Dietary factors impact on the association between CTSS variants and obesity related traits

BACKGROUND/AIMS: Cathepsin S, a protein coded by the CTSS gene, is implicated in adipose tissue biology--this protein enhances adipose tissue development. Our hypothesis is that common variants in CTSS play a role in body weight regulation and in the development of obesity and that these effects are influenced by dietary factors--increased by high protein, glycemic index and energy diets. METHODS: Four tag SNPs (rs7511673, rs11576175, rs10888390 and rs1136774) were selected to capture all common variation in the CTSS region. Association between these four SNPs and several adiposity measurements (BMI, waist circumference, waist for given BMI and being a weight gainer-experiencing the greatest degree of unexplained annual weight gain during follow-up or not) given, where applicable, both as baseline values and gain during the study period (6-8 years) were tested in 11,091 European individuals (linear or logistic regression models). We also examined the interaction between the CTSS variants and dietary factors--energy density, protein content (in grams or in % of total energy intake) and glycemic index--on these four adiposity phenotypes. RESULTS: We found several associations between CTSS polymorphisms and anthropometric traits including baseline BMI (rs11576175 (SNP N°2), p = 0.02, β = -0.2446), and waist change over time (rs7511673 (SNP N°1), p = 0.01, β = -0.0433 and rs10888390 (SNP N°3), p = 0.04, β = -0.0342). In interaction with the percentage of proteins contained in the diet, rs11576175 (SNP N°2) was also associated with the risk of being a weight gainer (p(interaction) = 0.01, OR = 1.0526)--the risk of being a weight gainer increased with the percentage of proteins contained in the diet. CONCLUSION: CTSS variants seem to be nominally associated to obesity related traits and this association may be modified by dietary protein intake.

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.2014

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.

Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease

More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10(-16), odds ratio ≈ 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models.

Keratin variants associate with progression of fibrosis during chronic hepatitis C infection

Keratins 8 and 18 (K8/K18) protect the liver from various forms of injury. Studies of liver explants from a large cohort of U.S. patients showed that K8/K18 mutations confer a risk to developing end-stage liver diseases, though which diseases are preferentially involved is unknown. We tested the hypothesis that K8/K18 variants are associated with chronic hepatitis C (CHC) and that their presence correlates with progression of fibrosis. Genomic DNA was isolated from peripheral blood of a well-characterized German cohort of 329 patients with CHC infection. Exonic regions were PCR-amplified and analyzed using denaturing high-performance liquid chromatography and DNA sequencing. Our findings showed: (1) amino acid altering keratin heterozygous variants in 24 of 329 CHC patients (7.3%) and non-coding heterozygous variants in 26 patients (7.8%), and (2) 3 new exonic K8 variants (T26R/G55A/A359T); 6 novel non-coding variants and one K18 coding variant (K18 S230T; 2 patients). The most common variants were K8 R341H (10 patients), K8 G62C (6 patients) and K8 I63V (4 patients). A novel and exclusive association of an intronic KRT8 IVS7+10delC deletion in all 10 patients with K8 R341H was observed. Notably, there was a significant association of exonic, but not of intronic K8 variants with increased fibrosis. In conclusion, previously described and novel K8 variants are present in a German population and collectively associate with progression of fibrosis in CHC infection. The unique 100% segregation of the most common K8 variant, R341H, with an intronic deletion suggests that one of these two genetic changes might lead to the other.

Identification of potentially pathogenic variants in candidate breast and ovarian cancer susceptibility genes in BRCAX patients

Mutations within the BRCA1 and BRCA2 genes account for approximately 20% of hereditary breast cancers, with a further 10%–15% being attributable to rare mutations in moderate-risk genes and common variants in low-risk genes. The genes harbouring mutations in the remaining ∼65% of hereditary breast cancers are unknown. The identification of mutation carriers in hereditary breast and ovarian cancer (hboc) families is critical for determining who is most at risk of developing the disease and therefore who should be offered risk-reducing procedures or more intensive screening, or both.

Many of the high- and moderate-risk genes for hereditary breast cancers encode proteins that work in concert to maintain genomic stability and in dna damage signalling and repair. A novel BRCA1 protein complex identified within the research group whose target genes are involved in dna repair provided novel candidates for hboc susceptibility genes. These 12 candidate genes were sequenced in a cohort of 675 affected individuals from the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) with hereditary breast or ovarian cancer, but with no mutations in known susceptibility genes (BRCAx patients). This analysis identified 20 individuals (each from a different BRCAx family) with different potentially pathogenic variants across 6 of the candidate hboc susceptibility genes. The family members of each BRCAx index case were tested for the presence of the specific mutation identified in the proband to examine segregation with disease. To further expand on the potential role of the novel candidate hboc susceptibility genes identified in this study, the genetic variation of a second cohort of 520 Northern Irish BRCAx patients is being characterized using a 61-gene panel.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease.

