Rare and low-frequency coding variants alter human adult height

Search Strategies for Alzheimer Protector Genes

Large families with autosomal dominant mutations leading to Alzheimer's disease and related conditions can show putative protective gene variants; however, no systematic search strategy exists to find these genes. Described here are the unique demographic circumstances and genetic setting in which the discovery of protective variants is likely. The identification of these genes may reveal pathways with therapeutic implications. ANN NEUROL 2023;94:613-617.

Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores

Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.

Trends in women's height and the effect of early childbearing on height retardation: An analysis of the height of Bangladeshi women born between 1974 and 1998

Background

Depending on race, ethnicity, and region, genetic variants determine human height by 65% to 80%, while the remaining variance of 20% to 35% is influenced by nutrition and other individual or environmental exposures in the early years of life. An improvement in nutrition and health in the early years in a population underprivileged in health and nutrition will likely increase the group's average height. Due to outstanding improvements in these areas in recent decades, we hypothesised that the average height of Bangladeshi women has increased. Moreover, because pregnancy at an early age affects women's health and nutrition, we hypothesised that women who began childbearing early would experience growth retardation compared to women who had pregnancies at a later age.

Methods

We used data from five national surveys conducted between 2004 and 2018 that collected height data from ever-married women aged 15-49 years. We analysed the height of women aged 20-29 years (born between 1974 and 1998) and examined the mean height by birth years, age at first birth (AFB), economic status, religion and region. We conducted multiple linear regression models, controlling for the differential effects of the socio-demographic characteristics on women's height over time and by AFB.

Results

The average height of women born between 1974 and 1998 significantly increased by 0.03 cm annually, with fluctuations between 150.3 and 151.6 cm. We also found an association between age at childbearing and height in adulthood - women who began childbearing before age 17 were approximately one centimetre shorter in adulthood than those who began childbearing at a later age.

Conclusions

We found evidence of an increasing trend in women's height in Bangladesh and an inhibiting effect of early teenage childbearing on attaining the potential growth of women. The findings call for further studies to investigate early childbearing and its consequences on women's and their children's growth in diverse settings, considering socio-cultural customs influencing early marriage and childbearing.

TMCO3, a Putative K+ :Proton Antiporter at the Golgi Apparatus, Is Important for Longitudinal Growth in Mice and Humans

Isolated short stature, defined as short stature without any other abnormalities, is a common heterogeneous condition in children. Exome sequencing identified the homozygous nonsense variant c.1832G>A/p.(Trp611*) in TMCO3 in two sisters with isolated short stature. Radiological studies, biochemical measurements, assessment of the skeletal status, and three-dimensional bone microarchitecture revealed no relevant skeletal and bone abnormalities in both sisters. The homozygous TMCO3 variant segregated with short stature in the family. TMCO3 transcript levels were reduced by ~50% in leukocyte-derived RNA of both sisters compared with controls, likely due to nonsense-mediated mRNA decay. In primary urinary cells of heterozygous family members, we detected significantly reduced TMCO3 protein levels. TMCO3 is functionally uncharacterized. We ectopically expressed wild-type TMCO3 in HeLa and ATDC5 chondrogenic cells and detected TMCO3 predominantly at the Golgi apparatus, whereas the TMCO3W611* mutant did not reach the Golgi. Coordinated co-expression of TMCO3W611* -HA and EGFP in HeLa cells confirmed intrinsic instability and/or degradation of the mutant. Tmco3 is expressed in all relevant mouse skeletal cell types. Highest abundance of Tmco3 was found in chondrocytes of the prehypertrophic zone in mouse and minipig growth plates where it co-localizes with a Golgi marker. Knockdown of Tmco3 in differentiated ATDC5 cells caused reduced and increased expression of Pthlh and Ihh, respectively. Measurement of long bones in Tmco3tm1b(KOMP)Wtsi knockout mice revealed significant shortening of forelimbs and hindlimbs. TMCO3 is a potential member of the monovalent cation:proton antiporter 2 (CPA2) family. By in silico tools and homology modeling, TMCO3 is predicted to have an N-terminal secretory signal peptide, forms a dimer localized to the membrane, and is organized in a dimerization and a core domain. The core domain contains the CPA2 motif essential for K+ binding and selectivity. Collectively, our data demonstrate that loss of TMCO3 causes growth defects in both humans and mice. © 2023 American Society for Bone and Mineral Research (ASBMR).

