Hundreds of variants clustered in genomic loci and biological pathways affect human height

A review of genetic risk in systemic lupus erythematosus

INTRODUCTION

Systemic Lupus Erythematosus (SLE) is a complex multisystem autoimmune disease with a wide range of signs and symptoms in affected individuals. The utilization of genome-wide association study (GWAS) technology has led to an explosion in the number of genetic risk factors mapped for autoimmune diseases, including SLE.

AREAS COVERED

In this review, we summarize the more recent genetic risk loci mapped in SLE, which bring the total number of loci mapped to approximately 200. We review prioritization analyses of the associated variants and experimental validation of the putative causal variants. This includes the implementation of new bioinformatic techniques to align genomic and functional data and the use of transcriptomics with single-cell RNA-sequencing, CRISPR genome editing, and Massive Parallel Reporter Assays to analyze non-coding regulatory genetics.

EXPERT OPINION

Despite progress in identifying more genetic risk loci and variant-gene pairs for SLE, understanding its pathogenesis and applying findings clinically remains challenging. The polygenic risk score (PRS) has been used as an application of SLE genetics, but with limited performance in non-EUR populations. In the next few years, advancements in proteomics, post-translational modification estimation, and whole-genome sequencing will enhance disease understanding.

Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle

Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.

The Stanniocalcin-PAPP-A-IGFBP-IGF Axis

The pappalysin metalloproteinases, PAPP-A and PAPP-A2, have emerged as highly specific proteolytic enzymes involved in the regulation of insulin-like growth factor (IGF) signaling. The only known pappalysin substrates are a subset of the IGF binding proteins (IGFBPs), which bind IGF-I or IGF-II with high affinity to antagonize receptor binding. Thus, by cleaving IGFBPs, the pappalysins have the potential to increase IGF bioactivity and hence promote IGF signaling. This is relevant both in systemic and local IGF regulation, in normal and several pathophysiological conditions. Stanniocalcin-1 and -2 were recently found to be potent pappalysin inhibitors, thus comprising the missing components of a complete proteolytic system, the stanniocalcin-PAPP-A-IGFBP-IGF axis. Here, we provide the biological context necessary for understanding the properties of this molecular network, and we review biochemical data, animal experiments, clinical data, and genetic data supporting the physiological operation of this branch as an important part of the IGF system. However, although in vivo data clearly illustrate its power, it is a challenge to understand its subtle operation, for example, multiple equilibria and inhibitory kinetics may determine how, where, and when the IGF receptor is stimulated. In addition, literally all of the regulatory proteins have suspected or known activities that are not directly related to IGF signaling. How such activities may integrate with IGF signaling is also important to address in the future.

Genetics of skeletal proportions in two different populations

Human height can be divided into sitting height and leg length, reflecting growth of different parts of the skeleton whose relative proportions are captured by the ratio of sitting to total height (as sitting height ratio, SHR). Height is a highly heritable trait, and its genetic basis has been well-studied. However, the genetic determinants of skeletal proportion are much less well-characterized. Expanding substantially on past work, we performed a genome-wide association study (GWAS) of SHR in ∼450,000 individuals with European ancestry and ∼100,000 individuals with East Asian ancestry from the UK and China Kadoorie Biobanks. We identified 565 loci independently associated with SHR, including all genomic regions implicated in prior GWAS in these ancestries. While SHR loci largely overlap height-associated loci (P < 0.001), the fine-mapped SHR signals were often distinct from height. We additionally used fine-mapped signals to identify 36 credible sets with heterogeneous effects across ancestries. Lastly, we used SHR, sitting height, and leg length to identify genetic variation acting on specific body regions rather than on overall human height.

Genome-wide CRISPR screening of chondrocyte maturation newly implicates genes in skeletal growth and height-associated GWAS loci

Alterations in the growth and maturation of chondrocytes can lead to variation in human height, including monogenic disorders of skeletal growth. We aimed to identify genes and pathways relevant to human growth by pairing human height genome-wide association studies (GWASs) with genome-wide knockout (KO) screens of growth-plate chondrocyte proliferation and maturation in vitro. We identified 145 genes that alter chondrocyte proliferation and maturation at early and/or late time points in culture, with 90% of genes validating in secondary screening. These genes are enriched in monogenic growth disorder genes and in KEGG pathways critical for skeletal growth and endochondral ossification. Further, common variants near these genes capture height heritability independent of genes computationally prioritized from GWASs. Our study emphasizes the value of functional studies in biologically relevant tissues as orthogonal datasets to refine likely causal genes from GWASs and implicates new genetic regulators of chondrocyte proliferation and maturation.

Global dispersal and adaptive evolution of domestic cattle: a genomic perspective

Domestic cattle have spread across the globe and inhabit variable and unpredictable environments. They have been exposed to a plethora of selective pressures and have adapted to a variety of local ecological and management conditions, including UV exposure, diseases, and stall-feeding systems. These selective pressures have resulted in unique and important phenotypic and genetic differences among modern cattle breeds/populations. Ongoing efforts to sequence the genomes of local and commercial cattle breeds/populations, along with the growing availability of ancient bovid DNA data, have significantly advanced our understanding of the genomic architecture, recent evolution of complex traits, common diseases, and local adaptation in cattle. Here, we review the origin and spread of domestic cattle and illustrate the environmental adaptations of local cattle breeds/populations.

Genetic dysregulation of an endothelial Ras signaling network in vein of Galen malformations

To elucidate the pathogenesis of vein of Galen malformations (VOGMs), the most common and severe congenital brain arteriovenous malformation, we performed an integrated analysis of 310 VOGM proband-family exomes and 336,326 human cerebrovasculature single-cell transcriptomes. We found the Ras suppressor p120 RasGAP ( RASA1 ) harbored a genome-wide significant burden of loss-of-function de novo variants (p=4.79×10 ^-7 ). Rare, damaging transmitted variants were enriched in Ephrin receptor-B4 ( EPHB4 ) (p=1.22×10 ^-5 ), which cooperates with p120 RasGAP to limit Ras activation. Other probands had pathogenic variants in ACVRL1 , NOTCH1 , ITGB1 , and PTPN11 . ACVRL1 variants were also identified in a multi-generational VOGM pedigree. Integrative genomics defined developing endothelial cells as a key spatio-temporal locus of VOGM pathophysiology. Mice expressing a VOGM-specific EPHB4 kinase-domain missense variant exhibited constitutive endothelial Ras/ERK/MAPK activation and impaired hierarchical development of angiogenesis-regulated arterial-capillary-venous networks, but only when carrying a "second-hit" allele. These results illuminate human arterio-venous development and VOGM pathobiology and have clinical implications.

Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation

We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.

Multiomic analyses implicate a neurodevelopmental program in the pathogenesis of cerebral arachnoid cysts

Cerebral arachnoid cysts (ACs) are one of the most common and poorly understood types of developmental brain lesion. To begin to elucidate AC pathogenesis, we performed an integrated analysis of 617 patient-parent (trio) exomes, 152,898 human brain and mouse meningeal single-cell RNA sequencing transcriptomes and natural language processing data of patient medical records. We found that damaging de novo variants (DNVs) were highly enriched in patients with ACs compared with healthy individuals (P = 1.57 × 10^-33). Seven genes harbored an exome-wide significant DNV burden. AC-associated genes were enriched for chromatin modifiers and converged in midgestational transcription networks essential for neural and meningeal development. Unsupervised clustering of patient phenotypes identified four AC subtypes and clinical severity correlated with the presence of a damaging DNV. These data provide insights into the coordinated regulation of brain and meningeal development and implicate epigenomic dysregulation due to DNVs in AC pathogenesis. Our results provide a preliminary indication that, in the appropriate clinical context, ACs may be considered radiographic harbingers of neurodevelopmental pathology warranting genetic testing and neurobehavioral follow-up. These data highlight the utility of a systems-level, multiomics approach to elucidate sporadic structural brain disease.

Identification and analysis of individuals who deviate from their genetically-predicted phenotype

Findings from genome-wide association studies have facilitated the generation of genetic predictors for many common human phenotypes. Stratifying individuals misaligned to a genetic predictor based on common variants may be important for follow-up studies that aim to identify alternative causal factors. Using genome-wide imputed genetic data, we aimed to classify 158,951 unrelated individuals from the UK Biobank as either concordant or deviating from two well-measured phenotypes. We first applied our methods to standing height: our primary analysis classified 244 individuals (0.15%) as misaligned to their genetically predicted height. We show that these individuals are enriched for self-reporting being shorter or taller than average at age 10, diagnosed congenital malformations, and rare loss-of-function variants in genes previously catalogued as causal for growth disorders. Secondly, we apply our methods to LDL cholesterol. We classified 156 (0.12%) individuals as misaligned to their genetically predicted LDL cholesterol and show that these individuals were enriched for both clinically actionable cardiovascular risk factors and rare genetic variants in genes previously shown to be involved in metabolic processes. Individuals whose LDL-C was higher than expected based on the genetic predictor were also at higher risk of developing coronary artery disease and type-two diabetes, even after adjustment for measured LDL-C, BMI and age, suggesting upward deviation from genetically predicted LDL-C is indicative of generally poor health. Our results remained broadly consistent when performing sensitivity analysis based on a variety of parametric and non-parametric methods to define individuals deviating from polygenic expectation. Our analyses demonstrate the potential importance of quantitatively identifying individuals for further follow-up based on deviation from genetic predictions.

Author Summary

Human genetics is becoming increasingly useful to help predict human traits across a population owing to findings from large-scale genetic association studies and advances in the power of genetic predictors. This provides an opportunity to potentially identify individuals that deviate from genetic predictions for a common phenotype under investigation. For example, an individual may be genetically predicted to be tall, but be shorter than expected. It is potentially important to identify individuals who deviate from genetic predictions as this can facilitate further follow-up to assess likely causes. Using 158,951 unrelated individuals from the UK Biobank, with height and LDL cholesterol, as exemplar traits, we demonstrate that approximately 0.15% & 0.12% of individuals deviate from their genetically predicted phenotypes respectively. We observed these individuals to be enriched for a range of rare clinical diagnoses, as well as rare genetic factors that may be causal. Our analyses also demonstrate several methods for detecting individuals who deviate from genetic predictions that can be applied to a range of continuous human phenotypes.

15 years of GWAS discovery: Realizing the promise

It has been 15 years since the advent of the genome-wide association study (GWAS) era. Here, we review how this experimental design has realized its promise by facilitating an impressive range of discoveries with remarkable impact on multiple fields, including population genetics, complex trait genetics, epidemiology, social science, and medicine. We predict that the emergence of large-scale biobanks will continue to expand to more diverse populations and capture more of the allele frequency spectrum through whole-genome sequencing, which will further improve our ability to investigate the causes and consequences of human genetic variation for complex traits and diseases.

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

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 genome-wide association study identifies distinct variants associated with pulmonary function among European and African ancestries from the UK Biobank

Pulmonary function is an indicator of well-being, and pulmonary pathologies are the third major cause of death worldwide. We analysed the UK Biobank genome-wide association summary statistics of pulmonary function for Europeans and individuals of recent African descent to identify variants associated with the trait in the two ancestries. Here, we show 627 variants in Europeans and 3 in Africans associated with three pulmonary function parameters. In addition to the 110 variants in Europeans previously reported to be associated with phenotypes related to pulmonary function, we identify 279 novel loci, including an ISX intergenic variant rs369476290 on chromosome 22 in Africans. Remarkably, we find no shared variants among Africans and Europeans. Furthermore, enrichment analyses of variants separately for each ancestry background reveal significant enrichment for terms related to pulmonary phenotypes in Europeans but not Africans. Further analysis of studies of pulmonary phenotypes reveals that individuals of European background are disproportionally overrepresented in datasets compared to Africans, with the gap widening over the past five years. Our findings extend our understanding of the different variants that modify the pulmonary function in Africans and Europeans, a promising finding for future GWASs and medical studies.

Cord blood epigenome-wide meta-analysis in six European-based child cohorts identifies signatures linked to rapid weight growth

BACKGROUND

Rapid postnatal growth may result from exposure in utero or early life to adverse conditions and has been associated with diseases later in life and, in particular, with childhood obesity. DNA methylation, interfacing early-life exposures and subsequent diseases, is a possible mechanism underlying early-life programming.

METHODS

Here, a meta-analysis of Illumina HumanMethylation 450K/EPIC-array associations of cord blood DNA methylation at single CpG sites and CpG genomic regions with rapid weight growth at 1 year of age (defined with reference to WHO growth charts) was conducted in six European-based child cohorts (ALSPAC, ENVIRONAGE, Generation XXI, INMA, Piccolipiù, and RHEA, N = 2003). The association of gestational age acceleration (calculated using the Bohlin epigenetic clock) with rapid weight growth was also explored via meta-analysis. Follow-up analyses of identified DNA methylation signals included prediction of rapid weight growth, mediation of the effect of conventional risk factors on rapid weight growth, integration with transcriptomics and metabolomics, association with overweight in childhood (between 4 and 8 years), and comparison with previous findings.

