Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Blood-born biomarkers for optic disc drusen
Author Affiliations & Notes
  • Yiting Zhang
    Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States
    Ophthalmology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • Xia Gong
    Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States
  • Heather Moss
    Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States
  • Shannon J. Beres
    Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States
  • Sophia Y Wang
    Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States
  • Yaping Joyce Liao
    Ophthalmology, Stanford University School of Medicine, Palo Alto, California, United States
  • Footnotes
    Commercial Relationships   Yiting Zhang None; Xia Gong None; Heather Moss None; Shannon Beres None; Sophia Wang None; Yaping Liao None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 104. doi:
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    • Get Citation

      Yiting Zhang, Xia Gong, Heather Moss, Shannon J. Beres, Sophia Y Wang, Yaping Joyce Liao; Blood-born biomarkers for optic disc drusen. Invest. Ophthalmol. Vis. Sci. 2024;65(7):104.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To evaluate differences in blood results and optical coherence tomography (OCT) changes between participants with or without optic disc drusen (ODD).

Methods : A retrospective study (July 2020-July 2023) at a single academic institution identified 122 patients through the STAnford Research Repository, with 66 confirmed ODD diagnoses. Swept-source and spectral-domain OCT, along with static perimetry, were used, and comprehensive clinical histories and detailed blood results were collected.

Results : In the study comparing 66 ODD patients (126 eyes) with 30 healthy controls (60 eyes), ODD patients showed thinner retinal nerve fiber layer (RNFL) and macular ganglion cell (GCC) thickness, along with worse static perimetry mean deviation (MD). Clinical notes revealed higher prevalence of smoking (78.79%, p=0.031), diabetes (18.18%, p=0.008), vitamin D deficiency (36.36%, p<0.001), and vitamin B supplement use (16.67%, p<0.001) in ODD patients. Elevated triglycerides (112.16 mg/dL, p=0.037) and calcium (9.43 mg/dL, p=0.034) were also observed in ODD patients.
Logistic statistical analysis identified elevated calcium as a high-risk factor for ODD, and a smoking history increased the risk of lower visual acuity (p=0.042). Reduced vitamin B supplementation correlated with thickness reduction in RNFL (superior p=0.024, nasal p=0.025, and inferior p=0.008), GCC (p<0.05), and static perimetry MD (p=0.017). Higher calcium levels were associated with superior RNFL thickness reduction (p=0.002).
Linear regression showed negative correlations between cholesterol level, ferritin, and superior RNFL thickness. Conversely, total iron binding capacity had a positive correlation, and HDL cholesterol correlated positively with static perimetry MD.

Conclusions : Patients with ODD displayed a higher prevalence of risk factors and specific blood abnormalities, indicating a complex interplay between systemic and ocular conditions.Less vitamin B supplementation was associated with worse thinning of retina, optic nerve and visual field deficiency. These findings highlight the complex interplay of systemic and ocular factors in this population and serve as springboard for designing targeted assessment and amelioration of risk factors for vision loss in ODD.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

 

Figure 1: Correlation Analysis Between Blood Biomarkers and Superior RNFL Thickness

Figure 1: Correlation Analysis Between Blood Biomarkers and Superior RNFL Thickness

 

Figure 2: Correlation Analysis Between Blood Biomarkers and Static Perimetry Mean Deviation

Figure 2: Correlation Analysis Between Blood Biomarkers and Static Perimetry Mean Deviation

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