Biology subjects

Karlsson, H.

Publications and source records attributed to Karlsson, H..

40 records · Page 3Linked to original sources

bioRxiv2021

Subcortical brain segmentation in 5-year-old children: validation of FSL-FIRST and FreeSurfer against manual segmentation

Developing accurate subcortical volumetric quantification tools is crucial for neurodevelopmental studies, as they could reduce the need for challenging and time-consuming manual segmentation. In this study the accuracy of two automated segmentation tools, FSL-FIRST (with three different boundary correction settings) and FreeSurfer were compared against manual segmentation of subcortical nuclei, including the hippocampus, amygdala, thalamus, putamen, globus pallidus, caudate and nucleus accumbens, using volumetric and correlation analyses in 80 5-year-olds. Both FSL-FIRST and FreeSurfer overestimated the volume on all structures except the caudate, and the accuracy varied depending on the structure. Small structures such as the amygdala and nucleus accumbens, which are visually difficult to distinguish, produced significant overestimations and weaker correlations with all automated methods. Larger and more readily distinguishable structures such as the caudate and putamen produced notably lower overestimations and stronger correlations. Overall, the segmentations performed by FSL-FIRSTs Default pipeline were the most accurate, while FreeSurfers results were weaker across the structures. In line with prior studies, the accuracy of automated segmentation tools was imperfect with respect to manually defined structures. However, apart from amygdala and nucleus accumbens, FSL-FIRSTs agreement could be considered satisfactory (Pearson correlation > 0.74, Intraclass correlation coefficient (ICC) > 0.68 and Dice Score coefficient (DSC) > 0.87) with highest values for the striatal structures (putamen, globus pallidus and caudate) (Pearson correlation > 0.77, ICC > 0.87 and DSC > 0.88, respectively). Overall, automated segmentation tools do not always provide satisfactory results, and careful visual inspection of the automated segmentations is strongly advised.

neuroscience↗

bioRxiv2021

Feasibility of FreeSurfer processing for T1-weighted brain images of 5-year-olds: semiautomated protocol of FinnBrain Neuroimaging Lab

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. One key challenge is the use of many different atlases, automated segmentation tools, manual edits in semiautomated protocols, and quality control protocols, which complicates comparisons between studies. In this article, we present our semiautomated segmentation protocol using FreeSurfer v6.0, ENIGMA consortium software, and the quality control protocol that was used in FinnBrain Birth Cohort Study. We used a dichotomous quality rating scale for inclusion and exclusion of images, and then explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were minor: less than 2% in all regions. Supplementary materials cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Our semiautomated segmentation protocol provides high quality pediatric neuroimaging data and could help investigators working with similar data sets.

neuroscience↗

bioRxiv2020

Neonatal levels of acute phase proteins and risk of autism spectrum disorders

BackgroundImmune signaling pathways influence neurodevelopment and are hypothesized to contribute to the etiology of autism spectrum disorders (ASD). We aimed to assess risk of ASD in relation to levels of neonatal acute phase proteins, key components of innate immune function, measured in neonatal dried blood spots. MethodWe included 924 ASD cases, 1092 unaffected population-based controls, and 203 unaffected siblings to ASD cases in this case-control study nested within the register-based Stockholm Youth Cohort. Concentrations of nine different acute phase proteins were measured in eluates from neonatal dried blood spots from cases, controls, and siblings using a bead-based multiplex assay. ResultsC reactive protein was consistently associated with odds of ASD in case-control comparisons, with higher odds associated with the highest quintile compared to the middle quintile (OR 1.50, 95% CI 1.10 - 2.04) in adjusted analyses. In contrast, the lowest quintiles of alpha-2-macroglobulin (3.71, 1.21 - 11.33), ferritin (4.20, 1.40 - 12.65), and Serum Amyloid P (3.05, 1.16 - 8.01) were associated with odds of ASD in the matched sibling comparison. Neonatal acute phase proteins varied with perinatal environmental factors and maternal/fetal phenotypes. Significant interactions in terms of risk for ASD were observed between neonatal acute phase proteins and maternal infection in late pregnancy, maternal anemia, and maternal psychiatric history. ConclusionsIndicators of the neonatal innate immune response are associated with risk for ASD, though the nature of these associations varies considerably with factors in the perinatal environment and the genetic background of the comparison group.

molecular biology↗

bioRxiv2020

Maternal antibodies to gliadin and autism spectrum disorders in offspring - A population-based case-control study in Sweden

ObjectiveIndividuals diagnosed with autism spectrum disorders (ASD) are reported to have higher levels of antibodies directed towards gliadin, a component of wheat gluten. However, no study has examined such antibodies in etiologically-relevant periods before diagnosis. The objective of this study is to investigate if maternal levels of immunoglobulin G antibodies directed at gliadin, during pregnancy and at the time of birth, are associated with ASD in offspring. MethodsIn this population-based study set in Sweden with 921 ASD cases and 1090 controls, we analyzed levels of anti-gliadin antibodies (AGA) in archived neonatal dried blood spots (NDBS, as maternal IgG is transferred to the fetus) and in paired maternal sera collected earlier in pregnancy for a subset of 547 cases and 428 controls. We examined associations to any ASD diagnosis and considering common comorbidities (i.e. intellectual disability [ID] and attention-deficit/hyperactivity disorder [ADHD]). We compared 206 ASD cases to their unaffected siblings to examine the potential for confounding by shared familial factors. ResultsHigh levels ([≥]90th percentile) of maternal AGA were associated with decreased odds of ASD, particularly ASD with comorbid ID, when measured in NDBS (OR 0.51, 95% CI 0.30-0.87) with a similar trend in maternal sera (0.55, 0.24-1.29). High levels of maternal AGA were similarly associated with lower odds of ASD with ID in the sibling comparison. ConclusionsThis first study of exposure to AGA in the pre- and perinatal periods suggests that high levels of maternal AGA are associated with lower odds of ASD with ID.

molecular biology↗