Genome-wide association studies in diverse populations

Bowel Habits, Obesity, Intestinal Microbiota and Their Influence on Hemorrhoidal Disease: a Mendelian Randomization Study

Purpose

Hemorrhoids (HEM) are the most common perianal disease, but current observational studies have yielded inconsistent results in investigating the risk factors. Our further exploration of the risk factors will help prevent the disease.

Patients and Methods

We conducted a two-sample bidirectional Mendelian randomization (MR) analysis using publicly available genome-wide association studies (GWAS) statistics from multiple consortia. The inverse-variance weighted (IVW) method was used for the primary analysis. We applied four complementary methods, including weighted median, weighted mode, MR-Egger regression, and Cochrane's Q value, to detect and correct the effects of horizontal pleiotropy.

Results

Genetically determined constipation (OR = 0.97, 95% CI: 0.91-1.03, P = 0.28) and diarrhea (OR = 1.00, 95% CI: 0.99-1.01, P = 0.90) did not have a causal effect on HEM but stool frequency (OR = 1.28, 95% CI: 1.05-1.55, P = 0.01), waist-to-hip ratio adjusted for BMI (OR = 1.11, 95% CI: 1.06-1.64, P = 1.59×10-5), and order Burkholderiales (OR = 1.09, 95% CI = 1.04-1.14, p = 1.63×10-4) had a causal effect on. Furthermore, we found a significant causal effect of constipation on HEM in the reverse MR analysis (OR = 1.21, 95% CI: 1.13-1.28, P = 3.72×10-9). The results of MR-Egger regression, Weighted Median, and Weighted Mode methods were consistent with those of the IVW method. Horizontal pleiotropy was unlikely to distort the causal estimates, as indicated by the sensitivity analysis.

Conclusion

Our MR analysis reveals a causal association between stool frequency and waist-to-hip ratio with HEM, despite variations in results reported by observational studies. Unexpectedly, we found a relationship between the order Burkholderiales in the gut flora and HEM, although the mechanism is unclear.

Shaping immunity: The influence of natural selection on population immune diversity

Humans exhibit considerable variability in their immune responses to the same immune challenges. Such variation is widespread and affects individual and population-level susceptibility to infectious diseases and immune disorders. Although the factors influencing immune response diversity are partially understood, what mechanisms lead to the wide range of immune traits in healthy individuals remain largely unexplained. Here, we discuss the role that natural selection has played in driving phenotypic differences in immune responses across populations and present-day susceptibility to immune-related disorders. Further, we touch on future directions in the field of immunogenomics, highlighting the value of expanding this work to human populations globally, the utility of modeling the immune response as a dynamic process, and the importance of considering the potential polygenic nature of natural selection. Identifying loci acted upon by evolution may further pinpoint variants critically involved in disease etiology, and designing studies to capture these effects will enrich our understanding of the genetic contributions to immunity and immune dysregulation.

Cross-ancestry genetic architecture and prediction for cholesterol traits

While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.

The causal association between artificial sweeteners and the risk of cancer: a Mendelian randomization study

Artificial sweeteners (ASs) have been widely added to food and beverages because of their properties of low calories and sweet taste. However, whether the consumption of ASs is causally associated with cancer risk is not clear. Here, we utilized the two-sample Mendelian randomization (MR) method to study the potential causal association. Genetic variants like single-nucleotide polymorphisms (SNPs) associated with exposure (AS consumption) were extracted from a genome-wide association study (GWAS) database including 64 949 Europeans and the influence of confounding was removed. The outcome was from 98 GWAS data and included several types of cancers like lung cancer, colorectal cancer, stomach cancer, breast cancer, and so on. The exposure-outcome SNPs were harmonized and then MR analysis was performed. The inverse-variance weighted (IVW) with random effects was used as the main analytical method accompanied by four complementary methods: MR Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses consisted of heterogeneity, pleiotropy, and leave-one-out analysis. Our results demonstrated that ASs added to coffee had a positive association with high-grade and low-grade serous ovarian cancer; ASs added to tea had a positive association with oral cavity and pharyngeal cancers, but a negative association with malignant neoplasm of the bronchus and lungs. No other cancers had a genetic causal association with AS consumption. Our MR study revealed that AS consumption had no genetic causal association with major cancers. Larger MR studies or RCTs are needed to investigate small effects and support this conclusion.

Epigenome-wide association study of DNA methylation in maternal blood leukocytes with BMI in pregnancy and gestational weight gain

OBJECTIVES

We aimed to discover CpG sites with differential DNA methylation in peripheral blood leukocytes associated with body mass index (BMI) in pregnancy and gestational weight gain (GWG) in women of European and South Asian ancestry. Furthermore, we aimed to investigate how the identified sites were associated with methylation quantitative trait loci, gene ontology, and cardiometabolic parameters.

METHODS

In the Epigenetics in pregnancy (EPIPREG) sample we quantified maternal DNA methylation in peripheral blood leukocytes in gestational week 28 with Illumina's MethylationEPIC BeadChip. In women with European (n = 303) and South Asian (n = 164) ancestry, we performed an epigenome-wide association study of BMI in gestational week 28 and GWG between gestational weeks 15 and 28 using a meta-analysis approach. Replication was performed in the Norwegian Mother, Father, and Child Cohort Study, the Study of Assisted Reproductive Technologies (MoBa-START) (n = 877, mainly European/Norwegian).

RESULTS

We identified one CpG site significantly associated with GWG (p 5.8 × 10-8) and five CpG sites associated with BMI at gestational week 28 (p from 4.0 × 10-8 to 2.1 × 10-10). Of these, we were able to replicate three in MoBa-START; cg02786370, cg19758958 and cg10472537. Two sites are located in genes previously associated with blood pressure and BMI. DNA methylation at the three replicated CpG sites were associated with levels of blood pressure, lipids and glucose in EPIPREG (p from 1.2 × 10-8 to 0.04).

CONCLUSIONS

We identified five CpG sites associated with BMI at gestational week 28, and one with GWG. Three of the sites were replicated in an independent cohort. Several genetic variants were associated with DNA methylation at cg02786379 and cg16733643 suggesting a genetic component influencing differential methylation. The identified CpG sites were associated with cardiometabolic traits.

CLINICALTRIALS

GOV REGISTRATION NO

Not applicable.

The Inclusion of Underrepresented Populations in Cardiovascular Genetics and Epidemiology

Novel genetic risk markers have helped us to advance the field of cardiovascular epidemiology and refine our current understanding and risk stratification paradigms. The discovery and analysis of variants can help us to tailor prognostication and management. However, populations underrepresented in cardiovascular epidemiology and cardiogenetics research may experience inequities in care if prediction tools are not applicable to them clinically. Therefore, the purpose of this article is to outline the barriers that underrepresented populations can face in participating in genetics research, to describe the current efforts to diversify cardiogenetics research, and to outline strategies that researchers in cardiovascular epidemiology can implement to include underrepresented populations. Mistrust, a lack of diverse research teams, the improper use of sensitive biodata, and the constraints of genetic analyses are all barriers for including diverse populations in genetics studies. The current work is beginning to address the paucity of ethnically diverse genetics research and has already begun to shed light on the potential benefits of including underrepresented and diverse populations. Reducing barriers for individuals, utilizing community-driven research processes, adopting novel recruitment strategies, and pushing for organizational support for diverse genetics research are key steps that clinicians and researchers can take to develop equitable risk stratification tools and improve patient care.

A Polygenic Risk Score for Predicting Racial and Genetic Susceptibility to Prurigo Nodularis

Prurigo nodularis (PN) is an understudied inflammatory skin disease characterized by pruritic, hyperkeratotic nodules. Identifying the genetic factors underlying PN could help to better understand its etiology and guide the development of therapies. In this study, we developed a polygenic risk score that predicts a diagnosis of PN (OR = 1.41, P = 1.6 × 10-5) in two independent and continentally distinct populations. We also performed GWASs, which uncovered genetic variants associated with PN, including one near PLCB4 (rs6039266: OR = 3.15, P = 4.8 × 10-8) and others near TXNRD1 (rs34217906: OR = 1.71, P = 6.4 × 10-7; rs7134193: OR = 1.57, P = 1.1 × 10-6). Finally, we discovered that Black patients have over a two-times greater genetic risk of developing PN (OR = 2.63, P = 7.8 × 10-4). Combining the polygenic risk score and self-reported race together was significantly predictive of PN (OR = 1.32, P = 4.7 × 10-3). Strikingly, this association was more significant with race than after adjusting for genetic ancestry. Because race is a sociocultural construct and not a genetically bound category, our findings suggest that genetics, environmental influence, and social determinants of health likely affect the development of PN and may contribute to clinically observed racial disparities.

Alcohol use polygenic risk score, social support, and alcohol use among European American and African American adults

Alcohol use is influenced by genetic and environmental factors. We examined the interactive effects between genome-wide polygenic risk scores for alcohol use (alc-PRS) and social support in relation to alcohol use among European American (EA) and African American (AA) adults across sex and developmental stages (emerging adulthood, young adulthood, and middle adulthood). Data were drawn from 4,011 EA and 1,274 AA adults from the Collaborative Study on the Genetics of Alcoholism who were between ages 18-65 and had ever used alcohol. Participants completed the Semi-Structured Assessment for the Genetics of Alcoholism and provided saliva or blood samples for genotyping. Results indicated that social support from friends, but not family, moderated the association between alc-PRS and alcohol use among EAs and AAs (only in middle adulthood for AAs); alc-PRS was associated with higher levels of alcohol use when friend support was low, but not when friend support was high. Associations were similar across sex but differed across developmental stages. Findings support the important role of social support from friends in buffering genetic risk for alcohol use among EA and AA adults and highlight the need to consider developmental changes in the role of social support in relation to alcohol use.

The Recombination Hotspot Paradox: Co-evolution between PRDM9 and its target sites

Recombination often concentrates in small regions called recombination hotspots where recombination is much higher than the genome's average. In many vertebrates, including humans, gene PRDM9 specifies which DNA motifs will be the target for breaks that initiate recombination, ultimately determining the location of recombination hotspots. Because the sequence that breaks (allowing recombination) is converted into the sequence that does not break (preventing recombination), the latter sequence is over-transmitted to future generations and recombination hotspots are self-destructive. Given their self-destructive nature, recombination hotspots should eventually become extinct in genomes where they are found. While empirical evidence shows that individual hotspots do become inactive over time (die), hotspots are abundant in many vertebrates: a contradiction called the Recombination Hotspot Paradox. What saves recombination hotspots from their foretold extinction? Here we formulate a co-evolutionary model of the interaction among sequence-specific gene conversion, fertility selection, and recurrent mutation. We find that allelic frequencies oscillate leading to stable limit cycles. From a biological perspective this means that when fertility selection is weaker than gene conversion, it cannot stop individual hotspots from dying but can save them from extinction by driving their re-activation (resuscitation). In our model, mutation balances death and resuscitation of hotspots, thus maintaining their number over evolutionary time. Interestingly, we find that multiple alleles result in oscillations that are chaotic and multiple targets in oscillations that are asynchronous between targets thus helping to maintain the average genomic recombination probability constant. Furthermore, we find that the level of expression of PRDM9 should control for the fraction of targets that are hotspots and the overall temperature of the genome. Therefore, our co-evolutionary model improves our understanding of how hotspots may be replaced, thus contributing to solve the Recombination Hotspot Paradox. From a more applied perspective our work provides testable predictions regarding the relation between mutation probability and fertility selection with life expectancy of hotspots.

Assessment of NLRP3 Gene Polymorphisms with Periodontitis as Compared with Healthy Periodontium in Iraqi Arabs Patients

OBJECTIVES

 The nod-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome regulates the maturation and release of the cytokines as well as the activation of caspase in response to danger signals derived from pathogenic infection, tissue damage, andmetabolic changes that have a role in the pathogenesis of different diseases as periodontitis. Yet, the susceptibility to this illness could be determined by population-based genetic differences. The aim of this study was to determine whether periodontitis in Arab populations from Iraq is correlated with NLRP3 gene polymorphisms and measure clinical periodontal parameters and investigate their association with genetic polymorphisms of the NLRP3.

MATERIALS AND METHODS

 The study sample consisted of 94 participants ranging from 30 to 55 years old, both males and females who fulfilled the study's criteria. The selected participants were divided into two groups: the periodontitis group (62 subjects) and the healthy control group (32 subjects). The examination of clinical periodontal parameters of all participants was carried out, followed by a collection of venous blood for NLRP3 genetic analysis using the polymerase chain reaction-sequencing technique.

