| 1. |
- Alexeyenko, Andrey, et al.
(författare)
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Network enrichment analysis : extension of gene-set enrichment analysis to gene networks
- 2012
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 13, s. 226-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. Results: We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. Conclusions: The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.
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| 2. |
- Bachmann, Julie, et al.
(författare)
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Affinity Proteomics Reveals Elevated Muscle Proteins in Plasma of Children with Cerebral Malaria
- 2014
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Ingår i: PLoS Pathogens. - : Public Library of Science (PLoS). - 1553-7366 .- 1553-7374. ; 10:4, s. e1004038-
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Tidskriftsartikel (refereegranskat)abstract
- Systemic inflammation and sequestration of parasitized erythrocytes are central processes in the pathophysiology of severe Plasmodium falciparum childhood malaria. However, it is still not understood why some children are more at risks to develop malaria complications than others. To identify human proteins in plasma related to childhood malaria syndromes, multiplex antibody suspension bead arrays were employed. Out of the 1,015 proteins analyzed in plasma from more than 700 children, 41 differed between malaria infected children and community controls, whereas 13 discriminated uncomplicated malaria from severe malaria syndromes. Markers of oxidative stress were found related to severe malaria anemia while markers of endothelial activation, platelet adhesion and muscular damage were identified in relation to children with cerebral malaria. These findings suggest the presence of generalized vascular inflammation, vascular wall modulations, activation of endothelium and unbalanced glucose metabolism in severe malaria. The increased levels of specific muscle proteins in plasma implicate potential muscle damage and microvasculature lesions during the course of cerebral malaria.
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| 3. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Tidskriftsartikel (refereegranskat)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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| 4. |
- Cui, Can, et al.
(författare)
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Associations between autoimmune diseases and amyotrophic lateral sclerosis : a register-based study
- 2021
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Ingår i: Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration. - : Informa Healthcare. - 2167-8421 .- 2167-9223. ; 22:3-4, s. 211-219
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To assess the associations of 43 autoimmune diseases with the subsequent risk of ALS and further evaluate the contribution of familial confounding to these associations.Methods: We conducted a nationwide register-based nested case-control study including 3561 ALS patients diagnosed during 1990-2013 in Sweden and 35,610 controls that were randomly selected from the general population and individually matched to the cases on age, sex, and county of birth. To evaluate the contribution of familial factors on the studied association, we additionally studied the first-degree relatives (siblings and children) of ALS patients and their controls.Results: Patients with ALS had a 47% higher risk of being previously diagnosed with autoimmune disease (OR 1.47, 95% confidence interval [CI] 1.31-1.64), compared with controls. A positive association was noted for several autoimmune diseases, including myasthenia gravis, polymyositis or dermatomyositis, Guillain-Barre syndrome, type 1 diabetes diagnosed younger than 30 years, multiple sclerosis, and hypothyreosis. The increased risk of any autoimmune disease was greatest during the year before ALS diagnosis, likely due to misdiagnosis. A statistically significantly increased risk was also noted during 2-5 years, but not earlier, before ALS diagnosis. First-degree relatives of ALS patients had however no increased risk of autoimmune diseases compared with first-degree relatives of controls.Conclusions: Although it is difficult to completely remove the potential effects of misdiagnosis, there is likely a positive association between autoimmune disease (such as type 1 diabetes and multiple sclerosis) and ALS, which is not fully explained by shared familial confounding factors.
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| 5. |
- Demissie, Meaza, et al.
(författare)
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Unequal group variances in microarray data analyses
- 2008
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 24:9, s. 1168-1174
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: In searching for differentially expressed (DE) genes in microarray data, we often observe a fraction of the genes to have unequal variability between groups. This is not an issue in large samples, where a valid test exists that uses individual variances separately. The problem arises in the small-sample setting, where the approximately valid Welch test lacks sensitivity, while the more sensitive moderated t-test assumes equal variance. Methods: We introduce a moderated Welch test (MWT) that allows unequal variance between groups. It is based on (i) weighting of pooled and unpooled standard errors and (ii) improved estimation of the gene-level variance that exploits the information from across the genes. Results: When a non-trivial proportion of genes has unequal variability, false discovery rate (FDR) estimates based on the standard t and moderated t-tests are often too optimistic, while the standard Welch test has low sensitivity. The MWT is shown to (i) perform better than the standard t, the standard Welch and the moderated t-tests when the variances are unequal between groups and (ii) perform similarly to the moderated t, and better than the standard t and Welch tests when the group variances are equal. These results mean that MWT is more reliable than other existing tests over wider range of data conditions. Availability: R package to perform MWT is available at http://www.meb.ki.se/similar to yudpaw Contact: yudi.pawitan@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.
