The CYP24A1 gene variant rs2762943 is associated with low serum 1,25-dihydroxyvitamin D levels in multiple sclerosis patients.

BACKGROUND AND PURPOSE: Vitamin D is considered to play a role in multiple sclerosis (MS) etiopathogenesis. A polymorphism in the CYP24A1 gene, rs2762943, was recently identified that was associated with an increased MS risk. CYP24A1 encodes a protein involved in the catabolism of the active form of vitamin D. The immunological effects of carrying the rs2762943 risk allele were investigated, as well as its role as genetic modifier. METHODS: Serum levels of 25-hydroxyvitamin D and 1,25-dihydroxyvitamin D (1,25(OH)2 D) were measured in a cohort of 167 MS patients. In a subgroup of patients, expression levels of major histocompatibility complex class II and co-stimulatory molecules were determined by flow cytometry, and serum levels of pro-inflammatory (interferon gamma, granulocyte macrophage colony-stimulating factor, C-X-C motif chemokine ligand 13) and anti-inflammatory (interleukin 10) cytokines and neurofilament light chain were measured by single-molecule array assays. The effect of the rs2762943 polymorphism on disease activity and disability measures was evaluated in 340 MS patients. RESULTS: Compared to non-carriers, carriers of the rs2762943 risk allele were characterized by reduced levels of 1,25(OH)2 D (p = 0.0001) and elevated levels of interferon gamma (p = 0.03) and granulocyte macrophage colony-stimulating factor (p = 0.008), whereas no significant differences were observed for the other markers. The presence of the rs2762943 risk allele had no significant impact on disease activity and disability outcomes during follow-up. However, risk allele carriers were younger at disease onset (p = 0.04). CONCLUSIONS: These findings suggest that the CYP24A1 rs2762943 polymorphism plays a more important role in MS susceptibility than in disease prognosis and is associated with lower 1,25(OH)2 D levels and a heightened pro-inflammatory environment in MS patients.

Not all roads lead to the immune system: the genetic basis of multiple sclerosis severity.

Multiple sclerosis is a leading cause of neurological disability in adults. Heterogeneity in multiple sclerosis clinical presentation has posed a major challenge for identifying genetic variants associated with disease outcomes. To overcome this challenge, we used prospectively ascertained clinical outcomes data from the largest international multiple sclerosis registry, MSBase. We assembled a cohort of deeply phenotyped individuals of European ancestry with relapse-onset multiple sclerosis. We used unbiased genome-wide association study and machine learning approaches to assess the genetic contribution to longitudinally defined multiple sclerosis severity phenotypes in 1813 individuals. Our primary analyses did not identify any genetic variants of moderate to large effect sizes that met genome-wide significance thresholds. The strongest signal was associated with rs7289446 (ß = -0.4882, P = 2.73 × 10-7), intronic to SEZ6L on chromosome 22. However, we demonstrate that clinical outcomes in relapse-onset multiple sclerosis are associated with multiple genetic loci of small effect sizes. Using a machine learning approach incorporating over 62 000 variants together with clinical and demographic variables available at multiple sclerosis disease onset, we could predict severity with an area under the receiver operator curve of 0.84 (95% CI 0.79-0.88). Our machine learning algorithm achieved positive predictive value for outcome assignation of 80% and negative predictive value of 88%. This outperformed our machine learning algorithm that contained clinical and demographic variables alone (area under the receiver operator curve 0.54, 95% CI 0.48-0.60). Secondary, sex-stratified analyses identified two genetic loci that met genome-wide significance thresholds. One in females (rs10967273; ßfemale = 0.8289, P = 3.52 × 10-8), the other in males (rs698805; ßmale = -1.5395, P = 4.35 × 10-8), providing some evidence for sex dimorphism in multiple sclerosis severity. Tissue enrichment and pathway analyses identified an overrepresentation of genes expressed in CNS compartments generally, and specifically in the cerebellum (P = 0.023). These involved mitochondrial function, synaptic plasticity, oligodendroglial biology, cellular senescence, calcium and G-protein receptor signalling pathways. We further identified six variants with strong evidence for regulating clinical outcomes, the strongest signal again intronic to SEZ6L (adjusted hazard ratio 0.72, P = 4.85 × 10-4). Here we report a milestone in our progress towards understanding the clinical heterogeneity of multiple sclerosis outcomes, implicating functionally distinct mechanisms to multiple sclerosis risk. Importantly, we demonstrate that machine learning using common single nucleotide variant clusters, together with clinical variables readily available at diagnosis can improve prognostic capabilities at diagnosis, and with further validation has the potential to translate to meaningful clinical practice change.

Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans.

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

A Whole-Genome Sequencing Study Implicates GRAMD1B in Multiple Sclerosis Susceptibility.

While the role of common genetic variants in multiple sclerosis (MS) has been elucidated in large genome-wide association studies, the contribution of rare variants to the disease remains unclear. Herein, a whole-genome sequencing study in four affected and four healthy relatives of a consanguineous Italian family identified a novel missense c.1801T > C (p.S601P) variant in the GRAMD1B gene that is shared within MS cases and resides under a linkage peak (LOD: 2.194). Sequencing GRAMD1B in 91 familial MS cases revealed two additional rare missense and two splice-site variants, two of which (rs755488531 and rs769527838) were not found in 1000 Italian healthy controls. Functional studies demonstrated that GRAMD1B, a gene with unknown function in the central nervous system (CNS), is expressed by several cell types, including astrocytes, microglia and neurons as well as by peripheral monocytes and macrophages. Notably, GRAMD1B was downregulated in vessel-associated astrocytes of active MS lesions in autopsied brains and by inflammatory stimuli in peripheral monocytes, suggesting a possible role in the modulation of inflammatory response and disease pathophysiology.

Ancestral risk modification for multiple sclerosis susceptibility detected across the Major Histocompatibility Complex in a multi-ethnic population.

The Major Histocompatibility Complex (MHC) makes the largest genetic contribution to multiple sclerosis (MS) susceptibility, with 32 independent effects across the region explaining 20% of the heritability in European populations. Variation is high across populations with allele frequency differences and population-specific risk alleles identified. We sought to identify MHC-specific MS susceptibility variants and assess the effect of ancestral risk modification within 2652 Latinx and Hispanic individuals as well as 2435 Black and African American individuals. We have identified several novel susceptibility alleles which are rare in European populations including HLA-B*53:01, and we have utilized the differing linkage disequilibrium patterns inherent to these populations to identify an independent role for HLA-DRB1*15:01 and HLA-DQB1*06:02 on MS risk. We found a decrease in Native American ancestry in MS cases vs controls across the MHC, peaking near the previously identified MICB locus with a decrease of ~5.5% in Hispanics and ~0.4% in African Americans. We have identified several susceptibility variants, including within the MICB gene region, which show global ancestry risk modification and indicate ancestral differences which may be due in part to correlated environmental factors. We have also identified several susceptibility variants for which MS risk is modified by local ancestry and indicate true ancestral genetic differences; including HLA-DQB1*06:02 for which MS risk for European allele carriers is almost two times the risk for African allele carriers. These results validate the importance of investigating MS susceptibility at an ancestral level and offer insight into the epidemiology of MS phenotypic diversity.

Characterization of CD41+ cells in the lymph node.

Lymph nodes (LNs) are the critical sites of immunity, and the stromal cells of LNs are crucial to their function. Our understanding of the stromal compartment of the LN has deepened recently with the characterization of nontraditional stromal cells. CD41 (integrin αIIb) is known to be expressed by platelets and hematolymphoid cells. We identified two distinct populations of CD41+Lyve1+ and CD41+Lyve1- cells in the LNs. CD41+Lyve1- cells appear in the LN mostly at the later stages of the lives of mice. We identified CD41+ cells in human LNs as well. We demonstrated that murine CD41+ cells express mesodermal markers, such as Sca-1, CD105 and CD29, but lack platelet markers. We did not observe the presence of platelets around the HEVs or within proximity to fibroblastic reticular cells of the LN. Examination of thoracic duct lymph fluid showed the presence of CD41+Lyve1- cells, suggesting that these cells recirculate throughout the body. FTY720 reduced their trafficking to lymph fluid, suggesting that their egress is controlled by the S1P1 pathway. CD41+Lyve1- cells of the LNs were sensitive to radiation, suggestive of their replicative nature. Single cell RNA sequencing data showed that the CD41+ cell population in naïve mouse LNs expressed largely stromal cell markers. Further studies are required to examine more deeply the role of CD41+ cells in the function of LNs.

Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets.

BACKGROUND: Multiple sclerosis (MS) is an autoimmune condition of the central nervous system with a well-characterized genetic background. Prior analyses of MS genetics have identified broad enrichments across peripheral immune cells, yet the driver immune subsets are unclear. RESULTS: We utilize chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals. We find that CD4 T and B cells are independently enriched for MS genetics and further refine the driver subsets to Th17 and memory B cells, respectively. We replicate our findings in data from untreated and treated MS patients and find that immunomodulatory treatments suppress chromatin accessibility at driver cell types. Integration of statistical fine-mapping and chromatin interactions nominate numerous putative causal genes, illustrating complex interplay between shared and cell-specific genes. CONCLUSIONS: Overall, our study finds that open chromatin regions in CD4 T cells and B cells independently drive MS genetic signals. Our study highlights how careful integration of genetics and epigenetics can provide fine-scale insights into causal cell types and nominate new genes and pathways for disease.

A multi-step genomic approach prioritized TBKBP1 gene as relevant for multiple sclerosis susceptibility.

BACKGROUND: Over 200 genetic loci have been associated with multiple sclerosis (MS) explaining ~ 50% of its heritability, suggesting that additional mechanisms may account for the "missing heritability" phenomenon. OBJECTIVE: To analyze a large cohort of Italian individuals to identify markers associated with MS with potential functional impact in the disease. METHODS: We studied 2571 MS and 3234 healthy controls (HC) of continental Italian origin. Discovery phase included a genome wide association study (1727 MS, 2258 HC), with SNPs selected according to their association in the Italian cohort only or in a meta-analysis of signals with a cohort of European ancestry (4088 MS, 7144 HC). Top associated loci were then tested in two Italian cohorts through array-based genotyping (903 MS, 884 HC) and pool-based target sequencing (588 MS, 408 HC). Finally, functional prioritization through conditional eQTL and mQTL has been performed. RESULTS: Top associated signals overlap with already known MS loci on chromosomes 3 and 17. Three SNPs (rs4267364, rs8070463, rs67919208), all involved in the regulation of TBKBP1, were prioritized to be functionally relevant. CONCLUSIONS: No evidence of novel signal of association with MS specific for the Italian continental population has been found; nevertheless, two MS loci seems to play a relevant role, raising the interest to further investigations for TBKBP1 gene.

Genetics and functional genomics of multiple sclerosis.

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease with genetic predisposition. Over the last decade, genome-wide association studies with increasing sample size led to the discovery of robustly associated genetic variants at an exponential rate. More than 200 genetic loci have been associated with MS susceptibility and almost half of its heritability can be accounted for. However, many challenges and unknowns remain. Definitive studies of disease progression and endophenotypes are yet to be performed, whereas the majority of the identified MS variants are not yet functionally characterized. Despite these shortcomings, the unraveling of MS genetics has opened up a new chapter on our understanding MS causal mechanisms.

Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome.

Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4+ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.

Two genetic variants explain the association of European ancestry with multiple sclerosis risk in African-Americans.

Epidemiological studies have suggested differences in the rate of multiple sclerosis (MS) in individuals of European ancestry compared to African ancestry, motivating genetic scans to identify variants that could contribute to such patterns. In a whole-genome scan in 899 African-American cases and 1155 African-American controls, we confirm that African-Americans who inherit segments of the genome of European ancestry at a chromosome 1 locus are at increased risk for MS [logarithm of odds (LOD) = 9.8], although the signal weakens when adding an additional 406 cases, reflecting heterogeneity in the two sets of cases [logarithm of odds (LOD) = 2.7]. The association in the 899 individuals can be fully explained by two variants previously associated with MS in European ancestry individuals. These variants tag a MS susceptibility haplotype associated with decreased CD58 gene expression (odds ratio of 1.37; frequency of 84% in Europeans and 22% in West Africans for the tagging variant) as well as another haplotype near the FCRL3 gene (odds ratio of 1.07; frequency of 49% in Europeans and 8% in West Africans). Controlling for all other genetic and environmental factors, the two variants predict a 1.44-fold higher rate of MS in European-Americans compared to African-Americans.

