Hugh Salter

Variation in interleukin 7 receptor alpha chain (IL7R) influences risk of multiple sclerosis

Multiple sclerosis is a chronic, often disabling, disease of the central nervous system affecting more than 1 in 1,000 people in most western countries. The inflammatory lesions typical of multiple sclerosis show autoimmune features and depend partly on genetic factors. Of these genetic factors, only the HLA gene complex has been repeatedly confirmed to be associated with multiple sclerosis, despite considerable efforts. Polymorphisms in a number of non-HLA genes have been reported to be associated with multiple sclerosis, but so far confirmation has been difficult. Here, we report compelling evidence that polymorphisms in IL7R, which encodes the interleukin 7 receptor α chain (IL7Rα), indeed contribute to the non-HLA genetic risk in multiple sclerosis, demonstrating a role for this pathway in the pathophysiology of this disease. In addition, we report altered expression of the genes encoding IL7Rα and its ligand, IL7, in the cerebrospinal fluid compartment of individuals with multiple sclerosis.

Multiple sclerosis: Identification and clinical evaluation of novel CSF biomarkers.

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that results in damage to myelin sheaths and axons in the central nervous system and which preferentially affects young adults. We performed a proteomics-based biomarker discovery study in which cerebrospinal fluid (CSF) from MS and control individuals was analyzed (n=112). Ten candidate biomarkers were selected for evaluation by quantitative immunoassay using an independent cohort of MS and control subjects (n=209). In relapsing-remitting MS (RRMS) patients there were significant increases in the CSF levels of alpha-1 antichymotrypsin (A1AC), alpha-1 macroglobulin (A2MG) and fibulin 1 as compared to control subjects. In secondary progressive MS (SPMS) four additional proteins (contactin 1, fetuin A, vitamin D binding protein and angiotensinogen (ANGT)) were increased as compared to control subjects. In particular, ANGT was increased 3-fold in SPMS, indicating a potential as biomarker of disease progression in MS. In PPMS, A1AC and A2MG exhibit significantly higher CSF levels than controls, with a trend of increase for ANGT. Classification models based on the biomarker panel could identify 70% of the RRMS and 80% of the SPMS patients correctly. Further evaluation was conducted in a pilot study of CSF from RRMS patients (n=36), before and after treatment with natalizumab.

Two genes encoding immune-regulatory molecules (LAG3 and IL7R) confer susceptibility to multiple sclerosis.

Multiple sclerosis (MS) is a T-cell-mediated disease of the central nervous system, characterized by damage to myelin and axons, resulting in progressive neurological disability. Genes may influence susceptibility to MS, but results of association studies are inconsistent, aside from the identification of HLA class II haplotypes. Whole-genome linkage screens in MS have both confirmed the importance of the HLA region and uncovered non-HLA loci that may harbor susceptibility genes. In this two-stage analysis, we determined genotypes, in up to 672 MS patients and 672 controls, for 123 single-nucleotide polymorphisms (SNPs) in 66 genes. Genes were chosen based on their chromosomal positions or biological functions. In stage one, 22 genes contained at least one SNP for which the carriage rate for one allele differed significantly (P<0.08) between patients and controls. After additional genotyping in stage two, two genes—each containing at least three significantly (P<0.05) associated SNPs—conferred susceptibility to MS: LAG3 on chromosome 12p13, and IL7R on 5p13. LAG3 inhibits activated T cells, while IL7R is necessary for the maturation of T and B cells. These results imply that germline allelic variation in genes involved in immune homeostasis—and, by extension, derangement of immune homeostasis—influence the risk of MS.

APOE genotypes and disease severity in multiple sclerosis.

Apolipoprotein E (apoE) is involved in the transport of lipids necessary for membrane repair and is encoded by a gene on chromosome 19q13, a region positive for linkage in two multiple sclerosis (MS) genome-wide screens. The APOE e4 allele confers susceptibility to both familial and sporadic Alzheimer’s disease (AD). Carriage of e4 is associated with defective dendritic remodeling in AD, and with unfavorable clinical outcome in head trauma and cerebrovascular disease. According to the results of previous studies, APOE e4 does not increase the risk of developing MS, but it may influence disease progression and ultimate disability. From a total cohort of over 900 MS patients, we compared APOE e2-4 genotypes in, roughly, the cohort’s least disabled and most disabled septiles. ‘Benign MS’ (n=124) was defined as an Expanded Disability Status Scale (EDSS) score of 3.0 or less, despite at least 10 years of disease duration, and ‘severe MS’ (n=140) as the attainment of an EDSS score of 6.0 within 8 years of disease onset. We found no significant differences in genotype or phenotype frequencies between the benign-MS and severe-MS septiles; however, the risk conferred by e4 rose progressively upon comparison of carriage rates in more narrowly defined anti-podal quantiles.

