Biobank Samples Research Articles

P1007 Influence of pharmacokinetic-pharmacodynamic failure mechanisms on outcomes in biologic therapy sequencing in inflammatory bowel disease

Abstract Background Increasing therapeutic options for inflammatory bowel disease (IBD) calls for tools to aid choice of sequencing. We investigated if pharmacokinetic (PK) and pharmacodynamic (PD) failure mechanisms prompting therapy change influenced subsequent outcomes when switching to a different biologic drug class. Methods Retrospective cohort study at a tertiary, Danish IBD center including all patients treated with first TNF-inhibitors, followed by vedolizumab, and then ustekinumab, as defined by national treatment regulations at time of study. Clinical and objective disease remission were defined by validated indices (HBI, SCCAI, Mayo, SES-CD). Treatment failure was defined by the treating physician and supported by clinical disease activity scorings and objective disease activity evaluations. Drug trough levels and anti-drug antibodies were measured at manifest treatment failure in routinely collected biobanked samples. PK-PD failure was defined according to maintenance drug concentrations: infliximab 8.0 µg/mL, adalimumab 12.0, golimumab 1.4, vedolizumab 15. Primary treatment failure despite dose intensification was ascribed to PD. Primary endpoints were steroid-free treatment persistence and one-year remission. Results The study included 112 patients switching from TNF-inhibitors to vedolizumab (infliximab n=61, adalimumab n=32, golimumab n=16, certolizumab pegol n=3) and 31 subsequently to ustekinumab. Treatment persistence on vedolizumab did not differ between patients discontinuing TNF-inhibitors due to PK (n=28, 31%) or PD (n=63, 69%) (mean 989 days [554-1,424] vs. 951 [659-1,242], p=0.93). One-year steroid-free clinical and objective remission rates on VDZ were also comparable between PK-PD groups (29% vs 35%, p=0.63 and 35% vs. 43%, p=0.48, respectively). Furthermore, treatment persistence on ustekinumab was neither different between patients having initially discontinued TNF-inhibitors due to PK or PD (1,553 [997-2,110], n=11) vs. 1,200 [762-1,639], n=14; p=0.42), nor later discontinued vedolizumab due to PK or PD (1,305 [832-1,778], n=11 vs. 1,323 [785-1,862], n=15; p=0.43). Clinical and objective remission on ustekinumab was also similar between these groups. Sensitivity analysis using other thresholds to define PK or PD failure were congruent to the above findings. Sensitivity analyses with exclusion of primary non-responders and multivariate analyses correcting for potential confounders also supported the findings. Conclusion Our study does not show evidence for inferior outcomes during subsequent sequencing to biologics with different modes of action in patients switching due to PK failures as compared to those with PD failure. Choice of sequencing may thus take into account other aspects such as efficacy, safety and costs.

Prevalence and Significance of the Presence of Anti-transglutaminase and Anti-endomysium Antibodies in Patients with Early Inflammatory Joint Disease.

Celiac disease (CD) affects the small intestine, leading to a progressive disappearance of intestinal villi, and can be found in association with several other autoimmune and inflammatory conditions. The main objective of this study was to determine the prevalence and the clinical significance of anti-transglutaminase and anti-endomysium antibodies in patients diagnosed with early rheumatoid arthritis (RA) and spondyloarthritis (SpA). We measured anti-transglutaminase and anti-endomysium antibodies in biobanked serum samples at inclusion in two French prospective multicenter cohorts of patients with suspected early rheumatoid arthritis (ESPOIR, n = 713) and spondyloarthritis (DESIR, n = 709). Results were compared with the clinical, laboratory, and radiographic findings obtained in patients during a 10-year follow-up period. In the DESIR cohort, anti-transglutaminase antibodies were evidenced at low levels (less than three times the upper limit of normal) in 2/709 (0.42%) patients and anti-endomysium antibodies in 0/709 (0%). In the ESPOIR cohort, anti-transglutaminase antibodies were evidenced in 6/713 (0.84%) patients and anti-endomysium antibodies in 1/713 (0.14%). Only the latter patient was confirmed to have celiac disease. Interestingly, this patient was ultimately diagnosed with Sjögren's disease, an autoimmune condition known to be associated with an increased risk of celiac disease. The very low identified prevalence of anti-transglutaminase and anti-endomysium antibodies suggests a negligible risk of celiac disease in patients with early-stage RA or SpA, which are among the most common inflammatory rheumatic conditions. Consequently, routine screening for celiac disease via these antibodies in patients presenting with early inflammatory rheumatic conditions should not be performed except in case of clinical suspicion of celiac disease.

