Variation of “single gene” measures from different assays by column or row position.

<p>The CT values for the randomly selected single gene MTHFR and the reference gene 36B4 by column are shown in (A) and (B) respectively. The variation of relative abundance of single gene MTHFR (measured as <i>MTHFR/36B4</i> ratio) by column and row is shown in (C) and (D) respectively.</p

Novel Luminex Assay for Telomere Repeat Mass Does Not Show Well Position Effects Like qPCR

<div><p>Telomere length is a potential biomarker of aging and risk for age-related diseases. For measurement of relative telomere repeat mass (TRM), qPCR is typically used primarily due to its low cost and low DNA input. But the position of the sample on a plate often impacts the qPCR-based TRM measurement. Recently we developed a novel, probe-based Luminex assay for TRM that requires ~50ng DNA and involves no DNA amplification. Here we report, for the first time, a comparison among TRM measurements obtained from (a) two singleplex qPCR assays (using two different primer sets), (b) a multiplex qPCR assay, and (c) our novel Luminex assay. Our comparison is focused on characterizing the effects of sample positioning on TRM measurement. For qPCR, DNA samples from two individuals (K and F) were placed in 48 wells of a 96-well plate. For each singleplex qPCR assay, we used two plates (one for Telomere and one for Reference gene). For the multiplex qPCR and the Luminex assay, the telomere and the reference genes were assayed from the same well. The coefficient of variation (CV) of the TRM for Luminex (7.2 to 8.4%) was consistently lower than singleplex qPCR (11.4 to 14.9%) and multiplex qPCR (19.7 to 24.3%). In all three qPCR assays the DNA samples in the left- and right-most columns showed significantly lower TRM than the samples towards the center, which was not the case for the Luminex assay (p = 0.83). For singleplex qPCR, 30.5% of the variation in TL was explained by column-to-column variation and 0.82 to 27.9% was explained by sample-to-sample variation. In contrast, only 5.8% of the variation in TRM for the Luminex assay was explained by column-to column variation and 50.4% was explained by sample-to-sample variation. Our novel Luminex assay for TRM had good precision and did not show the well position effects of the sample that were seen in all three of the qPCR assays that were tested.</p></div

PCR primers and thermocycling conditions.

<p>PCR primers and thermocycling conditions.</p

Variation of Telomere products by column.

<p>Column number is shown in x-axis and the quantity of Telomere product is shown in y-axis. CT-values of Telomere product (inversely proportional to PCR product quantity) from SP-qPCR-set1, SP-qPCR-set2 and MP-qPCR are shown in fig (A), (B) and (C) respectively. Quantity of Telomere product measured by Luminex assay is shown in (D).</p

Percentage of variation in the data that can be explained by variation in different factors.

<p>Percentage of variation in the data that can be explained by variation in different factors.</p

Datasheet1_Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record.docx

BackgroundSickle cell trait/disease (SCT/SCD) are enriched among Black people and associated with various comorbidities. The overrepresentation of these characteristics prevents traditional regression approach obtaining convincing evidence for the independent effect of SCT/SCD on other health outcomes. This study aims to investigate the association between SCT/SCD and COVID-19-related outcomes using causal inference approaches that balance the covariate.MethodsWe leveraged electronic health record (EHR) data from the University of Chicago Medicine between March 2020 and December 2021. Demographic characteristics were retrieved. Medical conditions were identified using ICD-10 codes. Five approaches, including two traditional regression approaches (unadjusted and adjusted) and three causal inference approaches [covariate balancing propensity score (CBPS) matching, CBPS weighting, and CBPS adjustment], were employed.ResultsA total of 112,334 patients were included in the study, among which 504 had SCT and 388 SCD. Patients with SCT/SCD were more likely to be non-Hispanic Black people, younger, female, non-smokers, and had a diagnosis of diabetes, heart failure, asthma, and cerebral infarction. Causal inference approaches achieved a balanced distribution of these covariates while traditional approaches failed. Across these approaches, SCD was consistently associated with COVID-19-related pneumonia (odds ratios (OR) estimates, 3.23 (95% CI: 2.13–4.89) to 2.57 (95% CI: 1.10–6.00)) and pain (OR estimates, 6.51 (95% CI: 4.68–9.06) to 2.47 (95% CI: 1.35–4.49)). While CBPS matching suggested an association between SCD and COVID-19-related acute respiratory distress syndrome (OR = 2.01, 95% CI: 0.97–4.17), this association was significant in other approaches (OR estimates, 2.96 (95% CI: 1.69–5.18) to 2.50 (95% CI: 1.43–4.37)). No association was observed between SCT and COVID-19-related outcomes in causal inference approaches.ConclusionUsing causal inference approaches, we provide comprehensive evidence for the link between SCT/SCD and COVID-19-related outcomes.</p

Genomic regions where the frequency of amplification or deletion is significantly different between MSI and MSS CRC samples.

<p>Amplification regions are shown in red; deletion regions are shown in blue; regions with no significant change are shown in green. Each column represents a single sample.</p

Common regions of amplification/deletion in this study and previous studies of other solid cancers.

<p>(a) Regions of amplification in our study (red circle) were also found in previous studies of other solid cancers (green circle); several are also known to be down-regulated by drugs that are approved or in development (blue circle). (b) Locations of the common regions of amplification in our study and previous studies of other solid cancers (intersection of red and green circles in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031968#pone-0031968-g013" target="_blank">Fig. 13a</a>) are shown. (c) Regions of deletion in our study (red circle) were also found in previous studies of other solid cancers (green circle); several are also known to be up-regulated by drugs that are approved or in development (blue circle). (d) Locations of the common regions of deletion in our study and previous studies of other solid cancers (intersection of red and green circles in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031968#pone-0031968-g013" target="_blank">Fig. 13d</a>) are shown.</p

Association of Chromosomal copy number changes with clinico-histopathological findings in MSI CRC cases (n = 24).

<p>*Copy number changes for some regions could not be analyzed for one sample.</p

Mosaic biallelic amplification in chromosome 8q for CRC tissue sample C1_T.

<p>BAF = 0.5 and CN = 2.6. Approximately 30% of cells have biallelic amplification (ABAB).</p