Single nucleotide polymorphisms and disease gene mapping

A Novel Interaction between a 23-SNP Genetic Risk Score and Monounsaturated Fatty Acid Intake on HbA1c Levels in Southeast Asian Women

Metabolic diseases result from interactions between genetic and lifestyle factors. Understanding the combined influences of single-nucleotide polymorphisms (SNPs) and lifestyle is crucial. This study employs genetic risk scores (GRS) to assess SNPs, providing insight beyond single gene/SNP studies by revealing synergistic effects. Here, we aim to investigate the association of a 23-SNP GRS with metabolic disease-related traits (obesity and type 2 diabetes) to understand if these associations are altered by lifestyle/dietary factors. For this study, 106 Minangkabau women were included and underwent physical, anthropometric, biochemical, dietary and genetic evaluations. The interaction of GRS with lifestyle factors was analyzed using linear regression models, adjusting for potential confounders. No statistically significant associations were observed between GRS and metabolic traits; however, this study demonstrates a novel interaction observed between 13-SNP GRS and monounsaturated fatty acid (MUFA) intake, and that it had an effect on HbA1c levels (p = 0.026). Minangkabau women with low MUFA intake (≤7.0 g/day) and >13 risk alleles had significantly higher HbA1c levels (p = 0.010). This finding has implications for public health, suggesting the need for large-scale studies to confirm our results before implementing dietary interventions in the Indonesian population. Identifying genetic influences on dietary response can inform personalized nutrition strategies to reduce the risk of metabolic disease.

Nanodiagnostics: A review of the medical capabilities of nanopores

Modern diagnostics strive to be accurate, fast, and inexpensive in addition to properly identifying the presence of a disease, infection, or illness. Early diagnosis is key; catching a disease in its early stages can be the difference between fatality and treatment. The challenge with many diseases is that detectability of the disease scales with disease progression. Since single molecule sensors, e.g., nanopores, can sense biomolecules at low concentrations, they have the potential to become clinically relevant in many of today's medical settings. With nanopore-based sensing, lower volumes and concentrations are required for detection, enabling it to be clinically beneficial. Other advantages to using nanopores include that they are tunable to an enormous variety of molecules and boast low costs, and fabrication is scalable for manufacturing. We discuss previous reports and the potential for incorporating nanopores into the medical field for early diagnostics, therapeutic monitoring, and identifying relapse/recurrence.

Differential genotypic signatures of Toll-like receptor polymorphisms among dengue-chikungunya mono- and co-infected Eastern Indian patients

Dengue (DENV) and chikungunya (CHIKV) viral infections trigger high patient morbidity and mortality. Mono-/co-infection of these viruses activates innate immune response, triggering Toll-like receptor (TLR) pathways. The present study investigated the differential role of TLR3, 7 and 8 single-nucleotide polymorphisms (SNPs) between mono- and co-infected Eastern Indian patients. Interaction of TLR polymorphic variants with signal peptidase complex (SPC18) was explored which might affect immune signalling against DENV/CHIKV infections. Out of 550 febrile symptomatic patients, 128 DENV-CHIKV co-infected samples were genotyped for eight SNPs of TLR3 (rs3775290-chr4:186083063), TLR7 (rs179008-chrX:12885540, rs5741880-chrX:12869297, rs179010-chrX:12884766, rs3853839-chrX:12889539) and TLR8 (rs5744080-chrX:12919685, rs3764879-chrX:12906578, rs3764880-chrX:12906707) by PCR-RFLP along with 157 healthy individuals. Statistical analysis established genotypic association of TLR SNPs with DENV-CHIKV co-infection, and difference between mono- and co-infected patients and their role in determining high viral load (HVL) during competitive viral replication among co-infected patients. In silico protein-protein docking evaluated interactive effect of TLR variants with SPC18. The findings revealed patients with CC genotypes of TLR7 and 8 SNPs were significantly susceptible towards co-infection, whereas specific genotypes of TLR7 and 8 imparted protection against co-infection. Differential analysis between mono-/co-infected patients revealed distinct genotypic distribution of TLR3, 7 and 8 SNPs. Co-infected patients with TT-rs179010 exhibited DENV-HVL, whereas CHIKV-HVL was detected among patients with other genotypes. Molecular docking of TLR7-rs179008 Q variant and TLR8-rs3764880 V variant with SPC18 generated better free binding energy. This study underlined the importance of TLR7 and 8 SNPs towards mono-/co-infection of DENV/CHIKV, with certain genotypes associated with co-infection susceptibility. Moreover, it suggested a probable role of specific genotypes of TLR7 and 8 polymorphisms imparting high dengue/chikungunya viral load among co-infected patients.

