Comparison of Proteomic Assessment Methods in Multiple Cohort Studies.

Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A Cross-Sectional Analysis of Telomere Length and Sleep in the Women's Health Initiative.

Telomere length is a heritable marker of cellular age that is associated with morbidity and mortality. Poor sleep behaviors, which are also associated with adverse health events, may be related to leukocyte telomere length (LTL). We studied a subpopulation of 3,145 postmenopausal women (1,796 European-American (EA) and 1,349 African-American (AA)) enrolled in the Women's Health Initiative in 1993-1998 with data on Southern blot-measured LTL and self-reported usual sleep duration and sleep disturbance. LTL-sleep associations were analyzed separately for duration and disturbance using weighted and confounder-adjusted linear regression models in the entire sample (AAs + EAs; adjusted for race/ethnicity) and in racial/ethnic strata, since LTL differs by ancestry. After adjustment for covariates, each additional daily hour of sleep beyond 5 hours, approximately, was associated with a 27-base-pair (95% confidence interval (CI): 6, 48) longer LTL in the entire sample. Associations between sleep duration and LTL were strongest among AAs (adjusted ß = 37, 95% CI: 4, 70); a similar, nonsignificant association was observed for EAs (adjusted ß = 20, 95% CI: -7, 48). Sleep disturbance was not associated with LTL in our study. Our models did not show departure from linearity (quadratic sleep terms: P ≥ 0.55). Our results suggest that longer sleep duration is associated with longer LTL in postmenopausal women.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Genetic basis of ethnic disparities in VTE risk.

In this issue of Blood, Hernandez et al identify and replicate single-nucleotide polymorphisms on chromosome 20 (and putatively on the THBD gene for thrombomodulin) that increased the risk of venous thromboembolism (VTE) by about 2.3-fold in African Americans (AAs) in the United States.