Changes in the type 2 diabetes gut mycobiome associate with metformin treatment across populations.

The human gut teems with a diverse ecosystem of microbes, yet non-bacterial portions of that community are overlooked in studies of metabolic diseases firmly linked to gut bacteria. Type 2 diabetes mellitus (T2D) is associated with compositional shifts in the gut bacterial microbiome and the mycobiome, the fungal portion of the microbiome. However, whether T2D and/or metformin treatment underpins fungal community changes is unresolved. To differentiate these effects, we curated a gut mycobiome cohort spanning 1,000 human samples across five countries and validated our findings in a murine experimental model. We use Bayesian multinomial logistic normal models to show that T2D and metformin both associate with shifts in the relative abundance of distinct gut fungi. T2D is associated with shifts in the Saccharomycetes and Sordariomycetes fungal classes, while the genera Fusarium and Tetrapisipora most consistently associate with metformin treatment. We confirmed the impact of metformin on individual gut fungi by administering metformin to healthy mice. Thus, metformin and T2D account for subtle, but significant and distinct variation in the gut mycobiome across human populations. This work highlights for the first time that metformin can confound associations of gut fungi with T2D and warrants the need to consider pharmaceutical interventions in investigations of linkages between metabolic diseases and gut microbial inhabitants. IMPORTANCE: This is the largest to-date multi-country cohort characterizing the human gut mycobiome, and the first to investigate potential perturbations in gut fungi from oral pharmaceutical treatment. We demonstrate the reproducible effects of metformin treatment on the human and murine gut mycobiome and highlight a need to consider metformin as a confounding factor in investigations between type 2 diabetes mellitus and the gut microbial ecosystem.

Exploring disease-specific metabolite signatures in hereditary angioedema patients.

Introduction: Hereditary angioedema (HAE) is a rare, life-threatening autosomal dominant genetic disorder caused by a deficient and/or dysfunctional C1 esterase inhibitor (C1-INH) (type 1 and type 2) leading to recurrent episodes of edema. This study aims to explore HAE patients' metabolomic profiles and identify novel potential diagnostic biomarkers for HAE. The study also examined distinguishing HAE from idiopathic angioedema (AE). Methods: Blood plasma samples from 10 HAE (types 1/2) patients, 15 patients with idiopathic AE, and 20 healthy controls were collected in Latvia and analyzed using LC-MS based targeted metabolomics workflow. T-test and fold change calculation were used to identify metabolites with significant differences between diseases and control groups. ROC analysis was performed to evaluate metabolite based classification model. Results: A total of 33 metabolites were detected and quantified. The results showed that isovalerylcarnitine, cystine, and hydroxyproline were the most significantly altered metabolites between the disease and control groups. Aspartic acid was identified as a significant metabolite that could differentiate between HAE and idiopathic AE. The mathematical combination of metabolites (hydroxyproline * cystine)/(creatinine * isovalerylcarnitine) was identified as the diagnosis signature for HAE. Furthermore, glycine/asparagine ratio could differentiate between HAE and idiopathic AE. Conclusion: Our study identified isovalerylcarnitine, cystine, and hydroxyproline as potential biomarkers for HAE diagnosis. Identifying new biomarkers may offer enhanced prospects for accurate, timely, and economical diagnosis of HAE, as well as tailored treatment selection for optimal patient care.

Cell-Free Microbial DNA Analysis: Effects of Blood Plasma and Serum Quantity, Biobanking Protocols, and Isolation Kits.

Recent studies highlight the presence of bacterial sequences in the human blood, suggesting potential clinical significance for circulating microbial signatures. These sequences could presumably serve in the diagnosis, prediction, or monitoring of various health conditions. Ensuring the similarity of samples before bacterial analysis is crucial, especially when combining samples from different biobanks prepared under varying conditions (such as different DNA extraction kits, centrifugation conditions, blood collection tubes, etc.). In this study, we aimed to analyze the impact of different sample collection and nucleic acid extraction criteria (blood collection tube, centrifugation, input volume, and DNA extraction kit) on circulating bacterial composition. Blood samples from four healthy individuals were collected into three different sample collection tubes: K2EDTA plasma tube, sodium citrate plasma tube, and gel tube for blood serum. Tubes were centrifugated at standard and double centrifugation conditions. DNA extraction was performed using 100, 200, and 500 µL plasma/serum input volumes. DNA extraction was performed using three different isolation kits: Norgen plasma/serum cell-free circulating DNA purification micro kit, Applied Biosystems MagMAX cell-free DNA isolation kit, and Qiagen QIAamp MinElute cell-free circulating DNA mini kit. All samples were subjected to 16S rRNA V1-V2 library preparation and sequencing. In total, 216 DNA and 18 water control samples were included in the study. According to PERMANOVA, PCoA, Mann-Whitney, and FDR tests the effect of the DNA extraction kit on the microbiota composition was the greatest, whereas the type of blood collection tube, centrifugation type, and sample input volume for the extraction had minor effects. Samples extracted with the Norgen DNA extraction kit were enriched with Gram-negative bacteria, whereas samples extracted with the Qiagen and MagMAX kits were enriched with Gram-positive bacteria. Bacterial profiles of samples prepared with the Qiagen and MagMAX DNA extraction kits were more similar, whereas samples prepared with the Norgen DNA extraction kit were significantly different from other groups.

