Age at type 2 diabetes onset, retinol binding protein 4 and risks of diabetic retinopathy: a real-world cross-sectional study

Age at type 2 diabetes onset, retinol binding protein 4 and risks of diabetic retinopathy: a real-world cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Age at type 2 diabetes onset, retinol binding protein 4 and risks of diabetic retinopathy: a real-world cross-sectional study Qiuju Zhou, Lisha Ni, Jun Li, Minghua Fan, Hui Shao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7940836/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Objective This study aimed to investigate the interaction between age at type 2 diabetes mellitus (T2DM) onset and serum retinol-binding protein 4 (RBP4) levels in relation to the risk of diabetic retinopathy (DR), examining whether RBP4 can serve as a potential biomarker for DR, particularly among patients with younger onset diabetes. Methods A cross-sectional analysis was conducted with 6,996 adults diagnosed with T2DM from the electronic medical records at Lishui People’s Hospital, Zhejiang, between January 2018 and June 2023. Participants were stratified by age at T2DM onset (< 65 years vs. ≥65 years) and serum RBP4 levels (< 40 vs. ≥40 pg/mL). The primary outcome was the presence of DR assessed through standardized fundus photography according to ETDRS criteria. Logistic regression models were employed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for DR. Results Elevated RBP4 levels (≥ 40 pg/mL) were significantly associated with an increased risk of DR among patients diagnosed with diabetes before 65 years of age (adjusted OR: 1.25, 95% CI: 1.10–1.42). Conversely, patients diagnosed at age 65 or older exhibited a reduced risk of DR associated with higher RBP4 levels (adjusted OR: 0.45, 95% CI: 0.33–0.61). Further subgroup analyses revealed significant interactions based on age groups (P for interaction < 0.001). Compared with younger-onset individuals, older-onset diabetic patients consistently demonstrated lower odds of DR, suggesting age as a critical determinant of DR risk. Conclusions Our findings underscore the age-dependent role of serum RBP4 as a biomarker for DR, indicating its predictive relevance primarily among younger diabetic patients. Age at diabetes onset emerges as a predominant factor influencing DR risk. These results advocate age-specific risk stratification and tailored management strategies to prevent diabetic retinopathy. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Endocrinology Health sciences/Medical research Health sciences/Risk factors Diabetic retinopathy Retinol-binding protein 4 Age at T2DM onset Biomarker Type 2 diabetes mellitus Figures Figure 1 Introduction Blood pressure (DR) remains a leading cause of visual impairment and blindness worldwide, significantly impacting quality of life and increasing healthcare burdens 1 , 2 . With the global prevalence of diabetes mellitus (DM) steadily rising especially type 2 DM (T2DM), understanding factors that contribute to the development and progression of DR is crucial for effective prevention and targeted interventions 3 , 4 . Previous research has identified several key determinants of DR risk, including duration of diabetes, glycemic control, hypertension, and dyslipidemia 5 , 6 . Recent studies have further emphasized the potential importance of the age at diabetes onset as a distinct risk factor. Evidence suggests that individuals diagnosed with diabetes at younger ages may experience prolonged hyperglycemic exposure, consequently elevating their cumulative risk for microvascular complications such as DR 6,7 . However, existing findings are inconsistent, and robust evidence from real-world clinical settings remains sparse. Additionally, emerging biomarkers such as retinol-binding protein 4 (RBP4) have gained interest for their potential roles in metabolic dysregulation and diabetic complications 8 . Elevated RBP4 levels have been associated with insulin resistance, inflammation, and endothelial dysfunction, all of which are implicated in the pathogenesis of DR 9,10 . Yet, the relationship between serum RBP4 levels and DR, particularly in the context of differing ages at diabetes onset, has not been thoroughly investigated. To address these knowledge gaps, we conducted a real-world cross-sectional study to explore the associations among age at diabetes onset, serum RBP4 levels, and the risk of DR. Methods Study design and population This cross-sectional study used data from the electronic medical records (EMRs) at Lishui People’s Hospital, Zhejiang, between January 2018 and June 2023. Participants included were adults diagnosed with type 2 diabetes mellitus (T2DM) and aged 18 years or older. Inclusion criteria required participants to have comprehensive demographic, clinical, and laboratory data, including serum retinol binding protein 4 (RBP4) levels. Exclusion criteria encompassed individuals with other retinal diseases, previous ocular surgeries, severe renal or hepatic