Genetic prediction and family structure in Huntington's chorea.

A deoxyribonucleic acid marker linked to the locus for Huntington''s chorea exists, but its possible use in the prediction of this disorder depends on the pedigree structure of individual families. Analysis of data from a population register for Huntington''s chorea in south Wales showed that only a minority of subjects at risk had the appropriate members of their family living to allow the presence or absence of the gene to be definitively predicted. However, the structure of the family allowed a degree of prediction (in particular, exclusion of the disorder) to be made for the fetus during pregnancies of these subjects in almost 90% of cases. Such a prediction need not alter the risk state for the parent at risk. The structure of the family will remain crucial for prediction even when current limitations of the linked marker have been overcome.     

Calculating risk changes after negative mutation test outcomes for autosomal dominant hereditary late-onset disorders

We demonstrate, in a specific scenario, the effect of negative test results from relatives in families at risk for an autosomal dominant hereditary late-onset disorder. A hypothetical pedigree, of a family at risk of Huntington's disease, was used to demonstrate the consequences for the risk status of various family members in the case where relatives have been tested, and found to be mutation negative. We argue that accurate assessment of conditional probabilities in clinical genetics is important for individuals at risk for hereditary disorders with Mendelian transmission patterns; our formulae offer the opportunity -- when simplifying assumptions are met -- to determine the changed risk status of individuals in such cases.     

Partners of Huntington patients: implications of the disease and opinions about predictive testing and prenatal diagnosis

Huntington's disease imposes a considerable burden on the patient and also on the family, especially on the partner. The present paper is based on a survey about the consequences of the disease from the point of view of the partner of the Huntington patient. The mental deterioration and the personality changes seem to be the most difficult aspects to cope with. The threat that their own children may later on develop the same disease is one of the most dramatic aspects. Most partners were aware of the availability of predictive testing for Huntington's disease and were concerned about the far-reaching consequences of the test result. There was a relatively high consensus that the test should only be delivered within a counseling context. Three out of four respondents were in favour of the availability of prenatal diagnosis for Huntington's disease.     

A theoretical psychological perspective on predictive testing for late onset hereditary diseases

Because of the burden of serious late onset hereditary diseases, psychological counselling is commonly included in the predictive testing procedure. We discuss the components of psychological counselling in the context of neurodegenerative disorders such as Huntington's disease, some hereditary cancers and some hereditary heart diseases. Psychological counselling should be tailored to the specific characteristics of the disease: penetrance and expression of the mutation, variability of the age at onset and efficacy of prevention and treatment, if available. Finally theories that have already been used for the psychological framing of counselling in the context of predictive testing or to formulate research hypotheses (e.g. Transactional Model of Stress and Coping, Common Sense Model of Self-regulation) are discussed.     

Effect of non-attenders on the potential of a primary care programme to reduce cardiovascular risk in the population. Family Heart Study Group.

OBJECTIVES--To determine the feasibility of enrolling non-attenders of a population based cardiovascular risk reduction programme (the British family heart study) into a further, similar programme and to assess the effect of non-attendance on the effectiveness of the programme. DESIGN--Follow up of non-attenders by practice nurses, including home visits if necessary, to administer questionnaires and obtain physiological measurements. SETTING--Eight general practices across England, Scotland, and Wales. SUBJECTS--Non-attenders in a cardiovascular risk factor screening and intervention programme compared with attenders. MAIN OUTCOME MEASURES--Number of non-attenders enrolled; sociodemographic characteristics; personal and family history of coronary heart disease; cardiovascular risk factors; and total coronary risk score. RESULTS--Data were collected from 106 (17%) of the 608 non-attending families (99 men and 42 women). Of the 543 non-attending families from five practices that attempted complete follow up, 256 had moved away or died. Only 76 were eventually enrolled into the study. The prevalence of coronary heart disease and a family history of coronary heart disease were similar among non-attenders and attenders as were the individual coronary risk factors studied except smoking. Women non-attenders were more likely to be current cigarette smokers than attenders (15/42 v 202/948, P = 0.02). CONCLUSIONS--The intensive follow up of non-attenders resulted in real intervention opportunities in only a small number. Since the effect of any intervention in a population is reduced by non-attendance audit of preventive medical programmes aimed at the population should allow for the effect of non-attenders on the overall results.     

Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population

Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.     

