Professor Cecilia Lindgren
|Research Area:||Genetics and Genomics|
|Technology Exchange:||Bioinformatics, Computational biology, SNP typing and Statistical genetics|
|Scientific Themes:||Genetics & Genomics|
|Keywords:||obesity, fat distribution, meta-analysis, genetic association and gene expression|
Obesity and its consequences are major and growing challenges for health care worldwide. Recently, the first common variants have been identified which influence overall levels of adiposity and predispose to obesity at the population level: these findings should lead to improved understanding of the mechanisms involved in the regulation of overall energy balance. However, not all obese individuals are equally vulnerable to diabetes, insulin resistance and the other adverse consequences of obesity, and it has long been appreciated that the distribution of fat (particularly the degree of central or visceral obesity) is an additional and independent determinant of individual risk of metabolic and cardiovascular disease.
Our research seeks to advance understanding of the mechanisms involved in obesity and the regulation of differential central fat accumulation in the belief that an appreciation of these mechanisms will complement advances in understanding of overall energy balance.
By applying a range of genetic and genomic approaches, we expect to identify genetic variants influencing regional fat distribution, and to illuminate some of the biological pathways involved. Our specific objectives are:
- To undertake identification of genetic variants influencing obesity and individual patterns of fat distribution and central obesity through large-scale genome-wide association meta-analysis and fine-mapping;
- To examine the relationships between sequence variation, expression of mRNA, microRNAs and molecular and physiological phenotypes, in human adipose samples, to identify adipose-specific pathways relevant to individual differences in obesity and central fat distribution;
- To follow-up of the key findings from genetic, epidemiological and functional perspectives.
This knowledge should support translational advances in the management of obesity through development of novel diagnostic and therapeutic options.
There are no collaborations listed for this principal investigator.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms. Hide abstract
Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. Hide abstract
Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions. Hide abstract
To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits. Hide abstract
The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes. Hide abstract
DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments. Hide abstract
Dissection of the Genetic Susceptibility of Obesity Traits and their comorbidities
Currently ~50% of the population in the UK is overweight with a further 25-30% that are obese and the socioeconomic cost incurred by obesity and related comorbidities are high. Obesity is a heritable and heterogeneous condition that is defined as the accumulation of excess body fat to the extent that it results in long-term adverse health outcomes (type 2 diabetes mellitus, hyperlipidemia, liver steatosis, cardiovascular disease, subfertility traits and certain types of cancer etc.). This studen ...
Genomics of polycystic ovary syndrome (PCOS)
Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathies affecting 5‐15% of women of reproductive age worldwide and causes more than 75% of cases of anovulatory infertility. The precise definition is an on‐going debate among researchers in the field but PCOS is generally characterized by hyperandrogenism, chronic anovulation and glucose homeostasis. The aetiology of PCOS is largely unknown though contains a clear genetic component. However, to date, the only available PCOS gen ...