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Browsing by Author "Bertram, Holli"
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Item Clinical predictors of non-response to lithium treatment in the Pharmacogenomics of Bipolar Disorder (PGBD) study(Wiley, 2021) Lin, Yian; Maihofer, Adam X.; Stapp, Emma; Ritchey, Megan; Alliey‐Rodriguez, Ney; Anand, Amit; Balaraman, Yokesh; Berrettini, Wade H.; Bertram, Holli; Bhattacharjee, Abesh; Calkin, Cynthia V.; Conroy, Carla; Coryell, William; D'Arcangelo, Nicole; DeModena, Anna; Biernacka, Joanna M.; Fisher, Carrie; Frazier, Nicole; Frye, Mark; Gao, Keming; Garnham, Julie; Gershon, Elliot; Glazer, Kara; Goes, Fernando S.; Goto, Toyomi; Karberg, Elizabeth; Harrington, Gloria; Jakobsen, Petter; Kamali, Masoud; Kelly, Marisa; Leckband, Susan G.; Lohoff, Falk W.; Stautland, Andrea; McCarthy, Michael J.; McInnis, Melvin G.; Mondimore, Francis; Morken, Gunnar; Nurnberger, John I.; Oedegaard, Ketil J.; Syrstad, Vigdis Elin Giever; Ryan, Kelly; Schinagle, Martha; Schoeyen, Helle; Andreassen, Ole A.; Shaw, Marth; Shilling, Paul D.; Slaney, Claire; Tarwater, Bruce; Calabrese, Joseph R.; Alda, Martin; Nievergelt, Caroline M.; Zandi, Peter P.; Kelsoe, John R.; Psychiatry, School of MedicineBackground Lithium is regarded as a first-line treatment for bipolar disorder (BD), but partial response and non-response commonly occurs. There exists a need to identify lithium non-responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response. Methods The PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse. Results A total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness. Conclusions In this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy.Item Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis(Springer Nature, 2024) Niemsiri, Vipavee; Rosenthal, Sara Brin; Nievergelt, Caroline M.; Maihofer, Adam X.; Marchetto, Maria C.; Santos, Renata; Shekhtman, Tatyana; Alliey-Rodriguez, Ney; Anand, Amit; Balaraman, Yokesh; Berrettini, Wade H.; Bertram, Holli; Burdick, Katherine E.; Calabrese, Joseph R.; Calkin, Cynthia V.; Conroy, Carla; Coryell, William H.; DeModena, Anna; Eyler, Lisa T.; Feeder, Scott; Fisher, Carrie; Frazier, Nicole; Frye, Mark A.; Gao, Keming; Garnham, Julie; Gershon, Elliot S.; Goes, Fernando S.; Goto, Toyomi; Harrington, Gloria J.; Jakobsen, Petter; Kamali, Masoud; Kelly, Marisa; Leckband, Susan G.; Lohoff, Falk W.; McCarthy, Michael J.; McInnis, Melvin G.; Craig, David; Millett, Caitlin E.; Mondimore, Francis; Morken, Gunnar; Nurnberger, John I.; O'Donovan, Claire; Øedegaard, Ketil J.; Ryan, Kelly; Schinagle, Martha; Shilling, Paul D.; Slaney, Claire; Stapp, Emma K.; Stautland, Andrea; Tarwater, Bruce; Zandi, Peter P.; Alda, Martin; Fisch, Kathleen M.; Gage, Fred H.; Kelsoe, John R.; Psychiatry, School of MedicineLithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.Item Salivary melatonin onset in youth at familial risk for bipolar disorder(Elsevier, 2019-04) Ghaziuddin, Neera; Shamseddeen, Wael; Bertram, Holli; McInnis, Melvin; Wilcox, Holly C.; Mitchell, Philip B.; Fullerton, Janice M.; Roberts, Gloria M. P.; Glowinski, Anne L.; Kamali, Masoud; Stapp, Emma; Hulvershorn, Leslie A.; Nurnberger, John; Armitage, Roseanne; Psychiatry, School of MedicineMelatonin secretion and polysomnography (PSG) were compared among a group of healthy adolescents who were at high familial risk for bipolar disorder (HR) and a second group at low familial risk (LR). Adolescent participants (n = 12) were a mean age 14 ± 2.3 years and included 8 females and 4 males. Saliva samples were collected under standardized condition light (red light) and following a 200 lux light exposure over two consecutive nights in a sleep laboratory. Red Light Melatonin onset (RLMO) was defined as saliva melatonin level exceeding the mean of the first 3 readings plus 2 standard deviations. Polysomnography