Genetic analysis of the structure of predisposition to diabetes mellitus. III. Genetic heterogeneity of diabetes mellitus with different ages of onset

The results of genetical-epidemiological analysis of the three conventional forms of diabetes mellitus (DM) differentiated for age-at-onset are presented (the form I - from 0 to 29 y. the form II - from 30 to 59 y. the form III - 60 y. and older). The estimates of heritability of liability to the forms I, II and III of DM were 0.57, 0.70 and 0.65, respectively. It was shown that genetic components of the forms I and II are virtually different: genetic correlation between these forms was rA = 0.216 +/- 0.203, which is statistically insignificant. These data support the hypothesis assuming genetic independence of juvenile and adult forms of DM. On the other hand, the forms II and III were found to have an essential number of genes in common: genetic correlation was rA = 0.495 +/- 0.134, being significant at the 5% level. Thus, the forms II and III of DM are not to be considered as two genetically distinct diseases. The low recurrence risks of the form I for siblings (not more than 3.6%) allow to reject the hypothesis of simple monogenic inheritance of juvenile DM and to propose multifactorial nature of the disease.     

Identification of shared genetic susceptibility locus for coronary artery disease, type 2 diabetes and obesity: a meta-analysis of genome-wide studies

ABSTRACT: Type 2 diabetes (2DM), obesity, and coronary artery disease (CAD) are frequently coexisted being as key components of metabolic syndrome. Whether there is shared genetic background underlying these diseases remained unclear. We performed a meta-analysis of 35 genome screens for 2DM, 36 for obesity or body mass index (BMI)-defined obesity, and 21 for CAD using genome search meta-analysis (GSMA), which combines linkage results to identify regions with only weak evidence and provide genetic interactions among different diseases. For each study, 120 genomic bins of approximately 30 cM were defined and ranked according to the best linkage evidence within each bin. For each disease, bin 6.2 achieved genomic significanct evidence, and bin 9.3, 10.5, 16.3 reached suggestive level for 2DM. Bin 11.2 and 16.3, and bin 10.5 and 9.3, reached suggestive evidence for obesity and CAD respectively. In pooled all three diseases, bin 9.3 and 6.5 reached genomic significant and suggestive evidence respectively, being relatively much weaker for 2DM/CAD or 2DM/obesity or CAD/obesity. Further, genomewide significant evidence was observed of bin 16.3 and 4.5 for 2DM/obesity, which is decreased when CAD was added. These findings indicated that bin 9.3 and 6.5 are most likely to be shared by 2DM, obesity and CAD. And bin 16.3 and 4.5 are potentially common regions to 2DM and obesity only. The observed shared susceptibility regions imply a partly overlapping genetic aspects of disease development. Fine scanning of these regions will definitely identify more susceptibility genes and causal variants.     

Analysis of genetic heterogeneity of bronchial asthma in relation with the age at the onset of disease

Earlier, the distribution of bronchial asthma (BA) morbidity with respect to the age of onset (AO) in the Moscow population was found to be bimodal. The distribution had two peaks (before and after 25 years of age) and a significant (P < 0.001) minimum between them. Based on these data, genetic heterogeneity of BA with respect to AO was hypothesized. The purpose of this study was to test this hypothesis via analysis of BA morbidity in families of probands with different AOs. The BA morbidity at different ages and the total recurrent risk of BA were estimated in 1518 relatives of 815 BA probands registered in several district outpatient clinics of Moscow. Based on the data obtained, phenotypic between relatives and correlation by genotype between early-onset and late-onset BA cases (with AOs under and over 25 years, respectively) were estimated. It was demonstrated for the first time that the age distribution of BA morbidity in families of probands was also bimodal. Moreover, when probands with early and late AOs were analyzed separately, proband relatives in each of the two groups exhibited these two peaks of morbidity. This suggests that BA that begins in adolescence and BA of adults are not genetically independent forms of the disease. This agrees with the data on the correlation by genotype between the "forms" with the early and late AOs, which does not significantly differ from 1. However, the prevalence of BA was higher in relatives of those probands who developed BA under the age of 25 compared to relatives of those who developed BA over the age of 25 (11.28 and 7.31%, respectively; P < 0.05). Therefore, patients with early-onset BA are more "burdened" genetically with respect to this disease. Since the BA genetic heterogeneity connected with AO has not been confirmed in this study, it is assumed that the observed bimodal distribution of BA morbidity with respect to age is accounted for by the effect of age itself. In other words, it is hypothesized that ontogenetic factors affect susceptibility to BA so that the susceptibility threshold varies with age.     

