Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases

Graves' disease and inflammatory bowel disease: A bidirectional Mendelian randomization

CONTEXT

Both Graves' disease (GD) and inflammatory bowel disease (IBD) are common autoimmune diseases that severely damage patients' quality of life. Previous epidemiological studies have suggested associations between GD and IBD. However, whether a causal relationship exists between these two diseases remains unknown.

OBJECTIVE

To infer a causal relationship between GD and IBD using bidirectional two-sample Mendelian randomization(MR).

METHODS

We performed bidirectional two-sample MR to infer a causal relationship between GD and IBD using GWAS summary data obtained from Biobank Japan (BBJ) and the International Inflammatory Bowel Disease Genetic Consortium (IIBDGC). Several methods (random-effect inverse variance weighted, weighted median, MR‒Egger regression, and MR-PRESSO) were used to ensure the robustness of the causal effect. Heterogeneity was measured based on Cochran's Q value. Horizontal pleiotropy was evaluated by MR‒Egger regression and leave-one-out analysis.

RESULTS

Genetically predicted IBD may increase the risk of GD by 24% (OR 1.24, 95% CI 1.01-1.52, p = 0.041). Crohn's disease (CD) may increase the risk of GD, whereas ulcerative colitis (UC) may prevent patients from developing GD. Conversely, genetically predicted GD may slightly increase the risk of CD, although evidence indicating that the presence of GD increased the risk of UC or IBD was lacking. Outlier-corrected results were consistent with raw causal estimates.

CONCLUSIONS

Our study revealed a potentially higher comorbidity rate for GD and CD. However, UC might represent a protective factor for GD. The underlying mechanism and potential common pathways await discovery.

The impact of SNP density on quantitative genetic analyses of body size traits in a wild population of Soay sheep

Understanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The 'animal model' is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome-wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome-wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high-density imputed SNP dataset revealed four new SNP-trait associations that were not found with the lower density dataset, as well as confirming all previously-found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre-correcting for covariates in a separate model.

Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics

By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10^-8 and a Bonferroni-corrected p < 4.6 × 10^-6, respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy.

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

A large genome-wide association study of QT interval length utilizing electronic health records

QT interval length is an important risk factor for adverse cardiovascular outcomes; however, the genetic architecture of QT interval remains incompletely understood. We conducted a genome-wide association study of 76,995 ancestrally diverse Kaiser Permanente Northern California members enrolled in the Genetic Epidemiology Research on Adult Health and Aging cohort using 448,517 longitudinal QT interval measurements, uncovering 9 novel variants, most replicating in 40,537 individuals in the UK Biobank and Population Architecture using Genomics and Epidemiology studies. A meta-analysis of all 3 cohorts (n = 117,532) uncovered an additional 19 novel variants. Conditional analysis identified 15 additional variants, 3 of which were novel. Little, if any, difference was seen when adjusting for putative QT interval lengthening medications genome-wide. Using multiple measurements in Genetic Epidemiology Research on Adult Health and Aging increased variance explained by 163%, and we show that the ≈6 measurements in Genetic Epidemiology Research on Adult Health and Aging was equivalent to a 2.4× increase in sample size of a design with a single measurement. The array heritability was estimated at ≈17%, approximately half of our estimate of 36% from family correlations. Heritability enrichment was estimated highest and most significant in cardiovascular tissue (enrichment 7.2, 95% CI = 5.7-8.7, P = 2.1e-10), and many of the novel variants included expression quantitative trait loci in heart and other relevant tissues. Comparing our results to other cardiac function traits, it appears that QT interval has a multifactorial genetic etiology.

The impact of fatty acids biosynthesis on the risk of cardiovascular diseases in Europeans and East Asians: a Mendelian randomization study

Despite early interest, the evidence linking fatty acids to cardiovascular diseases (CVDs) remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the etiology of several CVD endpoints in up to 1 153 768 European (maximum 123 668 cases) and 212 453 East Asian (maximum 29 319 cases) ancestry individuals. As instruments, we selected single nucleotide polymorphisms mapping to genes with well-known roles in PUFA (i.e. FADS1/2 and ELOVL2) and MUFA (i.e. SCD) biosynthesis. Our findings suggest that higher PUFA biosynthesis rate (proxied by rs174576 near FADS1/2) is related to higher odds of multiple CVDs, particularly ischemic stroke, peripheral artery disease and venous thromboembolism, whereas higher MUFA biosynthesis rate (proxied by rs603424 near SCD) is related to lower odds of coronary artery disease among Europeans. Results were unclear for East Asians as most effect estimates were imprecise. By triangulating multiple approaches (i.e. uni-/multi-variable Mendelian randomization, a phenome-wide scan, genetic colocalization and within-sibling analyses), our results are compatible with higher low-density lipoprotein (LDL) cholesterol (and possibly glucose) being a downstream effect of higher PUFA biosynthesis rate. Our findings indicate that PUFA and MUFA biosynthesis are involved in the etiology of CVDs and suggest LDL cholesterol as a potential mediating trait between PUFA biosynthesis and CVDs risk.

Prediction of the cell-type-specific transcription of non-coding RNAs from genome sequences via machine learning

Gene transcription is regulated through complex mechanisms involving non-coding RNAs (ncRNAs). As the transcription of ncRNAs, especially of enhancer RNAs, is often low and cell type specific, how the levels of RNA transcription depend on genotype remains largely unexplored. Here we report the development and utility of a machine-learning model (MENTR) that reliably links genome sequence and ncRNA expression at the cell type level. Effects on ncRNA transcription predicted by the model were concordant with estimates from published studies in a cell-type-dependent manner, regardless of allele frequency and genetic linkage. Among 41,223 variants from genome-wide association studies, the model identified 7,775 enhancer RNAs and 3,548 long ncRNAs causally associated with complex traits across 348 major human primary cells and tissues, such as rare variants plausibly altering the transcription of enhancer RNAs to influence the risks of Crohn's disease and asthma. The model may aid the discovery of causal variants and the generation of testable hypotheses for biological mechanisms driving complex traits.

Denisovan and Neanderthal archaic introgression differentially impacted the genetics of complex traits in modern populations

BACKGROUND

Introgression from extinct Neanderthal and Denisovan human species has been shown to contribute to the genetic pool of modern human populations and their phenotypic spectrum. Evidence of how Neanderthal introgression shaped the genetics of human traits and diseases has been extensively studied in populations of European descent, with signatures of admixture reported for instance in genes associated with pigmentation, immunity, and metabolic traits. However, limited information is currently available about the impact of archaic introgression on other ancestry groups. Additionally, to date, no study has been conducted with respect to the impact of Denisovan introgression on the health and disease of modern populations. Here, we compare the way evolutionary pressures shaped the genetics of complex traits in East Asian and European populations, and provide evidence of the impact of Denisovan introgression on the health of East Asian and Central/South Asian populations.