RESULTS

Forty-seven CpGs were associated with rapid weight growth at suggestive p-value <1e-05 and, among them, three CpGs (cg14459032, cg25953130 annotated to ARID5B, and cg00049440 annotated to KLF9) passed the genome-wide significance level (p-value <1.25e-07). Sixteen differentially methylated regions (DMRs) were identified as associated with rapid weight growth at false discovery rate (FDR)-adjusted/Siddak p-values < 0.01. Gestational age acceleration was associated with decreasing risk of rapid weight growth (p-value = 9.75e-04). Identified DNA methylation signals slightly increased the prediction of rapid weight growth in addition to conventional risk factors. Among the identified signals, three CpGs partially mediated the effect of gestational age on rapid weight growth. Both CpGs (N=3) and DMRs (N=3) were associated with differential expression of transcripts (N=10 and 7, respectively), including long non-coding RNAs. An AURKC DMR was associated with childhood overweight. We observed enrichment of CpGs previously reported associated with birthweight.

CONCLUSIONS

Our findings provide evidence of the association between cord blood DNA methylation and rapid weight growth and suggest links with prenatal exposures and association with childhood obesity providing opportunities for early prevention.

Abnormal lens thickening in a child with Weill-Marchesani syndrome 4: A 3-year follow-up case report

Background

Weill-Marchesani syndrome 4 (WMS4) is caused by ADAMTS17 gene variant and clinical abnormalities including lenticular myopia, ectopia lentis, glaucoma, microspherophakia, brachydactyly, and short stature. Due to free of heart defects and joint stiffness compared with other WMS forms, WMS4 has an insidious onset and is often misdiagnosed as high myopia. We combined multiple imaging biometry and whole-exome sequencing to diagnose a case of WMS4 with a 3-year follow-up.

Case presentation

An 8-year-old boy presented to our ophthalmology department with progressive myopia for 1 year. He had high myopia in both eyes with normal funds, intraocular pressure, and axial length. Ocular examination revealed thicker lenses (right 4.38 mm, left 4.31 mm) with a smaller equatorial diameter (right 7.33 mm and left 7.17 mm) compared to normal children of the same age. Finger length measurement indicates brachydactyly. Whole-exome sequencing identified compound heterozygous missense variants c.2984G > A (p.Arg995Gln) and c.2254A > G (p.Ile752Val) in the ADAMTS17 gene. During the 3 years of follow-up, the thickness of lenses increased significantly (right 4.49 mm, left 4.48 mm), but the equatorial diameter of the lenses had no significant change (right 7.32 mm, left 7.21 mm). As the equivalent lens power increased, the patient's myopia spherical refractive error rose accordingly. Although the anterior chamber angle remained open during follow-up, the intraocular pressure increased to right 20.4 mmHg and left 19.6 mmHg, Iridodonesis and short stature were present.

Conclusion

This case report highlights the abnormal thickening of the lens in WMS4 compared to the physiological thinning process during childhood. Comprehensive clinical examinations and genetic testing may improve diagnosis, which allows early therapeutic interventions for complications and better visual outcomes for the patient.

Statistical Methods for Disease Risk Prediction with Genotype Data

Single-nucleotide polymorphism (SNP) is the basic unit to understand the heritability of complex traits. One attractive application of the susceptible SNPs is to construct prediction models for assessing disease risk. Here, we introduce prediction methods for human traits using SNPs data, including the polygenic risk score (PRS), linear mixed models (LMMs), penalized regressions, and methods for controlling population stratification.

Structural insights into the covalent regulation of PAPP-A activity by proMBP and STC2

Originally discovered in the circulation of pregnant women as a protein secreted by placental trophoblasts, the metalloprotease pregnancy-associated plasma protein A (PAPP-A) is also widely expressed by many other tissues. It cleaves insulin-like growth factor-binding proteins (IGFBPs) to increase the bioavailability of IGFs and plays essential roles in multiple growth-promoting processes. While the vast majority of the circulatory PAPP-A in pregnancy is proteolytically inactive due to covalent inhibition by proform of eosinophil major basic protein (proMBP), the activity of PAPP-A can also be covalently inhibited by another less characterized modulator, stanniocalcin-2 (STC2). However, the structural basis of PAPP-A proteolysis and the mechanistic differences between these two modulators are poorly understood. Here we present two cryo-EM structures of endogenous purified PAPP-A in complex with either proMBP or STC2. Both modulators form 2:2 heterotetramer with PAPP-A and establish extensive interactions with multiple domains of PAPP-A that are distal to the catalytic cleft. This exosite-binding property results in a steric hindrance to prevent the binding and cleavage of IGFBPs, while the IGFBP linker region-derived peptides harboring the cleavage sites are no longer sensitive to the modulator treatment. Functional investigation into proMBP-mediated PAPP-A regulation in selective intrauterine growth restriction (sIUGR) pregnancy elucidates that PAPP-A and proMBP collaboratively regulate extravillous trophoblast invasion and the consequent fetal growth. Collectively, our work reveals a novel covalent exosite-competitive inhibition mechanism of PAPP-A and its regulatory effect on placental function.

A Genetic Approach in the Evaluation of Short Stature

Short stature is considered a condition in which the height is 2 standard deviations below the mean height of a given age, sex, and population group. Human height is a polygenic and heterogeneous characteristic, and its heritability is reported to be approximately 80%. More than 600 variants associated with human growth were detected in the genome-wide association studies. Rare and common variants concurrently affect human height. The rare variations that play a role in human height determination and have a strong impact on protein functions lead to monogenic short stature phenotypes, which are a highly heterogeneous group. With rapidly developing technologies in the last decade, molecular genetic tests have begun to be used widely in clinical genetics, and thus, the genetic etiology of several rare diseases has been elucidated. Identifying the genetic etiology underlying idiopathic short stature which represents phenotypically heterogeneous group of diseases ranging from isolated short stature to severe and syndromic short stature has promoted the understanding of the genetic regulation of growth plate and longitudinal bone growth. In cases of short stature, definite molecular diagnosis based on genetic evaluation enables the patient and family to receive genetic counseling on the natural course of the disease, prognosis, genetic basis, and recurrence risk. The determination of the genetic etiology in growth disorders is essential for the development of novel targeted therapies and crucial in the development of mutation-specific treatments in the future.

