Deriving a multi-subject functional-connectivity atlas to inform connectome estimation

MICCAI 2014 preprintInternational audienceThe estimation of functional connectivity structure from functional neuroimaging data is an important step toward understanding the mechanisms of various brain diseases and building relevant biomarkers. Yet, such inferences have to deal with the low signal-to-noise ratio and the paucity of the data. With at our disposal a steadily growing volume of publicly available neuroimaging data, it is however possible to improve the estimation procedures involved in connectome mapping. In this work, we propose a novel learning scheme for functional connectivity based on sparse Gaussian graphical models that aims at minimizing the bias induced by the regularization used in the estimation, by carefully separating the estimation of the model support from the coefficients. Moreover, our strategy makes it possible to include new data with a limited computational cost. We illustrate the physiological relevance of the learned prior, that can be identified as a functional connectivity atlas, based on an experiment on 46 subjects of the Human Connectome Dataset

Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models

International audienceCurrent theories hold that brain function is highly related with long-range physical connections through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise cortical parcella-tion based on extrinsic connectivity remains challenging. Current par-cellation methods are computationally expensive; need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity. To tackle these problems, we propose a parsimonious model for the extrinsic con-nectivity and an efficient parcellation technique based on clustering of tractograms. Our technique allows the creation of single subject and groupwise parcellations of the whole cortex. The parcellations obtained with our technique are in agreement with anatomical and functional par-cellations in the literature. In particular, the motor and sensory cortex are subdivided in agreement with the human homunculus of Penfield. We illustrate this by comparing our resulting parcels with an anatomical atlas and the motor strip mapping included in the Human Connectome Project data

GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study

Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity

The INFIR Cohort Study: investigating prediction, detection and pathogenesis of neuropathy and reactions in leprosy. Methods and baseline results of a cohort of multibacillary leprosy patients in North India

The aim of this study was to find predictors of neuropathy and reactions, determine the most sensitive methods for detecting peripheral neuropathy, study the pathogenesis of neuropathy and reactions and create a bank of specimen, backed up by detailed clinical documentation. A multi-centre cohort study of 303 multibacillary leprosy patients in Northern India was followed for 2 years. All newly registered MB patients requiring a full course of MDT, who were smear positive and/or had six or more skin lesions and/or had two or more nerve trunks involved, were eligible. A detailed history was taken and physical and neurological examinations were performed. Nerve function was assessed at each visit with nerve conduction testing, warm and cold detection thresholds, vibrometry, dynamometry, monofilaments and voluntary muscle testing. Because the latter two are widely used in leprosy clinics, they were used as ‘gold standard’ for sensory and motor impairment. Other outcome events were type 1 and 2 reactions and neuritis. All subjects had a skin biopsy at registration, repeated at the time of an outcome event, along with a skin biopsy at registration, repeated at the time of an outcome event, along with a nerve biopsy. These were examined using a variety immunohistological techniques. Blood sampling for serological testing was done at every 4-weekly clinic visit. At diagnosis, 115 patients had an outcome event of recent onset. Many people had skin lesions overlying a major nerve trunk, which were shown to be significantly associated with an increased of sensory or motor impairment. The most important adjusted odds ratios for motor impairment were, facial 4.5 (1.3-16) and ulnar 3.5 (1.0-8.5); for sensory impairment they were, ulnar 2.9 (1.3-6.5), median 3.6 (1.1-12) and posterior tibial 4.0 (1.8-8.7). Nerve enlargement was found in 94% of patients, while only 24% and 3% had paraesthesia and nerve tenderness on palpation, respectively. These increased the risk of reactions only marginally. Seven subjects had abnormal tendon reflexes and seven abnormal joint position sense. In all but one case, there impairments were accompanied by abnormalities in two or more other nerve function tests and thus seemed in indicate more serve neuropathy. At diagnosis, 38% of a cohort of newly diagnosed MB leprosy patients had recent or new reactions or nerve damage at the time of intake into the study. The main risk factor for neuropathy found in this baseline analysis was the presence of skin lesions overlying nerve trunks. They increased the risk of sensory or motor impairment in the concerned nerve by 3-4 times. For some nerves, reactional signs in the lesions further increased this risk to 6-8 times the risk for those without such lesions. Patients with skin lesions overlying peripheral nerve trunks should be carefully monitored for development of sensory or motor impairment

Mapping Brains on Grids of Features for Schizophrenia Analysis

This paper exploits the embedding provided by the countinggrid model and proposes a framework for the classification and the analysis of brain MRI images. Each brain, encoded by a count of local features, is mapped into a window on a grid of feature distributions. Similar sample are mapped in close proximity on the grid and their commonalities in their feature distributions are reflected in the overlap of windows on thegrid. Here we exploited these properties to design a novel kernel and a visualization strategy which we applied to the analysis of schizophrenic patients. Experiments report a clear improvement in classification accuracy as compared with similar methods. Moreover, our visualizations are able to highlight brain clusters and to obtain a visual interpretation of the features related to the disease