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Genetic variants of PNPLA3, TM6SF2, SAMM50 and metabolomic profiles
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ์๊ณผ๋ํ ์ํ๊ณผ, 2021.8. ์ด๊ฒฝ์ฌ.๋ฐฐ๊ฒฝ
์ผ๋ถ ์ ์ ์ ๋ณ์ด์ ๋ค๋ฅธ ๋์ฌ์ฒด ์์์ด ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐ์งํ๊ณผ ๊ด๋ จ๋์ด ์๋ค๊ณ ๋ณด๊ณ ๋๊ณ ์์ง๋ง ์ ์ ์ ๋ณ์ด์ ๋์ฌ์ฒด ๋ถ์์ ๋์์ ์ํํ ์ฐ๊ตฌ๋ ๊ฑฐ์ ์์ผ๋ฉฐ ์์์ฒญ์๋
์ง๋จ์์๋ ์ํ๋ ์ฐ๊ตฌ๊ฐ ์๋ค.
๋ชฉ์
๋ณธ ์ฐ๊ตฌ์ ๋ชฉ์ ์ ์์ ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐ ์งํ์ ๋ฏธ์น๋ ์ ์ ์ ๋ณ์ด์ ์ํฅ์ ํ์
ํ๊ณ , ๋๋ถ์ด ํ์์ ๋์กฐ๊ตฐ์ ๋์ฌ์ฒด ์ฐจ์ด์ ์ ์ ์๋ณ์ด์ ์ฐ๊ด์ฑ์ ๋ถ์ํ์ฌ ์ง๋ณ์ ๋ณ์ธ์ ๋ณด๋ค ๋ช
ํํ ๊ท๋ช
ํ๊ณ ์ ํจ์ด๋ค.
๋ฐฉ๋ฒ
์ ์ ์ ๋ถ์์ ์ํ์ฌ 228๋ช
์ ์์ ํ์์ 225๋ช
์ ๋์กฐ๊ตฐ (๊ณผ์ฒด์ค 69, ์ ์์ฒด์ค 156๋ช
)์ด ๋ฑ๋ก๋์๊ณ ๊ทธ์ค 105๋ช
์ ํ์์ 61๋ช
์ ๋์กฐ๊ตฐ (๊ณผ์ฒด์ค 118๋ช
, ์ ์์ฒด์ค 48๋ช
)์ ๋์ฌ์ฒด ๋ถ์์ ์ํด ํฌํจํ์๋ค. ๋ค์๊ณผ ๊ฐ์ PNPLA3 (rs738409), TM6SF2 (rs58542926) and SAMM50 (rs2073080, rs3761472) 4๊ฐ์ ์ ์ ์ ๋ณ์ด๋ฅผ ๋ถ์ํ์๋ค. ํ์ฅ ๋์ฌ์ฒด๋ Biocrates AbsoluteIDQ p400 kit์ Thermo Q Exactive Plus orbitrap mass spectrometer๋ฅผ ํตํด ๋ถ์ํ์๋ค. ๋ชจ๋ ์ฐธ๊ฐ์๋ ์ ์ฒด๊ณ์ธก์ ์ํํ์๊ณ ์ผ๋ฐ ํ์ก๊ฒ์ฌ์, ๊ฐ๊ธฐ๋ฅ๊ฒ์ฌ๋ฅผ ๋ฐ์์ผ๋ฉฐ, ๊ณผ์ฒด์ค์ง๋จ์์๋ ๋ณต๋ถ๋๋ ์ ํ์, ๊ณต๋ณต ํ๋น, ์ธ์๋ฆฐ, ์ง๋ฐฉ๋ถ์์ ์ํํ์๋ค. ๊ฐ ์ด์ํ๋ฅผ ํตํด ์ง๋ฐฉ๊ฐ ์ ๋ฌด์ ์ง๋ฐฉ๊ฐ ๋จ๊ณ๋ฅผ ํ๊ฐํ์์ผ๋ฉฐ ๋น์นจ์ต์ ์ฌ์ ํ ์ ์๋ฅผ ๋ฐ๋ผ ์ฌ์ ํ ์ ๋๋ฅผ ํ๊ฐํ์๋ค. ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐ์งํ์ ์ํฅ์ ๋ฏธ์น๋ ์ ์ ์ ๋ณ์ด์ ๋์ฌ์ฒด ์ฐจ์ด๋ ๋ชจ๋ ์ผ๋ฐ์์ ์ง๋จ๊ณผ ๊ณผ์ฒด์ค์ง๋จ์์ ๋ถ์ํ์๋ค.
๊ฒฐ๊ณผ
PNPPLA3 (rs738409), TM6SF2 (rs58542926), SAMM50 (rs2073080, rs3761472) ๋ณ์ด๋ ์ผ๋ฐ ์์์ง๋จ (์น์ฐ๋น: 1.99~ 3.26, P <0.05)๊ณผ ๊ณผ์ฒด์ค์์์ง๋จ (์น์ฐ๋น: 2.22~ 22.94, P <0.05์์ ๋
๋ฆฝ์ ์ผ๋ก NAFLD์ํ์ ๋์๋ค. ๋ค๋ฅธ ๋
๋ฆฝ์ ์ธ ์ํ์ธ์๋ ์ฒด์ง๋์ง์-Z ์ ์์, ๋จ์ฑ์ด์์ผ๋ฉฐ, ๊ณผ์ฒด์ค์ง๋จ์์๋ ๊ณต๋ณต ์ธ์๋ฆฐ์ด ์ถ๊ฐ์ ์ธ ์ํ ์ธ์์๋ค. ์ด ์ ์ ์๋ณ์ด๋ค์ ๋์ด, ์ฑ๋ณ, ์ฒด์ง๋์ง์-Z์ ์์ ๊ด๋ จ์์ด ์๋ผ๋ ์๋ฏธ๋
ธ ์ ์ดํจ์์, ์ด์ํ์์ ์ง๋ฐฉ๊ฐ ์ ๋, ์ฌ์ ํ ์์น๋ฅผ ์ฆ๊ฐ์์ผฐ๋ค. ์ด๋ฌํ ์ ์ ์ ์ํฅ์ ์ ์ฒด ์์ ์ง๋จ๋ณด๋ค ๊ณผ์ฒด์ค์ง๋จ์์ ๋์ฑ ์ปธ๋ค. ๊ณผ์ฒด์ค์ง๋จ๊ณผ, ์ ์์ฒด์ค ์ง๋จ ๋ชจ๋์์ ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐ์งํ ํ์๋ ๋์กฐ๊ตฐ์ ๋นํด ๋ ๋์ ํ์ฅ ๋ฅ์ , ์์ด์๋ฅ์ , ๋ฐ๋ฆฐ ๊ฐ์ branched chain ์๋ฏธ๋
ธ์ฐ๊ณผ, ๊ธ๋ฃจํ๋ฉ์ดํธ, ํ์ด๋ก์ , ํฌ์คํํฐ๋์ฝ๋ฆฐ, ์คํ๊ณ ๋ง์ด์๋ฆฐ, ๋ค์ด๊ธ๋ฆฌ์ธ๋ผ์ด๋, ์ค์ฑ์ง๋ฐฉ ๋๋๋ฅผ ๋ณด์์ผ๋ฉฐ ์ด๊ฒ๋ค์ค branched chain ์๋ฏธ๋
ธ์ฐ, ๊ธ๋ฃจํ๋ฉ์ดํธ ๋ฑ์ HOMA-IR๊ณผ ์์ฑ์๊ด๊ด๊ณ๋ฅผ ๋ณด์๋ค. ๊ธ๋ผ์ด์ , ๊ธ๋ฃจํ๋ฏผ, ์ธ๋ฆฐ ๋๋๋ ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐํ์์์ ๋ฎ์์ผ๋ฉฐ ๊ธ๋ผ์ด์ , ๊ธ๋ฃจํ๋ฏผ์ HOMA-IR๊ณผ ์์ ์๊ด๊ด๊ณ๋ฅผ ๋ณด์ฌ ํ์์ ๋์กฐ๊ตฐ๊ฐ์ ๋์ฌ์ฒด ์ฐจ์ด๋ ์ธ์๋ฆฐ์ ํญ์ฑ๊ณผ ์ฐ๊ด์ด ์์์ ์์ฌํ์๋ค. TM6SF2 ๋ณ์ด๊ฐ ์๋ ํ์์์๋ ๋ณ์ด๊ฐ ์๋ ํ์๋ณด๋ค ๋ ๋ฎ์ ํ์ฅ ํฌ์คํํฐ๋์ฝ๋ฆฐ, ์คํ๊ณ ๋ง์ด์๋ฆฐ, ์ค์ฑ์ง๋ฐฉ ๋๋๋ฅผ ๋ํ๋์ผ๋ฉฐ ์ด๊ฒ์ ๋น์์ฝ์ฑ์ง๋ฐฉ๊ฐ ์ ๋ฌด์ ๋ฐ๋๋๋ ๋ถํฌ์๋ค.
