Wyniki wyszukiwania - Biblioteka Nauki

1

An association of the MCP-1 and CCR2 single nucleotide polymorphisms with colorectal cancer prevalence

100%

Walczak A. , Przybyłowska-Sygut K. , Sygut A. , Cieślak A. , Mik M. , Dziki Ł. , Dziki A. , Majsterek I.

Polish Journal of Surgery

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2017

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tom 89(5)

1-5

EN

The aim of the study: We evaluated the connection between the presence of the -2518 A/G MCP-1 as well as 190 G/A CCR2 polymorphic variants and colorectal cancer (CRC) occurrence. Material and methods: Study group consisted of subjects with different stages of CRC as well as healthy controls. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Results: W observed an association between the colorectal cancer and the GG genotype of the -2518 A/G MCP-1 single nucleotide polymorphism. No statistically significant correlation was found between CRC and the 190 G/A CCR2 polymorphism. Conclusion: The results of this study support the hypothesis that polymorphism in the MCP-1 gene may contribute to the etiology of colorectal cancer.

2

Sampling properties of estimators of nucleotide diversity at discovered SNP sites

100%

Renwick A. , Bonnen P. E. , Trikka D. , Nelson D. L. , Chakraborty R. , Kimmel M.

International Journal of Applied Mathematics and Computer Science

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2003

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tom 13

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nr 3

385-394

EN

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of variant frequencies at SNP sites, with an additional probability that there is no SNP at any given site. Under this model of allele frequency distributions at SNP sites, we show that nucleotide diversity is always underestimated. However, the extent of bias does not seem to exceed 10-15% for the analyzed data. We find that our model of allele frequency distributions at SNP sites is consistent with SNP statistics derived based on new SNP data at ATM, BLM, RQL and WRN gene regions. The application of the theory to these new SNP data as well as to the literature data at the LPL gene region indicates that in spite of ascertainment biases, the observed differences of nucleotide diversity across these gene regions are real. This provides interesting evidence concerning the heterogeneity of the rates of nucleotide substitution across the genome.

3

Hepatocyte nuclear factor 4 alpha P2 promoter variants associate with insulin resistance

100%

Saif-Ali R. , Harun R. , Al-Jassabi S. , Wan Ngah W.

Acta Biochimica Polonica

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2011

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tom 58

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nr 2

179-186

EN

This study aimed to investigate the associations of hepatocyte nuclear factor 4 (HNF4) alpha single nucleotide polymorphisms (SNPs) and haplotype with insulin resistance and metabolic syndrome parameters. Nine SNPs spanning the HNF4 alpha P2 promoter (rs4810424, rs1884613 and rs1884614) and coding region (rs2144908, rs6031551, rs6031552, rs1885088, rs1028583 and rs3818247) were genotyped in 160 subjects without diabetes or metabolic syndrome. The HNF4 alpha P2 promoter SNPs rs4810424, rs1884613 and rs1884614 were associated with insulin resistance (p = 0.017; 0.037; 0.024) and body mass index (BMI) (p = 0.03; 0.035; 0.039). The intron 1D SNP rs2144908 was associated with high-density lipoprotein cholesterol (HDLc) (p = 0.020) and the intron 9 SNP rs3818247 showed association with systolic (p = 0.02) and diastolic (p = 0.034) blood pressure. HNF4 alpha common haplotype CCCGTC associated with higher insulin resistance (p = 0.022), fasting blood glucose (FBG) (p = 0.035) and lower HDLc (p = 0.001). In conclusion, subjects with HNF4 alpha P2 variants and haplotypes have been shown to have a higher insulin resistance and are therefore at a higher risk for developing type 2 diabetes mellitus.

4

Association between RBMS1 gene rs7593730 and BCAR1 gene rs7202877 and Type 2 diabetes mellitus in the Chinese Han population

88%

Kazakova E. , Chen M. , Jamaspishvili E. , Lin Z. , Yu J. , Sun L. , Qiao H.

