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Non-Peer Reviewe

Die klinische Diagnose des Noonan-Syndroms:eine Querschnittsuntersuchung zur Extraktion der relevantesten klinischen Merkmale mittels logistischer Regressionsanalyse

Das Noonan-Syndrom (NS) ist ein autosomal-dominanter Symptomkomplex, der durch variable Ausprägungen vielfältiger Merkmale charakterisiert ist. In 30-50% liegt eine Mutation im PTPN11 Gen vor, sodass die Diagnose eines NS anhand klinischer Merkmale gestellt wird. Mittels binärer logistischer Regression wurden aus der Vielzahl der Merkmale die relevantesten Items extrahiert: sichtbares/tastbares Pterygium colli, Herzfehler, Thoraxdeformität, weiter Mamillenabstand, antimongoloide Lidachse, Ptosis, Mikro-/Retrogenie und tiefer/inverser Haaransatz. Mit diesen Informationen gelang es ein Modell zu entwickeln, anhand dessen die Wahrscheinlichkeit für das Vorliegen eines NS für jede untersuchte Person berechnet werden kann. Es gelang eine nahezu 100% richtige Unterscheidung von Personen mit und ohne NS. Weitere Untersuchungen werden zeigen, ob unser Modell Patienten mit NS in der Normalbevölkerung detektieren kann und wie weit eine Unterscheidung von ähnlichen Syndromen gelingt

Weekly Paclitaxel plus Capecitabine versus Docetaxel Every 3 Weeks plus Capecitabine in Metastatic Breast Cancer

Background. We performed a randomized phase II study comparing efficacy and toxicity of weekly paclitaxel 80 mg/m2 (Weetax) with three weekly docetaxel 75 mg/m2 (Threetax), both in combination with oral capecitabine 1000 mg/m2 twice daily for 2 weeks followed by a 1-week break. Patients. Thirty-seven women with confirmed metastatic breast cancer were randomized. Results. Median TTF was 174 (Weetax) versus 147 days (Threetax) (=0.472). Median OS was 933 (Weetax) versus 464 days (Threetax) (=0.191). Reasons for TTF were PD 8/18 (Weetax), 9/19 (Threetax); and toxicity: 8/18 (Weetax), 8/19 (Threetax). ORR was 72% (Weetax) versus 26% (Threetax) (=0.01). The Threetax-combination resulted in a higher incidence of leuco-/neutropenia compared to Weetax. Grade II anemia was more pronounced in the Weetax group. No difference was found in quality of life. Conclusion. Taxanes in combination with capecitabine resulted in a high level of toxicity. Taxanes and capecitabine should be considered given sequentially and not in combination

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum

A JEDI NMR pulse experiment incorporating relaxational, diffusional and J-modulation peak editing has been implemented for a low field (80 MHz proton resonance frequency) spectrometer system to measure quantitatively two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation. JEDI spectra capture a unique signature of two biomarker signals from acetylated glycoproteins (Glyc) and the supramolecular phospholipid composite (SPC) signals that are relatively enhanced by the combination of relaxation, diffusion and J-editing properties of the JEDI experiment that strongly attenuate contributions from the other molecular species in plasma. The SPC/Glyc ratio data were essentially identical in the 600 MHz and 80 MHz spectra obtained (R2 = 0.97) and showed significantly different ratios for control (n = 28) versus SARS-CoV-2 positive patients (n = 29) (p = 5.2 × 10−8 and 3.7 × 10−8 respectively). Simplification of the sample preparation allows for data acquisition in a similar time frame to high field machines (∼4 min) and a high-throughput version with 1 min experiment time could be feasible. These data show that these newly discovered inflammatory biomarkers can be measured effectively on low field NMR instruments that do not not require housing in a complex laboratory environment, thus lowering the barrier to clinical translation of this diagnostic technology

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum.

A JEDI NMR pulse experiment incorporating relaxational, diffusional and J-modulation peak editing has been implemented for a low field (80 MHz proton resonance frequency) spectrometer system to measure quantitatively two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation. JEDI spectra capture a unique signature of two biomarker signals from acetylated glycoproteins (Glyc) and the supramolecular phospholipid composite (SPC) signals that are relatively enhanced by the combination of relaxation, diffusion and J-editing properties of the JEDI experiment that strongly attenuate contributions from the other molecular species in plasma. The SPC/Glyc ratio data were essentially identical in the 600 MHz and 80 MHz spectra obtained (R2 = 0.97) and showed significantly different ratios for control (n = 28) versus SARS-CoV-2 positive patients (n = 29) (p = 5.2 × 10-8 and 3.7 × 10-8 respectively). Simplification of the sample preparation allows for data acquisition in a similar time frame to high field machines (∼4 min) and a high-throughput version with 1 min experiment time could be feasible. These data show that these newly discovered inflammatory biomarkers can be measured effectively on low field NMR instruments that do not not require housing in a complex laboratory environment, thus lowering the barrier to clinical translation of this diagnostic technology

