Association of the IL-10 gene family locus on chromosome 1 with juvenile idiopathic arthritis (JIA)

The cytokine IL-10 and its family members have been implicated in autoimmune diseases and we have previously reported that genetic variants in IL-10 were associated with a rare group of diseases called juvenile idiopathic arthritis (JIA). The aim of this study was to fine map genetic variants within the IL-10 cytokine family cluster on chromosome 1 using linkage disequilibrium (LD)-tagging single nucleotide polymorphisms (tSNPs) approach with imputation and conditional analysis to test for disease associations

Gene co-expression networks shed light into diseases of brain iron accumulation

Aberrant brain iron deposition is observed in both common and rare neurodegenerative disorders, including those categorized as Neurodegeneration with Brain Iron Accumulation (NBIA), which are characterized by focal iron accumulation in the basal ganglia. Two NBIA genes are directly involved in iron metabolism, but whether other NBIA-related genes also regulate iron homeostasis in the human brain, and whether aberrant iron deposition contributes to neurodegenerative processes remains largely unknown. This study aims to expand our understanding of these iron overload diseases and identify relationships between known NBIA genes and their main interacting partners by using a systems biology approach. We used whole-transcriptome gene expression data from human brain samples originating from 101 neuropathologically normal individuals (10 brain regions) to generate weighted gene co-expression networks and cluster the 10 known NBIA genes in an unsupervised manner. We investigated NBIA-enriched networks for relevant cell types and pathways, and whether they are disrupted by iron loading in NBIA diseased tissue and in an in vivo mouse model. We identified two basal ganglia gene co-expression modules significantly enriched for NBIA genes, which resemble neuronal and oligodendrocytic signatures. These NBIA gene networks are enriched for iron-related genes, and implicate synapse and lipid metabolism related pathways. Our data also indicates that these networks are disrupted by excessive brain iron loading. We identified multiple cell types in the origin of NBIA disorders. We also found unforeseen links between NBIA networks and iron-related processes, and demonstrate convergent pathways connecting NBIAs and phenotypically overlapping diseases. Our results are of further relevance for these diseases by providing candidates for new causative genes and possible points for therapeutic intervention

Application of a New Method for GWAS in a Related Case/Control Sample with Known Pedigree Structure: Identification of New Loci for Nephrolithiasis

In contrast to large GWA studies based on thousands of individuals and large meta-analyses combining GWAS results, we analyzed a small case/control sample for uric acid nephrolithiasis. Our cohort of closely related individuals is derived from a small, genetically isolated village in Sardinia, with well-characterized genealogical data linking the extant population up to the 16th century. It is expected that the number of risk alleles involved in complex disorders is smaller in isolated founder populations than in more diverse populations, and the power to detect association with complex traits may be increased when related, homogeneous affected individuals are selected, as they are more likely to be enriched with and share specific risk variants than are unrelated, affected individuals from the general population. When related individuals are included in an association study, correlations among relatives must be accurately taken into account to ensure validity of the results. A recently proposed association method uses an empirical genotypic covariance matrix estimated from genome-screen data to allow for additional population structure and cryptic relatedness that may not be captured by the genealogical data. We apply the method to our data, and we also investigate the properties of the method, as well as other association methods, in our highly inbred population, as previous applications were to outbred samples. The more promising regions identified in our initial study in the genetic isolate were then further investigated in an independent sample collected from the Italian population. Among the loci that showed association in this study, we observed evidence of a possible involvement of the region encompassing the gene LRRC16A, already associated to serum uric acid levels in a large meta-analysis of 14 GWAS, suggesting that this locus might lead a pathway for uric acid metabolism that may be involved in gout as well as in nephrolithiasis

A candidate regulatory variant at the TREM gene cluster associates with decreased Alzheimer's disease risk and increased TREML1 and TREM2 brain gene expression

