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

[This corrects the article DOI: 10.1016/j.xhgg.2022.100099.].

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

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

Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes.

Most genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered. We conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 case subjects and 279,507 control subjects from 7 European-ancestry cohorts, including the UK Biobank. We identified 51 loci associated with type 2 diabetes, including five variants undetected by prior additive analyses. Two of the five variants had minor allele frequency of <5% and were each associated with more than a doubled risk in homozygous carriers. Using two additional cohorts, FinnGen and a Danish cohort, we replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19; P = 1 × 10-16) and a stronger effect in men than in women (for interaction, P = 7 × 10-7). The signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL cholesterol and a 20% increase in triglycerides; colocalization analysis linked this signal to reduced expression of the nearby PELO gene. These results demonstrate that recessive models, when compared with GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes.

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.

FGL1 as a modulator of plasma D-dimer levels: Exome-wide marker analysis of plasma tPA, PAI-1, and D-dimer.

BACKGROUND: Use of targeted exome-arrays with common, rare variants and functionally enriched variation has led to discovery of new genes contributing to population variation in risk factors. Plasminogen activator-inhibitor 1 (PAI-1), tissue plasminogen activator (tPA), and the plasma product D-dimer are important components of the fibrinolytic system. There have been few large-scale genome-wide or exome-wide studies of PAI-1, tPA, and D-dimer. OBJECTIVES: We sought to discover new genetic loci contributing to variation in these traits using an exome-array approach. METHODS: Cohort-level analyses and fixed effects meta-analyses of PAI-1 (n = 15 603), tPA (n = 6876,) and D-dimer (n = 19 306) from 12 cohorts of European ancestry with diverse study design were conducted, including single-variant analyses and gene-based burden testing. RESULTS: Five variants located in NME7, FGL1, and the fibrinogen locus, all associated with D-dimer levels, achieved genome-wide significance (P < 5 × 10-8 ). Replication was sought for these 5 variants, as well as 45 well-imputed variants with P < 1 × 10-4 in the discovery using an independent cohort. Replication was observed for three out of the five significant associations, including a novel and uncommon (0.013 allele frequency) coding variant p.Trp256Leu in FGL1 (fibrinogen-like-1) with increased plasma D-dimer levels. Additionally, a candidate-gene approach revealed a suggestive association for a coding variant (rs143202684-C) in SERPINB2, and suggestive associations with consistent effect in the replication analysis include an intronic variant (rs11057830-A) in SCARB1 associated with increased D-dimer levels. CONCLUSION: This work provides new evidence for a role of FGL1 in hemostasis.

The impact of non-additive genetic associations on age-related complex diseases.

Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases.

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.

Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort.

BACKGROUND: Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. METHODS: We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107). RESULTS: Heritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with LINC01432 (p=1.9×10-9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10-10) and variants in IRF4 (p=2.8×10-57), SLC45A2 (p=2.2×10-130), HERC2 (p=2.8×10-176), OCA2 (p=2.4×10-121) and MC1R (p=7.7×10-22) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold <5×10-9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9. CONCLUSION: Considering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits.

A cancer-associated polymorphism in ESCRT-III disrupts the abscission checkpoint and promotes genome instability.

Cytokinetic abscission facilitates the irreversible separation of daughter cells. This process requires the endosomal-sorting complexes required for transport (ESCRT) machinery and is tightly regulated by charged multivesicular body protein 4C (CHMP4C), an ESCRT-III subunit that engages the abscission checkpoint (NoCut) in response to mitotic problems such as persisting chromatin bridges within the midbody. Importantly, a human polymorphism in CHMP4C (rs35094336, CHMP4CT232) increases cancer susceptibility. Here, we explain the structural and functional basis for this cancer association: The CHMP4CT232 allele unwinds the C-terminal helix of CHMP4C, impairs binding to the early-acting ESCRT factor ALIX, and disrupts the abscission checkpoint. Cells expressing CHMP4CT232 exhibit increased levels of DNA damage and are sensitized to several conditions that increase chromosome missegregation, including DNA replication stress, inhibition of the mitotic checkpoint, and loss of p53. Our data demonstrate the biological importance of the abscission checkpoint and suggest that dysregulation of abscission by CHMP4CT232 may synergize with oncogene-induced mitotic stress to promote genomic instability and tumorigenesis.

Publisher Correction: Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes.

In the originally published version of this Article, the affiliation details for Santi González, Jian'an Luan and Claudia Langenberg were inadvertently omitted. Santi González should have been affiliated with 'Barcelona Supercomputing Center (BSC), Joint BSC-CRG-IRB Research Program in Computational Biology, 08034 Barcelona, Spain', and Jian'an Luan and Claudia Langenberg should have been affiliated with 'MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK'. Furthermore, the abstract contained an error in the SNP ID for the rare variant in chromosome Xq23, which was incorrectly given as rs146662057 and should have been rs146662075. These errors have now been corrected in both the PDF and HTML versions of the Article.

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes.

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.

