The visual health of children diagnosed with developmental disabilities has received limited attention, partly due to the intricate nature of their conditions. This study aims to clarify the associations between developmental disabilities and ocular disorders, exploring both correlations and potential causal relationships, to emphasize the importance of providing focused ocular attention for these children. This 3-year cross-sectional study included 13,889 students (309 with developmental disorders). Refractive errors were compared between those with and without developmental disorders. Mendelian randomization established genetic causal links between developmental and visual disorders. GWAS of brain MRI data identified shared regions influencing both conditions. Developmental disabilities were significantly associated with higher prevalence (OR 1.846, 95% CI 1.418–2.404, p < 0.001) and severity (OR 3.137, 95% CI 2.399–4.103, p < 0.001) of astigmatism. An in-depth analysis of genetic factors consistently emphasizes cognitive, perceptual, emotional, and behavioral disparities, as substantial determinant for the risk of astigmatism (OR 1.057, 95% CI 1.019 to 1.096, p = 0.003). Furthermore, an array of developmental disorders emerges as contributory elements to the development of cataracts, retinal diseases, and glaucoma. Importantly, the TBSS L2 retrolenticular part of the internal capsule and SWI T2 star caudate concomitantly correlates with both developmental disabilities and ocular pathologies. Children with developmental disabilities have a higher risk of developing ocular conditions. Early and comprehensive ophthalmological assessment by a multidisciplinary team is essential to promote optimal visual outcomes and quality of life for these children.
In recent decades, advancements in neonatal intensive care unit (NICU) technology have significantly improved the survival rates of preterm and extremely low birth weight (ELBW) infants. In the United States, approximately 500,000 infants, constituting 12% of all live births, are born prematurely each year. Globally, a staggering 15 million babies, representing 5–18% of all births, are delivered preterm annually (Howson et al., 2013; McCabe et al., 2014; Neel et al., 2019). Although survival rates for ELBW infants have risen since the 1990s, the prevalence of developmental disabilities among these infants remains a significant concern (Doyle & Victorian Infant Collaborative Study Group, 2004; Spittle & Orton, 2014). Studies indicate that up to 50% of ELBW infants develop developmental disabilities, including motor, cognitive, or behavioral disorders, such as delayed language skills, fine motor disorders, dysexecutive syndrome, autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), and learning difficulties (Juul & Ferriero, 2014; O’Shea et al., 2009; Petrou et al., 2019; Schendel & Bhasin, 2008; Taylor & Clark, 2016). Additionally, cerebral palsy (CP) is observed in 5 to 15% of these children (Hee Chung et al., 2020; Petrou et al., 2019). Current small-scale vision screening studies conducted in different regions have revealed that children with developmental disorders are more prone to experiencing visual acuity and visual disorders such as refractive errors, strabismus, nystagmus, and cataracts. Remarkably, up to 86% of children with intellectual disabilities (IDs) present with oculo-visual disorders (Dowdeswell et al., 1995; Nielsen et al., 2007; Sasmal et al., 2011). Specifically, in the eastern part of Taiwan, China, common ocular disorders in children with developmental disabilities include strabismus (14.9%), nystagmus (9.1%), and cataract (1.7%) (Nielsen al., 2007). Another study (Ikeda et al., 2013), focusing on children with ASD from Cardinal Glennon Children’s Medical Center, reported the highest prevalence of various ocular disorders. Among them, astigmatism exhibited the highest prevalence, followed by strabismus and amblyopia. Importantly, similar findings have been observed in other regions as well (Choi et al., 2022a, 2022b; Kabatas et al., 2015).
