Leprosy as a genetic model for susceptibility to common infectious diseases

Leprosy (Hansen’s disease) is a human infectious disease that can be effectively treated with long-term administration of multi-drug therapy. In 2006, over 250,000 new cases were reported to the World Health Organization. In the nineteenth century, disagreement among leprologists regarding the hereditary or infectious nature of leprosy was resolved with the identification of the etiological agent, Mycobacterium leprae. However, epidemiological studies maintain the importance of host genetics in leprosy susceptibility. A model free genome-wide linkage scan in multi-case families from Vietnam led to the positional cloning of global genetic risk factors in the PARK2/PACRG and LTA genes. The process of identifying the susceptibility variants provided invaluable insight into the replication of genetic effects, particularly the importance of considering population-specific linkage-disequilibrium structure. As such, these studies serve to improve our understanding of leprosy pathogenesis by implicating novel biological pathways while simultaneously providing a genetic model for common infectious diseases.     

Immunogenetics of leishmanial and mycobacterial infections: the Belem Family Study.

In the 1970s and 1980s, analysis of recombinant inbred, congenic and recombinant haplotype mouse strains permitted us to effectively ''scan'' the murine genome for genes controlling resistance and susceptibility to leishmanial infections. Five major regions of the genome were implicated in the control of infections caused by different Leishmania species which, because they show conserved synteny with regions of the human genome, immediately provides candidate gene regions for human disease susceptibility genes. A common intramacrophage niche for leishmanial and mycobacterial pathogens, and a similar spectrum of immune response and disease phenotypes, also led to the prediction that the same genes/candidate gene regions might be responsible for genetic susceptibility to mycobacterial infections such as leprosy and tuberculosis. Indeed, one of the murine genes (Nramp1) was identified for its role in controlling a range of intramacrophage pathogens including leishmania, salmonella and mycobacterium infections. In recent studies, multicase family data on visceral leishmaniasis and the mycobacterial diseases, tuberculosis and leprosy, have been collected from north-eastern Brazil and analysed to determine the role of these candidate genes/regions in determining disease susceptibility. Complex segregation analysis provides evidence for one or two major genes controlling susceptibility to tuberculosis in this population. Family-based linkage analyses (combined segregation and linkage analysis; sib-pair analysis), which have the power to detect linkage between marker loci in candidate gene regions and the putative disease susceptibility genes over 10-20 centimorgans, and transmission disequilibrium testing, which detects allelic associations over 1 centimorgan (ca. 1 megabase), have been used to examine the role of four regions in determining disease susceptibility and/or immune response phenotype. Our results demonstrate: (i) the major histocompatibility complex (MHC: H-2 in mouse, HLA in man: mouse chromosome 17/human 6p; candidates class II and class III including TNF alpha/beta genes) shows both linkage to, and allelic association with, leprosy per se, but is only weakly associated with visceral leishmaniasis and shows neither linkage to nor allelic association with tuberculosis; (ii) no evidence for linkage between NRAMP1, the positionally cloned candidate for the murine macrophage resistance gene Ity/Lsh/Bcg (mouse chromosome 1/human 2q35), and susceptibility to tuberculosis or visceral leishmaniasis could be demonstrated in this Brazilian population; (iii) the region of human chromosome 17q (candidates NOS2A, SCYA2-5) homologous with distal mouse chromosome 11, originally identified as carrying the Scl1 gene controlling healing versus nonhealing responses to Leishmania major, is linked to tuberculosis susceptibility; and (iv) the ''T helper 2'' cytokine gene cluster (proximal murine chromosome 11/human 5q; candidates IL4, IL5, IL9, IRF1, CD14) controlling later phases of murine L. major infection, is not linked to human disease susceptibility for any of the three infections, but shows linkage to and highly significant allelic association with ability to mount an immune response to mycobacterial antigens. These studies demonstrate that the ''mouse-to-man'' strategy, refined by our knowledge of the human immune response to infection, can lead to the identification of important candidate gene regions in man.     

