Max Planck Institute of Psychiatry

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Abstract Data are reported on a series of short‐form (SF) screening scales of DSM‐III‐R psychiatric disorders developed from the World Health Organization's Composite International Diagnostic Interview (CIDI). A multi‐step procedure was used to generate CIDI‐SF screening scales for each of eight DSM disorders from the US National Comorbidity Survey (NCS). This procedure began with the subsample of respondents who endorsed the CIDI diagnostic stem question for a given disorder and then used a series of stepwise regression analyses to select a subset of screening questions to maximize reproduction of the full CIDI diagnosis. A small number of screening questions, between three and eight for each disorder, was found to account for the significant associations between symptom ratings and CIDI diagnoses. Summary scales made up of these symptom questions correctly classify between 77% and 100% of CIDI cases and between 94% and 99% of CIDI non‐cases in the NCS depending on the diagnosis. Overall classification accuracy ranged from a low of 93% for major depressive episode to a high of over 99% for generalized anxiety disorder. Pilot testing in a nationally representative telephone survey found that the full set of CIDI‐SF scales can be administered in an average of seven minutes compared to over an hour for the full CIDI. The results are quite encouraging in suggesting that diagnostic classifications made in the full CIDI can be reproduced with excellent accuracy with the CIDI‐SF scales. Independent verification of this reproduction accuracy, however, is needed in a data set other than the one in which the CIDI‐SF was developed. Copyright © 1998 Whurr Publishers Ltd.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

UNLABELLED: Here we describe an R library for genome-wide association (GWA) analysis. It implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures implemented in base R and special R libraries for genetic analysis. We evaluated GenABEL using one simulated and two real data sets. We conclude that GenABEL enables the analysis of GWA data on desktop computers. AVAILABILITY: http://cran.r-project.org.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Brain-derived neurotrophic factor (BDNF), a member of the nerve growth factor (NGF) gene family, has been shown to influence the survival and differentiation of specific classes of neurons in vitro and in vivo. The possibility that neurotrophins are also involved in processes of neuronal plasticity has only recently begun to receive attention. To determine whether BDNF has a function in processes such as long-term potentiation (LTP), we produced a strain of mice with a deletion in the coding sequence of the BDNF gene. We then used hippocampal slices from these mice to investigate whether LTP was affected by this mutation. Homo- and heterozygous mutant mice showed significantly reduced LTP in the CA1 region of the hippocampus. The magnitude of the potentiation, as well as the percentage of cases in which LTP could be induced successfully, was clearly affected. According to the criteria tested, important pharmacological, anatomical, and morphological parameters in the hippocampus of these animals appear to be normal. These results suggest that BDNF might have a functional role in the expression of LTP in the hippocampus.

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses.

Therapeutic drug monitoring (TDM) is the quantification and interpretation of drug concentrations in blood to optimize pharmacotherapy. It considers the interindividual variability of pharmacokinetics and thus enables personalized pharmacotherapy. In psychiatry and neurology, patient populations that may particularly benefit from TDM are children and adolescents, pregnant women, elderly patients, individuals with intellectual disabilities, patients with substance abuse disorders, forensic psychiatric patients or patients with known or suspected pharmacokinetic abnormalities. Non-response at therapeutic doses, uncertain drug adherence, suboptimal tolerability, or pharmacokinetic drug-drug interactions are typical indications for TDM. However, the potential benefits of TDM to optimize pharmacotherapy can only be obtained if the method is adequately integrated in the clinical treatment process. To supply treating physicians and laboratories with valid information on TDM, the TDM task force of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) issued their first guidelines for TDM in psychiatry in 2004. After an update in 2011, it was time for the next update. Following the new guidelines holds the potential to improve neuropsychopharmacotherapy, accelerate the recovery of many patients, and reduce health care costs.

BACKGROUND: Infectious, autoimmune, and neurodegenerative diseases are associated with profound psychological disturbances. Studies in animals clearly demonstrate that cytokines mediate illness-associated behavioral changes. However, the mechanisms underlying the respective psychological alterations in humans have not been established yet. Therefore, we investigated the effects of low-dose endotoxemia, a well-established and safe model of host-defense activation, on emotional, cognitive, immunological, and endocrine parameters. METHODS: In a double-blind, crossover study, 20 healthy male volunteers completed psychological questionnaires and neuropsychological tests 1, 3, and 9 hours after intravenous injection of Salmonella abortus equi endotoxin (0.8 ng/kg) or saline in 2 experimental sessions. Blood samples were collected hourly, and rectal temperature and heart rate were monitored continuously. RESULTS: Endotoxin had no effects on physical sickness symptoms, blood pressure, or heart rate. Endotoxin caused a mild increase in rectal temperature (0.5 degrees C), and increased the circulating levels of tumor necrosis factor alpha (TNF-alpha), soluble TNF receptors, interleukin (IL)-6, IL-1 receptor antagonist, and cortisol. After endotoxin administration, the subjects showed a transient significant increase in the levels of anxiety (effect size [ES] = 0.55) and depressed mood (ES = 0.66). Verbal and nonverbal memory functions were significantly decreased (ES = 0.55 to 0.64). Significant positive correlations were found between cytokine secretion and endotoxin-induced anxiety (r = 0.49 to r = 0.60), depressed mood (r = 0.40 to r = 0.75), and decreases in memory performance (r = 0.46 to r = 0.68). CONCLUSIONS: In humans, a mild stimulation of the primary host defense has negative effects on emotional and memory functions, which are probably caused by cytokine release. Hence, cytokines represent a novel target for neuropsychopharmacological research.

