Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Continuum solvation models, such as Poisson-Boltzmann and Generalized Born methods, have become increasingly popular tools for investigating the influence of electrostatics on biomolecular structure, energetics and dynamics. However, the use of such methods requires accurate and complete structural data as well as force field parameters such as atomic charges and radii. Unfortunately, the limiting step in continuum electrostatics calculations is often the addition of missing atomic coordinates to molecular structures from the Protein Data Bank and the assignment of parameters to biomolecular structures. To address this problem, we have developed the PDB2PQR web service (http://agave.wustl.edu/pdb2pqr/). This server automates many of the common tasks of preparing structures for continuum electrostatics calculations, including adding a limited number of missing heavy atoms to biomolecular structures, estimating titration states and protonating biomolecules in a manner consistent with favorable hydrogen bonding, assigning charge and radius parameters from a variety of force fields, and finally generating 'PQR' output compatible with several popular computational biology packages. This service is intended to facilitate the setup and execution of electrostatics calculations for both experts and non-experts and thereby broaden the accessibility to the biological community of continuum electrostatics analyses of biomolecular systems.

Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease.Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody-based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to ϳ80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body. Molecular & Cellular Proteomics 13: 10.1074/mcp.M113.035600, 397-406, 2014.Central questions in human biology relate to how cells, tissues, and organs differ in the expression of genes and proteins and what consequences the global expression pattern has for the phenotype of various cells with different functions in the body. Therefore, the annotation of the human protein-coding genes with regards to the spatial, temporal, and functional space represents one of the greatest challenges in human biology (1). Important questions related to this are how many of the genes actually code for functional proteins, how many are expressed in a tissue-specific manner, and how many proteins have "housekeeping" functions and are therefore expressed in all cells? These questions have a major impact not only on efforts to try to understand human biology, but also for applied medical research, such as pharmaceutical drug development and biomarker discovery in the field of translational medicine.Several efforts have been initiated in the aftermath of the genome project to systematically annotate the putative protein-coding part of the human genome. Genome annotation efforts, such as Ensembl (2) and RefSeq (3), have provided an increasingly accurate map with at present ϳ20,000 proteincoding genes. Similarly, the ENCODE consortium has been launched to provide an integrated encyclopedia of DNA eleFrom the ‡Science for Life Laboratory, KTH -Royal Institute of Technology, SE-171 21 Stockholm, Sweden; §Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden; ¶Department

AimsThe first aim was to critically evaluate the extent to which familial hypercholesterolaemia (FH) is underdiagnosed and undertreated. The second aim was to provide guidance for screening and treatment of FH, in order to prevent coronary heart disease (CHD).Methods and resultsOf the theoretical estimated prevalence of 1/500 for heterozygous FH, <1% are diagnosed in most countries. Recently, direct screening in a Northern European general population diagnosed approximately 1/200 with heterozygous FH. All reported studies document failure to achieve recommended LDL cholesterol targets in a large proportion of individuals with FH, and up to 13-fold increased risk of CHD. Based on prevalences between 1/500 and 1/200, between 14 and 34 million individuals worldwide have FH. We recommend that children, adults, and families should be screened for FH if a person or family member presents with FH, a plasma cholesterol level in an adult ≥8 mmol/L(≥310 mg/dL) or a child ≥6 mmol/L(≥230 mg/dL), premature CHD, tendon xanthomas, or sudden premature cardiac death. In FH, low-density lipoprotein cholesterol targets are <3.5 mmol/L(<135 mg/dL) for children, <2.5 mmol/L(<100 mg/dL) for adults, and <1.8 mmol/L(<70 mg/dL) for adults with known CHD or diabetes. In addition to lifestyle and dietary counselling, treatment priorities are (i) in children, statins, ezetimibe, and bile acid binding resins, and (ii) in adults, maximal potent statin dose, ezetimibe, and bile acid binding resins. Lipoprotein apheresis can be offered in homozygotes and in treatment-resistant heterozygotes with CHD.ConclusionOwing to severe underdiagnosis and undertreatment of FH, there is an urgent worldwide need for diagnostic screening together with early and aggressive treatment of this extremely high-risk condition.

Type 2 diabetes (T2D) is a result of complex gene-environment interactions, and several risk factors have been identified, including age, family history, diet, sedentary lifestyle and obesity. Statistical models that combine known risk factors for T2D can partly identify individuals at high risk of developing the disease. However, these studies have so far indicated that human genetics contributes little to the models, whereas socio-demographic and environmental factors have greater influence. Recent evidence suggests the importance of the gut microbiota as an environmental factor, and an altered gut microbiota has been linked to metabolic diseases including obesity, diabetes and cardiovascular disease. Here we use shotgun sequencing to characterize the faecal metagenome of 145 European women with normal, impaired or diabetic glucose control. We observe compositional and functional alterations in the metagenomes of women with T2D, and develop a mathematical model based on metagenomic profiles that identified T2D with high accuracy. We applied this model to women with impaired glucose tolerance, and show that it can identify women who have a diabetes-like metabolism. Furthermore, glucose control and medication were unlikely to have major confounding effects. We also applied our model to a recently described Chinese cohort and show that the discriminant metagenomic markers for T2D differ between the European and Chinese cohorts. Therefore, metagenomic predictive tools for T2D should be specific for the age and geographical location of the populations studied.

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AimsTo appraise the clinical and genetic evidence that low-density lipoproteins (LDLs) cause atherosclerotic cardiovascular disease (ASCVD).Methods and resultsWe assessed whether the association between LDL and ASCVD fulfils the criteria for causality by evaluating the totality of evidence from genetic studies, prospective epidemiologic cohort studies, Mendelian randomization studies, and randomized trials of LDL-lowering therapies. In clinical studies, plasma LDL burden is usually estimated by determination of plasma LDL cholesterol level (LDL-C). Rare genetic mutations that cause reduced LDL receptor function lead to markedly higher LDL-C and a dose-dependent increase in the risk of ASCVD, whereas rare variants leading to lower LDL-C are associated with a correspondingly lower risk of ASCVD. Separate meta-analyses of over 200 prospective cohort studies, Mendelian randomization studies, and randomized trials including more than 2 million participants with over 20 million person-years of follow-up and over 150 000 cardiovascular events demonstrate a remarkably consistent dose-dependent log-linear association between the absolute magnitude of exposure of the vasculature to LDL-C and the risk of ASCVD; and this effect appears to increase with increasing duration of exposure to LDL-C. Both the naturally randomized genetic studies and the randomized intervention trials consistently demonstrate that any mechanism of lowering plasma LDL particle concentration should reduce the risk of ASCVD events proportional to the absolute reduction in LDL-C and the cumulative duration of exposure to lower LDL-C, provided that the achieved reduction in LDL-C is concordant with the reduction in LDL particle number and that there are no competing deleterious off-target effects.ConclusionConsistent evidence from numerous and multiple different types of clinical and genetic studies unequivocally establishes that LDL causes ASCVD.