Metabolomic Profiling of Open-Angle Glaucoma Etiologic Endotypes: Tohoku Multi-Omics Glaucoma Study

被引：1

作者：

Hanyuda, Akiko ^{[1
,2
,3
]}

Raita, Yoshihiko ^{[4
]}

Ninomiya, Takahiro ^{[3
]}

Hashimoto, Kazuki ^{[3
]}

Takada, Naoko ^{[3
]}

Sato, Kota ^{[3
,5
]}

Inoue, Jin ^{[6
,7
]}

Koshiba, Seizo ^{[6
,7
]}

Tamiya, Gen ^{[6
]}

Narita, Akira ^{[6
]}

Akiyama, Masato ^{[8
,9
]}

Omodaka, Kazuko ^{[3
]}

Tsuda, Satoru ^{[3
]}

Yokoyama, Yu ^{[3
]}

Himori, Noriko ^{[1
,3
,10
]}

Yamamoto, Yasuko ^{[1
,11
]}

Taniguchi, Takazumi ^{[1
,11
]}

Negishi, Kazuno ^{[1
]}

Nakazawa, Toru ^{[3
,5
,12
]}

机构：

[1] Keio Univ, Sch Med, Dept Ophthalmol, Shinjuku Ku, Tokyo, Japan

[2] Natl Canc Ctr, Inst Canc Control, Div Epidemiol, Chuo Ku, Tokyo, Japan

[3] Tohoku Univ, Grad Sch Med, Dept Ophthalmol, 1-1 Seiryo Machi Aoba Ku, Sendai, Miyagi 9808574, Japan

[4] Okinawa Prefectural Chubu Hosp, Dept Nephrol, Uruma, Naha, Japan

[5] Tohoku Univ, Grad Sch Med, Dept Adv Ophthalm Med, Aoba Ku, Sendai, Miyagi, Japan

[6] Tohoku Univ, Dept Integrat Genom, Tohoku Med Megabank Org, Aoba Ku, Sendai, Miyagi, Japan

[7] Tohoku Univ, Adv Res Ctr Innovat Next Generat Med INGEM, Aoba Ku, Sendai, Miyagi, Japan

[8] Kyushu Univ, Grad Sch Med Sci, Dept Ocular Pathol & Imaging Sci, Higashi Ku, Fukuoka, Japan

[9] Kyushu Univ, Grad Sch Med Sci, Dept Otolaryngol, Higashi Ku, Fukuoka, Japan

[10] Tohoku Univ, Grad Sch Biomed Engn, Dept Aging Vis Healthcare, Aoba Ku, Sendai, Miyagi, Japan

[11] Santen Pharmaceut Co Ltd, Ophthalmol Innovat Ctr, Ikoma, Nara, Japan

[12] Tohoku Univ, Grad Sch Med, Dept Retinal Dis Control, Ophthalmol, Aoba Ku, Sendai, Miyagi, Japan

来源：

INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE | 2024年 / 65卷 / 13期

基金：

日本科学技术振兴机构;

关键词：

endotypes; glaucoma; machine learning (ML); metabolomics; pathophysiology; HEAD BLOOD-FLOW; VISUAL-FIELD; MITOCHONDRIAL DYSFUNCTION; INTRAOCULAR-PRESSURE; COMMON VARIANTS; ASSOCIATION; RISK;

D O I：

10.1167/iovs.65.13.44

中图分类号：

R77 [眼科学];

学科分类号：

100212 ;

摘要：

PURPOSE . The purpose of this study was to investigate biologically meaningful endotypes of open-angle glaucoma (OAG) by applying unsupervised machine learning to plasma metabolites. METHODS . This retrospective longitudinal cohort study enrolled consecutive patients aged >= 20 years with OAG at Tohoku University Hospital from January 2017 to January 2020. OAG was confirmed based on comprehensive ophthalmic examinations. Among the 523 patients with OAG with available clinical metabolomic data, 173 patients were longitudinally followed up for >= 2 years, with available data from >= 5 reliable visual field (VF) tests without glaucoma surgery. We collected fasting blood samples and clinical data at enrollment and nuclear magnetic resonance spectroscopy to profile 45 plasma metabolites in a targeted approach. After computing a distance matrix of preprocessed metabolites with Pearson distance, gap statistics determined the optimal number of OAG endotypes. Its risk factors, clinical presentations, metabolomic profiles, and progression rate of sector- based VF loss were compared across endotypes. RESULTS . Five distinct OAG endotypes were identified. The highest-risk endotype (endotype B) showed a significant faster progression of central VF loss (P = 0.007). Compared with patients with other endotypes, those with endotype B were more likely to have a high prevalence of dyslipidemia, cold extremities, oxidative stress, and low OAG genetic risk scores. Pathway analysis of metabolomic profiles implicated altered fatty acid and ketone body metabolism in this endotype, with 34 differentially enriched pathways (false discovery rate [FDR] < 0.05). CONCLUSIONS . Integrated metabolomic profiles identified five distinct etiologic endotypes of OAG, suggesting pathological mechanisms related with a high-risk group of central vision loss progression in the Japanese population.

引用

页数：11

共 59 条

[31] Comparative analysis of tear cytokines in patients with glaucoma, ocular hypertension, and healthy controls [J].