These scattered small-scale research studies (Choi et al., 2022a, 2022b; Chen al., 2023; Kabatas et al., 2015) highlight the urgent need for further attention and comprehensive examination of ocular disorders in children with developmental disabilities. However, children with developmental disorders may have different behavioral patterns and face unique challenges in their daily lives (Mantri-Langeveldt et al., 2019). Establishing a causal relationship between developmental disorders and ocular disorders in the absence of fully excluding the influence of other underlying factors can be challenging. Moreover, due to objective constraints, such as difficulties in obtaining optimal cooperation or the limited ability of these children to effectively communicate their experiences, conducting extensive examinations for this population is often challenging. Considering these constraints, this current investigation expands on cross-sectional data analysis and utilizes Mendelian randomization analysis to genetically unravel the association between developmental disabilities and ocular and visual anomalies. By leveraging genetic data, this approach can provide insights into the potential causal relationships and underlying mechanisms linking developmental disabilities and ocular disorders. We hypothesize that there are significant associations between developmental disabilities and ocular and visual anomalies, with shared abnormal brain region signals potentially contributing to the co-occurrence of these two conditions. The findings may inform targeted screening efforts and early intervention strategies, facilitating timely and tailored support for affected children, ultimately aiming to enhance the overall well-being and quality of life of children with developmental disabilities.
Methods
Cross-Sectional Association Study
The study emanated from the “Investigation on Visual Habits and Eye Health among Primary and Secondary School Students in Tianjin Project”. The sample for this study was drawn from annual campus vision census records spanning from 2021 to 2023. Each year, the sample consisted of 3 special education schools and 10 randomly selected regular education schools. The sample size was determined by including all students from the accessible special education schools in the region, ensuring a comprehensive representation of students with developmental disabilities. To provide a sufficient comparison group, a control group of regular education schools was included at a ratio greater than 1:3. The final sample comprised 309 students with developmental disabilities out of 13,889 total participants, representing 2.22% of the study population. This proportion falls within the global estimated range of developmental disabilities prevalence among children, which is 0.22–7.10% (Olusanya et al., 2023), indicating that the sample is representative of the general population. In 2021, the cohort comprised 84 students with definite developmental disabilities (specifically, individuals with a confirmed diagnosis of intellectual developmental disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, specific learning disorder, developmental coordination disorder, communication disorders, cerebral palsy, fetal alcohol spectrum disorders, genetic and chromosomal disorders with developmental consequences, or epilepsy-related developmental disabilities) and 4,067 typically developing students. The subsequent year, 2022, witnessed 118 students with developmental disabilities and 6341 typically developing students. In 2023, the cohort encompassed 107 students with developmental disabilities and 4961 typically developing students. A total of 13,889 participants were eventually included in the study. The meticulous visual acuity evaluations were administered by ophthalmologists from Tianjin Eye Hospital’s Optometry Center. This encompassed assessments of distance visual acuity and Computerized Optometry, performed without ciliary muscle paralysis. In this study, astigmatism was identified as a cylinder measurement of ≥ 0.75 diopters (D) in either eye, myopia was characterized by a spherical equivalent refraction (SER) of ≤ -0.50D in either eye, and hyperopia was discerned by a SER of ≥ + 2.00 D in either eye (Sandhu et al., 2012; Jiang et al., 2019). The study workflow, sample size, and the handling of missing values are illustrated in Supplementary Fig. 1A. The analytical methodology proceeded through the following steps: (1) Distinct refractive errors were analyzed in cohorts with developmental disabilities and typically developing peers across three years, utilizing three cross-sectional assessments; Nonparametric tests were thoughtfully employed due to non-normal data distribution, elucidating differences between the groups; (2) Investigation of the association between developmental disorders and astigmatism was conducted using a generalized mixed linear model; (3) Additionally, a stratified analysis by age and gender was conducted.
Mendelian Randomization Analysis
In the context of a two-sample Mendelian randomization (MR) study, publicly available genome-wide association studies (GWASs) were employed as the primary data source. Rigorous measures were taken to ensure the distinct origins of GWAS datasets for the exposure and outcome factors from separate but congruent racial populations, as expounded in Supplementary Table 1. The analytical framework, depicted in Supplementary Fig. 1B, encompassed two core components: (1) Genetic Association between Developmental Disabilities and Ocular Parameters: This entailed the identification of genetic associations between developmental disabilities and ocular parameters along with visual disorders; (2) Shared Regions of Developmental Disabilities and Ocular Disorders: This facet involved the identification of genomic regions exerting joint influences on both developmental disabilities and ocular disorders, executed through the screening of brain MRI GWAS data.