impairments, autoimmune diseases (including type 1 diabetes mellitus), or incomplete data. The original dataset included 7,891 patients with T2DM and 6,996 of them were enrolled in the final analysis (see flow chart in Fig. 1). This study was approved by the Institution Review Board of Lishui People’s Hospital (2024-025-01). Informed consents were waived because we used de-identified anonymous data. All methods were performed in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Data collection and covariate measurements Data were systematically collected during routine check-ups. Participants were required to fast for a minimum of 12 hours prior to laboratory assessments. Anthropometric measurements included height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg), measured with standardized equipment. Body Mass Index (BMI) was calculated as weight (kg)/height squared (m²) 11 . Blood pressure (BP) was measured with an automated sphygmomanometer after participants rested seated for at least five minutes, taking two measurements three minutes apart and using the average 12 . Clinical history regarding diabetes duration, hypertension, dyslipidemia, and other comorbidities was gathered via standardized questionnaires. Laboratory assessments included fasting plasma glucose, hemoglobin A1c (HbA1c), serum lipid profiles (total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides), renal function markers (estimated glomerular filtration rate, eGFR), and RBP4 levels. Fasting plasma glucose and lipid profiles were measured using standard enzymatic methods, HbA1c through high-performance liquid chromatography (HPLC), and RBP4 concentrations (pg/mL) via enzyme-linked immunosorbent assay (ELISA, abcam ab196264, Shanghai, China). Ophthalmologic evaluation Diabetic retinopathy (DR) was assessed through fundus photography performed by trained ophthalmologists blinded to participants' clinical details, using standardized digital fundus imaging (CR-2 AF Digital Retinal Camera, Canon Inc., Tokyo, Japan). DR severity was graded according to the Early Treatment Diabetic Retinopathy Study (ETDRS) criteria by two independent ophthalmologists. Discrepancies were resolved through consultation with a senior ophthalmologist. Definitions and outcomes T2DM in the present study was determined based on the SUPREME-DM criteria as follows: (a) one or more of the International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) codes for type 2 diabetes associated with inpatient encounters; (b) two or more ICD codes associated with outpatient encounters on different days within 2 years; (c) a combination of two or more of the following variables associated with outpatient encounters on different days within 2 years: ICD codes, fasting glucose level ≥ 7.0 mmol/L, 2-hour glucose level ≥ 11.1 mmol/L, random glucose level ≥ 11.1 mmol/L, HbA1c ≥ 6.5% and prescription of an antidiabetic medication. 13 Age at type 2 diabetes onset was categorized into early-onset (diagnosed at age < 65 years old) and late-onset (≥ 65 years old). The primary outcome was the presence of diabetic retinopathy, categorized as either absent or present based on ETDRS criteria 14 . Statistical analysis Continuous variables were presented as means ± standard deviation (SD), and categorical variables were reported as numbers (percentages). Patients were categorized based on the age at T2DM onset (< 65 years old or ≥ 65 years old) and RBP4 levels (< 40 pg/ml or ≥ 40 pg/ml, which was the median RBP4 levels within our analytic dataset). Differences between groups were evaluated using chi-square tests for categorical variables and independent t-tests or ANOVA for continuous variables. Multivariable logistic regression analyses were conducted to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between age at diabetes onset, RBP4 levels, and DR risk. Models were sequentially adjusted: Model 1 (unadjusted), Model 2 (adjusted for age and sex), and Model 3 (additionally adjusted for BMI, BP, LDL-cholesterol, triglycerides, HbA1c, diabetes duration, eGFR, and medication usage). Subgroup analyses explored interactions by sex, BMI categories (≥ 24 or < 24 kg/m²), and HbA1c categories (≥ 7.0% or < 7.0%). All statistical analyses were performed using R version 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria), with two-sided p-values < 0.05 considered statistically significant. Results A total of 6,996 participants were analyzed in this study, stratified by age at diabetes mellitus (DM) onset (< 65 years vs. ≥65 years) and retinol-binding protein 4 (RBP4) levels (< 40 vs. ≥40). Participants with an older age at DM onset (≥ 65 years) had significantly higher average ages (approximately 76 years) compared to those with younger onset (< 65 years, average age approximately 56 years; P < 0.001). Individuals in the older onset group exhibited significantly lower estimated glomerular filtration rates (eGFR) (approximately 77–78 mL/min/1.73 m² vs. 97–99 mL/min/1.73 m², P < 0.001) and lower