Allogeneic CD19-targeted CAR-T therapy in patients with severe myositis and systemic sclerosis.

Allogeneic chimeric antigen receptor (CAR)-T cells hold great promise for expanding the accessibility of CAR-T therapy, whereas the risks of allograft rejection have hampered its application. Here, we genetically engineered healthy-donor-derived, CD19-targeting CAR-T cells using CRISPR-Cas9 to address the issue of immune rejection and treated one patient with refractory immune-mediated necrotizing myopathy and two patients with diffuse cutaneous systemic sclerosis with these cells. This study was registered at ClinicalTrials.gov (NCT05859997). The infused cells persisted for over 3 months, achieving complete B cell depletion within 2 weeks of treatment. During the 6-month follow-up, we observed deep remission without cytokine release syndrome or other serious adverse events in all three patients, primarily shown by the significant improvement in the clinical response index scores for the two diseases, respectively, and supported by the observations of reversal of inflammation and fibrosis. Our results demonstrate the high safety and promising immune modulatory effect of the off-the-shelf CAR-T cells in treating severe refractory autoimmune diseases.

Immune mechanisms in fibrotic interstitial lung disease.

Fibrotic interstitial lung diseases (fILDs) have poor survival rates and lack effective therapies. Despite evidence for immune mechanisms in lung fibrosis, immunotherapies have been unsuccessful for major types of fILD. Here, we review immunological mechanisms in lung fibrosis that have the potential to impact clinical practice. We first examine innate immunity, which is broadly involved across fILD subtypes. We illustrate how innate immunity in fILD involves a complex interplay of multiple cell subpopulations and molecular pathways. We then review the growing evidence for adaptive immunity in lung fibrosis to provoke a re-examination of its role in clinical fILD. We close with future directions to address key knowledge gaps in fILD pathobiology: (1) longitudinal studies emphasizing early-stage clinical disease, (2) immune mechanisms of acute exacerbations, and (3) next-generation immunophenotyping integrating spatial, genetic, and single-cell approaches. Advances in these areas are essential for the future of precision medicine and immunotherapy in fILD.

Microbial transmission in the social microbiome and host health and disease.

Although social interactions are known to drive pathogen transmission, the contributions of socially transmissible host-associated mutualists and commensals to host health and disease remain poorly explored. We use the concept of the social microbiome-the microbial metacommunity of a social network of hosts-to analyze the implications of social microbial transmission for host health and disease. We investigate the contributions of socially transmissible microbes to both eco-evolutionary microbiome community processes (colonization resistance, the evolution of virulence, and reactions to ecological disturbance) and microbial transmission-based processes (transmission of microbes with metabolic and immune effects, inter-specific transmission, transmission of antibiotic-resistant microbes, and transmission of viruses). We consider the implications of social microbial transmission for communicable and non-communicable diseases and evaluate the importance of a socially transmissible component underlying canonically non-communicable diseases. The social transmission of mutualists and commensals may play a significant, under-appreciated role in the social determinants of health and may act as a hidden force in social evolution.

A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases.

The gut fungal community represents an essential element of human health, yet its functional and metabolic potential remains insufficiently elucidated, largely due to the limited availability of reference genomes. To address this gap, we presented the cultivated gut fungi (CGF) catalog, encompassing 760 fungal genomes derived from the feces of healthy individuals. This catalog comprises 206 species spanning 48 families, including 69 species previously unidentified. We explored the functional and metabolic attributes of the CGF species and utilized this catalog to construct a phylogenetic representation of the gut mycobiome by analyzing over 11,000 fecal metagenomes from Chinese and non-Chinese populations. Moreover, we identified significant common disease-related variations in gut mycobiome composition and corroborated the associations between fungal signatures and inflammatory bowel disease (IBD) through animal experimentation. These resources and findings substantially enrich our understanding of the biological diversity and disease relevance of the human gut mycobiome.

A genome-wide spectrum of tandem repeat expansions in 338,963 humans.

The Genome Aggregation Database (gnomAD), widely recognized as the gold-standard reference map of human genetic variation, has largely overlooked tandem repeat (TR) expansions, despite the fact that TRs constitute ∼6% of our genome and are linked to over 50 human diseases. Here, we introduce the TR-gnomAD (https://wlcb.oit.uci.edu/TRgnomAD), a biobank-scale reference of 0.86 million TRs derived from 338,963 whole-genome sequencing (WGS) samples of diverse ancestries (39.5% non-European samples). TR-gnomAD offers critical insights into ancestry-specific disease prevalence using disparities in TR unit number frequencies among ancestries. Moreover, TR-gnomAD is able to differentiate between common, presumably benign TR expansions, which are prevalent in TR-gnomAD, from those potentially pathogenic TR expansions, which are found more frequently in disease groups than within TR-gnomAD. Together, TR-gnomAD is an invaluable resource for researchers and physicians to interpret TR expansions in individuals with genetic diseases.

Structurally divergent and recurrently mutated regions of primate genomes.

We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.

Human determinants of age-dependent patterns of death from infection.

Regardless of microbial virulence (i.e., the global infection-fatality ratio), age generally drives the prevalence of death from infection in unvaccinated humans. Four mortality patterns are recognized: the common U- and L-shaped curves of endemic infections and the unique W- and J-shaped curves of pandemic infections. We suggest that these patterns result from different sets of human genetic and immunological determinants. In this model, it is the interplay between (1) monogenic genotypes affecting immunity to primary infection that preferentially manifest early in life and related genotypes or their phenocopies, including auto-antibodies, which manifest later in life and (2) the occurrence and persistence of adaptive, acquired immunity to primary or cross-reactive infections, which shapes the age-dependent pattern of human deaths from infection.

CAG repeat expansions create splicing acceptor sites and produce aberrant repeat-containing RNAs.

Expansions of CAG trinucleotide repeats cause several rare neurodegenerative diseases. The disease-causing repeats are translated in multiple reading frames and without an identifiable initiation codon. The molecular mechanism of this repeat-associated non-AUG (RAN) translation is not known. We find that expanded CAG repeats create new splice acceptor sites. Splicing of proximal donors to the repeats produces unexpected repeat-containing transcripts. Upon splicing, depending on the sequences surrounding the donor, CAG repeats may become embedded in AUG-initiated open reading frames. Canonical AUG-initiated translation of these aberrant RNAs may account for proteins that have been attributed to RAN translation. Disruption of the relevant splice donors or the in-frame AUG initiation codons is sufficient to abrogate RAN translation. Our findings provide a molecular explanation for the abnormal translation products observed in CAG trinucleotide repeat expansion disorders and add to the repertoire of mechanisms by which repeat expansion mutations disrupt cellular functions.

Type I and type III interferons: From basic biology and genetics to clinical development for COVID-19 and beyond.

Type I and type III interferons (IFNs) constitute a key antiviral defense systems of the body, inducing viral resistance to cells and mediating diverse innate and adaptive immune functions. Defective type I and type III IFN responses have recently emerged as the 'Achilles heel' in COVID-19, with such patients developing severe disease and exhibiting a high risk for critical pneumonia and death. Here, we review the biology of type I and type III IFNs, their similarities and important functional differences, and their roles in SARS-CoV-2 infection. We also appraise the various mechanisms proposed to drive defective IFN responses in COVID-19 with particular emphasis to the ability of SARS-CoV-2 to suppress IFN production and activities, the genetic factors involved and the presence of autoantibodies neutralizing IFNs and accounting for a large proportion of individuals with severe COVID-19. Finally, we discuss the long history of the type I IFN therapeutics for the treatment of viral diseases, cancer and multiple sclerosis, the various efforts to use them in respiratory infections, and the newly emerging type III IFN therapeutics, with emphasis to the more recent studies on COVID-19 and their potential use as broad spectrum antivirals for future epidemics or pandemics.

JAK/STAT defects and immune dysregulation, and guiding therapeutic choices.

