Transethnic differences in GWAS signals: A simulation study

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Common Risk Variants in AHI1 Are Associated With Childhood Steroid Sensitive Nephrotic Syndrome

Introduction

Steroid-sensitive nephrotic syndrome (SSNS) is the most common form of kidney disease in children worldwide. Genome-wide association studies (GWAS) have demonstrated the association of SSNS with genetic variation at HLA-DQ/DR and have identified several non-HLA loci that aid in further understanding of disease pathophysiology. We sought to identify additional genetic loci associated with SSNS in children of Sri Lankan and European ancestry.

Methods

We conducted a GWAS in a cohort of Sri Lankan individuals comprising 420 pediatric patients with SSNS and 2339 genetic ancestry matched controls obtained from the UK Biobank. We then performed a transethnic meta-analysis with a previously reported European cohort of 422 pediatric patients and 5642 controls.

Results

Our GWAS confirmed the previously reported association of SSNS with HLA-DR/DQ (rs9271602, P = 1.12 × 10-27, odds ratio [OR] = 2.75). Transethnic meta-analysis replicated these findings and identified a novel association at AHI1 (rs2746432, P = 2.79 × 10-8, OR = 1.37), which was also replicated in an independent South Asian cohort. AHI1 is implicated in ciliary protein transport and immune dysregulation, with rare variation in this gene contributing to Joubert syndrome type 3.

Conclusions

Common variation in AHI1 confers risk of the development of SSNS in both Sri Lankan and European populations. The association with common variation in AHI1 further supports the role of immune dysregulation in the pathogenesis of SSNS and demonstrates that variation across the allele frequency spectrum in a gene can contribute to disparate monogenic and polygenic diseases.

The genetic and evolutionary basis of gene expression variation in East Africans

BACKGROUND

Mapping of quantitative trait loci (QTL) associated with molecular phenotypes is a powerful approach for identifying the genes and molecular mechanisms underlying human traits and diseases, though most studies have focused on individuals of European descent. While important progress has been made to study a greater diversity of human populations, many groups remain unstudied, particularly among indigenous populations within Africa. To better understand the genetics of gene regulation in East Africans, we perform expression and splicing QTL mapping in whole blood from a cohort of 162 diverse Africans from Ethiopia and Tanzania. We assess replication of these QTLs in cohorts of predominantly European ancestry and identify candidate genes under selection in human populations.

RESULTS

We find the gene regulatory architecture of African and non-African populations is broadly shared, though there is a considerable amount of variation at individual loci across populations. Comparing our analyses to an equivalently sized cohort of European Americans, we find that QTL mapping in Africans improves the detection of expression QTLs and fine-mapping of causal variation. Integrating our QTL scans with signatures of natural selection, we find several genes related to immunity and metabolism that are highly differentiated between Africans and non-Africans, as well as a gene associated with pigmentation.

CONCLUSION

Extending QTL mapping studies beyond European ancestry, particularly to diverse indigenous populations, is vital for a complete understanding of the genetic architecture of human traits and can reveal novel functional variation underlying human traits and disease.

Genome-wide association study of the risk of chronic kidney disease and kidney-related traits in the Japanese population: J-Kidney-Biobank

Chronic kidney disease (CKD) is a syndrome characterized by a gradual loss of kidney function with decreased estimated glomerular filtration rate (eGFR), which may be accompanied by an increase in the urine albumin-to-creatinine ratio (UACR). Although trans-ethnic genome-wide association studies (GWASs) have been conducted for kidney-related traits, there have been few analyses in the Japanese population, especially for the UACR trait. In this study, we conducted a GWAS to identify loci related to multiple kidney-related traits in Japanese individuals. First, to detect loci associated with CKD, eGFR, and UACR, we performed separate GWASs with the following two datasets: 475 cases of CKD diagnosed at seven university hospitals and 3471 healthy subjects (dataset 1) and 3664 cases of CKD-suspected individuals with eGFR <60 ml/min/1.73 m² or urinary protein ≥ 1+ and 5952 healthy subjects (dataset 2). Second, we performed a meta-analysis between these two datasets and detected the following associated loci: 10 loci for CKD, 9 loci for eGFR, and 22 loci for UACR. Among the loci detected, 22 have never been reported previously. Half of the significant loci for CKD were shared with those for eGFR, whereas most of the loci associated with UACR were different from those associated with CKD or eGFR. The GWAS of the Japanese population identified novel genetic components that were not previously detected. The results also suggest that the group primarily characterized by increased UACR possessed genetically different features from the group characterized by decreased eGFR.

Social Adversity Reduces Polygenic Score Expressivity for General Cognitive Ability, but Not Height

It has been hypothesized that even 'perfect' polygenic scores (PGSs) composed of only causal variants may not be fully portable between different social groups owing to gene-by-environment interactions modifying the expression of relevant variants. The impacts of such interactions involving two forms of social adversity (low socioeconomic status [SES] and discrimination) are examined in relation to the expressivity of a PGS for educational attainment composed of putatively causal variants in a large, representatively sampled and genotyped cohort of US children. A relatively small-magnitude Scarr-Rowe effect is present (SES × PGSEDU predicting General Cognitive Ability [GCA]; sR = .02, 95% CI [.00, .04]), as is a distinct discrimination × PGSEDU interaction predicting GCA (sR = -.02, 95% CI [-.05, 00]). Both are independent of the confounding main effects of 10 ancestral principal components, PGSEDU, SES, discrimination and interactions among these factors. No sex differences were found. These interactions were examined in relation to phenotypic and genotypic data on height, a prospectively more socially neutral trait. They were absent in both cases. The discrimination × PGSEDU interaction is a co-moderator of the differences posited in modern versions of Spearman's hypothesis (along with shared environmentality), lending support to certain environmental explanations of those differences. Behavior-genetic analysis of self-reported discrimination indicates that it is nonsignificantly heritable (h2 = .027, 95% CI [-.05, .10]), meaning that it is not merely proxying some underlying source of heritable phenotypic variability. This suggests that experiences of discrimination might stem instead from the action of purely social forces.

Histone acetylome-wide associations in immune cells from individuals with active Mycobacterium tuberculosis infection

Host cell chromatin changes are thought to play an important role in the pathogenesis of infectious diseases. Here we describe a histone acetylome-wide association study (HAWAS) of an infectious disease, on the basis of genome-wide H3K27 acetylation profiling of peripheral blood granulocytes and monocytes from persons with active Mycobacterium tuberculosis (Mtb) infection and healthy controls. We detected >2,000 differentially acetylated loci in either cell type in a Singapore Chinese discovery cohort (n = 46), which were validated in a subsequent multi-ethnic Singapore cohort (n = 29), as well as a longitudinal cohort from South Africa (n = 26), thus demonstrating that HAWAS can be independently corroborated. Acetylation changes were correlated with differential gene expression. Differential acetylation was enriched near potassium channel genes, including KCNJ15, which modulates apoptosis and promotes Mtb clearance in vitro. We performed histone acetylation quantitative trait locus (haQTL) analysis on the dataset and identified 69 candidate causal variants for immune phenotypes among granulocyte haQTLs and 83 among monocyte haQTLs. Our study provides proof-of-principle for HAWAS to infer mechanisms of host response to pathogens.

Genome-wide histone acetylation profiling in cohorts of patients with active and latent tuberculosis reveals acetylation changes in host immune cells modulating potassium channel expression and apoptosis response.

Influence of Cannabinoid Receptor 1 Genetic Variants on the Subjective Effects of Smoked Cannabis

As many jurisdictions consider relaxing cannabis legislation and usage is increasing in North America and other parts of the world, there is a need to explore the possible genetic differences underlying the subjective effects of cannabis. This pilot study investigated specific genetic variations within the cannabinoid receptor 1 (CNR1) gene for association with the subjective effects of smoked cannabis. Data were obtained from a double-blinded, placebo-controlled clinical trial studying the impact of cannabis intoxication on driving performance. Participants randomized to the active cannabis group who consented to secondary genetic analysis (n = 52) were genotyped at the CNR1 rs1049353 and rs2023239 polymorphic areas. Maximum value and area under the curve (AUC) analyses were performed on subjective measures data. Analysis of subjective effects by genotype uncovered a global trend towards greater subjective effects for rs1049353 T-allele- and rs2023239 C-allele-carrying subjects. However, significant differences attributed to allelic identity were only documented for a subset of subjective effects. Our findings suggest that rs1049353 and rs2023239 minor allele carriers experience augmented subjective effects during acute cannabis intoxication.

Genetic influences on susceptibility to rheumatoid arthritis in African-Americans

Large meta-analyses of rheumatoid arthritis (RA) susceptibility in European (EUR) and East Asian (EAS) populations have identified >100 RA risk loci, but genome-wide studies of RA in African-Americans (AAs) are absent. To address this disparity, we performed an analysis of 916 AA RA patients and 1392 controls and aggregated our data with genotyping data from >100 000 EUR and Asian RA patients and controls. We identified two novel risk loci that appear to be specific to AAs: GPC5 and RBFOX1 (PAA < 5 × 10-9). Most RA risk loci are shared across different ethnicities, but among discordant loci, we observed strong enrichment of variants having large effect sizes. We found strong evidence of effect concordance for only 3 of the 21 largest effect index variants in EURs. We used the trans-ethnic fine-mapping algorithm PAINTOR3 to prioritize risk variants in >90 RA risk loci. Addition of AA data to those of EUR and EAS descent enabled identification of seven novel high-confidence candidate pathogenic variants (defined by posterior probability > 0.8). In summary, our trans-ethnic analyses are the first to include AAs, identified several new RA risk loci and point to candidate pathogenic variants that may underlie this common autoimmune disease. These findings may lead to better ways to diagnose or stratify treatment approaches in RA.