๊ฒฐ๋ก
๋ณธ ์ฐ๊ตฌ๋ ์์์ฒญ์๋
์ฐ๋ น์์ ์ต์ด๋ก ๋ค์ํ ์ ์ ์ ๋ณ์ด์ ํ์ฅ ๋์ฌ์ฒด๋ฅผ ๋์์ ๋ถ์ํ ์ฐ๊ตฌ์ด๋ค. PNPLA3, TM6SF2, SAMM50 ์ ์์์ฒญ์๋
์ผ๋ฐ์ง๋จ๊ณผ ๊ณผ์ฒด์ค์ง๋จ ๋ชจ๋์์ ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐ์งํ์ ๋ฐ์๊ณผ ์ค์ฆ๋์ ๋
๋ฆฝ์ ์ผ๋ก ์ํฅ์ ๋ฏธ์ณค์ผ๋ฉฐ ๊ทธ ์ํฅ์ ๊ณผ์ฒด์ค์ง๋จ์์ ์ปธ๋ค. 101๊ฐ์ ๋์ฌ์ฒด๊ฐ ๋น์์ฝ์ฑ ์ง๋ฐฉ๊ฐ์งํ๊ณผ ๋์กฐ๊ตฐ ์ฌ์ด์ ์ฐจ์ด๊ฐ ์์์ผ๋ฉฐ ๊ทธ์ค 49๊ฐ๋ ์ธ์๋ฆฐ ์ ํญ์ฑ๊ณผ ๊ด๋ จ์ด ์์๋ค. TM6SF2 ๋ณ์ด๋ฅผ ๊ฐ์ง ์ฌ๋์ ํ์ฅ ์ง๋ฐฉ๋๋๊ฐ ๋ ๋ฎ์์ผ๋ฉฐ, ์ด๊ฒ์ ์ผ๋ฐ์ ์ธ NAFLDํ์์๋ ๋ฐ๋๋๋ ์์์ด์์ผ๋ฉฐ ๋ค๋ฅธ ์ ์ ์ ๋ณ์ด์ ๋ฐ๋ฅธ ๋์ฌ์ฒด ๋ณํ๋ ํ์ ์ฐ๊ตฌ๊ฐ ํ์ํ๊ฒ ๋ค.Background
Some genetic variants and different metabolomic profiles have been reported to be associated with nonalcoholic fatty liver disease (NAFLD). Few studies have reported various genetic variants and associated metabolites simultaneously, and no study has been conducted in pediatric populations.
Objective
The aim of this study was to investigate the effects of genetic variants on pediatric NAFLD and analyze metabolic differences between NAFLD patients and controls in a pediatric population. In addition, other risk factors for pediatric NAFLD were aimed to investigate.
Methods
NAFLD was defined if hepatic steatosis was shown on ultrasound. A total of 228 NAFLD patients (body mass index-Z [BMI-Z] = 2.51 ยฑ 1.01) and 225 controls (BMI-Z = 0.22 ยฑ 1.48) were included. All participants underwent examination by anthropometry and blood cell count and liver function analysis. Four variants of PNPLA3 (rs738409), TM6SF2 (rs58542926) and SAMM50 (rs2073080, rs3761472) were genotyped by TaqMan allelic discrimination assay. Metabolic profiles were checked in children with overweight. The pediatric NAFLD fibrosis score (PNFS), the AST/platelet ratio index (APRI) and fibrosis-4 (FIB-4) were used to evaluate the degree of hepatic fibrosis. Genetic risk factors for NAFLD in all participants were analyzed by adjusting for age, sex and BMI-Z. Subgroup analysis was conducted in children with overweight with more metabolic adjustments. The genetic risk score was calculated to evaluate the synergetic effects of 4 genetic variants.
