Despite advances in managing traditional risk factors, coronary artery disease (CAD) remains the leading cause of mortality. Circulating hematopoietic cells influence risk for CAD separately from traditional risk factors, but the role of a key regulating organ, the spleen, is unknown. The understudied spleen is a representation of the hematopoietic system optimally suited for unbiased radiologic investigations toward mechanistic insights. Here, we leveraged deep learning to extract 107 splenic radiomic features from abdominal magnetic resonance imaging (MRI) scans of 42,059 UK Biobank participants and of 2745 Mass General Brigham Biobank (MGBB) participants. Of these, 10 features from UK Biobank were associated with CAD. Genome-wide association analysis of CAD-associated features identified 219 loci, including 9p21. Variants at 9p21, the strongest yet mechanistically elusive CAD locus, were associated with splenic features such as run-length nonuniformity, reflecting heterogeneity of continuous texture regions. Research MRI findings were consistent internally, but external clinical validation highlighted challenges in translating analyses of abdominal MRI scans to routine clinical practice because of variability in imaging protocols and greater clinical heterogeneity among patients. Our study, combining deep learning with genomics, presents a framework to uncover potential splenic involvement in CAD and emphasizes translational gaps between research and clinical radiomics.
Cerebrospinal fluid (CSF) is a key component of healthy brain function, constantly circulating to maintain brain homeostasis. Large waves of CSF flow appear in nonrapid eye movement (NREM) sleep, and these CSF flow waves are associated with neural slow waves in the electroencephalogram (EEG). Whether neural slow waves are causally linked to CSF flow, and whether this flow can be enhanced, is not yet established. We developed a technique for performing closed-loop auditory stimulation of sleep slow waves with simultaneous magnetic resonance imaging (MRI) using real-time denoising and a neural network-based strategy for stimulus targeting. We first established that our technique could increase EEG slow waves during sleep inside the MRI scanner in healthy adults. We then found that closed-loop auditory stimulation during sleep caused increased CSF flow waves. Furthermore, this CSF flow effect was phase dependent and only apparent when auditory stimuli were aligned with slow-wave peaks. Widespread hemodynamic waves were also elicited by the stimulus, suggesting a brain-wide modulation contributing to this CSF flow effect. This work demonstrates that closed-loop slow-wave neurofeedback causes waves of CSF flow and provides a technique for simultaneous modulation and imaging of CSF flow during sleep that can next be explored as a potential translational tool in clinical populations.
Immune checkpoint inhibitors (ICIs) have transformed Merkel cell carcinoma (MCC) outcomes, but most patients with MCC develop resistance. We identified T cell receptor (TCR)MCC1, a highly avid, HLA-A*02:01-restricted TCR targeting the Merkel cell polyomavirus (MCPyV) oncoprotein large-T antigen15-23. Seven patients with ICI-refractory metastatic MCPyV+ MCC received TCRMCC1-transduced cells (TTCR-MCC1 cells) after lymphodepleting chemotherapy or HLA-enhancing interventions [radiation or interferon gamma-1b (Actimmune)], with concurrent ICIs (NCT03747484). TTCR-MCC1 cells trafficked to tumor sites and expressed a gene expression profile compatible with T cell activation, with tumor regression observed in two patients. However, therapeutic activity was limited by HLA class I silencing, a common mechanism of immune escape in MCC. In one patient, delayed tumor regression coincided with endogenous effector immune activation and restoration of MCC HLA expression, implying that robust local responses could reverse HLA silencing. To overcome this barrier, we engineered CD4 and CD8 TTCR-MCC1 cells to coexpress CD8αβ and a CD200R-CD28 switch receptor, enabling CD4 T cell engagement and T cell costimulation. These modifications enhanced tumor infiltration, increased HLA expression, and improved control of HLAlow MCC in vivo in mice. These findings support the feasibility of TCR-engineered cell therapy for MCPyV+ MCC and provide a blueprint for overcoming immune evasion via targeted localized enhancement of antigen presentation.
Snakebite envenoming causes more than 100,000 deaths annually, with India bearing nearly half of this burden. Current equine plasma-derived antivenoms suffer from variable efficacy, safety concerns, and limited cross-neutralization of geographically diverse venoms. Here, we report a rationally designed recombinant antivenom composed of five nanobodies (VHHs) that target the α-neurotoxins, cytotoxins, and phospholipases A2 prevalent in the venoms of cobra and king cobra species from India. These VHHs were previously identified and functionally validated against homologous toxin families from African elapids. In murine preincubation and rescue models of snakebite envenoming, the cocktail prevented mortality after injection with venom from the monocled cobra (Naja kaouthia), both king cobra species (Ophiophagus kaalinga and Ophiophagus hannah) from the Western Ghats and Northeast India, and pan-Indian populations of spectacled cobra (Naja naja). These findings demonstrate the feasibility of developing broad-spectrum nanobody-based recombinant antivenoms with continent-wide coverage as a safe and regionally adaptable biologic for snakebite envenoming therapy.
Despite the introduction of genome sequencing (GS) for rare disease diagnostics, a genetic cause is not identified in most patients. Here, we explored the potential of proteomics to improve the diagnostic yield in 424 patients with rare diseases from the 100,000 Genomes Project (100kGP) without a genetic diagnosis. Serum proteomic profiling was performed using the Olink Explore 1536 assay (N = 1463 proteins). For 13 patients without genetic diagnoses, detection of lower serum protein "outliers" (z-score < -2) led to confirmed genetic diagnoses by resolving variants of uncertain significance or prioritizing genes for targeted GS reanalysis. For 23 additional patients without genetic diagnoses (64% of findings), we identified candidate gene-disease links and variants through convergent evidence from lower protein outliers and variants ranked through the variant prioritization tool Exomiser. For example, we identified a candidate heterozygous missense variant [Genome Aggregation Database (gnomAD) minor allele frequency = 0.006%] in tyrosine kinase with immunoglobulin-like and epidermal growth factor homology domains 1 (TIE1) that was only present in a patient with lower TIE1 serum abundance (z-score = -5.12) and their father, both of whom were affected by the same monogenic cardiac disorder, but in no other individuals from the 100kGP. Missense (52.5%) and splice region (27.5%) variants accounted for most diagnostic or candidate variants prioritized. This proof-of-principle study demonstrated that serum proteomics can support rare disease diagnosis and identify disease-causing genes in patients undiagnosed after GS, although successful implementation will likely depend on tissue specificity of protein expression, detectability in blood, proteomic platform coverage, and sensitivity.
