Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

A meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain.publishedVersio

No differential gene expression for CD4+ T cells of MS patients and healthy controls.

Background: Multiple sclerosis-associated genetic variants indicate that the adaptive immune system plays an important role in the risk of developing multiple sclerosis. It is currently not well understood how these multiple sclerosis-associated genetic variants contribute to multiple sclerosis risk. CD4þ T cells are suggested to be involved in multiple sclerosis disease processes. Objective: We aim to identify CD4þ T cell differential gene expression between multiple sclerosis patients and healthy controls in order to understand better the role of these cells in multiple sclerosis. Methods: We applied RNA sequencing on CD4þ T cells from multiple sclerosis patients and healthy controls. Results: We did not identify significantly differentially expressed genes in CD4þ T cells from multiple sclerosis patients. Furthermore, pathway analyses did not identify enrichment for specific pathways in multiple sclerosis. When we investigated genes near multiple sclerosis-associated genetic variants, we did not observe significant enrichment of differentially expressed genes. Conclusion: We conclude that CD4þ T cells from multiple sclerosis patients do not show significant differential gene expression. Therefore, gene expression studies of all circulating CD4þ T cells may not result in viable biomarkers. Gene expression studies of more specific subsets of CD4þ T cells remain justified to understand better which CD4þ T cell subsets contribute to multiple sclerosis pathology

No differential gene expression for CD4+ T cells of MS patients and healthy controls.

Background Multiple sclerosis-associated genetic variants indicate that the adaptive immune system plays an important role in the risk of developing multiple sclerosis. It is currently not well understood how these multiple sclerosis-associated genetic variants contribute to multiple sclerosis risk. CD4+ T cells are suggested to be involved in multiple sclerosis disease processes. Objective We aim to identify CD4+ T cell differential gene expression between multiple sclerosis patients and healthy controls in order to understand better the role of these cells in multiple sclerosis. Methods We applied RNA sequencing on CD4+ T cells from multiple sclerosis patients and healthy controls. Results We did not identify significantly differentially expressed genes in CD4+ T cells from multiple sclerosis patients. Furthermore, pathway analyses did not identify enrichment for specific pathways in multiple sclerosis. When we investigated genes near multiple sclerosis-associated genetic variants, we did not observe significant enrichment of differentially expressed genes. Conclusion We conclude that CD4+ T cells from multiple sclerosis patients do not show significant differential gene expression. Therefore, gene expression studies of all circulating CD4+ T cells may not result in viable biomarkers. Gene expression studies of more specific subsets of CD4+ T cells remain justified to understand better which CD4+ T cell subsets contribute to multiple sclerosis pathology

The interaction between smoking and HLA genes in multiple sclerosis: replication and refinement

Interactions between environment and genetics may contribute to multiple sclerosis (MS) development. We investigated whether the previously observed interaction between smoking and HLA genotype in the Swedish population could be replicated, refined and extended to include other populations. We used six independent case–control studies from five different countries (Sweden, Denmark, Norway, Serbia, United States). A pooled analysis was performed for replication of previous observations (7190 cases, 8876 controls). Refined detailed analyses were carried out by combining the genetically similar populations from the Nordic studies (6265 cases, 8401 controls). In both the pooled analyses and in the combined Nordic material, interactions were observed between HLA-DRB*15 and absence of HLA-A*02 and between smoking and each of the genetic risk factors. Two way interactions were observed between each combination of the three variables, invariant over categories of the third. Further, there was also a three way interaction between the risk factors. The difference in MS risk between the extremes was considerable; smokers carrying HLA-DRB1*15 and lacking HLA-A*02 had a 13-fold increased risk compared with never smokers without these genetic risk factors (OR 12.7, 95% CI 10.8–14.9). The risk of MS associated with HLA genotypes is strongly influenced by smoking status and vice versa. Since the function of HLA molecules is to present peptide antigens to T cells, the demonstrated interactions strongly suggest that smoking alters MS risk through actions on adaptive immunity

Increased DNA methylation of SLFN12 in CD4+ and CD8+ T cells from multiple sclerosis patients

DNA methylation is an epigenetic mark that is influenced by environmental factors and is associated with changes to gene expression and phenotypes. It may link environmental exposures to disease etiology or indicate important gene pathways involved in disease pathogenesis. We identified genomic regions that are differentially methylated in T cells of patients with relapsing remitting multiple sclerosis (MS) compared to healthy controls. DNA methylation was assessed at 450,000 genomic sites in CD4+ and CD8+ T cells purified from peripheral blood of 94 women with MS and 94 healthy women, and differentially methylated regions were identified using bumphunter. Differential DNA methylation was observed near four loci: MOG/ZFP57, HLA-DRB1, NINJ2/LOC100049716, and SLFN12. Increased methylation of the first exon of the SLFN12 gene was observed in both T cell subtypes and remained present after restricting analyses to samples from patients who had never been on treatment or had been off treatment for more than 2.5 years. Genes near the regions of differential methylation in T cells were assessed for differential expression in whole blood samples from a separate population of 1,329 women with MS and 97 healthy women. Gene expression of HLA-DRB1, NINJ2, and SLFN12 was observed to be decreased in whole blood in MS patients compared to controls. We conclude that T cells from MS patients display regions of differential DNA methylation compared to controls, and corresponding gene expression differences are observed in whole blood. Two of the genes that showed both methylation and expression differences, NINJ2 and SLFN12, have not previously been implicated in MS. SLFN12 is a particularly compelling target of further research, as this gene is known to be down-regulated during T cell activation and up-regulated by type I interferons (IFNs), which are used to treat MS

Deep neural networks learn general and clinically relevant representations of the ageing brain

Abstract The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data - the brain age delta - has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into one of the largest and most diverse datasets assembled (n=53542), and trained convolutional neural networks (CNNs) to predict age. We achieved state-of-the-art performance on unseen data from unknown scanners (n=2553), and showed that higher brain age delta is associated with diabetes, alcohol intake and smoking. Using transfer learning, the intermediate representations learned by our model complemented and partly outperformed brain age delta in predicting common brain disorders. Our work shows we can achieve generalizable and biologically plausible brain age predictions using CNNs trained on heterogeneous datasets, and transfer them to clinical use cases

A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis.

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available

A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility

Genome-wide association studies (GWASs) perform per-SNP association tests to identify variants involved in disease or trait susceptibility. However, such an approach is not powerful enough to unravel genes that are not individually contributing to the disease/trait, but that may have a role in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted of ITGAL, ICAM1 and ICAM3 genes, could be of interest to develop novel therapeutic targets

Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

A meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain

Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

A meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain