Browsing by Subject "pathway analysis"

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  • Lahtinen, Alexandra (Helsingin yliopisto, 2018)
    The need to sleep is physiologically regulated and lack of sleep results in impaired daily performance and feeling of tiredness. If sleep disturbance persists for a long time, the risk of many somatic and mental disorders increases. The study of the key molecular processes triggered by insufficient sleep could foster the assessment and enhance the methods of prevention and cure of these long-term health risks. Both insufficient and mistimed sleep have been shown to strongly affect cell transcriptome in animal models and in the studies of selected human cohorts. However, our understanding of the epigenetic modifications, particularly DNA methylation, triggered by the sleep loss remains limited. Here, we performed an epigenome-wide association study in the whole blood samples of men from the general population reporting lack of sleep and of men diagnosed with a shift work disorder. We combined the results from the two independent samples and identified a set of differentially methylated positions (DMPs) common for both cohorts. We further analyzed this set of DMPs by various computational tools, in order to explore altered biological pathways in individuals suffering from lack of sleep. As a result, we discovered a neurological pathway enriched for genes with DMPs, suggesting that curtailed sleep may result in the changes in processes related to synaptic plasticity. We also observed the loss of methylation in the majority of DMPs, in agreement with an earlier observation on the night shift workers. In order to investigate the effect of DNA methylation on gene expression, we performed correlational analyses of M values of the DMPs and the levels of corresponding gene expression. Since methylation levels might fluctuate according to the time of the blood sampling, we also studied the correlation of the DMPs with the time of the sampling. The analysis of genomic locations of the DMPs revealed enrichment of genomic loci involved in syndromes with symptoms of disturbances in visual processing and regulation of circadian rhythm. Our findings suggest that there is a distinctive pattern of genes showing diversity of epigenetic modifications in relation to insufficient sleep in men. The molecular mechanisms behind the observed associations require further investigation, both in general population based samples comprising both genders or occupational cohorts, and in experimental data.
  • MacKeith, Ada (Helsingin yliopisto, 2019)
    Sleep difficulties have been on the rise for the past decade. Insomnia and sleep difficulties have associations with an increased risk of overall mortality, as well as with a diverse array of complex diseases, such as coronary heart disease, major depressive disorder, fibromyalgia and Alzheimer’s disease. Epigenomics provides information on how environmental factors influence the genome via epigenetic mechanisms, such as DNA methylation. Thus far, epigenome-wide association studies looking at the effects of sleep disturbances on the methylome have provided evidence of distinctive methylation patterns in insufficient sleep, involving biological processes related to neuroplasticity and neurodegeneration. However, more knowledge is needed to determine how the severity of sleeping difficulties influence the methylome. This thesis investigates the effects of increasing sleep difficulties on DNA methylation with an epigenome-wide association study. The study sample is derived from the Health 2000 general population survey. Subjects were divided into three different groups by their self-reported level of sleeping difficulty, and methylation measurements performed from whole blood samples utilizing the Illumina Infinium MethylationEPIC kit, encompassing >850,000 CpG sites. To identify differentially methylated sites, a multivariable regression model was used with age, gender, smoking, alcohol use, cell type distribution and plate and array data as covariates. None of the differentially methylated CpG sites identified remained significant after multiple testing correction. To gain more information regarding which biological processes the methylated sites may be part of, those CpG sites with an uncorrected p-value of <0.0005 were subjected to pathway analysis. Notable significant pathways included oxytocin- and serotonin receptor-mediated signalling pathways and Alzheimer’s disease-amyloid secretase pathway. Altogether, six pathways remained significant after multiple testing correction, with a total of 12 different genes appearing in them. Furthermore, a post-hoc regression analysis was conducted between these 12 genes and their corresponding CpG sites, and health-related quality of life questionnaire responses. Significant results included associations between sleep, and discomfort and symptoms (including pain). As an additional analysis, a database search was conducted to learn more about the genes’ functionality at the level of phenotype. Results included some variant trait associations to sleep, Alzheimer’s disease and cognitive performance. The associations to Alzheimer’s disease and cognitive performance warrant further research with a similar additive model, perhaps with a larger sample.