Localization and identification of human quantitative trait loci: king harvest has surely come

The scientific process of localization and subsequent identification of genes influencing risk of common diseases is still in its infancy. Initial localization of disease-related loci has traditionally been performed using family-based linkage methods to scan the genome. Early pronouncements of the failure of this approach for common diseases were premature and based on comparing suboptimal linkage designs with overly optimistic and empirically unproven association-based designs. On the contrary, substantial recent progress in the positional cloning of genes influencing such complex phenotypes suggests that modern approaches based around a family-based linkage paradigm will be successful. In particular, the rapidly growing emphasis on the analysis of the genetic basis of quantitative correlates of disease risk represents a novel and promising approach in which initial localization is performed using linkage and subsequent identification utilizes association approaches in positional candidate genes.     

Leprosy as a genetic disease

Leprosy (Hansen??s disease) is a human infectious disease whose etiological agent, Mycobacterium leprae, was identified by G. H. A. Hansen in the 19th century. Despite the high efficacy of multidrug therapy (<0.1% annual relapse rate), transmission is persistent. In 2008, approximately 250,000 new cases were reported to the World Health Organization. Clinically, leprosy presents as either the paucibacillary (1?C5 lesions) or the multibacillary (>5 lesions) subtype, highly reflective of a Th1 (cell-mediated) or Th2 (humoral) host immune response, respectively. Subsequent to Mycobacterium leprae exposure, epidemiological studies (e.g., twin studies and complex segregation analyses) maintain the importance of host genetics in susceptibility to leprosy. The results of genome-wide analyses (linkage and association) and candidate gene studies suggest an independent genetic control over both susceptibility to leprosy per se and development of clinical subtype. Moreover, the emergence of a shared genetic background between leprosy and several inflammatory/autoimmune diseases suggests that leprosy is a suitable model for studying the genetic architecture and subsequent pathogenesis of both infectious and inflammatory/autoimmune diseases. We provide the example of NOD2 (Crohn??s disease gene) and LTA (myocardial infarction gene) and the implication of a common genetic risk factor between these two diseases and leprosy. The value of leprosy as a model disease therefore extends far beyond this ancient disease to common afflictions of the 21st century.     

Molecular genetic approaches for studying the etiology of diabetic nephropathy

A critical challenge faced by clinical nephrologists today is the escalating number of patients developing end stage renal disease, a major proportion of which is attributed to diabetic nephropathy (DN). The need for new measures to prevent and treat this disease cannot be overemphasized. To this end, modern genetic approaches provide powerful tools to investigate the etiology of DN. Human studies have already established the importance of genetic susceptibility for DN. Several major susceptibility loci have been identified using linkage studies. In addition, linkage studies in rodents have pinpointed promising chromosomal segments that influence renal traits. Besides augmenting our understanding of disease pathogenesis, these animal studies may facilitate the cloning of disease susceptibility genes in man through the identification of homologous regions that contribute to renal disease. In human diabetes, various genes have been evaluated for their risk contribution to DN. This widespread strategy has been propelled by our knowledge of the glucose-activated pathways underlying DN. Evidence has emerged that a true association does indeed exist for some candidate genes. Furthermore, the in vivo manipulation of gene expression has shown that these genes can modify features of DN in transgenic and knockout rodent models, thus corroborating the findings from human association studies. Still, the exact molecular mechanisms involving these genes remain to be fully elucidated. This formidable task may be accomplished by continuing to harness the synergy between human and experimental genetic approaches. In this respect, our review provides a first synthesis of the current literature to facilitate this challenging effort.     

