EBioMedicine最新文献

Background: The antibody repertoire in the blood encodes a comprehensive record of an individual's immunological encounters. Knowing the individuality of the repertoire would benefit in vaccinations, and also in personalising treatments. Formation of the immunoglobulin G (IgG) antibody repertoire starts before birth.

Methods: Here, we used a mimotope variation analysis (MVA) method to gain deeper insight into the repertoire of maternal antibodies actively transferred to newborns during pregnancy with the follow-up at 6 months.

Findings: Our study of 25 mothers and their neonates highlighted the strong correlation between maternal and neonatal antibody levels with comparable antigen-specificity shortly after birth. However, a noticeable blunting or interference in the antibody response was observed at the epitope level, revealing distinct patterns of recognition of antigenic determinants between mothers and their infants at 6 months, particularly concerning common latent viral infections like cytomegalovirus (CMV).

Interpretation: Comprehensive understanding of the characteristics of placental IgG antibody transmission is essential for effectively leveraging and manipulating these mechanisms to benefit newborn health.

Funding: This research was supported by funds from the Estonian Ministry of Education and Research, the Estonian Research Council and by grants from the EU's HE programme.

Background: Disruptions in synaptic function and exposure to early life trauma are both implicated in the development of depression, though the underlying mechanisms remain poorly understood.

Methods: To investigate this relationship, we developed an expression-based polygenic score (ePRS) that captures individual variations in the expression of genes co-expressed with the synaptic protein Syntaxin 1A (STX1A) in the prefrontal cortex (PFC). This polygenic score allows us to explore the impact of variations on synaptic function and childhood trauma on the susceptibility to depressive symptoms in adulthood.

Findings: Our findings indicate that the PFC-ePRS-STX1A score moderates the effects of childhood trauma on the diagnosis of depression in adult females from the UK Biobank (Logistic regression, β = -0.150, p = 0.001, N = 72,812). A similar result was found in an independent cohort (ALSPAC), where PFC-ePRS-STX1A moderated the effects of childhood trauma on depressive symptoms in younger adult females, confirming the sex-specific moderation effect (GEE analysis, ages 22-23, β = -1.063, p = 0.0046, N = 1846). Functional enrichment analysis of the STX1A-coexpressed network revealed key biological processes related to protein synthesis, with 25.8% associated gene products localised to synaptic components at both pre and postsynaptic sites.

Interpretation: This highlights the critical role of synaptic plasticity function in the PFC in shaping the long-term effects of early trauma on depression. Our methodology and results offer valuable insights into individual vulnerability to depression following early trauma and highlight synaptic function as a potential target for interventions aimed at mitigating depression risk.

Funding: JPB Foundation; Hope for Depression Research Foundation; CAPES; Fonds de recherche du Québec, and CIHR.

Background: Nigrostriatal iron accumulation is a hallmark of ageing and neurodegenerative diseases, but the molecular mechanisms regulating iron deposition in the human brain remain unclear. Identifying genes linked to iron accumulation could reveal new pathways for neuroprotection and therapeutic targeting.

Methods: We performed a discovery-replication transcriptome-wide association study (TWAS), integrating GWAS data for quantitative susceptibility mapping and T2∗ MRI measures (n = 29,579) with expression quantitative trait locus data for the substantia nigra, putamen, and caudate. Single-tissue analyses were complemented by multi-tissue TWAS, colocalisation, and summary Mendelian randomisation (SMR + HEIDI) to evaluate biological plausibility and causal evidence. Functional enrichment and comparison with ageing and Parkinson's disease transcriptomic datasets were conducted.

Findings: We identified 230 genes associated with nigrostriatal iron, of which 40 were replicable. Of these, 32 had no previous reported links to brain iron. Replicated genes converged on metal ion transport and inflammatory pathways, with notable associations involving calcium channel (CACNB2), zinc transporter (SLC39A12/ZIP12), and sorting nexin (SNX31) genes. SMR + HEIDI and colocalisation highlighted several putatively causal genes, including SNX31 and TMEM206. Overlap with Parkinson's disease substantia nigra differential expression data highlighted a subset of genes (5.22%), particularly SLC39A12.

