Sitosterolemia: a new mutation in a Mediterranean patient

Network-based association analysis to infer new disease-gene relationships using large-scale protein interactions

Protein-protein interactions integrated with disease-gene associations represent important information for revealing protein functions under disease conditions to improve the prevention, diagnosis, and treatment of complex diseases. Although several studies have attempted to identify disease-gene associations, the number of possible disease-gene associations is very small. High-throughput technologies have been established experimentally to identify the association between genes and diseases. However, these techniques are still quite expensive, time consuming, and even difficult to perform. Thus, based on currently available data and knowledge, computational methods have served as alternatives to provide more possible associations to increase our understanding of disease mechanisms. Here, a new network-based algorithm, namely, Disease-Gene Association (DGA), was developed to calculate the association score of a query gene to a new possible set of diseases. First, a large-scale protein interaction network was constructed, and the relationship between two interacting proteins was calculated with regard to the disease relationship. Novel plausible disease-gene pairs were identified and statistically scored by our algorithm using neighboring protein information. The results yielded high performance for disease-gene prediction, with an F-measure of 0.78 and an AUC of 0.86. To identify promising candidates of disease-gene associations, the association coverage of genes and diseases were calculated and used with the association score to perform gene and disease selection. Based on gene selection, we identified promising pairs that exhibited evidence related to several important diseases, e.g., inflammation, lipid metabolism, inborn errors, xanthomatosis, cerebellar ataxia, cognitive deterioration, malignant neoplasms of the skin and malignant tumors of the cervix. Focusing on disease selection, we identified target genes that were important to blistering skin diseases and muscular dystrophy. In summary, our developed algorithm is simple, efficiently identifies disease–gene associations in the protein-protein interaction network and provides additional knowledge regarding disease-gene associations. This method can be generalized to other association studies to further advance biomedical science.

Two novel variants of the ABCG5 gene cause xanthelasmas and macrothrombocytopenia: a brief review of hematologic abnormalities of sitosterolemia

Essentials Diagnosis of sitosterolemia, a rare recessive or syndromic disorder, is usually delayed. Peripheral blood smear is extremely useful for establishing the suspicion of sitosterolemia. High-throughput sequencing technology enables the molecular diagnosis of inherited thrombocytopenias. Accurate characterization of sitosterolemia helps us determine appropriate management.

SUMMARY

Background Sitosterolemia (STSL) is a recessive inherited disorder caused by pathogenic variants in the ABCG5 and ABCG8 genes. Increased levels of plasma plant sterols (PSs) usually result in xanthomas and premature coronary atherosclerosis, although hematologic abnormalities may occasionally be present. This clinical picture is unfamiliar to many physicians, and patients may be at high risk of misdiagnosis. Objectives To report two novel ABCG5 variants causing STSL in a Spanish patient, and review the clinical and mutational landscape of STSL. Patient/Methods A 46-year-old female was referred to us with lifelong macrothrombocytopenia. She showed familial hypercholesterolemia-related xanthomas. Molecular analysis was performed with high-throughput sequencing. Plasma PS levels were evaluated with gas-liquid chromatography. The STSL landscape was reviewed with respect to specific online databases and all reports published since 1974. Results A blood smear revealed giant platelets and stomatocytes. Novel compound heterozygous variants were detected in exons 7 (c.914C>G) and 13 (c.1890delT) of ABCG5. The patient showed an increased plasma level of sitosterol. These findings support the diagnosis of STSL. In our review, we identified only 25 unrelated STLS patients who presented with hematologic abnormalities including macrothrombocytopenia. It remains unknown why only some patients develop hematologic abnormalities. Conclusions This is the first Spanish STSL patient to be reported and molecularly characterized. The early diagnosis of STLS is strongly supported by the presence of stomatocytes in blood smears. The definitive diagnosis of STSL by measurement of serum PS levels and molecular analyses prompted the use of ezetimibe therapy.

Plant Sterols, Stanols, and Sitosterolemia

Phytosterolemia (sitosterolemia) is a rare autosomal recessive sterol storage disease caused by mutations in either of the adenosine triphosphate (ATP) binding cassette transporter genes; (ABC) G5 or ABCG8, leading to impaired elimination of plant sterols and stanols, with their increased accumulation in the blood and tissues. Thus the disease is characterized by substantially elevated serum plant sterols and stanols, with moderate to high plasma cholesterol levels, and increased risk of premature atherosclerosis. Hematologic abnormalities including macrothrombocytopenia, stomatocytosis and hemolysis are frequently observed in sitosterolemia patients. Currently, ezetimibe, a sterol absorption inhibitor, is used as the routine treatment for sitosterolemia, with reported improvement in plant sterol levels and hemolytic parameters. This review summarizes the research related to the health impact of plant sterols and stanols on sitosterolemia.