Candidate gene association study in type 2 diabetes indicates a role for genes involved in beta-cell function as well as insulin action

Type 2 diabetes is an increasingly common, serious metabolic disorder with a substantial inherited component. It is characterised by defects in both insulin secretion and action. Progress in identification of specific genetic variants predisposing to the disease has been limited. To complement ongoing positional cloning efforts, we have undertaken a large-scale candidate gene association study. We examined 152 SNPs in 71 candidate genes for association with diabetes status and related phenotypes in 2,134 Caucasians in a case-control study and an independent quantitative trait (QT) cohort in the United Kingdom. Polymorphisms in five of 15 genes (33%) encoding molecules known to primarily influence pancreatic beta-cell function-ABCC8 (sulphonylurea receptor), KCNJ11 (KIR6.2), SLC2A2 (GLUT2), HNF4A (HNF4alpha), and INS (insulin)-significantly altered disease risk, and in three genes, the risk allele, haplotype, or both had a biologically consistent effect on a relevant physiological trait in the QT study. We examined 35 genes predicted to have their major influence on insulin action, and three (9%)-INSR, PIK3R1, and SOS1-showed significant associations with diabetes. These results confirm the genetic complexity of Type 2 diabetes and provide evidence that common variants in genes influencing pancreatic beta-cell function may make a significant contribution to the inherited component of this disease. This study additionally demonstrates that the systematic examination of panels of biological candidate genes in large, well-characterised populations can be an effective complement to positional cloning approaches. The absence of large single-gene effects and the detection of multiple small effects accentuate the need for the study of larger populations in order to reliably identify the size of effect we now expect for complex diseases.     

Evolution, revolution and heresy in the genetics of infectious disease susceptibility

Infectious pathogens have long been recognized as potentially powerful agents impacting on the evolution of human genetic diversity. Analysis of large-scale case-control studies provides one of the most direct means of identifying human genetic variants that currently impact on susceptibility to particular infectious diseases. For over 50 years candidate gene studies have been used to identify loci for many major causes of human infectious mortality, including malaria, tuberculosis, human immunodeficiency virus/acquired immunodeficiency syndrome, bacterial pneumonia and hepatitis. But with the advent of genome-wide approaches, many new loci have been identified in diverse populations. Genome-wide linkage studies identified a few loci, but genome-wide association studies are proving more successful, and both exome and whole-genome sequencing now offer a revolutionary increase in power. Opinions differ on the extent to which the genetic component to common disease susceptibility is encoded by multiple high frequency or rare variants, and the heretical view that most infectious diseases might even be monogenic has been advocated recently. Review of findings to date suggests that the genetic architecture of infectious disease susceptibility may be importantly different from that of non-infectious diseases, and it is suggested that natural selection may be the driving force underlying this difference.     

Genetics and genomics in infectious disease susceptibility.

The past decade has witnessed a rapid transition from the first positional cloning of an infectious disease susceptibility gene (Slc11a1, also called Nramp1) in the mouse to genome-wide scans in human multicase families and the identification of potential disease-causing genes by simple inspection of the public human genome databases. Pathogen genome projects have facilitated multilocus sequence typing of pathogen isolates and studies of ecological fitness and virulence patterns in disease-causing isolates. Comparative sequence analysis of pathogen strains and functional genomics studies are now underway, hopefully providing new insight into infectious disease susceptibility.     

The battle of two genomes: genetics of bacterial host/pathogen interactions in mice

Genetic factors strongly determine the outcome of infectious diseases caused by various pathogens. The molecular mechanisms of resistance and susceptibility in humans, however, remains largely unknown. Complex interactions of multiple genes that control the host response to a pathogen further complicate the picture. Animal models have a tremendous potential to dissect the complex genetic system of host–pathogen interaction into single components. This is particularly true for the mouse, which will continue to develop into an invaluable tool in the identification and cloning of host resistance genes. Three main approaches have been taken to establish mouse models for human infectious diseases: 1) Production of mouse mutants by gene targeting; 2) positional cloning of host-resistance genes in mutant mice; and 3) mapping and characterization of quantitative trait loci (QTL) controlling the complex aspects of host–pathogen interactions. The contribution of all three methods to the understanding of infectious diseases in humans will be reviewed in this work, with a special emphasis on the studies of resistance/susceptibility mechanism in bacterial infections. Received: 7 September 2000 / Accepted: 23 November 2000     

Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD.     

Current strategies in the search for low penetrance genes in cancer

The genetic etiology of most cancers remains largely unclear and it has been hypothesised that common genetic variants with modest effects on disease susceptibility cause the bulk of this unexplained risk. Case-control association studies are considered the most effective strategy to identify these low-penetrance genes. While traditionally, such studies have focused on putative functional single nucleotide polymorphisms (SNPs) in candidate genes, a more comprehensive approach can now be taken, as a result of a number of recent developments: the mapping of the human genome, including the identification of almost ten million SNPs; and the development of high-throughput genotyping technologies that enable hundreds of thousands of SNPs to be genotyped in a single reaction, in multiple subjects and at an affordable cost. All common genomic variation can be captured by genotyping SNPs in gene-, pathway- or genome-wide-based strategies and these are now being applied to many diseases, including cancer. We present an outline of each of these approaches, including recent published examples, and discuss a number of challenges that remain to be addressed.     

From genomic advances to public health benefits: the unbearable lightness of being stuck

Genetic determinants of common human diseases are still poorly understood. Due to large investments, many small successes have been made and the research field is rapidly expanding. However, genetic susceptibility variants showing repeatable associations with common diseases are usually of small effect. They are therefore unlikely to individually explain substantial share of disease burden in any community or provide new insights into disease pathogenesis that could lead to development of new drugs effective in considerable portion of the disease cases in a population. Genetic architecture of common diseases is beginning to reveal an incredible diversity of potential genetic causes that act through somewhat limited number of mechanisms with important contribution of environmental interactions. In light of these findings, we present current understanding of genetic architecture of a spectrum of human diseases. We address the encountered problems in susceptibility gene identification, review the success of leading gene identification strategies and discuss current prospects for translating genomic advances into measurable public health benefits.     

Molecular genetics of atherosclerosis

Atherosclerosis is a complex multifocal arterial disease involving interactions of multiple genetic and environmental factors. Advances in techniques of molecular genetics have revealed that genetic polymorphisms significantly influence susceptibility to atherosclerotic vascular diseases. A large number of candidate genes, genetic polymorphisms and susceptibility loci associated with atherosclerotic diseases have been identified in recent years and their number is rapidly increasing. In this review we focus on some of the major candidate genes and genetic polymorphisms associated with human atherosclerotic vascular diseases.     

Genomics: implications for toxicology

The primary goal of the Environmental Genome Project (EGP) is the identification of human polymorphisms indicative of susceptibility to specific environmental agents. Despite evidence for a substantial genetic contribution to disease variation in the population, progress towards identifying specific genes has been slow. To date, most of the advances in our understanding of human diseases has come from genetic analyses of monogenic diseases that affect a relatively small portion of the population. The principal strategy of the EGP involves resequencing DNA samples from populations representative of the US racial and ethnic groups to develop a database of variations. Polymorphisms in specific genes may also be detected by gene-expression profiling. The identification of polymorphisms by resequencing is straightforward, and can be accomplished with minimal difficulty. Gene-expression profiling is still problematic; however, determining the functional significance of the allelic variations will be a monumental challenge involving sophisticated proteomics and population-based and animal model studies. These studies will change radically the practice of public health and clinical medicine, and the approach to the development of pharmaceuticals.     

