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Patient disposition
A flowchart that illustrates enrollment of patients with RET fusion–positive solid tumors in the safety (n = 29) and efficacy-evaluable (n = 23) populations in the context of the overall study population of 587 patients, as well as the status of these patients at the data cutoff. aOther RET-mutant tumors (n = 15), no or unknown RET status (n = 2) and prior treatment with a RET inhibitor (n = 23). bThree patients (two with colon cancer and one with cholangiocarcinoma) had additional driver mutations (KRAS, PIK3CB and BRAF).
Individual tumor response and treatment duration waterfall and swimlane plots for the efficacy-evaluable population
In 23 patients eligible for efficacy analyses: a, tumor response by BICR and maximum change from baseline in target lesion size, showing each patient’s tumor type and RET fusion partner; b, treatment duration, indicating the corresponding tumor type and the timeline for response, where the dotted line represents median time to response (1.9 months). One patient with progression based on a new site of disease did not have post-baseline assessment of RECIST target lesions and so is not shown in a.
Time-dependent disease evaluations in two patients after pralsetinib treatment
Baseline and 8-week disease evaluation in a 51-year-old woman with RET–NCOA4 fusion–positive cholangiocarcinoma: a, at first disease evaluation after 8 weeks receiving pralsetinib, a left hepatic lobe lesion measuring 2 × 3 cm at baseline had reduced to 1.2 × 1.9 cm; b, a prior heterogeneously enhancing soft tissue mass in the right gluteal muscles had decreased in size and enhancement and showed increased cystic and necrotic components compared to baseline scans. c, Baseline, 5-month and 19-month disease evaluation in a 60-year-old woman with a RET–CCDC6 fusion–positive sarcoma presenting as two muscular masses in the right upper arm.
Article
  • Vivek SubbiahVivek Subbiah
  • Philippe A. CassierPhilippe A. Cassier
  • Salvatore SienaSalvatore Siena
  • [...]
  • Giuseppe CuriglianoGiuseppe Curigliano
Oncogenic RET fusions occur in diverse cancers. Pralsetinib is a potent, selective inhibitor of RET receptor tyrosine kinase. ARROW (NCT03037385, ongoing) was designed to evaluate pralsetinib efficacy and safety in patients with advanced RET-altered solid tumors. Twenty-nine patients with 12 different RET fusion–positive solid tumor types, excluding non-small-cell lung cancer and thyroid cancer, who had previously received or were not candidates for standard therapies, were enrolled. The most common RET fusion partners in 23 efficacy-evaluable patients were CCDC6 (26%), KIF5B (26%) and NCOA4 (13%). Overall response rate, the primary endpoint, was 57% (95% confidence interval, 35–77) among these patients. Responses were observed regardless of tumor type or RET fusion partner. Median duration of response, progression-free survival and overall survival were 12 months, 7 months and 14 months, respectively. The most common grade ≥3 treatment-related adverse events were neutropenia (31%) and anemia (14%). These data validate RET as a tissue-agnostic target with sensitivity to RET inhibition, indicating pralsetinib’s potential as a well-tolerated treatment option with rapid, robust and durable anti-tumor activity in patients with diverse RET fusion–positive solid tumors. Results from the precision oncology ARROW trial identify the RET receptor tyrosine kinase as a tissue-agnostic target and the drug pralsetinib’s potential as a well-tolerated treatment option with rapid, robust and durable anti-tumor activity in patients with diverse RET fusion–positive solid tumors.
 
Article
  • Selim ChaibSelim Chaib
  • Tamar TchkoniaTamar Tchkonia
  • James L. KirklandJames L. Kirkland
Interlinked and fundamental aging processes appear to be a root-cause contributor to many disorders and diseases. One such process is cellular senescence, which entails a state of cell cycle arrest in response to damaging stimuli. Senescent cells can arise throughout the lifespan and, if persistent, can have deleterious effects on tissue function due to the many proteins they secrete. In preclinical models, interventions targeting those senescent cells that are persistent and cause tissue damage have been shown to delay, prevent or alleviate multiple disorders. In line with this, the discovery of small-molecule senolytic drugs that selectively clear senescent cells has led to promising strategies for preventing or treating multiple diseases and age-related conditions in humans. In this Review, we outline the rationale for senescent cells as a therapeutic target for disorders across the lifespan and discuss the most promising strategies—including recent and ongoing clinical trials—for translating small-molecule senolytics and other senescence-targeting interventions into clinical use. Cellular senescence has emerged as a promising therapeutic target for disorders across the lifespan; this Review highlights the most promising strategies for translating senescence-targeting interventions into clinical use in the near future.
 
Plasma biomarkers and Aβ pathology
a,b, Effect sizes of plasma biomarker levels change by AT groups (a; n = 397; n = 249 A−T−, n = 104 A+T−, n = 31 A+T+, n = 13 A−T+) and by CSF/PET groups (b; n = 339; n = 224 CSF/PET Aβ negative, n = 89 low burden, n = 26 CSF/PET Aβ positive). Individuals with a low burden of Aβ pathology were defined as CSF Aβ42/40 <0.071 and Aβ PET <30 Centiloids. The effect size of group differences was estimated by calculating Cohen’s d, in which the dependent variable was the residual of log(transformed) plasma biomarkers regressed on age and sex. The error bars denote the 95% CIs. c,d, The graphs represent the z-score changes of each plasma biomarker using the mean and the s.d. of that plasma biomarker in the group of participants with CSF Aβ42/40 >0.1 as a reference. The resulting z-scores are shown as a function of Aβ PET Centiloids (c) or CSF Aβ42/40 (d) using a robust local weighted regression method. The vertical dashed lines depict the Aβ PET 12 Centiloids (c) and CSF Aβ42/40 positivity cut-off (d). The horizontal dashed lines depict the abnormality threshold held at 1.5 and 2 s.d. above the mean. The horizontal axis direction of CSF Aβ42/40 (d) was inverted. e, Association of plasma biomarkers with Aβ PET at the voxel level. Associations were tested using voxel-wise, univariate, independent, linear regression models with age and sex as covariates. All plasma biomarkers showed a significant association with Aβ deposition in orbitofrontal and precuneus. These associations were stronger with plasma p-tau231 and p-tau217 and also extended to the insula and striatum. Statistical significance was set at P < 0.001 uncorrected for multiple comparisons with a cluster size of k > 100 voxels. All tests were one sided but contrasts in both directions were tested. No significant associations were found in the opposite direction. Statistical maps were resliced to 0.5 mm³ (cubic) for visualization purposes.
Article
Blood biomarkers indicating elevated amyloid-β (Aβ) pathology in preclinical Alzheimer’s disease are needed to facilitate the initial screening process of participants in disease-modifying trials. Previous biofluid data suggest that phosphorylated tau231 (p-tau231) could indicate incipient Aβ pathology, but a comprehensive comparison with other putative blood biomarkers is lacking. In the ALFA+ cohort, all tested plasma biomarkers (p-tau181, p-tau217, p-tau231, GFAP, NfL and Aβ42/40) were significantly changed in preclinical Alzheimer’s disease. However, plasma p-tau231 reached abnormal levels with the lowest Aβ burden. Plasma p-tau231 and p-tau217 had the strongest association with Aβ positron emission tomography (PET) retention in early accumulating regions and associated with longitudinal increases in Aβ PET uptake in individuals without overt Aβ pathology at baseline. In summary, plasma p-tau231 and p-tau217 better capture the earliest cerebral Aβ changes, before overt Aβ plaque pathology is present, and are promising blood biomarkers to enrich a preclinical population for Alzheimer’s disease clinical trials. A comprehensive comparison of Alzheimer’s disease blood biomarkers in cognitively unimpaired individuals reveals that plasma p-tau231 and p-tau217 capture very early Aβ changes, showing promise as markers to enrich a preclinical population for Alzheimer’s disease clinical trials
 
Article
  • Annaliesa S. AndersonAnnaliesa S. Anderson
Pfizer had successes during COVID-19 by streamlining decisions and running several steps in parallel, a lightspeed approach that can be applied to other diseases.
 
