Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

A meta-analysis and polygenic score study identifies novel genetic markers for waist-hip ratio in African populations

OBJECTIVE

Understanding the genetic underpinnings of anthropometric traits in diverse populations is crucial for gaining insights into their biological mechanisms and potential implications for health.

METHODS

We conducted a genome-wide association study, meta-analysis, and gene set analysis of waist-hip ratio (WHR), WHR adjusted for BMI (WHRadjBMI), waist circumference, BMI, and height using the African Collaborative Center for Microbiome and Genomics Research (ACCME) cohort (n = ~11,000) for discovery and polygenic score target analyses and the Africa America Diabetes Mellitus (AADM) study (n = ~5200) for replication and polygenic score validation. We generated and compared polygenic scores from European, African, Afro-Caribbean, and multiethnic ancestry populations.

RESULTS

The top loci associated with each trait in the meta-analysis were in CD36 (rs3211826 [p = 5.90 × 10-12] for WHR and rs73709003 [p = 1.75 × 10-13] for WHRadjBMI), IFI27L1 (rs59775050 [p = 2.66 × 10-08] for waist circumference), INPP4B (rs2636629 [p = 1.44 × 10-09] for BMI), and HMGA1 (rs6937622 [p = 1.40 × 10-15] for height) gene regions. A novel variant rs7797157, near GNAT3, was also significantly associated with WHR (p = 2.50 × 10-10) and WHRadjBMI (p = 2.66 × 10-11). The ancestry-specific parameters for the best predictive polygenic scores were European ancestry (R2 = 0.68%; p = 1.63 × 10-16) and multiethnic ancestry (R2 = 0.06%; p = 1.29 × 10-02) for WHR; European ancestry (R2 = 1.36%; p = 2.94 × 10-31) and multiethnic ancestry (R2 = 1.12%; p = 3.52 × 10-25) for BMI; and European ancestry (R2 = 3.16%; p = 2.95 × 10-73), African ancestry (R2 = 4.16%; p = 1.75 × 10-96), and African and Afro-Caribbean ancestry (R2 = 2.67%; p = 4.35 × 10-62) for height.

CONCLUSIONS

The discovery of a novel locus for WHR and genetic signals for each trait and the assessment of polygenic score performance underscore the importance of conducting well-powered studies in diverse populations.

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.

Association of ZBTB38 gene polymorphism (rs724016) with height and fetal hemoglobin in individuals with sickle cell anemia

Objectives

Our study evaluated the association of the polymorphism rs724016 in the ZBTB38 gene, previously associated with height in other populations, with predictors of height, clinical outcomes, and laboratory parameters in sickle cell anemia (SCA).

Methods

Cross-sectional study with individuals with SCA and aged between 3 and 20 years. Clinical, laboratory, molecular, and bone age (BA) data were evaluated. Levels of IGF-1 and IGFBP-3 were adjusted for BA, target height (TH) was calculated as the mean parental height standard deviation score (SDS), and predicted adult height (PAH) SDS was calculated using BA.

Results

We evaluated 80 individuals with SCA. The homozygous genotype of the G allele of rs724016 was associated with a lower height SDS (p < 0.001) and, in a additive genetic model, was negatively associated with HbF levels (p = 0.016). Lower adjusted IGF-1 levels were associated with co-inheritance of alpha-thalassemia and with the absence of HU therapy. Elevated HbF levels were associated with a lower deficit in adjusted growth potential (TH minus PAH).

Conclusion

Our analysis shows that SNP rs724016 in the ZBTB38 is associated with shorter height and lower HbF levels, an important modifier of SCA.

Longitudinal analysis of epigenome-wide DNA methylation reveals novel loci associated with BMI change in East Asians

BACKGROUND

Obesity is a global public health concern linked to chronic diseases such as cardiovascular disease and type 2 diabetes (T2D). Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may contribute to obesity. However, the molecular mechanism underlying the longitudinal change of BMI has not been well-explored, especially in East Asian populations.

METHODS

This study performed a longitudinal epigenome-wide association analysis of DNA methylation to uncover novel loci associated with BMI change in 533 individuals across two Chinese cohorts with repeated DNA methylation and BMI measurements over four years.

