Biology subjects

Olsson, T.

Publications and source records attributed to Olsson, T..

12 recordsLinked to original sources

bioRxiv2026

Genomic impact of the second plague pandemic on three human populations

The second plague pandemic (early 14th-early 19th centuries), which was caused by Yersinia pestis, had a profound demographic, socio-economic and cultural impact across Eurasia and North Africa. Many regions in Europe and the Middle East are estimated to have lost 40-60% of their human populations, with some areas suffering even higher mortality. Whether exposure to Y. pestis drove strong positive selection on protective genetic variants in the human genome, and how it shaped migration patterns, remains debated, despite several recent studies based on ancient DNA. Here, we analyse a markedly larger, higher coverage, and geographically diverse dataset based on shotgun sequencing of genomes from 529 ancient individuals to a mean depth 8.8x dating to either before or after the arrival of the pandemic at three sites in northern Europe: Trondheim (Norway), Lund (Sweden) and Vilnius (Lithuania). Genome-wide scans for signatures of selection provide no evidence for strong positive selection acting on specific genetic variants driven by Y. pestis exposure: we neither replicate selection signatures reported by previous studies nor identify new genome-wide significant candidates. However, for all three sites, we observe evidence for a reduction in long-range immigration, indicated by a drop in the diversity of ancestry that followed the arrival of Y. pestis and broadly coincided with the end of the Viking Age, Christianisation and the onset of the Little Ice Age. Our results shed important light on the demographic impact of major sociohistorical changes that occurred during the late Medieval period in Scandinavia and the Baltic region and link Christianisation to increased diversity in ancestry before the pandemic.

genomics↗

bioRxiv2026

Epigenomic profiling of cerebrospinal fluid cells identifies immune regulatory alterations and implicates protocadherins in multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS), where DNA methylation may play a role by connecting genetic and environmental risk factors. We performed whole-genome DNA methylation profiling of cerebrospinal fluid (CSF) cells from relapsing-remitting MS patients and matched controls, identifying 2,710 differentially methylated positions (DMPs) and 4,330 regions (DMRs). These changes were enriched in immune signaling, adhesion and migration processes, and were accompanied by corresponding RNA expression changes. MS-associated methylation changes enriched in the cohesin chromatin regulation pathway mapped to enhancers of T helper 17 (Th17) cells, whereas in other T cell types they were mapping to bivalent enhancers and repressed chromatin. Notably, this pathway comprised multiple Protocadherin (PCDH) genes, typically expressed in neuronal cells, that displayed consistent methylation and expression changes in CSF cells. Expression of shared intracellular domain of PCDH{gamma} cluster proteins was confirmed in peripheral blood T cells by flow cytometry as well as expression of PCDH{gamma} cluster genes in memory CD4+ T cell subsets. Moreover, co-expression analysis suggests a role of PCDH genes in aryl hydrocarbon receptor (AHR) signaling. In summary, DNA methylation changes in CSF resident cells reflect dysregulated T cell activation and migration in MS and suggest a novel role of protocadherin molecules in MS pathogenesis.

immunology↗

bioRxiv2025

The olfactory bulb reflects structural plasticity within a genetically stable olfactory network

The olfactory bulb (OB), the first central relay of the olfactory pathway, plays a critical role in odor perception and exhibits remarkable structural plasticity shaped by environmental influences. This raises a fundamental question about the extent to which the structure of the OB is genetically determined. While both OB volume and function have been implicated in a range of neurodegenerative and neuropsychiatric disorders, such as Parkinsons disease, schizophrenia, and depression, all of which involve known genetic risk factors, the heritability of the OB structure remains poorly understood. Here, we investigated the heritability of OB volume and the broader olfactory network architecture in a large sample of healthy young adults (n = 941; aged 22-35 years), including monozygotic and dizygotic twin pairs. Using a deep learning-based segmentation model, we first automatically segmented OB volumes and then employed a support vector machine framework to classify zygosity based on within-pair morphological similarity. The OB volume alone showed weak classification performance in distinguishing between monozygotic and dizygotic twins, suggesting limited heritability. However, integrating OB volume with morphometric features from olfactory-associated brain regions, including the hippocampus, parahippocampal gyrus, entorhinal cortex, and medial orbitofrontal cortices, substantially improved classification performance. This effect was specific to the olfactory network, underscoring the distributed nature of genetic influence in this system. These findings suggest that the OB, despite being a highly plastic and environmentally responsive structure, is embedded within a genetically coordinated neural network.

neuroscience↗

bioRxiv2025

Methodological determinants of signal quality in electrobulbogram recordings

The electrobulbogram (EBG) is a new, non-invasive method for measuring the functional activity of the human olfactory bulb (OB). To date, the EBG has been used to assess how the OB process odor identity, valence, intensity, and it has shown promise as an early biomarker for Parkinsons disease. However, current implementation of the EBG method depends on several methodological components, including subject specific co-registration of electrode positions through neuronavigation and EEG source reconstruction, which may limit accessibility for many research groups. In this study, we test the quality and reliability of the OB signal under different configurations to potentially remedy this. Specifically, we compare six EBG setups that vary in the use of subject-specific T1 scans versus a template head model, co-registered versus template electrode positions, and individualized versus template-based OB location. Our results indicate that strongest EBG signals are obtained when using subject-specific T1 scans in combination with co-registered electrode positions. However, we obtained significant EBG activity even when using a fully template-based configuration. Our anatomical analysis of OB location of 941 individuals reveals that in 86% of cases, the OB is centered within the spatial resolution bounds of the EEG source dipole, supporting the feasibility of detecting olfactory bulb signals without precise individual anatomical mapping using template coordinates. These findings suggest that while subject-specific configurations enhance signal quality, the EBG method remains robust enough to yield meaningful results even with less complex setups. This enables a broader adoption of the EBG method in both clinical and research settings.

neuroscience↗

bioRxiv2023

Distinct transcriptomic and epigenomic responses of mature oligodendrocytes during disease progression in a mouse model of multiple sclerosis

Multiple sclerosis (MS) is a chronic demyelinating autoimmune disease that targets mature oligodendrocytes (MOLs) and their myelin. MOLs are transcriptionally heterogeneous and can transition to immune-like states in the context of MS. However, the intricacies of their dynamics throughout disease progression remain poorly understood. Here, we employed simultaneous single-cell multiome ATAC and RNA sequencing targeting oligodendroglia (OLGs) from the experimental autoimmune encephalomyelitis (EAE) MS mouse model at different stages of the disease course. We found that the transition to immune OLG states appear already at the early stages of EAE and persist to the late stages of the disease. Interestingly, transcription factor activity suggested immunosuppression in MOLs at early stages of EAE and we also observed a transitory activation of a regenerative program in MOLs at this stage. Importantly, different MOLs exhibit a differential responsiveness to EAE, with MOL2 exhibiting a stronger transcriptional immune response than MOL5/6. Moreover, we observed divergent responses at the epigenetic level of MOL2 and MOL5/6 during disease evolution. Thus, our single-cell multiomic resource highlights dynamic and distinct responses of OLG subpopulations to the evolving environment in EAE, which might modulate their response to regenerative therapeutic interventions in MS.

neuroscience↗

bioRxiv2023

Single cell-resolution in situ sequencing elucidates spatial dynamics of multiple sclerosis lesion and disease evolution

Multiple sclerosis (MS) is a neurological disease characterised by multifocal lesions and smouldering pathology. While single-cell analyses have provided insights into neuropathology, cellular processes underlying MS remain poorly understood. We modelled the cellular dynamics of MS by examining temporal and regional rates of disease progression in the experimental autoimmune encephalomyelitis (EAE) mouse model. By performing single-cell spatial expression profiling using In situ sequencing, we annotated disease neighbourhoods during lesion evolution and found centrifugal propagation of active lesions. We demonstrated that disease-associated (DA) glia are dynamic and induced independently of lesions, preceding their formation. Single-cell spatial analysis of human archival MS spinal cord confirmed differential distribution of DA-glia, enabled deconvolution of active and inactive lesions into sub-compartments, and identification of new lesion areas. By establishing a spatial resource of mouse and human MS neuropathology at a single-cell resolution, our study unveils the intricate cellular dynamics underlying MS disease evolution.

