The Faculty of Medicine

Background Involvement of low density lipoprotein (LDL) immune complexes (ICs) in atherogenesis has been proposed. Human FccRIIa receptor (CD32) plays a crucial role in the phagocytosis of IgG 2 ICs and a functional point mutation 131His ⁄ Arg diminishes IgG 2 binding to the receptor.

Background Involvement of low density lipoprotein (LDL) immune complexes (ICs) in atherogenesis has been proposed. Human FccRIIa receptor (CD32) plays a crucial role in the phagocytosis of IgG 2 ICs and a functional point mutation 131His ⁄ Arg diminishes IgG 2 binding to the receptor.

Background Involvement of low density lipoprotein (LDL) immune complexes (ICs) in atherogenesis has been proposed. Human FccRIIa receptor (CD32) plays a crucial role in the phagocytosis of IgG 2 ICs and a functional point mutation 131His ⁄ Arg diminishes IgG 2 binding to the receptor.

High plasma total homocysteine (tHcy), low dietary intake of folate and other B vitamins, and genetic polymorphisms related to metabolism of homocysteine may interactively contribute to the risk of cardiovascular disease. We investigated whether known mutations in genes regulating homocysteine metabolism affect the responsiveness of serum folate and plasma tHcy to high intake of natural folate from food. Healthy females (n ϭ 37) aged 22-57 y volunteered to participate in a crossover dietary intervention with two 5-wk diet periods (low and high folate diets). Concentrations of serum and RBC folate, serum vitamin B-12 and plasma tHcy were measured at baseline and at the end of each diet period. The prevalences of C677T transition of methylenetetrahydrofolate reductase (MTHFR) gene, 844ins68 of cystathionine ␤-synthase (CBS) gene and A2756G mutation of methionine synthase (MS) gene were determined. Compared with the low folate diet, the high folate diet increased the serum folate concentration by 85% (P Ͻ 0.001), 77% (P Ͻ 0.001) and 55% (P Ͻ 0.05) in the subjects with the genotypes C/C (n ϭ 19), C/T (n ϭ 13) and T/T (n ϭ 5), respectively, of the MTHFR gene. Also, the plasma tHcy of the subjects with the genotypes C/C, C/T and T/T was decreased by 11% (P Ͻ 0.001), 15% (P Ͻ 0.01) and 18% (P Ͻ 0.05), respectively, during the high folate diet period. The subjects carrying the G2756 allele of the MS gene (n ϭ 15) had a more extensive reduction (P Ͻ 0.05) of plasma tHcy during the high folate diet period than the subjects with the genotype A/A (n ϭ 22). The 844ins68 of CBS gene did not affect plasma tHcy concentrations or diet responsiveness. In conclusion, diet responsiveness of plasma homocysteine may be genetically regulated.

Context: Plasma oxidized low-density lipoprotein (OxLDL) is known to be associated with obesity, metabolic syndrome, and diabetes. Objective: The objective of the study was to investigate the association between plasma IgA, IgM, and IgG titers to OxLDL, phosphocholine (PC), and streptococcal cell wall polysaccharide (CWPS) and markers of glucose metabolism, type 2 diabetes, and liver adiposity. Setting and Participants: A population-based cohort of middle-aged Finns (n ϭ 1039) participated in the study. Design: Plasma IgM, IgG, and IgA to copper oxidized LDL (CuOx-LDL) and malondialdehyde-modified low-density lipoprotein (MDA-LDL), PC, and CWPS were determined with chemiluminescent ELISA and liver adiposity with ultrasonography. Results: IgA autoantibody titers to OxLDL and PC, but not CWPS, were positively associated with fasting blood glucose and plasma insulin levels and inversely with insulin sensitivity index. IgA to OxLDL was significantly higher (P ϭ 0.013 for CuOx-LDL and P ϭ 0.016 for MDA-LDL) and IgG to OxLDL significantly lower (P ϭ 0.036 for CuOx-LDL and P ϭ 0.001 for MDA-LDL) among the subjects with type 2 diabetes compared with subjects with normal or impaired glucose metabolism when adjusted for age, sex, body mass index, smoking, and alcohol consumption. Logistic regression analysis showed that high plasma IgA to OxLDL and low IgG to MDA-LDL were independent risk factors for type 2 diabetes. Plasma IgA titers to OxLDL demonstrated a significant association with liver adiposity (P ϭ 0.012) and ␥-glutamyltransferase levels (P ϭ 0.002). Conclusions: Plasma IgA titers to OxLDL were positively and IgG titers negatively associated with markers of glucose metabolism. High plasma IgA and low IgG to OxLDL were independent risk factors for type 2 diabetes.

