Investigation of familial multiple sclerosis genetics

Abstract

Multiple sclerosis (MS) is a chronic, neuroinflammatory, neurodegenerative disease of the central nervous system. Several lines of evidence have shown that the primary pathophysiological mechanism of MS is the infiltration of autoreactive lymphocytes through the blood-brain barrier, attacking central nervous system components such as myelin and resulting in oligodendrocyte death. This process has been thought to be responsible for axonal pathology and neuronal loss, which result in progressive neuronal dysfunction in some patients. Over the recent years, the roles of astrocytes, microglia, and pericytes have also been increasingly shown in MS pathology. To date, several studies have revealed disease-related cellular pathways that emphasize the different pathological components of the disease; however, underlying mechanisms in MS development and progression are yet to be elucidated. Consistently with its heterogeneous clinical presentation and complex pathophysiology, MS also has a complex inheritance pattern and develops in genetically susceptible individuals under environmental influences. Many studies have been carried out using different approaches and methods to identify genomic regions and variants that cause genetic predisposition to MS, identifying hundreds of common variants as well as candidate rare variants that increase the risk of MS. Today, MS associations of 233 common variants, as well as hundreds of suggestive associations, have been identified. However, all significant common variants, together with the suggestive effects, can cumulatively explain approximately half of MS heritability. Meta-analyses have shown that rare variants can further explain up to 5% MS heritability, still leaving a large proportion of MS genetics unknown. In this thesis study, it was aimed to reveal novel information on MS genetics and pathogenesis. Multiplex MS families with more than two affected family members were collected to identify possible novel genes that contribute to the high MS aggregation in these families. Seven multiplex MS families with the highest number of affected individuals and parental consanguinities were selected, and SNP genotyping (710K or 2.5M, Illumina) was performed (N=41). Candidate MS-associated genomic regions were identified through linkage analysis and homozygosity mapping. Exome sequencing (N=56) revealed that there were no fully penetrant, homozygous, rare, exonic variants segregating within the families. However, two variants were found to be segregated with the disease with an autosomal dominant inheritance pattern in the LRRC6 gene (rs139131485) in family FMS01 and RNF217 (rs73580047) gene in family FMS05, which may increase the risk of MS in corresponding families. Additionally, many incompletely penetrant, rare and low-frequency variants were identified. Subsequently, a weighted sum score analysis including previously identified common MS-associated risk variants and polygenic risk score (PRS) analysis were conducted in MS families (24 affected, 17 unaffected), 23 sporadic MS cases, 63 individuals in 19 non-MS control families, and 1272 independent, ancestry-matched controls to determine whether an increased burden of known MS-associated common variants explain the increased MS risk in these families. Logistic regression analyses showed that familial MS cases had higher sum scores (OR=2.16, P=0.002; OR=2.4, P=0.014) and PRS (OR=1.84, P=0.0077; OR=2.27, P=0.049) compared with the population controls and control families, respectively. Moreover, affected individuals in the MS families had higher weighted sum score and PRS values compared with the unaffected family members; however, the differences were not significant after Bonferroni correction. When individual families were observed, it was seen that the higher sum score and PRS trends in MS cases were evident in only three of the families, and in others, there were no apparent differences in the sum score and PRS values between the affected and unaffected family members or the unaffected individuals had higher sum score and PRS values compared with their relatives with MS, further supporting the polygenic inheritance of MS. Sporadic MS cases had significantly higher PRS compared with both affected and unaffected individuals in MS families, control families, and population controls (P=0.02, P=0.0055, P=0.003, and P=0.0008, respectively), supporting the presence of higher rare risk variation loading in the familial cases. There was no significant difference in the sum scores of familial and sporadic MS cases, possibly due to the high degree of convergence between common and rare risk variation in significant loci for MS. As part of this thesis study, we also performed an integrated bioinformatic analysis using genomic and proteomic data of an unrelated MS group. For this, first, SNP genotyping (300K, Illumina) was performed for 11 unrelated MS cases selected from our MS family cohort whose cerebrospinal fluid samples had been previously included in our proteomic study, in which 2D-gel electrophoresis, mass spectrophotometry, and pathway analyses had been conducted, revealing 151 differentially expressed proteins between MS cases with different clinical MS phenotypes and non-MS controls. To integrate the genomic and proteomic datasets of this patient group to reveal the most relevant disease pathways, pathway enrichment analyses of MS-associated SNPs and differentially-expressed proteins were conducted using the functional enrichment tool, PANOGA. Nine shared pathways were detected between the genomic and proteomic datasets after merging and clustering the enriched pathways. Among those, complement and coagulation cascade was the most significantly associated pathway (hsa04610, P=6.96×10−30). Other pathways involved in neurological or immunological mechanisms included adherens junctions (hsa04520, P=6.64 × 10−25), pathogenic Escherichia coli infection (hsa05130, P=9.03×10−14), and prion diseases (hsa05020, P=5.13×10−13). We conclude that despite the overall increased genetic burden in familial MS cases, weighted sum score and PRS distributions among affected and unaffected family members within individual families revealed that known susceptibility alleles can explain disease development in some high-risk multiplex families, while in others, additional genetic factors remain to be identified through more detailed genomic analyses such as genome sequencing. Additionally, integrating multiple omics datasets of the same patients helps reduce false negative and positive results of genome-wide SNP associations and highlights the most prominent cellular players among the complex pathophysiological mechanisms in MS.