Boyang Ji

Dr. Boyang Ji

Department of Biology and Biological Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden
orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 February 2022 in Nature Medicine
Verified
Journal Article
Open access
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SFSebastien Fromentin
Sebastien Fromentin
SFSofia Kirke Forslund
Sofia Kirke Forslund
KCKanta Chechi
Kanta Chechi
JAJudith Aron-Wisnewsky
Judith Aron-Wisnewsky
RCRima Chakaroun
Rima Chakaroun
OPOluf Pedersen
Oluf Pedersen
Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.

3 April 2017 in Nature Microbiology
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Journal Article
Closed access
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JNJens Christian Nielsen
Jens Christian Nielsen
SGSietske Grijseels
Sietske Grijseels
SPSylvain Prigent
Sylvain Prigent
Boyang JiBoyang Ji
Boyang Ji
JDJacques Dainat
Jacques Dainat
JNJens Nielsen
Jens Nielsen

8 December 2021 in Nature
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Journal Article
Closed access
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SFSofia Kirke Forslund
Sofia Kirke Forslund
RCRima Chakaroun
Rima Chakaroun
MZMaria Zimmermann-Kogadeeva
Maria Zimmermann-Kogadeeva
LMLajos Marko
Lajos Marko
JAJudith Aron-Wisnewsky
Judith Aron-Wisnewsky
PBPeer Bork
Peer Bork

1 October 2020 in Bioresource Technology
Verified
Journal Article
Closed access
JWJinpeng Wang
Jinpeng Wang
RLRodrigo Ledesma-Amaro
Rodrigo Ledesma-Amaro
Yongjun WeiYongjun Wei
Yongjun Wei
Boyang JiBoyang Ji
Boyang Ji
Xiao-Jun JiXiao-Jun Ji
Xiao-Jun Ji

23 July 2019 in Nature Microbiology
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Journal Article
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PDF file
MKManish Kumar
Manish Kumar
Boyang JiBoyang Ji
Boyang Ji
KZKarsten Zengler
Karsten Zengler
JNJens Nielsen
Jens Nielsen

21 April 2016 in Nutrition and Healthy Aging
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Journal Article
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MKManish Kumar
Manish Kumar
PBParizad Babaei
Parizad Babaei
Boyang JiBoyang Ji
Boyang Ji
JNJens Nielsen
Jens Nielsen
The human gut microbiota alters with the aging process. In the first 2-3 years of life, the gut microbiota varies extensively in composition and metabolic functions. After this period, the gut microbiota demonstrates adult-like more stable and diverse microbial species. However, at old age, deterioration of physiological functions of the human body enforces the decrement in count of beneficial species (e.g. Bifidobacteria) in the gut microbiota, which promotes various gut-related diseases (e.g. inflammatory bowel disease). Use of plant-based diets and probiotics/prebiotics may elevate the abundance of beneficial species and prevent gut-related diseases. Still, the connections between diet, microbes, and host are only partially known. To this end, genome-scale metabolic modeling can help to explore these connections as well as to expand the understanding of the metabolic capability of each species in the gut microbiota. This systems biology approach can also predict metabolic variations in the gut microbiota during ageing, and hereby help to design more effective probiotics/prebiotics.