Candidate gene association analysis of multiple sclerosis in the Jordanian Arab population: A case-control study

Multiple sclerosis (MS) is a clinically heterogeneous multifactorial disorder which is one of the most prevalent neurological disorders of females and young people. Both genetic and environmental factors are playing an important role in the pathophysiology of MS. The main objective of this study is to identify the relationship between numbers of genetic variants within different candidate genes (IL7R, LAG3, and CD40) and the risk of developing MS in the Jordanian Arab population. This case-control study consists of 218 MS patients chosen from neurology clinics at different hospitals in Jordan and ethnically matched 227 healthy controls. Genomic DNA was extracted from blood samples. Genotyping of the candidate gene polymorphisms was conducted using the Sequenom MassARRAY system. Statistical analysis was performed to identify the genetic association of the studied SNPs with MS. Twenty-one variants were studied, three of them were found to be associated with MS (rs6897932 (P-value = 0.01) and rs13188960 (P-value = 0.005) within IL7R gene and LAG3 rs2365095, (P-value = 0.03) within LAG3 gene). Moreover, no significant association was found between MS and the genetic polymorphisms of the CD40 gene. After correction for multiple comparisons, only rs13188960 SNP remained significantly with MS. This is the first study of the genetic association with MS in the Jordanian Arab population to provided evidence of the genetic association of IL7R (rs6897932, rs13188960) and LAG3 (rs2365095) gene polymorphisms with MS. These findings may contribute to our understanding of MS and optimize the therapy protocol for individuals.

Unraveling the susceptibility of paracoccidioidomycosis: Insights towards the pathogen-immune interplay and immunogenetics

Paracoccidioidomycosis (PCM) is a life-threatening systemic mycosis caused by Paracoccidioides spp. This disease comprises three clinical forms: symptomatic acute and chronic forms (PCM disease) and PCM infection, a latent form without clinical symptoms. PCM disease differs markedly according to severity, clinical manifestations, and host immune response. Fungal virulence factors and adhesion molecules are determinants for entry, latency, immune escape and invasion, and dissemination in the host. Neutrophils and macrophages play a paramount role in first-line defense against the fungus through the recognition of antigens by pattern recognition receptors (PRRs), activating their microbicidal machinery. Furthermore, the clinical outcome of the PCM is strongly associated with the variability of cytokines and immunoglobulins produced by T and B cells. While the mechanisms that mediate susceptibility or resistance to infection are dictated by the immune system, some genetic factors may alter gene expression and its final products and, hence, modulate how the organism responds to infection and injury. This review outlines the main findings relative to this topic, addressing the complexity of the immune response triggered by Paracoccidioides spp. infection from preclinical investigations to studies in humans. Here, we focus on mechanisms of fungal pathogenesis, the patterns of innate and adaptive immunity, and the genetic and molecular basis related to immune response and susceptibility to the development of the PCM and its clinical forms. Immunogenetic features such as HLA system, cytokines/cytokines receptors genes and other immune-related genes, and miRNAs are likewise discussed. Finally, we point out the occurrence of PCM in patients with primary immunodeficiencies and call attention to the research gaps and challenges faced by the PCM field.

Relationship between miR-155 and miR-146a polymorphisms and susceptibility to multiple sclerosis in an Egyptian cohort

Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system. It was previously demonstrated that miR-155 and miR-146a served a vital role in the pathophysiology of MS, and single nucleotide polymorphisms in miR-155 and miR-146a were found to be associated with the susceptibility to different autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis and type I diabetes. The aim of the present study was to analyze the association between susceptibility to MS and two genetic polymorphisms (miR-155 rs767649 A>T and miR-146a rs57095329 A>G) in a cohort of Egyptian patients. The presence of the two polymorphisms were analyzed in 114 patients with MS and 152 healthy controls using quantitative PCR. The present study demonstrated for the first time that: The TT genotype and T allele in miR-155 (rs767649 A>T) polymorphism were associated with an increased risk of MS; the miR-146a (rs57095329 A>G) mutated G allele conferred protection against the development of MS in all genetic models; miR-155 rs767649 A>T was a risk associated polymorphism of MS in females, but not in males; and miR-155 rs767649 AT/TT and miR-146a rs57095329 GG genotypes showed significantly higher distributions among patients with higher Expanded Disability Status Scale scores and secondary progressive MS subgroups. Therefore, miR-155 rs767649 polymorphism may confer susceptibility to MS, whereas miR-146a rs57095329 may be protective against MS in an Egyptian cohort.

