Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies.

Objective: Congenital hyperinsulinism (CHI) is the most frequent cause of severe and persistent hypoglycaemia from birth. Understanding the pathophysiology and genetic defects behind hyperinsulinism and its complications provides clues to timely diagnosis and management. The aim of this study was to evaluate the underlying genetic aetiology of a specific Iranian pediatric cohort with CHI.

Methods: A total of 44 unrelated children, 20 girls and 24 boys, with an initial diagnosis or history of CHI from all regions of Iran were recruited between 2016 and 2019. Targeted next generation sequencing (tNGS) was performed for the genes found in about half of CHI patients.

Results: Mutations were identified in 24 cases (55%). Patients with a confirmed genetic cause were mainly diagnosed below age of one year old (p=0.01), had fewer other syndromic features, excluding seizure, (p=0.03), were less diazoxide responsive (p=0.04) and were more diazoxide unresponsive leading to pancreatectomy (p=0.007) compared to those with no identified mutations. Among 24 patients with identified genetic mutations, 17 (71%) had a mutation in ABCC8, 3 (12%) in KCNJ11, 3 (12%) in HADH, and 1 patient had a mutation in KMT2D. These included five novel mutations in ABCC8, KCNJ11, and KMT2D.

Conclusion: This is the biggest genetic study of CHI in Iran. A high frequency of recessive forms of CHI, especially HADH mutations, in our study could be due to a high rate of consanguineous marriage. We recommend tNGS to screen for all the CHI genes.

Aims

Change in weight, HbA1c, lipids, blood pressure and cardiometabolic events over time is variable in individuals with type 2 diabetes. We hypothesized that people with a genetic predisposition to a more favourable adiposity distribution could have a less severe clinical course/progression.

Methods

We involved people with type 2 diabetes from two UK‐based cohorts: 11,914 individuals with GP follow‐up data from the UK Biobank and 723 from Salford. We generated a ‘favourable adiposity’ genetic score and conducted cross‐sectional and longitudinal studies to test its association with weight, BMI, lipids, blood pressure, medication use and risk of myocardial infarction and stroke using 15 follow‐up time points with 1‐year intervals.

Results

The ‘favourable adiposity’ genetic score was cross‐sectionally associated with higher weight (effect size per 1 standard deviation higher genetic score: 0.91kg [0.59,1.23]) and BMI (0.30kg/m2 [0.19,0.40]), but higher high‐density lipoprotein (0.02mmol/L [0.01,0.02]) and lower triglycerides (‐0.04mmol/L [‐0.07,‐0.02]) in the UK Biobank at baseline, and this pattern of association was consistent across follow‐up.

There was a trend for participants with higher ‘favourable adiposity’ genetic score to have lower risk of myocardial infarction and/or stroke (odds ratio 0.79 [0.62,1.00]) compared to those with lower score. A one standard deviation higher score was associated with lower odds of using lipid‐lowering (0.91 [0.86,0.97]) and anti‐hypertensive medication (0.95 [0.91,0.99]).

Conclusions

In individuals with type 2 diabetes, having more ‘favourable adiposity’ alleles is associated with a marginally better lipid profile long‐term and having lower odds of requiring lipid‐lowering or anti‐hypertensive medication in spite of relatively higher adiposity.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

Type 2 diabetes is more common in non‐Europeans and starts at a younger age and at lower BMI cut‐offs. This review discusses the insights from genetic studies about pathophysiological mechanisms which determine risk of disease with a focus on the role of adiposity and body fat distribution in ethnic disparity in risk of type 2 diabetes. During the past decade, genome‐wide association studies (GWAS) have identified more than 400 genetic variants associated with the risk of type 2 diabetes. The Eurocentric nature of these genetic studies has made them less effective in identifying mechanisms that make non‐Europeans more susceptible to higher risk of disease. One possible mechanism suggested by epidemiological studies is the role of ethnic difference in body fat distribution. Using genetic variants associated with an ability to store extra fat in a safe place, which is subcutaneous adipose tissue, we discuss how different ethnic groups could be genetically less susceptible to type 2 diabetes by developing a more favourable fat distribution.

