A versatile gene-based test for genome-wide association studies

Neurotransmitter Pathway Genes in Cognitive Decline During Aging: Evidence for GNG4 and KCNQ2 Genes

BACKGROUND/RATIONALE

Experimental studies support the role of neurotransmitter genes in dementia risk, but human studies utilizing single variants in candidate genes have had limited success.

METHODS

We used the gene-based testing program Versatile Gene-based Association Study to assess whether aggregate variation across 6 neurotransmitter pathways influences risk of cognitive decline in 8159 cognitively normal elderly (≥65 years old) adults from 3 community-based cohorts.

RESULTS

Common genetic variation in GNG4 and KCNQ2 was associated with cognitive decline. In human brain tissue data sets, both GNG4 and KCNQ2 show higher expression in hippocampus relative to other brain regions; GNG4 expression decreases with advancing age. Both GNG4 and KCNQ2 show highest expression in fetal astrocytes.

CONCLUSION

Genetic variation analyses and gene expression data suggest that GNG4 and KCNQ2 may be associated with cognitive decline in normal aging. Gene-based testing of neurotransmitter pathways may confirm and reveal novel risk genes in future studies of healthy cognitive aging.

GPU Accelerated Browser for Neuroimaging Genomics

Neuroimaging genomics is an emerging field that provides exciting opportunities to understand the genetic basis of brain structure and function. The unprecedented scale and complexity of the imaging and genomics data, however, have presented critical computational bottlenecks. In this work we present our initial efforts towards building an interactive visual exploratory system for mining big data in neuroimaging genomics. A GPU accelerated browsing tool for neuroimaging genomics is created that implements the ANOVA algorithm for single nucleotide polymorphism (SNP) based analysis and the VEGAS algorithm for gene-based analysis, and executes them at interactive rates. The ANOVA algorithm is 110 times faster than the 4-core OpenMP version, while the VEGAS algorithm is 375 times faster than its 4-core OpenMP counter part. This approach lays a solid foundation for researchers to address the challenges of mining large-scale imaging genomics datasets via interactive visual exploration.

A sibling method for identifying vQTLs

The propensity of a trait to vary within a population may have evolutionary, ecological, or clinical significance. In the present study we deploy sibling models to offer a novel and unbiased way to ascertain loci associated with the extent to which phenotypes vary (variance-controlling quantitative trait loci, or vQTLs). Previous methods for vQTL-mapping either exclude genetically related individuals or treat genetic relatedness among individuals as a complicating factor addressed by adjusting estimates for non-independence in phenotypes. The present method uses genetic relatedness as a tool to obtain unbiased estimates of variance effects rather than as a nuisance. The family-based approach, which utilizes random variation between siblings in minor allele counts at a locus, also allows controls for parental genotype, mean effects, and non-linear (dominance) effects that may spuriously appear to generate variation. Simulations show that the approach performs equally well as two existing methods (squared Z-score and DGLM) in controlling type I error rates when there is no unobserved confounding, and performs significantly better than these methods in the presence of small degrees of confounding. Using height and BMI as empirical applications, we investigate SNPs that alter within-family variation in height and BMI, as well as pathways that appear to be enriched. One significant SNP for BMI variability, in the MAST4 gene, replicated. Pathway analysis revealed one gene set, encoding members of several signaling pathways related to gap junction function, which appears significantly enriched for associations with within-family height variation in both datasets (while not enriched in analysis of mean levels). We recommend approximating laboratory random assignment of genotype using family data and more careful attention to the possible conflation of mean and variance effects.

Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.

Associations of NADPH oxidase-related genes with blood pressure changes and incident hypertension: The GenSalt Study

Previous studies have indicated that reactive oxygen species produced by NADPH oxidase (Nox) are important risk factors of hypertension. The current study aims to examine the associations of Nox-related genes with longitudinal blood pressure (BP) changes and the risk of incident hypertension in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) follow-up study. A total of 1,768 participants from 633 families were included in our analysis. Nine BP measurements were obtained in the morning at baseline and during two follow-up visits. The mixed-effect models were used to investigate the associations of 52 tagged single-nucleotide polymorphisms in 11 Nox-related genes with BP changes and incident hypertension. Gene-based analyses were performed by truncated product method (TPM) and Versatile Gene-based Association Study (VEGAS). Over the 7.2 years of follow-up, systolic BP (SBP) and diastolic BP (DBP) increased, and 32.1% (512) of participants developed hypertension. SNPs rs12094228, rs16861188 and rs12066019 in NCF2 were significantly associated with longitudinal change in SBP (P_interaction = 1.1 × 10^-3, 2.8 × 10^-3 and 1.2 × 10^-3, respectively). Gene-based analyses revealed that NCF2 was significantly associated with SBP (P_TPM = 1.00 × 10^-6, P_VEGAS = 1.26 × 10^-4) and DBP changes (P_TPM = 5.84 × 10^-4, P_VEGAS = 1.04 × 10^-3). These findings suggested that NCF2 may play an important role in BP changes over time in the Han Chinese population.

A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

Blood levels of growth differentiation factor-15 (GDF-15), also known as macrophage inhibitory cytokine-1 (MIC-1), have been associated with various pathological processes and diseases, including cardiovascular disease and cancer. Prior studies suggest genetic factors play a role in regulating blood MIC-1/GDF-15 concentration. In the current study, we conducted the largest genome-wide association study (GWAS) to date using a sample of ∼5,400 community-based Caucasian participants, to determine the genetic variants associated with MIC-1/GDF-15 blood concentration. Conditional and joint (COJO), gene-based association, and gene-set enrichment analyses were also carried out to identify novel loci, genes, and pathways. Consistent with prior results, a locus on chromosome 19, which includes nine single nucleotide polymorphisms (SNPs) (top SNP, rs888663, p = 1.690 × 10^-35), was significantly associated with blood MIC-1/GDF-15 concentration, and explained 21.47% of its variance. COJO analysis showed evidence for two independent signals within this locus. Gene-based analysis confirmed the chromosome 19 locus association and in addition, a putative locus on chromosome 1. Gene-set enrichment analyses showed that the“COPI-mediated anterograde transport” gene-set was associated with MIC-1/GDF15 blood concentration with marginal significance after FDR correction (p = 0.067). In conclusion, a locus on chromosome 19 was associated with MIC-1/GDF-15 blood concentration with genome-wide significance, with evidence for a new locus (chromosome 1). Future studies using independent cohorts are needed to confirm the observed associations especially for the chromosomes 1 locus, and to further investigate and identify the causal SNPs that contribute to MIC-1/GDF-15 levels.

