Huntington's disease: new aspects on phenotype and genotype

Huntington's disease typically presents with involuntary movements, cognitive decline and behavioural abnormalities; however, new data show a greater spectrum and more complexity in the mode of presentation than previously appreciated. On one hand efforts are under way to better assess all aspects of the evolving phenotype over the course of the disease, on the other hand large cohorts have been prospectively followed-up and similar efforts are now being started in China. In this communication, we briefly review the most salient findings from the last couple of years. The recently established large cohorts allow the performance of accurate studies examining correlation of genetic polymorphisms with specific aspects of the phenotype thus allowing for some mechanistic insight into the causes of phenotypic variation. While Huntington's disease is the most frequent hereditary cause of chorea, other disorders with similar clinical phenotypes, including neuroacanthocytosis, are now better known, including a better understanding of the primary cause as well as the pathophysiology at the molecular level. Studies on the mechanisms of disease in these different disorders may shed light on the respective pathomechanisms and may open new approaches to a better understanding and additional treatment options for choreatiform neurodegenerative disorders.

Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

Background Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the pre-determined sensitivity and specificity. Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and sampling bias.

Towards optimal treatment with growth hormone in short children and adolescents: evidence and theses

Treatment with growth hormone (GH) has become standard practice for replacement in GH-deficient children or pharmacotherapy in a variety of disorders with short stature. However, even today, the reported adult heights achieved often remain below the normal range. In addition, the treatment is expensive and may be associated with long-term risks. Thus, a discussion of the factors relevant for achieving an optimal individual outcome in terms of growth, costs, and risks is required. In the present review, the heterogenous approaches of treatment with GH are discussed, considering the parameters available for an evaluation of the short- and long-term outcomes at different stages of treatment. This discourse introduces the potential of the newly emerging prediction algorithms in comparison to other more conventional approaches for the planning and evaluation of the response to GH. In rare disorders such as those with short stature, treatment decisions cannot easily be deduced from personal experience. An interactive approach utilizing the derived experience from large cohorts for the evaluation of the individual patient and the required decision-making may facilitate the use of GH. Such an approach should also lead to avoiding unnecessary long-term treatment in unresponsive individuals.

A 600 kb deletion syndrome at 16p11.2 leads to energy imbalance and neuropsychiatric disorders

BACKGROUND: The recurrent ~600 kb 16p11.2 BP4-BP5 deletion is among the most frequent known genetic aetiologies of autism spectrum disorder (ASD) and related neurodevelopmental disorders. OBJECTIVE: To define the medical, neuropsychological, and behavioural phenotypes in carriers of this deletion. METHODS: We collected clinical data on 285 deletion carriers and performed detailed evaluations on 72 carriers and 68 intrafamilial non-carrier controls. RESULTS: When compared to intrafamilial controls, full scale intelligence quotient (FSIQ) is two standard deviations lower in carriers, and there is no difference between carriers referred for neurodevelopmental disorders and carriers identified through cascade family testing. Verbal IQ (mean 74) is lower than non-verbal IQ (mean 83) and a majority of carriers require speech therapy. Over 80% of individuals exhibit psychiatric disorders including ASD, which is present in 15% of the paediatric carriers. Increase in head circumference (HC) during infancy is similar to the HC and brain growth patterns observed in idiopathic ASD. Obesity, a major comorbidity present in 50% of the carriers by the age of 7 years, does not correlate with FSIQ or any behavioural trait. Seizures are present in 24% of carriers and occur independently of other symptoms. Malformations are infrequently found, confirming only a few of the previously reported associations. CONCLUSIONS: The 16p11.2 deletion impacts in a quantitative and independent manner FSIQ, behaviour and body mass index, possibly through direct influences on neural circuitry. Although non-specific, these features are clinically significant and reproducible. Lastly, this study demonstrates the necessity of studying large patient cohorts ascertained through multiple methods to characterise the clinical consequences of rare variants involved in common diseases.