A functional IFN-λ4-generating DNA polymorphism could protect older asthmatic women from aeroallergen sensitization and associate with clinical features of asthma.

Lambda interferons (IFNLs) have immunomodulatory functions at epithelial barrier surfaces. IFN-λ4, a recent member of this family is expressed only in a subset of the population due to a frameshift-causing DNA polymorphism rs368234815. We examined the association of this polymorphism with atopy (aeroallergen sensitization) and asthma in a Polish hospital-based case-control cohort comprising of well-characterized adult asthmatics (n = 326) and healthy controls (n = 111). In the combined cohort, we saw no association of the polymorphism with asthma and/or atopy. However, the IFN-λ4-generating ΔG allele protected older asthmatic women (>50 yr of age) from atopic sensitization. Further, ΔG allele significantly associated with features of less-severe asthma including bronchodilator response and corticosteroid usage in older women in this Polish cohort. We tested the association of related IFNL locus polymorphisms (rs12979860 and rs8099917) with atopy, allergic rhinitis and presence/absence of asthma in three population-based cohorts from Europe, but saw no significant association of the polymorphisms with any of the phenotypes in older women. The polymorphisms associated marginally with lower occurrence of asthma in men/older men after meta-analysis of data from all cohorts. Functional and well-designed replication studies may reveal the true positive nature of these results.

Dysregulation of Placental miRNA in Maternal Obesity Is Associated With Pre- and Postnatal Growth.

Context: Human placenta exhibits a specific microRNA (miRNA) expression pattern. Some of these miRNAs are dysregulated in pregnancy disorders such as preeclampsia and intrauterine growth restriction and are potential biomarkers for these pathologies. Objective: To study the placental miRNA profile in pregnant women with pregestational overweight/obesity (preOB) or gestational obesity (gestOB) and explore the associations between placental miRNAs dysregulated in maternal obesity and prenatal and postnatal growth. Methods: TaqMan Low Density Arrays and real-time polymerase chain reaction were used to profile the placental miRNAs in 70 pregnant women (20 preOB, 25 gestOB, and 25 control). Placentas and newborns were weighed at delivery, and infants were weighed at 1, 4, and 12 months of age. Results: Eight miRNAs were decreased in placentas from preOB or gestOB (miR-100, miR-1269, miR-1285, miR-181, miR-185, miR-214, miR-296, and miR-487) (all P < 0.05). Among them, miR-100, miR-1285, miR-296, and miR-487 were associated with maternal metabolic parameters (all P < 0.05) and were predictors of lower birth weight (all P < 0.05; R2 > 30%) and increased postnatal weight gain (all P < 0.05; R2 > 20%). In silico analysis showed that these miRNAs were related to cell proliferation and insulin signaling pathways. miR-296 was also present in plasma samples and associated with placental expression and prenatal and postnatal growth parameters (all P < 0.05). Conclusions: We identified a specific placental miRNA profile in maternal obesity. Placental miRNAs dysregulated in maternal obesity may be involved in mediation of growth-promoting effects of maternal obesity on offspring and could be used as early markers of prenatal and postnatal growth.

Altered Circulating miRNA Expression Profile in Pregestational and Gestational Obesity.

CONTEXT: MicroRNAs (miRNAs) are valuable circulating biomarkers and therapeutic targets for metabolic diseases. OBJECTIVE: The objective of the study was to define the pattern of circulating miRNAs in pregestational and gestational obesity and to explore their associations with maternal metabolic parameters and with markers for pre- and postnatal growth. design, settings, and main outcome measure: TaqMan low-density arrays were used to profile plasma miRNAs in six women with pregestational obesity (PregestOB), six with gestational obesity (GestOB), and six with normal pregnancies (control) during the second trimester of gestation. The most relevant miRNAs were validated in 70 pregnant women (20 PregestOB, 25 GestOB, and 25 control). Maternal metabolic parameters including glucose, glycated hemoglobin, homeostasis model assessment index of insulin resistance, C-peptide, and lipids were assessed. Placentas were weighed at delivery and newborns also during 6 months of life. RESULTS: We identified 13 circulating miRNAs differentially expressed in maternal obesity, including decreased levels of miR-29c, miR-99b, miR-103, miR-221, and miR-340 and increased levels of miR-30a-5p, miR-130a, and miR-150 in GestOB; and decreased levels of miR-122, miR-324-3p, miR-375, and miR-652 and increased levels of miR-625 in both PregestOB and GestOB (P < .05 to P < .0001 vs control). Decreased levels of several of these miRNAs associated with a more adverse maternal metabolic status (more pregnancy weight gain, glucose, glycated hemoglobin, homeostasis model assessment index of insulin resistance, C-peptide, and triacylglycerol and less high density lipoprotein cholesterol), with more placental weight, weight at birth, and weight at 6 months of life (all P < .05 to P < .001). CONCLUSIONS: This study provides the first identification of altered circulating miRNAs in maternal obesity and suggests a possible role of such miRNAS as markers for pre- and postnatal growth.