Longitudinal NMR-Based Metabolomics Study Reveals How Hospitalized COVID-19 Patients Recover: Evidence of Dyslipidemia and Energy Metabolism Dysregulation.

Long COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), can manifest as long-term symptoms in multiple organ systems, including respiratory, cardiovascular, neurological, and metabolic systems. In patients with severe COVID-19, immune dysregulation is significant, and the relationship between metabolic regulation and immune response is of great interest in determining the pathophysiological mechanisms. We aimed to characterize the metabolomic footprint of recovering severe COVID-19 patients at three consecutive timepoints and compare metabolite levels to controls. Our findings add proof of dysregulated amino acid metabolism in the acute phase and dyslipidemia, glycoprotein level alterations, and energy metabolism disturbances in severe COVID-19 patients 3-4 months post-hospitalization.

Single-Cell RNA Sequencing Reveals Alterations in Patient Immune Cells with Pulmonary Long COVID-19 Complications.

Since the emergence of the COVID-19 pandemic, the effects of SARS-CoV-2 have been extensively researched. While much is already known about the acute phase of the infection, increasing attention has turned to the prolonged symptoms experienced by a subset of individuals, commonly referred to as long COVID-19 patients. This study aims to delve deeper into the immune landscape of patients with prolonged symptoms by implementing single-cell mRNA analysis. A 71-year-old COVID-19 patient presenting with persistent viral pneumonia was recruited, and peripheral blood samples were taken at 3 and 2 years post-acute infection onset. Patients and control peripheral blood mononuclear cells (PBMCs) were isolated and single-cell sequenced. Immune cell population identification was carried out using the ScType script. Three months post-COVID-19 patients' PBMCs contained a significantly larger immature neutrophil population compared to 2-year and control samples. However, the neutrophil balance shifted towards a more mature profile after 18 months. In addition, a notable increase in the CD8+ NKT-like cells could be observed in the 3-month patient sample as compared to the later one and control. The subsequent change in these cell populations over time may be an indicator of an ongoing failure to clear the SARS-CoV-2 infection and, thus, lead to chronic COVID-19 complications.

Evaluating the Efficacy of Type 2 Diabetes Polygenic Risk Scores in an Independent European Population.

Numerous type 2 diabetes (T2D) polygenic risk scores (PGSs) have been developed to predict individuals' predisposition to the disease. An independent assessment and verification of the best-performing PGS are warranted to allow for a rapid application of developed models. To date, only 3% of T2D PGSs have been evaluated. In this study, we assessed all (n = 102) presently published T2D PGSs in an independent cohort of 3718 individuals, which has not been included in the construction or fine-tuning of any T2D PGS so far. We further chose the best-performing PGS, assessed its performance across major population principal component analysis (PCA) clusters, and compared it with newly developed population-specific T2D PGS. Our findings revealed that 88% of the published PGSs were significantly associated with T2D; however, their performance was lower than what had been previously reported. We found a positive association of PGS improvement over the years (p-value = 8.01 × 10-4 with PGS002771 currently showing the best discriminatory power (area under the receiver operating characteristic (AUROC) = 0.669) and PGS003443 exhibiting the strongest association PGS003443 (odds ratio (OR) = 1.899). Further investigation revealed no difference in PGS performance across major population PCA clusters and when compared with newly developed population-specific PGS. Our findings revealed a positive trend in T2D PGS performance, consistently identifying high-T2D-risk individuals in an independent European population.