The long-term effects of genomic selection: 2. Changes in allele frequencies of causal loci and new mutations

Genetic selection has been applied for many generations in animal, plant, and experimental populations. Selection changes the allelic architecture of traits to create genetic gain. It remains unknown whether the changes in allelic architecture are different for the recently introduced technique of genomic selection compared to traditional selection methods and whether they depend on the genetic architectures of traits. Here, we investigate the allele frequency changes of old and new causal loci under 50 generations of phenotypic, pedigree, and genomic selection, for a trait controlled by either additive, additive and dominance, or additive, dominance, and epistatic effects. Genomic selection resulted in slightly larger and faster changes in allele frequencies of causal loci than pedigree selection. For each locus, allele frequency change per generation was not only influenced by its statistical additive effect but also to a large extent by the linkage phase with other loci and its allele frequency. Selection fixed a large number of loci, and 5 times more unfavorable alleles became fixed with genomic and pedigree selection than with phenotypic selection. For pedigree selection, this was mainly a result of increased genetic drift, while genetic hitchhiking had a larger effect on genomic selection. When epistasis was present, the average allele frequency change was smaller (∼15% lower), and a lower number of loci became fixed for all selection methods. We conclude that for long-term genetic improvement using genomic selection, it is important to consider hitchhiking and to limit the loss of favorable alleles.

A whole-genome reference panel of 14,393 individuals for East Asian populations accelerates discovery of rare functional variants

Underrepresentation of non-European (EUR) populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72,298 subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East Asian specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects. We suggest that this dataset will add to the potential value of Asian precision medicine.

Stanniocalcin-2 inhibits skeletal muscle growth and is upregulated in functional overload-induced hypertrophy

AIMS

Stanniocalcin-2 (STC2) has recently been implicated in human muscle mass variability by genetic analysis. Biochemically, STC2 inhibits the proteolytic activity of the metalloproteinase PAPP-A, which promotes muscle growth by upregulating the insulin-like growth factor (IGF) axis. The aim was to examine if STC2 affects skeletal muscle mass and to assess how the IGF axis mediates muscle hypertrophy induced by functional overload.

METHODS

We compared muscle mass and muscle fiber morphology between Stc2-/- (n = 21) and wild-type (n = 15) mice. We then quantified IGF1, IGF2, IGF binding proteins -4 and -5 (IGFBP-4, IGFBP-5), PAPP-A and STC2 in plantaris muscles of wild-type mice subjected to 4-week unilateral overload (n = 14).

RESULTS

Stc2-/- mice showed up to 10% larger muscle mass compared with wild-type mice. This increase was mediated by greater cross-sectional area of muscle fibers. Overload increased plantaris mass and components of the IGF axis, including quantities of IGF1 (by 2.41-fold, p = 0.0117), IGF2 (1.70-fold, p = 0.0461), IGFBP-4 (1.48-fold, p = 0.0268), PAPP-A (1.30-fold, p = 0.0154) and STC2 (1.28-fold, p = 0.019).

CONCLUSION

Here we provide evidence that STC2 is an inhibitor of muscle growth upregulated, along with other components of the IGF axis, during overload-induced muscle hypertrophy.

Rare variant analyses in large-scale cohorts identified SLC13A1 associated with chronic pain

ABSTRACT

Chronic pain is a prevalent disease with increasing clinical challenges. Genome-wide association studies in chronic pain patients have identified hundreds of common pathogenic variants, yet they only explained a portion of individual variance of chronic pain. With the advances in next-generation sequencing technologies, it is now feasible to conduct rarer variants studies in large-scale databases. Here, we performed gene-based rare variant analyses in 200,000 human subjects in the UK biobank whole-exome sequencing database for investigating 9 different chronic pain states and validated our findings in 3 other large-scale databases. Our analyses identified the SLC13A1 gene coding for sodium/sulfate symporter associated with chronic back pain and multisite pain at the genome-wide level and with chronic headache, knee, and neck and shoulder pain at the nominal level. Seven loss-of-function rare variants were identified within the gene locus potentially contributing to the development of chronic pain, with 2 of them individually associated with back pain and multisite pain. These 2 rare variants were then tested for replication in 3 other biobanks, and the strongest evidence was found for rs28364172 as an individual contributor. Transcriptional analyses of Slc13a1 in rodents showed substantial regulation of its expression in the dorsal root ganglia and the sciatic nerve in neuropathic pain assays. Our results stress the importance of the SLC13A1 gene in sulfate homeostasis in the nervous system and its critical role in preventing pain states, thus suggesting new therapeutic approaches for treating chronic pain in a personalized manner, especially in people with mutations in the SLC13A1 gene.

Diallel panel reveals a significant impact of low-frequency genetic variants on gene expression variation in yeast

Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level.

Genome-wide association study of thoracic aortic aneurysm and dissection in the Million Veteran Program

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

COVID-19 severity: does the genetic landscape of rare variants matter?