The genomic landscape of RT
a, Summary of the study. mut., mutation. b, Increase in genomic alterations and epigenetic changes compared to healthy naive and memory B cells over the disease course. Center line indicates median; box limits indicate upper and lower quartiles; whiskers indicate 1.5 × interquartile range; and points indicate individual samples. c, Driver alterations of CLL and RT. New drivers in RT are labeled in blue. Each column represents a sample and genes are represented in rows. The transparency of the color of mutations and CNAs indicates the cancer cell fraction (CCF). The number of tumors harboring an alteration at the time of transformation is indicated for each biological group of drivers (left). Complex structural alterations are shown below, together with the total number of SVs. LOH, loss of heterozygosity. d, Schema of the CCND3 insertion next to the constant region IGLC1 in the RT sample of patient 835. e, Reciprocal translocation between MYCN and class-switch recombination (CSR) region of IGHG3 in the RT sample of patient 816 (top). MYCN expression based on bulk RNA-seq (bottom). f, Chromoplexy disrupting SMARCA4 in the RT sample of patient 4,675. g, The circos plot (left) displays the SVs (links) and CNAs (inner circle) found in the RT sample of patient 1,669. CNAs are colored by type and SVs are colored according to their occurrence within specific complex events. Target driver genes are annotated. Chromosome-specific plots (right) illustrate selected complex rearrangements affecting one or multiple driver genes with CNAs and SVs colored by type.
Mutational processes in RT
a, Principal component analysis (PCA) of the 96-mutational profile of CLL and RT. b, Signatures identified de novo in CLL/RT not reported in COSMIC. The main peaks of each signature are labeled in black. c, Contribution of mutational processes in CLL/RT. RT time points are marked in a rose color. B, peripheral blood; L, lymph node; M, bone marrow; (M), M-CLL. d, Therapies received before RT and presence/absence of SBS-melphalan, SBS-ganciclovir and SBS-RT at time of RT for each patient. mAB, monoclonal antibody; TBI, total body irradiation; Inh., inhibitor; Sig., signatures. e, Phylogenetic relationship of subclones and contribution of each mutational signature to their mutational profile. f, Relative contribution of mutational processes in CLL (no. 1) and RT subclones (top). Number of mutations (muts) in RT subclones (bottom). w/, with. g, Detection (top) and variant allele frequency (VAF) (bottom) of mutations assigned to the RT subclone during the disease course in patients 12 and 63 by high-coverage UMI-based NGS. Mutations are grouped according to the main peaks of SBS-RT. P values were obtained by Fisher’s test. LC, low confidence; HC, high confidence; NA, not available. h, Distribution of the CCF of the single-nucleotide variants (SNVs) assigned to the RT subclone based on WGS and stratified according to the main peaks of the SBS-RT. i, Relative contribution of mutational processes in regions of kataegis in CLL and RT (left). Two cases acquiring mutations in the immunoglobulin genes at time of RT (right). j, Clonal evolution along the disease course in patient 12 inferred from WGS. Abbreviations for treatment regimens are detailed in Extended Data Fig. 1a. Each subclone is depicted by a different color and number and its CCF is proportional to its height in each time point (vertical line). The phylogeny of the subclones with the main driver alterations is shown (top). Flow cytometry analysis for time points (T) 4, 5 and 6 (bottom). The size of the cells (forward scatter (FSC) versus side scatter (SSC), first row) and the expression levels of CD20 and CD38 (second row) differentiated CLL cells (yellowish) and the two larger size tumor populations (pale and dark rose color, respectively). Numbers along axes are divided by 1,000.
Early seeding of RT
a, Evolution of the RT subclone along the disease course based on WGS. Time lapse between the first and last sample analyzed (bottom). RT time points are marked in a rose color. Summary of the three patterns observed (right). b, Fish plot showing the clonal evolution along the course of the disease in patient 19 inferred from WGS analysis. Each subclone is depicted by a different color and number and its CCF is proportional to its height at each time point (vertical lines). Phylogeny of the subclones and main driver events (right). c, Mutation tree reconstructed by scDNA-seq for case 19 together with the fraction of cells carrying each specific combination of mutations in each time point. The total number of cells per sample is shown at the bottom. The number of cells assigned to each subclone is shown in Supplementary Table 20. d, Schematic representation of the clinical course and samples analyzed for patient 3,495 together with the size of the IGH subclones identified using high-coverage NGS analyses. Abbreviations for treatment regimens are detailed in Extended Data Fig. 1a. e, Clinical course and IGH subclones identified by DNA- and RNA-based NGS in patient 12. f, Uniform Manifold and Projection (UMAP) plot for case 12 based on the scRNA-seq data of all time points colored by annotation. g, Expression of key marker genes in each cluster identified in case 12. h, Distribution of cell-cycle phase scores for each cluster based on scRNA-seq in case 12. i, UMAP visualization split by time point in case 12 with the fraction of RT cells annotated. ‘n’, number of cells. j, Chromosomal alterations detected by WGS in chromosomes 1, 11 and 14 in CLL and RT samples of patient 12 (top). Copy number profile of RT cells detected at the different time points according to scRNA-seq. Only a subset of RT cells from time point 6 (time of diagnosis of RT) was included for illustrative purposes (bottom).
Proliferation, OXPHOS and BCR pathways dominate the epigenome and transcriptome of RT
a, PCA of the bulk epigenetic and transcriptomic layers analyzed. b, Heat map showing 150 regions with increased H3K27ac levels in RT. c, TF enriched within the ATAC peaks identified in the regions of increase H3K27ac in RT. The motif, percentage of RT-specific active regions and regions with increased H3K27ac in CLL that contained the motif and TF expression (bulk RNA-seq) in CLL and RT are shown. Center line indicates median; box limits indicate upper and lower quartiles; whiskers indicate 1.5 × interquartile range; points indicate individual samples. P values were derived using a one-tailed Wilcoxon rank-sum test. d, Heat map showing the DEGs between CLL and RT identified by bulk RNA-seq. Samples used in the differential expression analysis (DEA) are indicated. The overlap of DEGs with DNA methylation changes, H3K27ac and ATAC peaks is shown on the right. Selected genes are annotated. e, Intersection of upregulated genes in RT compared to CLL in scRNA-seq analyses. f, epiCMIT evolution from CLL to RT. P values were derived by paired Wilcoxon signed-rank test. g, Summary of the main gene sets modulated in RT based on bulk RNA-seq. NES, normalized enrichment score; ROS, reactive oxygen species. h, Gene set enrichment plot for OXPHOS and BCR signaling (bulk RNA-seq). i, OXPHOS and BCR signaling scores depicted at single-cell level for case 12 (all time points together). RT and CLL cells are highlighted (left). Ridge plots show the OXPHOS and BCR score across clusters (right). j, OXPHOS and BCR signaling scores of CLL and RT cells of patient 12 across time points by scRNA-seq. k, Distribution of OXPHOS and BCR signaling scores at a single-cell level across different time points of nine cases included in the study of Penter et al.⁴³. Center line indicates median; box limits indicate upper and lower quartiles; whiskers indicate 1.5 × interquartile range; points indicate outliers. B, peripheral blood; M, bone marrow. *Sample collected under treatment with ibrutinib.
Cellular respiration, BCR signaling and OXPHOS inhibition in RT cells
a, Oxygen consumption of intact CLL and RT cells of three patients at routine respiration (routine), oligomycin-inhibited leak respiration (uncoupled) and uncoupler-stimulated ETC. Each dot represents a technical replicate. The mean of the replicates is shown using a horizontal line (left). Summary of the routine respiration of CLL and RT cells of the three patients collapsed (right). b, Calcium kinetics of tumoral cells (CD19⁺, CD5⁺) upon stimulation with 4-hydroxytamoxifen (4-OHT) and anti-BCR (black arrow). Basal calcium was adjusted at 5 × 10⁹ Indo-1 ratio for 60 s before cell stimulation with F(ab′)2 anti-human IgM + H2O2 at 37 °C. Then, Ca²⁺ flux was recorded up to 500 s (left). Summary of the calcium release after BCR stimulation of CLL and RT cells. Average mean fluorescence after stimulation is represented (right). c, Cell proliferation after 72-h incubation with or without IACS-010759 (IACS) at 100 nM. Percentage of proliferating cells was determined by carboxyfluorescein succinimidyl ester (CFSE) cell tracer. Two technical replicates of each sample were performed (left). Summary of the proliferation for each CLL and RT cells with or without IACS treatment after 72 h. The normalized percentage of growth inhibition is indicated (right).
Article
  • Ferran NadeuFerran Nadeu
  • Romina RoyoRomina Royo
  • Ramon Massoni-BadosaRamon Massoni-Badosa
  • [...]
  • Elías CampoElías Campo
Richter transformation (RT) is a paradigmatic evolution of chronic lymphocytic leukemia (CLL) into a very aggressive large B cell lymphoma conferring a dismal prognosis. The mechanisms driving RT remain largely unknown. We characterized the whole genome, epigenome and transcriptome, combined with single-cell DNA/RNA-sequencing analyses and functional experiments, of 19 cases of CLL developing RT. Studying 54 longitudinal samples covering up to 19 years of disease course, we uncovered minute subclones carrying genomic, immunogenetic and transcriptomic features of RT cells already at CLL diagnosis, which were dormant for up to 19 years before transformation. We also identified new driver alterations, discovered a new mutational signature (SBS-RT), recognized an oxidative phosphorylation (OXPHOS)high–B cell receptor (BCR)low-signaling transcriptional axis in RT and showed that OXPHOS inhibition reduces the proliferation of RT cells. These findings demonstrate the early seeding of subclones driving advanced stages of cancer evolution and uncover potential therapeutic targets for RT. Single-cell genomic and transcriptomic analyses of longitudinal samples of patients with Richter syndrome reveal the presence and dynamics of clones driving transformation from chronic lymphocytic leukemia years before clinical manifestation
 
