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- Jakobson Mo, Susanna, et al.
(författare)
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VNTR polymorphism in the SLC6A3 gene does not influence dopamine transporter availability measured by [18F]FE-PE2I PET or [123I]FP-Cit SPECT
- 2022
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Ingår i: Nuclear medicine communications. - : Wolters Kluwer. - 0143-3636 .- 1473-5628. ; 43:3, s. 247-255
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To investigate the potential impact of polymorphism in the 3'-untranslated region (3'UTR) of the SLC6A3 gene (DAT1) on normal variation in dopamine transporter (DAT) imaging with [18F]FE-PE2I PET and [123I]FP-Cit SPECT.METHODS: Thirty-six individuals (mean age 70.4±5.4 years) with normal [18F]FE-PE2I PET and [123I]FP-Cit SPECT were genotyped for variable number of tandem repeats (VNTR) in the 3′UTR of the DAT1 gene. The DAT-availability in the caudate and putamen as measured with [18F]FE-PE2I PET and [123I]FP-Cit SPECT, as well as in the substantia nigra with [18F]FE-PE2I PET were compared between the participants carrying one or two 9-repeat alleles (i.e. 9R+10R or 9R+9R; 47%) and the participants without a 9R allele (i.e. 10R+10R or 10R+11R; 53%). Nonparametric tests, linear regression analysis and mixed model analysis were used to assess any statistical difference in measured DAT availability between the two allele groups.RESULTS: The measured DAT-availability in PET- and SPECT-imaging tended to be slightly higher in the 9R-group; however, the difference did not reach statistical significance in either the caudate or the putamen or the substantia nigra. Instead, age did have a significant effect on the DAT level (P < 0.05) notwithstanding the genotype.CONCLUSION: No significant effect of DAT1-genotype was detectable in imaging with [18F]FE-PE2I PET or [123I]FP-Cit, instead, age accounted for the normal variation in DAT-PET and DAT-SPECT.
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| 2. |
- Kellgren, Therese, 1983-
(författare)
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Hidden patterns that matter : statistical methods for analysis of DNA and RNA data
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Understanding how the genetic variations can affect characteristics and function of organisms can help researchers and medical doctors to detect genetic alterations that cause disease and reveal genes that causes antibiotic resistance. The opportunities and progress associated with such data come however with challenges related to statistical analysis. It is only by using properly designed and employed tools, that we can extract the information about hidden patterns. In this thesis we present three types of such analysis. First, the genetic variant in the gene COL17A1 that causes corneal dystrophy with recurrent erosions is reveled. By studying Next-generation sequencing data, the order of the nucleotides in the DNAsequence was be obtained, which enabled us to detect interesting variants in the genome. Further, we present results of an experimental design study with the aim to make the best selection from a family that is affected by an inherited disease. In second part of the work, we analyzed a novel antibiotic resistance Staphylococcus epidermidis clone that is only found in northern Europe. By investigating its genetic data, we revealed similarities to a world known antibiotic resistance clone. As a result, the antibiotic resistance profile is established from the DNA sequences. Finally, we also focus on the challenges related to the abundance of genetic data from different sources. The increasing number of public gene expression datasets gives us opportunity to increase our understanding by using information from multiple sources simultaneously. Naturally, this requires merging independent datasets together. However, when doing so, the technical and biological variation in the joined data increases. We present a pre-processing method to construct gene co-expression networks from a large diverse gene-expression dataset.
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