Stacked kinship CNN vs. GBLUP for genomic predictions of additive and complex continuous phenotypes

Deep learning is impacting many fields of data science with often spectacular results. However, its application to whole-genome predictions in plant and animal science or in human biology has been rather limited, with mostly underwhelming results. While most works focus on exploring alternative network architectures, in this study we propose an innovative representation of marker genotype data and tested it against the GBLUP (Genomic BLUP) benchmark with linear and nonlinear phenotypes. From publicly available cattle SNP genotype data, different types of genomic kinship matrices are stacked together in a 3D pile from where 2D grayscale slices are extracted and fed to a deep convolutional neural network (DNN). We simulated nine phenotype scenarios with combinations of additivity, dominance and epistasis, and compared the DNN to GBLUP-A (computed using only the additive kinship matrix) and GBLUP-optim (additive, dominance, and epistasis kinship matrices, as needed). Results varied depending on the accuracy metric employed, with DNN performing better in terms of root mean squared error (1-12% lower than GBLUP-A; 1-9% lower than GBLUP-optim) but worse in terms of Pearson's correlation (0.505 for DNN compared to 0.672 and 0.669 of GBLUP-A and GBLUP-optim for fully additive case; 0.274 for DNN, 0.279 for GBLUP-A, and 0.477 for GBLUP-optim for fully dominant case). The proposed approach offers a basis to explore further the application of DNN to tabular data in whole-genome predictions.

BICOSS: Bayesian iterative conditional stochastic search for GWAS

Background

Single marker analysis (SMA) with linear mixed models for genome wide association studies has uncovered the contribution of genetic variants to many observed phenotypes. However, SMA has weak false discovery control. In addition, when a few variants have large effect sizes, SMA has low statistical power to detect small and medium effect sizes, leading to low recall of true causal single nucleotide polymorphisms (SNPs).

Results

We present the Bayesian Iterative Conditional Stochastic Search (BICOSS) method that controls false discovery rate and increases recall of variants with small and medium effect sizes. BICOSS iterates between a screening step and a Bayesian model selection step. A simulation study shows that, when compared to SMA, BICOSS dramatically reduces false discovery rate and allows for smaller effect sizes to be discovered. Finally, two real world applications show the utility and flexibility of BICOSS.

Conclusions

When compared to widely used SMA, BICOSS provides higher recall of true SNPs while dramatically reducing false discovery rate.

Adult Height, 22q11.2 Deletion Extent, and Short Stature in 22q11.2 Deletion Syndrome

The 22q11.2 deletion syndrome (22q11.2DS) manifests as a wide range of medical conditions across a number of systems. Pediatric growth deficiency with some catch-up growth is reported, but there are few studies of final adult height. We aimed to investigate how final adult height in 22q11.2DS compared with general population norms, and to examine predictors of short stature in in a cohort of 397 adults with 22q11.2DS (aged 17.6–76.3 years) with confirmed typical 22q11.2 microdeletion (overlapping the LCR22A to LCR22B region). We defined short stature as <3rd percentile using population norms. For the subset (n = 314, 79.1%) with 22q11.2 deletion extent, we used a binomial logistic regression model to predict short stature in 22q11.2DS, accounting for effects of sex, age, ancestry, major congenital heart disease (CHD), moderate-to-severe intellectual disability (ID), and 22q11.2 deletion extent. Adult height in 22q11.2DS showed a normal distribution but with a shift to the left, compared with population norms. Those with short stature represented 22.7% of the 22q11.2DS sample, 7.6-fold greater than population expectations (p < 0.0001). In the regression model, moderate-to-severe ID, major CHD, and the common LCR22A-LCR22D (A-D) deletion were significant independent risk factors for short stature while accounting for other factors (model p = 0.0004). The results suggest that the 22q11.2 microdeletion has a significant effect on final adult height distribution, and on short stature with effects appearing to arise from reduced gene dosage involving both the proximal and distal sub-regions of the A-D region. Future studies involving larger sample sizes with proximal nested 22q11.2 deletions, longitudinal lifetime data, parental heights, and genotype data will be valuable.

Associations between forensic loci and expression levels of neighboring genes may compromise medical privacy

A set of 20 short tandem repeats (STRs) is used by the US criminal justice system to identify suspects and to maintain a database of genetic profiles for individuals who have been previously convicted or arrested. Some of these STRs were identified in the 1990s, with a preference for markers in putative gene deserts to avoid forensic profiles revealing protected medical information. We revisit that assumption, investigating whether forensic genetic profiles reveal information about gene-expression variation or potential medical information. We find six significant correlations (false discovery rate = 0.23) between the forensic STRs and the expression levels of neighboring genes in lymphoblastoid cell lines. We explore possible mechanisms for these associations, showing evidence compatible with forensic STRs causing expression variation or being in linkage disequilibrium with a causal locus in three cases and weaker or potentially spurious associations in the other three cases. Together, these results suggest that forensic genetic loci may reveal expression levels and, perhaps, medical information.

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

A Prism Vote method for individualized risk prediction of traits in genotype data of Multi-population

Multi-population cohorts offer unprecedented opportunities for profiling disease risk in large samples, however, heterogeneous risk effects underlying complex traits across populations make integrative prediction challenging. In this study, we propose a novel Bayesian probability framework, the Prism Vote (PV), to construct risk predictions in heterogeneous genetic data. The PV views the trait of an individual as a composite risk from subpopulations, in which stratum-specific predictors can be formed in data of more homogeneous genetic structure. Since each individual is described by a composition of subpopulation memberships, the framework enables individualized risk characterization. Simulations demonstrated that the PV framework applied with alternative prediction methods significantly improved prediction accuracy in mixed and admixed populations. The advantage of PV enlarges as genetic heterogeneity and sample size increase. In two real genome-wide association data consists of multiple populations, we showed that the framework considerably enhanced prediction accuracy of the linear mixed model in five-group cross validations. The proposed method offers a new aspect to analyze individual's disease risk and improve accuracy for predicting complex traits in genotype data.

Low-coverage sequencing in a deep intercross of the Virginia body weight lines provides insight to the polygenic genetic architecture of growth: novel loci revealed by increased power and improved genome-coverage

Genetic dissection of highly polygenic traits is a challenge, in part due to the power necessary to confidently identify loci with minor effects. Experimental crosses are valuable resources for mapping such traits. Traditionally, genome-wide analyses of experimental crosses have targeted major loci using data from a single generation (often the F₂) with individuals from later generations being generated for replication and fine-mapping. Here, we aim to confidently identify minor-effect loci contributing to the highly polygenic basis of the long-term, bi-directional selection responses for 56-d body weight in the Virginia body weight chicken lines. To achieve this, a strategy was developed to make use of data from all generations (F₂-F₁₈) of the advanced intercross line, developed by crossing the low and high selected lines after 40 generations of selection. A cost-efficient low-coverage sequencing based approach was used to obtain high-confidence genotypes in 1Mb bins across 99.3% of the chicken genome for >3,300 intercross individuals. In total, 12 genome-wide significant, and 30 additional suggestive QTL reaching a 10% FDR threshold, were mapped for 56-d body weight. Only 2 of these QTL reached genome-wide significance in earlier analyses of the F₂ generation. The minor-effect QTL mapped here were generally due to an overall increase in power by integrating data across generations, with contributions from increased genome-coverage and improved marker information content. The 12 significant QTL explain >37% of the difference between the parental lines, three times more than 2 previously reported significant QTL. The 42 significant and suggestive QTL together explain >80%. Making integrated use of all available samples from multiple generations in experimental crosses are economically feasible using the low-cost, sequencing-based genotyping strategies outlined here. Our empirical results illustrate the value of this strategy for mapping novel minor-effect loci contributing to complex traits to provide a more confident, comprehensive view of the individual loci that form the genetic basis of the highly polygenic, long-term selection responses for 56-d body weight in the Virginia body weight chicken lines.

