Clinical chemistry最新文献

Background: Polygenic risk scores (PRS) are measures of genetic susceptibility to human health traits. With the advent of large data repositories combining genetic data and phenotypic information, PRS are providing valuable insights into the genetic architecture of complex diseases and are transforming the landscape of precision medicine.

Content: PRS have emerged as tools with clinical utility in human disease. Herein, details on how to develop PRS are provided, followed by 5 areas in which they can be used to improve human health: (a) augmenting risk prediction, (b) refining diagnosis, (c) guiding treatment choices, (d) making clinical trials more efficient, and (e) improving public health. Finally, some of the ongoing challenges to the clinical implementation of PRS are noted.

Summary: PRS can offer valuable information for providers and patients, including identifying risk of disease earlier in life and before the onset of clinical risk factors, guiding treatment decisions, improving public health outcomes, and making clinical trials more efficient. The future of genomic-informed risk assessments of disease is through integrated risk models that combine genetic factors including PRS, monogenic, and somatic DNA information with nongenetic risk factors such as clinical risk estimators and multiomic data. However, adopting PRS in a clinical setting at scale faces some challenges, including cross-ancestry performance, standardization and calibration of risk models, downstream clinical decision-making from risk information, and seamless integration into existing health systems.

Background: Disease-causing copy-number variants (CNVs) often encompass contiguous genes and can be detected using chromosomal microarray analysis (CMA). Conversely, CNVs affecting single disease-causing genes have historically been challenging to detect due to their small sizes.

Methods: A custom comprehensive CMA (Baylor College of Medicine - BCM v11.2) containing 400k probes and featuring exonic coverage for >4200 known or candidate disease-causing genes was utilized for the detection of CNVs at single-exon resolution. CMA results across a consecutive clinical cohort of more than 13 000 patients referred for genetic investigation at Baylor Genetics were examined. The genomic characteristics of CNVs impacting single protein-coding genes were investigated.

Results: Pathogenic or likely pathogenic (P/LP) CNVs (n = 190) affecting single protein-coding genes were detected in 188 patients, accounting for 9.9% (188/1894) of patients with P/LP CMA findings. The P/LP monogenic CNVs accounted for 9.2% (190/2058) of all P/LP nuclear CNVs detected by CMA. A total of 57.9% (110/190) of P/LP monogenic CNVs were smaller than 50 kb in size. Single exons were affected by 26.3% (50/190) of P/LP monogenic CNVs while 13.2% (25/190) affected 2 exons. CNVs were detected across 107 unique genes associated with predominantly autosomal dominant (AD) and X-linked (XL) conditions but also contributed to autosomal recessive (AR) conditions.

Conclusions: CMA with exon-targeted coverage of disease-associated genes facilitated the detection of small CNVs affecting single protein-coding genes, adding substantial clinical sensitivity to comprehensive CNV investigation. This approach resolved monogenic CNVs associated with autosomal and X-linked monogenic etiologies and yielded multiple significant findings. Monogenic CNVs represent an underrecognized subset of disease-causing alleles for Mendelian disorders.

Pharmacogenomics (PGx) is focused on the relationship between an individual's genetic makeup and their response to medications, with the overarching aim of guiding prescribing decisions to improve drug efficacy and reduce adverse events. The PGx and genomic medicine communities have worked independently for over 2 decades, developing separate standards and terminology, making implementation of PGx across all areas of genomic medicine difficult. To address this issue, the Clinical Genome Resource (ClinGen) Pharmacogenomics Working Group (PGxWG) was established by the National Institutes of Health (NIH)-funded ClinGen to initially create frameworks for evaluating gene-drug response clinical validity and actionability aligned with the ClinGen frameworks for evaluating monogenic gene-disease relationships, and a framework for classifying germline PGx variants similar to the American College of Medical Genetics (ACMG) and Association of Molecular Pathology (AMP) system for interpretation of disease-causing variants. These frameworks will leverage decades of work from well-established PGx resources facilitating buy-in among PGx stakeholders. In this report, we describe the background and major activities of the ClinGen PGxWG, and how this initiative will facilitate the critical inclusion of PGx into the larger context of genomic medicine.

Background: Cell-free DNA (cfDNA) technology has allowed for cerebrospinal fluid (CSF), a previously underutilized biofluid, to be analyzed in new ways. The interrogation of CSF-derived cfDNA is giving rise to novel molecular insights, particularly in pediatric central nervous system (CNS) tumors, where invasive tumor tissue acquisition may be challenging. Contemporary disease monitoring is currently restricted to radiographic surveillance by magnetic resonance imaging and CSF cytology to directly detect abnormal cells and cell clusters. Alternatively, cfDNA is often present in the CSF from pediatric patients with both malignant and nonmalignant CNS tumors and can be accessed by minimally invasive lumbar puncture and other CSF-liberating procedures, offering a promising alternative for longitudinal molecular disease analysis and surveillance.

Content: This review explores the use of low-pass whole genome sequencing (LP-WGS) to analyze cfDNA from the CSF of pediatric patients with CNS tumors. This platform is uniquely poised for the detection of tumors harboring copy number variants, which are prevalent in this population. The utility and sensitivity of LP-WGS as a clinical tool is explored and discussed in the context of alternative CSF liquid biopsy interrogation modalities, including nanopore sequencing and methylation array.

Summary: Analysis of CSF-derived cfDNA by LP-WGS has broad diagnostic, prognostic, and clinical implications for pediatric patients with CNS tumors. Careful interpretation of LP-WGS results may aid in therapeutic targeting of pediatric CNS tumors and may provide insight into tumor heterogeneity and evolution over time, without the need for invasive and potentially risky tissue sampling.

Background: Mate-pair sequencing detects both balanced and unbalanced structural variants (SVs) and simultaneously informs in relation to both genomic location and orientation of SVs for enhanced variant classification and clinical interpretation, while chromosomal microarray analysis (CMA) only reports deletion/duplication. Herein, we evaluated its diagnostic utility in a prospective back-to-back prenatal comparative study with CMA.

Methods: From October 2021 to September 2023, 426 fetuses with ultrasound anomalies were prospectively recruited for mate-pair sequencing and CMA in parallel for prenatal genetic diagnosis. Balanced/unbalanced SVs and regions with absence of heterozygosity (AOH) were detected and classified independently, and comparisons were made between mate-pair sequencing and CMA to assess concordance. In addition, novel SVs were investigated for potential RNA perturbations using cultured cells, whenever available.

Results: Mate-pair sequencing and CMA successfully yielded results for all 426 fetuses without the need for cell culturing. In addition, mate-pair sequencing identified 19 cases with aneuploidies, 16 cases with pathogenic simple deletions/duplications, and 5 cases with pathogenic translocations/insertions, providing a 25% incremental diagnostic yield compared to CMA (9.4%, 40/426 vs 7.6%, 32/426). Furthermore, by identifying the location and orientation of SVs, mate-pair sequencing improved the variant interpretation and/or follow-up approach for 40.0% (12) of the 30 cases with likely clinically significant deletions/duplications reported by CMA. Lastly, both platforms reported 3 cases (3/426) with multiple regions of AOH likely attributable to parental consanguinity.

Conclusions: Mate-pair sequencing detects additional balanced/unbalanced SVs and improves variant interpretation in comparison to CMA, indicating its potential to serve as a comprehensive prenatal cytogenomic diagnostic method.

Background: Institutions of higher education (IHE) have been a focus of SARS-CoV-2 transmission studies but there is limited information on how viral diversity and transmission at IHE changed as the pandemic progressed.

Methods: Here we analyze 3606 viral genomes from unique COVID-19 episodes collected at a public university in Seattle, Washington from September 2020 to September 2022.

Results: Across the study period, we found evidence of frequent viral transmission among university affiliates with 60% (n = 2153) of viral genomes from campus specimens genetically identical to at least one other campus specimen. Moreover, viruses from students were observed in transmission clusters at a higher frequency than in the overall dataset while viruses from symptomatic infections were observed in transmission clusters at a lower frequency. Although only a small percentage of community viruses were identified as possible descendants of viruses isolated in university study specimens, phylodynamic modeling suggested a high rate of transmission events from campus into the local community, particularly during the 2021-2022 academic year.

Conclusions: We conclude that viral transmission was common within the university population throughout the study period but that not all university affiliates were equally likely to be involved. In addition, the transmission rate from campus into the surrounding community may have increased during the second year of the study, possibly due to return to in-person instruction.

Background: Genetic screening has advanced from prenatal cell-free DNA (cfDNA) screening for aneuploidies (cfDNA-ANP) to single-gene disorders (cfDNA-SGD). Clinical validation studies have been promising in pregnancies with anomalies but are limited in the general population.

Methods: Chart review and laboratory data identified pregnancies with cfDNA-SGD screening for 25 autosomal dominant conditions at our academic center. Screening was identified as routine by International Classification of Diseases (ICD) 10 codes and chart review. Ultrasound anomalies or known family history of a condition on the panel were excluded. Retrospective chart review investigated test concordance, outcomes, and phenotypes.

Results: cfDNA-SGD was completed for 3480/37 050 (9.4%) pregnancies, of which 2745 (78.9%) were for routine screening. Fourteen (0.51%, 14/2745) had high-risk results defined as pathogenic/likely pathogenic (P/LP) variants: 6 (0.22%) likely fetal variants, and 8 (0.29%) maternal variants with 50% risk for fetal inheritance. Diagnostic testing detected 6/6 fetal and 6/8 maternal cfDNA-SGD variants (2/8 pregnant individuals declined testing but had clinical features on physical exam). Variants were detected in 11/14 pregnancies/newborns and in 9/14 (64.3%) parents/gamete donors. There were no false positives identified by cfDNA-SGD; however, 2 variants were discrepantly classified between the cfDNA-SGD and diagnostic testing laboratories. All pregnancies had normal imaging and 9 had mild postnatal phenotypes. Three terminated pregnancy following diagnostic testing.

Conclusions: Our study demonstrated that 0.51% of routine cfDNA-SGD was high risk, prompting comprehensive evaluation for pregnancies and parents. Routine cfDNA-SGD allowed for early identification and intervention, but raises counseling challenges due to variable expressivity, limited genotype-phenotype correlations, and discrepant variant classification.