W. Ian Lipkin’s research while affiliated with Columbia University and other places

Dengue fever, a vector-borne disease caused by four serotypes of dengue virus (DENV), ranges from asymptomatic to severe illness, including hemorrhagic fever and shock syndrome. A 2023 outbreak (August 2023–May 2024) in Mali affected six districts in Bamako, causing 1,422 confirmed cases with a 2.7% fatality rate. In this study, viral sequencing provided insights into the molecular epidemiology and transmission dynamics of this outbreak. From September to October 2023, 23 of 42 suspected cases detected through national dengue surveillance activities were tested using the pan-vertebrate virus metagenomics method (virome capture sequencing platform for vertebrate viruses [VirCapSeq-VERT]). Sequencing data were analyzed using the Rapid Identification of Microbes pipeline, and Bayesian phylogenetic inference with Monte Carlo methods was used to assess viral genomic evolution. Among 23 patients, 61% were male, and the median age was 37 years (range: 20–74). The most common symptoms were fever (93.1%), headache (56.5%), and asthenia (47.8%). The largest proportion experienced dengue with warning signs (65.2%), followed by dengue without warning signs (30.4%) and severe dengue (4.4%). The successful sequencing of 19 samples revealed dengue virus serotype 3 (DENV-3; genotype III) in 15 (65.21%) samples and dengue virus serotype 1 (DENV-1; genotype III) in 4 (17.39%) samples. The DENV-1 sequences were analogous to West African sequences, and the DENV-3 were clustered with West African, Asian, and Caribbean sequences. In this study of DENV in Mali, we offer insights into the molecular epidemiology of the virus and underscore the benefits of the genomic surveillance of arboviruses in West Africa.

Scoring systems for organ dysfunction (e.g., the quick Sepsis-related Organ Failure Assessment [qSOFA], Modified Early Warning Score [MEWS], and Universal Vital Assessment [UVA]) are proposed as clinical criteria for sepsis. The content validity of these scoring systems is poorly understood in sub-Saharan Africa, where the global sepsis burden is concentrated. In a prospective cohort of 288 adults hospitalized with suspected sepsis in Uganda, we show that qSOFA, MEWS, and UVA scores were significantly associated with soluble mediators of innate and adaptive immune activation, endothelial dysfunction, and fibrinolysis. Results were consistent after adjustment for demographics, illness duration, and HIV or malaria coinfection. In resource-limited settings in sub-Saharan Africa, organ dysfunction scores may stratify patients at highest risk of poor outcomes and those with more dysregulated host responses. Further studies are needed to better define these relationships, including the temporal dynamics of dysregulated host responses and organ dysfunction in sepsis.

Objectives Globally, the burden of sepsis is highest in malaria endemic areas of sub-Saharan Africa. The influence of malaria on biological heterogeneity inherent to sepsis in this setting is poorly understood. We sought to determine shared and distinct features of the host response in malarial and non-malarial sepsis in sub-Saharan Africa. Design and Setting Analysis of Olink proteomic data from prospective observational cohort studies of sepsis conducted at public hospitals in Uganda (discovery cohort [Entebbe, urban], n = 238; validation cohort [Tororo, rural], n = 253). Patients Adults (age ≥ 18 yr) hospitalized with sepsis. Interventions None. Measurements and Main Results The frequency of malaria-associated (malarial) sepsis was 20% in the discovery cohort and 28% in the validation cohort. In both cohorts, a shared host response was predominant, with less than or equal to 8% of proteins differentially expressed (Benjamini-Hochberg-adjusted p ≤ 0.05) between malarial and non-malarial sepsis, after adjustment for demographic variables and HIV and tuberculosis coinfection. In both cohorts, malarial sepsis was associated with increased expression of immunosuppressive proteins (interleukin-10, leukocyte immunoglobulin-like receptor B1, killer cell immunoglobulin-like receptor 3DL1), including those associated with Tcell exhaustion and apoptosis (lymphocyte activation gene 3, T cell immunoglobulin and mucin domain containing 4). A classifier model including these immunosuppressive proteins showed reasonable discrimination (area under the receiver operating characteristic curves, 0.73 [95% CI, 0.65–0.81] and 0.72 [0.65–0.79]) and calibration (Brier scores 0.14 and 0.18) for stratification of malarial sepsis in the discovery and validation cohorts, respectively. Conclusions Host responses are largely conserved in malarial and non-malarial sepsis but may be distinguished by a signature of relative immunosuppression in the former. Further investigations are needed to differentiate mechanisms of malarial and non-malarial sepsis, with the goal of informing pathogen-stratified and pathogen-agnostic treatment strategies.

