Objective: To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (?220 samples). Methods: Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. Results: A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E–6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E–4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1, ATP5A1, and VDAC3. Conclusions: We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers.
COBISS.SI-ID: 4688556
Purpose We sought to determine the analytical sensitivity of several extended exome variation analysis approaches in terms of their contribution to diagnostic yield and their clinical feasibility. Methods We retrospectively analyzed the results of genetic testing in 1,059 distinct cases referred for exome sequencing to our institution. In these, we routinely employed extended exome analysis approaches in addition to basic variant analysis, including (i) copy-number variation (CNV) detection, (ii) nonconsensus splice defect detection, (ii) genomic breakpoint detection, (iv) homozygosity mapping, and (v) mitochondrial variant analysis. Results Extended exome analysis approaches assisted in identification of causative genetic variant in 44 cases, which represented a 4.2% increase in diagnostic yield. The greatest contribution was associated with CNV analysis (1.8%) and splice variant prediction (1.2%), and the remaining approaches contributed an additional 1.2%. Analysis of workload has shown that on average nine additional variants per case had to be interpreted in the extended analysis. Conclusion We show that extended exome analysis approaches improve the diagnostic yield of heterogeneous genetic disorders and result in considerable increase of diagnostic yield of exome sequencing with a minor increase of interpretative workload.
COBISS.SI-ID: 4601516
The aim of this study was to examine whether there is an association among genetic variability in leptin (LEP) and leptin receptor (LEPR) genes and male infertility. We performed a case–control study and were searching for an association between polymorphisms of LEP and LEPR genes and male infertility. The study group consisted of 317 patients with idiopathic infertility and a control group of 241 fertile men from Slovenia. Four single nucleotide polymorphisms (SNPs) in LEP gene and four single nucleotide polymorphisms (SNPs) in LEPR gene were chosen and genotyped. Statistically significant SNP was further validated in additional 255 infertile patients and 168 controls from Serbia and Macedonia. In the Slovenian population, we found a statistically significant difference in genotype distribution for rs10244329 polymorphism in LEP gene (recessive genotype model, p value = 0.048). The trend toward statistically significant difference in genotype distribution for rs10244329 polymorphism was confirmed in the Serbian and Macedonian populations (p value = 0.07). Our data suggest that genetic variability in the LEP gene might be associated with male infertility warranting further confirmation and mechanistic investigations.
COBISS.SI-ID: 4071340