Biology subjects

Kaakinen, M.

Publications and source records attributed to Kaakinen, M..

7 recordsLinked to original sources

bioRxiv2025

Sleep increases propagation speed of physiological brain pulsations

During sleep, there is an increase in the brain cerebrospinal fluid (CSF) solute convection driven by physiological pulsations. Although the main drivers of CSF flow, namely cardiac, respiratory, and vasomotor pulsations, become more powerful during sleep, there is relatively little information regarding their effects on CSF flow velocity across human brain during sleep. Here, we used functional magnetic resonance encephalography (MREG) to measure non-invasively changes in brain water flow during to sleep by tracking the propagating ultrafast signal changes induced by physiological brain pulsations. We first undertook a phantom study confirming that dense optical flow analysis of MREG data accurately detects water flow velocity, and reflects the power of the physiological pulsations. We then applied the method to quantify CSF water flow velocity in brain of healthy volunteers during EEG-verified awake and sleep recordings of ultrafast MREG data. Sleep induced an increase in CSF flow speed, as demonstrated by elevated vasomotor and respiratory pulsation speeds, while the speed of cardiovascular impulse propagation remained unchanged. The speed increases match previous findings of respective pulsation power changes, and correlated with slow delta EEG power. The sleep-induced CSF flow speed increases occurred dynamically over both pulsation cycles, without the large effects on flow directions reported previously in several neurological conditions. In conclusion, sleep increases 3D water flow speed dynamically in human brain regions showing concomitant pulse power increases, supporting a porous media model of hydrodynamics in brain cortex.

neuroscience↗

bioRxiv2023

Blood pressure lowering enhances cerebrospinal fluid efflux primarily via the lymphatic vasculature

BackgroundInside the incompressible cranium, the volume of cerebrospinal fluid (CSF) is directly linked to blood volume: a change in either will induce a compensatory change in the other. Vasodilatory lowering of blood pressure has been shown to result in an increase of intracranial pressure, which, in normal circumstances should return to equilibrium by increased fluid efflux. In this study, we investigated the effect of blood pressure lowering (BPL) on fluorescent CSF tracer absorption into the systemic blood circulation. MethodsBPL was performed by an i.v. administration of nitric oxide donor sodium nitroprusside (5 {micro}g kg-1 min-1) or the Ca2+-channel blocker nicardipine hydrochloride (0.5 {micro}g kg-1 min-1) for 10 and 15 to 40 mins, respectively. The effect of BPL on CSF clearance was investigated by measuring the efflux of fluorescent tracers (40 kDa FITC-dextran, 45 kDa Texas Red-conjugated ovalbumin) into blood and deep cervical lymph nodes. ResultsNicardipine and sodium nitroprusside reduced blood pressure by 32.0 {+/-} 19.6% and 22.0 {+/-} 2.5%, while temporarily elevating in intracranial pressure by 14.0 {+/-} 6.0% and 11.6 {+/-} 2.0%, respectively. BPL significantly increased tracer accumulation into deep cervical lymph nodes and systemic circulation, but reduced perivascular inflow along penetrating arteries in the brain. The enhanced tracer efflux by BPL into the systemic circulation was markedly reduced (-66.7%) by ligation of lymphatic vessels draining into deep cervical lymph nodes. ConclusionsThis is the first study showing that CSF clearance can be improved with acute hypotensive treatment and that the effect of the treatment is reduced by ligation of a lymphatic drainage pathway. Enhanced CSF clearance by BPL may have therapeutic potential in diseases with dysregulated CSF flow.

neuroscience↗

bioRxiv2022

Claudin5 protects the peripheral endothelial barrier in an organ and vessel type-specific manner

