Validation in genetic association studies

Classification of feline hypertrophic cardiomyopathy-associated gene variants according to the American College of Medical Genetics and Genomics guidelines

Introduction

The correct labeling of a genetic variant as pathogenic is important as breeding decisions based on incorrect DNA tests can lead to the unwarranted exclusion of animals, potentially compromising the long-term health of a population. In human medicine, the American college of Medical Genetics (ACMG) guidelines provide a framework for variant classification. This study aims to apply these guidelines to six genetic variants associated with hypertrophic cardiomyopathy (HCM) in certain cat breeds and to propose a modified criterion for variant classification.

Methods

Genetic samples were sourced from five cat breeds: Maine Coon, Sphynx, Ragdoll, Devon Rex, and British Short- and Longhair. Allele frequencies were determined, and in the subset with phenotypes available, odds ratios to determine the association with HCM were calculated. In silico evaluation followed with joint evidence and data from other publications assisting in the classification of each variant.

Results

Two variants, MYBPC3:c.91G > C [A31P] and MYBPC3:c.2453C > T [R818W], were designated as pathogenic. One variant, MYH7:c.5647G > A [E1883K], was found likely pathogenic, while the remaining three were labeled as variants of unknown significance.

Discussion

Routine genetic testing is advised solely for the MYBPC3:c.91G > C [A31P] in the Maine Coon and MYBPC3:c.2453C > T [R818W] in the Ragdoll breed. The human ACMG guidelines serve as a suitable foundational tool to ascertain which variants to include; however, refining them for application in veterinary medicine might be beneficial.

Validation and Extension of the Association Between Potentially Excess Oxygen Exposure and Death in Mechanically Ventilated Children

OBJECTIVES

"Cumulative excess oxygen exposure" (CEOE)-previously defined as the mean hourly administered Fio2 above 0.21 when the corresponding hourly Spo2 was 95% or above-was previously shown to be associated with mortality. The objective of this study was to examine the relationship among Fio2, Spo2, and mortality in an independent cohort of mechanically ventilated children.

DESIGN

Retrospective cross-sectional study.

SETTING

Quaternary-care PICU.

PATIENTS

All patients admitted to the PICU between 2012 and 2021 and mechanically ventilated via endotracheal tube for at least 24 hours.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Among 3,354 patients, 260 (8%) died. Higher CEOE quartile was associated with increased mortality (p = 0.001). The highest CEOE quartile had an 87% increased risk of mortality (95% CI, 7-236) compared with the first CEOE quartile. The hazard ratio for extended CEOE exposure, which included mechanical ventilation data from throughout the patients' mechanical ventilation time rather than only from the first 24 hours of mechanical ventilation, was 1.03 (95% CI, 1.02-1.03).

CONCLUSIONS

Potentially excess oxygen exposure in patients whose oxygen saturation was at least 95% was associated with increased mortality.

Genetic determinants of Biofilm formation of Helicobacter pylori using whole-genome sequencing

BACKGROUND

Infection with Helicobacter pylori as the cause of gastric cancer is a global public health concern. In addition to protecting germs from antibiotics, biofilms reduce the efficacy of H. pylori eradication therapy. The nucleotide polymorphisms (SNPs) related with the biofilm forming phenotype of Helicobacter pylori were studied.

RESULTS

Fifty-six H. pylori isolate from Bangladeshi patients were included in this cross-sectional study. Crystal violet assay was used to quantify biofilm amount, and the strains were classified into high- and low-biofilm formers As a result, strains were classified as 19.6% high- and 81.4% low-biofilm formers. These phenotypes were not related to specific clades in the phylogenetic analysis. The accessories genes associated with biofilm from whole-genome sequences were extracted and analysed, and SNPs among the previously reported biofilm-related genes were analysed. Biofilm formation was significantly associated with SNPs of alpA, alpB, cagE, cgt, csd4, csd5, futB, gluP, homD, and murF (P < 0.05). Among the SNPs reported in alpB, strains encoding the N156K, G160S, and A223V mutations were high-biofilm formers.

CONCLUSIONS

This study revealed the potential role of SNPs in biofilm formation and proposed a method to detect mutation in biofilm from whole-genome sequences.

Deep Learning Techniques for the Effective Prediction of Alzheimer’s Disease: A Comprehensive Review

“Alzheimer’s disease” (AD) is a neurodegenerative disorder in which the memory shrinks and neurons die. “Dementia” is described as a gradual decline in mental, psychological, and interpersonal qualities that hinders a person’s ability to function autonomously. AD is the most common degenerative brain disease. Among the first signs of AD are missing recent incidents or conversations. “Deep learning” (DL) is a type of “machine learning” (ML) that allows computers to learn by doing, much like people do. DL techniques can attain cutting-edge precision, beating individuals in certain cases. A large quantity of tagged information with multi-layered “neural network” architectures is used to perform analysis. Because significant advancements in computed tomography have resulted in sizable heterogeneous brain signals, the use of DL for the timely identification as well as automatic classification of AD has piqued attention lately. With these considerations in mind, this paper provides an in-depth examination of the various DL approaches and their implementations for the identification and diagnosis of AD. Diverse research challenges are also explored, as well as current methods in the field.

Biparental Crossing and QTL Mapping for Validation of Genome-Wide Association Studies

Association mapping (AM), also known as genome-wide association studies (GWAS), is increasingly being employed in crop plants for the identification of QTL/genes and marker-trait associations (MTAs) in natural populations. Large numbers of such associations have been identified for variety of traits in different crop plants. However, not many of these associations have been used practically in the crop improvement program due to lack of validation. Although there are different ways through which the results of AM/GWAS could be validated, the best approach is to develop a biparental population for the trait of interest. An overview of the steps involved in the validation of results of AM using biparental mapping population in plants is provided in this chapter.

Little Evidence of Modified Genetic Effect of rs16969968 on Heavy Smoking Based on Age of Onset of Smoking

INTRODUCTION

Tobacco smoking is the leading cause of preventable death globally. Smoking quantity, measured in cigarettes per day, is influenced both by the age of onset of regular smoking (AOS) and by genetic factors, including a strong effect of the nonsynonymous single-nucleotide polymorphism rs16969968. A previous study by Hartz et al. reported an interaction between these two factors, whereby rs16969968 risk allele carriers who started smoking earlier showed increased risk for heavy smoking compared with those who started later. This finding has yet to be replicated in a large, independent sample.

METHODS

We performed a preregistered, direct replication attempt of the rs16969968 × AOS interaction on smoking quantity in 128 383 unrelated individuals from the UK Biobank, meta-analyzed across ancestry groups. We fit statistical association models mirroring the original publication as well as formal interaction tests on multiple phenotypic and analytical scales.

RESULTS

We replicated the main effects of rs16969968 and AOS on cigarettes per day but failed to replicate the interaction using previous methods. Nominal significance of the rs16969968 × AOS interaction term depended strongly on the scale of analysis and the particular phenotype, as did associations stratified by early/late AOS. No interaction tests passed genome-wide correction (α = 5e-8), and all estimated interaction effect sizes were much smaller in magnitude than previous estimates.

CONCLUSIONS

We failed to replicate the strong rs16969968 × AOS interaction effect previously reported. If such gene-moderator interactions influence complex traits, they likely depend on scale of measurement, and current biobanks lack the power to detect significant genome-wide associations given the minute effect sizes expected.