RESULTS

Leveraging genome-wide association statistics from the Biobank Japan and UK Biobank, we assessed whether Denisovan and Neanderthal introgression together with other evolutionary genomic signatures were enriched for the heritability of physiological and pathological conditions in populations of East Asian and European descent. In EAS, Denisovan-introgressed loci were enriched for coronary artery disease heritability (1.69-fold enrichment, p=0.003). No enrichment for archaic introgression was observed in EUR. We also performed a phenome-wide association study of Denisovan and Neanderthal alleles in six ancestry groups available in the UK Biobank. In EAS, the Denisovan-introgressed SNP rs62391664 in the major histocompatibility complex region was associated with albumin/globulin ratio (beta=-0.17, p=3.57×10^-7). Neanderthal-introgressed alleles were associated with psychiatric and cognitive traits in EAS (e.g., "No Bipolar or Depression"-rs79043717 beta=-1.5, p=1.1×10^-7), and with blood biomarkers (e.g., alkaline phosphatase-rs11244089 beta=0.1, p=3.69×10^-116) and red hair color (rs60733936 beta=-0.86, p=4.49×10^-165) in EUR. In the other ancestry groups, Neanderthal alleles were associated with several traits, also including the use of certain medications (e.g., Central/South East Asia: indapamide - rs732632 beta=-2.38, p=5.22×10^-7).

CONCLUSIONS

Our study provides novel evidence regarding the impact of archaic introgression on the genetics of complex traits in worldwide populations, highlighting the specific contribution of Denisovan introgression in EAS populations.

Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease

BACKGROUND

The value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations.  METHODS: An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case-control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold.

RESULTS

In the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634-0.646), 0.718 (95% CI, 0.713-0.723), and 0.753 (95% CI, 0.748-0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and - 0.023 (95% CI, - 0.025 to - 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category.

CONCLUSIONS

Addition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.

Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA_1c) was performed and identified 115 significant loci with four novel genetic variants (HACL1, RAD21, ASH1L and GAK). Transcriptomics data also strengthen the relevancy of the findings to metabolic disorders, thus contributing to better understanding of pathogenesis. In addition, genetic risk scores are constructed and validated for absolute risks prediction of T2D in Taiwanese population. In conclusion, our data-driven approach without a priori hypothesis is useful for novel gene discovery and validation on top of disease risk prediction for unique non-European population.

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis

Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.

The role of ATG16L2 in autophagy and disease

Macroautophagy/autophagy, a fundamental cell process for nutrient recycling and defense against pathogens (termed xenophagy), is crucial to human health. ATG16L2 (autophagy related 16 like 2) is an autophagic protein and a paralog of ATG16L1. Both proteins are implicated in similar diseases such as cancer and other chronic diseases; however, most autophagy studies to date have primarily focused on the function of ATG16L1, with ATG16L2 remaining uncharacterized and understudied. Overexpression of ATG16L2 has been reported in various cancers including colorectal, gastric, and prostate carcinomas, whereas altered methylation of ATG16L2 has been associated with lung cancer formation and poorer response to therapy in leukemia. In addition, ATG16L2 polymorphisms have been implicated in a range of other diseases including inflammatory bowel diseases and neurodegenerative disorders. Despite this likely role in human health, the function of this enigmatic protein in autophagy remains unknown. Here, we review current studies on ATG16L2 and collate evidence that suggests that this protein is a potential modulator of autophagy as well as the implications this has on pathogenesis.Abbreviations: ATG5: autophagy related 5; ATG12: autophagy related 12; ATG16L1: autophagy related 16 like 1; ATG16L2: autophagy related 16 like 2; CD: Crohn disease; IBD: inflammatory bowel diseases; IRGM: immunity related GTPase M; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; PE: phosphatidylethanolamine; RB1CC1: RB1 inducible coiled-coil 1; SLE: systemic lupus erythematosus; WIPI2B: WD repeat domain, phosphoinositide interacting 2B.

Genome-Wide Integration of Genetic and Genomic Studies of Atopic Dermatitis: Insights into Genetic Architecture and Pathogenesis

Atopic dermatitis (AD) is a common heterogeneous, chronic, itching, and inflammatory skin disease. Genetic studies have identified multiple AD susceptibility genes. However, the genetic architecture of AD has not been elucidated. In this study, we conducted a large-scale meta-analysis of AD (35,647 cases and 1,013,885 controls) to characterize the genetic basis of AD. The heritability of AD in different datasets varied from 0.6 to 7.1%. We identified 31 previously unreported genes by integrating multiomics data. Among the 31 genes, MCL1 was identified as a potential treatment target for AD by mediating gene‒drug interactions. Tissue enrichment analyses and phenome-wide association study provided strong support for the role of the hemic and immune systems in AD. Across 1,207 complex traits and diseases, genetic correlations indicated that AD shared links with multiple respiratory phenotypes. The phenome-wide Mendelian randomization analysis (Mendelian randomization‒phenome-wide association study) revealed that the age of onset of diabetes exhibited a positive causal effect on AD (inverse-variance weighted β = 0.39, SEM = 0.09, P = 2.77 × 10^-5). Overall, these results provide important insights into the genetic architecture of AD and will lead to a more thorough and complete understanding of the molecular mechanisms underlying AD.

A Novel apaQTL-SNP for the Modification of Non-Small-Cell Lung Cancer Susceptibility across Histological Subtypes

Background: Alternative polyadenylation (APA) events may be modulated by single nucleotide polymorphisms (SNPs). Therefore, this study aims to evaluate the association between APA quantitative trait loci (apaQTLs)-related SNPs (apaQTL-SNPs) and non-small-cell lung cancer (NSCLC) risk. Methods: APA-related genes associated with NSCLC (LUAD and LUSC) were first identified, and the respective apaQTL-SNPs of those genes were selected. Then, a two-phase case-control study was performed to evaluate the association between candidate apaQTL-SNPs and NSCLC risk. Results: A total of 7 LUAD- and 21 LUSC-associated apaQTL-SNPs were selected. In the first phase, the apaQTL-SNP rs10138506 was significantly associated with LUAD risk (p < 0.05), whereas the other two apaQTL-SNPs (rs1130698 and rs1130719) were significantly associated with LUSC risk (p < 0.05). In the second phase, the variant G allele of rs10138506 was still significantly associated with an increased risk of LUAD (OR = 1.42, 95%CI = 1.02−1.98, p = 0.038). Functional annotation indicated that the variant G allele of rs10138506 was significantly associated with a higher PDUI value of CHURC1. Meanwhile, 3′RACE experiments verified the presence of two poly(A) sites (proximal and distal) in CHURC1, while qRT-PCR results indicated that different genotypes of rs1127968 which, in perfect LD with rs10138506, can mediate changes in the lengths of the 3′UTR of CHURC1 isoforms. Conclusion: The variant G allele of rs10138506 in CHURC1 was correlated with a longer 3′UTR of CHURC1 mRNA and an increased LUAD risk. Further studies should evaluate the interaction between rs10138506 and different 3′UTR lengths of CHURC1 that regulate LUAD development.

