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1.
Hepatol Commun ; 6(6): 1361-1372, 2022 06.
Artículo en Inglés | MEDLINE | ID: mdl-35134262

RESUMEN

Alcohol-associated liver disease is the leading cause of chronic liver disease. We hypothesized that the expression of specific coding genes is critical for the progression of alcoholic cirrhosis (AC) from compensated to decompensated states. For the discovery phase, we performed RNA sequencing analysis of 16 peripheral blood RNA samples, 4 healthy controls (HCs) and 12 patients with AC. The DEGs from the discovery cohort were validated by quantitative polymerase chain reaction in a separate cohort of 17 HCs and 48 patients with AC (17 Child-Pugh A, 16 Child-Pugh B, and 15 Child-Pugh C). We observed that the numbers of differentially expressed messenger RNAs (mRNAs) were more pronounced with worsening disease severity. Pathway analysis for differentially expressed genes for patients with Child-Pugh A demonstrated genes involved innate immune responses; those in Child-Pugh B belonged to genes related to oxidation and alternative splicing; those in Child-Pugh C related to methylation, acetylation, and alternative splicing. We found significant differences in the expression of heme oxygenase 1 (HMOX1) and ribonucleoprotein, PTB binding 1 (RAVER1) in peripheral blood of those who died during the follow-up when compared to those who survived. Conclusion: Unique mRNAs that may implicate disease progression in patients with AC were identified by using a transcriptomic approach. Future studies to confirm our results are needed, and comprehensive mechanistic studies on the implications of these genes in AC pathogenesis and progression should be further explored.


Asunto(s)
Cirrosis Hepática Alcohólica , Transcriptoma , Perfilación de la Expresión Génica , Humanos , Cirrosis Hepática Alcohólica/genética , ARN Mensajero/genética , Índice de Severidad de la Enfermedad , Transcriptoma/genética
2.
Transl Res ; 240: 87-98, 2022 02.
Artículo en Inglés | MEDLINE | ID: mdl-34743014

RESUMEN

Appropriate screening tool for excessive alcohol use (EAU) is clinically important as it may help providers encourage early intervention and prevent adverse outcomes. We hypothesized that patients with excessive alcohol use will have distinct serum metabolites when compared to healthy controls. Serum metabolic profiling of 22 healthy controls and 147 patients with a history of EAU was performed. We employed seemingly unrelated regression to identify the unique metabolites and found 67 metabolites (out of 556), which were differentially expressed in patients with EAU. Sixteen metabolites belong to the sphingolipid metabolism, 13 belong to phospholipid metabolism, and the remaining 38 were metabolites of 25 different pathways. We also found 93 serum metabolites that were significantly associated with the total quantity of alcohol consumption in the last 30 days. A total of 15 metabolites belong to the sphingolipid metabolism, 11 belong to phospholipid metabolism, and 7 metabolites belong to lysolipid. Using a Venn diagram approach, we found the top 10 metabolites with differentially expressed in EAU and significantly associated with the quantity of alcohol consumption, sphingomyelin (d18:2/18:1), sphingomyelin (d18:2/21:0,d16:2/23:0), guanosine, S-methylmethionine, 10-undecenoate (11:1n1), sphingomyelin (d18:1/20:1, d18:2/20:0), sphingomyelin (d18:1/17:0, d17:1/18:0, d19:1/16:0), N-acetylasparagine, sphingomyelin (d18:1/19:0, d19:1/18:0), and 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1). The diagnostic performance of the top 10 metabolites, using the area under the ROC curve, was significantly higher than that of commonly used markers. We have identified a unique metaboloic signature among patients with EAU. Future studies to validate and determine the kinetics of these markers as a function of alcohol consumption are needed.


Asunto(s)
Consumo de Bebidas Alcohólicas/sangre , Consumo de Bebidas Alcohólicas/metabolismo , Metaboloma , Metabolómica , Adulto , Estudios de Casos y Controles , Estudios de Cohortes , Femenino , Humanos , Modelos Lineales , Masculino , Redes y Vías Metabólicas , Curva ROC
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