The effects of dyslipidemia on the risk of type 2 diabetes (T2D) and related traits are not clear. We used regression models and 140 lipid-associated genetic variants to estimate associations between circulating HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), and triglycerides and T2D and related traits. Each genetic test was corrected for effects of variants on the other two lipid types and surrogates of adiposity. We used the largest data sets available: 34,840 T2D case and 114,981 control subjects from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) consortium and up to 133,010 individuals without diabetes for insulin secretion and sensitivity from the MAGIC (Meta-Analyses of Glucose and Insulin-related traits Consortium) and GENESIS (GENEticS of Insulin Sensitivity) studies. Eight of 21 associations between groups of variants and diabetes traits were significant at the nominal level, including those between genetically determined lower HDL-C (β = -0.12, P = 0.03) and T2D and genetically determined lower LDL-C (β = -0.21, P = 5 × 10(-6)) and T2D. Although some of these may represent causal associations, we discuss why caution must be used when using Mendelian randomization in the context of circulating lipid levels and diabetes traits. In conclusion, we found evidence of links between genetic variants associated with lipids and T2D, but deeper knowledge of the underlying genetic mechanisms of specific lipid variants is needed before drawing definite conclusions about causality based on Mendelian randomization methodology.

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

The objective of this study was to investigate a sudden increase in methicillin-resistant Staphylococcus aureus (MRSA) cases primarily in one maternity ward at the Center for Children's and Women's Health at Linköping University Hospital, Sweden. Approximately 300 individuals including patients, their family members, and healthcare workers were screened for MRSA. The antibiotic susceptibility was tested and isolates polymerase chain reaction (PCR)-positive for the mecA gene were spa typed. Isolates with the same antibiogram and spa type were further whole genome sequenced. Compliance to current cleaning and hygiene routines was also controlled, and environmental samples collected. The results showed that a total of 13 individuals were involved in the outbreak. It was caused by a t386 MRSA strain (ST-1, NCBI-accession AB505628) with additional resistance to erythromycin and clindamycin. All cases were epidemiologically connected to the index patient, who had recently emigrated from a high-endemic area for MRSA. With improved cleaning and better compliance to basic hygiene routines, no further cases were reported. This study demonstrates how rapid an MRSA strain can disseminate in a ward with susceptible patients and insufficient cleaning and hygiene. For a better control of MRSA, clinical cultures and screening samples need to be obtained early and more extensively than according to the current recommendations.

The patterns of reproductive timing and senescence vary within and across species owing to differences in reproductive strategies, but our understanding of the molecular underpinnings of such variation is incomplete. This is perhaps particularly true for sex differences. We investigated the evolution of sex-specific gene expression associated with life history divergence in replicated populations of the seed beetle Acanthoscelides obtectus, experimentally evolving under (E)arly or (L)ate life reproduction for >200 generations which has resulted in strongly divergent life histories. We detected 1,646 genes that were differentially expressed in E and L lines, consistent with a highly polygenic basis of life history evolution. Only 30% of differentially expressed genes were similarly affected in males and females. The evolution of long life was associated with significantly reduced sex differences in expression, especially in non-reproductive tissues. The expression differences were overall more pronounced in females, in accordance with their greater phenotypic divergence in lifespan. Functional enrichment analysis revealed differences between E and L beetles in gene categories previously implicated in aging, such as mitochondrial function and defense response. The results show that divergent life history evolution can be associated with profound changes in gene expression that alter the transcriptome in a sex-specific way, highlighting the importance of understanding the mechanisms of aging in each sex.

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole genome sequencing (WGS) and use long-read WGS for validation in a sub-cohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (p<8.22×10-10). Of these, five CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated to measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Large-scale genome-wide association studies (GWAS) have so far identified 45 loci that are robustly associated with coronary heart disease (CHD) in data from adult men and women of European descent. To examine whether the CHD-associated loci are associated with measures of atherosclerosis in data from up to 9582 individuals of European ancestry. Forty-five SNPs representing the CHD-associated loci were genotyped in middle-aged to elderly individuals of European descent from four independent population-based studies (IMPROVE, MDC-CC, ULSAM and PIVUS). Intima-media thickness (IMT) was measured by external B-mode ultrasonography at the far wall of the bulb (sinus) and common carotid artery. Plaque presence was defined as a maximal IMT of the bulb >1.5 mm. We meta-analysed single-SNP associations across the four studies, and combined them in a genetic predisposition score. We subsequently examined the association of the genetic predisposition score with prevalent CHD and the three indices of atherosclerosis, adjusting for sex, age and Framingham risk factors. As anticipated, the genetic predisposition score was associated with prevalent CHD, with each additional risk allele increasing the odds of disease by 5.5% (p = 4.1 × 10(-6)). Moreover, each additional CHD-risk allele across the 45 loci was associated with a 0.24% increase in IMT (p = 4.0 × 10(-3)), and with a 2.8% increased odds of plaque presence (p = 7.4 × 10(-6)) at the far wall of the bulb. The genetic predisposition score was not associated with IMT of the common carotid artery (p = 0.47). Our results suggest that the association between the 45 previously identified loci and CHD at least partly acts through atherosclerosis.

Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.