Metabolomic and genetic architecture of gestational diabetes subtypes

AIMS/HYPOTHESIS

Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes.

METHODS

This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM).

RESULTS

Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM.

CONCLUSIONS/INTERPRETATION

This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes

BACKGROUND

Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear.

METHODS

We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women.

RESULTS

All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation.

CONCLUSIONS

Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications.

FUNDING

Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.

Urinary metal profiles in mother-offspring pairs and their association with early dysglycemia in the International Hyperglycemia and Adverse Pregnancy Outcome Follow Up Study (HAPO-FUS)

BACKGROUND

Variations in dietary intake and environmental exposure patterns of essential and non-essential trace metals influence many aspects of human health throughout the life span.

OBJECTIVE

To examine the relationship between urine profiles of essential and non-essential metals in mother-offspring pairs and their association with early dysglycemia.

METHODS

Herein, we report findings from an ancillary study to the international Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study (HAPO-FUS) that examined urinary essential and non-essential metal profiles from mothers and offspring ages 10-14 years (1012 mothers, 1013 offspring, 968 matched pairs) from 10 international sites.

RESULTS

Our analysis demonstrated a diverse exposure pattern across participating sites. In multiple regression modelling, a positive association between markers of early dysglycemia and urinary zinc was found in both mothers and offspring after adjustment for common risk factors for diabetes. The analysis showed weaker, positive, and negative associations of the 2-h glucose value with urinary selenium and arsenic respectively. A positive association between 2-h glucose values and cadmium was found only in mothers in the fully adjusted model when participants with established diabetes were excluded. There was a high degree of concordance between mother and offspring urinary metal profiles. Mother-to-offspring urinary metal ratios were unique for each metal, providing insights into changes in their homeostasis across the lifespan.

SIGNIFICANCE

Urinary levels of essential and non-essential metals are closely correlated between mothers and their offspring in an international cohort. Urinary levels of zinc, selenium, arsenic, and cadmium showed varying degrees of association with early dysglycemia in a comparatively healthy cohort with a low rate of preexisting diabetes.

IMPACT STATEMENT

Our data provides novel evidence for a strong correlation between mother and offspring urinary metal patterns with a unique mother-to-offspring ratio for each metal. The study also provides new evidence for a strong positive association between early dysglycemia and urinary zinc, both in mothers and offspring. Weaker positive associations with urinary selenium and cadmium and negative associations with arsenic were also found. The low rate of preexisting diabetes in this population provides the unique advantage of minimizing the confounding effect of preexisting, diabetes related renal changes that would alter the relationship between dysglycemia and renal metal excretion.

Genetic variation in the human leukocyte antigen region confers susceptibility to Clostridioides difficile infection

Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10-14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

Genetic Predictors of Blood Pressure Traits are Associated with Preeclampsia

Background

Preeclampsia, a pregnancy complication characterized by hypertension after 20 gestational weeks, is a major cause of maternal and neonatal morbidity and mortality. The mechanisms leading to preeclampsia are unclear; however, there is evidence that preeclampsia is highly heritable. We evaluated the association of polygenic risk scores (PRS) for blood pressure traits and preeclampsia to assess whether there is shared genetic architecture.

Methods

Participants were obtained from Vanderbilt University's BioVU, the Electronic Medical Records and Genomics network, and the Penn Medicine Biobank. Non-Hispanic Black and White females of reproductive age with indications of pregnancy and genotype information were included. Preeclampsia was defined by ICD codes. Summary statistics for diastolic blood pressure (DBP), systolic blood pressure (SBP), and pulse pressure (PP) PRS were obtained from Giri et al 2019. Associations between preeclampsia and each PRS were evaluated separately by race and study population before evidence was meta-analyzed. Prediction models were developed and evaluated using 10-fold cross validation.

Results

In the 3,504 Black and 5,009 White individuals included, the rate of preeclampsia was 15.49%. The DBP and SBP PRSs were associated with preeclampsia in Whites but not Blacks. The PP PRS was significantly associated with preeclampsia in Blacks and Whites. In trans-ancestry meta-analysis, all PRSs were associated with preeclampsia (OR DBP =1.10, 95% CI=1.02-1.17, p =7.68×10 -3 ; OR SBP =1.16, 95% CI=1.09-1.23, p =2.23×10 -6 ; OR PP =1.14, 95% CI=1.07-1.27, p =9.86×10 -5 ). However, addition of PRSs to clinical prediction models did not improve predictive performance.

Conclusions

Genetic factors contributing to blood pressure regulation in the general population also predispose to preeclampsia.

Multi-ancestry genome- and phenome-wide association studies of diverticular disease in electronic health records with natural language processing enriched phenotyping algorithm

OBJECTIVE

Diverticular disease (DD) is one of the most prevalent conditions encountered by gastroenterologists, affecting ~50% of Americans before the age of 60. Our aim was to identify genetic risk variants and clinical phenotypes associated with DD, leveraging multiple electronic health record (EHR) data sources of 91,166 multi-ancestry participants with a Natural Language Processing (NLP) technique.

