In-depth correlation analysis between tear glucose and blood glucose using a wireless smart contact lens

• Published in: Nature communications Vol. 15; no. 1; pp. 2828 - 15
• Main Authors: Park, Wonjung, Seo, Hunkyu, Kim, Jeongho, Hong, Yeon-Mi, Song, Hayoung, Joo, Byung Jun, Kim, Sumin, Kim, Enji, Yae, Che-Gyem, Kim, Jeonghyun, Jin, Jonghwa, Kim, Joohee, Lee, Yong-ho, Kim, Jayoung, Kim, Hong Kyun, Park, Jang-Ung
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.04.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 13/105; 14/105; 14/34; 142/126; 64; 692/53/2421; 692/699/317; 692/700/139; 9/10; Animal models; Animals; Blood; Blood Glucose; Contact lenses; Contact Lenses, Hydrophilic; Correlation analysis; Data acquisition; Diabetes; Diabetes mellitus; Diabetes Mellitus - diagnosis; Glucose; Glucose - analysis; Humanities and Social Sciences; Humans; Lag time; Monitoring; multidisciplinary; Science; Science (multidisciplinary); Tears; Tears - chemistry
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-47123-9

Tears have emerged as a promising alternative to blood for diagnosing diabetes. Despite increasing attempts to measure tear glucose using smart contact lenses, the controversy surrounding the correlation between tear glucose and blood glucose still limits the clinical usage of tears. Herein, we present an in-depth investigation of the correlation between tear glucose and blood glucose using a wireless and soft smart contact lens for continuous monitoring of tear glucose. This smart contact lens is capable of quantitatively monitoring the tear glucose levels in basal tears excluding the effect of reflex tears which might weaken the relationship with blood glucose. Furthermore, this smart contact lens can provide an unprecedented level of continuous tear glucose data acquisition at sub-minute intervals. These advantages allow the precise estimation of lag time, enabling the establishment of the concept called ‘personalized lag time’. This demonstration considers individual differences and is successfully applied to both non-diabetic and diabetic humans, as well as in animal models, resulting in a high correlation. The correlation between tear glucose and blood glucose is still controversial. Here, the authors demonstrated the correlation between tear glucose and blood glucose in both animal models and human subjects using smart contact lenses.