Genome-wide Association Studies Findings Research Articles

Transcriptome-wide association study: Opportunity and challenges for cancer studies

Genome-wide association studies (GWAS) have uncovered thousands of single nucleotide polymorphism (SNP) loci that are associated with complex traits. However, the majority of GWAS discoveries are located in non-coding regions and the biological mechanisms behind these associations are not well understood. Transcriptome-wide association studies (TWAS) have gained popularity in recent years by generating biological interpretable discoveries and facilitating the identification of novel associations that have been missed by GWAS. TWAS has identified more than hundreds of susceptibility genes for many complex diseases and traits, including cancers. Here, in this review, we first summarize TWAS methods, then discuss the opportunities for cancer studies and finally review current challenges and future directions for this method.

Transcriptomics insights into interpreting AMD-GWAS discoveries for biological and clinical applications

Genome-wide association studies (GWAS) have been successful in identifying genetic risk factors for a large number of complex diseases, including age-related macular degeneration (AMD), which is a highly heritable complex disease affecting millions of elderly individuals. However, the progress of elucidating the functional relevance of genetic findings in AMD has been slow, as most risk factors are non-coding, and we have little insight into the causal genes and disease mechanisms. In the last few years, gene expression regulation is emerging as a dominant mechanism through which GWAS risk variants lead to the disease. The purpose of this review is to provide an overview of how transcriptome studies can help in identifying the genes, pathways and therapeutic targets underlying GWAS discoveries in AMD. These approaches help pave the road for mechanistic understanding of GWAS findings and drive translational advances that will lead to improved AMD management and treatment.

The construction of a haplotype reference panel using extremely low coverage whole genome sequences and its application in genome-wide association studies and genomic prediction in Duroc pigs

Extremely low coverage whole genome sequencing (lcWGS) is an economical technique to obtain high-density single nucleotide polymorphisms (SNPs). Here, we explored the feasibility of constructing a haplotype reference panel (lcHRP) using lcWGS and evaluated the effects of lcHRP through a genome-wide association study (GWAS) and genomic prediction in pigs. A total of 297 and 974 Duroc pigs were genotyped using lcWGS and a 50 K SNP array, respectively. We obtained 19,306,498 SNPs using lcWGS with an accuracy of 0.984. With the help of lcHRP, the accuracy of imputation from the SNP array to lcWGS was 0.922. Compared to the SNP array findings, those from the imputation-based GWAS identified more signals across four traits. With the integration of the top 1% imputation-based GWAS findings as genomic features, the accuracies of genomic prediction was improved by 6.0% to 13.2%. This study showed the great potential of lcWGS in pigs' molecular breeding.

Integrative analysis of eQTL and GWAS summary statistics reveals novel genes related to Alzheimer's disease

AbstractBackgroundLarge‐scale genome wide association studies (GWASs) have identified many genetic variants associated with Alzheimer’s disease (AD) and related traits. While many GWAS findings were found to co‐localize with expression quantitative trait loci (eQTL), it is of great interest to investigate the functional effect of GWAS hits on the downstream transcriptomic level. Considering the lack of gene expression data from the brain tissue, we propose to integrate the summary statistics from AD GWAS and brain eQTL analysis to investigate potential transcriptomic alterations inside AD brains. We further validate our findings using the brain gene expression data from the ROS/MAP cohort.MethodWe used the GWAS summary statistics from IGAP[1] and brain eQTL results from BRAINEAC[2]. Summary Mendelian Randomization (SMR) and Heterogeneity in Dependent Instruments (HEIDI) tests were applied to identify highly significant genes related to AD in temporal cortex, frontal cortex and hippocampal regions. For significant genes identified from each region, we further performed differential gene expression analysis using the RNA‐Seq data from the corresponding brain tissue in the Mayo Clinic cohort. SNPs from these genes were tested for association with FDG intensity and thickness of corresponding brain regions using the data from ADNI. Finally, we performed pathway analysis using ClueGO.ResultSMR and HEIDI test identified 32 genes significantly associated with AD in the transcriptomic level, but only in temporal cortex. 10 of them were further validated with altered expression in AD temporal cortex region in the Mayo cohort (Fig.1). 19 SNPs from these genes were significantly related to the FDG intensity and thickness of temporal cortex regions, predominantly present in TOMM40 and NECTIN genes. Top pathways enriched by these genes are Neutrophil degranulation and cell surface interactions at vascular wall (Fig.2).ConclusionWe identified several SNPs with potential regulatory role in mediating the expression level of genes, which are found altered in AD brains and associated with multiple neuroimaging phenotypes. With evidence from multiple sources, these SNPs, their downstream genes and related pathways could serve as potential targets for further therapeutic intervention of AD.

