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EARLY DIAGNOSIS OF NEUROLOGICAL DISEASE USING PEAK DEGENERATION AGES OF MULTIPLE BIOMARKERS.

ABSTRACT: Neurological diseases are due to the loss of structure or function of neurons that eventually leads to cognitive deficit, neuropsychiatric symptoms, and impaired activities of daily living. Identifying sensitive and specific biological and clinical markers for early diagnosis allows recruiting patients into a clinical trial to test therapeutic intervention. However, many biomarker studies considered a single biomarker at one time that fails to provide precise prediction for disease age at onset. In this paper, we use longitudinally collected measurements from multiple biomarkers and measurement error-corrected clinical diagnosis ages to identify which biomarkers and what features of biomarker trajectories are useful for early diagnosis. Specifically, we assume that the subject-specific biomarker trajectories depend on unobserved states of underlying latent variables with the conditional mean follows a nonlinear sigmoid shape. We show that peak degeneration age of the biomarker trajectory is useful for early diagnosis. We propose an Expectation-Maximization (EM) algorithm to obtain the maximum likelihood estimates of all parameters and conduct extensive simulation studies to examine the performance of the proposed methods. Finally, we apply our methods to studies of Alzheimer's disease and Huntington's disease and identify a few important biomarkers that can be used for early diagnosis.

SUBMITTER: Gao F

PROVIDER: S-EPMC6822567 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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EARLY DIAGNOSIS OF NEUROLOGICAL DISEASE USING PEAK DEGENERATION AGES OF MULTIPLE BIOMARKERS.

Gao Fei F Wang Yüanjia Y Zeng Donglin D

The annals of applied statistics 20190617 2

Neurological diseases are due to the loss of structure or function of neurons that eventually leads to cognitive deficit, neuropsychiatric symptoms, and impaired activities of daily living. Identifying sensitive and specific biological and clinical markers for early diagnosis allows recruiting patients into a clinical trial to test therapeutic intervention. However, many biomarker studies considered a single biomarker at one time that fails to provide precise prediction for disease age at onset. ...[more]

PMID: 31673303

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Project description:MicroRNA (miRNA or miR) is stably present in plasma. It has been reported that miRNA could be used for detecting cancer. Circulating miRNAs are being increasingly recognized as powerful biomarkers in a number of different pathologies, including in breast cancer. The aim of the current study was to establish and validate miRNA sets that are useful for the early diagnosis of breast cancer. Specifically, the current study intended to determine whether miRNA biomarkers were tumor-specific and to statistically verify whether circulating miRNA analysis could be used for breast cancer diagnosis. In the present study, a total of nine candidate miRNA biomarkers were selected by examining reference miRNAs associated with the generation and progression of breast cancer to identify novel miRNAs that could be used to detect early breast cancer. A total of 226 plasma samples from patients with breast cancer were used. In addition, 146 plasma healthy samples were used as non-cancer controls. These samples were divided into training and validation cohorts. The training cohort was used to identify a combination of miRNA that could detect breast cancer. The validation cohort was used to validate this combination of miRNA. Total RNAs were isolated from collected samples. A total of 9 miRNAs were quantified using reverse-transcription quantitative PCR. A total of nine candidate miRNA expression levels were compared between patients with breast cancer and healthy controls. It was indicated that combinations of two or more of the nine miRNAs could detect breast cancer with higher accuracy than the use of a single biomarker. As a representative example, combinations of four miRNAs (miR-1246+miR-206+miR-24+miR-373) of the nine miRNAs had a sensitivity of 98%, a specificity of 96% and an accuracy of 97% for breast cancer detection in the validation cohort. The results of the present study suggest that multiple miRNAs could be used as potential biomarkers for early diagnosis of breast cancer. These biomarkers are expected to overcome limitations of mammography when used as an auxiliary diagnosis of mammography.

Dataset Information

EARLY DIAGNOSIS OF NEUROLOGICAL DISEASE USING PEAK DEGENERATION AGES OF MULTIPLE BIOMARKERS.

Publications

EARLY DIAGNOSIS OF NEUROLOGICAL DISEASE USING PEAK DEGENERATION AGES OF MULTIPLE BIOMARKERS.

Similar Datasets

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