Disclosure of Huntington's disease to family members: the dilemma of known but unknowing parties

Predictive genetic testing presents unique issues in the legal and ethical debate concerning disclosure of information within the physician-patient relationship. A duty to disclose information to family members has been found when the disclosure is likely to result in the ability to mitigate the damaging effects of the disease. When evaluating the situation where a individual is at risk of Huntington's disease, the analysis must be different, as shown in this paper, and necessitates an ethical and legal examination of the consequences of receipt of the information on family members, those known but unknowing parties who are at risk of inheriting a genetic disease. This paper analyzes the potential legal duty of a physician to disclose or withhold genetic information from the family members of patients. Existing statutes governing genetic information do not directly address the interests of family members. Courts that have ruled on the duty to disclose medical or genetic information have analyzed these issues using traditional concepts of tort law. Yet the situation presented by Huntington's disease is unique and demands a different framework for analysis, given the late onset and lack of curative or ameliorative treatment. This paper also analyzes the ethical standards to be invoked when considering violating the privacy of a patient or a family member. The principles of autonomy and self-determination of family members are considered, versus the risk of harm and the privacy interest in not knowing potentially devastating information.     

A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait.     

Improving genetic risk prediction by leveraging pleiotropy

An important task of human genetics studies is to predict accurately disease risks in individuals based on genetic markers, which allows for identifying individuals at high disease risks, and facilitating their disease treatment and prevention. Although hundreds of genome-wide association studies (GWAS) have been conducted on many complex human traits in recent years, there has been only limited success in translating these GWAS data into clinically useful risk prediction models. The predictive capability of GWAS data is largely bottlenecked by the available training sample size due to the presence of numerous variants carrying only small to modest effects. Recent studies have shown that different human traits may share common genetic bases. Therefore, an attractive strategy to increase the training sample size and hence improve the prediction accuracy is to integrate data from genetically correlated phenotypes. Yet, the utility of genetic correlation in risk prediction has not been explored in the literature. In this paper, we analyzed GWAS data for bipolar and related disorders and schizophrenia with a bivariate ridge regression method, and found that jointly predicting the two phenotypes could substantially increase prediction accuracy as measured by the area under the receiver operating characteristic curve. We also found similar prediction accuracy improvements when we jointly analyzed GWAS data for Crohn’s disease and ulcerative colitis. The empirical observations were substantiated through our comprehensive simulation studies, suggesting that a gain in prediction accuracy can be obtained by combining phenotypes with relatively high genetic correlations. Through both real data and simulation studies, we demonstrated pleiotropy can be leveraged as a valuable asset that opens up a new opportunity to improve genetic risk prediction in the future.     

Explainable deep transfer learning model for disease risk prediction using high-dimensional genomic data

Building an accurate disease risk prediction model is an essential step in the modern quest for precision medicine. While high-dimensional genomic data provides valuable data resources for the investigations of disease risk, their huge amount of noise and complex relationships between predictors and outcomes have brought tremendous analytical challenges. Deep learning model is the state-of-the-art methods for many prediction tasks, and it is a promising framework for the analysis of genomic data. However, deep learning models generally suffer from the curse of dimensionality and the lack of biological interpretability, both of which have greatly limited their applications. In this work, we have developed a deep neural network (DNN) based prediction modeling framework. We first proposed a group-wise feature importance score for feature selection, where genes harboring genetic variants with both linear and non-linear effects are efficiently detected. We then designed an explainable transfer-learning based DNN method, which can directly incorporate information from feature selection and accurately capture complex predictive effects. The proposed DNN-framework is biologically interpretable, as it is built based on the selected predictive genes. It is also computationally efficient and can be applied to genome-wide data. Through extensive simulations and real data analyses, we have demonstrated that our proposed method can not only efficiently detect predictive features, but also accurately predict disease risk, as compared to many existing methods.     

Ascertainment and Prevention of Genetic Disease

A genetic register system has been developed for the ascertainment and prevention of genetic disease. Its potential value is illustrated with data collected from 478 families with serious genetic disorders which had been seen during the past five years. Of these 249 were referred specifically for genetic counselling, autosomal dominant disorders accounting for the largest group of families with individuals at high risk of becoming affected. Of 717 individuals at high risk of having affected children (or carrier daughters in the case of X-linked recessive disorders), only 101 were referred specifically for counselling. Many were referred only after the birth of an affected child which might otherwise have been prevented. A genetic register system linked to practitioner, hospital, and health department records could be a valuable means of preventing genetic disease.     