triglyceride levels compared to younger-onset groups (P < 0.001). For individuals who developed diabetes before the age of 65, elevated RBP4 levels (≥ 40) were associated with a significantly increased risk of diabetic retinopathy (DR), with an adjusted odds ratio (OR) of 1.25 (95% CI: 1.10–1.42) compared to those with lower RBP4 levels (< 40). In contrast, among individuals who developed diabetes at age 65 or older, higher RBP4 levels were associated with a reduced risk of DR, showing an adjusted OR of 0.45 (95% CI: 0.33–0.61). When comparing within the older-onset group (≥ 65 years) specifically, higher RBP4 levels again suggested an increased, though not statistically significant, risk of DR (adjusted OR: 1.39; 95% CI: 0.94–2.06). This indicates nuanced differences based on age at onset and RBP4 concentrations. Subgroup analyses indicated significant interactions based on age categories (P for interaction < 0.001). Specifically, participants aged < 65 years with higher RBP4 levels had consistently elevated odds of DR (OR: 1.24; 95% CI: 1.07–1.43). In contrast, those aged ≥ 65 years showed decreased odds (OR: 0.54; 95% CI: 0.39–0.74). No significant interactions were observed based on sex, lipid-lowering medications, antihypertensive medications, or glucose-lowering medications, although there were varying degrees of increased odds of DR associated with higher RBP4 levels within specific subgroups. Additionally, participants who monitored their blood glucose levels more frequently (> 3 times per week) demonstrated higher protective motivation compared to those monitoring less frequently (≤ 3 times per week; OR: 2.95; 95% CI: 1.68–5.20; P < 0.001). Exercise habits and medical expense payment methods were significant in univariate analyses but not in multivariate logistic regression. Discussion Our findings highlight significant interactions between age at T2DM onset and RBP4 levels concerning diabetic retinopathy (DR) risk. We observed notable differential association between RBP4 levels and DR risk based on the age at DM onset. Higher RBP4 levels were significantly associated with the odds of DR in individuals who developed diabetes at a younger age (< 65 years). Conversely, in the older-onset group (≥ 65 years), higher RBP4 levels correlated with a reduced risk of DR. Further analysis within the older-onset group (≥ 65 years) indicated an increased but not statistically significant risk of DR with higher RBP4 levels. These findings suggested that RBP4 could serve as a valuable biomarker for identifying younger-onset diabetic patients who are at heightened risk of developing DR. The direct comparison between younger and older DM onset groups revealed that patients with older DM onset exhibited a lower overall risk of DR, suggesting that age itself may be the most significant risk factor influencing DR development. This aligns with existing literature indicating that the predictive value of RBP4 as a biomarker for DR may not extend to older-onset diabetic populations. These findings suggested an age-dependent role of RBP4, highlighting the importance of age stratification when evaluating potential biomarkers 14 , 15 . Among patients who developed diabetes at age 65 or older, either higher or lower RBP4 levels were associated with a reduced odds of DR when compared with patients with younger onset and lower RBP4 levels. This inverse relationship underscored that older age at diabetes onset is often associated with a less aggressive disease progression and potentially lower rates of certain microvascular complications. Our findings were consistent with prior research indicating that elevated RBP4 may exacerbate insulin resistance and endothelial dysfunction, thereby accelerating microvascular damage leading to DR. RBP4 has been reported to impair insulin signaling pathways, leading to increased glucose production and reduced glucose uptake by peripheral tissues 16 , 17 . Additionally, RBP4-induced endothelial dysfunction contributes to vascular inflammation and oxidative stress, crucial factors in the pathogenesis and progression of diabetic microvascular complications like DR 18–20 . The upregulation of RBP4 is also associated with increased expression of adhesion molecules, promoting leukocyte adhesion to endothelial cells, and subsequent microvascular injury. 