Integrative genomics identifies new genes associated with severe COPD and emphysema

BACKGROUND

Genome-wide association studies have identified several genetic risk loci for severe chronic obstructive pulmonary disease (COPD) and emphysema. However, these studies do not fully explain disease heritability and in most cases, fail to implicate specific genes. Integrative methods that combine gene expression data with GWAS can provide more power in discovering disease-associated genes and give mechanistic insight into regulated genes.

METHODS

We applied a recently described method that imputes gene expression using reference transcriptome data to genome-wide association studies for two phenotypes (severe COPD and quantitative emphysema) and blood and lung tissue gene expression datasets. We further tested the potential causality of individual genes using multi-variant colocalization.

RESULTS

We identified seven genes significantly associated with severe COPD, and five genes significantly associated with quantitative emphysema in whole blood or lung. We validated results in independent transcriptome databases and confirmed colocalization signals for PSMA4, EGLN2, WNT3, DCBLD1, and LILRA3. Three of these genes were not located within previously reported GWAS loci for either phenotype. We also identified genetically driven pathways, including those related to immune regulation.

CONCLUSIONS

An integrative analysis of GWAS and gene expression identified novel associations with severe COPD and quantitative emphysema, and also suggested disease-associated genes in known COPD susceptibility loci.

TRIAL REGISTRATION

NCT00608764 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: November 2007, Date Registered: January 28, 2008 (retrospectively registered); NCT00292552 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: December 2005, Date Registered: February 14, 2006 (retrospectively registered).

Multibreed genomic prediction using multitrait genomic residual maximum likelihood and multitask Bayesian variable selection

Genomic prediction is applicable to individuals of different breeds. Empirical results to date, however, show limited benefits in using information on multiple breeds in the context of genomic prediction. We investigated a multitask Bayesian model, presented previously by others, implemented in a Bayesian stochastic search variable selection (BSSVS) model. This model allowed for evidence of quantitative trait loci (QTL) to be accumulated across breeds or for both QTL that segregate across breeds and breed-specific QTL. In both cases, single nucleotide polymorphism effects were estimated with information from a single breed. Other models considered were a single-trait and multitrait genomic residual maximum likelihood (GREML) model, with breeds considered as different traits, and a single-trait BSSVS model. All single-trait models were applied to each of the 2 breeds separately and to the pooled data of both breeds. The data used included a training data set of 6,278 Holstein and 722 Jersey bulls, as well as 374 Jersey validation bulls. All animals had genotypes for 474,773 single nucleotide polymorphisms after editing and phenotypes for milk, fat, and protein yields. Using the same training data, BSSVS consistently outperformed GREML. The multitask BSSVS, however, did not outperform single-trait BSSVS, which used pooled Holstein and Jersey data for training. Thus, the rigorous assumption that the traits are the same in both breeds yielded a slightly better prediction than a model that had to estimate the correlation between the breeds from the data. Adding the Holstein data significantly increased the accuracy of the single-trait GREML and BSSVS in predicting the Jerseys for milk and protein, in line with estimated correlations between the breeds of 0.66 and 0.47 for milk and protein yields, whereas only the BSSVS model significantly improved the accuracy for fat yield with an estimated correlation between breeds of only 0.05. The relatively high genetic correlations for milk and protein yields, and the superiority of the pooling strategy, is likely the result of the observed admixture between both breeds in our data. The Bayesian model was able to detect several QTL in Holsteins, which likely enabled it to outperform GREML. The inability of the multitask Bayesian models to outperform a simple pooling strategy may be explained by the fact that the pooling strategy assumes equal effects in both breeds; furthermore, this assumption may be valid for moderate- to large-sized QTL, which are important for multibreed genomic prediction.

Heritability and Genome-Wide Association Analyses of Serum Uric Acid in Middle and Old-Aged Chinese Twins

Serum uric acid (SUA), as the end product of purine metabolism, has proven emerging roles in human disorders. Here based on a sample of 379 middle and old-aged Chinese twin pairs, we aimed to explore the magnitude of genetic impact on SUA variation by performing sex-limitation twin modeling analyses and further detect specific genetic variants related to SUA by conducting a genome-wide association study. Monozygotic (MZ) twin correlation for SUA level (rMZ = 0.56) was larger than for dizygotic (DZ) twin correlation (rDZ = 0.39). The common effects sex-limitation model provided the best fit with additive genetic parameter (A) accounting for 46.3%, common or shared environmental parameter (C) accounting for 26.3% and unique/nonshared environmental parameter (E) accounting for 27.5% for females and 29.9, 33.1, and 37.0% for males, respectively. Although no SUA-related genetic variants reached genome-wide significance level, 25 SNPs were suggestive of association (P < 1 × 10-5). Most of the SNPs were located in an intronic region and detected to have regulatory effects on gene transcription. The cell-type specific enhancer of skeletal muscle was detected which has been reported to implicate SUA. Two promising genetic regions on chromosome 17 around rs2253277 and chromosome 14 around rs11621523 were found. Gene-based analysis found 167 genes nominally associated with SUA level (P < 0.05), including PTGR2, ENTPD5, well-known SLC2A9, etc. Enrichment analysis identified one pathway of transmembrane transport of small molecules and 20 GO gene sets involving in ion transport, transmembrane transporter activity, hydrolase activity acting on acid anhydrides, etc. In conclusion, SUA shows moderate heritability in women and low heritability in men in the Chinese population and genetic variations are significantly involved in functional genes and regulatory domains that mediate SUA level. Our findings provide clues to further elucidate molecular physiology of SUA homeostasis and identify new diagnostic biomarkers and therapeutic targets for hyperuricemia and gout.

Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer's disease

BACKGROUND

Simultaneous consideration of two neuropathological traits related to Alzheimer's disease (AD) has not been attempted in a genome-wide association study.

METHODS

We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data.

RESULTS

Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10-8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10-8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10-6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10-3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10-3) and visual (P = 5.6 × 10-4) cortices.

CONCLUSIONS

Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target.