Genetic susceptibility to thrombosis and its relationship to physiological risk factors: the GAIT study. Genetic Analysis of Idiopathic Thrombophilia

Although there are a number of well-characterized genetic defects that lead to increased risk of thrombosis, little information is available on the relative importance of genetic factors in thrombosis risk in the general population. We performed a family-based study of the genetics of thrombosis in the Spanish population to assess the heritability of thrombosis and to identify the joint actions of genes on thrombosis risk and related quantitative hemostasis phenotypes. We examined 398 individuals in 21 extended pedigrees. Twelve pedigrees were ascertained through a proband with idiopathic thrombosis, and the remaining pedigrees were randomly ascertained. The heritability of thrombosis liability and the genetic correlations between thrombosis and each of the quantitative risk factors were estimated by means of a novel variance component method that used a multivariate threshold model. More than 60% of the variation in susceptibility to common thrombosis is attributable to genetic factors. Several quantitative risk factors exhibited significant genetic correlations with thrombosis, indicating that some of the genes that influence quantitative variation in these physiological correlates also influence the risk of thrombosis. Traits that exhibited significant genetic correlations with thrombosis included levels of several coagulation factors (factors VII, VIII, IX, XI, XII, and von Willebrand), tissue plasminogen activator, homocysteine, and the activated protein C ratio. This is the first study that quantifies the genetic component of susceptibility to common thrombosis. The high heritability of thrombosis risk and the significant genetic correlations between thrombosis and related risk factors suggest that the exploitation of correlated quantitative phenotypes will aid the search for susceptibility genes.     

Parkinson's disease: a genetic perspective

Parkinson's disease (PD) is a common neurodegenerative disorder in the aging population, affecting more than 1% over the age of 65 years. Certain rare forms of the disease are monogenic, representing 5-10% of PD patients, but there is increasing evidence that multiple genetic risk factors are important also for common forms of PD. To date, 13 genetic loci, PARK1-13, have been suggested for rare forms of PD such as autosomal dominant and autosomal recessive PD. At six of these loci, genes have been identified and reported by several groups to carry mutations that are linked to affected family members. Genes in which mutations have been linked to familial PD have also been shown to be candidate genes for idiopathic forms of PD, as those same genes may also carry other mutations that merely increase the risk. Four of the PARK genes, SNCA at PARK1, UCH-L1 at PARK5, PINK1 at PARK6 and LRRK2 at PARK8, have been implicated in sporadic PD. There are indeed multiple genetic risk factors that combine in different ways to increase or decrease risk, and several of these need to be identified in order to begin unwinding the causative pathways leading to the different forms of PD. In this review, we present the molecular genetics of PD that are understood today, to help explain the pathways leading to neurodegeneration.     

