New Study by Korea National Institute of Health Demonstrates Pre-emptive Approach to Predicting Prediabetes
Update 22.12.2022
Korean researchers develop a new model to predict the development of prediabetes based on metabolic markers.
Prediabetes
(PD)—a condition where blood sugar is higher than normal but not high enough to
be classified as Type 2 diabetes (T2D)—often progresses to T2D. This progress
can be halted with early detection of PD. Researchers at the Korea National
Institute of Health have now developed a method to accurately predict PD,
giving people a chance to prevent the condition from developing into T2D
through medication and lifestyle changes.
New study by KNIH proposes a
model that improves chances of diagnosis and treatment monitoring of
prediabetes.
Photo courtesy: Shutterstock
While initially considered a “disease of the rich,” Type 2 diabetes
(T2D) is a highly prevalent condition today. A chronic disease in which the
body either cannot utilize or doesn't produce enough insulin, T2D contributes
to high rates of mortality and morbidity. However, like a traffic signal that
flashes yellow before flashing red, our bodies produce a state of prediabetes (PD)
before T2D.
PD ̶ where blood sugar levels begin to rise, but do
not attain the level considered for a diagnosis of diabetes ̶ is a precursor to
T2D and can be diagnosed with biochemical methods such as impaired fasting
glucose (IFG), impaired glucose tolerance (IGT), and combined IFG/IGT. Clinical
risk factors (CRF), such as a person’s age, sex, body mass index (BMI) and
cholesterol levels also help in predicting diabetes risk. However, these
methods are inconsistent and time-consuming. Additionally, due to its
subclinical nature, PD is often diagnosed late, or goes undetected, progressing
into T2D with a slew of associated complications like cardiovascular and kidney disease, and nerve and retinal injuries.
A team of researchers at the Korean National
Institute of Health (KNIH), led by Dr. Heun‑Sik Lee, decided to tackle the
diagnosis of PD with a pre-emptive, targeted metabolomic approach.
Metabolomics is, quite simply put, the study of metabolites—by-products
of biological processes in our bodies. Dr. Lee explains, “These are
sensitive markers, with prior studies identifying associations between several
metabolites and PD. Most of these studies, however, were conducted among
Caucasian and European populations, not Koreans.”
In
their latest study, supported by intramural grants from the Korea National
Institute of Health (2019-NG-053-00;2017-NI73004-00; 2013-NG73001-00) and published
in Nature’s Scientific Reports, the
team quantified specific metabolites present in 1723 participants
in the Korea Association REsource (KARE) cohort, from which 500 normal
individuals were followed up for 6 years, and their disease progression was
monitored. The levels of these metabolites were measured in comparison to
established markers of diabetes and PD, like fasting glucose, 2 h-PPG, HbA1c,
and HOMA-IR levels.
Of the initial 39
markers, statistical analyses revealed 12 novel, independent
metabolites, which were significantly associated with the development of PD. “We
identified five amino acids, four glycerophospholipids, two sphingolipids, and one
acylcarnitine. Six of these markers were linked to an increased risk of PD, whereas the
others were associated with a decreased risk at baseline,” Dr. Lee
elaborates.
These
metabolites formed the KARE model, which was more efficient in predicting the
future development of PD compared to other metabolite models, CRF, or fasting
glucose. How is this useful, though?
Dr. Lee
explains, “Our prediction model could help detect PD early. Upon diagnosis,
patients can be advised lifestyle and dietary modifications, or medications to
manage their blood sugar so that their condition doesn’t progress to T2D.” In
fact, combining the KARE model with existing diagnostic criteria (like metabolic markers,
CRF, and fasting glucose levels) yielded the best prediction performance, the
team found. Moreover, the KARE model could also be used to monitor PD and
determine its prognosis (by measuring changes in levels of the 12 metabolic
markers it includes), leading to the development of effective medicines
for PD.
In other words, the model would give treatment
providers a chance to prepare patients early in their fight against T2D, contributing
immensely to the global fight against T2D!
Reference
Authors
Title of original paper
Journal |
Heun‑Sik Lee, Tae‑Joon Park, Jeong‑Min Kim, Jun Ho Yun, Ho‑Yeong Yu, Yeon‑Jung Kim, Bong‑Jo Kim
Identification of metabolic markers
predictive of prediabetes in a Korean population
Scientific
Reports |
|
|
DOI
Affiliations |
Division of Genome Research, Center for Genome
Science, National Institute of Health, Osong Health Technology Administration
Complex |
About National Institute of
Health in Korea
The Korea National
Institute of Health (KNIH), one of the major operating components of the
Ministry of Health and Welfare, leads the nation’s medical research. Over the
past seven decades, the KNIH has made unwavering efforts to enhance the
public’s health and innovate biomedical research. The KNIH seeks to eradicate
diseases and make people healthier. The KNIH establishes a scientific basis and
evidence underlying health policy as well as provides national research
infrastructures. We also promote public health research. To this end, we make
efforts to enrich a health research environment by granting funds to research
projects and keeping our resources, data, and facilities more open and
accessible to researchers.
Website: http://www.nih.go.kr/NIH_ENG/
About Dr. Heun‑Sik Lee
Heun‑Sik Lee is a
researcher at the Division of Structural and Functional Genomics, Center for
Genome Science, Korea National Institute of Health. He has published over 45
papers. His research areas include DNA methylation, gene expression
transcription, gene regulation, genomics regulation and Meta-Analysis.