Regional enrichment analyses on genetic profiles for schizophrenia and bipolar disorder

Both schizophrenia (SZ) and bipolar disorder (BD) are highly heritable psychiatric disorders. The significant genomic risk loci are of great importance but with no guarantee of known functional impact and they cannot totally explain the genetic inheritance. In this study we present regional enrichment analyses across the genome, aiming to strike a balance between individual risk loci and integrated regional effects. Chromosomes were partitioned into 2 million base-pair regions (indicated by an underscore sign in the cytogenetic bands) on which enrichment tests are performed. In the discovery phase, we leverage the Psychiatric Genomics Consortium SZ and BD initial association test results for European Ancestry (EA) population and dbGAP SNP data for African Ancestry (AA) population. 78 and 48 regions show significantly enriched associations with SZ and BD respectively in the EA population, and nine are in common including MHC, 3p21.1, 7p22.3_2, 2q32.3_2, 8q24.3_4, and 19q13.33_1. The most unique SZ associated region is 1p21.3_3, while the most unique BD associated region is 6q25.2_1. For the AA population fewer regions are discovered with only 10% overlapping with that of EA population. A replication test using Wellcome Trust Case Control Consortium data for EA population verified 9% of the SZ enriched regions and 40% of the BD enriched regions. In summary, we showed that regional enrichment analyses produce reliable genetic association profiles using about one tenth of samples compared to single base-pair genome wide association approach. The identified association regions will be useful for further genetic functional studies.

Adjusting for Familial Relatedness in the Analysis of GWAS Data

Relatedness within a sample can be of ancient (population stratification) or recent (familial structure) origin, and can either be known (pedigree data) or unknown (cryptic relatedness). All of these forms of familial relatedness have the potential to confound the results of genome-wide association studies. This chapter reviews the major methods available to researchers to adjust for the biases introduced by relatedness and maximize power to detect associations. The advantages and disadvantages of different methods are presented with reference to elements of study design, population characteristics, and computational requirements.

PR Interval Associated Genes, Atrial Remodeling and Rhythm Outcome of Catheter Ablation of Atrial Fibrillation-A Gene-Based Analysis of GWAS Data

Background: PR interval prolongation has recently been shown to associate with advanced left atrial remodeling and atrial fibrillation (AF) recurrence after catheter ablation. While different genome-wide association studies (GWAS) have implicated 13 loci to associate with the PR interval as an AF endophenotype their subsequent associations with AF remodeling and response to catheter ablation are unknown. Here, we perform a gene-based analysis of GWAS data to test the hypothesis that PR interval candidate genes also associate with left atrial remodeling and arrhythmia recurrence following AF catheter ablation.

Methods and Results: Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing AF catheter ablation were genotyped for ~1,000,000 SNPs. Gene-based association was investigated using VEGAS (versatile gene-based association study). Among the 13 candidate genes, SLC8A1, MEIS1, ITGA9, SCN5A, and SOX5 associated with the PR interval. Of those, ITGA9 and SOX5 were significantly associated with left atrial low voltage areas and left atrial diameter and subsequently with AF recurrence after radiofrequency catheter ablation.

Conclusion: This study suggests contributions of ITGA9 and SOX5 to AF remodeling expressed as PR interval prolongation, low voltage areas and left atrial dilatation and subsequently to response to catheter ablation. Future and larger studies are necessary to replicate and apply these findings with the aim of designing AF pathophysiology-based multi-locus risk scores.

Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations

Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.

Methods and Tools in Genome-wide Association Studies

Many traits, such as height, the response to a given drug, or the susceptibility to certain diseases are presumably co-determined by genetics. Especially in the field of medicine, it is of major interest to identify genetic aberrations that alter an individual's risk to develop a certain phenotypic trait. Addressing this question requires the availability of comprehensive, high-quality genetic datasets. The technological advancements and the decreasing cost of genotyping in the last decade led to an increase in such datasets. Parallel to and in line with this technological progress, an analysis framework under the name of genome-wide association studies was developed to properly collect and analyze these data. Genome-wide association studies aim at finding statistical dependencies-or associations-between a trait of interest and point-mutations in the DNA. The statistical models used to detect such associations are diverse, spanning the whole range from the frequentist to the Bayesian setting.Since genetic datasets are inherently high-dimensional, the search for associations poses not only a statistical but also a computational challenge. As a result, a variety of toolboxes and software packages have been developed, each implementing different statistical methods while using various optimizations and mathematical techniques to enhance the computations.This chapter is devoted to the discussion of widely used methods and tools in genome-wide association studies. We present the different statistical models and the assumptions on which they are based, explain peculiarities of the data that have to be accounted for and, most importantly, introduce commonly used tools and software packages for the different tasks in a genome-wide association study, complemented with examples for their application.

Genome-Wide MicroRNA Analysis Implicates miR-30b/d in the Etiology of Alopecia Areata

Alopecia areata (AA) is one of the most common forms of human hair loss. Although genetic studies have implicated autoimmune processes in AA etiology, understanding of the etiopathogenesis is incomplete. Recent research has implicated microRNAs, a class of small noncoding RNAs, in diverse autoimmune diseases. To our knowledge, no study has investigated the role of microRNAs in AA. In this study, gene-based analyses were performed for microRNAs using data of the largest genome-wide association meta-analysis of AA to date. Nominally, significant P-values were obtained for 78 of the 617 investigated microRNAs. After correction for multiple testing, three of the 78 microRNAs remained significant. Of these, miR-30b/d was the most significant microRNA for the follow-up analyses, which also showed lower expression in the hair follicle of AA patients. Target gene analyses for the three microRNAs showed 42 significantly associated target genes. These included IL2RA, TNXB, and ERBB3, which had been identified as susceptibility loci in previous genome-wide association studies. Using luciferase assay, site-specific miR-30b regulation of the AA risk genes IL2RA, STX17, and TNXB was validated. This study implicates microRNAs in the pathogenesis of AA. This finding may facilitate the development of future treatment strategies.

Genome-Wide Gene-Potassium Interaction Analyses on Blood Pressure: The GenSalt Study (Genetic Epidemiology Network of Salt Sensitivity)

BACKGROUND

Gene-environmental interaction analysis can identify novel genetic factors for blood pressure (BP). We performed genome-wide analyses to identify genomic loci that interact with potassium to influence BP using single-marker (1 and 2 df joint tests) and gene-based tests among Chinese participants of the GenSalt study (Genetic Epidemiology Network of Salt Sensitivity).

