Systematic evaluation of coding variation identifies a candidate causal variant in TM6SF2 influencing total cholesterol and myocardial infarction risk

Blood lipid levels are heritable, treatable risk factors for cardiovascular disease. We systematically assessed genome-wide coding variation to identify novel lipid genes, fine-map known lipid loci, and evaluate whether low frequency variants with large effect exist. Using an exome array, we genotyped 80,137 coding variants in 5,643 Norwegians. We followed up 18 variants in 4,666 Norwegians to identify 10 loci with coding variants associated with a lipid trait (P < 5×10(−8)). One coding variant in TM6SF2 (p.Glu167Lys), residing in a GWAS locus for lipid levels, modifies total cholesterol levels and is associated with myocardial infarction. Transient overexpression and knockdown of TM6SF2 in mouse produces alteration in serum lipid profiles consistent with the association observed in humans, identifying TM6SF2 as the functional gene at a large GWAS locus previously known as NCAN/CILP2/PBX4 or 19p13. This study demonstrates that systematic assessment of coding variation can quickly point to a candidate causal gene

The impact of low-frequency and rare variants on lipid levels.

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing

Opportunities and challenges of radiotherapy for treating cancer

The past 20 years have seen dramatic changes in the delivery of radiation therapy, but the impact of radiobiology on the clinic has been far less substantial. A major consideration in the use of radiotherapy has been on how best to exploit differences between the tumour and host tissue characteristics, which in the past has been achieved empirically by radiation-dose fractionation. New advances are uncovering some of the mechanistic processes that underlie this success story. In this Review, we focus on how these processes might be targeted to improve the outcome of radiotherapy at the individual patient level. This approach would seem a more productive avenue of treatment than simply trying to increase the radiation dose delivered to the tumour