Antibodies to phosphocholine and oxidized LDL (oxLDL) are proposed to modify progression of atherosclerosis. We investigated the prognostic value of antibodies to phosphocholine (PCho), Streptococcus pneumoniae cell wall polysaccharide (CWPS) and oxLDL in defining long-term CVD survival. CVD incidence was followed for 18 years and analyzed with baseline plasma IgM, IgG and IgA antibody levels to PCho, CWPS and oxLDL in 1044 subjects of Oulu Project Elucidating Risk of Atherosclerosis study (OPERA). During the follow-up period, 195 subjects (18.7%) had a CVD event. Cox model with ACC/AHA CVD adjustments (ASCVD) showed that IgA levels to PCho and IgA to CWPS were statistically significant factors predicting CVD risk. IgM and IgG antibodies to PCho, CWPS and oxLDL had no effect on CVD risk after adjusting for other risk factors. Net reclassification improvement (categories: 17-year risk <15%, 15-30%, >30%), was 0.06 (-0.001-0.12, p < 0.054), and IDI was 0.0124 (0.0036-0.0211, ...

This study's aim was to assess the role of interleukin (IL)-5 in modulating the levels of antibodies binding to oxidized low-density lipoprotein (OxLDL) in human atherosclerosis. Background Various pro-and anti-inflammatory cytokines have been implicated in atherogenesis, and recent findings in mice indicate that the cytokine IL-5 plays a protective role in atherosclerosis in part via the induction of antibodies binding to OxLDL. Methods Plasma IL-5 levels and antibody titers to 2 most commonly used models of OxLDL (copper OxLDL and malondialdehyde-modified LDL) were measured in 1,011 Finnish middle-aged subjects with chemiluminescent enzyme-linked immunosorbent assay. Intima-media thickness (IMT) was assessed ultrasonographically from the internal carotid artery, the bifurcation, and the common carotid artery. Results There was a significant positive association between plasma IL-5 levels and antibody titers to copper OxLDL (p ϭ 0.010 and p ϭ 0.044, immunoglobin [Ig] M and G, respectively) and IgM to malondialdehyde-modified LDL (p Ͻ 0.001) in the association analysis performed between different IL-5 quartiles. Furthermore, plasma IL-5 levels were found to be inversely associated with bifurcational IMT, and even after adjustments for traditional risk factors of atherosclerosis (age, gender, smoking, systolic blood pressure, LDL, and body mass index), IL-5 remained an independent determinant of the mean bifurcational IMT (p ϭ 0.010). Conclusions Our data demonstrate that plasma IL-5 levels are related to the plasma levels of antibodies binding to OxLDL and to decreased subclinical atherosclerosis in humans. These results are in line with earlier findings in murine atherosclerosis and indicate for the first time that IL-5 may play a role in human atherosclerosis.

Recently discovered glymphatic brain clearance mechanisms utilizing physiological pulsations have been shown to fail at removing waste materials such as amyloid and tau plaques in neurodegenerative diseases. Since cardiovascular pulsations are a main driving force of the clearance, this research investigates if commonly available blood oxygen level-dependent (BOLD) signals at 1.5 and 3 T could detect abnormal physiological pulsations in neurodegenerative diseases. Coefficient of variation in BOLD signal (CVBOLD) was used to estimate contribution of physiological signals in Alzheimer’s disease (AD) and behavioural variant frontotemporal dementia (bvFTD). 17 AD patients and 18 bvFTD patients were compared to 24 control subjects imaged with a 1.5 T setup from a local institute. AD results were further verified with 3 T data from the Alzheimer’s disease neuroimaging initiative (ADNI) repository with 30 AD patients and 40 matched controls. Effect of motion and gray matter atrophy was eva...