Factors Associated With Minority Patient Enrollment in a Gastric Cancer Biobank.

Human tissue samples are essential for translational cancer research. However, less than 20% of current biobank and genomic samples were obtained from minority patients, which may lead to biased understanding of cancer biology. The objective of this study was to identify factors associated with patient enrollment in our institution's gastric cancer biobank. Patients with suspected or confirmed gastric or gastroesophageal junction cancer undergoing surgical procedures at our institution were invited to enroll in a prospective gastric cancer biobank. We retrospectively reviewed patients who were invited to enroll from 2017 to 2023 at our safety-net and university hospitals. We compared patients who enrolled to those who declined to identify factors that predict enrollment. Hispanic patients had similar odds of enrollment as non-Hispanic White patients (odds ratio (OR): 1.22, 95% confidence interval (CI): 0.54-2.73, P=0.63). Non-Hispanic minorities (Black/African Americans and Asians) were less likely to enroll when compared to non-Hispanic Whites (OR: 0.41, 95% CI: 0.18-0.95, P=0.04). Minority patients treated at our safety-net hospital had higher odds of enrollment than those treated at our university hospital (OR: 2.62, 95% CI: 1.11-5.99, P=0.02). Efforts to improve diversity in biomedical research cannot consider minority patients as a monolithic cohort. Instead, targeted interventions that address diverse cultural concerns and improve access to enrollment at safety-net centers are requisite.

A scalable variational inference approach for increased mixed-model association power.

The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71% and 7.07% more than FastGWA. Quickdraws had costs comparable to REGENIE, FastGWA and SAIGE on the UK Biobank Research Analysis Platform service, while being substantially faster than BOLT-LMM. These results highlight the promise of leveraging machine learning techniques for scalable GWASs without sacrificing power or robustness.

A biobank resource for placental malaria and placental health research

Background Malaria during pregnancy is a serious threat to maternal and child health in malaria-endemic regions. Malaria during pregnancy often leads to placental malaria, which has severely detrimental effects on fetal outcomes, including fetal growth restriction, preterm delivery, and stillbirth. However, the mechanisms by which placental malaria causes adverse outcomes remain poorly understood. Crucially, there are no tools for detecting and/or intervening in placental malaria during pregnancy. This is mainly because the placenta is inaccessible to research during pregnancy. Nonetheless, its accessibility after delivery offers unique opportunities for studying placental diseases. To support such research, collecting and biobanking naturally-infected placental samples in the geographical context in which diseases of interest occur is crucial. Methods Here, we describe the establishment of a biobank of samples obtained from a malaria-endemic region of Kenya, which aims to enhance research capacity in this important but under-studied health challenge. Histology, PCR, and isothermal identical multirepeat sequence PCR were used to determine the placental malaria status of biobank samples. Results Our biobank characterization indicates that placental malaria affects most pregnancies in the malaria-endemic region, despite mothers being asymptomatic during pregnancy and having received anti-malaria chemoprophylaxis. Of the techniques used to detect placental malaria, isothermal identical multirepeat sequence PCR detected the highest number of placental malaria-positive samples (54.2%), compared with placental histology (37.3%), and placenta tissue PCR (17%). However, results from the various techniques did not overlap fully. Conclusion Our observations highlight the need to rigorously characterize placental samples from malaria-endemic regions, including by using multiple complementary techniques, even in cases of undetectable malaria during pregnancy. It may also be beneficial to obtain samples from non-malaria-endemic regions for use as placental malaria-naïve controls.

Geospatial distribution of Hepatitis E seroprevalence in Nepal, 2021.

