Citations

AbstractBackgroundThe syndrome of mild cognitive impairment (MCI) is classified into different subtypes– amnestic MCI (aMCI) and non‐amnestic MCI based on cognitive domains impacted, while different underlying disease etiologies cause the impairments. The Memory Support System (MSS), a memory‐support tool which utilizes a calendar/planner, has been shown to have positive impact on daily functioning in MCI (Chandler et al., 2017). We have previously shown that cognitive impairment severity and personality traits are associated with MSS learning (De Wit et al., 2021; Khayoun et al., 2021). In this study, we hypothesized that 1) participants with single domain aMCI (SD‐aMCI) will have higher MSS learning scores than multi‐domain aMCI (MD‐aMCI), and 2) participants with suspected Alzheimer’s disease (AD) etiology will have lower MSS learning scores than other etiologies.MethodParticipants (mean age = 75.2) underwent daily MSS training between 2017 and 2021 as part of the 10‐day Mayo Clinic HABIT program. The MSS learning success score (LSS) was determined by how far participants progressed in three learning phases of increasing difficulty: Acquisition (0‐2 points), Application (3‐4 points), and Adaptation (5‐6 points; Greenway et al., 2008). Ordinal logistic regression analysis was used to predict MSS learning scores between SD‐aMCI (n = 142) versus MD‐aMCI (n = 119), and AD etiology (n = 213) versus other neurodegenerative etiologies (n = 57). Dementia Rating Scale‐2 scores (Jurica, 2001) were included to control for cognitive severity.ResultCompared to participants with SD‐aMCI, those with MD‐aMCI had 54.1% lower odds of having higher LSS at training end (p = .004), after controlling for cognitive impairment severity. AD versus other etiology’s impact on LSS was nonsignificant.ConclusionParticipants with MD‐aMCI showed poorer MSS learning efficiency than participants with SD‐aMCI. Etiology did not impact MSS learning. Results suggest having more than just memory impairment (e.g., additional language or executive dysfunction) reduces MSS learning, regardless of overall impairment level. Additional MSS training may be needed to facilitate learning for these individuals.

Blinatumomab is an efficacious immunotherapeutic agent in B cell acute lymphoblastic leukemia (B-ALL). However, the pharmacogenomic basis of leukemia response to blinatumomab is unclear. Using genome-wide CRISPR, we comprehensively identified leukemia intrinsic factors of blinatumomab sensitivity, i.e., the loss of CD58 as a top driver for resistance, in addition to CD19 . Screening 1639 transcription factor genes, we then identified PAX5 as the key activator of CD58. ALL with the PAX5 P80R mutation also expressed the lowest level of CD58 among 20 ALL molecular subtypes in 1988 patients. Genome editing confirmed the effects of this mutation on CD58 expression and blinatumomab sensitivity in B-ALL, with validation in patient leukemic blasts. We described a PAX5-driven enhancer at the CD58 locus, which was disrupted by PAX5 P80R, and the loss of CD58 abolished blinatumomab-induced T cell activation with global changes in transcriptomic/epigenomic program. In conclusion, we identified previously unidentified genetic mechanisms of blinatumomab resistance in B-ALL, suggesting strategies for genomics-guided treatment individualization.

Abstract Differential abundance analysis (DAA) is one central statistical task in microbiome data analysis. A robust and powerful DAA tool can help identify highly confident microbial candidates for further biological validation. Current microbiome studies frequently generate correlated samples from different microbiome sampling schemes such as spatial and temporal sampling. In the past decade, a number of DAA tools for correlated microbiome data (DAA-c) have been proposed. Disturbingly, different DAA-c tools could sometimes produce quite discordant results. To recommend the best practice to the field, we performed the first comprehensive evaluation of existing DAA-c tools using real data-based simulations. Overall, the linear model-based methods LinDA, MaAsLin2 and LDM are more robust than methods based on generalized linear models. The LinDA method is the only method that maintains reasonable performance in the presence of strong compositional effects.

ABSTRACT G0S2 and HIG2 are two selective inhibitors of ATGL (also known as PNPLA2), the key enzyme for intracellular lipolysis. Whereas G0S2 regulates triglyceride (TG) mobilization in adipocytes and hepatocytes, HIG2 functions to enhance intracellular TG accumulation under hypoxic conditions. A homologous hydrophobic domain (HD) is shared by G0S2 and HIG2 (also known as HILPDA) for binding to ATGL. However, the determinants of their lipid droplet (LD) localization are unknown. Here, we study how G0S2 and HIG2 are targeted to LDs, and identify both ATGL-independent and -dependent mechanisms. Structural prediction and studies in cells reveal that ATGL-independent localization of G0S2 to both the endoplasmic reticulum (ER) and LDs is mediated by a hairpin structure consisting of two hydrophobic sequences. Positively charged residues in the hinge region play a crucial role in sorting G0S2, which initially localizes to ER, to LDs. Interestingly, the role of these positive charges becomes dispensable when ATGL is co-expressed. In comparison, HIG2, which lacks a similar hairpin structure, is dependent on ATGL for its full LD targeting. Thus, our studies identify specific structural features and mechanisms for mediating accumulation of these two ATGL inhibitors on LDs.

Introduction: The voltage-gated proton channel Hv1 is a member of the voltage-gated ion channel family. Hv1 channel controls acid extrusion and regulates pH homeostasis in various cell types. Recent evidence showed that the Hv1 were expressed in the heart. Hypothesis: We propose the Hv1 channel is associated with cardiac function. Methods: To investigate the role of Hv1 in cardiac myocytes, we performed a transcriptomic analysis of wild-type (WT) and Hv1-/- mouse hearts. Results: Hv1 null hearts exhibited a differential transcriptome profile compared with wild-type hearts. The RNA-seq data indicating impaired pH homeostasis in Hv1 null hearts were the downregulated NADPH oxidoreductases (NOXs) and decreased expression of Cl-/HCO3- exchanger. Additionally, Hv1 null hearts exhibited differential expression of cardiac ion channels, suggesting a potential role of Hv1 in cardiac electrophysiological remodeling. Conclusions: The data indicated that Hv1 was involved in cardiac pH homeostasis and showed that Hv1 was a regulator of gene transcriptional networks controlling NOX signaling and CO2 homeostasis in the heart. The study highlights the importance of Hv1 in cardiac function and may present a new target associated with heart diseases.

Abstract Myeloid cells comprising up to 50% of total tumor mass in glioblastoma (GBM) contribute to tumor progression and immunosuppression. Restraining glioma-induced myeloid cell infiltration increases functional T cells within the tumors, improves the efficacy of checkpoint blockade, and significantly extends mouse survival. Here, we focus on an ion channel, voltage-gated proton channel Hv1, which is mainly expressed in myeloid cells and shapes the physiological functions of myeloid cells. Our bioinformatics analysis demonstrated that elevated Hv1 expression in the tumor mass correlates with poor disease prognosis in patients. Using the leading immunocompetent model of GBM in mice, we showed that Hv1 knockout mice (Hv1-/-) exhibit slower glioma progression and prolonged survival. Notably, in vivo two-photon imaging, immunofluorescence, and full-spectrum flow cytometry revealed that Hv1-/- mice have reduced monocyte/macrophage infiltration, higher frequency of MHCII+ among all infiltrating myeloid cells, and increased PD-1+CD4+ T cells in the tumor-burdened hemisphere. As a result, we combined anti-PD-1 treatment with Hv1 knockout in the middle stage of glioma, and found that approximately 30% of Hv1-/- mice were cured. Together, our results demonstrated that Hv1 regulates myeloid infiltration and could be a novel therapeutic target for the treatment of GBM.