Nanoparticle-Assisted Immunoassays for Point-of-Care Testing - With Specific Interest in Minimally Interference-Prone Assays for Cardiac Troponin I

Cardiac troponins (cTn) I and T are the current golden standard biochemical markers in the diagnosis and risk stratification of patients with suspected acute coronary syndrome. During the past few years, novel assays capable of detecting cTn‐concentrations in >50% of apparently healthy individuals have become readily available. With the emerging of these high sensitivity cTn assays, reductions in the assay specificity have caused elevations in the measured cTn levels that do not correlate with the clinical picture of the patient. The increased assay sensitivity may reveal that various analytical interference mechanisms exist. This doctoral thesis focused on developing nanoparticle‐assisted immunometric assays that could possibly be applied to an automated point‐of‐care system. The main objective was to develop minimally interference‐prone assays for cTnI by employing recombinant antibody fragments. Fast 5‐ and 15‐minute assays for cTnI and D‐dimer, a degradation product of fibrin, based on intrinsically fluorescent nanoparticles were introduced, thus highlighting the versatility of nanoparticles as universally applicable labels. The utilization of antibody fragments in different versions of the developed cTnI‐assay enabled decreases in the used antibody amounts without sacrificing assay sensitivity. In addition, the utilization of recombinant antibody fragments was shown to significantly decrease the measured cTnI concentrations in an apparently healthy population, as well as in samples containing known amounts of potentially interfering factors: triglycerides, bilirubin, rheumatoid factors, or human anti‐mouse antibodies. When determining the specificity of four commercially available antibodies for cTnI, two out of the four cross‐reacted with skeletal troponin I, but caused crossreactivity issues in patient samples only when paired together. In conclusion, the results of this thesis emphasize the importance of careful antibody selection when developing cTnI assays. The results with different recombinant antibody fragments suggest that the utilization of antibody fragments should strongly be encouraged in the immunoassay field, especially with analytes such as cTnI that require highly sensitive assay approaches.

Analyzing change in medication use - statistical approaches

The objective of this study was to gain an understanding of the effects of population heterogeneity, missing data, and causal relationships on parameter estimates from statistical models when analyzing change in medication use. From a public health perspective, two timely topics were addressed: the use and effects of statins in populations in primary prevention of cardiovascular disease and polypharmacy in older population. Growth mixture models were applied to characterize the accumulation of cardiovascular and diabetes medications among apparently healthy population of statin initiators. The causal effect of statin adherence on the incidence of acute cardiovascular events was estimated using marginal structural models in comparison with discrete-time hazards models. The impact of missing data on the growth estimates of evolution of polypharmacy was examined comparing statistical models under different assumptions for missing data mechanism. The data came from Finnish administrative registers and from the population-based Geriatric Multidisciplinary Strategy for the Good Care of the Elderly study conducted in Kuopio, Finland, during 2004–07. Five distinct patterns of accumulating medications emerged among the population of apparently healthy statin initiators during two years after statin initiation. Proper accounting for time-varying dependencies between adherence to statins and confounders using marginal structural models produced comparable estimation results with those from a discrete-time hazards model. Missing data mechanism was shown to be a key component when estimating the evolution of polypharmacy among older persons. In conclusion, population heterogeneity, missing data and causal relationships are important aspects in longitudinal studies that associate with the study question and should be critically assessed when performing statistical analyses. Analyses should be supplemented with sensitivity analyses towards model assumptions.

Erectile dysfunction in cardiovascular risk population

The inability to achieve and to maintain erection, erectile dysfunction, is a bothersome symptom of elderly men. Moreover, there is a high comorbidity between cardiovascular diseases and erectile dysfunction. However, very little is known concerning the risk factors of ED in apparently healthy men without comorbidities affecting the arteries. A cross-sectional population survey was conducted from August 2005 to September 2007 in two rural towns of Harjavalta and Kokemäki in Finland. Excluding those with previously diagnosed cardiovascular diseases, diabetes or chronic kidney disease, every community-dwelling inhabitant was invited to take part in the survey. Of the 2939 45- to 70-year-old men invited, 2049 responded. Selecting those at risk for cardiovascular diseases, 1000 eligible men were examined. According to the International Index of Erectile Function short form 57% of the studied men reported erectile dysfunction. Increasing age, smoking, depressive symptoms, decreasing pulmonary function, sedentary lifestyle, non-marital status and low education level were associated with increasing risk of erectile dysfunction. However, hypertension, diabetes, obesity, hypercholesterolemia were not associated with erectile dysfunction, although these associations have been described in numerous previous studies. Moreover, erectile dysfunction was not associated with increasing risk of pre-diabetes. In apparently healthy men, increasing age, smoking, depressive symptoms, decreasing pulmonary function, sedentary lifestyle, non-marital status, low education level but not hypertension, obesity, hypercholesterolemia, diabetes or pre-diabetes were associated with increasing risk of erectile dysfunction.

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.