Genetic Characteristics of Latvian Patients with Familial Hypercholesterolemia: The First Analysis from Genome-Wide Sequencing

BACKGROUND

There is limited data on the genetic characteristics of patients with familial hypercholesterolemia (FH) in Latvia. We aim to describe monogenic variants in patients from the Latvian Registry of FH (LRFH).

METHODS

Whole genome sequencing with 30× coverage was performed in unrelated index cases from the LRFH and the Genome Database of Latvian Population. LDLR, APOB, PCSK9, LDLRAP1, ABCG5, ABCG8, LIPA, LPA, CYP27A1, and APOE genes were analyzed. Only variants annotated as pathogenic (P) or likely pathogenic (LP) using the FH Variant Curation Expert Panel guidelines for LDLR and adaptations for APOB and PCSK9 were reported.

RESULTS

Among 163 patients, the mean highest documented LDL-cholesterol level was 7.47 ± 1.60 mmol/L, and 79.1% of patients had LDL-cholesterol ≥6.50 mmol/L. A total of 15 P/LP variants were found in 34 patients (diagnostic yield: 20.9%): 14 in the LDLR gene and 1 in the APOB gene. Additionally, 24, 54, and 13 VUS were detected in LDLR, APOB, and PCSK9, respectively. No P/LP variants were identified in the other tested genes.

CONCLUSIONS

Despite the high clinical likelihood of FH, confirmed P/LP variants were detected in only 20.9% of patients in the Latvian cohort when assessed with genome-wide next generation sequencing.

Global perspective of familial hypercholesterolaemia: a cross-sectional study from the EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC)

BACKGROUND

The European Atherosclerosis Society Familial Hypercholesterolaemia Studies Collaboration (FHSC) global registry provides a platform for the global surveillance of familial hypercholesterolaemia through harmonisation and pooling of multinational data. In this study, we aimed to characterise the adult population with heterozygous familial hypercholesterolaemia and described how it is detected and managed globally.

METHODS

Using FHSC global registry data, we did a cross-sectional assessment of adults (aged 18 years or older) with a clinical or genetic diagnosis of probable or definite heterozygous familial hypercholesterolaemia at the time they were entered into the registries. Data were assessed overall and by WHO regions, sex, and index versus non-index cases.

FINDINGS

Of the 61 612 individuals in the registry, 42 167 adults (21 999 [53·6%] women) from 56 countries were included in the study. Of these, 31 798 (75·4%) were diagnosed with the Dutch Lipid Clinic Network criteria, and 35 490 (84·2%) were from the WHO region of Europe. Median age of participants at entry in the registry was 46·2 years (IQR 34·3-58·0); median age at diagnosis of familial hypercholesterolaemia was 44·4 years (32·5-56·5), with 40·2% of participants younger than 40 years when diagnosed. Prevalence of cardiovascular risk factors increased progressively with age and varied by WHO region. Prevalence of coronary disease was 17·4% (2·1% for stroke and 5·2% for peripheral artery disease), increasing with concentrations of untreated LDL cholesterol, and was about two times lower in women than in men. Among patients receiving lipid-lowering medications, 16 803 (81·1%) were receiving statins and 3691 (21·2%) were on combination therapy, with greater use of more potent lipid-lowering medication in men than in women. Median LDL cholesterol was 5·43 mmol/L (IQR 4·32-6·72) among patients not taking lipid-lowering medications and 4·23 mmol/L (3·20-5·66) among those taking them. Among patients taking lipid-lowering medications, 2·7% had LDL cholesterol lower than 1·8 mmol/L; the use of combination therapy, particularly with three drugs and with proprotein convertase subtilisin-kexin type 9 inhibitors, was associated with a higher proportion and greater odds of having LDL cholesterol lower than 1·8 mmol/L. Compared with index cases, patients who were non-index cases were younger, with lower LDL cholesterol and lower prevalence of cardiovascular risk factors and cardiovascular diseases (all p<0·001).

INTERPRETATION

Familial hypercholesterolaemia is diagnosed late. Guideline-recommended LDL cholesterol concentrations are infrequently achieved with single-drug therapy. Cardiovascular risk factors and presence of coronary disease were lower among non-index cases, who were diagnosed earlier. Earlier detection and greater use of combination therapies are required to reduce the global burden of familial hypercholesterolaemia.

FUNDING

Pfizer, Amgen, Merck Sharp & Dohme, Sanofi-Aventis, Daiichi Sankyo, and Regeneron.

The minor house dust mite allergen Der p 13 is a fatty acid-binding protein and an activator of a TLR2-mediated innate immune response

BACKGROUND

The house dust mite (HDM) allergen Der p 13 could be a lipid-binding protein able to activate key innate signaling pathways in the initiation of the allergic response. We investigated the IgE reactivity of recombinant Der p 13 (rDer p 13), its lipid-binding activities, and its capacity to stimulate airway epithelium cells.

METHODS

Purified rDer p 13 was characterized by mass spectrometry, circular dichroism, fluorescence-based lipid-binding assays, and in silico structural prediction. IgE-binding activity and allergenic potential of Der p 13 were examined by ELISA, basophil degranulation assays, and in vitro airway epithelial cell activation assays.

RESULTS

Protein modeling and biophysical analysis indicated that Der p 13 adopts a β-barrel structure with a predominately apolar pocket representing a potential binding site for hydrophobic ligands. Fluorescent lipid-binding assays confirmed that the protein is highly selective for ligands and that it binds a fatty acid with a dissociation constant typical of lipid transporter proteins. The low IgE-binding frequency (7%, n = 224) in Thai HDM-allergic patients as well as the limited propensity to activate basophil degranulation classifies Der p 13 as a minor HDM allergen. Nevertheless, the protein with its presumptively associated lipid(s) triggered the production of IL-8 and GM-CSF in respiratory epithelial cells through a TLR2-, MyD88-, NF-kB-, and MAPK-dependent signaling pathway.

CONCLUSIONS

Although a minor allergen, Der p 13 may, through its lipid-binding capacity, play a role in the initiation of the HDM-allergic response through TLR2 activation.

A new generation of statistical potentials for proteins

We propose a novel and flexible derivation scheme of statistical, database-derived, potentials, which allows one to take simultaneously into account specific correlations between several sequence and structure descriptors. This scheme leads to the decomposition of the total folding free energy of a protein into a sum of lower order terms, thereby giving the possibility to analyze independently each contribution and clarify its significance and importance, to avoid overcounting certain contributions, and to deal more efficiently with the limited size of the database. In addition, this derivation scheme appears as quite general, for many previously developed potentials can be expressed as particular cases of our formalism. We use this formalism as a framework to generate different residue-based energy functions, whose performances are assessed on the basis of their ability to discriminate genuine proteins from decoy models. The optimal potential is generated as a combination of several coupling terms, measuring correlations between residue types, backbone torsion angles, solvent accessibilities, relative positions along the sequence, and interresidue distances. This potential outperforms all tested residue-based potentials, and even several atom-based potentials. Its incorporation in algorithms aiming at predicting protein structure and stability should therefore substantially improve their performances.

Protein decoy sets for evaluating energy functions

Energy functions are crucial ingredients of protein tertiary structure prediction methods. Assessing the quality of energy functions is therefore of prime importance. It requires the elaboration of a standard evaluation scheme, whose key elements are: i). sets that contain the native and several non-native structures of proteins (decoys) in order to test whether the energy functions display the expected quality features and ii). measures to evaluate the reliability of energy functions. We present here a survey of the recent advances in these two related fields. In a first part, we analyze and review the large number of decoy sets that are available on the web, and we summarize the characteristics of a challenging decoy set. We then discuss how to define the quality of energy functions and review the measures related to it.

PoPMuSiC, rationally designing point mutations in protein structures

PoPMuSiC is an efficient tool for rational computer-aided design of single-site mutations in proteins and peptides. Two types of queries can be submitted. The first option allows to estimate the changes in folding free energy for specific point mutations given by the user. In the second option, all possible point mutations in a given protein or protein region are performed and the most stabilizing or destabilizing mutations, or the neutral mutations with respect to thermodynamic stability, are selected. For each sequence position or secondary structure the deviation from the most stable sequence is moreover evaluated, which helps to identify the most suitable sites for the introduction of mutations.

