Power estimation for non-standardized multisite studies

AbstractA concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions

Genome-wide significant association with seven novel multiple sclerosis risk loci

Objective: A recent large-scale study in multiple sclerosis (MS) using the ImmunoChip platform reported on 11 loci that showed suggestive genetic association with MS. Additional data in sufficiently sized and independent data sets are needed to assess whether these loci represent genuine MS risk factors. Methods: The lead SNPs of all 11 loci were genotyped in 10 796 MS cases and 10 793 controls from Germany, Spain, France, the Netherlands, Austria and Russia, that were independent from the previously reported cohorts. Association analyses were performed using logistic regression based on an additive model. Summary effect size estimates were calculated using fixed-effect meta-analysis. Results: Seven of the 11 tested SNPs showed significant association with MS susceptibility in the 21 589 individuals analysed here. Meta-analysis across our and previously published MS case-control data (total sample size n=101 683) revealed novel genome-wide significant association with MS susceptibility (p<5×10−8) for all seven variants. This included SNPs in or near LOC100506457 (rs1534422, p=4.03×10−12), CD28 (rs6435203, p=1.35×10−9), LPP (rs4686953, p=3.35×10−8), ETS1 (rs3809006, p=7.74×10−9), DLEU1 (rs806349, p=8.14×10−12), LPIN3 (rs6072343, p=7.16×10−12) and IFNGR2 (rs9808753, p=4.40×10−10). Cis expression quantitative locus effects were observed in silico for rs6435203 on CD28 and for rs9808753 on several immunologically relevant genes in the IFNGR2 locus. Conclusions: This study adds seven loci to the list of genuine MS genetic risk factors and further extends the list of established loci shared across autoimmune diseases

Genome-wide significant association with seven novel multiple sclerosis risk loci

Objective: A recent large-scale study in multiple sclerosis (MS) using the ImmunoChip platform reported on 11 loci that showed suggestive genetic association with MS. Additional data in sufficiently sized and independent data sets are needed to assess whether these loci represent genuine MS risk factors. Methods: The lead SNPs of all 11 loci were genotyped in 10 796 MS cases and 10 793 controls from Germany, Spain, France, the Netherlands, Austria and Russia, that were independent from the previously reported cohorts. Association analyses were performed using logistic regression based on an additive model. Summary effect size estimates were calculated using fixed-effect meta-analysis. Results: Seven of the 11 tested SNPs showed significant association with MS susceptibility in the 21 589 individuals analysed here. Meta-analysis across our and previously published MS case-control data (total sample size n=101 683) revealed novel genome-wide significant association with MS susceptibility (p<5×10−8) for all seven variants. This included SNPs in or near LOC100506457 (rs1534422, p=4.03×10−12), CD28 (rs6435203, p=1.35×10−9), LPP (rs4686953, p=3.35×10−8), ETS1 (rs3809006, p=7.74×10−9), DLEU1 (rs806349, p=8.14×10−12), LPIN3 (rs6072343, p=7.16×10−12) and IFNGR2 (rs9808753, p=4.40×10−10). Cis expression quantitative locus effects were observed in silico for rs6435203 on CD28 and for rs9808753 on several immunologically relevant genes in the IFNGR2 locus. Conclusions: This study adds seven loci to the list of genuine MS genetic risk factors and further extends the list of established loci shared across autoimmune diseases

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Genome-Wide Association Study Identifies Novel Restless Legs Syndrome Susceptibility Loci on 2p14 and 16q12.1

Peer reviewe

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Multiple sclerosis is a complex neurological disease, with 3c20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFN\u3b3 biology, and NF\u3baB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS. In a large multi-cohort study, unexplained heritability for multiple sclerosis is detected in low-frequency coding variants that are missed by GWAS analyses, further underscoring the role of immune genes in MS pathology

Génétique de la sclérose en plaques (criblage anonyme du génome et gènes candidats)

PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Hereditary Spastic Paraplegia SPG13 Is Associated with a Mutation in the Gene Encoding the Mitochondrial Chaperonin Hsp60

SPG13, an autosomal dominant form of pure hereditary spastic paraplegia, was recently mapped to chromosome 2q24-34 in a French family. Here we present genetic data indicating that SPG13 is associated with a mutation, in the gene encoding the human mitochondrial chaperonin Hsp60, that results in the V72I substitution. A complementation assay showed that wild-type HSP60 (also known as “HSPD1”), but not HSP60 (V72I), together with the co-chaperonin HSP10 (also known as “HSPE1”), can support growth of Escherichia coli cells in which the homologous chromosomal groESgroEL chaperonin genes have been deleted. Taken together, our data strongly indicate that the V72I variation is the first disease-causing mutation that has been identified in HSP60

Genetic interaction of CTLA-4 with HLA-DR15 in multiple sclerosis patients

Multiple sclerosis is a chronic inflammatory disease of the central nervous system with a genetic component. Until now, the more consistent association with the disease is found with the major histocompatibility complex, especially HLA-DRB1*1501-DQB1*0602 haplotype. In this report, we demonstrate the interaction of Cytotoxic T Lymphocyte-associated antigen 4 (CTLA-4 [CD152]) gene with DRB1*15 haplotype in multiple sclerosis genetic susceptibility. Our data were obtained from two European independent family-based studies including 610 multiple sclerosis family trios. Ann Neurol 2003;54:119-122Fondation pour la Recherche Médicale (ARS 2.09 Bertrand Fontaine), by Association pour la Recherche sur la Sclérose en Plaques, by Italian Foundation for Multiple Sclerosis, by INSERM, and by the French Ministry of Research (Centre d'Investigations Cliniques Pitié‐Salpétrière and Centre de Resources Biologiques