Article, 2024
Review: Opportunities and barriers for omics-based biomarker discovery in steatotic liver diseases
Journal of Hepatology,
ISSN
1600-0641,
0168-8278,
10.1016/j.jhep.2024.03.035
Contributors
Thiele, Maja Sofie
0000-0003-1854-1924
[1]
[2]
Villesen, Ida Falk
0000-0001-7921-9707
[1]
[2]
Niu, Lili
0000-0003-4571-4368
[3]
[4]
Johansen, Stine
0000-0002-5031-2294
[1]
Sulek, Karolina
[5]
Nishijima, Suguru
0000-0002-8444-9272
[6]
Van Espen, Lore
0000-0002-3870-4551
[7]
[8]
Keller, Marisa Isabell
0000-0002-1485-415X
[6]
Israelsen, Mads Egerod
0000-0001-9443-5846
[1]
[2]
Suvitaival, Tommi
0000-0002-2583-4912
[5]
De Zawadzki, Andressa
0000-0002-7442-3474
[5]
Juel, Helene Baek
0000-0002-5763-8545
[3]
Brol, Maximilian Joseph
0000-0003-2879-7560
[9]
Stinson, Sara Elisabeth
[3]
Huang, Yun
[3]
Silva, Maria Camilla Alvarez
[3]
Kuhn, Michael
0000-0002-2841-872X
[6]
Anastasiadou, Ema
[10]
Leeming, Diana Julie
[11]
Karsdal, Morten Asser
0000-0002-4764-5100
[11]
Matthijnssens, Jelle
0000-0003-1188-9733
[7]
[8]
Arumugam, Manimozhiyan
[3]
Dalgaard, Louise Torp
0000-0002-3598-2775
[12]
Legido-Quigley, Cristina
0000-0002-4018-214X
[5]
Mann, Matthias
[3]
[4]
Trebicka, Jonel
[9]
Bork, Peer
0000-0002-2627-833X
[6]
[13]
[14]
Jensen, Lars Juhl
0000-0001-7885-715X
[3]
Hansen, Torben
[3]
Krag, Aleksander Ahm
0000-0002-9598-4932
(Corresponding author)
[1]
[2]
consortia, the MicrobLiver and GALAXY
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
Consortium, Galaxy
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
Krag, Aleksander
Bork, Peer
Hansen, Torben
Arumugam, Manimozhiyan
Trebicka, Jonel
Karsdal, Morten
Anastasiadou, Ema
Israelsen, Hans
Melberg, Hans Olav
0000-0002-2349-5902
Legido-Quigley, Cristina
Thiele, Maja
Consortium, Microbliver
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
Mann, Matthias
Matthijnssens, Jelle
Affiliations
- [1]
Odense University Hospital
[NORA names:
Region of Southern Denmark; Hospital; Denmark; Europe, EU; Nordic; OECD];
- [2]
University of Southern Denmark
[NORA names:
SDU University of Southern Denmark; University; Denmark; Europe, EU; Nordic; OECD];
- [3]
University of Copenhagen
[NORA names:
KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD];
- [4]
Max Planck Institute of Biochemistry
[NORA names:
Germany; Europe, EU; OECD];
- [5]
Steno Diabetes Center
[NORA names:
Steno Diabetes Centers; Hospital; Denmark; Europe, EU; Nordic; OECD];
(... more)
- [6]
European Molecular Biology Laboratory
[NORA names:
Germany; Europe, EU; OECD];
- [7]
KU Leuven
[NORA names:
Belgium; Europe, EU; OECD];
- [8]
Rega Institute for Medical Research
[NORA names:
Belgium; Europe, EU; OECD];
- [9]
University of Münster
[NORA names:
Germany; Europe, EU; OECD];
- [10]
Idryma Iatroviologikon Ereunon Akademias Athinon, Greece
[NORA names:
Greece; Europe, EU; OECD];
- [11]
Nordic Bioscience (Denmark)
[NORA names:
Nordic Bioscience;
Private Research; Denmark; Europe, EU; Nordic; OECD];
- [12]
Roskilde University
[NORA names:
RUC Roskilde University;
University; Denmark; Europe, EU; Nordic; OECD];
- [13]
Max Delbrück Center for Molecular Medicine
[NORA names:
Germany; Europe, EU; OECD];
- [14]
University of Würzburg
[NORA names:
Germany; Europe, EU; OECD]
(less)
Abstract
The rising prevalence of liver diseases related to obesity and excessive use of alcohol is fuelling an increasing demand for accurate biomarkers aimed at community screening, diagnosis of steatohepatitis and significant fibrosis, monitoring, prognostication and prediction of treatment efficacy. Breakthroughs in omics methodologies and the power of bioinformatics have created an excellent opportunity to apply technological advances to clinical needs, for instance in the development of precision biomarkers for personalised medicine. Via omics technologies, biological processes from the genes to circulating protein, as well as the microbiome - including bacteria, viruses and fungi, can be investigated on an axis. However, there are important barriers to omics-based biomarker discovery and validation, including the use of semi-quantitative measurements from untargeted platforms, which may exhibit high analytical, inter- and intra-individual variance. Standardising methods and the need to validate them across diverse populations presents a challenge, partly due to disease complexity and the dynamic nature of biomarker expression at different disease stages. Lack of validity causes lost opportunities when studies fail to provide the knowledge needed for regulatory approvals, all of which contributes to a delayed translation of these discoveries into clinical practice. While no omics-based biomarkers have matured to clinical implementation, the extent of data generated has enabled the hypothesis-free discovery of a plethora of candidate biomarkers that warrant further validation. To explore the many opportunities of omics technologies, hepatologists need detailed knowledge of commonalities and differences between the various omics layers, and both the barriers to and advantages of these approaches.
Keywords
accurate biomarkers,
alcohol,
approach,
approval,
axis,
bacteria,
barriers,
bioinformatics,
biological processes,
biomarker discovery,
biomarker expression,
biomarkers,
breakthrough,
circulating proteins,
clinical implementation,
clinical need,
clinical practice,
commonalities,
community,
community screening,
complex,
data,
delayed translation,
demand,
development,
diagnosis,
diagnosis of steatohepatitis,
differences,
discovery,
disease,
disease complex,
disease stage,
diverse populations,
dynamic nature,
efficacy,
excellent opportunity,
excessive use,
excessive use of alcohol,
expression,
fibrosis,
fungi,
genes,
hepatologists,
implementation,
increasing demand,
inter-,
intra-individual variance,
knowledge,
knowledge of commonalities,
lack,
lack of validation,
layer,
liver disease,
measurements,
medicine,
method,
methodology,
microbiome,
monitoring,
nature,
needs,
obesity,
omics,
omics layers,
omics methodologies,
omics technologies,
omics-based biomarkers,
opportunities,
personalised medicine,
platform,
population,
power,
power of bioinformatics,
practice,
precision biomarkers,
prediction,
prediction of treatment efficacy,
prevalence,
prevalence of liver disease,
process,
prognostication,
protein,
regulatory approval,
screening,
semi-quantitative measurement,
stage,
standardisation,
standardised methods,
steatohepatitis,
steatotic liver disease,
study,
technology,
translation,
treatment efficacy,
untargeted platform,
use of alcohol,
validity,
variance,
virus
Funders
Data Provider: Digital Science