An Intergenic rs9275596 Polymorphism on Chr. 6p21 Is Associated with Multiple Sclerosis in Latvians

Background and objectives: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, leading to demyelination of neurons and potentially debilitating physical and mental symptoms. The disease is more prevalent in women than in men. The major histocompatibility complex (MHC) region has been identified as a major genetic determinant for autoimmune diseases, and its role in some neurological disorders including MS was evaluated. An intergenic single-nucleotide polymorphism (SNP), rs9275596, located between the HLA-DQB1 and HLA-DQA2 genes, is in significant association with various autoimmune diseases according to genome-wide association studies (GWASs). A cumulative effect of this SNP with other polymorphisms from this region was revealed. The aim of the study was to verify the data on rs9275596 association in multiple sclerosis in a case/control study of the Latvian population and to evaluate eventual functional significance of allele substitutions. Materials and Methods: rs9275596 (chr6:32713854; GRCh38.p12) was genotyped in 273 MS patients and 208 controls on main and sex-specific associations. Eventual functional significance of allele substitutions was evaluated in silico using publicly available tools. Results: The rs9275596 rare alleles were identified as a disease susceptibility factor in association with the MS main group and in affected females (p < 0.001 and p < 0.01, respectively). Risk factor genotypes with rare alleles included were associated with the MS common cohort (p < 0.002) and female cohort (odds ratio, OR = 2.24) and were identified as disease susceptible in males (OR = 2.41). It was shown that structural changes of rs9275596 affect the secondary structure of DNA. Functional significance of allele substitutions was evaluated on the eventual sequence affinity to transcription factors (TFs) and splicing signals similarity. A possible impact of the particular polymorphisms on the transcription and splicing efficiency is discussed. Conclusions: Our results suggest susceptibility of rs9275596 to multiple sclerosis in Latvians.

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Association analysis of juvenile idiopathic arthritis genetic susceptibility factors in Estonian patients

Clinical Rheumatology ◽

10.1007/s10067-021-05756-x ◽

2021 ◽

Author(s):

Tiit Nikopensius ◽

Priit Niibo ◽

Toomas Haller ◽

Triin Jagomägi ◽

Ülle Voog-Oras ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Juvenile Idiopathic Arthritis ◽

Autoimmune Diseases ◽

Genetic Risk ◽

Association Studies ◽

Control Sample ◽

Case Control ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition of childhood. Genetic association studies have revealed several JIA susceptibility loci with the strongest effect size observed in the human leukocyte antigen (HLA) region. Genome-wide association studies have augmented the number of JIA-associated loci, particularly for non-HLA genes. The aim of this study was to identify new associations at non-HLA loci predisposing to the risk of JIA development in Estonian patients. Methods We performed genome-wide association analyses in an entire JIA case–control sample (All-JIA) and in a case–control sample for oligoarticular JIA, the most prevalent JIA subtype. The entire cohort was genotyped using the Illumina HumanOmniExpress BeadChip arrays. After imputation, 16,583,468 variants were analyzed in 263 cases and 6956 controls. Results We demonstrated nominal evidence of association for 12 novel non-HLA loci not previously implicated in JIA predisposition. We replicated known JIA associations in CLEC16A and VCTN1 regions in the oligoarticular JIA sample. The strongest associations in the All-JIA analysis were identified at PRKG1 (P = 2,54 × 10−6), LTBP1 (P = 9,45 × 10−6), and ELMO1 (P = 1,05 × 10−5). In the oligoarticular JIA analysis, the strongest associations were identified at NFIA (P = 5,05 × 10−6), LTBP1 (P = 9,95 × 10−6), MX1 (P = 1,65 × 10−5), and CD200R1 (P = 2,59 × 10−5). Conclusion This study increases the number of known JIA risk loci and provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis. The reported loci are involved in molecular pathways of immunological relevance and likely represent genomic regions that confer susceptibility to JIA in Estonian patients. Key Points• Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease with heterogeneous presentation and genetic predisposition.• Present genome-wide association study for Estonian JIA patients is first of its kind in Northern and Northeastern Europe.• The results of the present study increase the knowledge about JIA risk loci replicating some previously described associations, so adding weight to their relevance and describing novel loci.• The study provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis.

