Finding new genes for non-syndromic hearing loss through an in silico prioritization study.

At present, 51 genes are already known to be responsible for Non-Syndromic hereditary Hearing Loss (NSHL), but the knowledge of 121 NSHL-linked chromosomal regions brings to the hypothesis that a number of disease genes have still to be uncovered. To help scientists to find new NSHL genes, we built a gene-scoring system, integrating Gene Ontology, NCBI Gene and Map Viewer databases, which prioritizes the candidate genes according to their probability to cause NSHL. We defined a set of candidates and measured their functional similarity with respect to the disease gene set, computing a score ( S S M avg) that relies on the assumption that functionally related genes might contribute to the same (disease) phenotype. A Kolmogorov-Smirnov test, comparing the pair-wise distribution on the disease gene set with the distribution on the remaining human genes, provided a statistical assessment of this assumption. We found at a p-value < 2.2.10 (-16) that the former pair-wise is greater than the latter, justifying a prioritization strategy based on the functional similarity of candidate genes respect to the disease gene set. A cross-validation test measured to what extent the S S M avg ranking for NSHL is different from a random ordering: adding 15% of the disease genes to the candidate gene set, the ranking of the disease genes in the first eight positions resulted statistically different from a hypergeometric distribution with a p-value = 2.04.10(-5) and a power > 0.99. The twenty top-scored genes were finally examined to evaluate their possible involvement in NSHL. We found that half of them are known to be expressed in human inner ear or cochlea and are mainly involved in remodeling and organization of actin formation and maintenance of the cilia and the endocochlear potential. These findings strongly indicate that our metric was able to suggest excellent NSHL candidates to be screened in patients and controls for causative mutations.

Treatment with flutamide, metformin, and their combination added to a hypocaloric diet in overweight-obese women with polycystic ovary syndrome: a randomized, 12-month, placebo-controlled study.

CONTEXT: The few controlled trials performed so far indicate that the addition of metformin and/or flutamide to a hypocaloric diet in obese women with polycystic ovary syndrome (PCOS) effectively influences different phenotypic aspects of the syndrome. All these studies are, however, characterized by a short to medium period of treatment. OBJECTIVE: Our objective was to investigate the long-term effects of these therapies. DESIGN AND SETTING: We conducted a prospective, randomized, placebo-controlled trial at a medical center. PATIENTS: Of 80 overweight-obese women with PCOS, 76 completed the study. INTERVENTIONS: Patients were placed on a hypocaloric diet for the first month and then on a hypocaloric diet plus placebo, metformin (850 mg, orally, twice a day), flutamide (250 mg, orally, twice a day), or metformin plus flutamide for the subsequent 12 months (20 subjects in each group). MAIN OUTCOME MEASURES: We assessed clinical features, computerized tomography measurement of fat distribution, androgens, lipids, and fasting and glucose-stimulated glucose and insulin levels at baseline and after 6 and 12 months of treatment. RESULTS: After 6 months, compared with placebo, flutamide further decreased visceral/sc fat mass (P = 0.044), androstenedione (P < 0.001), dehydroepiandrosterone sulfate (P < 0.001), and hirsutism score (P < 0.001), whereas metformin further increased frequency of menstruation (P = 0.039). After 12 months, flutamide maintained the effects observed after 6 months on visceral/sc fat mass (P = 0.033) and androstenedione (P < 0.001), whereas it produced an additional decrease in dehydroepiandrosterone sulfate (P = 0.020) and hirsutism score (P = 0.019); metformin further improved the menstrual pattern (P = 0.013). Moreover, after 12 months, flutamide improved more than placebo the menstrual pattern (P = 0.008), glucose-stimulated glucose levels (P = 0.041), insulin sensitivity (P < 0.001), and low-density lipoprotein cholesterol levels (P = 0.003), whereas metformin decreased glucose-stimulated insulin levels (P = 0.014). The combination of the two drugs maintained the specific effect of each of the compounds, without any additive or synergistic effect. CONCLUSIONS: These findings add relevance to the usefulness of metformin and flutamide in the treatment of dieting overweight-obese PCOS women and provide a rationale for targeting different therapeutic options according to the required outcomes in the long term.