Biology subjects

Friedman, C.

Publications and source records attributed to Friedman, C..

6 recordsLinked to original sources

bioRxiv2026

Technology solutions for immune loci: integrated high-resolution KIR genotyping reveals allelic, structural, and KIR-HLA diversity across 24 human populations

High-resolution genotyping of killer cell immunoglobulin-like receptor (KIR) genes remains challenging because of extensive sequence homology, copy-number variation, and complex haplotype structures. Although KIR allelic variation influences receptor expression and function, routine typing has largely been limited to gene presence or absence. Here, we evaluated an integrated short-read sequencing system combining a four-reaction, two-stage multiplex PCR assay (ScisGo-KIR-v3), centralized cloud-based copy-aware allele analysis, and interactive genotype review. The system was applied to 2,298 individuals representing 24 populations from the 1000 Genomes Project, with matched high-resolution HLA class I genotypes. Independent validation against complete, phased PacBio KIR sequences from 48 samples demonstrated 98.6% automated copy-number concordance and 92.8% combined copy-number and allele concordance across 768 gene-sample comparisons. Following desktop review, all evaluated assignments were concordant with the reference sequences. In a separate comparison of four computational genotyping methods involving 311 shared samples, the automated Scisco pipeline showed the lowest overall mismatch with the four-method consensus (1.62%). Population analyses identified substantial allele diversity and distinct centromeric and telomeric haplotype-motif distributions. Although exact haplotype pairs were frequently ambiguous, structural assignments became increasingly resolvable at the motif level, and motif backgrounds exhibited characteristic allele compositions. Paired KIR and HLA analysis revealed inherited receptor-ligand configurations concealed by gene-content typing. Among 1,401 KIR3DL1/HLA-B Bw4 co-carriers, 57 lacked an allele annotated for ordinary surface expression, while 457 of 1,175 KIR2DS4 co-carriers of six specified HLA-C allotypes carried only truncated receptor forms. Allele-specific KIR2DL1 and KIR2DS5 classifications further distinguished receptor properties and published ligand-binding annotations that varied among populations. Although potential receptor-ligand repertoire composition differed across populations, analyses did not establish preferential KIR-HLA genetic association after accounting for population structure and multiple testing. Together, these findings demonstrate that integrated short-read KIR genotyping can provide scalable, high-resolution allele and copy-number information while explicitly retaining uncertainty in inferred haplotype structures. Compatibility with established HLA laboratory workflows provides a practical foundation for incorporating allele-resolved KIR analysis into immunogenetic research and future clinical investigations.

genetics↗

bioRxiv2023

An epigenome-wide association study of child appetitive traits and DNA methylation

Childhood appetitive traits are consistently associated with obesity risk, and yet their etiology is poorly understood. Appetitive traits are complex phenotypes which are hypothesized to be influenced by both genetic and environmental factors, as well as their interactions. Early-life epigenetic processes, such as DNA methylation (DNAm), may be involved in the developmental programming of appetite regulation in childhood. In the current study, we meta-analyzed epigenome-wide association studies (EWASs) of cord blood DNAm and early-childhood appetitive traits. Data were from two independent cohorts: the Generation R Study (n=1,086, Rotterdam, the Netherlands) and the Healthy Start study (n=236, Colorado, USA). DNAm at autosomal methylation sites in cord blood was measured using the Illumina Infinium HumanMethylation450 BeadChip. Parents reported on their childs food responsiveness, emotional undereating, satiety responsiveness and food fussiness using the Childrens Eating Behaviour Questionnaire at age 4-5 years. Multiple regression models were used to examine the association of DNAm (predictor) at the individual site- and regional-level (using DMRff) with each appetitive trait (outcome), adjusting for covariates. Bonferroni-correction was applied to adjust for multiple testing. There were no associations of DNAm and any appetitive trait at the individual site-level. However, at the regional level, we identified 45 associations of DNAm with food responsiveness, 7 associations of DNAm with emotional undereating, 13 associations of DNAm with satiety responsiveness, and 9 associations of DNAm with food fussiness. This study shows that DNAm in the newborn may partially explain variation in appetitive traits expressed in early childhood and provides preliminary support for early programming of child appetitive traits through DNAm. Investigating differential DNAm associated with appetitive traits could be an important first step in identifying biological pathways underlying the development of these behaviors.

genetics↗

bioRxiv2022

The Children's Brain Tumor Network (CBTN) - Accelerating Research in Pediatric Central Nervous System Tumors through Collaboration and Open Science