Rare variants affecting host defense against pathogens may be involved in COVID-19 severity, but most rare variants are not expected to have a major impact on the course of COVID-19. We hypothesized that the accumulation of weak effects of many rare functional variants throughout the exome may contribute to the overall risk in patients with severe disease. This assumption is consistent with the omnigenic model of the relationship between genetic and phenotypic variation in complex traits, according to which association signals tend to spread across most of the genome through gene regulatory networks from genes outside the major pathways to disease-related genes. We performed whole-exome sequencing and compared the burden of rare variants in 57 patients with severe and 29 patients with mild/moderate COVID-19. At the whole-exome level, we observed an excess of rare, predominantly high-impact (HI) variants in the group with severe COVID-19. Restriction to genes intolerant to HI or damaging missense variants increased enrichment for these classes of variants. Among various sets of genes, an increased signal of rare HI variants was demonstrated predominantly for primary immunodeficiency genes and the entire set of genes associated with immune diseases, as well as for genes associated with respiratory diseases. We advocate taking the ideas of the omnigenic model into account in COVID-19 studies.

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.

Weighted multiple testing procedures in genome-wide association studies

Multiple testing procedures controlling the false discovery rate (FDR) are increasingly used in the context of genome wide association studies (GWAS), and weighted multiple testing procedures that incorporate covariate information are efficient to improve the power to detect associations. In this work, we evaluate some recent weighted multiple testing procedures in the specific context of GWAS through a simulation study. We also present a new efficient procedure called wBHa that prioritizes the detection of genetic variants with low minor allele frequencies while maximizing the overall detection power. The results indicate good performance of our procedure compared to other weighted multiple testing procedures. In particular, in all simulated settings, wBHa tends to outperform other procedures in detecting rare variants while maintaining good overall power. The use of the different procedures is illustrated with a real dataset.

Hidden protein-altering variants influence diverse human phenotypes

Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-altering SVs from UK Biobank whole-exome sequencing data (n=468,570) using haplotype-informed methods capable of detecting sub-exonic SVs and variation within segmental duplications. Incorporating SVs into analyses of rare variants predicted to cause gene loss-of-function (pLoF) identified 100 associations of pLoF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 appeared to confer one of the strongest protective effects of gene LoF on hypertension risk (OR = 0.86 [0.82-0.90]). Protein-coding variation in rapidly-evolving gene families within segmental duplications-previously invisible to most analysis methods-appeared to generate some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype, and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.

Heritability and circulating concentrations of pregnancy-associated plasma protein-A and stanniocalcin-2 in elderly monozygotic and dizygotic twins

Introduction

Pregnancy-associated plasma protein-A (PAPP-A) is an IGF-activating enzyme suggested to influence aging-related diseases. However, knowledge on serum PAPP-A concentration and regulation in elderly subjects is limited. Therefore, we measured serum PAPP-A in elderly same-sex monozygotic (MZ) and dizygotic (DZ) twins, as this allowed us to describe the age-relationship of PAPP-A, and to test the hypothesis that serum PAPP-A concentrations are genetically determined. As PAPP-A is functionally related to stanniocalcin-2 (STC2), an endogenous PAPP-A inhibitor, we included measurements on STC2 as well as IGF-I and IGF-II.

Methods

The twin cohort contained 596 subjects (250 MZ twins, 346 DZ twins), whereof 33% were males. The age ranged from 73.2 to 94.3 (mean 78.8) years. Serum was analyzed for PAPP-A, STC2, IGF-I, and IGF-II by commercial immunoassays.

Results

In the twin cohort, PAPP-A increased with age (r=0.19; P<0.05), whereas IGF-I decreased (r=-0.12; P<0.05). Neither STC2 nor IGF-II showed any age relationship. When analyzed according to sex, PAPP-A correlated positively with age in males (r=0.18; P<0.05) and females (r=0.25; P<0.01), whereas IGF-I correlated inversely in females only (r=-0.15; P<0.01). Males had higher levels of PAPP-A (29%), STC2 (18%) and IGF-I (19%), whereas serum IGF-II was 28% higher in females (all P<0.001). For all four proteins, within-pair correlations were significantly higher for MZ twins than for DZ twins, and they demonstrated substantial and significant heritability, which after adjustment for age and sex averaged 59% for PAPP-A, 66% for STC2, 58% for IGF-I, and 52% for IGF-II.

Discussion

This twin study confirms our hypothesis that the heritability of PAPP-A serum concentrations is substantial, and the same is true for STC2. As regards the age relationship, PAPP-A increases with age, whereas STC2 remains unchanged, thereby supporting the idea that the ability of STC2 to inhibit PAPP-A enzymatic activity decreases with increasing age.

Genetically adjusted PSA levels for prostate cancer screening

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

Rare genetic variants underlie outlying levels of DNA methylation and gene-expression

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

The Genetic Landscape of Children Born Small for Gestational Age with Persistent Short Stature

INTRODUCTION

Among children born small for gestational age, 10-15% fail to catch up and remain short (SGA-SS). The underlying mechanisms are mostly unknown. We aimed to decipher genetic aetiologies of SGA-SS within a large single-centre cohort.

METHODS

Out of 820 patients treated with growth hormone (GH), 256 were classified as SGA-SS (birth length and/or birth weight <-2 SD for gestational age and life-minimum height <-2.5 SD). Those with the DNA triplet available (child and both parents) were included in the study (176/256). Targeted testing (karyotype/FISH/MLPA/specific Sanger sequencing) was performed if a specific genetic disorder was clinically suggestive. All remaining patients underwent MS-MLPA to identify Silver-Russell syndrome, and those with unknown genetic aetiology were subsequently examined using whole-exome sequencing or targeted panel of 398 growth-related genes. Genetic variants were classified using ACMG guidelines.

RESULTS

The genetic aetiology was elucidated in 74/176 (42%) children. Of these, 12/74 (16%) had pathogenic or likely pathogenic (P/LP) gene variants affecting pituitary development (LHX4, OTX2, PROKR2, PTCH1, POU1F1), the GH-IGF-1 or IGF-2 axis (GHSR, IGFALS, IGF1R, STAT3, HMGA2), 2/74 (3%) the thyroid axis (TRHR, THRA), 17/74 (23%) the cartilaginous matrix (ACAN, various collagens, FLNB, MATN3), and 7/74 (9%) the paracrine chondrocyte regulation (FGFR3, FGFR2, NPR2). In 12/74 (16%), we revealed P/LP affecting fundamental intracellular/intranuclear processes (CDC42, KMT2D, LMNA, NSD1, PTPN11, SRCAP, SON, SOS1, SOX9, TLK2). SHOX deficiency was found in 7/74 (9%), Silver-Russell syndrome in 12/74 (16%) (11p15, UPD7), and miscellaneous chromosomal aberrations in 5/74 (7%) children.

CONCLUSIONS

The high diagnostic yield sheds a new light on the genetic landscape of SGA-SS, with a central role for the growth plate with substantial contributions from the GH-IGF-1 and thyroid axes and intracellular regulation and signalling.

Using inbreeding to test the contribution of non-additive genetic effects to additive genetic variance: a case study in Drosophila serrata

Additive genetic variance, V_A, is the key parameter for predicting adaptive and neutral phenotypic evolution. Changes in demography (e.g. increased close-relative inbreeding) can alter V_A, but how they do so depends on the (typically unknown) gene action and allele frequencies across many loci. For example, V_A increases proportionally with the inbreeding coefficient when allelic effects are additive, but smaller (or larger) increases can occur when allele frequencies are unequal at causal loci with dominance effects. Here, we describe an experimental approach to assess the potential for dominance effects to deflate V_A under inbreeding. Applying a powerful paired pedigree design in Drosophila serrata, we measured 11 wing traits on half-sibling families bred via either random or sibling mating, differing only in homozygosity (not allele frequency). Despite close inbreeding and substantial power to detect small V_A, we detected no deviation from the expected additive effect of inbreeding on genetic (co)variances. Our results suggest the average dominance coefficient is very small relative to the additive effect, or that allele frequencies are relatively equal at loci affecting wing traits. We outline the further opportunities for this paired pedigree approach to reveal the characteristics of V_A, providing insight into historical selection and future evolutionary potential.

Adult Body Height Is Associated with the Risk of Type 2 but Not Type 1 Diabetes Mellitus: A Retrospective Cohort Study of 783,029 Individuals in Germany

Background: Diabetes mellitus is a major global health burden associated with high morbidity and mortality. Although a short adult body height has been associated with increased risk of type 2 diabetes (T2D), there are large inconsistencies between the studies. Therefore, we aimed to investigate the association between body height and T2D in a large cohort of adult outpatients in Germany. Methods: A total of 783,029 adult outpatients with available body height data from the Disease Analyzer (IQVIA) database were included in Germany between 2010 and 2020. The incidence of diabetes mellitus (type 1 and type 2) was evaluated as a function of the patients’ body height stratified by age, sex, and body-mass-index (BMI). Results: In both women and men in all age groups, incidence of T2D decreased with the increasing body height (<50, 51–60, 61–70, and >70 years). There was no association between the body height and the individual HbA1c value. In multivariable Cox regression analyses adjusted for patient age and BMI, hazard ratios for the development of T2D were 1.15 (95% CI: 1.13–1.17) for each 10 cm decrease in body height in women and 1.10 (95% CI: 1.09–1.12) in men. No significant association was found between body height and the development of T1D. Conclusions: We present the first data from a large cohort of outpatients in Germany, providing strong evidence for an association between adult body height and T2D. These data add to the current literature and might help in implementing body height into existing diabetes risk stratification tools to further reduce morbidity and mortality worldwide.