  • Yohannes, Dawit A.; de Kauwe, Andrea; Kaukinen, Katri; Kurppa, Kalle; Mäki, Markku; Anderson, Robert P.; Linnarsson, Sten; Greco, Dario; Saavalainen, Päivi (2020)
    The pathological mechanisms that lead to the onset and reactivation of celiac disease (CD) remain largely unknown. While gluten free diet (GFD) improves the intestinal damage and associated clinical symptoms in majority of cases, it falls short of providing full recovery. Additionally, late or misdiagnosis is also common as CD presents with a wide range of symptoms. Clear understanding of CD pathogenesis is thus critical to address both diagnostic and treatment concerns. We aimed to study the molecular impact of short gluten exposure in GFD treated CD patients, as well as identify biological pathways that remain altered constitutively in CD regardless of treatment. Using RNAseq profiling of PBMC samples collected from treated CD patients and gluten challenged patient and healthy controls, we explored the peripheral transcriptome in CD patients following a short gluten exposure. Short gluten exposure of just three days was enough to alter the genome-wide PBMC transcriptome of patients. Pathway analysis revealed gluten-induced upregulation of mainly immune response related pathways, both innate and adaptive, in CD patients. We evaluated the perturbation of biological pathways in sample-specific manner. Compared to gluten exposed healthy controls, pathways related to tight junction, olfactory transduction, metabolism of unsaturated fatty acids (such as arachidonic acid), metabolism of amino acids (such as cysteine and glutamate), and microbial infection were constitutively altered in CD patients regardless of treatment, while GFD treatment appears to mostly normalize immune response pathways to "healthy" state. Upstream regulator prediction analysis using differentially expressed genes identified constitutively activated regulators relatively proximal to previously reported CD associated loci, particularly SMARCA4 on 19p13.2 and CSF2 on 5q31. We also found constitutively upregulated genes in CD that are in CD associated genetic loci such as MEF2BNB-MEF2B (BORCS8-MEF2B) on 19p13.11 and CSTB on 21q22.3. RNAseq revealed strong effects of short oral gluten challenge on whole PBMC fraction and constitutively altered pathways in CD PBMC suggesting important factors other than gluten in CD pathogenesis.
  • Habermann, Jens K.; Buendgen, Nana K.; Gemoll, Timo; Hautaniemi, Sampsa; Lundgren, Caroline; Wangsa, Danny; Doering, Jana; Bruch, Hans-Peter; Nordstroem, Britta; Roblick, Uwe J.; Jornvall, Hans; Auer, Gert; Ried, Thomas (2011)
  • Int Myasthenia Gravis Genomics Con; Chia, Ruth; Saez-Atienzar, Sara; Murphy, Natalie; Tienari, Pentti J.; Traynor, Bryan J. (2022)
    Myasthenia gravis is a chronic autoimmune disease characterized by autoantibody-mediated interference of signal transmission across the neuromuscular junction. We performed a genome-wide association study (GWAS) involving 1,873 patients diagnosed with acetylcholine receptor antibody-positive myasthenia gravis and 36,370 healthy individuals to identify disease-associated genetic risk loci. Replication of the discovered loci was attempted in an independent cohort from the UK Biobank. We also performed a transcriptome-wide association study (TWAS) using expression data from skeletal muscle, whole blood, and tibial nerve to test the effects of disease-associated polymorphisms on gene expression. We discovered two signals in the genes encoding acetylcholine receptor subunits that are the most common antigenic target of the autoantibodies: a GWAS signal within the cholinergic receptor nicotinic alpha 1 subunit (CHRNA1) gene and a TWAS association with the cholinergic receptor nicotinic beta 1 subunit (CHRNB1) gene in normal skeletal muscle. Two other loci were discovered on 10p14 and 11q21, and the previous association signals at PTPN22, HLA-DQA1/HLA-B, and TNFRSF11A were confirmed. Subgroup analyses demonstrate that early-and late-onset cases have different genetic risk factors. Genetic correlation analysis confirmed a genetic link between myasthenia gravis and other autoimmune diseases, such as hypothyroidism, rheumatoid arthritis, multiple sclerosis, and type 1 diabetes. Finally, we applied Priority Index analysis to identify potentially druggable genes/proteins and pathways. This study provides insight into the genetic architecture underlying myasthenia gravis and demonstrates that genetic factors within the loci encoding acetylcholine receptor subunits contribute to its pathogenesis.
