Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci

Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants

The National Lung Matrix Trial: translating the biology of stratification in advanced non-small-cell lung cancer

© The Author 2015.Background: The management of NSCLC has been transformed by stratified medicine. The National Lung Matrix Trial (NLMT) is a UK-wide study exploring the activity of rationally selected biomarker/targeted therapy combinations. Patients and methods: The Cancer Research UK (CRUK) Stratified Medicine Programme 2 is undertaking the large volume national molecular pre-screening which integrates with the NLMT. At study initiation, there are eight drugs being used to target 18 molecular cohorts. The aim is to determine whether there is sufficient signal of activity in any drug-biomarker combination to warrant further investigation. A Bayesian adaptive design that gives a more realistic approach to decision making and flexibility to make conclusions without fixing the sample size was chosen. The screening platform is an adaptable 28-gene Nextera next-generation sequencing platform designed by Illumina, covering the range of molecular abnormalities being targeted. The adaptive design allows new biomarker-drug combination cohorts to be incorporated by substantial amendment. The pre-clinical justification for each biomarker-drug combination has been rigorously assessed creating molecular exclusion rules and a trumping strategy in patients harbouring concomitant actionable genetic abnormalities. Discrete routes of pathway activation or inactivation determined by cancer genome aberrations are treated as separate cohorts. Key translational analyses include the deep genomic analysis of pre- and post-treatment biopsies, the establishment of patient-derived xenograft models and longitudinal ctDNA collection, in order to define predictive biomarkers, mechanisms of resistance and early markers of response and relapse. Conclusion: The SMP2 platform will provide large scale genetic screening to inform entry into the NLMT, a trial explicitly aimed at discovering novel actionable cohorts in NSCLC

Genomic insights into the origin of farming in the ancient Near East

We report genome-wide ancient DNA from 44 ancient Near Easterners ranging in time between ~12,000 and 1,400 BC, from Natufian hunter–gatherers to Bronze Age farmers. We show that the earliest populations of the Near East derived around half their ancestry from a ‘Basal Eurasian’ lineage that had little if any Neanderthal admixture and that separated from other non-African lineages before their separation from each other. The first farmers of the southern Levant (Israel and Jordan) and Zagros Mountains (Iran) were strongly genetically differentiated, and each descended from local hunter–gatherers. By the time of the Bronze Age, these two populations and Anatolian-related farmers had mixed with each other and with the hunter–gatherers of Europe to greatly reduce genetic differentiation. The impact of the Near Eastern farmers extended beyond the Near East: farmers related to those of Anatolia spread westward into Europe; farmers related to those of the Levant spread southward into East Africa; farmers related to those of Iran spread northward into the Eurasian steppe; and people related to both the early farmers of Iran and to the pastoralists of the Eurasian steppe spread eastward into South Asia

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease