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Additional file 1. An additional table is available describing the variables and regression results included in each binary logistic regression model created for each survey question separated by imputed and complete case datasets. The file name is “BLR-Additional Table 1-BMC.xlsx” and it titled “Logistic Regression Models”.

Additional file 4: Table S3. A. Results for 34 independent ARIC Discovery Meta-Analysis identified mtDNA-CN associated CpGs across all studied cohorts and Validation Meta-Analysis/All Cohort Meta-Analysis. Validation meta-analysis included CHS AA, CHS EA and FHS EA cohorts (P

Additional file7: Table S18. DNAmeQTL analysis for the loci significantly associated with DNAme-based XCI status calls. See additional files. These loci were independently tested as DNAmeQTLs in females and males, with some columns color coded based on sex (pink female, light blue male). There are also columns with the median and mean DNAme value at the gene’s island for samples with the reference or alternate allele at that loci; these columns are color coded based on whether the allele is in the range to escape from XCI (DNAme<0.01, blue) or in the range to be subject to XCI (DNAme>0.15, orange). There are mean and median columns for both males and females, but only the female columns are color coded based on XCI status. There are boxes around the genes with female median values with one allele in the range to escape XCI and the other allele in the range to be subject to XCI.

Additional file 4. Individual data values.

Additional file 1. Appendix

Related Article: Sumanta Garai, Luciana M. Leo, Anna-Maria Szczesniak, Dow P. Hurst, Peter C. Schaffer, Ayat Zagzoog, Tallan Black, Jeffrey R. Deschamps, Elke Miess, Stefan Schulz, David R. Janero, Alex Straiker, Roger G. Pertwee, Mary E. Abood, Melanie E. M. Kelly, Patricia H. Reggio, Robert B. Laprairie, Ganesh A. Thakur|2021|J.Med.Chem.|64|8104|doi:10.1021/acs.jmedchem.1c00040

Additional file 6. Autocorrelation z scores between pairs of stimulated and unstimulated chromatograms.

Many roles of human platelets in health and disease are linked to their ability to transport and secrete a variety of small molecules and proteins carried in dense (δ-) and α-granules. Determination of granule number and content is important for diagnosis of platelet disorders and for studies of platelet structure, function, and development. We have optimized methods for detection and localization of platelet proteins via antibody and lectin staining, imaging via structured illumination laser fluorescence microscopy (SIM), and three-dimension (3D) image analysis. The methods were validated via comparison with published studies based on electron microscopy and high-resolution fluorescence microscopy. The α-granule cargo proteins thrombospondin-1 (TSP1), osteonectin (SPARC), fibrinogen (FGN), and Von Willebrand factor (VWF) were localized within the granule lumen, as was the proteoglycan serglycin (SRGN). Colocalization analysis indicates that staining with fluorescently labeled wheat germ agglutinin (WGA) allows detection of α-granules as effectively as immunostaining for cargo proteins, with the advantage of not requiring antibodies. RAB27B was observed to be concentrated at dense granules, allowing them to be counted via visual scoring and object analysis. We present a workflow for counting dense and α-granules via object analysis of 3D SIM images of platelets stained for RAB27B and with WGA. Abbreviation: SIM: structured illumination microscopy; WGA: wheat germ agglutinin; FGN: fibrinogen; TSP1: thrombospondin 1; ER: endoplasmic reticulum Platelets support blood clotting, wound healing, and other essential processes. These functions rely on the ability of platelets to transport and release small molecules like serotonin carried in dense granules and a wide range of proteins carried in alpha granules. Several conditions have been linked to abnormalities in one or more of platelet granule number, content, structure, and function. These conditions can be difficult to diagnose because platelet granules are so small they cannot be consistently resolved by conventional light microscopy, while higher power electron microscopy is not widely accessible. The goal of this study was to develop a method for counting and examining platelet dense and alpha granules without the need of electron microscopy. Key to this was the discovery that alpha granules can be reliably stained with the plant lectin wheat germ agglutinin, which has the advantages of being a smaller and less expensive molecule than the antibodies commonly used to detect alpha granule cargo proteins. We also establish that dense granules can be detected with high specificity via antibody staining of the membrane-associated protein RAB27B. We used structured illumination laser fluorescence microscopy to obtain high-resolution images of stained platelets. These were assembled into 3D renders using image analysis software, which was used to validate a protocol for rapidly counting granules within individual platelets. Our method supports the relatively rapid, accurate, and cost-effective assessment of platelet granules. We have already shown that it can confirm dense granule deficiency, and we anticipate that this approach will also prove useful in diagnosing and studying alpha granule abnormalities.