Biology subjects

Baranzini, S. E.

Publications and source records attributed to Baranzini, S. E..

6 recordsLinked to original sources

bioRxiv2026

Innate Immune Dysregulation Precedes Clinical Onset in Neuromyelitis Optica

Neuromyelitis optica spectrum disorder (NMOSD) is a disabling inflammatory central nervous system (CNS) disease characterized by pathogenic aquaporin 4 (AQP4) autoantibodies. The biological events that precede clinical onset remain unknown. In a unique longitudinal NMOSD cohort from the U.S. Department of Defense Serum Repository, with samples collected up to 24 years before onset, we applied discovery proteomics (~5,400 proteins), pan-viral antibody profiling (VirScan), and in silico analyses to characterize preclinical NMOSD versus matched healthy controls. Innate immune activation, particularly CXCL1 elevation, was the dominant immunological feature of preclinical NMOSD, preceding onset by ~12.7 years. AQP4-IgG was detectable more than 3 years before onset, while CNS injury markers increased only after disease manifestation. VirScan identified enhanced CMV-specific antibody reactivity following AQP4- IgG seroconversion, and network analyses revealed interactions between NMOSD-associated and CMV-derived proteins. Together, these findings establish a novel multi-hit model of NMOSD, with implications for understanding antibody-mediated autoimmunity more broadly.

immunology↗

bioRxiv2025

Evaluating the Contribution of Genome 3D Folding to Variation in Human Height Using Machine Learning

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, yet the majority lie in noncoding regions, making it difficult to determine their functional impact. Alterations to the three-dimensional (3D) spatial interactions among gene regulatory elements are increasingly recognized as a mechanism by which genetic variants influence gene expression. However, experimentally evaluating whether variants disrupt 3D-genome structure is not feasible at GWAS scale. To address this, we developed a computational framework that integrates GWAS summary statistics with predictions from the Akita sequence-based deep learning model of 3D chromatin contacts. We applied the framework to 9,917 genomic regions associated with human height, assessing both individual variants and haplotypes for their predicted impact on 3D genome architecture. Only a small fraction of height-associated haplotypes had substantial predicted disruption of 3D folding (17 regions, 0.17%, exceeded a disruption score of 0.1). Considering all common variants in a haplotype together generally produced greater perturbations than individual variants, but several highly divergent regions were driven by single variants. We highlight a variant that disrupts the binding motif at a confirmed CTCF binding site and is predicted to modify 3D genome contacts with the LCOR promoter, suggesting that 3D-genome-mediated disruption of gene regulation underlies the association with height. This work presents a scalable and interpretable strategy for integrating 3D genome modeling with GWAS, enabling investigation of this important regulatory mechanism in the connection of non-coding genetic variation to complex traits.

genetics↗

bioRxiv2024

Restoring the Multiple Sclerosis Associated Imbalance of Gut Indole Metabolites Promotes Remyelination and Suppresses Neuroinflammation

In multiple sclerosis (MS) the circulating metabolome is dysregulated, with indole lactate (ILA) being one of the most significantly reduced metabolites. We demonstrate that oral supplementation of ILA impacts key MS disease processes in two preclinical models. ILA reduces neuroinflammation by dampening immune cell activation as well as infiltration; and promotes remyelination and in vitro oligodendrocyte differentiation through the aryl hydrocarbon receptor (AhR). Supplementation of ILA, a reductive indole metabolite, restores the gut microbiomes oxidative/reductive metabolic balance by lowering circulating indole acetate (IAA), an oxidative indole metabolite, that blocks remyelination and oligodendrocyte maturation. The ILA-induced reduction in circulating IAA is linked to changes in IAA-producing gut microbiota taxa and pathways that are also dysregulated in MS. Notably, a lower ILA:IAA ratio correlates with worse MS outcomes. Overall, these findings identify ILA as a potential anti-inflammatory remyelinating agent and provide insights into the role of gut dysbiosis-related metabolic alterations in MS progression. One Sentence SummaryIndole lactate, a postbiotic metabolite reduced in MS, corrects gut microbiome metabolic imbalances associated with remyelination and neuroinflammation.

neuroscience↗

bioRxiv2019

Integrating Biomedical Research and Electronic Health Records to Create Knowledge Based Biologically Meaningful Machine Readable Embeddings

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. In an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients were connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm was used to create Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine.

systems biology↗

bioRxiv2017

The Multiple Sclerosis Genomic Map: Role of peripheral immune cells and resident microglia in susceptibility

AbstractWe assembled and analyzed genetic data of 47,351 multiple sclerosis (MS) subjects and 68,284 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 independent associations within the extended MHC. We used an ensemble of methods to prioritize up to 551 potentially associated MS susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we do find enrichment for MS genes in these brain - resident immune cells. Thus, while MS is most likely initially triggered by perturbation of peripheral immune responses the functional responses of microglia and other brain cells are also altered and may have a role in targeting an autoimmune process to the central nervous system.\n\nOne Sentence SummaryWe report a detailed genetic and genomic map of multiple sclerosis, and describe the role of putatively affected genes in the peripheral immune system and brain resident microglia.

genetics↗

bioRxiv2016

Systematic integration of biomedical knowledge prioritizes drugs for repurposing

The ability to computationally predict whether a compound treats a disease would improve the economy and success rate of drug approval. This study describes Project Rephetio to systematically model drug efficacy based on 755 existing treatments. First, we constructed Hetionet (neo4j.het.io), an integrative network encoding knowledge from millions of biomedical studies. Hetionet v1.0 consists of 47,031 nodes of 11 types and 2,250,197 relationships of 24 types. Data was integrated from 29 public resources to connect compounds, diseases, genes, anatomies, pathways, biological processes, molecular functions, cellular components, pharmacologic classes, side effects, and symptoms. Next, we identified network patterns that distinguish treatments from non-treatments. Then we predicted the probability of treatment for 209,168 compound-disease pairs (het.io/repurpose). Our predictions validated on two external sets of treatment and provided pharmacological insights on epilepsy, suggesting they will help prioritize drug repurposing candidates. This study was entirely open and received realtime feedback from 40 community members.

bioinformatics↗