cell biology↗

bioRxiv2020

Systematic GWAS-assessment of disease modules reveals a multi-omic MS module strongly associated with risk factors

BackgroundThere are few (if any) practical guidelines for predictive and falsifiable multi-omics data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules. MethodsWe assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omics integration of 19 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor associated genes from several independent cohorts. ResultsOur benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS-genes. The multi-omics case study using MS revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module was differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10-47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS. ConclusionWe believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omics approaches for complex diseases.

bioinformatics↗

bioRxiv2020

Profiling of small non-coding RNAs across cellular and biofluid compartments: implications for multiple sclerosis immunopathology

Multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system (CNS), is associated with dysregulation of microRNAs (miRNA). We here analyzed all classes of small non-coding RNAs (sncRNAs) in matching peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF) cells and cell-free CSF from relapsing-remitting (RRMS, n=12 in relapse, n=11 in remission), secondary progressive (SPMS, n=6) MS patients and non-inflammatory and inflammatory neurological disease controls (NINDC, n=11; INDC, n=5). We show widespread changes in small nuclear, nucleolar, transfer RNAs and miRNAs. In CSF cells, 133/133 and 115/117 differentially expressed sncRNAs are increased in RRMS relapse compared to remission and RRMS compared to NINDC, respectively. In contrast, 65/67 differentially expressed PBMC sncRNAs are decreased in RRMS compared to NINDC. The striking contrast between periphery and CNS suggests that sncRNA-mediated mechanisms, including alternative splicing, RNA degradation and mRNA translation, regulate the transcriptome of pathogenic cells primarily in the target organ.

molecular biology↗

bioRxiv2020

The genetic structure of Norway

The aim of the present study was to describe the genetic structure of the Norwegian population using genotypes from 6369 unrelated individuals with detailed information about places of residence. Using standard single marker- and haplotype-based approaches, we report evidence of two regions with distinctive patterns of genetic variation, one in the far northeast, and another in the south of Norway, as indicated by fixation indices, haplotype sharing, homozygosity and effective population size. We detect and quantify a component of Uralic Sami ancestry that is enriched in the North. On a finer scale, we find that rates of migration have been affected by topography like mountain ridges. In the broader Scandinavian context, we detect elevated relatedness between the mid- and northern border areas towards Sweden. The main finding of this study is that despite Norways long maritime history and as a former Danish territory, the region closest to mainland Europe in the south appears to have been the most isolated region in Norway, highlighting the open sea as a barrier to gene flow.

genetics↗

bioRxiv2019

Increased serological response against human herpesvirus 6A is associated with risk for multiple sclerosis

Human herpesvirus (HHV)-6A or HHV-6B involvement in multiple sclerosis (MS) etiology has remained controversial mainly due to the lack of serological methods that can distinguish the two viruses.\n\nA novel multiplex serological assay measuring IgG reactivity against the immediate-early protein 1 from HHV-6A (IE1A) and HHV-6B (IE1B) was used in a MS cohort (8742 persons with MS and 7215 matched controls), and a pre-MS cohort (478 individuals and 476 matched controls) to investigate this further.\n\nThe IgG response against IE1A was positively associated with MS (OR = 1.55, p = 9x10-22), and increased risk of future MS (OR = 2.22, p = 2x10-5). An interaction was observed between IE1A and Epstein-Barr virus (EBV) antibody responses for MS risk (attributable proportion = 0.24, p = 6x10-6). In contrast, the IgG response against IE1B was negatively associated with MS (OR = 0.74, p = 6x10-11). The association did not differ between MS subtypes or vary with severity of disease. The genetic control of HHV-6A/B antibody responses were located to the Human Leukocyte Antigen (HLA) region and the strongest association for IE1A was the DRB1*13:01-DQA1*01:03-DQB1*06:03 haplotype while the main association for IE1B was DRB1*13:02-DQA1*01:02-DQB1*06:04.\n\nIn conclusion a role for HHV-6A in MS etiology is supported by an increased serological response against HHV-6A IE1 protein, an interaction with EBV, and an association to HLA genes.

