Circulating glucuronic acid predicts healthspan and longevity in humans and mice

Ho, Ambrose Chung–Wai; Sinick, Jonah; Esko, Tõnu; Fischer, Krista; Menni, Cristina; Zierer, Jonas; Matey-Hernandez, Maria; Fortney, Kristen; Morgen, Eric

doi:10.18632/aging.102281

Cited by 15 publications

(18 citation statements)

References 91 publications

(74 reference statements)

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“…Multiple mechanisms may underlie the increased levels of glucuronic acid. One of the most reasonable possibilities involves the cleavage of glucuronic acid from glucuronidated xenobiotics by gut β-glucuronidase-bacteria [ 65 ]. Escherichia are among the opportunistic pathogens in the human gut that harbor a β-glucuronidase enzyme [ 66 , 67 ] and cause the release of glucuronic acid and, consequently, of xenobiotics, such as environmental toxins and drug metabolites with pro-inflammatory effects, that interfere with their inactivation and elimination via the GI tract [ 65 , 68 ].…”

Section: Discussionmentioning

confidence: 99%

Clinical Phenotypes of Parkinson’s Disease Associate with Distinct Gut Microbiota and Metabolome Enterotypes

Melis¹,

Palmas

Pisanu

et al. 2021

Biomolecules

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Parkinson’s disease (PD) is a clinically heterogenic disorder characterized by distinct clinical entities. Most studies on motor deficits dichotomize PD into tremor dominant (TD) or non-tremor dominant (non-TD) with akinetic-rigid features (AR). Different pathophysiological mechanisms may affect the onset of motor manifestations. Recent studies have suggested that gut microbes may be involved in PD pathogenesis. The aim of this study was to investigate the gut microbiota and metabolome composition in PD patients in relation to TD and non-TD phenotypes. In order to address this issue, gut microbiota and the metabolome structure of PD patients were determined from faecal samples using 16S next generation sequencing and gas chromatography–mass spectrometry approaches. The results showed a reduction in the relative abundance of Lachnospiraceae, Blautia, Coprococcus, Lachnospira, and an increase in Enterobacteriaceae, Escherichia and Serratia linked to non-TD subtypes. Moreover, the levels of important molecules (i.e., nicotinic acid, cadaverine, glucuronic acid) were altered in relation to the severity of phenotype. We hypothesize that the microbiota/metabolome enterotypes associated to non-TD subtypes may favor the development of gut inflammatory environment and gastrointestinal dysfunctions and therefore a more severe α-synucleinopathy. This study adds important information to PD pathogenesis and emphasizes the potential pathophysiological link between gut microbiota/metabolites and PD motor subtypes.

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“…Repeated measures of blood-based biomarkers in rodents may be limited due to the amount of blood required/available. Previous longitudinal studies in rodents have mainly focused on markers of longevity (Acuna-Castillo et al, 2006;Ho et al, 2019). Thus, a blood-based biomarker concerning cognitive function represents an important area for exploration in future longitudinal studies.…”

Section: Blood Biomarkersmentioning

confidence: 99%

Cognitive Reserve in Model Systems for Mechanistic Discovery: The Importance of Longitudinal Studies

McQuail

Dunn

Stern

et al. 2021

Front. Aging Neurosci.

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The goal of this review article is to provide a resource for longitudinal studies, using animal models, directed at understanding and modifying the relationship between cognition and brain structure and function throughout life. We propose that forthcoming longitudinal studies will build upon a wealth of knowledge gleaned from prior cross-sectional designs to identify early predictors of variability in cognitive function during aging, and characterize fundamental neurobiological mechanisms that underlie the vulnerability to, and the trajectory of, cognitive decline. Finally, we present examples of biological measures that may differentiate mechanisms of the cognitive reserve at the molecular, cellular, and network level.