MATERIALS AND METHODS

We developed a NLP-enriched phenotyping algorithm that incorporated colonoscopy or abdominal imaging reports to identify patients with diverticulosis and diverticulitis from multicenter EHRs. We performed genome-wide association studies (GWAS) of DD in European, African and multi-ancestry participants, followed by phenome-wide association studies (PheWAS) of the risk variants to identify their potential comorbid/pleiotropic effects in clinical phenotypes.

RESULTS

Our developed algorithm showed a significant improvement in patient classification performance for DD analysis (algorithm PPVs ≥ 0.94), with up to a 3.5 fold increase in terms of the number of identified patients than the traditional method. Ancestry-stratified analyses of diverticulosis and diverticulitis of the identified subjects replicated the well-established associations between ARHGAP15 loci with DD, showing overall intensified GWAS signals in diverticulitis patients compared to diverticulosis patients. Our PheWAS analyses identified significant associations between the DD GWAS variants and circulatory system, genitourinary, and neoplastic EHR phenotypes.

DISCUSSION

As the first multi-ancestry GWAS-PheWAS study, we showcased that heterogenous EHR data can be mapped through an integrative analytical pipeline and reveal significant genotype-phenotype associations with clinical interpretation.

CONCLUSION

A systematic framework to process unstructured EHR data with NLP could advance a deep and scalable phenotyping for better patient identification and facilitate etiological investigation of a disease with multilayered data.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics

OBJECTIVE

High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach.

METHODS

This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.

RESULTS

Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.

CONCLUSIONS

This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

The power of genetic diversity in genome-wide association studies of lipids

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

Metabolomic and genetic associations with insulin resistance in pregnancy

AIMS/HYPOTHESIS

Our study aimed to integrate maternal metabolic and genetic data related to insulin sensitivity during pregnancy to provide novel insights into mechanisms underlying pregnancy-induced insulin resistance.

METHODS

Fasting and 1 h serum samples were collected from women in the Hyperglycemia and Adverse Pregnancy Outcome study who underwent an OGTT at ∼28 weeks' gestation. We obtained targeted and non-targeted metabolomics and genome-wide association data from 1600 and 4528 mothers, respectively, in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai); 1412 of the women had both metabolomics and genome-wide association data. Insulin sensitivity was calculated using a modified insulin sensitivity index that included fasting and 1 h glucose and C-peptide levels after a 75 g glucose load.

RESULTS

Per-metabolite and network analyses across the four ancestries identified numerous metabolites associated with maternal insulin sensitivity before and 1 h after a glucose load, ranging from amino acids and carbohydrates to fatty acids and lipids. Genome-wide association analyses identified 12 genetic variants in the glucokinase regulatory protein gene locus that were significantly associated with maternal insulin sensitivity, including a common functional missense mutation, rs1260326 (β = -0.2004, p = 4.67 × 10^-12 in a meta-analysis across the four ancestries). This SNP was also significantly associated with multiple fasting and 1 h metabolites during pregnancy, including fasting and 1 h triacylglycerols and 2-hydroxybutyrate and 1 h lactate, 2-ketoleucine/ketoisoleucine and palmitoleic acid. Mediation analysis suggested that 1 h palmitoleic acid contributes, in part, to the association of rs1260326 with maternal insulin sensitivity, explaining 13.7% (95% CI 4.0%, 23.3%) of the total effect.

CONCLUSIONS/INTERPRETATION

The present study demonstrates commonalities between metabolites and genetic variants associated with insulin sensitivity in the gravid and non-gravid states and provides insights into mechanisms underlying pregnancy-induced insulin resistance. Graphical abstract.

All thresholds of maternal hyperglycaemia from the WHO 2013 criteria for gestational diabetes identify women with a higher genetic risk for type 2 diabetes

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). Conclusions: The different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common, complex genetic disorder affecting up to 15% of reproductive-age women worldwide, depending on the diagnostic criteria applied. These diagnostic criteria are based on expert opinion and have been the subject of considerable controversy. The phenotypic variation observed in PCOS is suggestive of an underlying genetic heterogeneity, but a recent meta-analysis of European ancestry PCOS cases found that the genetic architecture of PCOS defined by different diagnostic criteria was generally similar, suggesting that the criteria do not identify biologically distinct disease subtypes. We performed this study to test the hypothesis that there are biologically relevant subtypes of PCOS.