Females present higher dose-adjusted drug concentrations of metoprolol and allopurinol/oxypurinol than males

Females present a higher risk of adverse drug reactions. Sex-related differences in drug concentrations may contribute to these observations but they remain understudied given the underrepresentation of females in clinical trials. The aim of this study was to investigate whether anthropometric and socioeconomic factors and comorbidities could explain sex-related differences in concentrations and dosing for metoprolol and oxypurinol, the active metabolite of allopurinol. We conducted an analysis of two cross-sectional studies. Participants were self-described "White" adults taking metoprolol or allopurinol selected from the Montreal Heart Institute Hospital Cohort. A total of 1007 participants were included in the metoprolol subpopulation and 459 participants in the allopurinol subpopulation; 73% and 86% of the participants from the metoprolol and allopurinol subpopulations were males, respectively. Females presented higher age- and dose-adjusted concentrations of both metoprolol and oxypurinol (both p < 0.03). Accordingly, females presented higher unadjusted and age-adjusted concentration:dose ratio of both metoprolol and allopurinol/oxypurinol compared to males (all p < 3.0 × 10^-4 ). Sex remained an independent predictor of metoprolol concentrations (p < 0.01), but not of oxypurinol concentrations, after adjusting for other predictors. In addition to sex, age, daily dose, use of moderate to strong CYP2D6 inhibitors, weight, and CYP2D6 genotype-inferred phenotype were associated with concentrations of metoprolol (all p < 0.01). Daily dose, weight, estimated glomerular filtration rate (eGFR), and employment status were associated with oxypurinol concentrations (all p < 0.01). Females present higher dose-adjusted concentrations of metoprolol and oxypurinol than males. This suggests the need for sex-specific dosing requirements for these drugs, although this hypothesis should be validated in prospective studies.

SUMMIT-FA: A new resource for improved transcriptome imputation using functional annotations

Transcriptome-wide association studies (TWAS) integrate gene expression prediction models and genome-wide association studies (GWAS) to identify gene-trait associations. The power of TWAS is determined by the sample size of GWAS and the accuracy of the expression prediction model. Here, we present a new method, the Summary-level Unified Method for Modeling Integrated Transcriptome using Functional Annotations (SUMMIT-FA), that improves the accuracy of gene expression prediction by leveraging functional annotation resources and a large expression quantitative trait loci (eQTL) summary-level dataset. We build gene expression prediction models using SUMMIT-FA with a comprehensive functional database MACIE and the eQTL summary-level data from the eQTLGen consortium. By applying the resulting models to GWASs for 24 complex traits and exploring it through a simulation study, we show that SUMMIT-FA improves the accuracy of gene expression prediction models in whole blood, identifies significantly more gene-trait associations, and improves predictive power for identifying "silver standard" genes compared to several benchmark methods.

Genome-wide association study reveals BET1L associated with survival time in the 137,693 Japanese individuals

Human lifespan is reported to be heritable. Although previous genome-wide association studies (GWASs) have identified several loci, a limited number of studies have assessed the genetic associations with the real survival information on the participants. We conducted a GWAS to identify loci associated with survival time in the Japanese individuals participated in the BioBank Japan Project by carrying out sex-stratified GWASs involving 78,029 males and 59,664 females. Of them, 31,324 (22.7%) died during the mean follow-up period of 7.44 years. We found a novel locus associated with survival (BET1L; P = 5.89 × 10^-9). By integrating with eQTL data, we detected a significant overlap with eQTL of BET1L in skeletal muscle. A gene-set enrichment analysis showed that genes related to the BCAR1 protein-protein interaction subnetwork influence survival time (P = 1.54 × 10^-7). These findings offer the candidate genes and biological mechanisms associated with human lifespan.

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.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Idiopathic Short Stature: What to Expect from Genomic Investigations

Short stature is a common concern for physicians caring for children. In traditional investigations, about 70% of children are healthy, without producing clinical and laboratory findings that justify their growth disorder, being classified as having constitutional short stature or idiopathic short stature (ISS). In such scenarios, the genetic approach has emerged as a great potential method to understand ISS. Over the last 30 years, several genes have been identified as being responsible for isolated short stature, with almost all of them being inherited in an autosomal-dominant pattern. Most of these defects are in genes related to the growth plate, followed by genes related to the growth hormone (GH)–insulin-like growth factor 1 (IGF1) axis and RAS-MAPK pathway. These patients usually do not have a specific phenotype, which hinders the use of a candidate gene approach. Through multigene sequencing analyses, it has been possible to provide an answer for short stature in 10–30% of these cases, with great impacts on treatment and follow-up, allowing the application of the concept of precision medicine in patients with ISS. This review highlights the historic aspects and provides an update on the monogenic causes of idiopathic short stature and suggests what to expect from genomic investigations in this field.