Correlation network analysis for data integration and biomarker selection.

High-throughput biomolecular profiling techniques such as transcriptomics, proteomics and metabolomics are increasingly being used in in vivo studies to recognize and characterize effects of xenobiotics on organs and systems. Of particular interest are biomarkers of treatment-related effects which are detectable in easily accessible biological fluids such as blood. A fundamental challenge in such biomarker studies is selecting among the plethora of biomolecular changes induced by a compound and revealed by molecular profiling, to identify biomarkers which are exclusively or predominantly due to specific processes. In this work we present a cross-compartment correlation network approach, involving no a priori supervision or design, to integrate proteomic, metabolomic and transcriptomic data for selecting circulating biomarkers. The case study we present is the identification of biomarkers of drug-induced hepatic toxicity effects in a rodent model. Biomolecular profiling of both blood plasma and liver tissue from Wistar Hannover rats administered a toxic compound yielded many hundreds of statistically significant molecular changes. We exploited drug-induced correlations between blood plasma analytes and liver tissue molecules across study animals in order to nominate selected plasma molecules as biomarkers of drug-induced hepatic alterations of lipid metabolism and urea cycle processes.

CTLA4 dimorphisms and the multiple sclerosis phenotype.

Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4), expressed on activated T cells, binds to B7 molecules on antigen-presenting cells. Signaling via CTLA-4 results in downregulation of ongoing T-cell clonal expansion. A single-nucleotide polymorphism (SNP) in exon 1 of CTLA4 is associated with susceptibility to several autoimmune diseases, including multiple sclerosis (MS). In this two-stage study, we investigated whether haplotypes composed of exon 1-SNP alleles and alleles of a promoter-region SNP influence age at onset, disease severity and disease course in MS. In stage 1, deviations in CTLA4 haplotype frequencies were observed in patients subgrouped by course; in stage 2, none of these original associations were confirmed.

Revolutionizing Alzheimer's disease and clinical trials through biomarkers

The Alzheimers Associations Research Roundtable met in May 2014 to explore recent progress in developing biomarkers to improve understanding of disease pathogenesis and expedite drug development. Although existing biomarkers have proved extremely useful for enrichment of subjects in clinical trials, there is a clear need to develop novel biomarkers that are minimally invasive and that more broadly characterize underlying pathogenic mechanisms, including neurodegeneration, neuroinflammation, and synaptic dysfunction. These may include blood‐based assays and new neuropsychological testing protocols, as well as novel ligands for positron emission tomography imaging, and advanced magnetic resonance imaging methodologies. In addition, there is a need for biomarkers that can serve as theragnostic markers of response to treatment. Standardization remains a challenge, although international consortia have made substantial progress in this area and provide lessons for future standardization efforts.

Possible allelic structure of IgG2a and IgG2c in mice

Earlier publication suggested that IgG2a and IgG2c (coding for Igh-1a and Igh-1b) are organized in tandem on the same chromosome as two distinct loci in mice. Our data suggest that IgG2a and IgG2c are not physically linked on the chromosome and are allelic - single locus in majority strains of mice. In another word, IgG2b-IgG2c-IgG2a haplotype proposed by Morgado et al. (1989) may exist in some strains of mice, but IgG2b-IgG2a and IgG2b-IgG2c are likely to be most common haplotypes in mice. Therefore, inbred mice may produce different IgG2a isotypes dependent on their origin (strain); C57B/6 and SJL mice secrete IgG2c while NMRI and DBA/2 mice secrete IgG2a only. The situation is more complicated for Swiss Webster mice (outbred) and Alzheimers disease transgenic (AD/Tg) mice with multi-genetic backgrounds; mice may secrete only IgG2a, or IgG2c, or both IgG2a and IgG2c. IgG2a and IgG2c likely have different immune profile (response, immune-decoration) in mice due to their divergence of protein sequence. If antibodies based on IgG2a (or IgG2c) are used in chronic studies for preclinical evaluation of antibody efficacy, characterization of IgG2a isotypes in advance becomes critical in the design of such biopharmaceutical projects in order to avoid immune response.