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The Genetic Basis of Hypertriglyceridemia

Current Atherosclerosis Reports ◽

10.1007/s11883-021-00939-y ◽

2021 ◽

Vol 23 (8) ◽

Author(s):

Germán D. Carrasquilla ◽

Malene Revsbech Christiansen ◽

Tuomas O. Kilpeläinen

Keyword(s):

Genetic Basis ◽

Association Studies ◽

Cumulative Effect ◽

Genome Wide Association Studies ◽

Genetic Loci ◽

Risk Variants ◽

Genome Wide ◽

Severe Hypertriglyceridemia ◽

Increased Risk ◽

Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

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Functional genomics of autoimmune diseases

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2019-216794 ◽

2021 ◽

pp. annrheumdis-2019-216794

Author(s):

Akari Suzuki ◽

Matteo Maurizio Guerrini ◽

Kazuhiko Yamamoto

Keyword(s):

Autoimmune Diseases ◽

Association Studies ◽

Linkage Disequilibrium Block ◽

Causal Variant ◽

Genome Wide Association Studies ◽

Coding Region ◽

Risk Variants ◽

Non Coding Rna ◽

Genome Wide ◽

Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

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Host Genetics and Gut Microbiome: Perspectives for Multiple Sclerosis

Genes ◽

10.3390/genes12081181 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1181

Author(s):

Alessandro Maglione ◽

Miriam Zuccalà ◽

Martina Tosi ◽

Marinella Clerico ◽

Simona Rolla

Keyword(s):

Multiple Sclerosis ◽

Environmental Factors ◽

Lupus Erythematosus ◽

Gut Microbiome ◽

Complex Disease ◽

Current Knowledge ◽

Association Studies ◽

Future Research ◽

Genome Wide Association Studies ◽

Host Genetics

As a complex disease, Multiple Sclerosis (MS)’s etiology is determined by both genetic and environmental factors. In the last decade, the gut microbiome has emerged as an important environmental factor, but its interaction with host genetics is still unknown. In this review, we focus on these dual aspects of MS pathogenesis: we describe the current knowledge on genetic factors related to MS, based on genome-wide association studies, and then illustrate the interactions between the immune system, gut microbiome and central nervous system in MS, summarizing the evidence available from Experimental Autoimmune Encephalomyelitis mouse models and studies in patients. Finally, as the understanding of influence of host genetics on the gut microbiome composition in MS is in its infancy, we explore this issue based on the evidence currently available from other autoimmune diseases that share with MS the interplay of genetic with environmental factors (Inflammatory Bowel Disease, Rheumatoid Arthritis and Systemic Lupus Erythematosus), and discuss avenues for future research.

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Application of Genetic Studies to Flow Cytometry Data and Its Impact on Therapeutic Intervention for Autoimmune Disease

Frontiers in Immunology ◽

10.3389/fimmu.2021.714461 ◽

2021 ◽

Vol 12 ◽

Author(s):

Valeria Orrù ◽

Maristella Steri ◽

Francesco Cucca ◽

Edoardo Fiorillo

Keyword(s):

Flow Cytometry ◽

Autoimmune Disease ◽

Autoimmune Diseases ◽

Immune Cell ◽

Disease Risk ◽

Association Studies ◽

Large Fraction ◽

Surface Protein ◽

Genome Wide Association Studies ◽

Human Immune System

In recent years, systematic genome-wide association studies of quantitative immune cell traits, represented by circulating levels of cell subtypes established by flow cytometry, have revealed numerous association signals, a large fraction of which overlap perfectly with genetic signals associated with autoimmune diseases. By identifying further overlaps with association signals influencing gene expression and cell surface protein levels, it has also been possible, in several cases, to identify causal genes and infer candidate proteins affecting immune cell traits linked to autoimmune disease risk. Overall, these results provide a more detailed picture of how genetic variation affects the human immune system and autoimmune disease risk. They also highlight druggable proteins in the pathogenesis of autoimmune diseases; predict the efficacy and side effects of existing therapies; provide new indications for use for some of them; and optimize the research and development of new, more effective and safer treatments for autoimmune diseases. Here we review the genetic-driven approach that couples systematic multi-parametric flow cytometry with high-resolution genetics and transcriptomics to identify endophenotypes of autoimmune diseases for the development of new therapies.

