Baheti, Saurabh

ABSTRACT Background Eosinophilic esophagitis is associated with epithelial barrier dysfunction. Epidemiologic studies suggest environmental factors promote disease pathogenesis. The common household detergent sodium dodecyl sulfate (SDS) induces epithelial barrier dysfunction and eosinophilic inflammation in mice. We hypothesized that acute SDS exposure would compromise the esophageal mucosal barrier in humans. Methods Healthy adults brushed with 2 g of an SDS‐containing toothpaste. Esophageal impedance was measured continuously pre‐/post‐toothbrushing to assess the effect of toothpaste on epithelial barrier function. SDS was measured in saliva using a methylene blue anionic substances assay. Participants completed 1‐h esophageal string tests (ESTs) pre‐/post‐toothbrushing and protein isolates from EST eluates from the proximal and distal esophagus were analyzed by tandem mass tag mass spectrometry. Results Ten of twelve subjects completed the clinical study. SDS in the initial expectorate measured immediately after toothbrushing varied markedly (median: 321.40 μg/mL; range: 169.90–1243.00 μg/mL) and was detectable in saliva in 80% of subjects (median: 9.55 μg/mL; range: 0–123.40 μg/mL) at 60 min post toothbrushing. Esophageal mucosal impedance decreased within 30 min of toothbrushing ( p < 0.01). Toothbrushing increased salivary viscosity and proteins associated with mucosal defense in EST eluates. The tight junction pathway was downregulated while the salivary secretion and complement and coagulation cascades pathways were upregulated in the proximal esophagus. Conclusion In healthy individuals, SDS remained detectable in saliva for a prolonged period after toothbrushing at concentrations previously shown to disrupt esophageal epithelial barrier function in vitro. Toothbrushing with an SDS‐containing toothpaste was associated with reduced esophageal mucosal impedance, altered salivary properties, and activated mucosal immune responses.

Abstract BACKGROUND: Anthracycline chemotherapy-related cardiomyopathy (CCM) is a serious adverse event that can occur several years after completion of breast cancer (BC) therapy. Demographic and clinical risk factors have failed to predict which patients will experience CCM. Genetic variants can account for a significant proportion of inter-individual variation. Knowledge of genetic risk variants prior to chemotherapy will be informative for risk stratification and early intervention. The goal of our study is to identify genetic variants that predispose patients to CCM. Methods: We developed a cardiotoxicity registry at Mayo Clinic, Florida that enrolls patients who are to undergo standard of care chemotherapy in the early BC setting. Patients were (and continue to be) enrolled and consented for chart review and DNA sequencing. We sequenced whole exomes of the first 136 patients (anthracycline N=55, anti-HER2 (no anthracycline) N=71, other chemotherapy, N=10), primarily focusing on Titin (TTN) truncating variants, known to be present in ∼25% of patients with primary dilated cardiomyopathy, and previously reported in 7.5% of patients with CCM, followed by exploration of increased burden of rare non-synonymous variants in 60 established genes for primary cardiomyopathy. Filtering of rare non-synonymous variants included minor allele frequency &lt;0.5% (in GnomAD database European, African and Asian ancestries) and CADDv1.7 PHRED score ≥20. Results: 18/55 (33%) patients treated with anthracycline experienced CCM. TTN truncating variants in were identified in 2/18 (11%) CCM patients and absent in 37 patients who did not experience CCM. Both patients with TTN variants had severe HF and required cardiac transplant. We identified a pathogenic variant in LMNA (p.Arg190Gln) in 1/18 (5.5%) patients and the same rare (p.Glu1127Gly) variant in RYR2 occurred in 2/18 (11%) of patients (Table 1). We noted enrichment of rare missense variants in anthracycline CCM patients compared to HER2 treated without anthracycline, CCM, p=0.0001. Conclusions: Pathogenic variants in TTN, LMNA, are enriched in BC patients (17%) who develop anthracycline-related cardiomyopathy. Early genetic screening may improve risk stratification and guide personalized cardiac monitoring to prevent CCM. Further research is needed to clarify the role of additional rare variants like RYR2 and to develop a CCM risk score based in idiopathic CM genes. Incorporating genetic risk assessments into treatment planning has the potential to enhance oncologic outcomes as well as long-term survivorship by preserving cardiac health. Citation Format: P. P. Advani, A. McPherson, J. Reddy, J. Schneider, S. Baheti, T. Nguyen, J. C. Ray, N. Norton. Genomic Insights into Anthracycline Cardiotoxicity: Enhancing Survivorship Care through Early Risk Identification [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-01-22.