  • Maleta, Kenneth; Fan, Yue-Mei; Luoma, Juho; Ashorn, Ulla; Bendabenda, Jaden; Dewey, Kathryn G.; Hyöty, Heikki; Knip, Mikael; Kortekangas, Emma; Lehto, Kirsi-Maarit; Matchado, Andrew; Nkhoma, Minyanga; Nurminen, Noora; Parkkila, Seppo; Purmonen, Sami; Veijola, Riitta; Oikarinen, Sami; Ashorn, Per (2021)
    Background: Insulin-like growth factor I (IGF-I) is the most important hormonal promoter of linear growth in infants and young children. Objectives: The objectives of this study were to compare plasma IGF-I concentration in a low- compared with a high-income country and characterize biological pathways leading to reduced IGF-I concentration in children in a low-income setting. Methods: We analyzed plasma IGF-I concentration from 716 Malawian and 80 Finnish children at 6-36 mo of age. In the Malawian children, we studied the association between IGF-I concentration and their environmental exposures; nutritional status; systemic and intestinal inflammation; malaria parasitemia and viral, bacterial, and parasitic enteric infections; as well as growth at 18 mo of age. We then conducted a pathway analysis to identify direct and indirect associations between these predictors and IGF-I concentration. Results: The mean IGF-I concentrations were similar in Malawi and Finland among 6-mo-old infants. At age 18 mo. the mean +/- SD concentration was almost double among the Finns compared with the Malawians [24.2 +/- 11.3 compared with 12.5 +/- 7.7 ng/mL., age- and sex-adjusted difference in mean (95% CI): 11.8 (9.9. 13.7) ng/mL; P <0.01]. Among 18-mo-old Malawians, plasma IGF-I concentration was inversely associated with systemic inflammation, malaria parasitemia, and intestinal Shigella. Campylobacter, and enterovirus infection and positively associated with the children's weight-for-length z score (WLZ), female sex, maternal height, mother's education, and dry season. Seasonally, mean plasma IGF-I concentration was highest in June and July and lowest in December and January, coinciding with changes in children's length gain and preceded by similar to 2 mo by the changes in their WLZ. Conclusions: The mean plasma IGF-I concentrations are similar in Malawi and Finland among 6-mo-old infants. Thereafter, mean concentrations rise markedly in Finland but not in Malawi. Systemic inflammation and clinically nonapparent infections are strongly associated with lower plasma IGF-I concentrations in Malawi through direct and indirect pathways.
  • Eising, Else; de Leeuw, Christiaan; Min, Josine L.; Anttila, Verneri; Verheijen, Mark H. G.; Terwindt, Gisela M.; Dichgans, Martin; Freilinger, Tobias; Kubisch, Christian; Ferrari, Michel D.; Smit, August B.; de Vries, Boukje; Palotie, Aarno; van den Maagdenberg, Arn M. J. M.; Posthuma, Danielle; Int Headache Genetics Consortium (2016)
    Background Migraine is a common episodic brain disorder characterized by recurrent attacks of severe unilateral headache and additional neurological symptoms. Two main migraine types can be distinguished based on the presence of aura symptoms that can accompany the headache: migraine with aura and migraine without aura. Multiple genetic and environmental factors confer disease susceptibility. Recent genome-wide association studies (GWAS) indicate that migraine susceptibility genes are involved in various pathways, including neurotransmission, which have already been implicated in genetic studies of monogenic familial hemiplegic migraine, a subtype of migraine with aura. Methods To further explore the genetic background of migraine, we performed a gene set analysis of migraine GWAS data of 4954 clinic-based patients with migraine, as well as 13,390 controls. Curated sets of synaptic genes and sets of genes predominantly expressed in three glial cell types (astrocytes, microglia and oligodendrocytes) were investigated. Discussion Our results show that gene sets containing astrocyte- and oligodendrocyte-related genes are associated with migraine, which is especially true for gene sets involved in protein modification and signal transduction. Observed differences between migraine with aura and migraine without aura indicate that both migraine types, at least in part, seem to have a different genetic background.
  • Liu, Chengyu; Lehtonen, Rainer; Hautaniemi, Sampsa (2018)
    Identification of intracellular pathways that play key roles in cancer progression and drug resistance is a prerequisite for developing targeted cancer treatments. The era of personalized medicine calls for computational methods that can function with one sample or very small set of samples. Developing such methods is challenging because standard statistical approaches pose several limiting assumptions, such as number of samples, that prevent their application when n approaches to one. We have developed a novel pathway analysis method called PerPAS to estimate pathway activity at a single sample level by integrating pathway topology and transcriptomics data. In addition, PerPAS is able to identify altered pathways between cancer and control samples as well as to identify key nodes that contribute to the pathway activity. In our case study using breast cancer data, we show that PerPAS can identify highly altered pathways that are associated with patient survival. PerPAS identified four pathways that were associated with patient survival and were successfully validated in three independent breast cancer cohorts. In comparison to two other pathway analysis methods that function at a single sample level, PerPAS had superior performance in both synthetic and breast cancer expression datasets. PerPAS is a free R package (