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.

Abnormally high spiking activity can damage neurons. Signaling systems to protect neurons from the consequences of abnormal discharge activity have been postulated. We generated conditional mutant mice that lack expression of the cannabinoid receptor type 1 in principal forebrain neurons but not in adjacent inhibitory interneurons. In mutant mice,the excitotoxin kainic acid (KA) induced excessive seizures in vivo. The threshold to KA-induced neuronal excitation in vitro was severely reduced in hippocampal pyramidal neurons of mutants. KA administration rapidly raised hippocampal levels of anandamide and induced protective mechanisms in wild-type principal hippocampal neurons. These protective mechanisms could not be triggered in mutant mice. The endogenous cannabinoid system thus provides on-demand protection against acute excitotoxicity in central nervous system neurons.

Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD-related differences in subcortical regions using shape analysis. In this meta-analysis of subcortical shape from the ENIGMA-MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta-analysis. Relative to CTL, patients with adolescent-onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = -0.164 to -0.180). Relative to first-episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = -0.173 to -0.184). Our results suggest that previously reported MDD-associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.

The cannabinoid receptor type 1 (CB1) and its endogenous ligands, the endocannabinoids, are involved in the regulation of food intake. Here we show that the lack of CB1 in mice with a disrupted CB1 gene causes hypophagia and leanness. As compared with WT (CB1+/+) littermates, mice lacking CB1 (CB1-/-) exhibited reduced spontaneous caloric intake and, as a consequence of reduced total fat mass, decreased body weight. In young CB1-/- mice, the lean phenotype is predominantly caused by decreased caloric intake, whereas in adult CB1-/- mice, metabolic factors appear to contribute to the lean phenotype. No significant differences between genotypes were detected regarding locomotor activity, body temperature, or energy expenditure. Hypothalamic CB1 mRNA was found to be coexpressed with neuropeptides known to modulate food intake, such as corticotropin-releasing hormone (CRH), cocaine-amphetamine-regulated transcript (CART), melanin-concentrating hormone (MCH), and preproorexin, indicating a possible role for endocannabinoid receptors within central networks governing appetite. CB1-/- mice showed significantly increased CRH mRNA levels in the paraventricular nucleus and reduced CART mRNA levels in the dorsomedial and lateral hypothalamic areas. CB1 was also detected in epidydimal mouse adipocytes, and CB1-specific activation enhanced lipogenesis in primary adipocyte cultures. Our results indicate that the cannabinoid system is an essential endogenous regulator of energy homeostasis via central orexigenic as well as peripheral lipogenic mechanisms and might therefore represent a promising target to treat diseases characterized by impaired energy balance.

A large International Restless Legs Syndrome (RLS) Study Group has been formed. As its first task, the group has taken upon itself the role of defining the clinical features of the RLS. As minimal criteria for diagnosis, the group proposes the following four features: (a) desire to move the extremities, often associated with paresthesias/dysesthesias; (b) motor restlessness; (c) worsening of symptoms at rest with at least temporary relief by activity, and (d) worsening of symptoms in the evening or night. Other features commonly seen in RLS include sleep disturbance, periodic limb movements in sleep and similar involuntary movements while awake, a normal neurological examination in the idiopathic form, a tendency for the symptoms to be worse in middle to older age, and, in some cases, a family history suggestive of an autosomal dominant mode of inheritance.