RESULTS

 The genetic analysis of NLRP3 genotypes at four single nucleotide polymorphisms (SNPs) (rs10925024, rs4612666, rs34777555, and rs10754557), by Hardy-Weinberg equilibrium, identified nonsignificant differences in studied groups. The C-T genotype among periodontitis was significantly different from controls, while the C-C genotype among control was significantly different from periodontitis at NLRP3 rs10925024. Overall, there were 35 SNPs in the periodontitis group and 10 SNPs in the control group for rs10925024 with significant differences versus nonsignificant differences of the other SNPs between the studied groups. Clinical attachment loss and NLRP3 rs10925024 additionally demonstrated a significant positive correlation in the periodontitis subjects.

CONCLUSION

 The findings suggested that polymorphisms of the NLRP3 gene may have a role and increasing the genetic susceptibility to periodontal disease in Arabs Iraqi patients.

Strategies for the Genomic Analysis of Admixed Populations

Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.

Genes of Predisposition to Childhood Beta-Cell Acute Lymphoblastic Leukemia in the Kazakh Population

BACKGROUND

Today, acute lymphoblastic leukemia is one of the most common malignant diseases of the hematopoietic system. The genetic predisposition to ALL is not fully explored in various ethnic populations.

OBJECTIVE

The study aimed to conduct a comparative analysis of the population frequencies of alleles and genotypes of polymorphic gene variants: immune regulation GATA3 (rs3824662); transcription and differentiation of B cells: ARID5B (rs7089424, rs10740055), IKZF1 (rs4132601); differentiation of hematopoietic cells: PIP4K2A (rs7088318); apoptosis: CEBPE (rs2239633), tumor suppressors: CDKN2A (rs3731249), TP53 (rs1042522); carcinogen metabolism: CBR3 (rs1056892), CYP1A1 (rs104894, rs4646903), according to genome-wide association studies analyses associated with the risk of developing pediatric beta-cell acute lymphoblastic leukemia (B-cell ALL), in an ethnically homogeneous population of Kazakhs with studied populations.

METHODS

The genomic database consists of 1800 conditionally healthy persons of Kazakh nationality, genotyped using OmniChip 2.5-8 Illumina chips at the deCODE genetics as part of the InterPregGen 7 project of the European Union (EU) framework program under Grant Agreement No. 282540.

RESULTS

High population frequencies of single nucleotide polymorphism (SNP) minor alleles identified for immune regulation genes - GATA3 rs3824662 - 42.5%; transcription and differentiation of B-cells genes - ARID5B rs7089424 - 33.1% and rs10740055 - 48.5%, which suggests their significant genetic contribution to the risk of development and prognosis of the effectiveness of B-cell ALL therapy in the Kazakh population. The significantly lower population frequency of the minor allele G rs1056892 CBR3 gene - 38.6% in the Kazakhs suggests its significant protective effect in reducing the risk of childhood B-cell ALL and the smaller number of cardiac complications after anthracycline therapy.

CONCLUSION

The obtained results will serve as a basis for developing effective methods for predicting the risk of development, early diagnosis, and effectiveness of treatment of B-cell ALL in children.

Biobank-scale methods and projections for sparse polygenic prediction from machine learning

In this paper we characterize the performance of linear models trained via widely-used sparse machine learning algorithms. We build polygenic scores and examine performance as a function of training set size, genetic ancestral background, and training method. We show that predictor performance is most strongly dependent on size of training data, with smaller gains from algorithmic improvements. We find that LASSO generally performs as well as the best methods, judged by a variety of metrics. We also investigate performance characteristics of predictors trained on one genetic ancestry group when applied to another. Using LASSO, we develop a novel method for projecting AUC and correlation as a function of data size (i.e., for new biobanks) and characterize the asymptotic limit of performance. Additionally, for LASSO (compressed sensing) we show that performance metrics and predictor sparsity are in agreement with theoretical predictions from the Donoho-Tanner phase transition. Specifically, a future predictor trained in the Taiwan Precision Medicine Initiative for asthma can achieve an AUC of [Formula: see text] and for height a correlation of [Formula: see text] for a Taiwanese population. This is above the measured values of [Formula: see text] and [Formula: see text], respectively, for UK Biobank trained predictors applied to a European population.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes

BACKGROUND

Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear.

RESULTS

By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection.

CONCLUSIONS

Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

Similarity and diversity of genetic architecture for complex traits between East Asian and European populations

BACKGROUND

Genome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently.

RESULTS

By leveraging summary statistics of 37 traits from East Asian (N_max=254,373) or European (N_max=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρ_g) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with [Formula: see text] ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs.

CONCLUSIONS

Our study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

Impact of cross-ancestry genetic architecture on GWASs in admixed populations

Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.

Proteome and genome integration analysis of obesity

ABSTRACT

The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.

Polygenic Risk Score in African populations: progress and challenges

Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects  single nucleotide polymorphisms (SNPs) that  contribute to the disease with low effect size  making it more precise at individual level risk prediction. PRS  analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with  low effect size but play an indispensable role to the observed phenotypic/trait variance.  PRS analysis has  applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies  show   that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that  lack of sufficient GWAS data and tools is  the limiting factor of applying PRS analysis to sub-Saharan populations.   We recommend developing Africa-specific PRS methods and tools for estimating and analyzing  African population data   for clinical  evaluation of PRSs of interest and predicting  rare diseases.

Polygenic Risk Score in African populations: progress and challenges

Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects  single nucleotide polymorphisms (SNPs) that  contribute to the disease with low effect size  making it more precise at individual level risk prediction. PRS  analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with  low effect size but play an indispensable role to the observed phenotypic/trait variance.  PRS analysis has  applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies  show   that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that  lack of sufficient GWAS data and tools is  the limiting factor of applying PRS analysis to sub-Saharan populations.   We recommend developing Africa-specific PRS methods and tools for estimating and analyzing  African population data   for clinical  evaluation of PRSs of interest and predicting  rare diseases.