METHODS AND RESULTS

Among 1876 GenSalt participants, the average of 3 urine samples was used to estimate potassium excretion. Nine BP measurements were taken using a random-zero sphygmomanometer. A total of 2.2 million single nucleotide polymorphisms were imputed using Affymetrix 6.0 genotype data and the Chinese Han of Beijing and Japanese of Tokyo HapMap reference panel. Promising findings (P<1.00×10-4) from GenSalt were evaluated for replication among 775 Chinese participants of the MESA (Multi-ethnic Study of Atherosclerosis). Single nucleotide polymorphism and gene-based results were meta-analyzed across the GenSalt and MESA studies to determine genome-wide significance. The 1 df tests identified interactions for ARL15 rs16882447 on systolic BP (P=2.83×10-9) and RANBP3L rs958929 on pulse pressure (P=1.58×10-8). The 2 df tests confirmed the ARL15 rs16882447 signal for systolic BP (P=1.15×10-9). Genome-wide gene-based analysis identified CC2D2A (P=2.59×10-7) at 4p15.32 and BNC2 (P=4.49×10-10) at 9p22.2 for systolic BP, GGNBP1 (P=1.18×10-8), and LINC00336 (P=1.36×10-8) at 6p21 for diastolic BP, DAB1 (P=1.05×10-13) at 1p32.2, and MIR4466 (P=5.34×10-8) at 6q25.3 for pulse pressure. The BNC2 (P=3.57×10-8) gene was also significant for mean arterial pressure.

CONCLUSIONS

We identified 2 novel BP loci and 6 genes through the examination of single nucleotide polymorphism- and gene-based interactions with potassium.

Copy number variation meta-analysis reveals a novel duplication at 9p24 associated with multiple neurodevelopmental disorders

Background

Neurodevelopmental and neuropsychiatric disorders represent a wide spectrum of heterogeneous yet inter-related disease conditions. The overlapping clinical presentations of these diseases suggest a shared genetic etiology. We aim to identify shared structural variants spanning the spectrum of five neuropsychiatric disorders.

Methods

We investigated copy number variations (CNVs) in five cohorts, including schizophrenia (SCZ), bipolar disease (BD), autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), and depression, from 7849 cases and 10,799 controls. CNVs were called based on intensity data from genome-wide SNP arrays and CNV frequency was compared between cases and controls in each disease cohort separately. Meta-analysis was performed via a gene-based approach. Quantitative PCR (qPCR) was employed to validate novel significant loci.

Results

In our meta-analysis, two genes containing CNVs with exonic overlap reached genome-wide significance threshold of meta P value < 9.4 × 10⁻⁶ for deletions and 7.5 × 10⁻⁶ for duplications. We observed significant overlap between risk CNV loci across cohorts. In addition, we identified novel significant associations of DOCK8/KANK1 duplications (meta P value = 7.5 × 10⁻⁷) across all cohorts, and further validated the CNV region with qPCR.

Conclusions

In the first large scale meta-analysis of CNVs across multiple neurodevelopmental/psychiatric diseases, we uncovered novel significant associations of structural variants in the locus of DOCK8/KANK1 shared by five diseases, suggesting common etiology of these clinically distinct neurodevelopmental conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0494-1) contains supplementary material, which is available to authorized users.

Functional mapping and annotation of genetic associations with FUMA

A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.

Prioritizing genetic variants is a major challenge in genome-wide association studies. Here, the authors develop FUMA, a web-based bioinformatics tool that uses a combination of positional, eQTL and chromatin interaction mapping to prioritize likely causal variants and genes.

Heritability and GWAS Analyses of Acne in Australian Adolescent Twins

Acne vulgaris is a skin disease with a multifactorial and complex pathology. While several twin studies have estimated that acne has a heritability of up to 80%, the genomic elements responsible for the origin and pathology of acne are still undiscovered. Here we performed a twin-based structural equation model, using available data on acne severity for an Australian sample of 4,491 twins and their siblings aged from 10 to 24. This study extends by a factor of 3 an earlier analysis of the genetic factors of acne. Acne severity was rated by nurses on a 4-point scale (1 = absent to 4 = severe) on up to three body sites (face, back, chest) and on up to three occasions (age 12, 14, and 16). The phenotype that we analyzed was the most severe rating at any site or age. The polychoric correlation for monozygotic twins was higher (r MZ = 0.86, 95% CI [0.81, 0.90]) than for dizygotic twins (r DZ = 0.42, 95% CI [0.35, 0.47]). A model that includes additive genetic effects and unique environmental effects was the most parsimonious model to explain the genetic variance of acne severity, and the estimated heritability was 0.85 (95% CI [0.82, 0.87]). We then conducted a genome-wide analysis including an additional 271 siblings - for a total of 4,762 individuals. A genome-wide association study (GWAS) scan did not detect loci associated with the severity of acne at the threshold of 5E-08 but suggestive association was found for three SNPs: rs10515088 locus 5q13.1 (p = 3.9E-07), rs12738078 locus 1p35.5 (p = 6.7E-07), and rs117943429 locus 18q21.2 (p = 9.1E-07). The 5q13.1 locus is close to PIK3R1, a gene that has a potential regulatory effect on sebocyte differentiation.

Inferring Relevant Cell Types for Complex Traits by Using Single-Cell Gene Expression

Previous studies have prioritized trait-relevant cell types by looking for an enrichment of genome-wide association study (GWAS) signal within functional regions. However, these studies are limited in cell resolution by the lack of functional annotations from difficult-to-characterize or rare cell populations. Measurement of single-cell gene expression has become a popular method for characterizing novel cell types, and yet limited work has linked single-cell RNA sequencing (RNA-seq) to phenotypes of interest. To address this deficiency, we present RolyPoly, a regression-based polygenic model that can prioritize trait-relevant cell types and genes from GWAS summary statistics and gene expression data. RolyPoly is designed to use expression data from either bulk tissue or single-cell RNA-seq. In this study, we demonstrated RolyPoly's accuracy through simulation and validated previously known tissue-trait associations. We discovered a significant association between microglia and late-onset Alzheimer disease and an association between schizophrenia and oligodendrocytes and replicating fetal cortical cells. Additionally, RolyPoly computes a trait-relevance score for each gene to reflect the importance of expression specific to a cell type. We found that differentially expressed genes in the prefrontal cortex of individuals with Alzheimer disease were significantly enriched with genes ranked highly by RolyPoly gene scores. Overall, our method represents a powerful framework for understanding the effect of common variants on cell types contributing to complex traits.

Systematical analyses of variants in DNase I hypersensitive sites to identify hepatocellular carcinoma susceptibility loci in a Chinese population

BACKGROUND AND AIM

Although several variants located at coding and non-coding regions were evaluated by previous studies, the evidence for associations between variants located in DNase I-hypersensitive sites (DHSs) and hepatocellular carcinoma (HCC) risk was still limited. Recent advances using ENCODE data indicated that genetic variants in DHSs played an important role in carcinogenesis. Therefore, systematically investigating the associations between regulatory variants in DHSs and HCC risk should be put on the agenda.