Hepatitis E virus (HEV) causes acute jaundice and poses an important public health problem in low- and middle-income countries. Limited surveillance capacity and suboptimal access to diagnostics leads to under-reporting of HEV infections in affected countries, including Nepal. Serum antibodies against HEV are indicative of past infection. We analyzed existing samples from a nationally representative serosurvey to describe the geospatial distribution and factors associated with HEV seroprevalence in Nepal, as a proxy for infection. A nationally representative cross-sectional serosurvey of 3,922 individuals ≥2 years old from 975 households spread across 65 wards throughout Nepal was conducted between November 2021 and January 2022. Bio-banked samples were tested for anti-HEV IgG. Seroprevalence and its 95% confidence interval were estimated by age, sex, ecological region, municipality type, and other waterborne-disease related risk factors. Bayesian geostatistical models were fitted to observed seroprevalence data and used to generate high-resolution maps of seroprevalence across Nepal. Available samples from 3,707 participants were tested for anti-HEV IgG, and 3,703 were used for final analysis. We found 20.8% (95% CI: 19.5-22.2) of participants had evidence of prior HEV infection. HEV seroprevalence increased with age, and was higher in males (23.5%, 95% CI: 21.5-25.5) than in females (18.6%, 95% CI: 16.9-20.3). Seroprevalence in hilly (28.9%, 95% CI: 26.6-31.2) and mountain (24.6%, 95% CI: 18.8-30.5) regions were significantly higher than in terai (14.2%, 95% CI: 12.7-15.8). While there was no significant difference between urban and rural populations, the predicted seroprevalence was highest in Kathmandu, the capital of Nepal, reaching seroprevalence of 50% in some selected area. No statistically significant differences were found for wealth quintile, water source, and toilet facility. This study provides population-based serologic evidence that HEV is endemic in Nepal, with the greatest risk of infection in Kathmandu.

Ethical considerations for biobanks serving underrepresented populations.

Biobanks are essential biological database resources for the scientific community, enabling research on the molecular, cellular, and genetic basis of human disease. They are crucial for computational, data-driven biomedical research, which advances precision medicine and the development of targeted therapies. However, biobanks often lack racial and ethnic diversity, with many data sets predominantly comprising individuals of white, primarily northern European, ancestry. Establishing or enhancing biobanks for the inclusion of historically underrepresented populations requires meticulous ethical and social planning beyond logistical, legal, and economic considerations. This guide provides a roadmap for building and sustaining diverse biobanks, emphasizing ethical guidelines and cultural sensitivity. We highlight the importance of obtaining informed consent from donors, respecting their bodily autonomy, and the economic and research benefits of diverse biobanks to enable precision medicine, drug discovery, and industry-academic partnerships. Prioritizing key ethical and social considerations allows biobanks to advance scientific knowledge while upholding the rights and autonomy of underrepresented populations. Diversity in biobank sample collection enhances research outcomes by ensuring findings are representative and applicable to various human population groups, fostering trust, promoting inclusivity, and addressing health disparities while informing health policy. This is vital to ensuring biobanking efforts contribute meaningfully to the advancement of health equity.

Chemical exposomics in biobanked plasma samples and associations with breast cancer risk factors.