Variants in ARID5B gene are associated with the development of acute lymphoblastic leukemia in Mexican children

A high impact of ARID5B SNPs on acute lymphoblastic leukemia (ALL) susceptibility has been described in Hispanic children; therefore, it is relevant to know if they influence the high incidence of childhood-ALL in Mexicans. Seven SNPs (rs10821936, rs10994982, rs7089424, rs2393732, rs2393782, rs2893881, rs4948488) of ARID5B were analyzed in 384 controls and 298 ALL children using genomic DNA and TaqMan probes. The SNPs were analyzed for deviation of Hardy-Weinberg equilibrium; Fisher's exact test was used to compare the genotypic and allelic frequencies between controls and patients. The association between SNPs and ALL susceptibility was calculated, and haplotype and ancestry analyses were conducted. All SNPs were associated with ALL, pre-B ALL, and hyperdiploid-ALL susceptibility (p < 0.05). No association with T-ALL and gene fusions was found (p > 0.05). The seven SNPs were associated with risk of pre-B ALL in younger children; however, rs2393732, rs2393782, rs2893881, and rs4948488 were not associated with susceptibility in older children and adolescents. The CAG haplotype (rs10821936, rs10994982, rs7089424) was strongly associated with ALL risk in our population (p < 0.00001). The frequency of all risk alleles in our ALL, pre-B, and hyperdiploid-ALL patients was higher than that in Hispanic children reported. This is the first report showing the association between rs2393732, rs2393782, and rs4948488 with pre-B hyperdiploid-ALL children. The G allele at rs2893881 confers major risk for pre-B hyperdiploid-ALL in Mexican (OR, 2.29) than in Hispanic children (OR, 1.71). The genetic background of our population could influence the susceptibility to ALL and explain its high incidence in Mexico.

Simpute: An Efficient Solution for Dense Genotypic Data

Single nucleotide polymorphism (SNP) data derived from array-based technology or massive parallel sequencing are often flawed with missing data. Missing SNPs can bias the results of association analyses. To maximize information usage, imputation is often adopted to compensate for the missing data by filling in the most probable values. To better understand the available tools for this purpose, we compare the imputation performances among BEAGLE, IMPUTE, BIMBAM, SNPMStat, MACH, and PLINK with data generated by randomly masking the genotype data from the International HapMap Phase III project. In addition, we propose a new algorithm called simple imputation (Simpute) that benefits from the high resolution of the SNPs in the array platform. Simpute does not require any reference data. The best feature of Simpute is its computational efficiency with complexity of order (mw + n), where n is the number of missing SNPs, w is the number of the positions of the missing SNPs, and m is the number of people considered. Simpute is suitable for regular screening of the large-scale SNP genotyping particularly when the sample size is large, and efficiency is a major concern in the analysis.

The human Major Histocompatibility Complex as a paradigm in genomics research

Since its discovery more than 50 years ago, the human Major Histocompatibility Complex (MHC) on chromosome 6p21.3 has been at the forefront of human genetic research. Here, we review from a historical perspective the major advances in our understanding of the nature and consequences of genetic variation which have involved the MHC, as well as highlighting likely future directions. As a consequence of its particular genomic structure, its remarkable polymorphism and its early implication in numerous diseases, the MHC has been considered as a model region for genomics, being the first substantial region to be sequenced and establishing fundamental concepts of linkage disequilibrium, haplotypic structure and meiotic recombination. Recently, the MHC became the first genomic region to be entirely re-sequenced for common haplotypes, while studies mapping gene expression phenotypes across the genome have strongly implicated variation in the MHC. This review shows how the MHC continues to provide new insights and remains in the vanguard of contemporary research in human genomics.

Cecal ligation and puncture

The model of cecal ligation and puncture (CLP) in rodents has been used extensively to investigate the clinical settings of sepsis and septic shock. This model produces a hyperdynamic, hypermetabolic state that can lead to a hypodynamic, hypometabolic stage, and eventual death. Blood cultures are positive for enteric organisms very early after CLP. The model has been widely used over the past 26 years and is highly versatile in adapting to a range of severity and testing objectives. It is inexpensive to prepare and technically straightforward. Aspects of sepsis research investigated using CLP include energetics, metabolism, resuscitation, antibiotic therapy, microbial factors, cardiovascular responses, immune function, mediator release, and cytokine expression patterns. The challenge of the small circulating blood volume in rodents can be overcome by using micromethods that enable analysis of small volumes, or alternatively, by using a large number of animals to obtain serial samples.

Integration of text- and data-mining using ontologies successfully selects disease gene candidates

Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (±18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues.