Genetic Risk Scores for Complex Disease Traits in Youth

Forensic height estimation using polygenic score in Korean population

Height is known to be a classically heritable trait controlled by complex polygenic factors. Numerous height-associated genetic variants across the genome have been identified so far. It is also a representative of externally visible characteristics (EVC) for predicting appearance in forensic science. When biological evidence at a crime scene is deficient in identifying an individual, the examination of forensic DNA phenotyping using some genetic variants could be considered. In this study, we aimed to predict 'height', a representative forensic phenotype, by using a small number of genetic variants when short tandem repeat (STR) analysis is hard with insufficient biological samples. Our results not only replicated previous genetic signals but also indicated an upward trend in polygenic score (PGS) with increasing height in the validation and replication stages for both genders. These results demonstrate that the established SNP sets in this study could be used for height estimation in the Korean population. Specifically, since the PGS model constructed in this study targets only a small number of SNPs, it contributes to enabling forensic DNA phenotyping even at crime scenes with a minimal amount of biological evidence. To the best of our knowledge, this was the first study to evaluate a PGS model for height estimation in the Korean population using GWAS signals. Our study offers insight into the polygenic effect of height in East Asians, incorporating genetic variants from non-Asian populations.

Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations

Key Points

Background

CKD is a risk factor of cardiovascular disease and early death. Recently, polygenic risk scores (PRSs) have been developed to quantify risk for CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PRS development overall. Moreover, European ancestry–derived PRSs demonstrate diminished predictive performance in African ancestry populations.

Methods

This study aimed to develop a PRS for CKD in Black American populations. We obtained score weights from a meta-analysis of genome-wide association studies for eGFR in the Million Veteran Program and Reasons for Geographic and Racial Differences in Stroke Study to develop an eGFR PRS. We optimized the PRS risk model in a cohort of participants from the Hypertension Genetic Epidemiology Network. Validation was performed in subsets of Black participants of the Trans-Omics in Precision Medicine Consortium and Genetics of Hypertension Associated Treatment Study.

Results

The prevalence of CKD—defined as stage 3 or higher—was associated with the PRS as a continuous predictor (odds ratio [95% confidence interval]: 1.35 [1.08 to 1.68]) and in a threshold-dependent manner. Furthermore, including APOL1 risk status—a putative variant for CKD with higher prevalence among those of sub-Saharan African descent—improved the score's accuracy. PRS associations were robust to sensitivity analyses accounting for traditional CKD risk factors, as well as CKD classification based on prior eGFR equations. Compared with previously published PRS, the predictive performance of our PRS was comparable with a European ancestry–derived PRS for kidney traits. However, single-ancestry PRSs were less predictive than multi-ancestry–derived PRSs.

Conclusions

In this study, we developed a PRS that was significantly associated with CKD with improved predictive accuracy when including APOL1 risk status. However, PRS generated from multi-ancestry populations outperformed single-ancestry PRS in our study.

Effects of endocrine disrupting chemicals and their interactions with genetic risk scores on cardiometabolic traits

Ubiquitous non-persistent endocrine disrupting chemicals (EDCs) have inconsistent associations with cardiometabolic traits. Additionally, large-scale genome-wide association studies (GWASs) have yielded many genetic risk variants for cardiometabolic traits and diseases. This study aimed to investigate the associations between a wide range of EDC exposures (parabens, bisphenols, and phthalates) and 14 cardiometabolic traits and whether these are moderated by their respective genetic risk scores (GRSs). Data were from 1074 participants aged 18 years or older of the Lifelines Cohort Study, a large population-based biobank. GRSs for 14 cardiometabolic traits were calculated based on genome-wide significant common variants from recent GWASs. The concentrations of 15 EDCs in 24-hour urine were measured by isotope dilution liquid chromatography tandem mass spectrometry technology. The main effects of trait-specific GRSs and each of the EDC exposures and their interaction effects on the 14 cardiometabolic traits were examined in multiple linear regression. The present study confirmed significant main effects for all GRSs on their corresponding cardiometabolic trait. Regarding the main effects of EDC exposures, 26 out of 280 EDC-trait tests were significant with explained variances ranging from 0.43 % (MMP- estimated glomerular filtration rate (eGFR)) to 2.37 % (PrP-waist-hip ratio adjusted body mass index (WHRadjBMI)). We confirmed the association of MiBP and MBzP with WHRadjBMI and body mass index (BMI), and showed that parabens, bisphenol F, and many other phthalate metabolites significantly contributed to the variance of WHRadjBMI, BMI, high-density lipoprotein (HDL), eGFR, fasting glucose (FG), and diastolic blood pressure (DBP). Only one association between BMI and bisphenol F was nominally significantly moderated by the GRS explaining 0.36 % of the variance. However, it did not survive multiple testing correction. We showed that non-persistent EDC exposures exerted effects on BMI, WHRadjBMI, HDL, eGFR, FG, and DBP. However no evidence for a modulating role of GRSs was found.

Psychiatric Polygenic Risk Scores Across Youth With Bipolar Disorder, Youth at High Risk for Bipolar Disorder, and Controls

OBJECTIVE

There is a pronounced gap in knowledge regarding polygenic underpinnings of youth bipolar disorder (BD). This study aimed to compare polygenic risk scores (PRSs) in youth with BD, youth at high clinical and/or familial risk for BD (HR), and controls.

METHOD

Participants were 344 youths of European ancestry (13-20 years old), including 136 youths with BD, 121 HR youths, and 87 controls. PRSs for BD, schizophrenia, major depressive disorder, and attention-deficit/hyperactivity disorder were constructed using independent genome-wide summary statistics from adult cohorts. Multinomial logistic regression was used to examine the association between each PRS and diagnostic status (BD vs HR vs controls). All genetic analyses controlled for age, sex, and 2 genetic principal components.

RESULTS

The BD group showed significantly higher BD-PRS than the control group (odds ratio = 1.54, 95% CI = 1.13-2.10, p = .006), with the HR group numerically intermediate. BD-PRS explained 7.9% of phenotypic variance. PRSs for schizophrenia, major depressive disorder, and attention-deficit/hyperactivity disorder were not significantly different among groups. In the BD group, BD-PRS did not significantly differ in relation to BD subtype, age of onset, psychosis, or family history of BD.

CONCLUSION

BD-PRS derived from adult genome-wide summary statistics is elevated in youth with BD. Absence of significant between-group differences in PRSs for other psychiatric disorders supports the specificity of BD-PRS in youth. These findings add to the biological validation of BD in youth and could have implications for early identification and diagnosis. To enhance clinical utility, future genome-wide association studies that focus specifically on early-onset BD are warranted, as are studies integrating additional genetic and environmental factors.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure sex and gender balance in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Monogenic and polygenic concepts in chronic kidney disease (CKD)

Kidney function is strongly influenced by genetic factors with both monogenic and polygenic factors contributing to kidney function. Monogenic disorders with primarily autosomal dominant inheritance patterns account for 10% of adult and 50% of paediatric kidney diseases. However, kidney function is also a complex trait with polygenic architecture, where genetic factors interact with environment and lifestyle factors. Family studies suggest that kidney function has significant heritability at 35-69%, capturing complexities of the genome with shared environmental factors. Genome-wide association studies estimate the single nucleotide polymorphism-based heritability of kidney function between 7.1 and 20.3%. These heritability estimates, measuring the extent to which genetic variation contributes to CKD risk, indicate a strong genetic contribution. Polygenic Risk Scores have recently been developed for chronic kidney disease and kidney function, and validated in large populations. Polygenic Risk Scores show correlation with kidney function but lack the specificity to predict individual-level changes in kidney function. Certain kidney diseases, such as membranous nephropathy and IgA nephropathy that have significant genetic components, may benefit most from polygenic risk scores for improved risk stratification. Genetic studies of kidney function also provide a potential avenue for the development of more targeted therapies and interventions. Understanding the development and validation of genomic scores is required to guide their implementation and identify the most appropriate potential implications in clinical practice. In this review, we provide an overview of the heritability of kidney function traits in population studies, explore both monogenic and polygenic concepts in kidney disease, with a focus on recently developed polygenic risk scores in kidney function and chronic kidney disease, and review specific diseases which are most amenable to incorporation of genomic scores.

Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

INTRODUCTION

The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations.

METHODS

Here, we examined how ancestrally diverse studies could clarify Lp(a)'s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations.

RESULTS

Fourteen genome-wide significant loci with numerous population specific signals of large effect were identified that enabled construction of Lp(a) PRS of moderate (R2=15% in East Asians) to high (R2=50% in Europeans) accuracy. For all populations, PRS showed promise as a 'rule out' for elevated Lp(a) because certainty of assignment to the low-risk threshold was high (88.0%-99.9%) across PRS thresholds (80th-99th percentile). Causal effects of increased Lp(a) with increased glycated haemoglobin were estimated for Europeans (p value =1.4×10-6), although inverse effects in Africans and East Asians suggested the potential for heterogeneous causal effects. Finally, Hispanic/Latinos were the only population in which known associations with coronary atherosclerosis and ischaemic heart disease were identified in external testing of Lp(a) PRS phenotypic effects.

CONCLUSIONS

Our results emphasise the merits of prioritising ancestral diversity when addressing Lp(a) evidence gaps.

Development of a genetic risk score to predict the risk of hypertension in European adolescents from the HELENA study

Introduction

From genome wide association study (GWAS) a large number of single nucleotide polymorphisms (SNPs) have previously been associated with blood pressure (BP) levels. A combination of SNPs, forming a genetic risk score (GRS) could be considered as a useful genetic tool to identify individuals at risk of developing hypertension from early stages in life. Therefore, the aim of our study was to build a GRS being able to predict the genetic predisposition to hypertension (HTN) in European adolescents.

Methods

Data were extracted from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study. A total of 869 adolescents (53% female), aged 12.5-17.5, with complete genetic and BP information were included. The sample was divided into altered (≥130 mmHg for systolic and/or ≥80 mmHg for diastolic) or normal BP. Based on the literature, a total of 1.534 SNPs from 57 candidate genes related with BP were selected from the HELENA GWAS database.

Results

From 1,534 SNPs available, An initial screening of SNPs univariately associated with HTN (p < 0.10) was established, to finally obtain a number of 16 SNPs significantly associated with HTN (p < 0.05) in the multivariate model. The unweighted GRS (uGRS) and weighted GRS (wGRS) were estimated. To validate the GRSs, the area under the curve (AUC) was explored using ten-fold internal cross-validation for uGRS (0.802) and wGRS (0.777). Further covariates of interest were added to the analyses, obtaining a higher predictive ability (AUC values of uGRS: 0.879; wGRS: 0.881 for BMI z-score). Furthermore, the differences between AUCs obtained with and without the addition of covariates were statistically significant (p < 0.05).

Conclusions

Both GRSs, the uGRS and wGRS, could be useful to evaluate the predisposition to hypertension in European adolescents.

Assessment of multi-population polygenic risk scores for lipid traits in African Americans

Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRS_LDL-Cwas nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available.

Investigation of heteroscedasticity in polygenic risk scores across 15 quantitative traits

The polygenic risk score (PRS) could be used to stratify individuals with high risk of diseases and predict complex trait of individual in a population. Previous studies developed a PRS-based prediction model using linear regression and evaluated the predictive performance of the model using the R ² value. One of the key assumptions of linear regression is that the variance of the residual should be constant at each level of the predictor variables, called homoscedasticity. However, some studies show that PRS models exhibit heteroscedasticity between PRS and traits. This study analyzes whether heteroscedasticity exists in PRS models of diverse disease-related traits and, if any, it affects the accuracy of PRS-based prediction in 354,761 Europeans from the UK Biobank. We constructed PRSs for 15 quantitative traits using LDpred2 and estimated the existence of heteroscedasticity between PRSs and 15 traits using three different tests of the Breusch-Pagan (BP) test, score test, and F test. Thirteen out of fifteen traits show significant heteroscedasticity. Further replication using new PRSs from the PGS catalog and independent samples (N = 23,620) from the UK Biobank confirmed the heteroscedasticity in ten traits. As a result, ten out of fifteen quantitative traits show statistically significant heteroscedasticity between the PRS and each trait. There was a greater variance of residuals as PRS increased, and the prediction accuracy at each level of PRS tended to decrease as the variance of residuals increased. In conclusion, heteroscedasticity was frequently observed in the PRS-based prediction models of quantitative traits, and the accuracy of the predictive model may differ according to PRS values. Therefore, prediction models using the PRS should be constructed by considering heteroscedasticity.

Fetal Bradycardia Caused by Monogenic Disorders-A Review of the Literature

Introduction: The standard obstetric definition of fetal bradycardia is a sustained fetal heart rate < 110 bpm over at least 10 min. Fetal bradycardia can be the first and only prenatal presentation of a heart disease. We present an overview on different genetic disorders that should be taken into consideration in case of diagnosed fetal bradycardia. Methods: A literature review was conducted using a PubMed- and OMIM-based search for monogenetic disorders causing fetal bradycardia in September 2022. Results: The review on the literature identified nine monogenic diseases that could lead to fetal bradycardia. Four of these disorders can be associated with extracardiac findings. Discussion: Genetic testing should be considered in cases with fetal bradycardia, especially in cases of additional extracardiac findings. Broad sequencing techniques and improved prenatal phenotyping could help to establish a diagnosis in an increasing number of cases.

Study of the Combined Effect of Maternal Tobacco Smoking and Polygenic Risk Scores on Birth Weight and Body Mass Index in Childhood

Background: Maternal smoking during pregnancy has adverse health effects on the offspring, including lower birth weight and increased risk for obesity. These outcomes are also influenced by common genetic polymorphisms. We aimed to investigate the combined effect of maternal smoking during pregnancy and genetic predisposition on birth weight and body mass index (BMI)-related traits in 1,086 children of the Human Early Life Exposome (HELIX) project.