METHODS

We conducted a case-control design (1538 HCC cases vs 1465 normal controls) to evaluate the effects on HCC for the variants located at the uniform DNase I hypersensitive sites sequencing peaks in a Chinese population.

RESULTS

We found two novel single nucleotide polymorphisms rs12309362 (odds ratio = 0.64, P = 5.61 × 10^-6 ) and rs9970827 (odds ratio = 0.73, P = 7.23 × 10^-6 ) significantly associated with decreased risk of HCC. Conditional analysis proved that both of them independently contributed to the susceptibility of HCC. Expression quantitative trait loci analysis found that A allele of rs12309362 was significantly associated with an elevated expression of phosphatase phosphoglycerate mutase 5 in liver tissues. In addition, gene-based analysis indicated that CEBPB (P = 1 × 10^-4 ) was associated with the risk of HCC, and the expression of CEBPB was significantly lower in 50 The Cancer Genome Atlas HCC tumor tissues compared with matched normal tissues.

CONCLUSIONS

Our results indicated that rs12309362 (G > A), rs9970827 (A > G) in DHSs, and elevated expression of CEBPB were associated with a decreased risk of HCC. These results may contribute us to understand the function of regulatory DNA sequences in HCC development.

Cognitive genomics: Searching for the genetic roots of neuropsychological functioning

OBJECTIVE

Human cognition has long been known to be under substantial genetic control. With the complete mapping of the human genome, genome-wide association studies for many complex traits have proliferated; however, the highly polygenic nature of intelligence has made the identification of the precise genes that influence both global and specific cognitive abilities more difficult than anticipated.

METHOD

Here, we review the latest developments in the genomics of cognition, including a discussion of methodological advances in the genetic analysis of complex traits, and shared genetic contributions to cognitive abilities and neuropsychiatric disorders.

RESULTS

A wealth of twin and family studies have provided compelling evidence for a strong heritable component of both global and specific cognitive abilities, and for the existence of "generalist genes" responsible for a large portion of the variance in diverse cognitive abilities. Increasingly sophisticated analytic tools and ever-larger sample sizes are now facilitating the identification of specific genetic and molecular underpinnings of cognitive abilities, leading to optimism regarding possibilities for novel treatments for illnesses related to cognitive function.

CONCLUSIONS

We conclude with a set of future directions for the field, which will further accelerate discoveries regarding the biological pathways relevant to cognitive abilities. These, in turn, may be further interrogated in order to link biological mechanisms to behavior. (PsycINFO Database Record

COMBAT: A Combined Association Test for Genes Using Summary Statistics

Genome-wide association studies (GWAS) have been widely used for identifying common variants associated with complex diseases. Traditional analysis of GWAS typically examines one marker at a time, usually single nucleotide polymorphisms (SNPs), to identify individual variants associated with a disease. However, due to the small effect sizes of common variants, the power to detect individual risk variants is generally low. As a complementary approach to SNP-level analysis, a variety of gene-based association tests have been proposed. However, the power of existing gene-based tests is often dependent on the underlying genetic models, and it is not known a priori which test is optimal. Here we propose a combined association test (COMBAT) for genes, which incorporates strengths from existing gene-based tests and shows higher overall performance than any individual test. Our method does not require raw genotype or phenotype data, but needs only SNP-level P-values and correlations between SNPs from ancestry-matched samples. Extensive simulations showed that COMBAT has an appropriate type I error rate, maintains higher power across a wide range of genetic models, and is more robust than any individual gene-based test. We further demonstrated the superior performance of COMBAT over several other gene-based tests through reanalysis of the meta-analytic results of GWAS for bipolar disorder. Our method allows for the more powerful application of gene-based analysis to complex diseases, which will have broad use given that GWAS summary results are increasingly publicly available.

Rethinking ovarian cancer genomics: where genome-wide association studies stand?

Genome-wide association studies (GWAS) allow the finding of genetic variants associated with several traits. Regarding ovarian cancer (OC), 15 GWAS have been conducted since 2009, with the discovery of 49 SNPs associated with disease susceptibility and 46 with impact in the clinical outcome of patients (p < 5.00 × 10-2). Among them, 14 variants reached the genome-wide significance (p < 5.00 × 10−8). Despite the results obtained, they should be validated in independent sets. So far, five validation studies have been conducted which could confirm the association of 12 OC susceptibility SNPs. Consequently, post-GWAS studies are crucial unravel the biological plausibility of GWAS’ findings and the allelic spectrum of OC.

Genome-Wide Meta-Analysis Unravels Interactions between Magnesium Homeostasis and Metabolic Phenotypes

Magnesium (Mg²⁺) homeostasis is critical for metabolism. However, the genetic determinants of the renal handling of Mg²⁺, which is crucial for Mg²⁺ homeostasis, and the potential influence on metabolic traits in the general population are unknown. We obtained plasma and urine parameters from 9099 individuals from seven cohorts, and conducted a genome-wide meta-analysis of Mg²⁺ homeostasis. We identified two loci associated with urinary magnesium (uMg), rs3824347 (P=4.4×10^-13) near TRPM6, which encodes an epithelial Mg²⁺ channel, and rs35929 (P=2.1×10^-11), a variant of ARL15, which encodes a GTP-binding protein. Together, these loci account for 2.3% of the variation in 24-hour uMg excretion. In human kidney cells, ARL15 regulated TRPM6-mediated currents. In zebrafish, dietary Mg²⁺ regulated the expression of the highly conserved ARL15 ortholog arl15b, and arl15b knockdown resulted in renal Mg²⁺ wasting and metabolic disturbances. Finally, ARL15 rs35929 modified the association of uMg with fasting insulin and fat mass in a general population. In conclusion, this combined observational and experimental approach uncovered a gene-environment interaction linking Mg²⁺ deficiency to insulin resistance and obesity.