The procedural delineation for each analysis was as follows ( Bowden et al., 2016; Hirschhorn & Daly, 2005; Hemani et al., 2017; Verbanck et al., 2018): (1) Instrumental Variable Selection: Single nucleotide polymorphisms (SNPs) demonstrating significant associations with the exposure factors were pinpointed as instrumental variables (IVs), abiding by predetermined thresholds (p < 5 × 10− 8, R2 < 0.001, window size = 10000 kb). Adjustments to the instrumental variable selection thresholds were implemented for several exposure factors owing to the limited number of available IVs (Thresholds: p < 5 × 10− 6, R2 < 0.001, window size = 10000 kb), barring SWI T2 star left caudate plus right caudate (p < 5 × 10− 8, R2 < 0.001, window size = 10000 kb); (2) Confounding Factor Assessment: Ensuring independence from confounding factors including age, sex, and other pertinent diseases, was accomplished via tests conducted using the PhenoScanner website (http://www.phenoscanner.medschl.cam.ac.uk/); (3) Weak Instrumental Variable Bias Evaluation: The F-value was employed to assess potential weak instrumental variable bias, ensuring F > 10 for included instrumental variables. F was calculated using the formula: F = (N - K − 1) / K * R2 / (1 - R2); (4) MR Analysis Approaches: The core MR analysis hinged predominantly upon the inverse variance weighting (IVW) method. Supplementary methods, including combined MR-Egger regression, weighted median estimator (WME), and weighted model, were also integrated; (5) Sensitivity and Heterogeneity Analysis: Cochran’s Q-test evaluated heterogeneity between individual SNP estimates, guiding the selection of appropriate analytical methods. IVW was employed as the primary method if p < 0.05 indicated no heterogeneity. The MR-Egger intercept method assessed the horizontal pleiotropy of IVs; if p < 0.05, IVW estimates might be biased. The MR-Polytomial Residuals and Outliers (MR-PRESSO) method identified and eliminated outliers to yield corrected MR estimates; (6) Results Consistency and Stability: Scatter plots gauged the congruence of results trends across various analytical methods, accompanied by leave-one-out sensitivity tests to affirm result stability.
Ethical Approval
Ethical Approval from the Ethics Committee of Tianjin Eye Hospital was obtained for a cross-sectional analysis with a waiver of informed consent (KY-2023045). This study scrupulously adhered to the principles outlined in the Declaration of Helsinki. Furthermore, the study was conducted in alignment with the reporting standards articulated in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) reporting guidelines.
Analysis Tools
All statistical analyses for this study were executed employing R software, version 4.2.2 (R Foundation for Statistical Computing). MR analyses were performed using the R package TwoSampleMR (version 0.4.23) and MR-PRESSO (version 1.0).
Results
Association Between Developmental Disabilities and Astigmatism
In this cross-sectional data analysis covering the period from 2021 to 2023, a consistent pattern emerged indicating a higher prevalence of astigmatism among students with developmental disabilities in comparison to their typically developing peers over the three-year span (69.05% vs. 67.10%, 74.58% vs. 68.86%, 77.57% vs. 66.35%, respectively; see Fig. 1A). Conversely, there were no analogous trends observed for other refractive errors (refer to Supplementary Fig. 2). Among those affected by astigmatism, individuals with developmental disabilities displayed greater magnitudes of astigmatism cylinder in comparison to their typically developing counterparts (median: 1.75D vs. 1.25D, p = 0.009; 2.125D vs. 1D, p < 0.001; 1.75D vs. 1.25D, p < 0.001), signifying a heightened severity of astigmatism within the developmental disabilities group relative to the normal group (refer to Fig. 1B).
Fig. 1
Prevalence and severity of astigmatism in children and adolescents with and without developmental disabilities. A Prevalence of astigmatism; B Severity of astigmatism
To gain deeper insights into the nexus between developmental disabilities and astigmatism, the populace was stratified into groups with astigmatism and without astigmatism. Non-parametric tests unveiled noteworthy distinctions between the two categories in terms of age (p < 0.001), sex (p < 0.001), spherical power (p < 0.001), and developmental status (p = 0.008) (see Supplementary Table 2). Consequently, the generalized mixed linear model was employed, with adjustments for age, sex, and spherical power, for the analysis of the relationship between developmental disabilities and astigmatism.