Pappalysins and Stanniocalcins and Their Relationship With the Peripheral IGF Axis in Newborns and During Development

CONTEXT

Pappalysins (PAPP-A, PAPP-A2) modulate body growth by increasing insulin-like growth factor I (IGF-I) bioavailability through cleavage of insulin-like growth factor binding proteins (IGFBPs) and are inhibited by stanniocalcins (STC1, STC2). Normative data on these novel factors, as well as on free IGF-I and uncleaved fractions of IGFBPs, are not well established.

OBJECTIVE

This work aimed to determine serum concentrations of PAPP-A, PAPP-A2, STC1, and STC2 in relationship with other growth hormone (GH)-IGF axis parameters during development.

METHODS

Full-term newborns (150; gestational age: 39.30 ± 1.10 weeks), 40 preterm newborns (30.87 ± 3.35 weeks), and 1071 healthy individuals (aged 1-30 years) were included in the study and divided according to their Tanner stages (males and females): I:163 males, 154 females; II:100 males, 75 females; III:83 males, 96 females; IV: 77 males, 86 females; and V:109 males,128 females.

RESULTS

Serum concentrations of PAPP-A, PAPP-A2, STC1, STC2, IGFBP-2, total IGFBP-4, and total IGFBP-5 were elevated at birth and declined throughout childhood. In postnatal life, PAPP-A2 concentrations decreased progressively in concomitance with the free/total IGF-I ratio; however, stanniocalcin concentrations remained stable. PAPP-A2 concentrations positively correlated with the free/total IGF-I ratio (r = +0.28; P < .001) and negatively with the intact/total IGFBP-3 ratio (r = -0.23; P < .001). PAPP-A concentrations inversely correlated with intact/total IGFBP-4 ratio (r = -0.21; P < .001), with PAPP-A concentrations being lower in females at all ages. Association studies indicate the importance of stanniocalcins and pappalysins in the control of this axis in an age-specific manner.

CONCLUSION

This study provides reference values of pappalysins and stanniocalcins, which modulate IGF-I activity by changing the concentrations of cleaved and uncleaved IGFBPs.

Inframe insertion and splice site variants in MFGE8 associate with protection against coronary atherosclerosis

Cardiovascular diseases are the leading cause of premature death and disability worldwide, with both genetic and environmental determinants. While genome-wide association studies have identified multiple genetic loci associated with cardiovascular diseases, exact genes driving these associations remain mostly uncovered. Due to Finland's population history, many deleterious and high-impact variants are enriched in the Finnish population giving a possibility to find genetic associations for protein-truncating variants that likely tie the association to a gene and that would not be detected elsewhere. In a large Finnish biobank study FinnGen, we identified an association between an inframe insertion rs534125149 in MFGE8 (encoding lactadherin) and protection against coronary atherosclerosis. This variant is highly enriched in Finland, and the protective association was replicated in meta-analysis of BioBank Japan and Estonian biobank. Additionally, we identified a protective association between splice acceptor variant rs201988637 in MFGE8 and coronary atherosclerosis, independent of the rs534125149, with no significant risk-increasing associations. This variant was also associated with lower pulse pressure, pointing towards a function of MFGE8 in arterial aging also in humans in addition to previous evidence in mice. In conclusion, our results suggest that inhibiting the production of lactadherin could lower the risk for coronary heart disease substantially.

Your height affects your health: genetic determinants and health-related outcomes in Taiwan

BACKGROUND

Height is an important anthropometric measurement and is associated with many health-related outcomes. Genome-wide association studies (GWASs) have identified hundreds of genetic loci associated with height, mainly in individuals of European ancestry.

METHODS

We performed genome-wide association analyses and replicated previously reported GWAS-determined single nucleotide polymorphisms (SNPs) in the Taiwanese Han population (Taiwan Biobank; n = 67,452). A genetic instrument composed of 251 SNPs was selected from our GWAS, based on height and replication results as the best-fit polygenic risk score (PRS), in accordance with the clumping and p-value threshold method. We also examined the association between genetically determined height (PRS₂₅₁) and measured height (phenotype). We performed observational (phenotype) and genetic PRS₂₅₁ association analyses of height and health-related outcomes.

RESULTS

GWAS identified 6843 SNPs in 89 genomic regions with genome-wide significance, including 18 novel loci. These were the most strongly associated genetic loci (EFEMP1, DIS3L2, ZBTB38, LCORL, HMGA1, CS, and GDF5) previously reported to play a role in height. There was a positive association between PRS₂₅₁ and measured height (p < 0.001). Of the 14 traits and 49 diseases analyzed, we observed significant associations of measured and genetically determined height with only eight traits (p < 0.05/[14 + 49]). Height was positively associated with body weight, waist circumference, and hip circumference but negatively associated with body mass index, waist-hip ratio, body fat, total cholesterol, and low-density lipoprotein cholesterol (p < 0.05/[14 + 49]).

CONCLUSIONS

This study contributes to the understanding of the genetic features of height and health-related outcomes in individuals of Han Chinese ancestry in Taiwan.

The Double Engines and Single Checkpoint Theory of Endometriosis

Endometriosis is a chronic disease characterized by the ectopic localization of the endometrial tissue in the peritoneal cavity. Consequently, it causes local pathological changes and systemic symptoms, affecting at least one in every ten women. This disease is difficult to diagnose early, it is prone to dissemination, is difficult to eradicate, tends to recur, and is regarded as “a cancer of no kill”. Indeed, the development of endometriosis closely resembles that of cancer in the way of mutagenesis, pelvic spreading, and immunological adaptation. While retrograde menstruation has been regarded as the primary cause of endometriosis, the role of ovulation and menstrual stimuli in the development of endometriosis has long been overlooked. The development of ovarian and peritoneal endometrioses, similar to the development of high-grade serous carcinoma in the fallopian tube fimbriae with intraperitoneal metastasis, depends highly on the carcinogens released during ovulation. Moreover, endometriosis carries an extremely hypermutated genome, which is non-inferior to the ultra-mutated endometrial cancer. The hypermutation would lead to an overproduction of new proteins or neoantigens. Because of this, the developing endometriosis may have to turn on the PD-1/PDL-1 “self-tolerance” checkpoint to evade immune surveillance, leaving an Achilles tendon for an immune checkpoint blockade. In this review, we present the double engines and single checkpoint theory of the genesis of endometriosis, provide the current pieces of evidence supporting the hypothesis, and discuss the new directions of prevention and treatment.