The chemical exposome includes exposure to numerous environmental and endogenous molecules, many of which have been linked to reproductive outcomes due to their endocrine-disrupting properties. As several breast cancer risk factors, including age and parity, are related to reproduction, it is imperative to investigate the interplay between such factors and the chemical exposome prior to conducting large scale exposome-basedbreast cancer studies. This pilot study aimed to provide an overview of the chemical exposome in plasma samples from healthy women and identify associations between environmental exposures and three risk factors for breast cancer: age, parity, and age at menarche. Plasma samples (n = 161), were selected based on reproductive history from 100 women participating in the Northern Sweden Health and Disease Study, between 1987 and 2006. Samples were analyzed by liquid chromatography high-resolution mass spectrometry (LC-HRMS) for 77 priority target analytes including contaminants and hormones, with simultaneous untargeted profiling of the chemical exposome and metabolome. Linear mixed effects models were applied to test associations between risk factors and chemical levels. Fifty-five target analytes were detected in at least one individual and over 94,000 untargeted features were detected across all samples. Among untargeted features, 430 could be annotated and were broadly classified as environmental (246), endogenous (167) or ambiguous (17). Applying mixed effect models to features detected in at least 70% of the samples (16,778), we found seven targeted analytes (including caffeine and various per- and poly-fluoroalkyl substances) and 38 untargeted features, positively associated with age. The directionality of these associations reversed for parity, decreasing with increasing births. Seven separate targeted analytes were associated with age at menarche. This study demonstrates how a comprehensive chemical exposome approach can be used to inform future research prioritization regarding associations between known and unknown substances, reproduction, and breast cancer risk. This study illustrates how chemical exposomics of long-term stored blood samples offers valuable insights to discover chemical exposures and their potential links to disease in humans, particularly those related to reproduction and breast cancer risk factors.

Importance of Human Faecal Biobanking: From Collection to Storage

Abstract The freezing and storage conditions of faecal samples in biobanks influence the preservation of the integrity and stability of genetic material and play a crucial role in scientific and clinical research quality. In recent years, there has been a particular increase in the number of studies related to the gut microbiome and the importance of its impact on the functioning human body. The review includes research on faecal microbiota transplantation (FMT), microbiome analysis, ‘-omics’ research, cancer and parasites. The primary topic addressed in this research is the impact of storage conditions and freezing methods for faecal samples on the stability and diversity of the gut microbiome. Standardizing procedures for storing and analyzing faecal samples is essential to carry out this task. This standardization is not a goal but a necessity for the quality control of the storage of faecal samples to reach comparative results and to develop new diagnostic methods. Collected data presented here highlight a crucial step in microbiota research concerning optimizing biobanking conditions for faecal samples.

Precision Medicine for Treating Alzheimer’s Disease in Down Syndrome

AbstractBackgroundIndividuals with Down Syndrome (DS) exhibit a genetic form of Alzheimer's disease (AD). In this study, we leveraged biobanked plasma samples from a completed clinical trial focused on anti‐inflammatory treatment, Vitamin E, for DS. The trial's primary endpoint was on cognition, and Vitamin E treatment was not found to be significantly beneficial. We examined whether applying precision medicine using an established proinflammatory endophenotype algorithm for AD therapy would reveal responders to anti‐inflammatory therapy as we have with other AD within the DS trial sample.MethodWe utilized biobanked plasma samples from the Phase 3 clinical trial titled "Vitamin E in Aged Persons with Down Syndrome (NCT00056329)." A pro‐inflammatory panel of proteins, including pre‐defined predictive protein and neuropathology markers, were assayed in baseline (n=138) and 36‐month (n=138) plasma samples. Response status was determined by evaluating the annual rate of change as measured by a combination of primary and secondary endpoints (BPT, VT, and BFDS). The predictive biomarker profile was established through SVM analyses to predict treatment response (yes/no) as the outcome variable.ResultPro‐inflammatory biomarkers IFN, IL10, IL12p70, 1L13, IL1B, IL2, IL4, IL6, IL8, and TNF𝛼 (along with APOE4 and demographic factors) were highly accurate in predicting the treatment responders with an AUC of 99.41%. Neuropathology markers, including Aβ40, Aβ42, Aβ42/Aβ40 ratio, NfL, GFAP, total tau, pTau181, and pTau231 with added demographic and APOE factors, predicted the responder status with an AUC of 73.98%. When the inflammatory and neuropathological data were combined into one algorithm, it produced an AUC of 97.35% (sensitivity of 81.69%, specificity of 100%) with an optimized cut‐off of 0.442 for distinguishing responder status.ConclusionOur findings confirmed the utility of our established AD pro‐inflammatory endophenotype for use in the DS population. We demonstrate that a protein algorithm encompassing markers related to inflammation and neuropathology can be used to generate a predictive biomarker endophenotype that can identify DS participants who are more likely to respond and benefit from anti‐inflammatory treatment. Our results demonstrate the feasibility of using precision medicine approaches for treating AD in DS. Our ongoing studies focus on understanding how these predictive algorithms relate to neuropathological progression in DS.