METHODS AND FINDINGS

Using biochemical and genotype data from a previously published PCOS genome-wide association study (GWAS), we investigated whether there were reproducible phenotypic subtypes of PCOS with subtype-specific genetic associations. Unsupervised hierarchical cluster analysis was performed on quantitative anthropometric, reproductive, and metabolic traits in a genotyped cohort of 893 PCOS cases (median and interquartile range [IQR]: age = 28 [25-32], body mass index [BMI] = 35.4 [28.2-41.5]). The clusters were replicated in an independent, ungenotyped cohort of 263 PCOS cases (median and IQR: age = 28 [24-33], BMI = 35.7 [28.4-42.3]). The clustering revealed 2 distinct PCOS subtypes: a "reproductive" group (21%-23%), characterized by higher luteinizing hormone (LH) and sex hormone binding globulin (SHBG) levels with relatively low BMI and insulin levels, and a "metabolic" group (37%-39%), characterized by higher BMI, glucose, and insulin levels with lower SHBG and LH levels. We performed a GWAS on the genotyped cohort, limiting the cases to either the reproductive or metabolic subtypes. We identified alleles in 4 loci that were associated with the reproductive subtype at genome-wide significance (PRDM2/KAZN, P = 2.2 × 10-10; IQCA1, P = 2.8 × 10-9; BMPR1B/UNC5C, P = 9.7 × 10-9; CDH10, P = 1.2 × 10-8) and one locus that was significantly associated with the metabolic subtype (KCNH7/FIGN, P = 1.0 × 10-8). We developed a predictive model to classify a separate, family-based cohort of 73 women with PCOS (median and IQR: age = 28 [25-33], BMI = 34.3 [27.8-42.3]) and found that the subtypes tended to cluster in families and that carriers of previously reported rare variants in DENND1A, a gene that regulates androgen biosynthesis, were significantly more likely to have the reproductive subtype of PCOS. Limitations of our study were that only PCOS cases of European ancestry diagnosed by National Institutes of Health (NIH) criteria were included, the sample sizes for the subtype GWAS were small, and the GWAS findings were not replicated.

CONCLUSIONS

In conclusion, we have found reproducible reproductive and metabolic subtypes of PCOS. Furthermore, these subtypes were associated with novel, to our knowledge, susceptibility loci. Our results suggest that these subtypes are biologically relevant because they appear to have distinct genetic architecture. This study demonstrates how phenotypic subtyping can be used to gain additional insights from GWAS data.

A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies

CONTEXT

As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice.

OBJECTIVE

Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment.

DESIGN, PATIENTS, AND METHODS

Leveraging the electronic health records (EHRs) of 124 852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS.

RESULTS

The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity", "type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension", and "sleep apnea" reaching phenome-wide significance.

CONCLUSIONS

Our study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome-phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.

Publisher Correction: Genome-wide association of polycystic ovary syndrome implicates alterations in gonadotropin secretion in European ancestry populations

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization

BACKGROUND

The extent to which obesity and genetics determine postoperative complications is incompletely understood.

METHODS

We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components.

RESULTS

Individuals with overweight or obese BMI (≥25 kg/m2) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10-20), and people with obesity (BMI ≥ 30 kg/m2) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10-5). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10-6) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10-6). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures.

CONCLUSIONS

Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.

Hyperandrogenemia is Common in Asymptomatic Women and is Associated with Increased Metabolic Risk

OBJECTIVE

Women with metabolic syndrome (MetS) have higher endogenous testosterone (T) levels than unaffected women. This study investigated whether hyperandrogenemia (HA) was a marker for increased cardiometabolic risk in reproductively normal premenopausal women.

METHODS

Reproductive hormones and metabolic parameters were assessed in 198 women with regular menses and no clinical hyperandrogenism (eumenorrheic [EM]). Hyperandrogenic EM women were compared with 110 women with NIH criteria polycystic ovary syndrome.

RESULTS

Twenty-two percent of EM women had HA. Levels of non-sex hormone-binding globulin (SHBG)-bound T were elevated in 68% of women, total T levels were elevated in 43% of women, and dehydroepiandrosterone sulfate levels were elevated in 30% of women. The prevalence of HA increased with BMI category (P = 0.01): 12% for BMI < 25 kg/m2 , 22% for BMI of 25 to 30 kg/m2 , and 31% for BMI ≥ 30 kg/m2 . MetS (adjusted odds ratio 2.9; 95% CI: 1.2-6.9) and dysglycemia risks (adjusted odds ratio 2.7; 95% CI: 1.2-5.8) were increased in hyperandrogenic EM women compared with normoandrogenic EM women, with adjustment for BMI. SHBG levels were independently associated with these metabolic end points (P < 0.001), whereas androgen levels were not. A cluster analysis confirmed that there was a discrete subset of EM women with HA and metabolic abnormalities.

CONCLUSIONS

HA is common in EM women and is associated with increased risks for MetS and dysglycemia. However, low SHBG levels rather than elevated androgen levels may be the primary predictor of this relationship with metabolic dysfunction.

Testing for paternal influences on offspring telomere length in a human cohort in the Philippines

OBJECTIVES

Telomeres, emerging biomarkers of aging, are comprised of DNA repeats located at chromosomal ends that shorten with cellular replication and age in most human tissues. In contrast, spermatocyte telomeres lengthen with age. These changes in telomere length (TL) appear to be heritable, as older paternal ages of conception (PAC) predict longer offspring TL. Mouse-model studies raise questions about the potential for effects of paternal experiences on human offspring TL, as they suggest that smoking, inflammation, DNA damage, and stressors all shorten sperm TL. Here, we examined whether factors from the paternal environment predict offspring TL as well as interact with PAC to predict offspring TL.

MATERIALS AND METHODS

Using data from the Philippines, we tested if smoking, psychosocial stressors, or shorter knee height (a measure of early life adversity) predict shorter offspring TL. We also tested if these interacted with PAC in predicting offspring TL.

RESULTS

While we did not find the predicted associations, we observed a trend toward fathers with shorter knee height having offspring with longer TL. In addition, we found that knee height interacted with PAC to predict offspring TL. Specifically, fathers with shorter knee heights showed a stronger positive effect of PAC on offspring TL.

