Biomedical subjects

Joseph L McClay

Publications and source records attributed to Joseph L McClay.

3 recordsLinked to original sources

PubMed2026

Epigenetic age acceleration is not strongly associated with cardiorespiratory fitness in heart failure: a pilot study.

BACKGROUND: In heart failure (HF), standard measures such as left ventricular ejection fraction and cardiopulmonary exercise testing incompletely capture interindividual differences in disease status or prognosis. DNA methylation (DNAm) epigenetic clocks, which estimate biological age and epigenetic age acceleration (EAA), may provide complementary insight into cardiorespiratory fitness and systemic aging in HF. RESEARCH DESIGN AND METHODS: We analyzed peripheral blood DNAm from fourteen patients enrolled in REDHART2, a clinical trial of interleukin-1 blockade following hospitalization for acute systolic HF. Genome-wide DNAm was assayed using Illumina EPIC arrays and several clocks were applied to these data. Associations between biological age or EAA and cardiorespiratory fitness measures, inflammatory markers, and clinical parameters were evaluated. RESULTS: All epigenetic clocks demonstrated moderate to strong correlations with chronological age. Biological age was consistently associated with measures of cardiorespiratory fitness, particularly oxygen consumption normalized to fat free mass (VO2_FFM). However, chronological age showed similar associations, and biological age did not significantly improve prediction of VO2 parameters beyond chronological age alone. EAA was not significantly associated with cardiorespiratory fitness for any clock. CONCLUSIONS: In this pilot study, neither biological age nor EAA provided significant predictive value beyond chronological age for cardiorespiratory fitness in patients with HF. CLINICAL TRIAL REGISTRATION NUMBER: NCT03797001.

DNA methylation↗

PubMed2026

Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches.

MOTIVATION: Short-read sequencing data can be affected by alignment artifacts in certain genomic regions. Removing reads overlapping these exclusion regions, previously known as Blacklists, help to potentially improve biological signal. Alternatively, "sponge" or decoy sequences have been proposed to reduce alignment artifacts. RESULTS: We examined the widely used Blacklist software and found that pre-generated exclusion sets were difficult to reproduce due to sensitivity to input data, aligner choice, and read length. We further explored the use of "sponge" sequences-unassembled genomic regions such as satellite DNA, ribosomal DNA, and mitochondrial DNA-as an alternative approach. We additionally investigated the effect of the T2T-CHM13 genome assembly on improving biological signals. Aligning reads to a genome that includes sponge sequences reduced signal correlation in ChIP-seq data comparably to Blacklist-derived exclusion sets while preserving biological signal. Sponge-based alignment also had minimal impact on RNA-seq gene counts, suggesting broader applicability beyond chromatin profiling. These results highlight the limitations of fixed exclusion sets, and recommend the use of the T2T-CHM13 assembly or, for the hg38 genome assembly, "sponge" sequences as an alignment-guided strategy for reducing artifacts and improving functional genomics analyses.

Software↗

PubMed2025

Beyond Blacklists: A Critical Assessment of Exclusion Set Generation Strategies and Alternative Approaches.

Short-read sequencing data can be affected by alignment artifacts in certain genomic regions. Removing reads overlapping these exclusion regions, previously known as Blacklists, help to potentially improve biological signal. Tools like the widely used Blacklist software facilitate this process, but their algorithmic details and parameter choices are not always clearly documented, affecting reproducibility and biological relevance. We examined the Blacklist software and found that pre-generated exclusion sets were difficult to reproduce due to variability in input data, aligner choice, and read length. We also identified and addressed a coding issue that led to over-annotation of high-signal regions. We further explored the use of "sponge" sequences-unassembled genomic regions such as satellite DNA, ribosomal DNA, and mitochondrial DNA-as an alternative approach. Aligning reads to a genome that includes sponge sequences reduced signal correlation in ChIP-seq data comparably to Blacklist-derived exclusion sets while preserving biological signal. Sponge-based alignment also had minimal impact on RNA-seq gene counts, suggesting broader applicability beyond chromatin profiling. These results highlight the limitations of fixed exclusion sets and suggest that sponge sequences offer a flexible, alignment-guided strategy for reducing artifacts and improving functional genomics analyses.

Journal Article↗