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

A genome-wide association study identifies a possible role for cannabinoid signalling in the pathogenesis of diabetic kidney disease

Diabetic kidney disease (DKD), also known as diabetic nephropathy, is the leading cause of renal impairment and end-stage renal disease. Patients with diabetes are at risk for DKD because of poor control of their blood glucose, as well as nonmodifiable risk factors including age, ethnicity, and genetics. This genome-wide association study (GWAS) was conducted for the first time in the Emirati population to investigate possible genetic factors associated with the development and progression of DKD. We included data on 7,921,925 single nucleotide polymorphism (SNPs) in 258 cases of type 2 diabetes mellitus (T2DM) who developed DKD and 938 control subjects with T2DM who did not develop DKD. GWAS suggestive results (P < 1 × 10-5) were further replicated using summary statistics from three cohorts with T2DM-induced DKD (Bio Bank Japan data, UK Biobank, and FinnGen Project data) and T1DM-induced DKD (UK-ROI cohort data from Belfast, UK). When conducting a multiple linear regression model for gene-set analyses, the CNR2 gene demonstrated genome-wide significance at 1.46 × 10-6. SNPs in CNR2 gene, encodes cannabinoid receptor 2 or CB2, were replicated in Japanese samples with the leading SNP rs2501391 showing a Pcombined = 9.3 × 10-7, and odds ratio = 0.67 in association with DKD associated with T2DM, but not with T1DM, without any significant association with T2DM itself. The allele frequencies of our cohort and those of the replication cohorts were in most cases markedly different. In addition, we replicated the association between rs1564939 in the GLRA3 gene and DKD in T2DM (P = 0.016, odds ratio = 0.54 per allele C). Our findings suggest evidence that cannabinoid signalling may be involved in the development of DKD through CB2, which is expressed in different kidney regions and known to be involved in insulin resistance, inflammation, and the development of kidney fibrosis.

Future prospects for human genetics and genomics in drug discovery

Evidence from human genetics supporting the therapeutic hypothesis increases the likelihood that a drug will succeed in clinical trials. Rare and common disease genetics yield a wide array of alleles with a range of effect sizes that can proxy for the effect of a drug in disease. Recent advances in large scale population collections and whole genome sequencing approaches have provided a rich resource of human genetic evidence to support drug target selection. As the range of phenotypes profiled increases and ever more alleles are discovered across world-wide populations, these approaches will increasingly influence multiple stages across the lifespan of a drug discovery programme.

Single nucleotide variants in microRNA biosynthesis genes in Mexican individuals

Background: MicroRNAs (miRNAs) are important regulators in a variety of biological processes, and their dysregulation is associated with multiple human diseases. Single nucleotide variants (SNVs) in genes involved in the processing of microRNAs may alter miRNA regulation and could present high allele heterogeneity in populations from different ethnic groups. Thus, the aim of this study was to genotype 15 SNVs in eight genes involved in the miRNA processing pathway in Mexican individuals and compare their frequencies across 21 populations from five continental groups.

Methods: Genomic DNA was obtained from 399 healthy Mexican individuals. SNVs in AGO2 (rs2293939 and rs4961280), DGCR8 (rs720012), DICER (rs3742330 and rs13078), DROSHA (rs10719 and rs6877842), GEMIN3 (rs197388 and rs197414), GEMIN4 (rs7813, rs2740349, and rs4968104), TNRC6B (rs9611280), and XP05 (rs11077 and rs34324334) were genotyped using TaqMan probes. The minor allele frequency of each SNV was compared to those reported in the 1,000 Genomes database using chi-squared. Sankey plot was created in the SankeyMATIC package to visualize the frequency range of each variant in the different countries analyzed.

Results: In Mexican individuals, all 15 SNVs were found in Hardy-Weinberg equilibrium, with frequencies ranging from 0.04 to 0.45. The SNVs rs4961280, rs2740349, rs34324334, and rs720012 in Mexican individuals had the highest minor allele frequencies worldwide, whereas the minor allele frequencies of rs197388, rs10719, rs197414, and rs1107 were among the lowest in Mexican individuals. The variants had high allele heterogeneity among the sub-continental populations, ranging from monomorphic, as was the case for rs9611280 and rs34324334 in African groups, to &gt;0.50, which was the case for variants rs11077 and rs10719 in most of the populations. Importantly, the variants rs197388, rs720012, and rs197414 had FST values &gt; 0.18, indicating a directional selective process. Finally, the SNVs rs13078 and rs10719 significantly correlated with both latitude and longitude.

Conclusion: These data indicate the presence of high allelic heterogeneity in the worldwide distribution of the frequency of SNVs located in components of the miRNA processing pathway, which could modify the genetic susceptibility associated with human diseases in populations with different ancestry.

Childhood trajectories of internalising and externalising problems associated with a polygenic risk score for neuroticism in a UK birth cohort study

Background

Neuroticism represents a personality disposition towards experiencing negative emotions more frequently and intensely. Longitudinal studies suggest that neuroticism increases risk of several psychological problems. Improved understanding of how this trait manifests in early life could help inform preventative strategies in those liable to neuroticism.

Methods

This study explored how a polygenic risk score for neuroticism (NEU PRS) is expressed from infancy to late childhood across various psychological outcomes using multivariable linear and ordinal regression models. In addition, we employed a three-level mixed-effect model to characterise child internalising and externalising trajectories and estimate how a child PRS associated with both their overall levels and rates of change in 5279 children aged 3-11 in the Avon Longitudinal Study of Parents and Children cohort.

Results

We found evidence that the NEU PRS was associated with a more emotionally sensitive temperament in early infancy in addition to higher emotional and behavioural problems and a higher risk of meeting diagnostic criteria for a variety of clinical disorders, particularly anxiety disorders, in childhood. The NEU PRS was associated with overall levels of internalising and externalising trajectories, with a larger magnitude of association on the internalising trajectory. The PRS was also associated with slower rates of reduction of internalising problems across childhood.

Conclusions

Our findings using a large, well-characterised birth cohort study suggest that phenotypic manifestations of a PRS for adult neuroticism can be detected as early as in infancy and that this PRS associates with several mental health problems and differences in emotional trajectories across childhood.

Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study

BACKGROUND

Evidence from observational studies and clinical trials suggests that the gut microbiota is associated with cancer. However, the causal association between gut microbiota and cancer remains to be determined.