was also completed during each night. HR youth, relative to LR, experienced a significantly earlier melatonin onset following 200 lux light exposure. Polysomnography revealed that LR youth, relative to HR, spent significantly more time in combined stages 3 and 4 (deep sleep) following red light exposure. Additionally, regardless of the group status (HR or LR), there was no significant difference in Red Light Melatonin Onset recorded at home or in the laboratory, implying its feasibility and reliability.Item The Human Phenotype Ontology in 2024: phenotypes around the world(Oxford University Press, 2024) Gargano, Michael A.; Matentzoglu, Nicolas; Coleman, Ben; Addo-Lartey, Eunice B.; Anagnostopoulos, Anna V.; Anderton, Joel; Avillach, Paul; Bagley, Anita M.; Bakštein, Eduard; Balhoff, James P.; Baynam, Gareth; Bello, Susan M.; Berk, Michael; Bertram, Holli; Bishop, Somer; Blau, Hannah; Bodenstein, David F.; Botas, Pablo; Boztug, Kaan; Čady, Jolana; Callahan, Tiffany J.; Cameron, Rhiannon; Carbon, Seth J.; Castellanos, Francisco; Caufield, J. Harry; Chan, Lauren E.; Chute, Christopher G.; Cruz-Rojo, Jaime; Dahan-Oliel, Noémi; Davids, Jon R.; de Dieuleveult, Maud; de Souza, Vinicius; de Vries, Bert B. A.; de Vries, Esther; DePaulo, J. Raymond; Derfalvi, Beata; Dhombres, Ferdinand; Diaz-Byrd, Claudia; Dingemans, Alexander J. M.; Donadille, Bruno; Duyzend, Michael; Elfeky, Reem; Essaid, Shahim; Fabrizzi, Carolina; Fico, Giovanna; Firth, Helen V.; Freudenberg-Hua, Yun; Fullerton, Janice M.; Gabriel, Davera L.; Gilmour, Kimberly; Giordano, Jessica; Goes, Fernando S.; Gore Moses, Rachel; Green, Ian; Griese, Matthias; Groza, Tudor; Gu, Weihong; Guthrie, Julia; Gyori, Benjamin; Hamosh, Ada; Hanauer, Marc; Hanušová, Kateřina; He, Yongqun Oliver; Hegde, Harshad; Helbig, Ingo; Holasová, Kateřina; Hoyt, Charles Tapley; Huang, Shangzhi; Hurwitz, Eric; Jacobsen, Julius O. B.; Jiang, Xiaofeng; Joseph, Lisa; Keramatian, Kamyar; King, Bryan; Knoflach, Katrin; Koolen, David A.; Kraus, Megan L.; Kroll, Carlo; Kusters, Maaike; Ladewig, Markus S.; Lagorce, David; Lai, Meng-Chuan; Lapunzina, Pablo; Laraway, Bryan; Lewis-Smith, David; Li, Xiarong; Lucano, Caterina; Majd, Marzieh; Marazita, Mary L.; Martinez-Glez, Victor; McHenry, Toby H.; McInnis, Melvin G.; McMurry, Julie A.; Mihulová, Michaela; Millett, Caitlin E.; Mitchell, Philip B.; Moslerová, Veronika; Narutomi, Kenji; Nematollahi, Shahrzad; Nevado, Julian; Nierenberg, Andrew A.; Novák Čajbiková, Nikola; Nurnberger, John I., Jr.; Ogishima, Soichi; Olson, Daniel; Ortiz, Abigail; Pachajoa, Harry; Perez de Nanclares, Guiomar; Peters, Amy; Putman, Tim; Rapp, Christina K.; Rath, Ana; Reese, Justin; Rekerle, Lauren; Roberts, Angharad M.; Roy, Suzy; Sanders, Stephan J.; Schuetz, Catharina; Schulte, Eva C.; Schulze, Thomas G.; Schwarz, Martin; Scott, Katie; Seelow, Dominik; Seitz, Berthold; Shen, Yiping; Similuk, Morgan N.; Simon, Eric S.; Singh, Balwinder; Smedley, Damian; Smith, Cynthia L.; Smolinsky, Jake T.; Sperry, Sarah; Stafford, Elizabeth; Stefancsik, Ray; Steinhaus, Robin; Strawbridge, Rebecca; Sundaramurthi, Jagadish Chandrabose; Talapova, Polina; Tenorio Castano, Jair A.; Tesner, Pavel; Thomas, Rhys H.; Thurm, Audrey; Turnovec, Marek; van Gijn, Marielle E.; Vasilevsky, Nicole A.; Vlčková, Markéta; Walden, Anita; Wang, Kai; Wapner, Ron; Ware, James S.; Wiafe, Addo A.; Wiafe, Samuel A.; Wiggins, Lisa D.; Williams, Andrew E.; Wu, Chen; Wyrwoll, Margot J.; Xiong, Hui; Yalin, Nefize; Yamamoto, Yasunori; Yatham, Lakshmi N.; Yocum, Anastasia K.; Young, Allan H.; Yüksel, Zafer; Zandi, Peter P.; Zankl, Andreas; Zarante, Ignacio; Zvolský, Miroslav; Toro, Sabrina; Carmody, Leigh C.; Harris, Nomi L.; Munoz-Torres, Monica C.; Danis, Daniel; Mungall, Christopher J.; Köhler, Sebastian; Haendel, Melissa A.; Robinson, Peter N.; Psychiatry, School of MedicineThe Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.