Acta Biochimica Polonica

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2018

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tom 65

|

nr 3

377-382

EN

Two recent studies found that RBMS1 gene rs7593730 and BCAR1 gene rs7202877 are related to type 2 diabetes. However, the association of these loci with type 2 diabetes mellitus (T2DM) has not been examined in Chinese. We performed a replication study to investigate the association of the 2 susceptibility loci with T2DM in the Chinese population. We genotyped 1961 Chinese participants (991 with T2DM and 970 controls) for each of the 2 single nucleotide polymorphisms (SNPs) rs7593730 in RBMS1 and rs7202877 near BCAR1 using SNPscan and examined their association with T2DM using logistic regression analysis. We also analyzed the correlation of the SNP alleles and clinical phenotypes. In additive model, genotype association analysis of BCAR1 rs7202877 loci revealed that the homozygous of rs7202877 GG carriers had significantly decreased T2DM risk compared to homozygous carriers of TT (P=0.038, OR 0.44, 95% CI 0.20-0.96). In the recessive model, the GG genotype GG had significantly decreased T2DM risk compared to GT+TT (P=0.043, OR 0.67, 95% CI 0.46-0.99). Allele G was statistically significantly correlated with TC (mmol/L) (P=0.036) and LDL-C (mmol/L) (P=0.007). As for rs7593730, the carriers of CT and TT genotype had significantly decreased T2DM risk compared to the carriers of CC genotype (CT: CC P=0.038, OR 0.71, 95% CI 0.51-0.98; TT: CC P=0.010, OR 0.32, 95% CI 0.13-0.76). In a dominant model, TT+CT: CC (P=0.013, OR 0.673, 95% CI 0.49-0.92) and in a recessive model, TT: CT+CC (P=0.019, OR 0.59, 95% CI 0.39-0.92). The T allele carriers had significantly decreased T2DM risk compared to the carriers of C (P=0.002, OR 0.65, 95% CI 0.50-0.86). Allele T was statistically correlated with FINS (P=0.010). In conclusion, our study showed that RBMS1 gene rs7593730 and BCAR1 gene rs7202877 were significantly associated with type 2 diabetes in the Chinese population.

5

The Gas6 gene rs8191974 and Ap3s2 gene rs2028299 are associated with type 2 diabetes in the northern Chinese Han population

88%

Kazakova E. , Zghuang T. , Li T. , Fang Q. , Han J. , Qiao H.

Acta Biochimica Polonica

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2017

|

tom 64

|

nr 2

227-231

EN

Previous studies in other countries have shown that single nucleotide polymorphisms (SNPs) in the growth arrest-specific gene 6 (Gas6; rs8191974) and adapter-related protein complex 3 subunit sigma-2 (Ap3s2; rs2028299) were associated with an increasedrisk for type 2 diabetes mellitus (T2DM). However, the association of these loci with T2DM has not been examined in Chinese populations. We performed a replication study to investigate the association of these susceptibility loci with T2DM in the Chinese population.We genotyped 1968 Chinese participants (996 with T2DM and 972controls) for rs8191974 in Gas6 and rs2028299 near Ap3s2, and examined their association with T2DM using a logistic regression analysis. We also analyzed the correlation of genotypes and clinical phenotypes. The distribution of the T allele of SNP rs8191974 in the Gas6 gene was significantly different between T2DM cases and controls when compared with the C allele (P<0.05, OR: 0.80, 95% CI: 0.69-0.94). The occurrence of the CT genotype and the dominant model was also significantly less frequent in the T2DM cases vs. controls when compared with the CC genotype (CT vs. CC: P<0.05, OR: 0.75, 95% CI:0.62-0.90; TT+CT vs. CC: P<0.05, OR:0.75, 95% CI:0.63-0.90). In SNP rs2028299, the allele C showed no statistically significant differencein distribution between the control and T2DM groups when compared with allele A. However, in male populations, the dominant model was statistically more frequent when compared with genotype AA (CC+CA vs. AA: P<0.05, OR:1.29, 95% CI:1.02-1.64), and in obesity-stratified analysis, we also observed a significant difference in the distribution of the dominant model between the T2DM cases and controls in subjects with BMI≥24 kg/m2 and BMI<28kg/m2 (CC+CA vs. AA: P<0.05, OR: 6.33, 95% CI:4.17-9.61). In conclusion, our study shows that SNPsrs8191974 and rs2028299 are significantly associated with T2DM in the Chinese population.