Inborn errors of immunity (IEIs) encompass a diverse spectrum of genetic disorders that disrupt the intricate mechanisms of the immune system, leading to a variety of clinical manifestations. Traditionally associated with an increased susceptibility to recurrent infections, IEIs have unveiled a broader clinical landscape, encompassing immune dysregulation disorders characterized by autoimmunity, severe allergy, lymphoproliferation, and even malignancy. This review delves into the intricate interplay between IEIs and the JAK-STAT signaling pathway, a critical regulator of immune homeostasis. Mutations within this pathway can lead to a wide array of clinical presentations, even within the same gene. This heterogeneity poses a significant challenge, necessitating individually tailored therapeutic approaches to effectively manage the diverse manifestations of these disorders. Additionally, JAK-STAT pathway defects can lead to simultaneous susceptibility to both infection and immune dysregulation. JAK inhibitors, with their ability to suppress JAK-STAT signaling, have emerged as powerful tools in controlling immune dysregulation. However, questions remain regarding the optimal selection and dosing regimens for each specific condition. Hematopoietic stem cell transplantation (HSCT) holds promise as a curative therapy for many JAK-STAT pathway disorders, but this procedure carries significant risks. The use of JAK inhibitors as a bridge to HSCT has been proposed as a potential strategy to mitigate these risks.

DNA sensors in metabolic and cardiovascular diseases: Molecular mechanisms and therapeutic prospects.

DNA sensors generally initiate innate immune responses through the production of type I interferons. While extensively studied for host defense against invading pathogens, emerging evidence highlights the involvement of DNA sensors in metabolic and cardiovascular diseases. Elevated levels of modified, damaged, or ectopically localized self-DNA and non-self-DNA have been observed in patients and animal models with obesity, diabetes, fatty liver disease, and cardiovascular disease. The accumulation of cytosolic DNA aberrantly activates DNA signaling pathways, driving the pathological progression of these disorders. This review highlights the roles of specific DNA sensors, such as cyclic AMP-GMP synthase and stimulator of interferon genes (cGAS-STING), absent in melanoma 2 (AIM2), toll-like receptor 9 (TLR9), interferon gamma-inducible protein 16 (IFI16), DNA-dependent protein kinase (DNA-PK), and DEAD-box helicase 41 (DDX41) in various metabolic disorders. We explore how DNA signaling pathways in both immune and non-immune cells contribute to the development of these diseases. Furthermore, we discuss the intricate interplay between metabolic stress and immune responses, offering insights into potential therapeutic targets for managing metabolic and cardiovascular disorders. Understanding the mechanisms of DNA sensor signaling in these contexts provides a foundation for developing novel interventions aimed at mitigating the impact of these pervasive health issues.

Assessing autosomal aneuploidy in ancient genomes.

Using genetic methods, aneuploidies can be detected in ancient human remains, which is so far the only way to reliably prove their existence in the past. As highlighted in recent studies by Rohrlach et al. and by Anastasiadou et al., this initial step enables a deeper exploration of the history of rare diseases, encompassing the social and historical contexts of the afflicted individuals.

Estimating disease heritability from complex pedigrees allowing for ascertainment and covariates.

We propose TetraHer, a method for estimating the liability heritability of binary phenotypes. TetraHer has five key features. First, it can be applied to data from complex pedigrees that contain multiple types of relationships. Second, it can correct for ascertainment of cases or controls. Third, it can accommodate covariates. Fourth, it can model the contribution of common environment. Fifth, it produces a likelihood that can be used for significance testing. We first demonstrate the validity of TetraHer on simulated data. We then use TetraHer to estimate liability heritability for 229 codes from the tenth International Classification of Diseases (ICD-10). We identify 107 codes with significant heritability (p < 0.05/229), which can be used in future analyses for investigating the genetic architecture of human diseases.

Mutations in SAMD7 cause autosomal-recessive macular dystrophy with or without cone dysfunction.

Sterile alpha motif domain containing 7 (SAMD7) is a component of the Polycomb repressive complex 1, which inhibits transcription of many genes, including those activated by the transcription factor Cone-Rod Homeobox (CRX). Here we report bi-allelic mutations in SAMD7 as a cause of autosomal-recessive macular dystrophy with or without cone dysfunction. Four of these mutations affect splicing, while another mutation is a missense variant that alters the repressive effect of SAMD7 on CRX-dependent promoter activity, as shown by in vitro assays. Immunostaining of human retinal sections revealed that SAMD7 is localized in the nuclei of both rods and cones, as well as in those of cells belonging to the inner nuclear layer. These results place SAMD7 as a gene crucial for human retinal function and demonstrate a significant difference in the role of SAMD7 between the human and the mouse retina.

