Investigation of DNA polymorphisms in SMAD genes for genetic predisposition to diabetic nephropathy in patients with type 1 diabetes mellitus

Aims/hypothesis: SMAD proteins are involved in multiple signalling pathways and are key modulators of gene expression. We hypothesised that genetic variation in selected SMAD genes contributes to susceptibility to diabetic nephropathy. Methods: We selected 13 haplotype tag (ht) single nucleotide polymorphisms (SNPs) from 67 variants identified by resequencing the SMAD2 and SMAD3 genes. For SMAD1, SMAD4 and SMAD5 genes, genotype data were downloaded for 217 SNPs from Phase II of the International HapMap project. Of these, 85 SNPs met our inclusion criteria, resulting in the selection of 13 tag SNPs for further investigation. A case-control approach was employed, using 267 nephropathic patients and 442 controls with type 1 diabetes from Ireland. Two further populations (totalling 1,407 patients, 2,238 controls) were genotyped to validate initial findings. Genotyping was conducted using iPLEX, TaqMan and gel electrophoresis.
Results: The distribution of genotypes was in Hardy-Weinberg equilibrium. Analysis by the ? 2 test of genotype and allele frequencies in patients versus controls in the Irish population (n?=?709) revealed evidence for the association of one allele at 5% level of significance (rs10515478, p uncorrected?=?0.006; p corrected?=?0.04). This finding represents a relatively small difference in allele frequency of 6.4% in the patient group compared with 10.7% in the control group; this difference was not supported in subsequent investigations using DNA from European individuals with similar phenotypic characteristics.
Conclusions/interpretation: We selected an appropriate subset of variants for the investigation of common genetic risk factors and assessed SMAD1 to SMAD5 genes for association with diabetic nephropathy. We conclude that common polymorphisms in these genes do not strongly influence genetic susceptibility to diabetic nephropathy in white individuals with type 1 diabetes mellitus.

HOX genes: seductive science, mysterious mechanisms

HOX genes are evolutionarily highly conserved. The HOX proteins which they encode are master regulators of embryonic development and continue to be expressed throughout postnatal life. The 39 human HOX genes are located in four clusters (A-D) on different chromosomes at 7p15, 17q21 [corrected] 12q13, and 2q31 respectively and are assumed to have arisen by duplication and divergence from a primordial homeobox gene. Disorders of limb formation, such as hand-foot-genital syndrome, have been traced to mutations in HOXA13 and HOXD13. Evolutionary conservation provides unlimited scope for experimental investigation of the functional control of the Hox gene network which is providing important insights into human disease. Chromosomal translocations involving the MLL gene, the human homologue of the Drosophila gene trithorax, create fusion genes which exhibit gain of function and are associated with aggressive leukaemias in both adults and children. To date 39 partner genes for MLL have been cloned from patients with leukaemia. Models based on specific translocations of MLL and individual HOX genes are now the subject of intense research aimed at understanding the molecular programs involved, and ultimately the design of chemotherapeutic agents for leukaemia. Investigation of the role of HOX genes in cancer has led to the concept that oncology may recapitulate ontology, a challenging postulate for experimentalists in view of the functional redundancy implicit in the HOX gene network.

The pathophysiology of HOX genes and their role in cancer

The HOM-C clustered prototype homeobox genes of Drosophila, and their counterparts, the HOX genes in humans, are highly conserved at the genomic level. These master regulators of development continue to be expressed throughout adulthood in various tissues and organs. The physiological and patho-physiological functions of this network of genes are being avidly pursued within the scientific community, but defined roles for them remain elusive. The order of expression of HOX genes within a cluster is co-ordinated during development, so that the 3' genes are expressed more anteriorly and earlier than the 5' genes. Mutations in HOXA13 and HOXD13 are associated with disorders of limb formation such as hand-foot-genital syndrome (HFGS), synpolydactyly (SPD), and brachydactyly. Haematopoietic progenitors express HOX genes in a pattern characteristic of the lineage and stage of differentiation of the cells. In leukaemia, dysregulated HOX gene expression can occur due to chromosomal translocations involving upstream regulators such as the MLL gene, or the fusion of a HOX gene to another gene such as the nucleoporin, NUP98. Recent investigations of HOX gene expression in leukaemia are providing important insights into disease classification and prediction of clinical outcome. Whereas the oncogenic potential of certain HOX genes in leukaemia has already been defined, their role in other neoplasms is currently being studied. Progress has been hampered by the experimental approach used in many studies in which the expression of small subsets of HOX genes was analysed, and complicated by the functional redundancy implicit in the HOX gene system. Attempts to elucidate the function of HOX genes in malignant transformation will be enhanced by a better understanding of their upstream regulators and downstream target genes.

Recapitulation of embryological programmes in renal fibrosis - The importance of epithelial cell plasticity and developmental genes

Chronic fibrosis represents the final common pathway in progressive renal disease. Myofibroblasts deposit the constituents of renal scar, thus crippling renal function. It has recently emerged that an important source of these pivotal effector cells is the injured renal epithelium. This review concentrates on the process of epithelial-mesenchymal transition (EMT) and its regulation. The role of the developmental gene, gremlin, which is reactivated in adult renal disease, is the subject of particular focus. This member of the cysteine knot protein superfamily is critical to the process of nephrogenesis but quiescent in normal adult kidney. There is increasing evidence that gremlin expression reactivates in diabetic nephropathy, and in the diseased fibrotic kidney per se. Known to antagonize members of the bone morphogenic protein (BMP) family, gremlin may also act downstream of TGF-beta in induction of EMT. An increased understanding of the extracellular modulation of EMT and, in particular, of the gremlin-BMP axis may result in strategies that can halt or reverse the devastating progression of chronic renal fibrosis. Copyright (c) 2006 S. Karger AG, Basel.

Integrated structure selection and parameter optimisation for eng-genes neural models

The eng-genes concept involves the use of fundamental known system functions as activation functions in a neural model to create a 'grey-box' neural network. One of the main issues in eng-genes modelling is to produce a parsimonious model given a model construction criterion. The challenges are that (1) the eng-genes model in most cases is a heterogenous network consisting of more than one type of nonlinear basis functions, and each basis function may have different set of parameters to be optimised; (2) the number of hidden nodes has to be chosen based on a model selection criterion. This is a mixed integer hard problem and this paper investigates the use of a forward selection algorithm to optimise both the network structure and the parameters of the system-derived activation functions. Results are included from case studies performed on a simulated continuously stirred tank reactor process, and using actual data from a pH neutralisation plant. The resulting eng-genes networks demonstrate superior simulation performance and transparency over a range of network sizes when compared to conventional neural models. (c) 2007 Elsevier B.V. All rights reserved.

Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae

Background: Gene networks are a representation of molecular interactions among genes or products thereof and, hence, are forming causal networks. Despite intense studies during the last years most investigations focus so far on inferential methods to reconstruct gene networks from experimental data or on their structural properties, e.g., degree distributions. Their structural analysis to gain functional insights into organizational principles of, e.g., pathways remains so far under appreciated.

Predicting Cell Cycle Regulated Genes by Causal Interactions

The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e. g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first.