Sources of bias in genomics research of oral and dental traits

Evidence regarding the genomic basis of oral/dental traits and diseases is a fundamental pillar of the emerging notion of precision health. During the last decade, technological advances have improved the feasibility and affordability of conducting genome-wide association studies (GWAS) and studying the associations of emanating data with both common and rare oral conditions. Most evidence thus far emanates from GWAS of dental caries and periodontal disease that have tested the associations of several million single nucleotide polymorphisms (SNPs) with typically binary, health vs. disease phenotypes. GWAS offer advantages over the previous candidate-gene studies, mainly owing to their agnostic (i.e., unbiased, or hypothesis-free) nature. Nevertheless, GWAS are prone to virtually all sources of random and systematic error. Here, we review common sources of bias in genomics research with focus on GWAS including: type I and II errors, population stratification and heterogeneity, selection bias, adjustment for heritable covariates, appropriate reference panels for imputation, and gene annotation. We argue that valid and precise phenotype measurement is a key requirement, as GWAS sample sizes and thus statistical power increase. Finally, we stress that the lack of diversity of populations with phenotypes and genotypes is a major limitation for the generalizability and ultimate translation of the emerging genomics evidence-base into oral health promotion for all.

The promise and reality of therapeutic discovery from large cohorts

Technological advances in rapid data acquisition have transformed medical biology into a data mining field, where new data sets are routinely dissected and analyzed by statistical models of ever-increasing complexity. Many hypotheses can be generated and tested within a single large data set, and even small effects can be statistically discriminated from a sea of noise. On the other hand, the development of therapeutic interventions moves at a much slower pace. They are determined from carefully randomized and well-controlled experiments with explicitly stated outcomes as the principal mechanism by which a single hypothesis is tested. In this paradigm, only a small fraction of interventions can be tested, and an even smaller fraction are ultimately deemed therapeutically successful. In this Review, we propose strategies to leverage large-cohort data to inform the selection of targets and the design of randomized trials of novel therapeutics. Ultimately, the incorporation of big data and experimental medicine approaches should aim to reduce the failure rate of clinical trials as well as expedite and lower the cost of drug development.

Future Preventive Gene Therapy of Polygenic Diseases from a Population Genetics Perspective

With the accumulation of scientific knowledge of the genetic causes of common diseases and continuous advancement of gene-editing technologies, gene therapies to prevent polygenic diseases may soon become possible. This study endeavored to assess population genetics consequences of such therapies. Computer simulations were used to evaluate the heterogeneity in causal alleles for polygenic diseases that could exist among geographically distinct populations. The results show that although heterogeneity would not be easily detectable by epidemiological studies following population admixture, even significant heterogeneity would not impede the outcomes of preventive gene therapies. Preventive gene therapies designed to correct causal alleles to a naturally-occurring neutral state of nucleotides would lower the prevalence of polygenic early- to middle-age-onset diseases in proportion to the decreased population relative risk attributable to the edited alleles. The outcome would manifest differently for late-onset diseases, for which the therapies would result in a delayed disease onset and decreased lifetime risk; however, the lifetime risk would increase again with prolonging population life expectancy, which is a likely consequence of such therapies. If the preventive heritable gene therapies were to be applied on a large scale, the decreasing frequency of risk alleles in populations would reduce the disease risk or delay the age of onset, even with a fraction of the population receiving such therapies. With ongoing population admixture, all groups would benefit over generations.

Global Ancestry and Cognitive Ability

Using data from the Philadelphia Neurodevelopmental Cohort, we examined whether European ancestry predicted cognitive ability over and above both parental socioeconomic status (SES) and measures of eye, hair, and skin color. First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans. The differences between these groups, which were equivalent to 14.72 IQ points, were primarily (75.59%) due to difference in general cognitive ability (g), consistent with Spearman’s hypothesis. We found a relationship between European admixture and g. This relationship existed in samples of (a) self-identified monoracial African-Americans (B = 0.78, n = 2,179), (b) monoracial African and biracial African-European-Americans, with controls added for self-identified biracial status (B = 0.85, n = 2407), and (c) combined European, African-European, and African-American participants, with controls for self-identified race/ethnicity (B = 0.75, N = 7,273). Controlling for parental SES modestly attenuated these relationships whereas controlling for measures of skin, hair, and eye color did not. Next, we validated four sets of polygenic scores for educational attainment (eduPGS). MTAG, the multi-trait analysis of genome-wide association study (GWAS) eduPGS (based on 8442 overlapping variants) predicted g in both the monoracial African-American (r = 0.111, n = 2179, p < 0.001), and the European-American (r = 0.227, n = 4914, p < 0.001) subsamples. We also found large race differences for the means of eduPGS (d = 1.89). Using the ancestry-adjusted association between MTAG eduPGS and g from the monoracial African-American sample as an estimate of the transracially unbiased validity of eduPGS (B = 0.124), the results suggest that as much as 20%–25% of the race difference in g can be naïvely explained by known cognitive ability-related variants. Moreover, path analysis showed that the eduPGS substantially mediated associations between cognitive ability and European ancestry in the African-American sample. Subtest differences, together with the effects of both ancestry and eduPGS, had near-identity with subtest g-loadings. This finding confirmed a Jensen effect acting on ancestry-related differences. Finally, we confirmed measurement invariance along the full range of European ancestry in the combined sample using local structural equation modeling. Results converge on genetics as a potential partial explanation for group mean differences in intelligence.