Carotid Atherosclerosis and Relation to Growth of Infrarenal Aortic Diameter and Follow-up Diameter: The Tromsø Study

AbstractObjectivesThis research aims to study how carotid atherosclerosis is related to growth of infrarenal aortic diameter and aneurysmal formation.DesignPopulation-based follow-up study.Materials and methodsAt baseline, ultrasound examination of the carotid artery and the abdominal aorta was performed in 4241 persons from a general population with no evidence of abdominal aortic aneurysm (AAA). The burden of atherosclerosis was assessed as carotid total plaque area (TPA). After a mean follow-up of 6.3 years, a new ultrasound examination was performed and measurements of the aortic diameter and carotid TPA were repeated. The effects on aortic diameter progression, follow-up diameter and risk for AAA were assessed in multiple linear and logistic regression models according to carotid TPA, adjusted for known risk factors.ResultsWhen analysing AAA as a dichotomous variable, a borderline association between atherosclerosis and AAA could be demonstrated. When modelling aortic diameter as a continuous variable, a 1-SD increase in 5 years' carotid plaque area (ΔTPA) was associated with a 0.12-mm growth in infrarenal aortic diameter (standard error (SE) 0.04) and a 0.20-mm wider aorta at follow-up (SE 0.06). No independent relation was seen for baseline atherosclerosis.ConclusionsCarotid plaque progression was positively related to growth in infrarenal aortic diameter and aortic diameter at follow-up. Whether this co-variation between plaque growth and aortic diameter growth is causally related or independent events is still an open question

Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles

Genome-wide association analyses identify 123 susceptibility loci for migraine and implicate neurovascular mechanisms in its pathophysiology. Subtype analyses highlight risk loci specific for migraine with or without aura in addition to shared risk variants.Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.Clinical epidemiolog

Progression of conventional cardiovascular risk factors and vascular disease risk in individuals: insights from the PROG-IMT consortium

Aims: Averaged measurements, but not the progression based on multiple assessments of carotid intima-media thickness, (cIMT) are predictive of cardiovascular disease (CVD) events in individuals. Whether this is true for conventional risk factors is unclear. Methods and results: An individual participant meta-analysis was used to associate the annualised progression of systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with future cardiovascular disease risk in 13 prospective cohort studies of the PROG-IMT collaboration (n = 34,072). Follow-up data included information on a combined cardiovascular disease endpoint of myocardial infarction, stroke, or vascular death. In secondary analyses, annualised progression was replaced with average. Log hazard ratios per standard deviation difference were pooled across studies by a random effects meta-analysis. In primary analysis, the annualised progression of total cholesterol was marginally related to a higher cardiovascular disease risk (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.00 to 1.07). The annualised progression of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol was not associated with future cardiovascular disease risk. In secondary analysis, average systolic blood pressure (HR 1.20 95% CI 1.11 to 1.29) and low-density lipoprotein cholesterol (HR 1.09, 95% CI 1.02 to 1.16) were related to a greater, while high-density lipoprotein cholesterol (HR 0.92, 95% CI 0.88 to 0.97) was related to a lower risk of future cardiovascular disease events. Conclusion: Averaged measurements of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol displayed significant linear relationships with the risk of future cardiovascular disease events. However, there was no clear association between the annualised progression of these conventional risk factors in individuals with the risk of future clinical endpoints

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

High Performance Computing Applications Using Parallel Data Processing Units

International audienceMulticore processors are growing with respect to the number of cores on a chip. In a parallel computation context, multicore platforms have several important features such as exploiting multiple parallel processes, having access to a shared memory with noticeably lower cost than the distributed alternative and optimizing different levels of parallelism. In this paper, we introduce the Parallel Data Processing Unit (PDPU) which is a group of objects that benefits from the shared memory of the multicore configuration and that consists of two parts: a shared memory for maintaining data consistent, and a set of objects that are processing the data, then producing and aggregating the results concurrently. We then implement two examples in Java that illustrate PDPU behavior, and compare them with their actor based counterparts and show significant performance improvements. We also put forward the idea of integrating PDPU with the actor model which will result in an optimization for a specific spectrum of problems in actor based development