21 , 22 Interestingly, our subgroup analysis revealed significant interactions based on age groups, underscoring age as a critical modifier in the RBP4-DR relationship. The increased odds of DR in younger individuals with elevated RBP4 might indicate heightened susceptibility to metabolic derangements at earlier ages, whereas older individuals could represent a selectively healthier cohort or reflect different pathophysiological pathways contributing to DR. Future longitudinal studies could elucidate these age-dependent mechanisms more comprehensively. Our findings also have several clinical implications. Firstly, stratification by age at DM onset and RBP4 levels could refine risk assessment for DR, allowing targeted early interventions. Healthcare providers should consider incorporating RBP4 measurements into routine clinical practice, especially for younger-onset diabetes patients, to identify those at higher risk for DR and tailor preventive strategies accordingly. Our study has several limitations that should be acknowledged. Firstly, the cross-sectional design precludes causal inference, and the convenience sampling from a single institution and the findings may be influenced by regional factors such as genetic background, healthcare access, and treatment practices, which limit generalizability. Additionally, the reliance on self-reported behavioral data could introduce reporting bias. Finally, although information on glucose-lowering and lipid-lowering medications was included in the regression models, detailed data on drug type, dose, and duration were lacking. Modern therapies such as GLP-1 receptor agonists, SGLT2 inhibitors, and statins could plausibly affect both RBP4 levels and retinopathy risk, and their confounding influence cannot be fully excluded. Conclusion In conclusion, this study provided novel insights into the complex interactions between age at DM onset, RBP4 levels, and DR risk. Our findings highlighted the need for personalized approaches in diabetic care, emphasizing both biochemical markers and behavioral interventions to optimize diabetes management and prevent complications such as DR. Declarations Author Contributions Study design and supervision: Q.Z., Data analysis and visualization: J.L. and H.S., Manuscript writing: M.F. and H.S., Funding acquisition: L.S. Conceptualization: L.S. Conflicts of Interest The authors declare that there were no conflicts of interest with respect to the authorship or the publication of this article. Acknowledgments We gratefully acknowledge all participants for their contributions to this study. Funding Lishui Science and Technology Program Project (No. 2024SJZC177). Zhejiang Medical and Health Science and Technology Program Project (No. 2022KY1445). Ethical approval This study was approved by the Institution Review Board of Lishui Hospital (2024-025-01). 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1","display":"","copyAsset":false,"role":"figure","size":178947,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Chart\u003c/p\u003e","description":"","filename":"flowchart.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7940836/v1/6aad4a0542f6b427e8b0d3c2.jpeg"},{"id":97372686,"identity":"92d567a9-9230-4f6c-9d7f-a758fb32464b","added_by":"auto","created_at":"2025-12-03 16:32:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":591885,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7940836/v1/edd64a1d-c4a8-4784-9326-9645e16cd0a1.pdf"},{"id":97266862,"identity":"8c95033b-d2f9-40e3-92bb-d8c5abd74330","added_by":"auto","created_at":"2025-12-02 14:36:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33324,"visible":true,"origin":"","legend":"","description":"","filename":"tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7940836/v1/2db0e7f319a35fe7047537e1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Age at type 2 diabetes onset, retinol binding protein 4 and risks of diabetic retinopathy: a real-world cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBlood pressure (DR) remains a leading cause of visual impairment and blindness worldwide, significantly impacting quality of life and increasing healthcare burdens\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. With the global prevalence of diabetes mellitus (DM) steadily rising especially type 2 DM (T2DM), understanding factors that contribute to the development and progression of DR is crucial for effective prevention and targeted interventions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePrevious research has identified several key determinants of DR risk, including duration of diabetes, glycemic control, hypertension, and dyslipidemia\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Recent studies have further emphasized the potential importance of the age at diabetes onset as a distinct risk factor. Evidence suggests that individuals diagnosed with diabetes at younger ages may experience prolonged hyperglycemic exposure, consequently elevating their cumulative risk for microvascular complications such as DR\u003csup\u003e6,7\u003c/sup\u003e. However, existing findings are inconsistent, and robust evidence from real-world clinical settings remains sparse.\u003c/p\u003e\u003cp\u003eAdditionally, emerging biomarkers such as retinol-binding protein 4 (RBP4) have gained interest for their potential roles in metabolic dysregulation and diabetic complications\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Elevated RBP4 levels have been associated with insulin resistance, inflammation, and endothelial dysfunction, all of which are implicated in the pathogenesis of DR\u003csup\u003e9,10\u003c/sup\u003e. Yet, the relationship between serum RBP4 levels and DR, particularly in the context of differing ages at diabetes onset, has not been thoroughly investigated.