Influenza in children – Diagnosis, treatment and prevention

Background: The burden of influenza on children is substantial. Although mortality rates are low, the incidence of influenza is highest in children, among whom also complications are frequent. A more accurate recognition of influenza in children could enable the rational use of antiviral drugs and help to avoid unnecessary courses of antibiotics. Limited data exists on the efficacy of oseltamivir treatment and the trivalent inactivated influenza vaccine (TIV) in children. Aims and methods: We sought for signs and symptoms that could help clinicians to diagnose influenza on clinical grounds in a case-control study in children <13 years of age. We further assessed the feasibility of different diagnostics methods during the early stage of the illness in children aged 1-3 years. The efficacy of early oseltamivir treatment (started <24h from the onset of symptoms) was evaluated in a randomized controlled trial (RCT) conducted in children 1-3 years of age, and the effectiveness of TIV to prevent laboratory-confirmed influenza was determined in a prospective, observational cohort study conducted among children aged 9 months to 3 years of age. Results: Fever was the only symptom predicting influenza in children. The sensitivity of conventionally used laboratory methods to detect influenza during the first 24h of illness was 92%. The sensitivity of the influenza rapid test in the same setting was 90% for influenza A and 25% for influenza B. Early oseltamivir treatment shortened the duration of the illness in children with influenza A by 3.5-4.0 days, but no efficacy was observed against influenza B. The effectiveness of TIV was 84% against the wellmatched influenza A, while no effectiveness against the mismatched influenza B was observed. Conclusions: Laboratory diagnostics are needed for a reliable diagnosis of influenza in children and were found sensitive already during the early stage of the illness. Early oseltamivir treatment was highly effective against influenza A, but no efficacy was seen against influenza B. TIV is effective also in young children if a good match between the vaccine and circulating strain is achieved.

Quantification and Clinical Relevance of Cystatin C

An aging population and increasing rates of diabetes mellitus contribute to a high prevalence of kidney dysfunction – approximately 10 percent of adults in developed countries have chronic kidney disease (CKD). CKD is a progressive loss of kidney function and this remains permanent. Early recognition of this condition is important for prevention or impeding severe adverse cardiac and renal outcomes. Cystatin C is a low molecular weight cysteine protease inhibitor that has emerged as a biomarker of kidney function. The special potential of plasma cystatin C in this setting is related to its independency of muscle mass, which is a remarkable limitation of the traditional marker creatinine. Cystatin C is a sensitive marker in diagnosing mild and moderate CKD, especially in small children, in the elderly and in conditions where muscle mass is affected. Cystatin C is quantified with immunoassays, mainly based on particle-enhanced nephelometry (PENIA) or turbidimetry (PETIA). The aim of this study was to develop a rapid and reliable assay for quantification of human cystatin C in plasma or serum by utilizing time-resolved fluorescence-based immunoassay methods. This was accomplished by utilizing different antibodies, including polyclonal and 7 monoclonal antibodies against cystatin C. Different assay designs were tested and the best assay was further modified to a dry-reagent double monoclonal assay run on an automated immunonalyzer. This assay was evaluated for clinical performance in estimating reduced kidney function and in predicting risk of adverse outcomes in patients with non-ST elevation acute coronary syndrome. Of the tested assay designs, heterogeneous non-competitive assay had the best performace and was chosen to be developed further. As an automated double monoclonal assay, this assay enabled a reliable measurement of clinically relevant cystatin C concentrations. It also showed a stronger concordance with the reference clearance method than the conventional PETIA method in patients with reduced kidney function. Risk of all-cause mortality and combined events, defined by death and myocardial infarction, increased with higher cystatin C and cystatin C remained an independent predictor of death and combined events after adjustment to nonbiochemical baseline factors. In conclusion, the developed dry-reagent double monoclonal assay allows rapid and reliable quantitative measurement of cystatin C. As measured with the developed assay, cystatin C is a potential predictor of adverse outcomes in cardiac patients.