Evidence of viral adaptation to HLA class I-restricted immune pressure in chronic hepatitis C virus infection

Cellular immune responses are an important correlate of hepatitis C virus (HCV) infection outcome. These responses are governed by the host's human leukocyte antigen (HLA) type, and HLA-restricted viral escape mutants are a critical aspect of this host-virus interaction. We examined the driving forces of HCV evolution by characterizing the in vivo selective pressure(s) exerted on single amino acid residues within nonstructural protein 3 (NS3) by the HLA types present in two host populations. Associations between polymorphisms within NS3 and HLA class I alleles were assessed in 118 individuals from Western Australia and Switzerland with chronic hepatitis C infection, of whom 82 (69%) were coinfected with human immunodeficiency virus. The levels and locations of amino acid polymorphisms exhibited within NS3 were remarkably similar between the two cohorts and revealed regions under functional constraint and selective pressures. We identified specific HCV mutations within and flanking published epitopes with the correct HLA restriction and predicted escaped amino acid. Additional HLA-restricted mutations were identified that mark putative epitopes targeted by cell-mediated immune responses. This analysis of host-virus interaction reveals evidence of HCV adaptation to HLA class I-restricted immune pressure and identifies in vivo targets of cellular immune responses at the population level.

Impact of weather and climate on the incidence of acute coronary syndromes

BACKGROUND: First investigations of the interactions between weather and the incidence of acute myocardial infarctions date back to 1938. The early observation of a higher incidence of myocardial infarctions in the cold season could be confirmed in very different geographical regions and cohorts. While the influence of seasonal variations on the incidence of myocardial infarctions has been extensively documented, the impact of individual meteorological parameters on the disease has so far not been investigated systematically. Hence the present study intended to assess the impact of the essential variables of weather and climate on the incidence of myocardial infarctions. METHODS: The daily incidence of myocardial infarctions was calculated from a national hospitalization survey. The hourly weather and climate data were provided by the database of the national weather forecast. The epidemiological and meteorological data were correlated by multivariate analysis based on a generalized linear model assuming a log-link-function and a Poisson distribution. RESULTS: High ambient pressure, high pressure gradients, and heavy wind activity were associated with an increase in the incidence of the totally 6560 hospitalizations for myocardial infarction irrespective of the geographical region. Snow- and rainfall had inconsistent effects. Temperature, Foehn, and lightning showed no statistically significant impact. CONCLUSIONS: Ambient pressure, pressure gradient, and wind activity had a statistical impact on the incidence of myocardial infarctions in Switzerland from 1990 to 1994. To establish a cause-and-effect relationship more data are needed on the interaction between the pathophysiological mechanisms of the acute coronary syndrome and weather and climate variables.

Myocardial infarction and post-traumatic stress disorder: frequency, outcome, and atherosclerotic mechanisms

BACKGROUND: Post-traumatic stress disorder (PTSD) may develop in the aftermath of an acute myocardial infarction (MI). Whether PTSD is a risk factor for cardiovascular disease (CVD) is elusive. The biological mechanisms linking PTSD with atherosclerosis are unclear. DESIGN: A critical review of 31 studies in the English language pursuing three aims: (i) to estimate the prevalence of PTSD in post-MI patients; (ii) to investigate the association of PTSD with cardiovascular endpoints; and (iii) to search for low-grade systemic inflammatory changes in PTSD pertinent to atherosclerosis. METHODS: We located studies by PubMed electronic library search and through checking the bibliographies of these sources. RESULTS: The weighted prevalence of PTSD after MI was 14.7% (range 0-25%; a total of 13 studies and 827 post-MI patients). Two studies reported a prospective association between PTSD and an increased risk of cardiovascular readmission in post-MI patients and of cardiovascular mortality in combat veterans, respectively. In a total of 11 studies, patients with PTSD had increased rates of physician-rated and self-reported cardiovascular diseases. Various cytokines and C-reactive protein were investigated in a total of seven studies suggesting that PTSD confers a pro-inflammatory state. CONCLUSIONS: Increasing evidence suggests that PTSD specifically related to MI develops considerably frequently in post-MI patients. More research is needed in larger cohorts applying a population design to substantiate findings suggesting PTSD is an atherogenic risk factor and to understand better the suspected behavioural and biological mechanisms involved.