Identification of candidate T-cell epitopes and molecular mimics in chronic Lyme disease

Elucidating the cellular immune response to infectious agents is a prerequisite for understanding disease pathogenesis and designing effective vaccines. In the identification of microbial T-cell epitopes, the availability of purified or recombinant bacterial proteins has been a chief limiting factor. In chronic infectious diseases such as Lyme disease, immune-mediated damage may add to the effects of direct infection by means of molecular mimicry to tissue autoantigens. Here, we describe a new method to effectively identify both microbial epitopes and candidate autoantigens. The approach combines data acquisition by positional scanning peptide combinatorial libraries and biometric data analysis by generation of scoring matrices. In a patient with chronic neuroborreliosis, we show that this strategy leads to the identification of potentially relevant T-cell targets derived from both Borrelia burgdorferi and the host. We also found that the antigen specificity of a single T-cell clone can be degenerate and yet the clone can preferentially recognize different peptides derived from the same organism, thus demonstrating that flexibility in T-cell recognition does not preclude specificity. This approach has potential applications in the identification of ligands in infectious diseases, tumors and autoimmune diseases.     

Human genetic susceptibility to infectious disease

Recent genome-wide studies have reported novel associations between common polymorphisms and susceptibility to many major infectious diseases in humans. In parallel, an increasing number of rare mutations underlying susceptibility to specific phenotypes of infectious disease have been described. Together, these developments have highlighted a key role for host genetic variation in determining the susceptibility to infectious disease. They have also provided insights into the genetic architecture of infectious disease susceptibility and identified immune molecules and pathways that are directly relevant to the human host defence.     

Prediction of human disease genes by human-mouse conserved coexpression analysis

Background

Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates.

Methodology/Principal Findings

We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases.

Conclusion

Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes.     

Identification of mitochondrial disease genes through integrative analysis of multiple datasets

Determining the genetic factors in a disease is crucial to elucidating its molecular basis. This task is challenging due to a lack of information on gene function. The integration of large-scale functional genomics data has proven to be an effective strategy to prioritize candidate disease genes. Mitochondrial disorders are a prevalent and heterogeneous class of diseases that are particularly amenable to this approach. Here we explain the application of integrative approaches to the identification of mitochondrial disease genes. We first examine various datasets that can be used to evaluate the involvement of each gene in mitochondrial function. The data integration methodology is then described, accompanied by examples of common implementations. Finally, we discuss how gene networks are constructed using integrative techniques and applied to candidate gene prioritization. Relevant public data resources are indicated. This report highlights the success and potential of data integration as well as its applicability to the search for mitochondrial disease genes.     

Candidate Gene Association Study in Type 2 Diabetes Indicates a Role for Genes Involved in β-Cell Function as Well as Insulin Action

Type 2 diabetes is an increasingly common, serious metabolic disorder with a substantial inherited component. It is characterised by defects in both insulin secretion and action. Progress in identification of specific genetic variants predisposing to the disease has been limited. To complement ongoing positional cloning efforts, we have undertaken a large-scale candidate gene association study. We examined 152 SNPs in 71 candidate genes for association with diabetes status and related phenotypes in 2,134 Caucasians in a case-control study and an independent quantitative trait (QT) cohort in the United Kingdom. Polymorphisms in five of 15 genes (33%) encoding molecules known to primarily influence pancreatic β-cell function—ABCC8 (sulphonylurea receptor), KCNJ11 (KIR6.2), SLC2A2 (GLUT2), HNF4A (HNF4α), and INS (insulin)—significantly altered disease risk, and in three genes, the risk allele, haplotype, or both had a biologically consistent effect on a relevant physiological trait in the QT study. We examined 35 genes predicted to have their major influence on insulin action, and three (9%)—INSR, PIK3R1, and SOS1—showed significant associations with diabetes. These results confirm the genetic complexity of Type 2 diabetes and provide evidence that common variants in genes influencing pancreatic β-cell function may make a significant contribution to the inherited component of this disease. This study additionally demonstrates that the systematic examination of panels of biological candidate genes in large, well-characterised populations can be an effective complement to positional cloning approaches. The absence of large single-gene effects and the detection of multiple small effects accentuate the need for the study of larger populations in order to reliably identify the size of effect we now expect for complex diseases.