RESULTS

We identified three novel CpG sites (cg14671384, cg25540824, and cg10848724) significantly associated with BMI change. Two of the identified CpG sites were located in regions previously associated with body shape and basal metabolic rate. Annotation of the top 20 BMI change-associated CpGs revealed strong connections to obesity and T2D. Notably, these CpGs exhibited active regulatory roles and located in genes with high expression in the liver and digestive tract, suggesting a potential regulatory pathway from genome to phenotypes of energy metabolism and absorption via DNA methylation. Cross-sectional and longitudinal EWAS comparisons indicated different mechanisms between CpGs related to BMI and BMI change.

CONCLUSION

This study enhances our understanding of the epigenetic dynamics underlying BMI change and emphasizes the value of longitudinal analyses in deciphering the complex interplay between epigenetics and obesity.

The association between DNA methylation and human height and a prospective model of DNA methylation-based height prediction

As a vital anthropometric characteristic, human height information not only helps to understand overall developmental status and genetic risk factors, but is also important for forensic DNA phenotyping. We utilized linear regression analysis to test the association between each CpG probe and the height phenotype. Next, we designed a methylation sequencing panel targeting 959 CpGs and subsequent height inference models were constructed for the Chinese population. A total of 11,730 height-associated sites were identified. By employing KPCA and deep neural networks, a prediction model was developed, of which the cross-validation RMSE, MAE and R2 were 5.62 cm, 4.45 cm and 0.64, respectively. Genetic factors could explain 39.4% of the methylation level variance of sites used in the height inference models. Collectively, we demonstrated an association between height and DNA methylation status through an EWAS analysis. Targeted methylation sequencing of only 959 CpGs combined with deep learning techniques could provide a model to estimate human height with higher accuracy than SNP-based prediction models.

Evaluation of genetic variants related to lipid levels among the North Indian population

Background: A heavy burden of cardiometabolic conditions on low- and middle-income countries like India that are rapidly undergoing urbanization remains unaddressed. Indians are known to have high levels of triglycerides and low levels of HDL-C along with moderately higher levels of LDL-C. The genome-wide findings from Western populations need to be validated in an Indian context for a better understanding of the underlying etiology of dyslipidemia in India. Objective: We aim to validate 12 genetic variants associated with lipid levels among rural and urban Indian populations and derive unweighted and weighted genetic risk scores (uGRS and wGRS) for lipid levels among the Indian population. Methods: Assuming an additive model of inheritance, linear regression models adjusted for all the possible covariates were run to examine the association between 12 genetic variants and total cholesterol, triglycerides, HDL-C, LDL-C, and VLDL-C among 2,117 rural and urban Indian participants. The combined effect of validated loci was estimated by allelic risk scores, unweighted and weighted by their effect sizes. Results: The wGRS for triglycerides and VLDL-C was derived based on five associated variants (rs174546 at FADS1, rs17482753 at LPL, rs2293889 at TRPS1, rs4148005 at ABCA8, and rs4420638 at APOC1), which was associated with 36.31 mg/dL of elevated triglyceride and VLDL-C levels (β = 0.95, SE = 0.16, p < 0.001). Similarly, every unit of combined risk score (rs2293889 at TRPS1 and rs4147536 at ADH1B) was associated with 40.62 mg/dL of higher total cholesterol (β = 1.01, SE = 0.23, p < 0.001) and 33.97 mg/dL of higher LDL-C (β = 1.03, SE = 0.19, p < 0.001) based on its wGRS (rs2293889 at TRPS1, rs4147536 at ADH1B, rs4420638 at APOC1, and rs660240 at CELSR2). The wGRS derived from five associated variants (rs174546 at FADS1, rs17482753 at LPL, rs4148005 at ABCA8, rs4420638 at APOC1, and rs7832643 at PLEC) was associated with 10.64 mg/dL of lower HDL-C (β = -0.87, SE = 0.14, p < 0.001). Conclusion: We confirm the role of eight genome-wide association study (GWAS) loci related to different lipid levels in the Indian population and demonstrate the combined effect of variants for lipid traits among Indians by deriving the polygenic risk scores. Similar studies among different populations are required to validate the GWAS loci and effect modification of these loci by lifestyle and environmental factors related to urbanization.

