Dataset Information

Urinary proteome profiling for children with autism using data-independent acquisition proteomics.

ABSTRACT:

Background

Autism is a complex neurodevelopmental disorder. Objective and reliable biomarkers are crucial for the clinical diagnosis of autism. Urine can accumulate early changes of the whole body and is a sensitive source for disease biomarkers.

Methods

The data-independent acquisition (DIA) strategy was used to identify differential proteins in the urinary proteome between autistic and non-autistic children aged 3-7 years. Receiver operating characteristic (ROC) curves were developed to evaluate the diagnostic performance of differential proteins.

Results

A total of 118 differential proteins were identified in the urine between autistic and non-autistic children, of which 18 proteins were reported to be related to autism. Randomized grouping statistical analysis indicated that 91.5% of the differential proteins were reliable. Functional analysis revealed that some differential proteins were associated with axonal guidance signaling, endocannabinoid developing neuron pathway, synaptic long-term depression, agrin interactions at neuromuscular junction, phosphatase and tensin homolog deleted on chromosome 10 (PTEN) signaling and synaptogenesis signaling pathway. The combination of cadherin-related family member 5 (CDHR5) and vacuolar protein sorting-associated protein 4B (VPS4B) showed the best discriminative performance between autistic and non-autistic children with an area under the curve (AUC) value of 0.987.

Conclusions

The urinary proteome could distinguish between autistic children and non-autistic children. This study will provide a promising approach for future biomarker research of neuropsychiatric disorders.

SUBMITTER: Meng W

PROVIDER: S-EPMC8349970 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Publications

Urinary proteome profiling for children with autism using data-independent acquisition proteomics.

Meng Wenshu W Huan Yuhang Y Gao Youhe Y

Translational pediatrics 20210701 7

<h4>Background</h4>Autism is a complex neurodevelopmental disorder. Objective and reliable biomarkers are crucial for the clinical diagnosis of autism. Urine can accumulate early changes of the whole body and is a sensitive source for disease biomarkers.<h4>Methods</h4>The data-independent acquisition (DIA) strategy was used to identify differential proteins in the urinary proteome between autistic and non-autistic children aged 3-7 years. Receiver operating characteristic (ROC) curves were deve ...[more]

PMID: 34430425

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Project description:Diabetic nephropathy (DN), as the one of most common complications of diabetes, is generally diagnosed based on a longstanding duration, albuminuria, and decreased kidney function. Some patients with the comorbidities of diabetes and other primary renal diseases have similar clinical features to DN, which is defined as non-diabetic renal disease (NDRD). It is necessary to distinguish between DN and NDRD, considering they differ in their pathological characteristics, treatment regimes, and prognosis. Renal biopsy provides a gold standard; however, it is difficult for this to be conducted in all patients. Therefore, it is necessary to discover non-invasive biomarkers that can distinguish between DN and NDRD. In this research, the urinary exosomes were isolated from the midstream morning urine based on ultracentrifugation combined with 0.22 μm membrane filtration. Data-independent acquisition-based quantitative proteomics were used to define the proteome profile of urinary exosomes from DN (n = 12) and NDRD (n = 15) patients diagnosed with renal biopsy and Type 2 diabetes mellitus (T2DM) patients without renal damage (n = 9), as well as healthy people (n = 12). In each sample, 3372 ± 722.1 proteins were identified on average. We isolated 371 urinary exosome proteins that were significantly and differentially expressed between DN and NDRD patients, and bioinformatic analysis revealed them to be mainly enriched in the immune and metabolic pathways. The use of least absolute shrinkage and selection operator (LASSO) logistic regression further identified phytanoyl-CoA dioxygenase domain containing 1 (PHYHD1) as the differential diagnostic biomarker, the efficacy of which was verified with another cohort including eight DN patients, five NDRD patients, seven T2DM patients, and nine healthy people. Additionally, a concentration above 1.203 μg/L was established for DN based on the ELISA method. Furthermore, of the 19 significantly different expressed urinary exosome proteins selected by using the protein-protein interaction network and LASSO logistic regression, 13 of them were significantly related to clinical indicators that could reflect the level of renal function and hyperglycemic management.

Dataset Information

Urinary proteome profiling for children with autism using data-independent acquisition proteomics.

Background

Methods

Results

Conclusions

Publications

Urinary proteome profiling for children with autism using data-independent acquisition proteomics.

Similar Datasets

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