Among them, 166 (105 NAFLD and 61 control) children were enrolled for metabolomic analysis. The plasma metabolome was quantified using a Biocrates AbsoluteIDQ p400 kit and Thermo Q Exactive Plus Orbitrap mass spectrometer.
Results
The four genetic variants (rs738409, rs58542926, rs2073080 and rs3761472), male sex and BMI-Z independently increased susceptibility to NAFLD. These variants remained significant risk factors with higher odds ratio in children with overweight in addition to fasting insulin and triglyceride. These variants increased the alanine aminotransferase level, PNFS, APRI, and FIB-4 independently. As the genetic risk score increased, aspartate transaminase, alanine aminotransferase, PNFS, APRI, and FIB-4 increased independently suggesting synergetic effects of these 4 variants.
NAFLD patients showed a higher plasma levels of branched chain amino acids (BCAAs, leucine, isoleucine, valine), tyrosine, phosphatidylcholines (PCs), sphingomyelins (SMs), diglyceride, triglycerides (TGs) than control. Some of these metabolites including BAAA, glutamate, PCs, SMs had positive association with homeostasis model assessment-estimated insulin resistance (HOMA-IR). Plasma levels of glutamine, glycine and serin were lower in NAFLD patients than control. Glutamine and glycine showed negative correlation with HOMA-IR. The carries of TM6SF2 variants significantly showed lower plasma PCs, SMs and TG compared to wild type and the distribution of metabolites was reversed to the NAFLD.
Conclusion
The effects of genetic variants and metabolomic profiles in children with NAFLD was first demonstrated in this study. Genetic variants of PNPLA3, TM6SF2 and SAMM50 are associated with the development and severity of pediatric NAFLD and their effects are greater in children with overweight than normal weight. These variants have synergetic effects on severity of pediatric NAFLD. A total of 49 metabolites showed significant differences between subjects with NAFLD and control, are associated with insulin resistance. While variants of TM6SF2 results in lower plasma lipids, other variants did not show significant differences in metabolome.Chapter 1. Introduction 1
Chapter 2. Method 4
Chapter 3. Results 15
Chapter 4. Discussion 46
Chapter 5. Conclusion 61
Chapter 6. Abbreviations 63
Chapter 7. Bibliography 65
Chapter 8. Supplementary tables 79
Chapter 9. Abstract in Korean 84
Chapter 10. Aknowledgements 87๋ฐ
Growing Educational Differentials in the Retreat from Marriage among Korean Men
Applying discrete-time hazard models to person-year data constructed from 1% microdata sample of 2010 Korean Census, we explore how menโs education affects their transition to first marriage, and how the relationship between education and marriage has changed across three 10-year birth cohorts of Korean men born from 1946 to 1975. Currently, there is only limited knowledge on how education is related to marriage formation and how the effect is contingent upon macro contexts of education, economy, and family among East Asian men. We find that the high educated delay marriage until later ages but catch up to the extent to which they are eventually more likely to marry than the low educated. There is a continued trend across cohorts toward the delay and avoidance of marriage at all educational levels. However, the trend of retreat from marriage has been more substantial for men with high school or less education compared to men with a university degree, leading to growing educational gaps over time in marriage. We discuss the findings in the contexts of deteriorating economic prospects of Korean men with lower education and also the declining pool of potential spouses for the low educated
Technical Efficiency in the Iron and Steel Industry: A Stochastic Frontier Approach
In this paper we examine the technical efficiency of firms in the iron and steel industry and try to identify the factors contributing to the industry's efficiency growth, using a time-varying stochastic frontier model. Based on our findings, which pertain to 52 iron and steel firms over the period of 1978-1997, POSCO and Nippon Steel were the most efficient firms, with their production, on average, exceeding 95 percent of their potential output. Our findings also shed light on possible sources of efficiency growth in the industry. If a firm is government-owned, its privatization is likely to improve its technical efficiency to a great extent. A firm's technical efficiency also tends to be positively related to its production level as measured by a share of the total world production of crude steel. Another important source of efficiency growth identified by our empirical findings is adoption of new technologies and equipment. Our findings clearly indicate that continued efforts to update technologies and equipment are critical in pursuit of efficiency in the iron and steel industry.