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Genetic variants and magnetic resonance imaging measures in multiple sclerosis: a systematic review

Journal of Medical Science ◽

10.20883/182 ◽

2016 ◽

Vol 85 (4) ◽

pp. 311

Author(s):

Jan Krzysztof Nowak ◽

Izabela Guzikowska-Ruszkowska ◽

Jadwiga Łopaciuch ◽

Wiesława Jankowska ◽

Ewa Piotrowska ◽

...

Keyword(s):

Multiple Sclerosis ◽

Systematic Review ◽

Magnetic Resonance ◽

Mr Imaging ◽

Genetic Variants ◽

Brain Atrophy ◽

Association Studies ◽

Genome Wide Association Studies ◽

Lesion Load ◽

The Relationship

Introduction. Although environmental factors play the major role in the etiopathogenesis of multiple sclerosis (MS), genetic factors are implicated as well. We aimed to summarize the current knowledge on the relationship between genetic variants and magnetic resonance (MR) imaging measures in MS.Material and Methods. A systematic review. In December 2016, Scopus (since the year 1980; including MEDLINE) was searched for studies meeting predefined criteria designed to identify articles regarding: multiple sclerosis, genetic variants, and MR imaging. These were then analyzed to identify publications linking polymorphisms and MR findings.Results. The search yielded 290 items; 26 were included in the final analysis. Two genome‑wide association studies (GWAS) and two projects employing panels of a few dozen of genes of interest provided most of the data. The other publications concerned no more than 5 genes at a time. Twenty studies reported positive findings. The relationship between HLA‑DRB1*15:01 or BDNF rs6265 (Val66Met) and the radiologic course of MS was not consistent across the studies. An intersection of the results of the two GWAS yielded: OPCML (rs11223055), PTPRD (rs1953594), and WWOX (rs11150140, rs1116525) (brain atrophy) as well as CDH13 (rs692612) and PLCB1 (rs6118257) (lesion load).Conclusions. Genetic variants were shown to correlate with MS‑related brain atrophy and lesion load. Further research in the field is required.

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What is Next for the Genetics of Multiple Sclerosis?

Autoimmune Diseases ◽

10.4061/2011/519450 ◽

2011 ◽

Vol 2011 ◽

pp. 1-3 ◽

Cited By ~ 4

Author(s):

Sreeram V. Ramagopalan ◽

David A. Dyment

Keyword(s):

Multiple Sclerosis ◽

Genetic Risk ◽

Neurological Disease ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

New Genes ◽

Histocompatibility Complex ◽

Genome Wide ◽

The Common

We review here our current understanding of the genetic aetiology of the common complex neurological disease multiple sclerosis (MS). The strongest genetic risk factor for MS is the major histocompatibility complex which was identified in the 1970s. In 2011, after a number of genome-wide association studies have been completed and have identified approximately 20 new genes for MS, we ask the question—what is next for the genetics of MS?

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Association of SNPs rs6498169 and rs10984447 with multiple sclerosis in Saudi patients: a model of the usefulness of familial aggregates in identifying genetic linkage in a multifactorial disease

Multiple Sclerosis Journal ◽

10.1177/1352458512440832 ◽

2012 ◽

Vol 18 (10) ◽

pp. 1395-1400 ◽

Cited By ~ 6

Author(s):

M Al Jumah ◽

M Al Balwi ◽

M Hussein ◽

S Kojan ◽

A Al Khathaami ◽

...