Abstract Clonal hematopoiesis (CH) of indeterminate potential (CHIP), driven by somatic mutations in leukemia-associated genes, confers increased risk of hematologic malignancies, cardiovascular disease, and all-cause mortality. In blood of healthy individuals, small CH clones can expand over time to reach 2% variant allele frequency (VAF), the current threshold for CHIP. Nevertheless, reliable detection of low-VAF CHIP mutations is challenging, often relying on deep targeted sequencing. Here, we present UNISOM, a streamlined workflow for enhancing CHIP detection from whole-genome and whole-exome sequencing data that are underpowered, especially for low VAFs. UNISOM utilizes a meta-caller for variant detection, in couple with machine learning models which classify variants into CHIP, germline, and artifact. In whole-exome sequencing data, UNISOM recovered nearly 80% of the CHIP mutations identified via deep targeted sequencing in the same cohort. Applied to whole-genome sequencing data from Mayo Clinic Biobank, it recapitulated the patterns previously established in much larger cohorts, including the most frequently mutated CHIP genes and predominant mutation types and signatures, as well as strong associations of CHIP with age and smoking status. Notably, 30% of the identified CHIP mutations had &lt; 5% VAFs, demonstrating its high sensitivity toward small mutant clones. This workflow is applicable to CHIP screening in population genomic studies. The UNISOM pipeline is freely available at https://github.com/shulanmayo/UNISOM and https://ngdc.cncb.ac.cn/biocode/tool/7816.

AbstractBackgroundAlzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non‐Hispanic White (NHW) population. To address this, Accelerating Medicines Partnership in AD (AMP‐AD) aimed to promote inclusivity in multi‐omics AD research, to unravel unique molecular signatures and pathways. The study aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial groups.MethodDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (980 unique individuals), 322 were from African American donors, 214 from Latino Americans, 551 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG samples, 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag‐based mass spectrometry (TMT‐MS). Following quality control (QC), proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. Differential protein expression was conducted within and across races after adjusting for batch using regression‐analysis.ResultIn total, 9,180 proteins from the DLPFC, and 9,734 proteins from STG brain tissues were quantified by TMT‐MS. Further analysis identified approximately 3,000 differentially abundant proteins in AD brains compared to controls within race. The AD‐associated differentially abundant proteins were strongly correlated between DLPFC and STG regions and with CERAD and Braak. Protein levels of MAPT and APP demonstrated equivalent disease‐related elevations in both African American and NHW individuals with AD. Notably, after adjusting for AD, significant differences in protein levels were identified across race.ConclusionThe proteomics approach employed by AMP‐AD sheds light on the brain proteome in AD across diverse racial groups, emphasizing the importance of inclusive research in establishing robust and generalizable discoveries. The identified proteins here could underscore racial disparities beyond disease association, contributing to a more nuanced understanding of AD pathophysiology.

AbstractBackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative disorder with few therapies to treat, mitigate or prevent its onset. Understanding of this disease is predominantly based on research in non‐Hispanic Whites (NHW) although AD disproportionately affects African Americans (AA) and Latin Americans (LA), underrepresented in AD research. To address this knowledge gap, the Accelerating Medicine Partnership for Alzheimer’s Disease (AMP‐AD) Diversity Working Group was launched to generate multi‐omics data from post‐mortem brain tissue from donors of predominantly AA and LA descent. Here, we focus on genomic and transcriptomics measures, made available through the AD Knowledge Portal (ADKP).MethodBrain tissue from dorsolateral prefrontal cortex (DLPFC), caudate nucleus (CN), superior temporal gyrus (STG) and temporal pole (TP) regions of AA (N = 299), LA (N = 344) and NHW (N = 532) donors was obtained through Mayo Clinic, Mt. Sinai School of Medicine, Emory, Columbia, Rush Alzheimer’s Disease Center, Banner Sun Health, and 1Florida. DNA extracted from DLPFC tissue samples (n = 641) was utilized for whole genome sequencing (WGS) at New York Genome Center (NYGC). RNAseq of 2,224 samples was conducted either at Mayo, Rush or NYGC. Sequencing reads were processed through GenomeGPS and MAPRseq pipelines for WGS and RNAseq data, respectively. Following quality control (QC), RNAseq data was normalized and assessed for sources of variation (SOV). Integration of WGS and RNAseq data to perform comparative eQTL analysis across multi‐ethnic populations and brain regions is ongoing.ResultWGS data for 621 donors, and RNAseq data generated at Mayo (n = 1,136 samples), Rush (n = 627), and NYGC (n = 779) sequencing centers, were deposited to the ADKP. Consensus processing of RNAseq data revealed site, sex, race/ethnicity, RIN, AD diagnosis, age at death and/or library batch as SOV across various sites and brain regions. Principal component analysis of gene expression measures revealed no major stratification by disease or brain region. Accompanying clinical metadata of donors have been distributed through ADKP.ConclusionThese multi‐omics data made available to the research community is expected to be an initial step towards bridging our data and knowledge gap to elucidate conserved and distinct AD related pathways across these underrepresented at‐risk populations.

