Genetics of anisotropy asymmetry: Registration and sample size effects

Brain asymmetry has been a topic of interest for neuroscientists for many years. The advent of diffusion tensor imaging (DTI) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. Even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. We fluidly registered 4 Tesla DTI scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. We computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (FA, GA). Quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. We studied how these heritability estimates varied with the type of registration target (T1- or T2-weighted) and with sample size. All methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.

Genetics of path lengths in brain connectivity networks: HARDI-based maps in 457 adults

Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length is purely topological, and does not take into account the physical length of the connections. The distance of the trajectory may also be highly relevant, but is typically overlooked in connectivity analyses. Here we combined genotyping, anatomical MRI and HARDI to understand how our genes influence the cortical connections, using whole-brain tractography. We defined a new measure, based on Dijkstra's algorithm, to compute path lengths for tracts connecting pairs of cortical regions. We compiled these measures into matrices where elements represent the physical distance traveled along tracts. We then analyzed a large cohort of healthy twins and show that our path length measure is reliable, heritable, and influenced even in young adults by the Alzheimer's risk gene, CLU.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

The multivariate A/C/E model and the genetics of fiber architecture

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

The ENIGMA Consortium: Large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

Non-major-histocompatibility-complex genetics of ankylosing spondylitis

There is strong evidence from twin and family studies indicating that a substantial proportion of the heritability of susceptibility to ankylosing spondylitis (AS) and its clinical manifestations is encoded by non-major-histocompatibility-complex genes. Efforts to identify these genes have included genomewide linkage studies and candidate gene association studies. One region, the interleukin (IL)-1 gene complex on chromosome 2, has been repeatedly associated with AS in both Caucasians and Asians. It is likely that more than one gene in this complex is involved in AS, with the strongest evidence to date implicating IL-1A. Identifying the genes underlying other linkage regions has been difficult due to the lack of obvious candidates and the low power of most studies to date to identify genes of the small to moderate magnitude that are likely to be involved. The field is moving towards genomewide association analysis, involving much larger datasets of unrelated cases and controls. Early successes using this approach in other diseases indicates that it is likely to identify genes in common diseases like AS, but there remains the risk that the common-variant, common-disease hypothesis will not hold true in AS. Nonetheless, it is appropriate for the field to be cautiously optimistic that the next few years will bring great advances in our understanding of the genetics of this condition.

Progress in the genetics of ankylosing spondylitis

Ankylosing spondylitis (AS) is a common, highly heritable, inflammatory arthropathy. In addition to being strongly associated with HLA-B27, a further 13 genes have been robustly associated with the disease. These genes highlight the involvement of the IL-23 pathway in disease pathogenesis, and indicate overlaps between the pathogenesis of AS, and of inflammatory bowel disease. Genetic associations in B27-positive and -negative disease are similar, with the main exception of association with ERAP1, which is restricted in association to B27-positive cases. This restriction, and the known function of ERAP1 in peptide trimming prior to HLA Class I presentation, indicates that HLA-B27 is likely to operate in AS by a mechanism involving aberrant peptide handling. These advances point to several potential novel therapeutic approaches in AS.

Genetics of ankylosing spondylitis

Ankylosing spondylitis is a common inflammatory rheumatic disease. Both susceptibility to and clinical manifestations of the disease are highly heritable. Although some genes, notably HLA-B27, have been implicated in susceptibility to the disease, the genetics of the condition are complex and many more genes involved in the condition await discovery.

Genetics of ankylosing spondylitis and rheumatoid arthritis: Where are we at currently, and how do they compare?

Both ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are common, highly heritable conditions, the pathogenesis of which are incompletely understood. Gene-mapping studies in both conditions have over the last couple of years made major breakthroughs in identifying the mechanisms by which these diseases occur. Considering RA, there is an over-representation of genes involved in TNF signalling and the NFκB pathway that have been shown to influence the disease risk. There is also considerable sharing of susceptibility genes between RA and other autoimmune diseases such as systemic lupus erythematosus, type 1 diabetes, autoimmune thyroid disease and celiac disease, with thus far little overlap with AS. In AS, genes involved in response to IL12/IL23, and in endoplasmic reticulum peptide presentation, have been identified, but a full genomewide association study has not yet been reported.