Genomic Answers for Kids: Toward more equitable access to genomic testing for rare diseases in rural populations.

Next-generation sequencing has revolutionized the speed of rare disease (RD) diagnoses. While clinical exome and genome sequencing represent an effective tool for many RD diagnoses, there is room to further improve the diagnostic odyssey of many RD patients. One recognizable intervention lies in increasing equitable access to genomic testing. Rural communities represent a significant portion of underserved and underrepresented individuals facing additional barriers to diagnosis and treatment. Primary care providers (PCPs) at local clinics, though sometimes suspicious of a potential benefit of genetic testing for their patients, have significant constraints in pursuing it themselves and rely on referrals to specialists. Yet, these referrals are typically followed by long waitlists and significant delays in clinical assessment, insurance clearance, testing, and initiation of diagnosis-informed care management. Not only is this process time intensive, but it also often requires multiple visits to urban medical centers for which distance may be a significant barrier to rural families. Therefore, providing early, "direct-to-provider" (DTP) local access to unrestrictive genomic testing is likely to help speed up diagnostic times and access to care for RD patients in rural communities. In a pilot study with a PCP clinic in rural Kansas, we observed a minimum 5.5 months shortening of time to diagnosis through the DTP exome sequencing program as compared to rural patients receiving genetic testing through the "traditional" PCP-referral-to-specialist scheme. We share our experience to encourage future partnerships beyond our center. Our efforts represent just one step in fostering greater diversity and equity in genomic studies.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning.

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits.

Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR < 0.05) with a median expected true positive rate (π1) across tissues of 0.806 and 0.390, respectively. The target proteins of trans-acting genes were enriched for transcription factor binding sites and autoimmune diseases in the GWAS catalog. Furthermore, we found a higher correlation between predicted expression and protein levels of the same underlying gene (R = 0.17) than observed expression (R = 0.10, p = 7.50 × 10-11). This indicates the cis-acting genetically regulated (heritable) component of gene expression is more consistent across tissues than total observed expression (genetics + environment) and is useful in uncovering the function of SNPs associated with complex traits.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning.

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (ß coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Historic obstacles and emerging opportunities in the field of developmental metabolism - lessons from Heidelberg.

The field of developmental metabolism is experiencing a technological revolution that is opening entirely new fields of inquiry. Advances in metabolomics, small-molecule sensors, single-cell RNA sequencing and computational modeling present new opportunities for exploring cell-specific and tissue-specific metabolic networks, interorgan metabolic communication, and gene-by-metabolite interactions in time and space. Together, these advances not only present a means by which developmental biologists can tackle questions that have challenged the field for centuries, but also present young scientists with opportunities to define new areas of inquiry. These emerging frontiers of developmental metabolism were at the center of a highly interactive 2023 EMBO workshop 'Developmental metabolism: flows of energy, matter, and information'. Here, we summarize key discussions from this forum, emphasizing modern developmental biology's challenges and opportunities.

Innate-like T cells in liver disease.

Mammalian innate-like T cells (ILTCs), including mucosal-associated invariant T (MAIT), natural killer T (NKT), and γδ T cells, are abundant tissue-resident lymphocytes that have recently emerged as orchestrators of hepatic inflammation, tissue repair, and immune homeostasis. This review explores the involvement of different ILTC subsets in liver diseases. We explore the mechanisms underlying the pro- and anti-inflammatory effector functions of ILTCs in a context-dependent manner. We highlight latest findings regarding the dynamic interplay between ILTC functional subsets and other immune and parenchymal cells which may inform candidate immunomodulatory strategies to achieve improved clinical outcomes in liver diseases. We present new insights into how distinct gene expression programs in hepatic ILTCs are induced, maintained, and reprogrammed in a context- and disease stage-dependent manner.