Modelling biological age based on plasma peptides in Han Chinese adults

Cao, Weijie; Zheng, Deqiang; Wang, Guohua; Zhang, Jie; Ge, Siqi; Singh, Manjot; Wang, Hao; Song, Manshu; Liu, Dong; Wang, Wei; Xu, Xizhu; Wang, Youxin

doi:10.18632/aging.103286

Cited by 13 publications

(11 citation statements)

References 45 publications

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“…In the mouse brain, C4A gene is mainly expressed in astrocytes and neurons 44 . C4A is involved in the classical complement activation pathway 45 and was reported to be associated with schizophrenia, aging, and Alzheimer’s disease 34 , 46 , 47 . Moreover, genetic variants in BTN3A2 and C4A were in different LD blocks, suggesting that both genes might be independent risk factors for mental disorders such as schizophrenia and MDD 37 .…”

Section: Discussionmentioning

confidence: 99%

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

et al. 2021

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Previous genome-wide association studies (GWAS) have identified potential genetic variants associated with the risk of major depressive disorder (MDD), but the underlying biological interpretation remains largely unknown. We aimed to prioritize genes that were pleiotropically or potentially causally associated with MDD. We applied the summary data-based Mendelian randomization (SMR) method integrating GWAS and gene expression quantitative trait loci (eQTL) data in 13 brain regions to identify genes that were pleiotropically associated with MDD. In addition, we repeated the analysis by using the meta-analyzed version of the eQTL summary data in the brain (brain-eMeta). We identified multiple significant genes across different brain regions that may be involved in the pathogenesis of MDD. The prime-specific gene BTN3A2 (corresponding probe: ENSG00000186470.9) was the top hit showing pleiotropic association with MDD in 9 of the 13 brain regions and in brain-eMeta, after correction for multiple testing. Many of the identified genes are located in the human major histocompatibility complex (MHC) region on chromosome 6 and are mainly involved in the immune response. Our SMR analysis indicated that multiple genes showed pleiotropic association with MDD across the brain regions. These findings provided important leads to a better understanding of the mechanism of MDD and revealed potential therapeutic targets for the prevention and effective treatment of MDD.

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Section: Discussionmentioning

confidence: 99%

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

et al. 2021

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“…Developing aging measures for the Chinese population is of great significance to solve aging-related issues in this large country, such as facilitating the early identification of adults at risk. To date, a few relevant studies have been conducted in the Chinese population (5,8,(19)(20)(21)(22)(23). Most of them used the multiple linear regression method (19,23) or the principal component analysis method (8,20,22).…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning-Based Aging Measure Among Middle-Aged and Older Chinese Adults: The China Health and Retirement Longitudinal Study

et al. 2021

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Objective: Biological age (BA) has been accepted as a more accurate proxy of aging than chronological age (CA). This study aimed to use machine learning (ML) algorithms to estimate BA in the Chinese population.Materials and methods: We used data from 9,771 middle-aged and older Chinese adults (≥45 years) in the 2011/2012 wave of the China Health and Retirement Longitudinal Study and followed until 2018. We used several ML algorithms (e.g., Gradient Boosting Regressor, Random Forest, CatBoost Regressor, and Support Vector Machine) to develop new measures of biological aging (ML-BAs) based on physiological biomarkers. R-squared value and mean absolute error (MAE) were used to determine the optimal performance of these ML-BAs. We used logistic regression models to examine the associations of the best ML-BA and a conventional aging measure—Klemera and Doubal method-BA (KDM-BA) we previously developed—with physical disability and mortality, respectively.Results: The Gradient Boosting Regression model performed the best, resulting in an ML-BA with an R-squared value of 0.270 and an MAE of 6.519. This ML-BA was significantly associated with disability in basic activities of daily living, instrumental activities of daily living, lower extremity mobility, and upper extremity mobility, and mortality, with odds ratios ranging from 1 to 7% (per 1-year increment in ML-BA, all P < 0.001), independent of CA. These associations were generally comparable to that of KDM-BA.Conclusion: This study provides a valid ML-based measure of biological aging for middle-aged and older Chinese adults. These findings support the application of ML in geroscience research and may help facilitate preventive and geroprotector intervention studies.

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“…In the mouse brain, C4A gene is mainly expressed in astrocyte and neurons [42]. C4A is involved in the classical complement activation pathway [43] and was reported to be associated with schizophrenia, aging and Alzheimer’s disease [32,44,45]. Moreover, genetic variants in BTN3A2 and C4A were in different LD blocks, suggesting that both genes might be independent risk factors for mental disorders such as schizophrenia and MDD [35].…”

Section: Discussionmentioning

confidence: 99%

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

Yang

Liu

Zhao

et al. 2020

Preprint

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Objectives: To prioritize genes that are pleiotropically or potentially causally associated with the risk of MDD. Methods: We applied the summary data-based Mendelian randomization (SMR) method integrating GWAS and expression quantitative trait loci (eQTL) data in 13 brain regions to identify genes that were pleiotropically associated with the risk of MDD. In addition, we repeated the analysis by using the meta-analyzed version of the eQTL summary data in the brain (brain-eMeta). Results: We identified multiple significant genes across different brain regions that may be involved in the pathogenesis of MDD. The prime-specific gene BTN3A2 (corresponding probe: ENSG00000186470.9) was the top hit showing pleotropic association with MDD in 9 of the 13 brain regions and in brain-eMeta, after correction for multiple testing. Many of the identified genes are located in the human major histocompatibility complex (MHC) region on chromosome 6 and are mainly involved in immune response. Conclusions: Our SMR analysis revealed that multiple genes showed pleiotropic association with MDD across the brain regions. These findings provide important leads to a better understanding of the mechanism of MDD, and reveals potential therapeutic targets for the prevention and effective treatment of MDD.

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Modelling biological age based on plasma peptides in Han Chinese adults

Cited by 13 publications

References 45 publications

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

A Machine Learning-Based Aging Measure Among Middle-Aged and Older Chinese Adults: The China Health and Retirement Longitudinal Study

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

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