Background: The Genome Database of the Latvian Population (LGDB) is a national biobank that collects, maintains, and processes health information, data, and biospecimens collected from representatives of the Latvian population. These specimens serve as a foundation for epidemiological research and prophylactic and therapeutic purposes.Methods: Participant recruitment and biomaterial and data processing were performed according to specifically designed standard protocols, taking into consideration international quality requirements. Legal and ethical aspects, including broad informed consent and personal data protection, were applied according to legal norms of the Republic of Latvia.Results: Since its start in 2006, the LGDB is comprised of biosamples and associated phenotypic and clinical information from over 31,504 participants, constituting approximately 1.5% of the Latvian population. The LGDB represents a mixed-design biobank and includes participants from the general population as well as disease-based cohorts. The standard set of biosamples stored in the LGDB consists of DNA, plasma, serum, and white blood cells; in some cohorts, these samples are complemented by cancer biopsies and microbiome and urine samples. The LGDB acts as a core structure for the Latvian Biomedical Research and Study Centre (BMC), representing the national node of Latvia in Biobanking and BioMolecular resources Research Infrastructure – European Research Infrastructure Consortium (BBMRI-ERIC).Conclusions: The development of the LGDB has enabled resources for biomedical research and promoted genetic testing in Latvia. Further challenges of the LGDB are the enrichment and harmonization of collected biosamples and data, the follow-up of selected participant groups, and continued networking and participation in collaboration projects.

Somatostatin (SST) is a small peptide that exerts inhibitory effects on a wide range of neuroendocrine cells. Due to the fact that somatostatin regulates cell growth and hormone secretion, somatostatin receptors (SSTRs) have become valuable targets for the treatment of different types of neuroendocrine tumours (NETs). NETs are a heterogeneous group of tumours that can develop in various parts of the body, including the digestive system, lungs, and pituitary. NETs are usually slow growing, but they are often diagnosed in advanced stages and can display aggressive behaviour. The mortality rate of NETs is not outstandingly increased compared to other malignant tumours, even in the metastatic setting. One of the intrinsic properties of NETs is the expression of SSTRs that serve as drug targets for SST analogues (SSAs), which can delay tumour progression and downregulate hormone overproduction. Additionally, in many NETs, it has been demonstrated that the SSTR expression level provides a prognostic value in predicting a therapeutic response. Furthermore, higher a SSTR expression correlates with a better survival rate in NET patients. In recent studies, other epigenetic regulators affecting SST signalling or SSA–mTOR inhibitor combination therapy in NETs have been considered as novel strategies for tumour control. In conclusion, SST signalling is a relevant regulator of NET functionality. Alongside classical SSA treatment regimens, future advanced therapies and treatment modalities are expected to improve the disease outcomes and overall health of NET patients.

Background: Public awareness and engagement are among the main prerequisites for protecting the rights of research participants and for successful and sustainable functioning of research biobanks. The aim of our study was to analyse public awareness and attitudes towards research biobanks in Latvia, and to compare these data with the results of the 2010 Eurobarometer study. We also analysed the influence of awareness and attitudes towards biobanks on willingness to participate in biobank studies and on preferred type of informed consent. Methods: We developed a 12-question survey repeating seven questions about biobanks from the 2010 Eurobarometer questionnaire and adding five others. After describing the study variables, we performed a two-stage analysis of the results. In the first stage we analysed differences between the answers from 2010 and 2019 and conducted univariate analyses of relationships among particular variables, and between those variables and the socio-demographic characteristics of participants. In the second stage we investigated multivariable associations of willingness to participate and type of consent with awareness, trust and the socio-economic characteristics of participants. Results: According to our study, the general public in Latvia is still not well informed about research biobanks. Fewer respondents have heard about research biobanks than in 2010. At the same time, the number of respondents who are willing to donate biological samples and personal data to a biobank has increased, e.g. the number of respondents who would definitely or probably be willing to provide information about themselves has increased from 25.8.% to 40.7 since 2010. Overall, concerns about the donation of different types of biological samples and data to a biobank have slightly decreased. Conclusions: Public awareness about biobanks is important for their sustainability. It needs to be increased not only by traditional methods of informing the public, but also by more innovative and participatory approaches, e.g. by citizen science projects. There is a need to strengthen the public visibility and trustworthiness of ethics committees in Latvia in the field of biobanking.

