Ogmen et al. report clinical features and disease mechanisms in patients with microcephaly-lymphedema-chorioretinopathy with KIF11 pathogenic variants, focusing on lymphatic function. The cover image shows confocal immunofluorescence microscopy of a paraffin section of human duodenum from a patient with a KIF11 variant. E-cadherin labels epithelial cells in yellow, PDPN marks lymphatic vessels in magenta, CD31 visualizes blood vessels in cyan, and nuclei are shown in orange. Image credit: Pia Ostergaard, Kazim Ogmen, Silvia Martin-Almedina, Felix Heymann, Rose Yinghan Behncke, and René Hägerling.
Alveolar macrophages (AMs) catabolize lipid-rich pulmonary surfactant to support gas exchange and have anti-inflammatory programming to limit tissue damage in response to minor challenges. GATA transcription factors (TFs) shape immune cell fates and GATA2 is expressed in a lung-specific manner in macrophages. GATA2 mutations and lung macrophage downregulation of GATA2 have been associated with chronic pulmonary pathologies in humans, but the role of GATA2 in coordinating AM function is not well defined. Using mice with myeloid-specific deletion of the GATA2 DNA binding C-terminal zinc finger domain, we show that GATA2 deficiency promotes enhanced inflammatory gene expression and metabolic dysfunction in AMs in response to type 2 stimuli. While homeostatic functions of AMs remain largely intact, GATA2 deficiency increases expression of type 2 response genes during IL-33-induced inflammation. Coincident with GATA2-dependent expression of genes in metabolic pathways, seahorse metabolic flux analysis indicates that AM metabolism is compromised in the absence of GATA2. AM GATA2-dependent gene networks are enriched for targets of TFs previously demonstrated to interact with GATA2 in other cellular contexts, including PU.1, PPARγ, and other regulators of AM function. Our data suggest that GATA2 modulates AM metabolic and transcriptomic programming to restrain responses and maintain AM identity during inflammation.
Morgan Jackson-Strong, Satarupa Ganguly, Aaron Francis, Flavia Rago, Jitendra Kanshana, Brandon A. Michalides, Lihong Teng, Omkar S. Betsur, Sonia Kruszelnicki, Karsen E. Shoger, Aaron Kim, Kay Bajpai, Amina Suleyman, Abigail Sekyere, Mika Hara, Varsha Sriram, Alok Kumar, Greg M. Delgoffe, Niranjana Natarajan, John F. Alcorn, Alison B. Kohan, Rachel A. Gottschalk
The biological mechanisms underlying long COVID in the pediatric population are poorly understood. Our study aimed to characterize the immune pathophysiology of long COVID in children and young people (CYP). We analyzed major immune cell compartments in PBMCs, as well as specific SARS-CoV-2 antibody response in CYP with (n=99) and without (n=18) long COVID at three months following acute infection. Our findings indicate that pediatric long COVID is associated with a dysregulated immune response characterized by altered innate immunity and overactivated T-, B- and NK-cell responses. Furthermore, CYP with long COVID had an impaired humoral response to SARS-CoV-2 marked by a dysregulated B-cell compartment and lower levels of anti-RBD IgG and IgA. This correlated with reduced neutralizing capacity against SARS-CoV-2. Random forest analysis identified CCR6 expression on myeloid cells as the most relevant biomarker that distinguishes long COVID from control individuals with 79% accuracy.
Jon Izquierdo-Pujol, Núria Pedreño-Lopez, Tetyana Pidkova, Maria Nevot, Victor Urrea, Fernando Laguía, Francisco Muñoz-López, Judith Dalmau, Alba Gonzalez-Aumatell, Clara Carreras-Abad, María Méndez, Carlos Rodrigo, Marta Massanella, Julià Blanco, Jorge Carrillo, Benjamin Trinité, Javier Martinez-Picado, Sara Morón-López
BACKGROUND. To construct multi-trait polygenic scores (PRS) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validate their performance in diverse cohorts, and identify PRS-related proteins for potential therapeutic targeting. METHODS. PRSmix+, a multi-trait PRS framework, is used to train a composite PRS (PRSmulti) in COPDGene non-Hispanic white participants (n=6,647). Associations of PRSmulti with COPD status (GOLD 2-4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American (n=2,466), ECLIPSE (n=1,858), MassGeneral Brigham Biobank (n=15,152), and All of Us (n=118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRSmulti and were validated with proteomic data in COPDGene (n=5,173) and UK Biobank (n=5,012). RESULTS. PRSmix+ selected 7 traits for PRSmulti. In multivariable models, PRSmulti was associated with COPD status (meta-analysis random effects (RE) OR 1.58 [95% CI: 1.28-1.94]) and exacerbation frequency (meta-analysis RE beta 0.21 [95% CI: 0.11-0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRSmulti outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRS that were also validated with measured protein levels in COPDGene and UK biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. CONCLUSIONS. Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. TRIAL REGISTRATION. COPDGene: NCT00608764; ECLIPSE: NCT00292552.
Chengyue Zhang, Iain R. Konigsberg, Yixuan He, Jingzhou Zhang, Tinashe Chikowore, William B. Feldman, Xiaowei Hu, Yi Ding, Bogdan Pasaniuc, Diana Chang, Qingwen Chen, Jessica A. Lasky-Su, Julian Hecker, Martin D. Tobin, Jing Chen, Sean Kalra, Katherine A. Pratte, Hae Kyung Im, Emily S. Wan, Ani Manichaikul, Edwin K. Silverman, Russell P. Bowler, Leslie A. Lange, Victor E. Ortega, Alicia R. Martin, Michael H. Cho, Matthew R. Moll
Sebastian Kämpf, Marjan Hematianlarki, Leon Altmann, Jessica M. Bright, Alyssa M. A. Toda, Zohreh Mirzapoor, Valentin Zollner, Anja Werner, Johanna Bulang, Barbara Radovani, Miriam Wöhner, William Avery, Mark J. Karbarz, Pamela B. Conley, Greg P. Coffey, Falk Nimmerjahn
Dual-degree medical students pursue additional training to prepare for careers in research, public health, and administration, but how these experiences influence residency application behaviors and outcomes are poorly understood. We analyzed 36,298 residency applicants from the TexasSTAR database spanning 2017-2023 to compare application, interview, and match patterns among single-degree MD applicants and those with MD-PhD, MD-MPH, MD-MBA, or MD-MSc degrees. Despite differences in academic metrics, application strategies, and interview rates, match rates were similar across degree groups. MD-PhD students applied to fewer programs but had the highest interview offer-to-application rate and matched at more prestigious programs based on Doximity rankings. Beyond traditional application metrics such as board scores, research productivity, grades, and honor society membership, strategies including away rotations, geographic preferencing, and program signaling were associated with increased interview offers and match success among all applicants but were less influential for dual-degree applicants. These findings suggest dual-degree applicants require specialized advising and evaluation.
Daniel C. Brock, Deborah D. Rupert, Toni Darville, Caroline S. Jansen, Elias M. Wisdom, Cynthia Y. Tang