Gamma glutamyltransferase and risk of dementia in prediabetes and diabetes

Eugene Han, Ji Yeon Lee, Kyung do Han, Hanna Cho, Kwang Joon Kim, Byung Wan Lee, Eun Seok Kang, Bong Soo Cha, Zobair M. Younossi, Yong ho Lee

Research output: Contribution to journalArticlepeer-review

Abstract

Diabetes is associated with cognitive impairment and greater risk for dementia, but the role of gamma-glutamyltransferase (γ-GT) in dementia has not been elucidated. We determined incident dementia including Alzheimer’s disease and vascular dementia, analyzing data from participants aged 40 years or older in the National Health Insurance Database, collected by the National Health Insurance Service in Korea, from January 2009 to December 2015. During a median follow-up of 7.6 years, 272,657 participants were diagnosed as having dementia. Higher serum γ-GT was associated with increased risk of dementia (HR = 1.22, 95% CI = 1.20–1.24), and had a strong positive association with early onset dementia (HR = 1.32, 95% CI = 1.24–1.40). An additive impact of higher γ-GT on dementia was observed regardless of glycemic status, and prevalent diabetes with the highest γ-GT quartile had a 1.8-fold increased dementia risk (HR = 1.82, 95% CI = 1.78–1.85). This effect of γ-GT concentration in diabetes was more prominent in individuals with vascular dementia (HR = 1.94, 95% CI = 1.84–2.04). In subgroup analysis, young age, male sex, and relatively healthy subjects with a higher γ-GT quartile had more increased dementia risk. In conclusion, γ-GT concentration as well as glycemic status could be a future risk factor for dementia in the general population.

Original languageEnglish
Article number6800
JournalScientific reports
Volume10
Issue number1
DOIs
Publication statusPublished - 2020 Dec 1

Bibliographical note

Funding Information:
This research was supported by the grant from the Korea Healthcare Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (HI17C0913), by the National Research Foundation of Korea grant funded from the Ministry of Science and ICT (NRF-2016R1A5A1010764) and Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2017–0–01779, A machine learning and statistical inference framework for explainable artificial intelligence).

All Science Journal Classification (ASJC) codes

  • General

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