TY  - JOUR
A1  - Davis, Lea K.
A1  - Yu, Dongmei
A1  - Keenan, Clare L.
A1  - Gamazon, Eric R.
A1  - Konkashbaev, Anuar I.
A1  - Derks, Eske M.
A1  - Neale, Benjamin M.
A1  - Yang, Jian
A1  - Lee, S. Hong
A1  - Evans, Patrick
A1  - Barr, Cathy L.
A1  - Bellodi, Laura
A1  - Benarroch, Fortu
A1  - Berrio, Gabriel Bedoya
A1  - Bienvenu, Oscar J.
A1  - Bloch, Michael H.
A1  - Blom, Rianne M.
A1  - Bruun, Ruth D.
A1  - Budman, Cathy L.
A1  - Camarena, Beatriz
A1  - Campbell, Desmond
A1  - Cappi, Carolina
A1  - Cardona Silgado, Julio C.
A1  - Cath, Danielle C.
A1  - Cavallini, Maria C.
A1  - Chavira, Denise A.
A1  - Chouinard, Sylvian
A1  - Conti, David V.
A1  - Cook, Edwin H.
A1  - Coric, Vladimir
A1  - Cullen, Bernadette A.
A1  - Deforce, Dieter
A1  - Delorme, Richard
A1  - Dion, Yves
A1  - Edlund, Christopher K.
A1  - Egberts, Karin
A1  - Falkai, Peter
A1  - Fernandez, Thomas V.
A1  - Gallagher, Patience J.
A1  - Garrido, Helena
A1  - Geller, Daniel
A1  - Girard, Simon L.
A1  - Grabe, Hans J.
A1  - Grados, Marco A.
A1  - Greenberg, Benjamin D.
A1  - Gross-Tsur, Varda
A1  - Haddad, Stephen
A1  - Heiman, Gary A.
A1  - Hemmings, Sian M. J.
A1  - Hounie, Ana G.
A1  - Illmann, Cornelia
A1  - Jankovic, Joseph
A1  - Jenike, Micheal A.
A1  - Kennedy, James L.
A1  - King, Robert A.
A1  - Kremeyer, Barbara
A1  - Kurlan, Roger
A1  - Lanzagorta, Nuria
A1  - Leboyer, Marion
A1  - Leckman, James F.
A1  - Lennertz, Leonhard
A1  - Liu, Chunyu
A1  - Lochner, Christine
A1  - Lowe, Thomas L.
A1  - Macciardi, Fabio
A1  - McCracken, James T.
A1  - McGrath, Lauren M.
A1  - Restrepo, Sandra C. Mesa
A1  - Moessner, Rainald
A1  - Morgan, Jubel
A1  - Muller, Heike
A1  - Murphy, Dennis L.
A1  - Naarden, Allan L.
A1  - Ochoa, William Cornejo
A1  - Ophoff, Roel A.
A1  - Osiecki, Lisa
A1  - Pakstis, Andrew J.
A1  - Pato, Michele T.
A1  - Pato, Carlos N.
A1  - Piacentini, John
A1  - Pittenger, Christopher
A1  - Pollak, Yehunda
A1  - Rauch, Scott L.
A1  - Renner, Tobias J.
A1  - Reus, Victor I.
A1  - Richter, Margaret A.
A1  - Riddle, Mark A.
A1  - Robertson, Mary M.
A1  - Romero, Roxana
A1  - Rosàrio, Maria C.
A1  - Rosenberg, David
A1  - Rouleau, Guy A.
A1  - Ruhrmann, Stephan
A1  - Ruiz-Linares, Andreas
A1  - Sampaio, Aline S.
A1  - Samuels, Jack
A1  - Sandor, Paul
A1  - Sheppard, Broke
A1  - Singer, Harvey S.
A1  - Smit, Jan H.
A1  - Stein, Dan J.
A1  - Strengman, E.
A1  - Tischfield, Jay A.
A1  - Valencia Duarte, Ana V.
A1  - Vallada, Homero
A1  - Van Nieuwerburgh, Flip
A1  - Veenstra-VanderWeele, Jeremy
A1  - Walitza, Susanne
A1  - Wang, Ying
A1  - Wendland, Jens R.
A1  - Westenberg, Herman G. M.
A1  - Shugart, Yin Yao
A1  - Miguel, Euripedes C.
A1  - McMahon, William
A1  - Wagner, Michael
A1  - Nicolini, Humberto
A1  - Posthuma, Danielle
A1  - Hanna, Gregory L.
A1  - Heutink, Peter
A1  - Denys, Damiaan
A1  - Arnold, Paul D.
A1  - Oostra, Ben A.
A1  - Nestadt, Gerald
A1  - Freimer, Nelson B.
A1  - Pauls, David L.
A1  - Wray, Naomi R.
A1  - Stewart, S. Evelyn
A1  - Mathews, Carol A.
A1  - Knowles, James A.
A1  - Cox, Nancy J.
A1  - Scharf, Jeremiah M.
T1  - Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture
JF  - PLoS Genetics
N2  - The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained by all SNPs for two phenotypically-related neurobehavioral disorders, obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS), using GCTA. Our analysis yielded a heritability point estimate of 0.58 (se = 0.09, p = 5.64e-12) for TS, and 0.37 (se = 0.07, p = 1.5e-07) for OCD. In addition, we conducted multiple genomic partitioning analyses to identify genomic elements that concentrate this heritability. We examined genomic architectures of TS and OCD by chromosome, MAF bin, and functional annotations. In addition, we assessed heritability for early onset and adult onset OCD. Among other notable results, we found that SNPs with a minor allele frequency of less than 5% accounted for 21% of the TS heritability and 0% of the OCD heritability. Additionally, we identified a significant contribution to TS and OCD heritability by variants significantly associated with gene expression in two regions of the brain (parietal cortex and cerebellum) for which we had available expression quantitative trait loci (eQTLs). Finally we analyzed the genetic correlation between TS and OCD, revealing a genetic correlation of 0.41 (se = 0.15, p = 0.002). These results are very close to previous heritability estimates for TS and OCD based on twin and family studies, suggesting that very little, if any, heritability is truly missing (i.e., unassayed) from TS and OCD GWAS studies of common variation. The results also indicate that there is some genetic overlap between these two phenotypically-related neuropsychiatric disorders, but suggest that the two disorders have distinct genetic architectures.