Abstract INTRODUCTION Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non‐Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups. METHODS Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis. Among 998 unique donors, 273 donors self‐identified as African American, 229 as Latino American, and 434 as NHW. RESULTS While amyloid precursor protein and the microtubule‐associated protein tau demonstrated higher abundance in AD brains, no significant race‐related differences were observed. Further proteome‐wide and focused analyses (specific amyloid beta [Aβ] species and the tau domains) supported the absence of racial differences in these AD pathologies within the brain proteome. DISCUSSION Our findings indicate that the racial differences in AD risk and clinical presentation are not underpinned by dramatically divergent patterns in the brain proteome, suggesting that other determinants account for these clinical disparities. Highlights We present a large‐scale proteome (∼10,000 proteins) of DLPFC (998) and STG (244) across AD cases. About 50% of samples were from racially and ethnically diverse brain donors. Key AD proteins (amyloid and tau) correlated with CERAD and Braak stages. No significant race‐related differences in amyloid and tau protein levels were observed in AD brains. AD‐associated protein changes showed a strong correlation between the brain proteomes of African American and White individuals. This dataset advances understanding of ethnoracial‐specific AD pathways and potential therapies.

Abstract Introduction: Screening for prostate cancer (PCa) with molecular markers is hindered by low tumor allele fraction (TAF) in liquid biopsy samples such as blood or urine. Others have suggested that tumor allele enrichment can be achieved by evaluating fragment-level methylation patterns generated by next generation sequencing (NGS). Here, we test this concept using target capture NGS on cfDNA from prediagnostic collected urine samples to discriminate PCa from otherwise healthy men. Methods: Buffered urines were collected from 23 patients with biopsy confirmed PCa (Gleason score 6-9) and 24 otherwise healthy age matched cancer-free controls. cfDNA was isolated and enzymatic methyl-seq libraries were prepared and enriched by hybrid capture using probes mapping to 197 differentially methylated regions (DMRs) from a previous PCa/normal tissue marker discovery study in our lab. These DMRs were subsequently vetted independently using a methylome-wide dataset from a cohort of 36 clean and disease control urines to ensure low non-cancer background signal (&lt;1%). Indexed libraries were sequenced at 560X deduplicated coverage and fragment-level CpG methylation information was extracted from individual sample .bam files. Mapped sequencing reads exhibiting concordant methylation were used to derive a quantitative α-score. Reads had to contain at minimum 5 CpGs and have an α-value (% 5mC per read) &gt; 60%. Positivity for the 197 markers required an α-score greater than 6 sigma (σ) above the mean of the control arm. Values were variance-adjusted to ensure equal weighting. Beta (β) analysis (mean % 5mC across all reads) of the data was also performed for comparison. Results: Of the 197 markers, 187 were positive for one or more PCa patients. Tumor-derived fragments were detected in 22 of 23 cases, which included 8 G-6, 9 G-7, 2 G-8, and 3 G-9 patients. 1 G-7 was missed, however the sequencing coverage for this sample was significantly lower than the others due to poor library enrichment. 2 of the 24 healthy controls were positive, one with extremely high fragment counts. Upon re-review of the full control cohort, this patient had been diagnosed with bladder cancer 2 years after urine collection. The 2nd patient had was diagnosed with lung cancer in a similar timeframe. The other 22 confirmed cancer-free controls had α-scores below the 6σ threshold. Using a co-captured reference gene (B3GALT6) to mimic genomic equivalents, the TAFs ranged from 0.015% to 8%. β analysis of the data detected only 13 PCa patients (&gt;6σ) and marker positivity was lower than the fragment-level approach. Conclusion: Target capture NGS coupled with fragment-level analysis is a rational approach for sensitive and specific detection of low tumor-derived DNA in liquid biopsy samples. For PCa assay in urine, we were able to uncover positivity in cancer patients approaching 1 in 10,000 ctDNA dilution levels. These results warrant further validation studies with this and other cancers. Citation Format: Tibor Bedekovics, William R. Taylor, Zhifu Sun, Saurabh Baheti, Xiaoming Cao, Kelli N. Burger, Karen A. Doering, Patrick H. Foote, Benjamin Gochanour, Douglas, W. Mahoney, Matthew T. Gettman, John B. Kisiel. Detection of prostate cancer in urine by fragment-level DNA methylation analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2424.