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GlycA, a novel marker for low grade inflammation, reflects gut microbiome diversity and is more accurate than high sensitive CRP in reflecting metabolomic profile.

ABSTRACT: INTRODUCTION:Gut microbiota is, along with adipose tissue, recognized as a source for many metabolic and inflammatory disturbances that may contribute to the individual's state of health. OBJECTIVES:We investigated in cross-sectional setting the feasibility of utilizing GlycA, a novel low grade inflammatory marker, and traditional low grade inflammatory marker, high sensitivity CRP (hsCRP), in reflecting serum metabolomics status and gut microbiome diversity. METHODS:Fasting serum samples of overweight/obese pregnant women (n?=?335, gestational weeks: mean 13.8) were analysed for hsCRP by immunoassay, GlycA and metabolomics status by NMR metabolomics and faecal samples for gut microbiome diversity by metagenomics. The benefits of GlycA as a metabolic marker were investigated against hsCRP. RESULTS:The GlycA concentration correlated with more of the metabolomics markers (144 out of 157), than hsCRP (55 out of 157) (FDR?

SUBMITTER: Mokkala K

PROVIDER: S-EPMC7306047 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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GlycA, a novel marker for low grade inflammation, reflects gut microbiome diversity and is more accurate than high sensitive CRP in reflecting metabolomic profile.

Mokkala Kati K Houttu Noora N Koivuniemi Ella E Sørensen Nikolaj N Nielsen Henrik Bjørn HB Laitinen Kirsi K

Metabolomics : Official journal of the Metabolomic Society 20200620 7

<h4>Introduction</h4>Gut microbiota is, along with adipose tissue, recognized as a source for many metabolic and inflammatory disturbances that may contribute to the individual's state of health.<h4>Objectives</h4>We investigated in cross-sectional setting the feasibility of utilizing GlycA, a novel low grade inflammatory marker, and traditional low grade inflammatory marker, high sensitivity CRP (hsCRP), in reflecting serum metabolomics status and gut microbiome diversity.<h4>Methods</h4>Fastin ...[more]

PMID: 32564244

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Project description:Although the primary objective of forensic DNA analyses of unidentified human remains is positive identification, cases involving historical or archaeological skeletal remains often lack reference samples for comparison. Massively parallel sequencing (MPS) offers an opportunity to provide biometric data in such cases, and these cases provide valuable data on the feasibility of applying MPS for characterization of modern forensic casework samples. In this study, MPS was used to characterize 140-year-old human skeletal remains discovered at a historical site in Deadwood, South Dakota, United States. The remains were in an unmarked grave and there were no records or other metadata available regarding the identity of the individual. Due to the high throughput of MPS, a variety of biometric markers could be typed using a single sample.Using MPS and suitable forensic genetic markers, more relevant information could be obtained from a limited quantity and quality sample. Results were obtained for 25/26 Y-STRs, 34/34 Y SNPs, 166/166 ancestry-informative SNPs, 24/24 phenotype-informative SNPs, 102/102 human identity SNPs, 27/29 autosomal STRs (plus amelogenin), and 4/8 X-STRs (as well as ten regions of mtDNA). The Y-chromosome (Y-STR, Y-SNP) and mtDNA profiles of the unidentified skeletal remains are consistent with the R1b and H1 haplogroups, respectively. Both of these haplogroups are the most common haplogroups in Western Europe. Ancestry-informative SNP analysis also supported European ancestry. The genetic results are consistent with anthropological findings that the remains belong to a male of European ancestry (Caucasian). Phenotype-informative SNP data provided strong support that the individual had light red hair and brown eyes.This study is among the first to genetically characterize historical human remains with forensic genetic marker kits specifically designed for MPS. The outcome demonstrates that substantially more genetic information can be obtained from the same initial quantities of DNA as that of current CE-based analyses.

Dataset Information

GlycA, a novel marker for low grade inflammation, reflects gut microbiome diversity and is more accurate than high sensitive CRP in reflecting metabolomic profile.

Publications

GlycA, a novel marker for low grade inflammation, reflects gut microbiome diversity and is more accurate than high sensitive CRP in reflecting metabolomic profile.

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