Page 1004 - Read Online

Kim et al. Hepatoma Res 2020;6:85 I http://dx.doi.org/10.20517/2394-5079.2020.96 Page 7 of 10

if an ideal prediction model based on genetic information is properly established, it could be possible to
stratify NAFLD before it develops or progresses, thus enabling intervention at an early stage or early age.
However, to properly apply this concept, results should be accumulated from multiple longitudinal studies.

Secondly, another important issue to consider when utilizing genetic information is the interaction between
environment and gene. For example, with regards to rs738409 in the PNPLA3 gene, it has been reported
[68]
that the variant’s effect is especially amplified in the setting of obesity . This suggests that adiposity
(environment) can influence how specific genetic information influences the full spectrum of NAFLD.
Considering this interaction between gene and environment, a prediction model based exclusively on
genetic information may not exhibit sufficient predictive power, while a model with integration of relevant
NAFLD-associated clinical factors would be more likely to reach significant predictive power.

Overall, prediction models that use both genetic information and relevant clinical factors derived from
longitudinal studies can achieve sufficient predictive power for NAFLD risk stratification at the individual
level.

CONCLUSION
The identification of genes associated with NAFLD development and progression is expected to provide
important insights into its pathophysiology, as well as to guide disease risk stratification and further new
opportunities for timely therapeutic intervention. Several genetic variants have been implicated in NAFLD
development and progression, and here we focused on the five genes whose associations with NAFLD
have been most extensively replicated. These genetic risk variants can improve the accuracy of NAFLD
diagnosis, and may also be useful for the identification of high-risk NAFLD patients who have unfavorable
prognoses. An understanding of these NAFLD-associated genetic risk factors will help identify individuals
at risk, and potentially guide the provision of appropriate treatments based on an individual’s risk and
likelihood of disease progression.

DECLARATIONS
Acknowledgements
The authors thank Medical Illustration & Design, part of the Medical Research Support Services of Yonsei
University College of Medicine, for all artistic support related to this work.

Authors’ contributions
Wrote and reviewed the manuscript: Kim DY, Park JY

Availability of data and materials
Not applicable.

Financial support and sponsorship
This research was supported by the Bio & Medical Technology Development Program of the National
Research Foundation (NRF) funded by the Ministry of Science & ICT (NRF-2020M3A9E4038694).

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.