Coronary heart disease (CHD) is a complex and heterogeneous cardiovascular disease. There are many genome-wide association studies (GWAS) performed worldwide to extract the causative genetic factors. Moreover, each population may have some exceptional genetic characteristic. Thus, the background of our study is from the previous Lithuanian studies (the LiVicordia Project), which demonstrated the differences of the atherosclerosis process between Lithuanian and Swedish male individuals.In this study we performed GWAS of 32 families of Lithuanian origin in search of significant candidate genetic markers [single nucleotide polymorphisms (SNPs)] of CHD in this population. After careful clinical and biochemical phenotype evaluation, the ∼770K SNPs genotyping (Illumina HumanOmniExpress-12 v1.0 array) and familial GWAS analyses were performed.Twelve SNPs were found to be significantly associated with the CHD phenotype (p value <0.0001; the power >0.65). The odds ratio (OR) values were calculated. Two SNPs (rs17046570 in the RTN4 gene and rs11743737 in the FBXL17 gene) stood out and may prove to be important genetic factors for CHD risk. Our results correspond with the findings in other studies, and these two SNPs may be the susceptibility loci for CHD.

BackgroundCongenital hearing loss (CHL) is diagnosed in 1 – 2 newborns in 1000, genetic factors contribute to two thirds of CHL cases in industrialised countries. Mutations of the GJB2 gene located in the DFNB1 locus (13q11-12) are a major cause of CHL worldwide.The aim of this cross-sectional study was to assess the contribution of the DFNB1 locus containing the GJB2 and GJB6 genes in the development of early onset hearing loss in the affected group of participants, to determine the population-specific mutational profile and DFNB1-related HL burden in Lithuanian population.MethodsClinical data were obtained from a collection of 158 affected participants (146 unrelated probands) with early onset non-syndromic HL. GJB2 and GJB6 gene sequencing and GJB6 gene deletion testing were performed. The data of GJB2 and GJB6 gene sequencing in 98 participants in group of self-reported healthy Lithuanian inhabitants were analysed.Statistic summary, homogeneity tests, and logistic regression analysis were used for the assessment of genotype-phenotype correlation.ResultsOur findings show 57.5 % of affected participants with two pathogenic GJB2 gene mutations identified. The most prevalent GJB2 mutations were c.35delG, p. (Gly12Valfs*2) (rs80338939) and c.313_326del14, p. (Lys105Glyfs*5) (rs111033253) with allele frequencies 64.7 % and 28.3 % respectively. GJB6 gene mutations were not identified in the affected group of participants. The statistical analysis revealed significant differences between GJB2(−) and GJB2(+) groups in disease severity (p = 0.001), and family history (p = 0.01). The probability of identification of GJB2 mutations in patients with various HL characteristics was estimated. The carrier rate of GJB2 gene mutations – 7.1 % (~1 in 14) was identified in the group of healthy participants and a high frequency of GJB2-related hearing loss was estimated in our population.DiscussionThe results show a very high proportion of GJB2-positive individuals in the research group affected with sensorineural HL. The allele frequency of c.35delG mutation (64.7 %) is consistent with many previously published studies in groups of affected individuals of Caucasian populations. The high frequency of the c.313_326del14 (28.3 % of pathogenic alleles) mutation in affected group of participants was an unexpected finding in our study suggesting not only a high frequency of carriers of this mutation in our population but also its possible origin in Lithuanian ancestors. The high frequency of carriers of the c.313_326del14 mutation in the entire Lithuanian population is supported by it being identified twice in the ethnic Lithuanian group of healthy participants (a frequency 2.0 % of carriers in the study group).ConclusionAnalysis of the allele frequency of GJB2 gene mutations revealed a high proportion of c. 313_326del14 (rs111033253) mutations in the GJB2-positive group suggesting its possible origin in Lithuanian forebears. The high frequency of carriers of GJB2 gene mutations in the group of healthy participants corresponds to the ...

BackgroundAlthough copy number variation (CNV) has received much attention, knowledge about the characteristics of CNVs such as occurrence rate and distribution in the genome between populations and within the same population is still insufficient. In this study, Illumina 770 K HumanOmniExpress-12 v1.0 (and v1.1) arrays were used to examine the diversity and distribution of CNVs in 286 unrelated individuals from the two main ethnolinguistic groups of the Lithuanian population (Aukštaičiai and Žemaičiai) (see Additional file 3). For primary data analysis, the Illumina GenomeStudio™ Genotyping Module v1.9 and two algorithms, cnvPartition 3.2.0 and QuantiSNP 2.0, were used to identify high-confidence CNVs.ResultsA total of 478 autosomal CNVs were detected by both algorithms, and those were clustered in 87 copy number variation regions (CNVRs), spanning ~12.5 Mb of the genome (see Table 1). At least 8.6 % of the CNVRs were unique and had not been reported in the Database of Genomic Variants. Most CNVRs (57.5 %) were rare, with a frequency of <1 %, whereas common CNVRs with at least 5 % frequency made up only 1.1 % of all CNVRs identified. About 49 % of non-singleton CNVRs were shared between Aukštaičiai and Žemaičiai, and the remaining CNVRs were specific to each group. Many of the CNVs detected (66 %) overlapped with known UCSC gene regions.ConclusionsThe ethnolinguistic groups of the Lithuanian population could not be differentiated based on CNV profiles, which may reflect their geographical proximity and suggest the homogeneity of the Lithuanian population. In addition, putative novel CNVs unique to the Lithuanian population were identified. The results of our study enhance the CNV map of the Lithuanian population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0373-6) contains supplementary material, which is available to authorized users.

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Next-generation sequencing (NGS) became an effective approach for finding novel causative genomic variants of genetic disorders and is increasingly used for diagnostic purposes. Public variant databases that gather data of pathogenic variants are being relied upon as a source for clinical diagnosis. However, research of pathogenic variants using public databases data could be carried out not only in patients, but also in healthy people. This could provide insights into the most common recessive disorders in populations. The study aim was to use NGS and data from the ClinVar database for the identification of pathogenic variants in the exomes of healthy individuals from the Lithuanian population. To achieve this, 96 exomes were sequenced. An average of 42 139 single-nucleotide variants (SNVs) and 2306 short INDELs were found in each individual exome. Pooled data of study exomes provided a total of 243 192 unique SNVs and 31 623 unique short INDELs. Three hundred and twenty-one unique SNVs were classified as pathogenic. Comparison of the European data from the 1000 Genomes Project with our data revealed five pathogenic genomic variants that are inherited in an autosomal recessive pattern and that statistically significantly differ from the European population data.