6

Single nucleotide polymorphisms applied in statistical inference of population growth

75%

Polański A. , Starosolski Z. , Świerniak A. , Kimmel M.

Biocybernetics and Biomedical Engineering

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2003

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tom Vol. 23, no. 4

45-61

EN

We have evaluated probability distributions of estimates of parameters of population growth, based on data on frequencies of alleles of unlinked SNP sites in DNA, modeled with the use of time dependent coalescence process acting together with mutation of a very low intensity. Probability distributions of maximum likelihood estimates of the product parameter of the present population effective size and exponent coefficient, for exponential scenario, have atoms at zero and long tails to the right. For stepwise scenario, log likelihood functions typically exhibit very long lines, covering many decades of the scale, of almost the same value of log likelihood. Observational data from [14] are consistent with the hypothesis of the population growth.

7

Sampling Properties of Estimators of Nucleotide Diversity at Discovered snp Sites

75%

Renwick A. , Bonnen P. E. , Trikka D. , Nelson D. L. , Chakraborty R. , Kimmel M.

International Journal of Applied Mathematics and Computer Science

|

2003

|

tom Vol. 13, no 3

385-394

EN

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of variant frequencies at SNP sites, with an additional probability that there is no SNP at any given site. Under this model of allele frequency distributions at SNP sites, we show that nucleotide diversity is always underestimated. However, the extent of bias does not seem to exceed 10-15% for the analyzed data. We find that our model of allele frequency distributions at SNP sites is consistent with SNP statistics derived based on new SNP data at ATM, BLM, RQL and WRN gene regions. The application of the theory to these new SNP data as well as to the literature data at the LPL gene region indicates that in spite of ascertainment biases, the observed differences of nucleotide diversity across these gene regions are real. This provides interesting evidence concerning the heterogeneity of the rates of nucleotide substitution across the genome.

8

Analiza możliwości zastosowania metod sztucznej inteligencji w medycynie sądowej

63%

Filipowicz E. , Kwiecień J. , Kłys M. , Filipowicz B.

Bio-Algorithms and Med-Systems

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2005

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tom Vol. 1, no. 1/2

3--8

PL

Artykuł opisuje zastosowanie nowych systemów bioinformatycznych w medycynie sądowej. Systemy biometryczne już znalazły zastosowanie między innymi w geometrycznej identyfikacji twarzy. Są one niezbędne w identyfikacji osobowej oraz w poszukiwaniu osób zaginionych. W ostatnich latach nastąpił bardzo szybki rozwój badań nad chromosomem Y, co pozwoliło na postęp w medycynie sądowej. Metody sztucznej inteligencji mogąbyć pomocne w badaniach spornego ojcostwa i ewolucji człowieka. Bioinformatyka oraz metody biologii molekularnej, metody multiplex PCR będą pełnić bardzo ważną funkcję w analizie sądowej DNA oraz w historycznych i genealogicznych badaniach.

EN

This article reviews new bioinformatic systems in forensic medicine. Biometric systems are already used in forensic medicine for face geometry identification. They are necessary in personal identification and missing persons investigations. The field of Y-chromosome analysis and its application to forensic science has undergone rapid improvement in recent years. Artificial Intelligence is usefull in paternity testing and in human evolutionary study. Bioinformatic systems and multiplex PCR assay w ill play an important role in the future of forensic DNA typing and historical and genealogical research.