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Niall J Lennon

Publications and source records attributed to Niall J Lennon.

2 recordsLinked to original sources

Development and pilot testing of a prostate cancer polygenic risk report.

BACKGROUND: Polygenic risk scores (PRS) are increasingly being incorporated into clinical care, yet optimal strategies for communicating PRS results to patients and clinicians remain undefined. Effective report design is critical to ensure comprehension and appropriate use, particularly for complex conditions such as prostate cancer where screening decisions are nuanced. We developed and pilot tested patient-facing materials to communicate integrated polygenic and monogenic risk for prostate cancer in the context of a randomized clinical trial. METHODS: We designed a summary report and accompanying Frequently Asked Questions (FAQ) page to communicate prostate cancer genetic risk within the Prostate Cancer, Genetic Risk, and Equitable Screening Study (ProGRESS). Materials were developed through an iterative, multidisciplinary process informed by existing literature on genomic risk communication. We conducted semi-structured interviews with a national sample of eight men eligible for prostate cancer screening to evaluate comprehension, interpretation of visual elements, perceived usefulness, and preferences for improvement. Interviews were transcribed and analyzed using reflexive thematic analysis. RESULTS: Participants generally found the summary report and FAQ page understandable and visually engaging. Graphical displays of absolute risk, particularly pictograph arrays, facilitated comprehension and helped contextualize risk. Visual cues such as color and bold formatting effectively directed attention to key information, with red coloring perceived as particularly salient for high-risk results. In contrast, more complex visualizations, including bell curves and incidence curves, were frequently misunderstood or not interpreted as intended. Participants expressed a desire for clearer guidance regarding next steps and additional accessible information, suggesting supplementary resources such as hyperlinks or QR codes. Concerns about readability included small font size and high text density. CONCLUSIONS: In this qualitative pilot study, patient-facing materials for communicating prostate cancer PRS were generally well received, with specific design features such as simple visualizations and clear formatting enhancing understanding. Findings highlight the importance of intuitive risk displays and actionable guidance in PRS reporting. These results provide practical insights to inform the design of genomic risk reports as PRS-based prostate cancer screening approaches move toward clinical implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05926102; date of registry: July 3, 2023.

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Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.

Rare diseases collectively affect 1 in 10 individuals, yet current genetic testing fails to identify a causal variant for most cases. At present, cytogenetic methods and/or sequencing approaches such as exome (ES) or short-read genome sequencing (srGS) represent the state-of-the-art for comprehensive clinical discovery of sequence and structural variants (SVs), including copy number variants, balanced SVs, complex SVs, and tandem repeats (TRs). Recently, long-read genome sequencing (lrGS), coupled with multiomics data, has presented great promise to resolve variation in genomic regions recalcitrant to characterization by srGS such as highly repetitive simple repeat sequences and segmental duplications. However, there are few guidelines to enable clinical interpretation of genetic variation in these highly repetitive genomic regions, and the enthusiasm of the field in adopting lrGS has made it difficult to assess the true added diagnostic yield of this technology due to widely variable and inconsistently applied analytic pipelines and variable degrees of pre-screening by ES or srGS. Here, we investigated the contribution of SVs to rare diseases using srGS as a front-line strategy when paired with highly sensitive SV discovery and evaluate the added diagnostic yield of incorporating lrGS for a subset of cases. Our srGS analysis encompassed 1,462 families (3,450 individuals) recruited through the Broad Institute Center for Mendelian Genetics and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) programs. Diagnostic SVs were identified in 5.4% of cases (79/1,462), of which 80% were uniquely detectable by srGS compared to standard cytogenetic techniques. For 96 families (including 10 families with a heterozygous variant observed in a known recessive gene of clinical relevance), we performed lrGS with methylation profiling, as well as long-read transcriptomic analyses in a subset of 20 trios. Analyses with lrGS yielded over 25,000 SVs per genome, 63% of which were not captured by srGS, along with an additional ~200 rare SNV/indels per genome not previously captured and 12 differentially methylated regions per genome. Among these, we identified only one diagnostic variant not interpreted by srGS, an apparently mosaic de novo SNV in CASK that was absent in the srGS callset due to allelic imbalance. No new diagnoses were supported by long-read transcriptomics or episignatures. In this well characterized rare disease cohort, the added diagnostic yield was thus 1.04% (1/96 families). Following a systematic literature review of prior lrGS studies, we find that most reported diagnoses were detectable by srGS and that our added diagnostic yield is consistent with those prior studies. These studies emphasize the significant impact of comprehensive SV discovery in rare disease cases and further demonstrate the power for increased discovery of novel genomic variation and episignatures from lrGS. Nonetheless, they also serve to temper expectations of dramatic diagnostic advances in rare disease patients until there is more extensive annotation of the functional and clinical impact of all coding and noncoding variation uniquely accessible to lrGS with extensive reference databases spanning highly repetitive genomic sequencing that could be enabled by this transformative technology.

Journal Article