\u003c/p\u003e\u003cp\u003eTo address these knowledge gaps, we conducted a real-world cross-sectional study to explore the associations among age at diabetes onset, serum RBP4 levels, and the risk of DR.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and population\u003c/p\u003e\u003cp\u003eThis cross-sectional study used data from the electronic medical records (EMRs) at Lishui People\u0026rsquo;s Hospital, Zhejiang, between January 2018 and June 2023. Participants included were adults diagnosed with type 2 diabetes mellitus (T2DM) and aged 18 years or older. Inclusion criteria required participants to have comprehensive demographic, clinical, and laboratory data, including serum retinol binding protein 4 (RBP4) levels. Exclusion criteria encompassed individuals with other retinal diseases, previous ocular surgeries, severe renal or hepatic impairments, autoimmune diseases (including type 1 diabetes mellitus), or incomplete data. The original dataset included 7,891 patients with T2DM and 6,996 of them were enrolled in the final analysis (see flow chart in Fig.\u0026nbsp;1). This study was approved by the Institution Review Board of Lishui People\u0026rsquo;s Hospital (2024-025-01). Informed consents were waived because we used de-identified anonymous data. All methods were performed in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e\u003cp\u003eData collection and covariate measurements\u003c/p\u003e\u003cp\u003eData were systematically collected during routine check-ups. Participants were required to fast for a minimum of 12 hours prior to laboratory assessments. Anthropometric measurements included height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg), measured with standardized equipment. Body Mass Index (BMI) was calculated as weight (kg)/height squared (m\u0026sup2;)\u003csup\u003e11\u003c/sup\u003e. Blood pressure (BP) was measured with an automated sphygmomanometer after participants rested seated for at least five minutes, taking two measurements three minutes apart and using the average\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eClinical history regarding diabetes duration, hypertension, dyslipidemia, and other comorbidities was gathered via standardized questionnaires. Laboratory assessments included fasting plasma glucose, hemoglobin A1c (HbA1c), serum lipid profiles (total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides), renal function markers (estimated glomerular filtration rate, eGFR), and RBP4 levels. Fasting plasma glucose and lipid profiles were measured using standard enzymatic methods, HbA1c through high-performance liquid chromatography (HPLC), and RBP4 concentrations (pg/mL) via enzyme-linked immunosorbent assay (ELISA, abcam ab196264, Shanghai, China).\u003c/p\u003e\u003cp\u003eOphthalmologic evaluation\u003c/p\u003e\u003cp\u003eDiabetic retinopathy (DR) was assessed through fundus photography performed by trained ophthalmologists blinded to participants' clinical details, using standardized digital fundus imaging (CR-2 AF Digital Retinal Camera, Canon Inc., Tokyo, Japan). DR severity was graded according to the Early Treatment Diabetic Retinopathy Study (ETDRS) criteria by two independent ophthalmologists. Discrepancies were resolved through consultation with a senior ophthalmologist.\u003c/p\u003e\u003cp\u003eDefinitions and outcomes\u003c/p\u003e\u003cp\u003eT2DM in the present study was determined based on the SUPREME-DM criteria as follows: (a) one or more of the International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) codes for type 2 diabetes associated with inpatient encounters; (b) two or more ICD codes associated with outpatient encounters on different days within 2 years; (c) a combination of two or more of the following variables associated with outpatient encounters on different days within 2 years: ICD codes, fasting glucose level\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L, 2-hour glucose level\u0026thinsp;\u0026ge;\u0026thinsp;11.1 mmol/L, random glucose level\u0026thinsp;\u0026ge;\u0026thinsp;11.1 mmol/L, HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5% and prescription of an antidiabetic medication.