Ilze Elbere

Latvian Biomedical Research and Study Centre

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Jānis Kloviņš

Latvian Biomedical Research and Study Centre

Ivars Silamiķelis

Latvian Biomedical Research and Study Centre

Ineta Kalniņa

Latvian Biomedical Research and Study Centre

Ilze Konrāde

Riga East University Hospital

Valdis Pīrāgs

Pauls Stradiņš Clinical University Hospital

Maija Rozenberga

Latvian Biomedical Research and Study Centre

Raitis Pečulis

Latvian Biomedical Research and Study Centre

Monta Ustinova

Latvian Biomedical Research and Study Centre

Linda Zaharenko

Latvian Biomedical Research and Study Centre

Zane Straume

Riga East University Hospital

Cooperative Institutions

University of Latvia

143

Unidad de Cirugía Artroscópica

123

Foundation for Ichthyosis and Related Skin Types

122

Latvia University of Life Sciences and Technologies

121

Riga Stradiņš University

Riga East University Hospital

Pauls Stradiņš Clinical University Hospital

Latvian Biomedical Research and Study Centre

Lund University

Skåne University Hospital

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FIT test-systems for mega-scale gut microbiome testing

Annals of Oncology (2017)

Dita Gudrā Dāvids Frīdmanis Jānis Kloviņš Ģirts Šķenders Ivars Silamiķelis

Ion semiconductor sequencing

10.1093/annonc/mdx261.032

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Citations (1)

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions

Frontiers in Microbiology (2021)

Isabel Moreno‐Indias Leo Lahti Miroslava Nedyalkova Ilze Elbere Gennady V. Roshchupkin

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.

Benchmarking

Biomedicine

Human Microbiome Project

10.3389/fmicb.2021.635781

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Significantly altered peripheral blood cell DNA methylation profile as a result of immediate effect of metformin use in healthy individuals

Clinical Epigenetics (2018)

Ilze Elbere Ivars Silamiķelis Monta Ustinova Ineta Kalniņa Linda Zaharenko

Metformin is a widely prescribed antihyperglycemic agent that has been also associated with multiple therapeutic effects in various diseases, including several types of malignancies. There is growing evidence regarding the contribution of the epigenetic mechanisms in reaching metformin's therapeutic goals; however, the effect of metformin on human cells in vivo is not comprehensively studied. The aim of our study was to examine metformin-induced alterations of DNA methylation profiles in white blood cells of healthy volunteers, employing a longitudinal study design. Twelve healthy metformin-naïve individuals where enrolled in the study. Genome-wide DNA methylation pattern was estimated at baseline, 10 h and 7 days after the start of metformin administration. The whole-genome DNA methylation analysis in total revealed 125 differentially methylated CpGs, of which 11 CpGs and their associated genes with the most consistent changes in the DNA methylation profile were selected: POFUT2, CAMKK1, EML3, KIAA1614, UPF1, MUC4, LOC727982, SIX3, ADAM8, SNORD12B, VPS8, and several differentially methylated regions as novel potential epigenetic targets of metformin. The main functions of the majority of top-ranked differentially methylated loci and their representative cell signaling pathways were linked to the well-known metformin therapy targets: regulatory processes of energy homeostasis, inflammatory responses, tumorigenesis, and neurodegenerative diseases. Here we demonstrate for the first time the immediate effect of short-term metformin administration at therapeutic doses on epigenetic regulation in human white blood cells. These findings suggest the DNA methylation process as one of the mechanisms involved in the action of metformin, thereby revealing novel targets and directions of the molecular mechanisms underlying the various beneficial effects of metformin. EU Clinical Trials Register, 2016-001092-74. Registered 23 March 2017, https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-001092-74/LV .

10.1186/s13148-018-0593-x

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

mBio (2024)

Emily Van Syoc Michelle Pistner Nixon Justin D. Silverman Yuhong Luo Frank J. Gonzalez

ABSTRACT 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.

10.1128/mbio.00169-24

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

Medicina (2024)

Zane Straume Nikola Krūmiņa Ilze Elbere Maija Rozenberga Dace Rudzīte

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.

Cross-sectional study

Coronavirus

10.3390/medicina60010182

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

Frontiers in Endocrinology (2023)

Monta Brīvība Laila Silamiķele Ineta Kalniņa Ivars Silamiķelis Līga Birzniece

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.

10.3389/fendo.2023.1232143

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Citations (7)

Gut microbiome encoded purine and amino acid pathways present prospective biomarkers for predicting metformin therapy efficacy in newly diagnosed T2D patients

Gut Microbes (2024)