The pathogenesis of numerous diseases is characterised by disruption of the junctions that form the endothelial cell (EC) barrier, the composition of which may differ greatly between organs. However, the expression level variability and precise contribution of different junctional proteins is poorly understood. Here, we focus on organs with continuous endothelium to identify structural and functional in vivo characteristics of the EC barrier. Assembly of multiple single-cell RNAseq datasets into a single integrated database revealed the variability in EC barrier patterning. Across tissues Claudin5 exhibited diminishing expression along the arteriovenous axis, which correlates with EC barrier integrity. Functional analysis identified tissue-specific differences in leakage patterning and response to agonist-induced leakage. We uncover that Claudin5 loss enhances agonist-induced leakage in an organotypic, vessel type-specific and size-selective manner in an inducible, EC-specific, knock-out mouse. Mechanistically, Claudin5 loss induces no change in junction ultrastructure but alters composition, with concomitant loss of zonula occludens-1 (ZO-1) expression and upregulation of VE-Cadherin. These findings uncover the organ-specific organisation of the EC barrier and distinct importance of Claudin5 in different vascular beds and will aid our ability to modify EC barrier stability in a targeted, organ-specific manner.

cell biology↗

bioRxiv2018

Genetics of fasting indices of glucose homeostasis using GWIS unravels tight relationships with inflammatory markers

PurposeHomeostasis Model Assessment of {beta}-cell function and Insulin Resistance (HOMA-B/-IR) indices are informative about the pathophysiological processes underlying type 2 diabetes (T2D). Data on both fasting glucose and insulin levels are required to calculate HOMA-B/-IR, leading to underpowered Genome-Wide Association studies (GWAS) of these traits.\n\nMethodsWe overcame such power loss issues by implementing Genome-Wide Inferred Statistics (GWIS) approach and subsequent dense genome-wide imputation of HOMA-B/-IR summary statistics with SS-imp to 1000 Genomes project variant density, reaching an analytical sample size of 75,240 European individuals without diabetes. We dissected mechanistic heterogeneity of glycaemic trait/T2D loci effects on HOMA-B/-IR and their relationships with 36 inflammatory and cardiometabolic phenotypes.\n\nResultsWe identified one/three novel HOMA-B (FOXA2)/HOMA-IR (LYPLAL1, PER4, PPP1R3B) loci. We detected novel strong genetic correlations between HOMA-IR/-B and Plasminogen Activator Inhibitor 1 (PAI-1, rg=0.92/0.78, P=2.13x10-4/2.54x10-3). HOMA-IR/-B were also correlated with C-Reactive Protein (rg=0.33/0.28, P=4.67x10-3/3.65x10-3). HOMA-IR was additionally correlated with T2D (rg=0.56, P=2.31x10-9), glycated haemoglobin (rg=0.28, P=0.024) and adiponectin (rg=-0.30, P=0.012).\n\nConclusionUsing innovative GWIS approach for composite phenotypes we report novel evidence for genetic relationships between fasting indices of insulin resistance/beta-cell function and inflammatory markers, providing further support for the role of inflammation in T2D pathogenesis.

genetics↗

bioRxiv2018

Machine Learning in Multi-Omics Data to Assess Longitudinal Predictors of Glycaemic Trait Levels

Type 2 diabetes (T2D) is a global health burden that will benefit from personalised risk prediction and targeted prevention programmes. Omics data have enabled more detailed risk prediction; however, most studies have focussed on directly on the ability of DNA variants predicting T2D onset with less attention given to epigenetic regulation and glycaemic trait variability. By applying machine learning to the longitudinal Northern Finland Birth Cohort 1966 (NFBC 1966) at 31 (T1) and 46 (T2) years old, we predicted fasting glucose (FG) and insulin (FI), glycated haemoglobin (HbA1c) and 2-hour glucose and insulin from oral glucose tolerance test (2hGlu, 2hIns) at T2 in 513 individuals from 1,001 variables at T1 and T2, including anthropometric, metabolic, metabolomic and epigenetic variables. We further tested whether the information obtained by the machine learning models in NFBC could be used to predict glycaemic traits in the independent French study with 48 matching predictors (DESIR, N=769, age range 30-65 years at recruitment, interval between data collections: 9 years). In this study, FG and FI were best predicted, with average R2 values of 0.38 and 0.53. Sex, branched-chain and aromatic amino acids, HDL-cholesterol, glycerol, ketone bodies, blood pressure at T2 and measurements of adiposity at T1, as well as multiple methylation marks at both time points were amongst the top predictors. In the validation analysis, we reached R2 values of 0.41/0.55 for FG/FI when trained and tested in NFBC1966 and 0.17/0.30 when trained in NFBC1966 and tested in DESIR. We identified clinically relevant sets of predictors from a large multi-omics dataset and highlighted the potential of methylation markers and longitudinal changes in prediction.