Integrated Skin Transcriptomics and Serum Multiplex Assays Reveal Novel Mechanisms of Wound Healing in Diabetic Foot Ulcers.

Nonhealing diabetic foot ulcers (DFUs) are characterized by low-grade chronic inflammation, both locally and systemically. We prospectively followed a group of patients who either healed or developed nonhealing chronic DFUs. Serum and forearm skin analysis, both at the protein expression and the transcriptomic level, indicated that increased expression of factors such as interferon-γ (IFN-γ), vascular endothelial growth factor, and soluble vascular cell adhesion molecule-1 were associated with DFU healing. Furthermore, foot skin single-cell RNA sequencing analysis showed multiple fibroblast cell clusters and increased inflammation in the dorsal skin of patients with diabetes mellitus (DM) and DFU specimens compared with control subjects. In addition, in myeloid cell DM and DFU upstream regulator analysis, we observed inhibition of interleukin-13 and IFN-γ and dysregulation of biological processes that included cell movement of monocytes, migration of dendritic cells, and chemotaxis of antigen-presenting cells pointing to an impaired migratory profile of immune cells in DM skin. The SLCO2A1 and CYP1A1 genes, which were upregulated at the forearm of nonhealers, were mainly expressed by the vascular endothelial cell cluster almost exclusively in DFU, indicating a potential important role in wound healing. These results from integrated protein and transcriptome analyses identified individual genes and pathways that can potentially be targeted for enhancing DFU healing.

Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

Targeted resequencing reveals rare variants enrichment in multiple sclerosis susceptibility genes.

Although genome-wide association studies have identified a number of common variants associated with multiple sclerosis (MS) susceptibility, little is known about the relevance of rare variants. Here, we aimed to explore the role of rare variants in 14 MS risk genes (FCRL1, RGS1, TIMMDC1, HHEX, CXCR5, LTBR, TSFM, GALC, TRAF3, STAT3, TNFSF14, IFI30, CD40, and CYP24A1) by targeted resequencing in an Iberian population of 524 MS cases and 546 healthy controls. Four rare variants-enriched regions within CYP24A1, FCRL1, RGS1, and TRAF3 were identified as significantly associated with MS. Functional studies revealed significantly decreased regulator of G protein signaling 1 (RGS1) gene expression levels in peripheral blood mononuclear cells from MS patients with RGS1 rare variants compared to noncarriers, whereas no significant differences in gene expression were observed for CYP24A1, FCRL1, and TRAF3 between rare variants carriers and noncarriers. Immunophenotyping showed significant decrease in RGS1 expression in peripheral blood B lymphocytes from MS patients with RGS1 rare variants relative to noncarriers. Lastly, peripheral blood mononuclear cell from MS patients carrying RGS1 rare variants showed significantly lower induction of RGS1 gene expression by interferon-ß compared to MS patients lacking RGS1 variants. The presence of rare variants in RGS1 reinforce the ideas of high genetic heterogeneity and a role of rare variants in MS pathogenesis.

Genetic and gene expression signatures in multiple sclerosis.

Multiple sclerosis (MS) exhibits a well-documented increased incidence in individuals with respective family history, that is, is a heritable disease. In the last decade, genome-wide association studies have enabled the agnostic interrogation of the whole genome at a large scale. To date, over 200 genetic associations have been described at the strict level of genome-wide significance. Our current understanding of MS genetics can explain up to half of the disease's heritability, raising the important question of whether this is enough information to leverage toward improving diagnosis in MS. Parallel advancements in technologies that allow the characterization of the full transcriptome down to the single-cell level have enabled the generation of an unprecedented wealth of information. Transcriptional changes of putative causal cells could be utilized to identify early signs of disease onset. These recent findings in genetics and genomics, coupled with new technologies and deeply phenotyped cohorts, have the potential to improve the diagnosis of MS.