Association of Genetic polymorphism of PPARγ-2, ACE,MTHFR, FABP-2 and FTO genes in risk prediction of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a non-autoimmune, complex, heterogeneous and polygenic metabolic disease condition characterized by persistent elevated blood glucose levels (hyperglycemia). India as said to be the diabetic capital of the world is likely to experience the largest increase in T2DM and a greater number of diabetic individuals in the world by the year 2030. Identification of specific genetic variations in a particular ethnic group has a critical role in understanding the risk of developing T2DM in a much efficient way in future. These genetic variations include numerous types of polymorphisms among which single nucleotide polymorphisms (SNPs) is the most frequent. SNPs are basically located within the regulatory elements of several gene sequences. There are scores of genes interacting with various environmental factors affecting various pathways and sometimes even the whole signalling network that cause diseases like T2DM. This review discusses the biomarkers for early risk prediction of T2DM. Such predictions could be used in order to understand the pathogenesis of T2DM and to better diagnostics, treatment, and eventually prevention.     

Insights into pathophysiology of dystropy through the analysis of gene networks: an example of bronchial asthma and tuberculosis

Co-existence of bronchial asthma (BA) and tuberculosis (TB) is extremely uncommon (dystropic). We assume that this is caused by the interplay between genes involved into specific pathophysiological pathways that arrest simultaneous manifestation of BA and TB. Identification of common and specific genes may be important to determine the molecular genetic mechanisms leading to rare co-occurrence of these diseases and may contribute to the identification of susceptibility genes for each of these dystropic diseases. To address the issue, we propose a new methodological strategy that is based on reconstruction of associative networks that represent molecular relationships between proteins/genes associated with BA and TB, thus facilitating a better understanding of the biological context of antagonistic relationships between the diseases. The results of our study revealed a number of proteins/genes important for the development of both BA and TB.     

Bayesian shared spatial‐component models to combine and borrow strength across sparse disease surveillance sources

When analyzing the geographical variations of disease risk, one common problem is data sparseness. In such a setting, we investigate the possibility of using Bayesian shared spatial component models to strengthen inference and correct for any spatially structured sources of bias, when distinct data sources on one or more related diseases are available. Specifically, we apply our models to analyze the spatial variation of risk of two forms of scrapie infection affecting sheep in Wales (UK) using three surveillance sources on each disease. We first model each disease separately from the combined data sources and then extend our approach to jointly analyze diseases and data sources. We assess the predictive performances of several nested joint models through pseudo cross‐validatory predictive model checks.     

The impact of age on genetic risk for common diseases

Inherited genetic variation contributes to individual risk for many complex diseases and is increasingly being used for predictive patient stratification. Previous work has shown that genetic factors are not equally relevant to human traits across age and other contexts, though the reasons for such variation are not clear. Here, we introduce methods to infer the form of the longitudinal relationship between genetic relative risk for disease and age and to test whether all genetic risk factors behave similarly. We use a proportional hazards model within an interval-based censoring methodology to estimate age-varying individual variant contributions to genetic relative risk for 24 common diseases within the British ancestry subset of UK Biobank, applying a Bayesian clustering approach to group variants by their relative risk profile over age and permutation tests for age dependency and multiplicity of profiles. We find evidence for age-varying relative risk profiles in nine diseases, including hypertension, skin cancer, atherosclerotic heart disease, hypothyroidism and calculus of gallbladder, several of which show evidence, albeit weak, for multiple distinct profiles of genetic relative risk. The predominant pattern shows genetic risk factors having the greatest relative impact on risk of early disease, with a monotonic decrease over time, at least for the majority of variants, although the magnitude and form of the decrease varies among diseases. As a consequence, for diseases where genetic relative risk decreases over age, genetic risk factors have stronger explanatory power among younger populations, compared to older ones. We show that these patterns cannot be explained by a simple model involving the presence of unobserved covariates such as environmental factors. We discuss possible models that can explain our observations and the implications for genetic risk prediction.     