Exploring the Impact of COVID-19 on Ulcerative Colitis Patients: A Lifestyle Perspective.

Background and Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 is the new coronavirus that caused the coronavirus disease 2019 (COVID-19) outbreak. Studies have increasingly reported the involvement of organs outside the respiratory system, including the gastrointestinal tract. Data on the association between COVID-19 and ulcerative colitis (UC) are lacking. Materials and Methods: In this one-centre cross-sectional study, 49 patients with UC from the Riga East Clinical University Hospital outpatient clinic were included from June 2021 to December 2021. The patients were divided into two groups according to their history of a confirmed positive or negative COVID-19 status. Data on their lifestyle, diet, and medications and the food supplements used by the patients were collected during interviews and analysed using the R 4.2.1 software. Results: Out of 49 patients, 33 (63.3%) were male and 13 (36.7%) were female, with a mean age of 32.33 ± 8.6 years. Fourteen patients (28.6%) had a confirmed COVID-19 infection in the last year. The most common COVID-19-related symptoms were a fever and rhinorrhoea. A third of patients followed the inflammatory bowel disease diet (16; 32.7%); out of these patients, 12 (34.3%) did not contract COVID-19 (OR: 0.78 (0.18; 2.98), p > 0.05). In the COVID-19-positive group, the majority of patients did not use vitamin D (11; 79% vs. 3; 21%, (OR: 0.38 (0.07; 1.51), p = 0.28) or probiotics (11; 78.6% vs. 3; 21.4%, OR: 1.33 (0.23; 6.28), p = 0.7). In the COVID-19-positive group, most patients did not smoke (12; 85.7% vs. 2; 14.3%, p = 0.475) and did not use alcohol (9; 64.3% vs. 5; 35.7%, OR: 0.63 (0.16; 2.57), p = 0.5). Most of the patients who participated in sports activities were COVID-negative (18; 51.4% vs. 6; 42.9%, p = 0.82). Conclusions: There were no statistically significant differences in the use of food supplements, probiotics, or vitamins; the lifestyle habits; or the COVID-19 status in patients with UC.

Gut Microbiome Composition and Dynamics in Hospitalized COVID-19 Patients and Patients with Post-Acute COVID-19 Syndrome.

The gut microbiome plays a pivotal role in the modulation of host responses during viral infections, and recent studies have underscored its significance in the context of coronavirus disease 2019 (COVID-19). We aimed to investigate the dynamics and compositional changes in the gut microbiome of COVID-19 patients, addressing both the acute phase and the recovery process, with a particular focus on the emergence of post-COVID-19 conditions. Involving 146 COVID-19 patients and 110 healthy controls, this study employed a shotgun metagenomics approach for cross-sectional and longitudinal analyses with one- and three-month follow-ups. We observed a decline in taxonomic diversity among hospitalized COVID-19 patients compared to healthy controls, while a subsequent increase in alpha diversity was shown during the recovery process. A notable contribution of Enterococcus faecium was identified in the acute phase of the infection, accompanied by an increasing abundance of butyrate-producing bacteria (e.g., Roseburia, Lachnospiraceae_unclassified) during the recovery period. We highlighted a protective role of the Prevotella genus in the long-term recovery process and suggested a potential significance of population-specificity in the early gut microbiome markers of post-acute COVID-19 syndrome. Our study represents distinctive gut microbiome signatures in COVID-19, with potential diagnostic and prognostic implications, pinpointing potential modulators of the disease progression.

Prevalence of SARS-CoV-2 in domestic cats (Felis catus) during COVID-19 pandemic in Latvia.

BACKGROUND: The causative agent of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is of zoonotic origin and has shown reverse zoonotic transmissibility. OBJECTIVES: The aim of this cross-sectional study was to investigate the serological and molecular prevalence of SARS-CoV-2 infection in the domestic cat (Felis catus) population from Latvia in natural conditions and subsequently perform viral genome analysis. METHODS: Oropharyngeal and rectal swabs and blood samples were collected from 273 domestic cats during the second wave of COVID-19 infection in Latvia. Molecular prevalence was determined by using reverse transcriptase-polymerase chain reaction (RT-PCR). Serum samples were analysed via double antigen enzyme-linked immunosorbent assay targeting the antibody against the nucleocapsid protein of SARS-CoV-2. Positive swab samples were analysed using whole viral genome sequencing and subsequent phylogenetic analysis of the whole genome sequencing data of the samples was performed. RESULTS: The overall SARS-CoV-2 RT-PCR positivity and seroprevalence was 1.1% (3/273) and 2.6% (7/273), respectively. The SARS-CoV-2 genome sequences from three RT-PCR positive cats were assigned to the three common lineages (PANGOLIN lineage S.1.; B.1.177.60. and B.1.1.7.) circulating in Latvia during the particular period of time. CONCLUSIONS: These findings indicate that feline infection with SARS-CoV-2 occurred during the second wave of the COVID-19 pandemic in Latvia, yet the overall prevalence was low. In addition, it seems like no special 'cat' pre-adaptations were necessary for successful infection of cats by the common lineages of SARS-CoV-2.