Estimating Patterns of CD4+ Lymphocyte Decline Using Data from a Prevalent Cohort of HIV Infected Individuals

In natural history studies of chronic disease, it is of interest to understand the evolution of key variables that measure aspects of disease progression. This is particularly true for immunological variables in persons infected with the Human Immunodeficiency Virus (HIV). The natural timescale for such studies is time since infection. However, most data available for analysis arise from prevalent cohorts, where the date of infection is unknown for most or all individuals. As a result, standard curve fitting algorithms are not immediately applicable. Here we propose two methods to circumvent this difficulty. The first uses repeated measurement data to provide information not only on the level of the variable of interest, but also on its rate of change, while the second uses an estimate of the expected time since infection. Both methods are based on the principal curves algorithm of Hastie and Stuetzle, and are applied to data from a prevalent cohort of HIV-infected homosexual men, giving estimates of the average pattern of CD4+ lymphocyte decline. These methods are applicable to natural history studies using data from prevalent cohorts where the time of disease origin is uncertain, provided certain ancillary information is available from external sources.

The Impact of Uncertainty in the AIDS Incubation Period on Reconstructions of the HIV Epidemic

Backcalculation is the primary method used to reconstruct past human immunodeficiency virus (HIV) infection rates, to estimate current prevalence of HIV infection, and to project future incidence of acquired immunodeficiency syndrome (AIDS). The method is very sensitive to uncertainty about the incubation period. We estimate incubation distributions from three sets of cohort data and find that the estimates for the cohorts are substantially different. Backcalculations employing the different estimates produce equally good fits to reported AIDS counts but quite different estimates of cumulative infections. These results suggest that the incubation distribution is likely to differ for different populations and that the differences are large enough to have a big impact on the resulting estimates of HIV infection rates. This seriously limits the usefulness of backcalculation for populations (such as intravenous drug users, heterosexuals, and women) that lack precise information on incubation times.

Uncertainty About the Incubation Period of AIDS and its Impact on Backcalculation

We analyze three sets of doubly-censored cohort data on incubation times, estimating incubation distributions using semi-parametric methods and assessing the comparability of the estimates. Weibull models appear to be inappropriate for at least one of the cohorts, and the estimates for the different cohorts are substantially different. We use these estimates as inputs for backcalculation, using a nonparametric method based on maximum penalized likelihood. The different incubations all produce fits to the reported AIDS counts that are as good as the fit from a nonstationary incubation distribution that models treatment effects, but the estimated infection curves are very different. We also develop a method for estimating nonstationarity as part of the backcalculation procedure and find that such estimates also depend very heavily on the assumed incubation distribution. We conclude that incubation distributions are so uncertain that meaningful error bounds are difficult to place on backcalculated estimates and that backcalculation may be too unreliable to be used without being supplemented by other sources of information in HIV prevalence and incidence.

How can we measure the impact of pollutants on respiratory function in very young children? Methodological aspects

There is increasing evidence that air pollution particularly affects infants and small preschool children. However, detecting air pollution effects on lung function in small children is technically difficult and requires non-invasive methods that can assess lung function and inflammatory markers in larger cohorts. This review discusses the principles, usefulness and shortcomings of various lung function techniques used to detect pollution effects in small children. The majority of these techniques have been used to detect effects of the dominant indoor pollutant, tobacco exposure. However there is increasing evidence that non-invasive lung function techniques can also detect the effects of outdoor air pollution.