DISCUSSION

While the reasons for these associations remain uncertain, shorter knee height is characteristic of earlier puberty. Since spermatocyte TL increases with the production of sperm, we speculate that individuals with earlier puberty, and its concomitant commencement of production of sperm, had more time to accumulate longer sperm telomeres.

Using Polygenic Scores in Social Science Research: Unraveling Childlessness

Biological, genetic, and socio-demographic factors are all important in explaining reproductive behavior, yet these factors are typically studied in isolation. In this study, we explore an innovative sociogenomic approach, which entails including key socio-demographic (marriage, education, occupation, religion, cohort) and genetic factors related to both behavioral [age at first birth (AFB), number of children ever born (NEB)] and biological fecundity-related outcomes (endometriosis, age at menopause and menarche, polycystic ovary syndrome, azoospermia, testicular dysgenesis syndrome) to explain childlessness. We examine the association of all sets of factors with childlessness as well as the interplay between them. We derive polygenic scores (PGS) from recent genome-wide association studies (GWAS) and apply these in the Health and Retirement Study (N = 10,686) and Wisconsin Longitudinal Study (N = 8,284). Both socio-demographic and genetic factors were associated with childlessness. Whilst socio-demographic factors explain 19-46% in childlessness, the current PGS explains <1% of the variance, and only PGSs from large GWASs are related to childlessness. Our findings also indicate that genetic and socio-demographic factors are not independent, with PGSs for AFB and NEB related to education and age at marriage. The explained variance by polygenic scores on childlessness is limited since it is largely a behavioral trait, with genetic explanations expected to increase somewhat in the future with better-powered GWASs. As genotyping of individuals in social science surveys becomes more prevalent, the method described in this study can be applied to other outcomes.

Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Variants in the fetal genome near pro-inflammatory cytokine genes on 2q13 associate with gestational duration

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10⁻¹⁴). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.

Gestational duration depends on both maternal and fetal genetic influences. Here, the authors perform a fetal genome-wide association meta-analysis and find that a locus on 2q13 is associated with pregnancy duration and further show that the lead SNP rs7594852 changes the binding properties of transcriptional repressor HIC1.

Early life growth and adult telomere length in a Filipino cohort study

OBJECTIVE

We investigated the relationship between early life growth patterns and blood telomere length (TL) in adulthood using conditional measures of lean and fat mass growth to evaluate potentially sensitive periods of early life growth.

METHODS

This study included data from 1562 individuals (53% male; age 20-22 years) participating in the Cebu Longitudinal Health and Nutrition Survey, located in metropolitan Cebu, Philippines. Primary exposures included length-for-age z-score (HAZ) and weight-for-age z-score (WAZ) at birth and conditional measures of linear growth and weight gain during four postnatal periods: 0-6, 6-12, and 12-24 months, and 24 months to 8.5 years. TL was measured at ~21 years of age. We estimated associations using linear regression.

RESULTS

The study sample had an average gestational age (38.5 ± 2 weeks) and birth size (HAZ = -0.2 ± 1.1, WAZ = -0.7 ± 1.0), but by age 8.5 years had stunted linear growth (HAZ = -2.1 ± 0.9) and borderline low weight (WAZ = -1.9 ± 1.0) relative to World Health Organization references. Heavier birth weight was associated with longer TL in early adulthood (P = .03), but this association was attenuated when maternal age at birth was included in the model (P = .07). Accelerated linear growth between 6 and 12 months was associated with longer TL in adulthood (P = .006), whereas weight gain between 12 and 24 months was associated with shorter TL in adulthood (P = .047).

CONCLUSIONS

In Cebu, individuals who were born heavier have longer TL in early adulthood, but that birthweight itself may not explain the association. Findings suggest that childhood growth is associated with the cellular senescence process in adulthood, implying early life well-being may be linked to adult health.

Bayesian estimation of genetic regulatory effects in high-throughput reporter assays

MOTIVATION

High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA.

RESULTS

We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters.

AVAILABILITY AND IMPLEMENTATION

The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functional Genetic Variation in the Anti-Müllerian Hormone Pathway in Women With Polycystic Ovary Syndrome

CONTEXT

Polycystic ovary syndrome (PCOS) is a highly heritable, common endocrine disorder characterized by hyperandrogenism, irregular menses, and polycystic ovaries. PCOS is often accompanied by elevated levels of anti-Müllerian hormone (AMH). AMH inhibits follicle maturation. AMH also inhibits steroidogenesis through transcriptional repression of CYP17A1. We recently identified 16 rare PCOS-specific pathogenic variants in AMH.

OBJECTIVE

To test whether additional members of the AMH signaling pathway also contribute to the etiology of PCOS.

PARTICIPANTS/DESIGN

Targeted resequencing of coding and regulatory regions of AMH and its specific type 2 receptor, AMHR2, was performed on 608 women affected with PCOS and 142 reproductively normal control women. Prediction tools of deleteriousness and in silico evidence of epigenetic modification were used to prioritize variants for functional evaluation. Dual-luciferase reporter assays and splicing assays were used to measure the impact of genetic variants on function.