Variations in the Relative Abundance of Gut Bacteria Correlate with Lipid Profiles in Healthy Adults.

The gut microbiome is a versatile system regulating numerous aspects of host metabolism. Among other traits, variations in the composition of gut microbial communities are related to blood lipid patterns and hyperlipidaemia, yet inconsistent association patterns exist. This study aims to assess the relationships between the composition of the gut microbiome and variations in lipid profiles among healthy adults. This study used data and samples from 23 adult participants of a previously conducted dietary intervention study. Circulating lipid measurements and whole-metagenome sequences of the gut microbiome were derived from 180 blood and faecal samples collected from eight visits distributed across an 11-week study. Lipid-related variables explained approximately 4.5% of the variation in gut microbiome compositions, with higher effects observed for total cholesterol and high-density lipoproteins. Species from the genera Odoribacter, Anaerostipes, and Parabacteroides correlated with increased serum lipid levels, whereas probiotic species like Akkermansia muciniphila were more abundant among participants with healthier blood lipid profiles. An inverse correlation with serum cholesterol was also observed for Massilistercora timonensis, a player in regulating lipid turnover. The observed correlation patterns add to the growing evidence supporting the role of the gut microbiome as an essential regulator of host lipid metabolism.

Whole-Genome Sequencing of 502 Individuals from Latvia: The First Step towards a Population-Specific Reference of Genetic Variation.

Despite rapid improvements in the accessibility of whole-genome sequencing (WGS), understanding the extent of human genetic variation is limited by the scarce availability of genome sequences from underrepresented populations. Developing the population-scale reference database of Latvian genetic variation may fill the gap in European genomes and improve human genomics research. In this study, we analysed a high-coverage WGS dataset comprising 502 individuals selected from the Genome Database of the Latvian Population. An assessment of variant type, location in the genome, function, medical relevance, and novelty was performed, and a population-specific imputation reference panel (IRP) was developed. We identified more than 18.2 million variants in total, of which 3.3% so far are not represented in gnomAD and dbSNP databases. Moreover, we observed a notable though distinct clustering of the Latvian cohort within the European subpopulations. Finally, our findings demonstrate the improved performance of imputation of variants using the Latvian population-specific reference panel in the Latvian population compared to established IRPs. In summary, our study provides the first WGS data for a regional reference genome that will serve as a resource for the development of precision medicine and complement the global genome dataset, improving the understanding of human genetic variation.

Metformin targets intestinal immune system signaling pathways in a high-fat diet-induced mouse model of obesity and insulin resistance.

Introduction: Research findings of the past decade have highlighted the gut as the main site of action of the oral antihyperglycemic agent metformin despite its pharmacological role in the liver. Extensive evidence supports metformin's modulatory effect on the composition and function of gut microbiota, nevertheless, the underlying mechanisms of the host responses remain elusive. Our study aimed to evaluate metformin-induced alterations in the intestinal transcriptome profiles at different metabolic states. Methods: The high-fat diet-induced mouse model of obesity and insulin resistance of both sexes was developed in a randomized block experiment and bulk RNA-Seq of the ileum tissue was the method of choice for comparative transcriptional profiling after metformin intervention for ten weeks. Results: We found a prominent transcriptional effect of the diet itself with comparatively fewer genes responding to metformin intervention. The overrepresentation of immune-related genes was observed, including pronounced metformin-induced upregulation of immunoglobulin heavy-chain variable region coding Ighv1-7 gene in both high-fat diet and control diet-fed animals. Moreover, we provide evidence of the downregulation NF-kappa B signaling pathway in the small intestine of both obese and insulin-resistant animals as well as control animals after metformin treatment. Finally, our data pinpoint the gut microbiota as a crucial component in the metformin-mediated downregulation of NF-kappa B signaling evidenced by a positive correlation between the Rel and Rela gene expression levels and abundances of Parabacteroides distasonis, Bacteroides spp., and Lactobacillus spp. in the gut microbiota of the same animals. Discussion: Our study supports the immunomodulatory effect of metformin in the ileum of obese and insulin-resistant C57BL/6N mice contributed by intestinal immunoglobulin responses, with a prominent emphasis on the downregulation of NF-kappa B signaling pathway, associated with alterations in the composition of the gut microbiome.