genomics↗

bioRxiv2018

Genetic determinants of risk and survival in pulmonary arterial hypertension

BackgroundPulmonary arterial hypertension (PAH) is a rare disorder leading to premature death. Rare genetic variants contribute to disease etiology but the contribution of common genetic variation to disease risk and outcome remains poorly characterized.\n\nMethodsWe performed two separate genome-wide association studies of PAH using data across 11,744 European-ancestry individuals (including 2,085 patients), one with genotypes from 5,895 whole genome sequences and another with genotyping array data from 5,849 further samples. Cross-validation of loci reaching genome-wide significance was sought by meta-analysis. We functionally annotated associated variants and tested associations with duration of survival.\n\nFindingsA locus at HLA-DPA1/DPB1 within the class II major histocompatibility (MHC) region and a second near SOX17 were significantly associated with PAH. The SOX17 locus contained two independent signals associated with PAH. Functional and epigenomic data indicate that the risk variants near SOX17 alter gene regulation via an enhancer active in endothelial cells. PAH risk variants determined haplotype-specific enhancer activity and CRISPR-inhibition of the enhancer reduced SOX17 expression. Analysis of median survival showed that PAH patients with two copies of the HLA-DPA1/DPB1 risk variant had a two-fold difference (>16 years versus 8 years), compared to patients homozygous for the alternative allele.\n\nInterpretationWe have found that common genetic variation at loci in HLA-DPA1/DPB1 and an enhancer near SOX17 are associated with PAH. Impairment of Sox17 function may be more common in PAH than suggested by rare mutations in SOX17. Allelic variation at HLA-DPB1 stratifies PAH patients for survival following diagnosis, with implications for future therapeutic trial design.\n\nFundingUK NIHR, BHF, UK MRC, Dinosaur Trust, NIH/NHLBI, ERS, EMBO, Wellcome Trust, EU, AHA, ACClinPharm, Netherlands CVRI, Dutch Heart Foundation, Dutch Federation of UMC, Netherlands OHRD and RNAS, German DFG, German BMBF, APH Paris, Inserm, Universite Paris-Sud, and French ANR.

genetics↗

bioRxiv2017

Genetic architecture of early childhood growth phenotypes gives insights into their link with later obesity

Early childhood growth patterns are associated with adult metabolic health, but the underlying mechanisms are unclear. We performed genome-wide meta-analyses and follow-up in up to 22,769 European children for six early growth phenotypes derived from longitudinal data: peak height and weight velocities, age and body mass index (BMI) at adiposity peak (AP ~9 months) and rebound (AR ~5-6 years). We identified four associated loci (P< 5x10-8): LEPR/LEPROT with BMI at AP, FTO and TFAP2B with Age at AR and GNPDA2 with BMI at AR. The observed AR-associated SNPs at FTO, TFAP2B and GNPDA2 represent known adult BMI-associated variants. The common BMI at AP associated variant at LEPR/LEPROT was not associated with adult BMI but was associated with LEPROT gene expression levels, especially in subcutaneous fat (P<2x10-51). We identify strong positive genetic correlations between early growth and later adiposity traits, and analysis of the full discovery stage results for Age at AR revealed enrichment for insulin-like growth factor 1 (IGF-1) signaling and apolipoprotein pathways. This genome-wide association study suggests mechanistic links between early childhood growth and adiposity in later childhood and adulthood, highlighting these early growth phenotypes as potential targets for the prevention of obesity.

genomics↗