RESULTS

We identified 20 additional variants in/near AMH and AMHR2 with significantly reduced signaling activity in in vitro assays. Collectively, from our previous study and as reported herein, we have identified a total of 37 variants with impaired activity in/near AMH and AMHR2 in 41 women affected with PCOS, or 6.7% of our PCOS cohort. Furthermore, no functional variants were observed in the 142 phenotyped controls. The functional variants were significantly associated with PCOS in our cohort of 608 women with PCOS and 142 controls (P = 2.3 × 10-5) and very strongly associated with PCOS relative to a larger non-Finnish European (gnomAD) population-based control cohort (P < 1 × 10-9).

CONCLUSION

The AMH signaling cascade plays an important role in PCOS etiology.

Palaeo-Eskimo genetic ancestry and the peopling of Chukotka and North America

Much of the American Arctic was first settled 5,000 years ago, by groups of people known as Palaeo-Eskimos. They were subsequently joined and largely displaced around 1,000 years ago by ancestors of the present-day Inuit and Yup'ik1-3. The genetic relationship between Palaeo-Eskimos and Native American, Inuit, Yup'ik and Aleut populations remains uncertain4-6. Here we present genomic data for 48 ancient individuals from Chukotka, East Siberia, the Aleutian Islands, Alaska, and the Canadian Arctic. We co-analyse these data with data from present-day Alaskan Iñupiat and West Siberian populations and published genomes. Using methods based on rare-allele and haplotype sharing, as well as established techniques4,7-9, we show that Palaeo-Eskimo-related ancestry is ubiquitous among people who speak Na-Dene and Eskimo-Aleut languages. We develop a comprehensive model for the Holocene peopling events of Chukotka and North America, and show that Na-Dene-speaking peoples, people of the Aleutian Islands, and Yup'ik and Inuit across the Arctic region all share ancestry from a single Palaeo-Eskimo-related Siberian source.

Older paternal ages and grandpaternal ages at conception predict longer telomeres in human descendants

Telomere length (TL) declines with age in most human tissues, and shorter TL appears to accelerate senescence. By contrast, men's sperm TL is positively correlated with age. Correspondingly, in humans, older paternal age at conception (PAC) predicts longer offspring TL. We have hypothesized that this PAC effect could persist across multiple generations, and thereby contribute to a transgenerational genetic plasticity that increases expenditures on somatic maintenance as the average age at reproduction is delayed within a lineage. Here, we examine TL data from 3282 humans together with PAC data across four generations. In this sample, the PAC effect is detectable in children and grandchildren. The PAC effect is transmitted through the matriline and patriline with similar strength and is characterized by a generational decay. PACs of more distant male ancestors were not significant predictors, although statistical power was limited in these analyses. Sensitivity analyses suggest that the PAC effect is linear, not moderated by offspring age, or maternal age, and is robust to controls for income, urbanicity and ancestry. These findings show that TL reflects the age at the reproduction of recent male matrilineal and patrilineal ancestors, with an effect that decays across generations.

Comparing signals of natural selection between three Indigenous North American populations

While many studies have highlighted human adaptations to diverse environments worldwide, genomic studies of natural selection in Indigenous populations in the Americas have been absent from this literature until very recently. Since humans first entered the Americas some 20,000 years ago, they have settled in many new environments across the continent. This diversity of environments has placed variable selective pressures on the populations living in each region, but the effects of these pressures have not been extensively studied to date. To help fill this gap, we collected genome-wide data from three Indigenous North American populations from different geographic regions of the continent (Alaska, southeastern United States, and central Mexico). We identified signals of natural selection in each population and compared signals across populations to explore the differences in selective pressures among the three regions sampled. We find evidence of adaptation to cold and high-latitude environments in Alaska, while in the southeastern United States and central Mexico, pathogenic environments seem to have created important selective pressures. This study lays the foundation for additional functional and phenotypic work on possible adaptations to varied environments during the history of population diversification in the Americas.

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Family-based quantitative trait meta-analysis implicates rare noncoding variants in DENND1A in polycystic ovary syndrome

CONTEXT

Polycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5-15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date.

OBJECTIVE

The objective of this study was to test whether rare genetic variants contribute to PCOS pathogenesis.Design, Patients, and Methods: We performed whole-genome sequencing on DNA from 261 individuals from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis.

RESULTS

We found rare variants in DENND1A (P=5.31×10-5, Padj=0.039) that were significantly associated with reproductive and metabolic traits in PCOS families.

CONCLUSIONS

Common variants in DENND1A have previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated that DENND1A is an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence that DENND1A plays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.

Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10⁻⁸. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype

The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome‐wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single‐nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA‐B herpes zoster (shingles) association and discovered a novel zoster‐associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29).

Lifetime socioeconomic status and early life microbial environments predict adult blood telomere length in the Philippines

OBJECTIVES

Psychosocial stress is postulated to hasten senescence in part by accelerating the shortening of telomere length (TL). One pathway through which this may happen is via increasing inflammation and innate immune system activation-a pathway which recent studies suggest acts more strongly for those who grew up in low microbial environments. Thus, we hypothesized that: (1) Psychosocial stress will be inversely associated with TL, (2) early life microbial environments will predict TL, and (3) microbial environments will moderate the association between psychosocial stress and TL.