MicroRNAs in Kawasaki disease: An update on diagnosis, therapy and monitoring

Kawasaki disease (KD) is an acute autoimmune vascular disease featured with a long stage of febrile. It predominantly afflicts children under 5 years old and causes an increased risk of cardiovascular combinations. The onset and progression of KD are impacted by many aspects, including genetic susceptibility, infection, and immunity. In recent years, many studies revealed that miRNAs, a novel class of small non-coding RNAs, may play an indispensable role in the development of KD via differential expression and participation in the central pathogenesis of KD comprise of the modulation of immunity, inflammatory response and vascular dysregulation. Although specific diagnose criteria remains unclear up to date, accumulating clinical evidence indicated that miRNAs, as small molecules, could serve as potential diagnostic biomarkers and exhibit extraordinary specificity and sensitivity. Besides, miRNAs have gained attention in affecting therapies for Kawasaki disease and providing new insights into personalized treatment. Through consanguineous coordination with classical therapies, miRNAs could overcome the inevitable drug-resistance and poor prognosis problem in a novel point of view. In this review, we systematically reviewed the existing literature and summarized those findings to analyze the latest mechanism to explore the role of miRNAs in the treatment of KD from basic and clinical aspects retrospectively. Our discussion helps to better understand the pathogenesis of KD and may offer profound inspiration on KD diagnosis, treatment, and prognosis.

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics

The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor-the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.

Evolutionary Origins of Metabolic Reprogramming in Cancer

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. These changes are not specific to tumors but also take place during the physiological growth of tissues. Indeed, the cellular and tissue mechanisms present in the tumor have their physiological counterpart in the repair of tissue lesions and wound healing. These molecular mechanisms have been acquired during metazoan evolution, first to eliminate the infection of the tissue injury, then to enter an effective regenerative phase. Cancer itself could be considered a phenomenon of antagonistic pleiotropy of the genes involved in effective tissue repair. Cancer and tissue repair are complex traits that share many intermediate phenotypes at the molecular, cellular, and tissue levels, and all of these are integrated within a Systems Biology structure. Complex traits are influenced by a multitude of common genes, each with a weak effect. This polygenic component of complex traits is mainly unknown and so makes up part of the missing heritability. Here, we try to integrate these different perspectives from the point of view of the metabolic changes observed in cancer.

Genetic association of leukocyte telomere length with Graves’ disease in Biobank Japan: A two-sample Mendelian randomization study

Background

Telomere length (TL) has been recognized to be fundamental to the risk of autoimmune disorders. However, the role of leukocyte TL in Graves’ disease has not yet been fully elucidated. In the study, we exploited the two-sample Mendelian randomization (MR) design to evaluate the causal effect of leukocyte TL on the risk of Graves’ disease.

Methods

Genome-wide association study (GWAS) data of leukocyte TL from the Singapore Chinese Health Study (SCHS) cohort and Graves’ disease from Biobank Japan (BBJ, 2176 cases and 210,277 controls) were analyzed. Nine single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) for TL. We used the inverse variance weighted (IVW) approach as the main estimator and MR-Egger regression, weighted median, simple mode, and weighed mode methods as complementary estimators. Horizontal pleiotropy was assessed using the intercept from MR-Egger.

Results

The analysis demonstrated that genetically predicted longer leukocyte TL was causally associated with a lower risk of Graves’ disease using the IVW method (odds ratio [OR]: 1.64, 95% confidence interval [CI]: 1.23-2.17, P=2.27e-04, and other complementary MR approaches achieved similar results. The intercept from the MR-Egger analysis provided no noticeable evidence of horizontal pleiotropy (β=0.02, P=0.641). MR-PRESSO method reported no outliers (P=0.266).

Conclusions

Our results provided evidence to support a genetic predisposition to shorter leukocyte TL with an increased risk of Graves’ disease. Further studies are warranted to explore the mechanism underlying the association.

Evaluating the impact of glucokinase activation on risk of cardiovascular disease: a Mendelian randomisation analysis

BACKGROUND

Glucokinase activators (GKAs) are an emerging class of glucose lowering drugs that activate the glucose-sensing enzyme glucokinase (GK). Pending formal cardiovascular outcome trials, we applied two-sample Mendelian randomisation (MR) to investigate the impact of GK activation on risk of cardiovascular diseases.

METHODS

We used independent genetic variants in or around the glucokinase gene meanwhile associated with HbA_1c at genome-wide significance (P < 5 × 10^-8) in the Meta-Analyses of Glucose and Insulin-related traits Consortium study (N = 146,806; European ancestry) as instrumental variables (IVs) to mimic the effects of GK activation. We assessed the association between genetically proxied GK activation and the risk of coronary artery disease (CAD; 122,733 cases and 424,528 controls), peripheral arterial disease (PAD; 7098 cases and 206,541 controls), stroke (40,585 cases and 406,111 controls) and heart failure (HF; 47,309 cases and 930,014 controls), using genome-wide association study summary statistics of these outcomes in Europeans. We compared the effect estimates of genetically proxied GK activation with estimates of genetically proxied lower HbA_1c on the same outcomes. We repeated our MR analyses in East Asians as validation.

RESULTS

Genetically proxied GK activation was associated with reduced risk of CAD (OR 0.38 per 1% lower HbA_1c, 95% CI 0.29-0.51, P = 8.77 × 10^-11) and HF (OR 0.54 per 1% lower HbA_1c, 95% CI 0.41-0.73, P = 3.55 × 10^-5). The genetically proxied protective effects of GKA on CAD and HF exceeded those due to non-targeted HbA_1c lowering. There was no causal relationship between genetically proxied GK activation and risk of PAD or stroke. The estimates in sensitivity analyses and in East Asians were generally consistent.

CONCLUSIONS

GKAs may protect against CAD and HF which needs confirmation by long-term clinical trials.

TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation

The statistical power of genome-wide association studies (GWASs) is affected by the effective sample size. However, the privacy and security concerns associated with individual-level genotype data pose great challenges for cross-institutional cooperation. The full-process cryptographic solutions are in demand but have not been covered, especially the essential principal-component analysis (PCA). Here, we present TrustGWAS, a complete solution for secure, large-scale GWAS, recapitulating gold standard results against PLINK without compromising privacy and supporting basic PLINK steps including quality control, linkage disequilibrium pruning, PCA, chi-square test, Cochran-Armitage trend test, covariate-supported logistic regression and linear regression, and their sequential combinations. TrustGWAS leverages pseudorandom number perturbations for PCA and multiparty scheme of multi-key homomorphic encryption for all other modules. TrustGWAS can evaluate 100,000 individuals with 1 million variants and complete QC-LD-PCA-regression workflow within 50 h. We further successfully discover gene loci associated with fasting blood glucose, consistent with the findings of the ChinaMAP project.

Genome-wide CRISPR screen identified a role for commander complex mediated ITGB1 recycling in basal insulin secretion

OBJECTIVES

Pancreatic beta cells secrete insulin postprandially and during fasting to maintain glucose homeostasis. Although glucose-stimulated insulin secretion (GSIS) has been extensively studied, much less is known about basal insulin secretion. Here, we performed a genome-wide CRISPR/Cas9 knockout screen to identify novel regulators of insulin secretion.