Pituitary neuroendocrine tumors (PitNETs) are non-metastatic neoplasms of the pituitary, which overproduce hormones leading to systemic disorders, or tumor mass effects causing headaches, vertigo or visual impairment. Recently, PitNETs have been investigated in large scale (exome and genome) molecular analyses (transcriptome microarrays and sequencing), to uncover novel markers. We performed a literature analysis on these studies to summarize the research data and extrapolate overlapping gene candidates, biomarkers, and molecular mechanisms. We observed a tendency in samples with driver mutations (GNAS, USP8) to have a smaller overall mutational rate, suggesting driver-promoted tumorigenesis, potentially changing transcriptome profiles in tumors. However, direct links from drivers to signaling pathways altered in PitNETs (Notch, Wnt, TGF-β, and cell cycle regulators) require further investigation. Modern technologies have also identified circulating nucleic acids, and pinpointed these as novel PitNET markers, i.e., miR-143-3p, miR-16-5p, miR-145-5p, and let-7g-5p, therefore these molecules must be investigated in the future translational studies. Overall, large-scale molecular studies have provided key insight into the molecular mechanisms behind PitNET pathogenesis, highlighting previously reported molecular markers, bringing new candidates into the research field, and reapplying traditional perspectives to newly discovered molecular mechanisms.

Metformin, a biguanide agent, is the first-line treatment for type 2 diabetes mellitus due to its glucose-lowering effect. Despite its wide application in the treatment of multiple health conditions, the glycemic response to metformin is highly variable, emphasizing the need for reliable biomarkers. We chose the RNA-Seq-based comparative transcriptomics approach to evaluate the systemic effect of metformin and highlight potential predictive biomarkers of metformin response in drug-naïve volunteers with type 2 diabetes in vivo. The longitudinal blood-derived transcriptome analysis revealed metformin-induced differential expression of novel and previously described genes involved in cholesterol homeostasis (SLC46A1 and LRP1), cancer development (CYP1B1, STAB1, CCR2, TMEM176B), and immune responses (CD14, CD163) after administration of metformin for three months. We demonstrate for the first time a transcriptome-based molecular discrimination between metformin responders (delta HbA1c ≥ 1% or 12.6 mmol/mol) and non-responders (delta HbA1c < 1% or 12.6 mmol/mol), that is determined by expression levels of 56 genes, explaining 13.9% of the variance in the therapeutic efficacy of the drug. Moreover, we found a significant upregulation of IRS2 gene (log₂FC 0.89) in responders compared to non-responders before the use of metformin. Finally, we provide evidence for the mitochondrial respiratory complex I as one of the factors related to the high variability of the therapeutic response to metformin in patients with type 2 diabetes mellitus.

Diabetes leads to reduced nitric oxide bioavailability, resulting in endothelial dysfunction. However, overproduction of nitric oxide due to hyperglycaemia is associated with oxidative stress and tissue damage. The objective of this study was to characterise nitric oxide production (NO) and added nitrite and nitrate (NO2‑+NO3‑) concentration in the blood and urine of patients with and without diabetic nephropathy. A total of 268 patients with type 1 diabetes and 69 healthy subjects were included. Diabetic nephropathy was defined as macroalbuminuria and/or estimated glomerular filtration rate below 60 ml/min/1.73 cm2. NO2‑+NO3‑ concentration was measured by Griess reaction. Production of NO was detected by electron paramagnetic resonance spectroscopy. Blood NO was demonstrated to be higher (P<0.001) and serum NO2‑+NO3‑ was lower (P=0.003) in patients with type 1 diabetes and no nephropathy vs. healthy subjects. However, serum NO2‑+NO3‑ concentration in patients with diabetes and nephropathy did not differ from the levels observed in healthy controls. Urine excretion of NO2‑+NO3‑ was significantly decreased in patients with nephropathy, compared with patients without diabetic kidney disease (P=0.006) and healthy subjects (P=0.010). A significant positive correlation was observed between urine NO2‑+NO3‑ and estimated glomerular filtration rate in patients with type 1 diabetes (P=0.002) and healthy subjects (P=0.008). Estimated glomerular filtration rate, albuminuria and diabetic nephropathy status were significant predictors of the whole blood NO and NO2‑+NO3‑ in serum and urine in patients with type 1 diabetes, as identified by linear regression models. The present study concludes that NO metabolism is impaired by type 1 diabetes and diabetic nephropathy.