Effects of polymorphisms in beta1-adrenoceptor and alpha-subunit of G protein on heart rate and blood pressure during exercise test. The finnish cardiovascular study.

J Appl Physiol vol 100, no 2, pp 507-511, 2006

Measurement of Bioactivity of Immunomodulatory Treatment of Relapsing Multiple Sclerosis. With Emphasis on MxA Protein

Background Multiple sclerosis (MS) is a demyelinating disease of the central nervous system, which mainly affects young adults. In Finland, approximately 2500 out of 6000 MS patients have relapsing MS and are treated with disease modifying drugs (DMD): interferon- β (INF-β-1a or INF-β-1b) and glatiramer acetate (GA). Depending on the used IFN-β preparation, 2 % to 40 % of patients develop neutralizing antibodies (NAbs), which abolish the biological effects of IFN-β, leading to reduced clinical and MRI detected efficacy. According to the Finnish Current Care Guidelines and European Federation of Neurological Societis (EFNS) guidelines, it is suggested tomeasure the presence of NAbs during the first 24 months of IFN-β therapy. Aims The aim of this thesis was to measure the bioactivity of IFN-β therapy by focusing on the induction of MxA protein (myxovirus resistance protein A) and its correlation to neutralizing antibodies (NAb). A new MxA EIA assay was set up to offer an easier and rapid method for MxA protein detection in clinical practice. In addition, the tolerability and safety of GA were evaluated in patients who haddiscontinued IFN-β therapy due to side effects and lack of efficacy. Results NAbs developed towards the end of 12 months of treatment, and binding antibodies were detectable before or parallel with them. The titer of NAb correlated negatively with the amount of MxA protein and the mean values of preinjection MxA levels never returned to true baseline in NAb negative patients, but tended to drop in the NAb positive group. The test results between MxA EIA and flow cytometric analysis showed significant correlation. GA reduced the relapse rate and was a safe and well-tolerated therapy in IFN-β-intolerant MS patients. Conclusions NAbs inhibit the induction of MxA protein, which can be used as a surrogate marker of the bioactivity of IFN-β therapy. Compared to flow cytometricanalysis and NAb assay, MxA-EIA seemed to be a sensitive and more practical method in clinical use to measure the actual bioactivity of IFN-β treatment, which is of value also from a cost-effective perspective.

From Molecular Blocks To Bioanalytical Assays: Combining Lanthanide Luminescence and Bioaffinity Binders for Protein Detection

Measuring protein biomarkers from sample matrix, such as plasma, is one of the basic tasks in clinical diagnostics. Bioanalytical assays used for the measuring should be able to measure proteins with high sensitivity and specificity. Furthermore, multiplexing capability would also be advantageous. To ensure the utility of the diagnostic test in point-of-care setting, additional requirements such as short turn-around times, ease-ofuse and low costs need to be met. On the other hand, enhancement of assay sensitivity could enable exploiting novel biomarkers, which are present in very low concentrations and which the current immunoassays are unable to measure. Furthermore, highly sensitive assays could enable the use of minimally invasive sampling. In the development of high-sensitivity assays the label technology and affinity binders are in pivotal role. Additionally, innovative assay designs contribute to the obtained sensitivity and other characteristics of the assay as well as its applicability. The aim of this thesis was to study the impact of assay components on the performance of both homogeneous and heterogeneous assays. Applicability of two different lanthanide-based label technologies, upconverting nanoparticles and switchable lanthanide luminescence, to protein detection was explored. Moreover, the potential of recombinant antibodies and aptamers as alternative affinity binders were evaluated. Additionally, alternative conjugation chemistries for production of the labeled binders were studied. Different assay concepts were also evaluated with respect to their applicability to point-of-care testing, which requires simple yet sensitive methods. The applicability of upconverting nanoparticles to the simultaneous quantitative measurement of multiple analytes using imaging-based detection was demonstrated. Additionally, the required instrumentation was relatively simple and inexpensive compared to other luminescent lanthanide-based labels requiring time-resolved measurement. The developed homogeneous assays exploiting switchable lanthanide luminescence were rapid and simple to perform and thus applicable even to point-ofcare testing. The sensitivities of the homogeneous assays were in the picomolar range, which are still inadequate for some analytes, such as cardiac troponins, requiring ultralow limits of detection. For most analytes, however, the obtained limits of detection were sufficient. The use of recombinant antibody fragments and aptamers as binders allowed site-specific and controlled covalent conjugation to construct labeled binders reproducibly either by using chemical modification or recombinant technology. Luminescent lanthanide labels were shown to be widely applicable for protein detection in various assay setups and to contribute assay sensitivity.

Prediction of Phosphorylation Sites from Protein Sequences

Phosphorylation is amongst the most crucial and well-studied post-translational modifications. It is involved in multiple cellular processes which makes phosphorylation prediction vital for understanding protein functions. However, wet-lab techniques are labour and time intensive. Thus, computational tools are required for efficiency. This project aims to provide a novel way to predict phosphorylation sites from protein sequences by adding flexibility and Sezerman Grouping amino acid similarity measure to previous methods, as discovering new protein sequences happens at a greater rate than determining protein structures. The predictor – NOPAY - relies on Support Vector Machines (SVMs) for classification. The features include amino acid encoding, amino acid grouping, predicted secondary structure, predicted protein disorder, predicted protein flexibility, solvent accessibility, hydrophobicity and volume. As a result, we have managed to improve phosphorylation prediction accuracy for Homo sapiens by 3% and 6.1% for Mus musculus. Sensitivity at 99% specificity was also increased by 6% for Homo sapiens and for Mus musculus by 5% on independent test sets. In this study, we have managed to increase phosphorylation prediction accuracy for Homo sapiens and Mus musculus. When there is enough data, future versions of the software may also be able to predict other organisms.