Promoting Healthy Lifestyles with Personalized, APOE Genotype Based Health Information: The Effects on Psychological-, Health Behavioral and Clinical Factors

There is an increasing demand for individualized, genotype-based health advice. The general population-based dietary recommendations do not always motivate people to change their life-style, and partly following this, cardiovascular diseases (CVD) are a major cause of death in worldwide. Using genotype-based nutrition and health information (e.g. nutrigenetics) in health education is a relatively new approach, although genetic variation is known to cause individual differences in response to dietary factors. Response to changes in dietary fat quality varies, for example, among different APOE genotypes. Research in this field is challenging, because several non-modifiable (genetic, age, sex) and modifiable (e.g. lifestyle, dietary, physical activity) factors together and with interaction affect the risk of life-style related diseases (e.g. CVD). The other challenge is the psychological factors (e.g. anxiety, threat, stress, motivation, attitude), which also have an effect on health behavior. The genotype-based information is always a very sensitive topic, because it can also cause some negative consequences and feelings (e.g. depression, increased anxiety). The aim of this series of studies was firstly to study how individual, genotype-based health information affects an individual’s health form three aspects, and secondly whether this could be one method in the future to prevent lifestyle-related diseases, such as CVD. The first study concentrated on the psychological effects; the focus of the second study was on health behavior effects, and the third study concentrated on clinical effects. In the fourth study of this series, the focus was on all these three aspects and their associations with each other. The genetic risk and health information was the APOE gene and its effects on CVD. To study the effect of APOE genotype-based health information in prevention of CVD, a total of 151 volunteers attended the baseline assessments (T0), of which 122 healthy adults (aged 20 – 67 y) passed the inclusion criteria and started the one-year intervention. The participants (n = 122) were randomized into a control group (n = 61) and an intervention group (n = 61). There were 21 participants in the intervention Ɛ4+ group (including APOE genotypes 3/4 and 4/4) and 40 participants in the intervention Ɛ4- group (including APOE genotypes 2/3 and 3/3). The control group included 61 participants (including APOE genotypes 3/4, 4/4, 2/3, 3/3 and 2/2). The baseline (T0) and follow-up assessments (T1, T2, T3) included detailed measurements of psychological (threat and anxiety experience, stage of change), and behavioral (dietary fat quality, consumption of vegetables, - high fat/sugar foods and –alcohol, physical activity and health and taste attitudes) and clinical factors (total-, LDL- HDL cholesterol, triglycerides, blood pressure, blood glucose (0h and 2h), body mass index, waist circumference and body fat percentage). During the intervention six different communication sessions (lectures on healthy lifestyle and nutrigenomics, health messages by mail, and personal discussion with the doctor) were arranged. The intervention groups (Ɛ4+ and Ɛ4-) received their APOE genotype information and health message at the beginning of the intervention. The control group received their APOE genotype information after the intervention. For the analyses in this dissertation, the results for 106/107 participants were analyzed. In the intervention, there were 16 participants in the high-risk (Ɛ4+) group and 35 in the low-risk (Ɛ4-) group. The control group had 55 participants in studies III-IV and 56 participants in studies I-II. The intervention had both short-term (≤ 6 months) and long-term (12 months) effects on health behavior and clinical factors. The short-term effects were found in dietary fat quality and waist circumference. Dietary fat quality improved more in the Ɛ4+ group than the Ɛ4- and the control groups as the personal, genotype-based health information and waist circumference lowered more in the Ɛ4+ group compared with the control group. Both these changes differed significantly between the Ɛ4+ and control groups (p<0.05). A long-term effect was found in triglyceride values (p<0.05), which lowered more in Ɛ4+ compared with the control group during the intervention. Short-term effects were also found in the threat experience, which increased mostly in the Ɛ4+ group after the genetic feedback (p<0.05), but it decreased after 12 months, although remaining at a higher level compared to the baseline (T0). In addition, Study IV found that changes in the psychological factors (anxiety and threat experience, motivation), health and taste attitudes, and health behaviors (dietary, alcohol consumption, and physical activity) did not directly explain the changes in triglyceride values and waist circumference. However, change caused by a threat experience may have affected the change in triglycerides through total- and HDL cholesterol. In conclusion, this dissertation study has given some indications that individual, genotypebased health information could be one potential option in the future to prevent lifestyle-related diseases in public health care. The results of this study imply that personal genetic information, based on APOE, may have positive effects on dietary fat quality and some cardiovascular risk markers (e.g., improvement in triglyceride values and waist circumference). This study also suggests that psychological factors (e.g. anxiety and threat experience) may not be an obstacle for healthy people to use genotype-based health information to promote healthy lifestyles. However, even in the case of very personal health information, in order to achieve a permanent health behavior change, it is important to include attitudes and other psychological factors (e.g. motivation), as well as intensive repetition and a longer intervention duration. This research will serve as a basis for future studies and its information can be used to develop targeted interventions, including health information based on genotyping that would aim at preventing lifestyle diseases. People’s interest in personalized health advices has increased, while also the costs of genetic screening have decreased. Therefore, generally speaking, it can be assumed that genetic screening as a part of the prevention of lifestyle-related diseases may become more common in the future. In consequence, more research is required about how to make genetic screening a practical tool in public health care, and how to efficiently achieve long-term changes.