Ionizing radiation and genetic risks: VI. Chronic multifactorial diseases: a review of epidemiological and genetical aspects of coronary heart disease,essential hypertension and diabetes mellitus

This paper provides a broad overview of the epidemiological and genetical aspects of common multifactorial diseases in man with focus on three well-studied ones, namely, coronary heart disease (CHD), essential hypertension (EHYT) and diabetes mellitus (DM). In contrast to mendelian diseases, for which a mutant gene either in the heterozygous or homozygous condition is generally sufficient to cause disease, for most multifactorial diseases, the concepts of `genetic susceptibility' and `risk factors' are more appropriate. For these diseases, genetic susceptibility is heterogeneous. The well-studied diseases such as CHD permit one to conceptualize the complex relationships between genotype and phenotype for chronic multifactorial diseases in general, namely that allelic variations in genes, through their products interacting with environmental factors, contribute to the quantitative variability of biological risk factor traits and thus ultimately to disease outcome. Two types of such allelic variations can be distinguished, namely those in genes whose mutant alleles have (i) small to moderate effects on the risk factor trait, are common in the population (polymorphic alleles) and therefore contribute substantially to the variability of biological risk factor traits and (ii) profound effects, are rare in the population and therefore contribute far less to the variability of biological risk factor traits. For all the three diseases considered in this review, a positive family history is a strong risk factor. CHD is one of the major contributors to mortality in most industrialized countries. Evidence from epidemiological studies, clinical correlations, genetic hyperlipidaemias etc., indicate that lipids play a key role in the pathogenesis of CHD. The known lipid-related risk factors include: high levels of low density lipoprotein cholesterol, low levels of high density lipoprotein cholesterol, high apoB levels (the major protein fraction of the low density lipoprotein particles) and elevated levels of Lp(a) lipoprotein. Among the risk factors which are not related to lipids are: high levels of homocysteine, low activity of paraoxonase and possibly also elevated plasma fibrinogen levels. In addition to the above, hypertension, diabetes and obesity (which themselves have genetic determinants) are important risk factors for CHD. Among the environmental risk factors are: high dietary fat intake, smoking, stress, lack of exercise etc. About 60% of the variability of the plasma cholesterol is genetic in origin. While a few genes have been identified whose mutant alleles have large effects on this trait (e.g., LDLR, familial defective apoB-100), variability in cholesterol levels among individuals in most families is influenced by allelic variation in many genes (polymorphisms) as well as environmental exposures. A proportion of this variation can be accounted for by two alleles of the apoE locus that increase (ϵ4) and decrease (ϵ2) cholesterol levels, respectively. A polymorphism at the apoB gene (XbaI) also has similar effects, but is probably not mediated through lipids. High density lipoprotein cholesterol levels are genetically influenced and are related to apoA1 and hepatic lipase (LIPC) gene functions. Mutations in the apoA1 gene are rare and there are data which suggest a role of allelic variation at or linked LIPC gene in high density lipoprotein cholesterol levels. Polymorphism at the apoA1–C3 loci is often associated with hypertriglyceridemia. The apo(a) gene which codes for Lp(a) is highly polymorphic, each allele determining a specific number of multiple tandem repeats of a unique coding sequence known as Kringle 4. The size of the gene correlates with the size of the Lp(a) protein. The smaller the size of the Lp(a) protein, the higher are the Lp(a) levels. Hyperhomocyst(e)inemia is a risk factor for myocardial infarction, stroke and peripheral vascular disease, but the precise nature and intensity of this association, the biochemical mechanisms involved and the role of environmental factors remain to be fully elucidated. Recently, it has been suggested that polymorphisms in genes that code for paraoxonase may need to be added to the list of genetic risk factors for CHD. There are suggestions that high plasma fibrinogen levels (which is exacerbated by smoking which also lowers high density lipoprotein cholesterol levels) may constitute yet another risk factor for CHD. Essential hypertension (EHYT) affects some 10–25% of the people of the industrial world. Its clinical relevance stems from the fact that it is one of the major risk factors for cardiovascular and renal diseases, especially, stroke, coronary heart disease and end-stage renal disease. The role of genetic factors in EHYT is clearly indicated by family studies in which correlations in blood pressure levels have been studied. The variations in the range and magnitude of these correlations however suggest that other, environmental factors must play an important role and which vary from individual to individual and population to population. No major genes controlling blood pressure have been identified. However during the past five years or so, linkage and association studies have shown that there are at least three gene loci, polymorphism at which may contribute to EHYT: these include the AGT, AT1 and ACE genes. Additionally, the molecular basis of three rare mendelian disorders associated with hypertension, namely those involved in glucocorticosteroid-remediable aldosteronism (GRA), Liddle syndrome and apparent mineralocorticosteroid excess (AME) have been delineated. On the basis of clinical phenotypes, four types of diabetes mellitus are distinguished, of which insulin-dependent diabetes melltius (IDDM) and non-insulin-dependent diabetes mellitus (NIDDM) have been the subject of extensive studies. IDDM is a group of heterogeneous diseases probably resulting from exposure to some environmental agent(s) in those individuals with a genetically-determined susceptibility. IDDM is the result of the destruction of insulin-producing β-cells of the pancreas, principally by immunologically-mediated (autoimmune) mechanisms. The major defined risk factor is genetic susceptibility: apart from IDDM1 (linked to the HLA complex) and IDDM2 (in the insulin gene region) at least 10 other genes are involved, mutations at which cause susceptibility to IDDM. There is recent evidence for the possible involvement of an endogenous retrovirus in the aetiology of acute onset IDDM. NIDDM is a very common disease and its prevalence varies in different populations. As in the case of IDDM, its major determinant is genetic susceptibility. Compared to IDDM, the concordance rates in monozygotic twins and risks to first-degree relatives are higher. With the exception of MODY subtype with earlier onset, most cases have onset in middle or late life. The known geographical variations in the prevalence and studies of migrant populations suggest that environmental factors might also be important. The number of genes mutations at which cause susceptibility to NIDDM is not yet known and so far, one putative major gene locus has recently been identified in a Mexican–American population. Several candidate genes are currently being investigated. The available data indicate that some of the genes act through inherited susceptibility to insulin resistance and to decreased capacity for insulin secretion. Rare forms are due to dominant mutations i.e., the MODY diabetes and rarer still are forms due to the production of abnormal insulin due to mutations in the insulin gene itself. Finally, a small proportion of diabetes may be due to mutations in the mitochondrial genome. The attributes, risk factors and interrelationships between the three diseases considered in this review clearly show that the task of using this information for reliably predicting the risk of any of these diseases is formidable, even for a scenario of no radiation exposures, not to mention radiation scenarios. Nonetheless, these data provide a useful framework for developing models aimed at quantifying the response of these diseases to an increase in mutation rate due to radiation. One such model is discussed in a later paper of this series.     