Genetic Characteristics of Latvian Patients with Familial Hypercholesterolemia: The First Analysis from Genome-Wide Sequencing.

BACKGROUND: There is limited data on the genetic characteristics of patients with familial hypercholesterolemia (FH) in Latvia. We aim to describe monogenic variants in patients from the Latvian Registry of FH (LRFH). METHODS: Whole genome sequencing with 30× coverage was performed in unrelated index cases from the LRFH and the Genome Database of Latvian Population. LDLR, APOB, PCSK9, LDLRAP1, ABCG5, ABCG8, LIPA, LPA, CYP27A1, and APOE genes were analyzed. Only variants annotated as pathogenic (P) or likely pathogenic (LP) using the FH Variant Curation Expert Panel guidelines for LDLR and adaptations for APOB and PCSK9 were reported. RESULTS: Among 163 patients, the mean highest documented LDL-cholesterol level was 7.47 ± 1.60 mmol/L, and 79.1% of patients had LDL-cholesterol ≥6.50 mmol/L. A total of 15 P/LP variants were found in 34 patients (diagnostic yield: 20.9%): 14 in the LDLR gene and 1 in the APOB gene. Additionally, 24, 54, and 13 VUS were detected in LDLR, APOB, and PCSK9, respectively. No P/LP variants were identified in the other tested genes. CONCLUSIONS: Despite the high clinical likelihood of FH, confirmed P/LP variants were detected in only 20.9% of patients in the Latvian cohort when assessed with genome-wide next generation sequencing.

Changes in the Type 2 diabetes gut mycobiome associate with metformin treatment across populations.

The human gut teems with a diverse ecosystem of microbes, yet non-bacterial portions of that community are overlooked in studies of metabolic diseases firmly linked to gut bacteria. Type 2 diabetes mellitus (T2D) associates with compositional shifts in the gut bacterial microbiome and fungal mycobiome, but whether T2D and/or pharmaceutical treatments underpin the community change is unresolved. To differentiate these effects, we curated a gut mycobiome cohort to-date spanning 1,000 human samples across 5 countries and a murine experimental model. We use Bayesian multinomial logistic normal models to show that metformin and T2D both associate with shifts in the relative abundance of distinct gut fungi. T2D associates with shifts in the Saccharomycetes and Sordariomycetes fungal classes, while the genera Fusarium and Tetrapisipora most consistently associate with metformin treatment. We confirmed the impact of metformin on individual gut fungi by administering metformin to healthy mice. Thus, metformin and T2D account for subtle, but significant and distinct variation in the gut mycobiome across human populations. This work highlights for the first time that oral pharmaceuticals can confound associations of gut fungi with T2D and warrants the need to consider pharmaceutical interventions in investigations of linkages between metabolic diseases and gut microbial inhabitants.

Metatranscriptome analysis of blood in healthy individuals and irritable bowel syndrome patients.

