanisms for diseases affecting the same physiological systems.…”

Section: Resultssupporting

confidence: 65%

A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank

et al. 2021

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Background Multimorbidities greatly increase the global health burdens, but the landscapes of their genetic risks have not been systematically investigated. Methods We used the hospital inpatient data of 385,335 patients in the UK Biobank to investigate the multimorbid relations among 439 common diseases. Post-GWAS analyses were performed to identify multimorbidity shared genetic risks at the genomic loci, network, as well as overall genetic architecture levels. We conducted network decomposition for the networks of genetically interpretable multimorbidities to detect the hub diseases and the involved molecules and functions in each module. Results In total, 11,285 multimorbidities among 439 common diseases were identified, and 46% of them were genetically interpretable at the loci, network, or overall genetic architecture levels. Multimorbidities affecting the same and different physiological systems displayed different patterns of the shared genetic components, with the former more likely to share loci-level genetic components while the latter more likely to share network-level genetic components. Moreover, both the loci- and network-level genetic components shared by multimorbidities converged on cell immunity, protein metabolism, and gene silencing. Furthermore, we found that the genetically interpretable multimorbidities tend to form network modules, mediated by hub diseases and featuring physiological categories. Finally, we showcased how hub diseases mediating the multimorbidity modules could help provide useful insights for the genetic contributors of multimorbidities. Conclusions Our results provide a systematic resource for understanding the genetic predispositions of multimorbidities and indicate that hub diseases and converged molecules and functions may be the key for treating multimorbidities. We have created an online database that facilitates researchers and physicians to browse, search, or download these multimorbidities (https://multimorbidity.comp-sysbio.org).

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Section: Resultssupporting

confidence: 65%

A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank

et al. 2021

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“…While this study did not verify the participants' incomes, if indeed 46% of those sampled had no income and 15.73% had an annual income of not more than SAR 8,673.19, keratoconus potentially has debilitating economic effects on the patients. Unlike Godefrooij et al [4], this study's findings show that the expenditure is a positive function of the disease duration, possibly because the costs depend on the quality of treatment/care and whether or not such treatments stem the progression of the condition [27].…”

Section: Keratoconus Expenditurecontrasting

confidence: 78%

The Lifetime Expenditure in People with Keratoconus in Saudi Arabia

Al-Atawi¹,

Ali²,

Alzahrani³

2023

Preprint

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Aim: This study measures and evaluates the socioeconomic burden of people living with keratoconus in Saudi Arabia. Methods: The study employed a cross-sectional design, a Keratoconus Economic Burden Questionnaire, and a convenient sample of 89 keratoconus patients (58.4% male) drawn from multiple regions in Saudi Arabia. It was conducted using online surveys and the data was analysed using appropriate quantitative techniques. Results: The mean age and annual income of participants were 33.24 years and Saudi Riyal (SAR) 33,505.6180 (SD=62,215.29), respectively, with only 37% being employed for wages. Up to 94.4% needed glasses or contact lenses at least once a week and 73.0% received care from optometrists. The condition forced 45.9% of the respondents to change careers or leisure activities, with a further 51.3% having to take time off work. The mean annual out-of-pocket expenses for buying and maintaining glasses or contact lenses as well as traveling and accommodation for keratoconus-related treatment were SAR 8,673.19 (SD=11,307.73), with 48.32 incurring upwards of SAR 12,000 over the period. The treatment costs increased with disease duration, r(89) = .216, p < .05. Regression results show that the existence of comorbid eye disease, changing glasses at least once a year, and wearing either glasses or contact lenses at least once a week individually have statistically significant, negative effects on the total annual keratoconus treatment costs, while disease duration, utilisation of optometrists, and taking time off had a statistically significant increase on the total cost (p<.05). Conclusion: With a prevalence rate of 1 in 375, progressive debilitation, and the lifetime nature of the disease, keratoconus is a critical public health concern in Saudi Arabia. The resulting visual impairment and discomfort as well as both direct and indirect economic burdens have considerable impacts on the patient's quality of life.

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“…To get a visual and more confident observation, we construct a high-confidence comorbidity network comprised of comorbidities with RR>15 (Fig. 1e), and are able to observe small and large clusters of comorbidities affecting the same physiological system, many of which are supported by previous studies ⍰ for examples, comorbidity clusters affecting the “Cardiovascular” [39], the “Ophthalmological” [40], the “Ear, Nose, Throat” [41], and the “Psychiatric” [42] categories. These findings suggest shared mechanisms for diseases affecting the same physiological systems.…”

Section: Resultsmentioning

confidence: 65%

A global overview of genetically interpretable comorbidities among common diseases in UK Biobank

Dong

Feng

Sun

et al. 2021

Preprint

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BackgroundComorbidities greatly increase global health burdens, but the landscapes of their genetic factors have not been systematically investigated.MethodsWe used the hospital inpatient data of 385,335 patients in UK Biobank to investigate the comorbid relations among 439 common diseases. Post-GWAS analyses were performed to identify comorbidity shared genetic risks at the genomic loci, network, as well as overall genetic architecture levels. We conducted network decomposition for interpretable comorbidity networks to detect the hub diseases and the involved molecules in comorbidity modules.Results11,285 comorbidities among 439 common diseases were identified, and 46% of them were genetically interpretable at the loci, network, or overall genetic architecture level. The comorbidities affecting the same and different physiological systems showed different patterns at the shared genetic components, with the former more likely to share loci-level genetic components while the latter more likely to share network-level genetic components. Moreover, both the loci- and network-level genetic components shared by comorbidities mainly converged on cell immunity, protein metabolism, and gene silencing. Furthermore, we found that the genetically interpretable comorbidities tend to form network modules, mediated by hub diseases and featuring physiological categories. Finally, we showcased how hub diseases mediating the comorbidity modules could help provide useful insights into the genetic contributors for comorbiditities.ConclusionsOur results provide a systematic resource for understanding the genetic predispositions of comorbidity, and indicate that hub diseases and converged molecules and functions may be the key for treating comorbidity. We have created an online database to facilitate researchers and physicians to browse, search or download these comorbidities (https://comorbidity.comp-sysbio.org).

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Contributing ocular comorbidity to end-of-life visual acuity in medically treated glaucoma patients, ocular hypertension and glaucoma suspect patients

Cited by 7 publications

References 28 publications

A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank

A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank

The Lifetime Expenditure in People with Keratoconus in Saudi Arabia

A global overview of genetically interpretable comorbidities among common diseases in UK Biobank

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