Genome-Wide Association Study on the Early-Phase Insulin Response to a Liquid Mixed Meal: Results From the NEO Study

Gene-Gene Interaction Between Factor-XI and ABO Genes in Cerebral Venous Thrombosis: The BEAST Study

BACKGROUND AND OBJECTIVES

Gene-gene interactions likely contribute to the etiology of multifactorial diseases such as cerebral venous thrombosis (CVT) and could be one of the main sources of known missing heritability. We explored Factor XI (F11) and ABO gene interactions among patients with CVT.

METHODS

Patients with CVT of European ancestry from the large Bio-Repository to Establish the Aetiology of Sinovenous Thrombosis (BEAST) international collaboration were recruited. Codominant modelling was used to determine interactions between genome-wide identified F11 and ABO genes with CVT status.

RESULTS

We studied 882 patients with CVT and 1,205 ethnically matched control participants (age: 42 ± 15 vs 43 ± 12 years, p = 0.08: sex: 71% male vs 68% female, p = 0.09, respectively). Individuals heterozygous (AT) for the risk allele (T) at both loci (rs56810541/F11 and rs8176645/ABO) had a 3.9 (95% CI 2.74-5.71, p = 2.75e-13) increase in risk of CVT. Individuals homozygous (TT) for the risk allele at both loci had a 13.9 (95% CI 7.64-26.17, p = 2.0e-15) increase in risk of CVT. The presence of a non-O blood group (A, B, AB) combined with TT/rs56810541/F11 increased CVT risk by OR = 6.8 (95% CI 4.54-10.33, p = 2.00e15), compared with blood group-O combined with AA.

DISCUSSION

Interactions between factor XI and ABO genes increase risk of CVT by 4- to 14-fold.

Prevalence of non-alcoholic fatty liver in the general Dutch population and in groups at increased risk

BACKGROUND AND AIM

Non-alcoholic fatty liver disease (NAFLD) is defined as a liver fat content ≥5.56%. It is of clinical interest to know the prevalence of NAFLD in people with a combination of metabolic risk factors. We aimed to examine the prevalence of NAFLD, including groups with metabolic risk factors.

METHODS AND RESULTS

In this cross-sectional analysis of the Netherlands Epidemiology of Obesity (NEO) study, liver fat content was assessed using proton magnetic resonance spectroscopy (H-MRS). Participants with excessive alcohol consumption or missing values were excluded, leaving a total of 1570 participants for the analyses. Mean (SD) age of the population was 55 years, BMI 25.9 (4.0) kg/m2 and 46% were men. The prevalence of NAFLD was 27% (95% CI 24-30). The prevalence of NAFLD was increased in participants with hypertriglyceridemia (57%, 52-63), obesity (62%, 58-66) and diabetes (69%, 61-77). The prevalence of NAFLD was highest in those with diabetes and obesity (79%, 71-87), obesity and hypertriglyceridemia (81%, 76-86) and with diabetes and hypertriglyceridemia (86%, 77-95). NAFLD was also present in 12% (8-16) of participants without overweight.

CONCLUSIONS

The prevalence of NAFLD in a middle-aged population in the Netherlands in 2010 was 27%. The prevalence of NAFLD is particularly increased in individuals with diabetes, obesity, and hypertriglyceridemia. This information may help clinicians and general practitioners in the risk stratification of their patients in daily practice.

Genome-wide association studies: utility and limitations for research in physiology

Physiological systems are subject to interindividual variation encoded by genetics. Genome-wide association studies (GWAS) operate by surveying thousands of genetic variants from a substantial number of individuals and assessing their association to a trait of interest, be it a physiological variable, a molecular phenotype (e.g. gene expression), or even a disease or condition. Through a myriad of methods, GWAS downstream analyses then explore the functional consequences of each variant and attempt to ascertain a causal relationship to the phenotype of interest, as well as to delve into its links to other traits. This type of investigation allows mechanistic insights into physiological functions, pathological disturbances and shared biological processes between traits (i.e. pleiotropy). An exciting example is the discovery of a new thyroid hormone transporter (SLC17A4) and hormone metabolising enzyme (AADAT) from a GWAS on free thyroxine levels. Therefore, GWAS have substantially contributed with insights into physiology and have been shown to be useful in unveiling the genetic control underlying complex traits and pathological conditions; they will continue to do so with global collaborations and advances in genotyping technology. Finally, the increasing number of trans-ancestry GWAS and initiatives to include ancestry diversity in genomics will boost the power for discoveries, making them also applicable to non-European populations.

High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease

AIMS/HYPOTHESIS

Type 2 diabetes is highly polygenic and influenced by multiple biological pathways. Rapid expansion in the number of type 2 diabetes loci can be leveraged to identify such pathways.

METHODS

We developed a high-throughput pipeline to enable clustering of type 2 diabetes loci based on variant-trait associations. Our pipeline extracted summary statistics from genome-wide association studies (GWAS) for type 2 diabetes and related traits to generate a matrix of 323 variants × 64 trait associations and applied Bayesian non-negative matrix factorisation (bNMF) to identify genetic components of type 2 diabetes. Epigenomic enrichment analysis was performed in 28 cell types and single pancreatic cells. We generated cluster-specific polygenic scores and performed regression analysis in an independent cohort (N=25,419) to assess for clinical relevance.

RESULTS

We identified ten clusters of genetic loci, recapturing the five from our prior analysis as well as novel clusters related to beta cell dysfunction, pronounced insulin secretion, and levels of alkaline phosphatase, lipoprotein A and sex hormone-binding globulin. Four clusters related to mechanisms of insulin deficiency, five to insulin resistance and one had an unclear mechanism. The clusters displayed tissue-specific epigenomic enrichment, notably with the two beta cell clusters differentially enriched in functional and stressed pancreatic beta cell states. Additionally, cluster-specific polygenic scores were differentially associated with patient clinical characteristics and outcomes. The pipeline was applied to coronary artery disease and chronic kidney disease, identifying multiple overlapping clusters with type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Our approach stratifies type 2 diabetes loci into physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes. The pipeline allows for efficient updating as additional GWAS become available and can be readily applied to other conditions, facilitating clinical translation of GWAS findings. Software to perform this clustering pipeline is freely available.

Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach

Understanding the genetic relationships between human disorders could lead to better treatment and prevention strategies, especially for individuals with multiple comorbidities. A common resource for studying genetic-disease relationships is the GWAS Catalog, a large and well curated repository of SNP-trait associations from various studies and populations. Some of these populations are contained within mega-biobanks such as the Million Veteran Program (MVP), which has enabled the genetic classification of several diseases in a large well-characterized and heterogeneous population. Here we aim to provide a network of the genetic relationships among diseases and to demonstrate the utility of quantifying the extent to which a given resource such as MVP has contributed to the discovery of such relations. We use a network-based approach to evaluate shared variants among thousands of traits in the GWAS Catalog repository. Our results indicate many more novel disease relationships that did not exist in early studies and demonstrate that the network can reveal clusters of diseases mechanistically related. Finally, we show novel disease connections that emerge when MVP data is included, highlighting methodology that can be used to indicate the contributions of a given biobank.

The Roles of Gut Microbiome and Plasma Metabolites in the Associations between ABO Blood Groups and Insulin Homeostasis: The Microbiome and Insulin Longitudinal Evaluation Study (MILES)

Non-O blood groups are associated with decreased insulin sensitivity and risk of type 2 diabetes. A recent study pinpointed the associations between ABO blood groups and gut microbiome, which may serve as potential mediators for the observed increased disease risks. We aimed to characterize associations between ABO haplotypes and insulin-related traits as well as potential mediating pathways. We assessed insulin homeostasis in African Americans (AAs; n = 109) and non-Hispanic whites (n = 210) from the Microbiome and Insulin Longitudinal Evaluation Study. The ABO haplotype was determined by six SNPs located in the ABO gene. Based on prior knowledge, we included 21 gut bacteria and 13 plasma metabolites for mediation analysis. In the white study cohort (60 ± 9 years, 42% male), compared to the O1 haplotype, A1 was associated with a higher Matsuda insulin sensitivity index, while a lower relative abundance of Bacteroides massiliensis and lactate levels. Lactate was a likely mediator of this association but not Bacteroides massiliensis. In the AAs group (57 ± 8 years, 33% male), we found no association between any haplotype and insulin-related traits. In conclusion, the A1 haplotype may promote healthy insulin sensitivity in non-Hispanic whites and lactate likely play a role in this process but not selected gut bacteria.

Connecting Genomics and Proteomics to Identify Protein Biomarkers for Adult and Youth-Onset Type 2 Diabetes: A Two-Sample Mendelian Randomization Study

Type 2 diabetes shows an increasing prevalence in both adults and children. Identification of biomarkers for both youth and adult-onset type 2 diabetes is crucial for development of screening tools or drug targets. In this study, using two-sample Mendelian randomization (MR), we identified 22 circulating proteins causally linked to adult type 2 diabetes and 11 proteins with suggestive evidence for association with youth-onset type 2 diabetes. Among these, colocalization analysis further supported a role in type 2 diabetes for C-type mannose receptor 2 (MR odds ratio [OR] 0.85 [95% CI 0.79-0.92] per genetically predicted SD increase in protein level), MANS domain containing 4 (MR OR 0.90 [95% CI 0.88-0.92]), sodium/potassium-transporting ATPase subunit β2 (MR OR 1.10 [95% CI 1.06-1.15]), endoplasmic reticulum oxidoreductase 1β (MR OR 1.09 [95% CI 1.05-1.14]), spermatogenesis-associated protein 20 (MR OR 1.12 [95% CI 1.06-1.18]), haptoglobin (MR OR 0.96 [95% CI 0.94-0.98]), and α1-3-N-acetylgalactosaminyltransferase and α1-3-galactosyltransferase (MR OR 1.04 [95% CI 1.03-1.05]). Our findings support a causal role in type 2 diabetes for a set of circulating proteins, which represent promising type 2 diabetes drug targets.

Genetic Studies of Metabolomics Change After a Liquid Meal Illuminate Novel Pathways for Glucose and Lipid Metabolism

Humans spend the greater part of the day in a postprandial state. However, the genetic basis of postprandial blood measures is relatively uncharted territory. We examined the genetics of variation in concentrations of postprandial metabolites (t = 150 min) in response to a liquid mixed meal through genome-wide association studies (GWAS) performed in the Netherlands Epidemiology of Obesity (NEO) study (n = 5,705). The metabolite response GWAS identified an association between glucose change and rs10830963:G in the melatonin receptor 1B (β [SE] -0.23 [0.03], P = 2.15 × 10^-19). In addition, the ANKRD55 locus led by rs458741:C showed strong associations with extremely large VLDL (XXLVLDL) particle response (XXLVLDL total cholesterol: β [SE] 0.17 [0.03], P = 5.76 × 10^-10; XXLVLDL cholesterol ester: β [SE] 0.17 [0.03], P = 9.74 × 10^-10), which also revealed strong associations with body composition and diabetes in the UK Biobank (P < 5 × 10^-8). Furthermore, the associations between XXLVLDL response and insulinogenic index, HOMA-β, Matsuda insulin sensitivity index, and HbA_1c in the NEO study implied the role of chylomicron synthesis in diabetes (with false discovery rate-corrected q <0.05). To conclude, genetic studies of metabolomics change after a liquid meal illuminate novel pathways for glucose and lipid metabolism. Further studies are warranted to corroborate biological pathways of the ANKRD55 locus underlying diabetes.

Genome-Wide Association Study Identifies First Locus Associated with Susceptibility to Cerebral Venous Thrombosis

OBJECTIVE

Cerebral venous thrombosis (CVT) is an uncommon form of stroke affecting mostly young individuals. Although genetic factors are thought to play a role in this cerebrovascular condition, its genetic etiology is not well understood.

METHODS

A genome-wide association study was performed to identify genetic variants influencing susceptibility to CVT. A 2-stage genome-wide study was undertaken in 882 Europeans diagnosed with CVT and 1,205 ethnicity-matched control subjects divided into discovery and independent replication datasets.

RESULTS

In the overall case-control cohort, we identified highly significant associations with 37 single nucleotide polymorphisms (SNPs) within the 9q34.2 region. The strongest association was with rs8176645 (combined p = 9.15 × 10-24 ; odds ratio [OR] = 2.01, 95% confidence interval [CI] = 1.76-2.31). The discovery set findings were validated across an independent European cohort. Genetic risk score for this 9q34.2 region increases CVT risk by a pooled estimate OR = 2.65 (95% CI = 2.21-3.20, p = 2.00 × 10-16 ). SNPs within this region were in strong linkage disequilibrium (LD) with coding regions of the ABO gene. The ABO blood group was determined using allele combination of SNPs rs8176746 and rs8176645. Blood groups A, B, or AB, were at 2.85 times (95% CI = 2.32-3.52, p = 2.00 × 10-16 ) increased risk of CVT compared with individuals with blood group O.

INTERPRETATION

We present the first chromosomal region to robustly associate with a genetic susceptibility to CVT. This region more than doubles the likelihood of CVT, a risk greater than any previously identified thrombophilia genetic risk marker. That the identified variant is in strong LD with the coding region of the ABO gene with differences in blood group prevalence provides important new insights into the pathophysiology of CVT. ANN NEUROL 2021;90:777-788.

Recent advances and current controversies in genetic testing for personalized nutrition

PURPOSE OF REVIEW

Considerable interest in personalized nutrition exists among the general public, policymakers, healthcare organizations and the private sector, but there is also skepticism of its utility. The present review aims to provide a summary of current controversies in the field of nutrigenomics, and to highlight recent research on the potential impact of implementing genetic testing for personalized nutrition in practice.

RECENT FINDINGS

Numerous companies already offer genetic testing for personalized nutrition based on research developments in nutritional genomics. However, controversy exists over whethexr genetics contributes to interindividual responses to diet; the utility of single genetic variants versus genetic risk scores; the ability of DNA-based nutritional advice to elicit positive behavior change and health effects; and whether genetic information makes a difference on the type of dietary advice provided. Potential factors contributing to the discrepant viewpoints are discussed.

SUMMARY

Despite the existing controversies, a solid body of evidence demonstrates that genetic testing for personalized nutrition is a powerful tool to guide dietary recommendations to improve health and performance, and to elicit positive behavior change.