METHODS

To identify genes that cell autonomously regulate insulin secretion, we engineered a Cas9-expressing MIN6 subclone that permits irreversible fluorescence labeling of exocytic insulin granules. Using a fluorescence-activated cell sorting assay of exocytosis in low glucose and high glucose conditions in individual cells, we performed a genome-wide CRISPR/Cas9 knockout screen.

RESULTS

We identified several members of the COMMD family, a conserved family of proteins with central roles in intracellular membrane trafficking, as positive regulators of basal insulin secretion, but not GSIS. Mechanistically, we show that the Commander complex promotes insulin granules docking in basal state. This is mediated, at least in part, by its function in ITGB1 recycling. Defective ITGB1 recycling reduces its membrane distribution, the number of focal adhesions and cortical ELKS-containing complexes.

CONCLUSIONS

We demonstrated a previously unknown function of the Commander complex in basal insulin secretion. We showed that by ITGB1 recycling, Commander complex increases cortical adhesions, which enhances the assembly of the ELKS-containing complexes. The resulting increase in the number of insulin granules near the plasma membrane strengthens basal insulin secretion.

Health inequities in the rheumatic diseases of childhood

PURPOSE OF REVIEW

To describe differences in disease manifestations and outcomes in pediatric rheumatic diseases as they occur in non-European-descended populations in North America.

RECENT FINDINGS

Differences in disease prevalence, clinical phenotypes, disease course, and outcomes have been described across the spectrum of pediatric-onset rheumatic diseases. Although these differences are commonly explained by differences in genetic risk or access to tertiary healthcare facilities, our emerging understanding of the immunobiology of historical/ongoing trauma suggest a more complex explanation for these observed differences.

SUMMARY

Health inequities as observed in pediatric rheumatic diseases are likely to emerge from a complex interplay between social and biological factors. The important contribution of historical and repetitive trauma deserves further exploration.

Genetic evidence for a causal relationship between type 2 diabetes and peripheral artery disease in both Europeans and East Asians

BACKGROUND

Observational studies have revealed that type 2 diabetes (T2D) is associated with an increased risk of peripheral artery disease (PAD). However, whether the two diseases share a genetic basis and whether the relationship is causal remain unclear. It is also unclear as to whether these relationships differ between ethnic groups.

METHODS

By leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D (European-based: N_case = 21,926, N_control = 342,747; East Asian-based: N_case = 36,614, N_control = 155,150) and PAD (European-based: N_case = 5673, N_control = 359,551; East Asian-based: N_case = 3593, N_control = 208,860), we explored the genetic correlation and putative causal relationship between T2D and PAD in both Europeans and East Asians using linkage disequilibrium score regression and seven Mendelian randomization (MR) models. We also performed multi-trait analysis of GWAS and two gene-based analyses to reveal candidate variants and risk genes involved in the shared genetic basis between T2D and PAD.

RESULTS

We observed a strong genetic correlation (r_g) between T2D and PAD in both Europeans (r_g = 0.51; p-value = 9.34 × 10^-15) and East Asians (r_g = 0.46; p-value = 1.67 × 10^-12). The MR analyses provided consistent evidence for a causal effect of T2D on PAD in both ethnicities (odds ratio [OR] = 1.05 to 1.28 for Europeans and 1.15 to 1.27 for East Asians) but not PAD on T2D. This putative causal effect was not influenced by total cholesterol, body mass index, systolic blood pressure, or smoking initiation according to multivariable MR analysis, and the genetic overlap between T2D and PAD was further explored employing an independent European sample through polygenic risk score regression. Multi-trait analysis of GWAS revealed two novel European-specific single nucleotide polymorphisms (rs927742 and rs1734409) associated with the shared genetic basis of T2D and PAD. Gene-based analyses consistently identified one gene ANKFY1 and gene-gene interactions (e.g., STARD10 [European-specific] to AP3S2 [East Asian-specific]; KCNJ11 [European-specific] to KCNQ1 [East Asian-specific]) associated with the trans-ethnic genetic overlap between T2D and PAD, reflecting a common genetic basis for the co-occurrence of T2D and PAD in both Europeans and East Asians.

CONCLUSIONS

Our study provides the first evidence for a genetically causal effect of T2D on PAD in both Europeans and East Asians. Several candidate variants and risk genes were identified as being associated with this genetic overlap. Our findings emphasize the importance of monitoring PAD status in T2D patients and suggest new genetic biomarkers for screening PAD risk among patients with T2D.

The Role of Polygenic Susceptibility on Air Pollution-Associated Asthma between German and Japanese Elderly Women

Polygenic susceptibility likely influences individual responses to air pollutants and the risk of asthma. We compared the role of polygenic susceptibility on air pollution-associated asthma between German and Japanese women. We investigated women that were enrolled in the German SALIA cohort (n = 771, mean age = 73 years) and the Japanese Shika cohort (n = 847, mean age = 67 years) with known asthma status. Adjusted logistic regression models were used to assess the associations between (1) particulate matter with a median aerodynamic diameter ≤ 2.5μm (PM2.5) and nitrogen dioxide (NO2), (2) polygenic risk scores (PRS), and (3) gene-environment interactions (G × E) with asthma. We found an increased risk of asthma in Japanese women after exposure to low pollutant levels (PM2.5: median = 12.7µg/m3, p-value < 0.001, NO2: median = 8.5µg/m3, p-value < 0.001) and in German women protective polygenic effects (p-value = 0.008). While we found no significant G × E effects, the direction in both groups was that the PRS increased the effect of PM2.5 and decreased the effect of NO2 on asthma. Our study confirms that exposure to low air pollution levels increases the risk of asthma in Japanese women and indicates polygenic effects in German women; however, there was no evidence of G × E effects. Future genome-wide G × E studies should further explore the role of ethnic-specific polygenic susceptibility to asthma.

