Dataset Information

MicroRNA Processing Pathway-Based Polygenic Score for Clear Cell Renal Cell Carcinoma in the Volga-Ural Region Populations of Eurasian Continent

ABSTRACT: The polygenic scores (PGSs) are developed to help clinicians in distinguishing individuals at high risk of developing disease outcomes from the general population. Clear cell renal cell carcinoma (ccRCC) is a complex disorder that involves numerous biological pathways, one of the most important of which is responsible for the microRNA biogenesis machinery. Here, we defined the biological-pathway-specific PGS in a case-control study of ccRCC in the Volga-Ural region of the Eurasia continent. We evaluated 28 DNA SNP variants, located in microRNA biogenesis genes, in 464 individuals with clinically diagnosed ccRCC and 1042 individuals without the disease. Individual genetic risks were defined using the SNP-variant effects derived from the ccRCC association analysis. The final weighted and unweighted PGS models were based on 21 SNPs, and 7 SNPs were excluded due to high LD. In our dataset, microRNA-machinery-weighted PGS revealed 1.69-fold higher odds (95% CI [1.51–1.91]) for ccRCC risk in individuals with ccRCC compared with controls with a p-value of 2.0 × 10−16. The microRNA biogenesis pathway weighted PGS predicted the risk of ccRCC with an area under the curve (AUC) = 0.642 (95%nCI [0.61–0.67]). Our findings indicate that DNA variants of microRNA machinery genes modulate the risk of ccRCC in Volga-Ural populations. Moreover, larger powerful genome-wide association studies are needed to reveal a wider range of genetic variants affecting microRNA processing. Biological-pathway-based PGSs will advance the development of innovative screening systems for future stratified medicine approaches in ccRCC.

SUBMITTER: Ivanova E

PROVIDER: S-EPMC9324265 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Hereditary cataracts are characterized by significant clinical and genetic heterogeneity, which can pose challenges for early DNA diagnosis. To comprehensively address this problem, it is essential to investigate the epidemiology of the disease, perform population studies to determine the spectrum and frequencies of mutations in the responsible genes, and examine clinical and genetic correlations. Based on modern concepts, non-syndromic hereditary cataracts are predominantly caused by genetic disease forms associated with mutations in crystallin and connexin genes. Therefore, a comprehensive approach to studying hereditary cataracts is necessary for early diagnosis and improved treatment outcomes. The crystallin (CRYAA, CRYAB, CRYGC, CRYGD, and CRYBA1) and connexin (GJA8, GJA3) genes were analyzed in 45 unrelated families from the Volga-Ural Region (VUR) with hereditary congenital cataracts. Pathogenic and probably pathogenic nucleotide variants were identified in ten unrelated families, nine of which had cataracts in an autosomal dominant pattern of inheritance. Two previously undescribed likely pathogenic missense variants were identified in the CRYAA gene: c.253C > T (p.L85F) in one family and c.291C > G (p.H97Q) in two families. The known mutation c.272_274delGAG (p.G91del) was found in the CRYBA1 gene in one family, while no pathogenic variants were found in the CRYAB, CRYGC, or CRYGD genes in the examined patients. In the GJA8 gene, the known mutation c.68G > C (p.R23T) was found in two families, and previously undescribed variants were identified in two other families: a c.133_142del deletion (p.W45Sfs*72) and a missense variant, c.179G > A (p.G60D). In one patient with a recessive form of cataract, two compound-heterozygous variants were identified-a previously undescribed likely pathogenic missense variant, c.143A > G (p.E48G), and a known variant with uncertain pathogenetic significance, c.741T > G (p.I24M). Additionally, a previously undescribed deletion, c.del1126_1139 (p.D376Qfs*69), was identified in the GJA3 gene in one family. In all families where mutations were identified, cataracts were diagnosed either immediately after birth or during the first year of life. The clinical presentation of the cataracts varied depending on the type of lens opacity, resulting in various clinical forms. This information emphasizes the importance of early diagnosis and genetic testing for hereditary congenital cataracts to guide appropriate management and improve outcomes.

Project description:BackgroundPolygenic risk scores (PRS) derived from European individuals have reduced portability across global populations, limiting their clinical implementation at worldwide scale. Here, we investigate the performance of a wide range of PRS models across four ancestry groups (Africans, Europeans, East Asians, and South Asians) for 14 conditions of high-medical interest.MethodsTo select the best-performing model per trait, we first compared PRS performances for publicly available scores, and constructed new models using different methods (LDpred2, PRS-CSx and SNPnet). We used 285 K European individuals from the UK Biobank (UKBB) for training and 18 K, including diverse ancestries, for testing. We then evaluated PRS portability for the best models in Europeans and compared their accuracies with respect to the best PRS per ancestry. Finally, we validated the selected PRS models using an independent set of 8,417 individuals from Biobank of the Americas-Genomelink (BbofA-GL); and performed a PRS-Phewas.ResultsWe confirmed a decay in PRS performances relative to Europeans when the evaluation was conducted using the best-PRS model for Europeans (51.3% for South Asians, 46.6% for East Asians and 39.4% for Africans). We observed an improvement in the PRS performances when specifically selecting ancestry specific PRS models (phenotype variance increase: 1.62 for Africans, 1.40 for South Asians and 0.96 for East Asians). Additionally, when we selected the optimal model conditional on ancestry for CAD, HDL-C and LDL-C, hypertension, hypothyroidism and T2D, PRS performance for studied populations was more comparable to what was observed in Europeans. Finally, we were able to independently validate tested models for Europeans, and conducted a PRS-Phewas, identifying cross-trait interplay between cardiometabolic conditions, and between immune-mediated components.ConclusionOur work comprehensively evaluated PRS accuracy across a wide range of phenotypes, reducing the uncertainty with respect to which PRS model to choose and in which ancestry group. This evaluation has let us identify specific conditions where implementing risk-prioritization strategies could have practical utility across diverse ancestral groups, contributing to democratizing the implementation of PRS.

Dataset Information

MicroRNA Processing Pathway-Based Polygenic Score for Clear Cell Renal Cell Carcinoma in the Volga-Ural Region Populations of Eurasian Continent

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