immunology↗

bioRxiv2019

Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis

Signal transduction deregulation is a hallmark of many complex diseases, including Multiple Sclerosis (MS). Here, we performed ex vivo multiplexed phosphoproteomic assays in PBMCs from 180 MS patients either untreated or treated with fingolimod, natalizumab, interferon-beta, glatiramer acetate or the experimental therapy epigallocatechin gallate (EGCG), and from 60 matched healthy controls. Fitting a bespoke literature-derived network of MS-related pathways using logic modeling yielded a signaling network specific for each patient. Patient models were merged to characterize healthy-, disease- and drug-specific signaling networks. We defined a co-druggability score based on the topology for each drugs network. We used this score to identify kinase interactions whose activity could be reverted to a "healthy-like" status by combination therapy. We predicted several combinations with approved MS drugs. Specifically, TAK1 kinase, involved in TGF-B, toll-like receptor, B-cell receptor and response to inflammation pathways was found to be highly deregulated and co-druggable with four MS drugs. One of these predicted combinations, Fingolimod with a TAK1 inhibitor, was validated in an animal model of MS. Our approach based on patient-specific signaling networks enables prediction of targets for combination therapy for MS and other complex diseases. One sentence summaryA new approach to predict combination therapies based on modeling signaling architecture using phosphoproteomics from patients with Multiple Sclerosis characterizes deregulated signaling pathways and reveals new therapeutic targets and drug combinations.

systems biology↗

bioRxiv2018

Statistical loadings and latent significance simplify and improve interpretation of multivariate projection models

Multivariate projection methods are unique in being both multivariable by combining many variables into stronger predictive features (latent variables), and multivariate for being able to model systematic variation both related and orthogonal to an observed response. Orthogonal partial least squares (OPLS) is a versatile multivariate projection method for analysis of correlation, discrimination and effect changes. However, currently OPLS is not fully using its multivariate potential since orthogonal systematic variation is not considered in model interpretation, resulting in univariate interpretation of variable significance. We present a strategy for improved interpretation of OPLS models based upon a post-hoc linear regression analysis that can be used with or without the orthogonal OPLS score(s) as a covariate to make the interpretation multivariate or univariate respectively. By selecting the observed response y or estimated response yhat as a one of the factors in the linear regression the results are related to either of the OPLS loadings w or p. Furthermore, converting the OPLS loading values to statistical t-values creates a direct link to statistical significance. Finally, by applying three different Boolean loadings W, P and W{wedge}P variable significance can be summarized based on three criteria. W and P reveal if the values in w or p respectively are outside the statistical limits with W{wedge}P being the logical conjunction of W and P (significant if outside limits in both W and P). Two examples are used to verify the proposed strategy. First, a synthetic example, simulating a mix of mass spectra, and second a clinical metabolomics study of a dietary intervention. In the simulated example we show that multivariate interpretation gives higher accuracy for estimation of true differences, mainly due to higher true positive rate. Furthermore, we highlight how application of W{wedge}P for summarizing variable significance leads to higher accuracy. For the metabolomics example, we show that a more detailed interpretation, i.e. larger number of significant metabolites of relevance, is obtained using the multivariate interpretation. In summary, the suggested strategy provides means for facilitated interpretation of OPLS models, beyond univariate statistics, and offers a multivariate tool for discovery of biomarker patterns, i.e. latent biomarkers.

bioinformatics↗