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Aggregation of multiple sclerosis genetic risk variants in multiple and single case families.

ABSTRACT: Multiple sclerosis (MS) is a multifactorial neurologic disease characterized by modest but tractable heritability. Genome-wide association studies have identified and/or validated multiple polymorphisms in approximately 16 genes associated with susceptibility. We aimed at investigating the aggregation of genetic MS risk markers in individuals by comparing multiple- and single-case families.A weighted log-additive integrative approach termed MS genetic burden (MSGB) was used to account for the well-established genetic variants from previous association studies and meta-analyses. The corresponding genetic burden and its transmission was analyzed in 1,213 independent MS families (810 sporadic and 403 multicase families).MSGB analysis demonstrated a higher aggregation of susceptibility variants in multicase compared to sporadic MS families. In addition, the aggregation of non-major histocompatibility complex single nucleotide polymorphisms depended neither on gender nor on the presence or absence of HLA-DRB1*15:01 alleles. Interestingly, although a greater MSGB in siblings of MS patients was associated with an increased risk of MS (odds ratio, 2.1; p = 0.001), receiver operating characteristic curves of MSGB differences between probands and sibs (area under the receiver operator curves, 0.57 [95% confidence interval, 0.53-0.61]) show that case-control status prediction of MS cannot be achieved with the currently available genetic data.The primary interest in the MSGB concept resides in its capacity to integrate cumulative genetic contributions to MS risk. This analysis underlines the high variability of family load with known common variants. This novel approach can be extended to other genetically complex diseases. Despite the emphasis on assembling large case-control datasets, multigenerational, multiaffected families remain an invaluable resource for advancing the understanding of the genetic architecture of complex traits.

SUBMITTER: Gourraud PA

PROVIDER: S-EPMC3511846 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Aggregation of multiple sclerosis genetic risk variants in multiple and single case families.

Gourraud Pierre-Antoine PA McElroy Joseph P JP Caillier Stacy J SJ Johnson Britt A BA Santaniello Adam A Hauser Stephen L SL Oksenberg Jorge R JR

Annals of neurology 20110101 1

<h4>Objective</h4>Multiple sclerosis (MS) is a multifactorial neurologic disease characterized by modest but tractable heritability. Genome-wide association studies have identified and/or validated multiple polymorphisms in approximately 16 genes associated with susceptibility. We aimed at investigating the aggregation of genetic MS risk markers in individuals by comparing multiple- and single-case families.<h4>Methods</h4>A weighted log-additive integrative approach termed MS genetic burden (MS ...[more]

PMID: 21280076

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Project description:BackgroundMultiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system with a well-established genetic contribution to susceptibility. Over 200 genetic regions have been linked to the inherited risk of developing MS, but the disease-causing variants and their functional effects at the molecular level are still largely unresolved. We hypothesised that MS-associated single-nucleotide polymorphisms (SNPs) affect the recognition and enzymatic cleavage of primary microRNAs (pri-miRNAs).MethodsOur study focused on 11 pri-miRNAs (9 primate-specific) that are encoded in genetic risk loci for MS. The levels of mature miRNAs and potential isoforms (isomiRs) produced from those pri-miRNAs were measured in B cells obtained from the peripheral blood of 63 MS patients and 28 healthy controls. We tested for associations between SNP genotypes and miRNA expression in cis using quantitative trait locus (cis-miR-eQTL) analyses. Genetic effects on miRNA stem-loop processing efficiency were verified using luciferase reporter assays. Potential direct miRNA target genes were identified by transcriptome profiling and computational binding site assessment.FindingsMature miRNAs and isomiRs from hsa-mir-26a-2, hsa-mir-199a-1, hsa-mir-4304, hsa-mir-4423, hsa-mir-4464 and hsa-mir-4492 could be detected in all B-cell samples. When MS patient subgroups were compared with healthy controls, a significant differential expression was observed for miRNAs from the 5' and 3' strands of hsa-mir-26a-2 and hsa-mir-199a-1. The cis-miR-eQTL analyses and reporter assays pointed to a slightly more efficient Drosha-mediated processing of hsa-mir-199a-1 when the MS risk allele T of SNP rs1005039 is present. On the other hand, the MS risk allele A of SNP rs817478, which substitutes the first C in a CNNC sequence motif, was found to cause a markedly lower efficiency in the processing of hsa-mir-4423. Overexpression of hsa-mir-199a-1 inhibited the expression of 60 protein-coding genes, including IRAK2, MIF, TNFRSF12A and TRAF1. The only target gene identified for hsa-mir-4423 was TMEM47.InterpretationWe found that MS-associated SNPs in sequence determinants of pri-miRNA processing can affect the expression of mature miRNAs. Our findings complement the existing literature on the dysregulation of miRNAs in MS. Further studies on the maturation and function of miRNAs in different cell types and tissues may help to gain a more detailed functional understanding of the genetic basis of MS.FundingThis study was funded by the Rostock University Medical Center (FORUN program, grant: 889002), Sanofi Genzyme (grant: GZ-2016-11560) and Merck Serono GmbH (Darmstadt, Germany, an affiliate of Merck KGaA, CrossRef Funder ID: 10.13039/100009945, grant: 4501860307). NB was supported by the Stiftung der Deutschen Wirtschaft (sdw) and the FAZIT foundation. EP was supported by the Landesgraduiertenförderung Mecklenburg-Vorpommern.

Dataset Information

Aggregation of multiple sclerosis genetic risk variants in multiple and single case families.

Publications

Aggregation of multiple sclerosis genetic risk variants in multiple and single case families.

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