A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

Genome wide analysis of gene expression changes in skin from patients with type 2 diabetes

Non-healing chronic ulcers are a serious complication of diabetes and are a major healthcare problem. While a host of treatments have been explored to heal or prevent these ulcers from forming, these treatments have not been found to be consistently effective in clinical trials. An understanding of the changes in gene expression in the skin of diabetic patients may provide insight into the processes and mechanisms that precede the formation of non-healing ulcers. In this study, we investigated genome wide changes in gene expression in skin between patients with type 2 diabetes and non-diabetic patients using next generation sequencing. We compared the gene expression in skin samples taken from 27 patients (13 with type 2 diabetes and 14 non-diabetic). This information may be useful in identifying the causal factors and potential therapeutic targets for the prevention and treatment of diabetic related diseases

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesOver the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) <1.15).We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls).We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P = 9 × 10(-6)). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a 'neurodevelopmental hub' on chromosome 8p11.23.This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4.National Institutes of Mental Health (NIMH, USA) ACE Network Autism Genetic Resource Exchange (AGRE) is a program of Autism Speaks (USA) The Autism Genome Project (AGP) from Autism Speaks (USA) Canadian Institutes of Health Research (CIHR), Genome Canada Health Research Board (Ireland) Hilibrand Foundation (USA) Medical Research Council (UK) National Institutes of Health (USA) Ontario Genomics Institute University of Toronto McLaughlin Centre Simons Foundation Johns Hopkins Autism Consortium of Boston NLM Family foundation National Institute of Health grants National Health Medical Research Council Scottish Rite Spunk Fund, Inc. Rebecca and Solomon Baker Fund APEX Foundation National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) endowment fund of the Nancy Pritzker Laboratory (Stanford) Autism Society of America Janet M. Grace Pervasive Developmental Disorders Fund The Lundbeck Foundation universities and university hospitals of Aarhus and Copenhagen Stanley Foundation Centers for Disease Control and Prevention (CDC) Netherlands Scientific Organization Dutch Brain Foundation VU University Amsterdam Trinity Centre for High Performance Computing through Science Foundation Ireland Autism Genome Project (AGP) from Autism Speak

Genome-wide association reveals genetic effects on human Aβ₄₂and τ protein levels in cerebrospinal fluids: a case control study

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease (AD) is common and highly heritable with many genes and gene variants associated with AD in one or more studies, including APOE ε2/ε3/ε4. However, the genetic backgrounds for normal cognition, mild cognitive impairment (MCI) and AD in terms of changes in cerebrospinal fluid (CSF) levels of Aβ_1-42, T-tau, and P-tau_181P, have not been clearly delineated. We carried out a genome-wide association study (GWAS) in order to better define the genetic backgrounds to these three states in relation to CSF levels.</p> <p>Methods</p> <p>Subjects were participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). The GWAS dataset consisted of 818 participants (mainly Caucasian) genotyped using the Illumina Human Genome 610 Quad BeadChips. This sample included 410 subjects (119 Normal, 115 MCI and 176 AD) with measurements of CSF Aβ_1-42, T-tau, and P-tau_181PLevels. We used PLINK to find genetic associations with the three CSF biomarker levels. Association of each of the 498,205 SNPs was tested using additive, dominant, and general association models while considering APOE genotype and age. Finally, an effort was made to better identify relevant biochemical pathways for associated genes using the ALIGATOR software.</p> <p>Results</p> <p>We found that there were some associations with APOE genotype although CSF levels were about the same for each subject group; CSF Aβ_1-42levels decreased with APOE gene dose for each subject group. T-tau levels tended to be higher among AD cases than among normal subjects. From adjusted result using APOE genotype and age as covariates, no SNP was associated with CSF levels among AD subjects. <it>CYP19A1 </it>'aromatase' (rs2899472), <it>NCAM2</it>, and multiple SNPs located on chromosome 10 near the <it>ARL5B </it>gene demonstrated the strongest associations with Aβ_1-42in normal subjects. Two genes found to be near the top SNPs, <it>CYP19A1 </it>(rs2899472, p = 1.90 × 10^-7) and <it>NCAM2 </it>(rs1022442, p = 2.75 × 10^-7) have been reported as genetic factors related to the progression of AD from previous studies. In AD subjects, APOE ε2/ε3 and ε2/ε4 genotypes were associated with elevated T-tau levels and ε4/ε4 genotype was associated with elevated T-tau and P-tau_181Plevels. Pathway analysis detected several biological pathways implicated in Normal with CSF β-amyloid peptide (Aβ_1-42).</p> <p>Conclusions</p> <p>Our genome-wide association analysis identified several SNPs as important factors for CSF biomarker. We also provide new evidence for additional candidate genetic risk factors from pathway analysis that can be tested in further studies.</p

Evaluating enhanced recovery after surgery: time to cover new ground and discover the missing patient voice

Multicomponent peri-operative interventions offer to accelerate patient recovery and improve cost-effectiveness. The recent National Institute of Health Research-commissioned evidence synthesis review by Nunns et al. considers the effectiveness and cost-effectiveness of all types of multicomponent interventions for older adults undergoing elective inpatient surgery. Enhanced recovery programmes (ERPs) were the most commonly evaluated intervention. An association between ERPs and decreased length of stay was observed, whilst complication rates and time to recovery were static or sometimes reduced. Important areas which lack research in the context of ERPs are patient-reported outcome measures, patients with complex needs and assessment of factors pertaining to successful ERP implementation. The next generation of ERP studies should seek to develop our understanding in these key areas

Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders

Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways

Multicomponent hospital-led interventions to reduce hospital stay for older adults following elective surgery: a systematic review

BackgroundElective older adult inpatient admissions are increasingly common. Older adults are at an elevated risk of adverse events in hospital, potentially increasing with lengthier hospital stay. Hospital-led organisational strategies may optimise hospital stay for elective older adult inpatients.ObjectivesTo evaluate the effectiveness and cost-effectiveness of hospital-led multicomponent interventions to reduce hospital stay for older adults undergoing elective hospital admissions.Data sourcesSeven bibliographic databases (MEDLINE, MEDLINE In-Process &amp; Other Non-Indexed Citations, EMBASE, Health Management Information Consortium, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature and Allied and Complementary Medicine Database) were searched from inception to date of search (August 2017), alongside carrying out of web searches, citation searching, inspecting relevant reviews, consulting stakeholders and contacting authors. This search was duplicated, with an additional cost-filter, to identify cost-effectiveness evidence.Review methodsComparative studies were sought that evaluated the effectiveness or cost-effectiveness of relevant interventions in elective inpatients with a mean or median age of ≥ 60 years. Study selection, data extraction and quality assessment were completed independently by two reviewers. The main outcome was length of stay, but all outcomes were considered. Studies were sorted by procedure, intervention and outcome categories. Where possible, standardised mean differences or odds ratios were calculated. Meta-analysis was performed when multiple randomised controlled trials had the same intervention, treatment procedure, comparator and outcome. Findings were explored using narrative synthesis.FindingsA total of 218 articles were included, with 80 articles from 73 effectiveness studies (n = 26,365 patients) prioritised for synthesis, including 34 randomised controlled trials conducted outside the UK and 39 studies from the UK, of which 12 were randomised controlled trials. Fifteen studies included cost-effectiveness data. The evidence was dominated by enhanced recovery protocols and prehabilitation, implemented to improve recovery from either colorectal surgery or lower limb arthroplasty. Six other surgical categories and four other intervention types were identified. Meta-analysis found that enhanced recovery protocols were associated with 1.5 days’ reduction in hospital stay among patients undergoing colorectal surgery (Cohen’sd = –0.51, 95% confidence interval –0.78 to –0.24;p &lt; 0.001) and with 5 days’ reduction among those undergoing upper abdominal surgery (Cohen’sd = –1.04, 95% confidence interval –1.55 to –0.53;p &lt; 0.001). Evidence from the UK was not pooled (owing to mixed study designs), but it echoed findings from the international literature. Length of stay usually was reduced with intervention or was no different. Other clinical outcomes also improved or were no worse with intervention. Patient-reported outcomes were not frequently reported. Cost and cost-effectiveness evidence came from 15 highly heterogeneous studies and was less conclusive.LimitationsStudies were usually of moderate or weak quality. Some intervention or treatment types were under-reported or absent. The reporting of variance data often precluded secondary analysis.ConclusionsEnhanced recovery and prehabilitation interventions were associated with reduced hospital stay without detriment to other clinical outcomes, particularly for patients undergoing colorectal surgery, lower limb arthroplasty or upper abdominal surgery. The impacts on patient-reported outcomes, health-care costs or additional service use are not well known.Future workFurther studies evaluating of the effectiveness of new enhanced recovery pathways are not required in colorectal surgery or lower limb arthroplasty. However, the applicability of these pathways to other procedures is uncertain. Future studies should evaluate the implementation of interventions to reduce service variation, in-hospital patient-reported outcomes, impacts on health and social care service use, and longer-term patient-reported outcomes.Study registrationThis study is registered as PROSPERO CRD42017080637.FundingThe National Institute for Health Research Health Services and Delivery Research programme.</jats:sec

An investigation of the effects of lipid-lowering medications: genome-wide linkage analysis of lipids in the HyperGEN study

BACKGROUND: Use of anti-hyperlipidemic medications compromises genetic analysis because of altered lipid profiles. We propose an empirical method to adjust lipid levels for medication effects so that the adjusted lipid values substitute the unmedicated lipid values in the genetic analysis. RESULTS: Published clinical trials were reviewed for HMG-CoA reductase inhibitors and fibric acid derivatives as mono-drug therapy. HMG-CoA reductase inhibitors showed similar effects in African Americans (AA) and non-African Americans (non-AA) for lowering total cholesterol (TC, -50.7 mg/dl), LDL cholesterol (LDL-C, -48.1 mg/dl), and triglycerides (TG, -19.7 mg/dl). Their effect on increasing HDL cholesterol (HDL-C) in AA (+0.4 mg/dl) was lower than in Non-AA (+2.3 mg/dl). The effects of fibric acid derivatives were estimated as -46.1 mg/dl for TC, -40.1 mg/dl for LDL-C, and +5.9 mg/dl for HDL-C in non-AA. The corresponding effects in AA were less extreme (-20.1 mg/dl, -11.4 mg/dl, and +3.1 mg/dl). Similar effect for TG (59.0 mg/dl) was shown in AA and non-AA. The above estimated effects were applied to a multipoint variance components linkage analysis on the lipid levels in 2,403 Whites and 2,214 AA in the HyperGEN study. The familial effects did vary depending on whether the lipids were adjusted for medication use. For example, the heritabilities increased after medication adjustment for TC and LDL-C, but did not change significantly for HDL-C and TG. CONCLUSION: Ethnicity-specific medication adjustments using our empirical method can be employed in epidemiological and genetic analysis of lipids.National Heart, Lung, and Blood Institute (HL554471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515