Genetic Basis of Attention Deficit Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neuropsychiatric disorders of childhood. Due to studies reporting that the effects of ADHD diagnosis on functioning may last throughout life, this disorder, which has great importance for child and adolescent psychiatry, started to attract greater attention recently in terms of adult psychiatry. A review, evaluating the results of studies conducted on the genetic basis of ADHD, which started to attract increasing attention both in our country and the world, was thought to help clinicians working in this field. PubMed and Turkish Psychiatry Index online search engines were screened using “attention deficit hyperactivity disorder”, “ADHD”, “genetics” as key words. The data obtained were combined with information gleaned from several textbooks. Based on previous studies, it could easily be concluded that ADHD is one of the most common heritable psychiatric disorder with distinguished genetic features. Despite its importance for diagnosis and treatment, the etiology of ADHD is still not clear and the disorder seems to be a complex problem arising from the effects of both genetic and environmental factors. Although previous studies revealed that ADHD displayed familial and hereditary transmission, stable patterns of Mendelian inheritance could not be discriminated by evaluation of pedigrees. Therefore, many studies have been conducted on the molecular genetic basis of ADHD recently. The previous studies did not report consistent results in identification of the genes responsible for ADHD which has been partially linked to heterogeneity of the disorder. Grouping relevant patients according to comorbidities and persistence in adolescence rather than DSM-IV subtypes could be an important alternative method for overcoming this limitation in the research studies

Transcriptional response of virus-infected cassava and identification of putative sources of resistance for cassava brown streak disease

Cassava (Manihot esculenta) is a major food staple in sub-Saharan Africa, which is severely affected by cassava brown streak disease (CBSD). The aim of this study was to identify resistance for CBSD as well as to understand the mechanism of putative resistance for providing effective control for the disease. Three cassava varieties; Kaleso, Kiroba and Albert were inoculated with cassava brown streak viruses by grafting and also using the natural insect vector the whitefly, Bemisia tabaci. Kaleso expressed mild or no disease symptoms and supported low concentrations of viruses, which is a characteristic of resistant plants. In comparison, Kiroba expressed severe leaf but milder root symptoms, while Albert was susceptible with severe symptoms both on leaves and roots. Real-time PCR was used to estimate virus concentrations in cassava varieties. Virus quantities were higher in Kiroba and Albert compared to Kaleso. The Illumina RNA-sequencing was used to further understand the genetic basis of resistance. More than 700 genes were uniquely overexpressed in Kaleso in response to virus infection compared to Albert. Surprisingly, none of them were similar to known resistant gene orthologs. Some of the overexpressed genes, however, belonged to the hormone signalling pathways and secondary metabolites, both of which are linked to plant resistance. These genes should be further characterised before confirming their role in resistance to CBSD

SOCS3 is a novel bi-functional regulator of muscle growth and wasting

poster abstractDisease states such as cancer and other inflammatory conditions often show elevated IL-6 levels that correlate with muscle wasting and mortality. Previously we reported that STAT3, a transcription factor downstream of IL-6 binding to its receptor, plays a causative role in cancer cachexia, and that STAT3 inhibition prevents muscle wasting. Others have also shown that STAT3 blockade rescues cachexia in a murine model of kidney failure. Altogether these results established STAT3 as a regulator of muscle mass. One of STAT3 downstream target genes is the Suppressor of cytokine signaling-3 (SOCS-3). Interestingly, SOCS3 has been reported to inhibit the IL-6/STAT3 signaling by means of a feedback mechanism. In particular, SOCS3 can prevent further STAT3 activation by inhibiting the activation of JAK kinases, competing for receptor binding motifs and targeting the receptor for proteasomal degradation. We thus sought to determine the role of SOCS3 in muscle growth regulation and whether SOCS3 can improve muscle wasting in conditions of high IL-6. Adenoviral-mediated SOCS3 overexpression in C2C12 myotubes caused hypertrophy and rescued IL-6-induced myofiber shrinkage. Similarly, SOCS3 gene transfer in the tibialis muscle of tumor hosts and burn-injured mice prevented muscle atrophy due to elevated IL-6. We then generated MLC-SOCS3 transgenic mice overexpressing SOCS3 from a muscle-specific promoter. Interestingly, these animals exhibit a complex sexually dimorphic phenotype. Indeed, female mice showed higher SOCS3 protein levels in skeletal muscle compared to the males, consistently with decreased pSTAT3 expression. Despite reduced or unchanged body weights, the MLC-SOCS3 transgenics generally showed larger skeletal muscles compared to their wild-type littermates. 1-weekold and adult MLC-SOCS3 mice were also characterized by significantly larger muscle cross-sectional area. However, only adult male mice showed reduced number of muscle fibers and increased number of central nuclei, thus suggesting that SOCS3 could affect myogenesis and differentiation. On this line and consistent with previous reports, primary myoblasts isolated from MLC-SOCS3 mice were shown to proliferate at a lower rate and formed hypertrophic fibers upon differentiation. Furthermore, MLC-SOCS3 myotubes as well as C2C12 expressing SOCS3 were refractory to both catabolic (IL-6) and anabolic (IGF-1 and GH) stimuli. These data suggest that SOCS3 could act as a bi-functional regulator of muscle growth, possibly by affecting differentiation and limiting both IL-6/STAT3- induced wasting as well as IGF-1/GH-associated signaling. Further investigation is needed to define whether SOCS3 may play a role in the activation of muscle satellite cells and to support the use of SOCS3 as a therapeutic approach in cachexia and sarcopenia