Obesity,diabetes mellitus,and pancreatic carcinogenesis: Correlations,prevention, and diagnostic implications

The prevalence of obesity, diabetes mellitus (DM), and pancreatic cancer (PC) has been consistently increasing in the last two decades worldwide. Sharing various influential risk factors in genetics and environmental inducers in pathogenesis, the close correlations of these three diseases have been demonstrated in plenty of clinical studies using multiple parameters among different populations. On the contrary, most measures aimed to manage and treat obesity and DM effectively reduce the risk and prevent PC occurrence, yet certain drugs can inversely promote pancreatic carcinogenesis instead. Most importantly, an elevation of blood glucose with or without a reduction in body weight, along with other potential tools, may provide valuable clues for detecting PC at an early stage in patients with obesity and DM, favoring a timely intervention and prolonging survival. Herein, the epidemiological and etiological correlations among these three diseases and the supporting clinical evidence of their connections are first summarized to favor a better and more thorough understanding of obesity- and DM-related pancreatic carcinogenesis. After comparing the distinct impacts of different weight-lowering and anti-diabetic treatments on the risk of PC, the possible diagnostic implications of hyperglycemia and weight loss in PC screening are also addressed in detail.     

The Immunogenetic Architecture of Autoimmune Disease

The development of most autoimmune diseases includes a strong heritable component. This genetic contribution to disease ranges from simple Mendelian inheritance of causative alleles to the complex interactions of multiple weak loci influencing risk. The genetic variants responsible for disease are being discovered through a range of strategies from linkage studies to genome-wide association studies. Despite the rapid advances in genetic analysis, substantial components of the heritable risk remain unexplained, either owing to the contribution of an as-yet unidentified, “hidden,” component of risk, or through the underappreciated effects of known risk loci. Surprisingly, despite the variation in genetic control, a great deal of conservation appears in the biological processes influenced by risk alleles, with several key immunological pathways being modified in autoimmune diseases covering a broad spectrum of clinical manifestations. The primary translational potential of this knowledge is in the rational design of new therapeutics to exploit the role of these key pathways in influencing disease. With significant further advances in understanding the genetic risk factors and their biological mechanisms, the possibility of genetically tailored (or “personalized”) therapy may be realized.Autoimmune diseases affect a significant proportion of the population, with >4% of the European population suffering from one or more of these disorders (Vyse and Todd 1996; Cooper et al. 2009; Eaton et al. 2010). Although all autoimmune diseases share similarities in the basic immunological mechanisms, in other aspects, such as clinical manifestation and age of onset, individual diseases vary widely. A few rare autoimmune diseases with Mendelian inheritance patterns within families occur including APS-1 (autoimmune polyendocrine syndrome type 1), IPEX (immunodysregulation, polyendocrinopathy, and enteropathy X-linked) syndrome, and ALPS (autoimmune lymphoproliferative syndrome). Most autoimmune diseases are, however, multifactorial in nature, with susceptibility controlled by multiple genetic and environmental factors.The genetic component of more common autoimmune diseases can be calculated in several different manners, including the sibling recurrence risk (λ_s) and the twin concordance rate. The sibling recurrence risk is the ratio of the lifetime risk in siblings of patients to the lifetime population risk, whereas the twin concordance rate measures the proportion of the siblings of affected twins that are also affected. Most common autoimmune diseases, such as multiple sclerosis (MS), type 1 diabetes (T1D), rheumatoid arthritis (RA), and inflammatory bowel disease (IBD) are characterized by a sibling recurrence risk between 6 and 20 (Vyse and Todd 1996), and concordance rates of 25%–50% in monozygotic twins and 2%–12% in dizygotic twins (Cooper et al. 1999). A substantial proportion of relatives may also have subclinical evidence of autoimmunity without developing clinically overt disease. For example, 19% of healthy siblings of MS patients show antibody production in the cerebrospinal fluid, compared to 4% of unrelated healthy controls (Haghighi et al. 2000), whereas 4% of healthy first-degree relatives display lesions that are indistinguishable from those seen in patients and are not seen in unrelated healthy controls (De Stefano et al. 2006). Furthermore, comorbidity with the development of several autoimmune diseases in the same patient and clustering of several autoimmune diseases within families above what is expected by chance appear common (Cooper et al. 2009; Zhernakova et al. 2009). Together these data show a strong genetic component to autoimmune disease development.     

Prediction of individual genetic risk of complex disease

Most common diseases are caused by multiple genetic and environmental factors. In the last 2 years, genome-wide association studies (GWAS) have identified polymorphisms that are associated with risk to common disease, but the effect of any one risk allele is typically small. By combining information from many risk variants, will it be possible to predict accurately each individual person's genetic risk for a disease? In this review we consider the lessons from GWAS and the implications for genetic risk prediction to common disease. We conclude that with larger GWAS sample sizes or by combining studies, accurate prediction of genetic risk will be possible, even if the causal mutations or the mechanisms by which they affect susceptibility are unknown.     

