Molecular pathways for intracellular cholesterol accumulation: common pathogenic mechanisms in Niemann-Pick disease Type C and cystic fibrosis

It has been less than two decades since the underlying genetic defects in Niemann-Pick disease Type C were first identified. These defects impair function of two proteins with a direct role in lipid trafficking, resulting in deposition of free cholesterol within late endosomal compartments and a multitude of effects on cell function and clinical manifestations. The rapid pace of research in this area has vastly improved our overall understanding of intracellular cholesterol homeostasis. Excessive cholesterol buildup has also been implicated in clinical manifestations associated with a number of genetically unrelated diseases including cystic fibrosis. Applying knowledge about anomalous cell signaling behavior in cystic fibrosis opens prospects for identifying similar previously unrecognized disease pathways in Niemann-Pick disease Type C. Recognition that Niemann-Pick disease Type C and cystic fibrosis both impair cholesterol regulatory pathways also provides a rationale for identifying common therapeutic targets.     

The use of molecular genetics in the improvement of agricultural populations

Substantial advances have been made in the genetic improvement of agriculturally important animal and plant populations through artificial selection on quantitative traits. Most of this selection has been on the basis of observable phenotype, without knowledge of the genetic architecture of the selected characteristics. However, continuing molecular genetic analysis of traits in animal and plant populations is leading to a better understanding of quantitative trait genetics. The genes and genetic markers that are being discovered can be used to enhance the genetic improvement of breeding stock through marker-assisted selection.     

胆固醇代谢紊乱的遗传学研究进展

心血管病已成为威胁我国人群健康的首要疾病,而胆固醇代谢紊乱是心血管病发生发展的重要危险因素之一。近年来高通量技术的推广和群体基因组学的发展极大地促进了复杂性状(或疾病)易感基因或突变的发现,为深入解析胆固醇代谢紊乱的遗传学病因提供了机会。文章整合传统遗传分析和近期GWAS筛查的结果,对胆固醇代谢紊乱的分子遗传研究进展进行了综述,结合通路富集分析揭示胆固醇代谢紊乱的功能背景,以期更好地理解胆固醇代谢紊乱致病的分子机制,为其防治提供线索。     

Complex adaptive system models and the genetic analysis of plasma HDL-cholesterol concentration

Despite remarkable advances in diagnosis and therapy, ischemic heart disease (IHD) remains a leading cause of morbidity and mortality in industrialized countries. Recent efforts to estimate the influence of genetic variation on IHD risk have focused on predicting individual plasma high-density lipoprotein cholesterol (HDL-C) concentration. Plasma HDL-C concentration (mg/dl), a quantitative risk factor for IHD, has a complex multifactorial etiology that involves the actions of many genes. Single gene variations may be necessary but are not individually sufficient to predict a statistically significant increase in risk of disease. The complexity of phenotype-genotype-environment relationships involved in determining plasma HDL-C concentration has challenged commonly held assumptions about genetic causation and has led to the question of which combination of variations, in which subset of genes, in which environmental strata of a particular population significantly improves our ability to predict high or low risk phenotypes. We document the limitations of inferences from genetic research based on commonly accepted biological models, consider how evidence for real-world dynamical interactions between HDL-C determinants challenges the simplifying assumptions implicit in traditional linear statistical genetic models, and conclude by considering research options for evaluating the utility of genetic information in predicting traits with complex etiologies.     

Scavenger receptor Class B type I as a potential risk stratification biomarker and therapeutic target in cardiovascular disease

Cardiovascular disease (CVD) is the leading cause of mortality globally. There are few useful markers available for CVD risk stratification that has proven clinical utility. Scavenger receptor B type I (SR-BI) is a cell surface protein that plays a major role in cholesterol homeostasis through its interaction with high-density lipoprotein-cholesterol (HDL-C) esters (CE). HDL delivers CE to the liver through selective uptake by the SR-BI. SR-BI also regulates the inflammatory response. It has been shown that SR-BI overexpression has beneficial, protective effects in atherogenesis, and there is considerable interest in developing antiatherogenic strategies that involve SR-BI-mediated increases in reverse cholesterol transport through HDL and/or low-density lipoprotein. Further investigations are essential to explore the clinical utility of this approach. Moreover, there is growing evidence showing associations between genetic variants with modulation of SR-BI function that may, thereby, increase CVD risk. The aim of the current review was to provide an overview of the possible molecular mechanisms by which SR-BI may affect CVD risk, and the clinical implications of this, with particular emphasis on preclinical studies on genetic changes of SR-BI and CVD risk.     