Optimality of the genetic code with respect to protein stability and amino-acid frequencies

BACKGROUND

The genetic code is known to be efficient in limiting the effect of mistranslation errors. A misread codon often codes for the same amino acid or one with similar biochemical properties, so the structure and function of the coded protein remain relatively unaltered. Previous studies have attempted to address this question quantitatively, by estimating the fraction of randomly generated codes that do better than the genetic code in respect of overall robustness. We extended these results by investigating the role of amino-acid frequencies in the optimality of the genetic code.

RESULTS

We found that taking the amino-acid frequency into account decreases the fraction of random codes that beat the natural code. This effect is particularly pronounced when more refined measures of the amino-acid substitution cost are used than hydrophobicity. To show this, we devised a new cost function by evaluating in silico the change in folding free energy caused by all possible point mutations in a set of protein structures. With this function, which measures protein stability while being unrelated to the code's structure, we estimated that around two random codes in a billion (109) are fitter than the natural code. When alternative codes are restricted to those that interchange biosynthetically related amino acids, the genetic code appears even more optimal.

CONCLUSIONS

These results lead us to discuss the role of amino-acid frequencies and other parameters in the genetic code's evolution, in an attempt to propose a tentative picture of primitive life.

Identification and ab initio simulations of early folding units in proteins

The location of protein subunits that form early during folding, constituted of consecutive secondary structure elements with some intrinsic stability and favorable tertiary interactions, is predicted using a combination of threading algorithms and local structure prediction methods. Two folding units are selected among the candidates identified in a database of known protein structures: the fragment 15-55 of 434 cro, an all-alpha protein, and the fragment 1-35 of ubiquitin, an alpha/beta protein. These units are further analyzed by means of Monte Carlo simulated annealing using several database-derived potentials describing different types of interactions. Our results suggest that the local interactions along the chain dominate in the first folding steps of both fragments, and that the formation of some of the secondary structures necessarily occurs before structure compaction. These findings led us to define a prediction protocol, which is efficient to improve the accuracy of the predicted structures. It involves a first simulation with a local interaction potential only, whose final conformation is used as a starting structure of a second simulation that uses a combination of local interaction and distance potentials. The root mean square deviations between the coordinates of predicted and native structures are as low as 2-4 A in most trials. The possibility of extending this protocol to the prediction of full proteins is discussed. Proteins 2001;42:164-176.

PoPMuSiC, an algorithm for predicting protein mutant stability changes: application to prion proteins

A novel tool for computer-aided design of single-site mutations in proteins and peptides is presented. It proceeds by performing in silico all possible point mutations in a given protein or protein region and estimating the stability changes with linear combinations of database-derived potentials, whose coefficients depend on the solvent accessibility of the mutated residues. Upon completion, it yields a list of the most stabilizing, destabilizing or neutral mutations. This tool is applied to mouse, hamster and human prion proteins to identify the point mutations that are the most likely to stabilize their cellular form. The selected mutations are essentially located in the second helix, which presents an intrinsic preference to form beta-structures, with the best mutations being T183-->F, T192-->A and Q186-->A. The T183 mutation is predicted to be by far the most stabilizing one, but should be considered with care as it blocks the glycosylation of N181 and this blockade is known to favor the cellular to scrapie conversion. Furthermore, following the hypothesis that the first helix might induce the formation of hydrophilic beta-aggregates, several mutations that are neutral with respect to the structure's stability but improve the helix hydrophobicity are selected, among which is E146-->L. These mutations are intended as good candidates to undergo experimental tests.

Different derivations of knowledge-based potentials and analysis of their robustness and context-dependent predictive power