Interpretation: Our data implicate a role of coordinated interactions among iron, zinc, and calcium homoeostasis pathways in nigrostriatal iron accumulation in the general population, with region-specific regulation differing between substantia nigra and dorsal striatum. These findings nominate new mechanistic targets for experimental validation in neurodegeneration.

Funding: Supported by the Singapore National Medical Research Council and SingHealth/Duke-NUS Academic Medical Centre.

Background: The COVID-19 pandemic led to a spectrum of post-acute sequelae including several neurological complications including cognitive dysfunction labelled Neurological PASC (N-PASC). We hypothesised that N-PASC was associated with changes in neurological biomarkers after COVID-19.

Methods: N-PASC was established when individuals reported accepted neurological symptoms persisting for ≥3 months arising alongside validated COVID-19. Plasma samples were retrieved from before and after COVID-19 onset among all (n = 227) essential workers who developed COVID-19 with N-PASC and demographically matched with data from 227 controls who either developed COVID-19 without N-PASC (n = 124) or did not develop COVID-19 before follow-up (n = 103). We used single molecular analysis measured pTau-181, GFAP, NfL, Aβ40/42, and total Aβ burden (IAB). Risk factors for N-PASC were examined prior to COVID-19 infection. Multivariable adjusted generalised linear longitudinal modelling with random intercepts was used to examine changes in biomarkers after COVID-19 onset.

Findings: N-PASC was only associated with higher IAB before COVID-19 onset (area under the receiver-operating curve = 0.77). Longitudinal analyses revealed plasma pTau-181 levels increased by 59.3% (95% C.I. = [45.2, 73.4] P = 0.006) following COVID-19 onset in participants who developed N-PASC that were worst among participants reporting central nervous symptoms persisting ≥1.5 years. Post-COVID-19 decreased GFAP and NfL were associated with peripheral symptoms of N-PASC, but not with increased pTau-181. Having ≥20% increases in pTau-181 were associated with increased Aβ40/42 levels at follow-up, and with central neurological symptoms including lingering brain fog and loss of taste/smell.

Interpretation: N-PASC with symptoms consistent with central damage were associated with increased pTau-181 levels. Increases in pTau-181 were associated with increased risk of changes to amyloid biomarkers consistent with Alzheimer's disease in participants with N-PASC and could therefore inform N-PASC prognostication.

Funding: This study was supported in part by funding from the Centers for Disease Control and Prevention (CDC/NIOSH CDC-75D30122c15522) and the National Institutes of Health (NIH/NIA AG049953).

Background: Elevated SARS-CoV-2 IgG4 levels following repeated COVID-19 mRNA boosters may impact blood and mucosal antibody functions against Omicron variants and sarbecoviruses. This study characterised the rise of IgG4 in blood and saliva following four consecutive COVID-19 mRNA doses and examined how IgG4 modulated neutralising and non-neutralising responses.

Methods: Paired plasma and saliva samples were collected pre- and post-mRNA boosters from homologous mRNA vaccinees (2 primary mRNA + 2 mRNA booster) or adenovirus-vector primed vaccinees (2 Vaxzevria + 4 mRNA booster). The breadth and proportion of IgG4 responses towards Omicron variants and sarbecoviruses were measured using multiplex bead arrays. Epitope blocking and depletion assays assessed immune imprinting. Live virus assays established IgG4's contribution towards neutralisation.

Findings: Plasma and salivary IgG4 antibodies binding Omicron variants and sarbecoviruses increased post-booster across both cohorts. Although non-neutralising responses significantly improved post-booster, they negatively correlated with IgG4 against all variants tested. Immune imprinting biased IgG4 responses towards the ancestral receptor binding motif, limiting neutralising IgG4 antibodies towards Omicron variants. Increased proportions of class-switched IgG4 also corresponded with decreased concentrations of spike-specific IgG1, particularly against the RBD, dampening neutralisation.