Applications of artificial intelligence multiomics in precision oncology

Cancer is the second leading worldwide disease that depends on oncogenic mutations and non-mutated genes for survival. Recent advancements in next-generation sequencing (NGS) have transformed the health care sector with big data and machine learning (ML) approaches. NGS data are able to detect the abnormalities and mutations in the oncogenes. These multi-omics analyses are used for risk prediction, early diagnosis, accurate prognosis, and identification of biomarkers in cancer patients. The availability of these cancer data and their analysis may provide insights into the biology of the disease, which can be used for the personalized treatment of cancer patients. Bioinformatics tools are delivering this promise by managing, integrating, and analyzing these complex datasets. The clinical outcomes of cancer patients are improved by the use of various innovative methods implicated particularly for diagnosis and therapeutics. ML-based artificial intelligence (AI) applications are solving these issues to a great extent. AI techniques are used to update the patients on a personalized basis about their treatment procedures, progress, recovery, therapies used, dietary changes in lifestyles patterns along with the survival summary of previously recovered cancer patients. In this way, the patients are becoming more aware of their diseases and the entire clinical treatment procedures. Though the technology has its own advantages and disadvantages, we hope that the day is not so far when AI techniques will provide personalized treatment to cancer patients tailored to their needs in much quicker ways.

Examination of runs of homozygosity in relation to height in an endogamous Namibian population

OBJECTIVES

Height is a complex, highly heritable polygenic trait subject to both genetic composition and environmental influences. Recent studies suggest that a large proportion of height heritability is determined by the cumulative effect of many low allele frequency variants across the genome. Previous research has also identified an inverse relationship between height and runs of homozygosity (ROH); however, this has yet to be examined within African populations. We aim to identify this association within the Himba, an endogamous Namibian population who are recently bottlenecked, resulting in elevated haplotype sharing and increased homozygosity.

MATERIALS AND METHODS

Here, we calculate the fraction of the genome composed of long runs of homozygosity (FROH) in a sample of 245 adults and use mixed effects models to assess its effect on height.

RESULTS

We find that Himba adults exhibit increased homozygosity. However, in contrast to previous studies in other populations, we do not find a significant effect of FROH on height within the Himba. We further estimated heritability of height, noting both an enrichment of distant relatives and greater developmental homogeneity across households; we find thath g 2 = 0.59 (SE ± 0.146), comparable to estimates reported in Europeans.

DISCUSSION

Our results may be due to other environmental variables we were not able to include, measurement error, or low statistical power, but may also imply that phenotypic expression resulting from increased homozygosity may vary from population to population.

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.

Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher's exact p = 7.3 × 10-4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.

Region-related patterns of the main physical development indicators observed in northerners in the ontogenetic aspect

Indicators of physical development appear to be environmentally sensitive and thus we can consider them the main characteristics of the population health.The aim. To assess the line of physical development main variables in the ontogenetic aspect (data from the North born male subjects aged from 8 to 77).Material and methods. Three thousand seven hundred and ninety-four male Caucasians from 17 age groups were examined to analyse their physical development.Results. The study showed longer body length variables as the region-related somatometric picture which is characteristic of male Caucasian northerners in comparison with those from other regions of the Russian Federation, as well as from other countries. Besides, they exhibited significantly lower body mass index and reported to have had lower body weight since the age of 17. We can see the modern northerners’ somatotype being influenced by regional extremes. That also includes the end of the body growth processes by the start of ontogenesis in the youth. The line pattern of annual growth observed in the body length and weight variables indicates a combined pronounced dynamics in the 11 to 16 age period. By the age of 60–77 years subjects tend to decrease in the body length with a significant increase in the body weight and body mass index by the age of 31–36.Conclusion. The study suggests that identifying risks for the development of noninfectious and cardiovascular diseases caused by accelerated BMI in older populations requires monitoring of the North inhabitants’ main physical development indicators as well as the body annual growth variables.

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.

Diagnostic yield of a multigene sequencing approach in children classified as idiopathic short stature

Objective

Most children with short stature remain without an etiologic diagnosis after extensive clinical and laboratory evaluation and are classified as idiopathic short stature (ISS). This study aimed to determine the diagnostic yield of a multigene analysis in children classified as ISS.

Design and methods

We selected 102 children with ISS and performed the genetic analysis as part of the initial investigation. We developed customized targeted panel sequencing, including all genes already implicated in the isolated short-stature phenotype. Rare and deleterious single nucleotide or copy number variants were assessed by bioinformatic tools.