METHODS

We utilized data from the Cebu Longitudinal Health and Nutrition Survey based in the Philippines (N = 1410). We determined early life microbial environments by season of birth and exposure to animal feces. Psychosocial stress measures included perceived stress in adulthood, lifetime socioeconomic status (SES), and parental instability in childhood. TL was measured in blood from young adults by qPCR.

RESULTS

Contrary to predictions, we found that higher SES was associated with shorter TL and no association of TL with the other stress variables. Individuals born in the higher microbial exposure season had shorter TL, but early life microbial environments did not moderate the association between psychosocial stress and TL.

CONCLUSIONS

The unexpected inverse association between SES and TL suggests that higher SES, while indexing lower psychosocial stress, may impact TL more strongly through nonstress factors in the Philippines, such as unhealthy behavior. The inverse association between microbial environments and TL is consistent with other evidence connecting early life infections to decreased life expectancies.

Reproduction predicts shorter telomeres and epigenetic age acceleration among young adult women

Evolutionary theory predicts that reproduction entails costs that detract from somatic maintenance, accelerating biological aging. Despite support from studies in human and non-human animals, mechanisms linking 'costs of reproduction' (CoR) to aging are poorly understood. Human pregnancy is characterized by major alterations in metabolic regulation, oxidative stress, and immune cell proliferation. We hypothesized that these adaptations could accelerate blood-derived cellular aging. To test this hypothesis, we examined gravidity in relation to telomere length (TL, n = 821) and DNA-methylation age (DNAmAge, n = 397) in a cohort of young (20-22 year-old) Filipino women. Age-corrected TL and accelerated DNAmAge both predict age-related morbidity and mortality, and provide markers of mitotic and non-mitotic cellular aging, respectively. Consistent with theoretical predictions, TL decreased (p = 0.031) and DNAmAge increased (p = 0.007) with gravidity, a relationship that was not contingent upon resource availability. Neither biomarker was associated with subsequent fertility (both p > 0.3), broadly consistent with a causal effect of gravidity on cellular aging. Our findings provide evidence that reproduction in women carries costs in the form of accelerated aging through two independent cellular pathways.

Pathogenic Anti-Müllerian Hormone Variants in Polycystic Ovary Syndrome

CONTEXT

Polycystic ovary syndrome (PCOS), a common endocrine condition, is the leading cause of anovulatory infertility.

OBJECTIVE

Given that common disease-susceptibility variants account for only a small percentage of the estimated PCOS heritability, we tested the hypothesis that rare variants contribute to this deficit in heritability.

DESIGN, SETTING, AND PARTICIPANTS

Unbiased whole-genome sequencing (WGS) of 80 patients with PCOS and 24 reproductively normal control subjects identified potentially deleterious variants in AMH, the gene encoding anti-Müllerian hormone (AMH). Targeted sequencing of AMH of 643 patients with PCOS and 153 control patients was used to replicate WGS findings.

MAIN OUTCOME MEASURES

Dual luciferase reporter assays measured the impact of the variants on downstream AMH signaling.

RESULTS

We found 24 rare (minor allele frequency < 0.01) AMH variants in patients with PCOS and control subjects; 18 variants were specific to women with PCOS. Seventeen of 18 (94%) PCOS-specific variants had significantly reduced AMH signaling, whereas none of 6 variants observed in control subjects showed significant defects in signaling. Thus, we identified rare AMH coding variants that reduced AMH-mediated signaling in a subset of patients with PCOS.

CONCLUSION

To our knowledge, this study is the first to identify rare genetic variants associated with a common PCOS phenotype. Our findings suggest decreased AMH signaling as a mechanism for the pathogenesis of PCOS. AMH decreases androgen biosynthesis by inhibiting CYP17 activity; a potential mechanism of action for AMH variants in PCOS, therefore, is to increase androgen biosynthesis due to decreased AMH-mediated inhibition of CYP17 activity.

Apolipoprotein L1 Variants and Blood Pressure Traits in African Americans

BACKGROUND

African Americans (AA) are disproportionately affected by hypertension-related health disparities. Apolipoprotein L1 (APOL1) risk variants are associated with kidney disease in hypertensive AAs.

OBJECTIVES

This study assessed the APOL1 risk alleles' association with blood pressure traits in AAs.

METHODS

The discovery cohort included 5,204 AA participants from Mount Sinai's BioMe biobank. Replication cohorts included additional BioMe (n = 1,623), Vanderbilt BioVU (n = 1,809), and Northwestern NUgene (n = 567) AA biobank participants. Single nucleotide polymorphisms determining APOL1 G1 and G2 risk alleles were genotyped in BioMe and imputed in BioVU/NUgene participants. APOL1 risk alleles' association with blood pressure-related traits was tested in the discovery cohort, a meta-analysis of replication cohorts, and a combined meta-analysis under recessive and additive models after adjusting for age, sex, body mass index, and estimated glomerular filtration rate.