Objective

Differences in the content and distribution of body fat and ectopic lipids may be responsible for ethnic variations in metabolic disease susceptibility. The aim of this study was to examine the ethnic distribution of body fat in two separate UK‐based populations.

Methods

Anthropometry and body composition were assessed in two separate UK cohorts: the Hammersmith cohort and the UK Biobank, both comprising individuals of South Asian descent (SA), individuals of Afro‐Caribbean descent (AC), and individuals of European descent (EUR). Regional adipose tissue stores and liver fat were measured by magnetic resonance techniques.

Results

The Hammersmith cohort (n = 747) had a mean (SD) age of 41.1 (14.5) years (EUR: 374 men, 240 women; SA: 68 men, 22 women; AC: 14 men, 29 women), and the UK Biobank (n = 9,533) had a mean (SD) age of 55.5 (7.5) years (EUR: 4,483 men, 4,873 women; SA: 80 men, 43 women, AC: 31 men, 25 women). Following adjustment for age and BMI, no significant differences in visceral adipose tissue or liver fat were observed between SA and EUR individuals in the either cohort.

Conclusions

Our data, consistent across two independent UK‐based cohorts, present a limited number of ethnic differences in the distribution of body fat depots associated with metabolic disease. These results suggest that the ethnic variation in susceptibility to features of the metabolic syndrome may not arise from differences in body fat.

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Background

A non-invasive method to grade the severity of steatohepatitis and liver fibrosis is magnetic resonance imaging (MRI) based corrected T1 (cT1). We aimed to identify genetic variants influencing liver cT1 and use genetics to understand mechanisms underlying liver fibroinflammatory disease and its link with other metabolic traits and diseases.

Methods

First, we performed a genome-wide association study (GWAS) in 14,440 Europeans in UK Biobank with liver cT1 measures. Second, we explored the effects of the cT1 variants on liver blood tests, and a range of metabolic traits and diseases. Third, we used Mendelian randomisation to test the causal effects of 24 predominantly metabolic traits on liver cT1 measures.

Results

We identified six independent genetic variants associated with liver cT1 that reached GWAS significance threshold (p<5x10-8). Four of the variants (rs75935921 in SLC30A10, rs13107325 in SLC39A8, rs58542926 in TM6SF2, rs738409 in PNPLA3) were also associated with elevated transaminases and had variable effects on liver fat and other metabolic traits. Insulin resistance, type 2 diabetes, non-alcoholic fatty liver and BMI were causally associated with elevated cT1 whilst favourable adiposity (instrumented by variants associated with higher adiposity but lower risk of cardiometabolic disease and lower liver fat) was found to be protective.

Conclusion

The association between two metal ion transporters and cT1 indicates an important new mechanism in steatohepatitis. Future studies are needed to determine whether interventions targeting the identified transporters might prevent liver disease in at risk individuals.

Recent developments in the field of genetics have accelerated our understanding of the aetiology of complex diseases. Type 2 diabetes mellitus and cancer are no exception, with large-scale genome-wide association studies (GWAS) facilitating exploration of the underlying pathology. Here, we discuss how genetics studies can be used to investigate the relationship between these complex diseases. Observational epidemiological studies consistently report that people with type 2 diabetes have a higher risk of several types of cancer. Indeed, type 2 diabetes and cancer share many common risk factors, such as obesity, ageing, poor diet and low levels of physical activity. However, questions remain regarding the biological mechanisms that link these two diseases. Large-scale GWAS of type 2 diabetes and cancer allow us to consider the evidence for shared genetic architecture. Several shared susceptibility genes have been identified, yet tissue specificity and direction of effect must be taken into account when considering common genetic aetiology. We also consider how GWAS, and associated techniques such as Mendelian randomisation, allow us to dissect the link between the two diseases and address questions such as ‘Does type 2 diabetes cause cancer or is the increased risk observed driven by higher adiposity or another associated metabolic feature?’