KW  - TIC disorders
KW  - missing heritability
KW  - complex diseases
KW  - neuropsychiatric disorders
KW  - common SNPS
KW  - gilles
KW  - family
KW  - brain
KW  - expression
KW  - autism
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-127377
SN  - 1553-7390
VL  - 9
IS  - 10
ER  - 
TY  - JOUR
A1  - Deeb, Wissam
A1  - Giordano, James J.
A1  - Rossi, Peter J.
A1  - Mogilner, Alon Y.
A1  - Gunduz, Aysegul
A1  - Judy, Jack W.
A1  - Klassen, Bryan T.
A1  - Butson, Christopher R.
A1  - Van Horne, Craig
A1  - Deny, Damiaan
A1  - Dougherty, Darin D.
A1  - Rowell, David
A1  - Gerhardt, Greg A.
A1  - Smith, Gwenn S.
A1  - Ponce, Francisco A.
A1  - Walker, Harrison C.
A1  - Bronte-Stewart, Helen M.
A1  - Mayberg, Helen S.
A1  - Chizeck, Howard J.
A1  - Langevin, Jean-Philippe
A1  - Volkmann, Jens
A1  - Ostrem, Jill L.
A1  - Shute, Jonathan B.
A1  - Jimenez-Shahed, Joohi
A1  - Foote, Kelly D.
A1  - Wagle Shukla, Aparna
A1  - Rossi, Marvin A.
A1  - Oh, Michael
A1  - Pourfar, Michael
A1  - Rosenberg, Paul B.
A1  - Silburn, Peter A.
A1  - de Hemptine, Coralie
A1  - Starr, Philip A.
A1  - Denison, Timothy
A1  - Akbar, Umer
A1  - Grill, Warren M.
A1  - Okun, Michael S.
T1  - Proceedings of the Fourth Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies
JF  - Frontiers in Integrative Neuroscience
N2  - This paper provides an overview of current progress in the technological advances and the use of deep brain stimulation (DBS) to treat neurological and neuropsychiatric disorders, as presented by participants of the Fourth Annual DBS Think Tank, which was convened in March 2016 in conjunction with the Center for Movement Disorders and Neurorestoration at the University of Florida, Gainesveille FL, USA. The Think Tank discussions first focused on policy and advocacy in DBS research and clinical practice, formation of registries, and issues involving the use of DBS in the treatment of Tourette Syndrome. Next, advances in the use of neuroimaging and electrochemical markers to enhance DBS specificity were addressed. Updates on ongoing use and developments of DBS for the treatment of Parkinson's disease, essential tremor, Alzheimer's disease, depression, post-traumatic stress disorder, obesity, addiction were presented, and progress toward innovation(s) in closed-loop applications were discussed. Each section of these proceedings provides updates and highlights of new information as presented at this year's international Think Tank, with a view toward current and near future advancement of the field.
KW  - deep brain stimulation
KW  - Parkinson’s disease
KW  - Alzheimer’s disease
KW  - closed-loop
KW  - depression
KW  - post-traumatic stress disorder
KW  - Tourette syndrome
KW  - DARPA
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-168493
VL  - 10
IS  - 38
ER  - 
TY  - JOUR
A1  - Arlt, Wiebke
A1  - Biehl, Michael
A1  - Taylor, Angela E.
A1  - Hahner, Stefanie
A1  - Libé, Rossella
A1  - Hughes, Beverly A.
A1  - Schneider, Petra
A1  - Smith, David J.
A1  - Stiekema, Han
A1  - Krone, Nils
A1  - Porfiri, Emilio
A1  - Opocher, Giuseppe
A1  - Bertherat, Jerôme
A1  - Mantero, Franco
A1  - Allolio, Bruno
A1  - Terzolo, Massimo
A1  - Nightingale, Peter
A1  - Shackleton, Cedric H. L.
A1  - Bertagna, Xavier
A1  - Fassnacht, Martin
A1  - Stewart, Paul M.
T1  - Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors
JF  - The Journal of Clinical Endocrinology & Metabolism
N2  - Context:
Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values.

Objective:
Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy.

Design:
Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids.

Results:
Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers.

Conclusions:
Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.
KW  - adrenal cortex hormones
KW  - urine
KW  - adrenal cortex neoplasms
KW  - mass spectrometry
KW  - metabolomics
Y1  - 2011
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-154682
VL  - 96
IS  - 12
SP  - 3775
EP  - 3784
ER  -