Pioglitazone reduces the incidence of Alzheimer’s disease: From genetics to population‐based validation

Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer's disease (AD). However, utilizing GWAS to identify high-confidence AD risk genes (ARGs) that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. To address this critical problem in the field, we have developed a genotype-informed, network-based methodology that interrogates pathogenesis to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein-protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs are significantly associated with decreased risk of AD compared with matched control populations: pioglitazone (P = 0.005, hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861-0.974), febuxostat (HR = 0.815, 95% CI 0.710-0.936, P = 0.004), and atenolol (HR = 0.949, 95% CI 0.923-0.976, P = 2.8 x 10-4 ). Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR =0.921, 95% CI 0.862-0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. In summary, we present an integrated, network-based methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD.

Genetic interaction study of Alzheimer's disease quantitative biomarkers: A polygenic risk score analysis and evaluation.

Relationship between genetic factors and pathological features of Alzheimer's disease (AD) may be studied with biomarker, using both polygenic risk scores (PRSs), as well as individual genetic variants in genome-wide association studies (GWAS). In the Swedish BioFINDER study, we used a priori PRS for AD based on findings in recent GWAS, and AD related biomarkers in cerebrospinal fluid (CSF) in cognitively unimpaired individuals (n = 751), Mild Cognitive Impairment (n = 212), and AD (n = 150) patients. AD related biomarkers were rank-based inverse normal transformed to be used as dependent variables in linear regression models adjusted for age, gender, education, APOE ε4, ε2 count and significant principal components. We also tested individual genetic variants in GWAS for each biomarker. Analyses were performed in the total sample, and after stratification on MMSE results. The PRS was associated with higher CSF P-tau 181 (p ≤1.2e-05) and T-tau (p ≤ 8.14e-05) and lower CSF Aβ42/40 (p ≤ 0.006) and Aβ42 (p ≤ 0.04) (Figure 1, 2). Gene Enrichment of PRS 5 genes [containing 1850 genetic variants mapped to 1607 genes] for Tau biomarker showed 13 Gene Ontology (GO) Biological Process (BP) terms at p-value < e-03 ("Dendrite Morphogenesis": top hit; p-value ≤ 9.20e-06) and 16 KEGG pathway term enriched for genes of PRS 5 ("Phosphatidylinositol signaling system": top hit; p-value ≤ 5.5e-06) (Figure 3, 4). Gene enrichment of PRS 7 [containing 62 genetic variants mapped to 58 genes] for Aβ biomarker returned 12 GO terms ("Integrin-Mediated Signaling Pathway": top hit; p-value ≤1.20e-03) and 1 term enriched for KEGG pathway (Hematopoietic cell lineage). In our predefined list of genes interacting with MAPT (22 genes) and APP (69 genes) we found 3 genes from MAPT and APP set that were involved in PRS 5 and PRS 7 respectively. We also found 9 genes from APP set that was involved in PRS 5. Elevated levels of AD related biomarkers are associated with polygenic risk scores in AD. These findings further strengthens the link between genetic and biomarker disease predictors and indicate a potential role for these markers in disease prediction and patient stratification in AD.

Analysis of rate of change in quantitative traits for identifying biomarker-mediated genetic effects on MCI and AD.