GWAS identifies population-specific new regulatory variants in FUT6 associated with plasma B12 concentrations in Indians

Vitamin B12 is an important cofactor in one-carbon metabolism whose dysregulation is associated with various clinical conditions. Indians have a high prevalence of B12 deficiency but little is known about the genetic determinants of circulating B12 concentrations in Indians. We performed a genome-wide association study in 1001 healthy participants in the Pune Maternal Nutrition Study (PMNS), replication studies in 3418 individuals from other Indian cohorts and by meta-analysis identified new variants, rs3760775 (P = 1.2 × 10⁻²³) and rs78060698 (P = 8.3 × 10⁻¹⁷) in FUT6 to be associated with circulating B12 concentrations. Although in-silico analysis replicated both variants in Europeans, differences in the effect allele frequency, effect size and the linkage disequilibrium structure of credible set variants with the reported variants suggest population-specific characteristics in this region. We replicated previously reported variants rs602662, rs601338 in FUT2, rs3760776, rs708686 in FUT6, rs34324219 in TCN1 (all P < 5 × 10⁻⁸), rs1131603 in TCN2 (P = 3.4 × 10⁻⁵), rs12780845 in CUBN (P = 3.0 × 10⁻³) and rs2270655 in MMAA (P = 2.0 × 10⁻³). Circulating B12 concentrations in the PMNS and Parthenon study showed a significant decline with increasing age (P < 0.001), however, the genetic contribution to B12 concentrations remained constant. Luciferase reporter and electrophoretic-mobility shift assay for the FUT6 variant rs78060698 using HepG2 cell line demonstrated strong allele-specific promoter and enhancer activity and differential binding of HNF4α, a key regulator of expression of various fucosyltransferases. Hence, the rs78060698 variant, through regulation of fucosylation may control intestinal host-microbial interaction which could influence B12 concentrations. Our results suggest that in addition to established genetic variants, population-specific variants are important in determining plasma B12 concentrations.

Gene-based association studies report genetic links for clinical subtypes of frontotemporal dementia

Genome-wide association studies in frontotemporal dementia showed limited success in identifying associated loci. This is possibly due to small sample size, allelic heterogeneity, small effect sizes of single genetic variants, and the necessity to statistically correct for testing millions of genetic variants. To overcome these issues, we performed gene-based association studies on 3348 clinically identified frontotemporal dementia cases and 9390 controls (discovery, replication and joint-cohort analyses). We report association of APOE and TOMM40 with behavioural variant frontotemporal dementia, and ARHGAP35 and SERPINA1 with progressive non-fluent aphasia. Further, we found the ɛ2 and ɛ4 alleles of APOE harbouring protective and risk increasing effects, respectively, in clinical subtypes of frontotemporal dementia against neurologically normal controls. The APOE-locus association with behavioural variant frontotemporal dementia indicates its potential risk-increasing role across different neurodegenerative diseases, whereas the novel genetic associations of ARHGAP35 and SERPINA1 with progressive non-fluent aphasia point towards a potential role of the stress-signalling pathway in its pathophysiology.

A Novel Approach for Pathway Analysis of GWAS Data Highlights Role of BMP Signaling and Muscle Cell Differentiation in Colorectal Cancer Susceptibility

Genome-wide association studies (GWAS) have revolutionized the field of gene mapping. As the GWAS field matures, it is becoming clear that for many complex traits, a proportion of the missing heritability is attributable to common variants of individually small effect. Detecting these small effects individually can be difficult, and statistical power would be increased if relevant variants could be grouped together for testing. Here, we propose a VEGAS2Pathway approach that aggregates association strength of individual markers into pre-specified biological pathways. It accounts for gene size and linkage disequilibrium between markers using simulations from the multivariate normal distribution. Pathway size is taken into account via a resampling approach. Importantly, since the approach only requires summary data, the method can easily be applied in all GWASs, including meta-analysis, singleton-based, family-based, and DNA-pooling-based designs. This approach is implemented in a user-friendly web page https://vegas2.qimrberghofer.edu.au and a command line tool. The web implementation uses gene-sets from the gene ontology (GO), curated gene-sets from MSigDB (containing canonical pathways and gene-sets from BIOCARTA, REACTOME, KEGG databases), PANTHER, and pathway commons databases, enabling analysis of a wide range of complex traits. We applied this method on a colorectal cancer GWAS meta-analysis data set (10,934 cases, 12,328 controls) from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). We report statistically significant enrichment of association signal for the 'BMP signaling' and 'muscle cell differentiation' pathways, suggesting a possible role for these pathways onto the risk of colorectal cancer.

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a "Regression with Summary Statistics" (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss.

A pathway analysis of genome-wide association study highlights novel type 2 diabetes risk pathways

Genome-wide association studies (GWAS) have been widely used to identify common type 2 diabetes (T2D) variants. However, the known variants just explain less than 20% of the overall estimated genetic contribution to T2D. Pathway-based methods have been applied into T2D GWAS datasets to investigate the biological mechanisms and reported some novel T2D risk pathways. However, few pathways were shared in these studies. Here, we performed a pathway analysis using the summary results from a large-scale meta-analysis of T2D GWAS to investigate more genetic signals in T2D. Here, we selected PLNK and VEGAS to perform the gene-based test and WebGestalt to perform the pathway-based test. We identified 8 shared KEGG pathways after correction for multiple tests in both methods. We confirm previous findings, and highlight some new T2D risk pathways. We believe that our results may be helpful to study the genetic mechanisms of T2D.

A genome-wide association study of cognitive function in Chinese adult twins

Multiple loci or genes have been identified using genome-wide association studies mainly in western countries but with inconsistent results. No similar studies have been conducted in the world's largest and rapidly aging Chinese population. The paper aimed to identify the specific genetic variants associated with cognitive function in middle and old-aged Chinese dizygotic twins (DZ). Cognitive function was measured on 139 pairs of DZ by Montreal Cognitive Assessment. The subjects were genotyped at 1048575 SNP positions. Regression-based mixed-effect kinship model of GWAS was conducted to test the SNPs. Gene-based analysis was performed on VEGAS2. The statistically significant genes were then subject to gene set enrichment analysis to further identify the specific biological pathways associated with cognitive function. No SNPs reached genome-wide significance although there were 13 SNPs of suggestive significance (P < 10-5). Gene-based analysis found 823 significant genes topped by TNRC18P1 (P = 1.00 × 10-6), FGFR1OP2 (P = 6.00 × 10-6), and AKR1D1 (P = 2.30 × 10-5). Enrichment analysis identified 46 biological pathways, mainly involving in signaling transmission, metabolic process and Alzheimer's disease. Analysis of SNPs involved in the regulatory motif detected cell-type specific enhancers involving aorta and colon smooth muscle both have been reported to implicate in cognition. We conclude that genetic variations are significantly involved in functional genes, biological pathways and the regulatory domain that mediate cognitive performances.

