Over a 100 years ago, William Bateson provided, through his observations of the transmission of alkaptonuria in first cousin offspring, evidence of the application of Mendelian genetics to certain human traits and diseases. His work was corroborated by Archibald Garrod (Archibald AE. The incidence of alkaptonuria: a study in chemical individuality. Lancert 1902;ii:1616-20) and William Farabee (Farabee WC. Inheritance of digital malformations in man. In: Papers of the Peabody Museum of American Archaeology and Ethnology. Cambridge, Mass: Harvard University, 1905; 65-78), who recorded the familial tendencies of inheritance of malformations of human hands and feet. These were the pioneers of the hunt for disease genes that would continue through the century and result in the discovery of hundreds of genes that can be associated with different diseases. Despite many ground-breaking discoveries during the last century, we are far from having a complete understanding of the intricate network of molecular processes involved in diseases, and we are still searching for the cures for most complex diseases. In the last few years, new genome sequencing and other high-throughput experimental techniques have generated vast amounts of molecular and clinical data that contain crucial information with the potential of leading to the next major biomedical discoveries. The need to mine, visualize and integrate these data has motivated the development of several informatics approaches that can broadly be grouped in the research area of 'translational bioinformatics'. This review highlights the latest advances in the field of translational bioinformatics, focusing on the advances of computational techniques to search for and classify disease genes.

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Advances in translational bioinformatics: computational approaches for the hunting of disease genes

Background 
Toll-like receptor 4 (TLR4) is a key innate immunity receptor that initiates an inflammatory response. Growing evidence suggests that mutation of TLR4 gene may play a role in the development of cancers. This study aimed to investigate the temporal relationship of single nucleotide polymorphisms of TLR4 and the risk of hepatocellular carcinoma, a single center-based case-control study was conducted.


Methods 
A systematic genetic analysis of sequence variants of TLR4 by evaluating ten single-nucleotide polymorphisms was performed from 216 hepatocellular carcinoma cases and 228 controls.


Results 
Six single nucleotide polymorphisms of the TLR4 in the 5′-untranslated region and intron were associated with risk of hepatocellular carcinoma. Individuals carrying the heterozygous genotypes for the rs10759930, rs2737190, rs10116253, rs1927914, rs12377632 and rs1927911 had significantly decreased risk of hepatocellular carcinoma (adjusted odds ratio [OR], from 0.527 to 0.578, P<0.01) comparing with those carrying wild-type homozygous genotypes. In haplotype analysis, one haplotype (GCCCTTAG) of TLR4 was associated significantly with decrease of the occurrence of hepatocellular carcinoma (OR, 0.556, 95% confidence interval [CI], 0.407–0.758, P = 0.000).


Conclusions 
Collectively, these results suggested that the risk of hepatocellular carcinoma was associated with TLR4 sequence variation. TLR4 single nucleotide polymorphisms may play an important protective role in the development of hepatocellular carcinoma.

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Single nucleotide polymorphisms of Toll-like receptor 4 decrease the risk of development of hepatocellular carcinoma.

Toll-like receptors (TLRs) participate in the defence against bacterial infections that are common in patients with Chronic Obstructive Pulmonary Disease (COPD). We studied all tagging SNPs in TLR2 and TLR4 and their associations with the level and change over time of both FEV1 and sputum inflammatory cells in moderate-to-severe COPD. Nine TLR2 SNPs and 17 TLR4 SNPs were genotyped in 110 COPD patients. Associations of SNPs with lung function and inflammatory cells in induced sputum were analyzed cross-sectionally with linear regression and longitudinally with linear mixed-effect models. Two SNPs in TLR2 (rs1898830 and rs11938228) were associated with a lower level of FEV1 and accelerated decline of FEV1 and higher numbers of sputum inflammatory cells. None of the TLR4 SNPs was associated with FEV1 level. Eleven out of 17 SNPs were associated with FEV1 decline, including rs12377632 and rs10759931, which were additionally associated with higher numbers of sputum inflammatory cells at baseline and with increase over time. This is the first longitudinal study showing that tagging SNPs in TLR2 and TLR4 are associated with the level and decline of lung function as well as with inflammatory cell numbers in induced sputum in COPD patients, suggesting a role in the severity and progression of COPD.