The relationship between genetic variations such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) is integral in the understanding of Alzheimer's Disease (AD). Given AD as a progressive disorder, QT-based rate of change (RoC) measures are important phenotypes to study in AD genetics. Further mediation analysis provides a promising method to help reveal causal relationship from genetic determinants to longitudinal changes in QTs and to clinical diagnosis. We analyzed the QT data from the Quantitative Templates for the Progression of Alzheimer's disease (QT-PAD, see http://www.pi4cs.org/qt-pad-challenge). QT-PAD is a single and shared data freeze from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including 16 imaging, cognitive and fluid AD QTs. RoC between baseline and month-12 visits was calculated for each QT. Genotyping data were obtained from the ADNI database and went through a standard QC procedure. Genome wide association study (GWAS) was performed using PLINK to examine genetic associations between 565,373 SNPs and the RoC for each QT. For each SNP-RoC association with p<1e-6, a subsequent mediation analysis was performed using the "Mediation" R package to examine the mediation relationship from SNP to RoC to five different diagnostic comparisons (see Table 1). Figure 1 shows the GWAS findings on the RoC measures for the studied QTs. The results included 19 SNPs and 14 QTs, where each SNP or each QT had at least one association with p<10-6 . Table 1 shows the mediation analysis results. RoC in FAQ mediates the effects of rs429358-APOE and rs4420638-APOC1 on all five diagnostic comparisons, and mediates the effect of rs769449-APOE on four comparisons. RoC in Ventricle mediates the effects of both TOMM40 SNPs on four comparisons. RoC in CDRSB mediates the effects of rs5011804-KRAS on three comparisons. Mediation analysis of longitudinal AD biomarkers revealed several candidate causal relationships from genetic determinants (i.e., SNPs from the APOE/TOMM40/APOC1 region and KRAS) to RoC measures in QTs (FAQ, Ventricle, CDRSB), and to various diagnostic comparisons in MCI and AD. The identified patterns warrant further investigation in independent cohorts for deconvoluting mechanistic complexity of AD.

Genetic association study of NOD2 and IL23R amino acid substitution polymorphisms in Saudi Inflammatory Bowel Disease patients

BackgroundInflammatory Bowel Disease (IBD) is a complex autoimmune disease whose genetic basis is not well explored in the highly consanguineous Saudi population. Therefore, this study aims to evaluate the relevance of NOD2 and IL23R genes polymorphisms, selected from Caucasian Genome-wide association study (GWAS) findings, as risk markers for IBD pathology in Saudi patients. Materials and MethodsThe genetic status of NOD2 and IL23R polymorphisms of 97 IBD patients and 100 healthy individuals was determined through real-time PCR based TaqMan Allelic Discrimination Assay. Genotype calls of TaqMan assay were further validated by the direct DNA sequencing method. The pathogenicity of the variants was further explored by computational predictions and by 3D structural modelling methods. ResultsOur study found no evidence for a significant association of Caucasian IBD risk alleles, i.e., NOD2 (P268S and R702W) and IL23R (G149R and R381Q) with IBD pathology in Saudi Arabian patients under dominant, recessive or co-dominant genetic models. Moreover, SNP-SNP interaction analysis with multidimensionality reduction assays have also confirmed the above findings. Our computational predictions of the variants suggest the variable deleterious nature and minor structural drifts on the tertiary protein structures. ConclusionThis study expands the genetic heterogeneity of IBD and concludes that Caucasian genetic risk markers have limited or of no use in estimating the risk of IBD development in Saudi patients. Future genetic association studies in Saudi Arabia need to employ genetic markers whose minor allele frequencies exceed 10% in Arab population to have robust outcomes.

Mapping GWAS loci to kidney genes and cell types

Estimated glomerular filtration rate (eGFR) has significant heritability, varying from 36% to 75% in different studies.1,2 Genome-wide association studies (GWAS) have now identified over 400 significant loci for eGFR, most of which map to noncoding regions.3,4 A major challenge for the field is now to identify causal genes and cell types for each of these loci to enable mechanistic interpretation of GWAS findings.

Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features.

Alzheimer's disease (AD) is a devastating neurological disorder primarily affecting the elderly. An estimated 6.2 million Americans age 65 and older are suffering from Alzheimer's dementia today. Brain magnetic resonance imaging (MRI) is widely used for the clinical diagnosis of AD. In the meanwhile, medical researchers have identified 40 risk locus using single-nucleotide polymorphisms (SNPs) information from Genome-wide association study (GWAS) in the past decades. However, existing studies usually treat MRI and GWAS separately. For instance, convolutional neural networks are often trained using MRI for AD diagnosis. GWAS and SNPs are frequently used to identify genomic traits. In this study, we propose a multi-modal AD diagnosis neural network that uses both MRIs and SNPs. The proposed method demonstrates a novel way to use GWAS findings by directly including SNPs in predictive models. We test the proposed methods on the Alzheimer's Disease Neuroimaging Initiative dataset. The evaluation results show that the proposed method improves the model performance on AD diagnosis and achieves 93.5% AUC and 96.1% AP, respectively, when patients have both MRI and SNP data. We believe this work brings exciting new insights to GWAS applications and sheds light on future research directions.

Post-partum psychosis and its association with bipolar disorder in the UK: a case-control study using polygenic risk scores

For more than 150 years, controversy over the status of post-partum psychosis has hindered research and caused considerable confusion for clinicians and women, with potentially negative consequences. We aimed to explore the hypothesis that genetic vulnerability differs between women with first-onset post-partum psychosis and those with bipolar disorder more generally. In this case-control study on first-onset post-partum psychosis and bipolar disorder in the UK, we included 203 women with first-onset post-partum psychosis (defined as a manic, mixed, or psychotic depression episode within 6 weeks of delivery without a psychiatric history) and 1225 parous women with a history of bipolar disorder. Information on women with bipolar disorder was obtained from the Bipolar Disorder Research Network database, and participants were recruited through screening community mental health teams across the UK and via the media and patient support organisations. All were assessed using a semistructured face-to-face psychiatric interview and psychiatric case note review. 2809 women from the general population were recruited via the national UK Blood Services and the 1958 Birth Cohort (UK National Child Development Study) as controls and matched to cases according to genetic ancestry. All self-reported their ethnicity as White and were recruited from across the UK. Polygenic risk scores (PRSs) were generated from discovery genome-wide association studies of schizophrenia, bipolar disorder, and major depression. Logistic regression was used to model the effect of each PRS on diagnosis, and the RRs and ORs presented were adjusted for ten principal components of genetic variation to account for population stratification. 203 women with first-onset post-partum psychosis (median age at interview: 46 years [IQR 37-55]) and 1225 women with bipolar disorder (49 years [41-58]) were recruited between September, 1991, and May, 2013, as well as 2809 controls. Women with first-onset post-partum psychosis had similar bipolar disorder and schizophrenia PRSs to women with bipolar disorder, which were significantly higher than those of controls. When compared with controls, women with first-onset post-partum psychosis had an adjusted relative risk ratio (RR) for bipolar disorder PRSs of 1·71 (95% CI 1·56-1·86, p<0·0001) and for schizophrenia PRSs of 1·82 (1·66-1·97, p<0·0001). The effect sizes were similar when comparing women with bipolar disorder to controls (adjusted RR 1·77 [1·69-1·84], p<0·0001 for bipolar disorder PRSs; 2·00 (1·92-2·08), p<0·0001 for schizophrenia PRSs). Although women with bipolar disorder also had higher major depression PRSs than did controls (1·24 [1·17-1·31], p<0·0001), women with first-onset post-partum psychosis did not differ from controls in their polygenic liability to major depression (0·97 (0·82-1·11), p=0·63). Our study supports the recognition of first-onset post-partum psychosis as a separate nosological entity within the bipolar disorder spectrum both in research and clinical settings. Wellcome Trust and Medical Research Council.

Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR.

Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust genetic associations. Leveraging relevant auxiliary covariates has the potential to boost statistical power to exceed the significance threshold. Particularly, abundant pleiotropy and the non-random distribution of SNPs across various functional categories suggests that leveraging GWAS test statistics from related traits and/or functional genomic data may boost GWAS discovery. While type 1 error rate control has become standard in GWAS, control of the false discovery rate can be a more powerful approach. The conditional false discovery rate (cFDR) extends the standard FDR framework by conditioning on auxiliary data to call significant associations, but current implementations are restricted to auxiliary data satisfying specific parametric distributions, typically GWAS p-values for related traits. We relax these distributional assumptions, enabling an extension of the cFDR framework that supports auxiliary covariates from arbitrary continuous distributions ("Flexible cFDR"). Our method can be applied iteratively, thereby supporting multi-dimensional covariate data. Through simulations we show that Flexible cFDR increases sensitivity whilst controlling FDR after one or several iterations. We further demonstrate its practical potential through application to an asthma GWAS, leveraging various functional genomic data to find additional genetic associations for asthma, which we validate in the larger, independent, UK Biobank data resource.