Polytomous disease mapping to detect uncommon risk factors for related diseases

A statistical model for jointly analysing the spatial variation of incidences of three (or more) diseases, with common and uncommon risk factors, is introduced. Deaths for different diseases are described by a logit model for multinomial responses (multinomial logit or polytomous logit model). For each area and confounding strata population (i.e. age-class, sex, race) the probabilities of death for each cause (the response probabilities) are estimated. A specic disease, the one having a common risk factor only, acts as the baseline category. The log odds are decomposed additively into shared (common to diseases different by the reference disease) and specic structured spatial variability terms, unstructured unshared spatial terms and confounders terms (such as age, race and sex) to adjust the crude observed data for their effects. Disease specic spatially structured effects are estimated; these are considered as latent variables denoting disease-specic risk factors. The model is presented with reference to a specic application. We considered the mortality data (from 1990 to 1994) relative to oral cavity, larynx and lung cancers in 13 age groups of males, in the 287 municipalities of Region of Tuscany (Italy). All these pathologies share smoking as a common risk factor; furthermore, two of them (oral cavity and larynx cancer) share alcohol consumption as a risk factor. All studies suggest that smoking and alcohol consumption are the major known risk factors for oral cavity and larynx cancers; nevertheless, in this paper, we investigate the possibility of other different risk factors for these diseases, or even the presence of an interaction effect (between smoking and alcohol risk factors) but with different spatial patterns for oral and larynx cancer. For each municipality and age-class the probabilities of death for each cause (the response probabilities) are estimated. Lung cancer acts as the baseline category. The log odds are decomposed additively into shared (common to oral cavity and larynx diseases) and specic structured spatial variability terms, unstructured unshared spatial terms and an age-group term. It turns out that oral cavity and larynx cancer have different spatial patterns for residual risk factors which are not the typical ones such as smoking habits and alcohol consumption. But, possibly, these patterns are due to different spatial interactions between smoking habits and alcohol consumption for the first and the second disease.     

Segregation and genetic-dispersion analysis of predisposition to adenoma and cancer of the large intestine]

Segregation analysis of inheritance of adenomas, colorectal cancer (CRC), and multiple primary malignant tumors (MPMT) revealed their low penetrance: from 3.2 to 29% for homozygotes and from 2.0 to 14.4% for heterozygotes. This cast a doubt on the monogenic type of their inheritance, although it formally corresponded to the quasidominant type, i.e., only a fraction of heterozygotes was expressed. Therefore, the multifactorial model of inheritance was tested, which seemed more adequate because genetic heterogeneity of adenomas, CRC, and MPMT was suggested from the data on genetic correlations between various clinical forms. Predisposition to various clinical forms of adenomas, CRC, and MPMT was shown to be specific, i.e., the ratio between genetic and environmental predisposition-determining factors reflected pathogenetic differences between these diseases. However, analysis of variance which revealed genetic (pathogenetic) distinctions between adenomas, CRC, and MPMT is insufficient to confirm complete nosologic identity of each of these clinical forms.     

A search for overlapping genetic susceptibility loci between non-Hodgkin lymphoma and autoimmune diseases

Non-Hodgkin lymphoma (NHL) is a hematological malignancy of the immune system, and, as with autoimmune and inflammatory diseases (ADs), is influenced by genetic variation in the major histocompatibility complex (MHC). Persons with a history of specific ADs also have increased risk of NHL. As the coexistence of ADs and NHL could be caused by factors common to both diseases, here we examined whether some of the associated genetic signals are shared. Overlapping risk loci for NHL subytpes and several ADs were explored using data from genome-wide association studies. Several common genomic regions and susceptibility loci were identified, suggesting a potential shared genetic background. Two independent MHC regions showed the main overlap, with several alleles in the human leukocyte antigen (HLA) class II region exhibiting an opposite risk effect for follicular lymphoma and type I diabetes. These results support continued investigation to further elucidate the relationship between lymphoma and autoimmune diseases.     

Recent Mitochondrial DNA Mutations Increase the Risk of Developing Common Late-Onset Human Diseases

Mitochondrial DNA (mtDNA) is highly polymorphic at the population level, and specific mtDNA variants affect mitochondrial function. With emerging evidence that mitochondrial mechanisms are central to common human diseases, it is plausible that mtDNA variants contribute to the “missing heritability” of several complex traits. Given the central role of mtDNA genes in oxidative phosphorylation, the same genetic variants would be expected to alter the risk of developing several different disorders, but this has not been shown to date. Here we studied 38,638 individuals with 11 major diseases, and 17,483 healthy controls. Imputing missing variants from 7,729 complete mitochondrial genomes, we captured 40.41% of European mtDNA variation. We show that mtDNA variants modifying the risk of developing one disease also modify the risk of developing other diseases, thus providing independent replication of a disease association in different case and control cohorts. High-risk alleles were more common than protective alleles, indicating that mtDNA is not at equilibrium in the human population, and that recent mutations interact with nuclear loci to modify the risk of developing multiple common diseases.     

Predisposition to multifactorial pathology in residents of the city in the zone around the "Maiak" atomic industry enterprise

According to present achievements in radiation and molecular genetics it is possible to expect that due to chronic radiation exposure the relative increasing of genetic risk in following generations will be observed. It will be due, in the first place, to increasing a percent of multifactorial diseases (MFD). Most of geneticists refer bronchial asthma (BA) to multifactorial diseases. Genetics and epidemiological analysis of liability to BA in population of Ozyorsk situated in the control area of "Mayak" Production Association (PA "Mayak") was accomplished. Population risk, as probability for an individual in population to develop BA up to the end of life is 2.69%. It's higher than in Moscow (2.03%) (p < 0.05). The excess is due to significantly higher values in females (2.96% against 1.93%). Population risk to fall ill of BA in females of Ozyorsk (2.96%) is significantly higher than in males (2.4%). Prevalence of BA in Ozyorsk (0.60%) is significantly higher than in Moscow (0.47%) due to higher values in females (0.65% against 0.47%). The total risk to fall ill of BA amongst relatives is 5.4% that is twice higher than the population risk. The heritability of BA is 0.71 (in Moscow-0.70).     

The possible role of 10398A and 16189C mtDNA variants in providing susceptibility toT2DM in two North Indian populations: a replicative study

The role of mitochondria in causing diseases is becoming evident as more and more studies are focusing on this organelle of the cell. This is largely attributed to its reactive oxygen species (ROS) production property. In the context of diabetes, ROS is suggested to trigger different forms of insulin resistance involving different mechanisms. The suggestive role of a mtDNA variant G10398A in increasing ROS production and the impaired response to oxidative stress due to T16189C variant is worth addressing as genetic susceptibility factors in type 2 diabetes mellitus (T2DM). A case control study on 312 T2DM cases and ethnically matched 466 controls involving two North Indian populations, referred as cohort 1 and cohort 2 (in a replicative study), was undertaken to test such a genetic association. A statistically significant association was observed for 10398A allele in both the cohorts [cohort1 (OR = 2.67 95% CI 1.77–4.00); cohort2 (OR = 1.76 95%CI 1.12–2.77)]. The analysis of G10398A/T16189C haplotypic combinations revealed that 10398A/16189C haplotype provides a risk in both the cohorts. To sum up the study suggests that 10398A and 16189C alleles provide susceptiblity to T2DM independently as well as together.     

Risikoberechnungen beim autosomal-rezessiven Erbgang

Genetic risk calculations are demonstrated for autosomal recessive diseases using Bayesian calculation tables. The Hardy-Weinberg law forms an important basis for the determination of a priori probabilities. We demonstrate how healthy relatives, molecular test results and complex genetic models affect the risk. Examples of autosomal recessive inheritance with cystic fibrosis (CF) and infantile spinal muscular atrophy (SMA) have been selected.