The generalisability of critical illness molecular phenotypes to low- and middle-income countries (LMICs) is unknown. We show that molecular phenotypes derived in high-income countries (hyperinflammatory and hypoinflammatory, reactive and uninflamed) stratify sepsis patients in Uganda by physiological severity, mortality risk and dysregulation of key pathobiological domains. A classifier model including data available at the LMIC bedside modestly discriminated phenotype assignment (area under the receiver operating characteristic curve (AUROC) 0.80, 95% CI 0.71 to 0.90 for hyperinflammatory vs hypoinflammatory; AUROC 0.74, 95% CI 0.65 to 0.83 for reactive vs uninflamed). Our findings highlight the potential for a globally relevant, clinicomolecular classification of critical illness and may support the inclusion of diverse populations in phenotype-targeted critical care trials. Improved laboratory capacity and access to rapid biomarker assays are likely necessary to optimise phenotype stratification in LMIC settings.

Unexplained fever poses significant diagnostic challenges in resource-limited settings like Bamako, Mali, where overlapping endemic diseases include malaria, HIV/AIDS, yellow fever, typhoid, and others. This study aimed to elucidate the infectious etiologies of acute febrile illnesses in this context. Acute febrile patients of any age were enrolled after informed consent or assent. Baseline clinical and demographic data were collected, and samples were analyzed by using rapid diagnostic tests, reverse transcriptase polymerase chain reaction, ELISA, and virus-targeted metagenomic sequencing (virome capture sequencing platform for vertebrate viruses [VirCapSeq-VERT]). Among 108 enrolled subjects, most were male (51.9%) and under 15 years old (56.5%). Measles virus was identified in 39.8% of cases, primarily among children. Other findings included Plasmodium spp. (12%), Salmonella spp. (13%), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; 8.7%). The virome capture sequencing platform for vertebrate viruses was used for 101 subjects, corroborating many routine test results and identifying additional cases of measles virus (1), SARS-CoV-2 (5), and numerous other agents. Notably, nearly all subjects showed evidence of herpesviruses (90%) and anelloviruses (98%). Hemorrhagic fever viruses were not observed. With the inclusion of VirCapSeq-VERT, identifiable pathogens were found in 79.6% of cases, leaving 20.4% without a clear etiology. The identification of more than one concurrent pathogen was common (41.5%). Integrating metagenomic sequencing with routine laboratory diagnostic testing enhances the detection of pathogens in acute febrile illnesses, highlighting its potential value in identifying infectious etiologies in resource-limited settings.

BACKGROUND Maternal immune-mediated conditions during pregnancy have been linked with increased risk of attention-deficit/hyperactivity disorder (ADHD) in offspring. However, we do not know the extent to which these associations are influenced by shared genetic predispositions, as opposed to maternal inflammatory/immune responses during pregnancy. This study contributes by using paternal immune-mediated conditions as a negative control to explore these underlying factors, as we investigate associations between maternal immune-mediated conditions during pregnancy and offspring ADHD. METHODS Prospective data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) was linked with the Medical Birth Registry of Norway (MBRN) and the Norwegian Patient Registry (NPR) to assess associations between prenatal exposure to maternal immune-mediated conditions and offspring ADHD risk up to age 18. Nationwide recruitment from 1999 to 2008 resulted in 104,270 eligible mother-child pairs. Among these, 21,340 children were exposed to maternal allergic conditions (asthma, allergies, atopic conditions) and 7,478 to other immune conditions (autoimmune, inflammatory). Paternal self-reported immune conditions served as negative controls for genetic confounding. Data was mostly collected through MoBa, with additional maternal condition cases sourced from MBRN, and children’s ADHD diagnoses obtained from NPR. Cox proportional hazard models estimated Hazard ratios for ADHD diagnoses. RESULTS Both overall categories were associated with increased offspring ADHD risk (allergic conditions HR 1.23 95% CI, 1.14–1.34; other immune conditions HR 1.36 95% CI, 1.21–1.53). Specifically, we found associations for maternal asthma (HR 1.47 95% CI, 1.30–1.67); allergies (HR 1.20 95% CI, 1.10–1.31); rheumatologic/musculoskeletal conditions (HR 1.64 95% CI, 1.28–2.10), Crohn’s disease/ulcerative colitis (adjusted HR 1.95 95% CI, 1.23–3.09), and endocrine conditions (HR 1.42 95% CI, 1.15–1.77), specifically, type 1 diabetes (adjusted HR 2.50 95% CI, 1.66–3.75). Although some paternal immune-mediated conditions (psoriasis, ulcerative colitis, Crohn’s disease) showed similar trends of increased ADHD risk in offspring, only paternal asthma was significantly associated (adjusted HR 1.26 95% CI, 1.10–1.45). CONCLUSIONS Several maternal immune-mediated conditions were associated with increased ADHD risk in offspring. Observations of higher, more consistent estimates of ADHD risk in offspring for most maternal immune-mediated conditions versus paternal ones indicate that unmeasured genetic confounding does not fully explain these associations. These results suggest direct effects on fetal development through events at the maternal-fetal interface which may alter fetal immune responses and potentially lead to greater risk of ADHD in the offspring. Asthma may be a possible exception to this mechanism, as paternal asthma was also linked with risk of offspring ADHD.

