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Andrews, E.

Publications and source records attributed to Andrews, E..

8 recordsLinked to original sources
bioRxiv2026

Beyond rumination: an ecological momentary assessment of daily thinking patterns in maladaptive daydreaming

Maladaptive daydreaming is a form of maladaptive repetitive thought characterized by excessive, dysfunctional fantasy engagement, with notable links to psychological distress and poor well-being. Although symptoms can be reliably measured along a continuum, it remains unclear how they manifest in the phenomenological characteristics of everyday thinking, as well as which thought characteristics are unique to maladaptive daydreaming versus shared with trait rumination, a transdiagnostic manifestation of maladaptive repetitive thinking that frequently co-occurs with maladaptive daydreaming. To advance these questions, we conducted a pre-registered study using ecological momentary assessment to track the everyday thoughts of 446 young adults (aged 18 to 34) spanning a range of maladaptive daydreaming symptom severity as assessed with the 16-item Maladaptive Daydreaming Scale. Higher maladaptive daydreaming scores were associated with several poor mental health indicators, including higher trait rumination. Positive associations between maladaptive daydreaming scores and both negatively-valenced and task-unrelated thinking emerged, yet these relationships were accounted for by variance shared with rumination. Beyond rumination, higher maladaptive daydreaming scores were uniquely associated with worse mood, as well as greater internally-oriented attention, more socially-oriented thought, and greater overall thought persistence. Maladaptive daydreaming also uniquely moderated the relationship between internal orientation and social orientation, such that the positive association between internal and social thought content became stronger at higher levels of maladaptive daydreaming. Overall, these findings provide novel evidence that maladaptive daydreaming levels are linked to unique socioemotional features and restricted dynamics, beyond its overlap with general ruminative distress in everyday life. These insights suggest that clinical interventions should target immersive fantasy engagement alongside transdiagnostic maladaptive repetitive thinking.

neuroscience↗
bioRxiv2026

ITPKB is a conserved regulator of natural killer cell desensitization/education that constrains antitumor immunity

Natural Killer (NK) cell desensitization induced by persistent stimulation limits durable antitumor immunity, yet the molecular mechanisms governing this dysfunctional state remain poorly defined. To identify conserved regulators of NK cell desensitization, we performed comparative transcriptomic analyses across multiple murine models of persistent activation and dysfunction. This approach defined a shared transcriptional program of desensitization and identified Itpkb to be upregulated across multiple distinct contexts. Genetic and pharmacological inhibition of ITPKB enhanced degranulation, cytokine production, and cytotoxicity in both murine and human NK cells under multiple desensitization settings. Mechanistically, ITPKB regulated signaling downstream of persistent activation through the IP3/IP4 axis, limiting calcium mobilization and NFAT-dependent transcriptional responses in desensitized NK cells. Furthermore, inhibition or deletion of ITPKB enhanced NK-cell mediated tumor control in vivo and improved the efficacy of adoptively transferred CAR-NK cells, underscoring the translational potential of targeting this pathway. Together, these findings identify ITPKB as a cell-intrinsic regulator of NK cell desensitization and support targeting the IP3/IP4 signaling axis to enhance NK cell-mediated antitumor immunity.

immunology↗
bioRxiv2025

Escape from SARS-CoV-2 Nsp1-mediated host shutoff by TIAR transcript reveals general features of Nsp1 resistance

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune escape strategies include general inhibition of host gene expression referred to as host shutoff. Viral non-structural protein 1 (Nsp1) is the main host shutoff factor that blocks protein translation and induces messenger RNA (mRNA) cleavage and degradation. Viral mRNAs are resistant to the translation shutoff and cleavage induced by Nsp1, and the 5 leader sequence present in all viral mRNAs has been shown to confer resistance. However, the exact molecular mechanism for escape from Nsp1 host shutoff has not been demonstrated. In our previous work, we analyzed the effects of Nsp1 on the expression and function of cellular proteins important for stress granule formation. We discovered that the host transcript for the TIA1 cytotoxic granule-associated RNA binding protein like 1 (TIAL1, commonly referred to as TIAR) is resistant to SARS-CoV-2 Nsp1 host shutoff. In this work, using reporter shutoff assays, we examined sequence and structural features of the TIAR 5 untranslated region (UTR) and discovered that the first 23 nucleotides of the TIAR transcript are both necessary and sufficient to confer resistance to the Nsp1. Furthermore, our work revealed that the lack of guanosines within a window of 10 to 18 nucleotides downstream from the 5 end is a defining feature of Nsp1-resistant transcripts shared between the SARS-CoV-2 leader sequence and the TIAR 5 UTR. Our findings are consistent with the model in which sequence features of 5 UTRs, rather than their secondary structure, confer resistance to Nsp1 host shutoff to both viral and cellular mRNAs.

molecular biology↗
bioRxiv2025

Intra-Tumoral Treg Ablation Unleashes NK Cell-Mediated Control of CD8 T Cell-Resistant Tumors

Cancer cells frequently lose MHC I to evade CD8+ T cell recognition. While Natural Killer (NK) cells are poised to target MHC I-deficient cancer cells, MHC I loss alone is often insufficient to unleash fully effective NK cell responses. Here we show that selective intra-tumoral (IT) ablation of regulatory T (Treg) cells elicited potent antitumor NK cell responses that controlled MHC I-deficient and even MHC I+ cancers. Tregs controlled the activation, maturation, and anti-tumor cytotoxic activity of NK cells within the tumor microenvironment. Mechanistically, IT Tregs prevented the cDC2-dependent induction of IL-2 production by CD4+ Tconv cells that was necessary for NK cell activation. Systemically administered antibodies that selectively depleted IT Tregs similarly empowered NK- dependent tumor control. These findings expand the breadth of Treg-mediated cancer immunosuppression to encompass antitumor NK cells and suggest that targeting Tregs in tumors can control CD8+ T cell-resistant cancers. One Sentence SummaryIT Treg ablation drives NK cell tumor control via CD4+ Tconv-derived IL-2, eliminating MHC I+/MHC I- cancers without systemic toxicity.

immunology↗
bioRxiv2025

Apolipoprotein E abundance is elevated in the brains of individuals with Down syndrome-Alzheimer's disease

Trisomy of chromosome 21, the cause of Down syndrome (DS), is the most commonly occurring genetic cause of Alzheimers disease (AD). Here, we compare the frontal cortex proteome of people with Down syndrome-Alzheimers disease (DSAD) to demographically matched cases of early-onset AD and healthy ageing controls. We find wide dysregulation of the proteome, beyond proteins encoded by chromosome 21, including an increase in the abundance of the key AD-associated protein, APOE, in people with DSAD compared to matched cases of AD. To understand the cell types that may contribute to changes in protein abundance, we undertook a matched single-nuclei RNA-sequencing study, which demonstrated that APOE expression was elevated in subtypes of astrocytes, endothelial cells and pericytes in DSAD. We further investigate how trisomy 21 may cause increased APOE. Increased abundance of APOE may impact the development of, or response to, AD pathology in the brain of people with DSAD, altering disease mechanisms with clinical implications. Overall, these data highlight that trisomy 21 alters both the transcriptome and proteome of people with DS in the context of AD, and that these differences should be considered when selecting therapeutic strategies for this vulnerable group of individuals who have high-risk of early-onset dementia.

neuroscience↗
bioRxiv2023

Genomic Landscape of Patients with Germline RUNX1 Variants and Familial Platelet Disorder with Myeloid Malignancies in a Natural History Study

Germline RUNX1 mutations lead to familial platelet disorder with associated myeloid malignancies (FPDMM), which is characterized by thrombocytopenia and a life-long risk (35-45%) of hematological malignancies. We recently launched a longitudinal natural history study for patients with FPDMM at the NIH Clinical Center. Among 29 families with research genomic data, 28 different germline RUNX1 variants were detected. Besides missense mutations enriched in Runt homology domain and loss-of-function mutations distributed throughout the gene, splice-region mutations and large deletions were detected in 6 and 7 families, respectively. In 24 of 54 (44.4%) non-malignant patients, somatic mutations were detected in at least one of the clonal hematopoiesis of indeterminate potential (CHIP) genes or acute myeloid leukemia (AML) driver genes. BCOR was the most frequently mutated gene (in 9 patients), and multiple BCOR mutations were identified in 4 patients. Mutations in 7 other CHIP or AML driver genes (DNMT3A, TET2, NRAS, SETBP1, SF3B1, KMT2C, and LRP1B) were also found in more than one non-malignant patient. Moreover, three unrelated patients (one with myeloid malignancy) carried somatic mutations in NFE2, which regulates erythroid and megakaryocytic differentiation. Sequential sequencing data from 19 patients demonstrated dynamic changes of somatic mutations over time, and stable clones were more frequently found in elderly patients. In summary, there are diverse types of germline RUNX1 mutations and high frequency of somatic mutations related to clonal hematopoiesis in patients with FPDMM. Monitoring dynamic changes of somatic mutations prospectively will benefit patients clinical management and reveal mechanisms for progression to myeloid malignancies. Key PointsO_LIComprehensive genomic profile of patients with FPDMM with germline RUNX1 mutations. C_LIO_LIRising clonal hematopoiesis related secondary mutations that may lead to myeloid malignancies. C_LI

genomics↗
bioRxiv2021

Pancreatic cancer risk predicted from disease trajectories using deep learning

Pancreatic cancer is an aggressive disease that typically presents late with poor patient outcomes. There is a pronounced medical need for early detection of pancreatic cancer, which can be addressed by identifying high-risk populations. Here we apply artificial intelligence (AI) methods to a dataset of 6 million patient records with 24,000 pancreatic cancer cases in the Danish National Patient Registry (DNPR) and, for comparison, a dataset of three million records with 3,900 pancreatic cancer cases in the United States Department of Veterans Affairs (US-VA) healthcare system. In contrast to existing methods that do not use temporal information, we explicitly train machine learning models on the time sequence of diseases in patient clinical histories and test the ability to predict cancer occurrence in time intervals of 3 to 60 months after risk assessment. For cancer occurrence within 36 months, the performance of the best model (AUROC=0.88, DNPR), trained and tested on disease trajectories, exceeds that of a model without longitudinal information (AUROC=0.85, DNPR). Performance decreases when disease events within a 3 month window before cancer diagnosis are excluded from training (AUROC[3m]=0.83). Independent training and testing on the US-VA dataset reaches comparable performance (AUROC=0.78, AUROC[3m]=0.76). These results raise the state-of-the-art level of performance of cancer risk prediction on real-world data sets and provide support for the design of prediction-surveillance programs based on risk assessment in a large population followed by affordable surveillance of a relatively small number of patients at highest risk. Use of AI on real-world clinical records has the potential to shift focus from treatment of late-stage to early-stage cancer, benefiting patients by improving lifespan and quality of life.

bioinformatics↗