TwinEQTL: Ultra Fast and Powerful Association Analysis for eQTL and GWAS in Twin Studies

We develop a computationally efficient alternative, TwinEQTL, to a linear mixed-effects model (LMM) for twin genome-wide association study (GWAS) data. Instead of analyzing all twin samples together with LMM, TwinEQTL first splits twin samples into two independent groups on which multiple linear regression analysis can be validly performed separately, followed by an appropriate meta-analysis-like approach to combine the two non-independent test results. Through mathematical derivations, we prove the validity of TwinEQTL algorithm and show that the correlation between two dependent test statistics at each single-nucleotide polymorphism (SNP) are independent of its minor allele frequency (MAF). Thus the correlation is constant across all SNPs. Through simulations, we show empirically that TwinEQTL has well controlled type I error with negligible power loss compared to the gold-standard linear mixed effects models. To accommodate eQTL analysis with twin subjects, we further implement TwinEQTL into a R package with much improved computational efficiency. Our approaches provide a significant leap in terms of computing speed for GWAS and eQTL analysis with twin samples.

Family Socioeconomic Position and Lung Cancer Risk: A Meta-Analysis and a Mendelian Randomization Study

Background

Family socioeconomic position (SEP) in childhood is an important factor to predict some chronic diseases. However, the association between family SEP in childhood and the risk of lung cancer is not clear.

Methods

A systematic search was performed to explore their relationship. We selected education level, socioeconomic positions of parents and childhood housing conditions to represent an individual family SEP. Hazard ratios (HRs) of lung cancer specific-mortality were synthesized using a random effects model. Two-sample Mendelian randomization (MR) was carried out with summary data from published genome-wide association studies of SEP to assess the possible causal relationship of SEP and risk of lung cancer.

Results

Through meta-analysis of 13 studies, we observed that to compared with the better SEP, the poorer SEP in the childhood was associated with the increased lung cancer risk in the adulthood (HR: 1.25, 95% CI: 1.10 to 1.43). In addition, the dose-response analysis revealed a positive correlation between the poorer SEP and increased lung cancer risk. Same conclusion was reached in MR [(education level) OR 0.50, 95% CI: 0.39 to 0.63; P &lt; 0.001].

Conclusion

This study indicates that poor family socioeconomic position in childhood is causally correlated with lung cancer risk in adulthood.

Systematic Review Registration

identifier: 159082.

Genetic architectures and selection signatures of body height in Chinese indigenous donkeys revealed by next-generation sequencing

Donkeys are widely distributed labour animals in the world. During the process of the domestication and artificial selection of domestic donkeys, body sizes show significant differences among different breeds of donkeys. Based on the genome resequencing data of 103 Chinese indigenous donkeys from 11 breeds (Biyang, Dezhou, Guangling, Hetian, Jiami, Kulun, Qingyang, Turfan, Tibetan, Xinjiang, and Yunnan), seven Spanish donkeys from two breeds (Zamorano~Leonés and Andalusian), and three wild donkeys, we investigated the population structures of Chinese domestic donkeys with different body sizes. We used F_ST and XP-EHH analyses to explore the selected regions related to body sizes. The results showed that Chinese indigenous donkeys have a closer relationship with African wild donkeys than with Asian wild donkeys. LCORL/NCAPG, FAM184B, TBX3, and IHH were identified as genes with strong signals in analysis of selection signature (F_ST and XP-EHH) in large and small donkeys. The seven identified variants can be served as candidate loci affecting the body size of Chinese donkeys. Five of seven loci were located in intron 9 of FAM184B and were in a haplotype block, and one of the identified variants (Chr03:112664848) located in the CDS region of the LCORL gene was found to cause stop-loss. These candidate genes and variants shed new light on the molecular basis of donkey body size and will facilitate the breeding activities of donkeys.

miR-155-3p: processing by-product or rising star in immunity and cancer?

MicroRNAs (miRNAs) are key players in gene regulation that target specific mRNAs for degradation or translational repression. Each miRNA is synthesized as a miRNA duplex comprising two strands (5p and 3p). However, only one of the two strands becomes active and is selectively incorporated into the RNA-induced silencing complex in a process known as miRNA strand selection. Recently, significant progress has been made in understanding the factors and processes involved in strand selection. Here, we explore the selection and functionality of the miRNA star strand (either 5p or 3p), which is generally present in the cell at low levels compared to its partner strand and, historically, has been thought to possess no biological activity. We also highlight the concepts of miRNA arm switching and miRNA isomerism. Finally, we offer insights into the impact of aberrant strand selection on immunity and cancer. Leading us through this journey is miR-155, a well-established regulator of immunity and cancer, and the increasing evidence that its 3p strand plays a role in these arenas. Interestingly, the miR-155-5p/-3p ratio appears to vary dependent on the timing of the immune response, and the 3p strand seems to play a regulatory role upon its partner 5p strand.

The Relationship between Fluid Milk, Water, and 100% Juice and Health Outcomes among Children and Adolescents

Beverages can provide improved nutrient intake and hydration, but also pose concerns related to overnutrition or contamination for children and adolescents who are in a time of critical growth. This narrative review aims to understand the impact of milk, 100% juice, and water consumption on health-related outcomes in youth. The literature review conducted used PubMed, Web of Science, and CABI global. Forty-five research articles met the quality criteria and were included. Health organization and governmental resources were also reviewed to identify current intake and consumption recommendations. All beverages in this review were associated with a variety of desirable and undesirable findings that spanned over 40 different health outcomes. Most studies that assessed milk lacked clear distinction between milk type (flavored vs. unflavored) or fat percentage, making it difficult to understand the impact of milk consumption. The relationship between milk intake and anthropometric-related outcomes were mixed within and across studies. Water was consistently associated with better hydration, while 100% juice and flavored milk intake was associated with more desirable dietary patterns or nutrients that children are currently not consuming adequate amounts of. The implications of these findings were discussed in the context of the National School Lunch Program (NSLP), while considering the impact of issues such as contaminated water and lactose intolerance. This review suggests that water may be an optimal default beverage option in the NSLP to promote hydration and accommodate beverage preferences for those with lactose intolerance.

A Statistical Explanation of the Dunning-Kruger Effect

An explanation of the Dunning-Kruger effect is provided which does not require any psychological explanation, because it is derived as a statistical artifact. This is achieved by specifying a simple statistical model which explicitly takes the (random) boundary constraints into account. The model fits the data almost perfectly.

