Progressive Brain Structural Impairment Assessed via Network and Causal Analysis in Patients With Hepatitis B Virus-Related Cirrhosis

Identifying Minimal Hepatic Encephalopathy: A New Perspective from Magnetic Resonance Imaging

Type C hepatic encephalopathy (HE) is a condition characterized by brain dysfunction caused by liver insufficiency and/or portal-systemic blood shunting, which manifests as a broad spectrum of neurological or psychiatric abnormalities, ranging from minimal HE (MHE), detectable only by neuropsychological or neurophysiological assessment, to coma. Though MHE is the subclinical phase of HE, it is highly prevalent in cirrhotic patients and strongly associated with poor quality of life, high risk of overt HE, and mortality. It is, therefore, critical to identify MHE at the earliest and timely intervene, thereby minimizing the subsequent complications and costs. However, proper and sensitive diagnosis of MHE is hampered by its unnoticeable symptoms and the absence of standard diagnostic criteria. A variety of neuropsychological or neurophysiological tests have been performed to diagnose MHE. However, these tests are nonspecific and susceptible to multiple factors (eg, aging, education), thereby limiting their application in clinical practice. Thus, developing an objective, effective, and noninvasive method is imperative to help detect MHE. Magnetic resonance imaging (MRI), a noninvasive technique which can produce many objective biomarkers by different imaging sequences (eg, Magnetic resonance spectroscopy, DWI, rs-MRI, and arterial spin labeling), has recently shown the ability to screen MHE from NHE (non-HE) patients accurately. As advanced MRI techniques continue to emerge, more minor changes in the brain could be captured, providing new means for early diagnosis and quantitative assessment of MHE. In addition, the advancement of artificial intelligence in medical imaging also presents the potential to mine more effective diagnostic biomarkers and further improves the predictive efficiency of MHE. Taken together, advanced MRI techniques may provide a new perspective for us to identify MHE in the future. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Regulation of mild cognitive impairment associated with liver disease by humoral factors derived from the gastrointestinal tract and MRI research progress: a literature review

Patients with liver disease are prone to various cognitive impairments. It is undeniable that cognitive impairment is often regulated by both the nervous system and the immune system. In this review our research focused on the regulation of mild cognitive impairment associated with liver disease by humoral factors derived from the gastrointestinal tract, and revealed that its mechanisms may be involved with hyperammonemia, neuroinflammation, brain energy and neurotransmitter metabolic disorders, and liver-derived factors. In addition, we share the emerging research progress in magnetic resonance imaging techniques of the brain during mild cognitive impairment associated with liver disease, in order to provide ideas for the prevention and treatment of mild cognitive impairment in liver disease.

Changes in dynamic and static brain fluctuation distinguish minimal hepatic encephalopathy and cirrhosis patients and predict the severity of liver damage

Purpose

Minimal hepatic encephalopathy (MHE) is characterized by mild neuropsychological and neurophysiological alterations that are not detectable by routine clinical examination. Abnormal brain activity (in terms of the amplitude of low-frequency fluctuation (ALFF) has been observed in MHE patients. However, little is known concerning temporal dynamics of intrinsic brain activity. The present study aimed to investigate the abnormal dynamics of brain activity (dynamic ALFF; dALFF) and static measures [static ALFF; (sALFF)] in MHE patients and to strive for a reliable imaging neuromarkers for distinguishing MHE patients from cirrhosis patients. In addition, the present study also investigated whether intrinsic brain activity predicted the severity of liver damage.

Methods

Thirty-four cirrhosis patients with MHE, 28 cirrhosis patients without MHE, and 33 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state magnetic resonance imaging (rs-fMRI). dALFF was estimated by combining the ALFF method with the sliding-window method, in which temporal variability was quantized over the whole-scan timepoints and then compared among the three groups. Additionally, dALFF, sALFF and both two features were utilized as classification features in a support vector machine (SVM) to distinguish MHE patients from cirrhosis patients. The severity of liver damage was reflected by the Child–Pugh score. dALFF, sALFF and both two features were used to predict Child–Pugh scores in MHE patients using a general linear model.

Results

Compared with HCs, MHE patients showed significantly increased dALFF in the left inferior occipital gyrus, right middle occipital gyrus, and right insula; increased dALFF was also observed in the right posterior lobe of the cerebellum (CPL) and right thalamus. Compared with HCs, noMHE patients exhibited decreased dALFF in the right precuneus. In contrast, compared with noMHE patients, MHE patients showed increased dALFF in the right precuneus, right superior frontal gyrus, and right superior occipital gyrus. Furthermore, the increased dALFF values in the left precuneus were positively associated with poor digit-symbol test (DST) scores (r = 0.356, p = 0.038); however, dALFF in the right inferior temporal gyrus (ITG) was negatively associated with the number connection test–A (NCT-A) scores (r = -0.784, p = 0.000). A significant positive correlation was found between dALFF in the left inferior occipital gyrus (IOG) and high blood ammonia levels (r = 0.424, p = 0.012). Notably, dALFF values yielded a higher classification accuracy than sALFF values in distinguishing MHE patients from cirrhosis patients. Importantly, the dALFF values predicted the Child–Pugh score (r = 0.140, p = 0.030), whereas sALFF values did not in the current dataset. Combining two features had high accuracy in classification in distinguishing MHE patients from cirrhotic patients and yielded prediction in the severity of liver damage.

Conclusion

These findings suggest that combining dALFF and sALFF features is a useful neuromarkers for distinguishing MHE patients from cirrhosis patients and highlights the important role of dALFF feature in predicting the severity of liver damage in MHE.

Reviewing the Potential Links between Viral Infections and TDP-43 Proteinopathies

Transactive response DNA binding protein 43 kDa (TDP-43) was discovered in 2001 as a cellular factor capable to inhibit HIV-1 gene expression. Successively, it was brought to new life as the most prevalent RNA-binding protein involved in several neurological disorders, such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). Despite the fact that these two research areas could be considered very distant from each other, in recent years an increasing number of publications pointed out the existence of a potentially important connection. Indeed, the ability of TDP-43 to act as an important regulator of all aspects of RNA metabolism makes this protein also a critical factor during expression of viral RNAs. Here, we summarize all recent observations regarding the involvement of TDP-43 in viral entry, replication and latency in several viruses that include enteroviruses (EVs), Theiler's murine encephalomyelitis virus (TMEV), human immunodeficiency virus (HIV), human endogenous retroviruses (HERVs), hepatitis B virus (HBV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), West Nile virus (WNV), and herpes simplex virus-2 (HSV). In particular, in this work, we aimed to highlight the presence of similarities with the most commonly studied TDP-43 related neuronal dysfunctions.