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAge at type 2 diabetes onset was categorized into early-onset (diagnosed at age\u0026thinsp;\u0026lt;\u0026thinsp;65 years old) and late-onset (\u0026ge;\u0026thinsp;65 years old). The primary outcome was the presence of diabetic retinopathy, categorized as either absent or present based on ETDRS criteria\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and categorical variables were reported as numbers (percentages). Patients were categorized based on the age at T2DM onset (\u0026lt;\u0026thinsp;65 years old or \u0026ge;\u0026thinsp;65 years old) and RBP4 levels (\u0026lt;\u0026thinsp;40 pg/ml or \u0026ge;\u0026thinsp;40 pg/ml, which was the median RBP4 levels within our analytic dataset). Differences between groups were evaluated using chi-square tests for categorical variables and independent t-tests or ANOVA for continuous variables. Multivariable logistic regression analyses were conducted to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between age at diabetes onset, RBP4 levels, and DR risk. Models were sequentially adjusted: Model 1 (unadjusted), Model 2 (adjusted for age and sex), and Model 3 (additionally adjusted for BMI, BP, LDL-cholesterol, triglycerides, HbA1c, diabetes duration, eGFR, and medication usage). Subgroup analyses explored interactions by sex, BMI categories (\u0026ge;\u0026thinsp;24 or \u0026lt;\u0026thinsp;24 kg/m\u0026sup2;), and HbA1c categories (\u0026ge;\u0026thinsp;7.0% or \u0026lt;\u0026thinsp;7.0%). All statistical analyses were performed using R version 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria), with two-sided p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 6,996 participants were analyzed in this study, stratified by age at diabetes mellitus (DM) onset (\u0026lt;\u0026thinsp;65 years vs. \u0026ge;65 years) and retinol-binding protein 4 (RBP4) levels (\u0026lt;\u0026thinsp;40 vs. \u0026ge;40). Participants with an older age at DM onset (\u0026ge;\u0026thinsp;65 years) had significantly higher average ages (approximately 76 years) compared to those with younger onset (\u0026lt;\u0026thinsp;65 years, average age approximately 56 years; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Individuals in the older onset group exhibited significantly lower estimated glomerular filtration rates (eGFR) (approximately 77\u0026ndash;78 mL/min/1.73 m\u0026sup2; vs. 97\u0026ndash;99 mL/min/1.73 m\u0026sup2;, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lower triglyceride levels compared to younger-onset groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eFor individuals who developed diabetes before the age of 65, elevated RBP4 levels (\u0026ge;\u0026thinsp;40) were associated with a significantly increased risk of diabetic retinopathy (DR), with an adjusted odds ratio (OR) of 1.25 (95% CI: 1.10\u0026ndash;1.42) compared to those with lower RBP4 levels (\u0026lt;\u0026thinsp;40). In contrast, among individuals who developed diabetes at age 65 or older, higher RBP4 levels were associated with a reduced risk of DR, showing an adjusted OR of 0.45 (95% CI: 0.33\u0026ndash;0.61). When comparing within the older-onset group (\u0026ge;\u0026thinsp;65 years) specifically, higher RBP4 levels again suggested an increased, though not statistically significant, risk of DR (adjusted OR: 1.39; 95% CI: 0.94\u0026ndash;2.06). This indicates nuanced differences based on age at onset and RBP4 concentrations.\u003c/p\u003e\u003cp\u003eSubgroup analyses indicated significant interactions based on age categories (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically, participants aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years with higher RBP4 levels had consistently elevated odds of DR (OR: 1.24; 95% CI: 1.07\u0026ndash;1.43). In contrast, those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years showed decreased odds (OR: 0.54; 95% CI: 0.39\u0026ndash;0.74). No significant interactions were observed based on sex, lipid-lowering medications, antihypertensive medications, or glucose-lowering medications, although there were varying degrees of increased odds of DR associated with higher RBP4 levels within specific subgroups.\u003c/p\u003e\u003cp\u003eAdditionally, participants who monitored their blood glucose levels more frequently (\u0026gt;\u0026thinsp;3 times per week) demonstrated higher protective motivation compared to those monitoring less frequently (\u0026le;\u0026thinsp;3 times per week; OR: 2.95; 95% CI: 1.68\u0026ndash;5.20; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Exercise habits and medical expense payment methods were significant in univariate analyses but not in multivariate logistic regression.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings highlight significant interactions between age at T2DM onset and RBP4 levels concerning diabetic retinopathy (DR) risk. We observed notable differential association between RBP4 levels and DR risk based on the age at DM onset. Higher RBP4 levels were significantly associated with the odds of DR in individuals who developed diabetes at a younger age (\u0026lt;\u0026thinsp;65 years). Conversely, in the older-onset group (\u0026ge;\u0026thinsp;65 years), higher RBP4 levels correlated with a reduced risk of DR. Further analysis within the older-onset group (\u0026ge;\u0026thinsp;65 years) indicated an increased but not statistically significant risk of DR with higher RBP4 levels. These findings suggested that RBP4 could serve as a valuable biomarker for identifying younger-onset diabetic patients who are at heightened risk of developing DR.