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“…DSEL (dermatan sulfate epimerase-like) is implicated in D-glucuronic acid metabolism and tumor rejection. A recent study has shown that glucuronic acid levels increase with age and predict future healthspan-related outcomes 40 . Furthermore, DSEL is highly expressed in the brain and has been found associated with AD in an imaging-wide association study 41 .…”

Section: Resultsmentioning

confidence: 99%

Identification of putative causal loci in whole-genome sequencing data via knockoff statistics

Liu

Wang

et al. 2021

Nat Commun

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The analysis of whole-genome sequencing studies is challenging due to the large number of rare variants in noncoding regions and the lack of natural units for testing. We propose a statistical method to detect and localize rare and common risk variants in whole-genome sequencing studies based on a recently developed knockoff framework. It can (1) prioritize causal variants over associations due to linkage disequilibrium thereby improving interpretability; (2) help distinguish the signal due to rare variants from shadow effects of significant common variants nearby; (3) integrate multiple knockoffs for improved power, stability, and reproducibility; and (4) flexibly incorporate state-of-the-art and future association tests to achieve the benefits proposed here. In applications to whole-genome sequencing data from the Alzheimer’s Disease Sequencing Project (ADSP) and COPDGene samples from NHLBI Trans-Omics for Precision Medicine (TOPMed) Program we show that our method compared with conventional association tests can lead to substantially more discoveries.

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“…There is growing interest in predicting the risks for diseases and complex traits using polygenic risk scores (Khera et al, 2018). Previous studies have predicted longevity and life span based mainly on animal models (Huang et al, 2004; Shen et al, 2014; Swindell et al, 2008) or the use of single biomarker (Ho et al, 2019; Whittemore et al, 2019). One recent study using the UK Biobank dataset applied polygenic risk score for life span prediction with good performance but was limited by utilizing summary statistics for life span based on parental data (Timmers et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…For example, a recent genetic study reported that a polygenic score could identify people with the top 10% parental survival PRS, who might outlive an average of 5 years those with the bottom 10% parental survival PRS (Timmers et al, 2019). In addition, circulating glucuronic acid levels (Ho et al, 2019) or telomeres (Whittemore et al, 2019) have been used as biomarkers for life span prediction. To date, there are very few studies that explore the potential of life span prediction by using a combination of genetic data, disease conditions, and lifestyle factors.…”

Section: Introductionmentioning

confidence: 99%

Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals

Liu

Song

et al. 2021

Aging Cell

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There is growing interest in studying the genetic contributions to longevity, but limited relevant genes have been identified. In this study, we performed a genetic association study of longevity in a total of 15,651 Chinese individuals. Novel longevity loci, BMPER (rs17169634; p = 7.91 × 10−15) and TMEM43/XPC (rs1043943; p = 3.59 × 10−8), were identified in a case–control analysis of 11,045 individuals. BRAF (rs1267601; p = 8.33 × 10−15) and BMPER (rs17169634; p = 1.45 × 10−10) were significantly associated with life expectancy in 12,664 individuals who had survival status records. Additional sex‐stratified analyses identified sex‐specific longevity genes. Notably, sex‐differential associations were identified in two linkage disequilibrium blocks in the TOMM40/APOE region, indicating potential differences during meiosis between males and females. Moreover, polygenic risk scores and Mendelian randomization analyses revealed that longevity was genetically causally correlated with reduced risks of multiple diseases, such as type 2 diabetes, cardiovascular diseases, and arthritis. Finally, we incorporated genetic markers, disease status, and lifestyles to classify longevity or not‐longevity groups and predict life span. Our predictive models showed good performance (AUC = 0.86 for longevity classification and explained 19.8% variance of life span) and presented a greater predictive efficiency in females than in males. Taken together, our findings not only shed light on the genetic contributions to longevity but also elucidate correlations between diseases and longevity.

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Circulating glucuronic acid predicts healthspan and longevity in humans and mice

Cited by 15 publications

References 91 publications

Clinical Phenotypes of Parkinson’s Disease Associate with Distinct Gut Microbiota and Metabolome Enterotypes

Cognitive Reserve in Model Systems for Mechanistic Discovery: The Importance of Longitudinal Studies

Identification of putative causal loci in whole-genome sequencing data via knockoff statistics

Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals

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