An assessment of the effect of the genotype on postoperative venous thromboembolism risk in 140,831 surgical patients

BackgroundPostoperative Venous Thromboembolism Events (VTE) constitute a major source of morbidity and mortality after surgery. The aim of this study was to investigate whether commonly occurring Single Nucleotide Polymorphisms (SNPs) are associated with VTE in the surgical setting. MethodsRetrospective study using data from the United Kingdom (UK) biobank, a genome biobank containing healthcare and genotyping data from more than 500.000 individuals. A cohort of 140,831patients with a registered surgical procedure was identified and used for a discovery genome wide association study (GWAS), with the remainder of the cohort (305,349 non-surgical patients) used as a replication cohort. Primary outcome was associations between SNPs and VTE within 30 days after a surgical procedure. Genome wide significance was set at p = 5 × 10−8. ResultsIn the surgical (discovery) cohort, no SNPs reached genome wide significance. The VTE association of the top candidate SNP in the ABO gene rs505922 (p = 3.33 × 10−7), was replicated in the general (replication) cohort (p = 2.42 × 10−59). Conclusionsand Relevance: This study did not identify associations between SNPs and postoperative VTE events reaching genome-wide significance, although the VTE relevance of top candidates were demonstrated.

From GWAS to Gene: Transcriptome-Wide Association Studies and Other Methods to Functionally Understand GWAS Discoveries.

Since their inception, genome-wide association studies (GWAS) have identified more than a hundred thousand single nucleotide polymorphism (SNP) loci that are associated with various complex human diseases or traits. The majority of GWAS discoveries are located in non-coding regions of the human genome and have unknown functions. The valley between non-coding GWAS discoveries and downstream affected genes hinders the investigation of complex disease mechanism and the utilization of human genetics for the improvement of clinical care. Meanwhile, advances in high-throughput sequencing technologies reveal important genomic regulatory roles that non-coding regions play in the transcriptional activities of genes. In this review, we focus on data integrative bioinformatics methods that combine GWAS with functional genomics knowledge to identify genetically regulated genes. We categorize and describe two types of data integrative methods. First, we describe fine-mapping methods. Fine-mapping is an exploratory approach that calibrates likely causal variants underneath GWAS signals. Fine-mapping methods connect GWAS signals to potentially causal genes through statistical methods and/or functional annotations. Second, we discuss gene-prioritization methods. These are hypothesis generating approaches that evaluate whether genetic variants regulate genes via certain genetic regulatory mechanisms to influence complex traits, including colocalization, mendelian randomization, and the transcriptome-wide association study (TWAS). TWAS is a gene-based association approach that investigates associations between genetically regulated gene expression and complex diseases or traits. TWAS has gained popularity over the years due to its ability to reduce multiple testing burden in comparison to other variant-based analytic approaches. Multiple types of TWAS methods have been developed with varied methodological designs and biological hypotheses over the past 5 years. We dive into discussions of how TWAS methods differ in many aspects and the challenges that different TWAS methods face. Overall, TWAS is a powerful tool for identifying complex trait-associated genes. With the advent of single-cell sequencing, chromosome conformation capture, gene editing technologies, and multiplexing reporter assays, we are expecting a more comprehensive understanding of genomic regulation and genetically regulated genes underlying complex human diseases and traits in the future.

W23. THE POSTPARTUM PSYCHOSIS INTERNATIONAL CONSORTIUM: RESULTS FROM GENOTYPE-PHENOTYPE ANALYSES

For more than 150 years, controversy over the status of post-partum psychosis has hindered research and caused considerable confusion for clinicians and women, with potentially negative consequences. We aimed to explore the hypothesis that genetic vulnerability differs between women with first-onset post-partum psychosis and those with bipolar disorder more generally.In this case-control study on first-onset post-partum psychosis and bipolar disorder in the UK, we included 203 women with first-onset post-partum psychosis (defined as a manic, mixed, or psychotic depression episode within 6 weeks of delivery without a psychiatric history) and 1225 parous women with a history of bipolar disorder. Information on women with bipolar disorder was obtained from the Bipolar Disorder Research Network database, and participants were recruited through screening community mental health teams across the UK and via the media and patient support organisations. All were assessed using a semistructured face-to-face psychiatric interview and psychiatric case note review. 2809 women from the general population were recruited via the national UK Blood Services and the 1958 Birth Cohort (UK National Child Development Study) as controls and matched to cases according to genetic ancestry. All self-reported their ethnicity as White and were recruited from across the UK. Polygenic risk scores (PRSs) were generated from discovery genome-wide association studies of schizophrenia, bipolar disorder, and major depression. Logistic regression was used to model the effect of each PRS on diagnosis, and the RRs and ORs presented were adjusted for ten principal components of genetic variation to account for population stratification.203 women with first-onset post-partum psychosis (median age at interview: 46 years [IQR 37–55]) and 1225 women with bipolar disorder (49 years [41–58]) were recruited between September, 1991, and May, 2013, as well as 2809 controls. Women with first-onset post-partum psychosis had similar bipolar disorder and schizophrenia PRSs to women with bipolar disorder, which were significantly higher than those of controls. When compared with controls, women with first-onset post-partum psychosis had an adjusted relative risk ratio (RR) for bipolar disorder PRSs of 1·71 (95% CI 1·56–1·86, p<0·0001) and for schizophrenia PRSs of 1·82 (1·66–1·97, p<0·0001). The effect sizes were similar when comparing women with bipolar disorder to controls (adjusted RR 1·77 [1·69–1·84], p<0·0001 for bipolar disorder PRSs; 2·00 (1·92–2·08), p<0·0001 for schizophrenia PRSs). Although women with bipolar disorder also had higher major depression PRSs than did controls (1·24 [1·17–1·31], p<0·0001), women with first-onset post-partum psychosis did not differ from controls in their polygenic liability to major depression (0·97 (0·82–1·11), p=0·63).Our study supports the recognition of first-onset post-partum psychosis as a separate nosological entity within the bipolar disorder spectrum both in research and clinical settings.Wellcome Trust and Medical Research Council.