Exploiting interactions among polymorphisms contributing to complex disease traits with boosted generative modeling.

Although there has been great success in identifying disease genes for simple, monogenic Mendelian traits, deciphering the genetic mechanisms involved in complex diseases remains challenging. One major approach is to identify configurations of interacting factors such as single nucleotide polymorphisms (SNPs) that confer susceptibility to disease. Traditional methods, such as the multiple dimensional reduction method and the combinatorial partitioning method, provide good tools to decipher such interactions amid a disease population with a single genetic cause. However, these traditional methods have not managed to resolve the issue of genetic heterogeneity, which is believed to be a very common phenomenon in complex diseases. There is rarely prior knowledge of the genetic heterogeneity of a disease, and traditional methods based on estimation over the entire population are unlikely to succeed in the presence of heterogeneity. We present a novel Boosted Generative Modeling (BGM) approach for structure-model the interactions leading to diseases in the context of genetic heterogeneity. Our BGM method bridges the ensemble and generative modeling approaches to genetic association studies under a case-control design. Generative modeling is employed to model the interaction network configuration and the causal relationships, while boosting is used to address the genetic heterogeneity problem. We perform our method on simulation data of complex diseases. The results indicate that our method is capable of modeling the structure of interaction networks among disease-susceptible loci and of addressing genetic heterogeneity issues where the traditional methods, such as multiple dimensional reduction method, fail to apply. Our BGM method provides an exploratory tool that identifies the variables (e.g., disease-susceptible loci) that are likely to correlate and contribute to the disease.     

A genomewide search using an original pairwise sampling approach for large genealogies identifies a new locus for total and low-density lipoprotein cholesterol in two genetically differentiated isolates of Sardinia

A powerful approach to mapping the genes for complex traits is to study isolated founder populations, in which genetic heterogeneity and environmental noise are likely to be reduced and in which extended genealogical data are often available. Using graph theory, we applied an approach that involved sampling from the large number of pairwise relationships present in an extended genealogy to reconstruct sets of subpedigrees that maximize the useful information for linkage mapping while minimizing calculation burden. We investigated, through simulation, the properties of the different sets in terms of bias in identity-by-descent (IBD) estimation and power decrease under various genetic models. We applied this approach to a small isolated population from Sardinia, the village of Talana, consisting of a unique large and complex pedigree, and performed a genomewide search through variance-components linkage analysis for serum lipid levels. We identified a region of significant linkage on chromosome 2 for total serum cholesterol and low-density lipoprotein (LDL) cholesterol. Through higher-density mapping, we obtained an increased linkage for both traits on 2q21.2-q24.1, with a LOD score of 4.3 for total serum cholesterol and of 3.9 for LDL cholesterol. A replication study was performed in an independent and larger set from a genetically differentiated isolated population of the same region of Sardinia, the village of Perdasdefogu. We obtained consistent linkage to the region for total serum cholesterol (LOD score 1.4) and LDL cholesterol (LOD score 2.2), with a level of concordance uncommon for complex traits, and refined the location of the quantitative-trait locus. Interestingly, the 2q21.1-22 region has also been linked to premature coronary heart disease in Finns, and, in the adjacent 2q14 region, significant linkage with triglycerides has been reported in Hutterites.     

Catabolism and biotechnological applications of cholesterol degrading bacteria

Cholesterol is a steroid commonly found in nature with a great relevance in biology, medicine and chemistry, playing an essential role as a structural component of animal cell membranes. The ubiquity of cholesterol in the environment has made it a reference biomarker for environmental pollution analysis and a common carbon source for different microorganisms, some of them being important pathogens such as Mycobacterium tuberculosis. This work revises the accumulated biochemical and genetic knowledge on the bacterial pathways that degrade or transform this molecule, given that the characterization of cholesterol metabolism would contribute not only to understand its role in tuberculosis but also to develop new biotechnological processes that use this and other related molecules as starting or target materials.     