Interpretation: Repeated COVID-19 mRNA boosters improved neutralising and non-neutralising activity across viral variants for both cohorts, though these responses were dampened by increasing IgG4 antibodies. This work emphasises the potential longitudinal effects of booster-induced IgG4 subclass switching.

Funding: This study was supported by the VC2 Research Fund and an NHMRC Investigator grant #2008092. Sample collection was supported by WHO Unity funds (2020/1085469-0) and WEHI Philanthropic Funds.

Background: Pompe disease (PD), caused by acid α-glucosidase (GAA) deficiency, leads to glycogen accumulation in various tissues including the central nervous system. While enzyme replacement therapy (ERT) is lifesaving, it does not cross the blood-brain barrier. CNS manifestations including sensorineural hearing loss, dysarthria, and cognitive delay-persist despite ERT. Hence, CNS-specific biomarkers are needed to identify at-risk patients and guide monitoring and treatment. This clinical, retrospective study evaluated the utility of plasma glial fibrillary acidic protein (GFAP) as a potential biomarker of CNS involvement in infantile-onset Pompe disease (IOPD) compared to plasma neurofilament light chain (NfL).

Methods: Plasma GFAP and NfL levels were measured longitudinally in 37 patients with PD (180 samples, ages 0.1-21 years) and 54 age- and sex-matched controls. Patients were grouped as (1) IOPD with severe neurologic involvement (n = 7), (2) IOPD with attenuated neurologic involvement (n = 13), and (3) late-onset PD without neurologic involvement (LOPD; n = 17). Neurologic status was determined via clinical examination and/or brain MRI white matter grading via Modified Fazekas Scores (MFS).

Findings: GFAP levels were highest in IOPD patients with severe neurologic involvement. Patients with IOPD in the attenuated neurologic involvement group had, on average, lower plasma GFAP concentrations than those with severe neurologic involvement but greater GFAP levels than patients with LOPD, which resembled controls. GFAP outperformed NfL in differentiating patients with IOPD from controls (AUC = 0.886 vs 0.705) and identifying severe from attenuated neurologic involvement group (AUC = 0.801 vs 0.745). NfL showed high variability between controls and PD subgroups.

Interpretation: Plasma GFAP levels reliably reflect CNS disease burden in IOPD and outperform NfL in diagnostic performance. GFAP may be a useful biomarker for detecting and monitoring CNS involvement in PD.

Funding: Funding was provided in part by Sanofi (Cambridge, Massachusetts, USA). Philanthropic support was provided in part by Judy and Monty Frost, Abigail and JB Spaulding, AG Cox Charity Trust and Macie's Mission.

Background: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality globally. Effective management hinges on early diagnosis, which is often impeded by non-specific symptoms and resource-intensive diagnostic methods. This study assesses the effectiveness of electrocardiograms (ECGs) analysed via deep learning as a tool for early COPD detection.

Methods: We utilised a Convolutional Neural Network model to analyse ECGs for detecting COPD. The primary outcome was the accuracy of a new clinical COPD diagnosis as determined by ICD codes. Performance was evaluated using Area-Under-the-Curve (AUC) metrics derived by testing against ECGs from a set of holdout patients, ECGs from patients from another hospital, and ECGs of patients with COPD within the UK BioBank (UKBB).

Findings: We analysed a total of 208,231 ECGs from 18,225 COPD cases, matched to 49,356 controls by age, sex, and race. The model exhibited robust performance across diverse populations with an AUC of 0⋅80 (0⋅80-0⋅80) in internal testing, 0⋅82 (0⋅81-0⋅82) in external validation and 0⋅75 (0⋅71-0⋅78) in the UKBB cohort. Subsequent analyses linked ECG-derived model predictions with spirometry data, and model explainability highlighted P-wave changes as indicative of COPD.

Interpretation: AI-powered ECG analysis offers a promising path for early COPD detection, potentially facilitating earlier and more effective management. Implementing such tools in clinical settings could significantly enhance COPD screening and diagnostic accuracy, thereby improving patient outcomes and addressing the global health burden of the disease.

