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Gao Q, Bi D, Li B, Ni M, Pang D, Li X, Zhang X, Xu Y, Zhao Q, Zhu C. The Association Between Branched-Chain Amino Acid Concentrations and the Risk of Autism Spectrum Disorder in Preschool-Aged Children. Mol Neurobiol 2024; 61:6031-6044. [PMID: 38265552 PMCID: PMC11249470 DOI: 10.1007/s12035-024-03965-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 01/15/2024] [Indexed: 01/25/2024]
Abstract
Several studies have linked branched-chain amino acid (BCAA) metabolism disorders with autism spectrum disorder (ASD), but the results have been inconsistent. The purpose of this study was to explore the association between BCAA concentrations and the risk of ASD. A total of 313 participants were recruited from two tertiary referral hospitals from May 2018 to July 2021. Concentrations of BCAAs in dried blood spots were analyzed using liquid chromatography-tandem mass spectrometry-based analysis. Multivariate analyses and restricted cubic spline models were used to identify the association between BCAAs and the risk of ASD, and a nomogram was developed by using multivariate logistic regression and the risk was determined by receiver operating characteristic curve analysis and calibration curve analysis. Concentrations of total BCAA, valine, and leucine/isoleucine were higher in the ASD group, and all of them were positively and non-linearly associated with the risk of ASD even after adjusting for potential confounding factors such as age, gender, body mass index, and concentrations of BCAAs (P < 0.05). The nomogram integrating total BCAA and valine showed a good discriminant AUC value of 0.756 (95% CI 0.676-0.835). The model could yield net benefits across a reasonable range of risk thresholds. In the stratified analysis, the diagnostic ability of the model was more pronounced in children older than 3 years. We provide evidence that increased levels of BCAAs are associated with the risk of ASD, and the nomogram model of BCAAs presented here can serve as a marker for the early diagnosis of ASD.
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Affiliation(s)
- Qi Gao
- Key Clinical Laboratory of Henan Province, Department of Clinical Laboratory, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Dan Bi
- Department of Pediatrics, Qilu Hospital of Shandong University, No. 107, Wen Hua Xi Road, Jinan, 250012, Shandong, China
| | - Bingbing Li
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Third Affiliated Hospital and Institute of Neuroscience of Zhengzhou University, Zhengzhou, 450052, China
| | - Min Ni
- Department of Henan Newborn Screening Center, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450054, China
| | - Dizhou Pang
- Center for Child Behavioral Development, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Xian Li
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Xiaoli Zhang
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Third Affiliated Hospital and Institute of Neuroscience of Zhengzhou University, Zhengzhou, 450052, China
| | - Yiran Xu
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Third Affiliated Hospital and Institute of Neuroscience of Zhengzhou University, Zhengzhou, 450052, China
| | - Qiang Zhao
- Key Clinical Laboratory of Henan Province, Department of Clinical Laboratory, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
| | - Changlian Zhu
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Third Affiliated Hospital and Institute of Neuroscience of Zhengzhou University, Zhengzhou, 450052, China.
- Center for Brain Repair and Rehabilitation, Institute of Neuroscience and Physiology, University of Gothenburg, 40530, Gothenburg, Sweden.
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Fu Y, Wang Y, Ren H, Guo X, Han L. Branched-chain amino acids and the risks of dementia, Alzheimer's disease, and Parkinson's disease. Front Aging Neurosci 2024; 16:1369493. [PMID: 38659706 PMCID: PMC11040674 DOI: 10.3389/fnagi.2024.1369493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/25/2024] [Indexed: 04/26/2024] Open
Abstract
Background We aimed to examine the association between blood levels of Branched-chain amino acids (BCAAs) - specifically isoleucine, leucine, and valine - and the susceptibility to three neurodegenerative disorders: dementia, Alzheimer's disease (AD), and Parkinson's disease (PD). Methods Based on data from the UK Biobank, a Cox proportional hazard regression model and a dose-response relationship were used to analyze the association between BCAAs and the risks of dementia, AD, and PD. We also generated a healthy lifestyle score and a polygenic risk score. Besides, we conducted a sensitivity analysis to ensure the robustness of our findings. Results After adjusting for multiple covariates, blood concentrations of isoleucine, leucine, and valine were significantly associated with a reduced risk of dementia and AD. This association remained robust even in sensitivity analyses. Similarly, higher levels of isoleucine and leucine in the blood were found to be associated with an increased risk of PD, but this positive correlation could potentially be explained by the presence of covariates. Further analysis using a dose-response approach revealed that a blood leucine concentration of 2.14 mmol/L was associated with the lowest risk of dementia. Conclusion BCAAs have the potential to serve as a biomarker for dementia and AD. However, the specific mechanism through which BCAAs are linked to the development of dementia, AD, and PD remains unclear and necessitates additional investigation.