Mother-child histocompatibility and risk of rheumatoid arthritis and systemic lupus erythematosus among mothers.

The study objective was to test the hypothesis that having histocompatible children increases the risk of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), possibly by contributing to the persistence of fetal cells acquired during pregnancy. We conducted a case control study using data from the UC San Francisco Mother Child Immunogenetic Study and studies at the Inova Translational Medicine Institute. We imputed human leukocyte antigen (HLA) alleles and minor histocompatibility antigens (mHags). We created a variable of exposure to histocompatible children. We estimated an average sequence similarity matching (SSM) score for each mother based on discordant mother-child alleles as a measure of histocompatibility. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals. A total of 138 RA, 117 SLE, and 913 control mothers were analyzed. Increased risk of RA was associated with having any child compatible at HLA-B (OR 1.9; 1.2-3.1), DPB1 (OR 1.8; 1.2-2.6) or DQB1 (OR 1.8; 1.2-2.7). Compatibility at mHag ZAPHIR was associated with reduced risk of SLE among mothers carrying the HLA-restriction allele B*07:02 (n = 262; OR 0.4; 0.2-0.8). Our findings support the hypothesis that mother-child histocompatibility is associated with risk of RA and SLE.

Time-Dependent Changes in Microglia Transcriptional Networks Following Traumatic Brain Injury.

The neuroinflammatory response to traumatic brain injury (TBI) is critical to both neurotoxicity and neuroprotection, and has been proposed as a potentially modifiable driver of secondary injury in animal and human studies. Attempts to broadly target immune activation have been unsuccessful in improving outcomes, in part because the precise cellular and molecular mechanisms driving injury and outcome at acute, subacute, and chronic time points after TBI remain poorly defined. Microglia play a critical role in neuroinflammation and their persistent activation may contribute to long-term functional deficits. Activated microglia are characterized by morphological transformation and transcriptomic changes associated with specific inflammatory states. We analyzed the temporal course of changes in inflammatory genes of microglia isolated from injured brains at 2, 14, and 60 days after controlled cortical impact (CCI) in mice, a well-established model of focal cerebral contusion. We identified a time dependent, injury-associated change in the microglial gene expression profile toward a reduced ability to sense tissue damage, perform housekeeping, and maintain homeostasis in the early stages following CCI, with recovery and transition to a specialized inflammatory state over time. This later state starts at 14 days post-injury and is characterized by a biphasic pattern of IFNγ, IL-4, and IL-10 gene expression changes, with concurrent proinflammatory and anti-inflammatory gene changes. Our transcriptomic data sets are an important step to understand microglial role in TBI pathogenesis at the molecular level and identify common pathways that affect outcome. More studies to evaluate gene expression at the single cell level and focusing on subacute and chronic timepoint are warranted.

Loss of LDAH associated with prostate cancer and hearing loss.

Great strides in gene discovery have been made using a multitude of methods to associate phenotypes with genetic variants, but there still remains a substantial gap between observed symptoms and identified genetic defects. Herein, we use the convergence of various genetic and genomic techniques to investigate the underpinnings of a constellation of phenotypes that include prostate cancer (PCa) and sensorineural hearing loss (SNHL) in a human subject. Through interrogation of the subject's de novo, germline, balanced chromosomal translocation, we first identify a correlation between his disorders and a poorly annotated gene known as lipid droplet associated hydrolase (LDAH). Using data repositories of both germline and somatic variants, we identify convergent genomic evidence that substantiates a correlation between loss of LDAH and PCa. This correlation is validated through both in vitro and in vivo models that show loss of LDAH results in increased risk of PCa and, to a lesser extent, SNHL. By leveraging convergent evidence in emerging genomic data, we hypothesize that loss of LDAH is involved in PCa and other phenotypes observed in support of a genotype-phenotype association in an n-of-one human subject.