Human CSF GABA Concentrations: Revised Dowd for Controls, but Not Decreased in Huntington''s Chorea

gamma-Aminobutyric acid (GABA) concentrations were measured in CSF specimens from two large groups of control subjects, one without neurological or psychiatric disease, and one with a variety of neurological disorders not known to involve altered GABAergic function in brain. CSF GABA was also measured in patients with Huntington's chorea and in patients with other choreiform disorders. GABA was measured in CSF by a modification of the ion exchange-fluorometric method that featured use of a relatively large cation exchange column, and a markedly decreased quantity of sulfosalicylic acid for deproteinization of CSF. Mean BABA concentrations in CSF were 87 and 77 nmol/liter for neurologically normal and abnormal control subjects, 82 nmol/liter for the Huntington's chorea patients, and 105 nmol/liter for patients with other forms of chorea. The mean concentration of homocarnosine was not reduced in CSF of Huntington's chorea patients as compared with controls. Mean CSF GABA concentrations found in control subjects were less than half the lowest control means previously reported. These low values are attributable in part to a reduction in on-column hydrolysis of conjugated forms of GABA in CSF, which can be produced by excessive sulfosalicylic acid, and in part to improved chromatographic resolution of GABA from other unknown o-phthalaldehyde-reactive compounds in CSF. Analysis of free GABA in CSF does not appear useful for diagnosis of suspected Huntington's chorea, nor as a possible predictive test for persons genetically at risk for Huntington's chorea.     

Huntington's disease. Contribution of clinical and epidemiological data to genetic counseling

From a regional survey (northwestern part of France 3,9 millions population) and from recent publications, the authors described clinical and epidemiologic aspects useful for genetic counselling. Besides the chronic chorea, the other clinical features justified the denomination "Huntington's disease". Misdiagnosis is frequent especially if the familial disorder is unknown. A prevalence of 50 X 10(-6) corresponds to 2750 choreics and 14.000 at risk descendants in France. Interfamilial heterogeneity is described from mean age of death which is 54.2 for the whole study: one third of families of late onset, around fifty (mean age of death: 64.6), one third of early onset, around thirty (mean age of death: 44.6). The 17 juvenile and infantile cases of the survey belong to this last group. The influence of gene-transmitters sex is more obvious if two generations are taken in account with a preponderance of fathers and grand-fathers in the early onset group and, to a lesser degree, of mothers and grand-mothers in the late onset group. The authors criticize the preclinical detection tests and, from attitudes of families, underline the ethical problems for the future predictive tests by genetic markers. The role of lay organisations is all the more important.     

The metabolic syndrome: should current criteria influence clinical practice?

PURPOSE OF REVIEW: Many studies have recommended use of metabolic syndrome as an 'alternative' means to assess vascular disease risk, but few have been rigorous, leading to confusion amongst physicians regarding risk screening. This review critically appraises this evidence and also evaluates the data linking metabolic syndrome to type 2 diabetes. RECENT FINDINGS: Although presence of metabolic syndrome predicts vascular events, such prediction is inferior and does not enhance simpler Framingham-based risk scores which can be determined using nonfasting blood samples. The dichotomous nature of metabolic syndrome criteria and lack of age, low-density lipoprotein cholesterol, and smoking in part account for their inferior predictive ability. Metabolic syndrome criteria better predict type 2 diabetes but diabetes screening, if adopted, will likely require a two-stage process, with the first stage not dependent on blood sampling. Nevertheless, recent interest in metabolic syndrome has contributed to greater interaction between diabetologists and cardiologists and highlighted more strongly the relevance of obesity to vascular risk. SUMMARY: Best evidence suggests that current metabolic syndrome criteria should not be used as an alternative to established charts for risk prediction for vascular disease. Clinical focus should remain on established risk factors to determine and reduce risk of vascular events.     

SVM-Prot: Web-based support vector machine software for functional classification of a protein from its primary sequence

Prediction of protein function is of significance in studying biological processes. One approach for function prediction is to classify a protein into functional family. Support vector machine (SVM) is a useful method for such classification, which may involve proteins with diverse sequence distribution. We have developed a web-based software, SVMProt, for SVM classification of a protein into functional family from its primary sequence. SVMProt classification system is trained from representative proteins of a number of functional families and seed proteins of Pfam curated protein families. It currently covers 54 functional families and additional families will be added in the near future. The computed accuracy for protein family classification is found to be in the range of 69.1-99.6%. SVMProt shows a certain degree of capability for the classification of distantly related proteins and homologous proteins of different function and thus may be used as a protein function prediction tool that complements sequence alignment methods. SVMProt can be accessed at http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.     

Influence of apolipoprotein E genotype on the transmission of Alzheimer disease in a community-based sample.

The epsilon 4 allele of the apolipoprotein E locus (APOE) has been found to be an important predictor of Alzheimer disease (AD). However, linkage analysis has not clarified the role of APOE in the transmission of AD. The results of the current study provide evidence that the pattern of transmission of memory disorders differs in nuclear families in which the AD-affected proband did carry an epsilon 4 allele versus those families in which the AD-affected proband did not carry an epsilon allele. Further, risk of AD due to APOE genotype in the probands is modified by family history of memory disorders, suggesting gene-by-gene interactions. Family history remained a significant predictor of AD for affected probands with some, but not all, APOE genotypes in a logistic regression analysis. Though nonadditive in the prediction of AD, APOE genotype and family history acted additively in the prediction of age at AD onset. The results of complex segregation analysis were inconsistent with Mendelian segregation of memory disorders both in families of affected probands who did or did not carry an epsilon 4 allele, yet these two groups had significantly different parameter estimates for their transmission models. These results are consistent with gene-by-gene interactions, but also could result from common elements in the familial environment.     

The sense and nonsense of direct-to-consumer genetic testing for cardiovascular disease

Expectations are high that increasing knowledge of the genetic basis of cardiovascular disease will eventually lead to personalised medicine—to preventive and therapeutic interventions that are targeted to at-risk individuals on the basis of their genetic profiles. Most cardiovascular diseases are caused by a complex interplay of many genetic variants interacting with many non-genetic risk factors such as diet, exercise, smoking and alcohol consumption. Since several years, genetic susceptibility testing for cardiovascular diseases is being offered via the internet directly to consumers. We discuss five reasons why these tests are not useful, namely: (1) the predictive ability is still limited; (2) the risk models used by the companies are based on assumptions that have not been verified; (3) the predicted risks keep changing when new variants are discovered and added to the test; (4) the tests do not consider non-genetic factors in the prediction of cardiovascular disease risk; and (5) the test results will not change recommendations of preventive interventions. Predictive genetic testing for multifactorial forms of cardiovascular disease clearly lacks benefits for the public. Prevention of disease should therefore remain focused on family history and on non-genetic risk factors as diet and physical activity that can have the strongest impact on disease risk, regardless of genetic susceptibility.     

Localization of the human dihydropteridine reductase gene to band p15.3 of chromosome 4 by in situ hybridization

We report the localization of the gene for dihydropteridine reductase (DHPR) to the human chromosome region 4p15.3 by in situ hybridization using a cDNA probe to the enzyme. The distal end of the short arm of chromosome 4 is of considerable interest because the gene responsible for Huntington's disease is located in this region. Although this part of the chromosome is being extensively studied, DHPR is the first well-characterised gene to be assigned to the region. Restriction enzyme fragment length polymorphisms have been detected with a number of restriction endonucleases, including AvaII and MspI. These features may make the DHPR cDNA clone a useful probe not only for prenatal diagnosis of DHPR deficiency but also for linkage studies of Huntington's disease.     

Predictive testing: presymptomatic diagnosis in neurogenetic disorders

Presymptomatic testing is available since 15 years for Huntington disease and it is now possible for a number of other neurogenetic disorders, mostly neurodegenerative disorders. The possibility of determining the genetic status of an at-risk person for the disorder which run in his family raises questions because of the absence of preventive and curative treatments in most instances. In addition, being carrier does not tell you when the disease will start and how it will evolve, impairing the possibilities of planning the future. A pluridisciplinary approach to predictive testing with care before, during and after the test taking into account the medical, social and psychological aspects of the disease is good practice. At the present time, only a minority of at-risk individuals request presymptomatic testing and almost 50 % do not pursue until the results. The consequences of the test may be harmful, more frequently after an unfavorable than after a favorable result. Although the motivations and the outcome in terms of request for prenatal testing after a carrier result are different in Huntington's disease and spinocerebellar ataxias, our experience underlines the benefit of pluridisciplinary care and of time for decision taking. For other disorders like familial Alzheimer's disease, or familial Creutzfeldt-Jakob disease, the experience in presymptomatic testing is still limited but the situation seems similar to Huntington's disease because of the presence of dementia. It will be interesting to study the motivations and the outcome of the tests in disorders like autosomal dominant spastic paraplegias which usually do not reduce the life expectancy. Nevertheless, the overall situation might change greatly when efficient treatments will become available in these disorders.     

Inherited deficiency of delta-aminolevulinic acid dehydratase.

Delta-aminolevulinic acid dehydratase (ALA-D) is the second enzyme in the porphyrin-heme pathway and converts delta-aminolevulinc acid (ALA) to porphobilinogen (PBG). A family is reported with an inherited deficiency of red cell ALA-D activity occurring over three generations in an autosomal dominant pattern. Intial experiments support the hypothesis that the mutation in this family may affect a regulatory gene, but enzyme purification and further study are required. Although no clinical manifestations of deficient ALA-D activity have been found in affected persons, families such as this may be at increased risk for the serious consequences of lead poisoning, which produces marked inhibition of ALA-D activity.