RESULTS

There were 14% to 16% of APOL1 variant allele homozygotes (2 copies of G1/G2) across cohorts. APOL1 risk alleles were associated under an additive model with systolic blood pressure (SBP) and age at diagnosis of hypertension, which was 2 to 5 years younger in the APOL1 variant allele homozygotes (Cox proportional hazards analysis, p value for combined meta-analysis [p_com] = 1.9 × 10^-5). APOL1 risk alleles were associated with overall SBP (p_com = 7.0 × 10^-8) and diastolic blood pressure (p_com = 2.8 × 10^-4). After adjustment for all covariates, those in the 20- to 29-year age range showed an increase in SBP of 0.94 ± 0.44 mm Hg (p_com = 0.01) per risk variant copy. APOL1-associated estimated glomerular filtration rate decline was observed starting a decade later in life in the 30- to 39-year age range.

CONCLUSIONS

APOL1 risk alleles are associated with higher SBP and earlier hypertension diagnoses in young AAs; this relationship appears to follow an additive model.

Genetic determinants of adiponectin regulation revealed by pregnancy

OBJECTIVE

This study investigated genetic determinants of adiponectin during pregnancy to reveal novel biology of adipocyte regulation.

METHODS

A genome-wide association study was conducted in 1,322 pregnant women from the Hyperglycemia and Adverse Pregnancy Outcome Study with adiponectin measured at ∼28 weeks of gestation. Variants reaching P < 5×10^-5 for de novo genotyping in two replication cohorts (Genetics of Glycemic regulation in Gestation and Growth N = 522; ECOGENE-21 N = 174) were selected.

RESULTS

In the combined meta-analysis, the maternal T allele of rs900400 located on chr3q25 (near LEKR1/CCNL1) was associated with lower maternal adiponectin (β ± standard error [SE] = -0.18 ± 0.03 standard deviation [SD] of adiponectin per risk allele; P = 1.5 ×10^-8 ; N = 2,004; multivariable adjusted models). In contrast, rs900400 showed only nominal association with adiponectin in a large sample of nonpregnant women (β ± SE = -0.012 ± 0.006; P = 0.05; N = 16,678 women from the ADIPOgen consortium). The offspring rs900400 T risk allele was associated with greater neonatal skinfold thickness (β ±SE = 0.19 ± 0.04 SD per risk allele; P = 4.1×10^-8 ; N = 1,489) and higher cord blood leptin (β ± SE = 0.28 ± 0.05 log-leptin per risk allele; P = 8.2 ×10^-9 ; N = 502), but not with cord blood adiponectin (P = 0.23; N = 495). The T allele of rs900400 was associated with higher expression of TIPARP in adipocytes.

CONCLUSIONS

These investigations of adipokines during pregnancy and early life suggest that rs900400 has a role in adipocyte function.

Associations between a fetal imprinted gene allele score and late pregnancy maternal glucose concentrations

Aim

We hypothesised that some of the genetic risk for gestational diabetes (GDM) is due to the fetal genome affecting maternal glucose concentrations. Previously, we found associations between fetal IGF2 gene variants and maternal glucose concentrations in late pregnancy.

Methods

In the present study, we tested associations between SNP alleles from 15 fetal imprinted genes and maternal glucose concentrations in late pregnancy in the Cambridge Baby Growth and Wellbeing cohorts (1160 DNA trios).

Results

Four fetal SNP alleles with the strongest univariate associations: paternally-transmitted IGF2 rs10770125 (P-value = 2 × 10^–4) and INS rs2585 (P-value = 7 × 10^–4), and maternally-transmitted KCNQ1(OT1) rs231841 (P-value = 1 × 10^–3) and KCNQ1(OT1) rs7929804 (P-value = 4 × 10^–3), were used to construct a composite fetal imprinted gene allele score which was associated with maternal glucose concentrations (P-value = 4.3 × 10^–6, n = 981, r² = 2.0%) and GDM prevalence (odds ratio per allele 1.44 (1.15, 1.80), P-value = 1 × 10^–3, n = 89 cases and 899 controls). Meta-analysis of the associations including data from 1367 Hyperglycaemia and Adverse Pregnancy Outcome Study participants confirmed the paternally-transmitted fetal IGF2/INS SNP associations (rs10770125, P-value = 3.2 × 10^–8, rs2585, P-value = 3.6 × 10^–5) and the composite fetal imprinted gene allele score association (P-value = 1.3 × 10^–8), but not the maternally-transmitted fetal KCNQ1(OT1) associations (rs231841, P-value = 0.4; rs7929804, P-value = 0.2).

Conclusion

This study suggests that polymorphic variation in fetal imprinted genes, particularly in the IGF2/INS region, contribute a small but significant part to the risk of raised late pregnancy maternal glucose concentrations.