Initially, a positive correlation between developmental disabilities and astigmatism was evident (OR 1.414, 95% CI 1.093–1.828, p = 0.008). This positive correlation endured even after adjusted the potential influence of age, gender, and spherical power (OR 1.846, 95% CI 1.418–2.404, p < 0.001). Upon scrutinizing the interrelation between developmental disabilities and the severity of astigmatism using a generalized mixed linear model, a positive correlation was discerned, indicative of an augmented degree of astigmatism among those with developmental disabilities (OR 2.972, 95% CI 2.272–3.888, p < 0.001). Following thorough adjustments for age, sex, and spherical power, this affirmative correlation endured (OR 3.137, 95% CI 2.399–4.103, p < 0.001) (see Table 1). The consistent association between developmental disabilities and astigmatism held true even in stratified analyses conducted among children and adolescents (see Fig. 2). Moreover, in sex-stratified analyses, the association between developmental disability and both the prevalence and severity of astigmatism exhibited a stronger magnitude in females compared to males (prevalence of astigmatism: female [OR 2.972, 95% CI 2.272–3.888, p < 0.001] vs. male [OR 1.712, 95% CI 1.232–2.378, p < 0.001]; severity of astigmatism: female [OR 3.522, 95% CI 2.244–5.527, p < 0.001] vs. male [OR 2.939, 95% CI 2.105–4.104, p < 0.001]).
Table 1
Factors associated with astigmatism
Characteristics
Crude
Adjusted
OR (95%CI)
p-value
OR (95%CI)
p-value
A. Associated with astigmatism occurrence
Age1
1.097 (1.082–1.113)
< 0.001
1.046 (1.030–1.062)
< 0.001
Sex2
0.791 (0.737–0.850)
< 0.001
0.733 (0.681–0.789)
< 0.001
Spherical power3
0.849 (0.836–0.863)
< 0.001
0.855 (0.840–0.871)
< 0.001
Developmental disabilities4
1.414 (1.093–1.828)
0.008
1.846 (1.418–2.404)
< 0.001
B. Associated with astigmatism severity
Age
1.010 (1.001–1.019)
0.029
0.999 (0.989–1.009)
0.88
Sex
0.948 (0.910–0.988)
0.011
0.942 (0.904–0.981)
0.004
Spherical power
0.979 (0.969–0.988)
< 0.001
0.969 (0.959–0.980)
< 0.001
Developmental disabilities
2.972 (2.272–3.888)
< 0.001
3.137 (2.399–4.103)
< 0.001
1Adjusted OR accounting for age: adjusted for covariates including sex, spherical power and developmental disabilities
2Adjusted OR accounting for sex: adjusted for covariates including age, spherical power and developmental disabilities
3Adjusted OR accounting for spherical powe: adjusted for covariates including age, sex and developmental disabilities
4Adjusted OR accounting for developmental disabilities: adjusted for covariates including age, sex and spherical power
Fig. 2
Correlation between developmental disabilities and astigmatism in pediatric and adolescent populations, including gender-based variations. A Relationships among children and adolescents, respectively; B Relationships among gender-specific populations
Developmental Disabilities’ Influence on Ocular Refraction
Multiple developmental disabilities were linked to ocular refraction outcomes through two-sample Mendelian randomization, suggesting a potential causal relationship. Genetically predicted cognitive, perceptual, emotional, or behavioral differences posed a risk for astigmatism (OR 1.057, 95% CI 1.019–1.096, p = 0.003), with ASD elevating the risk by up to 1.010-fold (OR 1.010, 95% CI 1.001–1.018, p = 0.038). Additionally, ADHD emerged as a risk factor for hyperopia (OR 1.008, 95% CI 1.001–1.016, p = 0.020). Beyond elevating refractive error risks, developmental disabilities displayed correlations with ocular parameters. Motor disorders, mixed disorders of conduct and emotions, wide developmental disorders, disorders of scholastic skills, ADHD, and ASD each influenced corneal-related biometric parameters. Specifically, disorders of scholastic skills (p = 0.023) and ASD (p = 0.020) had discernible impacts on corneal astigmatism angles, as depicted in Fig. 3.