The possibility of defining effective potentials from known protein structures, which are sufficiently accurate to be used for protein-structure-prediction purposes, is investigated. Three types of distance potentials and three types of backbone torsion potentials are defined, based on propensities of amino acid pairs to be separated by a given spatial distance or to be associated to a backbone torsion angle domain. Their differences reside in the way the physical correlations between the amino acids and the conformational states are extracted from the bulk interactions due to the presence of many residues in a protein. For the distance potentials, a physical meaning can be associated to the different definitions, given that some of the potentials favor hydrophobic interactions and others favor interactions between oppositely charged residues. The performance of the different torsion and distance potentials in structure prediction procedures, in particular native-fold recognition and evaluation of protein stability changes upon point mutations, is analyzed. It appears to differ according to the specific proteins and protein environments. In particular, one of the distance potentials performs better than the others for membrane proteins and in protein regions involving charged residues, but less well in other protein regions. Furthermore, the dependence of the potentials on the characteristics of the proteins from which they are derived is analyzed. It is shown that the dependence of the potentials on the length, amino acid composition and secondary-structure content of the proteins from the dataset is either very limited or rather strong, according to the type of potential. The results obtained suggest that the main problem limiting the performance of database-derived potentials is their lack of universality: each potential describes with satisfactory accuracy only the interactions present in certain protein environments.

Predicting protein stability changes upon mutation using database-derived potentials: solvent accessibility determines the importance of local versus non-local interactions along the sequence

For 238 mutations of residues totally or partially buried in the protein core, we estimate the folding free energy changes upon mutation using database-derived potentials and correlate them with the experimentally measured ones. Several potentials are tested, representing different kinds of interactions. Local interactions along the chain are described by torsion potentials, based on propensities of amino acids to be associated with backbone torsion angle domains. Non-local interactions along the sequence are represented by distance potentials, derived from propensities of amino acid pairs or triplets to be at a given spatial distance. We find that for the set of totally buried residues, the best performing potential is a combination of a distance potential and a torsion potential weighted by a factor of 0.4; it yields a correlation coefficient between computed and measured changes in folding free energy of 0.80. For mutations of partially buried residues, the best potential is a combination of a torsion potential and a distance potential weighted by a factor of 0.7, and for the previously analysed mutations of solvent accessible residues, it is a torsion potential taken individually; the respective correlation coefficients reach 0.82 and 0.87. These results show that distance potentials, dominated by hydrophobic interactions, represent best the main interactions stabilizing the protein core, whereas torsion potentials, describing local interactions along the chain, represent best the interactions at the protein surface. The prediction accuracy reached by the distance potentials is, however, lower than that of the torsion potentials. A possible reason for this is that distance potentials would not describe correctly the effect on protein stability due to cavity formation upon mutating a large into a small amino acid. Last but not least, our results indicate that although local interactions, responsible for secondary structure formation, do not dominate in the protein core, they are not negligible for all that. They have a significant weight in the delicate balance between all the interactions that ensure protein stability.

Stability changes upon mutation of solvent-accessible residues in proteins evaluated by database-derived potentials

The stability changes in peptides and proteins caused by the substitution of a single amino acid, which can be measured experimentally by the change in folding free energy, are evaluated here using effective potentials derived from known protein structures. The analysis is focused on mutations of residues that are accessible to the solvent. These represent in total 106 mutations, introduced at different sites in barnase, bacteriophage T4 lysozyme and chymotrypsin inhibitor 2, and in a synthetic helical peptide. Assuming that the mutations do not modify the backbone structure, the changes in folding free energies are computed using various types of database-derived potentials and are compared with the measured ones. Distance-dependent residue-residue potentials are found to be inadequate for estimating the stability changes caused by these mutations, as they are dominated by hydrophobic interactions, which do not play an essential role at the protein surface. On the contrary, the potentials based on backbone torsion angle propensities yield quite good results. Indeed, for a subset of 96 out of the 106 mutations, the computed and measured changes in folding free energy correlate with a linear correlation coefficient of 0.87. Moreover, the ten mutations that are excluded from the correlation either seem to cause modifications of the backbone structure or to involve strong hydrophobic interactions, which are atypical for solvent-accessible residues. We find furthermore that raising the ionic strength of the solvent used for measuring the changes in folding free energies improves the correlation, as it tends to mask the electrostatic interactions. When adding to these 106 mutations 44 mutations performed in staphylococcal nuclease and chemotactic protein, which were first discarded because some of them were suspected to affect the backbone conformation or the denatured state, the correlation between measured and computed folding free energy changes remains quite good: the correlation coefficient is 0.86 for 135 out of the 150 mutations. The success of the backbone torsion potentials in predicting stability changes indicates that the approximations made for deriving these potentials are adequate. It suggests moreover that the local interactions along the chain dominate at the protein surface.