Genome-wide study of resistant hypertension identified from electronic health records

Resistant hypertension is defined as high blood pressure that remains above treatment goals in spite of the concurrent use of three antihypertensive agents from different classes. Despite the important health consequences of resistant hypertension, few studies of resistant hypertension have been conducted. To perform a genome-wide association study for resistant hypertension, we defined and identified cases of resistant hypertension and hypertensives with treated, controlled hypertension among >47,500 adults residing in the US linked to electronic health records (EHRs) and genotyped as part of the electronic MEdical Records & GEnomics (eMERGE) Network. Electronic selection logic using billing codes, laboratory values, text queries, and medication records was used to identify resistant hypertension cases and controls at each site, and a total of 3,006 cases of resistant hypertension and 876 controlled hypertensives were identified among eMERGE Phase I and II sites. After imputation and quality control, a total of 2,530,150 SNPs were tested for an association among 2,830 multi-ethnic cases of resistant hypertension and 876 controlled hypertensives. No test of association was genome-wide significant in the full dataset or in the dataset limited to European American cases (n = 1,719) and controls (n = 708). The most significant finding was CLNK rs13144136 at p = 1.00x10^-6 (odds ratio = 0.68; 95% CI = 0.58–0.80) in the full dataset with similar results in the European American only dataset. We also examined whether SNPs known to influence blood pressure or hypertension also influenced resistant hypertension. None was significant after correction for multiple testing. These data highlight both the difficulties and the potential utility of EHR-linked genomic data to study clinically-relevant traits such as resistant hypertension.

Early life infection, but not breastfeeding, predicts adult blood telomere lengths in the Philippines

OBJECTIVES

Telomeres are repetitive DNA at chromosomes ends that shorten with age due to cellular replication and oxidative stress. As telomeres shorten, this can eventually place limits on cell replication and contribute to senescence. Infections are common during early development and activate cellular immune responses that involve clonal expansion and oxidative stress. As such, a high infectious disease burden might shorten blood telomere length (BTL) and accelerate the pace of immune senescence.

METHODS

To test this, BTL measured in young adults (21.7 ± 0.3 years old) from the Philippines (N = 1,759) were linked to prospectively collected early life data on infectious burden.

RESULTS

As predicted, increased early life diarrheal prevalence was associated with shorter adult BTL. The association was most marked for infections experienced from 6 to 12 months, which corresponds with weaning and maximal diarrheal burden. A standard deviation increase in infections at 6-12 m predicts a 45 bp decrease in BTL, equivalent to 3.3 years of adult telomeric aging in this population. Contrary to expectations, breastfeeding duration was not associated with BTL, nor did effects vary by sex.

CONCLUSIONS

These findings show that infancy diarrheal disease predicts a marker of cellular aging in adult immune cells. These findings suggest that early life infectious burden may influence late life health, or alternatively, that short TL in early life increases infectious disease susceptibility.

The role of testosterone in coordinating male life history strategies: The moderating effects of the androgen receptor CAG repeat polymorphism

Partnered fathers often have lower testosterone than single non-parents, which is theorized to relate to elevated testosterone (T) facilitating competitive behaviors and lower T contributing to nurturing. Cultural- and individual-factors moderate the expression of such psychobiological profiles. Less is known about genetic variation's role in individual psychobiological responses to partnering and fathering, particularly as related to T. We examined the exon 1 CAG (polyglutamine) repeat (CAGn) within the androgen receptor (AR) gene. AR CAGn shapes T's effects after it binds to AR by affecting AR transcriptional activity. Thus, this polymorphism is a strong candidate to influence individual-level profiles of "androgenicity." While males with a highly androgenic profile are expected to engage in a more competitive-oriented life history strategy, low androgenic men are at increased risk of depression, which could lead to similar outcomes for certain familial dynamics, such as marriage stability and parenting. Here, in a large longitudinal study of Filipino men (n=683), we found that men who had high androgenicity (elevated T and shorter CAGn) or low androgenicity (lower T and longer CAGn) showed elevated likelihood of relationship instability over the 4.5-year study period and were also more likely be relatively uninvolved with childcare as fathers. We did not find that CAGn moderated men's T responses to the fatherhood transition. In total, our results provide evidence for invested fathering and relationship stability at intermediate levels of androgenicity and help inform our understanding of variation in male reproductive strategies and the individual hormonal and genetic differences that underlie it.

Atopic Dermatitis Susceptibility Variants in Filaggrin Hitchhike Hornerin Selective Sweep

Human skin has evolved rapidly, leaving evolutionary signatures in the genome. The filaggrin (FLG) gene is widely studied for its skin-barrier function in humans. The extensive genetic variation in this gene, especially common loss-of-function (LoF) mutations, has been established as primary risk factors for atopic dermatitis. To investigate the evolution of this gene, we analyzed 2,504 human genomes and genotyped the copy number variation of filaggrin repeats within FLG in 126 individuals from diverse ancestral backgrounds. We were unable to replicate a recent study claiming that LoF of FLG is adaptive in northern latitudes with lower ultraviolet light exposure. Instead, we present multiple lines of evidence suggesting that FLG genetic variation, including LoF variants, have little or no effect on fitness in modern humans. Haplotype-level scrutinization of the locus revealed signatures of a recent selective sweep in Asia, which increased the allele frequency of a haplotype group (Huxian haplogroup) in Asian populations. Functionally, we found that the Huxian haplogroup carries dozens of functional variants in FLG and hornerin (HRNR) genes, including those that are associated with atopic dermatitis susceptibility, HRNR expression levels and microbiome diversity on the skin. Our results suggest that the target of the adaptive sweep is HRNR gene function, and the functional FLG variants that involve susceptibility to atopic dermatitis, seem to hitchhike the selective sweep on HRNR. Our study presents a novel case of a locus that harbors clinically relevant common genetic variation with complex evolutionary trajectories.