Genetic architecture of adiposity measures among Asians: Findings from GWAS

Adiposity has gradually become a global public threat over the years with drastic increase in the attributable deaths and disability adjusted life years (DALYs). Given an increased metabolic risk among Asians as compared to Europeans for any given body mass index (BMI) and considering the differences in genetic architecture between them, the present review aims to summarize the findings from genome-wide scans for various adiposity indices and related anthropometric measures from Asian populations. The search for related studies, published till February 2022, were made on PubMed and GWAS Catalog using search strategy built with relevant keywords joined by Boolean operators. It was recorded that out of a total of 47 identified studies, maximum studies are from Korean population (n = 14), followed by Chinese (n = 7), and Japanese (n = 6). Nearly 200 loci have been identified for BMI, 660 for height, 16 for weight, 28 for circumferences (waist and hip), 32 for ratios (waist hip ratio [WHR] and thoracic hip ratio [THR]), 5 for body fat, 16 for obesity, and 28 for adiposity-related blood markers among Asians. It was observed that though, most of the loci were unique for each trait, there were 3 loci in common to BMI and WHR. Apart from validation of variants identified in European setting, there were many novel loci discovered in Asian populations. Notably, 125 novel loci form Asian studies have been reported for BMI, 47 for height, 5 for waist circumference, and 2 for adiponectin level to the existing knowledge of the genetic framework of adiposity and related measures. It is necessary to examine more advanced adiposity measures, specifically of relevance to abdominal adiposity, a major risk factor for cardiometabolic disorders among Asians. Moreover, in spite of being one continent, there is diversity among different ethnicities across Asia in terms of lifestyle, climate, geography, genetic structure and consequently the phenotypic manifestations. Hence, it is also important to consider ethnic specific studies for identifying and validating reliable genetic variants of adiposity measures among Asians.

Tensin-3 is involved in osteogenic versus adipogenic fate of human bone marrow stromal cells

BACKGROUND

The tightly controlled balance between osteogenic and adipogenic differentiation of human bone marrow-derived stromal cells (BMSCs) is critical to maintain bone homeostasis. Age-related osteoporosis is characterized by low bone mass with excessive infiltration of adipose tissue in the bone marrow compartment. The shift of BMSC differentiation from osteoblasts to adipocytes could result in bone loss and adiposity.

METHODS

TNS3 gene expression during osteogenic and adipogenic differentiation of BMSCs was evaluated by qPCR and Western blot analyses. Lentiviral-mediated knockdown or overexpression of TNS3 was used to assess its function. The organization of cytoskeleton was examined by immunofluorescent staining at multiple time points. The role of TNS3 and its domain function in osteogenic differentiation were evaluated by ALP activity, calcium assay, and Alizarin Red S staining. The expression of Rho-GTP was determined using the RhoA pull-down activation assay.

RESULTS

Loss of TNS3 impaired osteogenic differentiation of BMSCs but promoted adipogenic differentiation. Conversely, TNS3 overexpression hampered adipogenesis while enhancing osteogenesis. The expression level of TNS3 determined cell shape and cytoskeletal reorganization during osteogenic differentiation. TNS3 truncation experiments revealed that for optimal osteogenesis to occur, all domains proved essential. Pull-down and immunocytochemical experiments suggested that TNS3 mediates osteogenic differentiation through RhoA.

CONCLUSIONS

Here, we identify TNS3 to be involved in BMSC fate decision. Our study links the domain structure in TNS3 to RhoA activity via actin dynamics and implicates an important role for TNS3 in regulating osteogenesis and adipogenesis from BMSCs. Furthermore, it supports the critical involvement of cytoskeletal reorganization in BMSC differentiation.