METHODS

We first identified two sets of gut microbiota based on phylum, class, order, family, and genus level information, and cancer data were obtained from the IEU Open GWAS project. We then performed two-sample Mendelian randomisation (MR) to determine whether the gut microbiota is causally associated with eight cancer types. Furthermore, we performed a bi-directional MR analysis to examine the direction of the causal relations.

RESULTS

We identified 11 causal relationships between genetic liability in the gut microbiome and cancer, including those involving the genus Bifidobacterium. We found 17 strong associations between genetic liability in the gut microbiome and cancer. Moreover, we found 24 associations between genetic liability in the gut microbiome and cancer using multiple datasets.

CONCLUSIONS

Our MR analysis revealed that the gut microbiota was causally associated with cancers and may be useful in providing new insights for further mechanistic and clinical studies of microbiota-mediated cancer.

Impact of cross-ancestry genetic architecture on GWAS in admixed populations

Genome-wide association studies (GWAS) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWAS in admixed populations, such as the need to correctly adjust for population stratification to balance type I error with statistical power. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes we find that modeling HetLanc in its absence reduces statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs HetLanc is not large enough for GWAS to benefit from modeling heterogeneity.

Genetic Liability, Exposure Severity, and Post-Traumatic Stress Disorder Predict Cognitive Impairment in World Trade Center Responders

BACKGROUND

There is a high incidence of cognitive impairment among World Trade Center (WTC) responders, comorbid with post-traumatic stress disorder (PTSD). Yet, it remains unknown whether genetic liability for Alzheimer's disease, PTSD, educational attainment, or for a combination of these phenotypes, is associated with cognitive impairment in this high-risk population. Similarly, whether the effects of genetic liability are comparable to PTSD and indicators of exposure severity remains unknown.

OBJECTIVE

In a study of 3,997 WTC responders, polygenic scores for Alzheimer's disease, PTSD, and educational attainment were used to test whether genome-wide risk for one or more of these phenotypes is associated with cognitive impairment, controlling for population stratification, while simultaneously estimating the effects of demographic factors and indicators of 9/11 exposure severity, including symptoms of PTSD.

RESULTS

Polygenic scores for Alzheimer's disease and educational attainment were significantly associated with an increase and decrease, respectively, in the hazard rate of mild cognitive impairment. The polygenic score for Alzheimer's disease was marginally associated with an increase in the hazard rate of severe cognitive impairment, but only age, exposure severity, and symptoms of PTSD were statistically significant predictors.

CONCLUSION

These results add to the emerging evidence that many WTC responders are suffering from mild cognitive impairments that resemble symptoms of Alzheimer's disease, as genetic liability for Alzheimer's disease predicted incidence of mild cognitive impairment. However, compared to polygenic scores, effect sizes were larger for PTSD and the type of work that responders completed during rescue and recovery efforts.

Genome-Wide Association Study of Adhesive Capsulitis Suggests Significant Genetic Risk Factors

BACKGROUND

Adhesive capsulitis of the shoulder involves loss of passive range of motion with associated pain and can develop spontaneously, with no obvious injury or inciting event. The pathomechanism of this disorder remains to be elucidated, but known risk factors for adhesive capsulitis include diabetes, female sex, and thyroid dysfunction. Additionally, transcriptional profiling and pedigree analyses have suggested a role for genetics. Identification of elements of genetic risk for adhesive capsulitis using population-based techniques can provide the basis for guiding both the personalized treatment of patients based on their genetic profiles and the development of new treatments by identification of the pathomechanism.

METHODS

A genome-wide association study (GWAS) was conducted using the U.K. Biobank (a collection of approximately 500,000 patients with genetic data and associated ICD-10 [International Classification of Diseases, 10th Revision] codes), comparing 2,142 patients with the ICD-10 code for adhesive capsulitis (M750) to those without. Separate GWASs were conducted controlling for 2 of the known risk factors of adhesive capsulitis-hypothyroidism and diabetes. Logistic regression analysis was conducted controlling for factors including sex, thyroid dysfunction, diabetes, shoulder dislocation, smoking, and genetics.

RESULTS

Three loci of significance were identified: rs34315830 (in WNT7B; odds ratio [OR] = 1.28; 95% confidence interval [CI], 1.22 to 1.39), rs2965196 (in MAU2; OR = 1.67; 95% CI, 1.39 to 2.00), and rs1912256 (in POU1F1; OR = 1.22; 95% CI, 1.14 to 1.31). These loci retained significance when controlling for thyroid dysfunction and diabetes. The OR for total genetic risk was 5.81 (95% CI, 4.08 to 8.31), compared with 1.70 (95% CI, 1.18 to 2.36) for hypothyroidism and 4.23 (95% CI, 2.32 to 7.05) for diabetes.

CONCLUSIONS

The total genetic risk associated with adhesive capsulitis was significant and similar to the risks associated with hypothyroidism and diabetes. Identification of WNT7B, POU1F1, and MAU2 implicates the Wnt pathway and cell proliferation response in the pathomechanism of adhesive capsulitis.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Animal-SNPAtlas: a comprehensive SNP database for multiple animals

Single-nucleotide polymorphisms (SNPs) as the most important type of genetic variation are widely used in describing population characteristics and play vital roles in animal genetics and breeding. Large amounts of population genetic variation resources and tools have been developed in human, which provided solid support for human genetic studies. However, compared with human, the development of animal genetic variation databases was relatively slow, which limits the genetic researches in these animals. To fill this gap, we systematically identified ∼ 499 million high-quality SNPs from 4784 samples of 20 types of animals. On that basis, we annotated the functions of SNPs, constructed high-density reference panels and calculated genome-wide linkage disequilibrium (LD) matrixes. We further developed Animal-SNPAtlas, a user-friendly database (http://gong_lab.hzau.edu.cn/Animal_SNPAtlas/) which includes high-quality SNP datasets and several support tools for multiple animals. In Animal-SNPAtlas, users can search the functional annotation of SNPs, perform online genotype imputation, explore and visualize LD information, browse variant information using the genome browser and download SNP datasets for each species. With the massive SNP datasets and useful tools, Animal-SNPAtlas will be an important fundamental resource for the animal genomics, genetics and breeding community.

Characterization of Genetic Risk of End-Stage Knee Osteoarthritis Treated with Total Knee Arthroplasty: A Genome-Wide Association Study

BACKGROUND

End-stage knee osteoarthritis (OA) is a highly debilitating disease for which total knee arthroplasty (TKA) serves as an effective treatment option. Although a genetic component to OA in general has been described, evaluation of the genetic contribution to end-stage OA of the knee is limited. To this end, we present a genome-wide association study involving patients undergoing TKA for primary knee OA to characterize the genetic features of severe disease on a population level.

METHODS

Individuals with the diagnosis of knee OA who underwent primary TKA were identified in the U.K. Biobank using administrative codes. The U.K. Biobank is a data repository containing prospectively collected clinical and genomic data for >500,000 patients. A genome-wide association analysis was performed using the REGENIE software package. Logistic regression was also used to compare the total genetic risk between subgroups stratified by age and body mass index (BMI).

RESULTS

A total of 16,032 patients with end-stage knee OA who underwent primary TKA were identified. Seven genetic loci were found to be significantly associated with end-stage knee OA. The odds ratio (OR) for developing end-stage knee OA attributable to genetics was 1.12 (95% confidence interval [CI], 1.10 to 1.14), which was lower than the OR associated with BMI (OR = 1.81; 95% CI, 1.78 to 1.83) and age (OR = 2.38; 95% CI, 2.32 to 2.45). The magnitude of the OR for developing end-stage knee OA attributable to genetics was greater in patients <60 years old than in patients ≥60 years old (p = 0.002).

CONCLUSIONS

This population-level genome-wide association study of end-stage knee OA treated with primary TKA was notable for identifying multiple significant genetic variants. These loci involve genes responsible for cartilage development, cartilage homeostasis, cell signaling, and metabolism. Age and BMI appear to have a greater impact on the risk of developing end-stage disease compared with genetic factors. The genetic contribution to the development of severe disease is greater in younger patients.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Coronavirus Host Genomics Study: South Africa (COVIGen-SA)

Host genetic factors are known to modify the susceptibility, severity, and outcomes of COVID-19 and vary across populations. However, continental Africans are yet to be adequately represented in such studies despite the importance of genetic factors in understanding Africa's response to the pandemic. We describe the development of a research resource for coronavirus host genomics studies in South Africa known as COVIGen-SA-a multicollaborator strategic partnership designed to provide harmonised demographic, clinical, and genetic information specific to Black South Africans with COVID-19. Over 2,000 participants have been recruited to date. Preliminary results on 1,354 SARS-CoV-2 positive participants from four participating studies showed that 64.7% were female, 333 had severe disease, and 329 were people living with HIV. Through this resource, we aim to provide insights into host genetic factors relevant to African-ancestry populations, using both genome-wide association testing and targeted sequencing of important genomic loci. This project will promote and enhance partnerships, build skills, and develop resources needed to address the COVID-19 burden and associated risk factors in South African communities.

Promoting Inclusive Recruitment: a Qualitative Study of Black Adults' Decision to Participate in Genetic Research

Underrepresentation of Black individuals in genetic research is a longstanding issue. There are well-documented strategies to improve the enrollment of Black participants; however, few studies explore these strategies-as well as the barriers and facilitators for participation-by sampling Black people who have previously participated in genetic research. This study explores the decision-making process of Black adults who have participated in genetic research to identify best practices in the recruitment of Black subjects in genetic research. We conducted 18 semi-structured interviews with Black adults with prior research participation in genetic studies housed at an urban academic medical center in the United States of America (USA). An online survey was conducted with the participants to gather demographic data and information on prior research participation. Trust in research was ascertained with the Corbie-Smith Distrust in Clinical Research Index. Two participants scored high levels of distrust using the validated index. Using thematic content analysis, 4 themes emerged from the interviews: (1) Participants are active players in health system, (2) information is power, and transparency is key, (3) therapeutic alliances and study characteristics facilitate participation, and (4) race pervades the research process. The decision to participate in genetic research for the participants in our study was prompted by participants' internal motivations and facilitated by trust in their doctor, trust in the institution, and ease of participation. Most participants viewed their enrollment in genetic research in the context of their own racial identity and the history of medical racism in the USA.

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations.

Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing

Background

Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking.

Methods

By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement.

Results

Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones.

Conclusion

Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03637-8.

No person left behind: Mapping the health policy landscape for genomics research in the Caribbean

The Caribbean has long been an under-represented geographical region in the field of genomics research. Such under-representation may result in Caribbean people being underserved by precision medicine and other public health benefits of genomics. A collaboration among regional and international researchers aims to address this issue through the H3ECaribbean project (Human Heredity, Environment, and Health in the Caribbean), which builds on the lessons and success of H3Africa. The Caribbean project aims to target issues of social justice by encouraging the inclusion of diverse Caribbean communities in genomics research. This paper explores a framework for the ethical and socially acceptable conduct of genomics research in the Caribbean, taking account of the cultural peculiarities of the region. This is done in part by exploring research ethics issues identified in indigenous communities in North America, Small Island Developing States, and similar endeavours from the African continent. The framework provides guidance for interacting with local community leaders, as well as detailing steps for obtaining informed consent of all participants. Specifically, the authors outline the methods to ensure effective interaction and enforce full transparency with study participants to combat historical neglect when working with under-represented communities in the Caribbean.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection.

Genetic mechanisms influencing COVID-19 susceptibility are not well understood. Here, the authors analyzed whole blood RNA-seq data of 465 Japanese individuals with COVID-19, highlighting thousands of fine-mapped variants affecting expression and splicing of genes, as well as the presence of COVID-19 severity-interaction eQTLs.

