Genetic studies in mood disorders

Mood disorders, including bipolar disorder (BPD) and major depressive disorder (MDD), are highly complex psychiatric disorders. Decades of genetic studies have generated a large number of putative genetic susceptibility variants. However, with exception of CACNA1C, SYNE1 and ANK3 in BPD no robust association has as yet been identified. In this thesis my aim was to find predisposing genetic risk factors for mood disorders. In paper I, my hypotheses were that the FKBP5 gene is a risk gene for MDD, contributes to severity and is involved in treatment response to an antidepressant, Citalopram. We tested for association of three markers using the STAR*D cohort (Level 1). Rs1360780 was significantly associated with MDD. Rs4713916 was significantly associated with remission following treatment with Citalopram when two study populations were analyzed together. We determined that there is a stratification issue and no correlation can be made for treatment response or severity of MDD. In paper II, my hypothesis was that candidate genes for MDD are acting synergistically to contribute to risk for MDD. We applied three different algorithms to evaluate SNP-SNP interactions. Although none of the interactions survived corrections for multiple comparisons, our results contribute valuable information to future genetic studies in MDD. The logistic regression methods identified large interaction effects. None of the top interactions explain a large proportion of MDD in the general population. Among the top interactions, none of the three algorithms identify identical pairs of markers for risk of MDD. Moreover, none of the top ranked interactions has previously been implicated to act synergistically in MDD-susceptibility. We also noted that markers selected for predicted interaction effects were not among the top interactions. In paper III, my hypothesis was that rare and highly penetrant large structural genomic variations (CNVs) increase the risk for BPD. We searched for CNVs across diagnostic boundaries and included individuals with BPD, schizophrenia (SZ) or schizoaffective disorder (SA). To increase the possibility that the CNV should be highly penetrant we searched for CNVs in affected individuals in BP-pedigrees and identified CNVs in the MAGI1 gene in two families and showed that it was more frequent in individuals with BPD, SZ and SA than controls. In paper IV, my hypothesis was that inherited CNVs contribute with risk to BPD irrespective of their frequency. We developed an algorithm that combines linkage-data with the CNV content within and across families. We identified one significant region with a CNV that maps to 19q13, and stretches over the PSG genes. The PSG proteins has been shown to activate TGF-?. Moreover, two CNV SNPs are reported as likely eQTL’s for regulation of NF?B. Thus, this CNV involves several putative molecular targets in BPD-etiology. In conclusion, the work conducted in this thesis has contributed to our knowledge of the etiology of mood disorders. For BPD we found two new susceptibility loci. In the analysis of MDD we increased the knowledge of the genetic interacting landscape in 63 candidate genes. We also showed that FKBP5 is associated with risk for MDD

Energy exchange between nonlinear oscillators: An entropy foundation

In the field of vibrations of complex structures, energy methods like SEA and a series of mid-frequency methods, represent an important resource for computational analysis. All these methods are based in general on a linear formulation of the elastic problem. However, when nonlinearities are present, for example related to clearance or stiffening of joints, these methods, in principle, cannot be applied. This paper, on the basis of a theory presented recently by one of the authors, proposes a foundation of a new energy method able to deal with nonlinearities when studying the energy exchange between subsystems. The idea relies on the concept of a thermodynamic vibroacoustic temperature, that can be directly defined when introducing the entropy of a vibrating structure. The theory is introduced in general, and examples of calculation of the power flow between nonlinear resonators are presented introducing stiffening and clearences for systems with many degrees of freedom

The Genetic Interacting Landscape of 63 Candidate Genes in Major Depressive Disorder: An Explorative Study

Background: Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Results: Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (\u3c 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (\u3c 0.15). Conclusions: We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied

Cerebrospinal fluid markers before and after shunting in patients with secondary and idiopathic normal pressure hydrocephalus

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to explore biochemical changes in the cerebrospinal fluid (CSF) induced by shunt surgery and the relationship between these changes and clinical improvement.</p> <p>Methods</p> <p>We measured clinical symptoms and analysed lumbar CSF for protein content, neurodegeneration and neurotransmission markers in patients with secondary (SNPH, n = 17) and idiopathic NPH (INPH, n = 18) before and 3 months after shunt surgery. Patients were divided into groups according to whether or not there was improvement in clinical symptoms after surgery.</p> <p>Results</p> <p>Preoperatively, the only pathological findings were elevated neurofilament protein (NFL), significantly more so in the SNPH patients than in the INPH patients, and elevated albumin content. Higher levels of NFL correlated with worse gait, balance, wakefulness and neuropsychological performance. Preoperatively, no differences were seen in any of the CSF biomarkers between patients that improved after surgery and those that did not improve. Postoperatively, a greater improvement in gait and balance performance correlated with a more pronounced reduction in NFL. Levels of albumin, albumin ratio, neuropeptide Y, vasoactive intestinal peptide and ganglioside GD3 increased significantly after shunting in both groups. In addition, Gamma amino butyric acid increased significantly in SNPH and tau in INPH.</p> <p>Conclusion</p> <p>We conclude that a number of biochemical changes occur after shunt surgery, but there are no marked differences between the SNPH and INPH patients. The results indicate that NFL may be a marker that can predict a surgically reversible state in NPH.</p

genome-wide linkage and copy number

A significant risk locus on 19q13 for bipolar disorder identified using a combine