Genome-Wide Association Study of Psychosis Proneness in the Finnish Population

The current study examined quantitative measures of psychosis proneness in a nonpsychotic population, in order to elucidate their underlying genetic architecture and to observe if there is any commonality to that already detected in the studies of individuals with overt psychotic conditions, such as schizophrenia and bipolar disorder. Heritability, univariate and multivariate genome-wide association (GWAs) tests, including a series of comprehensive gene-based association analyses, were developed in 4269 nonpsychotic persons participating in the Northern Finland Birth Cohort 1966 study with information on the following psychometric measures: Hypomanic Personality, Perceptual Aberration, Physical and Social Anhedonia (also known as Chapman's Schizotypia scales), and Schizoidia scale. Genome-wide genetic data was available for ~9.84 million SNPs. Heritability estimates ranged from 16% to 27%. Phenotypic, genetic and environmental correlations ranged from 0.04-0.43, 0.25-0.73, and 0.12-0.43, respectively. Univariate GWAs tests revealed an intronic SNP (rs12449097) at the TMC7 gene (16p12.3) that significantly associated (P = 3.485 × 10-8) with the hypomanic scale. Bivariate GWAs tests including the hypomanic and physical anhedonia scales suggested a further borderline significant SNP (rs188320715; P-value = 5.261 × 10-8, ~572 kb downstream the ARID1B gene at 6q25.3). Gene-based tests highlighted 20 additional genes of which 5 had previously been associated to schizophrenia and/or bipolar disorder: CSMD1, CCDC141, SLC1A2, CACNA1C, and SNAP25. Altogether the findings explained from 3.7% to 14.1% of the corresponding trait heritability. In conclusion, this study provides preliminary genomic evidence suggesting that qualitatively similar biological factors may underlie different psychosis proneness measures, some of which could further predispose to schizophrenia and bipolar disorder.

Genome-wide scan in Hispanics highlights candidate loci for brain white matter hyperintensities

Objective:

To investigate genetic variants influencing white matter hyperintensities (WMHs) in the understudied Hispanic population.

Methods:

Using 6.8 million single nucleotide polymorphisms (SNPs), we conducted a genome-wide association study (GWAS) to identify SNPs associated with WMH volume (WMHV) in 922 Hispanics who underwent brain MRI as a cross-section of 2 community-based cohorts in the Northern Manhattan Study and the Washington Heights–Inwood Columbia Aging Project. Multiple linear modeling with PLINK was performed to examine the additive genetic effects on ln(WMHV) after controlling for age, sex, total intracranial volume, and principal components of ancestry. Gene-based tests of association were performed using VEGAS. Replication was performed in independent samples of Europeans, African Americans, and Asians.

Results:

From the SNP analysis, a total of 17 independent SNPs in 7 genes had suggestive evidence of association with WMHV in Hispanics (p < 1 × 10⁻⁵) and 5 genes from the gene-based analysis with p < 1 × 10⁻³. One SNP (rs9957475 in GATA6) and 1 gene (UBE2C) demonstrated evidence of association (p < 0.05) in the African American sample. Four SNPs with p < 1 × 10⁻⁵ were shown to affect binding of SPI1 using RegulomeDB.

Conclusions:

This GWAS of 2 community-based Hispanic cohorts revealed several novel WMH-associated genetic variants. Further replication is needed in independent Hispanic samples to validate these suggestive associations, and fine mapping is needed to pinpoint causal variants.

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

Background

Autoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4⁺ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes.

Results

Within 4 h, activation of CD4⁺ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases, we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach.

Conclusions

Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1285-0) contains supplementary material, which is available to authorized users.

Shared genetic variants for polypoidal choroidal vasculopathy and typical neovascular age-related macular degeneration in East Asians

Polypoidal choroidal vasculopathy (PCV), a subtype of age-related macular degeneration (AMD) more frequently seen in East Asians, has both common and distinct clinical manifestations with typical neovascular AMD (tAMD). We aim to examine the extent to which common genetic variants are shared between these two subtypes. We performed the meta-analysis of association in a total of 1062 PCV patients, 1157 tAMD patients and 5275 controls of East Asian descent from the Genetics of AMD in Asians Consortium at the 34 known AMD loci. A total of eight loci were significantly associated with PCV, including age-related maculopathy susceptibility 2 (ARMS2)-HtrA serine peptidase 1 (HTRA1), complement factor H (CFH), C2-CFB-SKIV2L, CETP, VEGFA, ADAMTS9-AS2 and TGFBR1 (P<5 × 10^-4) from the single-nucleotide polymorphism-based test and COL4A3 from the gene-based tests (P_gene=2.02 × 10^-4). PCV and tAMD are genetically highly correlated (r_g=0.69, P=4.68 × 10^-3), with AMD known loci accounting for up to 36% variation. Weaker association for PCV was observed at ARMS2-HTRA1 (P_dif=4.39 × 10^-4) and KMT2E-SRPK2(P_dif=4.43 × 10^-3), compared with tAMD. Variants at CFH, CETP and VEGFA exhibited different association signals in East Asians, in contrast to those in European individuals. Our data suggest a substantially shared genetic susceptibility for PCV and tAMD, while also highlight the unique associations for PCV, which is useful in understanding the pathogenesis of PCV.

The SNP-set based association study identifies ITGA1 as a susceptibility gene of attention-deficit/hyperactivity disorder in Han Chinese

Genome-wide association studies, which detect the association between single-nucleotide polymorphisms (SNPs) and disease susceptibility, have been extensively applied to study attention-deficit/hyperactivity disorder (ADHD), but genome-wide significant associations have not been found yet. Genetic heterogeneity and insufficient genomic coverage may account for the missing heritability. We performed a two-stage association study for ADHD in the Han Chinese population. In the discovery stage, 1033 ADHD patients and 950 healthy controls were genotyped using both the Affymetrix Genome-Wide Human SNP Array 6.0 and the Illumina Infinium HumanExome BeadChip. The genotyped SNPs were combined to generate a powerful SNP set with better genomic coverage especially for the nonsynonymous variants. In addition to the association of single SNPs, we collected adjacent SNPs as SNP sets, which were determined by either genes or successive sliding windows, to evaluate their synergetic effect. The candidate susceptibility SNPs were further replicated in an independent cohort of 1441 ADHD patients and 1447 healthy controls. No genome-wide significant SNPs or gene-based SNP sets were found to be associated with ADHD. However, two continuous sliding windows located in ITGA1 (P-value=8.33E-7 and P-value=8.43E-7) were genome-wide significant. The quantitative trait analyses also demonstrated their association with ADHD core symptoms and executive functions. The association was further validated by follow-up replications for four selected SNPs: rs1979398 (P-value=2.64E-6), rs16880453 (P-value=3.58E-4), rs1531545 (P-value=7.62E-4) and rs4074793 (P-value=2.03E-4). Our results suggest that genetic variants in ITGA1 may be involved in the etiology of ADHD and the SNP-set based analysis is a promising strategy for the detection of underlying genetic risk factors.