Familial Mediterranean fever, from pathogenesis to treatment: a contemporary review

Familial Mediterranean fever (FMF) (OMIM #249100) is the most common hereditary autoinflammatory disease in the world. FMF is caused by gain of function mutations of MEFV gene which encodes an immune regulatory protein, pyrin. Over the last few years, we have witnessed several new developments in the pathogenesis, genetic testing, diagnosis, comorbidities, disease related damage and treatment approaches to FMF. Elucidation of some of the pathogenic mechanisms has led to the discovery of pathways involved in inflammatory, metabolic, cardiovascular and degenerative diseases. The use of next generation sequencing in FMF has revealed many new gene variants whose clinical significance may be clarified by developing functional assays and biomarkers. Clinically, although FMF is considered an episodic disease characterized by brief attacks, recent systematic studies have defined several associated chronic inflammatory conditions. Colchicine is the mainstay of FMF treatment, and interleukin (IL)-1 antagonists are the treatment of choice in refractory or intolerant cases. Experience of IL-1 antagonists, anakinra and canakinumab, is now available in thousands of colchicine resistant or intolerant FMF patients. In this contemporary review, we surveyed current FMF knowledge in the light of these recent advances

Baicalin administration attenuates hyperglycemia-induced malformation of cardiovascular system

In this study, the effects of Baicalin on the hyperglycemia-induced cardiovascular malformation during embryo development were investigated. Using early chick embryos, an optimal concentration of Baicalin (6 μM), was identified which could prevent hyperglycemia-induced cardiovascular malformation of embryos. Hyperglycemia-enhanced cell apoptosis was reduced in embryos and HUVECs in the presence of Baicalin. Hyperglycemia-induced excessive ROS production was inhibited when Baicalin was administered. Analyses of SOD, GSH-Px, MAQE and GABAA suggested Baicalin plays an antioxidant role in chick embryos possibly through suppression of outwardly rectifying Cl(-) in the high-glucose microenvironment. In addition, hyperglycemia-enhanced autophagy fell in the presence of Baicalin, through affecting the ubiquitin of p62 and accelerating autophagy flux. Both Baicalin and Vitamin C could decrease apoptosis, but CQ did not, suggesting autophagy to be a protective function on the cell survival. In mice, Baicalin reduced the elevated blood glucose level caused by streptozotocin (STZ). Taken together, these data suggest that hyperglycemia-induced embryonic cardiovascular malformation can be attenuated by Baicalin administration through suppressing the excessive production of ROS and autophagy. Baicalin could be a potential candidate drug for women suffering from gestational diabetes mellitus

Solar flare prediction using advanced feature extraction, machine learning and feature selection

YesNovel machine-learning and feature-selection algorithms have been developed to study: (i) the flare prediction capability of magnetic feature (MF) properties generated by the recently developed Solar Monitor Active Region Tracker (SMART); (ii) SMART's MF properties that are most significantly related to flare occurrence. Spatio-temporal association algorithms are developed to associate MFs with flares from April 1996 to December 2010 in order to differentiate flaring and non-flaring MFs and enable the application of machine learning and feature selection algorithms. A machine-learning algorithm is applied to the associated datasets to determine the flare prediction capability of all 21 SMART MF properties. The prediction performance is assessed using standard forecast verification measures and compared with the prediction measures of one of the industry's standard technologies for flare prediction that is also based on machine learning - Automated Solar Activity Prediction (ASAP). The comparison shows that the combination of SMART MFs with machine learning has the potential to achieve more accurate flare prediction than ASAP. Feature selection algorithms are then applied to determine the MF properties that are most related to flare occurrence. It is found that a reduced set of 6 MF properties can achieve a similar degree of prediction accuracy as the full set of 21 SMART MF properties