Biology subjects

Alpert, A.

Publications and source records attributed to Alpert, A..

5 recordsLinked to original sources

bioRxiv2025

Systems level analysis of B-cell development identifies BDNF as a driver for human B lymphopoiesis

B-cell aplasia is a major consequence of aging, chemotherapy, and B-cell-depleting immunotherapies, compromising immune protection against infections, cancer, and vaccines. Yet, unlike the myeloid and erythroid lineages, no strategy exists to accelerate human B-cell reconstitution. Here, we used an integrative systems biology approach to identify regulators of human B lymphopoiesis in the bone marrow (BM) microenvironment. By combining single-cell transcriptomic analysis of human BM with intercellular communication mapping, we generated an initial set of candidate factors predicted to act on developing B cells. To distinguish biologically meaningful putative regulators from a broad candidate space, we further intersected these findings with orthogonal human datasets capturing age-impaired B lymphopoiesis and protein dynamics associated with B-cell depletion and reconstitution. This convergent prioritization strategy highlighted a focused set of putative regulators, among which brain-derived neurotrophic factor (BDNF) emerged repeatedly as a top putative regulator. Functional interrogation in progenitor BM cells showed that several prioritized putative regulators induced transcriptional programs linked to early immune development, with BDNF consistently promoting pathways associated with B-cell differentiation. Importantly, in a human in vitro BM co-culture system, BDNF enhanced the differentiation of CD34+ hematopoietic progenitors into CD19+ progenitor B cells. Together, these findings identify BDNF as a previously unrecognized regulator of early human B lymphopoiesis and establish a general framework for uncovering functional hematopoietic regulators by integrating single-cell analysis with complementary biological and clinical signals. This approach may support future strategies to improve immune reconstitution in settings of prolonged B-cell depletion.

systems biology↗

bioRxiv2021

Multiple trajectory alignment reconstructs disease dynamics for discovery and clinical benefit

Diseases change over time, both phenotypically and in underlying driving molecular processes. Though understanding disease progression dynamics is critical for diagnostics and treatment, capturing these dynamics is difficult, due to their complexity and the high heterogeneity between individuals. We developed TimeAx, an algorithm which builds a comparative framework for capturing disease dynamics using high-dimensional short time-series data. We demonstrate TimeAx utility by studying disease progression dynamics for multiple diseases and data types. Notably, for urothelial bladder cancer tumorigenesis, we identified a stromal pro-invasion point on the disease progression axis, characterized by massive immune cell infiltration to the tumor microenvironment and increased mortality. Moreover, the continuous TimeAx model differentiated between early and late tumors within the same tumor subtype, uncovering novel molecular transitions and potential targetable pathways. Overall, we present a powerful approach for studying disease progression dynamics, providing improved molecular interpretability and clinical benefits for patient stratification and outcome prediction.

systems biology↗

bioRxiv2021

A personalized network framework reveals predictive axis of anti-TNF response across diseases

Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we used a novel computational approach termed Disruption Networks to generate a new data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. The new data-type extends beyond the feature level space, to the relations space, by quantifying individual-level breaking or rewiring of cross-feature relations. Applying disruption network to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.

systems biology↗

bioRxiv2018

High Resolution Comparison of Cancer-Related Developmental Processes Using Trajectory Alignment

Abnormal differentiation is a key feature of cancer, yet currently there is no framework that enables a comparative analysis of differentiation processes across patients while preserving their individual-level resolution. Here, we present devMap, an algorithm that uses high-dimensional trajectory alignment to anchor cancer-related developmental processes to a common backbone process, thus allowing for their systematic comparison. We applied devMap to bone marrow samples from healthy individuals and AML patients profiled by single-cell mass-cytometry at cancer diagnosis and following treatment. devMap standardization enabled us to infer the developmental status of the AML samples and characterize its evolution following treatment and in relapse. Application of devMap on an external dataset of AML bone marrow samples revealed conserved patterns of developmental signaling responses in AML that were obscured by traditional methodologies for developmental inference.

systems biology↗

bioRxiv2018

Immune cellular homeostasis in early life is determined by genetic variants of cellular production and turnover

Complex physiological functionality is often the outcome of multiple interacting cell-types, yet mechanistically how a large number of trait-associated genes yield a single multi-cellular network governing the phenotype has not been well defined. Individuals immune-cellular profiles at homeostasis show high heritability and inter-individual variation with functional and clinical implications. We profiled immune cellular variation by mass-cytometry in 55 genetically diverse mouse strains. We identify 788 genes associated with cellular homeostasis, supporting a polygenic model where 52% of genes correspond to core homeostatic functions whose genetic variants suffice to predict phenotype. Trait genes form a multi-cellular network architecture showing increased functional complexity over evolutionary timescales for shared regulation to all cells, specialized cell-specific programs, and between-cell synchronization. Contrasting to human studies suggests the regulatory network expands with environmental exposure history. Our findings shed light on the origin of immune-cellular variation and regulatory architectures that may generalize to other environmentally sensitive systems.

immunology↗