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Affiliation(s)
- Yidong Fu
- Department of Rehabilitation Medicine, Ningbo No. 2 Hospital, Ningbo, China
| | - Yue Wang
- School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Huiming Ren
- Department of Rehabilitation Medicine, Ningbo No. 2 Hospital, Ningbo, China
| | - Xu Guo
- Department of Rehabilitation Medicine, Ningbo No. 2 Hospital, Ningbo, China
| | - Liyuan Han
- Department of Clinical Epidemiology, Ningbo No. 2 Hospital, Ningbo, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
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Flores AC, Zhang X, Kris-Etherton PM, Sliwinski MJ, Shearer GC, Gao X, Na M. Metabolomics and Risk of Dementia: A Systematic Review of Prospective Studies. J Nutr 2024; 154:826-845. [PMID: 38219861 DOI: 10.1016/j.tjnut.2024.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/16/2024] Open
Abstract
BACKGROUND The projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and progression. Identifying novel biomarkers in the preclinical or prodromal phase of dementia may be important for predicting early disease risk. Applying metabolomic techniques to prediagnostic samples in prospective studies provides the opportunity to identify potential disease biomarkers. OBJECTIVE The objective of this systematic review was to summarize the evidence on the associations between metabolite markers and risk of dementia and related dementia subtypes in human studies with a prospective design. DESIGN We searched PubMed, PsycINFO, and Web of Science databases from inception through December 8, 2023. Thirteen studies (mean/median follow-up years: 2.1-21.0 y) were included in the review. RESULTS Several metabolites detected in biological samples, including amino acids, fatty acids, acylcarnitines, lipid and lipoprotein variations, hormones, and other related metabolites, were associated with risk of developing dementia. Our systematic review summarized the adjusted associations between metabolites and dementia risk; however, our findings should be interpreted with caution because of the heterogeneity across the included studies and potential sources of bias. Further studies are warranted with well-designed prospective cohort studies that have defined study populations, longer follow-up durations, the inclusion of additional diverse biological samples, standardization of techniques in metabolomics and ascertainment methods for diagnosing dementia, and inclusion of other related dementia subtypes. CONCLUSIONS This study contributes to the limited systematic reviews on metabolomics and dementia by summarizing the prospective associations between metabolites in prediagnostic biological samples with dementia risk. Our review discovered additional metabolite markers associated with the onset of developing dementia and may help aid in the understanding of dementia etiology. The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/prospero/; registration ID: CRD42022357521).
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Affiliation(s)
- Ashley C Flores
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Xinyuan Zhang
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Penny M Kris-Etherton
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Martin J Sliwinski
- Center for Healthy Aging, The Pennsylvania State University, University Park, PA, United States; Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, United States
| | - Greg C Shearer
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Xiang Gao
- School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
| | - Muzi Na
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States.
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Bhalala OG, Watson R, Yassi N. Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease. Int J Mol Sci 2024; 25:1231. [PMID: 38279230 PMCID: PMC10816901 DOI: 10.3390/ijms25021231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 01/28/2024] Open
Abstract
Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.
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Affiliation(s)
- Oneil G. Bhalala
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia; (R.W.); (N.Y.)
- Department of Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
| | - Rosie Watson
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia; (R.W.); (N.Y.)
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
| | - Nawaf Yassi
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia; (R.W.); (N.Y.)
- Department of Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3050, Australia
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