Fig. 3
Genetic causal links between developmental disabilities and ocular parameters, alongside visual disorders
Elevated Vulnerability to Ocular Disorders Due to Developmental Disabilities
In the context of MR examining genetic causal relationships between developmental disabilities and visual disorders (refer to Fig. 3), cognitive, perceptual, emotional, or behavioral differences heightened the susceptibility to cataract (OR 1.012, 95% CI 1.003 to 1.022, p = 0.003). Individuals with specific developmental disorders of motor function exhibited a 1.002-fold increased likelihood of requiring eye surgery (OR 1.002, 95% CI 1.001 to 1.004, p = 0.020). Moreover, wide developmental disorders amplified the risk of retinal diseases, with genetically predicted wide developmental disorders elevating the incidence of retinal detachment by 1.001-fold (OR 1.001, 95% CI 1.000 to 1.001, p = 0.001). Additionally, ADHD emerged as a risk factor for glaucoma (OR 1.003, 95% CI 1.001 to 1.005, p = 0.010).
Potential Causal Relationships
Having established the link between developmental disabilities and visual disorders, we proceeded to explore potential intrinsic connections. To this end, we conducted a screening of GWAS utilizing brain MRIs from the UKBiobank database, aiming to identify shared regions implicated in both disorders. The findings revealed (see Fig. 4) a concurrent association between genetically predicted enhancement of “TBSS L2 Retrolenticular part of the internal capsule” and “SWI T2 star left caudate plus right caudate” signals with the co-occurrence of developmental disabilities and ocular disorders. Specifically, a unit increase in TBSS L2 Retrolenticular part of internal capsule signal was linked to a 1.291-fold elevation in the likelihood of personality and behavioral disorders resulting from brain disease, damage, or dysfunction (OR 1.291, 95% CI 1.021 to 1.632, p = 0.033). Similarly, the presence of mixed disorders of conduct and emotions, as well as ASD, saw a corresponding 1.291-fold increase (OR 1.291, 95% CI 1.021 to 1.632, p = 0.033). Moreover, the risk of ASD increased by 1.307-fold (OR 1.307, 95% CI 1.006 to 1.697, p = 0.045). Concomitantly, there was a 1.268-fold elevated risk of astigmatism (OR 1.268, 95% CI 1.095 to 1.469, p = 0.002) and a 1.549-fold increased risk of secondary glaucoma (OR 1.549, 95% CI 1.041 to 2.304, p = 0.031).
Fig. 4
Common dMRI of brain alterations in developmental disabilities and ocular diseases. A IDP dMRI TBSS L2 Retrolenticular part of internal capsule; B SWI T2 star left caudate plus right caudate
Likewise, a one-unit enhancement in SWI T2 star left caudate plus right caudate signal exhibited a 1.044-fold rise in the probability of encountering symptoms and signs encompassing cognition, perception, emotional state, and behavior (OR 1.044, 95% CI 1.002 to 1.087, p = 0.039). This enhancement also corresponded to an escalated risk for the presence of astigmatism (p = 0.049), paralytic strabismus (p = 0.008), and disorders of the eyelid (p = 0.018).
Complete sensitivity analysis results for Mendelian randomization are presented in Supplementary Table 3. Supplementary Fig. 3 displays scatter plots illustrating causal trends across four analytical methods in MR analysis. Additionally, Supplementary Fig. 4 depicts leave-one-out plots for the causal association in MR analysis.