Patient flowchart
aAE was moderate arthralgia. bSubjects were excluded from the PP population because of either no week 8 LDL-C assessment (n = 1 each in the placebo and obicetrapib 5 mg groups) or because the week 8 LDL-C assessment occurred more than 5 days after the obicetrapib dose (n = 1 in the obicetrapib 10 mg group). AE, adverse event; ITT, intent to treat; PK, pharmacokinetic; PP, per protocol.
Median lipoprotein lipid concentrations
a–d, LDL-C concentrations measured by the Friedewald formula (a), Apo B (b), HDL-C (c) and Lp(a) (d) for the placebo (blue), obicetrapib 5 mg (green) and obicetrapib 10 mg (red) groups (n = 40 each), administered on a background of high-intensity statin treatment at baseline and after 4 and 8 weeks of treatment (only after 8 weeks of treatment for Lp(a)).
Article
  • Stephen J. NichollsStephen J. Nicholls
  • Marc DitmarschMarc Ditmarsch
  • John J. KasteleinJohn J. Kastelein
  • [...]
  • Michael H. DavidsonMichael H. Davidson
Global guidelines for the management of high-cardiovascular-risk patients include aggressive goals for low-density lipoprotein cholesterol (LDL-C). Statin therapy alone is often insufficient to reach goals and nonstatin options have limitations. Here, we tested the lipid-lowering effects of the cholesteryl ester transfer protein (CETP) inhibitor drug obicetrapib in a randomized, double-blind, placebo-controlled trial in dyslipidaemic patients (n = 120, median LDL-C 88 mg dl−1) with background high-intensity statin treatment (NCT04753606). Over the course of 8 weeks, treatment with 5 mg or 10 mg obicetrapib resulted in a significant decrease as compared with placebo in median LDL-C concentration (by up to 51%; P < 0.0001), the primary trial outcome. As compared with placebo, obicetrapib treatment also significantly (P < 0.0001) decreased apolipoprotein B (by up to 30%) and non-high-density lipoprotein cholesterol (non-HDL-C) concentration (by up to 44%), and significantly (P < 0.0001) increased HDL-C concentration (by up to 165%; the secondary trial outcomes) and had an acceptable safety profile. These results support the potential of obicetrapib to address an unmet medical need for high-cardiovascular-risk patients. In a phase 2 randomized clinical trial, an inhibitor of cholesteryl ester transfer protein (CETP), obicetrapib, lowered low-density lipoprotein cholesterol when administered in conjunction with high-intensity statins, paving the way for studies investigating the effects of obicetrapib on cardiovascular events.
 
Article
  • Karen O’LearyKaren O’Leary
CONSORT flow diagram of the TUXEDO-1 trial. BM, brain metastases.
Waterfall plot of responses in patients evaluable for response by RANO-BM criteria in the TUXEDO-1 trial. Blue bars illustrate the radiographic change of maximum brain metastasis size after start of trastuzumab deruxtecan therapy compared to the baseline measurement. Red dotted lines denote thresholds for response and progression by RANO-BM criteria.
Kaplan–Meier plot showing progression-free survival times (months) in the TUXEDO-1 trial.
Article
Trastuzumab deruxtecan is an antibody–drug conjugate with high extracranial activity in human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer. We conducted the prospective, open-label, single-arm, phase 2 TUXEDO-1 trial. We enrolled patients aged ≥18 years with HER2-positive breast cancer and newly diagnosed untreated brain metastases or brain metastases progressing after previous local therapy, previous exposure to trastuzumab and pertuzumab and no indication for immediate local therapy. Patients received trastuzumab deruxtecan intravenously at the standard dose of 5.4 mg per kg bodyweight once every 3 weeks. The primary endpoint was intracranial response rate measured according to the response assessment in neuro-oncology brain metastases criteria. A Simon two-stage design was used to compare a null hypothesis of <26% response rate against an alternative of 61%. Fifteen patients were enrolled in the intention-to-treat population of patients who received at least one dose of study drug. Two patients (13.3%) had a complete intracranial response, nine (60%) had a partial intracranial response and three (20%) had stable disease as the best intracranial response, with a best overall intracranial response rate of 73.3% (95% confidential interval 48.1–89.1%), thus meeting the predefined primary outcome. No new safety signals were observed and global quality-of-life and cognitive functioning were maintained over the treatment duration. In the TUXEDO-1 trial (NCT04752059, EudraCT 2020-000981-41), trastuzumab deruxtecan showed a high intracranial response rate in patients with active brain metastases from HER2-positive breast cancer and should be considered as a treatment option in this setting.
 