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1, 2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

IL10 Low-Frequency Variants in Behçet's Disease Patients

To explain the missing heritability after the genome-wide association studies era, sequencing studies allow the identification of low-frequency variants with a stronger effect on disease risk. Common variants in the interleukin 10 gene (IL10) have been consistently associated with Behçet's disease (BD) and the goal of this study is to investigate the role of low-frequency IL10 variants in BD susceptibility.

Evaluation of novel Streptococcus pyogenes vaccine candidates incorporating multiple conserved sequences from the C-repeat region of the M-protein

A major challenge for Streptococcus pyogenes vaccine development is the identification of epitopes that confer protection from infection by multiple S. pyogenes M-types. Here we have identified and characterised the distribution of common variant sequences from individual repeat units of the C-repeat region (CRR) of M-proteins representing 77 different M-types. Three polyvalent fusion vaccine candidates (SV1, SV2 and SV3) incorporating the most common variants were subsequently expressed and purified, and demonstrated to be alpha-helical by Circular Dichroism (CD), a secondary conformational characteristic of the CRR in the M-protein. Antibodies raised against each of these constructs recognise M-proteins that vary in their CRR, and bind to the surface of multiple S. pyogenes isolates. Antibodies raised against SV1, containing five variant sequences, also kill heterologous S. pyogenes isolates in in vitro bactericidal assays. Further structural characterisation of this construct demonstrated the conformation of SV1 was stable at different pHs, and thermal unfolding of SV1 a reversible process. Our findings demonstrate that linkage of multiple variant sequences into a single recombinant construct overcomes the need to embed the variant sequences in foreign helix promoting flanking sequences for conformational stability, and demonstrates the viability of the polyvalent candidates as global S. pyogenes vaccine candidates.

Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease

Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.

Brain structure in healthy adults is related to serum transferrin and the H63D polymorphism in the HFE gene

Control of iron homeostasis is essential for healthy central nervous system function: iron deficiency is associated with cognitive impairment, yet iron overload is thought to promote neurodegenerative diseases. Specific genetic markers have been previously identified that influence levels of transferrin, the protein that transports iron throughout the body, in the blood and brain. Here, we discovered that transferrin levels are related to detectable differences in the macro- and microstructure of the living brain. We collected brain MRI scans from 615 healthy young adult twins and siblings, of whom 574 were also scanned with diffusion tensor imaging at 4 Tesla. Fiber integrity was assessed by using the diffusion tensor imaging-based measure of fractional anisotropy. In bivariate genetic models based on monozygotic and dizygotic twins, we discovered that partially overlapping additive genetic factors influenced transferrin levels and brain microstructure. We also examined common variants in genes associated with transferrin levels, TF and HFE, and found that a commonly carried polymorphism (H63D at rs1799945) in the hemochromatotic HFE gene was associated with white matter fiber integrity. This gene has a well documented association with iron overload. Our statistical maps reveal previously unknown influences of the same gene on brain microstructure and transferrin levels. This discovery may shed light on the neural mechanisms by which iron affects cognition, neurodevelopment, and neurodegeneration.

A commonly carried genetic variant in the delta opioid receptor gene, OPRD1, is associated with smaller regional brain volumes: Replication in elderly and young populations

Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.

Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N1198) using genome-wide search

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10 -6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

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.

High-throughput sequencing of IL23R reveals a low-frequency, nonsynonymous single-nucleotide polymorphism that is associated with ankylosing spondylitis in a Han Chinese population

Objective Ankylosing spondylitis (AS) is a highly heritable common inflammatory arthritis that targets the spine and sacroiliac joints of the pelvis, causing pain and stiffness and leading eventually to joint fusion. Although previous studies have shown a strong association of IL23R with AS in white Europeans, similar studies in East Asian populations have shown no association with common variants of IL23R, suggesting either that IL23R variants have no role or that rare genetic variants contribute. The present study was undertaken to screen IL23R to identify rare variants associated with AS in Han Chinese. Methods A 170-kb region containing IL23R and its flanking regions was sequenced in 50 patients with AS and 50 ethnically matched healthy control subjects from a Han Chinese population. In addition, the 30-kb region of peak association in white Europeans was sequenced in 650 patients with AS and 1,300 healthy controls. Validation genotyping was undertaken in 846 patients with AS and 1,308 healthy controls. Results We identified 1,047 variants, of which 729 were not found in the dbSNP genomic build 130. Several potentially functional rare variants in IL23R were identified, including one nonsynonomous single-nucleotide polymorphism (nsSNP), Gly149Arg (position 67421184 GA on chromosome 1). Validation genotyping showed that the Gly149Arg variant was associated with AS (odds ratio 0.61, P = 0.0054). Conclusion This is the first study to implicate rare IL23R variants in the pathogenesis of AS. The results identified a low-frequency nsSNP with predicted loss-of-function effects that was protectively associated with AS in Han Chinese, suggesting that decreased function of the interleukin-23 (IL-23) receptor protects against AS. These findings further support the notion that IL-23 signaling has an important role in the pathogenesis of AS.