Polygenic Risk Score Improves Cataract Prediction in East Asian Population

Cataracts, characterized by crystalline lens opacities in human eyes, is the leading cause of blindness globally. Due to its multifactorial complexity, the molecular mechanisms remain poorly understood. Larger cohorts of genome-wide association studies (GWAS) are needed to investigate cataracts’ genetic basis. In this study, a GWAS was performed on the largest Han population to date, analyzing a total of 7079 patients and 13,256 controls from the Taiwan Biobank (TWB) 2.0 cohort. Two cataract-associated SNPs with an adjustment of p < 1 × 10−7 in the older groups and nine SNPs with an adjustment of p < 1 × 10−6 in the younger group were identified. Except for the reported AGMO in animal models, most variations, including rs74774546 in GJA1 and rs237885 in OXTR, were not identified before this study. Furthermore, a polygenic risk score (PRS) was created for the young and old populations to identify high-risk cataract individuals, with areas under the receiver operating curve (AUROCs) of 0.829 and 0.785, respectively, after covariate adjustments. Younger individuals had 17.45 times the risk while older people had 10.97 times the risk when comparing individuals in the highest and lowest PRS quantiles. Validation analysis on an independent TWB1.0 cohort revealed AUROCs of 0.744 and 0.659.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

Associations between six dietary habits and risk of hepatocellular carcinoma: A Mendelian randomization study

Diet is reported to be associated with hepatocellular carcinoma (HCC), but whether there is a causal relationship remains unclear. This study aimed to explore the potential causal associations between dietary habits and HCC risk using Mendelian randomization in an East Asian population. From the BioBank Japan, we obtained summary-level genome-wide association studies data for the following six dietary habits: ever/never drinker (n = 165,084), alcohol consumption (n = 58,610), coffee consumption (n = 152,634), tea consumption (n = 152,653), milk consumption (n = 152,965), and yoghurt consumption (n = 152,097). We also obtained data on HCC (1866 cases and 195,745 controls). Single-nucleotide polymorphisms (SNPs) that were associated with exposures (p < 5 × 10^-8 ) were selected as instrumental variables (IVs). Five, two, and six SNPs were identified for ever/never drinkers, alcohol consumption, and coffee consumption. One SNP was used for consumption of tea, milk, and yoghurt. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by inverse variance weighted (for an IV with more than one SNP) or Wald ratio (for an IV with one SNP). Ever/never drinkers (OR, 1.11; 95% CI, 1.05-1.18; p < 0.001) and alcohol consumption (OR, 1.57; 95% CI, 1.32-1.86; p < 0.001) were positively associated with HCC risk. Conversely, coffee consumption was inversely related to HCC risk (OR, 0.69; 95% CI, 0.53-0.90; p = 0.007). Similar inverse associations were observed for consumption of tea, milk, and yoghurt, with ORs (95% CIs) of 0.11 (0.05-0.26), 0.18 (0.09-0.34), and 0.18 (0.09-0.34), respectively (all p < 0.001). Conclusion: There are potential causal associations between six dietary habits and HCC risk. Our findings inform clinical practice by providing evidence on the impact of dietary habits on HCC.

Construction and Application of Polygenic Risk Scores in Autoimmune Diseases

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited predictive power; however, when aggregated (e.g., via polygenic risk score method), they could provide meaningful risk predictions for a myriad of diseases. In this review, we describe the recent advances in GWAS for autoimmune diseases and the practical application of this knowledge to predict an individual’s susceptibility/severity for autoimmune diseases such as systemic lupus erythematosus (SLE) via the polygenic risk score method. We provide an overview of methods for deriving different polygenic risk scores and discuss the strategies to integrate additional information from correlated traits and diverse ancestries. We further advocate for the need to integrate clinical features (e.g., anti-nuclear antibody status) with genetic profiling to better identify patients at high risk of disease susceptibility/severity even before clinical signs or symptoms develop. We conclude by discussing future challenges and opportunities of applying polygenic risk score methods in clinical care.

Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles

Asthma is ranked among the most common chronic conditions and has become a significant public health issue due to the recent and rapid increase in its prevalence. Investigations into the underlying genetic factors predict a heritable component for its incidence, estimated between 35% and 90% of causation. Despite the application of large-scale genome-wide association studies (GWAS) and admixture mapping approaches, the proportion of variants identified accounts for less than 15% of the observed heritability of the disease. The discrepancy between the predicted heritable component of disease and the proportion of heritability mapped to the currently identified susceptibility loci has been termed the ‘missing heritability problem.’ Here, we examine recent studies involving both the analysis of genetically encoded features that contribute to asthma and also the role of non-encoded heritable characteristics, including epigenetic, environmental, and developmental aspects of disease. The importance of vertical maternal microbiome transfer and the influence of maternal immune factors on fetal conditioning in the inheritance of disease are also discussed. In order to highlight the broad array of biological inputs that contribute to the sum of heritable risk factors associated with allergic disease incidence that, together, contribute to the induction of a pro-atopic state. Currently, there is a need to develop in-depth models of asthma risk factors to overcome the limitations encountered in the interpretation of GWAS results in isolation, which have resulted in the missing heritability problem. Hence, multiomics analyses need to be established considering genetic, epigenetic, and functional data to create a true systems biology-based approach for analyzing the regulatory pathways that underlie the inheritance of asthma and to develop accurate risk profiles for disease.

Genome-Wide Association Study of Intracranial Artery Stenosis Followed by Phenome-Wide Association Study

The genetic background of intracranial artery stenosis (ICAS), a major cause of ischemic stroke, remains elusive. We performed the world's first genome-wide association study (GWAS) of ICAS using DNA samples from Japanese subjects, to identify the genetic factors associated with ICAS and their correlation with clinical features. We also conducted a phenome-wide association study (PheWAS) of the top variant identified via GWAS to determine its association with systemic disease. The GWAS involved 408 patients with ICAS and 349 healthy controls and utilized an Asian Screening Array of venous blood samples. The PheWAS was performed using genotypic and phenotypic data of the Biobank Japan Project, which contained information on 46 diseases and 60 quantitative trait data from > 150,000 Japanese individuals. The GWAS revealed that the East Asian-specific functional variant of RNF213, rs112735431 (c.14429G > A, p.Arg4810Lys), was associated with ICAS (odds ratio, 12.3; 95% CI 5.5 to 27.5; P = 7.8 × 10^-10). Stratified analysis within ICAS cases demonstrated that clinical features of those with and without the risk allele were different. PheWAS indicated that high blood pressure and angina were significantly associated with RNF213 rs112735431. The first GWAS of ICAS, which stratifies subpopulations within the ICAS cases with distinct clinical features, revealed that RNF213 rs112735431 was the most significant variant associated with ICAS. Thus, RNF213 rs112735431 shows potential as an important clinical biomarker that characterizes pleiotropic risk in various vascular diseases, such as blood pressure and angina, thereby facilitating personalized medicine for systemic vascular diseases in East Asian populations.

Mendelian randomization analysis of 37 clinical factors and coronary artery disease in East Asian and European populations

BACKGROUND

Coronary artery disease (CAD) remains the leading cause of mortality worldwide despite enormous efforts devoted to its prevention and treatment. While many genetic loci have been identified to associate with CAD, the intermediate causal risk factors and etiology have not been fully understood. This study assesses the causal effects of 37 heritable clinical factors on CAD in East Asian and European populations.

METHODS

We collected genome-wide association summary statistics of 37 clinical factors from the Biobank Japan (42,793 to 191,764 participants) and the UK Biobank (314,658 to 442,817 participants), paired with summary statistics of CAD from East Asians (29,319 cases and 183,134 controls) and Europeans (91,753 cases and 311,344 controls). These clinical factors covered 12 cardiometabolic traits, 13 hematological indices, 7 hepatological and 3 renal function indices, and 2 serum electrolyte indices. We performed univariable and multivariable Mendelian randomization (MR) analyses in East Asians and Europeans separately, followed by meta-analysis.