\u003c/p\u003e\u003cp\u003eThe direct comparison between younger and older DM onset groups revealed that patients with older DM onset exhibited a lower overall risk of DR, suggesting that age itself may be the most significant risk factor influencing DR development. This aligns with existing literature indicating that the predictive value of RBP4 as a biomarker for DR may not extend to older-onset diabetic populations. These findings suggested an age-dependent role of RBP4, highlighting the importance of age stratification when evaluating potential biomarkers\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Among patients who developed diabetes at age 65 or older, either higher or lower RBP4 levels were associated with a reduced odds of DR when compared with patients with younger onset and lower RBP4 levels. This inverse relationship underscored that older age at diabetes onset is often associated with a less aggressive disease progression and potentially lower rates of certain microvascular complications.\u003c/p\u003e\u003cp\u003eOur findings were consistent with prior research indicating that elevated RBP4 may exacerbate insulin resistance and endothelial dysfunction, thereby accelerating microvascular damage leading to DR. RBP4 has been reported to impair insulin signaling pathways, leading to increased glucose production and reduced glucose uptake by peripheral tissues\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Additionally, RBP4-induced endothelial dysfunction contributes to vascular inflammation and oxidative stress, crucial factors in the pathogenesis and progression of diabetic microvascular complications like DR\u003csup\u003e18\u0026ndash;20\u003c/sup\u003e. The upregulation of RBP4 is also associated with increased expression of adhesion molecules, promoting leukocyte adhesion to endothelial cells, and subsequent microvascular injury.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eInterestingly, our subgroup analysis revealed significant interactions based on age groups, underscoring age as a critical modifier in the RBP4-DR relationship. The increased odds of DR in younger individuals with elevated RBP4 might indicate heightened susceptibility to metabolic derangements at earlier ages, whereas older individuals could represent a selectively healthier cohort or reflect different pathophysiological pathways contributing to DR. Future longitudinal studies could elucidate these age-dependent mechanisms more comprehensively.\u003c/p\u003e\u003cp\u003eOur findings also have several clinical implications. Firstly, stratification by age at DM onset and RBP4 levels could refine risk assessment for DR, allowing targeted early interventions. Healthcare providers should consider incorporating RBP4 measurements into routine clinical practice, especially for younger-onset diabetes patients, to identify those at higher risk for DR and tailor preventive strategies accordingly.\u003c/p\u003e\u003cp\u003eOur study has several limitations that should be acknowledged. Firstly, the cross-sectional design precludes causal inference, and the convenience sampling from a single institution and the findings may be influenced by regional factors such as genetic background, healthcare access, and treatment practices, which limit generalizability. Additionally, the reliance on self-reported behavioral data could introduce reporting bias. Finally, although information on glucose-lowering and lipid-lowering medications was included in the regression models, detailed data on drug type, dose, and duration were lacking. Modern therapies such as GLP-1 receptor agonists, SGLT2 inhibitors, and statins could plausibly affect both RBP4 levels and retinopathy risk, and their confounding influence cannot be fully excluded.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study provided novel insights into the complex interactions between age at DM onset, RBP4 levels, and DR risk. Our findings highlighted the need for personalized approaches in diabetic care, emphasizing both biochemical markers and behavioral interventions to optimize diabetes management and prevent complications such as DR.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design and supervision:\u0026nbsp;Q.Z.,\u003c/p\u003e\n\u003cp\u003eData analysis and visualization: J.L. and H.S.,\u003c/p\u003e\n\u003cp\u003eManuscript writing: M.F. and H.S.,\u003c/p\u003e\n\u003cp\u003eFunding acquisition:\u0026nbsp;L.S.\u003c/p\u003e\n\u003cp\u003eConceptualization: L.S.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there were no conflicts of interest with respect to the authorship or the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge all participants for their contributions to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLishui Science and Technology Program Project (No. 2024SJZC177).\u003c/p\u003e\n\u003cp\u003eZhejiang Medical and Health Science and Technology Program Project (No. 2022KY1445).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institution Review Board of Lishui Hospital (2024-025-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData may be available upon request (contact the corresponding author).