Polymorphisms in the estrogen receptor alpha gene (ESR1), daily cycling estrogen and mammographic density phenotypes

Background Single nucleotide polymorphisms (SNPs) involved in the estrogen pathway and SNPs in the estrogen receptor alpha gene (ESR1 6q25) have been linked to breast cancer development, and mammographic density is an established breast cancer risk factor. Whether there is an association between daily estradiol levels, SNPs in ESR1 and premenopausal mammographic density phenotypes is unknown. Methods We assessed estradiol in daily saliva samples throughout an entire menstrual cycle in 202 healthy premenopausal women in the Norwegian Energy Balance and Breast Cancer Aspects I study. DNA was genotyped using the Illumina Golden Gate platform. Mammograms were taken between days 7 and 12 of the menstrual cycle, and digitized mammographic density was assessed using a computer-assisted method (Madena). Multivariable regression models were used to study the association between SNPs in ESR1, premenopausal mammographic density phenotypes and daily cycling estradiol. Results We observed inverse linear associations between the minor alleles of eight measured SNPs (rs3020364, rs2474148, rs12154178, rs2347867, rs6927072, rs2982712, rs3020407, rs9322335) and percent mammographic density (p-values: 0.002–0.026), these associations were strongest in lean women (BMI, ≤23.6 kg/m2.). The odds of above-median percent mammographic density (>28.5 %) among women with major homozygous genotypes were 3–6 times higher than those of women with minor homozygous genotypes in seven SNPs. Women with rs3020364 major homozygous genotype had an OR of 6.46 for above-median percent mammographic density (OR: 6.46; 95 % Confidence Interval 1.61, 25.94) when compared to women with the minor homozygous genotype. These associations were not observed in relation to absolute mammographic density. No associations between SNPs and daily cycling estradiol were observed. However, we suggest, based on results of borderline significance (p values: 0.025–0.079) that the level of 17β-estradiol for women with the minor genotype for rs3020364, rs24744148 and rs2982712 were lower throughout the cycle in women with low (28.5 %) percent mammographic density, when compared to women with the major genotype. Conclusion Our results support an association between eight selected SNPs in the ESR1 gene and percent mammographic density. The results need to be confirmed in larger studies

17β-Estradiol Levels During An Entire Menstrual Cycle In Response To Adult Stature and Insulin, Of Possible Importance For Breast Cancer Risk: The EBBA-I study.

Background: The normal breast cells develop into malignant cells as a result of a complex interplay between genetic, environmental, nutritional and hormonal factors. Attained adult stature and insulin levels, risk factors for breast cancer, may also vary in response to the same factors. Thus, we hypothesize that 17β-estradiol, a key factor in the carcinogenesis of the breast, may vary in response to adult height in combination with insulin levels of possible importance of breast cancer risk. Methods: Among 204 healthy women, aged 25-35 years who participated in the Norwegian EBBA-I study, 17β-estradiol concentrations were measured in daily saliva samples throughout one entire menstrual cycle using radioimmunoassay (RIA). Attained height (cm) was measured, and serum concentrations of insulin were determined in fasting blood samples. The associations between adult height, insulin and 17β-estradiol levels throughout a menstrual cycle were studied using multivariate linear regression analyses and linear mixed models for repeated measures. Adjustments for potential confounding factors were performed. Results: A 37.2 % increase in 17β-estradiol levels was observed during the entire menstrual cycle among women with an adult height ≥170 cm (upper tertile) and insulin levels ≥ 90 pmol/L (upper tertile) compared to women with the same attained adult height, and insulin levels < 90pmol/L. The association was even more pronounced when we looked into those women with attained adult height ≥170 cm (upper tertile) and serum insulin ≥ 101 pmol/L (upper quartile) (Fig. 1). Adjustments for potential confounding factors were performed. Conclusion: Our findings support that premenopausal levels of 17β-estradiol vary in response to adult height and insulin levels, suggesting that women who become taller are put at risk for higher estradiol levels throughout the entire menstrual cycle when their insulin levels rise, of possible importance for breast cancer risk.AnthropologyHuman Evolutionary Biolog

Altered dietary behaviour during pregnancy impacts systemic metabolic phenotypes

RationaleEvidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers.MethodsFrom the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated.ResultsThere were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p &lt; 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group.ConclusionMetabolic phenotypes of pregnant women who had a high alignment with the MD were significantly different from pregnant women who had a poor alignment with the MD. The metabolite profiles aligned with reported food intake. Differences were most significant biomarkers of systemic inflammation and selected gut-microbial metabolites. This research expands our understanding of the mechanisms driving health outcomes during the perinatal period and provides additional biomarkers for investigation in pregnant women to assess potential health risks