- Browse by Author
Browsing by Author "Maihofer, Adam X."
Now showing 1 - 4 of 4
Results Per Page
Sort Options
Item Alcohol Use and Alcohol Use Disorder Differ in their Genetic Relationships with PTSD: A Genomic Structural Equation Modelling Approach(Elsevier, 2022) Bountress, Kaitlin E.; Brick, Leslie A.; Sheerin, Christina; Grotzinger, Andrew; Bustamante, Daniel; Hawn, Sage E.; Gillespie, Nathan; Kirkpatrick, Robert M.; Kranzler, Henry; Morey, Rajendra; Edenberg, Howard J.; Maihofer, Adam X.; Disner, Seth; Ashley-Koch, Allison; Peterson, Roseann; Lori, Adriana; Stein, Dan J.; Kimbrel, Nathan; Nievergelt, Caroline; Andreassen, Ole A.; Luykx, Jurjen; Javanbakht, Arash; Youssef, Nagy A.; Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group; Amstadter, Ananda B.; Biochemistry and Molecular Biology, School of MedicinePurpose: Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. Basic procedures: We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. Main findings: When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). Principal conclusions: These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.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 Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder(Springer Nature, 2024) Nievergelt, Caroline M.; Maihofer, Adam X.; Atkinson, Elizabeth G.; Chen, Chia-Yen; Choi, Karmel W.; Coleman, Jonathan R. I.; Daskalakis, Nikolaos P.; Duncan, Laramie E.; Polimanti, Renato; Aaronson, Cindy; Amstadter, Ananda B.; Andersen, Soren B.; Andreassen, Ole A.; Arbisi, Paul A.; Ashley-Koch, Allison E.; Austin, S. Bryn; Avdibegoviç, Esmina; Babić, Dragan; Bacanu, Silviu-Alin; Baker, Dewleen G.; Batzler, Anthony; Beckham, Jean C.; Belangero, Sintia; Benjet, Corina; Bergner, Carisa; Bierer, Linda M.; Biernacka, Joanna M.; Bierut, Laura J.; Bisson, Jonathan I.; Boks, Marco P.; Bolger, Elizabeth A.; Brandolino, Amber; Breen, Gerome; Bressan, Rodrigo Affonseca; Bryant, Richard A.; Bustamante, Angela C.; Bybjerg-Grauholm, Jonas; Bækvad-Hansen, Marie; Børglum, Anders D.; Børte, Sigrid; Cahn, Leah; Calabrese, Joseph R.; Caldas-de-Almeida, Jose Miguel; Chatzinakos, Chris; Cheema, Sheraz; Clouston, Sean A. P.; Colodro-Conde, Lucía; Coombes, Brandon J.; Cruz-Fuentes, Carlos S.; Dale, Anders M.; Dalvie, Shareefa; Davis, Lea K.; Deckert, Jürgen; Delahanty, Douglas L.; Dennis, Michelle F.; Desarnaud, Frank; DiPietro, Christopher P.; Disner, Seth G.; Docherty, Anna R.; Domschke, Katharina; Dyb, Grete; Džubur Kulenović, Alma; Edenberg, Howard J.; Evans, Alexandra; Fabbri, Chiara; Fani, Negar; Farrer, Lindsay A.; Feder, Adriana; Feeny, Norah C.; Flory, Janine D.; Forbes, David; Franz, Carol E.; Galea, Sandro; Garrett, Melanie E.; Gelaye, Bizu; Gelernter, Joel; Geuze, Elbert; Gillespie, Charles F.; Goleva, Slavina B.; Gordon, Scott D.; Goçi, Aferdita; Grasser, Lana Ruvolo; Guindalini, Camila; Haas, Magali; Hagenaars, Saskia; Hauser, Michael A.; Heath, Andrew C.; Hemmings, Sian