Periodic Reporting for period 3 - IMPACT (High-Dimensional single cell mapping of inflammatory disease signatures in monozygotic twins)
Reporting period: 2024-01-01 to 2025-06-30
Multiple Sclerosis (MS) is a chronic inflammatory disease, where immune cell invasion into the central nervous system causes immunopathology and neurological deficit. Although disease-modifying therapies dramatically reduce disease activity, they hold the potential for severe adverse effects while long-term disability prospects remain poor. Moreover, there is to date no biomarker for monitoring the disease activity and to guide therapy decisions. I propose that the key to identifying such biomarkers is to combine single-cell mapping of leukocytes across well-curated patient cohorts with unbiased machine-learning based data interrogation. Using such an approach, we have already delineated a disease signature in a helper T cell population specific for MS. However, the immune compartment of cross-sectional cohorts is influenced by the individual genetic make-up, which masks disease-specific signals and hinders a more precise characterization of involved immune cell populations.
In this project, we pursue the following specific goals:
- Aim 1: Interrogate the immune compartment of a unique cohort of monozygotic twin pairs -discordant for MS - and deeply analyse peripheral blood lymphocytes by single-cell mass cytometry, combined TcR and single cell sequencing, and epigenetic profiling.
- Aim 2: Develop representation-learning methods to account for the paired genetics of twins or longitudinal samples and to include clinical covariates into the high-dimensional data set.
- Aim 3: to use well-defined patient samples of MS-like disorders (MS-Mimics) and longitudinal samples of patients undergoing disease-modifying therapy (e.g. B cell depletion, autologous stem cell transplant) using single-cell mass cytometry.
Overall, the goal is to leverage the dimensionality of disease signatures to gain a better understanding of MS, translate this into biomarkers for monitoring disease activity, and inform new treatment options.
In this project, we pursue the following specific goals:
- Aim 1: Interrogate the immune compartment of a unique cohort of monozygotic twin pairs -discordant for MS - and deeply analyse peripheral blood lymphocytes by single-cell mass cytometry, combined TcR and single cell sequencing, and epigenetic profiling.
- Aim 2: Develop representation-learning methods to account for the paired genetics of twins or longitudinal samples and to include clinical covariates into the high-dimensional data set.
- Aim 3: to use well-defined patient samples of MS-like disorders (MS-Mimics) and longitudinal samples of patients undergoing disease-modifying therapy (e.g. B cell depletion, autologous stem cell transplant) using single-cell mass cytometry.
Overall, the goal is to leverage the dimensionality of disease signatures to gain a better understanding of MS, translate this into biomarkers for monitoring disease activity, and inform new treatment options.
We are pleased to report that Aim 1 — the comprehensive interrogation of the immune compartment in monozygotic twin pairs discordant for multiple sclerosis — has been completed, and the results have been published in two high-impact journals with visibility in both the medical and basic biology fields (Ingelfinger, Gerdes et al. Nature, 2022; Ingelfinger et al. Med, 2024). Our approach eliminated the majority of bias attributed to variable genetic and early environmental influences in a heterogenous population and allowed for the distillation of clearly disease driven immune signatures in MS. Beyond the strong genetic predisposition endowed by a variant of the IL-2Ra, we found that the IL-2 pathway is also highly related to the environmental risk of developing MS. Additional dysregulations were observed in the myeloid compartment with an elevated GM-CSF sensing in a subset of monocytic cells of MS individuals.
Aim 2, the development of representation-learning methods to account for paired or longitudinal samples is ongoing. Several breakthroughs were accomplished by collaborations with our teams computational biologists and collaborating labs. Some of these accomplishments can be read in (Diebold et al., 2022; Ingelfinger et al., 2022a-c; Kreutmair et al., 2022a-b; Nuñez et al. 2023, Driessen, Unger et al. 2024; Ingelfinger et al., 2024; Ulutekin, Galli et al., 2024).
Aim 3, using patient samples of MS-like disorders (MS-Mimics) and longitudinal samples of patients undergoing disease-modifying therapy is ongoing. The identification of a biomarkers for monitoring the disease response upon Dimethyl fumarate is published (Diebold et al., 2022). The investigation of MS patients undergoing B cell depletion therapy identified key mechanistic underpinnings of this clinically highly successful treatment. Upregulated CD27 expression on T cells suggested that disruption of T–B cell interactions contribute to the therapeutic effect. After confirming this finding in a second independent cohort, the work was published (Ulutekin, Galli et al. Cell Rep Med, 2024).
For the investigation of MS-Mimics, we transitioned from CyTOF to single-cell spectral flow cytometry due to the latter's superior dynamic range, sensitivity, and acquisition speed. We developed the expertise and tools in our lab to push that technology to the limit by creating panels with 40-45 parameters. MOG-IgG antibody disease (MOG-AD) is a typical MS-mimic since it can share symptoms with MS, but differs in the clinical course and treatment. We found that MOG-AD patients show expanded activated B cell subsets with a phenotype similar to lupus patients. Additionally circulating CXCR3⁺ CD4⁺ memory T cells are reduced - likely due to their retention in the inflamed central nervous system, as seen in a transgenic mouse model. A manuscript summarizing the findings is under revision.
Aim 2, the development of representation-learning methods to account for paired or longitudinal samples is ongoing. Several breakthroughs were accomplished by collaborations with our teams computational biologists and collaborating labs. Some of these accomplishments can be read in (Diebold et al., 2022; Ingelfinger et al., 2022a-c; Kreutmair et al., 2022a-b; Nuñez et al. 2023, Driessen, Unger et al. 2024; Ingelfinger et al., 2024; Ulutekin, Galli et al., 2024).
Aim 3, using patient samples of MS-like disorders (MS-Mimics) and longitudinal samples of patients undergoing disease-modifying therapy is ongoing. The identification of a biomarkers for monitoring the disease response upon Dimethyl fumarate is published (Diebold et al., 2022). The investigation of MS patients undergoing B cell depletion therapy identified key mechanistic underpinnings of this clinically highly successful treatment. Upregulated CD27 expression on T cells suggested that disruption of T–B cell interactions contribute to the therapeutic effect. After confirming this finding in a second independent cohort, the work was published (Ulutekin, Galli et al. Cell Rep Med, 2024).
For the investigation of MS-Mimics, we transitioned from CyTOF to single-cell spectral flow cytometry due to the latter's superior dynamic range, sensitivity, and acquisition speed. We developed the expertise and tools in our lab to push that technology to the limit by creating panels with 40-45 parameters. MOG-IgG antibody disease (MOG-AD) is a typical MS-mimic since it can share symptoms with MS, but differs in the clinical course and treatment. We found that MOG-AD patients show expanded activated B cell subsets with a phenotype similar to lupus patients. Additionally circulating CXCR3⁺ CD4⁺ memory T cells are reduced - likely due to their retention in the inflamed central nervous system, as seen in a transgenic mouse model. A manuscript summarizing the findings is under revision.
Our project has significantly advanced the understanding of immune dysregulation in MS through novel study designs and integrative methodologies.
In Aim 1, we interrogated the immune system in monozygotic twin pairs discordant for MS, controlling for genetic and early environmental factors. This unique approach enabled the identification of true disease-driven immune alterations, including the involvement of the IL-2 signaling pathway in both genetic and environmental MS risk, and GM-CSF hypersensitivity in monocytes. These findings were published in Nature (2022) and Med (2024).
In Aim 2, we are applied emerging computational tools for paired and longitudinal immune data, and developed new computations pipelines for data analysis. Several resulting publications (e.g. Diebold et al., 2022; Ingelfinger et al., 2022a-c; Kreutmair et al., 2022a-b; Nuñez et al. 2023, Driessen, Unger et al. 2024; Ingelfinger et al., 2024; Ulutekin, Galli et al., 2024) have already demonstrated the power of this approach in immune profiling.
In Aim 3, using samples from patients on therapy and with MS-like disorders, we identified biomarkers of treatment response (e.g. to Dimethyl fumarate) and provided mechanistic insights into B cell depletion therapy, specifically the disruption of T–B cell interactions via CD27/CD70 signaling (Cell Reports Medicine, 2024).
Technologically, we transitioned to high-parameter single-cell spectral flow cytometry, enabling deep immune phenotyping in complex diseases such as MOG-IgG antibody disease. Here, we found expanded lupus-like B cells and reduced CXCR3⁺ T cells, with findings under revision.
In Aim 1, we interrogated the immune system in monozygotic twin pairs discordant for MS, controlling for genetic and early environmental factors. This unique approach enabled the identification of true disease-driven immune alterations, including the involvement of the IL-2 signaling pathway in both genetic and environmental MS risk, and GM-CSF hypersensitivity in monocytes. These findings were published in Nature (2022) and Med (2024).
In Aim 2, we are applied emerging computational tools for paired and longitudinal immune data, and developed new computations pipelines for data analysis. Several resulting publications (e.g. Diebold et al., 2022; Ingelfinger et al., 2022a-c; Kreutmair et al., 2022a-b; Nuñez et al. 2023, Driessen, Unger et al. 2024; Ingelfinger et al., 2024; Ulutekin, Galli et al., 2024) have already demonstrated the power of this approach in immune profiling.
In Aim 3, using samples from patients on therapy and with MS-like disorders, we identified biomarkers of treatment response (e.g. to Dimethyl fumarate) and provided mechanistic insights into B cell depletion therapy, specifically the disruption of T–B cell interactions via CD27/CD70 signaling (Cell Reports Medicine, 2024).
Technologically, we transitioned to high-parameter single-cell spectral flow cytometry, enabling deep immune phenotyping in complex diseases such as MOG-IgG antibody disease. Here, we found expanded lupus-like B cells and reduced CXCR3⁺ T cells, with findings under revision.