Image Quality Assessment and Reliability Analysis of Artificial Intelligence-Based Tumor Classification of Stimulated Raman Histology of Tumor Biobank Samples.

Stimulated Raman histology (SRH) is a label-free optical imaging method for rapid intraoperative analysis of fresh tissue samples. Analysis of SRH images using Convolutional Neural Networks (CNN) has shown promising results for predicting the main histopathological classes of neurooncological tumors. Due to the relatively low number of rare tumor representations in CNN training datasets, a valid prediction of rarer entities remains limited. To develop new reliable analysis tools, larger datasets and greater tumor variety are crucial. One way to accomplish this is through research biobanks storing frozen tumor tissue samples. However, there is currently no data available regarding the pertinency of previously frozen tissue samples for SRH analysis. The aim of this study was to assess image quality and perform a comparative reliability analysis of artificial intelligence-based tumor classification using SRH in fresh and frozen tissue samples. In a monocentric prospective study, tissue samples from 25 patients undergoing brain tumor resection were obtained. SRH was acquired in fresh and defrosted samples of the same specimen after varying storage durations at -80 °C. Image quality was rated by an experienced neuropathologist, and prediction of histopathological diagnosis was performed using two established CNNs. The image quality of SRH in fresh and defrosted tissue samples was high, with a mean image quality score of 1.96 (range 1-5) for both groups. CNN analysis showed high internal consistency for histo-(Cα 0.95) and molecular (Cα 0.83) pathological tumor classification. The results were confirmed using a dataset with samples from the local tumor biobank (Cα 0.91 and 0.53). Our results showed that SRH appears comparably reliable in fresh and frozen tissue samples, enabling the integration of tumor biobank specimens to potentially improve the diagnostic range and reliability of CNN prediction tools.

Preanalytical (Mis)Handling of Plasma Investigated by 1H NMR Metabolomics.

The preanalytical handling of plasma, how it is drawn, processed, and stored, influences its composition. Samples in biobanks often lack this information and, consequently, important information about their quality. Especially metabolite concentrations are affected by preanalytical handling, making conclusions from metabolomics studies particularly sensitive to misinterpretations. The perturbed metabolite profile, however, also offers an attractive choice for assessing the preanalytical history from the measured data. Here we show that it is possible using Orthogonal Projections to Latent Structures Discriminative Analysis to divide plasma NMR data into a multivariate "original sample space" suitable for further less biased metabolomics analysis and an orthogonal "preanalytical handling space" describing the changes occurring from preanalytical mishandling. Apart from confirming established preanalytical effects on metabolite levels, e.g., the consequent changes in glucose, lactate, ornithine, and pyruvate, the sample preparation protocol involved methanol precipitation which allowed the observation of reversible changes in short-chain fatty acid concentrations as a function of temperature.

Validation and TaqMan Conversion of a Molecular Chronotype Assessment Approach.

The present study aimed to develop a TaqMan genotyping card for molecular chronotype assessment based on a predictive panel of 35 previously identified genetic variants. A reliable TaqMan assay was successfully developed for 33 out of the 35 chronotype-predictive variants. The resulting TaqMan genotyping card was utilized to genetically characterize 196 new individuals (in addition to the previously studied 96) and the Morningness-Eveningness Questionnaire was utilized for their phenotypical chronotype assessment. The predictive panel performance was validated on (a) a group of morning and evening individuals (logistic regression model), (b) a representative sample of the original study population also including intermediate chronotypes (linear regression model) and, (c) 25,986 individuals from the Estonian Biobank, for whom Munich Chronotype Questionnaire scores were available. The validation of the morningness-eveningness logistic regression model on 25 morning and 21 evening types resulted in a predictive value of 72%, confirming the reliability of the predictive panel and the success of its conversion into a TaqMan genotyping card. By contrast, the inclusion of intermediate individuals in the model led to a significant decrease in predictive performance (45% on 100 individuals [25 morning, 54 intermediate, and 21 evening]), with intermediate types being the most affected. No significant associations were observed between the genotype panel and chronotype in the Estonian Biobank sample. In conclusion, our genotyping card might represent a promising molecular chronotyping tool for the Italian population. Its performance in other populations is worthy of further study.