Rigorous Simulation Model of Kerogen Pyrolysis for the In-situ Upgrading of Oil Shales
Oil shale is a vast, yet untapped energy source, and the pyrolysis of kerogen in the oil shales releases recoverable hydrocarbons. In this dissertation, we investigate how to increase process efficiency and decrease the costs of in-situ upgrading process for kerogen pyrolysis, which is applicable to the majority of the oil shales. In-situ upgrading processes include (a) Shell In-situ Conversion Process (ICP), (b) ExxonMobil Electrofrac, and (c) Texas A&M (TAMU) Steamfrac. We evaluate these three processes in realistic scenarios using our newly developed multi-phase, multi-component, nonisothermal simulator.
Kerogen pyrolysis is represented by 6 kinetic reactions resulting in 10 components and 4 phases. Expanding TAMU Flow and Transport Simulator (FTSim), we develop a fully functional capability that describes the kerogen pyrolysis and the accompanying system changes. The simulator describes the coupled process of mass transport and heat flow through porous and fractured media, and accurately accounts for phase equilibria and transitions. It provides a powerful tool to evaluate the efficiency and the productivity of the in-situ upgrading processes.
We validate our simulator by reproducing the field production data of the Shell ICP implemented in Green River Formation. We conduct the sensitivity analyses of the presence and absence of pre-existing fracture system, oil shale grade, permeability of the fracture network, and thermal conductivity of the formation. Validated model has the oil shale grade of 25 gal/ton, fracture domain permeability of 150 md, and formation thermal conductivity of 2.0 W/m-K.
In the application cases, we analyze the significant factors affecting each process. In the Shell ICP, the ExxonMobil Electrofrac, and the TAMU Steamfrac, we study the effects of heater temperature, electrical conductivities of injection material, and steam injection strategy, respectively. We find that the best case of the Shell ICP showed the highest energy efficiency of 144 %. The best cases of the ExxonMobil Electrofrac and the TAMU Steamfrac show the energy efficiency of 74.1 %, and 54.1 %, respectively. We obtain positive Net Present Value (NPV) in the TAMU Steamfrac by much less number of wells than the Shell ICP and the ExxonMobil Electrofrac, though it has the lowest energy efficiency
Reactive oxygen species regulate urokinase plasminogen activator expression and cell invasion via mitogen-activated protein kinase pathways after treatment with hepatocyte growth factor in stomach cancer cells
Abstract Background Reactive oxygen species (ROS) are closely associated with the intracellular signal cascade, thus strongly implicating involvement in tumor progression. However, the mechanism by which ROS are generated and how ROS target downstream molecules to trigger tumor metastasis is unclear. In this study, we investigated the underlying signal pathways in ROS-induced urokinase plasminogen activator (uPA) expression in the human gastric cancer cells, NUGC-3 and MKN-28. Methods and Results Intracellular ROS, as determined using the fluorescent probe, 2'-7' dichlorofluorescein diacetate, decreased after treatment with hepatocyte growth factor (HGF). We confirmed that Rac-1 regulated ROS production after activation of the AKT pathway with HGF. Exogenously added H2O2 promoted the expression of HGF, but not in a dose-dependent manner and also showed negative expression of HGF after co-treatment with H2O2 and HGF. Treatment with NAC, an intracellular free radical scavenger, decreased the enhancement of uPA production and tumor invasion in both cells. We clarified the downstream pathways regulated by ROS after treatment with H2O2, which showed negative control between FRK and p38 kinase activities for uPA regulation. Conclusion HGF regulates Rac-1-induced ROS production through the Akt pathway and ROS regulates uPA production and invasion via MAP kinase, which provides novel insight into the mechanisms underlying the progression of gastric cancer.</p
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