Introduction: We hypothesized that common Alzheimer's disease (AD)-associated variants within the triggering receptor expressed on myeloid (TREM) gene cluster influence disease through gene expression. Methods: Expression microarrays on temporal cortex and cerebellum from ∼400 neuropathologically diagnosed subjects and two independent RNAseq replication cohorts were used for expression quantitative trait locus analysis. Results: A variant within a DNase hypersensitive site 5′ of TREM2, rs9357347-C, associates with reduced AD risk and increased TREML1 and TREM2 levels (uncorrected P = 6.3 × 10−3 and 4.6 × 10−2, respectively). Meta-analysis on expression quantitative trait locus results from three independent data sets (n = 1006) confirmed these associations (uncorrected P = 3.4 × 10−2 and 3.5 × 10−3, Bonferroni-corrected P = 6.7 × 10−2 and 7.1 × 10−3, respectively). Discussion: Our findings point to rs9357347 as a functional regulatory variant that contributes to a protective effect observed at the TREM locus in the International Genomics of Alzheimer's Project genome-wide association study meta-analysis and suggest concomitant increase in TREML1 and TREM2 brain levels as a potential mechanism for protection from AD

The Women's international study of long-duration oestrogen after menopause (WISDOM): a randomised controlled trial

BACKGROUND: At the time of feasibility work and final design of the trial there was no randomised control trial evidence for the long-term risks and benefits of hormone replacement therapy. Observational studies had suggested that long term use of estrogen was likely to be associated, amongst other things, with reduced risks of osteoporosis and ischaemic heart disease and increased risks of breast and endometrial cancer. Concomitant use of progestogens had been shown to protect against endometrial cancer, but there were few data showing how progestogen might affect estrogen actions on other conditions. Disease specific risks from observational studies suggested that, overall, long-term HRT was likely to be beneficial. Several studies showed that mortality from all causes was lower in HRT users than in non-users. Some secondary cardiovascular prevention trials were ongoing but evidence was also required for a range of outcomes in healthy women. The WISDOM trial was designed to compare combined estrogen and progestogen versus placebo, and estrogen alone versus combined estrogen and progestogen. During the development of WISDOM the Women's Health Initiative trial was designed, funded and started in the US. DESIGN: Randomised, placebo, controlled, trial. METHODS: The trial was set in general practices in the UK (384), Australia (94), and New Zealand (24). In these practices 284175 women aged 50–69 years were registered with 226282 potentially eligible. We sought to randomise 22300 postmenopausal women aged 50 – 69 and treat for ten years. The interventions were: conjugated equine estrogens, 0.625 mg orally daily; conjugated equine estrogens plus medroxyprogesterone acetate 2.5/5.0 mg orally daily; matched placebo. Primary outcome measures were: major cardiovascular disease, osteoporotic fractures, breast cancer and dementia. Secondary outcomes were: other cancers, all cause death, venous thromboembolism and cerebro-vascular disease. RESULTS: The trial was prematurely closed during recruitment following publication of early results from the Women's Health Initiative. At the time of closure, 56583 had been screened, 8980 entered run-in, and 5694 (26% of target of 22,300) randomised. Those women randomised had received a mean of one year of therapy, mean age was 62.8 years and total follow-up time was 6491 person years. DISCUSSION: The WISDOM experience leads to some simple messages. The larger a trial is the more simple it needs to be to ensure cost effective and timely delivery. When a trial is very costly and beyond the resources of one country, funders and investigators should make every effort to develop international collaboration with joint funding

Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively

Defining the Role of the MHC in Autoimmunity: A Review and Pooled Analysis

The major histocompatibility complex (MHC) is one of the most extensively studied regions in the human genome because of the association of variants at this locus with autoimmune, infectious, and inflammatory diseases. However, identification of causal variants within the MHC for the majority of these diseases has remained difficult due to the great variability and extensive linkage disequilibrium (LD) that exists among alleles throughout this locus, coupled with inadequate study design whereby only a limited subset of about 20 from a total of approximately 250 genes have been studied in small cohorts of predominantly European origin. We have performed a review and pooled analysis of the past 30 years of research on the role of the MHC in six genetically complex disease traits – multiple sclerosis (MS), type 1 diabetes (T1D), systemic lupus erythematosus (SLE), ulcerative colitis (UC), Crohn's disease (CD), and rheumatoid arthritis (RA) – in order to consolidate and evaluate the current literature regarding MHC genetics in these common autoimmune and inflammatory diseases. We corroborate established MHC disease associations and identify predisposing variants that previously have not been appreciated. Furthermore, we find a number of interesting commonalities and differences across diseases that implicate both general and disease-specific pathogenetic mechanisms in autoimmunity

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics

Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. / Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. / Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. / Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. / Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. / Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies