The high recurrence rate and invasive diagnostic and monitoring methods in bladder cancer (BCa) clinical management require the development of new non-invasive molecular tools for early detection, particularly for low-grade and low-stage BCa as well as for risk stratification. By using an in-solution digestion method and label-free data-independent LC-MS/MS coupled with ion mobility, we profiled the BCa tissues from initiation to advanced stages and confidently identified and quantified 1619 proteins (≥2 peptides). A statistically significant difference in abundance (Anova ≤ 0.05) showed 494 proteins. Significant correlation with stage with steady up or down with BCa stages showed 15 proteins. Testing of NNMT, GALK1, and HTRA1 in urine samples showed excellent diagnostic potential for NNMT and GALK1 with AUC of 1.000 (95% CI: 1.000–1.000; p < 0.0001) and 0.801 (95% CI: 0.655–0.947; p < 0.0001), respectively. NNMT and GALK1 also showed very good potential in discriminating non-invasive low-grade from invasive high-grade BCa with AUC of 0.763 (95% CI: 0.606–0.921; p = 0.001) and 0.801 (95% CI: 0.653–0.950; p < 0.0001), respectively. The combination of NNMT and GALK1 increased prognostic accuracy (AUC = 0.813). Our results broaden the range of potential novel candidates for non-invasive BCa diagnosis and prognosis.

As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002–2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.

Background/Objectives: Expanded carrier screening (ECS) panels often rely on pan-ethnic databases, such as the ACMG Tier 3 panel, but their ability to capture population-specific reproductive risk is uncertain. We characterized pathogenic/likely pathogenic (P/LP) variants and at-risk-couple (ARC) probabilities in an underrepresented population from North Macedonia to inform ECS gene prioritization. Methods: NGS data from 1438 subjects of Macedonian, Albanian, and other local ancestry, referred for rare-disease diagnostics, were analyzed across 1795 candidate autosomal recessive/X-linked genes. P/LP variants were compared with gnomAD exomes v2.1.1 non-Finnish European frequencies (Fisher’s exact test). Gene-specific ARC probabilities ranked genes and generated cumulative ARC curves per subgroup. Results: We identified 2007 P/LP variants across 1096 genes. One hundred variants in 89 genes reached an allele frequency ≥ 1/200 in the Macedonian or Albanian subgroups; over one-third were absent from candidate ECS panels, mostly linked to severe or variable phenotypes. ARC saturated rapidly: genes with carrier counts ≥ 1/100 (ACMG Tier 2) accounted for over 85% of total ARC, and with ≥1/200 (ACMG Tier 3) for more than 93%. Total ARC among autosomal recessive panel genes (X-linked genes analyzed separately) was 3.42%, rising to 5.02% in the Albanian subgroup. Excluding top hypomorphic variants reduced ARC by 34–37%, highlighting variant-specific penetrance. The highest-ARC genes diverged between subgroups, with limited overlap with pan-ethnic panels. Conclusions: Population-specific carrier frequencies influence gene prioritization and estimated reproductive-risk probabilities for ECS. Population-tailored ECS panels that incorporate local carrier-frequency data, including embryonic/fetal-lethal genes, and account for hypomorphic alleles to avoid overestimating reproductive risk probabilities could improve the identification of couples at increased reproductive risk, particularly in underrepresented populations.

Pharmacogenetics (PGx) plays a critical role in optimizing drug therapy by tailoring treatment based on individual genetic profiles, with the potential to improve clinical outcomes. Accurate data on allele and phenotype distributions in specific populations is essential for effective clinical application. This study presents the first comprehensive PGx landscape of the population in North Macedonia, using extended whole exome sequencing (WES) data. All individuals in the cohort had at least one aberrant phenotype across key pharmacogenes, consistent with global findings. Significant differences in haplotype frequencies were observed compared to broader European populations, underscoring the importance of region-specific PGx data. Of the 78 AMP-recommended alleles, 27 were identified, with all of participants carrying at least one Tier 1 allele. Compared to previous targeted studies in our population, WES enabled detection of lower-frequency AMP alleles and rare CYP2D6 variants not typically captured by local genotyping assays. Based on in silico functional impact predictions, 128 novel putative non-functional variants were identified across 19 pharmacogenes, including 17 in AMP-recommended genes such as DPYD, CYP3A4, and VKORC1—where novel variants were sometimes more frequent than those previously reported. These findings highlight the presence of additional clinically relevant variants beyond standard panels and emphasize the limitations of targeted genotyping. However, challenges remain, particularly for complex genes like CYP2D6, where short-read WES cannot fully resolve haplotypes. This study reinforces the need for improved sequencing methodologies and guidelines for interpreting novel PGx variants, while demonstrating the value of population-specific profiling to advance precision medicine and inform clinical practice.

Genomic epidemiology has proven to be a useful tool for investigating pandemic outbreaks and tracking pathogen spread and evolution. This study describes the circulation of SARS-CoV-2 strains in N. Macedonia during a period of one year, encompassing three waves of the COVID-19 pandemic. A certain percentage (2-3%) of positive cases were continuously selected and analyzed by whole genome sequencing (WGS) technology. Using this approach, a total of 337 SARS-CoV-2 genomes were sequenced and 26 different lineages belonging to 7 clades were detected. During the first wave of the pandemic, the most dominant lineage was B.1.1, followed by B.1.1.70, which became the most dominant in the second wave. The B.1.1.7 lineage completely overpassed all other variants in the third wave. Our study strengthens the notion that the progression of COVID-19 pandemic is associated with emergence of new SARS-CoV-2 variants with increased virulence. The measure of the impact of this viral dynamic on the spread of the pandemic should be evaluated in association with other factors that might influence the transmission.