Alternative Splicing, RNA Editing, and the Current Limits of Next Generation Sequencing

The advent of next generation sequencing (NGS) has fostered a shift in basic analytic strategies of a gene expression analysis in diverse pathologies for the purposes of research, pharmacology, and personalized medicine. What was once highly focused research on individual signaling pathways or pathway members has, from the time of gene expression arrays, become a global analysis of gene expression that has aided in identifying novel pathway interactions, the discovery of new therapeutic targets, and the establishment of disease-associated profiles for assessing progression, stratification, or a therapeutic response. But there are significant caveats to this analysis that do not allow for the construction of the full picture. The lack of timely updates to publicly available databases and the "hit and miss" deposition of scientific data to these databases relegate a large amount of potentially important data to "garbage", begging the question, "how much are we really missing?" This brief perspective aims to highlight some of the limitations that RNA binding/modifying proteins and RNA processing impose on our current usage of NGS technologies as relating to cancer and how not fully appreciating the limitations of current NGS technology may negatively affect therapeutic strategies in the long run.

Multi-ethnic imputation system (MI-System): a genotype imputation server for high-dimensional data

OBJECTIVE

Genotype imputation is a commonly used technique that infers un-typed variants into a study's genotype data, allowing better identification of causal variants in disease studies. However, due to overrepresentation of Caucasian studies, there's a lack of understanding of genetic basis of health-outcomes in other ethnic populations. Therefore, facilitating imputation of missing key-predictor-variants that can potentially improve a risk health-outcome prediction model, specifically for Asian ancestry, is of utmost relevance.

METHODS

We aimed to construct an imputation and analysis web-platform, that primarily facilitates, but is not limited to, genotype imputation on East-Asians. The goal is to provide a collaborative imputation platform for researchers in the public domain, towards rapidly and efficiently conducting accurate genotype imputation.

RESULTS

We present an online genotype imputation platform, Multi-ethnic Imputation System (MI-System) (https://misystem.cgm.ntu.edu.tw/), that offers users 3 established pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1 for conducting imputation analyses. In addition to 1000 Genomes and Hapmap3, a new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. MI-System further offers functions to create customized reference panels to be used for imputation, conduct quality control, split whole genome data into chromosomes, and convert genome builds.

CONCLUSION

Users can upload their genotype data and perform imputation with minimum effort and resources. The utility functions further can be utilized to preprocess user uploaded data with easy clicks. MI-System potentially contributes to Asian-population genetics research, while eliminating the requirement for high performing computational resources and bioinformatics expertise. It will enable an increased pace of research and provide a knowledge-base for genetic carriers of complex diseases, therefore greatly enhancing patient-driven research.

STATEMENT OF SIGNIFICANCE

Multi-ethnic Imputation System (MI-System), primarily facilitates, but is not limited to, imputation on East-Asians, through 3 established prephasing-imputation pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1, where users can upload their genotype data and perform imputation and other utility functions with minimum effort and resources. A new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. Utility functions include (a) create customized reference panels, (b) conduct quality control, (c) split whole genome data into chromosomes, and (d) convert genome builds. Users can also combine 2 reference panels using the system and use combined panels as reference to conduct imputation using MI-System.

Human height: a model common complex trait

CONTEXT

Like other complex phenotypes, human height reflects a combination of environmental and genetic factors, but is notable for being exceptionally easy to measure. Height has therefore been commonly used to make observations later generalised to other phenotypes though the appropriateness of such generalisations is not always considered.

OBJECTIVES

We aimed to assess height's suitability as a model for other complex phenotypes and review recent advances in height genetics with regard to their implications for complex phenotypes more broadly.

METHODS

We conducted a comprehensive literature search in PubMed and Google Scholar for articles relevant to the genetics of height and its comparatibility to other phenotypes.

RESULTS

Height is broadly similar to other phenotypes apart from its high heritability and ease of measurment. Recent genome-wide association studies (GWAS) have identified over 12,000 independent signals associated with height and saturated height's common single nucleotide polymorphism based heritability of height within a subset of the genome in individuals similar to European reference populations.

CONCLUSIONS

Given the similarity of height to other complex traits, the saturation of GWAS's ability to discover additional height-associated variants signals potential limitations to the omnigenic model of complex-phenotype inheritance, indicating the likely future power of polygenic scores and risk scores, and highlights the increasing need for large-scale variant-to-gene mapping efforts.

A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program

BACKGROUND

Height has been associated with many clinical traits but whether such associations are causal versus secondary to confounding remains unclear in many cases. To systematically examine this question, we performed a Mendelian Randomization-Phenome-wide association study (MR-PheWAS) using clinical and genetic data from a national healthcare system biobank.

METHODS AND FINDINGS

Analyses were performed using data from the US Veterans Affairs (VA) Million Veteran Program in non-Hispanic White (EA, n = 222,300) and non-Hispanic Black (AA, n = 58,151) adults in the US. We estimated height genetic risk based on 3290 height-associated variants from a recent European-ancestry genome-wide meta-analysis. We compared associations of measured and genetically-predicted height with phenome-wide traits derived from the VA electronic health record, adjusting for age, sex, and genetic principal components. We found 345 clinical traits associated with measured height in EA and an additional 17 in AA. Of these, 127 were associated with genetically-predicted height at phenome-wide significance in EA and 2 in AA. These associations were largely independent from body mass index. We confirmed several previously described MR associations between height and cardiovascular disease traits such as hypertension, hyperlipidemia, coronary heart disease (CHD), and atrial fibrillation, and further uncovered MR associations with venous circulatory disorders and peripheral neuropathy in the presence and absence of diabetes. As a number of traits associated with genetically-predicted height frequently co-occur with CHD, we evaluated effect modification by CHD status of genetically-predicted height associations with risk factors for and complications of CHD. We found modification of effects of MR associations by CHD status for atrial fibrillation/flutter but not for hypertension, hyperlipidemia, or venous circulatory disorders.

CONCLUSIONS

We conclude that height may be an unrecognized but biologically plausible risk factor for several common conditions in adults. However, more studies are needed to reliably exclude horizontal pleiotropy as a driving force behind at least some of the MR associations observed in this study.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

Advances in integrative African genomics

There has been a rapid increase in human genome sequencing in the past two decades, resulting in the identification of millions of previously unknown genetic variants. However, African populations are under-represented in sequencing efforts. Additional sequencing from diverse African populations and the construction of African-specific reference genomes is needed to better characterize the full spectrum of variation in humans. However, sequencing alone is insufficient to address the molecular and cellular mechanisms underlying variable phenotypes and disease risks. Determining functional consequences of genetic variation using multi-omics approaches is a fundamental post-genomic challenge. We discuss approaches to close the knowledge gaps about African genomic diversity and review advances in African integrative genomic studies and their implications for precision medicine.

Genome-wide association study identifies genetic risk loci for adiposity in a Taiwanese population

Overweight and obese are risk factors for various diseases. In Taiwan, the combined prevalence of overweight and obesity has increased dramatically. Here, we conducted a genome-wide association study (GWAS) on four adiposity traits, including body-mass index (BMI), body fat percentage (BF%), waist circumference (WC), and waist-hip ratio (WHR), using the data for more than 21,000 subjects in Taiwan Biobank. Associations were evaluated between 6,546,460 single-nucleotide polymorphisms (SNPs) and adiposity traits, yielding 13 genome-wide significant (GWS) adiposity-associated trait-loci pairs. A known gene, FTO, as well as two BF%-associated loci (GNPDA2-GABRG1 [4p12] and RNU6-2-PIAS1 [15q23]) were identified as pleiotropic effects. Moreover, RALGAPA1 was found as a specific genetic predisposing factor to high BMI in a Taiwanese population. Compared to other populations, a slightly lower heritability of the four adiposity traits was found in our cohort. Surprisingly, we uncovered the importance of neural pathways that might influence BF%, WC and WHR in the Taiwanese (East Asian) population. Additionally, a moderate genetic correlation between the WHR and BMI (γg = 0.52; p = 2.37×10−9) was detected, suggesting different genetic determinants exist for abdominal adiposity and overall adiposity. In conclusion, the obesity-related genetic loci identified here provide new insights into the genetic underpinnings of adiposity in the Taiwanese population.

A Genetic Map of the Modern Urban Society of Amsterdam

Genetic differences between individuals underlie susceptibility to many diseases. Genome-wide association studies (GWAS) have discovered many susceptibility genes but were often limited to cohorts of predominantly European ancestry. Genetic diversity between individuals due to different ancestries and evolutionary histories shows that this approach has limitations. In order to gain a better understanding of the associated genetic variation, we need a more global genomics approach including a greater diversity. Here, we introduce the Healthy Life in an Urban Setting (HELIUS) cohort. The HELIUS cohort consists of participants living in Amsterdam, with a level of diversity that reflects the Dutch colonial and recent migration past. The current study includes 10,283 participants with genetic data available from seven groups of inhabitants, namely, Dutch, African Surinamese, South-Asian Surinamese, Turkish, Moroccan, Ghanaian, and Javanese Surinamese. First, we describe the genetic variation and admixture within the HELIUS cohort. Second, we show the challenges during imputation when having a genetically diverse cohort. Third, we conduct a body mass index (BMI) and height GWAS where we investigate the effects of a joint analysis of the entire cohort and a meta-analysis approach for the different subgroups. Finally, we construct polygenic scores for BMI and height and compare their predictive power across the different ethnic groups. Overall, we give a comprehensive overview of a genetically diverse cohort from Amsterdam. Our study emphasizes the importance of a less biased and more realistic representation of urban populations for mapping genetic associations with complex traits and disease risk for all.

Protein-coding repeat polymorphisms strongly shape diverse human phenotypes

Many human proteins contain domains that vary in size or copy number because of variable numbers of tandem repeats (VNTRs) in protein-coding exons. However, the relationships of VNTRs to most phenotypes are unknown because of difficulties in measuring such repetitive elements. We developed methods to estimate VNTR lengths from whole-exome sequencing data and impute VNTR alleles into single-nucleotide polymorphism haplotypes. Analyzing 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 786 phenotypes identified some of the strongest associations of common variants with human phenotypes, including height, hair morphology, and biomarkers of health. Accounting for large-effect VNTRs further enabled fine-mapping of associations to many more protein-coding mutations in the same genes. These results point to cryptic effects of highly polymorphic common structural variants that have eluded molecular analyses to date.

Association Analysis of Candidate Variants in Admixed Brazilian Patients With Genetic Generalized Epilepsies

Genetic generalized epilepsies (GGEs) include well-established epilepsy syndromes with generalized onset seizures: childhood absence epilepsy, juvenile myoclonic epilepsy (JME), juvenile absence epilepsy (JAE), myoclonic absence epilepsy, epilepsy with eyelid myoclonia (Jeavons syndrome), generalized tonic–clonic seizures, and generalized tonic–clonic seizures alone. Genome-wide association studies (GWASs) and exome sequencing have identified 48 single-nucleotide polymorphisms (SNPs) associated with GGE. However, these studies were mainly based on non-admixed, European, and Asian populations. Thus, it remains unclear whether these results apply to patients of other origins. This study aims to evaluate whether these previous results could be replicated in a cohort of admixed Brazilian patients with GGE. We obtained SNP-array data from 87 patients with GGE, compared with 340 controls from the BIPMed public dataset. We could directly access genotypes of 17 candidate SNPs, available in the SNP array, and the remaining 31 SNPs were imputed using the BEAGLE v5.1 software. We performed an association test by logistic regression analysis, including the first five principal components as covariates. Furthermore, to expand the analysis of the candidate regions, we also interrogated 14,047 SNPs that flank the candidate SNPs (1 Mb). The statistical power was evaluated in terms of odds ratio and minor allele frequency (MAF) by the genpwr package. Differences in SNP frequencies between Brazilian and Europeans, sub-Saharan African, and Native Americans were evaluated by a two-proportion Z-test. We identified nine flanking SNPs, located on eight candidate regions, which presented association signals that passed the Bonferroni correction (rs12726617; rs9428842; rs1915992; rs1464634; rs6459526; rs2510087; rs9551042; rs9888879; and rs8133217; p-values <3.55e^–06). In addition, the two-proportion Z-test indicates that the lack of association of the remaining candidate SNPs could be due to different genomic backgrounds observed in admixed Brazilians. This is the first time that candidate SNPs for GGE are analyzed in an admixed Brazilian population, and we could successfully replicate the association signals in eight candidate regions. In addition, our results provide new insights on how we can account for population structure to improve risk stratification estimation in admixed individuals.