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCheung, N., Mitchell, P. \u0026amp; Wong, T. 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Retinol-binding protein 4 induces inflammation in human endothelial cells by an NADPH oxidase- and nuclear factor kappa B-dependent and retinol-independent mechanism. \u003cem\u003eMolecular Cell. biology Dec.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (24), 5103\u0026ndash;5115. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/mcb.00820-12\u003c/span\u003e\u003cspan address=\"10.1128/mcb.00820-12\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Diabetic retinopathy, Retinol-binding protein 4, Age at T2DM onset, Biomarker, Type 2 diabetes mellitus","lastPublishedDoi":"10.21203/rs.3.rs-7940836/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7940836/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aimed to investigate the interaction between age at type 2 diabetes mellitus (T2DM) onset and serum retinol-binding protein 4 (RBP4) levels in relation to the risk of diabetic retinopathy (DR), examining whether RBP4 can serve as a potential biomarker for DR, particularly among patients with younger onset diabetes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional analysis was conducted with 6,996 adults diagnosed with T2DM from the electronic medical records at Lishui People\u0026rsquo;s Hospital, Zhejiang, between January 2018 and June 2023. Participants were stratified by age at T2DM onset (\u0026lt;\u0026thinsp;65 years vs. \u0026ge;65 years) and serum RBP4 levels (\u0026lt;\u0026thinsp;40 vs. \u0026ge;40 pg/mL). The primary outcome was the presence of DR assessed through standardized fundus photography according to ETDRS criteria. Logistic regression models were employed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for DR.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eElevated RBP4 levels (\u0026ge;\u0026thinsp;40 pg/mL) were significantly associated with an increased risk of DR among patients diagnosed with diabetes before 65 years of age (adjusted OR: 1.25, 95% CI: 1.10\u0026ndash;1.42). Conversely, patients diagnosed at age 65 or older exhibited a reduced risk of DR associated with higher RBP4 levels (adjusted OR: 0.45, 95% CI: 0.33\u0026ndash;0.61). Further subgroup analyses revealed significant interactions based on age groups (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Compared with younger-onset individuals, older-onset diabetic patients consistently demonstrated lower odds of DR, suggesting age as a critical determinant of DR risk.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur findings underscore the age-dependent role of serum RBP4 as a biomarker for DR, indicating its predictive relevance primarily among younger diabetic patients. Age at diabetes onset emerges as a predominant factor influencing DR risk. These results advocate age-specific risk stratification and tailored management strategies to prevent diabetic retinopathy.\u003c/p\u003e","manuscriptTitle":"Age at type 2 diabetes onset, retinol binding protein 4 and risks of diabetic retinopathy: a real-world cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 14:36:10","doi":"10.21203/rs.3.rs-7940836/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-09T06:31:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-03T08:48:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-24T19:11:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-18T15:56:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41536943507160976773969157985940595145","date":"2025-12-17T03:32:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33874328862352426722062701525155056983","date":"2025-12-13T00:39:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110629383573220257074576229612003487645","date":"2025-12-12T15:54:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18213867233644619005916510456110255506","date":"2025-12-11T04:23:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-28T12:16:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-28T12:15:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-13T09:57:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-12T07:09:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-11-12T07:06:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a7c2a826-26a5-4f48-a4e9-4180ee7c336e","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":58807888,"name":"Health sciences/Biomarkers"},{"id":58807889,"name":"Health sciences/Diseases"},{"id":58807890,"name":"Health sciences/Endocrinology"},{"id":58807891,"name":"Health sciences/Medical research"},{"id":58807892,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-20T15:09:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 14:36:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7940836","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7940836","identity":"rs-7940836","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}