αAβ–Gas6 promotes selective phagocytosis of oAβ through TAM receptors
a, Schematic of human Gas6 fusion proteins. b, Immunoblotting showing that the expression of C-terminal FLAG modified fusion proteins in conditioned medium. The conditioned medium was collected 2 d after transfection in HEK293T cells (W and K refer to warfarin and Vitamin K treatment, respectively). c, FACS quantification of the relative number of HMC3 cells bound to oAβ- (left) or FITC- (right) conjugated fluorescent beads. d,e, Representative live HMC3 images (d) and quantitative bar graphs (e) after treatment with specific Gas6 fusion proteins (18 h). f, Quantification of phagocytosis of pHrodo and oAβ double-conjugated beads (5.7-μm size) by THP-1Axl (after 4-h incubation) in the presence of αAβ–Gas6 and Cytochalasin D (10 μM). g,h, Immunoprecipitation analysis for tyrosine phosphorylation of AXL in THP-1Axl. Target cells were starved with serum-reduced media for 24 h and incubated with Mo/Di/Tri Aβ or oAβ (250 nM) in presence of αAβ–Gas6 (0.2 μg ml⁻¹) for 10 min (g) and with oAβ (5 μM) in presence of αAβ–Gas6 (1 or 4 μg ml⁻¹) for 10 min (h). i, Quantification of the phagocytosis of oAβ-pHrodo by primary microglia (left) and astrocytes (right) (after 12-h incubation) in the presence of αAβ–Gas6 and functional blocking antibodies for TYRO3 (10 μg ml⁻¹), AXL (10 μg ml⁻¹), and MERTK (30 μg ml⁻¹). e,f,i, pHrodo Red signal was normalized by areas of HMC3 (e), THP-1Axl (f), primary microglia (i, left), and primary astrocytes (i, right). b–i, Representative data from n = 3 biological replicates. One-way ANOVA followed by Tukey’s multiple comparisons test. Error bars indicate s.e.m. DIC, differential interference contrast; IB, immunoblotting; IP, immunoprecipitation; NS, not significant.
Source data
αAβ–Gas6 mediates phagocytosis of oAβ without inducing pro-inflammatory responses
a, Representative dose–response curves showing αAβ–Gas6- (left) or aducanumab- (right) induced phagocytosis of oAβ-pHrodo by primary microglia after 12-h incubation. Half-maximum effective concentration (EC50) of αAβ–Gas6 and aducanumab: 9.0711 nM and 1.1227 nM, respectively. n = 4. b, Quantitative bar graphs showing the protein levels of secreted TNF in the media after incubating LPS (200 ng ml⁻¹) pre-treated microglia with oAβ (5 μM) in the presence of PBS, aducanumab (5 μg ml⁻¹) or αAβ–Gas6 (5 μg ml⁻¹) for 1 h. n = 3. c, Relative mRNA levels of Socs1 (left) and Socs3 (right) by RT–qPCR analysis in primary microglia after treatment of aducanumab (5 μg ml⁻¹) or αAβ–Gas6 (5 μg ml⁻¹) along with oAβ (5 μM) for 3 h. The fold change values were normalized to the untreated group. n = 4. d, Immunoblotting showing the phosphorylation of STAT1 in primary microglia after treatment of αAβ–Gas6 (5 μg ml⁻¹) or aducanumab (5 μg ml⁻¹). e,f, Representative quantitative graph showing the live uptake kinetics of oAβ-pHrodo after addition of αAβ–Gas6 (10 μg ml⁻¹) or aducanumab (10 μg ml⁻¹) to primary microglia (e) or astrocytes (f). n = 4. g,h, Quantitative bar graphs showing the mRNA levels of pro-inflammatory cytokines (Tnf, Il1a and Il1b) measured by RT–qPCR in primary microglia (g) or astrocytes (h). mRNA expression levels were normalized by the LPS-treated group (g) or the nontreated control group (h). Statistical differences were marked by comparing the oAβ-treated group and others. n = 4. i, Representative confocal z-stack images of neurons (MAP2, red) and fragmented axons (green) from the cortical tri-culture system. NT, nontreated. Scale bar, 30 μm. j, Quantification bar graphs of areas (left) and numbers (right) of neuronal fragmentation in NT and oAβ-, oAβ + aducanumab-, and oAβ + αAβ–Gas6-treated groups. n = 15, 15, 13, 15. n value represents the number of biological replicates (a–c, e–h) or independent experiments from three biological replicates (j). a,e,f, pHrodo Red signal was normalized by areas of primary microglia (a, e) and primary astrocytes (f). Two-sided unpaired Student’s t-test (c); one-way ANOVA followed by Tukey’s multiple comparisons test (b, e, f, g, h, j). Error bars indicate s.e.m. AU, arbitrary units; DIV, days in vitro; RT–qPCR, quantitative PCR with reverse transcription.
Source data
Direct delivery of αAβ–Gas6 protein enhances glial phagocytosis of Aβ plaques
a, Schematic illustration of cannula-mediated protein delivery into the 6-m-old 5xFAD lateral ventricles. b, Representative confocal z-stack images of Aβ plaques (Thioflavin-T, green, white arrows) in the dentate gyrus of PBS-, aducanumab-, and αAβ–Gas6-infused 5xFAD mice. Quantification bar graphs of the number (left) and area (right) of Thioflavin-T. Scale bar, 200 μm. n = 10, 11, 11 (b, left). n = 11, 11, 11 (b, right). c,d, Representative confocal z-stack images of microglia (c, IBA1, blue) and astrocytes (d, S100β, blue) co-stained with lysosomes (c, CD68; d, CathD, green) and Aβ plaques (no. 2454, red). Right panels are three-dimensional (3D) reconstructed enlarged images of yellow dotted boxes in left and middle panels, showing engulfed Aβ plaques (red, white arrows) in the lysosomes (green) inside glial cells (cobalt blue). Scale bars, 10 μm. e,f, Quantification bar graphs of the areas of engulfed Aβ plaques by microglia (e) and astrocytes (f) normalized by plaque area. n = 14, 19, 13 (e). n = 12, 10, 11 (f). g, Schematic illustration of CAA induction and intrathecal protein administration to the 9-m-old 5xFAD and APP/PS1 mice. h, Representative confocal z-stack images of CAA (Thioflavin-T, green, white arrows, top) and slide scanner images of microhemorrhage (Prussian blue, dark blue, white arrows, bottom) in CAA-induced 5xFAD (left) and APP/PS1 (right). White dashed lines indicate the leptomeningeal surface of cortex. Scale bars, 100 μm. i, Quantification bar graphs of the CAA area in the 5xFAD (left) and APP/PS1 (right). n = 12, 12, 12 (left). n = 12, 11, 12 (right). j, Quantification bar graphs of the microhemorrhage frequency in the 5xFAD (top) and APP/PS1 (bottom). n = 20, 20, 21 (top). n = 12, 11, 12 (bottom). One-way ANOVA followed by Tukey’s multiple comparisons test. i,j, Two-sided unpaired Student’s t-test. Mean ± s.e.m. For b–f, n value represents independent experiments from 3 (PBS and αAβ–Gas6) or 4 (aducanumab) mice. For h–j, n value represents independent experiments from 3 mice per group for APP/PS1 and 6 mice per group for 5xFAD.
Source data
LV-αAβ–Gas6 mediates Aβ clearance and behavior rescue in 5xFAD mice
a, Schematic illustration of LV injection into the 8-m-old 5xFAD hippocampal CA1. b, Representative confocal z-stack images of ZsGreen (green) and Aβ plaques (Congo Red, magenta) in the CA1 of LV-control-, LV-aducanumab-, and LV-αAβ–Gas6-injected 5xFAD mice. Quantification bar graphs of the number (left) and area (right) of Congo Red. Scale bars, 200 μm. n = 19, 20, 16. c,d, Representative confocal z-stack images of microglia (c, IBA1, blue) and astrocytes (d, S100β, blue) co-stained with lysosomes (c, CD68; d, CathD, green) and Aβ plaques (no. 2454, red). Right panels are 3D reconstructed enlarged images of yellow dotted boxes in left and middle panels showing engulfed Aβ plaques (red, white arrows) in the lysosomes (green) inside glial cells (cobalt blue). Scale bars, 10 μm. e,f, Quantification bar graphs of the areas of engulfed Aβ plaques by microglia (e) and astrocytes (f) normalized by Aβ plaque area. n = 20, 21, 21 (e). n = 10, 12, 10 (f). g,h, Representative single plane confocal images showing microglia (IBA1, blue), excitatory synapses (g, PSD95; h, vGLUT2, green), and lysosomes (CD68, red) (left). Right panels are 3D reconstructed enlarged images of cyan dotted boxes in left and middle panels, showing engulfed synapses (green, white arrows) in the lysosomes (red) inside microglia (cobalt blue). Scale bars, 5 μm. i,j, Quantification bar graphs of the areas of engulfed synapses by microglia normalized by synapse area (i, PSD95; j, vGLUT2) in LV-control-injected WT and LV-injected 5xFAD. n = 27, 25, 23, 22 (i). n = 18, 34, 38, 36 (j). k, Graphical illustration of NOL and NOR tests. l,m, Discrimination indexes of NOL (l) and NOR (m) tests for WT and LV-injected 5xFAD mice. n = 13, 10, 10, 10 (l). n = 13, 8, 10, 10 (m). One-way ANOVA followed by Tukey’s multiple comparisons test. e,j, Two-sided unpaired Student’s t-test. Mean ± s.e.m.; n value represents independent experiments from 3 to 5 mice per group (b, e, f, i, j). For l and m, n value represents mice number per group.
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LV-αAβ–Gas6 suppresses inflammatory gene expression in 5xFAD mice
a, UMAP plot showing total cell clusters and annotation of brain cells from 9-m-old 5xFAD hippocampus injected with LV-control, LV-aducanumab, and LV-αAβ–Gas6. b, UMAP clustering of microglia showing the normalized expression of Tnf, Il1b, Ccl3, and Ccl4 within defined clusters. c, Violin plots of Tnf and Il1b mRNA expression levels in the Stage1- and Stage2-DAM populations of LV-injected hippocampus. Gene expressions were compared with each other by using two-sided Wilcoxon rank-sum test. d,e, Scatter plots showing DEGs of LV-αAβ–Gas6 versus LV-aducanumab in Stage1- (d) and Stage2-DAM (e). DEGs: log2FC > 0.5 and adjusted P < 0.05. f, Dot plots showing the scaled expression levels of DEGs of LV-αAβ–Gas6 versus LV-aducanumab in the Stage1- (left) and Stage2-DAMs (right). Scaled gene set scores (average, over genes in the set, of log2[normalized UMI + 1]). g, Dot plots showing scaled expression levels of homeostatic, reactive astrocyte genes (left), chemokines, and cytokines (right) in the LV-injected hippocampus. f,g, Dot color, expression level; dot radius, proportion of cells expressing the gene. For a–g, we used n = 2 biological replicates for each group. DEG, differentially expressed genes; FC, fold change.
Article
Clearing amyloid-β (Aβ) through immunotherapy is one of the most promising therapeutic approaches to Alzheimer’s disease (AD). Although several monoclonal antibodies against Aβ have been shown to substantially reduce Aβ burden in patients with AD, their effects on improving cognitive function remain marginal. In addition, a significant portion of patients treated with Aβ-targeting antibodies experience brain edema and microhemorrhage associated with antibody-mediated Fc receptor activation in the brain. Here, we develop a phagocytosis inducer for Aβ consisting of a single-chain variable fragment of an Aβ-targeting monoclonal antibody fused with a truncated receptor binding domain of growth arrest-specific 6 (Gas6), a bridging molecule for the clearance of dead cells via TAM (TYRO3, AXL, and MERTK) receptors. This chimeric fusion protein (αAβ–Gas6) selectively eliminates Aβ plaques through TAM receptor-dependent phagocytosis without inducing NF-kB-mediated inflammatory responses or reactive gliosis. Furthermore, αAβ–Gas6 can induce synergistic clearance of Aβ by activating both microglial and astrocytic phagocytosis, resulting in better behavioral outcomes with substantially reduced synapse elimination and microhemorrhage in AD and cerebral amyloid angiopathy model mice compared with Aβ antibody treatment. Our results suggest that αAβ–Gas6 could be a novel immunotherapeutic agent for AD that overcomes the side effects of conventional antibody therapy.
 