BACKGROUND: The German National Health Interview and Examination Survey (GHS) is the first government mandated nationwide study to investigate jointly the prevalence of somatic and mental disorders within one study in the general adult population in Germany. This paper reports results from its Mental Health Supplement (GHS-MHS) on 4-week 12-month, and selected lifetime prevalence of a broad range of DSM-IV mental disorders, their co-morbidity and correlates in the community. METHODS: The sample of the GHS-MHS (n=4181; multistage stratified random sample drawn from population registries; conditional response rate: 87.6%) can be regarded as representative for the German population aged 18-65. Diagnoses are based on fully structured computer assisted clinical interviews (M-CIDI), conducted by clinically trained interviewers. RESULTS: 12-month prevalence for any DSM-IV study disorder is 31% (lifetime: 43%; 4-week: 20%) with anxiety disorders, mood disorders and somatoform syndromes being the most frequent diagnoses. Retrospective age of onset information reveals that most disorders begin early in life. Co-morbidity rates among mental disorders range from 44% to 94%. Correlates of increased rates of mental disorders and co-morbidity were: female gender (except for substance disorders), not being married, low social class, and poor somatic health status. Health care utilization for mental disorders depended on co-morbidity (30% in 'pure', 76% in highly co-morbid cases) and varied from 33% for substance use disorders to 75% for panic disorder. CONCLUSIONS: Results confirm and extend results from other national studies using the same assessment instruments with regard to prevalence, co-morbidity and sociodemographic correlates, covering a broader range of DSM-IV disorders [i.e. somatoform disorders, all anxiety disorders (except PTSD), mental disorders due to substance or general medical factor, eating disorders]. Intervention rates were higher than in previous studies, yet still low overall.

Vascular endothelial growth factor (VEGF) is a secreted angiogenic mitogen whose target cell specificity appears to be restricted to vascular endothelial cells. Such factors are likely candidates for regulatory molecules involved in endothelial growth control. We have characterized the murine VEGF gene and have analysed its expression pattern in embryogenesis, particularly during brain angiogenesis. Analysis of cDNA clones predicted the existence of three molecular forms of VEGF which differ in size due to heterogeneity at the carboxy terminus of the protein. The predicted mature proteins consist of 120, 164 or 188 amino acid residues. Homodimers of the two lower molecular weight forms, but not of the higher molecular weight form, were secreted by COS cells transfected with the corresponding cDNAs and were equally potent in stimulating the growth of endothelial cells. During brain development, VEGF transcript levels were abundant in the ventricular neuroectoderm of embryonic and postnatal brain when endothelial cells proliferate rapidly but were reduced in the adult when endothelial cell proliferation has ceased. The temporal and spatial expression of VEGF is consistent with the hypothesis that VEGF is synthesized and released by the ventricular neuroectoderm and may induce the ingrowth of capillaries from the perineural vascular plexus. In addition to the transient expression during brain development, a persistent expression of VEGF was observed in epithelial cells adjacent to fenestrated endothelium, e.g. in choroid plexus and in kidney glomeruli. The data are consistent with a role of VEGF as a multifunctional regulator of endothelial cell growth and differentiation.

Absence of a common diagnostic interview has hampered cross-national syntheses of epidemiological evidence on major depressive episodes (MDE). Community epidemiological surveys using the World Health Organization Composite International Diagnostic Interview administered face-to-face were carried out in 10 countries in North America (Canada and the US), Latin America (Brazil, Chile, and Mexico), Europe (Czech Republic, Germany, the Netherlands, and Turkey), and Asia (Japan). The total sample size was more than 37,000. Lifetime prevalence estimates of hierarchy-free DSM-III-R/DSM-IV MDE varied widely, from 3% in Japan to 16.9% in the US, with the majority in the range of 8% to 12%. The 12-month/lifetime prevalence ratio was in the range 40% to 55%, the 30-day/12-month prevalence ratio in the range 45% to 65%, and median age of onset in the range 20 to 25 in most countries. Consistent socio-demographic correlates included being female and unmarried. Respondents in recent cohorts reported higher lifetime prevalence, but lower persistence than those in earlier cohorts. Major depressive episodes were found to be strongly co-morbid with, and temporally secondary to, anxiety disorders in all countries, with primary panic and generalized anxiety disorders the most powerful predictors of the first onset of secondary MDE. Major depressive episodes are a commonly occurring disorder that usually has a chronic-intermittent course. Effectiveness trials are needed to evaluate the impact of early detection and treatment on the course of MDE as well as to evaluate whether timely treatment of primary anxiety disorders would reduce the subsequent onset, persistence, and severity of secondary MDE.

The most characteristic property of microglia is their swift activation in response to neuronal stress and their capacity for site-directed phagocytosis. The transformation of microglia into intrinsic brain macrophages appears to be under strict control and takes place if neuronal and/or terminal degeneration occurs in response to nerve lesion. The differentiation of microglia into brain macrophages is accompanied by the release of several secretory products, e.g., proteinases, cytokines, reactive oxygen intermediates, and reactive nitrogen intermediates. Interference with the microglial activation or the productions of cytotoxic metabolites by microglia may thus offer new therapeutic opportunities for the prevention of neuronal cell death in CNS disease.