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- Byberg, Liisa, 1972-
(författare)
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Plasminogen Activator Inhibitor-1 and the Insulin Resistance Syndrome
- 2002
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this thesis, different aspects of the insulin resistance syndrome in relation to plasminogen activator inhibitor-1 (PAI-1) activity are investigated in a longitudinal population-based study. Participants were men investigated at ages 50 and 70 with follow-up data on mortality.High PAI-1 activity was associated with low insulin sensitivity, high concentrations of serum triglycerides, high body mass index and high waist/hip ratio, independently of each other and of potential confounders. Low birth weight predicted high blood pressure, insulin resistance, truncal obesity and high PAI-1 activity but not the abdominal obesity or dyslipidaemia present in the insulin resistance syndrome. Increased physical activity level between 50 and 70 years of age, in the absence of active intervention, was associated with improved glucose, insulin, proinsulin and lipoprotein metabolism. Insulin and proinsulin seemed to be important factors that mediate much of the association between a sedentary lifestyle and increased risk of cardiovascular disease. The reported dietary intake of both mono- and polyunsaturated fatty acids was positively associated with PAI-1 activity, whereas saturated fatty acid intake displayed no association. The associations present between PAI-1 activity and the fatty acid proportions in serum cholesterol esters were partly influenced by factors related with the insulin resistance syndrome.This thesis provides further knowledge to the epidemiological view of the interrelations of the insulin resistance syndrome, PAI-1, birth weight, and lifestyle factors as physical activity and dietary habits. PAI-1 is a part of the insulin resistance syndrome and is associated both with modifiable and non-modifiable factors related with this syndrome.
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| 2. |
- Frånberg, Mattias, 1985-
(författare)
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Statistical methods for detecting gene-gene and gene-environment interactions in genome-wide association studies
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Despite considerable effort to elucidate the genetic architecture of multi-factorial traits and diseases, there remains a gap between the estimated heritability (e.g., from twin studies) and the heritability explained by discovered genetic variants. The existence of interactions between different genes, and between genes and the environment, has frequently been hypothesized as a likely cause of this discrepancy. However, the statistical inference of interactions is plagued by limited sample sizes, high computational requirements, and incomplete knowledge of how the measurement scale and parameterization affect the analysis.This thesis addresses the major statistical, computational, and modeling issues that hamper large-scale interaction studies today. Furthermore, it investigates whether gene-gene and gene-environment interactions are significantly involved in the development of diseases linked to atherosclerosis. Firstly, I develop two statistical methods that can be used to study of gene-gene interactions: the first is tailored for limited sample size situations, and the second enables multiple analyses to be combined into large meta-analyses. I perform comprehensive simulation studies to determine that these methods have higher or equal statistical power than contemporary methods, scale-invariance is required to guard against false positives, and that saturated parameterizations perform well in terms of statistical power. In two studies, I apply the two proposed methods to case/control data from myocardial infarction and associated phenotypes. In both studies, we identify putative interactions for myocardial infarction but are unable to replicate the interactions in a separate cohort. In the second study, however, we identify and replicate a putative interaction involved in Lp(a) plasma levels between two variants rs3103353 and rs9458157. Secondly, I develop a multivariate statistical method that simultaneously estimates the effects of genetic variants, environmental variables, and their interactions. I show by extensive simulations that this method achieves statistical power close to the optimal oracle method. We use this method to study the involvement of gene-environment interactions in intima-media thickness, a phenotype relevant for coronary artery disease. We identify a putative interaction between a genetic variant in the KCTD8 gene and alcohol use, thus suggesting an influence on intima-media thickness. The methods developed to support the analyses in this thesis as well as a selection of other prominent methods in the field is implemented in a software package called besiq.In conclusion, this thesis presents statistical methods, and the associated software, that allows large-scale studies of gene-gene and gene-environment interactions to be effortlessly undertaken.
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