Reproducibility in the UK biobank of genome-wide significant signals discovered in earlier genome-wide association studies

With the establishment of large biobanks, discovery of single nucleotide variants (SNVs, also known as single nucleotide polymorphisms (SNVs)) associated with various phenotypes has accelerated. An open question is whether genome-wide significant SNVs identified in earlier genome-wide association studies (GWAS) are replicated in later GWAS conducted in biobanks. To address this, we examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, “replication” GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNVs (of which 6289 reached P < 5e−8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0%; although lower for binary than quantitative phenotypes (58.1% versus 94.8% respectively). There was a 18.0% decrease in SNV effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNV effect size, phenotype trait (binary or quantitative), and discovery P value, we built and validated a model that predicted SNV replication with area under the Receiver Operator Curve = 0.90. While non-replication may reflect lack of power rather than genuine false-positives, these results provide insights about which discovered associations are likely to be replicated across subsequent GWAS.

GWAS meta-analysis followed by Mendelian randomization revealed potential control mechanisms for circulating α-Klotho levels

The protein α-Klotho acts as transmembrane co-receptor for fibroblast growth factor 23 (FGF23) and is a key regulator of phosphate homeostasis. However, α-Klotho also exists in a circulating form, with pleiotropic, but incompletely understood functions and regulation. Therefore, we undertook a genome-wide association study (GWAS) meta-analysis followed by Mendelian randomization (MR) of circulating α-Klotho levels.Plasma α-Klotho levels were measured by enzyme-linked immunosorbent assay (ELISA) in the Ludwigshafen Risk and Cardiovascular Health and Avon Longitudinal Study of Parents and Children (mothers) cohorts, followed by a GWAS meta-analysis in 4376 individuals across the two cohorts.Six signals at five loci were associated with circulating α-Klotho levels at genome-wide significance (P < 5 × 10−8), namely ABO, KL, FGFR1, and two post-translational modification genes, B4GALNT3 and CHST9. Together, these loci explained >9% of the variation in circulating α-Klotho levels. MR analyses revealed no causal relationships between α-Klotho and renal function, FGF23-dependent factors such as vitamin D and phosphate levels, or bone mineral density. The screening for genetic correlations with other phenotypes followed by targeted MR suggested causal effects of liability of Crohn’s disease risk [Inverse variance weighted (IVW) beta = 0.059 (95% confidence interval 0.026, 0.093)] and low-density lipoprotein cholesterol levels [−0.198 (−0.332, −0.063)] on α-Klotho.Our GWAS findings suggest that two enzymes involved in post-translational modification, B4GALNT3 and CHST9, contribute to genetic influences on α-Klotho levels, presumably by affecting protein turnover and stability. Subsequent evidence from MR analyses on α-Klotho levels suggest regulation by mechanisms besides phosphate-homeostasis and raise the possibility of cross-talk with FGF19- and FGF21-dependent pathways, respectively. Significance statement: α-Klotho as a transmembrane protein is well investigated along the endocrine FGF23-α-Klotho pathway. However, the role of the circulating form of α-Klotho, which is generated by cleavage of transmembrane α-Klotho, remains incompletely understood. Genetic analyses might help to elucidate novel regulatory and functional mechanisms. The identification of genetic factors related to circulating α-Klotho further enables MR to examine causal relationships with other factors. The findings from the first GWAS meta-analysis of circulating α-Klotho levels identified six genome-wide significant signals across five genes. Given the function of two of the genes identified, B4GALNT3 and CHST9, it is tempting to speculate that post-translational modification significantly contributes to genetic influences on α-Klotho levels, presumably by affecting protein turnover and stability.

From genetics to systems biology of stress-related mental disorders

Many individuals will be exposed to some form of traumatic stress in their lifetime which, in turn, increases the likelihood of developing stress-related disorders such as post-traumatic stress disorder (PTSD), major depressive disorder (MDD) and anxiety disorders (ANX). The development of these disorders is also influenced by genetics and have heritability estimates ranging between ∼30 and 70%. In this review, we provide an overview of the findings of genome-wide association studies for PTSD, depression and ANX, and we observe a clear genetic overlap between these three diagnostic categories. We go on to highlight the results from transcriptomic and epigenomic studies, and, given the multifactorial nature of stress-related disorders, we provide an overview of the gene-environment studies that have been conducted to date. Finally, we discuss systems biology approaches that are now seeing wider utility in determining a more holistic view of these complex disorders.

Identification of novel loci influencing refractive error in East Asian populations using an extreme phenotype design

The global “myopia boom” has raised significant international concerns. Despite a higher myopia prevalence in Asia, previous large-scale genome-wide association studies (GWASs) were mostly based on European descendants. Here, we report a GWAS of spherical equivalent (SE) in 1852 Chinese Han individuals with extreme SE from Guangzhou (631 < −6.00D and 574 > 0.00D) and Wenzhou (593 < −6.00D and 54 > −1.75D), followed by a replication study in two independent cohorts with totaling 3538 East Asian individuals. The discovery GWAS and meta-analysis identify three novel loci, which show genome-wide significant associations with SE, including 1q25.2 FAM163A, 10p11.22 NRP1/PRAD3, and 10p11.21 ANKRD30A/MTRNR2L7, together explaining 3.34% of SE variance. 10p11.21 is successfully replicated. The allele frequencies of all three loci show significant differences between major continental groups (P < 0.001). The SE reducing (more myopic) allele of rs10913877 (1q25.2 FAM163A) demonstrates the highest frequency in East Asians and much lower frequencies in Europeans and Africans (EAS = 0.60, EUR = 0.20, and AFR = 0.18). The gene-based analysis additionally identifies three novel genes associated with SE, including EI24, LHX5, and ARPP19. These results provide new insights into myopia pathogenesis and indicate the role of genetic heterogeneity in myopia epidemiology among different ethnicities.

Genome-wide Association Study Identified Chromosome 8 Locus Associated with Medication-Related Osteonecrosis of the Jaw.

Medication‐related osteonecrosis of the jaw (MRONJ) is a rare but serious drug‐related adverse event. To identify pharmacogenomic markers of MRONJ associated with bisphosphonate therapy, we conducted a genomewide association study (GWAS) meta‐analysis followed by functional analysis of 5,008 individuals of European ancestry treated with bisphosphonates, which includes the largest number of MRONJ cases to date (444 cases and 4,564 controls). Discovery GWAS was performed in randomly selected 70% of the patients with cancer and replication GWAS was performed in the remaining 30% of the patients with cancer treated with intravenous bisphosphonates followed by meta‐analysis of all 3,639 patients with cancer. GWAS was also performed in 1,369 patients with osteoporosis treated with oral bisphosphonates. The lead single‐nucleotide polymorphism (SNP), rs2736308 on chromosome 8, was associated with an increased risk of MRONJ with an odds ratio (OR) of 2.71 and 95% confidence interval (CI) of 1.90–3.86 (P = 3.57*10−8) in the meta‐analysis of patients with cancer. This SNP was validated in the MRONJ GWAS in patients with osteoporosis (OR: 2.82, 95% CI: 1.55–4.09, P = 6.84*10−4). The meta‐analysis combining patients with cancer and patients with osteoporosis yielded the same lead SNP rs2736308 on chromosome 8 as the top SNP (OR: 2.74, 95% CI: 2.09–3.39, P = 9.65*10−11). This locus is associated with regulation of the BLK, CTSB, and FDFT1 genes, which had been associated with bone mineral density. FDFT1 encodes a membrane‐associated enzyme, which is implicated in the bisphosphonate pathway. This study provides insights into the potential mechanism of MRONJ.