Search

Cardiac troponin and N-terminal pro-brain natriuretic peptide (NT-proBNP) are known to associate with incident dementia. The purpose of our study was to examine whether high-sensitivity cardiac troponin I (hs-TnI) and NT-proBNP are associated with incident dementia and Alzheimer's disease (AD) independently of each other. Our study was a part of the national population-based health examination survey, FINRISK 1997, with a total sample of 7114 subjects, including 407 incident dementia cases and 319 AD cases during the follow-up time of 18 years. Using multivariate Cox regression analyses, we calculated the hazard ratios (HR) for hs-TnI and NT-proBNP. Analyses were adjusted for the previously known dementia/AD risk factors, including the apoE genotype. NT-proBNP was independently associated with incident dementia (HR 1.32, 95% CI 1.17-1.49) and AD (HR 1.30, 95% CI 1.13-1.5). Hs-TnI was also associated with incident dementia (HR 1.12, 95% CI 1.02-1.23), but not independent of NT-proBNP (HR 1.10, 95% CI 0.99-1.21). Hs-TnI was not associated with incident AD. The results remained similar in cause-specific Cox regression models and among subjects over 40 years of age. NT-proBNP and hs-TnI improved the reclassification of dementia risk in 10 years follow-up, and hs-TNI also in 18 years of follow-up. Neither hs-TnI nor NT-proBNP was able to outperform each other in risk reclassification of dementia. Both cardiovascular biomarkers, NT-proBNP and hs-TnI, were associated with incident dementia independently of traditional dementia risk factors including the apoE genotype. NT-proBNP was also associated with AD. Both markers offered a better dementia risk reclassification compared with traditional risk factors.

Short sleep duration or insomnia may lead to an increased risk of various psychiatric and cardio-metabolic conditions. Since DNA methylation plays a critical role in the regulation of gene expression, studies of differentially methylated positions (DMPs) might be valuable for understanding the mechanisms underlying insomnia. We performed a cross-sectional genome-wide analysis of DNA methylation in relation to self-reported insufficient sleep in individuals from a community-based sample (79 men, aged 39.3 ± 7.3), and in relation to shift work disorder in an occupational cohort (26 men, aged 44.9 ± 9.0). The analysis of DNA methylation data revealed that genes corresponding to selected DMPs form a distinctive pathway: “Nervous System Development” (FDR P value

BackgroundRapid computational and technological developments made large amounts of omics data available in different biological levels. It is becoming clear that simultaneous data analysis methods are needed for better interpretation and understanding of the underlying systems biology. Different methods have been proposed for this task, among them Partial Least Squares (PLS) related methods. To also deal with orthogonal variation, systematic variation in the data unrelated to one another, we consider the Two-way Orthogonal PLS (O2PLS): an integrative data analysis method which is capable of modeling systematic variation, while providing more parsimonious models aiding interpretation.ResultsA simulation study to assess the performance of O2PLS showed positive results in both low and higher dimensions. More noise (50 % of the data) only affected the systematic part estimates. A data analysis was conducted using data on metabolomics and transcriptomics from a large Finnish cohort (DILGOM). A previous sequential study, using the same data, showed significant correlations between the Lipo-Leukocyte (LL) module and lipoprotein metabolites. The O2PLS results were in agreement with these findings, identifying almost the same set of co-varying variables. Moreover, our integrative approach identified other associative genes and metabolites, while taking into account systematic variation in the data. Including orthogonal components enhanced overall fit, but the orthogonal variation was difficult to interpret.ConclusionsSimulations showed that the O2PLS estimates were close to the true parameters in both low and higher dimensions. In the presence of more noise (50 %), the orthogonal part estimates could not distinguish well between joint and unique variation. The joint estimates were not systematically affected. Simultaneous analysis with O2PLS on metabolome and transcriptome data showed that the LL module, together with VLDL and HDL metabolites, were important for the metabolomic and transcriptomic relation. This is in agreement with an earlier study. In addition more gene expression and metabolites are identified being important for the joint covariation.

Background Techniques enabling targeted re-sequencing of the protein coding sequences of the human genome on next generation sequencing instruments are of great interest. We conducted a systematic comparison of the solution-based exome capture kits provided by Agilent and Roche NimbleGen. A control DNA sample was captured with all four capture methods and prepared for Illumina GAII sequencing. Sequence data from additional samples prepared with the same protocols were also used in the comparison. Results We developed a bioinformatics pipeline for quality control, short read alignment, variant identification and annotation of the sequence data. In our analysis, a larger percentage of the high quality reads from the NimbleGen captures than from the Agilent captures aligned to the capture target regions. High GC content of the target sequence was associated with poor capture success in all exome enrichment methods. Comparison of mean allele balances for heterozygous variants indicated a tendency to have more reference bases than variant bases in the heterozygous variant positions within the target regions in all methods. There was virtually no difference in the genotype concordance compared to genotypes derived from SNP arrays. A minimum of 11× coverage was required to make a heterozygote genotype call with 99% accuracy when compared to common SNPs on genome-wide association arrays. Conclusions Libraries captured with NimbleGen kits aligned more accurately to the target regions. The updated NimbleGen kit most efficiently covered the exome with a minimum coverage of 20×, yet none of the kits captured all the Consensus Coding Sequence annotated exons.