Introduction. Although the presence of micro-organisms in the blood of healthy humans is a relatively new concept, there is a growing amount of evidence that blood might have its own microbiome.Gap Statement. Previous research has targeted the taxonomic composition of the blood microbiome using DNA-based sequencing methods, while little information is known about the presence of microbial transcripts obtained from the blood and their relation to conditions connected with increased gut permeability.Aim. To detect potentially alive and active micro-organisms and investigate differences in taxonomic composition between healthy people and patients with irritable bowel syndrome (IBS), we used the metatranscriptomics approach.Methodology. We collected blood samples from 23 IBS patients and 26 volunteers from the general population, and performed RNAseq on the isolated RNA. Reads corresponding to microbial genomes were identified with Kraken 2's standard plus protozoa and fungi database, and re-estimated at genus level with Bracken 2.7. We looked for trends in the taxonomic composition, making a comparison between the IBS and control groups, accounting for other different factors.Results. The dominant genera in the blood microbiome were found to be Cutibacterium, Bradyrhizobium, Escherichia, Pseudomonas, Micrococcus, Delftia, Mediterraneibacter, Staphylococcus, Stutzerimonas and Ralstonia. Some of these are typical environmental bacteria and could partially represent contamination. However, analysis of sequences from the negative controls suggested that some genera which are characteristic of the gut microbiome (Mediterraneibacter, Blautia, Collinsella, Klebsiella, Coprococcus, Dysosmobacter, Anaerostipes, Faecalibacterium, Dorea, Simiaoa, Bifidobacterium, Alistipes, Prevotella, Ruminococcus) are less likely to be a result of contamination. Differential analysis of microbes between groups showed that some taxa associated with the gut microbiome (Blautia, Faecalibacterium, Dorea, Bifidobacterium, Clostridium, Christensenella) are more prevalent in IBS patients compared to the general population. No significant correlations with any other factors were identified.Conclusion. Our findings support the existence of the blood microbiome and suggest the gut and possibly the oral microbiome as its origin, while the skin microbiome is a possible but less certain source. The blood microbiome is likely influenced by states of increased gut permeability such as IBS.

Spatial variation of the gut microbiome in response to long-term metformin treatment in high-fat diet-induced type 2 diabetes mouse model of both sexes.

Antidiabetic drug metformin alters the gut microbiome composition in the context of type 2 diabetes and other diseases; however, its effects have been mainly studied using fecal samples, which offer limited information about the intestinal site-specific effects of this drug. Our study aimed to characterize the spatial variation of the gut microbiome in response to metformin treatment by using a high-fat diet-induced type 2 diabetes mouse model of both sexes. Four intestinal parts, each at the luminal and mucosal layer level, were analyzed in this study by performing 16S rRNA sequencing covering six variable regions (V1-V6) of the gene and thus allowing to obtain in-depth information about the microbiome composition. We identified significant differences in gut microbiome diversity in each of the intestinal parts regarding the alpha and beta diversities. Metformin treatment altered the abundance of different genera in all studied intestinal sites, with the most pronounced effect in the small intestine, where Lactococcus increased remarkably. The abundance of Lactobacillus was substantially lower in male mice compared to female mice in all locations, in addition to an enrichment of opportunistic pathogens. Diet type and intestinal layer had significant effects on microbiome composition at each of the sites studied. We observed a different effect of metformin treatment on the analyzed subsets, indicating the multiple dimensions of metformin's effect on the gut microbiome.

Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors.

Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer and data analyzed using two separate workflows and variant calling algorithms: GATK and Strelka2. A combination of two data analysis pipelines discovered 144 PitNET specific somatic variants (mean = 9.6, range 0-19 per PitNET) of which all were SNVs. Also, we detected previously known GNAS PitNET mutation and identified somatic variants in 11 genes, which have contained somatic variants in previous WES and WGS studies of PitNETs. Noteworthy, this is the third study detecting somatic variants in gene RYR1 in the exomes of PitNETs. In conclusion, we have identified two novel PitNET candidate genes (AC002519.6 and AHNAK) with recurrent somatic variants in our PitNET cohort and found 13 genes overlapping from previous PitNET studies that contain somatic variants. Our study demonstrated that the use of multiple sequencing data analysis pipelines can provide more accurate identification of somatic variants in PitNETs.

Case Report: Micro-RNAs in Plasma From Bilateral Inferior Petrosal Sinus Sampling and Peripheral Blood From Corticotroph Pituitary Neuroendocrine Tumors.

