Dataset Information

Perifovea retinal thickness as an ophthalmic biomarker for mild cognitive impairment and early Alzheimer's disease.

ABSTRACT:

Introduction

The aim of this study was to investigate retinal thickness as a biomarker for identifying patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

Methods

The retinal thickness, utilizing the spectral domain optical coherence tomography, was compared among 73 patients with AD, 51 patients with MCI, 67 cognitive normal control (NC) subjects.

Results

The retinal thickness of ganglion cell complex and peripapillary retinal nerve fiber layer decreased in both AD and MCI patients, in comparison with NC subjects (AD vs. NC, P < .01; MCI vs. NC, P < .01). The inner retinal layers in macular area in MCI exhibited significant thinning compared with NC (P < .001). Remarkable association was found between the retinal thickness and brain volume (P < .05). Better correlation was seen between the inner perifovea retinal thickness and the hippocampal and entorhinal cortex volume (r: 0.427-0.644, P < .01).

Discussion

The retinal thickness, especially the inner retinal layer thickness, is a potentially early AD marker indicating neurodegeneration.

SUBMITTER: Tao R

PROVIDER: S-EPMC6558027 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Publications

Perifovea retinal thickness as an ophthalmic biomarker for mild cognitive impairment and early Alzheimer's disease.

Tao Rui R Lu Zhaozeng Z Ding Ding D Fu Shuhao S Hong Zhen Z Liang Xiaoniu X Zheng Li L Xiao Yiqin Y Zhao Qianhua Q

Alzheimer's & dementia (Amsterdam, Netherlands) 20190606

<h4>Introduction</h4>The aim of this study was to investigate retinal thickness as a biomarker for identifying patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD).<h4>Methods</h4>The retinal thickness, utilizing the spectral domain optical coherence tomography, was compared among 73 patients with AD, 51 patients with MCI, 67 cognitive normal control (NC) subjects.<h4>Results</h4>The retinal thickness of ganglion cell complex and peripapillary retinal nerve fiber layer decr ...[more]

PMID: 31206006

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Project description:<h4><strong>INTRODUCTION </strong>Alzheimer's disease is a prevalent disease with a heavy global burden and is suggested to be a metabolic disease in the brain in recent years. The metabolome is considered to be the most promising phenotype which reflects changes in genetic, transcript, and protein profiles as well as environmental effects. Aiming to obtain a comprehensive understanding and convenient diagnosis of MCI and AD from another perspective, researchers are working on AD metabolomics. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.</h4><p><strong>METHODS </strong>We first enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples and conducted an LC-MS/MS analysis. In parallel, clinical data were collected and clinical examinations were performed. After statistical and bioinformatics analyzes, significant risk factors and differential urinary metabolites were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.</p><p><strong>RESULTS </strong>57 AD patients, 43 MCI patients and 62 CN subjects were enrolled. A total of 2,140 metabolites were identified among which 125 significantly differed between the AD and CN groups, including 46 upregulated ones and 79 downregulated ones. In parallel, there were 93 significant differential metabolites between the MCI and CN groups, including 23 upregulated ones and 70 downregulated ones. AD diagnostic panel (30 metabolites+ age + APOE) achieved an AUC of 0.9575 in the test set while MCI diagnostic panel (45 metabolites+ age + APOE) achieved an AUC of 0.7333 in the test set. Atropine, S-Methyl-L-cysteine-S-oxide, D-Mannose 6-phosphate (M6P), Spiculisporic Acid, N-Acetyl-L-methionine, 13,14-dihydro-15-keto-tetranor Prostaglandin D2, Pyridoxal 5'-Phosphate (PLP) and 17(S)-HpDHA were considered valuable for both AD and MCI diagnosis and defined as hub metabolites. Besides, diagnostic metabolites were weakly correlated with cognitive functions.</p><p><strong>DISCUSSION </strong>In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN. Atropine, M6P and PLP were evidence-based hub metabolites in AD.</p>

Dataset Information

Perifovea retinal thickness as an ophthalmic biomarker for mild cognitive impairment and early Alzheimer's disease.

Introduction

Methods

Results

Discussion

Publications

Perifovea retinal thickness as an ophthalmic biomarker for mild cognitive impairment and early Alzheimer's disease.

Similar Datasets

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