M. J.; Hesselbrock, Victor; Hickie, Ian B.; Hogan, Kelleigh; Hougaard, David Michael; Huang, Hailiang; Huckins, Laura M.; Hveem, Kristian; Jakovljević, Miro; Javanbakht, Arash; Jenkins, Gregory D.; Johnson, Jessica; Jones, Ian; Jovanovic, Tanja; Karstoft, Karen-Inge; Kaufman, Milissa L.; Kennedy, James L.; Kessler, Ronald C.; Khan, Alaptagin; Kimbrel, Nathan A.; King, Anthony P.; Koen, Nastassja; Kotov, Roman; Kranzler, Henry R.; Krebs, Kristi; Kremen, William S.; Kuan, Pei-Fen; Lawford, Bruce R.; Lebois, Lauren A. M.; Lehto, Kelli; Levey, Daniel F.; Lewis, Catrin; Liberzon, Israel; Linnstaedt, Sarah D.; Logue, Mark W.; Lori, Adriana; Lu, Yi; Luft, Benjamin J.; Lupto, Michelle K.; Luykx, Jurjen J.; Makotkine, Iouri; Maples-Keller, Jessica L.; Marchese, Shelby; Marmar, Charles; Martin, Nicholas G.; Martínez-Levy, Gabriela A.; McAloney, Kerrie; McFarlane, Alexander; McLaughlin, Katie A.; McLean, Samuel A.; Medland, Sarah E.; Mehta, Divya; Meyers, Jacquelyn; Michopoulos, Vasiliki; Mikita, Elizabeth A.; Milani, Lili; Milberg, William; Miller, Mark W.; Morey, Rajendra A.; Morris, Charles Phillip; Mors, Ole; Mortensen, Preben Bo; Mufford, Mary S.; Nelson, Elliot C.; Nordentoft, Merete; Norman, Sonya B.; Nugent, Nicole R.; O'Donnell, Meaghan; Orcutt, Holly K.; Pan, Pedro M.; Panizzon, Matthew S.; Pathak, Gita A.; Peters, Edward S.; Peterson, Alan L.; Peverill, Matthew; Pietrzak, Robert H.; Polusny, Melissa A.; Porjesz, Bernice; Powers, Abigail; Qin, Xue-Jun; Ratanatharathorn, Andrew; Risbrough, Victoria B.; Roberts, Andrea L.; Rothbaum, Alex O.; Rothbaum, Barbara O.; Roy-Byrne, Peter; Ruggiero, Kenneth J.; Rung, Ariane; Runz, Heiko; Rutten, Bart P. F.; Saenz de Viteri, Stacey; Salum, Giovanni Abrahão; Sampson, Laura; Sanchez, Sixto E.; Santoro, Marcos; Seah, Carina; Seedat, Soraya; Seng, Julia S.; Shabalin, Andrey; Sheerin, Christina M.; Silove, Derrick; Smith, Alicia K.; Smoller, Jordan W.; Sponheim, Scott R.; Stein, Dan J.; Stensland, Synne; Stevens, Jennifer S.; Sumner, Jennifer A.; Teicher, Martin H.; Thompson, Wesley K.; Tiwari, Arun K.; Trapido, Edward; Uddin, Monica; Ursano, Robert J.; Valdimarsdóttir, Unnur; Van Hooff, Miranda; Vermetten, Eric; Vinkers, Christiaan H.; Voisey, Joanne; Wang, Yunpeng; Wang, Zhewu; Waszczuk, Monika; Weber, Heike; Wendt, Frank R.; Werge, Thomas; Williams, Michelle A.; Williamson, Douglas E.; Winsvold, Bendik S.; Winternitz, Sherry; Wolf, Christiane; Wolf, Erika J.; Xia, Yan; Xiong, Ying; Yehuda, Rachel; Young, Keith A.; Young, Ross McD.; Zai, Clement C.; Zai, Gwyneth C.; Zervas, Mark; Zhao, Hongyu; Zoellner, Lori A.; Zwart, John-Anker; deRoon-Cassini, Terri; van Rooij, Sanne J. H.; van den Heuvel, Leigh L.; AURORA Study; Estonian Biobank Research Team; FinnGen Investigators; HUNT All-In Psychiatry; Stein, Murray B.; Ressler, Kerry J.; Koenen, Karestan C.; Biochemistry and Molecular Biology, School of MedicinePost-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.