Scavenger receptor regulation and atherosclerosis

Atherosclerosis and its complications, such as coronary heart disease, heart infarction and stroke, are the leading causes of death in the developed world. High blood pressure, diabetes, smoking and a diet high in cholesterol and lipids clearly increase the likelihood of premature atherosclerosis, albeit other factors, such as the individual genetic makeup, may play an additional role. During atherosclerosis, uncontrolled cholesterol and lipid accumulation in macrophages and smooth muscle cells leads to foam cell formation and to the progression of the atherosclerotic plaque. This review will focus on foam cell formation within the atherosclerotic lesion, the involvement of the scavenger receptor genes in this process, and the possibility to interfere with scavenger receptor function to reduce the progression of atherosclerosis. To date, the regulatory mechanisms for the expression of scavenger receptor genes and their role in atherosclerosis are not well characterized. Knowledge on this subject could lead to a better understanding of the process, prevention and therapy of this disease.     

Detection of genetic heterogeneity among pedigrees through complex segregation analysis: an application to hypercholesterolemia

Several methods for investigating genetic heterogeneity for extreme levels of a quantitative trait with hypothesized multiple genetic etiologies require a priori stratification of families and/or identification of distinct phenotypes among affected individuals. We present a statistical approach for detecting genetic heterogeneity that does not rely on either a priori stratification or discrete disease phenotypes. Complex segregation analysis was applied to total serum cholesterol measurements in 709 relatives of 98 healthy index cases selected from 3,666 school children surveyed for lipid levels in Rochester, Minnesota. Thirty-three of the index cases and 109 relatives had hypercholesterolemia (cholesterol levels greater than the 95th percentile for their age and sex). Through application of the mixed genetic model and then estimation of conditional probabilities for having the mutant allele at the major locus, genetic heterogeneity for hypercholesterolemia was indicated. In three of 70 pedigrees with one or more hypercholesterolemics, there is strong evidence for segregation at a major locus. In the remaining pedigrees, only polygene variation and/or environmental variation are associated with cholesterol variability. Grandparents in the three pedigrees that were segregating at the major locus had the highest rates of death due to coronary heart disease. This study establishes that the mixed model has the potential to identify pedigrees with different genetic etiologies for variability in quantitative traits.     

Do Molecular Markers Inform About Pleiotropy?

The availability of dense panels of common single-nucleotide polymorphisms and sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGRs). At the onset, traits were analyzed trait by trait, but recently, WGRs have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (e.g., pleiotropy) using genomic data is conjectural.     

Procreative beneficence: why we should select the best children

Eugenic selection of embryos is now possible by employing in vitro fertilization (IVF) and preimplantation genetic diagnosis (PGD). While PGD is currently being employed for the purposes of detecting chromosomal abnormalities or inherited genetic abnormalities, it could in principle be used to test any genetic trait such as hair colour or eye colour.
Genetic research is rapidly progressing into the genetic basis of complex traits like intelligence and a gene has been identified for criminal behaviour in one family. Once the decision to have IVF is made, PGD has few 'costs' to couples, and people would be more inclined to use it to select less serious medical traits, such as a lower risk of developing Alzheimer Disease, or even for non-medical traits. PGD has already been used to select embryos of a desired gender in the absence of any history of sex-linked genetic disease.
I will argue that: (1) some non-disease genes affect the likelihood of us leading the best life; (2) we have a reason to use information which is available about such genes in our reproductive decision-making; (3) couples should select embryos or fetuses which are most likely to have the best life, based on available genetic information, including information about non-disease genes. I will also argue that we should allow selection for non-disease genes even if this maintains or increases social inequality. I will focus on genes for intelligence and sex selection.
I will defend a principle which I call Procreative Beneficence: couples (or single reproducers) should select the child, of the possible children they could have, who is expected to have the best life, or at least as good a life as the others, based on the relevant, available information.     

Breeding for immune responsiveness and disease resistance1

Animal production efficiency, and product volume and quality can be greatly increased by reducing disease losses. Genetic variation, a prerequisite for successful selection, has been found in animals and poultry exposed to a variety of viral, bacterial and parasitic infections. Breeding for disease resistance can play a significant role alone or in combination with other control measures including disease eradication, vaccination and medication. Feasibility of simultaneously improving resistance to specific diseases and production traits has been demonstrated. However, selection for specific resistance to all diseases of animals and poultry is impossible. Development of general disease resistance through indirect selection primarily on immune response traits may be the best long-term strategy but its applicability is presently limited by insufficient understanding of resistance mechanisms. Another hindrance may be negative genetic correlations among various immune response functions: phagocytosis, cell mediated and humoral immunity. To better assess the feasibility of increasing general disease resistance by indirect selection we must obtain estimates of heritability for immune response, disease resistance, and economic production traits, as well as genetic correlations among these traits. The present level of disease resistance in farm animals resulted from natural selection and from correlated responses to selection for production traits while the influence of artificial selection for resistance was minimal. Future research should be directed towards developing and applying breeding techniques that will increase resistance to diseases without compromising production efficiency and product quailty. This will require cooperation of immunogeneticists, veterinarians and animal and poultry breeders. Significant progress in the improvement of resistance to diseases may result from the application of new techniques of molecular genetics and cell manipulation.     