Short-time gene expression response to valproic acid and valproic acid analogs in mouse embryonic stem cells.

Prediction of developmental toxicity in vitro could be based on short-time toxicogenomic endpoints in embryo-derived cell lines. Microarray studies in P19 mouse embryocarcinoma cells and mouse embryos have indicated that valproic acid (VPA), an inducer of neural tube defects, deregulates the expression of many genes, including those critically involved in neural tube development. In this study, we exposed undifferentiated R1 mouse embryonic stem cells to VPA and VPA analogs for 6 h and used CodeLink whole-genome expression microarrays to define VPA-responsive genes correlating with teratogenicity. Compared with the nonteratogenic analog 2-ethyl-4-methylpentanoic acid, VPA and the teratogenic VPA analog (S)-2-pentyl-4-pentynoic acid deregulated a much larger number of genes. Five genes (of ∼2500 array probes correlating with the separation) were sufficient to effectively separate teratogens from nonteratogens. A large fraction of the target genes correlating with teratogenicity are functionally related to embryonic development and morphogenesis, including neural tube formation and closure. Similar responses in R1 were found for most genes previously identified as VPA responsive in P19 and embryos. A subset of target genes was evaluated as candidate markers predictive of potential teratogenicity against a range of known teratogens using TaqMan expression arrays. These marker genes showed a positive predictive value for the teratogens butyrate and trichostatin A, which like VPA and (S)-2-pentyl-4-pentynoic acid are known histone deacetylase (HDAC) inhibitors but not for compounds that are likely to act by other mechanisms. This indicates that HDAC inhibition may be a major mechanism by which VPA induces gene deregulation and possibly teratogenicity.

MONITORING THE SOLUBLE AMYLOID PRECURSOR PROTEIN ALPHA (SAPPA) AND BETA (SAPPB) FRAGMENTS IN PLASMA AND CSF FROM HEALTHY INDIVIDUALS TREATED WITH BACE INHIBITOR AZD3293 IN A MULTIPLE ASCENDING DOSE STUDY: PHARMACOKINETIC AND PHARMACODYNAMIC CORRELATE

Subjects Completing Month 12, n (%) 28(77.8) 27(73) 30(83.3) 29(78.4) Male, n (%) 13(36.1) 18(48.6) 19(52.8) 12(32.4) Mean Age (SD) 73.3(8.79) 73.5(8.34) 74.1(9.26) 70.5(8.68) ApoE *e4 Carriers, n (%) 22(61.1) 22(59.5) 22(61.1) 22(59.5) Symptomatic AD Treatment 29(80.6) 30(81.1) 34(94.4) 30(81.1) Mean Florbetapir PET GCA SUVR (SD) 1.74(0.294) 1.75(0.313) 1.87(0.299) 1.85(0.316) Mean MMSE Total Score (SD) 22.3(2.84) 22.3(2.78) 21.5(2.47) 21.9(2.99) Mean ADAS-Cog/11 Total Score (SD) 18.3(6.70) 19.6(9.47) 20.9(7.66) 18.4(8.34) Mean DAD Total Score (SD) 86.5(15.31) 81.7(17.41) 86.1(12.92) 85.2(13.25) Florbetapir PET GCA SUVR Change From Baseline at Month 12 Within-treatment LS Mean 0.000 -0.014 -0.066 -0.021 (95% CI) (-0.062, .063) (-0.078, .050) (-0.129, -0.004) (-0.084, 0.004) p-value 0.991 0.661 0.038 0.492 Florbetapir PET GCA SUVR Change From Baseline at Month 12 Between-treatment Difference of LS Means -0.015 -0.067 -0.022 (95% CI) (-0.103, 0.074) (-0.155, 0.022) (-0.109, 0.066) p-value 0.747 0.138 0.627 Poster Presentations: P1 P447