Methods: Maternal smoking during pregnancy was self-reported. Phenotypic traits were assessed at birth or at the age of 8 years. Ten polygenic risk scores (PRSs) per trait were calculated using the PRSice v2 program. For birth weight, we estimated two sets of PRSs based on two different base GWAS summary statistics: PRS-EGG, which includes HELIX children, and PRS-PanUK, which is completely independent. The best PRS per trait (highest R2) was selected for downstream analyses, and it was treated in continuous or categorized into three groups. Multivariate linear regression models were applied to evaluate the association of the explanatory variables with the traits of interest. The combined effect was evaluated by including an interaction term in the regression models and then running models stratified by the PRS group.

Results: BMI-related traits were correlated among them but not with birth weight. A similar pattern was observed for their PRSs. On average, the PRSs explained ∼4% of the phenotypic variation, with higher PRS values related to higher trait values (p-value &lt;5.55E-08). Sustained maternal smoking was associated with lower birth weight and higher BMI and related traits (p-value &lt;2.99E-02). We identified a gene by environment (GxE) interaction for birth weight between sustained maternal smoking and the PRS-EGG in three groups (p-value interaction = 0.01), which was not replicated with the PRS-PanUK (p-value interaction = 0.341). Finally, we did not find any statistically significant GxE interaction for BMI-related traits (p-value interaction &gt;0.237).

Conclusion: Sustained maternal smoking and the PRSs were independently associated with birth weight and childhood BMI-related traits. There was low evidence of GxE interactions.

GeNuIne (gene-nutrient interactions) Collaboration: towards implementing multi-ethnic population-based nutrigenetic studies of vitamin B12 and D deficiencies and metabolic diseases

Gene-nutrient interactions (GeNuIne) collaboration, a large-scale collaborative project, has been initiated to investigate the impact of gene-nutrient interactions on cardiometabolic diseases using population-based studies from ethnically diverse populations. In this project, the relationship between deficiencies of vitamins B12 and D, and metabolic diseases was explored using a nutrigenetic approach. A genetic risk score (GRS) analysis was used to examine the combined effect of several genetic variations that have been shown to be associated with metabolic diseases and vitamin B12 and D deficiencies, respectively. In Sri Lankan, Indonesian and Brazilian populations, those carrying a high B12-GRS had an increased risk of metabolic diseases under the influence of dietary protein, fibre and carbohydrate intakes, respectively; however, in Asian Indians, genetically instrumented metabolic disease risk showed a significant association with low vitamin B12 status. With regards to nutrigenetic studies on vitamin D status, although high metabolic-GRS showed an interaction with dietary carbohydrate intake on vitamin D status, the study in Indonesian women demonstrated a vitamin D GRS-carbohydrate interaction on body fat percentage. In summary, these nutrigenetic studies from multiple ethnic groups have provided evidence for the influence of the dietary factors on the relationship between vitamin B12/D deficiency and metabolic outcomes. Furthermore, these studies highlight the existence of genetic heterogeneity in gene-diet interactions across ethnically diverse populations, which further implicates the significance of personalised dietary approaches for the prevention of these micronutrient deficiencies and metabolic diseases.

Polygenic scores for dyslipidemia: the emerging genomic model of plasma lipoprotein trait inheritance

PURPOSE OF REVIEW

Contemporary polygenic scores, which summarize the cumulative contribution of millions of common single-nucleotide variants to a phenotypic trait, can have effects comparable to monogenic mutations. This review focuses on the emerging use of 'genome-wide' polygenic scores for plasma lipoproteins to define the etiology of clinical dyslipidemia, modify the severity of monogenic disease, and inform therapeutic options.

RECENT FINDINGS

Polygenic scores for low-density lipoprotein cholesterol (LDL-C), triglycerides, and high-density lipoprotein cholesterol are associated with severe hypercholesterolemia, hypertriglyceridemia, or hypoalphalipoproteinemia, respectively. These polygenic scores for LDL-C or triglycerides associate with risk of incident coronary artery disease (CAD) independent of polygenic scores designed specifically for CAD and may identify individuals that benefit most from lipid-lowering medication. Additionally, the severity of hypercholesterolemia and CAD associated with familial hypercholesterolemia-a common monogenic disorder-is modified by these polygenic factors. The current focus of polygenic scores for dyslipidemia is to design predictive polygenic scores for diverse populations and determining how these polygenic scores could be implemented and standardized for use in the clinic.

SUMMARY

Polygenic scores have shown early promise for the management of dyslipidemias, but several challenges need to be addressed before widespread clinical implementation to ensure that potential benefits are robust and reproducible, equitable, and cost-effective.