RESULTS

Univariable MR analyses identified reliable causal evidence (P < 0.05/37) of 10 cardiometabolic traits (height, body mass index [BMI], blood pressure, glycemic and lipid traits) and 4 other clinical factors related to red blood cells (red blood cell count [RBC], hemoglobin, hematocrit) and uric acid (UA). Interestingly, while generally consistent, we identified population heterogeneity in the causal effects of BMI and UA, with higher effect sizes in East Asians than those in Europeans. After adjusting for cardiometabolic factors in multivariable MR analysis, red blood cell traits (RBC, meta-analysis odds ratio 1.07 per standard deviation increase, 95% confidence interval 1.02-1.13; hemoglobin, 1.10, 1.03-1.16; hematocrit, 1.10, 1.04-1.17) remained significant (P < 0.05), while UA showed an independent causal effect in East Asians only (1.12, 1.06-1.19, P = 3.26×10^-5).

CONCLUSIONS

We confirmed the causal effects of 10 cardiometabolic traits on CAD and identified causal risk effects of RBC, hemoglobin, hematocrit, and UA independent of traditional cardiometabolic factors. We found no causal effects for 23 clinical factors, despite their reported epidemiological associations. Our findings suggest the physiology of red blood cells and the level of UA as potential intervention targets for the prevention of CAD.

Genetically Predicted Serum Albumin and Risk of Colorectal Cancer: A Bidirectional Mendelian Randomization Study

Purpose

Colorectal cancer (CRC) is the third–most frequently diagnosed cancer globally. Studies have linked low serum albumin with increased risk of CRC, but the causal nature of the association remains unclear. In the present study, we explored the potential causal relationship using bidirectional Mendelian randomization (MR).

Methods

Instrumental variants for albumin were obtained from a genome-wide association study (GWAS) on 102,223 Eastern Asian participants to investigate the effect of albumin on CRC. Summary statistics of CRC were obtained from a GWAS on 7,062 CRC cases and 195,745 controls of Eastern Asian ancestry. Bidirectional MR analysis was performed using inverse variance weighting (IVW) for primary analysis, supplemented with a maximum likelihood–based method, MR-PRESSO test, leave-one-out analysis, and MR-Egger regression. Stratification analyses were further performed.

Results

We found that genetically predicted serum albumin per unit was associated with a lower risk of CRC (OR 0.75, 95% CI 0.59–0.95 with IVW). No evidence of pleiotropy was observed. Sex-stratified MR analysis showed that serum albumin was inversely associated with risk of CRC in men (OR 0.71, 95% CI 0.53–0.96), but not in women (OR 0.81, 95% CI 0.55–1.19) using IVW. Reverse MR analysis suggested a genetic predisposition toward CRC was not associated with serum albumin.

Conclusion

Our study revealed a suggestive sex disparity in the effect of albumin, which deserves further exploration of the potential biological mechanism.

Break on through: The role of innate immunity and barrier defence in atopic dermatitis and psoriasis

The human skin can be affected by a multitude of diseases including inflammatory conditions such as atopic dermatitis and psoriasis. Here, we describe how skin barrier integrity and immunity become dysregulated during these two most common inflammatory skin conditions. We summarise recent advances made in the field of the skin innate immune system and its interaction with adaptive immunity. We review gene variants associated with atopic dermatitis and psoriasis that affect innate immune mechanisms and skin barrier integrity. Finally, we discuss how current and future therapies may affect innate immune responses and skin barrier integrity in a generalized or more targeted approach in order to ameliorate disease in patients.

Genome-Wide Mapping of Plasma IgG N-Glycan Quantitative Trait Loci Identifies a Potentially Causal Association between IgG N-Glycans and Rheumatoid Arthritis

Observational studies highlight associations of IgG N-glycosylation with rheumatoid arthritis (RA); however, the causality between these conditions remains to be determined. Standard and multivariable two-sample Mendelian randomization (MR) analyses integrating a summary genome-wide association study for RA and IgG N-glycan quantitative trait loci (IgG N-glycan-QTL) data were performed to explore the potentially causal associations of IgG N-glycosylation with RA. After correcting for multiple testing (p < 2 × 10^-3), the standard MR analysis based on the inverse-variance weighted method showed a significant association of genetically instrumented IgG N-glycan (GP4) with RA (odds ratio_GP4 = 0.906, 95% confidence interval = 0.857-0.958, p = 5.246 × 10^-4). In addition, we identified seven significant associations of genetically instrumented IgG N-glycans with RA by multivariable MR analysis (p < 2 × 10^-3). Results were broadly consistent in sensitivity analyses using MR_Lasso, MR_weighted median, MR_Egger regression, and leave-one-out analysis with different instruments (all p values <0.05). There was limited evidence of pleiotropy bias (all p values > 0.05). In conclusion, our MR analysis incorporating genome-wide association studies and IgG N-glycan-QTL data revealed that IgG N-glycans were potentially causally associated with RA. Our findings shed light on the role of IgG N-glycosylation in the development of RA. Future studies are needed to validate our findings and to explore the underlying physiological mechanisms in the etiology of RA.

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

BACKGROUND

Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes.

OBJECTIVES

To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events.

METHODS

Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10-9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27).

RESULTS

Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes.

CONCLUSIONS

The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.

Hepatitis B infection is causally associated with extrahepatic cancers: A Mendelian randomization study

Background

Evidence from observational studies suggests that chronic hepatitis B virus (HBV) infection is associated with extrahepatic cancers. However, the causal association between chronic HBV infection and extrahepatic cancers remains to be determined.

Methods

We performed two-sample Mendelian randomization (MR) to investigate whether chronic HBV infection is causally associated with extrahepatic cancers. We identified four independent genetic variants strongly associated (P-value < 5 × 10⁻⁸) with the exposure, chronic HBV infection in 1371 cases and 2938 controls of East Asian ancestry in Korea, which were used as instrumental variables. Genome-wide association summary level data for outcome variables, that included cancer of the biliary tract, cervix, colorectum, endometrium, esophagus, gastric, hepatocellular carcinoma, lung, ovary and pancreas were obtained from Biobank Japan.

Findings

Using the multivariable inverse variance weighted method, we found genetic liability to chronic HBV infection causally associated with extrahepatic cancers including cervical cancer (odds ratio [OR] = 1.57, 95% confidence interval [CI] = 1.29–1.91, P-value = 0.0001) and gastric cancer (OR = 1.12, 95% CI = 1.05–1.19, P-value = 0.0001). Moreover, chronic HBV infection (OR = 1.20, 95% CI = 1.07–1.34, P-value = 0.0021) was causally associated with hepatocellular carcinoma, supporting a well-established association between chronic HBV infection and hepatocellular carcinoma.

Interpretation

: Our MR analysis revealed that chronic HBV infection is causally associated with extrahepatic cancers including cervical and gastric cancers.

Funding

None.

Sex-specific effect of serum urate levels on coronary heart disease and myocardial infarction prevention: A Mendelian randomization study

BACKGROUND AND AIMS

Observational studies have examined serum urate levels in relation to coronary heart disease (CHD) and myocardial infarction (MI). Whether these associations are causal remains controversial, due to confounding factors and reverse causality. We aim to investigate the causality of these associations using Mendelian randomization method.

METHODS AND RESULTS

Instrumental variables were obtained from the largest genome-wide association studies of serum urate (457,690 individuals) to date. Summary statistics were from CARDIoGRAMplusC4D consortium (60,801 CHD cases; 43,676 MI cases), FinnGen (21,012 CHD cases; 12,801 MI cases), UK Biobank (10,157 CHD cases; 7018 MI cases), and Biobank Japan (29,319 CHD cases). Inverse-variance weighted method was applied as the main results. Other statistical methods and reverse MR analysis were conducted in the supplementary analyses. Elevated genetically determined serum urate levels were associated with increased risks of CHD and MI. The association pattern remained for the datasets in FinnGen, the combined results of three independent data sources (CHD: odds ratio (OR), 1.10; 95%CI, 1.06-1.15; p = 4.2 × 10^-6; MI: OR, 1.12; 95%CI, 1.07-1.18; p = 2.7 × 10^-6), and East Asian population. Interestingly, sex-specific subgroup analyses revealed that these associations kept in men only, but not among women in individuals of European ancestry. No consistent evidence was found for the causal effect of CHD or MI on serum urate levels.

CONCLUSION

We provide consistent evidence for the causal effect of genetically predicted serum urate levels on CHD and MI, but not the reverse effect. Urate-lowering therapy may be of cardiovascular benefit in the prevention of CHD and MI, especially for men.

Metabolomic Associations of Asthma in the Hispanic Community Health Study/Study of Latinos

Asthma disproportionally affects Hispanic and/or Latino backgrounds; however, the relation between circulating metabolites and asthma remains unclear. We conducted a cross-sectional study associating 640 individual serum metabolites, as well as twelve metabolite modules, with asthma in 3347 Hispanic/Latino background participants (514 asthmatics, 15.36%) from the Hispanic/Latino Community Health Study/Study of Latinos. Using survey logistic regression, per standard deviation (SD) increase in 1-arachidonoyl-GPA (20:4) was significantly associated with 32% high odds of asthma after accounting for clinical risk factors (p = 6.27 × 10−5), and per SD of the green module, constructed using weighted gene co-expression network, was suggestively associated with 25% high odds of asthma (p = 0.006). In the stratified analyses by sex and Hispanic and/or Latino backgrounds, the effect of 1-arachidonoyl-GPA (20:4) and the green module was predominantly observed in women (OR = 1.24 and 1.37, p < 0.001) and people of Cuban and Puerto-Rican backgrounds (OR = 1.25 and 1.27, p < 0.01). Mutations in Fatty Acid Desaturase 2 (FADS2) affected the levels of 1-arachidonoyl-GPA (20:4), and Mendelian Randomization analyses revealed that high genetically regulated 1-arachidonoyl-GPA (20:4) levels were associated with increased odds of asthma (p < 0.001). The findings reinforce a molecular basis for asthma etiology, and the potential causal effect of 1-arachidonoyl-GPA (20:4) on asthma provides an opportunity for future intervention.

Genome-wide risk prediction of common diseases across ancestries in one million people

Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate. All four PRSs had similar accuracy across European and Asian populations, with poorer transferability in the smaller group of individuals of African ancestry. The PRSs had highly similar effect sizes in different populations of European ancestry, and in early- and late-settlement regions with different recent population bottlenecks in Finland. Comparing genome-wide PRSs to PRSs containing a smaller number of variants, the highly polygenic, genome-wide PRSs generally displayed higher effect sizes and better transferability across global ancestries. Our findings indicate that in the populations investigated, the current genome-wide polygenic scores for common diseases have potential for clinical utility within different health-care settings for individuals of European ancestry, but that the utility in individuals of African ancestry is currently much lower.

Using genetics to assess the association of commonly used antihypertensive drugs with diabetes, glycaemic traits and lipids: a trans-ancestry Mendelian randomisation study

AIMS/HYPOTHESIS

Diabetes and hyperlipidaemia are common comorbidities in people with hypertension. Despite similar protective effects on CVD, different classes of antihypertensive drugs have different effects on CVD risk factors, including diabetes, glucose metabolism and lipids. However, these pleiotropic effects have not been assessed in long-term, large randomised controlled trials, especially for East Asians.

METHODS

We used Mendelian randomisation to obtain unconfounded associations of ACE inhibitors, β-blockers (BBs) and calcium channel blockers (CCBs). Specifically, we used genetic variants in drug target genes and related to systolic BP in Europeans and East Asians, and applied them to the largest available genome-wide association studies of diabetes (74,124 cases and 824,006 controls in Europeans, 77,418 cases and 356,122 controls in East Asians), blood glucose levels, HbA_1c, and lipids (LDL-cholesterol, HDL-cholesterol and triacylglycerols) (approximately 0.5 million Europeans and 0.1 million East Asians). We used coronary artery disease (CAD) as a control outcome and used different genetic instruments and analysis methods as sensitivity analyses.

RESULTS

As expected, genetically proxied ACE inhibition, BBs and CCBs were related to lower risk of CAD in both ancestries. Genetically proxied ACE inhibition was associated with a lower risk of diabetes (OR 0.85, 95% CI 0.78-0.93), and genetic proxies for BBs were associated with a higher risk of diabetes (OR 1.05, 95% CI 1.02-1.09). The estimates were similar in East Asians, and were corroborated by systematic review and meta-analyses of randomised controlled trials. In both ancestries, genetic proxies for BBs were associated with lower HDL-cholesterol and higher triacylglycerols, and genetic proxies for CCBs were associated with higher LDL-cholesterol. The estimates were robust to the use of different genetic instruments and analytical methods.

CONCLUSIONS/INTERPRETATION

Our findings suggest protective association of genetically proxied ACE inhibition with diabetes, while genetic proxies for BBs and CCBs possibly relate to an unfavourable metabolic profile. Developing a deeper understanding of the pathways underlying these diverse associations would be worthwhile, with implications for drug repositioning as well as optimal CVD prevention and treatment strategies in people with hypertension, diabetes and/or hyperlipidaemia.

XPXP: improving polygenic prediction by cross-population and cross-phenotype analysis

MOTIVATION

As increasing sample sizes from genome-wide association studies (GWASs), polygenic risk scores (PRSs) have shown great potential in personalized medicine with disease risk prediction, prevention and treatment. However, the PRS constructed using European samples becomes less accurate when it is applied to individuals from non-European populations. It is an urgent task to improve the accuracy of PRSs in under-represented populations, such as African populations and East Asian populations.

RESULTS

In this article, we propose a cross-population and cross-phenotype (XPXP) method for construction of PRSs in under-represented populations. XPXP can construct accurate PRSs by leveraging biobank-scale datasets in European populations and multiple GWASs of genetically correlated phenotypes. XPXP also allows to incorporate population-specific and phenotype-specific effects, and thus further improves the accuracy of PRS. Through comprehensive simulation studies and real data analysis, we demonstrated that our XPXP outperformed existing PRS approaches. We showed that the height PRSs constructed by XPXP achieved 9% and 18% improvement over the runner-up method in terms of predicted R2 in East Asian and African populations, respectively. We also showed that XPXP substantially improved the stratification ability in identifying individuals at high genetic risk of type 2 diabetes.

AVAILABILITY AND IMPLEMENTATION

The XPXP software and all analysis code are available at github.com/YangLabHKUST/XPXP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method

The killer cell immunoglobulin-like receptor (KIR) recognizes human leukocyte antigen (HLA) class I molecules and modulates the function of natural killer cells. Despite its role in immunity, the complex genomic structure has limited a deep understanding of the KIR genomic landscape. Here we conduct deep sequencing of 16 KIR genes in 1,173 individuals. We devise a bioinformatics pipeline incorporating copy number estimation and insertion or deletion (indel) calling for high-resolution KIR genotyping. We define 118 alleles in 13 genes and demonstrate a linkage disequilibrium structure within and across KIR centromeric and telomeric regions. We construct a KIR imputation reference panel (n_reference = 689, imputation accuracy = 99.7%), apply it to biobank genotype (n_total = 169,907), and perform phenome-wide association studies of 85 traits. We observe a dearth of genome-wide significant associations, even in immune traits implicated previously to be associated with KIR (the smallest p = 1.5 × 10^-4). Our pipeline presents a broadly applicable framework to evaluate innate immunity in large-scale datasets.

Genetic variants in choline metabolism pathway are associated with the risk of bladder cancer in the Chinese population

Choline metabolism alteration is considered as a metabolic hallmark in cancer, reflecting the complex interactions between carcinogenic signaling pathways and cancer metabolism, but little is known about whether genetic variants in the metabolism pathway contribute to the susceptibility of bladder cancer. Herein, a case-control study comprising 580 patients and 1,101 controls was carried out to analyze the association of bladder cancer with genetic variants on candidate genes involved in the choline metabolism pathway using unconditional logistic regression. Gene expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were applied for differential gene expression analysis. Cox regression was also applied to estimate the role of candidate genes on bladder cancer prognosis. Our results demonstrated that C allele of rs6810830 in ENPP6 was a significant protective allele of bladder cancer, compared to the T allele [Odds ratio (OR) = 0.74, 95% confidence interval (CI) = 0.64-0.86, P = 7.14 × 10^-5 in additive model]. Besides, we also found that the expression of ENPP6 remarkably decreased in bladder tumors compared with normal tissues. Moreover, high expression of ENPP6 was associated with worse overall survival (OS) in bladder cancer patients [hazard ratio (HR) with their 95% CI 1.39 (1.02-1.90), P = 0.039]. In conclusion, our results suggested that SNP rs6810830 (T > C) in ENPP6 might be a potential susceptibility loci for bladder cancer, and these findings provided novel insights into the underlying mechanism of choline metabolism in cancers.

Genetic validation of neurokinin 3 receptor antagonists for ischemic heart disease prevention in men – A one-sample Mendelian randomization study

Background

Ischemic heart disease (IHD) is a leading cause of mortality, particularly for men. Few interventions have focused on protecting specifically men. Emerging evidence may implicate testosterone. Neurokinin 3 receptor (NK3R) antagonists, an existing class of drugs being considered as treatments for reproductive conditions in women, affect testosterone; this study addresses genetic validation of their use to prevent IHD in men.

Methods

A one-sample Mendelian randomization (MR) study using the UK Biobank cohort study, based on independent (r² < 0.005) genetic variants predicting testosterone in men (n = 157738) at genome wide significance in the target gene for NK3R antagonists (TACR3), was used to assess associations with IHD (cases=15056, non-cases=151964) and positive control outcomes (relative age voice broke, children fathered, hypertension) in men and a negative control outcome (IHD) in women using summary statistics. A two-sample MR study using the PRACTICAL consortium was used for the positive control outcome of prostate cancer.

Findings

Two relevant TACR3 genetic variants (rs116646027 and rs1351623) were identified in men. Genetically mimicked NK3R antagonists were inversely associated with IHD (odds ratio 0.54 per standard deviation lower testosterone, 95% confidence interval 0.31, 0.94) and with control outcomes (older relative age voice broke, fewer children and lower risk of hypertension and prostate cancer) as expected in men and in women (unrelated to IHD).

Interpretation

Genetic validation of a role of NK3R antagonists in IHD suggests their consideration as a new means of preventing IHD in men. Whether they protect against prostate cancer might bear further consideration.

Celebrities in the heart, strangers in the pancreatic beta cell: Voltage-gated potassium channels Kv 7.1 and Kv 11.1 bridge long QT syndrome with hyperinsulinaemia as well as type 2 diabetes

Voltage‐gated potassium (K_v) channels play an important role in the repolarization of a variety of excitable tissues, including in the cardiomyocyte and the pancreatic beta cell. Recently, individuals carrying loss‐of‐function (LoF) mutations in KCNQ1, encoding K_v7.1, and KCNH2 (hERG), encoding K_v11.1, were found to exhibit post‐prandial hyperinsulinaemia and episodes of hypoglycaemia. These LoF mutations also cause the cardiac disorder long QT syndrome (LQTS), which can be aggravated by hypoglycaemia. Interestingly, patients with LQTS also have a higher burden of diabetes compared to the background population, an apparent paradox in relation to the hyperinsulinaemic phenotype, and KCNQ1 has been identified as a type 2 diabetes risk gene. This review article summarizes the involvement of delayed rectifier K⁺ channels in pancreatic beta cell function, with emphasis on K_v7.1 and K_v11.1, using the cardiomyocyte for context. The functional and clinical consequences of LoF mutations and polymorphisms in these channels on blood glucose homeostasis are explored using evidence from pre‐clinical, clinical and genome‐wide association studies, thereby evaluating the link between LQTS, hyperinsulinaemia and type 2 diabetes.

10 Years of GWAS discovery in endometrial cancer: Aetiology, function and translation

Endometrial cancer is a common gynaecological cancer with increasing incidence and mortality. In the last decade, endometrial cancer genome-wide association studies (GWAS) have provided a resource to explore aetiology and for functional interpretation of heritable risk variation, informing endometrial cancer biology. Indeed, GWAS data have been used to assess relationships with other traits through correlation and Mendelian randomisation analyses, establishing genetic relationships and potential risk factors. Cross-trait GWAS analyses have increased statistical power and identified novel endometrial cancer risk variation related to other traits. Functional analysis of risk loci has helped prioritise candidate susceptibility genes, revealing molecular mechanisms and networks. Lastly, risk scores generated using endometrial cancer GWAS data may allow for clinical translation through identification of patients at high risk of disease. In the next decade, this knowledge base should enable substantial progress in our understanding of endometrial cancer and, potentially, new approaches for its screening and treatment.