JEL Classification

A22; C24; C91; D84; D91; I21.

An integrative skeletal and paleogenomic analysis of stature variation suggests relatively reduced health for early European farmers

Human culture, biology, and health were shaped dramatically by the onset of agriculture ∼12,000 y B.P. This shift is hypothesized to have resulted in increased individual fitness and population growth as evidenced by archaeological and population genomic data alongside a decline in physiological health as inferred from skeletal remains. Here, we consider osteological and ancient DNA data from the same prehistoric individuals to study human stature variation as a proxy for health across a transition to agriculture. Specifically, we compared “predicted” genetic contributions to height from paleogenomic data and “achieved” adult osteological height estimated from long bone measurements for 167 individuals across Europe spanning the Upper Paleolithic to Iron Age (∼38,000 to 2,400 B.P.). We found that individuals from the Neolithic were shorter than expected (given their individual polygenic height scores) by an average of −3.82 cm relative to individuals from the Upper Paleolithic and Mesolithic (P = 0.040) and −2.21 cm shorter relative to post-Neolithic individuals (P = 0.068), with osteological vs. expected stature steadily increasing across the Copper (+1.95 cm relative to the Neolithic), Bronze (+2.70 cm), and Iron (+3.27 cm) Ages. These results were attenuated when we additionally accounted for genome-wide genetic ancestry variation: for example, with Neolithic individuals −2.82 cm shorter than expected on average relative to pre-Neolithic individuals (P = 0.120). We also incorporated observations of paleopathological indicators of nonspecific stress that can persist from childhood to adulthood in skeletal remains into our model. Overall, our work highlights the potential of integrating disparate datasets to explore proxies of health in prehistory.

Convergence of case-specific epigenetic alterations identify a confluence of genetic vulnerabilities tied to opioid overdose

Opioid use disorder is a highly heterogeneous disease driven by a variety of genetic and environmental risk factors which have yet to be fully elucidated. Opioid overdose, the most severe outcome of opioid use disorder, remains the leading cause of accidental death in the United States. We interrogated the effects of opioid overdose on the brain using ChIP-seq to quantify patterns of H3K27 acetylation in dorsolateral prefrontal cortical neurons isolated from 51 opioid-overdose cases and 51 accidental death controls. Among opioid cases, we observed global hypoacetylation and identified 388 putative enhancers consistently depleted for H3K27ac. Machine learning on H3K27ac patterns predicted case-control status with high accuracy. We focused on case-specific regulatory alterations, revealing 81,399 hypoacetylation events, uncovering vast inter-patient heterogeneity. We developed a strategy to decode this heterogeneity based on convergence analysis, which leveraged promoter-capture Hi-C to identify five genes over-burdened by alterations in their regulatory network or "plexus": ASTN2, KCNMA1, DUSP4, GABBR2, ENOX1. These convergent loci are enriched for opioid use disorder risk genes and heritability for generalized anxiety, number of sexual partners, and years of education. Overall, our multi-pronged approach uncovers neurobiological aspects of opioid use disorder and captures genetic and environmental factors perpetuating the opioid epidemic.

Clinical Profiles and Genetic Spectra of 814 Chinese Children With Short Stature

CONTEXT

Data and studies based on exome sequencing for the genetic evaluation of short stature are limited, and more large-scale studies are warranted. Some factors increase the likelihood of a monogenic cause of short stature, including skeletal dysplasia, severe short stature, and small for gestational age (SGA) without catch-up growth. However, whether these factors can serve as predictors of molecular diagnosis remains unknown.

OBJECTIVE

We aimed to explore the diagnostic efficiency of the associated risk factors and their exome sequences for screening.

METHODS

We defined and applied factors that increased the likelihood of monogenic causes of short stature in diagnostic genetic tests based on next-generation sequencing (NGS) in 814 patients with short stature and at least 1 other factor.

RESULTS

Pathogenic/likely pathogenic (P/LP) variants in genes, copy number variations, and chromosomal abnormalities were identified in 361 patients. We found P/LP variants among 111 genes, and RASopathies comprised the most important etiology. Short stature combined with other phenotypes significantly increased the likelihood of a monogenic cause, including skeletal dysplasia, facial dysmorphism, and intellectual disability, compared with simple severe short stature (<-3 SD scores). We report novel candidate pathogenic genes, KMT2C for unequivocal growth hormone insensitivity and GATA6 for SGA.

CONCLUSION

Our study identified the diagnostic characteristics of NGS in short stature with different risk factors. Our study provides novel insights into the current understanding of the etiology of short stature in patients with different phenotypes.

Partitioning gene-mediated disease heritability without eQTLs

Unknown SNP-to-gene regulatory architecture complicates efforts to link noncoding GWAS associations with genes implicated by sequencing or functional studies. eQTLs are often used to link SNPs to genes, but expression in bulk tissue explains a small fraction of disease heritability. A simple but successful approach has been to link SNPs with nearby genes via base pair windows, but genes may often be regulated by SNPs outside their window. We propose the abstract mediation model (AMM) to estimate (1) the fraction of heritability mediated by the closest or kth-closest gene to each SNP and (2) the mediated heritability enrichment of a gene set (e.g., genes with rare-variant associations). AMM jointly estimates these quantities by matching the decay in SNP enrichment with distance from genes in the gene set. Across 47 complex traits and diseases, we estimate that the closest gene to each SNP mediates 27% (SE: 6%) of heritability and that a substantial fraction is mediated by genes outside the ten closest. Mendelian disease genes are strongly enriched for common-variant heritability; for example, just 21 dyslipidemia genes mediate 25% of LDL heritability (211× enrichment, p = 0.01). Among brain-related traits, genes involved in neurodevelopmental disorders are only about 4× enriched, but gene expression patterns are highly informative, as they have detectable differences in per-gene heritability even among weakly brain-expressed genes.

Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank

Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.

Early anthropometric indicators of type 2 diabetes mellitus

PURPOSE OF REVIEW

With the rapidly increasing incidence of type 2 diabetes mellitus (T2DM) in youth (as in adults), it is critical to recognize phenotypic markers that can help predict and potentially prevent its onset, and reduce the associated burden of the disease for patients, families, and society. In this review, we summarize the most recent literature characterizing growth, puberty, and body composition in youth at risk for or who have T2DM.

RECENT FINDINGS

There is an inverse, nonlinear relationship between birth weight and future risk of developing T2DM. Height seems to have an inverse correlation with risk for diabetes. Earlier onset of puberty in males and females is associated with the T2DM phenotype. While adiposity is a known correlate of T2DM, visceral adiposity as represented by waist circumference has emerged as one of the key determinants of T2DM in population-based studies globally. Thresholds for body mass index vary across ethnicities in predicting risk for T2DM, depending on genetic factors and fat-distribution profiles.

SUMMARY

Emerging links between T2DM and dysregulated parameters of growth and development highlight the importance of early recognition of modifiable risk factors and the creation of individualized screening protocols.

VIDEO ABSTRACT

http://links.lww.com/COE/A31.

Detection of selection signatures in South African Mutton Merino sheep using whole-genome sequencing data

The South African Mutton Merino (SAMM), a dual-purpose (meat and wool) sheep breed, is characterized by its excellent performance on growth, carcass traits and meat quality compared to other fine-wool Merino breeds. Nowadays, the SAMM breed has been widely used to cross with commercial and indigenous fine-wool or coarse-wool breeds to improve the growth and meat performance in many countries. To date, however, little is known about the genetic basis for its prominent characteristics. In this study, whole-genome sequences of 10 SAMM were sequenced and the selection signatures were analyzed together with those of 39 Australian Merino and Chinese Merino (wool-type Merino) by F_ST , iHS, and XP-EHH methods. In total, 313 genes in 277 regions were identified by at least 2 methods with the signal of selection and 21 of them were identified by all three methods. We highlighted a list of interesting genes, including GHR, LCORL, SMO, NCAPG, DCC, IBSP, PPARGC1A, PACRGL, PRDM5, XYLB, AHCYL2, TEFM, AFG1L, and FAM184B, which have been shown to be involved in growth, carcass traits, and meat quality by previous studies. Herein, GHR, encoding a transmembrane receptor for growth hormone, is the most notable one. We report the first study on selection signatures analysis of SAMM at whole-genome sequence level. These results provide new insights into the genetic mechanisms underlying the growth and carcass traits in SAMM.

Identification of the genetic mechanism that associates L3MBTL3 to multiple sclerosis

Multiple sclerosis (MS) is a complex and demyelinating disease of the central nervous system. One of the challenges of the post-GWAS era is to understand the molecular basis of statistical associations to reveal gene networks and potential therapeutic targets. The L3MBTL3 locus has been associated with MS risk by GWAS. To identify the causal variant of the locus, we performed fine mapping in a cohort of 3440 MS patients and 1688 healthy controls. The variant that best explained the association was rs6569648 (P = 4.13E-10, OR = 0.71, 95% CI = 0.64-0.79), which tagged rs7740107, located in intron 7 of L3MBTL3. The rs7740107 (A/T) variant has been reported to be the best expression and splice quantitative trait locus (eQTL and sQTL) of the region in up to 35 human GTEx tissues. By sequencing RNA from blood of 17 MS patients and quantification by digital qPCR, we determined that this eQTL/sQTL originated from the expression of a novel short transcript starting in intron 7 near rs7740107. The short transcript was translated into three proteins starting at different translation initiation codons. These N-terminal truncated proteins lacked the region where L3MBTL3 interacts with the transcriptional regulator RBPJ (Recombination Signal Binding Protein for Immunoglobulin Kappa J Region) which, in turn, regulates the Notch signaling pathway. Our data and other functional studies suggest that the genetic mechanism underlying the MS association of rs7740107 affects not only the expression of L3MBTL3 isoforms, but might also involve the Notch signaling pathway.

Phenome-wide association study of the major histocompatibility complex region in the Korean population identifies novel association signals

Human leukocyte antigen (HLA) gene variants in the major histocompatibility complex (MHC) region are associated with numerous complex human diseases and quantitative traits. Previous phenome-wide association studies (PheWAS) for this region demonstrated that HLA association patterns to the phenome have both population-specific and population-shared components. We performed MHC PheWAS in the Korean population by analyzing associations between phenotypes and genetic variants in the MHC region using the Korea Biobank Array project data samples from the Korean Genome and Epidemiology Study (KoGES) cohorts. Using this single-population dataset, we curated and analyzed 82 phenotypes for 125 673 Korean individuals after imputing HLA using CookHLA, a recently developed imputation framework. More than one-third of these phenotypes showed significant associations, confirming 56 known associations and discovering 13 novel association signals that were not reported previously. In addition, we analyzed heritability explained by the variants in the MHC region and genetic correlations among phenotypes based on the MHC variants.

Genetic and genomic characterization followed by single-step genomic evaluation of withers height in German Warmblood horses

Reliability of genomic predictions is influenced by the size and genetic composition of the reference population. For German Warmblood horses, compilation of a reference population has been enabled through the cooperation of five German breeding associations. In this study, preliminary data from this joint reference population were used to genetically and genomically characterize withers height and to apply single-step methodology for estimating genomic breeding values for withers height. Using data on 2113 mares and their genomic information considering about 62,000 single nucleotide polymorphisms (SNPs), analysis of the genomic relationship revealed substructures reflecting breed origin and different breeding goals of the contributing breeding associations. A genome-wide association study confirmed a known quantitative trait locus (QTL) for withers height on equine chromosome (ECA) 3 close to LCORL and identified a further significant peak on ECA 1. Using a single-step approach with a combined relationship matrix, the estimated heritability for withers height was 0.31 (SE = 0.08) and the corresponding genomic breeding values ranged from − 2.94 to 2.96 cm. A mean reliability of 0.38 was realized for these breeding values. The analyses of withers height showed that compiling a reference population across breeds is a suitable strategy for German Warmblood horses. The single-step method is an appealing approach for practical genomic prediction in horses, because not many genotypes are available yet and animals without genotypes can by this way directly contribute to the estimation system.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

A data-adaptive Bayesian regression approach for polygenic risk prediction

MOTIVATION

Polygenic risk score (PRS) has been widely exploited for genetic risk prediction due to its accuracy and conceptual simplicity. We introduce a unified Bayesian regression framework, NeuPred, for PRS construction, which accommodates varying genetic architectures and improves overall prediction accuracy for complex diseases by allowing for a wide class of prior choices. To take full advantage of the framework, we propose a summary-statistics-based cross-validation strategy to automatically select suitable chromosome-level priors, which demonstrates a striking variability of the prior preference of each chromosome, for the same complex disease, and further significantly improves the prediction accuracy.

RESULTS

Simulation studies and real data applications with seven disease datasets from the Wellcome Trust Case Control Consortium cohort and eight groups of large-scale genome-wide association studies demonstrate that NeuPred achieves substantial and consistent improvements in terms of predictive r2 over existing methods. In addition, NeuPred has similar or advantageous computational efficiency compared with the state-of-the-art Bayesian methods.

AVAILABILITY AND IMPLEMENTATION

The R package implementing NeuPred is available at https://github.com/shuangsong0110/NeuPred.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.