Biomedical subjects

Yong He

Publications and source records attributed to Yong He.

3 recordsLinked to original sources

PubMed2026

Personalized functional topography-based multisite brain age prediction modeling reveals divergent neurodevelopment in major depression.

Major depressive disorder (MDD) is associated with widespread alterations in functional brain networks across the lifespan. However, heterogeneity in atypical brain development among patients with MDD remains largely uncharacterized. Using a multisite resting-state functional MRI dataset consisting of 1,105 MDD patients and 1,065 healthy controls, we constructed a harmonized multicenter brain age prediction model based on individualized functional topography and identified two patient subgroups with positive or negative brain age gaps (BAGs). In patients with a positive BAG (BAG+), expansion of the salience network (SAL) into the dorsolateral prefrontal and ventrolateral prefrontal cortices, in addition to contraction of the sensorimotor and dorsal attention networks (DAN), contributes to accelerated brain aging. Conversely, in the negative BAG (BAG-) group, SAL expansion into the orbitofrontal cortex (OFC) and contraction of the visual and sensorimotor networks (SMN) were linked to delayed brain development. These subgroups also exhibited distinct neurodevelopmental trajectories. Clinically, BAG+ patients showed stronger associations between higher-order network topography and mood symptoms, whereas BAG- patients exhibited links between visual/default mode network topography and insomnia. At the molecular level, both groups showed enrichment of genes related to synaptic signaling but displayed distinct expression patterns and divergent expression trajectories in key neurodevelopmental gene sets. Notably, antidepressant treatment modulated the brain in ways that were specific to each subgroup. These findings reveal heterogeneous neurodevelopmental profiles in MDD with distinct biological and clinical signatures, offering insights into personalized precision medicine for this disorder.

Humans↗

PubMed2025

Immunopathogenic mechanisms and immunoregulatory therapies in MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease (NAFLD), is the most prevalent chronic liver disease worldwide, with an estimated global prevalence of approximately 30%; however, effective pharmacotherapies are still limited due to its complex pathogenesis and etiology. Therefore, a more thorough understanding of disease pathogenesis is urgently needed. An increasing number of studies suggest that MASLD and its progressive form, metabolic dysfunction-associated steatohepatitis (MASH), are driven by chronic overnutrition, multiple genetic susceptibility factors, and pathogenic consequences, including hepatocyte damage and liver inflammation. Hepatic inflammation is the key event fueling the conversion from simple steatosis to steatohepatitis and fibrosis. Current therapies for MASH, including the recently approved thyroid hormone receptor-beta agonist resmetirom or the available incretin mimetics, mainly target metabolic injury to the liver but not inflammation directly. In this review, we provide an in-depth discussion of current data related to the immunological mechanisms of MASLD and summarize the effects of current and experimental therapies on immunoregulation in MASLD.

Humans↗

PubMed2024

Shared differential factors underlying individual spontaneous neural activity abnormalities in major depressive disorder.

BACKGROUND: In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion. METHODS: To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization. RESULTS: Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability. CONCLUSIONS: This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.

Humans↗