Background: Dyslexia is characterized by difficulty with learning to read fluently and with accurate comprehension despite normal intelligence. It affects 5–10% of school-age children. Familial studies repeatedly showed that first-degree relatives of affected individuals have a 30–50% risk of developing the disorder. Twin studies showed that heritability was approximately 50% with a higher concordance rate for monozygotic twins compared to dizygotic twins. Although genetic factors contribute to dyslexia, very little is known on the genes associated with the condition. Preliminary data: Our project consists in the complementary analysis of (i) a cohort of 209 patients with dyslexia, 89 relatives and 95 very well phenotyped controls and (ii) an extended pedigree (Nantaise family) with 12 members diagnosed with dyslexia in three generations. For all the individuals of the project, we genotyped >600K SNPs in order to detect SNP association and copy-number variants (CNVs). For the extended pedigree, we also used linkage analysis and whole genome sequence (WGS). Our preliminary results indicate that a single region on chromosome 7q36 is segregating with dyslexia in the Nantaise family. The region is located within CNTNAP2, a gene previously proposed as a susceptibility gene, but without formal proof of its association. The WGS data of three affected and three unaffected individuals of the pedigree was performed to detect all the variants in the linkage region. Project: We proposed to use this unique resource in France to characterize the genetic profile of patients with dyslexia. We will (i) detect the CNVs present in the patients and (ii) detect the variants in the linkage region.

Chronic inflammatory diseases such as rheumatoid arthritis, inflammatory bowel disease, spondyloarthritis (SpA) and psoriasis cause significant morbidity and are a substantial burden for the affected individuals and the society. An important obstacle to early diagnosis and the development of more specific and effective therapies is the very limited understanding of the pathogenesis of these diseases. In the past years genome-wide association studies have identified many genes that were not known to be involved in pathogenesis, and have linked several genes in immune pathways to inflammatory diseases, indicating that the immune system plays an essential role in the pathogenesis of these diseases. The current challenge is to correlate these genetic variants with the effector mechanisms implicated in pathogenesis, to allow translation of the genetic data into relevant diagnostics and innovative treatment strategies. To meet this challenge, we have designed a clinical study that examines the immune signaling pathways, the transcriptional networks and the genotype in the same SpA patient, in order to establish a link between genetic variation, cellular phenotype and function, and pathology. This approach will advance our understanding of the pathogenic mechanisms, and identify novel and relevant diagnostic tools, therapeutic targets and biomarkers. The long-term outcome of this strategy will be the rational design of specific therapies tailored to the genotype of the patient.

It has been shown that methylation can act as a kind of memory of the immune system. For patients with co-infections, it is of particular importance to know when to begin an anti-retroviral therapy, especially if they are already infected with tuberculosis. The goal of this study is to find hyper or hypo methylated loci related to the reaction of HIV patients (co-infected or not) to different kind of treatments.

This project aims at identifying novel genetic traits that regulate the anti-tumor activities of NK cells and homeostasis of NK cells and other ILC using an unique mouse resource, the Collaborative Cross (CC). CC is a panel of recombinant inbred mice derived from randomized breeding of eight laboratory inbred strains combining high genetic diversity with the advantage of inbred mouse strains. We have identified CC strains that diverge in their anti-tumor immune responses and are characterizing the molecular mechanisms responsible for these differences. Ultimately, these diverse genetic traits may lead to the development of novel therapies for cancer.

Comparison of Microsatellites and Multi Locus Sequences Typing approaches. Fungi: Pneumocytis jirovecii