Oura Health Ltd.'s provided the surveillance smart rings for the study, but did not participate in the analysis. The manuscript in question is published as a preprint in bioRxiv, but we guarantee that it does not infringe any subsequent copyright or license agreement. 3 3 We would like to thank all study subjects for their participation in the study. We also thank Tuomas Konttajärvi for assistance in measurements and preprocessing of EEG data, Jani Häkli, Annastiina Kivipää, Tarja Holtinkoski, Aleksi Rasila, Taneli Hautaniemi, Miia Lampinen and others who assisted in measurements or otherwise contributed. We are grateful for devices and data provided by Oura. We wish to acknowledge Jussi Kantola for data management and reconstruction of MREG data, the CSC-IT Center for Science Ltd.

Objective
Epilepsy causes measurable irregularity over a range of brain signal frequencies, as well as autonomic nervous system functions that modulate heart and respiratory rate variability. Imaging dynamic neuronal signals utilizing simultaneously acquired ultra-fast 10 Hz magnetic resonance encephalography (MREG), direct current electroencephalography (DC-EEG), and near-infrared spectroscopy (NIRS) can provide a more comprehensive picture of human brain function. Spectral entropy (SE) is a nonlinear method to summarize signal power irregularity over measured frequencies. SE was used as a joint measure to study whether spectral signal irregularity over a range of brain signal frequencies based on synchronous multimodal brain signals could provide new insights in the neural underpinnings of epileptiform activity.

Methods
Ten patients with focal drug-resistant epilepsy (DRE) and ten healthy controls (HC) were scanned with 10 Hz MREG sequence in combination with EEG, NIRS (measuring oxygenated, deoxygenated, and total hemoglobin: HbO, Hb, and HbT, respectively), and cardiorespiratory signals. After pre-processing, voxelwise SEMREG was estimated from MREG data. Different neurophysiological and physiological subfrequency band signals were further estimated from MREG, DC-EEG, and NIRS: fullband (0–5 Hz, FB), near FB (0.08–5 Hz, NFB), brain pulsations in very-low (0.009–0.08 Hz, VLFP), respiratory (0.12–0.4 Hz, RFP), and cardiac (0.7–1.6 Hz, CFP) frequency bands. Global dynamic fluctuations in MREG and NIRS were analyzed in windows of 2 min with 50% overlap.

Results
Right thalamus, cingulate gyrus, inferior frontal gyrus, and frontal pole showed significantly higher SEMREG in DRE patients compared to HC. In DRE patients, SE of cortical Hb was significantly reduced in FB (p = .045), NFB (p = .017), and CFP (p = .038), while both HbO and HbT were significantly reduced in RFP (p = .038, p = .045, respectively). Dynamic SE of HbT was reduced in DRE patients in RFP during minutes 2 to 6. Fitting to the frontal MREG and NIRS results, DRE patients showed a significant increase in SEEEG in FB in fronto-central and parieto-occipital regions, in VLFP in parieto-central region, accompanied with a significant decrease in RFP in frontal pole and parietal and occipital (O2, Oz) regions.

Conclusion
This is the first study to show altered spectral entropy from synchronous MREG, EEG, and NIRS in DRE patients. Higher SEMREG in DRE patients in anterior cingulate gyrus together with SEEEG and SENIRS results in 0.12–0.4 Hz can be linked to altered parasympathetic function and respiratory pulsations in the brain. Higher SEMREG in thalamus in DRE patients is connected to disturbances in anatomical and functional connections in epilepsy. Findings suggest that spectral irregularity of both electrophysiological and hemodynamic signals are altered in specific way depending on the physiological frequency range.