IMPLICATIONS

We failed to replicate the strong rs16969968 × AOS interaction effect on smoking quantity previously reported. If such gene-moderator interactions influence complex traits, current biobanks lack the power to detect significant genome-wide associations given the minute effect sizes expected. Furthermore, many potential interaction effects are likely to depend on the scale of measurement employed.

Genomic analysis of ionome-related QTLs in Arabidopsis thaliana

Ionome contributes to maintain cell integrity and acts as cofactors for catalyzing regulatory pathways. Identifying ionome contributing genomic regions provides a practical framework to dissect the genetic architecture of ionomic traits for use in biofortification. Meta-QTL (MQTL) analysis is a robust method to discover stable genomic regions for traits regardless of the genetic background. This study used information of 483 QTLs for ionomic traits identified from 12 populations for MQTL analysis in Arabidopsis thaliana. The selected QTLs were projected onto the newly constructed genetic consensus map and 33 MQTLs distributed on A. thaliana chromosomes were identified. The average confidence interval (CI) of the drafted MQTLs was 1.30 cM, reduced eight folds from a mean CI of 10.88 cM for the original QTLs. Four MQTLs were considered as stable MQTLs over different genetic backgrounds and environments. In parallel to the gene density over the A. thaliana genome, the genomic distribution of MQTLs over the genetic and physical maps indicated the highest density at non- and sub-telomeric chromosomal regions, respectively. Several candidate genes identified in the MQTLs intervals were associated with ion transportation, tolerance, and homeostasis. The genomic context of the identified MQTLs suggested nine chromosomal regions for Zn, Mn, and Fe control. The QTLs for potassium (K) and phosphorus (P) were the most frequently co-located with Zn (78.3%), Mn (76.2%), and Fe (88.2% and 70.6%) QTLs. The current MQTL analysis demonstrates that meta-QTL analysis is cheaper than, and as informative as genome-wide association study (GWAS) in refining the known QTLs.

Clinical epigenomics for cardiovascular disease: Diagnostics and therapies

The study of epigenomics has advanced in recent years to span the regulation of a single genetic locus to the structure and orientation of entire chromosomes within the nucleus. In this review, we focus on the challenges and opportunities of clinical epigenomics in cardiovascular disease. As an integrator of genetic and environmental inputs, and because of advances in measurement techniques that are highly reproducible and provide sequence information, the epigenome is a rich source of potential biosignatures of cardiovascular health and disease. Most of the studies to date have focused on the latter, and herein we discuss observations on epigenomic changes in human cardiovascular disease, examining the role of protein modifiers of chromatin, noncoding RNAs and DNA modification. We provide an overview of cardiovascular epigenomics, discussing the challenges of data sovereignty, data analysis, doctor-patient ethics and innovations necessary to implement precision health.

Genome-wide association mapping in maize: status and prospects

Genome-wide association study (GWAS) provides a robust and potent tool to retrieve complex phenotypic traits back to their underlying genetics. Maize is an excellent crop for performing GWAS due to diverse genetic variability, rapid decay of linkage disequilibrium, availability of distinct sub-populations and abundant SNP information. The application of GWAS in maize has resulted in successful identification of thousands of genomic regions associated with many abiotic and biotic stresses. Many agronomic and quality traits of maize are severely affected by such stresses and, significantly affecting its growth and productivity. To improve productivity of maize crop in countries like India which contribute only 2% to the world's total production in 2019-2020, it is essential to understand genetic complexity of underlying traits. Various DNA markers and trait associations have been revealed using conventional linkage mapping methods. However, it has achieved limited success in improving polygenic complex traits due to lower resolution of trait mapping. The present review explores the prospects of GWAS in improving yield, quality and stress tolerance in maize besides, strengths and challenges of using GWAS for molecular breeding and genomic selection. The information gathered will facilitate elucidation of genetic mechanisms of complex traits and improve efficiency of marker-assisted selection in maize breeding.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02799-4.

Non-coding variants in MYH11, FZD3, and SORCS3 are associated with dementia in women

INTRODUCTION

Recent studies suggest that both sex-specific genetic risk factors and those shared between dementia and stroke are involved in dementia pathogenesis.

METHODS

We performed both single-variant and gene-based genome-wide association studies of >11,000 whole genome sequences from the Women's Health Initiative cohort to discover loci associated with dementia, with adjustment for age, ethnicity, stroke, and venous thromboembolism status. Evidence for prior evidence of association and differential gene expression in dementia-related tissues and samples was gathered for each locus.

RESULTS

Our multiethnic studies identified significant associations between variants within APOE, MYH11, FZD3, SORCS3, and GOLGA8B and risk of dementia. Ten genes implicated by these loci, including MYH11, FZD3, SORCS3, and GOLGA8B, were differentially expressed in the context of Alzheimer's disease.

DISCUSSION

Our association of MYH11, FZD3, SORCS3, and GOLGA8B with dementia is supported by independent functional studies in human subjects, model systems, and associations with shared risk factors for stroke and dementia.

Challenges in understanding host genetics and severity of community-acquired pneumonia

A heritable predisposition to early death due to infection was observed three decades ago [1]. Apart from exciting discoveries in the field of primary immunodeficiencies, genetic variants predisposing to severe infection and outcome at a population level remain largely elusive [2, 3]. Genetic association studies on sepsis were largely based on a candidate gene approach. In 2015, Rautanenet al. [4] reported the first genome-wide association study (GWAS) in sepsis. A meta-analysis of three independent cohorts of critically ill patients with sepsis recruited in numerous centres from Europe, Canada, United States, Australia, New Zealand and South Africa was performed. They reported that the C allele of the single-nucleotide variant (SNV) rs4957796 at the FER gene was associated with a protective additive effect in 28-day survival only in patients with pneumonia, but not in those with other causes of sepsis. Schönewecket al. [5] did not replicate the findings Rautanenet al. [4] in a mixed cohort of patients of European ancestry with severe sepsis admitted at German intensive care units (ICUs). However, their study was underpowered for mortality. Hinzet al.[6], in a cohort of white patients with acute respiratory distress syndrome (ARDS) due to pneumonia from a single Centre in Germany, found that the rs4957796 TT genotype was associated with a higher 90-day mortality exclusively in the small subgroup of patients with severe ARDS.

This study found no association of the top two associated FER variants with severity of community-acquired pneumonia. Precise characterisation of phenotypes may be required in order to unravel the genetic mechanisms predisposing to poor outcome in sepsis.https://bit.ly/3jc9SmR

The impact of different sources of heterogeneity on loss of accuracy from genomic prediction models

Cross-study validation (CSV) of prediction models is an alternative to traditional cross-validation (CV) in domains where multiple comparable datasets are available. Although many studies have noted potential sources of heterogeneity in genomic studies, to our knowledge none have systematically investigated their intertwined impacts on prediction accuracy across studies. We employ a hybrid parametric/non-parametric bootstrap method to realistically simulate publicly available compendia of microarray, RNA-seq, and whole metagenome shotgun microbiome studies of health outcomes. Three types of heterogeneity between studies are manipulated and studied: (i) imbalances in the prevalence of clinical and pathological covariates, (ii) differences in gene covariance that could be caused by batch, platform, or tumor purity effects, and (iii) differences in the "true" model that associates gene expression and clinical factors to outcome. We assess model accuracy, while altering these factors. Lower accuracy is seen in CSV than in CV. Surprisingly, heterogeneity in known clinical covariates and differences in gene covariance structure have very limited contributions in the loss of accuracy when validating in new studies. However, forcing identical generative models greatly reduces the within/across study difference. These results, observed consistently for multiple disease outcomes and omics platforms, suggest that the most easily identifiable sources of study heterogeneity are not necessarily the primary ones that undermine the ability to accurately replicate the accuracy of omics prediction models in new studies. Unidentified heterogeneity, such as could arise from unmeasured confounding, may be more important.

GSTP1 and ABCB1 Polymorphisms Predicting Toxicities and Clinical Management on Carboplatin and Paclitaxel-Based Chemotherapy in Ovarian Cancer

Variation in drug disposition genes might contribute to susceptibility to toxicities and interindividual differences in clinical management on chemotherapy for epithelial ovarian cancer (EOC). This study was designed to explore the association of GST and ABCB1 genetic variation with hematologic and neurologic toxicity, changes in chemotherapy, and disease prognosis in Brazilian women with EOC. A total of 112 women with a confirmed histological diagnosis of EOC treated with carboplatin/paclitaxel were enrolled (2014–2019). The samples were analyzed by multiplex polymerase chain reaction (PCR) for the deletion of GSTM1 and GSTT1 genes. GSTP1 (c.313A>G/rs1695) and ABCB1 (c.1236C>T/rs1128503; c.3435C>T/rs1045642; c.2677G>T>A/rs2032582) single nucleotide polymorphisms (SNPs) were detected by real‐time PCR. Subjects with the GSTP1 c.313A>G had reduced risk of anemia (odds ratio (OR): 0.17, 95% confidence interval (CI): 0.04–0.69, P = 0.01, dominant model) and for thrombocytopenia (OR: 0.27, 95% CI: 0.12–0.64, P < 0.01; OR 0.18, 95% CI 0.03–0.85, P = 0.03, either dominant or recessive model), respectively. The GSTP1 c.313A>G AG genotype was associated with a lower risk of dose delay (OR: 0.35, 95% CI: 0.13–0.90, P = 0.03). The ABCB1 c.1236C>T was associated with increased risk of thrombocytopenia (OR: 0.15, 95% CI: 0.03–0.82, P = 0.03), whereas ABCB1 c.3435C>T had increased risk of grade 2 and 3 neurotoxicity (OR: 3.61, 95% CI: 1.08–121.01, P = 0.03) in recessive model (CC + CT vs. TT). This study suggests that GSTP1 c.313A>G, ABCB1 c.1236C>T, and c.3435C>T SNP detection is a potential predictor of hematological toxicity and neurotoxicity and could help predict the clinical management of women with EOC.

Mutations in sphingolipid metabolism genes are associated with ADHD

Attention deficit hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder in children, with genetic factors accounting for 75-80% of the phenotypic variance. Recent studies have suggested that ADHD patients might present with atypical central myelination that can persist into adulthood. Given the essential role of sphingolipids in myelin formation and maintenance, we explored genetic variation in sphingolipid metabolism genes for association with ADHD risk. Whole-exome genotyping was performed in three independent cohorts from disparate regions of the world, for a total of 1520 genotyped subjects. Cohort 1 (MTA (Multimodal Treatment study of children with ADHD) sample, 371 subjects) was analyzed as the discovery cohort, while cohorts 2 (Paisa sample, 298 subjects) and 3 (US sample, 851 subjects) were used for replication. A set of 58 genes was manually curated based on their roles in sphingolipid metabolism. A targeted exploration for association between ADHD and 137 markers encoding for common and rare potentially functional allelic variants in this set of genes was performed in the screening cohort. Single- and multi-locus additive, dominant and recessive linear mixed-effect models were used. During discovery, we found statistically significant associations between ADHD and variants in eight genes (GALC, CERS6, SMPD1, SMPDL3B, CERS2, FADS3, ELOVL5, and CERK). Successful local replication for associations with variants in GALC, SMPD1, and CERS6 was demonstrated in both replication cohorts. Variants rs35785620, rs143078230, rs398607, and rs1805078, associated with ADHD in the discovery or replication cohorts, correspond to missense mutations with predicted deleterious effects. Expression quantitative trait loci analysis revealed an association between rs398607 and increased GALC expression in the cerebellum.

Genome-wide whole blood transcriptome profiling in a large European cohort of systemic sclerosis patients

Objectives

The analysis of annotated transcripts from genome-wide expression studies may help to understand the pathogenesis of complex diseases, such as systemic sclerosis (SSc). We performed a whole blood (WB) transcriptome analysis on RNA collected in the context of the European PRECISESADS project, aiming at characterising the pathways that differentiate SSc from controls and that are reproducible in geographically diverse populations.

Methods

Samples from 162 patients and 252 controls were collected in RNA stabilisers. Cases and controls were divided into a discovery (n=79+163; Southern Europe) and validation cohort (n=83+89; Central-Western Europe). RNA sequencing was performed by an Illumina assay. Functional annotations of Reactome pathways were performed with the Functional Analysis of Individual Microarray Expression (FAIME) algorithm. In parallel, immunophenotyping of 28 circulating cell populations was performed. We tested the presence of differentially expressed genes/pathways and the correlation between absolute cell counts and RNA transcripts/FAIME scores in regression models. Results significant in both populations were considered as replicated.

Results

Overall, 15 224 genes and 1277 functional pathways were available; of these, 99 and 225 were significant in both sets. Among replicated pathways, we found a deregulation in type-I interferon, Toll-like receptor cascade, tumour suppressor p53 protein function, platelet degranulation and activation. RNA transcripts or FAIME scores were jointly correlated with cell subtypes with strong geographical differences; neutrophils were the major determinant of gene expression in SSc-WB samples.

Conclusions

We discovered a set of differentially expressed genes/pathways validated in two independent sets of patients with SSc, highlighting a number of deregulated processes that have relevance for the pathogenesis of autoimmunity and SSc.

Aggressive prostate cancer phenotype and genome-wide association studies: where are we now?

The majority of prostate cancer (PCa) is indolent, however, a percentage of patients are initially diagnosed with metastatic disease, for which there is a worse prognosis. There is a lack of biomarkers to identify men at greater risk for developing aggressive PCa. Genome-wide association studies (GWAS) scan the genome to search associations of SNPs with specific traits, like cancer. To date, eight GWAS have resulted in the reporting of 16 SNPs associated with aggressive PCa (p < 5.00 × 10^-2). Still, validation studies need to be conducted to confirm the obtained results as GWAS can generate false-positive results. Furthermore, post-GWAS studies provide a better understanding of the functional consequences.

The Association of Aquaporin-1 Gene with Marathon Running Performance Level: a Confirmatory Study Conducted in Male Hispanic Marathon Runners

Background

Replication studies are essential for identifying credible associations between alleles and phenotypes. Validation of genotype-phenotype associations in the sports and exercise field is rare. An initial genetic association study suggested that rs1049305 (C > G) in the 3′ untranslated region (3′UTR) of the aquaporin-1 (AQP1) gene was associated with marathon running (MR) performance level in Hispanic males. To validate this finding, we conducted a replication analysis in an independent case-control sample of Hispanic male marathon runners (n = 1430; cases n = 713 and controls n = 717). A meta-analysis was utilized to test the extent of the association between the initial results and the present report. It also provided to test the heterogeneity (variation) between the two studies.