Objective: Circulating miRNAs are found in bodily fluids including plasma and can serve as biomarkers for diseases. The aim of this study was to provide the first insight into the landscape of circulating miRNAs in close proximity to the adrenocorticotropic hormone (ACTH) secreting PitNET. To achieve this objective next-generation sequencing of miRNAs in plasma from bilateral inferior petrosal sinus sampling (BIPSS) - a gold standard in diagnosing ACTH-secreting PitNETs was carried out and selected miRNA candidates were further tested by RT-qPCR in independent patient cohorts. Methods: Sinistral (left) and dextral (right) BIPSS blood samples of the patient were collected in three time points: before the administration of corticotropin-releasing hormone, 5 and 15 minutes after stimulation. In differential expression analysis, sinistral plasma was compared with dextral. The selected miRNA candidates were tested in plasma by RT-qPCR in two patient groups: 1) in five ACTH secreting PitNET patients with plasma samples taken before and 24 hours after surgery, 2) in 12 ACTH secreting PitNET patients vs. 9 non-functioning PitNET patients. Results: BIPSS concluded that the highest amount of ACTH was released in the sinistral side at the 5th minute mark indicating a presence of a tumor. The highest amount of differentially expressed miRNAs was observed 5 minutes after stimulation (20 upregulated, 14 downregulated). At the 5th minute mark in sinistral plasma, two miRNAs were identified: hsa-miR-7-5p and hsa-miR-375-3p that were highly upregulated compared to other BIPSS samples and peripheral plasma samples. Further testing by qPCR revealed significant reduction of miR-7-5p in plasma 24 hours after surgery and upregulation in plasma of ACTH secreting PitNET patients compared to non-functioning PitNET patients (P =0.0013). Conclusions: By stimulating the ACTH secreting PitNET with CRH a rapid increase of two miRNAs (hsa-mir-7-5p, hsa-mir-375-3p) and ACTH can be observed in sinistral inferior petrosal (tumor side). A decrease of miR-7-5p in plasma after surgery and upregulation in plasma of ACTH secreting PitNET patients was discovered implying that further studies of this miRNA as diagnostic marker is needed.

Toll-Like Receptor 1 Locus Re-examined in a Genome-Wide Association Study Update on Anti-Helicobacter pylori IgG Titers.

BACKGROUND & AIMS: A genome-wide significant association between anti-Helicobacter pylori (H pylori) IgG titers and Toll-like receptor (TLR1/6/10) locus on 4p14 was demonstrated for individuals of European ancestry, but not uniformly replicated. We re-investigated this association in an updated genome-wide association study (GWAS) meta-analysis for populations with low gastric cancer incidence, address potential causes of cohort heterogeneity, and explore functional implications of genetic variation at the TLR1/6/10 locus. METHODS: The dichotomous GWAS (25% individuals exhibiting highest anti-H pylori IgG titers vs remaining 75%) included discovery and replication sampls of, respectively, n = 15,685 and n = 9676, all of European ancestry. Longitudinal analysis of serologic data was performed on H pylori-eradicated subjects (n = 132) and patients under surveillance for premalignant gastric lesions (n = 107). TLR1/6/10 surface expression, TLR1 mRNA, and cytokine levels were measured in leukocyte subsets of healthy subjects (n = 26) genotyped for TLR1/6/10 variants. RESULTS: The association of the TLR1/6/10 locus with anti-H pylori IgG titers (rs12233670; ß = -0.267 ± SE 0.034; P = 4.42 × 10-15) presented with high heterogeneity and failed replication. Anti-H pylori IgG titers declined within 2-4 years after eradication treatment (P = 0.004), and decreased over time in patients with premalignant gastric lesions (P < 0.001). Variation at the TLR1/6/10 locus affected TLR1-mediated cytokine production and TLR1 surface expression on monocytes (P = 0.016) and neutrophils (P = 0.030), but not mRNA levels. CONCLUSIONS: The association between anti-H pylori IgG titers and TLR1/6/10 locus was not replicated across cohorts, possibly owing to dependency of anti-H pylori IgG titers on therapy, clearance, and antibody decay. H pylori-mediated immune cell activation is partly mediated via TLR1 signaling, which in turn is affected by genetic variation.

Impact of the pre-examination phase on multicenter metabolomic studies.

The development of metabolomics in clinical applications has been limited by the lack of validation in large multicenter studies. Large population cohorts and their biobanks are a valuable resource for acquiring insights into molecular disease mechanisms. Nevertheless, most of their collections are not tailored for metabolomics and have been created without specific attention to the pre-analytical requirements for high-quality metabolome assessment. Thus, comparing samples obtained by different pre-analytical procedures remains a major challenge. Here, 1H NMR-based analyses are used to demonstrate how human serum and plasma samples collected with different operating procedures within several large European cohort studies from the Biobanking and Biomolecular Resources Infrastructure - Large Prospective Cohorts (BBMRI-LPC) consortium can be easily revealed by supervised multivariate statistical analyses at the initial stages of the process, to avoid biases in the downstream analysis. The inter-biobank differences are discussed in terms of deviations from the validated CEN/TS 16945:2016 / ISO 23118:2021 norms. It clearly emerges that biobanks must adhere to the evidence-based guidelines in order to support wider-scale application of metabolomics in biomedicine, and that NMR spectroscopy is informative in comparing the quality of different sample sources in multi cohort/center studies.