Hematological data before and after transplantation
a–d, The cell counts of WBCs (a), lymphocytes (b), neutrophils (c) and platelets (d) in the peripheral blood of each patient over time, with blue indicating patient 1 and red patient 2. The dashed lines indicate the normal range for each value. e,f, The fluctuations in the immune cell fraction for each patient before and after transplantation are shown below with patient 1 in e and patient 2 in f.
Source data
Key laboratory values of clinical outcomes
a, The counts of RBCs over time for patient 1, who was β⁰/β⁰ (indicated in blue), and patient 2, who was β⁺/β⁺ (indicated in red). b, About 2 months after transplantation, consistent levels of Hb were observed, with blue indicating patient 1 and red patient 2. The dashed lines indicate the normal range for each value. c,d, Representation of Hb adducts (left y axis) and the changes in the percentages of F-cells (circulating red cells that express HbF) over time (right y axis) for patient 1 (c) and patient 2 (d). e,f, The progressive decrease in the ferritin level (left y axis) and change of transferrin level (right y axis) before and after transplantation are shown in e for patient 1 and in f for patient 2.
Source data
Gene-editing efficiency and outcome analysis
a, Frequencies of allelic editing in input and nucleated peripheral blood cells at various times after transplantation, with blue indicating patient 1 and red patient 2. b,c, Frequencies of allelic editing in cells of various types from peripheral blood samples obtained 6, 8, 9, 10, 11, 15 and 18 months after transplantation in b (for patient 1) and c (for patient 2). d,e, Percentage stacked histograms show the distribution of top 20 indel patterns in PBMCs from patient 1 (d) and patient 2 (e) over time. (They are shown as position: deletion (D) or insertion (I): base count and name; protospacer adjacent motif position is defined as 21–23.) f,g, The editing frequency of various types of cells in the bone marrow of patients 1 (f) and 2 (g) at Mo9 after transplantation. h,i, Relative loss of edited alleles repaired by MMEJ (−9 to −20 bp) and gain of edited alleles repaired by NHEJ (−8 to +6 bp) in transplanted cells over time (for patient 1 in h, patient 2 in i).
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Transcriptional impact of BCL11A enhancer editing in PBMCs from treated patients at single-cell resolution
a, The uniform Manifold Approximation and Projection (UMAP) plot representing 13 color-coded cell clusters identified in merged single-cell transcriptomes of PBMCs from two heathy donors, one patient sample before treatment and three patient samples at different time points after treatment. Cluster names were manually assigned. b, Stacked bar plots showing distribution of the identified clusters (a) across samples. c, Violin plots showing BCL11A expression (log(transformed)) for the B-cell or pDC clusters from edited and unedited groups, both showing no difference (B cells, Wilcoxon’s two-sided test, P = 0.51; pDCs, Wilcoxon’s two-sided test, P = 0.58). d, Heatmap depicting average expression of selected genes related to B-cell development and proliferation in the B-cell cluster. Expression values were normalized per gene with 0 reflecting the lowest expression and 2 the highest expression. e, Plot showing differential gene expression with fold-change (log2(FC)) between unedited (n = 3) and edited (n = 3) plotted versus −log10(FDR). Aggregation of single-cell transcriptome data to pseudo-bulk data for each respective sample was used for analysis. No differentially expressed genes (false discovery rate (FDR) < 0.5) were identified. f, Violin plots showing IGHD and IGHM expression (log(transformed)) for the B-cell cluster from the edited and unedited groups. Both show no significant difference (IGHD, Wilcoxon’s two-sided test, P = 0.11; IGHM, Wilcoxon’s two-sided test, P = 0.016). g, At Mo9 after transplantation, the relative expression of BCL11A gene in B cells (CD19⁺) and erythroid cells (CD235a⁺) in the bone marrow of both patients.
Source data
Article
Gene editing to disrupt the GATA1-binding site at the +58 BCL11A erythroid enhancer could induce γ-globin expression, which is a promising therapeutic strategy to alleviate β-hemoglobinopathy caused by HBB gene mutation. In the present study, we report the preliminary results of an ongoing phase 1/2 trial (NCT04211480) evaluating safety and efficacy of gene editing therapy in children with blood transfusion-dependent β-thalassemia (TDT). We transplanted BCL11A enhancer-edited, autologous, hematopoietic stem and progenitor cells into two children, one carrying the β0/β0 genotype, classified as the most severe type of TDT. Primary endpoints included engraftment, overall survival and incidence of adverse events (AEs). Both patients were clinically well with multilineage engraftment, and all AEs to date were considered unrelated to gene editing and resolved after treatment. Secondary endpoints included achieving transfusion independence, editing rate in bone marrow cells and change in hemoglobin (Hb) concentration. Both patients achieved transfusion independence for >18 months after treatment, and their Hb increased from 8.2 and 10.8 g dl−1 at screening to 15.0 and 14.0 g dl−1 at the last visit, respectively, with 85.46% and 89.48% editing persistence in bone marrow cells. Exploratory analysis of single-cell transcriptome and indel patterns in edited peripheral blood mononuclear cells showed no notable side effects of the therapy. Preliminary results from a phase 1/2 trial with 18-month follow-up show that transplantation of CRISPR–Cas9 BCL11A-edited autologous hematopoietic cells in two children with β-thalassemia was safe and achieved transfusion independence.
 