Results

The replication study showed a statistically significant (p ≤ 0.05) association between rs1049305 (C > G) of the AQP1 gene and MR performance level. Association test results using a fixed effect model for the combined, original study and the present report, yielded an odds ratio = 1.28, 95% confidence interval = 1.13–1.45, p = 0.0001. The extent of the measures of heterogeneity was Tau-squared = 0, H statistic = 1, I² statistic = 0, and Cochran’s Q test (Q = 0.29; p value 0.59), indicated the variation between studies were due to chance and not to differences in heterogeneity between the two studies. Within the limitations of the present replication, contrast of two studies and its effects on meta-analysis, the findings were robust.

Conclusion

This study successfully replicated the results of Martínez et al. (Med Sportiva 13:251-5, 2009). The meta-analysis provided further epidemiological credibility for the hypothesis of association between the DNA rs1049305 (C > G) variation in the 3′UTR of the AQP1 gene and MR running performance level in Hispanics male marathon runners. It is not precluded that a linked DNA structure in the surrounding molecular neighborhood could be of influence by been part of the overly complex phenotype of MR performance level.

The Apoptosis Pathway and CASP8 Variants Conferring Risk for Acute and Overuse Musculoskeletal Injuries

Rotator cuff tendinopathy (RCT), anterior cruciate ligament (ACL) ruptures, and carpal tunnel syndrome (CTS), are examples of chronic (RCT and CTS) and acute (ACL ruptures) musculoskeletal soft tissue injuries. These injuries are multifactorial in nature, with several identified intrinsic and extrinsic risk factors. Previous studies have implicated specific sequence variants within genes encoding structural and regulatory components of the extracellular matrix of tendons and/ligaments to predispose individuals to these injuries. An example, includes the association of sequence variants within the apoptotic regulatory gene, caspase-8 (CASP8) with other musculoskeletal injury phenotypes, such as Achilles tendinopathy. The primary aim of this study was, therefore, to investigate previously implicated DNA sequence variants within CASP8: rs3834129 (ins/del) and rs1045485 (G/C), and the rs13113 (T/A) identified using a whole exome sequencing approach, with risk of musculoskeletal injury phenotypes (RCT, ACL ruptures, and CTS) in three independent studies. In addition, the aim was to implicate a CASP8 genomic interval in the modulation of risk of RCT, ACL ruptures, or CTS. It was found that the AA genotype of CASP8 rs13113 (T/A) was independently associated with increased risk for CTS. In addition, it was found that the del-C haplotype (rs3834129-rs1045485) was significantly associated with non-contact ACL ruptures, which is in alignment with previous research findings. Collectively, the results of this study implicate the apoptosis pathway as biologically significant in the underlying pathogenesis of musculoskeletal injury phenotypes. These findings should be repeated in larger sample cohorts and across different populations. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:680-688, 2020.

Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data

Deep learning, a state-of-the-art machine learning approach, has shown outstanding performance over traditional machine learning in identifying intricate structures in complex high-dimensional data, especially in the domain of computer vision. The application of deep learning to early detection and automated classification of Alzheimer's disease (AD) has recently gained considerable attention, as rapid progress in neuroimaging techniques has generated large-scale multimodal neuroimaging data. A systematic review of publications using deep learning approaches and neuroimaging data for diagnostic classification of AD was performed. A PubMed and Google Scholar search was used to identify deep learning papers on AD published between January 2013 and July 2018. These papers were reviewed, evaluated, and classified by algorithm and neuroimaging type, and the findings were summarized. Of 16 studies meeting full inclusion criteria, 4 used a combination of deep learning and traditional machine learning approaches, and 12 used only deep learning approaches. The combination of traditional machine learning for classification and stacked auto-encoder (SAE) for feature selection produced accuracies of up to 98.8% for AD classification and 83.7% for prediction of conversion from mild cognitive impairment (MCI), a prodromal stage of AD, to AD. Deep learning approaches, such as convolutional neural network (CNN) or recurrent neural network (RNN), that use neuroimaging data without pre-processing for feature selection have yielded accuracies of up to 96.0% for AD classification and 84.2% for MCI conversion prediction. The best classification performance was obtained when multimodal neuroimaging and fluid biomarkers were combined. Deep learning approaches continue to improve in performance and appear to hold promise for diagnostic classification of AD using multimodal neuroimaging data. AD research that uses deep learning is still evolving, improving performance by incorporating additional hybrid data types, such as-omics data, increasing transparency with explainable approaches that add knowledge of specific disease-related features and mechanisms.

Genome-wide association study identifies new susceptible loci of IgA nephropathy in Koreans

Background

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Recent evidence suggests that genetic factors are related to the pathogenesis of IgAN. We conducted a genome-wide association study (GWAS) to identify novel genetic susceptibility loci for IgAN in a Korean population.

Methods

We enrolled 188 biopsy-confirmed IgAN cases and 455 healthy controls for the discovery stage and explored associations between IgAN and single nucleotide polymorphisms (SNPs) using a customized DNA chip. The significant SNPs from the discovery samples were then selected for replication in an independent cohort with 310 biopsy-confirmed IgAN cases and 438 healthy controls.

Results

In the first stage, two SNPs (rs10172700 in LOC105373592 and rs2296136 in ANKRD16) were selected for further association analysis in the next stage. In the replication cohort, rs2296136 in ANKRD16 was significantly associated with IgAN (odds ratio [OR] = 1.40, 95% confidence interval [CI] 0.99–1.98, p = 0.05 in log-additive model, OR = 1.55, 95% CI = 1.06–−2.27, p = 0.02 in dominant model, and OR = 0.70, 95% CI = 0.17–−2.84, p = 0.62 in recessive model). rs2296136 in ANKRD16 also showed a significant association with IgAN in the entire study population combining GWAS and replication study (p = 0.0045 in log-additive model, p = 0.0027 in dominant model, and p = 0.76 in recessive model).

Conclusions

The SNPs identified in the present study could be good candidate markers for predicting IgAN in Koreans, although further experimental validation is needed.

Statistical learning approaches in the genetic epidemiology of complex diseases

In this paper, we give an overview of methodological issues related to the use of statistical learning approaches when analyzing high-dimensional genetic data. The focus is set on regression models and machine learning algorithms taking genetic variables as input and returning a classification or a prediction for the target variable of interest; for example, the present or future disease status, or the future course of a disease. After briefly explaining the basic motivation and principle of these methods, we review different procedures that can be used to evaluate the accuracy of the obtained models and discuss common flaws that may lead to over-optimistic conclusions with respect to their prediction performance and usefulness.