On-site electronic consent in pediatrics using generic Informed Consent Service (gICS): Creating a specialized setup and collecting consent data.

Enrolling in a clinical trial or study requires informed consent. Furthermore, it is crucial to ensure proper consent when storing samples in biobanks for future research, as these samples may be used in studies beyond their initial purpose. For pediatric studies, consent must be obtained from both the child and their legal guardians, requiring the recording of multiple consents at once. Electronic consent has become more popular recently due to its ability to prevent errors and simplify the documentation of multiple consents. However, integrating consent capture into existing study software structures remains a challenge. This report evaluates the usability of the generic Informed Consent Service (gICS) of the University Medicine Greifswald (UMG) for obtaining electronic consent in pediatric studies. The setup was designed to integrate seamlessly with the current infrastructure and meet the specific needs of a multi-user, multi-study environment. The study was conducted in a pediatric research setting, where additional informed consent was obtained separately for the biobank. Over a period of 54 weeks, 1061 children and adolescents aged 3 to 17 years participated in the study. Out of these, 348 agreed also to participate in the biobank. The analysis included a total of 2066 consents and assents, with 945 paper-based and 1121 electronic consents. The study assessed the error susceptibility of electronic versus paper-based consents and found a significant reduction rate of errors of 94.7%. These findings provide valuable insights into the use of gICS in various studies and the practical implementation of electronic consent software in pediatric medicine.

The Development of a Non-Invasive Screening Method Based on Serum microRNAs to Quantify the Percentage of Liver Steatosis.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is often asymptomatic and underdiagnosed; consequently, there is a demand for simple, non-invasive diagnostic tools. In this study, we developed a method to quantify liver steatosis based on miRNAs, present in liver and serum, that correlate with liver fat. The miRNAs were analyzed by miRNAseq in liver samples from two cohorts of patients with a precise quantification of liver steatosis. Common miRNAs showing correlation with liver steatosis were validated by RT-qPCR in paired liver and serum samples. Multivariate models were built using partial least squares (PLS) regression to predict the percentage of liver steatosis from serum miRNA levels. Leave-one-out cross validation and external validation were used for model selection and to estimate predictive performance. The miRNAseq results disclosed (a) 144 miRNAs correlating with triglycerides in a set of liver biobank samples (n = 20); and (b) 124 and 102 miRNAs correlating with steatosis by biopsy digital image and MRI analyses, respectively, in liver samples from morbidly obese patients (n = 24). However, only 35 miRNAs were common in both sets of samples. RT-qPCR allowed to validate the correlation of 10 miRNAs in paired liver and serum samples. The development of PLS models to quantitatively predict steatosis demonstrated that the combination of serum miR-145-3p, 122-5p, 143-3p, 500a-5p, and 182-5p provided the lowest root mean square error of cross validation (RMSECV = 1.1, p-value = 0.005). External validation of this model with a cohort of mixed MASLD patients (n = 25) showed a root mean squared error of prediction (RMSEP) of 5.3. In conclusion, it is possible to predict the percentage of hepatic steatosis with a low error rate by quantifying the serum level of five miRNAs using a cost-effective and easy-to-implement RT-qPCR method.

Mosaic chromosomal alterations (mCAs) in individuals with monoclonal B-cell lymphocytosis (MBL)

MBL is a precursor condition to chronic lymphocytic leukemia (CLL), characterized by monoclonal B-cells in blood. Mosaic chromosomal alterations (mCAs) are a form of clonal hematopoiesis that include gains, losses, and copy-neutral loss-of-heterozygosity of large DNA segments. Both MBL and mCAs have been found to increase the risk of CLL and lymphoid malignancies, and the aim of our study was to investigate how mCAs relate to MBL, which is currently unknown. We analyzed genetic, flow cytometric, and hematologic data from 4632 individuals from the Mayo Clinic Biobank and CLL Database. MBL was detected using flow cytometry and classified as high-count (HC) or low-count (LC) MBL based on clone size. mCAs were detected primarily from whole blood DNA using sensitive SNP-array-based analyses. mCAs commonly altered in CLL (deletion of 6q, 11q, 13q, 17p, and trisomy 12) were specific (>99%) to individuals with MBL and CLL. HC-MBL and LC-MBL individuals were 881-fold and 8-fold, respectively, more likely to harbor CLL-associated mCAs than those without MBL. The cell fraction bearing these mCAs typically exceeded the B-cell fraction, suggesting their origin prior to the B-cell lineage. Integrating genetic and blood count data enabled detecting HC-MBL with high specificity in a biobank sample. These results quantify the contribution of mCAs to MBL and could enable large studies of HC-MBL without the need for flow cytometric screening.

Untargeted Lipidomic Profiling of Amniotic Fluid Reveals Dysregulated Lipid Metabolism in Healthy Normal-Weight Mothers with Fetal Macrosomia.

Alterations in maternal lipid metabolism have been elucidated by several studies in relation to macrosomia. However, the lipidome of the intrauterine compartment associated with macrosomia, particularly in early pregnancy, remains largely unknown. (1) To compare the lipidomic profile of early 2nd trimester amniotic fluid (AF) of healthy mothers with normal body mass index who gave birth to large-for-gestational age (LGA) versus appropriate-for-gestational age (AGA) infants; and (2) to examine if insulin and glucose concentrations in AF were associated with the AF lipidomic profile. In this nested case-control study, bio-banked AF samples were collected from pregnant women undergoing routine amniocentesis at 12-22 weeks of gestation. A subsample of 15 LGA infants (cases) were contrasted with 15 AGA infants (controls). An untargeted lipidomics analysis using liquid chromatography quadrupole time-of-flight mass spectrometry was conducted. Univariate and multivariate statistical analyses (principal component analysis and partial least-squares discriminant analysis) were used to extract differentially abundant (DA) features with high variable importance in projection (VIP) scores. LGA AF was characterized by elevations of 30 phosphatidic acid species. Among other DA features, sphingomyelin (SM 14:0;O2/20:1) had the highest VIP score and was markedly elevated in LGA AF. Neither insulin nor glucose was associated with 2nd trimester AF lipidomic profiles in these healthy, normal-weight mothers. These findings provide evidence of early dysregulated lipid metabolism in healthy, normal-weight mothers with LGA infants.

Management of Post-transplant Infections in Collaborating Hospitals (MATCH) Programme: a prospective cohort of all transplant recipients at Copenhagen University Hospital—Rigshospitalet, Denmark

PurposeThe Management of Post-transplant Infections in Collaborating Hospitals (MATCH) programme, initiated in 2011 and still ongoing, was created to 1) optimise the implementation of existing preventive strategies against viral infections...

Sex-biased proteomic regulation in obesity

Abstract Background Obesity is a major risk factor for heart failure with preserved ejection fraction, particularly in women. Obesity-associated inflammation is thought to contribute to this relationship. However, the role of biological sex in the regulation of circulating inflammatory proteins in obesity is not well understood. Purpose We aimed to explore sex differences in the plasma inflammatory protein profile in obese subjects. Methods Clinical data and samples were collected from 450 women and men with a body mass index (BMI) >27 kg/m² without known cardiovascular disease participating in the FAT associated CardiOvasculaR dysfunction study. Obesity was defined as BMI≥30 kg/m². Olink’s Target 96 inflammation panel, which profiles 92 proteins using proximity extension assay technology, was analysed in biobank samples. A comprehensive correlation analysis was performed to describe relationships between protein biomarkers and clinical variables. Gene enrichment analysis was performed to shed light on biological pathways associated with differentially expressed proteins (DEPs). To determine the functional significance of the DEPs, we used the repositories Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Pearson correlation coefficients were calculated to assess linear associations between the DEPs and relevant clinical variables. Results Women and men did not differ by age (49±9 vs 48±9 years), BMI (32.3±4.6 vs 31.6±3.7 kg/m²) or in prevalences of diabetes (both 11%) or obesity (65% vs 62%) (all p>0.05). However, hypertension was more common in men than women (74% vs 52%, p<0.001). In men (n=188), obesity was associated with downregulation of monocyte chemotactic protein 3, tumor necrosis factor (ligand) superfamily member 12, interleukin 10 and protein S100-A12 and with upregulation of neurotrophin-3 (all p<0.05), thereby suggesting a mechanism for the observed impaired inflammatory response and insulin resistance. In women (n=262), obesity was associated with the downregulation of interleukin 7, interleukin 12 subunit beta, interleukin 6, and C-X-C motif chemokine 11, suggesting a state of persistent low-grade inflammation. In addition, the upregulated sulfotransferase 1A1 and SIR2-like protein 2 proteins indicate a physiologic adaptation to oxidative stress and the metabolic excess endemic to obesity. Conclusion We found that the abundance of several circulating inflammatory proteins was altered in presence of obesity, and that the plasma proteomic profile differed by sex. Interestingly, there was no overlap in the DEPs between women and men in the presence of obesity. These findings support the hypothesis that the pathophysiological mechanisms driving obesity-associated inflammation and immune dysregulation differ by sex. In turn, this may aid in the pursuit of discovering sex-specific biomarkers to identify obese individuals at particular risk of heart failure.

Plasma levels of human growth differentiation factor 15 (GDF-15) and their effect of alirocumab on major adverse cardiovascular events and all-cause death after acute coronary syndrome

Abstract Background Human growth differentiation factor 15 (GDF-15) is a stress response cytokine of the transforming growth factor-β superfamily with roles in health and disease, cell survival and inflammation, and whose elevated plasma levels impair muscle metabolism and cause cachexia. GDF-15 also may play multiple roles in the pathophysiology of cardiovascular disease. Methods The ODYSSEY OUTCOMES trial compared the PCSK9 inhibitor alirocumab to placebo added to high-intensity or maximum-tolerated statin in patients post-acute coronary syndrome (ACS). We assessed in >11,000 patients for whom biobank samples were available, the relation between GDF-15 levels (Roche Diagnostics) at baseline and at 4 months with risk of major adverse cardiovascular events (MACE; primary endpoint, comprising coronary heart disease death, non-fatal myocardial infarction, fatal/non-fatal ischaemic stroke, unstable angina requiring hospitalization) and all-cause death, with adjustment for age and sex. Results Median GDF-15 (quartile [Q]1, Q3) at baseline was 1022 (755, 1465) pg/mL and was reduced by a placebo-adjusted median of 22 pg/mL with alirocumab (p=0.0009) at month 4. This lowering of GDF-15 by alirocumab may represent the first such report via pharmacotherapy. In the placebo group, baseline GDF-15 was significantly associated with risks of MACE (Figure Panel A) and death (Panel B). Relative risk reduction with alirocumab did not vary according to baseline GDF-15 levels for MACE (Panel C) and death (Panel D). Four-year MACE absolute risk reduction [ARR (95% CI)] with alirocumab at Q1 and Q3 of baseline GDF-15 was 2.0% (0.1%, 3.9%) and 2.6% (0.2%, 5.0%), respectively. Reduction of GDF-15 with alirocumab at month 4 was not associated with subsequent MACE (p=0.46) but was associated with death (p=0.0009), with greater reductions translating to lower risk. Conclusion In patients with recent ACS, GDF-15 is a strong predictor of both MACE and death. Reduction of GDF-15 with alirocumab at month 4 was not associated with subsequent MACE but was associated with death (p=0.0009), with greater ARR reductions translating to lower risk. Figure. Splines for baseline GDF-15 vs risk of MACE (Panel A; spline p<0.0001) or all-cause death (Panel B; spline p<00001) through 4 years in the placebo group; treatment hazard ratio for MACE (Panel C; spline p=0.52) and all-cause death (Panel D; spline p=0.78). All splines reflect adjustment for age and sexFigure