The genetics of osteoporosis: Future diagnostic possibilities

The risk of developing osteoporosis is determined by the interaction of several mostly unknown genes and environmental factors. Genetic studies in osteoporosis have largely focussed on association studies of a small number of candidate genes, with few linkage studies performed, and large areas of the genome remaining unexplored. Identifying the genes involved in osteoporosis would be a major advance in our understanding of the causation of the disease, and lead to advances in diagnosis, risk prediction, and potentially preventive and therapeutic measures.

Genetics and the pathogenesis of ankylosing spondylitis

Purpose of review The field of genetic research in ankylosing spondylitis (AS) is advancing rapidly. The purpose of this review is to outline recent findings, particularly, in regard to genetic studies of the major histocompatibility complex (MHC) and the non-MHC genes IL23R, ERAP1, and killer cell immunologlobulin-like receptor (KIR) complex, in AS. Recent findings: Convincing evidence has been reported for the existence of further non-B27 MHC genes involved in AS. Strong, replicated association has been reported with IL23R and ERAP1 and AS. The IL23R finding strongly implicates the TH17 lymphocyte system in AS aetiopathogenesis. Suggestive evidence of a role for KIR gene polymorphism in AS exists, but definitive findings are awaited. Summary: The findings suggest that further genome-wide studies in large case-control cohorts are likely to be very productive in this disease. The IL23R findings and subsequent immunological investigations suggest that targeted intervention in the TH17 system is likely to have major therapeutic benefit, as it does in the genetically related diseases, inflammatory bowel disease and psoriasis.

Genetics of ankylosing spondylitis

Purpose of Review Over the past 3 years, several new genes and gene deserts have been identified that are associated with ankylosing spondylitis (AS). The purpose of this review is to discuss the major findings of these studies, and the answers they provide and questions they raise about the pathogenesis of this common condition. Recent Findings: Five genes/genetic regions have now definitively been associated with AS [the major histocompatibility complex (MHC), IL23R, ERAP1, 2p15 and 21q22]. Strong evidence to support association with the disease has been demonstrated for the genes IL1R2, ANTXR2, TNFSF15, TNFR1 and a region on chromosome 16q including the gene TRADD. There is an overrepresentation of genes involved in Th17 lymphocyte differentiation/activation among genes associated with AS and the related diseases inflammatory bowel disease and psoriasis, pointing strongly to this pathway as playing a major causative role in the disease. Increasing information about differential association of HLA-B27 subtypes with disease suggests a hierarchy of strength of association of those alleles with AS, providing a useful test as to the validity of different potential mechanisms of association of HLA-B27 with AS. The mechanism underlying the association of the gene deserts, 2p15 and 21q22, suggests the involvement of noncoding RNA in AS etiopathogenesis. Summary: The increasing list of genes identified as being definitely involved in AS provides a useful platform for hypothesis-driven research in the field, providing a potential alternative route to determining the underlying mechanisms involved in the disease to research focusing on HLA-B27 alone.

Genetic aspects of susceptibility, severity, and clinical expression in ankylosing spondylitis

While twin studies have previously demonstrated high heritability of susceptibility to ankylosing spondylitis (AS), it is only recently that the involvement of genetic factors in determining the severity of the disease has been demonstrated. The genes involved in determining the rate of ankylosis in AS are likely to be different from those involved in the underlying immunologic events, and represent important potential targets for treatment of AS. This article will describe the progress that has been made in the genetic epidemiology of AS, and in identifying the genes involved.

Genetics of ankylosing spondylitis

Ankylosing spondylitis (AS) is a chronic inflammatory arthritis that affects the spine and sacroiliac joints. It causes significant disability and is associated with a number of other features including peripheral arthritis, anterior uveitis, psoriasis and inflammatory bowel disease (IBD). Significant progress has been made in the genetics of AS have in the last five years, leading to new treatments in trial, and major leaps in understanding of the aetiopathogenesis of the disease.