Genome-wide association study identifies new susceptibility loci for diabetic nephropathy in Korean patients with type 2 diabetes mellitus

Genetic factors are considered to be important in the pathogenesis of diabetic nephropathy (DN). Despite several genome-wide association studies (GWASs) demonstrating that specific polymorphisms of candidate genes were associated with DN, there were some limitations in previous studies. We conducted a GWAS using customized DNA chips to identify novel susceptibility loci for DN in Korean. We analyzed a total of 414 DN cases and 474 normoalbuminuric diabetic hyper-controls across two stages using customized DNA chips containing 98 667 single nucleotide polymorphisms (SNPs). We explored the associations between SNPs and DN in samples from 87 DN cases, mostly confirmed by renal biopsy, and 104 diabetic hyper-controls, and replicated these associations in independent cohort samples with 327 DN cases and 370 diabetic hyper-controls. The top significant SNPs from the discovery samples were selected for replication in the independent cohort. rs3765156 in PIK3C2B was significantly associated with DN in the replication cohort after multiple test. The SNPs identified in our study provide new insights into the pathogenesis of DN in the Korean population. Additional studies are needed to determine biological effects and clinical utility of our findings.

Cellular and Molecular Mechanisms of Autoimmune Hepatitis

Autoimmune hepatitis is an uncommon idiopathic syndrome of immune-mediated destruction of hepatocytes, typically associated with autoantibodies. The disease etiology is incompletely understood but includes a clear association with human leukocyte antigen (HLA) variants and other non-HLA gene variants, female sex, and the environment. Pathologically, there is a CD4+ T cell-rich lymphocytic inflammatory infiltrate with variable hepatocyte necrosis and subsequent hepatic fibrosis. Attempts to understand pathogenesis are informed by several monogenetic syndromes that may include autoimmune liver injury, by several drug and environmental agents that have been identified as triggers in a minority of cases, by human studies that point toward a central role for CD4+ effector and regulatory T cells, and by animal models of the disease. Nonspecific immunosuppression is the current standard therapy. Further understanding of the disease's cellular and molecular mechanisms may assist in the design of better-targeted therapies, aid the limitation of adverse effects from therapy, and inform individualized risk assessment and prognostication.

Presidential address: Six open questions to genetic epidemiologists

Given the rapid pace with which genomics and other ‐omics disciplines are evolving, it is sometimes necessary to shift down a gear to consider more general scientific questions. In this line, in my presidential address I formulate six questions for genetic epidemiologists to ponder on. These cover the areas of reproducibility, statistical significance, chance findings, precision medicine and related fields such as bioinformatics and data science. Possible hints at responses are presented to foster our further discussion of these topics.

Pharmacogenomics in epithelial ovarian cancer first-line treatment outcome: validation of GWAS-associated NRG3 rs1649942 and BRE rs7572644 variants in an independent cohort

The identification of predictive biomarkers for the first-line treatment of epithelial ovarian cancer (EOC) remains a challenge. Although genome-wide association studies (GWAS) have identified several genetic polymorphisms as predictors of EOC clinical outcome, the subsequent validation has not yet been performed. This study aims to validate the influence of Neuregulin 3 (NRG3) rs1649942 and Brain and reproductive organ-expressed (TNFRSF1A modulator) (BRE) rs7572644 GWAS-identified variants in an independent cohort of EOC patients from the North region of Portugal (n = 339) submitted to first-line treatment. Polymorphism genotypes were determined by real-time PCR using validated assays. Patients carrying the NRG3 rs1649942 A allele presented a significantly longer overall survival (OS) when compared to GG-genotype patients (log-rank test, P = 0.011) in the FIGO IV stage subgroup. No impact was observed for early-stage patients or considering disease-free survival (DFS) as an outcome. For FIGO I/II stage patients, BRE rs7572644 C allele carriers exhibit a decreased OS (P = 0.014) and DFS (P = 0.032) when compared to TT-homozygous patients. Furthermore, a Multivariate Cox regression analysis revealed a three-fold increase in the risk of death (HR, 3.09; P = 0.015) and recurrence (HR, 3.33; P = 0.009) for FIGO I/II C allele carriers. No significant impact was observed for late-stage patients. The BRE rs7572644 and NRG3 rs1649942 genetic variants were validated in an independent cohort of EOC Portuguese patients, particularly in specific subgroups considering FIGO staging. Further functional post-GWAS analyses are indispensable to understand the biological mechanisms underlying the observed results.

A Case of Need: Linking Traits to Genebank Accessions

Genebanks are responsible for collecting, maintaining, characterizing, documenting, and distributing plant genetic resources for research, education, and breeding purposes. The rationale for requests of plant materials varies highly from areas of anthropology, social science, small-holder farmers, the commercial sector, rehabilitation of degraded systems, all the way to crop improvement and basic research. Matching "the right" accessions to a particular request is not always a straightforward process especially when genetic resource collections are large and the user does not already know which accession or even which species they want to study. Some requestors have limited knowledge of the crop; therefore, they do not know where to begin and thus, initiate the search by consultation with crop curators to help direct their request to the most suitable germplasm. One way to enhance the use of genebank material and aid in the selection of genetic resources is to have thoroughly cataloged agronomic, biochemical, genomic, and other traits linked to genebank accessions. In general, traits of importance to most users include genotypes that thrive under various biotic and abiotic stresses, morphological traits (color, shape, size of fruits), plant architecture, disease resistance, nutrient content, yield, and crop specific quality traits. In this review, we discuss methods for linking traits to genebank accessions, examples of linked traits, and some of the complexities involved, while reinforcing why it is critical to have well characterized accessions with clear trait data publicly available.

Nasal DNA methylation is associated with childhood asthma

AIM

We aim to study DNA methylation (DNAm) variations associated with childhood asthma.

METHODS

Nasal DNAm was compared between sibling pairs discordant for asthma, 29 sib pairs for genome-wide association studies and 54 sib pairs for verification by pyrosequencing. Associations of methylation with asthma symptoms, allergy and environmental exposures were evaluated. In vitro experiments and functional genomic analyses were performed to explore biologic relevance.

RESULTS

Three CpGs were associated with asthma. cg14830002 was associated with allergies in nonasthmatics. cg23602092 was associated with asthma symptoms. cg14830002 and cg23602092 were associated with traffic-related air pollution exposure. Nearby genes were transcriptionally regulated by diesel exhaust, house dust mite and 5-aza-2'-deoxycytidine. Active chromatin marks and transcription factor binding were found around these sites.

CONCLUSION

We identified novel DNAm variations associated with childhood asthma and suggested new disease-contributing epigenetic mechanisms.

Efficient estimation of disease odds ratios for follow-up genetic association studies

In the past decade, genome-wide association studies have identified thousands of susceptible variants associated with complex human diseases and traits. Conducting follow-up genetic association studies has become a standard approach to validate the findings of genome-wide association studies. One problem of high interest in genetic association studies is to accurately estimate the strength of the association, which is often quantified by odds ratios in case-control studies. However, estimating the association directly by follow-up studies is inefficient since this approach ignores information from the genome-wide association studies. In this article, an estimator called GFcom, which integrates information from genome-wide association studies and follow-up studies, is proposed. The estimator includes both the point estimate and corresponding confidence interval. GFcom is more efficient than competing estimators regarding MSE and the length of confidence intervals. The superiority of GFcom is particularly evident when the genome-wide association study suffers from severe selection bias. Comprehensive simulation studies and applications to three real follow-up studies demonstrate the performance of the proposed estimator. An R package, "GFcom", implementing our method is publicly available at https://github.com/JiyuanHu/GFcom .

Genetic predisposition to lung adenocarcinoma among never-smoking Chinese with different epidermal growth factor receptor mutation status

OBJECTIVES

The inconsistent findings from genetic association studies may be related to the heterogeneity in different molecular subtypes of lung cancer. This study evaluated the predisposing single-nucleotide polymorphisms (SNPs) in epidermal growth factor receptor (EGFR) mutant and EGFR wild-type lung adenocarcinoma separately among never-smokers.