/pdf/toll-like-receptor-tlr2-and-tlr4-polymorphisms-and-chronic-50bz6j4ykr.pdf

Toll-Like Receptor (TLR2 and TLR4) Polymorphisms and Chronic Obstructive Pulmonary Disease

Insulin-like growth factor 1 receptor (IGF1R) acts as a critical mediator of cell proliferation and survival. Many single nucleotide polymorphisms (SNPs) found in the IGF1R gene have been associated with various diseases, including both breast and prostate cancer. The genetics of these diseases could be better understood by knowing the functions of these SNPs. In this study, we performed a comprehensive analysis of the functional and structural impact of all known SNPs in this gene using publicly available computational prediction tools. Out of a total of 2412 SNPs in IGF1R retrieved from dbSNP, we found 32 nsSNPs, 58 sSNPs, 83 mRNA 3' UTR SNPs, and 2225 intronic SNPs. Among the nsSNPs, a total of six missense nsSNPs were found to be damaging by both a sequence homology-based tool (SIFT) and a structural homology-based method (PolyPhen), and one nonsense nsSNP was found. Further, we modeled mutant proteins and compared the total energy values with the native IGF1R protein, and showed that a mutation from arginine to cysteine at position 1216 (rs61740868) on the surface of the protein caused the greatest impact on stability. Also, the FASTSNP tool suggested that 31 sSNPs and 3 intronic SNPs might affect splicing regulation. Based on our investigation, we report potential candidate SNPs for future studies on IGF1R mutations.

/pdf/a-comprehensive-in-silico-analysis-of-the-functional-and-4m79vec03y.pdf

A Comprehensive In Silico Analysis of the Functional and Structural Impact of SNPs in the IGF1R Gene

Recent genome-wide association studies (GWAS) have reported multiple genetic variations at 5p15.33 (TERT-CLPTM1L) associated with risk of lung cancer. However, most of the associated variations identified by GWAS thus far are unlikely to be the actual causal variants, but may be mostly marker-single nucleotide polymorphisms tagging functional variations that influence gene expression. This study aimed to explore the function-validated and potentially functional variations in TERT-CLPTM1L locus conferring susceptibility to lung cancer. A case–control study including 502 cases and 502 controls in Chinese Han population was firstly conducted. Bioinformatic approaches are applied to prioritize genetic variations based on their potential functionality. In the logistic regression analysis, TERT-rs2853669, rs2736108, and CLPTM1L-rs31490 were significant associated with increased risk of lung cancer (OR = 1.46, 95% CI = 1.22–1.75; OR = 1.22, 95% CI = 1.00–1.49 and OR = 1.74, 95% CI = 1.35–2.23 under additive model, respectively). The significant associations were observed in non-small-cell lung cancer but not-in-small-cell lung cancer, and more prominent in adenocarcinoma. Haplotype analysis presented a significant allele-dose effect of haplotypes in increasing risk of lung cancer (P for trend = 1.894 × 10−6). Moreover, significant multiplicative interactions were observed between smoking and these three polymorphisms of TERT-rs2853669, rs2736108, and CLPTM1L-rs31490, even after bonferroni correction for multiple comparisons (Pinteraction = 1.316 × 10−9, 3.912 × 10−4, and 2.483 × 10−5, respectively). These findings indicated that the function-validated and potentially functional variations in TERT-CLPTM1L locus, modified by smoking, may play a substantial role in the susceptibility to lung cancer. © 2013 Wiley Periodicals, Inc.

Genetic variations in TERT-CLPTM1L locus are associated with risk of lung cancer in Chinese population.

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans Understanding the functions of SNPs can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols To explore possible relationships between genetic mutation and phenotypic variation, different computational algorithm tools like Sorting Intolerant from Tolerant, Polymorphism Phenotyping, UTRscan, FASTSNP, and PupaSuite were used for prioritization of high-risk SNPs in coding region (exonic nonsynonymous SNPs) and noncoding regions (intronic and exonic 5' and 3'-untranslated region (UTR) SNPs) In this work, we have analyzed the SNPs that can alter the expression and function of transcriptional factor TP53 as a pipeline and for providing a guide to experimental work We identified the possible mutations and proposed modeled structure for the mutant proteins and compared them with the native protein These nsSNPs play a critical role in cancer association studies aiming to explain the disparity in cancer treatment responses as well as to improve the effectiveness of the cancer treatments Our results endorse the study with in vivo experimental protocols

Pragnya Hota

Papers

Applications of computational algorithm tools to identify functional SNPs