Article
  • Irith De BaetselierIrith De Baetselier
  • Christophe Van DijckChristophe Van Dijck
  • Chris KenyonChris Kenyon
  • [...]
  • Bea VuylstekeBea Vuylsteke
The magnitude of the 2022 multi-country monkeypox virus outbreak has surpassed any preceding outbreak. It is unclear whether asymptomatic or otherwise undiagnosed infections are fuelling this epidemic. We aimed to assess whether undiagnosed infections occurred among men attending a Belgian sexual health clinic in May 2022. We retrospectively screened 224 samples collected for gonorrhoea and chlamydia testing using a monkeypox virus (MPXV) PCR assay, and identified MPXV DNA-positive samples from four men. At the time of sampling, one man had a painful rash, and three men had reported no symptoms. Upon clinical examination 21 to 37 days later, these three men were free of clinical signs and they reported not having experienced any symptoms. Serology confirmed MPXV exposure in all three men, and MPXV was cultured from two cases. These findings show that certain cases of monkeypox remain undiagnosed, and suggest that testing and quarantining of individuals reporting symptoms may not suffice to contain the outbreak. Findings of unrecognized or asymptomatic monkeypox (MPXV) virus infections with replication-competent virus in humans suggest a lack of recognized, clinical symptoms could play a role in virus transmission and the magnitude of the 2022 MPXV outbreak.
 
Article
Incorporating genetic factors into risk models improves the prediction of severe obesity for survivors of childhood cancer, which could promote early interventions and better long-term care.
 
Article
Pigs offer a potentially plentiful supply of organs for humans, but widespread xenotransplantation will require a collaborative and iterative approach to research, as well as involvement of transplant patients and the public.
 
Article
SIGNAL is a multicenter, randomized, double-blind, placebo-controlled phase 2 study (no. NCT02481674) established to evaluate pepinemab, a semaphorin 4D (SEMA4D)-blocking antibody, for treatment of Huntington’s disease (HD). The trial enrolled a total of 265 HD gene expansion carriers with either early manifest (EM, n = 179) or late prodromal (LP, n = 86) HD, randomized (1:1) to receive 18 monthly infusions of pepinemab ( n = 91 EM, 41 LP) or placebo ( n = 88 EM, 45 LP). Pepinemab was generally well tolerated, with a relatively low frequency of serious treatment-emergent adverse events of 5% with pepinemab compared to 9% with placebo, including both EM and LP participants. Coprimary efficacy outcome measures consisted of assessments within the EM cohort of (1) a two-item HD cognitive assessment family comprising one-touch stockings of Cambridge (OTS) and paced tapping (PTAP) and (2) clinical global impression of change (CGIC). The differences between pepinemab and placebo in mean change (95% confidence interval) from baseline at month 17 for OTS were −1.98 (−4.00, 0.05) (one-sided P = 0.028), and for PTAP 1.43 (−0.37, 3.23) (one-sided P = 0.06). Similarly, because a significant treatment effect was not observed for CGIC, the coprimary endpoint, the study did not meet its prespecified primary outcomes. Nevertheless, a number of other positive outcomes and post hoc subgroup analyses—including additional cognitive measures and volumetric magnetic resonance imaging and fluorodeoxyglucose–positron-emission tomography imaging assessments—provide rationale and direction for the design of a phase 3 study and encourage the continued development of pepinemab in patients diagnosed with EM HD.
 
Article
Greater emphasis on reproducibility and reusability will advance computational pathology quickly and sustainably, ultimately optimizing clinical workflows and benefiting patient health.
 
CONSORT diagram and molecular screening of the CHRONOS trial. Results of ctDNA ddPCR analysis and distribution of RAS, BRAF and EGFR ECD mutations in patients screened within the CHRONOS trial. Abbreviations: ctDNA, circulating tumor DNA; ddPCR, droplet digital PCR; ECD, ectodomain.
Waterfall plot depicts best responses to panitumumab rechallenge within the CHRONOS trial according to RECIST 1.1 (a). Spider plot displays best responses according to RECIST 1.1 and duration of response to panitumumab rechallenge (b). Magenta, progressive disease; gray, stable disease; blue, partial response; black, unconfirmed partial response; * progressive disease exclusively due to the onset of a new metastatic lesion.
Tree graph describing ctDNA RAS/BRAF/EGFR status of patients screened for CHRONOS enrollment according to the time interval between the end of the last anti-EGFR course and the date of the CHRONOS ctDNA screening. Top: patients with WT sample; color-coded objective response to rechallenge with panitumumab on a time scale displaying PFS. Bottom: patients with mutated sample and mutations retrieved leading to CHRONOS screening failure. αEGFR, anti-EGFR. Abbreviations: MT, mutant; WT, wild-type.
Alterations identified by NGS on tissue samples collected before CHRONOS enrollment (upper panel), on ctDNA at baseline to panitumumab rechallenge (middle panel) and on ctDNA at progression to panitumumab rechallenge (lower panel). As per inclusion criteria, all patients enrolled achieved complete or partial response to prior anti-EGFR antibodies either as monotherapy or in combination with cytotoxic agents. Mutations in the genes (NRAS/KRAS/BRAF/EGFR) of the molecular screening panel and KRAS/EGFR amplifications are highlighted in yellow.
Article
Anti-epidermal growth factor receptor (EGFR) monoclonal antibodies are approved for the treatment of RAS wild-type (WT) metastatic colorectal cancer (mCRC), but the emergence of resistance mutations restricts their efficacy. We previously showed that RAS , BRAF and EGFR mutant alleles, which appear in circulating tumor DNA (ctDNA) during EGFR blockade, decline upon therapy withdrawal. We hypothesized that monitoring resistance mutations in blood could rationally guide subsequent therapy with anti-EGFR antibodies. We report here the results of CHRONOS, an open-label, single-arm phase 2 clinical trial exploiting blood-based identification of RAS / BRAF / EGFR mutations levels to tailor a chemotherapy-free anti-EGFR rechallenge with panitumumab (ClinicalTrials.gov: NCT03227926 ; EudraCT 2016-002597-12). The primary endpoint was objective response rate. Secondary endpoints were progression-free survival, overall survival, safety and tolerability of this strategy. In CHRONOS, patients with tissue- RAS WT tumors after a previous treatment with anti-EGFR-based regimens underwent an interventional ctDNA-based screening. Of 52 patients, 16 (31%) carried at least one mutation conferring resistance to anti-EGFR therapy and were excluded. The primary endpoint of the trial was met; and, of 27 enrolled patients, eight (30%) achieved partial response and 17 (63%) disease control, including two unconfirmed responses. These clinical results favorably compare with standard third-line treatments and show that interventional liquid biopsies can be effectively and safely exploited in a timely manner to guide anti-EGFR rechallenge therapy with panitumumab in patients with mCRC. Further larger and randomized trials are warranted to formally compare panitumumab rechallenge with standard-of-care therapies in this patient setting.
 
Article
We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD. To overcome limitations of previous genome-wide association studies of coronary artery disease, this study incorporates a cohort of individuals containing large fractions of Black and Hispanic individuals to provide a wider view of the genetic landscape of this disease.
 
BMI and its categories in survivors of childhood cancer and community controls
Cumulative distributions of BMI and age/sex-adjusted prevalence and 95% CIs (shown as texts) of BMI categories among survivors of childhood cancer and community controls in the SJLIFE cohort, stratified by ancestry.
Genetic risk prediction of obesity and severe obesity in survivors of childhood cancer
AUC estimates of prediction models for obesity or higher and severe obesity developed among survivors of European ancestry from the SJLIFE cohort and its validation among survivors of European ancestry from the CCSS. The ‘clinical+lifestyle’ prediction models included sex; irradiation to brain, chest, pelvis, abdomen and hypothalamus–pituitary axis; exposure to glucocorticoids; smoking; and physical activity. To these models, a genetic predictor (GRSrare) based on 14 rare/low-frequency variants strongly implicated in BMI in the general population was added, followed by another well-established genetic predictor (GRScommon) based on ~2.1 million common variants genome-wide.
Article
Adult survivors of childhood cancer have high rates of obesity, which, in combination with the cardiotoxic effects of specific cancer therapies, places them at high risk for cardiovascular morbidity. Here we show the contribution of genetic risk scores (GRSs) to increase prediction of those survivors of childhood cancer who are at risk for severe obesity (body mass index ≥40 kg m−2) as an adult. Among 2,548 individuals of European ancestry from the St. Jude Lifetime Cohort Study who were 5-year survivors of childhood cancer, the GRS was found to be associated with 53-fold-higher odds of severe obesity. Addition of GRSs to risk prediction models based on cancer treatment exposures and lifestyle factors significantly improved model prediction (area under the curve increased from 0.68 to 0.75, resulting in the identification of 4.3-times more high-risk survivors), which was independently validated in 6,064 individuals from the Childhood Cancer Survivor Study. Genetic predictors improve identification of patients who could benefit from heightened surveillance and interventions to mitigate the risk of severe obesity and associated cardio-metabolic complications. A report from large cohorts of adult survivors of childhood cancer demonstrates that genetic risk scores improve the risk prediction of developing severe obesity, providing opportunities for surveillance and mitigation interventions
 
Symptoms associated with SARS-CoV-2 ≥ 12 weeks after infection.
Article
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is associated with a range of persistent symptoms impacting everyday functioning, known as post-COVID-19 condition or long COVID. We undertook a retrospective matched cohort study using a UK-based primary care database, Clinical Practice Research Datalink Aurum, to determine symptoms that are associated with confirmed SARS-CoV-2 infection beyond 12 weeks in non-hospitalized adults and the risk factors associated with developing persistent symptoms. We selected 486,149 adults with confirmed SARS-CoV-2 infection and 1,944,580 propensity score-matched adults with no recorded evidence of SARS-CoV-2 infection. Outcomes included 115 individual symptoms, as well as long COVID, defined as a composite outcome of 33 symptoms by the World Health Organization clinical case definition. Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) for the outcomes. A total of 62 symptoms were significantly associated with SARS-CoV-2 infection after 12 weeks. The largest aHRs were for anosmia (aHR 6.49, 95% CI 5.02–8.39), hair loss (3.99, 3.63–4.39), sneezing (2.77, 1.40–5.50), ejaculation difficulty (2.63, 1.61–4.28) and reduced libido (2.36, 1.61–3.47). Among the cohort of patients infected with SARS-CoV-2, risk factors for long COVID included female sex, belonging to an ethnic minority, socioeconomic deprivation, smoking, obesity and a wide range of comorbidities. The risk of developing long COVID was also found to be increased along a gradient of decreasing age. SARS-CoV-2 infection is associated with a plethora of symptoms that are associated with a range of sociodemographic and clinical risk factors. A retrospective analysis of primary care records in the United Kingdom reveals individual symptoms associated with SARS-CoV-2 infections, which persisted for 12 weeks or more after infection, as well as risk factors associated with developing long COVID.
 
Kaplan-Meier curves after G47Δ initiation
a–c, Kaplan–Meier curves for OS after G47∆ initiation (a), PFS after G47∆ initiation (b) and OS based on IDH1 status after G47Δ initiation (c). The data were analyzed and Kaplan–Meier curves created on 1 March 2022.
Source data
Representative case (patient no. 1) treated with G47Δ
a, MRI images at indicated observation time points. Characteristic MRI changes were observed at every G47Δ administration, that is, a clearing of contrast-enhancement at the injection site and an enlargement of the entire target lesion. G47∆ was injected to different coordinates from previous injections, so the area of contrast-enhancement clearing increased as the doses increased, leading to a large hollow within the target lesion with an increase in diameter after six G47∆ doses. The MRI changes ceased after the last G47∆ injection and the target lesion stayed stable until 4 months after G47∆ therapy, when the tumor showed a regrowth. The regrown tumor was resected at 6 months but further regrew at 9 months, and the patient died of exacerbation of the disease at 16.2 months after G47∆ initiation. b, Planning MRI using StealthStation Surgical Navigation System at the 6th dose, displaying administration routes from the 2nd to 6th dose (10 injections) overlaid in the same image. c, Histology of biopsy specimens. Biopsies were performed before indicated injections and were obtained from coordinates different from previous G47∆ injections. CD4⁺ and CD8⁺ lymphocytes infiltrating within the tumor increased abundantly in number as G47∆ injections were repeated. In contrast, the number of tumor-infiltrating Foxp3⁺ cells remained low throughout repeated G47∆ injections. Representative of four biopsy specimens. d, Histology of resected tumor at regrowth. The numbers of tumor-infiltrating CD4⁺ and CD8⁺ lymphocytes remained high in the regrown tumor resected 6 months after the last G47∆ administration. A higher number of Foxp3⁺ cells are observed in the tumor at regrowth than in tumors during G47∆ treatment. Representative of three tissue samples. HE, haematoxylin and eosin; m, month(s).
Representative case (patient no. 10) showing a long-term efficacy via antitumor immunity
a, MRI images at indicated observation time points. G47∆ was injected into the target lesion (green arrows), causing the characteristic appearance of contrast-enhancement clearing at the injection site and an enlargement of the entire target lesion. After four doses, a new lesion (yellow arrow) appeared in the left basal ganglia remote from the target lesion, so G47∆ therapy was terminated. However, at the first follow-up 1 month after the last G47∆ administration, the new lesion disappeared (orange arrow at 1 month). Eventually, in the observations that followed, the target lesion decreased in size (orange arrow at 6 months). Remote new lesions further appeared at 24 months and the patient died of exacerbation of the disease at 38.9 months after G47∆ initiation. b, Histology of biopsy specimens. Biopsies were performed before indicated injections and were obtained from coordinates different from previous G47∆ injections. Similar to patient no. 1, CD4⁺ and CD8⁺ lymphocytes infiltrating within the tumor increased abundantly in number as G47∆ injections were repeated, whereas the number of tumor-infiltrating Foxp3⁺ cells remained low throughout repeated G47∆ injections.
Article
This investigator-initiated, phase 2, single-arm trial primarily assessed the efficacy of G47∆, a triple-mutated, third-generation oncolytic herpes simplex virus type 1, in 19 adult patients with residual or recurrent, supratentorial glioblastoma after radiation therapy and temozolomide (UMIN-CTR Clinical Trial Registry UMIN000015995). G47Δ was administered intratumorally and repeatedly for up to six doses. The primary endpoint of 1-yr survival rate after G47∆ initiation was 84.2% (95% confidence interval, 60.4–96.6; 16 of 19). The prespecified endpoint was met and the trial was terminated early. Regarding secondary endpoints, the median overall survival was 20.2 (16.8–23.6) months after G47∆ initiation and 28.8 (20.1–37.5) months from the initial surgery. The most common G47∆-related adverse event was fever (17 of 19) followed by vomiting, nausea, lymphocytopenia and leukopenia. On magnetic resonance imaging, enlargement of and contrast-enhancement clearing within the target lesion repeatedly occurred after each G47∆ administration, which was characteristic to this therapy. Thus, the best overall response in 2 yr was partial response in one patient and stable disease in 18 patients. Biopsies revealed increasing numbers of tumor-infiltrating CD4⁺/CD8⁺ lymphocytes and persistent low numbers of Foxp3⁺ cells. This study showed a survival benefit and good safety profile, which led to the approval of G47∆ as the first oncolytic virus product in Japan.
 