Breeding for immune responsiveness and disease resistance

Animal production efficiency, and product volume and quality can be greatly increased by reducing disease losses. Genetic variation, a prerequisite for successful selection, has been found in animals and poultry exposed to a variety of viral, bacterial and parasitic infections. Breeding for disease resistance can play a significant role alone or in combination with other control measures including disease eradication, vaccination and medication. Feasibility of simultaneously improving resistance to specific diseases and production traits has been demonstrated. However, selection for specific resistance to all diseases of animals and poultry is impossible. Development of general disease resistance through indirect selection primarily on immune response traits may be the best long-term strategy but its applicability is presently limited by insufficient understanding of resistance mechanisms. Another hindrance may be negative genetic correlations among various immune response functions: phagocytosis, cell mediated and humoral immunity. To better assess the feasibility of increasing general disease resistance by indirect selection we must obtain estimates of heritability for immune response, disease resistance, and economic production traits, as well as genetic correlations among these traits. The present level of disease resistance in farm animals resulted from natural selection and from correlated responses to selection for production traits while the influence of artificial selection for resistance was minimal. Future research should be directed towards developing and applying breeding techniques that will increase resistance to diseases without compromising production efficiency and product quality. This will require cooperation of immunogeneticists, veterinarians and animal and poultry breeders. Significant progress in the improvement of resistance to diseases may result from the application of new techniques of molecular genetics and cell manipulation.     

HDL: structure, function and metabolism.

The major advances in our knowledge of the structure, function and metabolism of the plasma lipoproteins have occurred as a result of the rapid increase in our knowledge of the structure and function of the apolipoproteins, lipoproteins, and the heterogeneity of the individual classes of lipoproteins. Over the last decade, there has been a tremendous increase in our knowledge of the structure and molecular properties of ApoA-I and ApoA-II which has permitted an analysis of the functions of these apolipoproteins in lipid and lipoprotein metabolism and the initiation of kinetic studies of HDL metabolism. The elucidation of the structures of the ApoA-I and ApoA-II genes has permitted the determination of genetic defects resulting in decreased levels of HDL and premature cardiovascular disease, as well as the identification of new diseases (e.g. hereditary systemic amyloidosis). The future focus of research on HDL will be the analysis of the individual lipoprotein particles within HDL which have different physiological functions and important roles in reverse cholesterol transport. An improved understanding of the role of HDL in the transport of cellular cholesterol to the liver and the exchange of cholesterol between plasma lipoproteins will provide critical information on cholesterol metabolism in normal subjects and permit the elucidation of the molecular defects of new genetic diseases which may be associated with the development of premature cardiovascular disease.     

Quantitative trait loci for white blood cell numbers in swine

Differential white blood cell counts are essential diagnostic parameters in veterinary practice but knowledge on the genetic architecture controlling variability of leucocyte numbers and relationships is sparse, especially in swine. Total leucocyte numbers (Leu) and the differential leucocyte counts, i.e. the fractions of lymphocytes (Lym), polymorphonuclear leucocytes [neutrophils (Neu), eosinophils (Eos) and basophils (Bas)] and monocytes (Mon) were measured in 139 F₂ pigs from a Meishan/Pietrain family, before and after challenge with the protozoan pathogen Sarcocystis miescheriana for genome-wide quantitative trait loci (QTL) analysis. After infection, the pigs passed through three stages representing acute disease, reconvalescence and chronic disease. Nine genome-wide significant and 29 putative, single QTL controlling leucocyte traits were identified on 15 chromosomes. Because leucocyte traits varied with health and disease status, QTL influencing the leucocyte phenotypes showed specific health/disease patterns. Regions on SSC1, 8 and 12 contained QTL for baseline leucocyte traits. Other QTL regions reached control on leucocyte traits only at distinct stages of the disease model. Two-thirds of the QTL have not been described before. Single QTL explained up to 19% of the phenotypic variance in the F₂ animals. Related traits were partly under common genetic influence. Our analysis confirms that leucocyte trait variation is associated with multiple chromosomal regions.     