MATERIALS AND METHODS

This was a two-stage case-control study. Never-smokers with pathologically confirmed lung adenocarcinoma and healthy controls were recruited in Hong Kong and Macau. Genomic DNA was extracted and genotyped by MassARRAY. In the discovery stage, 51 SNPs were investigated at the SNP, gene and pathway level among 103 EGFR mutant and 78 EGFR wild-type lung adenocarcinoma cases compared with matched controls. In the validation stage, SNPs that were identified with significant lung cancer risk were replicated in a separate cohort of 84 lung adenocarcinoma cases and compared with 103 Chinese Han, Beijing and 105 Chinese Han, Southern public controls from the 1000 genome database.

RESULTS AND CONCLUSION

The genetic association of IL-6 rs2069840 with EGFR mutant lung adenocarcinoma was ascertained. In the discovery stage, haplotype GGG in three SNPs (rs2069840, rs2069852, rs2066992) of IL-6, synergetic effects of IL-6 rs2069840 and environmental tobacco smoke in the workplace were found to be related to EGFR mutant lung adenocarcinoma. ERCC2 rs238406 showed a marginally significant association with EGFR mutant lung adenocarcinoma in the validation stage (P=0.096). ERCC2 rs50871 and ATM rs611646 showed significant association with EGFR wild-type lung adenocarcinoma in the discovery stage. In conclusion, IL-6 rs2069840 conferred susceptibility to EGFR mutant lung adenocarcinoma in a Hong Kong and Macau never-smoking Chinese population.

What is precision medicine?

The term “precision medicine” has become very popular over recent years, fuelled by scientific as well as political perspectives. Despite its popularity, its exact meaning, and how it is different from other popular terms such as “stratified medicine”, “targeted therapy” or “deep phenotyping” remains unclear. Commonly applied definitions focus on the stratification of patients, sometimes referred to as a novel taxonomy, and this is derived using large-scale data including clinical, lifestyle, genetic and further biomarker information, thus going beyond the classical “signs-and-symptoms” approach.

While these aspects are relevant, this description leaves open a number of questions. For example, when does precision medicine begin? In which way does the stratification of patients translate into better healthcare? And can precision medicine be viewed as the end-point of a novel stratification of patients, as implied, or is it rather a greater whole?

To clarify this, the aim of this paper is to provide a more comprehensive definition that focuses on precision medicine as a process. It will be shown that this proposed framework incorporates the derivation of novel taxonomies and their role in healthcare as part of the cycle, but also covers related terms.

The performance of a new local false discovery rate method on tests of association between coronary artery disease (CAD) and genome-wide genetic variants

The maximum entropy (ME) method is a recently-developed approach for estimating local false discovery rates (LFDR) that incorporates external information allowing assignment of a subset of tests to a category with a different prior probability of following the null hypothesis. Using this ME method, we have reanalyzed the findings from a recent large genome-wide association study of coronary artery disease (CAD), incorporating biologic annotations. Our revised LFDR estimates show many large reductions in LFDR, particularly among the genetic variants belonging to annotation categories that were known to be of particular interest for CAD. However, among SNPs with rare minor allele frequencies, the reductions in LFDR were modest in size.

Analyzing a single nucleotide polymorphism in schizophrenia: a meta-analysis approach

BACKGROUND

Schizophrenia is a severe mental disorder affecting >21 million people worldwide. Some genetic studies reported that single nucleotide polymorphism (SNP) involving variant rs1344706 from the ZNF804A gene in human beings is associated with the risk of schizophrenia in several populations. Similar results tend to conflict with other reports in literature, indicating that no true significant association exists between rs1344706 and schizophrenia. We seek to determine the level of association of this SNP with schizophrenia in the Asian population using more recent genome-wide association study (GWAS) datasets.

METHODS

Applying a computational approach with inclusion of more recent GWAS datasets, we conducted a meta-analysis to examine the level of association of SNP rs1344706 and the risk of schizophrenia disorder among the Asian population constituting Chinese, Indonesians, Japanese, Kazakhs and Singaporeans. For a total of 21 genetic studies, including a total of 28,842 cases and 35,630 controls, regression analysis, publication bias, Cochran's Q and I2 tests were performed. The DerSimonian and Laird random-effects model was used to assess the association of the genetic variant to schizophrenia. Leave-one-out sensitivity analysis was also conducted to determine the influence of each study on the final outcome of the association study.

RESULTS

Our summarized analysis for Asian population revealed a pooled odds ratio of 1.06, 95% confidence interval of 1.01-1.11 and two-tailed P-value of 0.0228. Our test for heterogeneity showed the presence of large heterogeneity (I2=53.44%, P =0.00207) and Egger's regression test (P =0.8763) and Begg's test (P =0.8347), indicating no presence of publication bias among our selected studies. In our sensitivity analysis, 10 different studies comprising of ~50% of the entire study had an impact on our final results as each leave-one-out test became insignificant. Our result suggests that genetic variant rs1344706 might be associated with the development of schizophrenia in Asians.

Association Between the Estrogen Receptor Beta (ESR2) Rs1256120 Single Nucleotide Polymorphism and Adolescent Idiopathic Scoliosis: A Systematic Review and Meta-Analysis

STUDY DESIGN

A systematic review and meta-analysis.

OBJECTIVE

The aim of this study was to assess and synthesize the current evidence on the association between the rs1256120 single nucleotide polymorphism (SNP) of the estrogen receptor beta gene (ESR2) and adolescent idiopathic scoliosis (AIS).

SUMMARY OF BACKGROUND DATA

Hormonal disturbance has been postulated as a potential etiological factor in the development of AIS. As estrogen receptors are important mediators of estrogen response, mutations in these genes, including rs1256120 of ESR2, have been chosen as susceptibility candidates for AIS predisposition. The association of rs1256120 with AIS has been investigated in several recent studies, but showed conflicting evidence. We conducted a systematic review to evaluate the strength of this body of evidence and quantitative synthesis to examine sources of heterogeneity.

METHODS

This study conformed to PRISMA guidelines. Using a sensitive search strategy, PubMed (MEDLINE), EMBASE, and HuGE Literature Finder databases were searched to identify relevant studies for inclusion in the systematic review and meta-analysis. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. The inverse variance model was used to calculate summary odds ratios (ORs) and corresponding 95% confidence intervals (CIs) for the allelic (C vs. T) and genotypic comparisons. Planned subgroup and sensitivity analyses were performed.

RESULTS

Three studies were included for systematic review and meta-analysis (n = 1264 AIS cases and n=1020 controls). A null relationship was found between rs1256120 and AIS (allelic OR = 1.20, 95% CI: 0.81-1.78, P = 0.36, I = 84.9%), with the first reported association likely to be false-positive and contributing substantially to heterogeneity.

CONCLUSION

Findings from the systematic review and meta-analysis suggest that rs1256120 of ESR2 is unlikely to be a predisposing or disease-modifying genetic risk factor for AIS.

LEVEL OF EVIDENCE

2.

The genetics revolution in rheumatology: large scale genomic arrays and genetic mapping

Susceptibility to rheumatic diseases, such as osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, juvenile idiopathic arthritis and psoriatic arthritis, includes a large genetic component. Understanding how an individual's genetic background influences disease onset and outcome can lead to a better understanding of disease biology, improved diagnosis and treatment, and, ultimately, to disease prevention or cure. The past decade has seen great progress in the identification of genetic variants that influence the risk of rheumatic diseases. The challenging task of unravelling the function of these variants is ongoing. In this Review, the major insights from genetic studies, gained from advances in technology, bioinformatics and study design, are discussed in the context of rheumatic disease. In addition, pivotal genetic studies in the main rheumatic diseases are highlighted, with insights into how these studies have changed the way we view these conditions in terms of disease overlap, pathways of disease and potential new therapeutic targets. Finally, the limitations of genetic studies, gaps in our knowledge and ways in which current genetic knowledge can be fully translated into clinical benefit are examined.

Meta-analysis on the association of VEGFR1 genetic variants with sunitinib outcome in metastatic renal cell carcinoma patients

VEGFR1 rs9582036 and rs9554320 were previously reported the association with sunitinib progression-free survival (PFS) and overall survival (OS) in patients with metastatic renal cell carcinoma (mRCC). Hereafter, the association of both single nucleotide polymorphisms (SNPs) with PFS/OS was confirmed in two independent mRCC cohorts. The aim of the current study was to validate the associations of both SNPs with sunitinib outcome in three independent well-characterized cohorts (SUTOX, CCF and SOGUG) including 286 sunitinib-treated mRCC patients, as well as to perform a meta-analysis of current and published data combined. We found that rs9582036 and rs9554320 showed a significant association with sunitinib PFS in the CCF cohort (HR: 0.254, 95%CI: 0.092-0.703; P=0.008 and HR: 0.430, 95%CI: 0.200-0.927; P=0.031, respectively). Patients with the variant genotype of rs9582036 and rs9554320 had a shorter median PFS. No significant association of both SNPs with sunitinib PFS or OS was detected in either the SUTOX or SOGUG cohort. After the combination of all available data into a meta-analysis, the association of both SNPs with sunitinib PFS or OS did not achieve the threshold for statistical significance. Our findings suggest that, although VEGFR1 rs9582036 and rs9554320 are involved in sunitinib therapy outcome, its clinical use as biomarkers for prediction of sunitinib outcome in mRCC patients is limited, due to inconsistent findings when analyzing all existing studies together.

Association between rs2294020 in X-linked CCDC22 and susceptibility to autoimmune diseases with focus on systemic lupus erythematosus

Autoimmune diseases often share common susceptibility genes. Most genetic variants associated with susceptibility to systemic lupus erythematosus are also associated with other autoimmune diseases. The X-linked variant rs2294020 is positioned in exon 7 of the CCDC22 gene. The encoded protein functions in the regulation of NF-κB, a master regulator in immune response. The aim of this study is to investigate whether the rs2294020 polymorphism may be a general susceptibility factor for autoimmunity. We evaluated case-control association between the occurrence of rs2294020 and different autoimmune diseases, including new data for systemic lupus erythematosus and previous genome-wide association studies (GWAS) (though most did not analyse the X chromosome) of psoriasis, celiac disease, Crohn's disease, ulcerative colitis, multiple sclerosis, vitiligo, type-1 diabetes, rheumatoid arthritis, and ankylosing spondylitis. Cases from patients affected by amyotrophic lateral sclerosis and type-2 diabetes were also included in the study. We detected nominal significant associations of rs2294020 with systemic lupus erythematosus (additive model test: p=0.01), vitiligo (p=0.016), psoriasis (p=0.038), and in only one of two studies of multiple sclerosis (p=0.03). Our results suggest that rs2294020 is associated with the risk of several autoimmune diseases in European populations, specifically with diseases that present themselves, among else, in the skin.

Single nucleotide polymorphisms in an intergenic chromosome 2q region associated with tissue factor pathway inhibitor plasma levels and venous thromboembolism

Essentials Tissue factor pathway inhibitor (TFPI) regulates the blood coagulation cascade. We replicated previously reported linkage of TFPI plasma levels to the chromosome 2q region. The putative causal locus, rs62187992, was associated with TFPI plasma levels and thrombosis. rs62187992 was marginally associated with TFPI expression in human aortic endothelial cells. Click to hear Ann Gil's presentation on new insights into thrombin activatable fibrinolysis inhibitor SUMMARY: Background Tissue factor pathway inhibitor (TFPI) regulates fibrin clot formation, and low TFPI plasma levels increase the risk of arterial thromboembolism and venous thromboembolism (VTE). TFPI plasma levels are also heritable, and a previous linkage scan implicated the chromosome 2q region, but no specific genes. Objectives To replicate the finding of the linkage region in an independent sample, and to identify the causal locus. Methods We first performed a linkage analysis of microsatellite markers and TFPI plasma levels in 251 individuals from the F5L Family Study, and replicated the finding of the linkage peak on chromosome 2q (LOD = 3.06). We next defined a follow-up region that included 112 603 single nucleotide polymorphisms (SNPs) under the linkage peak, and meta-analyzed associations between these SNPs and TFPI plasma levels across the F5L Family Study and the Marseille Thrombosis Association (MARTHA) Study, a study of 1033 unrelated VTE patients. SNPs with false discovery rate q-values of < 0.10 were tested for association with TFPI plasma levels in 892 patients with coronary artery disease in the AtheroGene Study. Results and Conclusions One SNP, rs62187992, was associated with TFPI plasma levels in all three samples (β = + 0.14 and P = 4.23 × 10-6 combined; β = + 0.16 and P = 0.02 in the F5L Family Study; β = + 0.13 and P = 6.3 × 10-4 in the MARTHA Study; β = + 0.17 and P = 0.03 in the AtheroGene Study), and contributed to the linkage peak in the F5L Family Study. rs62187992 was also associated with clinical VTE (odds ratio 0.90, P = 0.03) in the INVENT Consortium of > 7000 cases and their controls, and was marginally associated with TFPI expression (β = + 0.19, P = 0.08) in human aortic endothelial cells, a primary site of TFPI synthesis. The biological mechanisms underlying these associations remain to be elucidated.

Where next for the reproducibility agenda in computational biology?

Background

The concept of reproducibility is a foundation of the scientific method. With the arrival of fast and powerful computers over the last few decades, there has been an explosion of results based on complex computational analyses and simulations. The reproducibility of these results has been addressed mainly in terms of exact replicability or numerical equivalence, ignoring the wider issue of the reproducibility of conclusions through equivalent, extended or alternative methods.

Results

We use case studies from our own research experience to illustrate how concepts of reproducibility might be applied in computational biology. Several fields have developed ‘minimum information’ checklists to support the full reporting of computational simulations, analyses and results, and standardised data formats and model description languages can facilitate the use of multiple systems to address the same research question. We note the importance of defining the key features of a result to be reproduced, and the expected agreement between original and subsequent results. Dynamic, updatable tools for publishing methods and results are becoming increasingly common, but sometimes come at the cost of clear communication. In general, the reproducibility of computational research is improving but would benefit from additional resources and incentives.

Conclusions

We conclude with a series of linked recommendations for improving reproducibility in computational biology through communication, policy, education and research practice. More reproducible research will lead to higher quality conclusions, deeper understanding and more valuable knowledge.