Results

We identified 20 heterozygous pathogenic (P) or likely pathogenic (LP) genetic variants in 17 of 102 patients (diagnostic yield = 16.7%). Three patients had more than one P/LP genetic alteration. Most of the findings were in genes associated with the growth plate differentiation: IHH (n = 4), SHOX (n = 3), FGFR3 (n = 2), NPR2 (n = 2), ACAN (n = 2), and COL2A1 (n = 1) or involved in the RAS/MAPK pathway: NF1 (n = 2), PTPN11 (n = 1), CBL (n = 1), and BRAF (n = 1). None of these patients had clinical findings to guide a candidate gene approach. The diagnostic yield was higher among children with severe short stature (35% vs 12.2% for height SDS ≤ or > -3; P = 0.034). The genetic diagnosis had an impact on clinical management for four children.

Conclusion

A multigene sequencing approach can determine the genetic etiology of short stature in up to one in six children with ISS, removing the term idiopathic from their clinical classification.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

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.

Influences of rare copy-number variation on human complex traits

The human genome contains hundreds of thousands of regions harboring copy-number variants (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs have been ascertainable from SNP-array data generated by large biobanks. We developed a computational approach leveraging haplotype sharing in biobank cohorts to more sensitively detect CNVs. Applied to UK Biobank, this approach accounted for approximately half of all rare gene inactivation events produced by genomic structural variation. This CNV call set enabled a detailed analysis of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (p < 5 × 10-8) likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling insights into dosage sensitivity of these genes and uncovering several gene-trait relationships. These results demonstrate the ability of haplotype-informed analysis to provide insights into the genetic basis of human complex traits.

SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification

Genes with moderate to low expression heritability may explain a large proportion of complex trait etiology, but such genes cannot be sufficiently captured in conventional transcriptome-wide association studies (TWASs), partly due to the relatively small available reference datasets for developing expression genetic prediction models to capture the moderate to low genetically regulated components of gene expression. Here, we introduce a method, the Summary-level Unified Method for Modeling Integrated Transcriptome (SUMMIT), to improve the expression prediction model accuracy and the power of TWAS by using a large expression quantitative trait loci (eQTL) summary-level dataset. We apply SUMMIT to the eQTL summary-level data provided by the eQTLGen consortium. Through simulation studies and analyses of genome-wide association study summary statistics for 24 complex traits, we show that SUMMIT improves the accuracy of expression prediction in blood, successfully builds expression prediction models for genes with low expression heritability, and achieves higher statistical power than several benchmark methods. Finally, we conduct a case study of COVID-19 severity with SUMMIT and identify 11 likely causal genes associated with COVID-19 severity.

Structure of the proteolytic enzyme PAPP-A with the endogenous inhibitor stanniocalcin-2 reveals its inhibitory mechanism

The metzincin metalloproteinase PAPP-A plays a key role in the regulation of insulin-like growth factor (IGF) signaling by specific cleavage of inhibitory IGF binding proteins (IGFBPs). Using single-particle cryo-electron microscopy (cryo-EM), we here report the structure of PAPP-A in complex with its endogenous inhibitor, stanniocalcin-2 (STC2), neither of which have been reported before. The highest resolution (3.1 Å) was obtained for the STC2 subunit and the N-terminal approximately 1000 residues of the PAPP-A subunit. The 500 kDa 2:2 PAPP-A·STC2 complex is a flexible multidomain ensemble with numerous interdomain contacts. In particular, a specific disulfide bond between the subunits of STC2 and PAPP-A prevents dissociation, and interactions between STC2 and a module located in the very C-terminal end of the PAPP-A subunit prevent binding of its main substrate, IGFBP-4. While devoid of activity towards IGFBP-4, the active site cleft of the catalytic domain is accessible in the inhibited PAPP-A·STC2 complex, as shown by its ability to hydrolyze a synthetic peptide derived from IGFBP-4. Relevant to multiple human pathologies, this unusual mechanism of proteolytic inhibition may support the development of specific pharmaceutical agents, by which IGF signaling can be indirectly modulated.

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.

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.

Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes

Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variations in human disease has not been explored at scale. Exome-sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variations across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 4,529 phenotypes using single-variant and gene tests of 394,841 individuals in the UK Biobank with exome-sequence data. We find that the discovery of genetic associations is tightly linked to frequency and is correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside the Genebass browser for rapidly exploring rare-variant association results.

Deleterious mutations and the rare allele burden on rice gene expression

Deleterious genetic variation is maintained in populations at low frequencies. Under a model of stabilizing selection, rare (and presumably deleterious) genetic variants are associated with increase or decrease in gene expression from some intermediate optimum. We investigate this phenomenon in a population of largely Oryza sativa ssp. indica rice landraces under normal unstressed wet and stressful drought field conditions. We include single nucleotide polymorphisms, insertion/deletion mutations, and structural variants in our analysis and find a stronger association between rare variants and gene expression outliers under the stress condition. We also show an association of the strength of this rare variant effect with linkage, gene expression levels, network connectivity, local recombination rate, and fitness consequence scores, consistent with the stabilizing selection model of gene expression.

Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease

AIMS/HYPOTHESIS

Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.

METHODS

We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets.

RESULTS

The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10-9; although not withstanding correction for multiple testing, p>9.3×10-9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p<2.7×10-6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10-6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10-11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10-8] and negatively with tubulointerstitial fibrosis [p=2.0×10-9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10-16], and SNX30 expression correlated positively with eGFR [p=5.8×10-14] and negatively with fibrosis [p<2.0×10-16]).

CONCLUSIONS/INTERPRETATION

Altogether, the results point to novel genes contributing to the pathogenesis of DKD.

DATA AVAILABILITY

The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( https://t1d.hugeamp.org/downloads.html ; https://t2d.hugeamp.org/downloads.html ; https://hugeamp.org/downloads.html ).

Importance of Including Non-European Populations in Large Human Genetic Studies to Enhance Precision Medicine

One goal of genomic medicine is to uncover an individual's genetic risk for disease, which generally requires data connecting genotype to phenotype, as done in genome-wide association studies (GWAS). While there may be clinical promise to employing prediction tools such as polygenic risk scores (PRS), it currently stands that individuals of non-European ancestry may not reap the benefits of genomic medicine because of underrepresentation in large-scale genetics studies. Here, we discuss why this inequity poses a problem for genomic medicine and the reasons for the low transferability of PRS across populations. We also survey the ancestry representation of published GWAS and investigate how estimates of ancestry diversity in GWASparticipants might be biased. We highlight the importance of expanding genetic research in Africa, one of the most underrepresented regions in human genomics research, and discuss issues of ethics, resources, and technology for equitable advancement of genomic medicine.

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data^1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank³. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Increased activity of the metalloproteinase PAPP-A promotes diabetes-induced glomerular hypertrophy

BACKGROUND

Diabetic nephropathy (DN) is a serious complication of diabetes and a common cause of end stage renal failure. Insulin-like growth factor (IGF)-signaling has been implicated in DN, but is mechanistically poorly understood. Here, we assessed the activity of the metalloproteinase PAPP-A, an activator of IGF activity, and its possible interaction with the endogenous PAPP-A inhibitors stanniocalcin (STC)-1 and -2 in the mammalian kidney under normal and hyperglycemic conditions.

METHODS AND RESULTS

Immunohistochemistry demonstrated that PAPP-A, its proteolytic substrate IGF binding protein-4, STC1 and STC2 are present in the human kidney. Endogenous inhibited complexes of PAPP-A (PAPP-A:STC1 and PAPP-A:STC2) were demonstrated in media conditioned by human mesangial cells (HMCs), suggesting that PAPP-A activity is regulated by the STCs in kidney tissue. A method for the selective detection of active PAPP-A in tissue was developed and a significant increase in glomerular active PAPP-A in human diabetic kidney relative to normal was observed. In DN patients, the estimated glomerular filtration rate correlated with PAPP-A activity. In diabetic mice, glomerular growth was reduced when PAPP-A activity was antagonized by adeno-associated virus-mediated overexpression of STC2.

CONCLUSION

We propose that PAPP-A activity in renal tissue is precisely balanced by STC1 and STC2. An imbalance in this equilibrium causing increased PAPP-A enzymatic activity potentially contributes to the development of DN, and thus, therapeutic targeting of PAPP-A activity may represent a novel strategy for its treatment.

An association study of ABCG2 rs2231142 on the concentrations of allopurinol and its metabolites

ABCG2 is a gene that codes for the human breast cancer resistance protein (BCRP). It is established that rs2231142 G>T, a single nucleotide polymorphism of the ABCG2 gene, is associated with gout and poor response to allopurinol, a uric acid‐lowering agent used to treat this condition. It has also been suggested that oxypurinol, the primary active metabolite of allopurinol, is a substrate of the BCRP. We thus hypothesized that carrying the rs2231142 variant would be associated with decreased oxypurinol concentrations, which would explain the lower reduction in uric acid. We performed a cross‐sectional study to investigate the association between the ABCG2 rs2231142 variant and oxypurinol, allopurinol, and allopurinol riboside concentrations in 459 participants from the Montreal Heart Institute Hospital Cohort. Age, sex, weight, use of diuretics, and estimated glomerular filtration rate were all significantly associated with oxypurinol plasma concentration. No association was found between rs2231142 and oxypurinol, allopurinol and allopurinol riboside plasma concentrations. Rs2231142 was not significantly associated with daily allopurinol dose in the overall population, but an association was observed in men, with T carriers receiving higher doses. Our results do not support a major role of ABCG2 in the pharmacokinetics of allopurinol or its metabolites. The underlying mechanism of the association between rs2231142 and allopurinol efficacy requires further investigation.

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.