Genetic Modification of Herbaceous Plants for Feed and Fuel

Referee: Dr. E. Charles Brummer, Forage Breeding and Genetics, 1204 Agromonomy, Iowa State University, Ames, IA 50011 Much of the research on the genetic modification of herbaceous plant cell walls has been conducted to improve the utilization of forages by ruminant livestock. The rumen of these animals is basically an anaerobic fermentation vat in which the micro flora break down the complex polysaccharides of plant cell walls into simpler compounds that can be further digested and absorbed by the mammalian digestive system. Research on improving the forage digestibility of switchgrass, Panicum virgatum L., and other herbaceous species has demonstrated that genetic improvements can be made in forage quality that can have significant economic value. To meet future energy needs, herbaceous biomass will need to be converted into a liquid fuel, probably ethanol, via conversion technologies still under development. If feedstock quality can be genetically improved, the economics and efficiency of the conversion processes could be significantly enhanced. Improving an agricultural product for improved end product use via genetic modification requires knowledge of desired quality attributes, the relative economic value of the quality parameters in relation to yield, genetic variation for the desired traits, or for molecular breeding, knowledge of genes to suppress or add, and knowledge of any associated negative consequences of genetic manipulation. Because conversion technology is still under development, desirable plant feedstock characteristics have not been completely delineated. Some traits such as cellulose and lignin concentration will undoubtably be important. Once traits that affect biomass feedstock conversion are identified, it will be highly feasible to genetically modify the feedstock quality of herbaceous plants using both conventional and molecular breeding techniques. The use of molecular markers and transformation technology will greatly enhance the capability of breeders to modify the morphologic structure and cell walls of herbaceous species. It will be necessary to monitor gene flow to remnant wild populations of biomass plants and have strategies available to curtail gene flow if it becomes a potential problem. It will also be necessary to monitor plant survival and long-term productivity as affected by these genetic changes to herbaceous species.     

Amyloid beta-protein interactions with membranes and cholesterol: causes or casualties of Alzheimer's disease

Amyloid beta-protein (Abeta) is thought to be one of the primary factors causing neurodegeneration in Alzheimer's disease (AD). This protein is an amphipathic molecule that perturbs membranes, binds lipids and alters cell function. Several studies have reported that Abeta alters membrane fluidity but the direction of this effect has not been consistently observed and explanations for this lack of consistency are proposed. Cholesterol is a key component of membranes and cholesterol interacts with Abeta in a reciprocal manner. Abeta impacts on cholesterol homeostasis and modification of cholesterol levels alters Abeta expression. In addition, certain cholesterol lowering drugs (statins) appear to reduce the risk of AD in human subjects. However, the role of changes in the total amount of brain cholesterol in AD and the mechanisms of action of statins in lowering the risk of AD are unclear. Here we discuss data on membranes, cholesterol, Abeta and AD, and propose that modification of the transbilayer distribution of cholesterol in contrast to a change in the total amount of cholesterol provides a cooperative environment for Abeta synthesis and accumulation in membranes leading to cell dysfunction including disruption in cholesterol homeostasis.     

Quantitative trait loci for red blood cell traits in swine

Haematological traits are essential diagnostic parameters in veterinary practice but knowledge on the genetic architecture controlling variability of erythroid traits is sparse, especially in swine. To identify QTL for erythroid traits in the pig, haematocrit (HCT), haemoglobin (HB), erythrocyte counts (RBC) and mean corpuscular haemoglobin content (MCHC) were measured in 139 F₂ pigs from a Meishan/Pietrain family, before and after challenge with the protozoan pathogen Sarcocystis miescheriana . The pigs passed through three stages representing acute disease, reconvalescence and chronic disease. Forty-three single QTL controlling erythroid traits were identified on 16 chromosomes. Twelve of the QTL were significant at the genome-wide level while 31 were significant at a chromosome-wide level. Because erythroid traits varied with health and disease status, QTL influencing the erythroid phenotypes showed specific health/disease patterns. Regions on SSC5, 7, 8, 12 and 13 contained QTL for baseline erythroid traits, while the other QTL regions affected distinct stages of the disease model. Single QTL explained 9–17% of the phenotypic variance in the F₂ animals. Related traits were partly under common genetic influence. Our analysis confirms that erythroid trait variation differs between Meishan and Pietrain breeds and that this variation is associated with multiple chromosomal regions.