MORTALITY IN THE MEDICARE POPULATION AND CHRONIC EXPOSURE TO FINE PARTICULATE AIR POLLUTION

Prospective cohort studies have provided evidence on longer-term mortality risks of fine particulate matter (PM2.5), but due to their complexity and costs, only a few have been conducted. By linking monitoring data to the U.S. Medicare system by county of residence, we developed a retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), comprising over 20 million enrollees in the 250 largest counties during 2000-2002. We estimated log-linear regression models having as outcome the age-specific mortality rate for each county and as the main predictor, the average level for the study period 2000. Area-level covariates were used to adjust for socio-economic status and smoking. We reported results under several degrees of adjustment for spatial confounding and with stratification into by eastern, central and western counties. We estimated that a 10 µg/m3 increase in PM25 is associated with a 7.6% increase in mortality (95% CI: 4.4 to 10.8%). We found a stronger association in the eastern counties than nationally, with no evidence of an association in western counties. When adjusted for spatial confounding, the estimated log-relative risks drop by 50%. We demonstrated the feasibility of using Medicare data to establish cohorts for follow-up for effects of air pollution. Particulate matter (PM) air pollution is a global public health problem (1). In developing countries, levels of airborne particles still reach concentrations at which serious health consequences are well-documented; in developed countries, recent epidemiologic evidence shows continued adverse effects, even though particle levels have declined in the last two decades (2-6). Increased mortality associated with higher levels of PM air pollution has been of particular concern, giving an imperative for stronger protective regulations (7). Evidence on PM and health comes from studies of acute and chronic adverse effects (6). The London Fog of 1952 provides dramatic evidence of the unacceptable short-term risk of extremely high levels of PM air pollution (8-10); multi-site time-series studies of daily mortality show that far lower levels of particles are still associated with short-term risk (5)(11-13). Cohort studies provide complementary evidence on the longer-term risks of PM air pollution, indicating the extent to which exposure reduces life expectancy. The design of these studies involves follow-up of cohorts for mortality over periods of years to decades and an assessment of mortality risk in association with estimated long-term exposure to air pollution (2-4;14-17). Because of the complexity and costs of such studies, only a small number have been conducted. The most rigorously executed, including the Harvard Six Cities Study and the American Cancer Society’s (ACS) Cancer Prevention Study II, have provided generally consistent evidence for an association of long- term exposure to particulate matter air pollution with increased all-cause and cardio-respiratory mortality (2,4,14,15). Results from these studies have been used in risk assessments conducted for setting the U.S. National Ambient Air Quality Standard (NAAQS) for PM and for estimating the global burden of disease attributable to air pollution (18,19). Additional prospective cohort studies are necessary, however, to confirm associations between long-term exposure to PM and mortality, to broaden the populations studied, and to refine estimates by regions across which particle composition varies. Toward this end, we have used data from the U.S. Medicare system, which covers nearly all persons 65 years of age and older in the United States. We linked Medicare mortality data to (particulate matter less than 2.5 µm in aerodynamic diameter) air pollution monitoring data to create a new retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), consisting of 20 million persons from 250 counties and representing about 50% of the US population of elderly living in urban settings. In this paper, we report on the relationship between longer-term exposure to PM2.5 and mortality risk over the period 2000 to 2002 in the MCAPS.

A coronary heart disease risk model for predicting the effect of potent antiretroviral therapy in HIV-1 infected men