Discussion
Initial epidemiological evidence from limited samples of children with developmental disabilities has hinted at potential divergences in visual characteristics compared to their typically developing counterparts. This study establishes a correlation and explores the potential causal relationship between developmental disability disorders and ocular disorders, leveraging comprehensive analyses of survey data and genetic insights from GWAS databases. The cross-sectional analysis unequivocally affirms that developmental disability disorders bear a heightened association with an increased risk of astigmatism, while the Mendelian randomization analysis provides evidence for a potential causal link. The cross-sectional study establishes the correlation between developmental disabilities and astigmatism, laying the foundation for further investigation into causality. By examining the association at a single point in time, the cross-sectional design effectively captures the prevalence of astigmatism among individuals with developmental disabilities compared to those without, thereby highlighting the increased risk. On the other hand, the Mendelian randomization analysis leverages genetic variants as instrumental variables to assess the causal relationship between developmental disabilities and astigmatism. By utilizing genetic markers that are associated with developmental disabilities but not directly related to astigmatism, this approach minimizes confounding factors and reverse causation, thus strengthening the inference of causality (Hemani et al., 2017). Genetically forecasted cognitive, perceptual, emotional, or behavioral differences elevate the risk of astigmatism by 1.057-fold, with ASD specifically accentuating a 1.010-fold rise. Additionally, disorders of scholastic skills and ASD distinctly influence corneal astigmatism angles. Impressively, a significant proportion (40%) of these children with developmental disabilities have never undergone eye assessments, and alarmingly, 95% of those with clinically significant refractive differences lack corrective measures (Puri et al., 2015). These findings underscore an acute need for tailored, enhanced vision care strategies catering to the unique needs of these children, with a profound impact on their quality of life and educational journey.
Perinatal adversity emerges as a salient determinant of visual impairment, encompassing elements like prematurity, unfavorable neonatal conditions, and neurological insults (Choi et al., 2022a, 2022b; Eken et al., 1996; Nielsen et al., 2007). Moving beyond the established realm of cerebral visual impairments (Lim et al., 2023; Teoh et al., 2021), our Mendelian randomization analysis discloses that genetically predicted cognitive, perceptual, emotional, or behavioral differences amplify the risk of cataracts by 1.012-fold. Moreover, specific developmental disorders of motor function entail a 1.002-fold elevated likelihood of requiring eye surgery in contrast to the general population. Concurrently, the presence of wide developmental disorders heightens susceptibility to retinal pathologies, while ADHD surfaces as a glaucoma risk factor. These robust findings underscore the indispensable urgency for implementing routine ocular evaluations for these susceptible populations, underscoring the imperative of timely and proactive interventions to stave off irreversible and severe vision impairment.
We leveraged GWAS data derived from brain MRI scans to elucidate potential intrinsic mechanisms of association. The findings unveiled that dMRI TBSS L2 Retrolenticular part of internal capsule signals were linked to personality and behavioral disorders arising from brain afflictions, damage, and dysfunction, alongside mixed disorders of conduct and emotions and ASD. These signals concurrently correlated with astigmatism and secondary glaucoma. The augmentation of SWI T2 star left caudate plus right caudate signals was associated with an elevated likelihood of Symptoms and signs involving cognition, perception, emotional state, and behavior, in addition to heightened risks of Astigmatism, Paralytic strabismus, and Disorders of eyelid. These observations harmonize with the outcomes of prevalence studies concerning children with developmental disabilities. The investigation encompassing special education institutions revealed that 46% exhibited manifestations affecting extraocular, anterior, or posterior segments. Notably, conjunctivitis was found in 12% of cases, and suspected glaucomatous optic discs accounted for 6% (Reynolds et al., 2024). Wong documented an overall ocular condition prevalence of 69% in Chinese children with Down syndrome, including refractive errors (58%), strabismus (20%), ptosis/conjunctivitis (7%), and glaucoma (0.7%) (Wong & Ho,1997). The shared presence of atypical brain MRI fields for developmental differences and ocular disorders further lends support to the robustness of the association between these two conditions, potentially indicating these brain regions’ pivotal roles in governing this interrelation.
In the cross-sectional analysis, developmental disabilities exhibited a significant positive correlation with both the prevalence (OR 1.846, 95% CI 1.418 to 2.404, p < 0.001) and severity (OR 3.137, 95% CI 2.399 to 4.103, p < 0.001) of astigmatism. Causal analysis of genetic factors yielded consistent findings, highlighting cognitive, perceptual, emotional, or behavioral differences (OR 1.057, 95% CI 1.019 to 1.096, p = 0.003) and ASD (OR 1.010, 95% CI 1.001–1.018, p = 0.038) as significant risk factors for astigmatism. Furthermore, disorders of scholastic skills and ASD distinctly impacted astigmatism angles.However, these results also suggest that the specific association strengths between different developmental disorder subgroups and ocular diseases vary, further emphasizing the heterogeneity within this population. Future research should aim to further elucidate the specific associations between individual developmental disorders and ocular conditions, as well as the potential impact of multiple diagnoses on visual health outcomes. Moreover, a spectrum of developmental disorders emerged as risk factors for cataracts, retinal diseases, and glaucoma. Notably, genetically predicted enhancement of TBSS L2 Retrolenticular part of internal capsule and SWI T2 star left caudate plus right caudate signaling concurrently associated with developmental disabilities and ocular diseases, offering robust evidence for their intrinsic co-morbidity. To conclude, children with developmental disabilities face elevated susceptibility to ocular diseases, underscoring the imperative for early ophthalmologic assessments to detect and address potential issues promptly, thereby mitigating avoidable burdens for this unique population.