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| 6. |
- Fahlén, Jessica, 1973-
(författare)
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Essays on spatial point processes and bioinformatics
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis consists of two separate parts. The first part consists of one paper and considers problems concerning spatial point processes and the second part includes three papers in the field of bioinformatics. The first part of the thesis is based on a forestry problem of estimating the number of trees in a region by using the information in an aerial photo, showing the area covered by the trees. The positions of the trees are assumed to follow either a binomial point process or a hard-core Strauss process. Furthermore, discs of equal size are used to represent the tree-crowns. We provide formulas for the expectation and the variance of the relative vacancy for both processes. The formulas are approximate for the hard-core Strauss process. Simulations indicate that the approximations are accurate. The second part of this thesis focuses on pre-processing of microarray data. The microarray technology can be used to measure the expression of thousands of genes simultaneously in a single experiment. The technique is used to identify genes that are differentially expressed between two populations, e.g. diseased versus healthy individuals. This information can be used in several different ways, for example as diagnostic tools and in drug discovery. The microarray technique involves a number of complex experimental steps, where each step introduces variability in the data. Pre-processing aims to reduce this variation and is a crucial part of the data analysis. Paper II gives a review over several pre-processing methods. Spike-in data are used to describe how the different methods affect the sensitivity and bias of the experiment. An important step in pre-processing is dye-normalization. This normalization aims to remove the systematic differences due to the use of different dyes for coloring the samples. In Paper III a novel dye-normalization, the MC-normalization, is proposed. The idea behind this normalization is to let the channels’ individual intensities determine the correction, rather than the average intensity which is the case for the commonly used MA-normalization. Spike-in data showed that the MC-normalization reduced the bias for the differentially expressed genes compared to the MA-normalization. The standard method for preserving patient samples for diagnostic purposes is fixation in formalin followed by embedding in paraffin (FFPE). In Paper IV we used tongue-cancer microRNA-microarray data to study the effect of FFPE-storage. We suggest that the microRNAs are not equally affected by the storage time and propose a novel procedure to remove this bias. The procedure improves the ability of the analysis to detect differentially expressed microRNAs.
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| 7. |
- Ganna, Andrea, et al.
(författare)
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Large-scale non-targeted metabolomic profiling in three human population-based studies
- 2016
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Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Non-targeted metabolomic profiling is used to simultaneously assess a large part of the metabolome in a biological sample. Here, we describe both the analytical and computational methods used to analyze a large UPLC–Q-TOF MS-based metabolomic profiling effort using plasma and serum samples from participants in three Swedish population-based studies of middle-aged and older human subjects: TwinGene, ULSAM and PIVUS. At present, more than 200 metabolites have been manually annotated in more than 3600 participants using an in-house library of standards and publically available spectral databases. Data available at the metabolights repository include individual raw unprocessed data, processed data, basic demographic variables and spectra of annotated metabolites. Additional phenotypical and genetic data is available upon request to cohort steering committees. These studies represent a unique resource to explore and evaluate how metabolic variability across individuals affects human diseases.
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| 8. |
- Ganna, Andrea, et al.
(författare)
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Rediscovery rate estimation for assessing the validation of significant findings in high-throughput studies
- 2015
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Ingår i: Briefings in Bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; 16:4, s. 563-575
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Tidskriftsartikel (refereegranskat)abstract
- It is common and advised practice in biomedical research to validate experimental or observational findings in a population different from the one where the findings were initially assessed. This practice increases the generalizability of the results and decreases the likelihood of reporting false-positive findings. Validation becomes critical when dealing with high-throughput experiments, where the large number of tests increases the chance to observe false-positive results. In this article, we review common approaches to determine statistical thresholds for validation and describe the factors influencing the proportion of significant findings from a 'training' sample that are replicated in a 'validation' sample. We refer to this proportion as rediscovery rate (RDR). In high-throughput studies, the RDR is a function of false-positive rate and power in both the training and validation samples. We illustrate the application of the RDR using simulated data and real data examples from metabolomics experiments. We further describe an online tool to calculate the RDR using t-statistics. We foresee two main applications. First, if the validation study has not yet been collected, the RDR can be used to decide the optimal combination between the proportion of findings taken to validation and the size of the validation study. Secondly, if a validation study has already been done, the RDR estimated using the training data can be compared with the observed RDR from the validation data; hence, the success of the validation study can be assessed.
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| 9. |
- Hall, Per, et al.
(författare)
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Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis : a cohort study
- 2006
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Ingår i: BMC Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 4, s. 16-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Postmenopausal hormone-replacement therapy (HRT) increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood. Methods: We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women. Results: HRT use in patients with estrogen receptor ( ER) protein positive tumors (n = 72) was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen. Conclusion: Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.
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| 10. |
- Hong, Mun-Gwan, et al.
(författare)
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A genome-wide assessment of variability in human serum metabolism
- 2013
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 34:3, s. 515-524
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Tidskriftsartikel (refereegranskat)abstract
- The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10(-13) -10(-91)). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.
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