BACKGROUND: Many HIV-infected patients on highly active antiretroviral therapy (HAART) experience metabolic complications including dyslipidaemia and insulin resistance, which may increase their coronary heart disease (CHD) risk. We developed a prognostic model for CHD tailored to the changes in risk factors observed in patients starting HAART. METHODS: Data from five cohort studies (British Regional Heart Study, Caerphilly and Speedwell Studies, Framingham Offspring Study, Whitehall II) on 13,100 men aged 40-70 and 114,443 years of follow up were used. CHD was defined as myocardial infarction or death from CHD. Model fit was assessed using the Akaike Information Criterion; generalizability across cohorts was examined using internal-external cross-validation. RESULTS: A parametric model based on the Gompertz distribution generalized best. Variables included in the model were systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, triglyceride, glucose, diabetes mellitus, body mass index and smoking status. Compared with patients not on HAART, the estimated CHD hazard ratio (HR) for patients on HAART was 1.46 (95% CI 1.15-1.86) for moderate and 2.48 (95% CI 1.76-3.51) for severe metabolic complications. CONCLUSIONS: The change in the risk of CHD in HIV-infected men starting HAART can be estimated based on typical changes in risk factors, assuming that HRs estimated using data from non-infected men are applicable to HIV-infected men. Based on this model the risk of CHD is likely to increase, but increases may often be modest, and could be offset by lifestyle changes.

Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies

OBJECTIVE: To estimate the prognosis over 5 years of HIV-1-infected, treatment-naive patients starting HAART, taking into account the immunological and virological response to therapy. DESIGN: A collaborative analysis of data from 12 cohorts in Europe and North America on 20,379 adults who started HAART between 1995 and 2003. METHODS: Parametric survival models were used to predict the cumulative incidence at 5 years of a new AIDS-defining event or death, and death alone, first from the start of HAART and second from 6 months after the start of HAART. Data were analysed by intention-to-continue-treatment, ignoring treatment changes and interruptions. RESULTS: During 61 798 person-years of follow-up, 1005 patients died and an additional 1303 developed AIDS. A total of 10 046 (49%) patients started HAART either with a CD4 cell count of less than 200 cells/microl or with a diagnosis of AIDS. The 5-year risk of AIDS or death (death alone) from the start of HAART ranged from 5.6 to 77% (1.8-65%), depending on age, CD4 cell count, HIV-1-RNA level, clinical stage, and history of injection drug use. From 6 months the corresponding figures were 4.1-99% for AIDS or death and 1.3-96% for death alone. CONCLUSION: On the basis of data collected routinely in HIV care, prognostic models with high discriminatory power over 5 years were developed for patients starting HAART in industrialized countries. A risk calculator that produces estimates for progression rates at years 1 to 5 after starting HAART is available from www.art-cohort-collaboration.org.

Prediction of first coronary events with the Framingham score: a systematic review

BACKGROUND: Uncertainty exists about the performance of the Framingham risk score when applied in different populations. OBJECTIVE: We assessed calibration of the Framingham risk score (ie, relationship between predicted and observed coronary event rates) in US and non-US populations free of cardiovascular disease. METHODS: We reviewed studies that evaluated the performance of the Framingham risk score to predict first coronary events in a validation cohort, as identified by Medline, EMBASE, BIOSIS, and Cochrane library searches (through August 2005). Two reviewers independently assessed 1496 studies for eligibility, extracted data, and performed quality assessment using predefined forms. RESULTS: We included 25 validation cohorts of different population groups (n = 128,000) in our main analysis. Calibration varied over a wide range from under- to overprediction of absolute risk by factors of 0.57 to 2.7. Risk prediction for 7 cohorts (n = 18658) from the United States, Australia, and New Zealand was well calibrated (corresponding figures: 0.87-1.08; for the 5 biggest cohorts). The estimated population risks for first coronary events were strongly associated (goodness of fit: R2 = 0.84) and in good agreement with observed risks (coefficient for predicted risk: beta = 0.84; 95% CI 0.41-1.26). In 18 European cohorts (n = 109499), the corresponding figures indicated close association (R2 = 0.72) but substantial overprediction (beta = 0.58, 95% CI 0.39-0.77). The risk score was well calibrated on the intercept for both population clusters. CONCLUSION: The Framingham score is well calibrated to predict first coronary events in populations from the United States, Australia, and New Zealand. Overestimation of absolute risk in European cohorts requires recalibration procedures.