Article
A real-time early warning system for sepsis detection shows promising adoption by healthcare providers and important improvements in patient outcomes.
 
Evolution of cardiovascular health status in a cohort of at-risk adults, across three blood pressure intervention scenarios
The probability of remaining free of hypertension, CVD or all-cause death among an example cohort of individuals aged 35–39 years in 2020 (global population, both sexes) as they age from 35–39 years in 2020 to 65–69 years in 2050.
Demographic decomposition of the change in new CVD cases in three blood pressure intervention scenarios between 2020 and 2050, by country income
The three factors that determine the change in the number of new CVD cases (y axis) are population aging, population growth and changes in age-specific CVD incidence rates. The former two are often referred to as demographic drivers; the latter is often referred to as epidemiological change. The net effect of these three factors on changes in CVD incidence is represented by the black points. LMIC, lower-middle-income countries; UMIC, upper-middle-income countries.
Long-term trends in CVD-specific 50q30 from 2010 to 2050 in three blood pressure intervention scenarios, by country income
Projections of population size and structure beyond 2019 factor in the demographic effects of excess mortality from the COVID-19 pandemic, but this does not considerably change mortality probabilities or long-term age-specific CVD death rates. LMIC, lower-middle-income countries; UMIC, upper-middle-income countries.
Year by which an 80-80-80 target would be achieved in each country
The three panels present results for the three blood pressure intervention scenarios outlined in the article.
Projected worldwide health consequences of blood pressure intervention scenarios
Article
As the leading cause of death worldwide, cardiovascular diseases (CVDs) present major challenges for health systems. In this study, we analyzed the effects of better population blood pressure control in the context of a proposed 80-80-80 target: 80% of individuals with hypertension are screened and aware of their diagnosis; 80% of those who are aware are prescribed treatment; and 80% of those on treatment have achieved guideline-specified blood pressure targets. We developed a population CVD model using country-level evidence on CVD rates, blood pressure levels and hypertension intervention coverage. Under realistic implementation conditions, most countries could achieve 80-80-80 targets by 2040, reducing all-cause mortality by 4–7% (76–130 million deaths averted over 2022–2050) and slowing the rise in CVD expected from population growth and aging (110–200 million cases averted). Although populous middle-income countries would account for most of the reduced CVD cases and deaths, low-income countries would experience the largest reductions in disease rates.
 
Article
Cholera is endemic in 47 countries, but deaths from this disease can be eliminated with a package of low-cost measures implemented by community healthcare workers.
 
Article
Infrequently dosed, longer-acting antiretroviral agents are making adherence to medication easier, leading to better outcomes for those living with HIV or at risk of infection.
 
Article
A study evaluating serial injections of oncolytic virus therapy shows promising outcomes in patients with glioblastoma, and opens the door to longitudinal study designs with the potential to yield rich molecular insights.
 
Article
The theory of syndemics has received increasing attention in clinical medicine since the onset of the COVID-19 pandemic, due to the synergistic interactions of the disease with pre-existing political, structural, social and health conditions. In simple terms, syndemics are synergistically interacting epidemics that occur in a particular context with shared drivers. When policymakers ask why some communities have higher death rates from COVID-19 compared with other communities, those working from a syndemics framework argue that multiple factors synergistically work in tandem, and populations with the highest morbidity and mortality experience the greatest impact of these interactions. In this Perspective, we use specific case examples to illustrate these concepts. We discuss the emergence of syndemics, how epidemics interact, and what scientists, clinicians and policymakers can do with this information. This Perspective delivers an introduction to syndemic thinking, and provides insights into how epidemics interact and what scientists, clinicians and policymakers can do with this information.
 
Waterfall diagram for the primary analysis cohort
Waterfall diagram describing the primary analysis and high-risk cohorts. A total of 590,736 unique adult patient encounters occurred during the study period. Of these, 6,877 patient encounters were included in our primary analysis, and 2,365 patient encounters were included in our analysis of high-risk patients.
Distribution of the time from which the TREWS alert was given to the time confirmation was entered for the target population
Each bar has a width of 1 h, and the bar height represents the number of subjects who had their alert confirmed in that 1-h time bin. The dashed line is placed at 3 h, such that bars to the left and right of the line correspond to subjects in the study and comparison arms, respectively. Note that 1,840 (27%) patients in the target population either did not have an evaluation entered or had their alert dismissed by a provider and thus do not appear in this plot.
Article
Early recognition and treatment of sepsis are linked to improved patient outcomes. Machine learning-based early warning systems may reduce the time to recognition, but few systems have undergone clinical evaluation. In this prospective, multi-site cohort study, we examined the association between patient outcomes and provider interaction with a deployed sepsis alert system called the Targeted Real-time Early Warning System (TREWS). During the study, 590,736 patients were monitored by TREWS across five hospitals. We focused our analysis on 6,877 patients with sepsis who were identified by the alert before initiation of antibiotic therapy. Adjusting for patient presentation and severity, patients in this group whose alert was confirmed by a provider within 3 h of the alert had a reduced in-hospital mortality rate (3.3%, confidence interval (CI) 1.7, 5.1%, adjusted absolute reduction, and 18.7%, CI 9.4, 27.0%, adjusted relative reduction), organ failure and length of stay compared with patients whose alert was not confirmed by a provider within 3 h. Improvements in mortality rate (4.5%, CI 0.8, 8.3%, adjusted absolute reduction) and organ failure were larger among those patients who were additionally flagged as high risk. Our findings indicate that early warning systems have the potential to identify sepsis patients early and improve patient outcomes and that sepsis patients who would benefit the most from early treatment can be identified and prioritized at the time of the alert Prospective evaluation of a machine learning-based early warning system for sepsis, deployed at five hospitals, showed that interaction of health-care providers with the system was associated with better patient outcomes, including reduced in-hospital mortality.
 
Included study population by study question
The waterfall diagram shows the included population for each study question. Study question 1 included 469,419 screened patients. This included all patients presenting to the ED or admitted to an observation or inpatient unit. Study questions 2 and 3.1 included 3,775 patients with sepsis who received an alert and who had no antibiotic orders before the alert, but who received antibiotics within 24 h after the alert. Study question 3.2 included the 2,463 of these patients who had an evaluation of their alert entered by a provider within 3 h of the alert and who also received antibiotic treatment over the course of 4 d or more.
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Machine learning-based clinical decision support tools for sepsis create opportunities to identify at-risk patients and initiate treatments at early time points, which is critical for improving sepsis outcomes. In view of the increasing use of such systems, better understanding of how they are adopted and used by healthcare providers is needed. Here, we analyzed provider interactions with a sepsis early detection tool (Targeted Real-time Early Warning System), which was deployed at five hospitals over a 2-year period. Among 9,805 retrospectively identified sepsis cases, the early detection tool achieved high sensitivity (82% of sepsis cases were identified) and a high rate of adoption: 89% of all alerts by the system were evaluated by a physician or advanced practice provider and 38% of evaluated alerts were confirmed by a provider. Adjusting for patient presentation and severity, patients with sepsis whose alert was confirmed by a provider within 3 h had a 1.85-h (95% CI 1.66–2.00) reduction in median time to first antibiotic order compared to patients with sepsis whose alert was either dismissed, confirmed more than 3 h after the alert or never addressed in the system. Finally, we found that emergency department providers and providers who had previous interactions with an alert were more likely to interact with alerts, as well as to confirm alerts on retrospectively identified patients with sepsis. Beyond efforts to improve the performance of early warning systems, efforts to improve adoption are essential to their clinical impact and should focus on understanding providers’ knowledge of, experience with and attitudes toward such systems. Prospective evaluation of a machine learning-based early warning system for sepsis, deployed at five hospitals, showed that healthcare providers interacted with the system at a high rate and that this interaction was associated with faster antibiotic ordering.
 
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