Funding: This work was supported in part through the computational and data resources and staff expertise provided by Scientific Computing and Data at the Icahn School of Medicine at Mount Sinai and supported by the Clinical and Translational Science Awards (CTSA) grant UL1TR004419 from the National Center for Advancing Translational Sciences; and R01HL167050-02 from the National Heart, Lung, and Blood Institute.

Background: The cerebrospinal fluid (CSF) provides a unique glimpse into the central nervous system (CNS) compartment and offers insights into immune processes associated with both healthy immune surveillance as well as inflammatory disorders of the CNS. The latter include demyelinating disorders, such as multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), that warrant different therapeutic approaches yet are not always straightforward to distinguish on clinical and imaging grounds alone.

Methods: We established a comprehensive phenotypic landscape of the paediatric CSF immune compartment across a range of non-inflammatory and inflammatory neurological disorders, with a focus on better elucidating CNS-associated immune mechanisms potentially involved in, and discriminating between, paediatric-onset MS (MS) and other paediatric-onset suspected neuroimmune disorders, including MOGAD.

Findings: CSF from paediatric patients with non-inflammatory neurological disorders is primarily composed of non-activated CD4+ T cells, with few if any B cells present. CSF from paediatric patients with acquired inflammatory demyelinating disorders is characterised by increased numbers of B cells compared to CSF of both patients with other inflammatory or non-inflammatory conditions. Certain features, including particular increased frequencies of antibody-secreting cells (ASCs) and decreased frequencies of CD14+ myeloid cells, distinguish MS from MOGAD and other acquired demyelinating syndromes.

Interpretation: Increased CSF ASC frequencies and decreased CSF CD14+ myeloid cell frequencies help distinguish paediatric-onset MS from paediatric-onset MOGAD and other acquired demyelinating syndromes. Our findings provide insight into CNS-associated immune mechanisms that may be present early in the clinical course of MS.

Funding: Stated in acknowledgements section of manuscript.

Background: Li-Fraumeni Syndrome (LFS) is a heterogenous cancer predisposition condition caused by pathogenic TP53 variants, characterised by a lifelong high risk of a broad spectrum of cancers. Certain pathogenic TP53 variants have been shown be immunogenic in a somatic context. Whether neoantigenicity contributes to LFS heterogeneity is unknown. In this study we analysed the correlations between predicted neoantigenic properties of pathogenic TP53 missense variants and LFS phenotypes.

Methods: MHC-I presentation scores were generated for the set of nonameric neo-peptides surrounding each TP53 missense variant against 145 different HLA-I using NetMHCpan 4.1 and the Allele Frequency Net Database. A predicted neoantigenic score (PNS) was calculated for each variant. Association study was performed between PNS, LFS presentation and individual HLA-I genotyping, in individuals carrying TP53 germline pathogenic variants using data from mutation databases and clinical registries. Genotype-phenotype data were leveraged from the public TP53 database (germline dataset, n = 3446; https://tp53.isb-cgc.org/) and two independent LFS clinical registries (n = 339). Individual correlations between HLA-I genotyping, TP53 missense variants and phenotypes were investigated in a group of 173 subjects with LFS.

Findings: Among individuals with frequent TP53 pathogenic variants, PNS was strongly correlated with median age at first cancer (range 18-43 years, R = 0.69, p = 0.0132). Compared to individuals with low PNS (<1) variants, those with high PNS (>2) variants showed delayed median age at first diagnosis (34 years vs. 25 years, p = 0.0009), fewer sarcomas (osteosarcoma [RR 0.29, p = 0.02]; soft-tissue [RR 0.41, p = 0.02]), and more cancer types typically not associated with LFS spectrum [RR 1.61, p = 0.02].

Interpretation: MHC-I neoantigenic properties of TP53 variants are associated with differences in cancer risk and spectrum in individuals with pathogenic TP53 variants, suggesting that individual variant-specific immune response could contribute to the heterogenous presentation of LFS.

Funding: European Commission, Fondation MSDAvenir, BMBF, Deutsche Kinderkrebsstiftung, European Regional Development Fund, Région Normandie, NIH, Mark Foundation, and Hertz Foundation.