Pediatric brain tumors are the leading cause of cancer-related death in children in the United States and contribute a disproportionate number of potential years of life lost compared to adult cancers. Moreover, survivors frequently suffer long-term side effects, including secondary cancers. The Childrens Brain Tumor Network (CBTN) is a multi-institutional international clinical research consortium created to advance therapeutic development through the collection and rapid distribution of biospecimens and data via open-science research platforms for real-time access and use by the global research community. The CBTNs 32 member institutions utilize a shared regulatory governance architecture at the Childrens Hospital of Philadelphia to accelerate and maximize the use of biospecimens and data. As of August 2022, CBTN has enrolled over 4,700 subjects, over 1,500 parents, and collected over 65,000 biospecimen aliquots for research. Additionally, over 80 preclinical models have been developed from collected tumors. Multi-omic data for over 1,000 tumors and germline material is currently available with data generation for > 5,000 samples underway. To our knowledge, CBTN provides the largest open-access pediatric brain tumor multi-omic dataset annotated with longitudinal clinical and outcome data, imaging, associated biospecimens, child-parent genomic pedigrees, and in vivo and in vitro preclinical models. Empowered by NIH-supported platforms such as the Kids First Data Resource and the Childhood Cancer Data Initiative, the CBTN continues to expand the resources needed for scientists to accelerate translational impact for improved outcomes and quality of life for children with brain and spinal cord tumors.

cancer biology↗

bioRxiv2022

HOPX governs a molecular and physiological switch between cardiomyocyte progenitor and maturation gene programs

This study establishes the homeodomain only protein, HOPX, as a determinant controlling the molecular switch between cardiomyocyte progenitor and maturation gene programs. Time-course single-cell gene expression with genome-wide footprinting reveal that HOPX interacts with and controls core cardiac networks by regulating the activity of mutually exclusive developmental gene programs. Upstream hypertrophy and proliferation pathways compete to regulate HOPX transcription. Mitogenic signals override hypertrophic growth signals to suppress HOPX and maintain cardiomyocyte progenitor gene programs. Physiological studies show HOPX directly governs genetic control of cardiomyocyte cell stress responses, electro-mechanical coupling, proliferation, and contractility. We use human genome-wide association studies (GWAS) to show that genetic variation in the HOPX-regulome is significantly associated with complex traits affecting cardiac structure and function. Collectively, this study provides a mechanistic link situating HOPX between competing upstream pathways where HOPX acts as a molecular switch controlling gene regulatory programs underpinning metabolic, signaling, and functional maturation of cardiomyocytes.

developmental biology↗

bioRxiv2017

Cardiac directed differentiation using small molecule Wnt modulation at single-cell resolution

Differentiation into diverse cell lineages requires the orchestration of gene regulatory networks guiding diverse cell fate choices. Utilizing human pluripotent stem cells, we measured expression dynamics of 17,718 genes from 43,168 cells across five time points over a thirty day time-course of in vitro cardiac-directed differentiation. Unsupervised clustering and lineage prediction algorithms were used to map fate choices and transcriptional networks underlying cardiac differentiation. We leveraged this resource to identify strategies for controlling in vitro differentiation as it occurs in vivo. HOPX, a non-DNA binding homeodomain protein essential for heart development in vivo was identified as dys-regulated in in vitro derived cardiomyocytes. Utilizing genetic gain and loss of function approaches, we dissect the transcriptional complexity of the HOPX locus and identify the requirement of hypertrophic signaling for HOPX transcription in hPSC-derived cardiomyocytes. This work provides a single cell dissection of the transcriptional landscape of cardiac differentiation for broad applications of stem cells in cardiovascular biology.

developmental biology↗

bioRxiv2017

Determining cell fate specification and genetic contribution to cardiac disease risk in hiPSC-derived cardiomyocytes at single cell resolution

The majority of genetic loci underlying common disease risk act through changing genome regulation, and are routinely linked to expression quantitative trait loci, where gene expression is measured using bulk populations of mature cells. A crucial step that is missing is evidence of variation in the expression of these genes as cells progress from a pluripotent to mature state. This is especially important for cardiovascular disease, as the majority of cardiac cells have limited properties for renewal postneonatal. To investigate the dynamic changes in gene expression across the cardiac lineage, we generated RNA-sequencing data captured from 43,168 single cells progressing through in vitro cardiac-directed differentiation from pluripotency. We developed a novel and generalized unsupervised cell clustering approach and a machine learning method for prediction of cell transition. Using these methods, we were able to reconstruct the cell fate choices as cells transition from a pluripotent state to mature cardiomyocytes, uncovering intermediate cell populations that do not progress to maturity, and distinct cell trajectories that terminate in cardiomyocytes that differ in their contractile forces. Second, we identify new gene markers that denote lineage specification and demonstrate a substantial increase in their utility for cell identification over current pluripotent and cardiogenic markers. By integrating results from analysis of the single cell lineage RNA-sequence data with population-based GWAS of cardiovascular disease and cardiac tissue eQTLs, we show that the pathogenicity of disease-associated genes is highly dynamic as cells transition across their developmental lineage, and exhibit variation between cell fate trajectories. Through the integration of single cell RNA-sequence data with population-scale genetic data we have identified genes significantly altered at cell specification events providing insights into a context-dependent role in cardiovascular disease risk. This study provides a valuable data resource focused on in vitro cardiomyocyte differentiation to understand cardiac disease coupled with new analytical methods with broad applications to single-cell data.

genomics↗