Mining alleles for tar spot complex resistance from CIMMYT's maize Germplasm Bank

The tar spot complex (TSC) is a devastating disease of maize (Zea mays L.), occurring in 17 countries throughout Central, South, and North America and the Caribbean, and can cause grain yield losses of up to 80%. As yield losses from the disease continue to intensify in Central America, Phyllachora maydis, one of the causal pathogens of TSC, was first detected in the United States in 2015, and in 2020 in Ontario, Canada. Both the distribution and yield losses due to TSC are increasing, and there is a critical need to identify the genetic resources for TSC resistance. The Seeds of Discovery Initiative at CIMMYT has sought to combine next-generation sequencing technologies and phenotypic characterization to identify valuable alleles held in the CIMMYT Germplasm Bank for use in germplasm improvement programs. Individual landrace accessions of the “Breeders' Core Collection” were crossed to CIMMYT hybrids to form 918 unique accessions topcrosses (F1 families) which were evaluated during 2011 and 2012 for TSC disease reaction. A total of 16 associated SNP variants were identified for TSC foliar leaf damage resistance and increased grain yield. These variants were confirmed by evaluating the TSC reaction of previously untested selections of the larger F1 testcross population (4,471 accessions) based on the presence of identified favorable SNPs. We demonstrated the usefulness of mining for donor alleles in Germplasm Bank accessions for newly emerging diseases using genomic variation in landraces.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

LmTag: functional-enrichment and imputation-aware tag SNP selection for population-specific genotyping arrays

Despite the rapid development of sequencing technology, single-nucleotide polymorphism (SNP) arrays are still the most cost-effective genotyping solutions for large-scale genomic research and applications. Recent years have witnessed the rapid development of numerous genotyping platforms of different sizes and designs, but population-specific platforms are still lacking, especially for those in developing countries. SNP arrays designed for these countries should be cost-effective (small size), yet incorporate key information needed to associate genotypes with traits. A key design principle for most current platforms is to improve genome-wide imputation so that more SNPs not included in the array (imputed SNPs) can be predicted. However, current tag SNP selection methods mostly focus on imputation accuracy and coverage, but not the functional content of the array. It is those functional SNPs that are most likely associated with traits. Here, we propose LmTag, a novel method for tag SNP selection that not only improves imputation performance but also prioritizes highly functional SNP markers. We apply LmTag on a wide range of populations using both public and in-house whole-genome sequencing databases. Our results show that LmTag improved both functional marker prioritization and genome-wide imputation accuracy compared to existing methods. This novel approach could contribute to the next generation genotyping arrays that provide excellent imputation capability as well as facilitate array-based functional genetic studies. Such arrays are particularly suitable for under-represented populations in developing countries or non-model species, where little genomics data are available while investment in genome sequencing or high-density SNP arrays is limited. $\textrm{LmTag}$ is available at: https://github.com/datngu/LmTag.

Genetics of Alzheimer Disease

PURPOSE OF REVIEW

This article discusses the spectrum of genetic risk in familial and sporadic forms of early- and late-onset Alzheimer disease (AD). Recent work illuminating the complex genetic architecture of AD is discussed in the context of high and low risk and what is known in different populations.

RECENT FINDINGS

A small proportion of AD is autosomal dominant familial AD caused by variants in PSEN1, PSEN2, or APP, although more recently described rare genetic changes can also increase risk substantially over the general population, with odds ratios estimated at 2 to 4. APOE remains the strongest genetic risk factor for late-onset AD, and understanding the biology of APOE has yielded mechanistic insights and leads for therapeutic interventions. Genome-wide studies enabled by rapidly developing technologic advances in sequencing have identified numerous risk factors that have a low impact on risk but are widely shared throughout the population and involve a repertoire of cell pathways, again shining light on potential paths to intervention. Population studies aimed at defining and stratifying genetic AD risk have been informative, although they are not yet widely applicable clinically because the studies were not performed in people with diverse ancestry and ethnicity and thus population-wide data are lacking.

SUMMARY

The value of genetic information to practitioners in the clinic is distinct from information sought by researchers looking to identify novel therapeutic targets. It is possible to envision a future in which genetic stratification joins other biomarkers to facilitate therapeutic choices and inform prognosis. Genetics already has transformed our understanding of AD pathogenesis and will, no doubt, continue to reveal the complexity of brain biology in health and disease.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Dissection of Maize Drought Tolerance at the Flowering Stage Using Genome-Wide Association Studies

Drought is one of the most critical environmental factors constraining maize production. When it occurs at the flowering stage, serious yield losses are caused, and often, the damage is irretrievable. In this study, anthesis to silk interval (ASI), plant height (PH), and ear biomass at the silking date (EBM) of 279 inbred lines were studied under both water-stress (WS) and well-water (WW) field conditions, for three consecutive years. Averagely, ASI was extended by 25.96%, EBM was decreased by 17.54%, and the PH was reduced by 12.47% under drought stress. Genome-wide association studies were carried out using phenotypic values under WS, WW, and drought-tolerance index (WS-WW or WS/WW) and applying a mixed linear model that controls both population structure and relative kinship. In total, 71, 159, and 21 SNPs, located in 32, 59, and 12 genes, were significantly (P < 10−5) associated with ASI, EBM, and PH, respectively. Only a few overlapped candidate genes were found to be associated with the same drought-related traits under different environments, for example, ARABIDILLO 1, glycoprotein, Tic22-like, and zinc-finger family protein for ASI; 26S proteasome non-ATPase and pyridoxal phosphate transferase for EBM; 11-ß-hydroxysteroid dehydrogenase, uncharacterised, Leu-rich repeat protein kinase, and SF16 protein for PH. Furthermore, most candidate genes were revealed to be drought-responsive in an association panel. Meanwhile, the favourable alleles/key variations were identified with a haplotype analysis. These candidate genes and their key variations provide insight into the genetic basis of drought tolerance, especially for the female inflorescence, and will facilitate drought-tolerant maize breeding.

VEGF-A, VEGFR1 and VEGFR2 single nucleotide polymorphisms and outcomes from the AGITG MAX trial of capecitabine, bevacizumab and mitomycin C in metastatic colorectal cancer

The phase III MAX clinical trial randomised patients with metastatic colorectal cancer (mCRC) to receive first-line capecitabine chemotherapy alone or in combination with the anti-VEGF-A antibody bevacizumab (± mitomycin C). We utilised this cohort to examine whether single nucleotide polymorphisms (SNPs) in VEGF-A, VEGFR1, and VEGFR2 are predictive of efficacy outcomes with bevacizumab or the development of hypertension. Genomic DNA extracted from archival FFPE tissue for 325 patients (69% of the MAX trial population) was used to genotype 16 candidate SNPs in VEGF-A, VEGFR1, and VEGFR2, which were analysed for associations with efficacy outcomes and hypertension. The VEGF-A rs25648 ‘CC’ genotype was prognostic for improved PFS (HR 0.65, 95% CI 0.49 to 0.85; P = 0.002) and OS (HR 0.70, 95% CI 0.52 to 0.94; P = 0.019). The VEGF-A rs699947 ‘AA’ genotype was prognostic for shorter PFS (HR 1.32, 95% CI 1.002 to 1.74; P = 0.048). None of the analysed SNPs were predictive of bevacizumab efficacy outcomes. VEGFR2 rs11133360 ‘TT’ was associated with a lower risk of grade ≥ 3 hypertension (P = 0.028). SNPs in VEGF-A, VEGFR1 and VEGFR2 did not predict bevacizumab benefit. However, VEGF-A rs25648 and rs699947 were identified as novel prognostic biomarkers and VEGFR2 rs11133360 was associated with less grade ≥ 3 hypertension.

Prevalence and correlates of joint pain among Chinese breast cancer survivors receiving aromatase inhibitor treatment

BACKGROUND

Aromatase inhibitor (AI)-induced joint pain is a common toxicity of AI treatment. Although many studies have been conducted to examine the occurrence and severity of AI-induced joint pain in breast cancer survivors, none of the studies focused on the Chinese population with breast cancer. Given that the differences in cultural background and the genetic structure between Asians and Caucasians may contribute to different phenotypes of joint pain, this cross-sectional study was therefore conducted to examine the prevalence of AI-induced joint pain among Chinese breast cancer survivors receiving AI treatment and the correlates of pain.

METHODS

This cross-sectional study was conducted in a tertiary hospital in China. Breast cancer survivors undergoing AI treatment were recruited to complete the following questionnaires: a self-designed baseline data form, the Nordic Musculoskeletal Questionnaire (NMQ), the Brief Pain Inventory (BPI), the 36-Item Short Form Health Survey (SF-36), and the Functional Assessment of Cancer Therapy-Breast (FACT-B). Based on the assessment results of NMQ (if the participant indicated pain in specific body parts), participants were then invited to complete other questionnaires to specifically assess the joint symptoms, including the Oxford Knee Score (OKS), the Oxford Hip Score (OHS), the Michigan Hand Outcomes Questionnaire (MHQ), and the Manchester Foot Pain Disability Questionnaire (MFPDQ). Descriptive analysis was used to analyse participants' baseline data and the prevalence of pain. Stepwise multiple regression was used to identify the correlates of pain.

RESULTS

Four hundred and ten participants were analysed. According to the NMQ, 71.7% of the participants experienced joint symptoms in at least one joint, and the most frequently mentioned joint was knee (39.0%). The diagram in BPI indicated that 28.0% of the participants had the worst pain around knees. In patients with knee pain, the mean OKS score was 40.46 ± 6.19. The sub-scores of BPI for pain intensity and pain interference were 1.30 ± 1.63 and 1.24 ± 1.79, respectively. Patients' poorer physical well-being/functioning, previous use of AI treatment, presence of osteoarthritis, and receiving of physiotherapy were identified as four common correlates of greater severity of pain and pain interference (p < 0.05).

CONCLUSIONS

Chinese breast cancer survivors can experience joint pain at various locations, particularly knees. In addition to increasing the use of interventions for pain alleviation, a comprehensive assessment of survivors' conditions such as physical functioning, history of AI treatment, and presence of osteoarthritis should be emphasized to identify survivors who need more attention and tailored interventions.

A missense variant in SHARPIN mediates Alzheimer's disease-specific brain damages

Established genetic risk factors for Alzheimer's disease (AD) account for only a portion of AD heritability. The aim of this study was to identify novel associations between genetic variants and AD-specific brain atrophy. We conducted genome-wide association studies for brain magnetic resonance imaging measures of hippocampal volume and entorhinal cortical thickness in 2643 Koreans meeting the clinical criteria for AD (n = 209), mild cognitive impairment (n = 1449) or normal cognition (n = 985). A missense variant, rs77359862 (R274W), in the SHANK-associated RH Domain Interactor (SHARPIN) gene was associated with entorhinal cortical thickness (p = 5.0 × 10^-9) and hippocampal volume (p = 5.1 × 10^-12). It revealed an increased risk of developing AD in the mediation analyses. This variant was also associated with amyloid-β accumulation (p = 0.03) and measures of memory (p = 1.0 × 10^-4) and executive function (p = 0.04). We also found significant association of other SHARPIN variants with hippocampal volume in the Alzheimer's Disease Neuroimaging Initiative (rs3417062, p = 4.1 × 10^-6) and AddNeuroMed (rs138412600, p = 5.9 × 10^-5) cohorts. Further, molecular dynamics simulations and co-immunoprecipitation indicated that the variant significantly reduced the binding of linear ubiquitination assembly complex proteins, SHPARIN and HOIL-1 Interacting Protein (HOIP), altering the downstream NF-κB signaling pathway. These findings suggest that SHARPIN plays an important role in the pathogenesis of AD.

Osteopontin Gene Polymorphisms Are Associated with Cardiovascular Risk Factors in Patients with Premature Coronary Artery Disease

Osteopontin (OPN) is considered a clinical predictor of cardiovascular disease. We aimed to evaluate the association of the OPN gene polymorphisms rs2728127 and rs11730582 with the development of premature coronary artery disease (pCAD), cardiovascular risk factors, and cardiometabolic parameters. We evaluated 1142 patients with pCAD and 1073 controls. Both polymorphisms were determined by Taqman assays. Similar allele and genotype frequencies were observed in both groups; additionally, an association of these polymorphisms with CAD and cardiometabolic parameters was observed in both groups. In patients with pCAD, the rs11730582 was associated with a high risk of hypoadiponectinemia (OR = 1.300, P _additive = 0.003), low risk of hypertension (OR = 0.709, P _{codominant 1} = 0.030), and low risk of having high non-HDL cholesterol (OR = 0.637, P _additive = 0.038). In the control group, the rs2728127 was associated with a low risk of fatty liver (OR = 0.766, P _additive = 0.038); while the rs11730582 was associated with a low risk of hypoadiponectinemia (OR = 0.728, P _dominant = 0.022), and risk of having elevated apolipoprotein B (OR = 1.400, P _dominant = 0.031). Our results suggest that in Mexican individuals, the rs11730582 and rs2728127 OPN gene polymorphisms are associated with some abnormal metabolic variables in patients with pCAD and controls.