Molecular proxies for climate maladaptation in a long-lived tree (Pinus pinaster Aiton, Pinaceae)

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change.

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence

Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.

Validation of association of the apolipoprotein E ε2 allele with neurodevelopmental dysfunction after cardiac surgery in neonates and infants

OBJECTIVE

Apolipoprotein E (APOE) genotype is a determinant of neurologic recovery after brain ischemia and traumatic brain injury. The APOE ε2 allele has been associated with worse neurodevelopmental (ND) outcome after repair of congenital heart defects (CHD) in infancy. Replication of this finding in an independent cohort is essential to validate the observed genotype-phenotype association.

METHODS

The association of APOE genotype with ND outcomes was assessed in a combined cohort of patients with single-ventricle CHD enrolled in the Single Ventricle Reconstruction and Infant Single Ventricle trials. ND outcome was assessed at 14 months using the Psychomotor Development Index (PDI) and Mental Development Index (MDI) of the Bayley Scales of Infant Development-II. Stepwise multivariable regression was performed to develop predictive models for PDI and MDI scores.

RESULTS

Complete data were available for 298 of 435 patients. After adjustment for preoperative and postoperative covariates, the APOE ε2 allele was associated with a lower PDI score (P = .038). Patients with the ε2 allele had a PDI score approximately 6 points lower than those without the risk allele, explaining 1.04% of overall PDI variance, because the ε2 allele was present in only 11% of the patients. There was a marginal effect of the ε2 allele on MDI scores (P = .058).

CONCLUSIONS

These data validate the association of the APOE ε2 allele with adverse early ND outcomes after cardiac surgery in infants, independent of patient and operative factors. Genetic variants that decrease neuroresilience and impair neuronal repair after brain injury are important risk factors for ND dysfunction after surgery for CHD.

Expansive marker analysis replicating the association of glaucoma susceptibility with human chromosome loci 1q43 and 10p12.31

Three human chromosome loci (1q43, 10p12.31, and 12q21.31) were recently associated with the susceptibility to primary open-angle glaucoma (POAG) in a Japanese population; however, this was not replicated in three subsequent studies using South Indian, Afro-Caribbean, and Chinese populations. To identify genetic markers that are robustly associated across ethnic populations, numerous markers in addition to the six in the three reported loci were examined in this study. A total of 31 single-nucleotide polymorphism (SNP) markers were genotyped for 1115 Korean participants, and many neighboring SNPs were imputed using the Korean HapMap Project genotype data. Each SNP was statistically tested for association with POAG susceptibility by comparisons among 211 POAG patients with 904 unaffected controls. A strong and statistically significant association was found with a previously unreported SNP, rs7098387 (odds ratio, OR=2.0 (1.4-3.0), P=0.00038) at the 10p12.31 locus (where 11 SNPs were typed and 38 imputed) in contrast to the reported rs7081455, which was too poorly correlated with newly associated rs7098387 (r2=0.003, D'=0.40) to show association. Additionally, a modest association was observed with the reported rs693421 (OR=1.4 (1.1-1.7), P=0.0082) and several other SNPs located within and around ZP4 at the 1q43 locus (10 SNPs typed and 14 imputed). However, no association was observed with the reported rs7961953 SNP or any other SNPs at the 12q21.31 locus, upstream of TMTC2 (10 SNPs typed and 29 imputed). Accordingly, POAG susceptibility association was replicated using rs7098387 (C) rather than rs7081455 (T) at the 10p12.31 locus and additionally with rs693421 (T) at the 1q43 locus.

Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives

A central challenge in systems biology and medical genetics is to understand how interactions among genetic loci contribute to complex phenotypic traits and human diseases. While most studies have so far relied on statistical modeling and association testing procedures, machine learning and predictive modeling approaches are increasingly being applied to mining genotype-phenotype relationships, also among those associations that do not necessarily meet statistical significance at the level of individual variants, yet still contributing to the combined predictive power at the level of variant panels. Network-based analysis of genetic variants and their interaction partners is another emerging trend by which to explore how sub-network level features contribute to complex disease processes and related phenotypes. In this review, we describe the basic concepts and algorithms behind machine learning-based genetic feature selection approaches, their potential benefits and limitations in genome-wide setting, and how physical or genetic interaction networks could be used as a priori information for providing improved predictive power and mechanistic insights into the disease networks. These developments are geared toward explaining a part of the missing heritability, and when combined with individual genomic profiling, such systems medicine approaches may also provide a principled means for tailoring personalized treatment strategies in the future.

Genetic susceptibility in IBD: overlap between ulcerative colitis and Crohn's disease

BACKGROUND

The etiology of ulcerative colitis (UC) and Crohn's disease (CD) involves both genetic and environmental components. Multiple UC and CD susceptibility genes have been identified through genome-wide association studies and subsequent meta-analyses. These studies have also highlighted the presence of genes common to both diseases, and shared with several other autoimmune disorders. The aim of this study was to identify single nucleotide polymorphisms (SNPs) recently identified by the International IBD Genetics Consortium (IIBDGC) demonstrating that highly significant associations with CD could also confer genetic susceptibility to UC.

METHODS

Statistical modeling was performed on 29 CD-associated SNPs. The study comprised of 1652 UC cases from the Australia and New Zealand IBD Consortium and 2363 Australian population-based controls.

RESULTS

After adjustment for multiple comparisons, only one SNP, rs3024505, was significantly associated with UC (P = 0.001). Independent chi-square analyses identified odds ratios of 2.22 (1.48-3.37) for the rare homozygous genotype, and 1.20 (1.06-1.35) for the minor allele. Five other SNPs demonstrated moderate to weak associations with UC.

CONCLUSIONS

Of the 29 SNPs conferring high genetic susceptibility to CD, 28 were not associated with UC, thus indicating that for this SNP set there is a low level of overlap between the two major forms of IBD. Only one SNP, rs3024505 (Chr 1q32.1, upstream of IL10), was associated with susceptibility to UC. The identification of this SNP replicates a finding from Franke et al (2008), where the rs3024505 SNP was strongly associated with UC across multiple European populations.

Genomic regions associated with bovine milk fatty acids in both summer and winter milk samples

Background

In this study we perform a genome-wide association study (GWAS) for bovine milk fatty acids from summer milk samples. This study replicates a previous study where we performed a GWAS for bovine milk fatty acids based on winter milk samples from the same population. Fatty acids from summer and winter milk are genetically similar traits and we therefore compare the regions detected in summer milk to the regions previously detected in winter milk GWAS to discover regions that explain genetic variation in both summer and winter milk.

Results

The GWAS of summer milk samples resulted in 51 regions associated with one or more milk fatty acids. Results are in agreement with most associations that were previously detected in a GWAS of fatty acids from winter milk samples, including eight ‘new’ regions that were not considered in the individual studies. The high correlation between the –log₁₀(P-values) and effects of SNPs that were found significant in both GWAS imply that the effects of the SNPs were similar on winter and summer milk fatty acids.

Conclusions

The GWAS of fatty acids based on summer milk samples was in agreement with most of the associations detected in the GWAS of fatty acids based on winter milk samples. Associations that were in agreement between both GWAS are more likely to be involved in fatty acid synthesis compared to regions detected in only one GWAS and are therefore worthwhile to pursue in fine-mapping studies.