A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.</p

Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development

The genomic landscape of 2,023 colorectal cancers

Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2–9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichiacolipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11–13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care

Trace element fingerprinting of cockle (Cerastoderma edule) shells can reveal harvesting location in adjacent areas

Determining seafood geographic origin is critical for controlling its quality and safeguarding the interest of consumers. Here, we use trace element fingerprinting (TEF) of bivalve shells to discriminate the geographic origin of specimens. Barium (Ba), manganese (Mn), magnesium (Mg), strontium (Sr) and lead (Pb) were quantified in cockle shells (Cerastoderma edule) captured with two fishing methods (by hand and by hand-raking) and from five adjacent fishing locations within an estuarine system (Ria de Aveiro, Portugal). Results suggest no differences in TEF of cockle shells captured by hand or by hand-raking, thus confirming that metal rakes do not act as a potential source of metal contamination that could somehow bias TEF results. In contrast, significant differences were recorded among locations for all trace elements analysed. A Canonical Analysis of Principal Coordinates (CAP) revealed that 92% of the samples could be successfully classified according to their fishing location using TEF. We show that TEF can be an accurate, fast and reliable method to determine the geographic origin of bivalves, even among locations separated less than 1 km apart within the same estuarine system. Nonetheless, follow up studies are needed to determine if TEF can reliably discriminate between bivalves originating from different ecosystems

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study

\ua9 The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society.Context: The role of glucagon-like peptide-1 (GLP-1) in type 2 diabetes (T2D) and obesity is not fully understood. Objective: We investigate the association of cardiometabolic, diet, and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. Methods: We analyzed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1 (n = 2127) individuals at risk of diabetes; cohort 2 (n = 789) individuals with new-onset T2D. Results: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin-resistant phenotype and observe a strong independent relationship with male sex, increased adiposity, and liver fat, particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycemia, higher adiposity, liver fat, male sex, and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit, and vegetables in people with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. Conclusion: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake, and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D

The genomic landscape of 2,023 colorectal cancers

Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2–9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichiacolipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11–13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders