Neurofilament medium polypeptide (NFM) protein concentration is increased in CSF and serum samples from patients with brain injury.

BACKGROUND: Brain injury is a medical emergency that needs to be diagnosed and treated promptly. Several proteins have been studied as biomarkers of this medical condition. The aims of this study were to: 1) evaluate the selectivity and precision of a commercial ELISA kit for neurofilament medium polypeptide (NFM) protein; and 2) evaluate the concentration in cerebrospinal fluid (CSF) and serum of healthy individuals and patients with brain damage. METHODS: An ELISA from Elabscience was used. The selectivity was evaluated using size-exclusion chromatography and mass spectrometry. Intra- and inter-batch coefficients of variation (CV) were also studied. Fifty-one CSF samples from 36 age-matched patients with hemorrhagic stroke (HS) (n=30), ischemic stroke (IS) (n=11) and healthy individuals (n=10) were assayed. In addition, serum samples from healthy volunteers (n=47), 68 serum samples from seven patients with HS, 106 serum samples from 12 patients with traumatic brain injury (TBI) and 68 serum samples from 68 patients with mild traumatic brain injury (mTBI) were also analyzed. RESULTS: NFM was identified in the chromatographic fraction with highest immunoreactivity. The intra- and inter-batch CVs were ≤10% and ≤13%, respectively. The CSF-NFM concentration in HS was significantly higher (p<0.0001) than in IS and controls. Serum NFM concentration ranged from 0.26 to 8.57 ng/mL in healthy individuals (median=2.29), from 0.97 to 42.4 ng/mL in HS (median=10.8) and from 3.48 to 45.4 ng/mL in TBI (median=14.7). Finally, 44% of patients with mTBI had increased NFM concentration, with significantly higher levels (p=0.01) in patients with polytrauma. CONCLUSIONS: To our knowledge this is the first study describing increased NFM levels in CSF and serum from patients with brain damage.

Identification of host endotypes using peripheral blood transcriptomics in a prospective cohort of patients with endocarditis.

OBJECTIVES: Host responses to infection are a major determinant of outcome. However, the existence of different response profiles in patients with endocarditis has not been addressed. Our objective was to apply transcriptomics to identify endotypes in patients with infective endocarditis. METHODS: A total of 32 patients with infective endocarditis were studied. Clinical data and blood samples were collected at diagnosis and RNA sequenced. Gene expression was used to identify two clusters (endocarditis endotype 1 [EE1] and endocarditis endotype 2 [EE2]). RNA sequencing was repeated after surgery. Transcriptionally active cell populations were identified by deconvolution. Differences between endotypes in clinical data, survival, gene expression, and molecular pathways involved were assessed. The identified endotypes were recapitulated in a cohort of COVID-19 patients. RESULTS: A total of 18 and 14 patients were assigned to EE1 and EE2, respectively, with no differences in clinical data. Patients assigned to EE2 showed an enrichment in genes related to T-cell maturation and a decrease in the activation of the signal transducer and activator of transcription protein family pathway, with higher counts of active T cells and lower counts of neutrophils. A total of 14 patients (nine in EE1 and five in EE2) were submitted to surgery. Surgery in EE2 patients shifted gene expression toward a EE1-like profile. In-hospital mortality was higher in EE1 (56% vs 14%, P = 0.027), with an adjusted hazard ratio of 12.987 (95% confidence interval 3.356-50). Translation of these endotypes to COVID-19 and non-COVID-19 septic patients yielded similar results in cell populations and outcome. CONCLUSIONS: Gene expression reveals two endotypes in patients with acute endocarditis, with different underlying pathogenetic mechanisms, responses to surgery, and outcomes.

Evaluation of population parameters and mathematical strategies for the calculation of prenatal risk of Down syndrome in the first trimester of pregnancy.

OBJECTIVE: To evaluate the population parameters applied to the calculation of risk for Down syndrome (DS) in the first trimester screening (FTS) and the comparison of performance obtained including or excluding maternal age from the mathematical algorithm. METHODS: Three different calculation engines for prenatal risk of DS were developed on the basis of the population parameters from the Serum, Urine and Ultrasound Screening Study, the Fetal Medicine Foundation, and a combination of both of them. These calculators were evaluated in 14,645 first trimester pregnant women, including 59 DS affected fetuses, comparing their performance with that obtained by our commercial software Elipse® (Perkin Elmer Life and Analytical Sciences, Turku, Finland). Advanced first trimester screening (AFS) strategy was also analyzed, and a hybrid strategy (FTS + AFS) was evaluated. RESULTS: By selecting population parameters from the Serum, Urine and Ultrasound Screening Study, the detection rate increased from 76% (Elipse) to 86% with a small increase in the false positive rate (FPR), from 3.3% to 3.7%, respectively. DS screening performance significantly improved by using the hybrid strategy (AFS in pregnant women under 35 years and FTS in pregnant women over 35 years), with a 92% detection rate (FPR: 3.9%). CONCLUSIONS: In the present study, a new hybrid screening strategy has been proposed to achieve DS detection rates higher than 90%, for a convenient <4% FPR.

Non-invasive fetal RHD genotyping in the first trimester of pregnancy.

BACKGROUND: Hemolytic disease of the fetus and newborn (HDN) is caused primarily by feto-maternal RhD incompatibility. Although all RhD negative pregnant women undergo routine antenatal RhD prophylaxis at 28 weeks of gestation, and following delivery if the newborn is RhD positive, HDN has not been eradicated. Here, we investigated fetal Rhesus D (RHD) genotype in maternal plasma during the first trimester of pregnancy in our area. METHODS: Plasma samples were obtained from 111 RhD negative pregnant women, between 9 and 13 weeks of gestation. DNA from maternal plasma containing cell-free fetal DNA (cffDNA) was analyzed by quantitative PCR (qPCR) to detect RHD exons 5 and 7. A beta-globin (HBB) sequence was quantified to estimate total DNA concentration. qPCR results were compared with newborn RhD determined in cord blood serum. The influence of several gestational parameters on DNA concentration was also analyzed. RESULTS: The specificity and sensitivity of the assay was 93% and 100%, respectively, with 97% diagnostic accuracy. Cell-free DNA concentrations during the first trimester of pregnancy were not affected by the gestational parameters studied (free-beta fraction of human chorionic gonadotropin and pregnancy-associated plasma protein A concentrations, fetal sex, materno-fetal ABO blood group incompatibility, maternal weight and gestational age). CONCLUSIONS: Non-invasive fetal RHD genotyping during the first trimester of pregnancy can be determined with a high specificity, thus representing a valuable tool for improving the management of RhD negative pregnant women. As a high percentage of pregnant women participate in the routine first trimester combined screening program for aneuploidies, the fetal RHD study could be of immediate implementation, since the same blood collection could be used.