Co-prescription of medication for bipolar disorder and diabetes mellitus : a nationwide population based study with focus on gender differences

BackgroundStudies have shown a correlation between bipolar disorder and diabetes mellitus. It is unclear if this correlation is a part of common pathophysiological pathways, or if medication for bipolar disorder has negative effects on blood sugar regulation.MethodsThe Norwegian prescription database was analyzed. Prescriptions for lithium, lamotrigine, carbamazepine and valproate were used as proxies for bipolar disorder. Prescriptions for insulin and oral anti-diabetic agents were used as proxies for diabetes mellitus. We explored the association between medication for bipolar disorder and diabetes medication by logistic regressionResultsWe found a strong association between concomitant use of medication to treat diabetes mellitus and mood stabilizers for the treatment of bipolar disorder. Females had a 30% higher risk compared to men of being treated for both disorders. Persons using oral anti-diabetic agents had higher odds of receiving valproate than either lithium or lamotrigine. Use of insulin as monotherapy seemed to have lower odds than oral anti-diabetic agents of co-prescription of mood stabilizers, compared to the general population.ConclusionsThis study showed a strong association between the use of mood stabilizers and anti-diabetic agents. The association was stronger among women than men

Community Detection in Social Networks

Social networks usually display a hierarchy of communities and it is the task of community detection algorithms to detect these communities and preferably also their hierarchical relationships. One common class of such hierarchical algorithms are the agglomerative algorithms. These algorithms start with one community per vertex in the network and keep agglomerating vertices together to form increasingly larger communities. Another common class of hierarchical algorithms are the divisive algorithms. These algorithms start with a single community comprising all the vertices of the network and then split the network into several connected components that are viewed as communities. We start this thesis by giving an introductory overview of the field of com- munity detection in part I, including complex networks, the basic groups of com- munity definitions, the modularity function, and a description of common com- munity detection techniques, including agglomerative and divisive algorithms. Then we proceed, in part II, with community detection algorithms that have been implemented and tested, with refined use of data structures, as part of this thesis. We start by describing, implementing and testing against benchmark graphs the greedy hierarchical agglomerative community detection algorithm proposed by Aaron Clauset, M. E. J. Newman, and Cristopher Moore in 2004 in the article Finding community structure in very large networks [5]. We continue with describing and implementing the hierarchical divisive algorithm proposed by Filippo Radicchi, Claudio Castellano, Federico Cecconi, Vittorio Loreto, and Domenico Parisi in 2004 in the article Defining and identifying communities in networks [28]. Instead of testing this algorithm against benchmark graphs we present a community detection web service that runs the algorithm by Radicchi et al. on the collaboration networks in the DBLP database of scientific publi- cations and co- authorships in the area of computer science. We allow the user to freely set the many parameters that we have defined for this algorithm. The final judgment on the results is measured by the modularity value or can be left to the knowledgeable user. A rough description of the design of the algorithms and of the web service is given, and all code is available at GitHub [10] [9]. Lastly, a few improvements both to the algorithm by Radicchi et al. and to the web service are presented.Master i InformatikkMAMN-INFINF39

On the role of NOS1 ex1f-VNTR in ADHD – allelic, subgroup, and meta-analysis

Attention deficit/hyperactivity disorder (ADHD) is a heritable neurodevelopmental disorder featuring complex genetics with common and rare variants contributing to disease risk. In a high proportion of cases, ADHD does not remit during adolescence but persists into adulthood. Several studies suggest that NOS1, encoding nitric oxide synthase I, producing the gaseous neurotransmitter NO, is a candidate gene for (adult) ADHD. We here extended our analysis by increasing the original sample, adding two further samples from Norway and Spain, and conducted subgroup and co-morbidity analysis. Our previous finding held true in the extended sample, and also meta-analysis demonstrated an association of NOS1 ex1fVNTR short alleles with adult ADHD (aADHD). Association was restricted to females, as was the case in the discovery sample. Subgroup analysis on the single allele level suggested that the repeat allele caused the association. Regarding subgroups, we found that NOS1 was associated with the hyperactive/impulsive ADHD subtype, but not to pure inattention. In terms of comorbidity, major depression, anxiety disorders, cluster C personality disorders and migraine were associated with short repeats, in particular the repeat allele. Also, short allele carriers had significantly lower IQ. Finally, we again demonstrated an influence of the repeat on gene expression in human post-mortem brain samples. These data validate the role of NOS-I in hyperactive/impulsive phenotypes and call for further studies into the neurobiological underpinnings of this association.PostprintPeer reviewe

Genome wide association study identifies variants in NBEA associated with migraine in bipolar disorder

C. Liu, J. Wedenoja, M. Kaunisto, K. Heikkilä, J. Kaprio, M. Wessman, M. Kallela, M. Färkkilä, V. Artto, J. Eriksson, A. Palotie, M. Daily työryhmän BiGs Consortium IHG Consortium jäseniä.Peer reviewe

Brain afferents to the medullary dorsal reticular nucleus: a retrograde and anterograde tracing study in the rat

The medullary dorsal reticular nucleus (DRt) was recently shown to belong to the supraspinal pain control system; neurons within this nucleus give origin to a descending projection that increases spinal nociceptive transmission and facilitates pain perception [Almeida et al. (1999), Eur. J. Neurosci., 11, 110-122]. In the present study, the areas of the brain that may modulate the activity of DRt neurons were investigated by using of tract-tracing techniques. Injection of a retrograde tracer into the DRt resulted in labelling in multiple areas of the brain. In the contralateral orbital, prelimbic, infralimbic, insular, motor and somatosensory cortices labelling was prominent, but a smaller ipsilateral projection from these same areas was also detected. Strong labelling was also noted in the central amygdaloid nucleus, bed nucleus of stria terminalis and substantia innominata. Labelled diencephalic areas were mainly confined to the hypothalamus, namely its lateral and posterior areas as well as the paraventricular nucleus. In the mesencephalon, the periaqueductal grey, red nucleus and deep mesencephalic nucleus were strongly labelled, whereas, in the brainstem, the parabrachial nuclei, rostroventromedial medulla, nucleus tractus solitarius, spinal trigeminal nucleus, and the parvocellular, dorsal, lateral and ventral reticular nuclei were the most densely labelled regions. All deep cerebellar nuclei were labelled bilaterally. These data suggest that the DRt integrates information from the somatosensory, antinociceptive, autonomic, limbic, pyramidal and extrapyramidal systems while triggering its descending facilitating action upon the spinal nociceptive transmission.BIOTECH project n° BIO4-CT98-007676.Pain Gulbenkian Programme.Fundação para a Ciência e a Tecnologia (FCT) - project POCTI/NSE/38952/2001