Keyword(s):

Multiple Sclerosis ◽

Association Studies ◽

Study Groups ◽

Genome Wide Association Studies ◽

Genotype Distribution ◽

Independent Control ◽

Control Groups ◽

Genome Wide ◽

Genetic Pool ◽

Multiple Sclerosis Patients

Objective: Genome-Wide association studies (GWAS) showed an association between subset of single-nucleotide polymorphism (SNPs) and multiple sclerosis. Our study aims to study this association in Saudi familial multiple sclerosis patients. Methods: Four subject groups were used in this study: sporadic MS (MS patients without family history), FMS (MS patients who have at least one family member diagnosed with MS), related controls (relatives of FMS patients who appear to be free of the disease) and independent controls (healthy volunteers). Subjects were genotyped for 15 SNPs. The variation in the genotype distribution was analyzed across study groups by using logistic regression. Results: 342 subjects were included. 99 were in the sporadic MS group, 22 were FMS, 89 were related control, and 132 were independent control. SNPS rs3135388, rs7577363, rs1321172, rs6897932, rs6498169, rs12487066, and rs4763655were associated with MS when MS and independent control groups were compared. Same SNPS were identified but with stronger association when the FMS and independent control groups were compared. Finally, when the patients and the controls were selected from a much more homogenous genetic pool from which it would be expected that only SNPs highly linked to MS would persist, only two SNPs rs6498169[OR 4.26, CI (1.17 – 15.51)];, and rs10984447 [OR 13.63, CI(1.54, 120.83) ][were associated with MS. Conclusions: Our results suggest that using a more homogenous genetic pool of cases and controls could help to identify the most significant MS-associated SNPs. Our finding is in agreement with other studies including larger sample size and more diverse populations.

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Genome-Wide Association Studies Suggest Limited Immune Gene Enrichment in Schizophrenia Compared to 5 Autoimmune Diseases

Schizophrenia Bulletin ◽

10.1093/schbul/sbw059 ◽

2016 ◽

Vol 42 (5) ◽

pp. 1176-1184 ◽

Cited By ~ 34

Author(s):

Jennie G. Pouget ◽

Vanessa F. Gonçalves ◽

Sarah L. Spain ◽

Hilary K. Finucane ◽

Soumya Raychaudhuri ◽

...

Keyword(s):

Autoimmune Diseases ◽

Association Studies ◽

Genome Wide Association ◽

Immune Gene ◽

Genome Wide Association Studies ◽

Gene Enrichment ◽

Genome Wide

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Capturing SNP Association across the NK Receptor and HLA Gene Regions in Multiple Sclerosis by Targeted Penalised Regression Models

Genes ◽

10.3390/genes13010087 ◽

2021 ◽

Vol 13 (1) ◽

pp. 87

Author(s):

Sean M. Burnard ◽

Rodney A. Lea ◽

Miles Benton ◽

David Eccles ◽

Daniel W. Kennedy ◽

...

Keyword(s):

Multiple Sclerosis ◽

Complex Traits ◽

Multiple Testing ◽

Large Scale ◽

Disease Risk ◽

Association Studies ◽

Meta Analysis ◽

Elastic Net ◽

Genome Wide Association Studies ◽

Multiple Testing Correction

Conventional genome-wide association studies (GWASs) of complex traits, such as Multiple Sclerosis (MS), are reliant on per-SNP p-values and are therefore heavily burdened by multiple testing correction. Thus, in order to detect more subtle alterations, ever increasing sample sizes are required, while ignoring potentially valuable information that is readily available in existing datasets. To overcome this, we used penalised regression incorporating elastic net with a stability selection method by iterative subsampling to detect the potential interaction of loci with MS risk. Through re-analysis of the ANZgene dataset (1617 cases and 1988 controls) and an IMSGC dataset as a replication cohort (1313 cases and 1458 controls), we identified new association signals for MS predisposition, including SNPs above and below conventional significance thresholds while targeting two natural killer receptor loci and the well-established HLA loci. For example, rs2844482 (98.1% iterations), otherwise ignored by conventional statistics (p = 0.673) in the same dataset, was independently strongly associated with MS in another GWAS that required more than 40 times the number of cases (~45 K). Further comparison of our hits to those present in a large-scale meta-analysis, confirmed that the majority of SNPs identified by the elastic net model reached conventional statistical GWAS thresholds (p < 5 × 10−8) in this much larger dataset. Moreover, we found that gene variants involved in oxidative stress, in addition to innate immunity, were associated with MS. Overall, this study highlights the benefit of using more advanced statistical methods to (re-)analyse subtle genetic variation among loci that have a biological basis for their contribution to disease risk.

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