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Huuki-Myers LA, Montgomery KD, Kwon SH, Cinquemani S, Eagles NJ, Gonzalez-Padilla D, Maden SK, Kleinman JE, Hyde TM, Hicks SC, Maynard KR, Collado-Torres L. Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex. bioRxiv 2024:2024.02.09.579665. [PMID: 38405805 PMCID: PMC10888823 DOI: 10.1101/2024.02.09.579665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Background Cellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets. Results A rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements. Conclusions Bisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.
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Affiliation(s)
- Louise A. Huuki-Myers
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Kelsey D. Montgomery
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Sophia Cinquemani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Nicholas J. Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | | | - Sean K. Maden
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Joel E. Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Thomas M. Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Stephanie C. Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Kristen R. Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Leonardo Collado-Torres
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, 21205, USA
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Tarabini M, Mauri N, Gaudio I, Cinquemani S, Moorhead A, Bongiovanni R, Feletti F. Hand-arm vibration in motocross:measurement and mitigation actions. Muscles Ligaments Tendons J 2020. [DOI: 10.32098/mltj.02.2020.13] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- M. Tarabini
- Department of Mechanical Engineering, Politecnico di Milano University, Milan, Italy
| | - N. Mauri
- School of Mechanical Engineering, Politecnico di Milano University, Milan, Italy
| | - I. Gaudio
- School of Mechanical Engineering, Politecnico di Milano University, Milan, Italy
| | - S. Cinquemani
- Department of Mechanical Engineering, Politecnico di Milano University, Milan, Italy
| | - A.P. Moorhead
- Department of Mechanical Engineering, Politecnico di Milano University, Milan, Italy
| | - R. Bongiovanni
- KITE s.r.l Centre Engineer, Mandello del Lario, Lecco, Italy
| | - F. Feletti
- Department of Diagnostic Imaging, Ausl Romagna, S. Maria delle Croci Hospital, Ravenna, Italy
- Department of Electronics Information and Bioengineering, Politecnico di Milano University, Milan, Italy
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D'Este D, Giada F, Sartori F, Noventa D, Cinquemani S, Mantovan R, Pascotto P. [The effects of enalapril on basal arterial pressure at rest and during exercise and on cardiac performance in hypertensive athletes]. G Ital Cardiol 1990; 20:935-9. [PMID: 2090533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A dose of 10 mg of enalapril was administered once a day to regularly trained hypertensive athletes (mean age 39 +/- 8.9 range 29-51) in order to evaluate the effect of the drug on ambulatory blood pressure and on blood pressure and physical performance during stress testing. STUDY DESIGN. This investigation was a randomized, double blind, cross-over versus placebo trial. At first, subjects whose blood pressure met the entry criteria (casual diastolic blood pressure greater than or equal to 95 mmHg), were subjected to 24-hour ambulatory blood pressure monitoring and maximal upright bicycle stress testing including measurement of O2 uptake. Then they were randomly assigned to treatment with placebo or enalapril. After one month they repeated stress testing and then they were crossed over. Stress testing was repeated in all subjects after two months. The 24-hour ambulatory blood pressure monitoring was repeated in all subjects during enalapril treatment only, by a non-blind investigator. RESULTS. Ambulatory blood pressure decreased significantly during enalapril and no changes in heart rate were observed during the monitoring. The results of bicycle stress testing, both in basal and during the placebo test were comparable as regards blood pressure response, maximal workload, effort duration, maximal heart rate and VO2 max. With enalapril systolic and diastolic blood pressure decreased significantly during stress testing both versus basal test and placebo test at each workload considered including maximal workload. No changes were observed during enalapril as regards maximal workload, effort duration, maximal heart rate and VO2 max. CONCLUSION. Our results suggest that enalapril could be effective in treating hypertensive athletes because it reduces blood pressure during physical effort without affecting physical performance. We conclude that enalapril could be considered a first-choice drug in hypertensive athletes doing aerobic sports.
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Affiliation(s)
- D D'Este
- Servizio di Cardiologia, Ospedale Civile di Mirano
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