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology.

Exome Sequencing of Extended Families with Alzheimer's Disease Identifies Novel Genes Implicated in Cell Immunity and Neuronal Function

Objective

Alzheimer’s disease (AD) is a neurodegenerative disorder for which more than 20 genetic loci have been implicated to date. However, studies demonstrate not all genetic factors have been identified. Therefore, in this study we seek to identify additional rare variants and novel genes potentially contributing to AD.

Methods

Whole exome sequencing was performed on 23 multi-generational families with an average of eight affected subjects. Exome sequencing was filtered for rare, nonsynonymous and loss-of-function variants. Alterations predicted to have a functional consequence and located within either a previously reported AD gene, a linkage peak (LOD>2), or clustering in the same gene across multiple families, were prioritized.

Results

Rare variants were found in known AD risk genes including AKAP9, CD33, CR1, EPHA1, INPP5D, NME8, PSEN1, SORL1, TREM2 and UNC5C. Three families had five variants of interest in linkage regions with LOD>2. Genes with segregating alterations in these peaks include CD163L1 and CLECL1, two genes that have both been implicated in immunity, CTNNA1, which encodes a catenin in the cerebral cortex and MIEF1, a gene that may induce mitochondrial dysfunction and has the potential to damage neurons. Four genes were identified with alterations in more than one family include PLEKHG5, a gene that causes Charcot-Marie-Tooth disease and THBS2, which promotes synaptogenesis.

Conclusion

Utilizing large families with a heavy burden of disease allowed for the identification of rare variants co-segregating with disease. Variants were identified in both known AD risk genes and in novel genes.

Glucocorticoid therapy regulates podocyte motility by inhibition of Rac1

Nephrotic syndrome (NS) occurs when the glomerular filtration barrier becomes excessively permeable leading to massive proteinuria. In childhood NS, immune system dysregulation has been implicated and increasing evidence points to the central role of podocytes in the pathogenesis. Children with NS are typically treated with an empiric course of glucocorticoid (Gc) therapy; a class of steroids that are activating ligands for the glucocorticoid receptor (GR) transcription factor. Although Gc-therapy has been the cornerstone of NS management for decades, the mechanism of action, and target cell, remain poorly understood. We tested the hypothesis that Gc acts directly on the podocyte to produce clinically useful effects without involvement of the immune system. In human podocytes, we demonstrated that the basic GR-signalling mechanism is intact and that Gc induced an increase in podocyte barrier function. Defining the GR-cistrome identified Gc regulation of motility genes. These findings were functionally validated with live-cell imaging. We demonstrated that treatment with Gc reduced the activity of the pro-migratory small GTPase regulator Rac1. Furthermore, Rac1 inhibition had a direct, protective effect on podocyte barrier function. Our studies reveal a new mechanism for Gc action directly on the podocyte, with translational relevance to designing new selective synthetic Gc molecules.

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution

RATIONALE

Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe-predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown.

OBJECTIVES

To identify the genetic influences of emphysema distribution in non-alpha-1 antitrypsin-deficient smokers.

METHODS

A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism-, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed.

MEASUREMENTS AND MAIN RESULTS

We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution.

CONCLUSIONS

This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Gene-wide Association Study Reveals RNF122 Ubiquitin Ligase as a Novel Susceptibility Gene for Attention Deficit Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder (ADHD) is a common childhood-onset neurodevelopmental condition characterized by pervasive impairment of attention, hyperactivity, and/or impulsivity that can persist into adulthood. The aetiology of ADHD is complex and multifactorial and, despite the wealth of evidence for its high heritability, genetic studies have provided modest evidence for the involvement of specific genes and have failed to identify consistent and replicable results. Due to the lack of robust findings, we performed gene-wide and pathway enrichment analyses using pre-existing GWAS data from 607 persistent ADHD subjects and 584 controls, produced by our group. Subsequently, expression profiles of genes surpassing a follow-up threshold of P-value < 1e-03 in the gene-wide analyses were tested in peripheral blood mononucleated cells (PBMCs) of 45 medication-naive adults with ADHD and 39 healthy unrelated controls. We found preliminary evidence for genetic association between RNF122 and ADHD and for its overexpression in adults with ADHD. RNF122 encodes for an E3 ubiquitin ligase involved in the proteasome-mediated processing, trafficking, and degradation of proteins that acts as an essential mediator of the substrate specificity of ubiquitin ligation. Thus, our findings support previous data that place the ubiquitin-proteasome system as a promising candidate for its involvement in the aetiology of ADHD.

Associations Between Vocal Symptoms and Genetic Variants in the Oxytocin Receptor and Arginine Vasopressin 1A Receptor Gene

PURPOSE

Oxytocin and arginine vasopressin are associated with different aspects of the stress response. As stress is regarded as a risk factor for vocal symptoms, we wanted to explore the association between the oxytocin receptor gene (OXTR) and arginine vasopressin 1A receptor gene (AVPR1A) single-nucleotide polymorphisms (SNPs) and vocal symptoms. We also wanted to explore whether such effects might be mediated by cortisol because oxytocin and vasopressin are associated with cortisol levels.

METHOD

A population-based sample (N = 657) of Finnish twins (born 1961-1989) completed a web questionnaire on the occurrence of vocal symptoms. A total of 170 participants submitted saliva samples for hormone analysis. A total of 20 OXTR and AVPR1A SNPs were analyzed.

RESULTS

Three OXTR polymorphisms (rs2270465, rs2268493, rs7632287) and 2 AVPR1A polymorphisms (rs1587097, rs1042615) showed nominal effects (p < .05) on vocal symptoms, of which 1 (rs1587097) remained significant after correcting for multiple testing (p = .003). We found potential mediation of the effect of the OXTR rs2268493 polymorphism on vocal symptoms through levels of cortisol.

CONCLUSIONS

The associations between variants of OXTR and AVPR1A and vocal symptoms indicate that oxytocin and vasopressin might influence vocal symptoms. The effect of oxytocin seems to be partly mediated through cortisol actions.

Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness

Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 × 10-8) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality.

10 Years of GWAS Discovery: Biology, Function, and Translation

Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.