Introduction
Functional magnetic resonance imaging (fMRI) combined with simultaneous electroencephalography (EEG-fMRI) has become a major tool in mapping epilepsy sources. In the absence of detectable epileptiform activity, the resting state fMRI may still detect changes in the blood oxygen level-dependent signal, suggesting intrinsic alterations in the underlying brain physiology.

Methods
In this study, we used coefficient of variation (CV) of critically sampled 10 Hz ultra-fast fMRI (magnetoencephalography, MREG) signal to compare physiological variance between healthy controls (n = 10) and patients (n = 10) with drug-resistant epilepsy (DRE).

Results
We showed highly significant voxel-level (p < 0.01, TFCE-corrected) increase in the physiological variance in DRE patients. At individual level, the elevations range over three standard deviations (σ) above the control mean (μ) CVMREG values solely in DRE patients, enabling patient-specific mapping of elevated physiological variance. The most apparent differences in group-level analysis are found on white matter, brainstem, and cerebellum. Respiratory (0.12–0.4 Hz) and very-low-frequency (VLF = 0.009–0.1 Hz) signal variances were most affected.

Conclusions
The CVMREG increase was not explained by head motion or physiological cardiorespiratory activity, that is, it seems to be linked to intrinsic physiological pulsations. We suggest that intrinsic brain pulsations play a role in DRE and that critically sampled fMRI may provide a powerful tool for their identification.

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning.

Recent studies pinpoint visually cued networks of avalanches with MEG/EEG data. Co-activation pattern (CAP) analysis can be used to detect single brain volume activity profiles and hemodynamic fingerprints of neuronal avalanches as sudden high signal activity peaks in classical fMRI data. In this study, we aimed to detect dynamic patterns of brain activity spreads with the use of ultrafast MR encephalography (MREG). MREG achieves 10 Hz whole brain sampling, allowing the estimation of spatial spread of an avalanche, even with the inherent hemodynamic delay of the BOLD signal. We developed a novel computational method to separate avalanche type fast activity spreads from motion artifacts, vasomotor fluctuations, and cardio-respiratory noise in human brain default mode network (DMN). Reproducible and classical DMN sources were identified using spatial ICA prior to advanced noise removal in order to assure that ICA converges to reproducible networks. Brain activity peaks were identified from parts of the DMN, and normalized MREG data around each peak were extracted individually to show dynamic avalanche type spreads as video clips within the DMN. Individual activity spread video clips of specific parts of the DMN were then averaged over the group of subjects. The experiments show that the high BOLD values around the peaks are mostly spreading along the spatial pattern of the particular DMN segment detected with ICA. With also the spread size and lifetime resembling the expected power law distributions, this indicates that the detected peaks are parts of activity avalanches, starting from (or crossing) the DMN. Furthermore, the split, one-sided sub-networks of the DMN show different spread directions within the same DMN framework. The results open possibilities to follow up brain activity avalanches in the hope to understand more about the system wide properties of diseases related to DMN dysfunction.

Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n ¼ 102) and patients with epilepsy (n ¼ 33) and furthermore to drug-naive seizure patients (n ¼ 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11-0.51 Hz) were significantly (P < 0.05) increased in patients with epilepsy, with an increase in both signal variance and power. At the individual level, over 80% of medicated and drug-naive seizure patients exhibited areas of abnormal brain signal power that correlated well with the known clinical diagnosis, while none of the controls showed signs of abnormality with the same threshold. The differences were most apparent in the basal brain structures, respiratory centres of brain stem, midbrain and temporal lobes. Notably, full-band, very low frequency (0.01-0.1 Hz) and cardiovascular (0.8-1.76 Hz) brain pulses showed no differences between groups. This study extends and confirms our previous results of abnormal fast functional MRI signal variance in epilepsy patients. Only respiratory-related brain pulsations were clearly increased with no changes in either physiological cardiorespiratory rates or head motion between the subjects. The regional alterations in brain pulsations suggest that mechanisms driving the cerebrospinal fluid homeostasis may be altered in epilepsy. Magnetic resonance encephalography has both increased sensitivity and high specificity for detecting the increased brain pulsations, particularly in times when other tools for locating epileptogenic areas remain inconclusive.