Ilze Elbere Zigmunds Orlovskis Laura Ansone Ivars Silamiķelis Lauma Jagare

Metformin is widely used for treating type 2 diabetes mellitus (T2D). However, the efficacy of metformin monotherapy is highly variable within the human population. Understanding the potential indirect or synergistic effects of metformin on gut microbiota composition and encoded functions could potentially offer new insights into predicting treatment efficacy and designing more personalized treatments in the future. We combined targeted metabolomics and metagenomic profiling of gut microbiomes in newly diagnosed T2D patients before and after metformin therapy to identify potential pre-treatment biomarkers and functional signatures for metformin efficacy and induced changes in metformin therapy responders. Our sequencing data were largely corroborated by our metabolic profiling and identified that pre-treatment enrichment of gut microbial functions encoding purine degradation and glutamate biosynthesis was associated with good therapy response. Furthermore, we identified changes in glutamine-associated amino acid (arginine, ornithine, putrescine) metabolism that characterize differences in metformin efficacy before and after the therapy. Moreover, metformin Responders' microbiota displayed a shifted balance between bacterial lipidA synthesis and degradation as well as alterations in glutamate-dependent metabolism of N-acetyl-galactosamine and its derivatives (e.g. CMP-pseudaminate) which suggest potential modulation of bacterial cell walls and human gut barrier, thus mediating changes in microbiome composition. Together, our data suggest that glutamine and associated amino acid metabolism as well as purine degradation products may potentially condition metformin activity via its multiple effects on microbiome functional composition and therefore serve as important biomarkers for predicting metformin efficacy.

10.1080/19490976.2024.2361491

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Citations (2)

Impact of Vitamins, Antibiotics, Probiotics, and History of COVID-19 on the Gut Microbiome in Ulcerative Colitis Patients: A Cross-Sectional Study

Medicina (2025)

Zane Straume Nikola Krūmiņa Ilze Elbere Maija Rozenberga Renārs Erts

Background and Objectives: The human gut microbiome is essential for the health of the host and is affected by antibiotics and coronavirus disease 2019 (COVID-19). The gut microbiome is recognized as a contributing factor in the development of ulcerative colitis. Specific vitamins and probiotics have been demonstrated to positively influence the microbiome by enhancing the prevalence of expected beneficial microorganisms. Materials and Methods: Forty-nine ulcerative colitis (UC) outpatients from Riga East Clinical University Hospital were enrolled in this cross-sectional study from June 2021 to December 2021. All patients were divided into groups based on history of COVID-19 (COVID-19 positive vs. COVID-19 negative) in the last six months. Information about antibiotic, probiotic, and vitamin intake were outlined, and faecal samples were collected. The MetaPhlAn v.2.6.0 tool was used for the taxonomic classification of the gut microbiome metagenome data. Statistical analysis was performed using R 4.2.1. Results: Of the 49 patients enrolled, 31 (63%) were male and 18 (37%) were female. Coronavirus disease 2019 was found in 14 (28.6%) patients in the last 6 months. Verrucomicrobia was statistically significantly lower in the COVID-19 positive group (M = 0.05; SD = 0.11) compared to the COVID-19 negative group (M = 0.5; SD = 1.22), p = 0.03. Antibiotic non-users had more Firmicutes in their microbiome than antibiotic users (p = 0.008). The most used vitamin supplement was vitamin D (N = 18), fifteen (42.9%) of the patients were COVID-19 negative and 3 (21.4%) were COVID-19 positive over the last six months (p > 0.05). Vitamin C users had more Firmicutes in their gut microbiome compared to non-users (Md = 72.8 [IQR: 66.6; 78.7] vs. Md = 60.1 [IQR: 42.4; 67.7]), p = 0.01. Conclusions: Antibiotic non-users had more Firmicutes than antibiotic users in their gut microbiome. Only vitamin C had statistically significant results; in users, more Firmicutes were observed. A mild course of COVID-19 may not influence ulcerative colitis patients' gut microbiome.

Gut microbiome

Inflammatory Bowel Diseases

10.3390/medicina61020284

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Identification Of Pathogenic Mutations And Application Of Polygenic Risk Scores In Early-Onset Diabetes Patients

Research Square (Research Square) (2024)

Ivanna Atava Raimonds Reščenko Monta Brīvība Līga Birzniece Ilze Elbere

Abstract Background: Maturity-onset Diabetes of the Young (MODY) presents a diagnostic challenge, with a large proportion of cases lacking identifiable genetic mutations, which could lead to sub-optimal medical treatment and, subsequently, a decline in patients’ life quality. This study investigates the utility of polygenic risk score (PRS) in distinguishing monogenic diabetes from early-onset type 1 diabetes (T1D) and type 2 diabetes (T2D) cases to enhance diagnostic accuracy. Methods: We investigated the genetic basis of early-onset diabetes in a Latvian cohort comprising 66 patients, contrasted with 174 non-diabetic controls, using whole-genome sequencing (WGS). Results: We identified 22 causative mutations in three MODY genes (GCK, HNF1A, and HNF4A), eight of them being novel. We selected and tested the best-performing population specific T1D and T2D PRS models on the established diabetic cohort and controls. Patients without genetically confirmed MODY had a significantly higher risk for T1D compared to controls. A 75% centile of T1D-PRS included only 8.7% of the genetically confirmed MODY patients, compared to 34% of patients without mutations, providing good specificity for the identification of indicative T1D at this PRS range. While T2D-PRS was increased in the diabetic cohort, it did not demonstrate an ability to discriminate between MODY-positive and negative subgroups. Conclusions: Our study demonstrates that the application of WGS improves diagnostic accuracy and highlights the potential of T1D-PRS as a critical tool for the stratification of MODY-suspected patients.

Polygenic risk score

Identification

10.21203/rs.3.rs-5361647/v1

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Alterations in DNA methylation from peripheral blood cells in humans threated with metformin

Endocrine Abstracts (2017)

Jānis Kloviņš Ilze Elbere Raitis Pečulis Ineta Kalniņa Linda Zaharenko

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

10.1530/endoabs.49.oc6.3

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