Biology subjects

Toppari, J.

Publications and source records attributed to Toppari, J..

4 recordsLinked to original sources

bioRxiv2021

Permutation-based significance analysis reduces the type 1 error rate in bisulfite sequencing data analysis of human umbilical cord blood samples

BackgroundDNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2 % of human CpG sites. To detect such associations outside these regions, we chose the bisulfite sequencing approach. MethodsWe collected and curated all available clinical data on 200 newborn infants; whose umbilical cord blood samples were analyzed with the reduced representation bisulfite sequencing (RRBS) method. A generalized linear mixed effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis. ResultsWe discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models. ConclusionsThe inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. With standard significance thresholds, type 1 error rates were high with both these implementations, across alternative parameter settings and analysis strategies. We conclude that comb-p and RADMeth are convenient methods for the detection of differentially methylated regions, but the statistical significance should either be determined empirically or before the spatial adjustment. Our RRBS data analysis workflow is available in https://github.com/EssiLaajala/RRBS_workflow.

bioinformatics↗

bioRxiv2018

Circulating Metabolites in Progression to Islet Autoimmunity and Type 1 Diabetes

Previous studies suggest that metabolic dysregulation precedes the onset of type 1 diabetes (T1D). However, these metabolic disturbances and their specific role in disease initiation remain poorly understood. Here we analysed polar metabolites from 415 longitudinal plasma samples in a prospective cohort of children in three study groups: those who progressed to T1D (PT1D), who seroconverted to one islet autoantibody (Ab) but not to T1D (P1Ab), and Ab-negative controls (CTR). In early infancy, PT1D associated with downregulated amino acids, sugar derivatives and fatty acids, including catabolites of microbial origin, as compared to CTR. Methionine remained persistently upregulated in PT1D as compared to CTR and P1Ab. Appearance of islet autoantibodies associated with decreased glutamic and aspartic acids. Our findings suggest that children who progress to T1D have a unique metabolic profile, which is however altered with the onset of islet autoantibodies. Our findings may assist in early prediction of T1D.

biochemistry↗

bioRxiv2018

Persistent alterations in plasma lipid profiles prior to introduction of gluten in the diet associate with progression to celiac disease

Background and AimsCeliac disease (CD) is a chronic enteropathy characterized by an autoimmune reaction in the small intestine in genetically-susceptible individuals. Gluten is the required environmental trigger of clinical CD, but the underlying causes of the autoimmune reaction remain unknown. Herein, we apply lipidomics to elucidate the early events preceding clinical CD in a prospective study of children observed from birth until diagnosis of CD and subsequent introduction of a gluten-free diet.\n\nMethodsMass spectrometry-based lipidomics profiling was applied to a longitudinal series of 233 plasma samples from the Type 1 Diabetes Prediction and Prevention (DIPP) study, spanning the period between birth and the introduction of a gluten-free diet following CD diagnosis (n=23 CD progressors, n=23 controls matched for gender, HLA risk, period of birth, and age).\n\nResults23 children progressed to CD at a mean age of 4.8 years. They showed increased amounts of triacylglycerols (TGs) of low carbon number and double bond count and a decreased level of phosphatidylcholines by 3 months of age as compared to controls. These differences were exacerbated with age but were not observed at birth. No significant differences were observed in essential (dietary) TGs such as those containing polyunsaturated fatty acids.\n\nConclusionOur findings suggest that abnormal lipid metabolism associated with development of clinical CD may occur prior to the introduction of gluten to the diet. Moreover, our data suggest that the specific TGs found elevated in CD progressors may be due to a host response to compromised intake of essential lipids in the small intestine, requiring de novo lipogenesis.

systems biology↗

bioRxiv2018

Dynamics of Plasma Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes: Type 1 Diabetes Prediction and Prevention Study (DIPP)

Type 1 diabetes (T1D) is one of the most prevalent autoimmune diseases among children in Western countries. Earlier metabolomics studies suggest that T1D is preceded by dysregulation of lipid metabolism. Here we used a lipidomics approach to analyze molecular lipids in a prospective series of 428 plasma samples from 40 children who progressed to T1D (PT1D), 40 children who developed at least a single islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and 40 matched controls (CTR). Sphingomyelins were found to be persistently downregulated in PT1D when compared to the P1Ab and CTR groups. Triacylglycerols and phosphatidylcholines were mainly downregulated in PT1D as compared to P1Ab at the age of 3 months. Our study suggests that children who progressed to islet autoimmunity or overt T1D are characterized by distinct lipidomic signatures, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.

biochemistry↗