Measles is vaccine-preventable extremely contagious disease caused by the measles virus. High vaccinationcoverage is needed to prevent outbreaks of disease. Although molecular surveillance of measles is critical tocharacterize outbreaks and track viral evolution, few whole-genome sequences of measles virus from West Africaare available despite continual outbreaks in the region. Using VirCapSeq-VERT, an enhanced and comprehensivemetagenomic sequencing technique that allows for simultaneous identification of all vertebrate viruses, 23 wild-type near-complete genomes of measles virus from across Mali were obtained from samples collected betweenJanuary 2012 to October 2022. Other febrile rash illnesses were also identified by VirCapSeq-VERT, demon-strating the advantage of using broad detection agnostic methods when the clinical diagnosis is unclear. Whereasone measles virus sequence was consistent with measles vaccine-associated rash illness (VARI), the remaining 38were classified within the B3.1 genotype. Broad surveillance throughout Mali reveals regional measles virustransmission across West and Central Africa into Mali, while local clinical testing in Bamako shows stablesequence conservation within genotype B3.1 evolving from Nigerian sequences. The genomic informationgenerated in this study is critical in addressing the lack of whole genome sequences available in West Africa andthese findings show the importance of phylogenetically tracking measles outbreaks given recent increases inmeasles cases globally.

Borrelia burgdorferi, the agent of Lyme disease, is estimated to cause >400,000 annual infections in the United States. Serology is the primary laboratory method to support the diagnosis of Lyme disease, but current methods have intrinsic limitations that require alternative approaches or targets. We used a high-density peptide array that contains >90,000 short overlapping peptides to catalog immunoreactive linear epitopes from >60 primary antigens of B. burgdorferi. We then pursued a machine learning approach to identify immunoreactive peptide panels that provide optimal Lyme disease serodiagnosis and can differentiate antibody responses at various stages of disease. We examined 226 serum samples from the Lyme Biobank and the National Institutes of Health, which included sera from 110 individuals diagnosed with Lyme disease, 31 probable cases from symptomatic individuals, and 85 healthy controls. Cases were grouped based on disease stage and presentation and included individuals with early localized, early disseminated, and late Lyme disease. We identified a peptide panel originating from 14 different epitopes that differentiated cases versus controls, whereas another peptide panel built from 12 unique epitopes differentiated subjects with various disease manifestations. Our method demonstrated an improvement in B. burgdorferi antibody detection over the current two-tiered testing approach and confirmed the key diagnostic role of VlsE and FlaB antigens at all stages of Lyme disease. We also uncovered epitopes that triggered a temporal antibody response that was useful for differentiation of early and late disease. Our findings can be used to streamline serologic targets and improve antibody-based diagnosis of Lyme disease. IMPORTANCE Serology is the primary method of Lyme disease diagnosis, but this approach has limitations, particularly early in disease. Currently employed antibody detection assays can be improved by the identification of alternative immunodominant epitopes and the selection of optimal diagnostic targets. We employed high-density peptide arrays that enabled precise epitope mapping for a wide range of B. burgdorferi antigens. In combination with machine learning, this approach facilitated the selection of serologic targets early in disease and the identification of serological indicators associated with different manifestations of Lyme disease. This study provides insights into differential antibody responses during infection and outlines a new approach for improved serologic diagnosis of Lyme disease.

Background Understanding of immune cell phenotypes associated with inflammatory and immunosuppressive host responses in sepsis is imprecise, particularly in low- and middle-income countries (LMICs), where the global sepsis burden is concentrated. In these settings, elucidation of immunophenotypes with prognostic importance is necessary to determine the relevance of emerging therapeutics and refine mechanistic investigations of sepsis immunopathology. Methods In a prospective cohort of adults hospitalized with suspected sepsis in Uganda (N = 43; median age 46 years [IQR 36-59], 24 [55.8%] living with HIV, 16 [37.2%] deceased at 60 days), we combined high-dimensional flow cytometry with unsupervised machine learning and manual gating to define peripheral immunophenotypes associated with increased risk of 60-day mortality. Results Patients who died showed heterogenous expansion of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), with increased and decreased abundance of CD16 neg PD-L1 dim and CD16 bright PD-L1 bright subsets, respectively, significantly associated with mortality. While differences between CD16 neg PD-L1 dim cell abundance and mortality risk appeared consistent throughout the course of illness, those for the CD16 bright PD-L1 bright subset were more pronounced early after illness onset. Independent of HIV co-infection, depletion of CD4 ⁺ T cells, dendritic cells, and CD56 ⁻ CD16 bright NK cells were significantly associated with mortality risk, as was expansion of immature, CD56 ⁺ CD16 ⁻ CD11c ⁺ NK cells. Abundance of T cells expressing inhibitory checkpoint proteins (PD-1, CTLA-4, LAG3) was similar between patients who died versus those who survived. Conclusions This is the first study to define high risk immunophenotypes among adults with sepsis in sub-Saharan Africa, an immunologically distinct region where biologically informed treatment strategies are needed. More broadly, our findings highlight the clinical importance and complexity of MDSC expansion during sepsis and support emerging data that suggest a host-protective role for PD-L1 myeloid checkpoints in acute critical illness.