The findings of this study underscore the critical importance of implementing regular vision screenings for children with developmental disabilities. Several studies have unequivocally demonstrated that initiating interventions within the first six months of life can lead to significant improvements in visual prognosis for 70% of affected children (Donahue et al., 2016; Salt & Sargent, 2017). Home-based intervention programs, such as the Developmental Journal of Visual Impairment (DJVI), which employ multi-modal stimulation involving visual, auditory, and tactile inputs, have been shown to enhance cognitive development indices by 11.7 DQ points in children with severe visual impairments (Dale et al., 2019). Therefore, early detection and intervention are paramount in preventing or mitigating the progression of ocular disorders, which may profoundly impact the quality of life and educational outcomes for these children. However, the management of ocular conditions in children with developmental disabilities necessitates the establishment of a comprehensive, lifecycle-based system spanning from screening to rehabilitation. Routine comprehensive eye examinations should be incorporated into the standard of care for individuals with developmental disabilities, with a frequency tailored to their specific needs and risk factors. Future research should focus on developing cross-diagnostic assessment tools, such as predictive models integrating eye-tracking parameters and genomics. At the policy level, efforts should be directed towards incorporating vision screening into routine pediatric healthcare and strengthening multidisciplinary collaborative networks. The ultimate goal is to achieve a synergistic effect between visual rehabilitation and neurodevelopmental promotion, thereby enhancing the quality of life and social participation of these children (Chokron & Dutton, 2023; Dale et al., 2019).
While this study primarily focuses on the association between developmental disabilities and visual impairments, it is important to acknowledge that children with developmental disabilities may also be at an increased risk for other sensory impairments, such as auditory dysfunction (Bonino et al., 2025). Future research should explore the potential connections between developmental disabilities and other sensory impairments, such as hearing, olfactory, gustatory, and tactile dysfunction (Barney et al., 2017). By expanding the scope of investigation to include these additional sensory domains, we can gain a more comprehensive understanding of the challenges faced by children with developmental disabilities and develop targeted interventions to address their needs.
Acknowledging the limitations inherent in this study is essential. Primarily, in the cross-sectional analysis, it would be advantageous to consider additional variables related to ocular diseases, such as behavioral habits and environmental exposures, which may influence the association between developmental disabilities and ocular disorders. Incorporating these factors in future research would provide a more comprehensive understanding of the observed associations. Secondly, despite employing gene-level association analysis using the large-scale FINNGEN and UKBiobank databases, the persisting constraint of a small sample size stemming from the specificity of the research subjects remains. The heterogeneity among individuals with different developmental disorders, as well as the impact of single versus multiple co-existing disease factors on the risk of ocular diseases, adds further complexity to the study. Future large-scale, multi-center studies with expanded target sample sizes are necessary to further elucidate the relationship between disabilities and visual impairments. Furthermore, the breadth of diseases within the developmental disorders cohort precluded specific associations for each ailment, necessitating the selection of representative conditions for analysis. Further evaluation is imperative to ascertain the varying benefits of enhanced vision across distinct patients with developmental disorders, facilitating the development of targeted clinical interventions.
Acknowledgments
Our sincere appreciation goes to the Finnish Gene Dataset and the UK Biobank database for generously providing the genome-wide association study data. The utilization of their expansive biobanks and comprehensive record collections has greatly enriched our analytical endeavors. We extend our gratitude to these invaluable resources.
Declarations
Conflict of Interest
No conflicting relationship exists for any author.
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